Horovod successfully initialized ... Loading pretrained model... Create EncryptCheckpointSaverHook. ================================= Start training cycle 01 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] ============================ GIT REPOSITORY ============================ BRANCH NAME: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ============================ MODEL STATISTICS =========================== # Model Weights: 28,650,305 # Trainable Weights: 44,067,009 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ============================ TRAINABLE VARIABLES ======================== [#0001] conv1/kernel:0 => (7, 7, 3, 64) [#0002] bn_conv1/gamma:0 => (64,) [#0003] bn_conv1/beta:0 => (64,) [#0004] block_1a_conv_1/kernel:0 => (1, 1, 64, 64) [#0005] block_1a_bn_1/gamma:0 => (64,) [#0006] block_1a_bn_1/beta:0 => (64,) [#0007] block_1a_conv_2/kernel:0 => (3, 3, 64, 64) [#0008] block_1a_bn_2/gamma:0 => (64,) [#0009] block_1a_bn_2/beta:0 => (64,) [#0010] block_1a_conv_3/kernel:0 => (1, 1, 64, 256) [#0011] block_1a_bn_3/gamma:0 => (256,) [#0012] block_1a_bn_3/beta:0 => (256,) [#0013] block_1a_conv_shortcut/kernel:0 => (1, 1, 64, 256) [#0014] block_1a_bn_shortcut/gamma:0 => (256,) [#0015] block_1a_bn_shortcut/beta:0 => (256,) [#0016] block_1b_conv_1/kernel:0 => (1, 1, 256, 64) [#0017] block_1b_bn_1/gamma:0 => (64,) [#0018] block_1b_bn_1/beta:0 => (64,) [#0019] block_1b_conv_2/kernel:0 => (3, 3, 64, 64) [#0020] block_1b_bn_2/gamma:0 => (64,) [#0021] block_1b_bn_2/beta:0 => (64,) [#0022] block_1b_conv_3/kernel:0 => (1, 1, 64, 256) [#0023] block_1b_bn_3/gamma:0 => (256,) [#0024] block_1b_bn_3/beta:0 => (256,) [#0025] block_1c_conv_1/kernel:0 => (1, 1, 256, 64) [#0026] block_1c_bn_1/gamma:0 => (64,) [#0027] block_1c_bn_1/beta:0 => (64,) [#0028] block_1c_conv_2/kernel:0 => (3, 3, 64, 64) [#0029] block_1c_bn_2/gamma:0 => (64,) [#0030] block_1c_bn_2/beta:0 => (64,) [#0031] block_1c_conv_3/kernel:0 => (1, 1, 64, 256) [#0032] block_1c_bn_3/gamma:0 => (256,) [#0033] block_1c_bn_3/beta:0 => (256,) [#0034] block_2a_conv_1/kernel:0 => (1, 1, 256, 128) [#0035] block_2a_bn_1/gamma:0 => (128,) [#0036] block_2a_bn_1/beta:0 => (128,) [#0037] block_2a_conv_2/kernel:0 => (3, 3, 128, 128) [#0038] block_2a_bn_2/gamma:0 => (128,) [#0039] block_2a_bn_2/beta:0 => (128,) [#0040] block_2a_conv_3/kernel:0 => (1, 1, 128, 512) [#0041] block_2a_bn_3/gamma:0 => (512,) [#0042] block_2a_bn_3/beta:0 => (512,) [#0043] block_2a_conv_shortcut/kernel:0 => (1, 1, 256, 512) [#0044] block_2a_bn_shortcut/gamma:0 => (512,) [#0045] block_2a_bn_shortcut/beta:0 => (512,) [#0046] block_2b_conv_1/kernel:0 => (1, 1, 512, 128) [#0047] block_2b_bn_1/gamma:0 => (128,) [#0048] block_2b_bn_1/beta:0 => (128,) [#0049] block_2b_conv_2/kernel:0 => (3, 3, 128, 128) [#0050] block_2b_bn_2/gamma:0 => (128,) [#0051] block_2b_bn_2/beta:0 => (128,) [#0052] block_2b_conv_3/kernel:0 => (1, 1, 128, 512) [#0053] block_2b_bn_3/gamma:0 => (512,) [#0054] block_2b_bn_3/beta:0 => (512,) [#0055] block_2c_conv_1/kernel:0 => (1, 1, 512, 128) [#0056] block_2c_bn_1/gamma:0 => (128,) [#0057] block_2c_bn_1/beta:0 => (128,) [#0058] block_2c_conv_2/kernel:0 => (3, 3, 128, 128) [#0059] block_2c_bn_2/gamma:0 => (128,) [#0060] block_2c_bn_2/beta:0 => (128,) [#0061] block_2c_conv_3/kernel:0 => (1, 1, 128, 512) [#0062] block_2c_bn_3/gamma:0 => (512,) [#0063] block_2c_bn_3/beta:0 => (512,) [#0064] block_2d_conv_1/kernel:0 => (1, 1, 512, 128) [#0065] block_2d_bn_1/gamma:0 => (128,) [#0066] block_2d_bn_1/beta:0 => (128,) [#0067] block_2d_conv_2/kernel:0 => (3, 3, 128, 128) [#0068] block_2d_bn_2/gamma:0 => (128,) [#0069] block_2d_bn_2/beta:0 => (128,) [#0070] block_2d_conv_3/kernel:0 => (1, 1, 128, 512) [#0071] block_2d_bn_3/gamma:0 => (512,) [#0072] block_2d_bn_3/beta:0 => (512,) [#0073] block_3a_conv_1/kernel:0 => (1, 1, 512, 256) [#0074] block_3a_bn_1/gamma:0 => (256,) [#0075] block_3a_bn_1/beta:0 => (256,) [#0076] block_3a_conv_2/kernel:0 => (3, 3, 256, 256) [#0077] block_3a_bn_2/gamma:0 => (256,) [#0078] block_3a_bn_2/beta:0 => (256,) [#0079] block_3a_conv_3/kernel:0 => (1, 1, 256, 1024) [#0080] block_3a_bn_3/gamma:0 => (1024,) [#0081] block_3a_bn_3/beta:0 => (1024,) [#0082] block_3a_conv_shortcut/kernel:0 => (1, 1, 512, 1024) [#0083] block_3a_bn_shortcut/gamma:0 => (1024,) [#0084] block_3a_bn_shortcut/beta:0 => (1024,) [#0085] block_3b_conv_1/kernel:0 => (1, 1, 1024, 256) [#0086] block_3b_bn_1/gamma:0 => (256,) [#0087] block_3b_bn_1/beta:0 => (256,) [#0088] block_3b_conv_2/kernel:0 => (3, 3, 256, 256) [#0089] block_3b_bn_2/gamma:0 => (256,) [#0090] block_3b_bn_2/beta:0 => (256,) [#0091] block_3b_conv_3/kernel:0 => (1, 1, 256, 1024) [#0092] block_3b_bn_3/gamma:0 => (1024,) [#0093] block_3b_bn_3/beta:0 => (1024,) [#0094] block_3c_conv_1/kernel:0 => (1, 1, 1024, 256) [#0095] block_3c_bn_1/gamma:0 => (256,) [#0096] block_3c_bn_1/beta:0 => (256,) [#0097] block_3c_conv_2/kernel:0 => (3, 3, 256, 256) [#0098] block_3c_bn_2/gamma:0 => (256,) [#0099] block_3c_bn_2/beta:0 => (256,) [#0100] block_3c_conv_3/kernel:0 => (1, 1, 256, 1024) [#0101] block_3c_bn_3/gamma:0 => (1024,) [#0102] block_3c_bn_3/beta:0 => (1024,) [#0103] block_3d_conv_1/kernel:0 => (1, 1, 1024, 256) [#0104] block_3d_bn_1/gamma:0 => (256,) [#0105] block_3d_bn_1/beta:0 => (256,) [#0106] block_3d_conv_2/kernel:0 => (3, 3, 256, 256) [#0107] block_3d_bn_2/gamma:0 => (256,) [#0108] block_3d_bn_2/beta:0 => (256,) [#0109] block_3d_conv_3/kernel:0 => (1, 1, 256, 1024) [#0110] block_3d_bn_3/gamma:0 => (1024,) [#0111] block_3d_bn_3/beta:0 => (1024,) [#0112] block_3e_conv_1/kernel:0 => (1, 1, 1024, 256) [#0113] block_3e_bn_1/gamma:0 => (256,) [#0114] block_3e_bn_1/beta:0 => (256,) [#0115] block_3e_conv_2/kernel:0 => (3, 3, 256, 256) [#0116] block_3e_bn_2/gamma:0 => (256,) [#0117] block_3e_bn_2/beta:0 => (256,) [#0118] block_3e_conv_3/kernel:0 => (1, 1, 256, 1024) [#0119] block_3e_bn_3/gamma:0 => (1024,) [#0120] block_3e_bn_3/beta:0 => (1024,) [#0121] block_3f_conv_1/kernel:0 => (1, 1, 1024, 256) [#0122] block_3f_bn_1/gamma:0 => (256,) [#0123] block_3f_bn_1/beta:0 => (256,) [#0124] block_3f_conv_2/kernel:0 => (3, 3, 256, 256) [#0125] block_3f_bn_2/gamma:0 => (256,) [#0126] block_3f_bn_2/beta:0 => (256,) [#0127] block_3f_conv_3/kernel:0 => (1, 1, 256, 1024) [#0128] block_3f_bn_3/gamma:0 => (1024,) [#0129] block_3f_bn_3/beta:0 => (1024,) [#0130] block_4a_conv_1/kernel:0 => (1, 1, 1024, 512) [#0131] block_4a_bn_1/gamma:0 => (512,) [#0132] block_4a_bn_1/beta:0 => (512,) [#0133] block_4a_conv_2/kernel:0 => (3, 3, 512, 512) [#0134] block_4a_bn_2/gamma:0 => (512,) [#0135] block_4a_bn_2/beta:0 => (512,) [#0136] block_4a_conv_3/kernel:0 => (1, 1, 512, 2048) [#0137] block_4a_bn_3/gamma:0 => (2048,) [#0138] block_4a_bn_3/beta:0 => (2048,) [#0139] block_4a_conv_shortcut/kernel:0 => (1, 1, 1024, 2048) [#0140] block_4a_bn_shortcut/gamma:0 => (2048,) [#0141] block_4a_bn_shortcut/beta:0 => (2048,) [#0142] block_4b_conv_1/kernel:0 => (1, 1, 2048, 512) [#0143] block_4b_bn_1/gamma:0 => (512,) [#0144] block_4b_bn_1/beta:0 => (512,) [#0145] block_4b_conv_2/kernel:0 => (3, 3, 512, 512) [#0146] block_4b_bn_2/gamma:0 => (512,) [#0147] block_4b_bn_2/beta:0 => (512,) [#0148] block_4b_conv_3/kernel:0 => (1, 1, 512, 2048) [#0149] block_4b_bn_3/gamma:0 => (2048,) [#0150] block_4b_bn_3/beta:0 => (2048,) [#0151] block_4c_conv_1/kernel:0 => (1, 1, 2048, 512) [#0152] block_4c_bn_1/gamma:0 => (512,) [#0153] block_4c_bn_1/beta:0 => (512,) [#0154] block_4c_conv_2/kernel:0 => (3, 3, 512, 512) [#0155] block_4c_bn_2/gamma:0 => (512,) [#0156] block_4c_bn_2/beta:0 => (512,) [#0157] block_4c_conv_3/kernel:0 => (1, 1, 512, 2048) [#0158] block_4c_bn_3/gamma:0 => (2048,) [#0159] block_4c_bn_3/beta:0 => (2048,) [#0160] l2/kernel:0 => (1, 1, 256, 256) [#0161] l2/bias:0 => (256,) [#0162] l3/kernel:0 => (1, 1, 512, 256) [#0163] l3/bias:0 => (256,) [#0164] l4/kernel:0 => (1, 1, 1024, 256) [#0165] l4/bias:0 => (256,) [#0166] l5/kernel:0 => (1, 1, 2048, 256) [#0167] l5/bias:0 => (256,) [#0168] post_hoc_d2/kernel:0 => (3, 3, 256, 256) [#0169] post_hoc_d2/bias:0 => (256,) [#0170] post_hoc_d3/kernel:0 => (3, 3, 256, 256) [#0171] post_hoc_d3/bias:0 => (256,) [#0172] post_hoc_d4/kernel:0 => (3, 3, 256, 256) [#0173] post_hoc_d4/bias:0 => (256,) [#0174] post_hoc_d5/kernel:0 => (3, 3, 256, 256) [#0175] post_hoc_d5/bias:0 => (256,) [#0176] rpn/kernel:0 => (3, 3, 256, 256) [#0177] rpn/bias:0 => (256,) [#0178] rpn-class/kernel:0 => (1, 1, 256, 3) [#0179] rpn-class/bias:0 => (3,) [#0180] rpn-box/kernel:0 => (1, 1, 256, 12) [#0181] rpn-box/bias:0 => (12,) [#0182] fc6/kernel:0 => (12544, 1024) [#0183] fc6/bias:0 => (1024,) [#0184] fc7/kernel:0 => (1024, 1024) [#0185] fc7/bias:0 => (1024,) [#0186] class-predict/kernel:0 => (1024, 19) [#0187] class-predict/bias:0 => (19,) [#0188] box-predict/kernel:0 => (1024, 76) [#0189] box-predict/bias:0 => (76,) [#0190] mask-conv-l0/kernel:0 => (3, 3, 256, 256) [#0191] mask-conv-l0/bias:0 => (256,) [#0192] mask-conv-l1/kernel:0 => (3, 3, 256, 256) [#0193] mask-conv-l1/bias:0 => (256,) [#0194] mask-conv-l2/kernel:0 => (3, 3, 256, 256) [#0195] mask-conv-l2/bias:0 => (256,) [#0196] mask-conv-l3/kernel:0 => (3, 3, 256, 256) [#0197] mask-conv-l3/bias:0 => (256,) [#0198] conv5-mask/kernel:0 => (2, 2, 256, 256) [#0199] conv5-mask/bias:0 => (256,) [#0200] mask_fcn_logits/kernel:0 => (1, 1, 256, 19) [#0201] mask_fcn_logits/bias:0 => (19,) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # ============================================= # Start Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # Pretrained weights loaded with success... Saving checkpoints for 0 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-0.tlt. timestamp: 1654915781.0045521 iteration: 5 throughput: 2.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09499 FastRCNN class loss: 0.29677 FastRCNN total loss: 0.39175 L1 loss: 0.0000e+00 L2 loss: 2.24264 Learning rate: 0.00018 Mask loss: 1.20578 RPN box loss: 0.16357 RPN score loss: 0.67579 RPN total loss: 0.83936 Total loss: 4.67953 timestamp: 1654915784.2905755 iteration: 10 throughput: 25.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.00076 FastRCNN class loss: 0.05642 FastRCNN total loss: 0.05717 L1 loss: 0.0000e+00 L2 loss: 2.24264 Learning rate: 0.00028 Mask loss: 1.07268 RPN box loss: 0.06853 RPN score loss: 0.60748 RPN total loss: 0.67601 Total loss: 4.0485 timestamp: 1654915787.390147 iteration: 15 throughput: 26.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12704 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.17582 L1 loss: 0.0000e+00 L2 loss: 2.24263 Learning rate: 0.00038 Mask loss: 0.68078 RPN box loss: 0.02377 RPN score loss: 0.49393 RPN total loss: 0.51771 Total loss: 3.61693 timestamp: 1654915790.54143 iteration: 20 throughput: 25.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.6341 FastRCNN class loss: 0.17179 FastRCNN total loss: 0.80589 L1 loss: 0.0000e+00 L2 loss: 2.24262 Learning rate: 0.00048 Mask loss: 0.67487 RPN box loss: 0.1131 RPN score loss: 0.32988 RPN total loss: 0.44297 Total loss: 4.16635 timestamp: 1654915793.6295133 iteration: 25 throughput: 25.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.57696 FastRCNN class loss: 0.14076 FastRCNN total loss: 0.71772 L1 loss: 0.0000e+00 L2 loss: 2.2426 Learning rate: 0.00058 Mask loss: 0.62703 RPN box loss: 0.17888 RPN score loss: 0.17971 RPN total loss: 0.35859 Total loss: 3.94594 timestamp: 1654915796.739582 iteration: 30 throughput: 25.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53901 FastRCNN class loss: 0.22229 FastRCNN total loss: 0.76131 L1 loss: 0.0000e+00 L2 loss: 2.24259 Learning rate: 0.00068 Mask loss: 0.60932 RPN box loss: 0.02334 RPN score loss: 0.12091 RPN total loss: 0.14425 Total loss: 3.75747 timestamp: 1654915799.8533642 iteration: 35 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54031 FastRCNN class loss: 0.18731 FastRCNN total loss: 0.72762 L1 loss: 0.0000e+00 L2 loss: 2.24257 Learning rate: 0.00078 Mask loss: 0.65826 RPN box loss: 0.02625 RPN score loss: 0.09519 RPN total loss: 0.12144 Total loss: 3.74989 timestamp: 1654915802.9563098 iteration: 40 throughput: 25.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51924 FastRCNN class loss: 0.19218 FastRCNN total loss: 0.71142 L1 loss: 0.0000e+00 L2 loss: 2.24255 Learning rate: 0.00088 Mask loss: 0.58451 RPN box loss: 0.04061 RPN score loss: 0.06726 RPN total loss: 0.10787 Total loss: 3.64635 timestamp: 1654915806.0925603 iteration: 45 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51794 FastRCNN class loss: 0.19749 FastRCNN total loss: 0.71543 L1 loss: 0.0000e+00 L2 loss: 2.24253 Learning rate: 0.00098 Mask loss: 0.50735 RPN box loss: 0.0645 RPN score loss: 0.05864 RPN total loss: 0.12314 Total loss: 3.58846 timestamp: 1654915809.1588006 iteration: 50 throughput: 26.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52218 FastRCNN class loss: 0.16266 FastRCNN total loss: 0.68484 L1 loss: 0.0000e+00 L2 loss: 2.24251 Learning rate: 0.00108 Mask loss: 0.6767 RPN box loss: 0.04795 RPN score loss: 0.04703 RPN total loss: 0.09498 Total loss: 3.69903 timestamp: 1654915812.266243 iteration: 55 throughput: 26.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45598 FastRCNN class loss: 0.15452 FastRCNN total loss: 0.61051 L1 loss: 0.0000e+00 L2 loss: 2.24248 Learning rate: 0.00117 Mask loss: 0.52122 RPN box loss: 0.18226 RPN score loss: 0.05059 RPN total loss: 0.23286 Total loss: 3.60706 timestamp: 1654915815.423953 iteration: 60 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5768 FastRCNN class loss: 0.35631 FastRCNN total loss: 0.9331 L1 loss: 0.0000e+00 L2 loss: 2.24245 Learning rate: 0.00127 Mask loss: 0.66925 RPN box loss: 0.04631 RPN score loss: 0.05081 RPN total loss: 0.09712 Total loss: 3.94192 timestamp: 1654915818.489287 iteration: 65 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47704 FastRCNN class loss: 0.1646 FastRCNN total loss: 0.64164 L1 loss: 0.0000e+00 L2 loss: 2.24242 Learning rate: 0.00137 Mask loss: 0.52633 RPN box loss: 0.09088 RPN score loss: 0.03786 RPN total loss: 0.12874 Total loss: 3.53914 timestamp: 1654915821.4674556 iteration: 70 throughput: 27.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53118 FastRCNN class loss: 0.2371 FastRCNN total loss: 0.76828 L1 loss: 0.0000e+00 L2 loss: 2.24239 Learning rate: 0.00147 Mask loss: 0.43199 RPN box loss: 0.1103 RPN score loss: 0.04178 RPN total loss: 0.15208 Total loss: 3.59475 timestamp: 1654915824.5475373 iteration: 75 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54812 FastRCNN class loss: 0.21401 FastRCNN total loss: 0.76213 L1 loss: 0.0000e+00 L2 loss: 2.24236 Learning rate: 0.00157 Mask loss: 0.47071 RPN box loss: 0.07888 RPN score loss: 0.04435 RPN total loss: 0.12322 Total loss: 3.59842 timestamp: 1654915827.639852 iteration: 80 throughput: 26.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50893 FastRCNN class loss: 0.10197 FastRCNN total loss: 0.6109 L1 loss: 0.0000e+00 L2 loss: 2.24232 Learning rate: 0.00167 Mask loss: 0.43663 RPN box loss: 0.0801 RPN score loss: 0.0323 RPN total loss: 0.1124 Total loss: 3.40225 timestamp: 1654915830.6851976 iteration: 85 throughput: 26.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55726 FastRCNN class loss: 0.22459 FastRCNN total loss: 0.78185 L1 loss: 0.0000e+00 L2 loss: 2.24228 Learning rate: 0.00177 Mask loss: 0.57439 RPN box loss: 0.06589 RPN score loss: 0.04891 RPN total loss: 0.1148 Total loss: 3.71333 timestamp: 1654915833.786059 iteration: 90 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53291 FastRCNN class loss: 0.14512 FastRCNN total loss: 0.67804 L1 loss: 0.0000e+00 L2 loss: 2.24224 Learning rate: 0.00187 Mask loss: 0.6206 RPN box loss: 0.05997 RPN score loss: 0.02869 RPN total loss: 0.08866 Total loss: 3.62954 timestamp: 1654915836.7935379 iteration: 95 throughput: 26.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49165 FastRCNN class loss: 0.12364 FastRCNN total loss: 0.61529 L1 loss: 0.0000e+00 L2 loss: 2.2422 Learning rate: 0.00197 Mask loss: 0.44419 RPN box loss: 0.0322 RPN score loss: 0.02507 RPN total loss: 0.05727 Total loss: 3.35895 timestamp: 1654915839.8669567 iteration: 100 throughput: 26.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44626 FastRCNN class loss: 0.10522 FastRCNN total loss: 0.55148 L1 loss: 0.0000e+00 L2 loss: 2.24216 Learning rate: 0.00207 Mask loss: 0.50772 RPN box loss: 0.07474 RPN score loss: 0.03481 RPN total loss: 0.10955 Total loss: 3.41091 timestamp: 1654915842.9912174 iteration: 105 throughput: 25.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54716 FastRCNN class loss: 0.16176 FastRCNN total loss: 0.70892 L1 loss: 0.0000e+00 L2 loss: 2.24212 Learning rate: 0.00217 Mask loss: 0.54172 RPN box loss: 0.06859 RPN score loss: 0.04628 RPN total loss: 0.11487 Total loss: 3.60763 timestamp: 1654915846.053702 iteration: 110 throughput: 26.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50942 FastRCNN class loss: 0.09404 FastRCNN total loss: 0.60346 L1 loss: 0.0000e+00 L2 loss: 2.24208 Learning rate: 0.00227 Mask loss: 0.5069 RPN box loss: 0.04407 RPN score loss: 0.03557 RPN total loss: 0.07964 Total loss: 3.43208 timestamp: 1654915849.114955 iteration: 115 throughput: 26.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50926 FastRCNN class loss: 0.14125 FastRCNN total loss: 0.65051 L1 loss: 0.0000e+00 L2 loss: 2.24203 Learning rate: 0.00237 Mask loss: 0.54738 RPN box loss: 0.04642 RPN score loss: 0.03351 RPN total loss: 0.07993 Total loss: 3.51985 timestamp: 1654915852.083869 iteration: 120 throughput: 26.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4561 FastRCNN class loss: 0.08183 FastRCNN total loss: 0.53793 L1 loss: 0.0000e+00 L2 loss: 2.24198 Learning rate: 0.00247 Mask loss: 0.34531 RPN box loss: 0.01207 RPN score loss: 0.01877 RPN total loss: 0.03084 Total loss: 3.15605 timestamp: 1654915855.1341934 iteration: 125 throughput: 26.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51787 FastRCNN class loss: 0.16004 FastRCNN total loss: 0.67791 L1 loss: 0.0000e+00 L2 loss: 2.24193 Learning rate: 0.00257 Mask loss: 0.43087 RPN box loss: 0.0707 RPN score loss: 0.03295 RPN total loss: 0.10365 Total loss: 3.45436 timestamp: 1654915858.21721 iteration: 130 throughput: 26.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46931 FastRCNN class loss: 0.17699 FastRCNN total loss: 0.6463 L1 loss: 0.0000e+00 L2 loss: 2.24188 Learning rate: 0.00267 Mask loss: 0.48061 RPN box loss: 0.15909 RPN score loss: 0.0375 RPN total loss: 0.19659 Total loss: 3.56538 timestamp: 1654915861.3472288 iteration: 135 throughput: 26.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41205 FastRCNN class loss: 0.12199 FastRCNN total loss: 0.53404 L1 loss: 0.0000e+00 L2 loss: 2.24183 Learning rate: 0.00277 Mask loss: 0.34975 RPN box loss: 0.07563 RPN score loss: 0.03609 RPN total loss: 0.11172 Total loss: 3.23734 timestamp: 1654915864.4851549 iteration: 140 throughput: 26.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54891 FastRCNN class loss: 0.18279 FastRCNN total loss: 0.73171 L1 loss: 0.0000e+00 L2 loss: 2.24177 Learning rate: 0.00287 Mask loss: 0.51045 RPN box loss: 0.05801 RPN score loss: 0.02839 RPN total loss: 0.0864 Total loss: 3.57033 timestamp: 1654915867.579215 iteration: 145 throughput: 26.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51252 FastRCNN class loss: 0.15237 FastRCNN total loss: 0.6649 L1 loss: 0.0000e+00 L2 loss: 2.24173 Learning rate: 0.00297 Mask loss: 0.52731 RPN box loss: 0.04005 RPN score loss: 0.02389 RPN total loss: 0.06393 Total loss: 3.49787 timestamp: 1654915870.6127386 iteration: 150 throughput: 26.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49684 FastRCNN class loss: 0.15613 FastRCNN total loss: 0.65297 L1 loss: 0.0000e+00 L2 loss: 2.24168 Learning rate: 0.00307 Mask loss: 0.51638 RPN box loss: 0.05969 RPN score loss: 0.03411 RPN total loss: 0.0938 Total loss: 3.50483 timestamp: 1654915873.7367845 iteration: 155 throughput: 26.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51043 FastRCNN class loss: 0.10362 FastRCNN total loss: 0.61405 L1 loss: 0.0000e+00 L2 loss: 2.24164 Learning rate: 0.00316 Mask loss: 0.38096 RPN box loss: 0.02748 RPN score loss: 0.01852 RPN total loss: 0.04601 Total loss: 3.28266 timestamp: 1654915876.8550456 iteration: 160 throughput: 26.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56044 FastRCNN class loss: 0.21791 FastRCNN total loss: 0.77836 L1 loss: 0.0000e+00 L2 loss: 2.24159 Learning rate: 0.00326 Mask loss: 0.42406 RPN box loss: 0.02902 RPN score loss: 0.02381 RPN total loss: 0.05283 Total loss: 3.49684 timestamp: 1654915879.9971116 iteration: 165 throughput: 25.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41471 FastRCNN class loss: 0.10686 FastRCNN total loss: 0.52157 L1 loss: 0.0000e+00 L2 loss: 2.24153 Learning rate: 0.00336 Mask loss: 0.42214 RPN box loss: 0.10933 RPN score loss: 0.02807 RPN total loss: 0.13739 Total loss: 3.32263 timestamp: 1654915883.1216364 iteration: 170 throughput: 25.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42343 FastRCNN class loss: 0.11542 FastRCNN total loss: 0.53886 L1 loss: 0.0000e+00 L2 loss: 2.24147 Learning rate: 0.00346 Mask loss: 0.50101 RPN box loss: 0.10763 RPN score loss: 0.04187 RPN total loss: 0.14951 Total loss: 3.43084 timestamp: 1654915886.2444615 iteration: 175 throughput: 25.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47994 FastRCNN class loss: 0.10806 FastRCNN total loss: 0.588 L1 loss: 0.0000e+00 L2 loss: 2.2414 Learning rate: 0.00356 Mask loss: 0.43015 RPN box loss: 0.02532 RPN score loss: 0.02822 RPN total loss: 0.05354 Total loss: 3.31309 timestamp: 1654915889.4654834 iteration: 180 throughput: 25.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43283 FastRCNN class loss: 0.12667 FastRCNN total loss: 0.5595 L1 loss: 0.0000e+00 L2 loss: 2.24133 Learning rate: 0.00366 Mask loss: 0.38318 RPN box loss: 0.09255 RPN score loss: 0.03294 RPN total loss: 0.12549 Total loss: 3.30949 timestamp: 1654915892.5710855 iteration: 185 throughput: 25.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49493 FastRCNN class loss: 0.19653 FastRCNN total loss: 0.69146 L1 loss: 0.0000e+00 L2 loss: 2.24125 Learning rate: 0.00376 Mask loss: 0.44731 RPN box loss: 0.11065 RPN score loss: 0.07215 RPN total loss: 0.1828 Total loss: 3.56281 timestamp: 1654915895.8200853 iteration: 190 throughput: 25.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4716 FastRCNN class loss: 0.11031 FastRCNN total loss: 0.58191 L1 loss: 0.0000e+00 L2 loss: 2.24117 Learning rate: 0.00386 Mask loss: 0.37921 RPN box loss: 0.09692 RPN score loss: 0.03608 RPN total loss: 0.133 Total loss: 3.33529 timestamp: 1654915899.0119028 iteration: 195 throughput: 25.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42602 FastRCNN class loss: 0.15056 FastRCNN total loss: 0.57659 L1 loss: 0.0000e+00 L2 loss: 2.24109 Learning rate: 0.00396 Mask loss: 0.49664 RPN box loss: 0.13174 RPN score loss: 0.02828 RPN total loss: 0.16002 Total loss: 3.47434 timestamp: 1654915902.2118478 iteration: 200 throughput: 25.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34604 FastRCNN class loss: 0.11818 FastRCNN total loss: 0.46423 L1 loss: 0.0000e+00 L2 loss: 2.24101 Learning rate: 0.00406 Mask loss: 0.36788 RPN box loss: 0.15396 RPN score loss: 0.0292 RPN total loss: 0.18316 Total loss: 3.25627 timestamp: 1654915905.5063264 iteration: 205 throughput: 25.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35963 FastRCNN class loss: 0.14266 FastRCNN total loss: 0.50229 L1 loss: 0.0000e+00 L2 loss: 2.24092 Learning rate: 0.00416 Mask loss: 0.36531 RPN box loss: 0.09644 RPN score loss: 0.03699 RPN total loss: 0.13344 Total loss: 3.24195 timestamp: 1654915908.7068574 iteration: 210 throughput: 25.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50787 FastRCNN class loss: 0.19113 FastRCNN total loss: 0.69899 L1 loss: 0.0000e+00 L2 loss: 2.24084 Learning rate: 0.00426 Mask loss: 0.52552 RPN box loss: 0.07917 RPN score loss: 0.03072 RPN total loss: 0.10989 Total loss: 3.57524 timestamp: 1654915911.8764193 iteration: 215 throughput: 25.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39455 FastRCNN class loss: 0.17247 FastRCNN total loss: 0.56702 L1 loss: 0.0000e+00 L2 loss: 2.24075 Learning rate: 0.00436 Mask loss: 0.3845 RPN box loss: 0.06665 RPN score loss: 0.02323 RPN total loss: 0.08988 Total loss: 3.28215 timestamp: 1654915915.216698 iteration: 220 throughput: 25.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36333 FastRCNN class loss: 0.15375 FastRCNN total loss: 0.51708 L1 loss: 0.0000e+00 L2 loss: 2.24066 Learning rate: 0.00446 Mask loss: 0.37191 RPN box loss: 0.07109 RPN score loss: 0.02238 RPN total loss: 0.09346 Total loss: 3.22311 timestamp: 1654915918.561205 iteration: 225 throughput: 25.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39043 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.48126 L1 loss: 0.0000e+00 L2 loss: 2.24057 Learning rate: 0.00456 Mask loss: 0.4651 RPN box loss: 0.06276 RPN score loss: 0.01863 RPN total loss: 0.08139 Total loss: 3.26832 timestamp: 1654915922.0555625 iteration: 230 throughput: 25.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5369 FastRCNN class loss: 0.17246 FastRCNN total loss: 0.70936 L1 loss: 0.0000e+00 L2 loss: 2.24047 Learning rate: 0.00466 Mask loss: 0.48097 RPN box loss: 0.03637 RPN score loss: 0.0309 RPN total loss: 0.06728 Total loss: 3.49808 timestamp: 1654915925.2703347 iteration: 235 throughput: 25.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31433 FastRCNN class loss: 0.11846 FastRCNN total loss: 0.43279 L1 loss: 0.0000e+00 L2 loss: 2.24037 Learning rate: 0.00476 Mask loss: 0.35342 RPN box loss: 0.01573 RPN score loss: 0.02171 RPN total loss: 0.03744 Total loss: 3.06403 timestamp: 1654915928.82221 iteration: 240 throughput: 25.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39555 FastRCNN class loss: 0.09701 FastRCNN total loss: 0.49256 L1 loss: 0.0000e+00 L2 loss: 2.24027 Learning rate: 0.00486 Mask loss: 0.372 RPN box loss: 0.04086 RPN score loss: 0.01649 RPN total loss: 0.05735 Total loss: 3.16218 timestamp: 1654915932.051454 iteration: 245 throughput: 25.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44693 FastRCNN class loss: 0.12268 FastRCNN total loss: 0.56962 L1 loss: 0.0000e+00 L2 loss: 2.24017 Learning rate: 0.00496 Mask loss: 0.37654 RPN box loss: 0.07578 RPN score loss: 0.03168 RPN total loss: 0.10747 Total loss: 3.2938 timestamp: 1654915935.2958086 iteration: 250 throughput: 25.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35425 FastRCNN class loss: 0.12093 FastRCNN total loss: 0.47519 L1 loss: 0.0000e+00 L2 loss: 2.24007 Learning rate: 0.00506 Mask loss: 0.46337 RPN box loss: 0.02467 RPN score loss: 0.01774 RPN total loss: 0.04242 Total loss: 3.22104 timestamp: 1654915938.6110945 iteration: 255 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35218 FastRCNN class loss: 0.10299 FastRCNN total loss: 0.45517 L1 loss: 0.0000e+00 L2 loss: 2.23997 Learning rate: 0.00515 Mask loss: 0.3568 RPN box loss: 0.02055 RPN score loss: 0.0259 RPN total loss: 0.04645 Total loss: 3.09839 timestamp: 1654915941.8922863 iteration: 260 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3712 FastRCNN class loss: 0.14808 FastRCNN total loss: 0.51927 L1 loss: 0.0000e+00 L2 loss: 2.23986 Learning rate: 0.00525 Mask loss: 0.36455 RPN box loss: 0.02272 RPN score loss: 0.02718 RPN total loss: 0.0499 Total loss: 3.17359 timestamp: 1654915945.1624153 iteration: 265 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41247 FastRCNN class loss: 0.12263 FastRCNN total loss: 0.5351 L1 loss: 0.0000e+00 L2 loss: 2.23976 Learning rate: 0.00535 Mask loss: 0.34862 RPN box loss: 0.09108 RPN score loss: 0.03373 RPN total loss: 0.12482 Total loss: 3.2483 timestamp: 1654915948.594956 iteration: 270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3905 FastRCNN class loss: 0.14712 FastRCNN total loss: 0.53762 L1 loss: 0.0000e+00 L2 loss: 2.23965 Learning rate: 0.00545 Mask loss: 0.41917 RPN box loss: 0.03716 RPN score loss: 0.022 RPN total loss: 0.05915 Total loss: 3.2556 timestamp: 1654915952.0858197 iteration: 275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45842 FastRCNN class loss: 0.19099 FastRCNN total loss: 0.64941 L1 loss: 0.0000e+00 L2 loss: 2.23954 Learning rate: 0.00555 Mask loss: 0.5179 RPN box loss: 0.03609 RPN score loss: 0.01966 RPN total loss: 0.05576 Total loss: 3.4626 timestamp: 1654915955.414387 iteration: 280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52796 FastRCNN class loss: 0.20464 FastRCNN total loss: 0.7326 L1 loss: 0.0000e+00 L2 loss: 2.23942 Learning rate: 0.00565 Mask loss: 0.55468 RPN box loss: 0.02734 RPN score loss: 0.02312 RPN total loss: 0.05045 Total loss: 3.57716 timestamp: 1654915958.7986336 iteration: 285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3285 FastRCNN class loss: 0.13419 FastRCNN total loss: 0.46269 L1 loss: 0.0000e+00 L2 loss: 2.23931 Learning rate: 0.00575 Mask loss: 0.28418 RPN box loss: 0.04618 RPN score loss: 0.0196 RPN total loss: 0.06578 Total loss: 3.05196 timestamp: 1654915962.1113381 iteration: 290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33793 FastRCNN class loss: 0.12506 FastRCNN total loss: 0.463 L1 loss: 0.0000e+00 L2 loss: 2.23919 Learning rate: 0.00585 Mask loss: 0.39026 RPN box loss: 0.06985 RPN score loss: 0.01531 RPN total loss: 0.08516 Total loss: 3.17761 timestamp: 1654915965.388647 iteration: 295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34622 FastRCNN class loss: 0.10463 FastRCNN total loss: 0.45084 L1 loss: 0.0000e+00 L2 loss: 2.23907 Learning rate: 0.00595 Mask loss: 0.34368 RPN box loss: 0.14209 RPN score loss: 0.02844 RPN total loss: 0.17053 Total loss: 3.20413 timestamp: 1654915968.7686589 iteration: 300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41291 FastRCNN class loss: 0.14292 FastRCNN total loss: 0.55583 L1 loss: 0.0000e+00 L2 loss: 2.23894 Learning rate: 0.00605 Mask loss: 0.33405 RPN box loss: 0.09256 RPN score loss: 0.03502 RPN total loss: 0.12758 Total loss: 3.25641 timestamp: 1654915972.0712607 iteration: 305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43312 FastRCNN class loss: 0.10902 FastRCNN total loss: 0.54214 L1 loss: 0.0000e+00 L2 loss: 2.23881 Learning rate: 0.00615 Mask loss: 0.50388 RPN box loss: 0.03894 RPN score loss: 0.02878 RPN total loss: 0.06772 Total loss: 3.35256 timestamp: 1654915975.3476164 iteration: 310 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33634 FastRCNN class loss: 0.15596 FastRCNN total loss: 0.49229 L1 loss: 0.0000e+00 L2 loss: 2.23868 Learning rate: 0.00625 Mask loss: 0.35625 RPN box loss: 0.06067 RPN score loss: 0.01741 RPN total loss: 0.07808 Total loss: 3.16531 timestamp: 1654915978.6723256 iteration: 315 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27783 FastRCNN class loss: 0.08792 FastRCNN total loss: 0.36575 L1 loss: 0.0000e+00 L2 loss: 2.23856 Learning rate: 0.00635 Mask loss: 0.32868 RPN box loss: 0.06035 RPN score loss: 0.02126 RPN total loss: 0.08161 Total loss: 3.0146 timestamp: 1654915981.9388933 iteration: 320 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32347 FastRCNN class loss: 0.1283 FastRCNN total loss: 0.45176 L1 loss: 0.0000e+00 L2 loss: 2.23844 Learning rate: 0.00645 Mask loss: 0.5008 RPN box loss: 0.02944 RPN score loss: 0.0143 RPN total loss: 0.04375 Total loss: 3.23475 timestamp: 1654915985.1787093 iteration: 325 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29807 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.38652 L1 loss: 0.0000e+00 L2 loss: 2.23831 Learning rate: 0.00655 Mask loss: 0.38227 RPN box loss: 0.07274 RPN score loss: 0.02029 RPN total loss: 0.09303 Total loss: 3.10013 timestamp: 1654915988.6213987 iteration: 330 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32265 FastRCNN class loss: 0.13182 FastRCNN total loss: 0.45447 L1 loss: 0.0000e+00 L2 loss: 2.23817 Learning rate: 0.00665 Mask loss: 0.4514 RPN box loss: 0.06657 RPN score loss: 0.03007 RPN total loss: 0.09665 Total loss: 3.24068 timestamp: 1654915992.0309637 iteration: 335 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36392 FastRCNN class loss: 0.12198 FastRCNN total loss: 0.4859 L1 loss: 0.0000e+00 L2 loss: 2.23804 Learning rate: 0.00675 Mask loss: 0.36046 RPN box loss: 0.06916 RPN score loss: 0.0343 RPN total loss: 0.10345 Total loss: 3.18785 timestamp: 1654915995.3222477 iteration: 340 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3779 FastRCNN class loss: 0.15493 FastRCNN total loss: 0.53284 L1 loss: 0.0000e+00 L2 loss: 2.2379 Learning rate: 0.00685 Mask loss: 0.4421 RPN box loss: 0.07588 RPN score loss: 0.01684 RPN total loss: 0.09272 Total loss: 3.30556 timestamp: 1654915998.5563912 iteration: 345 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38139 FastRCNN class loss: 0.15382 FastRCNN total loss: 0.53522 L1 loss: 0.0000e+00 L2 loss: 2.23776 Learning rate: 0.00695 Mask loss: 0.35557 RPN box loss: 0.03464 RPN score loss: 0.02979 RPN total loss: 0.06442 Total loss: 3.19297 timestamp: 1654916001.7557268 iteration: 350 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29494 FastRCNN class loss: 0.14338 FastRCNN total loss: 0.43832 L1 loss: 0.0000e+00 L2 loss: 2.23762 Learning rate: 0.00705 Mask loss: 0.37607 RPN box loss: 0.1046 RPN score loss: 0.06543 RPN total loss: 0.17003 Total loss: 3.22204 timestamp: 1654916005.0426688 iteration: 355 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32958 FastRCNN class loss: 0.08247 FastRCNN total loss: 0.41205 L1 loss: 0.0000e+00 L2 loss: 2.23747 Learning rate: 0.00714 Mask loss: 0.29506 RPN box loss: 0.07202 RPN score loss: 0.01489 RPN total loss: 0.08691 Total loss: 3.03148 timestamp: 1654916008.2984228 iteration: 360 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41432 FastRCNN class loss: 0.20315 FastRCNN total loss: 0.61747 L1 loss: 0.0000e+00 L2 loss: 2.23732 Learning rate: 0.00724 Mask loss: 0.43327 RPN box loss: 0.09414 RPN score loss: 0.02702 RPN total loss: 0.12116 Total loss: 3.40921 timestamp: 1654916011.6302202 iteration: 365 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31506 FastRCNN class loss: 0.11495 FastRCNN total loss: 0.43001 L1 loss: 0.0000e+00 L2 loss: 2.23717 Learning rate: 0.00734 Mask loss: 0.42253 RPN box loss: 0.05348 RPN score loss: 0.02251 RPN total loss: 0.07599 Total loss: 3.1657 timestamp: 1654916014.9639692 iteration: 370 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40228 FastRCNN class loss: 0.14705 FastRCNN total loss: 0.54932 L1 loss: 0.0000e+00 L2 loss: 2.23702 Learning rate: 0.00744 Mask loss: 0.30646 RPN box loss: 0.07263 RPN score loss: 0.01687 RPN total loss: 0.0895 Total loss: 3.1823 timestamp: 1654916018.2932394 iteration: 375 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33998 FastRCNN class loss: 0.1112 FastRCNN total loss: 0.45119 L1 loss: 0.0000e+00 L2 loss: 2.23686 Learning rate: 0.00754 Mask loss: 0.43902 RPN box loss: 0.08194 RPN score loss: 0.0215 RPN total loss: 0.10344 Total loss: 3.2305 timestamp: 1654916021.5744436 iteration: 380 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3787 FastRCNN class loss: 0.25022 FastRCNN total loss: 0.62892 L1 loss: 0.0000e+00 L2 loss: 2.23671 Learning rate: 0.00764 Mask loss: 0.4355 RPN box loss: 0.05548 RPN score loss: 0.02148 RPN total loss: 0.07696 Total loss: 3.37809 timestamp: 1654916024.8545485 iteration: 385 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51159 FastRCNN class loss: 0.20501 FastRCNN total loss: 0.7166 L1 loss: 0.0000e+00 L2 loss: 2.23655 Learning rate: 0.00774 Mask loss: 0.43907 RPN box loss: 0.14263 RPN score loss: 0.07685 RPN total loss: 0.21948 Total loss: 3.6117 timestamp: 1654916028.2051935 iteration: 390 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31713 FastRCNN class loss: 0.11128 FastRCNN total loss: 0.42841 L1 loss: 0.0000e+00 L2 loss: 2.23639 Learning rate: 0.00784 Mask loss: 0.46217 RPN box loss: 0.02642 RPN score loss: 0.01593 RPN total loss: 0.04235 Total loss: 3.16932 timestamp: 1654916031.4410925 iteration: 395 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35098 FastRCNN class loss: 0.16229 FastRCNN total loss: 0.51328 L1 loss: 0.0000e+00 L2 loss: 2.23622 Learning rate: 0.00794 Mask loss: 0.46694 RPN box loss: 0.11333 RPN score loss: 0.01718 RPN total loss: 0.13051 Total loss: 3.34694 timestamp: 1654916034.8929102 iteration: 400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32245 FastRCNN class loss: 0.10135 FastRCNN total loss: 0.4238 L1 loss: 0.0000e+00 L2 loss: 2.23605 Learning rate: 0.00804 Mask loss: 0.31569 RPN box loss: 0.0562 RPN score loss: 0.01822 RPN total loss: 0.07442 Total loss: 3.04996 timestamp: 1654916038.05885 iteration: 405 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3585 FastRCNN class loss: 0.15679 FastRCNN total loss: 0.51529 L1 loss: 0.0000e+00 L2 loss: 2.23588 Learning rate: 0.00814 Mask loss: 0.34293 RPN box loss: 0.01366 RPN score loss: 0.01241 RPN total loss: 0.02606 Total loss: 3.12016 timestamp: 1654916041.3603008 iteration: 410 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40146 FastRCNN class loss: 0.15424 FastRCNN total loss: 0.5557 L1 loss: 0.0000e+00 L2 loss: 2.23571 Learning rate: 0.00824 Mask loss: 0.37409 RPN box loss: 0.05714 RPN score loss: 0.04061 RPN total loss: 0.09775 Total loss: 3.26325 timestamp: 1654916044.6289856 iteration: 415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36999 FastRCNN class loss: 0.11863 FastRCNN total loss: 0.48862 L1 loss: 0.0000e+00 L2 loss: 2.23553 Learning rate: 0.00834 Mask loss: 0.29186 RPN box loss: 0.03754 RPN score loss: 0.02064 RPN total loss: 0.05818 Total loss: 3.07418 timestamp: 1654916047.9552689 iteration: 420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28055 FastRCNN class loss: 0.08781 FastRCNN total loss: 0.36835 L1 loss: 0.0000e+00 L2 loss: 2.23535 Learning rate: 0.00844 Mask loss: 0.35185 RPN box loss: 0.05474 RPN score loss: 0.01663 RPN total loss: 0.07137 Total loss: 3.02692 timestamp: 1654916051.217489 iteration: 425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38001 FastRCNN class loss: 0.13945 FastRCNN total loss: 0.51946 L1 loss: 0.0000e+00 L2 loss: 2.23517 Learning rate: 0.00854 Mask loss: 0.44292 RPN box loss: 0.10031 RPN score loss: 0.03009 RPN total loss: 0.1304 Total loss: 3.32795 timestamp: 1654916054.4390464 iteration: 430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40003 FastRCNN class loss: 0.15368 FastRCNN total loss: 0.55371 L1 loss: 0.0000e+00 L2 loss: 2.235 Learning rate: 0.00864 Mask loss: 0.38174 RPN box loss: 0.0471 RPN score loss: 0.02189 RPN total loss: 0.06899 Total loss: 3.23944 timestamp: 1654916057.752005 iteration: 435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28111 FastRCNN class loss: 0.13779 FastRCNN total loss: 0.41889 L1 loss: 0.0000e+00 L2 loss: 2.23482 Learning rate: 0.00874 Mask loss: 0.36423 RPN box loss: 0.11491 RPN score loss: 0.02884 RPN total loss: 0.14375 Total loss: 3.1617 timestamp: 1654916061.058127 iteration: 440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35789 FastRCNN class loss: 0.1282 FastRCNN total loss: 0.48608 L1 loss: 0.0000e+00 L2 loss: 2.23465 Learning rate: 0.00884 Mask loss: 0.3782 RPN box loss: 0.05451 RPN score loss: 0.0186 RPN total loss: 0.07311 Total loss: 3.17205 timestamp: 1654916064.2880664 iteration: 445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18504 FastRCNN class loss: 0.09318 FastRCNN total loss: 0.27821 L1 loss: 0.0000e+00 L2 loss: 2.23448 Learning rate: 0.00894 Mask loss: 0.31629 RPN box loss: 0.06584 RPN score loss: 0.01739 RPN total loss: 0.08323 Total loss: 2.91221 timestamp: 1654916067.4984946 iteration: 450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27082 FastRCNN class loss: 0.1025 FastRCNN total loss: 0.37332 L1 loss: 0.0000e+00 L2 loss: 2.23429 Learning rate: 0.00904 Mask loss: 0.37329 RPN box loss: 0.06136 RPN score loss: 0.03027 RPN total loss: 0.09164 Total loss: 3.07253 timestamp: 1654916070.833855 iteration: 455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27402 FastRCNN class loss: 0.17671 FastRCNN total loss: 0.45073 L1 loss: 0.0000e+00 L2 loss: 2.2341 Learning rate: 0.00913 Mask loss: 0.45253 RPN box loss: 0.11662 RPN score loss: 0.03727 RPN total loss: 0.1539 Total loss: 3.29125 timestamp: 1654916074.0796332 iteration: 460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21459 FastRCNN class loss: 0.09414 FastRCNN total loss: 0.30873 L1 loss: 0.0000e+00 L2 loss: 2.23392 Learning rate: 0.00923 Mask loss: 0.33464 RPN box loss: 0.08316 RPN score loss: 0.01864 RPN total loss: 0.10181 Total loss: 2.9791 timestamp: 1654916077.417054 iteration: 465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23295 FastRCNN class loss: 0.09656 FastRCNN total loss: 0.32951 L1 loss: 0.0000e+00 L2 loss: 2.23373 Learning rate: 0.00933 Mask loss: 0.34971 RPN box loss: 0.00857 RPN score loss: 0.01319 RPN total loss: 0.02176 Total loss: 2.9347 timestamp: 1654916080.728868 iteration: 470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35681 FastRCNN class loss: 0.19904 FastRCNN total loss: 0.55585 L1 loss: 0.0000e+00 L2 loss: 2.23352 Learning rate: 0.00943 Mask loss: 0.37494 RPN box loss: 0.08719 RPN score loss: 0.03794 RPN total loss: 0.12512 Total loss: 3.28943 timestamp: 1654916083.996708 iteration: 475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30115 FastRCNN class loss: 0.10208 FastRCNN total loss: 0.40323 L1 loss: 0.0000e+00 L2 loss: 2.23334 Learning rate: 0.00953 Mask loss: 0.36454 RPN box loss: 0.0521 RPN score loss: 0.01296 RPN total loss: 0.06506 Total loss: 3.06617 timestamp: 1654916087.2533078 iteration: 480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29192 FastRCNN class loss: 0.13559 FastRCNN total loss: 0.42751 L1 loss: 0.0000e+00 L2 loss: 2.23316 Learning rate: 0.00963 Mask loss: 0.32576 RPN box loss: 0.05086 RPN score loss: 0.01882 RPN total loss: 0.06967 Total loss: 3.05611 timestamp: 1654916090.5811892 iteration: 485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25742 FastRCNN class loss: 0.11634 FastRCNN total loss: 0.37376 L1 loss: 0.0000e+00 L2 loss: 2.23298 Learning rate: 0.00973 Mask loss: 0.28804 RPN box loss: 0.07953 RPN score loss: 0.02623 RPN total loss: 0.10575 Total loss: 3.00053 timestamp: 1654916093.9373705 iteration: 490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22591 FastRCNN class loss: 0.09307 FastRCNN total loss: 0.31897 L1 loss: 0.0000e+00 L2 loss: 2.23278 Learning rate: 0.00983 Mask loss: 0.30065 RPN box loss: 0.08521 RPN score loss: 0.03159 RPN total loss: 0.1168 Total loss: 2.9692 timestamp: 1654916097.121504 iteration: 495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4357 FastRCNN class loss: 0.14266 FastRCNN total loss: 0.57836 L1 loss: 0.0000e+00 L2 loss: 2.2326 Learning rate: 0.00993 Mask loss: 0.40144 RPN box loss: 0.05017 RPN score loss: 0.02282 RPN total loss: 0.07299 Total loss: 3.28539 timestamp: 1654916100.4566264 iteration: 500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41957 FastRCNN class loss: 0.19013 FastRCNN total loss: 0.6097 L1 loss: 0.0000e+00 L2 loss: 2.2324 Learning rate: 0.01003 Mask loss: 0.33112 RPN box loss: 0.02903 RPN score loss: 0.01377 RPN total loss: 0.0428 Total loss: 3.21601 timestamp: 1654916103.7489014 iteration: 505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44194 FastRCNN class loss: 0.11379 FastRCNN total loss: 0.55574 L1 loss: 0.0000e+00 L2 loss: 2.23221 Learning rate: 0.01013 Mask loss: 0.4534 RPN box loss: 0.01666 RPN score loss: 0.0142 RPN total loss: 0.03086 Total loss: 3.27221 timestamp: 1654916107.0729797 iteration: 510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23079 FastRCNN class loss: 0.07925 FastRCNN total loss: 0.31004 L1 loss: 0.0000e+00 L2 loss: 2.23201 Learning rate: 0.01023 Mask loss: 0.25151 RPN box loss: 0.05193 RPN score loss: 0.02016 RPN total loss: 0.07208 Total loss: 2.86564 timestamp: 1654916110.3547437 iteration: 515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2206 FastRCNN class loss: 0.11315 FastRCNN total loss: 0.33375 L1 loss: 0.0000e+00 L2 loss: 2.23179 Learning rate: 0.01033 Mask loss: 0.28402 RPN box loss: 0.06118 RPN score loss: 0.0265 RPN total loss: 0.08768 Total loss: 2.93724 timestamp: 1654916113.5493407 iteration: 520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35566 FastRCNN class loss: 0.1007 FastRCNN total loss: 0.45636 L1 loss: 0.0000e+00 L2 loss: 2.23158 Learning rate: 0.01043 Mask loss: 0.28035 RPN box loss: 0.03338 RPN score loss: 0.01488 RPN total loss: 0.04826 Total loss: 3.01655 timestamp: 1654916116.6781704 iteration: 525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25599 FastRCNN class loss: 0.10719 FastRCNN total loss: 0.36318 L1 loss: 0.0000e+00 L2 loss: 2.23137 Learning rate: 0.01053 Mask loss: 0.2974 RPN box loss: 0.13572 RPN score loss: 0.01594 RPN total loss: 0.15166 Total loss: 3.04361 timestamp: 1654916119.9223976 iteration: 530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45017 FastRCNN class loss: 0.15786 FastRCNN total loss: 0.60804 L1 loss: 0.0000e+00 L2 loss: 2.23116 Learning rate: 0.01063 Mask loss: 0.43369 RPN box loss: 0.11947 RPN score loss: 0.01854 RPN total loss: 0.13801 Total loss: 3.41089 timestamp: 1654916123.1255085 iteration: 535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30245 FastRCNN class loss: 0.15782 FastRCNN total loss: 0.46027 L1 loss: 0.0000e+00 L2 loss: 2.23093 Learning rate: 0.01073 Mask loss: 0.37806 RPN box loss: 0.03368 RPN score loss: 0.02503 RPN total loss: 0.05872 Total loss: 3.12798 timestamp: 1654916126.3342602 iteration: 540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24277 FastRCNN class loss: 0.13164 FastRCNN total loss: 0.37441 L1 loss: 0.0000e+00 L2 loss: 2.23071 Learning rate: 0.01083 Mask loss: 0.2653 RPN box loss: 0.0238 RPN score loss: 0.00947 RPN total loss: 0.03327 Total loss: 2.90369 timestamp: 1654916129.7088258 iteration: 545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3529 FastRCNN class loss: 0.12252 FastRCNN total loss: 0.47543 L1 loss: 0.0000e+00 L2 loss: 2.23049 Learning rate: 0.01093 Mask loss: 0.36653 RPN box loss: 0.09552 RPN score loss: 0.0531 RPN total loss: 0.14862 Total loss: 3.22107 timestamp: 1654916132.986074 iteration: 550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33635 FastRCNN class loss: 0.17571 FastRCNN total loss: 0.51206 L1 loss: 0.0000e+00 L2 loss: 2.23026 Learning rate: 0.01103 Mask loss: 0.43094 RPN box loss: 0.02755 RPN score loss: 0.0388 RPN total loss: 0.06636 Total loss: 3.23962 timestamp: 1654916136.2548623 iteration: 555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30415 FastRCNN class loss: 0.11645 FastRCNN total loss: 0.42059 L1 loss: 0.0000e+00 L2 loss: 2.23002 Learning rate: 0.01112 Mask loss: 0.373 RPN box loss: 0.05534 RPN score loss: 0.02812 RPN total loss: 0.08346 Total loss: 3.10707 timestamp: 1654916139.4675317 iteration: 560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40544 FastRCNN class loss: 0.16772 FastRCNN total loss: 0.57316 L1 loss: 0.0000e+00 L2 loss: 2.22979 Learning rate: 0.01122 Mask loss: 0.38551 RPN box loss: 0.07926 RPN score loss: 0.03343 RPN total loss: 0.1127 Total loss: 3.30115 timestamp: 1654916142.7169602 iteration: 565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23023 FastRCNN class loss: 0.10155 FastRCNN total loss: 0.33178 L1 loss: 0.0000e+00 L2 loss: 2.22956 Learning rate: 0.01132 Mask loss: 0.33649 RPN box loss: 0.09207 RPN score loss: 0.01693 RPN total loss: 0.109 Total loss: 3.00683 timestamp: 1654916146.052779 iteration: 570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39021 FastRCNN class loss: 0.12113 FastRCNN total loss: 0.51134 L1 loss: 0.0000e+00 L2 loss: 2.22932 Learning rate: 0.01142 Mask loss: 0.46247 RPN box loss: 0.07417 RPN score loss: 0.01943 RPN total loss: 0.0936 Total loss: 3.29673 timestamp: 1654916149.3061142 iteration: 575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25878 FastRCNN class loss: 0.08901 FastRCNN total loss: 0.34779 L1 loss: 0.0000e+00 L2 loss: 2.22909 Learning rate: 0.01152 Mask loss: 0.28034 RPN box loss: 0.03444 RPN score loss: 0.01234 RPN total loss: 0.04678 Total loss: 2.90399 timestamp: 1654916152.6549897 iteration: 580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35495 FastRCNN class loss: 0.19003 FastRCNN total loss: 0.54498 L1 loss: 0.0000e+00 L2 loss: 2.22885 Learning rate: 0.01162 Mask loss: 0.42951 RPN box loss: 0.05696 RPN score loss: 0.02177 RPN total loss: 0.07873 Total loss: 3.28207 timestamp: 1654916155.9292116 iteration: 585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33679 FastRCNN class loss: 0.1724 FastRCNN total loss: 0.50919 L1 loss: 0.0000e+00 L2 loss: 2.22861 Learning rate: 0.01172 Mask loss: 0.43478 RPN box loss: 0.02895 RPN score loss: 0.04236 RPN total loss: 0.07131 Total loss: 3.24389 timestamp: 1654916159.2018514 iteration: 590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27109 FastRCNN class loss: 0.17661 FastRCNN total loss: 0.4477 L1 loss: 0.0000e+00 L2 loss: 2.22836 Learning rate: 0.01182 Mask loss: 0.34013 RPN box loss: 0.04624 RPN score loss: 0.0153 RPN total loss: 0.06154 Total loss: 3.07773 timestamp: 1654916162.3781374 iteration: 595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30096 FastRCNN class loss: 0.13736 FastRCNN total loss: 0.43832 L1 loss: 0.0000e+00 L2 loss: 2.22812 Learning rate: 0.01192 Mask loss: 0.25948 RPN box loss: 0.0373 RPN score loss: 0.01898 RPN total loss: 0.05628 Total loss: 2.9822 timestamp: 1654916165.6429746 iteration: 600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41604 FastRCNN class loss: 0.13982 FastRCNN total loss: 0.55587 L1 loss: 0.0000e+00 L2 loss: 2.22787 Learning rate: 0.01202 Mask loss: 0.28135 RPN box loss: 0.09515 RPN score loss: 0.01964 RPN total loss: 0.11479 Total loss: 3.17987 timestamp: 1654916168.834599 iteration: 605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35963 FastRCNN class loss: 0.17439 FastRCNN total loss: 0.53403 L1 loss: 0.0000e+00 L2 loss: 2.22761 Learning rate: 0.01212 Mask loss: 0.36054 RPN box loss: 0.09127 RPN score loss: 0.01635 RPN total loss: 0.10762 Total loss: 3.22979 timestamp: 1654916172.1442654 iteration: 610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24393 FastRCNN class loss: 0.11169 FastRCNN total loss: 0.35562 L1 loss: 0.0000e+00 L2 loss: 2.22736 Learning rate: 0.01222 Mask loss: 0.41552 RPN box loss: 0.0781 RPN score loss: 0.02236 RPN total loss: 0.10045 Total loss: 3.09895 timestamp: 1654916175.3347104 iteration: 615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41607 FastRCNN class loss: 0.14236 FastRCNN total loss: 0.55842 L1 loss: 0.0000e+00 L2 loss: 2.2271 Learning rate: 0.01232 Mask loss: 0.3305 RPN box loss: 0.07485 RPN score loss: 0.02367 RPN total loss: 0.09853 Total loss: 3.21456 timestamp: 1654916178.6516197 iteration: 620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39084 FastRCNN class loss: 0.1721 FastRCNN total loss: 0.56294 L1 loss: 0.0000e+00 L2 loss: 2.22684 Learning rate: 0.01242 Mask loss: 0.33761 RPN box loss: 0.04604 RPN score loss: 0.01261 RPN total loss: 0.05865 Total loss: 3.18604 timestamp: 1654916181.9485497 iteration: 625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3061 FastRCNN class loss: 0.17053 FastRCNN total loss: 0.47663 L1 loss: 0.0000e+00 L2 loss: 2.22658 Learning rate: 0.01252 Mask loss: 0.33435 RPN box loss: 0.04238 RPN score loss: 0.01416 RPN total loss: 0.05654 Total loss: 3.09411 timestamp: 1654916185.1778638 iteration: 630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17827 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.26243 L1 loss: 0.0000e+00 L2 loss: 2.22632 Learning rate: 0.01262 Mask loss: 0.24735 RPN box loss: 0.10299 RPN score loss: 0.01407 RPN total loss: 0.11706 Total loss: 2.85316 timestamp: 1654916188.4913251 iteration: 635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29248 FastRCNN class loss: 0.10144 FastRCNN total loss: 0.39392 L1 loss: 0.0000e+00 L2 loss: 2.22605 Learning rate: 0.01272 Mask loss: 0.4293 RPN box loss: 0.02047 RPN score loss: 0.01483 RPN total loss: 0.0353 Total loss: 3.08457 timestamp: 1654916191.7887156 iteration: 640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35732 FastRCNN class loss: 0.19468 FastRCNN total loss: 0.552 L1 loss: 0.0000e+00 L2 loss: 2.22578 Learning rate: 0.01282 Mask loss: 0.34256 RPN box loss: 0.09133 RPN score loss: 0.02541 RPN total loss: 0.11674 Total loss: 3.23708 timestamp: 1654916195.1186938 iteration: 645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32677 FastRCNN class loss: 0.17506 FastRCNN total loss: 0.50183 L1 loss: 0.0000e+00 L2 loss: 2.22552 Learning rate: 0.01292 Mask loss: 0.35914 RPN box loss: 0.04377 RPN score loss: 0.01423 RPN total loss: 0.05801 Total loss: 3.1445 timestamp: 1654916198.4011724 iteration: 650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27106 FastRCNN class loss: 0.11021 FastRCNN total loss: 0.38127 L1 loss: 0.0000e+00 L2 loss: 2.22525 Learning rate: 0.01302 Mask loss: 0.29963 RPN box loss: 0.0595 RPN score loss: 0.0194 RPN total loss: 0.0789 Total loss: 2.98505 timestamp: 1654916201.7541904 iteration: 655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32914 FastRCNN class loss: 0.10823 FastRCNN total loss: 0.43737 L1 loss: 0.0000e+00 L2 loss: 2.22498 Learning rate: 0.01311 Mask loss: 0.40533 RPN box loss: 0.03136 RPN score loss: 0.01438 RPN total loss: 0.04574 Total loss: 3.11341 timestamp: 1654916204.9141912 iteration: 660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27802 FastRCNN class loss: 0.15249 FastRCNN total loss: 0.4305 L1 loss: 0.0000e+00 L2 loss: 2.2247 Learning rate: 0.01321 Mask loss: 0.54113 RPN box loss: 0.13416 RPN score loss: 0.02345 RPN total loss: 0.15761 Total loss: 3.35395 timestamp: 1654916208.28275 iteration: 665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32453 FastRCNN class loss: 0.12907 FastRCNN total loss: 0.4536 L1 loss: 0.0000e+00 L2 loss: 2.22442 Learning rate: 0.01331 Mask loss: 0.3424 RPN box loss: 0.03125 RPN score loss: 0.01656 RPN total loss: 0.04781 Total loss: 3.06824 timestamp: 1654916211.6560886 iteration: 670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33148 FastRCNN class loss: 0.1381 FastRCNN total loss: 0.46958 L1 loss: 0.0000e+00 L2 loss: 2.22415 Learning rate: 0.01341 Mask loss: 0.36926 RPN box loss: 0.04256 RPN score loss: 0.01675 RPN total loss: 0.05931 Total loss: 3.1223 timestamp: 1654916214.9314482 iteration: 675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20326 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.26545 L1 loss: 0.0000e+00 L2 loss: 2.22387 Learning rate: 0.01351 Mask loss: 0.25034 RPN box loss: 0.00616 RPN score loss: 0.00685 RPN total loss: 0.01301 Total loss: 2.75267 timestamp: 1654916218.2890701 iteration: 680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31742 FastRCNN class loss: 0.10792 FastRCNN total loss: 0.42534 L1 loss: 0.0000e+00 L2 loss: 2.22358 Learning rate: 0.01361 Mask loss: 0.2409 RPN box loss: 0.06548 RPN score loss: 0.01513 RPN total loss: 0.08061 Total loss: 2.97043 timestamp: 1654916221.499016 iteration: 685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24489 FastRCNN class loss: 0.11298 FastRCNN total loss: 0.35787 L1 loss: 0.0000e+00 L2 loss: 2.2233 Learning rate: 0.01371 Mask loss: 0.3828 RPN box loss: 0.05211 RPN score loss: 0.018 RPN total loss: 0.07012 Total loss: 3.03408 timestamp: 1654916224.8650184 iteration: 690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3597 FastRCNN class loss: 0.18798 FastRCNN total loss: 0.54768 L1 loss: 0.0000e+00 L2 loss: 2.22302 Learning rate: 0.01381 Mask loss: 0.38844 RPN box loss: 0.05319 RPN score loss: 0.01753 RPN total loss: 0.07071 Total loss: 3.22985 timestamp: 1654916228.1084473 iteration: 695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32094 FastRCNN class loss: 0.1521 FastRCNN total loss: 0.47304 L1 loss: 0.0000e+00 L2 loss: 2.22275 Learning rate: 0.01391 Mask loss: 0.45053 RPN box loss: 0.08851 RPN score loss: 0.01854 RPN total loss: 0.10705 Total loss: 3.25337 timestamp: 1654916231.3929648 iteration: 700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22684 FastRCNN class loss: 0.12621 FastRCNN total loss: 0.35305 L1 loss: 0.0000e+00 L2 loss: 2.22246 Learning rate: 0.01401 Mask loss: 0.3584 RPN box loss: 0.04898 RPN score loss: 0.02791 RPN total loss: 0.07688 Total loss: 3.01079 timestamp: 1654916234.6093085 iteration: 705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3151 FastRCNN class loss: 0.09434 FastRCNN total loss: 0.40945 L1 loss: 0.0000e+00 L2 loss: 2.22217 Learning rate: 0.01411 Mask loss: 0.35705 RPN box loss: 0.01805 RPN score loss: 0.00952 RPN total loss: 0.02757 Total loss: 3.01624 timestamp: 1654916237.980656 iteration: 710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25839 FastRCNN class loss: 0.07948 FastRCNN total loss: 0.33787 L1 loss: 0.0000e+00 L2 loss: 2.22188 Learning rate: 0.01421 Mask loss: 0.26061 RPN box loss: 0.03014 RPN score loss: 0.01622 RPN total loss: 0.04636 Total loss: 2.86673 timestamp: 1654916241.289756 iteration: 715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23361 FastRCNN class loss: 0.09796 FastRCNN total loss: 0.33158 L1 loss: 0.0000e+00 L2 loss: 2.22158 Learning rate: 0.01431 Mask loss: 0.28335 RPN box loss: 0.03838 RPN score loss: 0.00863 RPN total loss: 0.04701 Total loss: 2.88351 timestamp: 1654916244.5908217 iteration: 720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32202 FastRCNN class loss: 0.11474 FastRCNN total loss: 0.43676 L1 loss: 0.0000e+00 L2 loss: 2.22129 Learning rate: 0.01441 Mask loss: 0.25561 RPN box loss: 0.08236 RPN score loss: 0.01848 RPN total loss: 0.10084 Total loss: 3.0145 timestamp: 1654916247.8879352 iteration: 725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33306 FastRCNN class loss: 0.11274 FastRCNN total loss: 0.4458 L1 loss: 0.0000e+00 L2 loss: 2.22098 Learning rate: 0.01451 Mask loss: 0.34392 RPN box loss: 0.02569 RPN score loss: 0.01037 RPN total loss: 0.03606 Total loss: 3.04676 timestamp: 1654916251.103063 iteration: 730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22667 FastRCNN class loss: 0.11221 FastRCNN total loss: 0.33889 L1 loss: 0.0000e+00 L2 loss: 2.22067 Learning rate: 0.01461 Mask loss: 0.27502 RPN box loss: 0.04811 RPN score loss: 0.01499 RPN total loss: 0.0631 Total loss: 2.89768 timestamp: 1654916254.4365447 iteration: 735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23256 FastRCNN class loss: 0.12237 FastRCNN total loss: 0.35493 L1 loss: 0.0000e+00 L2 loss: 2.22037 Learning rate: 0.01471 Mask loss: 0.23967 RPN box loss: 0.05466 RPN score loss: 0.02068 RPN total loss: 0.07535 Total loss: 2.89031 timestamp: 1654916257.7721841 iteration: 740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32488 FastRCNN class loss: 0.10424 FastRCNN total loss: 0.42912 L1 loss: 0.0000e+00 L2 loss: 2.22007 Learning rate: 0.01481 Mask loss: 0.35129 RPN box loss: 0.05367 RPN score loss: 0.0246 RPN total loss: 0.07827 Total loss: 3.07874 timestamp: 1654916261.1819875 iteration: 745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3442 FastRCNN class loss: 0.1388 FastRCNN total loss: 0.483 L1 loss: 0.0000e+00 L2 loss: 2.21976 Learning rate: 0.01491 Mask loss: 0.51733 RPN box loss: 0.03992 RPN score loss: 0.01395 RPN total loss: 0.05387 Total loss: 3.27396 timestamp: 1654916264.44072 iteration: 750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34175 FastRCNN class loss: 0.13829 FastRCNN total loss: 0.48004 L1 loss: 0.0000e+00 L2 loss: 2.21944 Learning rate: 0.01501 Mask loss: 0.29872 RPN box loss: 0.07615 RPN score loss: 0.03452 RPN total loss: 0.11067 Total loss: 3.10887 timestamp: 1654916267.7652833 iteration: 755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24433 FastRCNN class loss: 0.13844 FastRCNN total loss: 0.38277 L1 loss: 0.0000e+00 L2 loss: 2.21912 Learning rate: 0.0151 Mask loss: 0.40381 RPN box loss: 0.10339 RPN score loss: 0.02592 RPN total loss: 0.12931 Total loss: 3.13502 timestamp: 1654916271.0931695 iteration: 760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26687 FastRCNN class loss: 0.13259 FastRCNN total loss: 0.39946 L1 loss: 0.0000e+00 L2 loss: 2.21882 Learning rate: 0.0152 Mask loss: 0.23781 RPN box loss: 0.04697 RPN score loss: 0.01807 RPN total loss: 0.06504 Total loss: 2.92113 timestamp: 1654916274.4694746 iteration: 765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28704 FastRCNN class loss: 0.13235 FastRCNN total loss: 0.41939 L1 loss: 0.0000e+00 L2 loss: 2.21852 Learning rate: 0.0153 Mask loss: 0.31893 RPN box loss: 0.05794 RPN score loss: 0.01853 RPN total loss: 0.07647 Total loss: 3.03332 timestamp: 1654916277.9159503 iteration: 770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30249 FastRCNN class loss: 0.119 FastRCNN total loss: 0.42149 L1 loss: 0.0000e+00 L2 loss: 2.21821 Learning rate: 0.0154 Mask loss: 0.26543 RPN box loss: 0.05336 RPN score loss: 0.01141 RPN total loss: 0.06477 Total loss: 2.96991 timestamp: 1654916281.0742917 iteration: 775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25857 FastRCNN class loss: 0.10576 FastRCNN total loss: 0.36433 L1 loss: 0.0000e+00 L2 loss: 2.21789 Learning rate: 0.0155 Mask loss: 0.29974 RPN box loss: 0.04883 RPN score loss: 0.0163 RPN total loss: 0.06513 Total loss: 2.94708 timestamp: 1654916284.3850102 iteration: 780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19577 FastRCNN class loss: 0.12465 FastRCNN total loss: 0.32042 L1 loss: 0.0000e+00 L2 loss: 2.21755 Learning rate: 0.0156 Mask loss: 0.39247 RPN box loss: 0.02559 RPN score loss: 0.00929 RPN total loss: 0.03488 Total loss: 2.96532 timestamp: 1654916287.6733773 iteration: 785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31849 FastRCNN class loss: 0.11107 FastRCNN total loss: 0.42956 L1 loss: 0.0000e+00 L2 loss: 2.21722 Learning rate: 0.0157 Mask loss: 0.32456 RPN box loss: 0.08425 RPN score loss: 0.02182 RPN total loss: 0.10607 Total loss: 3.07741 timestamp: 1654916291.0900283 iteration: 790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25725 FastRCNN class loss: 0.15398 FastRCNN total loss: 0.41123 L1 loss: 0.0000e+00 L2 loss: 2.21689 Learning rate: 0.0158 Mask loss: 0.25348 RPN box loss: 0.04309 RPN score loss: 0.02038 RPN total loss: 0.06347 Total loss: 2.94507 timestamp: 1654916294.3268547 iteration: 795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27825 FastRCNN class loss: 0.16282 FastRCNN total loss: 0.44107 L1 loss: 0.0000e+00 L2 loss: 2.21657 Learning rate: 0.0159 Mask loss: 0.36809 RPN box loss: 0.05538 RPN score loss: 0.02165 RPN total loss: 0.07703 Total loss: 3.10276 timestamp: 1654916297.6220508 iteration: 800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33521 FastRCNN class loss: 0.09904 FastRCNN total loss: 0.43425 L1 loss: 0.0000e+00 L2 loss: 2.21624 Learning rate: 0.016 Mask loss: 0.30617 RPN box loss: 0.03656 RPN score loss: 0.01016 RPN total loss: 0.04673 Total loss: 3.00339 timestamp: 1654916301.0513787 iteration: 805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2835 FastRCNN class loss: 0.16025 FastRCNN total loss: 0.44375 L1 loss: 0.0000e+00 L2 loss: 2.21592 Learning rate: 0.0161 Mask loss: 0.33521 RPN box loss: 0.10078 RPN score loss: 0.01802 RPN total loss: 0.11879 Total loss: 3.11367 timestamp: 1654916304.2677066 iteration: 810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24604 FastRCNN class loss: 0.0646 FastRCNN total loss: 0.31063 L1 loss: 0.0000e+00 L2 loss: 2.21558 Learning rate: 0.0162 Mask loss: 0.29979 RPN box loss: 0.01131 RPN score loss: 0.0079 RPN total loss: 0.01922 Total loss: 2.84522 timestamp: 1654916307.598277 iteration: 815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2285 FastRCNN class loss: 0.09992 FastRCNN total loss: 0.32842 L1 loss: 0.0000e+00 L2 loss: 2.21524 Learning rate: 0.0163 Mask loss: 0.29129 RPN box loss: 0.14135 RPN score loss: 0.01517 RPN total loss: 0.15653 Total loss: 2.99148 timestamp: 1654916310.8834546 iteration: 820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35846 FastRCNN class loss: 0.17437 FastRCNN total loss: 0.53284 L1 loss: 0.0000e+00 L2 loss: 2.2149 Learning rate: 0.0164 Mask loss: 0.32467 RPN box loss: 0.02857 RPN score loss: 0.0099 RPN total loss: 0.03847 Total loss: 3.11087 timestamp: 1654916314.193217 iteration: 825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41054 FastRCNN class loss: 0.14836 FastRCNN total loss: 0.55891 L1 loss: 0.0000e+00 L2 loss: 2.21455 Learning rate: 0.0165 Mask loss: 0.51065 RPN box loss: 0.07966 RPN score loss: 0.02072 RPN total loss: 0.10038 Total loss: 3.38449 timestamp: 1654916317.4248307 iteration: 830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21504 FastRCNN class loss: 0.10891 FastRCNN total loss: 0.32396 L1 loss: 0.0000e+00 L2 loss: 2.21421 Learning rate: 0.0166 Mask loss: 0.29145 RPN box loss: 0.04744 RPN score loss: 0.02135 RPN total loss: 0.06878 Total loss: 2.89839 timestamp: 1654916320.7384427 iteration: 835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31027 FastRCNN class loss: 0.13231 FastRCNN total loss: 0.44258 L1 loss: 0.0000e+00 L2 loss: 2.21386 Learning rate: 0.0167 Mask loss: 0.34494 RPN box loss: 0.06896 RPN score loss: 0.01776 RPN total loss: 0.08671 Total loss: 3.0881 timestamp: 1654916324.0403578 iteration: 840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2367 FastRCNN class loss: 0.10651 FastRCNN total loss: 0.34321 L1 loss: 0.0000e+00 L2 loss: 2.21352 Learning rate: 0.0168 Mask loss: 0.27786 RPN box loss: 0.03883 RPN score loss: 0.01228 RPN total loss: 0.05111 Total loss: 2.8857 timestamp: 1654916327.3678439 iteration: 845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26587 FastRCNN class loss: 0.14764 FastRCNN total loss: 0.41351 L1 loss: 0.0000e+00 L2 loss: 2.21317 Learning rate: 0.0169 Mask loss: 0.29776 RPN box loss: 0.0145 RPN score loss: 0.01938 RPN total loss: 0.03389 Total loss: 2.95833 timestamp: 1654916330.7581112 iteration: 850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18082 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.25833 L1 loss: 0.0000e+00 L2 loss: 2.21282 Learning rate: 0.017 Mask loss: 0.32589 RPN box loss: 0.05075 RPN score loss: 0.01369 RPN total loss: 0.06443 Total loss: 2.86147 timestamp: 1654916334.025043 iteration: 855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22728 FastRCNN class loss: 0.11664 FastRCNN total loss: 0.34391 L1 loss: 0.0000e+00 L2 loss: 2.21247 Learning rate: 0.01709 Mask loss: 0.23217 RPN box loss: 0.05447 RPN score loss: 0.01724 RPN total loss: 0.07171 Total loss: 2.86026 timestamp: 1654916337.4323647 iteration: 860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24101 FastRCNN class loss: 0.16254 FastRCNN total loss: 0.40355 L1 loss: 0.0000e+00 L2 loss: 2.21212 Learning rate: 0.01719 Mask loss: 0.3487 RPN box loss: 0.07618 RPN score loss: 0.02897 RPN total loss: 0.10514 Total loss: 3.06952 timestamp: 1654916344.196641 iteration: 865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31819 FastRCNN class loss: 0.12654 FastRCNN total loss: 0.44473 L1 loss: 0.0000e+00 L2 loss: 2.21175 Learning rate: 0.01729 Mask loss: 0.29193 RPN box loss: 0.04943 RPN score loss: 0.00933 RPN total loss: 0.05876 Total loss: 3.00717 timestamp: 1654916347.49157 iteration: 870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28483 FastRCNN class loss: 0.11406 FastRCNN total loss: 0.39888 L1 loss: 0.0000e+00 L2 loss: 2.2114 Learning rate: 0.01739 Mask loss: 0.26429 RPN box loss: 0.16189 RPN score loss: 0.03164 RPN total loss: 0.19353 Total loss: 3.0681 timestamp: 1654916350.7963104 iteration: 875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28186 FastRCNN class loss: 0.14638 FastRCNN total loss: 0.42823 L1 loss: 0.0000e+00 L2 loss: 2.21106 Learning rate: 0.01749 Mask loss: 0.36608 RPN box loss: 0.09015 RPN score loss: 0.0172 RPN total loss: 0.10735 Total loss: 3.11272 timestamp: 1654916353.9641669 iteration: 880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32315 FastRCNN class loss: 0.12847 FastRCNN total loss: 0.45163 L1 loss: 0.0000e+00 L2 loss: 2.21069 Learning rate: 0.01759 Mask loss: 0.41446 RPN box loss: 0.07018 RPN score loss: 0.04984 RPN total loss: 0.12001 Total loss: 3.19679 timestamp: 1654916357.3392355 iteration: 885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24038 FastRCNN class loss: 0.12503 FastRCNN total loss: 0.36542 L1 loss: 0.0000e+00 L2 loss: 2.21032 Learning rate: 0.01769 Mask loss: 0.20325 RPN box loss: 0.05243 RPN score loss: 0.02002 RPN total loss: 0.07245 Total loss: 2.85145 timestamp: 1654916360.70256 iteration: 890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24264 FastRCNN class loss: 0.10612 FastRCNN total loss: 0.34875 L1 loss: 0.0000e+00 L2 loss: 2.20993 Learning rate: 0.01779 Mask loss: 0.31671 RPN box loss: 0.07711 RPN score loss: 0.02839 RPN total loss: 0.1055 Total loss: 2.98089 timestamp: 1654916363.9146082 iteration: 895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2142 FastRCNN class loss: 0.12241 FastRCNN total loss: 0.33661 L1 loss: 0.0000e+00 L2 loss: 2.20955 Learning rate: 0.01789 Mask loss: 0.20564 RPN box loss: 0.03075 RPN score loss: 0.01365 RPN total loss: 0.0444 Total loss: 2.7962 timestamp: 1654916367.2257814 iteration: 900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20359 FastRCNN class loss: 0.12878 FastRCNN total loss: 0.33237 L1 loss: 0.0000e+00 L2 loss: 2.20917 Learning rate: 0.01799 Mask loss: 0.32861 RPN box loss: 0.04796 RPN score loss: 0.03873 RPN total loss: 0.0867 Total loss: 2.95685 timestamp: 1654916370.4602573 iteration: 905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25215 FastRCNN class loss: 0.08572 FastRCNN total loss: 0.33787 L1 loss: 0.0000e+00 L2 loss: 2.20881 Learning rate: 0.01809 Mask loss: 0.23204 RPN box loss: 0.03283 RPN score loss: 0.01818 RPN total loss: 0.05101 Total loss: 2.82972 timestamp: 1654916373.7908435 iteration: 910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25145 FastRCNN class loss: 0.11619 FastRCNN total loss: 0.36764 L1 loss: 0.0000e+00 L2 loss: 2.20843 Learning rate: 0.01819 Mask loss: 0.36906 RPN box loss: 0.08194 RPN score loss: 0.04778 RPN total loss: 0.12972 Total loss: 3.07486 timestamp: 1654916377.160369 iteration: 915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28069 FastRCNN class loss: 0.14965 FastRCNN total loss: 0.43033 L1 loss: 0.0000e+00 L2 loss: 2.20805 Learning rate: 0.01829 Mask loss: 0.27576 RPN box loss: 0.11702 RPN score loss: 0.02466 RPN total loss: 0.14167 Total loss: 3.05582 timestamp: 1654916380.4688563 iteration: 920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31481 FastRCNN class loss: 0.10933 FastRCNN total loss: 0.42414 L1 loss: 0.0000e+00 L2 loss: 2.20767 Learning rate: 0.01839 Mask loss: 0.34316 RPN box loss: 0.04699 RPN score loss: 0.01393 RPN total loss: 0.06092 Total loss: 3.03589 timestamp: 1654916383.8192527 iteration: 925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27011 FastRCNN class loss: 0.09224 FastRCNN total loss: 0.36234 L1 loss: 0.0000e+00 L2 loss: 2.20728 Learning rate: 0.01849 Mask loss: 0.34804 RPN box loss: 0.02746 RPN score loss: 0.01229 RPN total loss: 0.03975 Total loss: 2.95741 timestamp: 1654916387.1275623 iteration: 930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24976 FastRCNN class loss: 0.10053 FastRCNN total loss: 0.35029 L1 loss: 0.0000e+00 L2 loss: 2.2069 Learning rate: 0.01859 Mask loss: 0.30392 RPN box loss: 0.09202 RPN score loss: 0.02964 RPN total loss: 0.12166 Total loss: 2.98278 timestamp: 1654916390.4104528 iteration: 935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46322 FastRCNN class loss: 0.13505 FastRCNN total loss: 0.59827 L1 loss: 0.0000e+00 L2 loss: 2.20652 Learning rate: 0.01869 Mask loss: 0.39309 RPN box loss: 0.03185 RPN score loss: 0.01462 RPN total loss: 0.04647 Total loss: 3.24435 timestamp: 1654916393.644479 iteration: 940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32521 FastRCNN class loss: 0.12689 FastRCNN total loss: 0.4521 L1 loss: 0.0000e+00 L2 loss: 2.20613 Learning rate: 0.01879 Mask loss: 0.28255 RPN box loss: 0.03709 RPN score loss: 0.01666 RPN total loss: 0.05375 Total loss: 2.99453 timestamp: 1654916396.914399 iteration: 945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31484 FastRCNN class loss: 0.09257 FastRCNN total loss: 0.40741 L1 loss: 0.0000e+00 L2 loss: 2.20574 Learning rate: 0.01889 Mask loss: 0.32312 RPN box loss: 0.01834 RPN score loss: 0.01271 RPN total loss: 0.03105 Total loss: 2.96731 timestamp: 1654916400.1451025 iteration: 950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22339 FastRCNN class loss: 0.13251 FastRCNN total loss: 0.3559 L1 loss: 0.0000e+00 L2 loss: 2.20536 Learning rate: 0.01899 Mask loss: 0.30974 RPN box loss: 0.07143 RPN score loss: 0.04937 RPN total loss: 0.1208 Total loss: 2.9918 timestamp: 1654916403.5038905 iteration: 955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29864 FastRCNN class loss: 0.12699 FastRCNN total loss: 0.42563 L1 loss: 0.0000e+00 L2 loss: 2.20498 Learning rate: 0.01908 Mask loss: 0.29295 RPN box loss: 0.06216 RPN score loss: 0.02551 RPN total loss: 0.08767 Total loss: 3.01123 timestamp: 1654916406.716477 iteration: 960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32352 FastRCNN class loss: 0.16263 FastRCNN total loss: 0.48615 L1 loss: 0.0000e+00 L2 loss: 2.20459 Learning rate: 0.01918 Mask loss: 0.3119 RPN box loss: 0.0315 RPN score loss: 0.01265 RPN total loss: 0.04415 Total loss: 3.04679 timestamp: 1654916410.1010814 iteration: 965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30382 FastRCNN class loss: 0.11756 FastRCNN total loss: 0.42138 L1 loss: 0.0000e+00 L2 loss: 2.20421 Learning rate: 0.01928 Mask loss: 0.33204 RPN box loss: 0.12974 RPN score loss: 0.01382 RPN total loss: 0.14356 Total loss: 3.10119 timestamp: 1654916413.3208432 iteration: 970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26127 FastRCNN class loss: 0.13001 FastRCNN total loss: 0.39128 L1 loss: 0.0000e+00 L2 loss: 2.20381 Learning rate: 0.01938 Mask loss: 0.31669 RPN box loss: 0.06092 RPN score loss: 0.02156 RPN total loss: 0.08248 Total loss: 2.99426 timestamp: 1654916416.606003 iteration: 975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24898 FastRCNN class loss: 0.13068 FastRCNN total loss: 0.37966 L1 loss: 0.0000e+00 L2 loss: 2.20342 Learning rate: 0.01948 Mask loss: 0.22891 RPN box loss: 0.06479 RPN score loss: 0.01149 RPN total loss: 0.07628 Total loss: 2.88827 timestamp: 1654916419.798218 iteration: 980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33713 FastRCNN class loss: 0.15497 FastRCNN total loss: 0.49209 L1 loss: 0.0000e+00 L2 loss: 2.20304 Learning rate: 0.01958 Mask loss: 0.24634 RPN box loss: 0.08058 RPN score loss: 0.01466 RPN total loss: 0.09524 Total loss: 3.03671 timestamp: 1654916423.0223355 iteration: 985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16809 FastRCNN class loss: 0.11033 FastRCNN total loss: 0.27842 L1 loss: 0.0000e+00 L2 loss: 2.20264 Learning rate: 0.01968 Mask loss: 0.4003 RPN box loss: 0.01011 RPN score loss: 0.00882 RPN total loss: 0.01893 Total loss: 2.9003 timestamp: 1654916426.294637 iteration: 990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2416 FastRCNN class loss: 0.11523 FastRCNN total loss: 0.35683 L1 loss: 0.0000e+00 L2 loss: 2.20223 Learning rate: 0.01978 Mask loss: 0.25064 RPN box loss: 0.06893 RPN score loss: 0.01032 RPN total loss: 0.07925 Total loss: 2.88895 timestamp: 1654916429.5456164 iteration: 995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18005 FastRCNN class loss: 0.09017 FastRCNN total loss: 0.27022 L1 loss: 0.0000e+00 L2 loss: 2.20182 Learning rate: 0.01988 Mask loss: 0.30339 RPN box loss: 0.1578 RPN score loss: 0.02821 RPN total loss: 0.18601 Total loss: 2.96145 timestamp: 1654916432.854605 iteration: 1000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24915 FastRCNN class loss: 0.07726 FastRCNN total loss: 0.32642 L1 loss: 0.0000e+00 L2 loss: 2.20141 Learning rate: 0.01998 Mask loss: 0.2969 RPN box loss: 0.10474 RPN score loss: 0.01171 RPN total loss: 0.11645 Total loss: 2.94118 timestamp: 1654916435.9839146 iteration: 1005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13873 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.20519 L1 loss: 0.0000e+00 L2 loss: 2.201 Learning rate: 0.02 Mask loss: 0.26121 RPN box loss: 0.09408 RPN score loss: 0.01288 RPN total loss: 0.10696 Total loss: 2.77436 timestamp: 1654916439.345927 iteration: 1010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28787 FastRCNN class loss: 0.10987 FastRCNN total loss: 0.39774 L1 loss: 0.0000e+00 L2 loss: 2.20061 Learning rate: 0.02 Mask loss: 0.27936 RPN box loss: 0.0901 RPN score loss: 0.01633 RPN total loss: 0.10643 Total loss: 2.98414 timestamp: 1654916442.634787 iteration: 1015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15782 FastRCNN class loss: 0.0743 FastRCNN total loss: 0.23212 L1 loss: 0.0000e+00 L2 loss: 2.20021 Learning rate: 0.02 Mask loss: 0.24123 RPN box loss: 0.01997 RPN score loss: 0.00919 RPN total loss: 0.02916 Total loss: 2.70272 timestamp: 1654916445.9982557 iteration: 1020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33659 FastRCNN class loss: 0.17865 FastRCNN total loss: 0.51524 L1 loss: 0.0000e+00 L2 loss: 2.19979 Learning rate: 0.02 Mask loss: 0.38996 RPN box loss: 0.05249 RPN score loss: 0.03143 RPN total loss: 0.08392 Total loss: 3.18892 timestamp: 1654916449.2723284 iteration: 1025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22907 FastRCNN class loss: 0.15924 FastRCNN total loss: 0.3883 L1 loss: 0.0000e+00 L2 loss: 2.19937 Learning rate: 0.02 Mask loss: 0.20909 RPN box loss: 0.0168 RPN score loss: 0.01258 RPN total loss: 0.02938 Total loss: 2.82614 timestamp: 1654916452.504466 iteration: 1030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23338 FastRCNN class loss: 0.13358 FastRCNN total loss: 0.36696 L1 loss: 0.0000e+00 L2 loss: 2.19895 Learning rate: 0.02 Mask loss: 0.32607 RPN box loss: 0.17412 RPN score loss: 0.02948 RPN total loss: 0.2036 Total loss: 3.09559 timestamp: 1654916455.827833 iteration: 1035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26068 FastRCNN class loss: 0.15863 FastRCNN total loss: 0.4193 L1 loss: 0.0000e+00 L2 loss: 2.19854 Learning rate: 0.02 Mask loss: 0.27365 RPN box loss: 0.04949 RPN score loss: 0.0224 RPN total loss: 0.0719 Total loss: 2.96338 timestamp: 1654916459.0486493 iteration: 1040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3383 FastRCNN class loss: 0.10948 FastRCNN total loss: 0.44778 L1 loss: 0.0000e+00 L2 loss: 2.19812 Learning rate: 0.02 Mask loss: 0.46813 RPN box loss: 0.07042 RPN score loss: 0.0196 RPN total loss: 0.09002 Total loss: 3.20406 timestamp: 1654916462.3072708 iteration: 1045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19468 FastRCNN class loss: 0.067 FastRCNN total loss: 0.26168 L1 loss: 0.0000e+00 L2 loss: 2.19771 Learning rate: 0.02 Mask loss: 0.28141 RPN box loss: 0.0487 RPN score loss: 0.01738 RPN total loss: 0.06608 Total loss: 2.80689 timestamp: 1654916465.4960523 iteration: 1050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22225 FastRCNN class loss: 0.1656 FastRCNN total loss: 0.38785 L1 loss: 0.0000e+00 L2 loss: 2.1973 Learning rate: 0.02 Mask loss: 0.27756 RPN box loss: 0.0661 RPN score loss: 0.01527 RPN total loss: 0.08137 Total loss: 2.94408 timestamp: 1654916468.665883 iteration: 1055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23546 FastRCNN class loss: 0.09589 FastRCNN total loss: 0.33135 L1 loss: 0.0000e+00 L2 loss: 2.19687 Learning rate: 0.02 Mask loss: 0.24343 RPN box loss: 0.03665 RPN score loss: 0.01395 RPN total loss: 0.05059 Total loss: 2.82224 timestamp: 1654916471.8547144 iteration: 1060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18924 FastRCNN class loss: 0.10677 FastRCNN total loss: 0.29601 L1 loss: 0.0000e+00 L2 loss: 2.19645 Learning rate: 0.02 Mask loss: 0.21171 RPN box loss: 0.08081 RPN score loss: 0.01598 RPN total loss: 0.0968 Total loss: 2.80097 timestamp: 1654916475.141398 iteration: 1065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22596 FastRCNN class loss: 0.10982 FastRCNN total loss: 0.33578 L1 loss: 0.0000e+00 L2 loss: 2.19605 Learning rate: 0.02 Mask loss: 0.28974 RPN box loss: 0.07659 RPN score loss: 0.01058 RPN total loss: 0.08716 Total loss: 2.90873 timestamp: 1654916478.4191327 iteration: 1070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26184 FastRCNN class loss: 0.14693 FastRCNN total loss: 0.40878 L1 loss: 0.0000e+00 L2 loss: 2.19565 Learning rate: 0.02 Mask loss: 0.27672 RPN box loss: 0.05791 RPN score loss: 0.02374 RPN total loss: 0.08165 Total loss: 2.9628 timestamp: 1654916481.8375716 iteration: 1075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2726 FastRCNN class loss: 0.10247 FastRCNN total loss: 0.37507 L1 loss: 0.0000e+00 L2 loss: 2.19523 Learning rate: 0.02 Mask loss: 0.31765 RPN box loss: 0.05404 RPN score loss: 0.00931 RPN total loss: 0.06336 Total loss: 2.9513 timestamp: 1654916485.1280918 iteration: 1080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.212 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.2902 L1 loss: 0.0000e+00 L2 loss: 2.19482 Learning rate: 0.02 Mask loss: 0.23981 RPN box loss: 0.04521 RPN score loss: 0.01173 RPN total loss: 0.05694 Total loss: 2.78177 timestamp: 1654916488.442655 iteration: 1085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26366 FastRCNN class loss: 0.15578 FastRCNN total loss: 0.41943 L1 loss: 0.0000e+00 L2 loss: 2.19441 Learning rate: 0.02 Mask loss: 0.31745 RPN box loss: 0.01057 RPN score loss: 0.00918 RPN total loss: 0.01975 Total loss: 2.95105 timestamp: 1654916491.773126 iteration: 1090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24319 FastRCNN class loss: 0.10998 FastRCNN total loss: 0.35317 L1 loss: 0.0000e+00 L2 loss: 2.194 Learning rate: 0.02 Mask loss: 0.26824 RPN box loss: 0.03555 RPN score loss: 0.01303 RPN total loss: 0.04858 Total loss: 2.864 timestamp: 1654916495.0664535 iteration: 1095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26176 FastRCNN class loss: 0.10718 FastRCNN total loss: 0.36894 L1 loss: 0.0000e+00 L2 loss: 2.1936 Learning rate: 0.02 Mask loss: 0.2995 RPN box loss: 0.11827 RPN score loss: 0.02656 RPN total loss: 0.14483 Total loss: 3.00686 timestamp: 1654916498.4116879 iteration: 1100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23554 FastRCNN class loss: 0.08572 FastRCNN total loss: 0.32126 L1 loss: 0.0000e+00 L2 loss: 2.19318 Learning rate: 0.02 Mask loss: 0.32523 RPN box loss: 0.20682 RPN score loss: 0.01824 RPN total loss: 0.22506 Total loss: 3.06474 timestamp: 1654916501.7424161 iteration: 1105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23243 FastRCNN class loss: 0.09075 FastRCNN total loss: 0.32318 L1 loss: 0.0000e+00 L2 loss: 2.19276 Learning rate: 0.02 Mask loss: 0.29876 RPN box loss: 0.06558 RPN score loss: 0.01276 RPN total loss: 0.07834 Total loss: 2.89305 timestamp: 1654916505.1279254 iteration: 1110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26439 FastRCNN class loss: 0.10044 FastRCNN total loss: 0.36483 L1 loss: 0.0000e+00 L2 loss: 2.19236 Learning rate: 0.02 Mask loss: 0.22099 RPN box loss: 0.04662 RPN score loss: 0.01974 RPN total loss: 0.06636 Total loss: 2.84454 timestamp: 1654916508.4446738 iteration: 1115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3077 FastRCNN class loss: 0.14354 FastRCNN total loss: 0.45123 L1 loss: 0.0000e+00 L2 loss: 2.19193 Learning rate: 0.02 Mask loss: 0.32863 RPN box loss: 0.09802 RPN score loss: 0.0183 RPN total loss: 0.11632 Total loss: 3.08811 timestamp: 1654916511.8143115 iteration: 1120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20059 FastRCNN class loss: 0.1156 FastRCNN total loss: 0.31619 L1 loss: 0.0000e+00 L2 loss: 2.1915 Learning rate: 0.02 Mask loss: 0.22883 RPN box loss: 0.08758 RPN score loss: 0.01457 RPN total loss: 0.10215 Total loss: 2.83867 timestamp: 1654916515.08108 iteration: 1125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19235 FastRCNN class loss: 0.08681 FastRCNN total loss: 0.27915 L1 loss: 0.0000e+00 L2 loss: 2.19109 Learning rate: 0.02 Mask loss: 0.26153 RPN box loss: 0.1209 RPN score loss: 0.01922 RPN total loss: 0.14011 Total loss: 2.87188 timestamp: 1654916518.489312 iteration: 1130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1775 FastRCNN class loss: 0.06419 FastRCNN total loss: 0.24169 L1 loss: 0.0000e+00 L2 loss: 2.19068 Learning rate: 0.02 Mask loss: 0.24115 RPN box loss: 0.00867 RPN score loss: 0.01137 RPN total loss: 0.02004 Total loss: 2.69355 timestamp: 1654916521.8505685 iteration: 1135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28218 FastRCNN class loss: 0.12185 FastRCNN total loss: 0.40402 L1 loss: 0.0000e+00 L2 loss: 2.19025 Learning rate: 0.02 Mask loss: 0.3144 RPN box loss: 0.01124 RPN score loss: 0.01246 RPN total loss: 0.0237 Total loss: 2.93238 timestamp: 1654916525.1030786 iteration: 1140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20407 FastRCNN class loss: 0.074 FastRCNN total loss: 0.27808 L1 loss: 0.0000e+00 L2 loss: 2.18985 Learning rate: 0.02 Mask loss: 0.21483 RPN box loss: 0.01353 RPN score loss: 0.0152 RPN total loss: 0.02873 Total loss: 2.71149 timestamp: 1654916528.382219 iteration: 1145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21963 FastRCNN class loss: 0.13276 FastRCNN total loss: 0.35239 L1 loss: 0.0000e+00 L2 loss: 2.18943 Learning rate: 0.02 Mask loss: 0.19494 RPN box loss: 0.09682 RPN score loss: 0.01553 RPN total loss: 0.11235 Total loss: 2.84911 timestamp: 1654916531.5709028 iteration: 1150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21984 FastRCNN class loss: 0.10497 FastRCNN total loss: 0.32481 L1 loss: 0.0000e+00 L2 loss: 2.189 Learning rate: 0.02 Mask loss: 0.28386 RPN box loss: 0.07511 RPN score loss: 0.01424 RPN total loss: 0.08935 Total loss: 2.88702 timestamp: 1654916534.9947078 iteration: 1155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21305 FastRCNN class loss: 0.11129 FastRCNN total loss: 0.32433 L1 loss: 0.0000e+00 L2 loss: 2.18858 Learning rate: 0.02 Mask loss: 0.24362 RPN box loss: 0.02817 RPN score loss: 0.01889 RPN total loss: 0.04706 Total loss: 2.80359 timestamp: 1654916538.2241647 iteration: 1160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28996 FastRCNN class loss: 0.10779 FastRCNN total loss: 0.39775 L1 loss: 0.0000e+00 L2 loss: 2.18816 Learning rate: 0.02 Mask loss: 0.25843 RPN box loss: 0.02579 RPN score loss: 0.01295 RPN total loss: 0.03873 Total loss: 2.88308 timestamp: 1654916541.4453642 iteration: 1165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27382 FastRCNN class loss: 0.13725 FastRCNN total loss: 0.41107 L1 loss: 0.0000e+00 L2 loss: 2.18775 Learning rate: 0.02 Mask loss: 0.34177 RPN box loss: 0.01792 RPN score loss: 0.00903 RPN total loss: 0.02695 Total loss: 2.96755 timestamp: 1654916544.6560051 iteration: 1170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2702 FastRCNN class loss: 0.09649 FastRCNN total loss: 0.36669 L1 loss: 0.0000e+00 L2 loss: 2.18734 Learning rate: 0.02 Mask loss: 0.27319 RPN box loss: 0.05991 RPN score loss: 0.01339 RPN total loss: 0.0733 Total loss: 2.90052 timestamp: 1654916547.9558506 iteration: 1175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2606 FastRCNN class loss: 0.10816 FastRCNN total loss: 0.36876 L1 loss: 0.0000e+00 L2 loss: 2.18693 Learning rate: 0.02 Mask loss: 0.26548 RPN box loss: 0.0308 RPN score loss: 0.02172 RPN total loss: 0.05252 Total loss: 2.87369 timestamp: 1654916551.3695145 iteration: 1180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36113 FastRCNN class loss: 0.12324 FastRCNN total loss: 0.48437 L1 loss: 0.0000e+00 L2 loss: 2.18652 Learning rate: 0.02 Mask loss: 0.33489 RPN box loss: 0.11749 RPN score loss: 0.0164 RPN total loss: 0.13389 Total loss: 3.13967 timestamp: 1654916554.6321306 iteration: 1185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17805 FastRCNN class loss: 0.10204 FastRCNN total loss: 0.2801 L1 loss: 0.0000e+00 L2 loss: 2.18609 Learning rate: 0.02 Mask loss: 0.27685 RPN box loss: 0.07141 RPN score loss: 0.01028 RPN total loss: 0.08169 Total loss: 2.82473 timestamp: 1654916557.9550543 iteration: 1190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34596 FastRCNN class loss: 0.14621 FastRCNN total loss: 0.49217 L1 loss: 0.0000e+00 L2 loss: 2.18569 Learning rate: 0.02 Mask loss: 0.28092 RPN box loss: 0.03376 RPN score loss: 0.01777 RPN total loss: 0.05153 Total loss: 3.01031 timestamp: 1654916561.204317 iteration: 1195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20528 FastRCNN class loss: 0.09889 FastRCNN total loss: 0.30417 L1 loss: 0.0000e+00 L2 loss: 2.18529 Learning rate: 0.02 Mask loss: 0.30918 RPN box loss: 0.06097 RPN score loss: 0.01399 RPN total loss: 0.07495 Total loss: 2.87359 timestamp: 1654916564.4330924 iteration: 1200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19226 FastRCNN class loss: 0.08259 FastRCNN total loss: 0.27485 L1 loss: 0.0000e+00 L2 loss: 2.18487 Learning rate: 0.02 Mask loss: 0.2236 RPN box loss: 0.0199 RPN score loss: 0.00777 RPN total loss: 0.02768 Total loss: 2.71099 timestamp: 1654916567.699622 iteration: 1205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30432 FastRCNN class loss: 0.18941 FastRCNN total loss: 0.49372 L1 loss: 0.0000e+00 L2 loss: 2.18448 Learning rate: 0.02 Mask loss: 0.34252 RPN box loss: 0.15084 RPN score loss: 0.01832 RPN total loss: 0.16916 Total loss: 3.18988 timestamp: 1654916571.0904024 iteration: 1210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1679 FastRCNN class loss: 0.06747 FastRCNN total loss: 0.23537 L1 loss: 0.0000e+00 L2 loss: 2.18408 Learning rate: 0.02 Mask loss: 0.2434 RPN box loss: 0.0542 RPN score loss: 0.01216 RPN total loss: 0.06636 Total loss: 2.72921 timestamp: 1654916574.2821636 iteration: 1215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22331 FastRCNN class loss: 0.12373 FastRCNN total loss: 0.34704 L1 loss: 0.0000e+00 L2 loss: 2.18367 Learning rate: 0.02 Mask loss: 0.29308 RPN box loss: 0.0486 RPN score loss: 0.01621 RPN total loss: 0.06481 Total loss: 2.8886 timestamp: 1654916577.5826373 iteration: 1220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20915 FastRCNN class loss: 0.09589 FastRCNN total loss: 0.30504 L1 loss: 0.0000e+00 L2 loss: 2.18327 Learning rate: 0.02 Mask loss: 0.26772 RPN box loss: 0.07747 RPN score loss: 0.01255 RPN total loss: 0.09002 Total loss: 2.84605 timestamp: 1654916580.7413285 iteration: 1225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19849 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.26818 L1 loss: 0.0000e+00 L2 loss: 2.18287 Learning rate: 0.02 Mask loss: 0.27584 RPN box loss: 0.0515 RPN score loss: 0.01246 RPN total loss: 0.06397 Total loss: 2.79086 timestamp: 1654916584.0036674 iteration: 1230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25297 FastRCNN class loss: 0.10737 FastRCNN total loss: 0.36034 L1 loss: 0.0000e+00 L2 loss: 2.18246 Learning rate: 0.02 Mask loss: 0.2731 RPN box loss: 0.04625 RPN score loss: 0.02847 RPN total loss: 0.07471 Total loss: 2.89062 timestamp: 1654916587.2252088 iteration: 1235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24616 FastRCNN class loss: 0.14427 FastRCNN total loss: 0.39043 L1 loss: 0.0000e+00 L2 loss: 2.18205 Learning rate: 0.02 Mask loss: 0.34804 RPN box loss: 0.06529 RPN score loss: 0.01708 RPN total loss: 0.08237 Total loss: 3.00289 timestamp: 1654916590.3866065 iteration: 1240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31425 FastRCNN class loss: 0.2092 FastRCNN total loss: 0.52345 L1 loss: 0.0000e+00 L2 loss: 2.18163 Learning rate: 0.02 Mask loss: 0.3346 RPN box loss: 0.0382 RPN score loss: 0.02302 RPN total loss: 0.06122 Total loss: 3.10089 timestamp: 1654916593.7133534 iteration: 1245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23376 FastRCNN class loss: 0.08788 FastRCNN total loss: 0.32164 L1 loss: 0.0000e+00 L2 loss: 2.18121 Learning rate: 0.02 Mask loss: 0.23224 RPN box loss: 0.09244 RPN score loss: 0.02032 RPN total loss: 0.11276 Total loss: 2.84784 timestamp: 1654916597.033901 iteration: 1250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24674 FastRCNN class loss: 0.08981 FastRCNN total loss: 0.33655 L1 loss: 0.0000e+00 L2 loss: 2.18078 Learning rate: 0.02 Mask loss: 0.24806 RPN box loss: 0.05018 RPN score loss: 0.01032 RPN total loss: 0.0605 Total loss: 2.82589 timestamp: 1654916600.3788707 iteration: 1255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27292 FastRCNN class loss: 0.09068 FastRCNN total loss: 0.3636 L1 loss: 0.0000e+00 L2 loss: 2.18034 Learning rate: 0.02 Mask loss: 0.22828 RPN box loss: 0.11433 RPN score loss: 0.0192 RPN total loss: 0.13353 Total loss: 2.90575 timestamp: 1654916603.5750976 iteration: 1260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22335 FastRCNN class loss: 0.10949 FastRCNN total loss: 0.33284 L1 loss: 0.0000e+00 L2 loss: 2.17991 Learning rate: 0.02 Mask loss: 0.29703 RPN box loss: 0.03688 RPN score loss: 0.01077 RPN total loss: 0.04765 Total loss: 2.85744 timestamp: 1654916606.8342092 iteration: 1265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27739 FastRCNN class loss: 0.1282 FastRCNN total loss: 0.4056 L1 loss: 0.0000e+00 L2 loss: 2.17952 Learning rate: 0.02 Mask loss: 0.2921 RPN box loss: 0.05116 RPN score loss: 0.01835 RPN total loss: 0.06952 Total loss: 2.94673 timestamp: 1654916610.092493 iteration: 1270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21668 FastRCNN class loss: 0.09091 FastRCNN total loss: 0.30759 L1 loss: 0.0000e+00 L2 loss: 2.17908 Learning rate: 0.02 Mask loss: 0.23072 RPN box loss: 0.01133 RPN score loss: 0.0119 RPN total loss: 0.02323 Total loss: 2.74063 timestamp: 1654916613.4700818 iteration: 1275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26273 FastRCNN class loss: 0.1058 FastRCNN total loss: 0.36853 L1 loss: 0.0000e+00 L2 loss: 2.17868 Learning rate: 0.02 Mask loss: 0.23176 RPN box loss: 0.05115 RPN score loss: 0.00946 RPN total loss: 0.0606 Total loss: 2.83957 timestamp: 1654916616.7390342 iteration: 1280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24278 FastRCNN class loss: 0.10854 FastRCNN total loss: 0.35133 L1 loss: 0.0000e+00 L2 loss: 2.17827 Learning rate: 0.02 Mask loss: 0.31049 RPN box loss: 0.06142 RPN score loss: 0.01183 RPN total loss: 0.07325 Total loss: 2.91335 timestamp: 1654916619.987295 iteration: 1285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28201 FastRCNN class loss: 0.11278 FastRCNN total loss: 0.3948 L1 loss: 0.0000e+00 L2 loss: 2.17787 Learning rate: 0.02 Mask loss: 0.28733 RPN box loss: 0.01435 RPN score loss: 0.00751 RPN total loss: 0.02186 Total loss: 2.88185 timestamp: 1654916623.3503559 iteration: 1290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25251 FastRCNN class loss: 0.11549 FastRCNN total loss: 0.36799 L1 loss: 0.0000e+00 L2 loss: 2.17743 Learning rate: 0.02 Mask loss: 0.30608 RPN box loss: 0.03488 RPN score loss: 0.00916 RPN total loss: 0.04405 Total loss: 2.89555 timestamp: 1654916626.6381166 iteration: 1295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27584 FastRCNN class loss: 0.11456 FastRCNN total loss: 0.3904 L1 loss: 0.0000e+00 L2 loss: 2.17702 Learning rate: 0.02 Mask loss: 0.28383 RPN box loss: 0.04758 RPN score loss: 0.01848 RPN total loss: 0.06606 Total loss: 2.91731 timestamp: 1654916630.0370662 iteration: 1300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25088 FastRCNN class loss: 0.11404 FastRCNN total loss: 0.36493 L1 loss: 0.0000e+00 L2 loss: 2.17661 Learning rate: 0.02 Mask loss: 0.19369 RPN box loss: 0.02789 RPN score loss: 0.01228 RPN total loss: 0.04017 Total loss: 2.7754 timestamp: 1654916633.314277 iteration: 1305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23196 FastRCNN class loss: 0.06831 FastRCNN total loss: 0.30027 L1 loss: 0.0000e+00 L2 loss: 2.1762 Learning rate: 0.02 Mask loss: 0.17973 RPN box loss: 0.03903 RPN score loss: 0.01554 RPN total loss: 0.05456 Total loss: 2.71077 timestamp: 1654916636.5364125 iteration: 1310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20234 FastRCNN class loss: 0.09676 FastRCNN total loss: 0.2991 L1 loss: 0.0000e+00 L2 loss: 2.17579 Learning rate: 0.02 Mask loss: 0.21923 RPN box loss: 0.05722 RPN score loss: 0.01146 RPN total loss: 0.06868 Total loss: 2.76279 timestamp: 1654916639.7756262 iteration: 1315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28212 FastRCNN class loss: 0.11593 FastRCNN total loss: 0.39805 L1 loss: 0.0000e+00 L2 loss: 2.17538 Learning rate: 0.02 Mask loss: 0.21642 RPN box loss: 0.10697 RPN score loss: 0.02521 RPN total loss: 0.13219 Total loss: 2.92204 timestamp: 1654916643.0324175 iteration: 1320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20213 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.29961 L1 loss: 0.0000e+00 L2 loss: 2.17497 Learning rate: 0.02 Mask loss: 0.20185 RPN box loss: 0.02657 RPN score loss: 0.00518 RPN total loss: 0.03176 Total loss: 2.70819 timestamp: 1654916646.3750017 iteration: 1325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31354 FastRCNN class loss: 0.10264 FastRCNN total loss: 0.41618 L1 loss: 0.0000e+00 L2 loss: 2.17457 Learning rate: 0.02 Mask loss: 0.36314 RPN box loss: 0.09788 RPN score loss: 0.02163 RPN total loss: 0.11951 Total loss: 3.07339 timestamp: 1654916649.5686905 iteration: 1330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26245 FastRCNN class loss: 0.17361 FastRCNN total loss: 0.43607 L1 loss: 0.0000e+00 L2 loss: 2.17415 Learning rate: 0.02 Mask loss: 0.26088 RPN box loss: 0.02836 RPN score loss: 0.01366 RPN total loss: 0.04202 Total loss: 2.91313 timestamp: 1654916653.0363104 iteration: 1335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25381 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.34347 L1 loss: 0.0000e+00 L2 loss: 2.17373 Learning rate: 0.02 Mask loss: 0.28327 RPN box loss: 0.01345 RPN score loss: 0.01165 RPN total loss: 0.02509 Total loss: 2.82556 timestamp: 1654916656.1634665 iteration: 1340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24093 FastRCNN class loss: 0.11199 FastRCNN total loss: 0.35292 L1 loss: 0.0000e+00 L2 loss: 2.17332 Learning rate: 0.02 Mask loss: 0.20363 RPN box loss: 0.0285 RPN score loss: 0.01007 RPN total loss: 0.03857 Total loss: 2.76844 timestamp: 1654916659.448172 iteration: 1345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25906 FastRCNN class loss: 0.14098 FastRCNN total loss: 0.40004 L1 loss: 0.0000e+00 L2 loss: 2.17289 Learning rate: 0.02 Mask loss: 0.39019 RPN box loss: 0.05653 RPN score loss: 0.02544 RPN total loss: 0.08197 Total loss: 3.04509 timestamp: 1654916662.6151547 iteration: 1350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15103 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.2291 L1 loss: 0.0000e+00 L2 loss: 2.17247 Learning rate: 0.02 Mask loss: 0.22538 RPN box loss: 0.03212 RPN score loss: 0.02232 RPN total loss: 0.05444 Total loss: 2.6814 timestamp: 1654916665.9418223 iteration: 1355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25213 FastRCNN class loss: 0.08455 FastRCNN total loss: 0.33668 L1 loss: 0.0000e+00 L2 loss: 2.17209 Learning rate: 0.02 Mask loss: 0.2028 RPN box loss: 0.04951 RPN score loss: 0.01223 RPN total loss: 0.06174 Total loss: 2.7733 timestamp: 1654916669.1644938 iteration: 1360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23451 FastRCNN class loss: 0.14688 FastRCNN total loss: 0.38139 L1 loss: 0.0000e+00 L2 loss: 2.17167 Learning rate: 0.02 Mask loss: 0.22564 RPN box loss: 0.04048 RPN score loss: 0.00602 RPN total loss: 0.04651 Total loss: 2.82521 timestamp: 1654916672.5703495 iteration: 1365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11743 FastRCNN class loss: 0.04285 FastRCNN total loss: 0.16028 L1 loss: 0.0000e+00 L2 loss: 2.17127 Learning rate: 0.02 Mask loss: 0.12875 RPN box loss: 0.02068 RPN score loss: 0.01045 RPN total loss: 0.03113 Total loss: 2.49143 timestamp: 1654916675.793384 iteration: 1370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22353 FastRCNN class loss: 0.13148 FastRCNN total loss: 0.35501 L1 loss: 0.0000e+00 L2 loss: 2.17085 Learning rate: 0.02 Mask loss: 0.24899 RPN box loss: 0.04765 RPN score loss: 0.01197 RPN total loss: 0.05962 Total loss: 2.83448 timestamp: 1654916679.0703883 iteration: 1375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26608 FastRCNN class loss: 0.1064 FastRCNN total loss: 0.37248 L1 loss: 0.0000e+00 L2 loss: 2.17043 Learning rate: 0.02 Mask loss: 0.34338 RPN box loss: 0.07216 RPN score loss: 0.01282 RPN total loss: 0.08498 Total loss: 2.97128 timestamp: 1654916682.398534 iteration: 1380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26155 FastRCNN class loss: 0.09382 FastRCNN total loss: 0.35537 L1 loss: 0.0000e+00 L2 loss: 2.17002 Learning rate: 0.02 Mask loss: 0.25104 RPN box loss: 0.07359 RPN score loss: 0.02258 RPN total loss: 0.09617 Total loss: 2.87259 timestamp: 1654916685.6211333 iteration: 1385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18021 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.25184 L1 loss: 0.0000e+00 L2 loss: 2.16962 Learning rate: 0.02 Mask loss: 0.19157 RPN box loss: 0.01443 RPN score loss: 0.01242 RPN total loss: 0.02685 Total loss: 2.63987 timestamp: 1654916688.9468393 iteration: 1390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25712 FastRCNN class loss: 0.09807 FastRCNN total loss: 0.35519 L1 loss: 0.0000e+00 L2 loss: 2.16921 Learning rate: 0.02 Mask loss: 0.26238 RPN box loss: 0.04387 RPN score loss: 0.00748 RPN total loss: 0.05135 Total loss: 2.83813 timestamp: 1654916692.1758401 iteration: 1395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18751 FastRCNN class loss: 0.11405 FastRCNN total loss: 0.30156 L1 loss: 0.0000e+00 L2 loss: 2.16881 Learning rate: 0.02 Mask loss: 0.22551 RPN box loss: 0.01856 RPN score loss: 0.00656 RPN total loss: 0.02513 Total loss: 2.72101 timestamp: 1654916695.4267616 iteration: 1400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17267 FastRCNN class loss: 0.0846 FastRCNN total loss: 0.25727 L1 loss: 0.0000e+00 L2 loss: 2.16839 Learning rate: 0.02 Mask loss: 0.24455 RPN box loss: 0.11779 RPN score loss: 0.01194 RPN total loss: 0.12973 Total loss: 2.79994 timestamp: 1654916698.6650488 iteration: 1405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24472 FastRCNN class loss: 0.17373 FastRCNN total loss: 0.41846 L1 loss: 0.0000e+00 L2 loss: 2.16799 Learning rate: 0.02 Mask loss: 0.26672 RPN box loss: 0.10113 RPN score loss: 0.02066 RPN total loss: 0.1218 Total loss: 2.97496 timestamp: 1654916702.0123825 iteration: 1410 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27848 FastRCNN class loss: 0.12916 FastRCNN total loss: 0.40763 L1 loss: 0.0000e+00 L2 loss: 2.16758 Learning rate: 0.02 Mask loss: 0.28577 RPN box loss: 0.01422 RPN score loss: 0.00838 RPN total loss: 0.0226 Total loss: 2.88358 timestamp: 1654916705.1978762 iteration: 1415 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28025 FastRCNN class loss: 0.17468 FastRCNN total loss: 0.45493 L1 loss: 0.0000e+00 L2 loss: 2.16717 Learning rate: 0.02 Mask loss: 0.24998 RPN box loss: 0.12699 RPN score loss: 0.01136 RPN total loss: 0.13835 Total loss: 3.01043 timestamp: 1654916708.4798274 iteration: 1420 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.177 FastRCNN class loss: 0.09601 FastRCNN total loss: 0.273 L1 loss: 0.0000e+00 L2 loss: 2.16675 Learning rate: 0.02 Mask loss: 0.21561 RPN box loss: 0.05181 RPN score loss: 0.00748 RPN total loss: 0.05929 Total loss: 2.71465 timestamp: 1654916711.772967 iteration: 1425 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22194 FastRCNN class loss: 0.10093 FastRCNN total loss: 0.32287 L1 loss: 0.0000e+00 L2 loss: 2.16634 Learning rate: 0.02 Mask loss: 0.26021 RPN box loss: 0.09602 RPN score loss: 0.03209 RPN total loss: 0.12811 Total loss: 2.87754 timestamp: 1654916715.0393145 iteration: 1430 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29762 FastRCNN class loss: 0.14186 FastRCNN total loss: 0.43948 L1 loss: 0.0000e+00 L2 loss: 2.16593 Learning rate: 0.02 Mask loss: 0.31579 RPN box loss: 0.06195 RPN score loss: 0.01459 RPN total loss: 0.07654 Total loss: 2.99774 timestamp: 1654916718.3456306 iteration: 1435 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24892 FastRCNN class loss: 0.09608 FastRCNN total loss: 0.345 L1 loss: 0.0000e+00 L2 loss: 2.1655 Learning rate: 0.02 Mask loss: 0.2221 RPN box loss: 0.07469 RPN score loss: 0.01291 RPN total loss: 0.0876 Total loss: 2.8202 timestamp: 1654916721.5268595 iteration: 1440 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21397 FastRCNN class loss: 0.1196 FastRCNN total loss: 0.33357 L1 loss: 0.0000e+00 L2 loss: 2.16509 Learning rate: 0.02 Mask loss: 0.29097 RPN box loss: 0.06393 RPN score loss: 0.0142 RPN total loss: 0.07813 Total loss: 2.86775 timestamp: 1654916724.8665447 iteration: 1445 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32661 FastRCNN class loss: 0.14834 FastRCNN total loss: 0.47495 L1 loss: 0.0000e+00 L2 loss: 2.16468 Learning rate: 0.02 Mask loss: 0.33041 RPN box loss: 0.09776 RPN score loss: 0.0143 RPN total loss: 0.11206 Total loss: 3.0821 timestamp: 1654916728.121098 iteration: 1450 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2084 FastRCNN class loss: 0.0998 FastRCNN total loss: 0.3082 L1 loss: 0.0000e+00 L2 loss: 2.16426 Learning rate: 0.02 Mask loss: 0.29056 RPN box loss: 0.03321 RPN score loss: 0.02089 RPN total loss: 0.0541 Total loss: 2.81712 timestamp: 1654916731.515837 iteration: 1455 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27452 FastRCNN class loss: 0.15157 FastRCNN total loss: 0.42608 L1 loss: 0.0000e+00 L2 loss: 2.16388 Learning rate: 0.02 Mask loss: 0.38515 RPN box loss: 0.06449 RPN score loss: 0.01711 RPN total loss: 0.08159 Total loss: 3.05671 timestamp: 1654916734.7815595 iteration: 1460 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21732 FastRCNN class loss: 0.10249 FastRCNN total loss: 0.31981 L1 loss: 0.0000e+00 L2 loss: 2.16348 Learning rate: 0.02 Mask loss: 0.22523 RPN box loss: 0.05027 RPN score loss: 0.01717 RPN total loss: 0.06743 Total loss: 2.77596 timestamp: 1654916738.0923448 iteration: 1465 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1968 FastRCNN class loss: 0.13089 FastRCNN total loss: 0.32768 L1 loss: 0.0000e+00 L2 loss: 2.1631 Learning rate: 0.02 Mask loss: 0.26666 RPN box loss: 0.04525 RPN score loss: 0.01416 RPN total loss: 0.05941 Total loss: 2.81685 timestamp: 1654916741.444968 iteration: 1470 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26545 FastRCNN class loss: 0.1809 FastRCNN total loss: 0.44635 L1 loss: 0.0000e+00 L2 loss: 2.16268 Learning rate: 0.02 Mask loss: 0.30415 RPN box loss: 0.06037 RPN score loss: 0.03034 RPN total loss: 0.09071 Total loss: 3.00389 timestamp: 1654916744.6988063 iteration: 1475 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24612 FastRCNN class loss: 0.11499 FastRCNN total loss: 0.36111 L1 loss: 0.0000e+00 L2 loss: 2.16225 Learning rate: 0.02 Mask loss: 0.29656 RPN box loss: 0.03917 RPN score loss: 0.01058 RPN total loss: 0.04976 Total loss: 2.86967 timestamp: 1654916747.9739144 iteration: 1480 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24799 FastRCNN class loss: 0.13649 FastRCNN total loss: 0.38448 L1 loss: 0.0000e+00 L2 loss: 2.16182 Learning rate: 0.02 Mask loss: 0.22327 RPN box loss: 0.04213 RPN score loss: 0.01215 RPN total loss: 0.05428 Total loss: 2.82385 timestamp: 1654916751.1692288 iteration: 1485 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23086 FastRCNN class loss: 0.1365 FastRCNN total loss: 0.36736 L1 loss: 0.0000e+00 L2 loss: 2.16143 Learning rate: 0.02 Mask loss: 0.24572 RPN box loss: 0.05774 RPN score loss: 0.01912 RPN total loss: 0.07686 Total loss: 2.85136 timestamp: 1654916754.56212 iteration: 1490 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18606 FastRCNN class loss: 0.09428 FastRCNN total loss: 0.28035 L1 loss: 0.0000e+00 L2 loss: 2.16102 Learning rate: 0.02 Mask loss: 0.18844 RPN box loss: 0.02721 RPN score loss: 0.00941 RPN total loss: 0.03662 Total loss: 2.66643 timestamp: 1654916757.8481884 iteration: 1495 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26374 FastRCNN class loss: 0.14497 FastRCNN total loss: 0.40871 L1 loss: 0.0000e+00 L2 loss: 2.16062 Learning rate: 0.02 Mask loss: 0.21384 RPN box loss: 0.05721 RPN score loss: 0.02491 RPN total loss: 0.08212 Total loss: 2.86528 timestamp: 1654916761.191638 iteration: 1500 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27839 FastRCNN class loss: 0.15795 FastRCNN total loss: 0.43634 L1 loss: 0.0000e+00 L2 loss: 2.16021 Learning rate: 0.02 Mask loss: 0.35004 RPN box loss: 0.07781 RPN score loss: 0.021 RPN total loss: 0.0988 Total loss: 3.04539 timestamp: 1654916764.3868346 iteration: 1505 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23479 FastRCNN class loss: 0.08387 FastRCNN total loss: 0.31866 L1 loss: 0.0000e+00 L2 loss: 2.15983 Learning rate: 0.02 Mask loss: 0.25706 RPN box loss: 0.04015 RPN score loss: 0.00475 RPN total loss: 0.0449 Total loss: 2.78045 timestamp: 1654916767.6849465 iteration: 1510 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22077 FastRCNN class loss: 0.09171 FastRCNN total loss: 0.31249 L1 loss: 0.0000e+00 L2 loss: 2.15944 Learning rate: 0.02 Mask loss: 0.29266 RPN box loss: 0.10692 RPN score loss: 0.02179 RPN total loss: 0.12871 Total loss: 2.8933 timestamp: 1654916771.065296 iteration: 1515 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20617 FastRCNN class loss: 0.098 FastRCNN total loss: 0.30417 L1 loss: 0.0000e+00 L2 loss: 2.15902 Learning rate: 0.02 Mask loss: 0.18749 RPN box loss: 0.02695 RPN score loss: 0.00893 RPN total loss: 0.03588 Total loss: 2.68656 timestamp: 1654916774.312686 iteration: 1520 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21805 FastRCNN class loss: 0.1146 FastRCNN total loss: 0.33265 L1 loss: 0.0000e+00 L2 loss: 2.15862 Learning rate: 0.02 Mask loss: 0.24119 RPN box loss: 0.09068 RPN score loss: 0.01928 RPN total loss: 0.10996 Total loss: 2.84241 timestamp: 1654916777.5876594 iteration: 1525 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16308 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.23656 L1 loss: 0.0000e+00 L2 loss: 2.15821 Learning rate: 0.02 Mask loss: 0.20063 RPN box loss: 0.01563 RPN score loss: 0.01092 RPN total loss: 0.02655 Total loss: 2.62195 timestamp: 1654916780.8361244 iteration: 1530 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12703 FastRCNN class loss: 0.0817 FastRCNN total loss: 0.20873 L1 loss: 0.0000e+00 L2 loss: 2.15779 Learning rate: 0.02 Mask loss: 0.27133 RPN box loss: 0.13239 RPN score loss: 0.01805 RPN total loss: 0.15044 Total loss: 2.78829 timestamp: 1654916784.1797013 iteration: 1535 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23348 FastRCNN class loss: 0.11754 FastRCNN total loss: 0.35103 L1 loss: 0.0000e+00 L2 loss: 2.15737 Learning rate: 0.02 Mask loss: 0.31216 RPN box loss: 0.09454 RPN score loss: 0.01235 RPN total loss: 0.10689 Total loss: 2.92745 timestamp: 1654916787.331627 iteration: 1540 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20419 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.29446 L1 loss: 0.0000e+00 L2 loss: 2.15695 Learning rate: 0.02 Mask loss: 0.39835 RPN box loss: 0.02592 RPN score loss: 0.00999 RPN total loss: 0.0359 Total loss: 2.88567 timestamp: 1654916790.7383385 iteration: 1545 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25132 FastRCNN class loss: 0.08148 FastRCNN total loss: 0.33281 L1 loss: 0.0000e+00 L2 loss: 2.15656 Learning rate: 0.02 Mask loss: 0.25964 RPN box loss: 0.02751 RPN score loss: 0.00972 RPN total loss: 0.03723 Total loss: 2.78624 timestamp: 1654916793.9717517 iteration: 1550 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12803 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 2.15616 Learning rate: 0.02 Mask loss: 0.21667 RPN box loss: 0.10819 RPN score loss: 0.00944 RPN total loss: 0.11763 Total loss: 2.67047 timestamp: 1654916797.323704 iteration: 1555 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26538 FastRCNN class loss: 0.10682 FastRCNN total loss: 0.3722 L1 loss: 0.0000e+00 L2 loss: 2.15575 Learning rate: 0.02 Mask loss: 0.191 RPN box loss: 0.02053 RPN score loss: 0.01046 RPN total loss: 0.03099 Total loss: 2.74994 timestamp: 1654916800.6111147 iteration: 1560 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17268 FastRCNN class loss: 0.0935 FastRCNN total loss: 0.26618 L1 loss: 0.0000e+00 L2 loss: 2.15536 Learning rate: 0.02 Mask loss: 0.21758 RPN box loss: 0.02832 RPN score loss: 0.01045 RPN total loss: 0.03877 Total loss: 2.67789 timestamp: 1654916803.8722918 iteration: 1565 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24398 FastRCNN class loss: 0.14276 FastRCNN total loss: 0.38674 L1 loss: 0.0000e+00 L2 loss: 2.15496 Learning rate: 0.02 Mask loss: 0.2534 RPN box loss: 0.05392 RPN score loss: 0.01835 RPN total loss: 0.07227 Total loss: 2.86736 timestamp: 1654916807.2491302 iteration: 1570 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25826 FastRCNN class loss: 0.13082 FastRCNN total loss: 0.38908 L1 loss: 0.0000e+00 L2 loss: 2.15455 Learning rate: 0.02 Mask loss: 0.34963 RPN box loss: 0.06306 RPN score loss: 0.0171 RPN total loss: 0.08016 Total loss: 2.97342 timestamp: 1654916810.352459 iteration: 1575 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20066 FastRCNN class loss: 0.13327 FastRCNN total loss: 0.33392 L1 loss: 0.0000e+00 L2 loss: 2.15412 Learning rate: 0.02 Mask loss: 0.25605 RPN box loss: 0.05063 RPN score loss: 0.0356 RPN total loss: 0.08623 Total loss: 2.83032 timestamp: 1654916813.679582 iteration: 1580 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25171 FastRCNN class loss: 0.08369 FastRCNN total loss: 0.33539 L1 loss: 0.0000e+00 L2 loss: 2.15371 Learning rate: 0.02 Mask loss: 0.2059 RPN box loss: 0.0421 RPN score loss: 0.01234 RPN total loss: 0.05444 Total loss: 2.74944 timestamp: 1654916816.9236574 iteration: 1585 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31403 FastRCNN class loss: 0.12545 FastRCNN total loss: 0.43947 L1 loss: 0.0000e+00 L2 loss: 2.1533 Learning rate: 0.02 Mask loss: 0.25864 RPN box loss: 0.07524 RPN score loss: 0.01217 RPN total loss: 0.08741 Total loss: 2.93882 timestamp: 1654916820.243239 iteration: 1590 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19076 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.26557 L1 loss: 0.0000e+00 L2 loss: 2.15289 Learning rate: 0.02 Mask loss: 0.23855 RPN box loss: 0.07874 RPN score loss: 0.03149 RPN total loss: 0.11024 Total loss: 2.76725 timestamp: 1654916823.4473877 iteration: 1595 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24054 FastRCNN class loss: 0.15285 FastRCNN total loss: 0.39339 L1 loss: 0.0000e+00 L2 loss: 2.15247 Learning rate: 0.02 Mask loss: 0.39078 RPN box loss: 0.02971 RPN score loss: 0.00766 RPN total loss: 0.03737 Total loss: 2.97401 timestamp: 1654916826.8728292 iteration: 1600 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29019 FastRCNN class loss: 0.20241 FastRCNN total loss: 0.4926 L1 loss: 0.0000e+00 L2 loss: 2.15204 Learning rate: 0.02 Mask loss: 0.38425 RPN box loss: 0.03874 RPN score loss: 0.01281 RPN total loss: 0.05155 Total loss: 3.08045 timestamp: 1654916830.1655772 iteration: 1605 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29982 FastRCNN class loss: 0.2047 FastRCNN total loss: 0.50452 L1 loss: 0.0000e+00 L2 loss: 2.15163 Learning rate: 0.02 Mask loss: 0.25079 RPN box loss: 0.06883 RPN score loss: 0.018 RPN total loss: 0.08683 Total loss: 2.99377 timestamp: 1654916833.5044448 iteration: 1610 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24813 FastRCNN class loss: 0.13315 FastRCNN total loss: 0.38128 L1 loss: 0.0000e+00 L2 loss: 2.15124 Learning rate: 0.02 Mask loss: 0.25731 RPN box loss: 0.04526 RPN score loss: 0.01743 RPN total loss: 0.06269 Total loss: 2.85253 timestamp: 1654916836.806377 iteration: 1615 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20309 FastRCNN class loss: 0.0905 FastRCNN total loss: 0.29359 L1 loss: 0.0000e+00 L2 loss: 2.15085 Learning rate: 0.02 Mask loss: 0.23023 RPN box loss: 0.04024 RPN score loss: 0.01689 RPN total loss: 0.05713 Total loss: 2.73179 timestamp: 1654916840.0372658 iteration: 1620 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29865 FastRCNN class loss: 0.14636 FastRCNN total loss: 0.44501 L1 loss: 0.0000e+00 L2 loss: 2.15043 Learning rate: 0.02 Mask loss: 0.24742 RPN box loss: 0.08995 RPN score loss: 0.0178 RPN total loss: 0.10776 Total loss: 2.95061 timestamp: 1654916843.4253368 iteration: 1625 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23822 FastRCNN class loss: 0.13107 FastRCNN total loss: 0.36929 L1 loss: 0.0000e+00 L2 loss: 2.15002 Learning rate: 0.02 Mask loss: 0.2427 RPN box loss: 0.2242 RPN score loss: 0.02027 RPN total loss: 0.24447 Total loss: 3.00647 timestamp: 1654916846.5439851 iteration: 1630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15092 FastRCNN class loss: 0.08759 FastRCNN total loss: 0.23851 L1 loss: 0.0000e+00 L2 loss: 2.14961 Learning rate: 0.02 Mask loss: 0.20992 RPN box loss: 0.14403 RPN score loss: 0.02194 RPN total loss: 0.16597 Total loss: 2.76401 timestamp: 1654916849.8336976 iteration: 1635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17241 FastRCNN class loss: 0.17509 FastRCNN total loss: 0.3475 L1 loss: 0.0000e+00 L2 loss: 2.1492 Learning rate: 0.02 Mask loss: 0.31429 RPN box loss: 0.06838 RPN score loss: 0.10883 RPN total loss: 0.17721 Total loss: 2.9882 timestamp: 1654916853.0251212 iteration: 1640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24095 FastRCNN class loss: 0.19163 FastRCNN total loss: 0.43258 L1 loss: 0.0000e+00 L2 loss: 2.14879 Learning rate: 0.02 Mask loss: 0.29523 RPN box loss: 0.05474 RPN score loss: 0.01429 RPN total loss: 0.06903 Total loss: 2.94563 timestamp: 1654916856.358115 iteration: 1645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19902 FastRCNN class loss: 0.07346 FastRCNN total loss: 0.27248 L1 loss: 0.0000e+00 L2 loss: 2.1484 Learning rate: 0.02 Mask loss: 0.24453 RPN box loss: 0.0744 RPN score loss: 0.01908 RPN total loss: 0.09348 Total loss: 2.75888 timestamp: 1654916859.5664225 iteration: 1650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26309 FastRCNN class loss: 0.12085 FastRCNN total loss: 0.38394 L1 loss: 0.0000e+00 L2 loss: 2.14799 Learning rate: 0.02 Mask loss: 0.22503 RPN box loss: 0.07402 RPN score loss: 0.02373 RPN total loss: 0.09775 Total loss: 2.85471 timestamp: 1654916862.8386056 iteration: 1655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26882 FastRCNN class loss: 0.10715 FastRCNN total loss: 0.37598 L1 loss: 0.0000e+00 L2 loss: 2.14758 Learning rate: 0.02 Mask loss: 0.22125 RPN box loss: 0.02573 RPN score loss: 0.01109 RPN total loss: 0.03682 Total loss: 2.78163 timestamp: 1654916866.0562081 iteration: 1660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26037 FastRCNN class loss: 0.15146 FastRCNN total loss: 0.41183 L1 loss: 0.0000e+00 L2 loss: 2.14717 Learning rate: 0.02 Mask loss: 0.24367 RPN box loss: 0.03909 RPN score loss: 0.01779 RPN total loss: 0.05687 Total loss: 2.85954 timestamp: 1654916869.2946634 iteration: 1665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14429 FastRCNN class loss: 0.06296 FastRCNN total loss: 0.20725 L1 loss: 0.0000e+00 L2 loss: 2.14678 Learning rate: 0.02 Mask loss: 0.20773 RPN box loss: 0.02239 RPN score loss: 0.00734 RPN total loss: 0.02973 Total loss: 2.59149 timestamp: 1654916872.6908953 iteration: 1670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23419 FastRCNN class loss: 0.09595 FastRCNN total loss: 0.33014 L1 loss: 0.0000e+00 L2 loss: 2.14637 Learning rate: 0.02 Mask loss: 0.23506 RPN box loss: 0.03895 RPN score loss: 0.01879 RPN total loss: 0.05775 Total loss: 2.76932 timestamp: 1654916875.9501555 iteration: 1675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22074 FastRCNN class loss: 0.1045 FastRCNN total loss: 0.32524 L1 loss: 0.0000e+00 L2 loss: 2.14598 Learning rate: 0.02 Mask loss: 0.21805 RPN box loss: 0.10712 RPN score loss: 0.00969 RPN total loss: 0.11681 Total loss: 2.80607 timestamp: 1654916879.1772747 iteration: 1680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24447 FastRCNN class loss: 0.11742 FastRCNN total loss: 0.36188 L1 loss: 0.0000e+00 L2 loss: 2.14559 Learning rate: 0.02 Mask loss: 0.206 RPN box loss: 0.02223 RPN score loss: 0.00832 RPN total loss: 0.03055 Total loss: 2.74402 timestamp: 1654916882.383496 iteration: 1685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2748 FastRCNN class loss: 0.19191 FastRCNN total loss: 0.46671 L1 loss: 0.0000e+00 L2 loss: 2.1452 Learning rate: 0.02 Mask loss: 0.32612 RPN box loss: 0.03691 RPN score loss: 0.01216 RPN total loss: 0.04907 Total loss: 2.9871 timestamp: 1654916885.7226558 iteration: 1690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17336 FastRCNN class loss: 0.1276 FastRCNN total loss: 0.30096 L1 loss: 0.0000e+00 L2 loss: 2.14476 Learning rate: 0.02 Mask loss: 0.2389 RPN box loss: 0.09053 RPN score loss: 0.01799 RPN total loss: 0.10852 Total loss: 2.79314 timestamp: 1654916889.0472162 iteration: 1695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21172 FastRCNN class loss: 0.1162 FastRCNN total loss: 0.32792 L1 loss: 0.0000e+00 L2 loss: 2.14436 Learning rate: 0.02 Mask loss: 0.20197 RPN box loss: 0.01764 RPN score loss: 0.00801 RPN total loss: 0.02565 Total loss: 2.69989 timestamp: 1654916892.3833115 iteration: 1700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18045 FastRCNN class loss: 0.09762 FastRCNN total loss: 0.27807 L1 loss: 0.0000e+00 L2 loss: 2.14395 Learning rate: 0.02 Mask loss: 0.23105 RPN box loss: 0.01897 RPN score loss: 0.004 RPN total loss: 0.02297 Total loss: 2.67604 timestamp: 1654916895.5921214 iteration: 1705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29171 FastRCNN class loss: 0.16277 FastRCNN total loss: 0.45448 L1 loss: 0.0000e+00 L2 loss: 2.14354 Learning rate: 0.02 Mask loss: 0.32034 RPN box loss: 0.05373 RPN score loss: 0.02512 RPN total loss: 0.07885 Total loss: 2.9972 timestamp: 1654916898.9115493 iteration: 1710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24211 FastRCNN class loss: 0.14588 FastRCNN total loss: 0.38799 L1 loss: 0.0000e+00 L2 loss: 2.14314 Learning rate: 0.02 Mask loss: 0.25873 RPN box loss: 0.08867 RPN score loss: 0.01876 RPN total loss: 0.10743 Total loss: 2.89729 timestamp: 1654916902.2191012 iteration: 1715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23617 FastRCNN class loss: 0.10737 FastRCNN total loss: 0.34355 L1 loss: 0.0000e+00 L2 loss: 2.14273 Learning rate: 0.02 Mask loss: 0.33168 RPN box loss: 0.05924 RPN score loss: 0.01695 RPN total loss: 0.07619 Total loss: 2.89414 timestamp: 1654916905.4742823 iteration: 1720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22819 FastRCNN class loss: 0.07462 FastRCNN total loss: 0.30281 L1 loss: 0.0000e+00 L2 loss: 2.14229 Learning rate: 0.02 Mask loss: 0.22199 RPN box loss: 0.07608 RPN score loss: 0.01442 RPN total loss: 0.0905 Total loss: 2.75759 timestamp: 1654916908.7886753 iteration: 1725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36424 FastRCNN class loss: 0.1529 FastRCNN total loss: 0.51713 L1 loss: 0.0000e+00 L2 loss: 2.1419 Learning rate: 0.02 Mask loss: 0.34441 RPN box loss: 0.08852 RPN score loss: 0.02356 RPN total loss: 0.11207 Total loss: 3.11552 timestamp: 1654916912.0108645 iteration: 1730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21559 FastRCNN class loss: 0.10121 FastRCNN total loss: 0.3168 L1 loss: 0.0000e+00 L2 loss: 2.14151 Learning rate: 0.02 Mask loss: 0.48808 RPN box loss: 0.03929 RPN score loss: 0.00912 RPN total loss: 0.04841 Total loss: 2.9948 timestamp: 1654916915.360037 iteration: 1735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24406 FastRCNN class loss: 0.13868 FastRCNN total loss: 0.38274 L1 loss: 0.0000e+00 L2 loss: 2.14111 Learning rate: 0.02 Mask loss: 0.23663 RPN box loss: 0.05905 RPN score loss: 0.03308 RPN total loss: 0.09213 Total loss: 2.85262 timestamp: 1654916918.5244775 iteration: 1740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21392 FastRCNN class loss: 0.07469 FastRCNN total loss: 0.28861 L1 loss: 0.0000e+00 L2 loss: 2.14074 Learning rate: 0.02 Mask loss: 0.20287 RPN box loss: 0.02141 RPN score loss: 0.00756 RPN total loss: 0.02897 Total loss: 2.66118 timestamp: 1654916921.8704584 iteration: 1745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23533 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.31455 L1 loss: 0.0000e+00 L2 loss: 2.14032 Learning rate: 0.02 Mask loss: 0.25711 RPN box loss: 0.01425 RPN score loss: 0.00862 RPN total loss: 0.02287 Total loss: 2.73485 timestamp: 1654916925.0332587 iteration: 1750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15865 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.23919 L1 loss: 0.0000e+00 L2 loss: 2.1399 Learning rate: 0.02 Mask loss: 0.24457 RPN box loss: 0.05395 RPN score loss: 0.0104 RPN total loss: 0.06435 Total loss: 2.688 timestamp: 1654916928.308981 iteration: 1755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12098 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.18005 L1 loss: 0.0000e+00 L2 loss: 2.1395 Learning rate: 0.02 Mask loss: 0.19325 RPN box loss: 0.05646 RPN score loss: 0.00783 RPN total loss: 0.06429 Total loss: 2.57708 timestamp: 1654916931.5177062 iteration: 1760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28129 FastRCNN class loss: 0.22062 FastRCNN total loss: 0.50191 L1 loss: 0.0000e+00 L2 loss: 2.13912 Learning rate: 0.02 Mask loss: 0.22923 RPN box loss: 0.06282 RPN score loss: 0.01746 RPN total loss: 0.08028 Total loss: 2.95055 timestamp: 1654916934.9054444 iteration: 1765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2534 FastRCNN class loss: 0.10709 FastRCNN total loss: 0.36049 L1 loss: 0.0000e+00 L2 loss: 2.13872 Learning rate: 0.02 Mask loss: 0.33101 RPN box loss: 0.1651 RPN score loss: 0.02554 RPN total loss: 0.19064 Total loss: 3.02086 timestamp: 1654916938.3181045 iteration: 1770 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25267 FastRCNN class loss: 0.09898 FastRCNN total loss: 0.35165 L1 loss: 0.0000e+00 L2 loss: 2.13833 Learning rate: 0.02 Mask loss: 0.2398 RPN box loss: 0.07576 RPN score loss: 0.01655 RPN total loss: 0.09231 Total loss: 2.82208 timestamp: 1654916941.6329596 iteration: 1775 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24248 FastRCNN class loss: 0.09715 FastRCNN total loss: 0.33964 L1 loss: 0.0000e+00 L2 loss: 2.13793 Learning rate: 0.02 Mask loss: 0.18754 RPN box loss: 0.07222 RPN score loss: 0.00941 RPN total loss: 0.08163 Total loss: 2.74673 timestamp: 1654916945.0261748 iteration: 1780 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28972 FastRCNN class loss: 0.10983 FastRCNN total loss: 0.39955 L1 loss: 0.0000e+00 L2 loss: 2.13753 Learning rate: 0.02 Mask loss: 0.26225 RPN box loss: 0.05524 RPN score loss: 0.01172 RPN total loss: 0.06696 Total loss: 2.86629 timestamp: 1654916948.2097344 iteration: 1785 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26563 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.36591 L1 loss: 0.0000e+00 L2 loss: 2.13712 Learning rate: 0.02 Mask loss: 0.19445 RPN box loss: 0.01465 RPN score loss: 0.0099 RPN total loss: 0.02455 Total loss: 2.72203 timestamp: 1654916951.4900515 iteration: 1790 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3202 FastRCNN class loss: 0.12153 FastRCNN total loss: 0.44173 L1 loss: 0.0000e+00 L2 loss: 2.13672 Learning rate: 0.02 Mask loss: 0.28738 RPN box loss: 0.06487 RPN score loss: 0.03262 RPN total loss: 0.09749 Total loss: 2.96333 timestamp: 1654916954.6951208 iteration: 1795 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16193 FastRCNN class loss: 0.08016 FastRCNN total loss: 0.24209 L1 loss: 0.0000e+00 L2 loss: 2.13631 Learning rate: 0.02 Mask loss: 0.30995 RPN box loss: 0.02475 RPN score loss: 0.00912 RPN total loss: 0.03387 Total loss: 2.72223 timestamp: 1654916958.0605366 iteration: 1800 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2402 FastRCNN class loss: 0.12703 FastRCNN total loss: 0.36723 L1 loss: 0.0000e+00 L2 loss: 2.13588 Learning rate: 0.02 Mask loss: 0.27966 RPN box loss: 0.07713 RPN score loss: 0.02488 RPN total loss: 0.10201 Total loss: 2.88478 timestamp: 1654916961.394692 iteration: 1805 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27245 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.36778 L1 loss: 0.0000e+00 L2 loss: 2.13547 Learning rate: 0.02 Mask loss: 0.23884 RPN box loss: 0.01499 RPN score loss: 0.01669 RPN total loss: 0.03168 Total loss: 2.77376 timestamp: 1654916964.6413796 iteration: 1810 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28006 FastRCNN class loss: 0.10145 FastRCNN total loss: 0.38151 L1 loss: 0.0000e+00 L2 loss: 2.13507 Learning rate: 0.02 Mask loss: 0.20251 RPN box loss: 0.03572 RPN score loss: 0.00531 RPN total loss: 0.04103 Total loss: 2.76012 timestamp: 1654916967.9057355 iteration: 1815 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23508 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.30531 L1 loss: 0.0000e+00 L2 loss: 2.13467 Learning rate: 0.02 Mask loss: 0.23443 RPN box loss: 0.08027 RPN score loss: 0.01758 RPN total loss: 0.09784 Total loss: 2.77225 timestamp: 1654916971.1740518 iteration: 1820 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27822 FastRCNN class loss: 0.13337 FastRCNN total loss: 0.41159 L1 loss: 0.0000e+00 L2 loss: 2.13429 Learning rate: 0.02 Mask loss: 0.27138 RPN box loss: 0.03097 RPN score loss: 0.01028 RPN total loss: 0.04125 Total loss: 2.8585 timestamp: 1654916974.5196826 iteration: 1825 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27414 FastRCNN class loss: 0.1916 FastRCNN total loss: 0.46574 L1 loss: 0.0000e+00 L2 loss: 2.13388 Learning rate: 0.02 Mask loss: 0.29868 RPN box loss: 0.07836 RPN score loss: 0.01556 RPN total loss: 0.09392 Total loss: 2.99222 timestamp: 1654916977.8071477 iteration: 1830 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19824 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.27885 L1 loss: 0.0000e+00 L2 loss: 2.13349 Learning rate: 0.02 Mask loss: 0.19401 RPN box loss: 0.04351 RPN score loss: 0.0084 RPN total loss: 0.05191 Total loss: 2.65826 timestamp: 1654916981.0577366 iteration: 1835 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26521 FastRCNN class loss: 0.10637 FastRCNN total loss: 0.37158 L1 loss: 0.0000e+00 L2 loss: 2.13309 Learning rate: 0.02 Mask loss: 0.22312 RPN box loss: 0.03503 RPN score loss: 0.00528 RPN total loss: 0.04031 Total loss: 2.7681 timestamp: 1654916984.3036041 iteration: 1840 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14167 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.21022 L1 loss: 0.0000e+00 L2 loss: 2.13268 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.0383 RPN score loss: 0.00563 RPN total loss: 0.04392 Total loss: 2.53925 timestamp: 1654916987.698594 iteration: 1845 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17496 FastRCNN class loss: 0.12586 FastRCNN total loss: 0.30081 L1 loss: 0.0000e+00 L2 loss: 2.13225 Learning rate: 0.02 Mask loss: 0.19754 RPN box loss: 0.05783 RPN score loss: 0.01516 RPN total loss: 0.07299 Total loss: 2.70359 timestamp: 1654916990.9741216 iteration: 1850 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14129 FastRCNN class loss: 0.084 FastRCNN total loss: 0.22529 L1 loss: 0.0000e+00 L2 loss: 2.13183 Learning rate: 0.02 Mask loss: 0.21319 RPN box loss: 0.09882 RPN score loss: 0.01424 RPN total loss: 0.11307 Total loss: 2.68338 timestamp: 1654916994.1816115 iteration: 1855 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23079 FastRCNN class loss: 0.10714 FastRCNN total loss: 0.33793 L1 loss: 0.0000e+00 L2 loss: 2.13142 Learning rate: 0.02 Mask loss: 0.2285 RPN box loss: 0.098 RPN score loss: 0.00949 RPN total loss: 0.10748 Total loss: 2.80534 timestamp: 1654916997.5102043 iteration: 1860 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26054 FastRCNN class loss: 0.11109 FastRCNN total loss: 0.37162 L1 loss: 0.0000e+00 L2 loss: 2.13104 Learning rate: 0.02 Mask loss: 0.26297 RPN box loss: 0.05449 RPN score loss: 0.01031 RPN total loss: 0.0648 Total loss: 2.83043 timestamp: 1654917000.7610736 iteration: 1865 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26927 FastRCNN class loss: 0.18324 FastRCNN total loss: 0.45251 L1 loss: 0.0000e+00 L2 loss: 2.13065 Learning rate: 0.02 Mask loss: 0.29178 RPN box loss: 0.08207 RPN score loss: 0.02995 RPN total loss: 0.11203 Total loss: 2.98696 timestamp: 1654917004.103047 iteration: 1870 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23107 FastRCNN class loss: 0.09793 FastRCNN total loss: 0.32899 L1 loss: 0.0000e+00 L2 loss: 2.13024 Learning rate: 0.02 Mask loss: 0.33939 RPN box loss: 0.05899 RPN score loss: 0.01318 RPN total loss: 0.07218 Total loss: 2.8708 timestamp: 1654917007.3472688 iteration: 1875 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28613 FastRCNN class loss: 0.09217 FastRCNN total loss: 0.3783 L1 loss: 0.0000e+00 L2 loss: 2.12983 Learning rate: 0.02 Mask loss: 0.26844 RPN box loss: 0.02527 RPN score loss: 0.01025 RPN total loss: 0.03552 Total loss: 2.8121 timestamp: 1654917010.7252707 iteration: 1880 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14503 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.2201 L1 loss: 0.0000e+00 L2 loss: 2.12943 Learning rate: 0.02 Mask loss: 0.23815 RPN box loss: 0.04046 RPN score loss: 0.0113 RPN total loss: 0.05176 Total loss: 2.63944 timestamp: 1654917013.9550974 iteration: 1885 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20226 FastRCNN class loss: 0.1189 FastRCNN total loss: 0.32117 L1 loss: 0.0000e+00 L2 loss: 2.12902 Learning rate: 0.02 Mask loss: 0.35256 RPN box loss: 0.04804 RPN score loss: 0.00739 RPN total loss: 0.05543 Total loss: 2.85819 timestamp: 1654917017.343692 iteration: 1890 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14688 FastRCNN class loss: 0.09481 FastRCNN total loss: 0.24168 L1 loss: 0.0000e+00 L2 loss: 2.12861 Learning rate: 0.02 Mask loss: 0.22474 RPN box loss: 0.03302 RPN score loss: 0.00987 RPN total loss: 0.04289 Total loss: 2.63792 timestamp: 1654917020.7410598 iteration: 1895 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29529 FastRCNN class loss: 0.16091 FastRCNN total loss: 0.4562 L1 loss: 0.0000e+00 L2 loss: 2.12821 Learning rate: 0.02 Mask loss: 0.28765 RPN box loss: 0.08629 RPN score loss: 0.01627 RPN total loss: 0.10256 Total loss: 2.97462 timestamp: 1654917023.982561 iteration: 1900 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21872 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.29553 L1 loss: 0.0000e+00 L2 loss: 2.12781 Learning rate: 0.02 Mask loss: 0.27038 RPN box loss: 0.08708 RPN score loss: 0.02207 RPN total loss: 0.10916 Total loss: 2.80288 timestamp: 1654917027.241623 iteration: 1905 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1889 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.26943 L1 loss: 0.0000e+00 L2 loss: 2.12741 Learning rate: 0.02 Mask loss: 0.27064 RPN box loss: 0.10239 RPN score loss: 0.01702 RPN total loss: 0.11941 Total loss: 2.78689 timestamp: 1654917030.4801376 iteration: 1910 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35807 FastRCNN class loss: 0.2155 FastRCNN total loss: 0.57357 L1 loss: 0.0000e+00 L2 loss: 2.12701 Learning rate: 0.02 Mask loss: 0.31906 RPN box loss: 0.07641 RPN score loss: 0.03007 RPN total loss: 0.10648 Total loss: 3.12611 timestamp: 1654917033.7603538 iteration: 1915 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22775 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.291 L1 loss: 0.0000e+00 L2 loss: 2.1266 Learning rate: 0.02 Mask loss: 0.17526 RPN box loss: 0.1836 RPN score loss: 0.01227 RPN total loss: 0.19587 Total loss: 2.78874 timestamp: 1654917036.9990947 iteration: 1920 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27014 FastRCNN class loss: 0.10662 FastRCNN total loss: 0.37676 L1 loss: 0.0000e+00 L2 loss: 2.12621 Learning rate: 0.02 Mask loss: 0.26093 RPN box loss: 0.00904 RPN score loss: 0.0074 RPN total loss: 0.01644 Total loss: 2.78033 timestamp: 1654917040.3503385 iteration: 1925 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19945 FastRCNN class loss: 0.0888 FastRCNN total loss: 0.28825 L1 loss: 0.0000e+00 L2 loss: 2.1258 Learning rate: 0.02 Mask loss: 0.3022 RPN box loss: 0.048 RPN score loss: 0.00971 RPN total loss: 0.05771 Total loss: 2.77395 timestamp: 1654917043.5721536 iteration: 1930 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28261 FastRCNN class loss: 0.1379 FastRCNN total loss: 0.42051 L1 loss: 0.0000e+00 L2 loss: 2.12538 Learning rate: 0.02 Mask loss: 0.27854 RPN box loss: 0.01497 RPN score loss: 0.01284 RPN total loss: 0.02781 Total loss: 2.85224 timestamp: 1654917046.9077356 iteration: 1935 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28973 FastRCNN class loss: 0.1602 FastRCNN total loss: 0.44993 L1 loss: 0.0000e+00 L2 loss: 2.12497 Learning rate: 0.02 Mask loss: 0.30501 RPN box loss: 0.08403 RPN score loss: 0.02469 RPN total loss: 0.10871 Total loss: 2.98863 timestamp: 1654917050.1449463 iteration: 1940 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25619 FastRCNN class loss: 0.16801 FastRCNN total loss: 0.4242 L1 loss: 0.0000e+00 L2 loss: 2.12455 Learning rate: 0.02 Mask loss: 0.27412 RPN box loss: 0.0298 RPN score loss: 0.00814 RPN total loss: 0.03794 Total loss: 2.86081 timestamp: 1654917053.4395087 iteration: 1945 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21247 FastRCNN class loss: 0.11488 FastRCNN total loss: 0.32735 L1 loss: 0.0000e+00 L2 loss: 2.12413 Learning rate: 0.02 Mask loss: 0.23516 RPN box loss: 0.01764 RPN score loss: 0.00812 RPN total loss: 0.02576 Total loss: 2.71241 timestamp: 1654917056.6304333 iteration: 1950 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2204 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.31121 L1 loss: 0.0000e+00 L2 loss: 2.12375 Learning rate: 0.02 Mask loss: 0.25172 RPN box loss: 0.07021 RPN score loss: 0.014 RPN total loss: 0.08421 Total loss: 2.7709 timestamp: 1654917059.849779 iteration: 1955 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20941 FastRCNN class loss: 0.09396 FastRCNN total loss: 0.30337 L1 loss: 0.0000e+00 L2 loss: 2.12334 Learning rate: 0.02 Mask loss: 0.27303 RPN box loss: 0.07183 RPN score loss: 0.012 RPN total loss: 0.08383 Total loss: 2.78358 timestamp: 1654917063.3063962 iteration: 1960 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16294 FastRCNN class loss: 0.10504 FastRCNN total loss: 0.26798 L1 loss: 0.0000e+00 L2 loss: 2.12295 Learning rate: 0.02 Mask loss: 0.19083 RPN box loss: 0.02818 RPN score loss: 0.00674 RPN total loss: 0.03492 Total loss: 2.61667 timestamp: 1654917066.5316978 iteration: 1965 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25471 FastRCNN class loss: 0.16396 FastRCNN total loss: 0.41867 L1 loss: 0.0000e+00 L2 loss: 2.12255 Learning rate: 0.02 Mask loss: 0.25505 RPN box loss: 0.06246 RPN score loss: 0.01163 RPN total loss: 0.07408 Total loss: 2.87036 timestamp: 1654917069.838653 iteration: 1970 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15399 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.23393 L1 loss: 0.0000e+00 L2 loss: 2.12215 Learning rate: 0.02 Mask loss: 0.27807 RPN box loss: 0.03652 RPN score loss: 0.01768 RPN total loss: 0.0542 Total loss: 2.68835 timestamp: 1654917073.123276 iteration: 1975 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31406 FastRCNN class loss: 0.15788 FastRCNN total loss: 0.47194 L1 loss: 0.0000e+00 L2 loss: 2.12176 Learning rate: 0.02 Mask loss: 0.35632 RPN box loss: 0.05584 RPN score loss: 0.03931 RPN total loss: 0.09516 Total loss: 3.04518 timestamp: 1654917076.3650134 iteration: 1980 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14242 FastRCNN class loss: 0.06782 FastRCNN total loss: 0.21024 L1 loss: 0.0000e+00 L2 loss: 2.12138 Learning rate: 0.02 Mask loss: 0.20777 RPN box loss: 0.04743 RPN score loss: 0.03356 RPN total loss: 0.08099 Total loss: 2.62038 timestamp: 1654917079.6182985 iteration: 1985 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27114 FastRCNN class loss: 0.15112 FastRCNN total loss: 0.42226 L1 loss: 0.0000e+00 L2 loss: 2.12097 Learning rate: 0.02 Mask loss: 0.25056 RPN box loss: 0.1007 RPN score loss: 0.02541 RPN total loss: 0.12611 Total loss: 2.91991 timestamp: 1654917082.8997746 iteration: 1990 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2302 FastRCNN class loss: 0.11346 FastRCNN total loss: 0.34366 L1 loss: 0.0000e+00 L2 loss: 2.12055 Learning rate: 0.02 Mask loss: 0.30302 RPN box loss: 0.04415 RPN score loss: 0.012 RPN total loss: 0.05616 Total loss: 2.82339 timestamp: 1654917086.206221 iteration: 1995 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15569 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.23694 L1 loss: 0.0000e+00 L2 loss: 2.12015 Learning rate: 0.02 Mask loss: 0.21126 RPN box loss: 0.0556 RPN score loss: 0.00883 RPN total loss: 0.06444 Total loss: 2.63279 timestamp: 1654917089.4292934 iteration: 2000 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15266 FastRCNN class loss: 0.12511 FastRCNN total loss: 0.27777 L1 loss: 0.0000e+00 L2 loss: 2.11977 Learning rate: 0.02 Mask loss: 0.16898 RPN box loss: 0.04682 RPN score loss: 0.01006 RPN total loss: 0.05687 Total loss: 2.6234 timestamp: 1654917092.7333565 iteration: 2005 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17059 FastRCNN class loss: 0.06566 FastRCNN total loss: 0.23624 L1 loss: 0.0000e+00 L2 loss: 2.11937 Learning rate: 0.02 Mask loss: 0.23302 RPN box loss: 0.00703 RPN score loss: 0.00924 RPN total loss: 0.01627 Total loss: 2.60491 timestamp: 1654917096.0072322 iteration: 2010 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26726 FastRCNN class loss: 0.10319 FastRCNN total loss: 0.37045 L1 loss: 0.0000e+00 L2 loss: 2.11897 Learning rate: 0.02 Mask loss: 0.31071 RPN box loss: 0.03203 RPN score loss: 0.01363 RPN total loss: 0.04567 Total loss: 2.84579 timestamp: 1654917099.3340316 iteration: 2015 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30793 FastRCNN class loss: 0.1338 FastRCNN total loss: 0.44173 L1 loss: 0.0000e+00 L2 loss: 2.11857 Learning rate: 0.02 Mask loss: 0.20191 RPN box loss: 0.06381 RPN score loss: 0.01544 RPN total loss: 0.07925 Total loss: 2.84145 timestamp: 1654917102.576419 iteration: 2020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24716 FastRCNN class loss: 0.15138 FastRCNN total loss: 0.39855 L1 loss: 0.0000e+00 L2 loss: 2.11816 Learning rate: 0.02 Mask loss: 0.27072 RPN box loss: 0.07403 RPN score loss: 0.02315 RPN total loss: 0.09718 Total loss: 2.8846 timestamp: 1654917105.910787 iteration: 2025 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2339 FastRCNN class loss: 0.14857 FastRCNN total loss: 0.38247 L1 loss: 0.0000e+00 L2 loss: 2.11775 Learning rate: 0.02 Mask loss: 0.2184 RPN box loss: 0.14326 RPN score loss: 0.02096 RPN total loss: 0.16422 Total loss: 2.88285 timestamp: 1654917109.257181 iteration: 2030 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25397 FastRCNN class loss: 0.1311 FastRCNN total loss: 0.38507 L1 loss: 0.0000e+00 L2 loss: 2.11737 Learning rate: 0.02 Mask loss: 0.26767 RPN box loss: 0.04503 RPN score loss: 0.0241 RPN total loss: 0.06914 Total loss: 2.83925 timestamp: 1654917112.655814 iteration: 2035 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1863 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.26749 L1 loss: 0.0000e+00 L2 loss: 2.11697 Learning rate: 0.02 Mask loss: 0.22216 RPN box loss: 0.04841 RPN score loss: 0.00975 RPN total loss: 0.05816 Total loss: 2.66478 timestamp: 1654917116.0146606 iteration: 2040 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.152 FastRCNN class loss: 0.08356 FastRCNN total loss: 0.23556 L1 loss: 0.0000e+00 L2 loss: 2.11658 Learning rate: 0.02 Mask loss: 0.15899 RPN box loss: 0.04633 RPN score loss: 0.01394 RPN total loss: 0.06027 Total loss: 2.5714 timestamp: 1654917119.3495226 iteration: 2045 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25863 FastRCNN class loss: 0.1583 FastRCNN total loss: 0.41693 L1 loss: 0.0000e+00 L2 loss: 2.11618 Learning rate: 0.02 Mask loss: 0.30224 RPN box loss: 0.07058 RPN score loss: 0.01527 RPN total loss: 0.08586 Total loss: 2.9212 timestamp: 1654917122.6321795 iteration: 2050 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18036 FastRCNN class loss: 0.06222 FastRCNN total loss: 0.24258 L1 loss: 0.0000e+00 L2 loss: 2.11577 Learning rate: 0.02 Mask loss: 0.36225 RPN box loss: 0.03847 RPN score loss: 0.01176 RPN total loss: 0.05023 Total loss: 2.77082 timestamp: 1654917125.9067605 iteration: 2055 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22757 FastRCNN class loss: 0.1204 FastRCNN total loss: 0.34797 L1 loss: 0.0000e+00 L2 loss: 2.11536 Learning rate: 0.02 Mask loss: 0.18258 RPN box loss: 0.04909 RPN score loss: 0.02252 RPN total loss: 0.07161 Total loss: 2.71752 timestamp: 1654917129.2206035 iteration: 2060 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30962 FastRCNN class loss: 0.1357 FastRCNN total loss: 0.44532 L1 loss: 0.0000e+00 L2 loss: 2.11498 Learning rate: 0.02 Mask loss: 0.23722 RPN box loss: 0.0292 RPN score loss: 0.01108 RPN total loss: 0.04028 Total loss: 2.8378 timestamp: 1654917132.4309087 iteration: 2065 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19333 FastRCNN class loss: 0.10826 FastRCNN total loss: 0.30158 L1 loss: 0.0000e+00 L2 loss: 2.11457 Learning rate: 0.02 Mask loss: 0.29316 RPN box loss: 0.111 RPN score loss: 0.01669 RPN total loss: 0.12768 Total loss: 2.837 timestamp: 1654917135.690403 iteration: 2070 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22988 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.29523 L1 loss: 0.0000e+00 L2 loss: 2.11417 Learning rate: 0.02 Mask loss: 0.18513 RPN box loss: 0.02049 RPN score loss: 0.00757 RPN total loss: 0.02806 Total loss: 2.62259 timestamp: 1654917138.9681861 iteration: 2075 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16784 FastRCNN class loss: 0.07944 FastRCNN total loss: 0.24728 L1 loss: 0.0000e+00 L2 loss: 2.11374 Learning rate: 0.02 Mask loss: 0.19469 RPN box loss: 0.04967 RPN score loss: 0.01694 RPN total loss: 0.06661 Total loss: 2.62232 timestamp: 1654917142.2409816 iteration: 2080 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13595 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.19528 L1 loss: 0.0000e+00 L2 loss: 2.11336 Learning rate: 0.02 Mask loss: 0.13111 RPN box loss: 0.06195 RPN score loss: 0.00819 RPN total loss: 0.07013 Total loss: 2.50989 timestamp: 1654917145.5619736 iteration: 2085 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21234 FastRCNN class loss: 0.08964 FastRCNN total loss: 0.30198 L1 loss: 0.0000e+00 L2 loss: 2.11297 Learning rate: 0.02 Mask loss: 0.25405 RPN box loss: 0.01268 RPN score loss: 0.00607 RPN total loss: 0.01875 Total loss: 2.68775 timestamp: 1654917148.8199842 iteration: 2090 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26525 FastRCNN class loss: 0.10983 FastRCNN total loss: 0.37508 L1 loss: 0.0000e+00 L2 loss: 2.11256 Learning rate: 0.02 Mask loss: 0.20359 RPN box loss: 0.07934 RPN score loss: 0.01876 RPN total loss: 0.0981 Total loss: 2.78933 timestamp: 1654917152.1401486 iteration: 2095 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2549 FastRCNN class loss: 0.13045 FastRCNN total loss: 0.38535 L1 loss: 0.0000e+00 L2 loss: 2.11217 Learning rate: 0.02 Mask loss: 0.27355 RPN box loss: 0.0166 RPN score loss: 0.00724 RPN total loss: 0.02383 Total loss: 2.79492 timestamp: 1654917155.365091 iteration: 2100 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22884 FastRCNN class loss: 0.1085 FastRCNN total loss: 0.33734 L1 loss: 0.0000e+00 L2 loss: 2.11179 Learning rate: 0.02 Mask loss: 0.18708 RPN box loss: 0.06824 RPN score loss: 0.02026 RPN total loss: 0.0885 Total loss: 2.72472 timestamp: 1654917158.6842182 iteration: 2105 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23014 FastRCNN class loss: 0.1134 FastRCNN total loss: 0.34354 L1 loss: 0.0000e+00 L2 loss: 2.11143 Learning rate: 0.02 Mask loss: 0.23239 RPN box loss: 0.04736 RPN score loss: 0.01948 RPN total loss: 0.06683 Total loss: 2.75419 timestamp: 1654917161.8786294 iteration: 2110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20491 FastRCNN class loss: 0.10205 FastRCNN total loss: 0.30697 L1 loss: 0.0000e+00 L2 loss: 2.11102 Learning rate: 0.02 Mask loss: 0.17379 RPN box loss: 0.049 RPN score loss: 0.0122 RPN total loss: 0.0612 Total loss: 2.65298 timestamp: 1654917165.193113 iteration: 2115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25517 FastRCNN class loss: 0.13902 FastRCNN total loss: 0.39419 L1 loss: 0.0000e+00 L2 loss: 2.1106 Learning rate: 0.02 Mask loss: 0.22172 RPN box loss: 0.04349 RPN score loss: 0.01221 RPN total loss: 0.0557 Total loss: 2.78221 timestamp: 1654917168.3743615 iteration: 2120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18175 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.26348 L1 loss: 0.0000e+00 L2 loss: 2.1102 Learning rate: 0.02 Mask loss: 0.20456 RPN box loss: 0.0637 RPN score loss: 0.02163 RPN total loss: 0.08533 Total loss: 2.66356 timestamp: 1654917171.612951 iteration: 2125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14989 FastRCNN class loss: 0.11565 FastRCNN total loss: 0.26554 L1 loss: 0.0000e+00 L2 loss: 2.10981 Learning rate: 0.02 Mask loss: 0.19857 RPN box loss: 0.07466 RPN score loss: 0.014 RPN total loss: 0.08867 Total loss: 2.66259 timestamp: 1654917174.756042 iteration: 2130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14657 FastRCNN class loss: 0.06261 FastRCNN total loss: 0.20918 L1 loss: 0.0000e+00 L2 loss: 2.10942 Learning rate: 0.02 Mask loss: 0.13984 RPN box loss: 0.05114 RPN score loss: 0.00725 RPN total loss: 0.05839 Total loss: 2.51684 timestamp: 1654917178.229285 iteration: 2135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18852 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.26538 L1 loss: 0.0000e+00 L2 loss: 2.10902 Learning rate: 0.02 Mask loss: 0.19699 RPN box loss: 0.02812 RPN score loss: 0.01155 RPN total loss: 0.03967 Total loss: 2.61106 timestamp: 1654917181.4780686 iteration: 2140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23765 FastRCNN class loss: 0.10342 FastRCNN total loss: 0.34107 L1 loss: 0.0000e+00 L2 loss: 2.10862 Learning rate: 0.02 Mask loss: 0.22208 RPN box loss: 0.03781 RPN score loss: 0.00865 RPN total loss: 0.04646 Total loss: 2.71822 timestamp: 1654917184.738014 iteration: 2145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24067 FastRCNN class loss: 0.11346 FastRCNN total loss: 0.35413 L1 loss: 0.0000e+00 L2 loss: 2.1082 Learning rate: 0.02 Mask loss: 0.22896 RPN box loss: 0.08215 RPN score loss: 0.02417 RPN total loss: 0.10631 Total loss: 2.7976 timestamp: 1654917188.0120609 iteration: 2150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24395 FastRCNN class loss: 0.10899 FastRCNN total loss: 0.35294 L1 loss: 0.0000e+00 L2 loss: 2.10782 Learning rate: 0.02 Mask loss: 0.21857 RPN box loss: 0.09244 RPN score loss: 0.03257 RPN total loss: 0.12501 Total loss: 2.80433 timestamp: 1654917191.1902301 iteration: 2155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22671 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.3126 L1 loss: 0.0000e+00 L2 loss: 2.10742 Learning rate: 0.02 Mask loss: 0.29093 RPN box loss: 0.07378 RPN score loss: 0.00968 RPN total loss: 0.08346 Total loss: 2.79441 timestamp: 1654917194.484275 iteration: 2160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15994 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.25086 L1 loss: 0.0000e+00 L2 loss: 2.10703 Learning rate: 0.02 Mask loss: 0.15623 RPN box loss: 0.05669 RPN score loss: 0.01603 RPN total loss: 0.07272 Total loss: 2.58685 timestamp: 1654917197.7033362 iteration: 2165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22505 FastRCNN class loss: 0.09503 FastRCNN total loss: 0.32008 L1 loss: 0.0000e+00 L2 loss: 2.10664 Learning rate: 0.02 Mask loss: 0.20625 RPN box loss: 0.03407 RPN score loss: 0.01228 RPN total loss: 0.04635 Total loss: 2.67932 timestamp: 1654917201.055555 iteration: 2170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16076 FastRCNN class loss: 0.08906 FastRCNN total loss: 0.24982 L1 loss: 0.0000e+00 L2 loss: 2.10623 Learning rate: 0.02 Mask loss: 0.2046 RPN box loss: 0.09486 RPN score loss: 0.00893 RPN total loss: 0.10379 Total loss: 2.66444 timestamp: 1654917204.3042176 iteration: 2175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25081 FastRCNN class loss: 0.11526 FastRCNN total loss: 0.36606 L1 loss: 0.0000e+00 L2 loss: 2.10584 Learning rate: 0.02 Mask loss: 0.25024 RPN box loss: 0.05728 RPN score loss: 0.03915 RPN total loss: 0.09643 Total loss: 2.81857 timestamp: 1654917207.6206732 iteration: 2180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34711 FastRCNN class loss: 0.17473 FastRCNN total loss: 0.52184 L1 loss: 0.0000e+00 L2 loss: 2.10544 Learning rate: 0.02 Mask loss: 0.25747 RPN box loss: 0.04663 RPN score loss: 0.01855 RPN total loss: 0.06519 Total loss: 2.94993 timestamp: 1654917211.0321503 iteration: 2185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10644 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.18152 L1 loss: 0.0000e+00 L2 loss: 2.10504 Learning rate: 0.02 Mask loss: 0.17674 RPN box loss: 0.03739 RPN score loss: 0.01282 RPN total loss: 0.05021 Total loss: 2.51351 timestamp: 1654917214.222896 iteration: 2190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20852 FastRCNN class loss: 0.11548 FastRCNN total loss: 0.324 L1 loss: 0.0000e+00 L2 loss: 2.10463 Learning rate: 0.02 Mask loss: 0.22061 RPN box loss: 0.06651 RPN score loss: 0.01177 RPN total loss: 0.07827 Total loss: 2.72752 timestamp: 1654917217.4690413 iteration: 2195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26254 FastRCNN class loss: 0.07659 FastRCNN total loss: 0.33914 L1 loss: 0.0000e+00 L2 loss: 2.10422 Learning rate: 0.02 Mask loss: 0.28889 RPN box loss: 0.04944 RPN score loss: 0.01095 RPN total loss: 0.06039 Total loss: 2.79264 timestamp: 1654917220.7509046 iteration: 2200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22403 FastRCNN class loss: 0.13687 FastRCNN total loss: 0.3609 L1 loss: 0.0000e+00 L2 loss: 2.10382 Learning rate: 0.02 Mask loss: 0.22701 RPN box loss: 0.05598 RPN score loss: 0.01631 RPN total loss: 0.07229 Total loss: 2.76402 timestamp: 1654917223.9975462 iteration: 2205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20566 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.27753 L1 loss: 0.0000e+00 L2 loss: 2.10341 Learning rate: 0.02 Mask loss: 0.18725 RPN box loss: 0.0322 RPN score loss: 0.00755 RPN total loss: 0.03975 Total loss: 2.60794 timestamp: 1654917227.1783173 iteration: 2210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27395 FastRCNN class loss: 0.13474 FastRCNN total loss: 0.40869 L1 loss: 0.0000e+00 L2 loss: 2.10301 Learning rate: 0.02 Mask loss: 0.33113 RPN box loss: 0.06319 RPN score loss: 0.044 RPN total loss: 0.10719 Total loss: 2.95002 timestamp: 1654917230.4476633 iteration: 2215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26598 FastRCNN class loss: 0.14928 FastRCNN total loss: 0.41526 L1 loss: 0.0000e+00 L2 loss: 2.10261 Learning rate: 0.02 Mask loss: 0.29936 RPN box loss: 0.03813 RPN score loss: 0.01236 RPN total loss: 0.05049 Total loss: 2.86771 timestamp: 1654917233.6329238 iteration: 2220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17064 FastRCNN class loss: 0.07582 FastRCNN total loss: 0.24646 L1 loss: 0.0000e+00 L2 loss: 2.10221 Learning rate: 0.02 Mask loss: 0.17004 RPN box loss: 0.03391 RPN score loss: 0.00607 RPN total loss: 0.03998 Total loss: 2.5587 timestamp: 1654917236.906774 iteration: 2225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29768 FastRCNN class loss: 0.12223 FastRCNN total loss: 0.41991 L1 loss: 0.0000e+00 L2 loss: 2.10181 Learning rate: 0.02 Mask loss: 0.2109 RPN box loss: 0.12316 RPN score loss: 0.0129 RPN total loss: 0.13606 Total loss: 2.86868 timestamp: 1654917240.1152816 iteration: 2230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1805 FastRCNN class loss: 0.07946 FastRCNN total loss: 0.25996 L1 loss: 0.0000e+00 L2 loss: 2.10142 Learning rate: 0.02 Mask loss: 0.20492 RPN box loss: 0.06494 RPN score loss: 0.01065 RPN total loss: 0.07559 Total loss: 2.64189 timestamp: 1654917243.4248712 iteration: 2235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16707 FastRCNN class loss: 0.13978 FastRCNN total loss: 0.30685 L1 loss: 0.0000e+00 L2 loss: 2.10101 Learning rate: 0.02 Mask loss: 0.15768 RPN box loss: 0.11215 RPN score loss: 0.01408 RPN total loss: 0.12623 Total loss: 2.69177 timestamp: 1654917246.619946 iteration: 2240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19904 FastRCNN class loss: 0.11532 FastRCNN total loss: 0.31436 L1 loss: 0.0000e+00 L2 loss: 2.10062 Learning rate: 0.02 Mask loss: 0.29146 RPN box loss: 0.04884 RPN score loss: 0.01221 RPN total loss: 0.06105 Total loss: 2.76749 timestamp: 1654917249.903764 iteration: 2245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19909 FastRCNN class loss: 0.1425 FastRCNN total loss: 0.34159 L1 loss: 0.0000e+00 L2 loss: 2.10023 Learning rate: 0.02 Mask loss: 0.24589 RPN box loss: 0.02941 RPN score loss: 0.0072 RPN total loss: 0.03661 Total loss: 2.72431 timestamp: 1654917253.1808078 iteration: 2250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25094 FastRCNN class loss: 0.12332 FastRCNN total loss: 0.37425 L1 loss: 0.0000e+00 L2 loss: 2.09983 Learning rate: 0.02 Mask loss: 0.16251 RPN box loss: 0.16228 RPN score loss: 0.01389 RPN total loss: 0.17616 Total loss: 2.81276 timestamp: 1654917256.4593508 iteration: 2255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20195 FastRCNN class loss: 0.08492 FastRCNN total loss: 0.28687 L1 loss: 0.0000e+00 L2 loss: 2.09942 Learning rate: 0.02 Mask loss: 0.28635 RPN box loss: 0.05257 RPN score loss: 0.00999 RPN total loss: 0.06256 Total loss: 2.7352 timestamp: 1654917259.7578995 iteration: 2260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20534 FastRCNN class loss: 0.13987 FastRCNN total loss: 0.3452 L1 loss: 0.0000e+00 L2 loss: 2.099 Learning rate: 0.02 Mask loss: 0.29273 RPN box loss: 0.07681 RPN score loss: 0.01396 RPN total loss: 0.09077 Total loss: 2.82771 timestamp: 1654917262.9510174 iteration: 2265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18279 FastRCNN class loss: 0.12147 FastRCNN total loss: 0.30426 L1 loss: 0.0000e+00 L2 loss: 2.09861 Learning rate: 0.02 Mask loss: 0.15586 RPN box loss: 0.08763 RPN score loss: 0.01806 RPN total loss: 0.10569 Total loss: 2.66442 timestamp: 1654917266.2214017 iteration: 2270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17562 FastRCNN class loss: 0.08055 FastRCNN total loss: 0.25618 L1 loss: 0.0000e+00 L2 loss: 2.09822 Learning rate: 0.02 Mask loss: 0.16737 RPN box loss: 0.12047 RPN score loss: 0.01659 RPN total loss: 0.13706 Total loss: 2.65882 timestamp: 1654917269.4192796 iteration: 2275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1581 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.24778 L1 loss: 0.0000e+00 L2 loss: 2.09782 Learning rate: 0.02 Mask loss: 0.16604 RPN box loss: 0.03256 RPN score loss: 0.01227 RPN total loss: 0.04483 Total loss: 2.55647 timestamp: 1654917272.7033935 iteration: 2280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19432 FastRCNN class loss: 0.09692 FastRCNN total loss: 0.29124 L1 loss: 0.0000e+00 L2 loss: 2.09744 Learning rate: 0.02 Mask loss: 0.21716 RPN box loss: 0.03425 RPN score loss: 0.0116 RPN total loss: 0.04585 Total loss: 2.65169 timestamp: 1654917275.9294164 iteration: 2285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25995 FastRCNN class loss: 0.18156 FastRCNN total loss: 0.44151 L1 loss: 0.0000e+00 L2 loss: 2.09703 Learning rate: 0.02 Mask loss: 0.26348 RPN box loss: 0.03065 RPN score loss: 0.00959 RPN total loss: 0.04023 Total loss: 2.84226 timestamp: 1654917279.1695771 iteration: 2290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17028 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.23752 L1 loss: 0.0000e+00 L2 loss: 2.09663 Learning rate: 0.02 Mask loss: 0.15296 RPN box loss: 0.01899 RPN score loss: 0.0063 RPN total loss: 0.02528 Total loss: 2.51239 timestamp: 1654917282.4115274 iteration: 2295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31699 FastRCNN class loss: 0.11366 FastRCNN total loss: 0.43065 L1 loss: 0.0000e+00 L2 loss: 2.09624 Learning rate: 0.02 Mask loss: 0.27813 RPN box loss: 0.02328 RPN score loss: 0.01725 RPN total loss: 0.04053 Total loss: 2.84554 timestamp: 1654917285.6829555 iteration: 2300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2686 FastRCNN class loss: 0.12888 FastRCNN total loss: 0.39748 L1 loss: 0.0000e+00 L2 loss: 2.09584 Learning rate: 0.02 Mask loss: 0.34513 RPN box loss: 0.0183 RPN score loss: 0.00732 RPN total loss: 0.02562 Total loss: 2.86407 timestamp: 1654917288.9299603 iteration: 2305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21232 FastRCNN class loss: 0.13316 FastRCNN total loss: 0.34547 L1 loss: 0.0000e+00 L2 loss: 2.09543 Learning rate: 0.02 Mask loss: 0.26297 RPN box loss: 0.06891 RPN score loss: 0.01816 RPN total loss: 0.08707 Total loss: 2.79095 timestamp: 1654917292.1975255 iteration: 2310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09544 FastRCNN class loss: 0.11674 FastRCNN total loss: 0.21219 L1 loss: 0.0000e+00 L2 loss: 2.09504 Learning rate: 0.02 Mask loss: 0.19799 RPN box loss: 0.05965 RPN score loss: 0.00576 RPN total loss: 0.06541 Total loss: 2.57062 timestamp: 1654917295.4950237 iteration: 2315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22221 FastRCNN class loss: 0.10744 FastRCNN total loss: 0.32965 L1 loss: 0.0000e+00 L2 loss: 2.09464 Learning rate: 0.02 Mask loss: 0.20655 RPN box loss: 0.06587 RPN score loss: 0.00981 RPN total loss: 0.07568 Total loss: 2.70653 timestamp: 1654917298.749571 iteration: 2320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25863 FastRCNN class loss: 0.12863 FastRCNN total loss: 0.38726 L1 loss: 0.0000e+00 L2 loss: 2.09425 Learning rate: 0.02 Mask loss: 0.23089 RPN box loss: 0.08519 RPN score loss: 0.03869 RPN total loss: 0.12388 Total loss: 2.83627 timestamp: 1654917302.0695474 iteration: 2325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25084 FastRCNN class loss: 0.08664 FastRCNN total loss: 0.33748 L1 loss: 0.0000e+00 L2 loss: 2.09386 Learning rate: 0.02 Mask loss: 0.19917 RPN box loss: 0.02959 RPN score loss: 0.01047 RPN total loss: 0.04006 Total loss: 2.67057 timestamp: 1654917305.2526221 iteration: 2330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18052 FastRCNN class loss: 0.10471 FastRCNN total loss: 0.28524 L1 loss: 0.0000e+00 L2 loss: 2.09346 Learning rate: 0.02 Mask loss: 0.19033 RPN box loss: 0.10264 RPN score loss: 0.01696 RPN total loss: 0.1196 Total loss: 2.68863 timestamp: 1654917308.543416 iteration: 2335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15324 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.21405 L1 loss: 0.0000e+00 L2 loss: 2.09307 Learning rate: 0.02 Mask loss: 0.18767 RPN box loss: 0.05096 RPN score loss: 0.01276 RPN total loss: 0.06372 Total loss: 2.5585 timestamp: 1654917311.7117164 iteration: 2340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16434 FastRCNN class loss: 0.11806 FastRCNN total loss: 0.2824 L1 loss: 0.0000e+00 L2 loss: 2.09267 Learning rate: 0.02 Mask loss: 0.24773 RPN box loss: 0.02125 RPN score loss: 0.00648 RPN total loss: 0.02773 Total loss: 2.65052 timestamp: 1654917315.0324357 iteration: 2345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21041 FastRCNN class loss: 0.08894 FastRCNN total loss: 0.29934 L1 loss: 0.0000e+00 L2 loss: 2.09228 Learning rate: 0.02 Mask loss: 0.28521 RPN box loss: 0.06813 RPN score loss: 0.01185 RPN total loss: 0.07998 Total loss: 2.75682 timestamp: 1654917318.4759216 iteration: 2350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25613 FastRCNN class loss: 0.11886 FastRCNN total loss: 0.375 L1 loss: 0.0000e+00 L2 loss: 2.09188 Learning rate: 0.02 Mask loss: 0.23102 RPN box loss: 0.02936 RPN score loss: 0.01103 RPN total loss: 0.04039 Total loss: 2.73829 timestamp: 1654917321.7602952 iteration: 2355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3062 FastRCNN class loss: 0.1274 FastRCNN total loss: 0.4336 L1 loss: 0.0000e+00 L2 loss: 2.0915 Learning rate: 0.02 Mask loss: 0.22173 RPN box loss: 0.06422 RPN score loss: 0.01818 RPN total loss: 0.08241 Total loss: 2.82924 timestamp: 1654917325.106666 iteration: 2360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09744 FastRCNN class loss: 0.0582 FastRCNN total loss: 0.15563 L1 loss: 0.0000e+00 L2 loss: 2.0911 Learning rate: 0.02 Mask loss: 0.31904 RPN box loss: 0.04553 RPN score loss: 0.00779 RPN total loss: 0.05332 Total loss: 2.61908 timestamp: 1654917328.3914814 iteration: 2365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15346 FastRCNN class loss: 0.15124 FastRCNN total loss: 0.3047 L1 loss: 0.0000e+00 L2 loss: 2.09071 Learning rate: 0.02 Mask loss: 0.18245 RPN box loss: 0.06729 RPN score loss: 0.00969 RPN total loss: 0.07697 Total loss: 2.65484 timestamp: 1654917331.7165391 iteration: 2370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17926 FastRCNN class loss: 0.09466 FastRCNN total loss: 0.27392 L1 loss: 0.0000e+00 L2 loss: 2.09034 Learning rate: 0.02 Mask loss: 0.22197 RPN box loss: 0.06959 RPN score loss: 0.01479 RPN total loss: 0.08438 Total loss: 2.67061 timestamp: 1654917334.975564 iteration: 2375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16833 FastRCNN class loss: 0.08822 FastRCNN total loss: 0.25655 L1 loss: 0.0000e+00 L2 loss: 2.08995 Learning rate: 0.02 Mask loss: 0.21 RPN box loss: 0.08476 RPN score loss: 0.00997 RPN total loss: 0.09473 Total loss: 2.65122 timestamp: 1654917338.1585062 iteration: 2380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17541 FastRCNN class loss: 0.09186 FastRCNN total loss: 0.26726 L1 loss: 0.0000e+00 L2 loss: 2.08954 Learning rate: 0.02 Mask loss: 0.19252 RPN box loss: 0.01643 RPN score loss: 0.00409 RPN total loss: 0.02051 Total loss: 2.56984 timestamp: 1654917341.5654738 iteration: 2385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18217 FastRCNN class loss: 0.1059 FastRCNN total loss: 0.28807 L1 loss: 0.0000e+00 L2 loss: 2.08912 Learning rate: 0.02 Mask loss: 0.22093 RPN box loss: 0.04553 RPN score loss: 0.0204 RPN total loss: 0.06594 Total loss: 2.66407 timestamp: 1654917344.8258443 iteration: 2390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15222 FastRCNN class loss: 0.07695 FastRCNN total loss: 0.22918 L1 loss: 0.0000e+00 L2 loss: 2.08873 Learning rate: 0.02 Mask loss: 0.21643 RPN box loss: 0.02519 RPN score loss: 0.00905 RPN total loss: 0.03424 Total loss: 2.56858 timestamp: 1654917348.2480414 iteration: 2395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17542 FastRCNN class loss: 0.05492 FastRCNN total loss: 0.23034 L1 loss: 0.0000e+00 L2 loss: 2.08833 Learning rate: 0.02 Mask loss: 0.17733 RPN box loss: 0.08408 RPN score loss: 0.00866 RPN total loss: 0.09273 Total loss: 2.58873 timestamp: 1654917351.5159266 iteration: 2400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22831 FastRCNN class loss: 0.10521 FastRCNN total loss: 0.33352 L1 loss: 0.0000e+00 L2 loss: 2.08795 Learning rate: 0.02 Mask loss: 0.19735 RPN box loss: 0.05409 RPN score loss: 0.0107 RPN total loss: 0.06479 Total loss: 2.68362 timestamp: 1654917354.9101171 iteration: 2405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2736 FastRCNN class loss: 0.13514 FastRCNN total loss: 0.40874 L1 loss: 0.0000e+00 L2 loss: 2.08756 Learning rate: 0.02 Mask loss: 0.26115 RPN box loss: 0.02367 RPN score loss: 0.01284 RPN total loss: 0.03651 Total loss: 2.79396 timestamp: 1654917358.120225 iteration: 2410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18426 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.27653 L1 loss: 0.0000e+00 L2 loss: 2.08716 Learning rate: 0.02 Mask loss: 0.24073 RPN box loss: 0.11376 RPN score loss: 0.01509 RPN total loss: 0.12884 Total loss: 2.73327 timestamp: 1654917361.4321716 iteration: 2415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14471 FastRCNN class loss: 0.0663 FastRCNN total loss: 0.21101 L1 loss: 0.0000e+00 L2 loss: 2.08675 Learning rate: 0.02 Mask loss: 0.16881 RPN box loss: 0.06863 RPN score loss: 0.00915 RPN total loss: 0.07778 Total loss: 2.54435 timestamp: 1654917364.5681727 iteration: 2420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2338 FastRCNN class loss: 0.0983 FastRCNN total loss: 0.3321 L1 loss: 0.0000e+00 L2 loss: 2.08636 Learning rate: 0.02 Mask loss: 0.22339 RPN box loss: 0.0375 RPN score loss: 0.02683 RPN total loss: 0.06433 Total loss: 2.70618 timestamp: 1654917367.9091024 iteration: 2425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19756 FastRCNN class loss: 0.12679 FastRCNN total loss: 0.32436 L1 loss: 0.0000e+00 L2 loss: 2.08596 Learning rate: 0.02 Mask loss: 0.32048 RPN box loss: 0.1108 RPN score loss: 0.0208 RPN total loss: 0.1316 Total loss: 2.8624 timestamp: 1654917371.2255166 iteration: 2430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26764 FastRCNN class loss: 0.1023 FastRCNN total loss: 0.36994 L1 loss: 0.0000e+00 L2 loss: 2.08558 Learning rate: 0.02 Mask loss: 0.23047 RPN box loss: 0.04428 RPN score loss: 0.00866 RPN total loss: 0.05294 Total loss: 2.73894 timestamp: 1654917374.428954 iteration: 2435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15524 FastRCNN class loss: 0.08024 FastRCNN total loss: 0.23548 L1 loss: 0.0000e+00 L2 loss: 2.08518 Learning rate: 0.02 Mask loss: 0.14018 RPN box loss: 0.01617 RPN score loss: 0.00823 RPN total loss: 0.0244 Total loss: 2.48525 timestamp: 1654917377.7625973 iteration: 2440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21081 FastRCNN class loss: 0.13007 FastRCNN total loss: 0.34088 L1 loss: 0.0000e+00 L2 loss: 2.08478 Learning rate: 0.02 Mask loss: 0.31964 RPN box loss: 0.11461 RPN score loss: 0.011 RPN total loss: 0.12561 Total loss: 2.8709 timestamp: 1654917380.937176 iteration: 2445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29352 FastRCNN class loss: 0.10556 FastRCNN total loss: 0.39908 L1 loss: 0.0000e+00 L2 loss: 2.08437 Learning rate: 0.02 Mask loss: 0.29481 RPN box loss: 0.05954 RPN score loss: 0.01694 RPN total loss: 0.07649 Total loss: 2.85475 timestamp: 1654917384.3106966 iteration: 2450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15379 FastRCNN class loss: 0.10265 FastRCNN total loss: 0.25645 L1 loss: 0.0000e+00 L2 loss: 2.084 Learning rate: 0.02 Mask loss: 0.2262 RPN box loss: 0.05894 RPN score loss: 0.02739 RPN total loss: 0.08633 Total loss: 2.65298 timestamp: 1654917387.579821 iteration: 2455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1979 FastRCNN class loss: 0.10993 FastRCNN total loss: 0.30783 L1 loss: 0.0000e+00 L2 loss: 2.0836 Learning rate: 0.02 Mask loss: 0.30555 RPN box loss: 0.00968 RPN score loss: 0.01371 RPN total loss: 0.02339 Total loss: 2.72038 timestamp: 1654917390.9559665 iteration: 2460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.245 FastRCNN class loss: 0.10048 FastRCNN total loss: 0.34547 L1 loss: 0.0000e+00 L2 loss: 2.0832 Learning rate: 0.02 Mask loss: 0.30271 RPN box loss: 0.04115 RPN score loss: 0.0128 RPN total loss: 0.05394 Total loss: 2.78533 timestamp: 1654917394.136349 iteration: 2465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18663 FastRCNN class loss: 0.09248 FastRCNN total loss: 0.27911 L1 loss: 0.0000e+00 L2 loss: 2.08282 Learning rate: 0.02 Mask loss: 0.19499 RPN box loss: 0.04506 RPN score loss: 0.00865 RPN total loss: 0.0537 Total loss: 2.61062 timestamp: 1654917397.4732885 iteration: 2470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16641 FastRCNN class loss: 0.12924 FastRCNN total loss: 0.29565 L1 loss: 0.0000e+00 L2 loss: 2.08243 Learning rate: 0.02 Mask loss: 0.21115 RPN box loss: 0.03025 RPN score loss: 0.01172 RPN total loss: 0.04197 Total loss: 2.6312 timestamp: 1654917400.7068825 iteration: 2475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13486 FastRCNN class loss: 0.07735 FastRCNN total loss: 0.2122 L1 loss: 0.0000e+00 L2 loss: 2.08203 Learning rate: 0.02 Mask loss: 0.22264 RPN box loss: 0.04938 RPN score loss: 0.01208 RPN total loss: 0.06146 Total loss: 2.57834 timestamp: 1654917404.0241477 iteration: 2480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18134 FastRCNN class loss: 0.14698 FastRCNN total loss: 0.32833 L1 loss: 0.0000e+00 L2 loss: 2.08165 Learning rate: 0.02 Mask loss: 0.25068 RPN box loss: 0.07475 RPN score loss: 0.01327 RPN total loss: 0.08802 Total loss: 2.74868 timestamp: 1654917407.356721 iteration: 2485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14187 FastRCNN class loss: 0.11367 FastRCNN total loss: 0.25554 L1 loss: 0.0000e+00 L2 loss: 2.08125 Learning rate: 0.02 Mask loss: 0.19848 RPN box loss: 0.07745 RPN score loss: 0.01036 RPN total loss: 0.08781 Total loss: 2.62308 timestamp: 1654917410.6301134 iteration: 2490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19446 FastRCNN class loss: 0.11221 FastRCNN total loss: 0.30667 L1 loss: 0.0000e+00 L2 loss: 2.08086 Learning rate: 0.02 Mask loss: 0.14924 RPN box loss: 0.00873 RPN score loss: 0.00717 RPN total loss: 0.01591 Total loss: 2.55267 timestamp: 1654917413.883278 iteration: 2495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14093 FastRCNN class loss: 0.08136 FastRCNN total loss: 0.22229 L1 loss: 0.0000e+00 L2 loss: 2.08047 Learning rate: 0.02 Mask loss: 0.16273 RPN box loss: 0.02668 RPN score loss: 0.0078 RPN total loss: 0.03448 Total loss: 2.49997 timestamp: 1654917417.151787 iteration: 2500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17492 FastRCNN class loss: 0.1262 FastRCNN total loss: 0.30113 L1 loss: 0.0000e+00 L2 loss: 2.08007 Learning rate: 0.02 Mask loss: 0.17474 RPN box loss: 0.09748 RPN score loss: 0.01119 RPN total loss: 0.10867 Total loss: 2.66461 timestamp: 1654917420.51548 iteration: 2505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24618 FastRCNN class loss: 0.09334 FastRCNN total loss: 0.33951 L1 loss: 0.0000e+00 L2 loss: 2.07968 Learning rate: 0.02 Mask loss: 0.19428 RPN box loss: 0.03755 RPN score loss: 0.01091 RPN total loss: 0.04846 Total loss: 2.66193 timestamp: 1654917423.73606 iteration: 2510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1774 FastRCNN class loss: 0.14587 FastRCNN total loss: 0.32326 L1 loss: 0.0000e+00 L2 loss: 2.07926 Learning rate: 0.02 Mask loss: 0.23693 RPN box loss: 0.07214 RPN score loss: 0.00775 RPN total loss: 0.07989 Total loss: 2.71934 timestamp: 1654917427.1734989 iteration: 2515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25129 FastRCNN class loss: 0.13264 FastRCNN total loss: 0.38394 L1 loss: 0.0000e+00 L2 loss: 2.07888 Learning rate: 0.02 Mask loss: 0.28763 RPN box loss: 0.11065 RPN score loss: 0.02075 RPN total loss: 0.13139 Total loss: 2.88184 timestamp: 1654917430.4342408 iteration: 2520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19811 FastRCNN class loss: 0.10611 FastRCNN total loss: 0.30422 L1 loss: 0.0000e+00 L2 loss: 2.07849 Learning rate: 0.02 Mask loss: 0.2553 RPN box loss: 0.0725 RPN score loss: 0.01375 RPN total loss: 0.08625 Total loss: 2.72426 timestamp: 1654917433.8200657 iteration: 2525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.199 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.28003 L1 loss: 0.0000e+00 L2 loss: 2.07808 Learning rate: 0.02 Mask loss: 0.23303 RPN box loss: 0.08048 RPN score loss: 0.03414 RPN total loss: 0.11462 Total loss: 2.70577 timestamp: 1654917437.0281763 iteration: 2530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18143 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.27837 L1 loss: 0.0000e+00 L2 loss: 2.0777 Learning rate: 0.02 Mask loss: 0.33885 RPN box loss: 0.02492 RPN score loss: 0.00583 RPN total loss: 0.03075 Total loss: 2.72567 timestamp: 1654917440.3184705 iteration: 2535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20391 FastRCNN class loss: 0.09943 FastRCNN total loss: 0.30334 L1 loss: 0.0000e+00 L2 loss: 2.07731 Learning rate: 0.02 Mask loss: 0.22738 RPN box loss: 0.05178 RPN score loss: 0.02355 RPN total loss: 0.07533 Total loss: 2.68336 timestamp: 1654917443.6472723 iteration: 2540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21207 FastRCNN class loss: 0.12252 FastRCNN total loss: 0.33459 L1 loss: 0.0000e+00 L2 loss: 2.07693 Learning rate: 0.02 Mask loss: 0.27946 RPN box loss: 0.07706 RPN score loss: 0.01729 RPN total loss: 0.09435 Total loss: 2.78533 timestamp: 1654917446.8527899 iteration: 2545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15384 FastRCNN class loss: 0.05668 FastRCNN total loss: 0.21052 L1 loss: 0.0000e+00 L2 loss: 2.07653 Learning rate: 0.02 Mask loss: 0.22589 RPN box loss: 0.07066 RPN score loss: 0.01044 RPN total loss: 0.0811 Total loss: 2.59404 timestamp: 1654917450.2452917 iteration: 2550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27716 FastRCNN class loss: 0.12866 FastRCNN total loss: 0.40581 L1 loss: 0.0000e+00 L2 loss: 2.07614 Learning rate: 0.02 Mask loss: 0.32197 RPN box loss: 0.02708 RPN score loss: 0.00797 RPN total loss: 0.03506 Total loss: 2.83897 timestamp: 1654917453.4497592 iteration: 2555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19865 FastRCNN class loss: 0.09231 FastRCNN total loss: 0.29097 L1 loss: 0.0000e+00 L2 loss: 2.07573 Learning rate: 0.02 Mask loss: 0.33574 RPN box loss: 0.10021 RPN score loss: 0.01255 RPN total loss: 0.11277 Total loss: 2.8152 timestamp: 1654917456.844191 iteration: 2560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1869 FastRCNN class loss: 0.17533 FastRCNN total loss: 0.36223 L1 loss: 0.0000e+00 L2 loss: 2.07534 Learning rate: 0.02 Mask loss: 0.27826 RPN box loss: 0.08339 RPN score loss: 0.0198 RPN total loss: 0.1032 Total loss: 2.81902 timestamp: 1654917460.044171 iteration: 2565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24323 FastRCNN class loss: 0.16678 FastRCNN total loss: 0.41001 L1 loss: 0.0000e+00 L2 loss: 2.07494 Learning rate: 0.02 Mask loss: 0.195 RPN box loss: 0.06477 RPN score loss: 0.01552 RPN total loss: 0.0803 Total loss: 2.76025 timestamp: 1654917463.379179 iteration: 2570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15202 FastRCNN class loss: 0.08566 FastRCNN total loss: 0.23767 L1 loss: 0.0000e+00 L2 loss: 2.07456 Learning rate: 0.02 Mask loss: 0.20003 RPN box loss: 0.0114 RPN score loss: 0.00302 RPN total loss: 0.01442 Total loss: 2.52668 timestamp: 1654917466.617758 iteration: 2575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26843 FastRCNN class loss: 0.12745 FastRCNN total loss: 0.39588 L1 loss: 0.0000e+00 L2 loss: 2.07416 Learning rate: 0.02 Mask loss: 0.26232 RPN box loss: 0.02645 RPN score loss: 0.01281 RPN total loss: 0.03927 Total loss: 2.77163 timestamp: 1654917469.7949133 iteration: 2580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20522 FastRCNN class loss: 0.13876 FastRCNN total loss: 0.34397 L1 loss: 0.0000e+00 L2 loss: 2.07379 Learning rate: 0.02 Mask loss: 0.26953 RPN box loss: 0.10463 RPN score loss: 0.0191 RPN total loss: 0.12373 Total loss: 2.81102 timestamp: 1654917473.118471 iteration: 2585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17598 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.2489 L1 loss: 0.0000e+00 L2 loss: 2.07337 Learning rate: 0.02 Mask loss: 0.2601 RPN box loss: 0.0362 RPN score loss: 0.00714 RPN total loss: 0.04334 Total loss: 2.62571 timestamp: 1654917476.2924724 iteration: 2590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18973 FastRCNN class loss: 0.09405 FastRCNN total loss: 0.28378 L1 loss: 0.0000e+00 L2 loss: 2.07298 Learning rate: 0.02 Mask loss: 0.16057 RPN box loss: 0.02289 RPN score loss: 0.0048 RPN total loss: 0.02769 Total loss: 2.54502 timestamp: 1654917479.5946488 iteration: 2595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31186 FastRCNN class loss: 0.1273 FastRCNN total loss: 0.43915 L1 loss: 0.0000e+00 L2 loss: 2.07258 Learning rate: 0.02 Mask loss: 0.2697 RPN box loss: 0.14406 RPN score loss: 0.02127 RPN total loss: 0.16533 Total loss: 2.94677 timestamp: 1654917482.842313 iteration: 2600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15392 FastRCNN class loss: 0.10612 FastRCNN total loss: 0.26004 L1 loss: 0.0000e+00 L2 loss: 2.0722 Learning rate: 0.02 Mask loss: 0.19785 RPN box loss: 0.04036 RPN score loss: 0.00766 RPN total loss: 0.04802 Total loss: 2.57811 timestamp: 1654917486.1870687 iteration: 2605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14234 FastRCNN class loss: 0.06893 FastRCNN total loss: 0.21127 L1 loss: 0.0000e+00 L2 loss: 2.07182 Learning rate: 0.02 Mask loss: 0.20792 RPN box loss: 0.00602 RPN score loss: 0.00606 RPN total loss: 0.01207 Total loss: 2.50308 timestamp: 1654917489.371579 iteration: 2610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17374 FastRCNN class loss: 0.11895 FastRCNN total loss: 0.29268 L1 loss: 0.0000e+00 L2 loss: 2.07143 Learning rate: 0.02 Mask loss: 0.19903 RPN box loss: 0.04477 RPN score loss: 0.00775 RPN total loss: 0.05252 Total loss: 2.61566 timestamp: 1654917492.551145 iteration: 2615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20553 FastRCNN class loss: 0.09222 FastRCNN total loss: 0.29775 L1 loss: 0.0000e+00 L2 loss: 2.07103 Learning rate: 0.02 Mask loss: 0.2577 RPN box loss: 0.05525 RPN score loss: 0.01266 RPN total loss: 0.06791 Total loss: 2.69439 timestamp: 1654917495.7155523 iteration: 2620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25801 FastRCNN class loss: 0.12256 FastRCNN total loss: 0.38057 L1 loss: 0.0000e+00 L2 loss: 2.07064 Learning rate: 0.02 Mask loss: 0.28528 RPN box loss: 0.03327 RPN score loss: 0.00999 RPN total loss: 0.04327 Total loss: 2.77976 timestamp: 1654917499.1114404 iteration: 2625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1916 FastRCNN class loss: 0.0858 FastRCNN total loss: 0.2774 L1 loss: 0.0000e+00 L2 loss: 2.07025 Learning rate: 0.02 Mask loss: 0.16532 RPN box loss: 0.04109 RPN score loss: 0.00725 RPN total loss: 0.04834 Total loss: 2.56131 timestamp: 1654917502.2739823 iteration: 2630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16327 FastRCNN class loss: 0.09324 FastRCNN total loss: 0.25652 L1 loss: 0.0000e+00 L2 loss: 2.06986 Learning rate: 0.02 Mask loss: 0.21108 RPN box loss: 0.03735 RPN score loss: 0.00971 RPN total loss: 0.04707 Total loss: 2.58452 timestamp: 1654917505.55584 iteration: 2635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19578 FastRCNN class loss: 0.09586 FastRCNN total loss: 0.29164 L1 loss: 0.0000e+00 L2 loss: 2.06945 Learning rate: 0.02 Mask loss: 0.19294 RPN box loss: 0.01357 RPN score loss: 0.00523 RPN total loss: 0.0188 Total loss: 2.57283 timestamp: 1654917508.889554 iteration: 2640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23757 FastRCNN class loss: 0.09107 FastRCNN total loss: 0.32864 L1 loss: 0.0000e+00 L2 loss: 2.06905 Learning rate: 0.02 Mask loss: 0.2244 RPN box loss: 0.04796 RPN score loss: 0.01056 RPN total loss: 0.05852 Total loss: 2.68061 timestamp: 1654917512.1270902 iteration: 2645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1483 FastRCNN class loss: 0.06485 FastRCNN total loss: 0.21315 L1 loss: 0.0000e+00 L2 loss: 2.06866 Learning rate: 0.02 Mask loss: 0.17258 RPN box loss: 0.08804 RPN score loss: 0.01514 RPN total loss: 0.10317 Total loss: 2.55756 timestamp: 1654917515.3796177 iteration: 2650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17727 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.25297 L1 loss: 0.0000e+00 L2 loss: 2.06826 Learning rate: 0.02 Mask loss: 0.18593 RPN box loss: 0.01766 RPN score loss: 0.0162 RPN total loss: 0.03386 Total loss: 2.54102 timestamp: 1654917518.66446 iteration: 2655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20584 FastRCNN class loss: 0.08513 FastRCNN total loss: 0.29097 L1 loss: 0.0000e+00 L2 loss: 2.06786 Learning rate: 0.02 Mask loss: 0.24048 RPN box loss: 0.03359 RPN score loss: 0.00918 RPN total loss: 0.04277 Total loss: 2.64208 timestamp: 1654917521.9144776 iteration: 2660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23774 FastRCNN class loss: 0.11117 FastRCNN total loss: 0.34891 L1 loss: 0.0000e+00 L2 loss: 2.06746 Learning rate: 0.02 Mask loss: 0.26121 RPN box loss: 0.02132 RPN score loss: 0.00953 RPN total loss: 0.03085 Total loss: 2.70843 timestamp: 1654917525.1431408 iteration: 2665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15996 FastRCNN class loss: 0.1214 FastRCNN total loss: 0.28137 L1 loss: 0.0000e+00 L2 loss: 2.06705 Learning rate: 0.02 Mask loss: 0.20348 RPN box loss: 0.05725 RPN score loss: 0.01019 RPN total loss: 0.06744 Total loss: 2.61935 timestamp: 1654917528.525019 iteration: 2670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23461 FastRCNN class loss: 0.0949 FastRCNN total loss: 0.32951 L1 loss: 0.0000e+00 L2 loss: 2.06668 Learning rate: 0.02 Mask loss: 0.22511 RPN box loss: 0.05347 RPN score loss: 0.01354 RPN total loss: 0.06702 Total loss: 2.68831 timestamp: 1654917531.7677047 iteration: 2675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22734 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.31884 L1 loss: 0.0000e+00 L2 loss: 2.0663 Learning rate: 0.02 Mask loss: 0.19159 RPN box loss: 0.01618 RPN score loss: 0.00833 RPN total loss: 0.02451 Total loss: 2.60124 timestamp: 1654917535.079353 iteration: 2680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17859 FastRCNN class loss: 0.13284 FastRCNN total loss: 0.31144 L1 loss: 0.0000e+00 L2 loss: 2.06591 Learning rate: 0.02 Mask loss: 0.35275 RPN box loss: 0.05537 RPN score loss: 0.00749 RPN total loss: 0.06286 Total loss: 2.79296 timestamp: 1654917538.363792 iteration: 2685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12819 FastRCNN class loss: 0.10951 FastRCNN total loss: 0.2377 L1 loss: 0.0000e+00 L2 loss: 2.06553 Learning rate: 0.02 Mask loss: 0.20794 RPN box loss: 0.09775 RPN score loss: 0.01487 RPN total loss: 0.11262 Total loss: 2.62379 timestamp: 1654917541.6377401 iteration: 2690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21733 FastRCNN class loss: 0.19934 FastRCNN total loss: 0.41667 L1 loss: 0.0000e+00 L2 loss: 2.06514 Learning rate: 0.02 Mask loss: 0.25736 RPN box loss: 0.09025 RPN score loss: 0.02291 RPN total loss: 0.11316 Total loss: 2.85232 timestamp: 1654917544.9024775 iteration: 2695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09986 FastRCNN class loss: 0.0572 FastRCNN total loss: 0.15706 L1 loss: 0.0000e+00 L2 loss: 2.06474 Learning rate: 0.02 Mask loss: 0.19995 RPN box loss: 0.04876 RPN score loss: 0.00388 RPN total loss: 0.05264 Total loss: 2.47439 timestamp: 1654917548.1075466 iteration: 2700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17542 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.26281 L1 loss: 0.0000e+00 L2 loss: 2.06434 Learning rate: 0.02 Mask loss: 0.24551 RPN box loss: 0.07382 RPN score loss: 0.0091 RPN total loss: 0.08293 Total loss: 2.65559 timestamp: 1654917551.3241293 iteration: 2705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18914 FastRCNN class loss: 0.10771 FastRCNN total loss: 0.29685 L1 loss: 0.0000e+00 L2 loss: 2.06395 Learning rate: 0.02 Mask loss: 0.27388 RPN box loss: 0.08566 RPN score loss: 0.0181 RPN total loss: 0.10376 Total loss: 2.73844 timestamp: 1654917554.5698059 iteration: 2710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1349 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.20276 L1 loss: 0.0000e+00 L2 loss: 2.06356 Learning rate: 0.02 Mask loss: 0.19901 RPN box loss: 0.02547 RPN score loss: 0.00655 RPN total loss: 0.03202 Total loss: 2.49735 timestamp: 1654917557.7908807 iteration: 2715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22852 FastRCNN class loss: 0.13053 FastRCNN total loss: 0.35906 L1 loss: 0.0000e+00 L2 loss: 2.06318 Learning rate: 0.02 Mask loss: 0.18485 RPN box loss: 0.04772 RPN score loss: 0.01228 RPN total loss: 0.06001 Total loss: 2.6671 timestamp: 1654917560.964318 iteration: 2720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18514 FastRCNN class loss: 0.09877 FastRCNN total loss: 0.28391 L1 loss: 0.0000e+00 L2 loss: 2.06278 Learning rate: 0.02 Mask loss: 0.25641 RPN box loss: 0.0775 RPN score loss: 0.0318 RPN total loss: 0.1093 Total loss: 2.71239 timestamp: 1654917564.3591413 iteration: 2725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23006 FastRCNN class loss: 0.12437 FastRCNN total loss: 0.35442 L1 loss: 0.0000e+00 L2 loss: 2.06239 Learning rate: 0.02 Mask loss: 0.28438 RPN box loss: 0.06808 RPN score loss: 0.01317 RPN total loss: 0.08125 Total loss: 2.78244 timestamp: 1654917567.517812 iteration: 2730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19518 FastRCNN class loss: 0.07469 FastRCNN total loss: 0.26986 L1 loss: 0.0000e+00 L2 loss: 2.062 Learning rate: 0.02 Mask loss: 0.12349 RPN box loss: 0.07551 RPN score loss: 0.00985 RPN total loss: 0.08536 Total loss: 2.5407 timestamp: 1654917570.915257 iteration: 2735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13644 FastRCNN class loss: 0.09675 FastRCNN total loss: 0.23319 L1 loss: 0.0000e+00 L2 loss: 2.06161 Learning rate: 0.02 Mask loss: 0.17185 RPN box loss: 0.02687 RPN score loss: 0.01391 RPN total loss: 0.04078 Total loss: 2.50743 timestamp: 1654917574.333707 iteration: 2740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30717 FastRCNN class loss: 0.11122 FastRCNN total loss: 0.41839 L1 loss: 0.0000e+00 L2 loss: 2.06122 Learning rate: 0.02 Mask loss: 0.22627 RPN box loss: 0.10232 RPN score loss: 0.00743 RPN total loss: 0.10975 Total loss: 2.81563 timestamp: 1654917577.5507865 iteration: 2745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21403 FastRCNN class loss: 0.11897 FastRCNN total loss: 0.333 L1 loss: 0.0000e+00 L2 loss: 2.06083 Learning rate: 0.02 Mask loss: 0.20086 RPN box loss: 0.14014 RPN score loss: 0.01673 RPN total loss: 0.15687 Total loss: 2.75156 timestamp: 1654917580.8156602 iteration: 2750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22543 FastRCNN class loss: 0.0904 FastRCNN total loss: 0.31583 L1 loss: 0.0000e+00 L2 loss: 2.06044 Learning rate: 0.02 Mask loss: 0.19291 RPN box loss: 0.08121 RPN score loss: 0.01193 RPN total loss: 0.09314 Total loss: 2.66232 timestamp: 1654917583.9920876 iteration: 2755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23712 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.32832 L1 loss: 0.0000e+00 L2 loss: 2.06006 Learning rate: 0.02 Mask loss: 0.29399 RPN box loss: 0.03787 RPN score loss: 0.02653 RPN total loss: 0.0644 Total loss: 2.74677 timestamp: 1654917587.2838953 iteration: 2760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24069 FastRCNN class loss: 0.1846 FastRCNN total loss: 0.42529 L1 loss: 0.0000e+00 L2 loss: 2.05967 Learning rate: 0.02 Mask loss: 0.219 RPN box loss: 0.03112 RPN score loss: 0.01468 RPN total loss: 0.04579 Total loss: 2.74975 timestamp: 1654917590.5241687 iteration: 2765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25381 FastRCNN class loss: 0.13751 FastRCNN total loss: 0.39132 L1 loss: 0.0000e+00 L2 loss: 2.05927 Learning rate: 0.02 Mask loss: 0.27552 RPN box loss: 0.02967 RPN score loss: 0.00626 RPN total loss: 0.03592 Total loss: 2.76204 timestamp: 1654917593.8436985 iteration: 2770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15252 FastRCNN class loss: 0.11266 FastRCNN total loss: 0.26519 L1 loss: 0.0000e+00 L2 loss: 2.05887 Learning rate: 0.02 Mask loss: 0.20074 RPN box loss: 0.05842 RPN score loss: 0.00997 RPN total loss: 0.06839 Total loss: 2.5932 timestamp: 1654917597.120506 iteration: 2775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15712 FastRCNN class loss: 0.12193 FastRCNN total loss: 0.27905 L1 loss: 0.0000e+00 L2 loss: 2.0585 Learning rate: 0.02 Mask loss: 0.19663 RPN box loss: 0.07765 RPN score loss: 0.02884 RPN total loss: 0.10648 Total loss: 2.64067 timestamp: 1654917600.4555488 iteration: 2780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17978 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.26596 L1 loss: 0.0000e+00 L2 loss: 2.05812 Learning rate: 0.02 Mask loss: 0.16227 RPN box loss: 0.03531 RPN score loss: 0.00432 RPN total loss: 0.03963 Total loss: 2.52598 timestamp: 1654917603.7347817 iteration: 2785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21468 FastRCNN class loss: 0.08129 FastRCNN total loss: 0.29598 L1 loss: 0.0000e+00 L2 loss: 2.05772 Learning rate: 0.02 Mask loss: 0.21375 RPN box loss: 0.09367 RPN score loss: 0.00741 RPN total loss: 0.10108 Total loss: 2.66853 timestamp: 1654917606.9233742 iteration: 2790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18125 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.26338 L1 loss: 0.0000e+00 L2 loss: 2.05732 Learning rate: 0.02 Mask loss: 0.19218 RPN box loss: 0.01784 RPN score loss: 0.00646 RPN total loss: 0.0243 Total loss: 2.53718 timestamp: 1654917610.2280326 iteration: 2795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18052 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.24235 L1 loss: 0.0000e+00 L2 loss: 2.05694 Learning rate: 0.02 Mask loss: 0.15453 RPN box loss: 0.01661 RPN score loss: 0.00937 RPN total loss: 0.02598 Total loss: 2.4798 timestamp: 1654917613.438176 iteration: 2800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28206 FastRCNN class loss: 0.14031 FastRCNN total loss: 0.42237 L1 loss: 0.0000e+00 L2 loss: 2.05654 Learning rate: 0.02 Mask loss: 0.23947 RPN box loss: 0.05252 RPN score loss: 0.01163 RPN total loss: 0.06415 Total loss: 2.78254 timestamp: 1654917616.83467 iteration: 2805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10919 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.17017 L1 loss: 0.0000e+00 L2 loss: 2.05615 Learning rate: 0.02 Mask loss: 0.14949 RPN box loss: 0.03187 RPN score loss: 0.00686 RPN total loss: 0.03873 Total loss: 2.41455 timestamp: 1654917620.0488195 iteration: 2810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23399 FastRCNN class loss: 0.14558 FastRCNN total loss: 0.37956 L1 loss: 0.0000e+00 L2 loss: 2.05575 Learning rate: 0.02 Mask loss: 0.29901 RPN box loss: 0.09389 RPN score loss: 0.0109 RPN total loss: 0.10479 Total loss: 2.83911 timestamp: 1654917623.453676 iteration: 2815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23157 FastRCNN class loss: 0.09013 FastRCNN total loss: 0.3217 L1 loss: 0.0000e+00 L2 loss: 2.05538 Learning rate: 0.02 Mask loss: 0.20005 RPN box loss: 0.02294 RPN score loss: 0.00518 RPN total loss: 0.02811 Total loss: 2.60524 timestamp: 1654917626.6909344 iteration: 2820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2262 FastRCNN class loss: 0.08822 FastRCNN total loss: 0.31442 L1 loss: 0.0000e+00 L2 loss: 2.05498 Learning rate: 0.02 Mask loss: 0.17406 RPN box loss: 0.026 RPN score loss: 0.00871 RPN total loss: 0.03472 Total loss: 2.57818 timestamp: 1654917630.0337737 iteration: 2825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19742 FastRCNN class loss: 0.10069 FastRCNN total loss: 0.29811 L1 loss: 0.0000e+00 L2 loss: 2.05458 Learning rate: 0.02 Mask loss: 0.24634 RPN box loss: 0.06779 RPN score loss: 0.01356 RPN total loss: 0.08135 Total loss: 2.68039 timestamp: 1654917633.4112873 iteration: 2830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20231 FastRCNN class loss: 0.11722 FastRCNN total loss: 0.31953 L1 loss: 0.0000e+00 L2 loss: 2.0542 Learning rate: 0.02 Mask loss: 0.20362 RPN box loss: 0.03922 RPN score loss: 0.01101 RPN total loss: 0.05023 Total loss: 2.62758 timestamp: 1654917636.5623355 iteration: 2835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21939 FastRCNN class loss: 0.10107 FastRCNN total loss: 0.32046 L1 loss: 0.0000e+00 L2 loss: 2.0538 Learning rate: 0.02 Mask loss: 0.16138 RPN box loss: 0.0931 RPN score loss: 0.01289 RPN total loss: 0.10599 Total loss: 2.64163 timestamp: 1654917639.8513799 iteration: 2840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29472 FastRCNN class loss: 0.14044 FastRCNN total loss: 0.43517 L1 loss: 0.0000e+00 L2 loss: 2.05342 Learning rate: 0.02 Mask loss: 0.26894 RPN box loss: 0.07263 RPN score loss: 0.03131 RPN total loss: 0.10394 Total loss: 2.86147 timestamp: 1654917643.0740545 iteration: 2845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09769 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.16535 L1 loss: 0.0000e+00 L2 loss: 2.05303 Learning rate: 0.02 Mask loss: 0.17452 RPN box loss: 0.06334 RPN score loss: 0.01136 RPN total loss: 0.0747 Total loss: 2.4676 timestamp: 1654917646.39499 iteration: 2850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19158 FastRCNN class loss: 0.09098 FastRCNN total loss: 0.28256 L1 loss: 0.0000e+00 L2 loss: 2.05265 Learning rate: 0.02 Mask loss: 0.17672 RPN box loss: 0.02972 RPN score loss: 0.01141 RPN total loss: 0.04113 Total loss: 2.55306 timestamp: 1654917649.6114857 iteration: 2855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23039 FastRCNN class loss: 0.18687 FastRCNN total loss: 0.41726 L1 loss: 0.0000e+00 L2 loss: 2.05226 Learning rate: 0.02 Mask loss: 0.26233 RPN box loss: 0.08119 RPN score loss: 0.01918 RPN total loss: 0.10037 Total loss: 2.83222 timestamp: 1654917653.0226402 iteration: 2860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16854 FastRCNN class loss: 0.08959 FastRCNN total loss: 0.25813 L1 loss: 0.0000e+00 L2 loss: 2.05188 Learning rate: 0.02 Mask loss: 0.14832 RPN box loss: 0.05061 RPN score loss: 0.00934 RPN total loss: 0.05995 Total loss: 2.51828 timestamp: 1654917656.2616093 iteration: 2865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1535 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.22976 L1 loss: 0.0000e+00 L2 loss: 2.0515 Learning rate: 0.02 Mask loss: 0.22869 RPN box loss: 0.01753 RPN score loss: 0.00592 RPN total loss: 0.02345 Total loss: 2.5334 timestamp: 1654917659.4400346 iteration: 2870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23455 FastRCNN class loss: 0.10904 FastRCNN total loss: 0.34359 L1 loss: 0.0000e+00 L2 loss: 2.05111 Learning rate: 0.02 Mask loss: 0.23868 RPN box loss: 0.059 RPN score loss: 0.01434 RPN total loss: 0.07334 Total loss: 2.70673 timestamp: 1654917662.667955 iteration: 2875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22305 FastRCNN class loss: 0.10749 FastRCNN total loss: 0.33054 L1 loss: 0.0000e+00 L2 loss: 2.05072 Learning rate: 0.02 Mask loss: 0.18774 RPN box loss: 0.03271 RPN score loss: 0.00615 RPN total loss: 0.03887 Total loss: 2.60786 timestamp: 1654917665.92439 iteration: 2880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15043 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.21486 L1 loss: 0.0000e+00 L2 loss: 2.05035 Learning rate: 0.02 Mask loss: 0.19995 RPN box loss: 0.01192 RPN score loss: 0.00522 RPN total loss: 0.01714 Total loss: 2.4823 timestamp: 1654917669.1068242 iteration: 2885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21177 FastRCNN class loss: 0.08982 FastRCNN total loss: 0.30159 L1 loss: 0.0000e+00 L2 loss: 2.04998 Learning rate: 0.02 Mask loss: 0.22549 RPN box loss: 0.02632 RPN score loss: 0.00672 RPN total loss: 0.03304 Total loss: 2.61009 timestamp: 1654917672.3970923 iteration: 2890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24392 FastRCNN class loss: 0.11513 FastRCNN total loss: 0.35904 L1 loss: 0.0000e+00 L2 loss: 2.0496 Learning rate: 0.02 Mask loss: 0.29548 RPN box loss: 0.01887 RPN score loss: 0.01615 RPN total loss: 0.03502 Total loss: 2.73914 timestamp: 1654917675.6535156 iteration: 2895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22163 FastRCNN class loss: 0.09355 FastRCNN total loss: 0.31519 L1 loss: 0.0000e+00 L2 loss: 2.04921 Learning rate: 0.02 Mask loss: 0.18735 RPN box loss: 0.1404 RPN score loss: 0.01238 RPN total loss: 0.15278 Total loss: 2.70453 timestamp: 1654917678.8789744 iteration: 2900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17425 FastRCNN class loss: 0.09529 FastRCNN total loss: 0.26954 L1 loss: 0.0000e+00 L2 loss: 2.04884 Learning rate: 0.02 Mask loss: 0.17601 RPN box loss: 0.09158 RPN score loss: 0.01409 RPN total loss: 0.10567 Total loss: 2.60006 timestamp: 1654917682.0255876 iteration: 2905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25067 FastRCNN class loss: 0.11816 FastRCNN total loss: 0.36883 L1 loss: 0.0000e+00 L2 loss: 2.04845 Learning rate: 0.02 Mask loss: 0.17603 RPN box loss: 0.05947 RPN score loss: 0.01084 RPN total loss: 0.07031 Total loss: 2.66361 timestamp: 1654917685.2873523 iteration: 2910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18501 FastRCNN class loss: 0.13703 FastRCNN total loss: 0.32204 L1 loss: 0.0000e+00 L2 loss: 2.04806 Learning rate: 0.02 Mask loss: 0.24649 RPN box loss: 0.05726 RPN score loss: 0.01643 RPN total loss: 0.07369 Total loss: 2.69028 timestamp: 1654917688.5343022 iteration: 2915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1095 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.17116 L1 loss: 0.0000e+00 L2 loss: 2.04768 Learning rate: 0.02 Mask loss: 0.13747 RPN box loss: 0.00845 RPN score loss: 0.00585 RPN total loss: 0.01431 Total loss: 2.37062 timestamp: 1654917691.799221 iteration: 2920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20041 FastRCNN class loss: 0.13571 FastRCNN total loss: 0.33612 L1 loss: 0.0000e+00 L2 loss: 2.04728 Learning rate: 0.02 Mask loss: 0.25596 RPN box loss: 0.04265 RPN score loss: 0.02263 RPN total loss: 0.06528 Total loss: 2.70464 timestamp: 1654917695.096947 iteration: 2925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35657 FastRCNN class loss: 0.16311 FastRCNN total loss: 0.51968 L1 loss: 0.0000e+00 L2 loss: 2.04688 Learning rate: 0.02 Mask loss: 0.49704 RPN box loss: 0.05292 RPN score loss: 0.00812 RPN total loss: 0.06104 Total loss: 3.12464 timestamp: 1654917698.308345 iteration: 2930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22407 FastRCNN class loss: 0.12153 FastRCNN total loss: 0.34559 L1 loss: 0.0000e+00 L2 loss: 2.04649 Learning rate: 0.02 Mask loss: 0.23137 RPN box loss: 0.07481 RPN score loss: 0.00783 RPN total loss: 0.08264 Total loss: 2.7061 timestamp: 1654917701.4866195 iteration: 2935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23297 FastRCNN class loss: 0.12789 FastRCNN total loss: 0.36087 L1 loss: 0.0000e+00 L2 loss: 2.04609 Learning rate: 0.02 Mask loss: 0.20133 RPN box loss: 0.03508 RPN score loss: 0.01031 RPN total loss: 0.04539 Total loss: 2.65368 timestamp: 1654917704.803531 iteration: 2940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1228 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.20035 L1 loss: 0.0000e+00 L2 loss: 2.04571 Learning rate: 0.02 Mask loss: 0.33622 RPN box loss: 0.03368 RPN score loss: 0.00421 RPN total loss: 0.0379 Total loss: 2.62017 timestamp: 1654917708.0746927 iteration: 2945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25468 FastRCNN class loss: 0.14649 FastRCNN total loss: 0.40118 L1 loss: 0.0000e+00 L2 loss: 2.04529 Learning rate: 0.02 Mask loss: 0.22837 RPN box loss: 0.04591 RPN score loss: 0.02832 RPN total loss: 0.07423 Total loss: 2.74907 timestamp: 1654917711.3354716 iteration: 2950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19725 FastRCNN class loss: 0.09031 FastRCNN total loss: 0.28756 L1 loss: 0.0000e+00 L2 loss: 2.04492 Learning rate: 0.02 Mask loss: 0.17696 RPN box loss: 0.10501 RPN score loss: 0.01406 RPN total loss: 0.11907 Total loss: 2.62852 timestamp: 1654917714.6523285 iteration: 2955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18269 FastRCNN class loss: 0.10669 FastRCNN total loss: 0.28938 L1 loss: 0.0000e+00 L2 loss: 2.04454 Learning rate: 0.02 Mask loss: 0.21423 RPN box loss: 0.01661 RPN score loss: 0.00821 RPN total loss: 0.02482 Total loss: 2.57296 timestamp: 1654917717.9348707 iteration: 2960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16705 FastRCNN class loss: 0.09707 FastRCNN total loss: 0.26412 L1 loss: 0.0000e+00 L2 loss: 2.04414 Learning rate: 0.02 Mask loss: 0.20064 RPN box loss: 0.02566 RPN score loss: 0.00569 RPN total loss: 0.03136 Total loss: 2.54026 timestamp: 1654917721.1613064 iteration: 2965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23718 FastRCNN class loss: 0.13793 FastRCNN total loss: 0.3751 L1 loss: 0.0000e+00 L2 loss: 2.04378 Learning rate: 0.02 Mask loss: 0.30178 RPN box loss: 0.04403 RPN score loss: 0.01004 RPN total loss: 0.05406 Total loss: 2.77473 timestamp: 1654917724.3632855 iteration: 2970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2718 FastRCNN class loss: 0.12441 FastRCNN total loss: 0.39621 L1 loss: 0.0000e+00 L2 loss: 2.04338 Learning rate: 0.02 Mask loss: 0.22048 RPN box loss: 0.03577 RPN score loss: 0.02488 RPN total loss: 0.06065 Total loss: 2.72072 timestamp: 1654917727.5313058 iteration: 2975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14496 FastRCNN class loss: 0.05752 FastRCNN total loss: 0.20248 L1 loss: 0.0000e+00 L2 loss: 2.04303 Learning rate: 0.02 Mask loss: 0.19861 RPN box loss: 0.01444 RPN score loss: 0.00397 RPN total loss: 0.01841 Total loss: 2.46252 timestamp: 1654917730.799814 iteration: 2980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26812 FastRCNN class loss: 0.0824 FastRCNN total loss: 0.35052 L1 loss: 0.0000e+00 L2 loss: 2.04263 Learning rate: 0.02 Mask loss: 0.23212 RPN box loss: 0.01046 RPN score loss: 0.00634 RPN total loss: 0.01679 Total loss: 2.64206 timestamp: 1654917734.057264 iteration: 2985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18681 FastRCNN class loss: 0.11745 FastRCNN total loss: 0.30425 L1 loss: 0.0000e+00 L2 loss: 2.04225 Learning rate: 0.02 Mask loss: 0.20123 RPN box loss: 0.01992 RPN score loss: 0.00881 RPN total loss: 0.02872 Total loss: 2.57645 timestamp: 1654917737.3852074 iteration: 2990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2845 FastRCNN class loss: 0.11155 FastRCNN total loss: 0.39606 L1 loss: 0.0000e+00 L2 loss: 2.04187 Learning rate: 0.02 Mask loss: 0.20237 RPN box loss: 0.04208 RPN score loss: 0.00941 RPN total loss: 0.05149 Total loss: 2.69178 timestamp: 1654917740.6830835 iteration: 2995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14004 FastRCNN class loss: 0.0714 FastRCNN total loss: 0.21144 L1 loss: 0.0000e+00 L2 loss: 2.0415 Learning rate: 0.02 Mask loss: 0.14677 RPN box loss: 0.08454 RPN score loss: 0.01543 RPN total loss: 0.09997 Total loss: 2.49968 timestamp: 1654917743.9321175 iteration: 3000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17426 FastRCNN class loss: 0.11169 FastRCNN total loss: 0.28595 L1 loss: 0.0000e+00 L2 loss: 2.04112 Learning rate: 0.02 Mask loss: 0.17353 RPN box loss: 0.04135 RPN score loss: 0.01481 RPN total loss: 0.05615 Total loss: 2.55676 timestamp: 1654917747.160111 iteration: 3005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2263 FastRCNN class loss: 0.13532 FastRCNN total loss: 0.36162 L1 loss: 0.0000e+00 L2 loss: 2.04074 Learning rate: 0.02 Mask loss: 0.28157 RPN box loss: 0.01771 RPN score loss: 0.01553 RPN total loss: 0.03324 Total loss: 2.71717 timestamp: 1654917750.3774793 iteration: 3010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2155 FastRCNN class loss: 0.18708 FastRCNN total loss: 0.40258 L1 loss: 0.0000e+00 L2 loss: 2.04035 Learning rate: 0.02 Mask loss: 0.32994 RPN box loss: 0.05412 RPN score loss: 0.01648 RPN total loss: 0.0706 Total loss: 2.84346 timestamp: 1654917753.6677158 iteration: 3015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2492 FastRCNN class loss: 0.15973 FastRCNN total loss: 0.40892 L1 loss: 0.0000e+00 L2 loss: 2.03994 Learning rate: 0.02 Mask loss: 0.17971 RPN box loss: 0.07005 RPN score loss: 0.01143 RPN total loss: 0.08148 Total loss: 2.71006 timestamp: 1654917756.9322677 iteration: 3020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15009 FastRCNN class loss: 0.0646 FastRCNN total loss: 0.21469 L1 loss: 0.0000e+00 L2 loss: 2.03955 Learning rate: 0.02 Mask loss: 0.18017 RPN box loss: 0.01291 RPN score loss: 0.00474 RPN total loss: 0.01766 Total loss: 2.45206 timestamp: 1654917760.2270658 iteration: 3025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29933 FastRCNN class loss: 0.12434 FastRCNN total loss: 0.42366 L1 loss: 0.0000e+00 L2 loss: 2.03916 Learning rate: 0.02 Mask loss: 0.23012 RPN box loss: 0.04861 RPN score loss: 0.00953 RPN total loss: 0.05815 Total loss: 2.7511 timestamp: 1654917763.4866316 iteration: 3030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13606 FastRCNN class loss: 0.09091 FastRCNN total loss: 0.22697 L1 loss: 0.0000e+00 L2 loss: 2.03879 Learning rate: 0.02 Mask loss: 0.33835 RPN box loss: 0.06783 RPN score loss: 0.01432 RPN total loss: 0.08215 Total loss: 2.68625 timestamp: 1654917766.7876875 iteration: 3035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20559 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.29175 L1 loss: 0.0000e+00 L2 loss: 2.03842 Learning rate: 0.02 Mask loss: 0.20828 RPN box loss: 0.01317 RPN score loss: 0.00492 RPN total loss: 0.01809 Total loss: 2.55653 timestamp: 1654917770.1834521 iteration: 3040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24852 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.318 L1 loss: 0.0000e+00 L2 loss: 2.03804 Learning rate: 0.02 Mask loss: 0.21011 RPN box loss: 0.09828 RPN score loss: 0.01344 RPN total loss: 0.11172 Total loss: 2.67787 timestamp: 1654917773.4207761 iteration: 3045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3675 FastRCNN class loss: 0.09189 FastRCNN total loss: 0.45938 L1 loss: 0.0000e+00 L2 loss: 2.03764 Learning rate: 0.02 Mask loss: 0.24696 RPN box loss: 0.10796 RPN score loss: 0.00908 RPN total loss: 0.11704 Total loss: 2.86103 timestamp: 1654917776.7049682 iteration: 3050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18183 FastRCNN class loss: 0.10005 FastRCNN total loss: 0.28187 L1 loss: 0.0000e+00 L2 loss: 2.03726 Learning rate: 0.02 Mask loss: 0.23561 RPN box loss: 0.04335 RPN score loss: 0.01427 RPN total loss: 0.05762 Total loss: 2.61236 timestamp: 1654917779.9268095 iteration: 3055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12803 FastRCNN class loss: 0.06312 FastRCNN total loss: 0.19115 L1 loss: 0.0000e+00 L2 loss: 2.03688 Learning rate: 0.02 Mask loss: 0.2352 RPN box loss: 0.0657 RPN score loss: 0.02742 RPN total loss: 0.09312 Total loss: 2.55635 timestamp: 1654917783.269638 iteration: 3060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31625 FastRCNN class loss: 0.11102 FastRCNN total loss: 0.42727 L1 loss: 0.0000e+00 L2 loss: 2.03649 Learning rate: 0.02 Mask loss: 0.19519 RPN box loss: 0.04614 RPN score loss: 0.01258 RPN total loss: 0.05872 Total loss: 2.71767 timestamp: 1654917786.4695363 iteration: 3065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1947 FastRCNN class loss: 0.08898 FastRCNN total loss: 0.28368 L1 loss: 0.0000e+00 L2 loss: 2.03612 Learning rate: 0.02 Mask loss: 0.16573 RPN box loss: 0.03542 RPN score loss: 0.0182 RPN total loss: 0.05361 Total loss: 2.53915 timestamp: 1654917789.8314004 iteration: 3070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21494 FastRCNN class loss: 0.10261 FastRCNN total loss: 0.31756 L1 loss: 0.0000e+00 L2 loss: 2.03573 Learning rate: 0.02 Mask loss: 0.26435 RPN box loss: 0.08768 RPN score loss: 0.01545 RPN total loss: 0.10313 Total loss: 2.72077 timestamp: 1654917793.036445 iteration: 3075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15761 FastRCNN class loss: 0.09311 FastRCNN total loss: 0.25072 L1 loss: 0.0000e+00 L2 loss: 2.03536 Learning rate: 0.02 Mask loss: 0.19488 RPN box loss: 0.07538 RPN score loss: 0.00998 RPN total loss: 0.08536 Total loss: 2.56633 timestamp: 1654917796.366802 iteration: 3080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17984 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.24764 L1 loss: 0.0000e+00 L2 loss: 2.03498 Learning rate: 0.02 Mask loss: 0.21375 RPN box loss: 0.0663 RPN score loss: 0.00585 RPN total loss: 0.07214 Total loss: 2.56852 timestamp: 1654917799.6406207 iteration: 3085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18117 FastRCNN class loss: 0.10524 FastRCNN total loss: 0.28641 L1 loss: 0.0000e+00 L2 loss: 2.0346 Learning rate: 0.02 Mask loss: 0.25535 RPN box loss: 0.06607 RPN score loss: 0.00994 RPN total loss: 0.07601 Total loss: 2.65237 timestamp: 1654917802.8944361 iteration: 3090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14173 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.20827 L1 loss: 0.0000e+00 L2 loss: 2.03423 Learning rate: 0.02 Mask loss: 0.19435 RPN box loss: 0.04327 RPN score loss: 0.00818 RPN total loss: 0.05145 Total loss: 2.4883 timestamp: 1654917806.1962004 iteration: 3095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24391 FastRCNN class loss: 0.13987 FastRCNN total loss: 0.38378 L1 loss: 0.0000e+00 L2 loss: 2.03386 Learning rate: 0.02 Mask loss: 0.37973 RPN box loss: 0.02697 RPN score loss: 0.00986 RPN total loss: 0.03684 Total loss: 2.83421 timestamp: 1654917809.384342 iteration: 3100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12748 FastRCNN class loss: 0.10245 FastRCNN total loss: 0.22994 L1 loss: 0.0000e+00 L2 loss: 2.03349 Learning rate: 0.02 Mask loss: 0.24443 RPN box loss: 0.09642 RPN score loss: 0.03068 RPN total loss: 0.1271 Total loss: 2.63495 timestamp: 1654917812.606355 iteration: 3105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2335 FastRCNN class loss: 0.13075 FastRCNN total loss: 0.36424 L1 loss: 0.0000e+00 L2 loss: 2.03311 Learning rate: 0.02 Mask loss: 0.21044 RPN box loss: 0.10942 RPN score loss: 0.01978 RPN total loss: 0.1292 Total loss: 2.73699 timestamp: 1654917815.7466557 iteration: 3110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2586 FastRCNN class loss: 0.16046 FastRCNN total loss: 0.41906 L1 loss: 0.0000e+00 L2 loss: 2.03273 Learning rate: 0.02 Mask loss: 0.30523 RPN box loss: 0.04317 RPN score loss: 0.01417 RPN total loss: 0.05734 Total loss: 2.81436 timestamp: 1654917819.0782824 iteration: 3115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11962 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.18609 L1 loss: 0.0000e+00 L2 loss: 2.03234 Learning rate: 0.02 Mask loss: 0.15736 RPN box loss: 0.05832 RPN score loss: 0.0104 RPN total loss: 0.06873 Total loss: 2.44452 timestamp: 1654917822.2607052 iteration: 3120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2539 FastRCNN class loss: 0.12799 FastRCNN total loss: 0.38189 L1 loss: 0.0000e+00 L2 loss: 2.03194 Learning rate: 0.02 Mask loss: 0.2294 RPN box loss: 0.04334 RPN score loss: 0.01498 RPN total loss: 0.05832 Total loss: 2.70156 timestamp: 1654917825.5258029 iteration: 3125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15712 FastRCNN class loss: 0.09966 FastRCNN total loss: 0.25678 L1 loss: 0.0000e+00 L2 loss: 2.03156 Learning rate: 0.02 Mask loss: 0.14696 RPN box loss: 0.04289 RPN score loss: 0.01186 RPN total loss: 0.05474 Total loss: 2.49004 timestamp: 1654917828.707559 iteration: 3130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10927 FastRCNN class loss: 0.05973 FastRCNN total loss: 0.169 L1 loss: 0.0000e+00 L2 loss: 2.03117 Learning rate: 0.02 Mask loss: 0.14156 RPN box loss: 0.03636 RPN score loss: 0.00345 RPN total loss: 0.03981 Total loss: 2.38153 timestamp: 1654917832.0661893 iteration: 3135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12994 FastRCNN class loss: 0.06813 FastRCNN total loss: 0.19807 L1 loss: 0.0000e+00 L2 loss: 2.03079 Learning rate: 0.02 Mask loss: 0.24081 RPN box loss: 0.10739 RPN score loss: 0.01483 RPN total loss: 0.12222 Total loss: 2.5919 timestamp: 1654917835.1998334 iteration: 3140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17953 FastRCNN class loss: 0.10564 FastRCNN total loss: 0.28517 L1 loss: 0.0000e+00 L2 loss: 2.03041 Learning rate: 0.02 Mask loss: 0.29184 RPN box loss: 0.05827 RPN score loss: 0.02168 RPN total loss: 0.07995 Total loss: 2.68737 timestamp: 1654917838.576555 iteration: 3145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28995 FastRCNN class loss: 0.13668 FastRCNN total loss: 0.42664 L1 loss: 0.0000e+00 L2 loss: 2.03001 Learning rate: 0.02 Mask loss: 0.31767 RPN box loss: 0.06734 RPN score loss: 0.01449 RPN total loss: 0.08183 Total loss: 2.85615 timestamp: 1654917841.851327 iteration: 3150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19928 FastRCNN class loss: 0.11674 FastRCNN total loss: 0.31602 L1 loss: 0.0000e+00 L2 loss: 2.02962 Learning rate: 0.02 Mask loss: 0.26589 RPN box loss: 0.09313 RPN score loss: 0.00882 RPN total loss: 0.10195 Total loss: 2.71348 timestamp: 1654917845.0451956 iteration: 3155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22981 FastRCNN class loss: 0.12052 FastRCNN total loss: 0.35033 L1 loss: 0.0000e+00 L2 loss: 2.02925 Learning rate: 0.02 Mask loss: 0.24938 RPN box loss: 0.06 RPN score loss: 0.011 RPN total loss: 0.071 Total loss: 2.69997 timestamp: 1654917848.3212516 iteration: 3160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18516 FastRCNN class loss: 0.1227 FastRCNN total loss: 0.30785 L1 loss: 0.0000e+00 L2 loss: 2.02889 Learning rate: 0.02 Mask loss: 0.21906 RPN box loss: 0.07848 RPN score loss: 0.03497 RPN total loss: 0.11345 Total loss: 2.66925 timestamp: 1654917851.5872447 iteration: 3165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19272 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.26671 L1 loss: 0.0000e+00 L2 loss: 2.0285 Learning rate: 0.02 Mask loss: 0.18253 RPN box loss: 0.0975 RPN score loss: 0.01609 RPN total loss: 0.11359 Total loss: 2.59134 timestamp: 1654917854.9217443 iteration: 3170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17502 FastRCNN class loss: 0.10983 FastRCNN total loss: 0.28486 L1 loss: 0.0000e+00 L2 loss: 2.02812 Learning rate: 0.02 Mask loss: 0.17013 RPN box loss: 0.10599 RPN score loss: 0.03306 RPN total loss: 0.13905 Total loss: 2.62215 timestamp: 1654917858.172638 iteration: 3175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20022 FastRCNN class loss: 0.12046 FastRCNN total loss: 0.32067 L1 loss: 0.0000e+00 L2 loss: 2.02773 Learning rate: 0.02 Mask loss: 0.20059 RPN box loss: 0.06725 RPN score loss: 0.0179 RPN total loss: 0.08515 Total loss: 2.63414 timestamp: 1654917861.4970095 iteration: 3180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29544 FastRCNN class loss: 0.19767 FastRCNN total loss: 0.49311 L1 loss: 0.0000e+00 L2 loss: 2.02735 Learning rate: 0.02 Mask loss: 0.28444 RPN box loss: 0.05513 RPN score loss: 0.01987 RPN total loss: 0.075 Total loss: 2.8799 timestamp: 1654917864.7735658 iteration: 3185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18654 FastRCNN class loss: 0.14917 FastRCNN total loss: 0.33571 L1 loss: 0.0000e+00 L2 loss: 2.02697 Learning rate: 0.02 Mask loss: 0.21082 RPN box loss: 0.06914 RPN score loss: 0.01827 RPN total loss: 0.08741 Total loss: 2.6609 timestamp: 1654917868.122727 iteration: 3190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2716 FastRCNN class loss: 0.18534 FastRCNN total loss: 0.45694 L1 loss: 0.0000e+00 L2 loss: 2.0266 Learning rate: 0.02 Mask loss: 0.263 RPN box loss: 0.10043 RPN score loss: 0.04926 RPN total loss: 0.1497 Total loss: 2.89625 timestamp: 1654917871.4204035 iteration: 3195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20841 FastRCNN class loss: 0.11724 FastRCNN total loss: 0.32566 L1 loss: 0.0000e+00 L2 loss: 2.02623 Learning rate: 0.02 Mask loss: 0.24547 RPN box loss: 0.01729 RPN score loss: 0.00793 RPN total loss: 0.02522 Total loss: 2.62257 timestamp: 1654917874.6246002 iteration: 3200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20451 FastRCNN class loss: 0.10364 FastRCNN total loss: 0.30815 L1 loss: 0.0000e+00 L2 loss: 2.02585 Learning rate: 0.02 Mask loss: 0.25781 RPN box loss: 0.08992 RPN score loss: 0.01554 RPN total loss: 0.10546 Total loss: 2.69726 timestamp: 1654917877.779242 iteration: 3205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24951 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.34297 L1 loss: 0.0000e+00 L2 loss: 2.02548 Learning rate: 0.02 Mask loss: 0.30645 RPN box loss: 0.02781 RPN score loss: 0.00863 RPN total loss: 0.03644 Total loss: 2.71135 timestamp: 1654917880.9874463 iteration: 3210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1414 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.22995 L1 loss: 0.0000e+00 L2 loss: 2.0251 Learning rate: 0.02 Mask loss: 0.16255 RPN box loss: 0.02041 RPN score loss: 0.00379 RPN total loss: 0.02419 Total loss: 2.4418 timestamp: 1654917884.2890053 iteration: 3215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23816 FastRCNN class loss: 0.16814 FastRCNN total loss: 0.4063 L1 loss: 0.0000e+00 L2 loss: 2.02473 Learning rate: 0.02 Mask loss: 0.22815 RPN box loss: 0.03231 RPN score loss: 0.00778 RPN total loss: 0.04009 Total loss: 2.69927 timestamp: 1654917887.5277166 iteration: 3220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25889 FastRCNN class loss: 0.09967 FastRCNN total loss: 0.35857 L1 loss: 0.0000e+00 L2 loss: 2.02433 Learning rate: 0.02 Mask loss: 0.31041 RPN box loss: 0.07367 RPN score loss: 0.01632 RPN total loss: 0.08999 Total loss: 2.7833 timestamp: 1654917890.8770194 iteration: 3225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13622 FastRCNN class loss: 0.06756 FastRCNN total loss: 0.20378 L1 loss: 0.0000e+00 L2 loss: 2.02396 Learning rate: 0.02 Mask loss: 0.18657 RPN box loss: 0.04297 RPN score loss: 0.00496 RPN total loss: 0.04793 Total loss: 2.46224 timestamp: 1654917894.1693296 iteration: 3230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21598 FastRCNN class loss: 0.10634 FastRCNN total loss: 0.32232 L1 loss: 0.0000e+00 L2 loss: 2.02361 Learning rate: 0.02 Mask loss: 0.17978 RPN box loss: 0.03508 RPN score loss: 0.0096 RPN total loss: 0.04469 Total loss: 2.5704 timestamp: 1654917897.4679964 iteration: 3235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24318 FastRCNN class loss: 0.14599 FastRCNN total loss: 0.38917 L1 loss: 0.0000e+00 L2 loss: 2.02322 Learning rate: 0.02 Mask loss: 0.45636 RPN box loss: 0.05736 RPN score loss: 0.01004 RPN total loss: 0.0674 Total loss: 2.93615 timestamp: 1654917900.6568325 iteration: 3240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22791 FastRCNN class loss: 0.12921 FastRCNN total loss: 0.35712 L1 loss: 0.0000e+00 L2 loss: 2.02283 Learning rate: 0.02 Mask loss: 0.30824 RPN box loss: 0.07964 RPN score loss: 0.01292 RPN total loss: 0.09256 Total loss: 2.78075 timestamp: 1654917903.9290442 iteration: 3245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24781 FastRCNN class loss: 0.14523 FastRCNN total loss: 0.39305 L1 loss: 0.0000e+00 L2 loss: 2.02243 Learning rate: 0.02 Mask loss: 0.23992 RPN box loss: 0.05521 RPN score loss: 0.02165 RPN total loss: 0.07687 Total loss: 2.73226 timestamp: 1654917907.1646898 iteration: 3250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19861 FastRCNN class loss: 0.10444 FastRCNN total loss: 0.30305 L1 loss: 0.0000e+00 L2 loss: 2.02204 Learning rate: 0.02 Mask loss: 0.19517 RPN box loss: 0.04328 RPN score loss: 0.00927 RPN total loss: 0.05255 Total loss: 2.57282 timestamp: 1654917910.4619143 iteration: 3255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26135 FastRCNN class loss: 0.1117 FastRCNN total loss: 0.37305 L1 loss: 0.0000e+00 L2 loss: 2.02165 Learning rate: 0.02 Mask loss: 0.28436 RPN box loss: 0.04529 RPN score loss: 0.01323 RPN total loss: 0.05852 Total loss: 2.73758 timestamp: 1654917913.7767758 iteration: 3260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.10817 FastRCNN total loss: 0.24812 L1 loss: 0.0000e+00 L2 loss: 2.02127 Learning rate: 0.02 Mask loss: 0.13557 RPN box loss: 0.05495 RPN score loss: 0.0107 RPN total loss: 0.06565 Total loss: 2.47061 timestamp: 1654917917.037775 iteration: 3265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17872 FastRCNN class loss: 0.10128 FastRCNN total loss: 0.28 L1 loss: 0.0000e+00 L2 loss: 2.02086 Learning rate: 0.02 Mask loss: 0.16809 RPN box loss: 0.04194 RPN score loss: 0.00809 RPN total loss: 0.05003 Total loss: 2.51898 timestamp: 1654917920.3427532 iteration: 3270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1465 FastRCNN class loss: 0.08682 FastRCNN total loss: 0.23331 L1 loss: 0.0000e+00 L2 loss: 2.02048 Learning rate: 0.02 Mask loss: 0.22359 RPN box loss: 0.02784 RPN score loss: 0.01564 RPN total loss: 0.04349 Total loss: 2.52087 timestamp: 1654917923.5317495 iteration: 3275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24298 FastRCNN class loss: 0.1197 FastRCNN total loss: 0.36268 L1 loss: 0.0000e+00 L2 loss: 2.02011 Learning rate: 0.02 Mask loss: 0.30023 RPN box loss: 0.05001 RPN score loss: 0.01824 RPN total loss: 0.06825 Total loss: 2.75127 timestamp: 1654917926.7802918 iteration: 3280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16497 FastRCNN class loss: 0.0858 FastRCNN total loss: 0.25077 L1 loss: 0.0000e+00 L2 loss: 2.01973 Learning rate: 0.02 Mask loss: 0.15584 RPN box loss: 0.04041 RPN score loss: 0.00598 RPN total loss: 0.04639 Total loss: 2.47273 timestamp: 1654917929.9775276 iteration: 3285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15735 FastRCNN class loss: 0.09584 FastRCNN total loss: 0.25319 L1 loss: 0.0000e+00 L2 loss: 2.01935 Learning rate: 0.02 Mask loss: 0.20442 RPN box loss: 0.07595 RPN score loss: 0.02248 RPN total loss: 0.09844 Total loss: 2.5754 timestamp: 1654917933.3292842 iteration: 3290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14123 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.23656 L1 loss: 0.0000e+00 L2 loss: 2.01896 Learning rate: 0.02 Mask loss: 0.18881 RPN box loss: 0.06862 RPN score loss: 0.01804 RPN total loss: 0.08666 Total loss: 2.53099 timestamp: 1654917936.4874814 iteration: 3295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20646 FastRCNN class loss: 0.10734 FastRCNN total loss: 0.31381 L1 loss: 0.0000e+00 L2 loss: 2.0186 Learning rate: 0.02 Mask loss: 0.17222 RPN box loss: 0.06424 RPN score loss: 0.00501 RPN total loss: 0.06924 Total loss: 2.57387 timestamp: 1654917939.711716 iteration: 3300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21156 FastRCNN class loss: 0.13069 FastRCNN total loss: 0.34225 L1 loss: 0.0000e+00 L2 loss: 2.01823 Learning rate: 0.02 Mask loss: 0.20687 RPN box loss: 0.0448 RPN score loss: 0.00929 RPN total loss: 0.05409 Total loss: 2.62144 timestamp: 1654917942.902561 iteration: 3305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22476 FastRCNN class loss: 0.14039 FastRCNN total loss: 0.36514 L1 loss: 0.0000e+00 L2 loss: 2.01787 Learning rate: 0.02 Mask loss: 0.23875 RPN box loss: 0.02767 RPN score loss: 0.01406 RPN total loss: 0.04173 Total loss: 2.66349 timestamp: 1654917946.138141 iteration: 3310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23201 FastRCNN class loss: 0.12296 FastRCNN total loss: 0.35497 L1 loss: 0.0000e+00 L2 loss: 2.01751 Learning rate: 0.02 Mask loss: 0.38844 RPN box loss: 0.05489 RPN score loss: 0.02366 RPN total loss: 0.07855 Total loss: 2.83946 timestamp: 1654917949.462495 iteration: 3315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20577 FastRCNN class loss: 0.11547 FastRCNN total loss: 0.32124 L1 loss: 0.0000e+00 L2 loss: 2.01712 Learning rate: 0.02 Mask loss: 0.26461 RPN box loss: 0.04762 RPN score loss: 0.01199 RPN total loss: 0.05961 Total loss: 2.66258 timestamp: 1654917952.6488068 iteration: 3320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23956 FastRCNN class loss: 0.12873 FastRCNN total loss: 0.36829 L1 loss: 0.0000e+00 L2 loss: 2.01675 Learning rate: 0.02 Mask loss: 0.24351 RPN box loss: 0.00479 RPN score loss: 0.01889 RPN total loss: 0.02368 Total loss: 2.65223 timestamp: 1654917955.921546 iteration: 3325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28609 FastRCNN class loss: 0.15122 FastRCNN total loss: 0.43731 L1 loss: 0.0000e+00 L2 loss: 2.01638 Learning rate: 0.02 Mask loss: 0.24396 RPN box loss: 0.00896 RPN score loss: 0.00511 RPN total loss: 0.01407 Total loss: 2.71172 timestamp: 1654917959.126641 iteration: 3330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26032 FastRCNN class loss: 0.1348 FastRCNN total loss: 0.39512 L1 loss: 0.0000e+00 L2 loss: 2.01601 Learning rate: 0.02 Mask loss: 0.22641 RPN box loss: 0.03516 RPN score loss: 0.00927 RPN total loss: 0.04442 Total loss: 2.68196 timestamp: 1654917962.424417 iteration: 3335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18602 FastRCNN class loss: 0.09679 FastRCNN total loss: 0.28281 L1 loss: 0.0000e+00 L2 loss: 2.01563 Learning rate: 0.02 Mask loss: 0.19403 RPN box loss: 0.04944 RPN score loss: 0.01683 RPN total loss: 0.06627 Total loss: 2.55875 timestamp: 1654917965.6781683 iteration: 3340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16234 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.24206 L1 loss: 0.0000e+00 L2 loss: 2.01523 Learning rate: 0.02 Mask loss: 0.1676 RPN box loss: 0.01701 RPN score loss: 0.01023 RPN total loss: 0.02724 Total loss: 2.45213 timestamp: 1654917968.9558308 iteration: 3345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24157 FastRCNN class loss: 0.09753 FastRCNN total loss: 0.3391 L1 loss: 0.0000e+00 L2 loss: 2.01487 Learning rate: 0.02 Mask loss: 0.21709 RPN box loss: 0.01849 RPN score loss: 0.00903 RPN total loss: 0.02752 Total loss: 2.59858 timestamp: 1654917972.1668 iteration: 3350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27704 FastRCNN class loss: 0.16853 FastRCNN total loss: 0.44557 L1 loss: 0.0000e+00 L2 loss: 2.01447 Learning rate: 0.02 Mask loss: 0.23739 RPN box loss: 0.05034 RPN score loss: 0.01797 RPN total loss: 0.06831 Total loss: 2.76575 timestamp: 1654917975.469602 iteration: 3355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2127 FastRCNN class loss: 0.10502 FastRCNN total loss: 0.31772 L1 loss: 0.0000e+00 L2 loss: 2.01411 Learning rate: 0.02 Mask loss: 0.32023 RPN box loss: 0.07926 RPN score loss: 0.01515 RPN total loss: 0.09441 Total loss: 2.74645 timestamp: 1654917978.6999848 iteration: 3360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25318 FastRCNN class loss: 0.12246 FastRCNN total loss: 0.37564 L1 loss: 0.0000e+00 L2 loss: 2.01372 Learning rate: 0.02 Mask loss: 0.19805 RPN box loss: 0.11771 RPN score loss: 0.01527 RPN total loss: 0.13298 Total loss: 2.72039 timestamp: 1654917981.9929812 iteration: 3365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21939 FastRCNN class loss: 0.13874 FastRCNN total loss: 0.35813 L1 loss: 0.0000e+00 L2 loss: 2.01334 Learning rate: 0.02 Mask loss: 0.24429 RPN box loss: 0.05213 RPN score loss: 0.01996 RPN total loss: 0.07208 Total loss: 2.68784 timestamp: 1654917985.339721 iteration: 3370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30315 FastRCNN class loss: 0.15047 FastRCNN total loss: 0.45362 L1 loss: 0.0000e+00 L2 loss: 2.01298 Learning rate: 0.02 Mask loss: 0.33028 RPN box loss: 0.07222 RPN score loss: 0.01393 RPN total loss: 0.08615 Total loss: 2.88303 timestamp: 1654917988.564223 iteration: 3375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14737 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.23714 L1 loss: 0.0000e+00 L2 loss: 2.01263 Learning rate: 0.02 Mask loss: 0.14652 RPN box loss: 0.01558 RPN score loss: 0.00609 RPN total loss: 0.02167 Total loss: 2.41796 timestamp: 1654917991.9124792 iteration: 3380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1502 FastRCNN class loss: 0.09356 FastRCNN total loss: 0.24376 L1 loss: 0.0000e+00 L2 loss: 2.01225 Learning rate: 0.02 Mask loss: 0.21333 RPN box loss: 0.01007 RPN score loss: 0.00662 RPN total loss: 0.0167 Total loss: 2.48604 timestamp: 1654917995.1098886 iteration: 3385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15028 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.23648 L1 loss: 0.0000e+00 L2 loss: 2.01187 Learning rate: 0.02 Mask loss: 0.16984 RPN box loss: 0.04298 RPN score loss: 0.01393 RPN total loss: 0.0569 Total loss: 2.47509 timestamp: 1654917998.4858453 iteration: 3390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2624 FastRCNN class loss: 0.14094 FastRCNN total loss: 0.40333 L1 loss: 0.0000e+00 L2 loss: 2.0115 Learning rate: 0.02 Mask loss: 0.29397 RPN box loss: 0.09959 RPN score loss: 0.01235 RPN total loss: 0.11194 Total loss: 2.82075 timestamp: 1654918001.7753334 iteration: 3395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26051 FastRCNN class loss: 0.12203 FastRCNN total loss: 0.38253 L1 loss: 0.0000e+00 L2 loss: 2.01116 Learning rate: 0.02 Mask loss: 0.34463 RPN box loss: 0.0412 RPN score loss: 0.00857 RPN total loss: 0.04977 Total loss: 2.7881 timestamp: 1654918005.100982 iteration: 3400 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1955 FastRCNN class loss: 0.11351 FastRCNN total loss: 0.30901 L1 loss: 0.0000e+00 L2 loss: 2.0108 Learning rate: 0.02 Mask loss: 0.22698 RPN box loss: 0.02119 RPN score loss: 0.00449 RPN total loss: 0.02568 Total loss: 2.57248 timestamp: 1654918008.3755522 iteration: 3405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16629 FastRCNN class loss: 0.09491 FastRCNN total loss: 0.2612 L1 loss: 0.0000e+00 L2 loss: 2.01043 Learning rate: 0.02 Mask loss: 0.20332 RPN box loss: 0.10561 RPN score loss: 0.01549 RPN total loss: 0.1211 Total loss: 2.59605 timestamp: 1654918011.5675106 iteration: 3410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17004 FastRCNN class loss: 0.06794 FastRCNN total loss: 0.23798 L1 loss: 0.0000e+00 L2 loss: 2.01005 Learning rate: 0.02 Mask loss: 0.23166 RPN box loss: 0.09739 RPN score loss: 0.0079 RPN total loss: 0.10529 Total loss: 2.58498 timestamp: 1654918014.8306336 iteration: 3415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16844 FastRCNN class loss: 0.09681 FastRCNN total loss: 0.26525 L1 loss: 0.0000e+00 L2 loss: 2.00967 Learning rate: 0.02 Mask loss: 0.23297 RPN box loss: 0.03924 RPN score loss: 0.02701 RPN total loss: 0.06625 Total loss: 2.57414 timestamp: 1654918018.0913613 iteration: 3420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17469 FastRCNN class loss: 0.097 FastRCNN total loss: 0.27168 L1 loss: 0.0000e+00 L2 loss: 2.00928 Learning rate: 0.02 Mask loss: 0.27088 RPN box loss: 0.05487 RPN score loss: 0.00781 RPN total loss: 0.06268 Total loss: 2.61452 timestamp: 1654918021.3143911 iteration: 3425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28002 FastRCNN class loss: 0.12155 FastRCNN total loss: 0.40157 L1 loss: 0.0000e+00 L2 loss: 2.00891 Learning rate: 0.02 Mask loss: 0.27871 RPN box loss: 0.05914 RPN score loss: 0.01599 RPN total loss: 0.07513 Total loss: 2.76432 timestamp: 1654918024.5999355 iteration: 3430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15119 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.21477 L1 loss: 0.0000e+00 L2 loss: 2.00854 Learning rate: 0.02 Mask loss: 0.13603 RPN box loss: 0.07531 RPN score loss: 0.01355 RPN total loss: 0.08886 Total loss: 2.4482 timestamp: 1654918027.9239907 iteration: 3435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18455 FastRCNN class loss: 0.1143 FastRCNN total loss: 0.29885 L1 loss: 0.0000e+00 L2 loss: 2.00816 Learning rate: 0.02 Mask loss: 0.27438 RPN box loss: 0.06366 RPN score loss: 0.0171 RPN total loss: 0.08076 Total loss: 2.66215 timestamp: 1654918031.171596 iteration: 3440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17531 FastRCNN class loss: 0.13934 FastRCNN total loss: 0.31464 L1 loss: 0.0000e+00 L2 loss: 2.00778 Learning rate: 0.02 Mask loss: 0.25615 RPN box loss: 0.03017 RPN score loss: 0.00626 RPN total loss: 0.03643 Total loss: 2.61501 timestamp: 1654918034.506351 iteration: 3445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22497 FastRCNN class loss: 0.13657 FastRCNN total loss: 0.36154 L1 loss: 0.0000e+00 L2 loss: 2.0074 Learning rate: 0.02 Mask loss: 0.27166 RPN box loss: 0.0133 RPN score loss: 0.0111 RPN total loss: 0.02441 Total loss: 2.66501 timestamp: 1654918037.8532841 iteration: 3450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20275 FastRCNN class loss: 0.10932 FastRCNN total loss: 0.31207 L1 loss: 0.0000e+00 L2 loss: 2.00704 Learning rate: 0.02 Mask loss: 0.22893 RPN box loss: 0.01618 RPN score loss: 0.01164 RPN total loss: 0.02781 Total loss: 2.57585 timestamp: 1654918041.0090828 iteration: 3455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19088 FastRCNN class loss: 0.09222 FastRCNN total loss: 0.28311 L1 loss: 0.0000e+00 L2 loss: 2.00669 Learning rate: 0.02 Mask loss: 0.11742 RPN box loss: 0.02865 RPN score loss: 0.00717 RPN total loss: 0.03582 Total loss: 2.44304 timestamp: 1654918044.3431506 iteration: 3460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18312 FastRCNN class loss: 0.10861 FastRCNN total loss: 0.29173 L1 loss: 0.0000e+00 L2 loss: 2.00631 Learning rate: 0.02 Mask loss: 0.24201 RPN box loss: 0.08641 RPN score loss: 0.01044 RPN total loss: 0.09685 Total loss: 2.63689 timestamp: 1654918047.596269 iteration: 3465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30563 FastRCNN class loss: 0.15162 FastRCNN total loss: 0.45725 L1 loss: 0.0000e+00 L2 loss: 2.00594 Learning rate: 0.02 Mask loss: 0.26755 RPN box loss: 0.04927 RPN score loss: 0.01756 RPN total loss: 0.06683 Total loss: 2.79758 timestamp: 1654918050.9224894 iteration: 3470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18697 FastRCNN class loss: 0.10864 FastRCNN total loss: 0.2956 L1 loss: 0.0000e+00 L2 loss: 2.00557 Learning rate: 0.02 Mask loss: 0.23232 RPN box loss: 0.02702 RPN score loss: 0.0081 RPN total loss: 0.03512 Total loss: 2.56862 timestamp: 1654918054.1649005 iteration: 3475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18465 FastRCNN class loss: 0.13666 FastRCNN total loss: 0.3213 L1 loss: 0.0000e+00 L2 loss: 2.00518 Learning rate: 0.02 Mask loss: 0.23819 RPN box loss: 0.08807 RPN score loss: 0.01249 RPN total loss: 0.10056 Total loss: 2.66524 timestamp: 1654918057.4926388 iteration: 3480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28178 FastRCNN class loss: 0.11738 FastRCNN total loss: 0.39916 L1 loss: 0.0000e+00 L2 loss: 2.00478 Learning rate: 0.02 Mask loss: 0.19423 RPN box loss: 0.09537 RPN score loss: 0.01334 RPN total loss: 0.10872 Total loss: 2.70689 timestamp: 1654918060.6905003 iteration: 3485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22975 FastRCNN class loss: 0.10688 FastRCNN total loss: 0.33663 L1 loss: 0.0000e+00 L2 loss: 2.00441 Learning rate: 0.02 Mask loss: 0.21329 RPN box loss: 0.02049 RPN score loss: 0.0149 RPN total loss: 0.03539 Total loss: 2.58972 timestamp: 1654918063.9949145 iteration: 3490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19863 FastRCNN class loss: 0.12326 FastRCNN total loss: 0.32188 L1 loss: 0.0000e+00 L2 loss: 2.00402 Learning rate: 0.02 Mask loss: 0.2387 RPN box loss: 0.0131 RPN score loss: 0.00952 RPN total loss: 0.02261 Total loss: 2.58722 timestamp: 1654918067.3944163 iteration: 3495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15311 FastRCNN class loss: 0.09257 FastRCNN total loss: 0.24567 L1 loss: 0.0000e+00 L2 loss: 2.00364 Learning rate: 0.02 Mask loss: 0.17137 RPN box loss: 0.03167 RPN score loss: 0.00979 RPN total loss: 0.04146 Total loss: 2.46215 timestamp: 1654918070.6525145 iteration: 3500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21064 FastRCNN class loss: 0.11191 FastRCNN total loss: 0.32255 L1 loss: 0.0000e+00 L2 loss: 2.00327 Learning rate: 0.02 Mask loss: 0.20243 RPN box loss: 0.03152 RPN score loss: 0.01784 RPN total loss: 0.04936 Total loss: 2.57762 timestamp: 1654918073.8885572 iteration: 3505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16102 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.24989 L1 loss: 0.0000e+00 L2 loss: 2.0029 Learning rate: 0.02 Mask loss: 0.1616 RPN box loss: 0.03317 RPN score loss: 0.00726 RPN total loss: 0.04044 Total loss: 2.45483 timestamp: 1654918077.077105 iteration: 3510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20485 FastRCNN class loss: 0.13249 FastRCNN total loss: 0.33735 L1 loss: 0.0000e+00 L2 loss: 2.00252 Learning rate: 0.02 Mask loss: 0.21696 RPN box loss: 0.09036 RPN score loss: 0.01527 RPN total loss: 0.10563 Total loss: 2.66246 timestamp: 1654918080.3269713 iteration: 3515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27962 FastRCNN class loss: 0.13968 FastRCNN total loss: 0.41931 L1 loss: 0.0000e+00 L2 loss: 2.00217 Learning rate: 0.02 Mask loss: 0.32133 RPN box loss: 0.02256 RPN score loss: 0.01166 RPN total loss: 0.03422 Total loss: 2.77703 timestamp: 1654918083.5449219 iteration: 3520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15788 FastRCNN class loss: 0.08181 FastRCNN total loss: 0.23969 L1 loss: 0.0000e+00 L2 loss: 2.00178 Learning rate: 0.02 Mask loss: 0.22104 RPN box loss: 0.02923 RPN score loss: 0.00722 RPN total loss: 0.03645 Total loss: 2.49895 timestamp: 1654918086.8556597 iteration: 3525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17282 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.24447 L1 loss: 0.0000e+00 L2 loss: 2.00141 Learning rate: 0.02 Mask loss: 0.14564 RPN box loss: 0.0517 RPN score loss: 0.00631 RPN total loss: 0.05801 Total loss: 2.44954 timestamp: 1654918090.0793123 iteration: 3530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24304 FastRCNN class loss: 0.09373 FastRCNN total loss: 0.33677 L1 loss: 0.0000e+00 L2 loss: 2.00103 Learning rate: 0.02 Mask loss: 0.22539 RPN box loss: 0.05029 RPN score loss: 0.0086 RPN total loss: 0.05889 Total loss: 2.62208 timestamp: 1654918093.441322 iteration: 3535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17431 FastRCNN class loss: 0.15439 FastRCNN total loss: 0.3287 L1 loss: 0.0000e+00 L2 loss: 2.00066 Learning rate: 0.02 Mask loss: 0.16285 RPN box loss: 0.06465 RPN score loss: 0.03099 RPN total loss: 0.09564 Total loss: 2.58786 timestamp: 1654918096.6241188 iteration: 3540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23198 FastRCNN class loss: 0.12154 FastRCNN total loss: 0.35352 L1 loss: 0.0000e+00 L2 loss: 2.00028 Learning rate: 0.02 Mask loss: 0.28563 RPN box loss: 0.04028 RPN score loss: 0.00657 RPN total loss: 0.04685 Total loss: 2.68629 timestamp: 1654918099.794099 iteration: 3545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16776 FastRCNN class loss: 0.08313 FastRCNN total loss: 0.25089 L1 loss: 0.0000e+00 L2 loss: 1.99989 Learning rate: 0.02 Mask loss: 0.19042 RPN box loss: 0.02522 RPN score loss: 0.00643 RPN total loss: 0.03165 Total loss: 2.47285 timestamp: 1654918103.1161342 iteration: 3550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1969 FastRCNN class loss: 0.09328 FastRCNN total loss: 0.29018 L1 loss: 0.0000e+00 L2 loss: 1.99953 Learning rate: 0.02 Mask loss: 0.21608 RPN box loss: 0.03402 RPN score loss: 0.00966 RPN total loss: 0.04368 Total loss: 2.54947 timestamp: 1654918106.3137844 iteration: 3555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15546 FastRCNN class loss: 0.07961 FastRCNN total loss: 0.23507 L1 loss: 0.0000e+00 L2 loss: 1.99918 Learning rate: 0.02 Mask loss: 0.25883 RPN box loss: 0.03298 RPN score loss: 0.00778 RPN total loss: 0.04076 Total loss: 2.53384 timestamp: 1654918109.6908755 iteration: 3560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18889 FastRCNN class loss: 0.09811 FastRCNN total loss: 0.287 L1 loss: 0.0000e+00 L2 loss: 1.99879 Learning rate: 0.02 Mask loss: 0.1535 RPN box loss: 0.02275 RPN score loss: 0.01014 RPN total loss: 0.0329 Total loss: 2.47218 timestamp: 1654918112.893885 iteration: 3565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23186 FastRCNN class loss: 0.10444 FastRCNN total loss: 0.3363 L1 loss: 0.0000e+00 L2 loss: 1.99839 Learning rate: 0.02 Mask loss: 0.16786 RPN box loss: 0.08247 RPN score loss: 0.01185 RPN total loss: 0.09432 Total loss: 2.59687 timestamp: 1654918116.256004 iteration: 3570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17078 FastRCNN class loss: 0.07596 FastRCNN total loss: 0.24674 L1 loss: 0.0000e+00 L2 loss: 1.99803 Learning rate: 0.02 Mask loss: 0.15023 RPN box loss: 0.06503 RPN score loss: 0.01269 RPN total loss: 0.07773 Total loss: 2.47273 timestamp: 1654918119.439559 iteration: 3575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13531 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.20723 L1 loss: 0.0000e+00 L2 loss: 1.99766 Learning rate: 0.02 Mask loss: 0.17424 RPN box loss: 0.02258 RPN score loss: 0.00524 RPN total loss: 0.02782 Total loss: 2.40694 timestamp: 1654918122.6553752 iteration: 3580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17146 FastRCNN class loss: 0.09647 FastRCNN total loss: 0.26793 L1 loss: 0.0000e+00 L2 loss: 1.99729 Learning rate: 0.02 Mask loss: 0.16972 RPN box loss: 0.06341 RPN score loss: 0.00798 RPN total loss: 0.07139 Total loss: 2.50632 timestamp: 1654918125.9163945 iteration: 3585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18974 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.26161 L1 loss: 0.0000e+00 L2 loss: 1.99692 Learning rate: 0.02 Mask loss: 0.12759 RPN box loss: 0.06499 RPN score loss: 0.0058 RPN total loss: 0.07079 Total loss: 2.45691 timestamp: 1654918129.2018297 iteration: 3590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16143 FastRCNN class loss: 0.07274 FastRCNN total loss: 0.23416 L1 loss: 0.0000e+00 L2 loss: 1.99653 Learning rate: 0.02 Mask loss: 0.23167 RPN box loss: 0.01465 RPN score loss: 0.00656 RPN total loss: 0.02121 Total loss: 2.48357 timestamp: 1654918132.4228916 iteration: 3595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26583 FastRCNN class loss: 0.19495 FastRCNN total loss: 0.46077 L1 loss: 0.0000e+00 L2 loss: 1.99612 Learning rate: 0.02 Mask loss: 0.38339 RPN box loss: 0.07046 RPN score loss: 0.01887 RPN total loss: 0.08933 Total loss: 2.92962 timestamp: 1654918135.7546144 iteration: 3600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19841 FastRCNN class loss: 0.08149 FastRCNN total loss: 0.2799 L1 loss: 0.0000e+00 L2 loss: 1.99574 Learning rate: 0.02 Mask loss: 0.18898 RPN box loss: 0.06468 RPN score loss: 0.02295 RPN total loss: 0.08764 Total loss: 2.55225 timestamp: 1654918139.0947824 iteration: 3605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12477 FastRCNN class loss: 0.07798 FastRCNN total loss: 0.20275 L1 loss: 0.0000e+00 L2 loss: 1.99536 Learning rate: 0.02 Mask loss: 0.09164 RPN box loss: 0.01424 RPN score loss: 0.00234 RPN total loss: 0.01657 Total loss: 2.30632 timestamp: 1654918142.3117657 iteration: 3610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17406 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.25188 L1 loss: 0.0000e+00 L2 loss: 1.99501 Learning rate: 0.02 Mask loss: 0.20238 RPN box loss: 0.02731 RPN score loss: 0.01177 RPN total loss: 0.03908 Total loss: 2.48834 timestamp: 1654918145.6185415 iteration: 3615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18909 FastRCNN class loss: 0.19294 FastRCNN total loss: 0.38203 L1 loss: 0.0000e+00 L2 loss: 1.99465 Learning rate: 0.02 Mask loss: 0.21817 RPN box loss: 0.03863 RPN score loss: 0.0065 RPN total loss: 0.04513 Total loss: 2.63998 timestamp: 1654918148.8211868 iteration: 3620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2276 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.30714 L1 loss: 0.0000e+00 L2 loss: 1.99428 Learning rate: 0.02 Mask loss: 0.20725 RPN box loss: 0.04045 RPN score loss: 0.0142 RPN total loss: 0.05465 Total loss: 2.56332 timestamp: 1654918152.2016754 iteration: 3625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16221 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.23559 L1 loss: 0.0000e+00 L2 loss: 1.99391 Learning rate: 0.02 Mask loss: 0.1889 RPN box loss: 0.07192 RPN score loss: 0.00713 RPN total loss: 0.07904 Total loss: 2.49744 timestamp: 1654918155.4675791 iteration: 3630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14871 FastRCNN class loss: 0.113 FastRCNN total loss: 0.26171 L1 loss: 0.0000e+00 L2 loss: 1.99352 Learning rate: 0.02 Mask loss: 0.20908 RPN box loss: 0.01748 RPN score loss: 0.00523 RPN total loss: 0.02271 Total loss: 2.48703 timestamp: 1654918158.773618 iteration: 3635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24718 FastRCNN class loss: 0.16023 FastRCNN total loss: 0.40741 L1 loss: 0.0000e+00 L2 loss: 1.99314 Learning rate: 0.02 Mask loss: 0.2734 RPN box loss: 0.17569 RPN score loss: 0.01706 RPN total loss: 0.19275 Total loss: 2.86671 timestamp: 1654918161.923119 iteration: 3640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17643 FastRCNN class loss: 0.09888 FastRCNN total loss: 0.2753 L1 loss: 0.0000e+00 L2 loss: 1.99277 Learning rate: 0.02 Mask loss: 0.1701 RPN box loss: 0.02851 RPN score loss: 0.00707 RPN total loss: 0.03559 Total loss: 2.47376 timestamp: 1654918165.3261824 iteration: 3645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19425 FastRCNN class loss: 0.10139 FastRCNN total loss: 0.29563 L1 loss: 0.0000e+00 L2 loss: 1.99239 Learning rate: 0.02 Mask loss: 0.21854 RPN box loss: 0.08322 RPN score loss: 0.02207 RPN total loss: 0.1053 Total loss: 2.61186 timestamp: 1654918168.5900729 iteration: 3650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1452 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.20776 L1 loss: 0.0000e+00 L2 loss: 1.99201 Learning rate: 0.02 Mask loss: 0.29324 RPN box loss: 0.04402 RPN score loss: 0.01059 RPN total loss: 0.05461 Total loss: 2.54762 timestamp: 1654918171.8333158 iteration: 3655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23811 FastRCNN class loss: 0.18271 FastRCNN total loss: 0.42082 L1 loss: 0.0000e+00 L2 loss: 1.99164 Learning rate: 0.02 Mask loss: 0.33381 RPN box loss: 0.04499 RPN score loss: 0.01953 RPN total loss: 0.06452 Total loss: 2.81079 timestamp: 1654918175.1937284 iteration: 3660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18539 FastRCNN class loss: 0.09833 FastRCNN total loss: 0.28372 L1 loss: 0.0000e+00 L2 loss: 1.99124 Learning rate: 0.02 Mask loss: 0.1694 RPN box loss: 0.09677 RPN score loss: 0.02358 RPN total loss: 0.12034 Total loss: 2.5647 timestamp: 1654918178.4101868 iteration: 3665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18513 FastRCNN class loss: 0.20432 FastRCNN total loss: 0.38944 L1 loss: 0.0000e+00 L2 loss: 1.99087 Learning rate: 0.02 Mask loss: 0.1864 RPN box loss: 0.06572 RPN score loss: 0.00927 RPN total loss: 0.07499 Total loss: 2.64171 timestamp: 1654918181.6317124 iteration: 3670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26305 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.3343 L1 loss: 0.0000e+00 L2 loss: 1.99051 Learning rate: 0.02 Mask loss: 0.16696 RPN box loss: 0.02454 RPN score loss: 0.00397 RPN total loss: 0.02851 Total loss: 2.52028 timestamp: 1654918184.840144 iteration: 3675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19612 FastRCNN class loss: 0.16723 FastRCNN total loss: 0.36335 L1 loss: 0.0000e+00 L2 loss: 1.99014 Learning rate: 0.02 Mask loss: 0.16053 RPN box loss: 0.04422 RPN score loss: 0.03045 RPN total loss: 0.07466 Total loss: 2.58869 timestamp: 1654918188.1557894 iteration: 3680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13133 FastRCNN class loss: 0.10827 FastRCNN total loss: 0.23961 L1 loss: 0.0000e+00 L2 loss: 1.98977 Learning rate: 0.02 Mask loss: 0.21362 RPN box loss: 0.03144 RPN score loss: 0.00418 RPN total loss: 0.03562 Total loss: 2.47862 timestamp: 1654918191.3668814 iteration: 3685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14541 FastRCNN class loss: 0.09015 FastRCNN total loss: 0.23557 L1 loss: 0.0000e+00 L2 loss: 1.98939 Learning rate: 0.02 Mask loss: 0.19077 RPN box loss: 0.03372 RPN score loss: 0.03798 RPN total loss: 0.0717 Total loss: 2.48743 timestamp: 1654918194.7239053 iteration: 3690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27239 FastRCNN class loss: 0.14959 FastRCNN total loss: 0.42198 L1 loss: 0.0000e+00 L2 loss: 1.98902 Learning rate: 0.02 Mask loss: 0.25352 RPN box loss: 0.02127 RPN score loss: 0.00425 RPN total loss: 0.02552 Total loss: 2.69005 timestamp: 1654918197.9272852 iteration: 3695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16366 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.23893 L1 loss: 0.0000e+00 L2 loss: 1.98864 Learning rate: 0.02 Mask loss: 0.16535 RPN box loss: 0.03122 RPN score loss: 0.01321 RPN total loss: 0.04443 Total loss: 2.43734 timestamp: 1654918201.154895 iteration: 3700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27128 FastRCNN class loss: 0.14143 FastRCNN total loss: 0.4127 L1 loss: 0.0000e+00 L2 loss: 1.98827 Learning rate: 0.02 Mask loss: 0.33289 RPN box loss: 0.10878 RPN score loss: 0.02705 RPN total loss: 0.13584 Total loss: 2.8697 timestamp: 1654918204.4802532 iteration: 3705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17255 FastRCNN class loss: 0.08072 FastRCNN total loss: 0.25327 L1 loss: 0.0000e+00 L2 loss: 1.98788 Learning rate: 0.02 Mask loss: 0.12466 RPN box loss: 0.02885 RPN score loss: 0.0046 RPN total loss: 0.03345 Total loss: 2.39927 timestamp: 1654918207.6598043 iteration: 3710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27319 FastRCNN class loss: 0.11194 FastRCNN total loss: 0.38513 L1 loss: 0.0000e+00 L2 loss: 1.98751 Learning rate: 0.02 Mask loss: 0.30049 RPN box loss: 0.02269 RPN score loss: 0.00855 RPN total loss: 0.03124 Total loss: 2.70438 timestamp: 1654918210.8470938 iteration: 3715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1549 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.23095 L1 loss: 0.0000e+00 L2 loss: 1.98716 Learning rate: 0.02 Mask loss: 0.16395 RPN box loss: 0.03314 RPN score loss: 0.01048 RPN total loss: 0.04362 Total loss: 2.42567 timestamp: 1654918214.0483444 iteration: 3720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16687 FastRCNN class loss: 0.09532 FastRCNN total loss: 0.26219 L1 loss: 0.0000e+00 L2 loss: 1.9868 Learning rate: 0.02 Mask loss: 0.1577 RPN box loss: 0.09318 RPN score loss: 0.00945 RPN total loss: 0.10264 Total loss: 2.50933 timestamp: 1654918217.378206 iteration: 3725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25759 FastRCNN class loss: 0.1157 FastRCNN total loss: 0.37329 L1 loss: 0.0000e+00 L2 loss: 1.98644 Learning rate: 0.02 Mask loss: 0.26839 RPN box loss: 0.04527 RPN score loss: 0.02362 RPN total loss: 0.06889 Total loss: 2.69701 timestamp: 1654918220.575468 iteration: 3730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22588 FastRCNN class loss: 0.1104 FastRCNN total loss: 0.33628 L1 loss: 0.0000e+00 L2 loss: 1.98606 Learning rate: 0.02 Mask loss: 0.31997 RPN box loss: 0.06177 RPN score loss: 0.00988 RPN total loss: 0.07165 Total loss: 2.71396 timestamp: 1654918223.9840903 iteration: 3735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19838 FastRCNN class loss: 0.14021 FastRCNN total loss: 0.33859 L1 loss: 0.0000e+00 L2 loss: 1.9857 Learning rate: 0.02 Mask loss: 0.21351 RPN box loss: 0.05188 RPN score loss: 0.00786 RPN total loss: 0.05974 Total loss: 2.59754 timestamp: 1654918227.1857939 iteration: 3740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21864 FastRCNN class loss: 0.09399 FastRCNN total loss: 0.31263 L1 loss: 0.0000e+00 L2 loss: 1.98532 Learning rate: 0.02 Mask loss: 0.16917 RPN box loss: 0.01508 RPN score loss: 0.0083 RPN total loss: 0.02337 Total loss: 2.49049 timestamp: 1654918230.523974 iteration: 3745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27842 FastRCNN class loss: 0.1114 FastRCNN total loss: 0.38982 L1 loss: 0.0000e+00 L2 loss: 1.98495 Learning rate: 0.02 Mask loss: 0.27909 RPN box loss: 0.04671 RPN score loss: 0.00807 RPN total loss: 0.05478 Total loss: 2.70864 timestamp: 1654918233.7778754 iteration: 3750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17726 FastRCNN class loss: 0.09183 FastRCNN total loss: 0.26909 L1 loss: 0.0000e+00 L2 loss: 1.98457 Learning rate: 0.02 Mask loss: 0.21454 RPN box loss: 0.06133 RPN score loss: 0.01273 RPN total loss: 0.07406 Total loss: 2.54225 timestamp: 1654918237.0427783 iteration: 3755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18059 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.23686 L1 loss: 0.0000e+00 L2 loss: 1.9842 Learning rate: 0.02 Mask loss: 0.18724 RPN box loss: 0.0236 RPN score loss: 0.00544 RPN total loss: 0.02904 Total loss: 2.43734 timestamp: 1654918240.4155438 iteration: 3760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1565 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.22952 L1 loss: 0.0000e+00 L2 loss: 1.98384 Learning rate: 0.02 Mask loss: 0.21595 RPN box loss: 0.04819 RPN score loss: 0.00922 RPN total loss: 0.05741 Total loss: 2.48672 timestamp: 1654918243.6369786 iteration: 3765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15754 FastRCNN class loss: 0.12357 FastRCNN total loss: 0.2811 L1 loss: 0.0000e+00 L2 loss: 1.98349 Learning rate: 0.02 Mask loss: 0.21992 RPN box loss: 0.05098 RPN score loss: 0.01059 RPN total loss: 0.06156 Total loss: 2.54607 timestamp: 1654918246.937752 iteration: 3770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22612 FastRCNN class loss: 0.09253 FastRCNN total loss: 0.31865 L1 loss: 0.0000e+00 L2 loss: 1.98311 Learning rate: 0.02 Mask loss: 0.26202 RPN box loss: 0.04236 RPN score loss: 0.01135 RPN total loss: 0.05371 Total loss: 2.61749 timestamp: 1654918250.2507086 iteration: 3775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15548 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.22252 L1 loss: 0.0000e+00 L2 loss: 1.98273 Learning rate: 0.02 Mask loss: 0.19322 RPN box loss: 0.04806 RPN score loss: 0.01435 RPN total loss: 0.06241 Total loss: 2.46089 timestamp: 1654918253.4912987 iteration: 3780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17177 FastRCNN class loss: 0.10022 FastRCNN total loss: 0.27198 L1 loss: 0.0000e+00 L2 loss: 1.98234 Learning rate: 0.02 Mask loss: 0.11908 RPN box loss: 0.03334 RPN score loss: 0.0095 RPN total loss: 0.04284 Total loss: 2.41624 timestamp: 1654918256.719961 iteration: 3785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26398 FastRCNN class loss: 0.09325 FastRCNN total loss: 0.35723 L1 loss: 0.0000e+00 L2 loss: 1.98196 Learning rate: 0.02 Mask loss: 0.25272 RPN box loss: 0.05584 RPN score loss: 0.01954 RPN total loss: 0.07538 Total loss: 2.6673 timestamp: 1654918260.1332638 iteration: 3790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25381 FastRCNN class loss: 0.10797 FastRCNN total loss: 0.36178 L1 loss: 0.0000e+00 L2 loss: 1.98159 Learning rate: 0.02 Mask loss: 0.25104 RPN box loss: 0.05837 RPN score loss: 0.02208 RPN total loss: 0.08044 Total loss: 2.67485 timestamp: 1654918263.327706 iteration: 3795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23219 FastRCNN class loss: 0.0853 FastRCNN total loss: 0.31749 L1 loss: 0.0000e+00 L2 loss: 1.98121 Learning rate: 0.02 Mask loss: 0.17196 RPN box loss: 0.04777 RPN score loss: 0.03695 RPN total loss: 0.08472 Total loss: 2.55538 timestamp: 1654918266.5230777 iteration: 3800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22406 FastRCNN class loss: 0.12659 FastRCNN total loss: 0.35065 L1 loss: 0.0000e+00 L2 loss: 1.98084 Learning rate: 0.02 Mask loss: 0.2138 RPN box loss: 0.03324 RPN score loss: 0.01015 RPN total loss: 0.04339 Total loss: 2.58869 timestamp: 1654918269.7445846 iteration: 3805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20288 FastRCNN class loss: 0.14941 FastRCNN total loss: 0.3523 L1 loss: 0.0000e+00 L2 loss: 1.98047 Learning rate: 0.02 Mask loss: 0.32407 RPN box loss: 0.07912 RPN score loss: 0.02236 RPN total loss: 0.10148 Total loss: 2.75831 timestamp: 1654918272.9712384 iteration: 3810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25059 FastRCNN class loss: 0.15538 FastRCNN total loss: 0.40598 L1 loss: 0.0000e+00 L2 loss: 1.98011 Learning rate: 0.02 Mask loss: 0.19381 RPN box loss: 0.06046 RPN score loss: 0.02208 RPN total loss: 0.08253 Total loss: 2.66244 timestamp: 1654918276.2546353 iteration: 3815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22828 FastRCNN class loss: 0.09536 FastRCNN total loss: 0.32365 L1 loss: 0.0000e+00 L2 loss: 1.97976 Learning rate: 0.02 Mask loss: 0.18983 RPN box loss: 0.04083 RPN score loss: 0.00586 RPN total loss: 0.04669 Total loss: 2.53992 timestamp: 1654918279.4720101 iteration: 3820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24048 FastRCNN class loss: 0.10676 FastRCNN total loss: 0.34724 L1 loss: 0.0000e+00 L2 loss: 1.97936 Learning rate: 0.02 Mask loss: 0.24114 RPN box loss: 0.05131 RPN score loss: 0.01207 RPN total loss: 0.06338 Total loss: 2.63113 timestamp: 1654918282.8861046 iteration: 3825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16582 FastRCNN class loss: 0.11114 FastRCNN total loss: 0.27696 L1 loss: 0.0000e+00 L2 loss: 1.97898 Learning rate: 0.02 Mask loss: 0.18884 RPN box loss: 0.12937 RPN score loss: 0.02202 RPN total loss: 0.15138 Total loss: 2.59615 timestamp: 1654918286.0935404 iteration: 3830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16293 FastRCNN class loss: 0.10106 FastRCNN total loss: 0.26399 L1 loss: 0.0000e+00 L2 loss: 1.9786 Learning rate: 0.02 Mask loss: 0.16044 RPN box loss: 0.04396 RPN score loss: 0.01187 RPN total loss: 0.05583 Total loss: 2.45886 timestamp: 1654918289.3683774 iteration: 3835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21146 FastRCNN class loss: 0.13487 FastRCNN total loss: 0.34633 L1 loss: 0.0000e+00 L2 loss: 1.97822 Learning rate: 0.02 Mask loss: 0.1899 RPN box loss: 0.01329 RPN score loss: 0.00657 RPN total loss: 0.01986 Total loss: 2.5343 timestamp: 1654918292.60075 iteration: 3840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12682 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.19672 L1 loss: 0.0000e+00 L2 loss: 1.97786 Learning rate: 0.02 Mask loss: 0.14184 RPN box loss: 0.02586 RPN score loss: 0.0087 RPN total loss: 0.03456 Total loss: 2.35098 timestamp: 1654918295.9342082 iteration: 3845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20252 FastRCNN class loss: 0.10862 FastRCNN total loss: 0.31114 L1 loss: 0.0000e+00 L2 loss: 1.97749 Learning rate: 0.02 Mask loss: 0.21027 RPN box loss: 0.03485 RPN score loss: 0.00729 RPN total loss: 0.04214 Total loss: 2.54105 timestamp: 1654918299.0929492 iteration: 3850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24217 FastRCNN class loss: 0.08086 FastRCNN total loss: 0.32303 L1 loss: 0.0000e+00 L2 loss: 1.97712 Learning rate: 0.02 Mask loss: 0.12299 RPN box loss: 0.05012 RPN score loss: 0.00726 RPN total loss: 0.05738 Total loss: 2.48051 timestamp: 1654918302.442949 iteration: 3855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1901 FastRCNN class loss: 0.11325 FastRCNN total loss: 0.30335 L1 loss: 0.0000e+00 L2 loss: 1.97673 Learning rate: 0.02 Mask loss: 0.24318 RPN box loss: 0.0053 RPN score loss: 0.00303 RPN total loss: 0.00832 Total loss: 2.53159 timestamp: 1654918305.8097134 iteration: 3860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15532 FastRCNN class loss: 0.13673 FastRCNN total loss: 0.29205 L1 loss: 0.0000e+00 L2 loss: 1.97635 Learning rate: 0.02 Mask loss: 0.28848 RPN box loss: 0.03039 RPN score loss: 0.00605 RPN total loss: 0.03644 Total loss: 2.59333 timestamp: 1654918309.0443835 iteration: 3865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12635 FastRCNN class loss: 0.07127 FastRCNN total loss: 0.19762 L1 loss: 0.0000e+00 L2 loss: 1.97598 Learning rate: 0.02 Mask loss: 0.15048 RPN box loss: 0.0338 RPN score loss: 0.00524 RPN total loss: 0.03904 Total loss: 2.36312 timestamp: 1654918312.3492167 iteration: 3870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16157 FastRCNN class loss: 0.07329 FastRCNN total loss: 0.23486 L1 loss: 0.0000e+00 L2 loss: 1.9756 Learning rate: 0.02 Mask loss: 0.23487 RPN box loss: 0.02049 RPN score loss: 0.00704 RPN total loss: 0.02753 Total loss: 2.47286 timestamp: 1654918315.627583 iteration: 3875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19997 FastRCNN class loss: 0.11342 FastRCNN total loss: 0.31339 L1 loss: 0.0000e+00 L2 loss: 1.97522 Learning rate: 0.02 Mask loss: 0.2181 RPN box loss: 0.06488 RPN score loss: 0.01784 RPN total loss: 0.08272 Total loss: 2.58943 timestamp: 1654918318.9511335 iteration: 3880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14944 FastRCNN class loss: 0.07716 FastRCNN total loss: 0.2266 L1 loss: 0.0000e+00 L2 loss: 1.97486 Learning rate: 0.02 Mask loss: 0.21937 RPN box loss: 0.05025 RPN score loss: 0.01714 RPN total loss: 0.0674 Total loss: 2.48822 timestamp: 1654918322.1555235 iteration: 3885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1499 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.22932 L1 loss: 0.0000e+00 L2 loss: 1.97451 Learning rate: 0.02 Mask loss: 0.23024 RPN box loss: 0.0309 RPN score loss: 0.00647 RPN total loss: 0.03737 Total loss: 2.47143 timestamp: 1654918325.5421982 iteration: 3890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18606 FastRCNN class loss: 0.10261 FastRCNN total loss: 0.28868 L1 loss: 0.0000e+00 L2 loss: 1.97413 Learning rate: 0.02 Mask loss: 0.22921 RPN box loss: 0.03212 RPN score loss: 0.01784 RPN total loss: 0.04996 Total loss: 2.54198 timestamp: 1654918328.8303502 iteration: 3895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21535 FastRCNN class loss: 0.09491 FastRCNN total loss: 0.31026 L1 loss: 0.0000e+00 L2 loss: 1.97376 Learning rate: 0.02 Mask loss: 0.21633 RPN box loss: 0.07257 RPN score loss: 0.01546 RPN total loss: 0.08803 Total loss: 2.58838 timestamp: 1654918332.0221686 iteration: 3900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18381 FastRCNN class loss: 0.1169 FastRCNN total loss: 0.30071 L1 loss: 0.0000e+00 L2 loss: 1.97339 Learning rate: 0.02 Mask loss: 0.19168 RPN box loss: 0.06604 RPN score loss: 0.01671 RPN total loss: 0.08275 Total loss: 2.54852 timestamp: 1654918335.2081914 iteration: 3905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26036 FastRCNN class loss: 0.14713 FastRCNN total loss: 0.4075 L1 loss: 0.0000e+00 L2 loss: 1.97303 Learning rate: 0.02 Mask loss: 0.18491 RPN box loss: 0.03083 RPN score loss: 0.00716 RPN total loss: 0.038 Total loss: 2.60343 timestamp: 1654918338.4044404 iteration: 3910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1944 FastRCNN class loss: 0.13204 FastRCNN total loss: 0.32644 L1 loss: 0.0000e+00 L2 loss: 1.97268 Learning rate: 0.02 Mask loss: 0.21326 RPN box loss: 0.10194 RPN score loss: 0.01218 RPN total loss: 0.11412 Total loss: 2.62649 timestamp: 1654918341.6353803 iteration: 3915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26337 FastRCNN class loss: 0.1157 FastRCNN total loss: 0.37907 L1 loss: 0.0000e+00 L2 loss: 1.9723 Learning rate: 0.02 Mask loss: 0.15297 RPN box loss: 0.02339 RPN score loss: 0.01373 RPN total loss: 0.03712 Total loss: 2.54147 timestamp: 1654918344.797781 iteration: 3920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16712 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.24376 L1 loss: 0.0000e+00 L2 loss: 1.97194 Learning rate: 0.02 Mask loss: 0.26151 RPN box loss: 0.05344 RPN score loss: 0.00758 RPN total loss: 0.06102 Total loss: 2.53823 timestamp: 1654918348.2635942 iteration: 3925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19438 FastRCNN class loss: 0.08455 FastRCNN total loss: 0.27893 L1 loss: 0.0000e+00 L2 loss: 1.97158 Learning rate: 0.02 Mask loss: 0.16011 RPN box loss: 0.0219 RPN score loss: 0.013 RPN total loss: 0.0349 Total loss: 2.44553 timestamp: 1654918351.4196124 iteration: 3930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18018 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.25457 L1 loss: 0.0000e+00 L2 loss: 1.9712 Learning rate: 0.02 Mask loss: 0.13277 RPN box loss: 0.03413 RPN score loss: 0.01103 RPN total loss: 0.04516 Total loss: 2.4037 timestamp: 1654918354.7416153 iteration: 3935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20759 FastRCNN class loss: 0.10227 FastRCNN total loss: 0.30986 L1 loss: 0.0000e+00 L2 loss: 1.97083 Learning rate: 0.02 Mask loss: 0.2213 RPN box loss: 0.02019 RPN score loss: 0.00744 RPN total loss: 0.02763 Total loss: 2.52962 timestamp: 1654918357.946619 iteration: 3940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19669 FastRCNN class loss: 0.0916 FastRCNN total loss: 0.28829 L1 loss: 0.0000e+00 L2 loss: 1.97044 Learning rate: 0.02 Mask loss: 0.19584 RPN box loss: 0.06541 RPN score loss: 0.01124 RPN total loss: 0.07666 Total loss: 2.53123 timestamp: 1654918361.325867 iteration: 3945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16147 FastRCNN class loss: 0.10635 FastRCNN total loss: 0.26782 L1 loss: 0.0000e+00 L2 loss: 1.97007 Learning rate: 0.02 Mask loss: 0.22371 RPN box loss: 0.05509 RPN score loss: 0.00937 RPN total loss: 0.06447 Total loss: 2.52607 timestamp: 1654918364.5211155 iteration: 3950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20067 FastRCNN class loss: 0.17977 FastRCNN total loss: 0.38045 L1 loss: 0.0000e+00 L2 loss: 1.96971 Learning rate: 0.02 Mask loss: 0.31836 RPN box loss: 0.04911 RPN score loss: 0.02091 RPN total loss: 0.07002 Total loss: 2.73853 timestamp: 1654918367.8506503 iteration: 3955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22291 FastRCNN class loss: 0.12809 FastRCNN total loss: 0.351 L1 loss: 0.0000e+00 L2 loss: 1.96934 Learning rate: 0.02 Mask loss: 0.28932 RPN box loss: 0.02332 RPN score loss: 0.01045 RPN total loss: 0.03377 Total loss: 2.64343 timestamp: 1654918371.1072097 iteration: 3960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19799 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.27072 L1 loss: 0.0000e+00 L2 loss: 1.96899 Learning rate: 0.02 Mask loss: 0.15949 RPN box loss: 0.05239 RPN score loss: 0.01253 RPN total loss: 0.06492 Total loss: 2.46412 timestamp: 1654918374.2633078 iteration: 3965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30391 FastRCNN class loss: 0.13389 FastRCNN total loss: 0.4378 L1 loss: 0.0000e+00 L2 loss: 1.96862 Learning rate: 0.02 Mask loss: 0.2815 RPN box loss: 0.05681 RPN score loss: 0.02051 RPN total loss: 0.07732 Total loss: 2.76524 timestamp: 1654918377.522766 iteration: 3970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19866 FastRCNN class loss: 0.10063 FastRCNN total loss: 0.2993 L1 loss: 0.0000e+00 L2 loss: 1.96825 Learning rate: 0.02 Mask loss: 0.33193 RPN box loss: 0.0345 RPN score loss: 0.01044 RPN total loss: 0.04494 Total loss: 2.64442 timestamp: 1654918380.7224164 iteration: 3975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26037 FastRCNN class loss: 0.12877 FastRCNN total loss: 0.38914 L1 loss: 0.0000e+00 L2 loss: 1.9679 Learning rate: 0.02 Mask loss: 0.23155 RPN box loss: 0.06915 RPN score loss: 0.01343 RPN total loss: 0.08258 Total loss: 2.67117 timestamp: 1654918383.990579 iteration: 3980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23033 FastRCNN class loss: 0.11889 FastRCNN total loss: 0.34922 L1 loss: 0.0000e+00 L2 loss: 1.96753 Learning rate: 0.02 Mask loss: 0.32852 RPN box loss: 0.0686 RPN score loss: 0.0153 RPN total loss: 0.08391 Total loss: 2.72918 timestamp: 1654918387.2810607 iteration: 3985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.199 FastRCNN class loss: 0.072 FastRCNN total loss: 0.271 L1 loss: 0.0000e+00 L2 loss: 1.96719 Learning rate: 0.02 Mask loss: 0.17695 RPN box loss: 0.01005 RPN score loss: 0.0035 RPN total loss: 0.01355 Total loss: 2.42868 timestamp: 1654918390.5800672 iteration: 3990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25681 FastRCNN class loss: 0.13861 FastRCNN total loss: 0.39542 L1 loss: 0.0000e+00 L2 loss: 1.96681 Learning rate: 0.02 Mask loss: 0.28914 RPN box loss: 0.01907 RPN score loss: 0.00954 RPN total loss: 0.02861 Total loss: 2.67999 timestamp: 1654918393.8105874 iteration: 3995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16028 FastRCNN class loss: 0.09584 FastRCNN total loss: 0.25612 L1 loss: 0.0000e+00 L2 loss: 1.96646 Learning rate: 0.02 Mask loss: 0.17027 RPN box loss: 0.06516 RPN score loss: 0.0144 RPN total loss: 0.07956 Total loss: 2.4724 timestamp: 1654918397.0383239 iteration: 4000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33573 FastRCNN class loss: 0.15183 FastRCNN total loss: 0.48756 L1 loss: 0.0000e+00 L2 loss: 1.96609 Learning rate: 0.02 Mask loss: 0.23358 RPN box loss: 0.04111 RPN score loss: 0.01101 RPN total loss: 0.05212 Total loss: 2.73935 timestamp: 1654918400.2500172 iteration: 4005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19713 FastRCNN class loss: 0.14797 FastRCNN total loss: 0.3451 L1 loss: 0.0000e+00 L2 loss: 1.96574 Learning rate: 0.02 Mask loss: 0.1857 RPN box loss: 0.01988 RPN score loss: 0.00736 RPN total loss: 0.02724 Total loss: 2.52378 timestamp: 1654918403.5321038 iteration: 4010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19837 FastRCNN class loss: 0.09536 FastRCNN total loss: 0.29373 L1 loss: 0.0000e+00 L2 loss: 1.96537 Learning rate: 0.02 Mask loss: 0.16028 RPN box loss: 0.04721 RPN score loss: 0.00958 RPN total loss: 0.05679 Total loss: 2.47617 timestamp: 1654918406.738255 iteration: 4015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15618 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.23198 L1 loss: 0.0000e+00 L2 loss: 1.96502 Learning rate: 0.02 Mask loss: 0.21105 RPN box loss: 0.03737 RPN score loss: 0.01177 RPN total loss: 0.04914 Total loss: 2.45718 timestamp: 1654918410.0566273 iteration: 4020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22412 FastRCNN class loss: 0.14396 FastRCNN total loss: 0.36807 L1 loss: 0.0000e+00 L2 loss: 1.96465 Learning rate: 0.02 Mask loss: 0.23789 RPN box loss: 0.0922 RPN score loss: 0.0133 RPN total loss: 0.1055 Total loss: 2.67611 timestamp: 1654918413.403706 iteration: 4025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14477 FastRCNN class loss: 0.07046 FastRCNN total loss: 0.21523 L1 loss: 0.0000e+00 L2 loss: 1.96428 Learning rate: 0.02 Mask loss: 0.30789 RPN box loss: 0.02192 RPN score loss: 0.00799 RPN total loss: 0.02991 Total loss: 2.51731 timestamp: 1654918416.632432 iteration: 4030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26861 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.38024 L1 loss: 0.0000e+00 L2 loss: 1.9639 Learning rate: 0.02 Mask loss: 0.19822 RPN box loss: 0.02305 RPN score loss: 0.00548 RPN total loss: 0.02854 Total loss: 2.5709 timestamp: 1654918419.9406664 iteration: 4035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2605 FastRCNN class loss: 0.09354 FastRCNN total loss: 0.35404 L1 loss: 0.0000e+00 L2 loss: 1.96352 Learning rate: 0.02 Mask loss: 0.20223 RPN box loss: 0.05497 RPN score loss: 0.0104 RPN total loss: 0.06537 Total loss: 2.58517 timestamp: 1654918423.0552626 iteration: 4040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28285 FastRCNN class loss: 0.19088 FastRCNN total loss: 0.47374 L1 loss: 0.0000e+00 L2 loss: 1.96315 Learning rate: 0.02 Mask loss: 0.28839 RPN box loss: 0.08288 RPN score loss: 0.01627 RPN total loss: 0.09915 Total loss: 2.82443 timestamp: 1654918426.3942182 iteration: 4045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14062 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.20586 L1 loss: 0.0000e+00 L2 loss: 1.9628 Learning rate: 0.02 Mask loss: 0.29821 RPN box loss: 0.04042 RPN score loss: 0.00843 RPN total loss: 0.04885 Total loss: 2.51572 timestamp: 1654918429.5576644 iteration: 4050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18081 FastRCNN class loss: 0.07152 FastRCNN total loss: 0.25233 L1 loss: 0.0000e+00 L2 loss: 1.96244 Learning rate: 0.02 Mask loss: 0.14887 RPN box loss: 0.03593 RPN score loss: 0.00626 RPN total loss: 0.04219 Total loss: 2.40583 timestamp: 1654918432.7980459 iteration: 4055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19406 FastRCNN class loss: 0.08752 FastRCNN total loss: 0.28158 L1 loss: 0.0000e+00 L2 loss: 1.96205 Learning rate: 0.02 Mask loss: 0.15733 RPN box loss: 0.05992 RPN score loss: 0.01349 RPN total loss: 0.0734 Total loss: 2.47436 timestamp: 1654918436.1014297 iteration: 4060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20558 FastRCNN class loss: 0.12369 FastRCNN total loss: 0.32927 L1 loss: 0.0000e+00 L2 loss: 1.96169 Learning rate: 0.02 Mask loss: 0.17146 RPN box loss: 0.06192 RPN score loss: 0.00915 RPN total loss: 0.07107 Total loss: 2.53349 timestamp: 1654918439.4148989 iteration: 4065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17771 FastRCNN class loss: 0.09589 FastRCNN total loss: 0.27361 L1 loss: 0.0000e+00 L2 loss: 1.96131 Learning rate: 0.02 Mask loss: 0.21785 RPN box loss: 0.02498 RPN score loss: 0.00977 RPN total loss: 0.03475 Total loss: 2.48752 timestamp: 1654918442.7205272 iteration: 4070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20429 FastRCNN class loss: 0.10916 FastRCNN total loss: 0.31345 L1 loss: 0.0000e+00 L2 loss: 1.96093 Learning rate: 0.02 Mask loss: 0.20911 RPN box loss: 0.03076 RPN score loss: 0.00411 RPN total loss: 0.03487 Total loss: 2.51836 timestamp: 1654918445.8954008 iteration: 4075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16652 FastRCNN class loss: 0.11373 FastRCNN total loss: 0.28026 L1 loss: 0.0000e+00 L2 loss: 1.96057 Learning rate: 0.02 Mask loss: 0.22008 RPN box loss: 0.03912 RPN score loss: 0.01389 RPN total loss: 0.05301 Total loss: 2.51392 timestamp: 1654918449.1084633 iteration: 4080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24566 FastRCNN class loss: 0.11238 FastRCNN total loss: 0.35804 L1 loss: 0.0000e+00 L2 loss: 1.9602 Learning rate: 0.02 Mask loss: 0.29816 RPN box loss: 0.05173 RPN score loss: 0.00769 RPN total loss: 0.05942 Total loss: 2.67583 timestamp: 1654918452.3372593 iteration: 4085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30098 FastRCNN class loss: 0.18335 FastRCNN total loss: 0.48433 L1 loss: 0.0000e+00 L2 loss: 1.95982 Learning rate: 0.02 Mask loss: 0.31909 RPN box loss: 0.12064 RPN score loss: 0.01572 RPN total loss: 0.13636 Total loss: 2.8996 timestamp: 1654918455.637189 iteration: 4090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24279 FastRCNN class loss: 0.12907 FastRCNN total loss: 0.37186 L1 loss: 0.0000e+00 L2 loss: 1.95946 Learning rate: 0.02 Mask loss: 0.22951 RPN box loss: 0.06261 RPN score loss: 0.01378 RPN total loss: 0.07639 Total loss: 2.63721 timestamp: 1654918458.9260883 iteration: 4095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15058 FastRCNN class loss: 0.09634 FastRCNN total loss: 0.24692 L1 loss: 0.0000e+00 L2 loss: 1.95909 Learning rate: 0.02 Mask loss: 0.12943 RPN box loss: 0.02968 RPN score loss: 0.00879 RPN total loss: 0.03847 Total loss: 2.37391 timestamp: 1654918462.2101862 iteration: 4100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21912 FastRCNN class loss: 0.0768 FastRCNN total loss: 0.29592 L1 loss: 0.0000e+00 L2 loss: 1.95873 Learning rate: 0.02 Mask loss: 0.19214 RPN box loss: 0.07583 RPN score loss: 0.01205 RPN total loss: 0.08788 Total loss: 2.53467 timestamp: 1654918465.4313107 iteration: 4105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20553 FastRCNN class loss: 0.12812 FastRCNN total loss: 0.33364 L1 loss: 0.0000e+00 L2 loss: 1.95839 Learning rate: 0.02 Mask loss: 0.19334 RPN box loss: 0.01887 RPN score loss: 0.00607 RPN total loss: 0.02494 Total loss: 2.51031 timestamp: 1654918468.617324 iteration: 4110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24189 FastRCNN class loss: 0.10635 FastRCNN total loss: 0.34824 L1 loss: 0.0000e+00 L2 loss: 1.95803 Learning rate: 0.02 Mask loss: 0.19836 RPN box loss: 0.0346 RPN score loss: 0.01134 RPN total loss: 0.04594 Total loss: 2.55057 timestamp: 1654918471.9141858 iteration: 4115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15644 FastRCNN class loss: 0.09177 FastRCNN total loss: 0.24821 L1 loss: 0.0000e+00 L2 loss: 1.95767 Learning rate: 0.02 Mask loss: 0.16979 RPN box loss: 0.04556 RPN score loss: 0.02166 RPN total loss: 0.06722 Total loss: 2.44289 timestamp: 1654918475.2262452 iteration: 4120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19726 FastRCNN class loss: 0.09408 FastRCNN total loss: 0.29134 L1 loss: 0.0000e+00 L2 loss: 1.95731 Learning rate: 0.02 Mask loss: 0.23092 RPN box loss: 0.07016 RPN score loss: 0.02128 RPN total loss: 0.09144 Total loss: 2.57101 timestamp: 1654918478.521027 iteration: 4125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30527 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.4022 L1 loss: 0.0000e+00 L2 loss: 1.95693 Learning rate: 0.02 Mask loss: 0.19869 RPN box loss: 0.04454 RPN score loss: 0.00943 RPN total loss: 0.05397 Total loss: 2.61178 timestamp: 1654918481.7461302 iteration: 4130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17223 FastRCNN class loss: 0.21005 FastRCNN total loss: 0.38228 L1 loss: 0.0000e+00 L2 loss: 1.95656 Learning rate: 0.02 Mask loss: 0.33344 RPN box loss: 0.05791 RPN score loss: 0.11642 RPN total loss: 0.17432 Total loss: 2.84661 timestamp: 1654918484.9979064 iteration: 4135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09099 FastRCNN class loss: 0.06848 FastRCNN total loss: 0.15947 L1 loss: 0.0000e+00 L2 loss: 1.95618 Learning rate: 0.02 Mask loss: 0.16626 RPN box loss: 0.07992 RPN score loss: 0.00697 RPN total loss: 0.08689 Total loss: 2.36881 timestamp: 1654918488.1764967 iteration: 4140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25902 FastRCNN class loss: 0.14463 FastRCNN total loss: 0.40365 L1 loss: 0.0000e+00 L2 loss: 1.95582 Learning rate: 0.02 Mask loss: 0.17143 RPN box loss: 0.08799 RPN score loss: 0.00877 RPN total loss: 0.09675 Total loss: 2.62764 timestamp: 1654918491.5098252 iteration: 4145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13899 FastRCNN class loss: 0.09438 FastRCNN total loss: 0.23338 L1 loss: 0.0000e+00 L2 loss: 1.95544 Learning rate: 0.02 Mask loss: 0.19975 RPN box loss: 0.0726 RPN score loss: 0.01138 RPN total loss: 0.08397 Total loss: 2.47255 timestamp: 1654918494.8156443 iteration: 4150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18312 FastRCNN class loss: 0.09789 FastRCNN total loss: 0.28101 L1 loss: 0.0000e+00 L2 loss: 1.95507 Learning rate: 0.02 Mask loss: 0.23761 RPN box loss: 0.03766 RPN score loss: 0.01205 RPN total loss: 0.04971 Total loss: 2.52341 timestamp: 1654918498.2819 iteration: 4155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17612 FastRCNN class loss: 0.10743 FastRCNN total loss: 0.28354 L1 loss: 0.0000e+00 L2 loss: 1.95471 Learning rate: 0.02 Mask loss: 0.25597 RPN box loss: 0.06793 RPN score loss: 0.00721 RPN total loss: 0.07514 Total loss: 2.56936 timestamp: 1654918501.5680058 iteration: 4160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.05915 FastRCNN total loss: 0.17031 L1 loss: 0.0000e+00 L2 loss: 1.95432 Learning rate: 0.02 Mask loss: 0.17258 RPN box loss: 0.02801 RPN score loss: 0.00301 RPN total loss: 0.03102 Total loss: 2.32823 timestamp: 1654918504.8867197 iteration: 4165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12061 FastRCNN class loss: 0.04368 FastRCNN total loss: 0.16428 L1 loss: 0.0000e+00 L2 loss: 1.95394 Learning rate: 0.02 Mask loss: 0.22408 RPN box loss: 0.07523 RPN score loss: 0.01635 RPN total loss: 0.09158 Total loss: 2.43387 timestamp: 1654918508.1326056 iteration: 4170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17901 FastRCNN class loss: 0.13431 FastRCNN total loss: 0.31332 L1 loss: 0.0000e+00 L2 loss: 1.95357 Learning rate: 0.02 Mask loss: 0.25975 RPN box loss: 0.02768 RPN score loss: 0.01417 RPN total loss: 0.04186 Total loss: 2.56849 timestamp: 1654918511.4155297 iteration: 4175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17102 FastRCNN class loss: 0.10012 FastRCNN total loss: 0.27113 L1 loss: 0.0000e+00 L2 loss: 1.95321 Learning rate: 0.02 Mask loss: 0.15692 RPN box loss: 0.04028 RPN score loss: 0.00818 RPN total loss: 0.04846 Total loss: 2.42972 timestamp: 1654918514.929452 iteration: 4180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21567 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.2868 L1 loss: 0.0000e+00 L2 loss: 1.95284 Learning rate: 0.02 Mask loss: 0.16553 RPN box loss: 0.0894 RPN score loss: 0.01012 RPN total loss: 0.09953 Total loss: 2.50471 timestamp: 1654918518.1338522 iteration: 4185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09182 FastRCNN class loss: 0.04688 FastRCNN total loss: 0.1387 L1 loss: 0.0000e+00 L2 loss: 1.95248 Learning rate: 0.02 Mask loss: 0.25626 RPN box loss: 0.00514 RPN score loss: 0.00548 RPN total loss: 0.01063 Total loss: 2.35806 timestamp: 1654918521.4935255 iteration: 4190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20605 FastRCNN class loss: 0.13804 FastRCNN total loss: 0.34409 L1 loss: 0.0000e+00 L2 loss: 1.9521 Learning rate: 0.02 Mask loss: 0.21557 RPN box loss: 0.06665 RPN score loss: 0.01538 RPN total loss: 0.08203 Total loss: 2.59379 timestamp: 1654918524.6673758 iteration: 4195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27745 FastRCNN class loss: 0.1628 FastRCNN total loss: 0.44025 L1 loss: 0.0000e+00 L2 loss: 1.95174 Learning rate: 0.02 Mask loss: 0.41859 RPN box loss: 0.07354 RPN score loss: 0.01586 RPN total loss: 0.0894 Total loss: 2.89999 timestamp: 1654918528.1488233 iteration: 4200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25008 FastRCNN class loss: 0.10342 FastRCNN total loss: 0.3535 L1 loss: 0.0000e+00 L2 loss: 1.95136 Learning rate: 0.02 Mask loss: 0.17014 RPN box loss: 0.04589 RPN score loss: 0.03324 RPN total loss: 0.07913 Total loss: 2.55412 timestamp: 1654918531.383387 iteration: 4205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19381 FastRCNN class loss: 0.10496 FastRCNN total loss: 0.29877 L1 loss: 0.0000e+00 L2 loss: 1.95098 Learning rate: 0.02 Mask loss: 0.31818 RPN box loss: 0.01579 RPN score loss: 0.01347 RPN total loss: 0.02926 Total loss: 2.59719 timestamp: 1654918534.670007 iteration: 4210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1487 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.20653 L1 loss: 0.0000e+00 L2 loss: 1.95062 Learning rate: 0.02 Mask loss: 0.16868 RPN box loss: 0.05478 RPN score loss: 0.00514 RPN total loss: 0.05992 Total loss: 2.38574 timestamp: 1654918537.940192 iteration: 4215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13902 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.20613 L1 loss: 0.0000e+00 L2 loss: 1.95026 Learning rate: 0.02 Mask loss: 0.28368 RPN box loss: 0.02126 RPN score loss: 0.00516 RPN total loss: 0.02641 Total loss: 2.46649 timestamp: 1654918541.2438602 iteration: 4220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22155 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.2982 L1 loss: 0.0000e+00 L2 loss: 1.94988 Learning rate: 0.02 Mask loss: 0.19601 RPN box loss: 0.06335 RPN score loss: 0.00544 RPN total loss: 0.06879 Total loss: 2.51288 timestamp: 1654918544.5431733 iteration: 4225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18969 FastRCNN class loss: 0.08652 FastRCNN total loss: 0.27621 L1 loss: 0.0000e+00 L2 loss: 1.94951 Learning rate: 0.02 Mask loss: 0.21547 RPN box loss: 0.06339 RPN score loss: 0.01132 RPN total loss: 0.07471 Total loss: 2.51589 timestamp: 1654918547.7951787 iteration: 4230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18348 FastRCNN class loss: 0.10998 FastRCNN total loss: 0.29346 L1 loss: 0.0000e+00 L2 loss: 1.94915 Learning rate: 0.02 Mask loss: 0.17556 RPN box loss: 0.02703 RPN score loss: 0.00492 RPN total loss: 0.03195 Total loss: 2.45012 timestamp: 1654918551.0446758 iteration: 4235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23649 FastRCNN class loss: 0.11187 FastRCNN total loss: 0.34836 L1 loss: 0.0000e+00 L2 loss: 1.94879 Learning rate: 0.02 Mask loss: 0.2047 RPN box loss: 0.04295 RPN score loss: 0.00973 RPN total loss: 0.05268 Total loss: 2.55452 timestamp: 1654918554.2253482 iteration: 4240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20623 FastRCNN class loss: 0.10751 FastRCNN total loss: 0.31374 L1 loss: 0.0000e+00 L2 loss: 1.94843 Learning rate: 0.02 Mask loss: 0.24868 RPN box loss: 0.02615 RPN score loss: 0.00498 RPN total loss: 0.03113 Total loss: 2.54198 timestamp: 1654918557.5131052 iteration: 4245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14158 FastRCNN class loss: 0.06554 FastRCNN total loss: 0.20712 L1 loss: 0.0000e+00 L2 loss: 1.94808 Learning rate: 0.02 Mask loss: 0.22161 RPN box loss: 0.03956 RPN score loss: 0.0073 RPN total loss: 0.04686 Total loss: 2.42367 timestamp: 1654918560.7543154 iteration: 4250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07537 FastRCNN class loss: 0.10307 FastRCNN total loss: 0.17844 L1 loss: 0.0000e+00 L2 loss: 1.94772 Learning rate: 0.02 Mask loss: 0.1507 RPN box loss: 0.01891 RPN score loss: 0.00823 RPN total loss: 0.02713 Total loss: 2.30399 timestamp: 1654918564.0763469 iteration: 4255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25532 FastRCNN class loss: 0.07284 FastRCNN total loss: 0.32816 L1 loss: 0.0000e+00 L2 loss: 1.94735 Learning rate: 0.02 Mask loss: 0.12646 RPN box loss: 0.07019 RPN score loss: 0.00525 RPN total loss: 0.07544 Total loss: 2.47741 timestamp: 1654918567.2171643 iteration: 4260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19073 FastRCNN class loss: 0.18458 FastRCNN total loss: 0.37531 L1 loss: 0.0000e+00 L2 loss: 1.94699 Learning rate: 0.02 Mask loss: 0.291 RPN box loss: 0.02435 RPN score loss: 0.00481 RPN total loss: 0.02916 Total loss: 2.64246 timestamp: 1654918570.4978836 iteration: 4265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15588 FastRCNN class loss: 0.14248 FastRCNN total loss: 0.29835 L1 loss: 0.0000e+00 L2 loss: 1.94663 Learning rate: 0.02 Mask loss: 0.17891 RPN box loss: 0.06729 RPN score loss: 0.04258 RPN total loss: 0.10988 Total loss: 2.53377 timestamp: 1654918573.816964 iteration: 4270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24542 FastRCNN class loss: 0.13695 FastRCNN total loss: 0.38237 L1 loss: 0.0000e+00 L2 loss: 1.94624 Learning rate: 0.02 Mask loss: 0.21409 RPN box loss: 0.03637 RPN score loss: 0.01134 RPN total loss: 0.04771 Total loss: 2.59042 timestamp: 1654918577.0145628 iteration: 4275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20173 FastRCNN class loss: 0.08912 FastRCNN total loss: 0.29085 L1 loss: 0.0000e+00 L2 loss: 1.94588 Learning rate: 0.02 Mask loss: 0.15895 RPN box loss: 0.02736 RPN score loss: 0.00658 RPN total loss: 0.03394 Total loss: 2.42961 timestamp: 1654918580.4652193 iteration: 4280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16546 FastRCNN class loss: 0.06507 FastRCNN total loss: 0.23053 L1 loss: 0.0000e+00 L2 loss: 1.94551 Learning rate: 0.02 Mask loss: 0.17339 RPN box loss: 0.04803 RPN score loss: 0.01076 RPN total loss: 0.05879 Total loss: 2.40823 timestamp: 1654918583.740804 iteration: 4285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16865 FastRCNN class loss: 0.10666 FastRCNN total loss: 0.27531 L1 loss: 0.0000e+00 L2 loss: 1.94516 Learning rate: 0.02 Mask loss: 0.22742 RPN box loss: 0.06374 RPN score loss: 0.00649 RPN total loss: 0.07023 Total loss: 2.51811 timestamp: 1654918586.973734 iteration: 4290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24848 FastRCNN class loss: 0.12959 FastRCNN total loss: 0.37807 L1 loss: 0.0000e+00 L2 loss: 1.9448 Learning rate: 0.02 Mask loss: 0.255 RPN box loss: 0.04789 RPN score loss: 0.015 RPN total loss: 0.06289 Total loss: 2.64075 timestamp: 1654918590.238676 iteration: 4295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20863 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.29029 L1 loss: 0.0000e+00 L2 loss: 1.94444 Learning rate: 0.02 Mask loss: 0.18962 RPN box loss: 0.04511 RPN score loss: 0.00497 RPN total loss: 0.05008 Total loss: 2.47443 timestamp: 1654918593.5165331 iteration: 4300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15263 FastRCNN class loss: 0.08084 FastRCNN total loss: 0.23347 L1 loss: 0.0000e+00 L2 loss: 1.94409 Learning rate: 0.02 Mask loss: 0.1883 RPN box loss: 0.0475 RPN score loss: 0.01481 RPN total loss: 0.06231 Total loss: 2.42817 timestamp: 1654918596.7775648 iteration: 4305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14561 FastRCNN class loss: 0.10297 FastRCNN total loss: 0.24858 L1 loss: 0.0000e+00 L2 loss: 1.94371 Learning rate: 0.02 Mask loss: 0.1838 RPN box loss: 0.03456 RPN score loss: 0.00776 RPN total loss: 0.04232 Total loss: 2.41841 timestamp: 1654918600.1050215 iteration: 4310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20406 FastRCNN class loss: 0.11458 FastRCNN total loss: 0.31865 L1 loss: 0.0000e+00 L2 loss: 1.94335 Learning rate: 0.02 Mask loss: 0.19836 RPN box loss: 0.12641 RPN score loss: 0.0158 RPN total loss: 0.14221 Total loss: 2.60256 timestamp: 1654918603.488794 iteration: 4315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23454 FastRCNN class loss: 0.18368 FastRCNN total loss: 0.41823 L1 loss: 0.0000e+00 L2 loss: 1.94297 Learning rate: 0.02 Mask loss: 0.24334 RPN box loss: 0.08502 RPN score loss: 0.0116 RPN total loss: 0.09662 Total loss: 2.70116 timestamp: 1654918606.6852543 iteration: 4320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1979 FastRCNN class loss: 0.11786 FastRCNN total loss: 0.31576 L1 loss: 0.0000e+00 L2 loss: 1.94263 Learning rate: 0.02 Mask loss: 0.18986 RPN box loss: 0.07762 RPN score loss: 0.02519 RPN total loss: 0.10281 Total loss: 2.55106 timestamp: 1654918609.9302895 iteration: 4325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23788 FastRCNN class loss: 0.10711 FastRCNN total loss: 0.34499 L1 loss: 0.0000e+00 L2 loss: 1.94226 Learning rate: 0.02 Mask loss: 0.17681 RPN box loss: 0.05837 RPN score loss: 0.03796 RPN total loss: 0.09633 Total loss: 2.5604 timestamp: 1654918613.1543052 iteration: 4330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18985 FastRCNN class loss: 0.11424 FastRCNN total loss: 0.3041 L1 loss: 0.0000e+00 L2 loss: 1.94189 Learning rate: 0.02 Mask loss: 0.19103 RPN box loss: 0.04008 RPN score loss: 0.00595 RPN total loss: 0.04603 Total loss: 2.48304 timestamp: 1654918616.3760314 iteration: 4335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14506 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.21759 L1 loss: 0.0000e+00 L2 loss: 1.94151 Learning rate: 0.02 Mask loss: 0.17134 RPN box loss: 0.05537 RPN score loss: 0.00844 RPN total loss: 0.06381 Total loss: 2.39425 timestamp: 1654918619.6514187 iteration: 4340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22072 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.29548 L1 loss: 0.0000e+00 L2 loss: 1.94114 Learning rate: 0.02 Mask loss: 0.14303 RPN box loss: 0.02825 RPN score loss: 0.00411 RPN total loss: 0.03236 Total loss: 2.41202 timestamp: 1654918622.916923 iteration: 4345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11376 FastRCNN class loss: 0.09771 FastRCNN total loss: 0.21147 L1 loss: 0.0000e+00 L2 loss: 1.94077 Learning rate: 0.02 Mask loss: 0.14336 RPN box loss: 0.069 RPN score loss: 0.00527 RPN total loss: 0.07427 Total loss: 2.36987 timestamp: 1654918626.1206422 iteration: 4350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33157 FastRCNN class loss: 0.20077 FastRCNN total loss: 0.53235 L1 loss: 0.0000e+00 L2 loss: 1.94042 Learning rate: 0.02 Mask loss: 0.38551 RPN box loss: 0.03396 RPN score loss: 0.02208 RPN total loss: 0.05605 Total loss: 2.91432 timestamp: 1654918629.4247854 iteration: 4355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15445 FastRCNN class loss: 0.10269 FastRCNN total loss: 0.25714 L1 loss: 0.0000e+00 L2 loss: 1.94006 Learning rate: 0.02 Mask loss: 0.21546 RPN box loss: 0.024 RPN score loss: 0.00447 RPN total loss: 0.02847 Total loss: 2.44113 timestamp: 1654918632.6299715 iteration: 4360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13609 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.20612 L1 loss: 0.0000e+00 L2 loss: 1.93971 Learning rate: 0.02 Mask loss: 0.14123 RPN box loss: 0.02494 RPN score loss: 0.00619 RPN total loss: 0.03114 Total loss: 2.31819 timestamp: 1654918636.0410144 iteration: 4365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18851 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.25939 L1 loss: 0.0000e+00 L2 loss: 1.93934 Learning rate: 0.02 Mask loss: 0.16657 RPN box loss: 0.03555 RPN score loss: 0.00649 RPN total loss: 0.04204 Total loss: 2.40734 timestamp: 1654918639.2871473 iteration: 4370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17581 FastRCNN class loss: 0.16557 FastRCNN total loss: 0.34138 L1 loss: 0.0000e+00 L2 loss: 1.93897 Learning rate: 0.02 Mask loss: 0.28398 RPN box loss: 0.08886 RPN score loss: 0.00394 RPN total loss: 0.0928 Total loss: 2.65713 timestamp: 1654918642.5158176 iteration: 4375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26007 FastRCNN class loss: 0.12063 FastRCNN total loss: 0.3807 L1 loss: 0.0000e+00 L2 loss: 1.9386 Learning rate: 0.02 Mask loss: 0.23201 RPN box loss: 0.04499 RPN score loss: 0.01056 RPN total loss: 0.05556 Total loss: 2.60687 timestamp: 1654918645.8666139 iteration: 4380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20736 FastRCNN class loss: 0.10979 FastRCNN total loss: 0.31714 L1 loss: 0.0000e+00 L2 loss: 1.93823 Learning rate: 0.02 Mask loss: 0.16477 RPN box loss: 0.06446 RPN score loss: 0.0136 RPN total loss: 0.07805 Total loss: 2.49819 timestamp: 1654918649.1034384 iteration: 4385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20876 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.29844 L1 loss: 0.0000e+00 L2 loss: 1.93787 Learning rate: 0.02 Mask loss: 0.18092 RPN box loss: 0.03075 RPN score loss: 0.00938 RPN total loss: 0.04013 Total loss: 2.45736 timestamp: 1654918652.3734562 iteration: 4390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13989 FastRCNN class loss: 0.09563 FastRCNN total loss: 0.23552 L1 loss: 0.0000e+00 L2 loss: 1.93751 Learning rate: 0.02 Mask loss: 0.13956 RPN box loss: 0.03324 RPN score loss: 0.00725 RPN total loss: 0.04049 Total loss: 2.35308 timestamp: 1654918655.565789 iteration: 4395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22952 FastRCNN class loss: 0.1434 FastRCNN total loss: 0.37293 L1 loss: 0.0000e+00 L2 loss: 1.93716 Learning rate: 0.02 Mask loss: 0.291 RPN box loss: 0.04177 RPN score loss: 0.02524 RPN total loss: 0.067 Total loss: 2.66809 timestamp: 1654918658.8327956 iteration: 4400 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16313 FastRCNN class loss: 0.10533 FastRCNN total loss: 0.26847 L1 loss: 0.0000e+00 L2 loss: 1.9368 Learning rate: 0.02 Mask loss: 0.17263 RPN box loss: 0.04755 RPN score loss: 0.02681 RPN total loss: 0.07436 Total loss: 2.45226 timestamp: 1654918662.0924172 iteration: 4405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14104 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.21495 L1 loss: 0.0000e+00 L2 loss: 1.93644 Learning rate: 0.02 Mask loss: 0.37527 RPN box loss: 0.02577 RPN score loss: 0.00539 RPN total loss: 0.03116 Total loss: 2.55782 timestamp: 1654918665.4874008 iteration: 4410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25719 FastRCNN class loss: 0.16355 FastRCNN total loss: 0.42074 L1 loss: 0.0000e+00 L2 loss: 1.93605 Learning rate: 0.02 Mask loss: 0.21035 RPN box loss: 0.04388 RPN score loss: 0.00742 RPN total loss: 0.0513 Total loss: 2.61844 timestamp: 1654918668.9258716 iteration: 4415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2409 FastRCNN class loss: 0.14672 FastRCNN total loss: 0.38762 L1 loss: 0.0000e+00 L2 loss: 1.93568 Learning rate: 0.02 Mask loss: 0.32022 RPN box loss: 0.08721 RPN score loss: 0.01209 RPN total loss: 0.0993 Total loss: 2.74282 timestamp: 1654918672.0941594 iteration: 4420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18286 FastRCNN class loss: 0.09618 FastRCNN total loss: 0.27904 L1 loss: 0.0000e+00 L2 loss: 1.93532 Learning rate: 0.02 Mask loss: 0.16907 RPN box loss: 0.01402 RPN score loss: 0.00293 RPN total loss: 0.01695 Total loss: 2.40037 timestamp: 1654918675.3636158 iteration: 4425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2254 FastRCNN class loss: 0.13249 FastRCNN total loss: 0.35789 L1 loss: 0.0000e+00 L2 loss: 1.93495 Learning rate: 0.02 Mask loss: 0.20105 RPN box loss: 0.06146 RPN score loss: 0.01864 RPN total loss: 0.0801 Total loss: 2.574 timestamp: 1654918678.6455204 iteration: 4430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24907 FastRCNN class loss: 0.09399 FastRCNN total loss: 0.34306 L1 loss: 0.0000e+00 L2 loss: 1.93461 Learning rate: 0.02 Mask loss: 0.18451 RPN box loss: 0.02815 RPN score loss: 0.00888 RPN total loss: 0.03703 Total loss: 2.49921 timestamp: 1654918681.929975 iteration: 4435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19507 FastRCNN class loss: 0.09473 FastRCNN total loss: 0.2898 L1 loss: 0.0000e+00 L2 loss: 1.93423 Learning rate: 0.02 Mask loss: 0.21895 RPN box loss: 0.06426 RPN score loss: 0.0187 RPN total loss: 0.08296 Total loss: 2.52594 timestamp: 1654918685.052019 iteration: 4440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13211 FastRCNN class loss: 0.12124 FastRCNN total loss: 0.25334 L1 loss: 0.0000e+00 L2 loss: 1.93387 Learning rate: 0.02 Mask loss: 0.21305 RPN box loss: 0.06245 RPN score loss: 0.01482 RPN total loss: 0.07727 Total loss: 2.47753 timestamp: 1654918688.3717377 iteration: 4445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23618 FastRCNN class loss: 0.11566 FastRCNN total loss: 0.35183 L1 loss: 0.0000e+00 L2 loss: 1.93351 Learning rate: 0.02 Mask loss: 0.25081 RPN box loss: 0.06328 RPN score loss: 0.01423 RPN total loss: 0.07751 Total loss: 2.61367 timestamp: 1654918691.496361 iteration: 4450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17827 FastRCNN class loss: 0.17298 FastRCNN total loss: 0.35125 L1 loss: 0.0000e+00 L2 loss: 1.93317 Learning rate: 0.02 Mask loss: 0.23032 RPN box loss: 0.05497 RPN score loss: 0.0166 RPN total loss: 0.07156 Total loss: 2.58629 timestamp: 1654918694.7893913 iteration: 4455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19327 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.26935 L1 loss: 0.0000e+00 L2 loss: 1.93281 Learning rate: 0.02 Mask loss: 0.24232 RPN box loss: 0.05918 RPN score loss: 0.01488 RPN total loss: 0.07407 Total loss: 2.51855 timestamp: 1654918698.0406046 iteration: 4460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19325 FastRCNN class loss: 0.07987 FastRCNN total loss: 0.27311 L1 loss: 0.0000e+00 L2 loss: 1.93246 Learning rate: 0.02 Mask loss: 0.1937 RPN box loss: 0.03371 RPN score loss: 0.00896 RPN total loss: 0.04267 Total loss: 2.44194 timestamp: 1654918701.2866542 iteration: 4465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08401 FastRCNN class loss: 0.06189 FastRCNN total loss: 0.14589 L1 loss: 0.0000e+00 L2 loss: 1.93209 Learning rate: 0.02 Mask loss: 0.146 RPN box loss: 0.11347 RPN score loss: 0.00787 RPN total loss: 0.12135 Total loss: 2.34533 timestamp: 1654918704.3843539 iteration: 4470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23258 FastRCNN class loss: 0.17024 FastRCNN total loss: 0.40282 L1 loss: 0.0000e+00 L2 loss: 1.93172 Learning rate: 0.02 Mask loss: 0.29672 RPN box loss: 0.01767 RPN score loss: 0.00734 RPN total loss: 0.02501 Total loss: 2.65627 timestamp: 1654918707.689158 iteration: 4475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26268 FastRCNN class loss: 0.17249 FastRCNN total loss: 0.43517 L1 loss: 0.0000e+00 L2 loss: 1.93137 Learning rate: 0.02 Mask loss: 0.21051 RPN box loss: 0.02459 RPN score loss: 0.01035 RPN total loss: 0.03494 Total loss: 2.61199 timestamp: 1654918711.05037 iteration: 4480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29843 FastRCNN class loss: 0.13192 FastRCNN total loss: 0.43035 L1 loss: 0.0000e+00 L2 loss: 1.93102 Learning rate: 0.02 Mask loss: 0.25649 RPN box loss: 0.03651 RPN score loss: 0.01577 RPN total loss: 0.05228 Total loss: 2.67015 timestamp: 1654918714.25836 iteration: 4485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14313 FastRCNN class loss: 0.04632 FastRCNN total loss: 0.18945 L1 loss: 0.0000e+00 L2 loss: 1.93066 Learning rate: 0.02 Mask loss: 0.11973 RPN box loss: 0.01939 RPN score loss: 0.00415 RPN total loss: 0.02354 Total loss: 2.26338 timestamp: 1654918717.584019 iteration: 4490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09624 FastRCNN class loss: 0.06232 FastRCNN total loss: 0.15856 L1 loss: 0.0000e+00 L2 loss: 1.9303 Learning rate: 0.02 Mask loss: 0.09941 RPN box loss: 0.07259 RPN score loss: 0.00785 RPN total loss: 0.08044 Total loss: 2.26872 timestamp: 1654918720.7035127 iteration: 4495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1393 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.19815 L1 loss: 0.0000e+00 L2 loss: 1.92994 Learning rate: 0.02 Mask loss: 0.15176 RPN box loss: 0.08908 RPN score loss: 0.00644 RPN total loss: 0.09552 Total loss: 2.37536 timestamp: 1654918723.9834337 iteration: 4500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16082 FastRCNN class loss: 0.08889 FastRCNN total loss: 0.24971 L1 loss: 0.0000e+00 L2 loss: 1.92958 Learning rate: 0.02 Mask loss: 0.17328 RPN box loss: 0.04742 RPN score loss: 0.00931 RPN total loss: 0.05673 Total loss: 2.4093 timestamp: 1654918727.2148952 iteration: 4505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20265 FastRCNN class loss: 0.13098 FastRCNN total loss: 0.33362 L1 loss: 0.0000e+00 L2 loss: 1.9292 Learning rate: 0.02 Mask loss: 0.32697 RPN box loss: 0.04474 RPN score loss: 0.00557 RPN total loss: 0.05032 Total loss: 2.64011 timestamp: 1654918730.4824836 iteration: 4510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20663 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.28164 L1 loss: 0.0000e+00 L2 loss: 1.92883 Learning rate: 0.02 Mask loss: 0.2376 RPN box loss: 0.02429 RPN score loss: 0.00772 RPN total loss: 0.03201 Total loss: 2.48009 timestamp: 1654918733.7404065 iteration: 4515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.243 FastRCNN class loss: 0.12548 FastRCNN total loss: 0.36848 L1 loss: 0.0000e+00 L2 loss: 1.92846 Learning rate: 0.02 Mask loss: 0.2579 RPN box loss: 0.07114 RPN score loss: 0.00959 RPN total loss: 0.08073 Total loss: 2.63557 timestamp: 1654918737.0687933 iteration: 4520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18066 FastRCNN class loss: 0.09319 FastRCNN total loss: 0.27384 L1 loss: 0.0000e+00 L2 loss: 1.92811 Learning rate: 0.02 Mask loss: 0.20224 RPN box loss: 0.08172 RPN score loss: 0.01035 RPN total loss: 0.09207 Total loss: 2.49626 timestamp: 1654918740.402323 iteration: 4525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17118 FastRCNN class loss: 0.10509 FastRCNN total loss: 0.27627 L1 loss: 0.0000e+00 L2 loss: 1.92777 Learning rate: 0.02 Mask loss: 0.19083 RPN box loss: 0.02931 RPN score loss: 0.00876 RPN total loss: 0.03807 Total loss: 2.43294 timestamp: 1654918743.6243045 iteration: 4530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1836 FastRCNN class loss: 0.0518 FastRCNN total loss: 0.2354 L1 loss: 0.0000e+00 L2 loss: 1.92742 Learning rate: 0.02 Mask loss: 0.10102 RPN box loss: 0.01129 RPN score loss: 0.00503 RPN total loss: 0.01633 Total loss: 2.28016 timestamp: 1654918746.9202278 iteration: 4535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18542 FastRCNN class loss: 0.10961 FastRCNN total loss: 0.29502 L1 loss: 0.0000e+00 L2 loss: 1.92707 Learning rate: 0.02 Mask loss: 0.19236 RPN box loss: 0.0477 RPN score loss: 0.01 RPN total loss: 0.0577 Total loss: 2.47215 timestamp: 1654918750.0498843 iteration: 4540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18639 FastRCNN class loss: 0.14559 FastRCNN total loss: 0.33198 L1 loss: 0.0000e+00 L2 loss: 1.92672 Learning rate: 0.02 Mask loss: 0.29706 RPN box loss: 0.06972 RPN score loss: 0.02908 RPN total loss: 0.0988 Total loss: 2.65456 timestamp: 1654918753.3615406 iteration: 4545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17697 FastRCNN class loss: 0.10835 FastRCNN total loss: 0.28533 L1 loss: 0.0000e+00 L2 loss: 1.92634 Learning rate: 0.02 Mask loss: 0.19986 RPN box loss: 0.0234 RPN score loss: 0.01309 RPN total loss: 0.03649 Total loss: 2.44801 timestamp: 1654918756.4608781 iteration: 4550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17263 FastRCNN class loss: 0.08219 FastRCNN total loss: 0.25482 L1 loss: 0.0000e+00 L2 loss: 1.92598 Learning rate: 0.02 Mask loss: 0.1648 RPN box loss: 0.04755 RPN score loss: 0.00366 RPN total loss: 0.05121 Total loss: 2.3968 timestamp: 1654918759.682814 iteration: 4555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18796 FastRCNN class loss: 0.12122 FastRCNN total loss: 0.30918 L1 loss: 0.0000e+00 L2 loss: 1.92563 Learning rate: 0.02 Mask loss: 0.17799 RPN box loss: 0.06781 RPN score loss: 0.00879 RPN total loss: 0.0766 Total loss: 2.4894 timestamp: 1654918762.879292 iteration: 4560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29124 FastRCNN class loss: 0.14311 FastRCNN total loss: 0.43435 L1 loss: 0.0000e+00 L2 loss: 1.92528 Learning rate: 0.02 Mask loss: 0.272 RPN box loss: 0.08846 RPN score loss: 0.02207 RPN total loss: 0.11053 Total loss: 2.74216 timestamp: 1654918766.1837223 iteration: 4565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14968 FastRCNN class loss: 0.13597 FastRCNN total loss: 0.28564 L1 loss: 0.0000e+00 L2 loss: 1.92494 Learning rate: 0.02 Mask loss: 0.2109 RPN box loss: 0.05578 RPN score loss: 0.01199 RPN total loss: 0.06777 Total loss: 2.48925 timestamp: 1654918769.4139864 iteration: 4570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17962 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.25459 L1 loss: 0.0000e+00 L2 loss: 1.92457 Learning rate: 0.02 Mask loss: 0.1422 RPN box loss: 0.08157 RPN score loss: 0.00957 RPN total loss: 0.09114 Total loss: 2.4125 timestamp: 1654918772.6946611 iteration: 4575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17185 FastRCNN class loss: 0.09473 FastRCNN total loss: 0.26658 L1 loss: 0.0000e+00 L2 loss: 1.92421 Learning rate: 0.02 Mask loss: 0.19205 RPN box loss: 0.02054 RPN score loss: 0.00851 RPN total loss: 0.02904 Total loss: 2.41188 timestamp: 1654918775.9939258 iteration: 4580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22739 FastRCNN class loss: 0.14192 FastRCNN total loss: 0.36932 L1 loss: 0.0000e+00 L2 loss: 1.92385 Learning rate: 0.02 Mask loss: 0.2202 RPN box loss: 0.0388 RPN score loss: 0.0103 RPN total loss: 0.04911 Total loss: 2.56247 timestamp: 1654918779.252953 iteration: 4585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11724 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.1799 L1 loss: 0.0000e+00 L2 loss: 1.92349 Learning rate: 0.02 Mask loss: 0.12835 RPN box loss: 0.00387 RPN score loss: 0.00852 RPN total loss: 0.0124 Total loss: 2.24414 timestamp: 1654918782.5578876 iteration: 4590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09886 FastRCNN class loss: 0.05663 FastRCNN total loss: 0.15549 L1 loss: 0.0000e+00 L2 loss: 1.92314 Learning rate: 0.02 Mask loss: 0.16521 RPN box loss: 0.01144 RPN score loss: 0.00392 RPN total loss: 0.01536 Total loss: 2.25921 timestamp: 1654918785.7589004 iteration: 4595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19326 FastRCNN class loss: 0.10421 FastRCNN total loss: 0.29746 L1 loss: 0.0000e+00 L2 loss: 1.92277 Learning rate: 0.02 Mask loss: 0.23311 RPN box loss: 0.02401 RPN score loss: 0.01562 RPN total loss: 0.03962 Total loss: 2.49297 timestamp: 1654918788.9458747 iteration: 4600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14292 FastRCNN class loss: 0.08307 FastRCNN total loss: 0.22599 L1 loss: 0.0000e+00 L2 loss: 1.92238 Learning rate: 0.02 Mask loss: 0.17945 RPN box loss: 0.04431 RPN score loss: 0.0092 RPN total loss: 0.05351 Total loss: 2.38132 timestamp: 1654918792.1832082 iteration: 4605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20696 FastRCNN class loss: 0.12622 FastRCNN total loss: 0.33318 L1 loss: 0.0000e+00 L2 loss: 1.92202 Learning rate: 0.02 Mask loss: 0.25053 RPN box loss: 0.07034 RPN score loss: 0.01295 RPN total loss: 0.08329 Total loss: 2.58901 timestamp: 1654918795.443976 iteration: 4610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15315 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.22269 L1 loss: 0.0000e+00 L2 loss: 1.92168 Learning rate: 0.02 Mask loss: 0.16744 RPN box loss: 0.02469 RPN score loss: 0.02426 RPN total loss: 0.04894 Total loss: 2.36075 timestamp: 1654918798.6130762 iteration: 4615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16744 FastRCNN class loss: 0.0911 FastRCNN total loss: 0.25854 L1 loss: 0.0000e+00 L2 loss: 1.92133 Learning rate: 0.02 Mask loss: 0.17879 RPN box loss: 0.07402 RPN score loss: 0.01777 RPN total loss: 0.09179 Total loss: 2.45045 timestamp: 1654918801.853627 iteration: 4620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18405 FastRCNN class loss: 0.1186 FastRCNN total loss: 0.30265 L1 loss: 0.0000e+00 L2 loss: 1.92097 Learning rate: 0.02 Mask loss: 0.2576 RPN box loss: 0.02673 RPN score loss: 0.00837 RPN total loss: 0.0351 Total loss: 2.51632 timestamp: 1654918805.0497923 iteration: 4625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2268 FastRCNN class loss: 0.16661 FastRCNN total loss: 0.3934 L1 loss: 0.0000e+00 L2 loss: 1.92062 Learning rate: 0.02 Mask loss: 0.19443 RPN box loss: 0.01428 RPN score loss: 0.00632 RPN total loss: 0.0206 Total loss: 2.52905 timestamp: 1654918808.2797313 iteration: 4630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22104 FastRCNN class loss: 0.13093 FastRCNN total loss: 0.35196 L1 loss: 0.0000e+00 L2 loss: 1.92026 Learning rate: 0.02 Mask loss: 0.30767 RPN box loss: 0.05961 RPN score loss: 0.00968 RPN total loss: 0.06929 Total loss: 2.64918 timestamp: 1654918811.390762 iteration: 4635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15955 FastRCNN class loss: 0.09273 FastRCNN total loss: 0.25227 L1 loss: 0.0000e+00 L2 loss: 1.91989 Learning rate: 0.02 Mask loss: 0.23898 RPN box loss: 0.05664 RPN score loss: 0.00614 RPN total loss: 0.06278 Total loss: 2.47393 timestamp: 1654918814.6895094 iteration: 4640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21228 FastRCNN class loss: 0.12448 FastRCNN total loss: 0.33675 L1 loss: 0.0000e+00 L2 loss: 1.91955 Learning rate: 0.02 Mask loss: 0.18203 RPN box loss: 0.03694 RPN score loss: 0.01111 RPN total loss: 0.04804 Total loss: 2.48638 timestamp: 1654918818.0042617 iteration: 4645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1573 FastRCNN class loss: 0.13224 FastRCNN total loss: 0.28954 L1 loss: 0.0000e+00 L2 loss: 1.9192 Learning rate: 0.02 Mask loss: 0.17251 RPN box loss: 0.03342 RPN score loss: 0.00574 RPN total loss: 0.03915 Total loss: 2.4204 timestamp: 1654918821.2539027 iteration: 4650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20028 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.30063 L1 loss: 0.0000e+00 L2 loss: 1.91883 Learning rate: 0.02 Mask loss: 0.16654 RPN box loss: 0.0766 RPN score loss: 0.00706 RPN total loss: 0.08366 Total loss: 2.46967 timestamp: 1654918824.6791503 iteration: 4655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14423 FastRCNN class loss: 0.06293 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 1.91848 Learning rate: 0.02 Mask loss: 0.18754 RPN box loss: 0.01168 RPN score loss: 0.00553 RPN total loss: 0.01721 Total loss: 2.33039 timestamp: 1654918827.8669803 iteration: 4660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18075 FastRCNN class loss: 0.12657 FastRCNN total loss: 0.30732 L1 loss: 0.0000e+00 L2 loss: 1.91811 Learning rate: 0.02 Mask loss: 0.15918 RPN box loss: 0.05719 RPN score loss: 0.01197 RPN total loss: 0.06916 Total loss: 2.45377 timestamp: 1654918831.1620643 iteration: 4665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18013 FastRCNN class loss: 0.1326 FastRCNN total loss: 0.31273 L1 loss: 0.0000e+00 L2 loss: 1.91776 Learning rate: 0.02 Mask loss: 0.21463 RPN box loss: 0.0661 RPN score loss: 0.01408 RPN total loss: 0.08018 Total loss: 2.52529 timestamp: 1654918834.3053918 iteration: 4670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09317 FastRCNN class loss: 0.03671 FastRCNN total loss: 0.12988 L1 loss: 0.0000e+00 L2 loss: 1.91739 Learning rate: 0.02 Mask loss: 0.16264 RPN box loss: 0.03682 RPN score loss: 0.00253 RPN total loss: 0.03935 Total loss: 2.24926 timestamp: 1654918837.7577646 iteration: 4675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22896 FastRCNN class loss: 0.14438 FastRCNN total loss: 0.37334 L1 loss: 0.0000e+00 L2 loss: 1.91704 Learning rate: 0.02 Mask loss: 0.20639 RPN box loss: 0.09365 RPN score loss: 0.01198 RPN total loss: 0.10563 Total loss: 2.6024 timestamp: 1654918840.936533 iteration: 4680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27054 FastRCNN class loss: 0.13322 FastRCNN total loss: 0.40376 L1 loss: 0.0000e+00 L2 loss: 1.91669 Learning rate: 0.02 Mask loss: 0.23984 RPN box loss: 0.09391 RPN score loss: 0.01043 RPN total loss: 0.10434 Total loss: 2.66462 timestamp: 1654918844.261317 iteration: 4685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13869 FastRCNN class loss: 0.11343 FastRCNN total loss: 0.25212 L1 loss: 0.0000e+00 L2 loss: 1.91632 Learning rate: 0.02 Mask loss: 0.24689 RPN box loss: 0.0442 RPN score loss: 0.01652 RPN total loss: 0.06072 Total loss: 2.47605 timestamp: 1654918847.621167 iteration: 4690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13203 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.22467 L1 loss: 0.0000e+00 L2 loss: 1.91597 Learning rate: 0.02 Mask loss: 0.18637 RPN box loss: 0.02689 RPN score loss: 0.00937 RPN total loss: 0.03626 Total loss: 2.36328 timestamp: 1654918850.7887294 iteration: 4695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18593 FastRCNN class loss: 0.14213 FastRCNN total loss: 0.32805 L1 loss: 0.0000e+00 L2 loss: 1.91562 Learning rate: 0.02 Mask loss: 0.24377 RPN box loss: 0.02783 RPN score loss: 0.00878 RPN total loss: 0.03661 Total loss: 2.52405 timestamp: 1654918854.030074 iteration: 4700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29669 FastRCNN class loss: 0.15 FastRCNN total loss: 0.44669 L1 loss: 0.0000e+00 L2 loss: 1.91527 Learning rate: 0.02 Mask loss: 0.25848 RPN box loss: 0.07375 RPN score loss: 0.02848 RPN total loss: 0.10223 Total loss: 2.72267 timestamp: 1654918857.184289 iteration: 4705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12241 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.18429 L1 loss: 0.0000e+00 L2 loss: 1.9149 Learning rate: 0.02 Mask loss: 0.19986 RPN box loss: 0.0278 RPN score loss: 0.00456 RPN total loss: 0.03237 Total loss: 2.33141 timestamp: 1654918860.4781847 iteration: 4710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18684 FastRCNN class loss: 0.11575 FastRCNN total loss: 0.3026 L1 loss: 0.0000e+00 L2 loss: 1.91453 Learning rate: 0.02 Mask loss: 0.17474 RPN box loss: 0.08816 RPN score loss: 0.0337 RPN total loss: 0.12186 Total loss: 2.51373 timestamp: 1654918863.7116458 iteration: 4715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15392 FastRCNN class loss: 0.08389 FastRCNN total loss: 0.23781 L1 loss: 0.0000e+00 L2 loss: 1.91415 Learning rate: 0.02 Mask loss: 0.2181 RPN box loss: 0.03404 RPN score loss: 0.00844 RPN total loss: 0.04247 Total loss: 2.41254 timestamp: 1654918867.0214486 iteration: 4720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20538 FastRCNN class loss: 0.07452 FastRCNN total loss: 0.27991 L1 loss: 0.0000e+00 L2 loss: 1.91381 Learning rate: 0.02 Mask loss: 0.18782 RPN box loss: 0.05618 RPN score loss: 0.01082 RPN total loss: 0.067 Total loss: 2.44853 timestamp: 1654918870.2089531 iteration: 4725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1812 FastRCNN class loss: 0.09229 FastRCNN total loss: 0.27349 L1 loss: 0.0000e+00 L2 loss: 1.91346 Learning rate: 0.02 Mask loss: 0.16191 RPN box loss: 0.03487 RPN score loss: 0.0142 RPN total loss: 0.04907 Total loss: 2.39793 timestamp: 1654918873.5060494 iteration: 4730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21237 FastRCNN class loss: 0.16062 FastRCNN total loss: 0.37299 L1 loss: 0.0000e+00 L2 loss: 1.9131 Learning rate: 0.02 Mask loss: 0.25164 RPN box loss: 0.04209 RPN score loss: 0.02113 RPN total loss: 0.06322 Total loss: 2.60096 timestamp: 1654918876.7300036 iteration: 4735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13021 FastRCNN class loss: 0.06013 FastRCNN total loss: 0.19034 L1 loss: 0.0000e+00 L2 loss: 1.91276 Learning rate: 0.02 Mask loss: 0.15562 RPN box loss: 0.01651 RPN score loss: 0.00394 RPN total loss: 0.02044 Total loss: 2.27916 timestamp: 1654918880.0456035 iteration: 4740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21051 FastRCNN class loss: 0.10937 FastRCNN total loss: 0.31988 L1 loss: 0.0000e+00 L2 loss: 1.9124 Learning rate: 0.02 Mask loss: 0.18418 RPN box loss: 0.0492 RPN score loss: 0.00867 RPN total loss: 0.05787 Total loss: 2.47433 timestamp: 1654918883.267174 iteration: 4745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15348 FastRCNN class loss: 0.09796 FastRCNN total loss: 0.25144 L1 loss: 0.0000e+00 L2 loss: 1.91204 Learning rate: 0.02 Mask loss: 0.22671 RPN box loss: 0.06247 RPN score loss: 0.00915 RPN total loss: 0.07162 Total loss: 2.4618 timestamp: 1654918886.425015 iteration: 4750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15367 FastRCNN class loss: 0.09034 FastRCNN total loss: 0.24401 L1 loss: 0.0000e+00 L2 loss: 1.91167 Learning rate: 0.02 Mask loss: 0.15566 RPN box loss: 0.01968 RPN score loss: 0.00753 RPN total loss: 0.02721 Total loss: 2.33854 timestamp: 1654918889.685487 iteration: 4755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14197 FastRCNN class loss: 0.12655 FastRCNN total loss: 0.26851 L1 loss: 0.0000e+00 L2 loss: 1.91131 Learning rate: 0.02 Mask loss: 0.23409 RPN box loss: 0.04702 RPN score loss: 0.02308 RPN total loss: 0.07009 Total loss: 2.48401 timestamp: 1654918892.84929 iteration: 4760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25283 FastRCNN class loss: 0.12847 FastRCNN total loss: 0.38129 L1 loss: 0.0000e+00 L2 loss: 1.91094 Learning rate: 0.02 Mask loss: 0.27715 RPN box loss: 0.02966 RPN score loss: 0.00763 RPN total loss: 0.0373 Total loss: 2.60668 timestamp: 1654918896.1408203 iteration: 4765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13877 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.2223 L1 loss: 0.0000e+00 L2 loss: 1.91058 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.04239 RPN score loss: 0.00857 RPN total loss: 0.05095 Total loss: 2.31594 timestamp: 1654918899.3678327 iteration: 4770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1859 FastRCNN class loss: 0.18417 FastRCNN total loss: 0.37007 L1 loss: 0.0000e+00 L2 loss: 1.91022 Learning rate: 0.02 Mask loss: 0.27493 RPN box loss: 0.04719 RPN score loss: 0.0118 RPN total loss: 0.05899 Total loss: 2.61421 timestamp: 1654918902.6532652 iteration: 4775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16205 FastRCNN class loss: 0.07331 FastRCNN total loss: 0.23536 L1 loss: 0.0000e+00 L2 loss: 1.90987 Learning rate: 0.02 Mask loss: 0.46539 RPN box loss: 0.08828 RPN score loss: 0.01101 RPN total loss: 0.09929 Total loss: 2.70992 timestamp: 1654918905.7842305 iteration: 4780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16047 FastRCNN class loss: 0.13425 FastRCNN total loss: 0.29472 L1 loss: 0.0000e+00 L2 loss: 1.90951 Learning rate: 0.02 Mask loss: 0.20051 RPN box loss: 0.02885 RPN score loss: 0.02532 RPN total loss: 0.05417 Total loss: 2.45891 timestamp: 1654918909.1322346 iteration: 4785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18587 FastRCNN class loss: 0.10078 FastRCNN total loss: 0.28664 L1 loss: 0.0000e+00 L2 loss: 1.90914 Learning rate: 0.02 Mask loss: 0.2252 RPN box loss: 0.0846 RPN score loss: 0.01527 RPN total loss: 0.09987 Total loss: 2.52085 timestamp: 1654918912.3667395 iteration: 4790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13456 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.20038 L1 loss: 0.0000e+00 L2 loss: 1.9088 Learning rate: 0.02 Mask loss: 0.20677 RPN box loss: 0.01509 RPN score loss: 0.00473 RPN total loss: 0.01982 Total loss: 2.33578 timestamp: 1654918915.7085822 iteration: 4795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23175 FastRCNN class loss: 0.11896 FastRCNN total loss: 0.35072 L1 loss: 0.0000e+00 L2 loss: 1.90845 Learning rate: 0.02 Mask loss: 0.21462 RPN box loss: 0.03174 RPN score loss: 0.00856 RPN total loss: 0.0403 Total loss: 2.5141 timestamp: 1654918919.1794713 iteration: 4800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24421 FastRCNN class loss: 0.13221 FastRCNN total loss: 0.37642 L1 loss: 0.0000e+00 L2 loss: 1.90812 Learning rate: 0.02 Mask loss: 0.2445 RPN box loss: 0.04685 RPN score loss: 0.01258 RPN total loss: 0.05943 Total loss: 2.58847 timestamp: 1654918922.4420018 iteration: 4805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20865 FastRCNN class loss: 0.12329 FastRCNN total loss: 0.33194 L1 loss: 0.0000e+00 L2 loss: 1.90777 Learning rate: 0.02 Mask loss: 0.21999 RPN box loss: 0.06378 RPN score loss: 0.00744 RPN total loss: 0.07122 Total loss: 2.53092 timestamp: 1654918925.7063105 iteration: 4810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23617 FastRCNN class loss: 0.08829 FastRCNN total loss: 0.32447 L1 loss: 0.0000e+00 L2 loss: 1.90741 Learning rate: 0.02 Mask loss: 0.17747 RPN box loss: 0.0322 RPN score loss: 0.00493 RPN total loss: 0.03713 Total loss: 2.44647 timestamp: 1654918928.8866644 iteration: 4815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12815 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.20603 L1 loss: 0.0000e+00 L2 loss: 1.90705 Learning rate: 0.02 Mask loss: 0.15414 RPN box loss: 0.02759 RPN score loss: 0.01188 RPN total loss: 0.03947 Total loss: 2.30669 timestamp: 1654918932.279711 iteration: 4820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10139 FastRCNN class loss: 0.05107 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 1.9067 Learning rate: 0.02 Mask loss: 0.12844 RPN box loss: 0.01756 RPN score loss: 0.00614 RPN total loss: 0.0237 Total loss: 2.21129 timestamp: 1654918935.468442 iteration: 4825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26788 FastRCNN class loss: 0.17605 FastRCNN total loss: 0.44393 L1 loss: 0.0000e+00 L2 loss: 1.90636 Learning rate: 0.02 Mask loss: 0.31493 RPN box loss: 0.10842 RPN score loss: 0.01485 RPN total loss: 0.12327 Total loss: 2.78848 timestamp: 1654918938.766199 iteration: 4830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21026 FastRCNN class loss: 0.0826 FastRCNN total loss: 0.29286 L1 loss: 0.0000e+00 L2 loss: 1.906 Learning rate: 0.02 Mask loss: 0.15422 RPN box loss: 0.02666 RPN score loss: 0.00519 RPN total loss: 0.03185 Total loss: 2.38493 timestamp: 1654918941.8976717 iteration: 4835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19544 FastRCNN class loss: 0.12153 FastRCNN total loss: 0.31697 L1 loss: 0.0000e+00 L2 loss: 1.90564 Learning rate: 0.02 Mask loss: 0.15157 RPN box loss: 0.06616 RPN score loss: 0.02083 RPN total loss: 0.08699 Total loss: 2.46117 timestamp: 1654918945.2064843 iteration: 4840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.147 FastRCNN class loss: 0.07099 FastRCNN total loss: 0.218 L1 loss: 0.0000e+00 L2 loss: 1.90528 Learning rate: 0.02 Mask loss: 0.15586 RPN box loss: 0.04044 RPN score loss: 0.00439 RPN total loss: 0.04484 Total loss: 2.32397 timestamp: 1654918948.4671497 iteration: 4845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11342 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.1653 L1 loss: 0.0000e+00 L2 loss: 1.90491 Learning rate: 0.02 Mask loss: 0.13299 RPN box loss: 0.01072 RPN score loss: 0.00513 RPN total loss: 0.01585 Total loss: 2.21904 timestamp: 1654918951.7664428 iteration: 4850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14244 FastRCNN class loss: 0.12127 FastRCNN total loss: 0.26371 L1 loss: 0.0000e+00 L2 loss: 1.90453 Learning rate: 0.02 Mask loss: 0.18436 RPN box loss: 0.02691 RPN score loss: 0.0107 RPN total loss: 0.03761 Total loss: 2.3902 timestamp: 1654918955.1444511 iteration: 4855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13172 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.20164 L1 loss: 0.0000e+00 L2 loss: 1.90416 Learning rate: 0.02 Mask loss: 0.26551 RPN box loss: 0.04487 RPN score loss: 0.00381 RPN total loss: 0.04868 Total loss: 2.41999 timestamp: 1654918958.3105605 iteration: 4860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20591 FastRCNN class loss: 0.10571 FastRCNN total loss: 0.31162 L1 loss: 0.0000e+00 L2 loss: 1.9038 Learning rate: 0.02 Mask loss: 0.18447 RPN box loss: 0.02858 RPN score loss: 0.0084 RPN total loss: 0.03698 Total loss: 2.43687 timestamp: 1654918961.5705903 iteration: 4865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21859 FastRCNN class loss: 0.10303 FastRCNN total loss: 0.32162 L1 loss: 0.0000e+00 L2 loss: 1.90346 Learning rate: 0.02 Mask loss: 0.22532 RPN box loss: 0.02758 RPN score loss: 0.03986 RPN total loss: 0.06744 Total loss: 2.51784 timestamp: 1654918964.7381258 iteration: 4870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18509 FastRCNN class loss: 0.09117 FastRCNN total loss: 0.27627 L1 loss: 0.0000e+00 L2 loss: 1.90312 Learning rate: 0.02 Mask loss: 0.15262 RPN box loss: 0.02328 RPN score loss: 0.01579 RPN total loss: 0.03907 Total loss: 2.37108 timestamp: 1654918967.9493904 iteration: 4875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19533 FastRCNN class loss: 0.11708 FastRCNN total loss: 0.3124 L1 loss: 0.0000e+00 L2 loss: 1.90277 Learning rate: 0.02 Mask loss: 0.20699 RPN box loss: 0.02884 RPN score loss: 0.01307 RPN total loss: 0.04191 Total loss: 2.46407 timestamp: 1654918971.1103706 iteration: 4880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23445 FastRCNN class loss: 0.17553 FastRCNN total loss: 0.40998 L1 loss: 0.0000e+00 L2 loss: 1.9024 Learning rate: 0.02 Mask loss: 0.35718 RPN box loss: 0.02719 RPN score loss: 0.0088 RPN total loss: 0.03599 Total loss: 2.70555 timestamp: 1654918974.4069264 iteration: 4885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21243 FastRCNN class loss: 0.14969 FastRCNN total loss: 0.36213 L1 loss: 0.0000e+00 L2 loss: 1.90204 Learning rate: 0.02 Mask loss: 0.1901 RPN box loss: 0.0675 RPN score loss: 0.00683 RPN total loss: 0.07433 Total loss: 2.5286 timestamp: 1654918977.607136 iteration: 4890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17061 FastRCNN class loss: 0.08956 FastRCNN total loss: 0.26016 L1 loss: 0.0000e+00 L2 loss: 1.90167 Learning rate: 0.02 Mask loss: 0.09852 RPN box loss: 0.01179 RPN score loss: 0.0064 RPN total loss: 0.0182 Total loss: 2.27855 timestamp: 1654918980.9825916 iteration: 4895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15345 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.23747 L1 loss: 0.0000e+00 L2 loss: 1.90131 Learning rate: 0.02 Mask loss: 0.17995 RPN box loss: 0.0432 RPN score loss: 0.01158 RPN total loss: 0.05478 Total loss: 2.3735 timestamp: 1654918984.131287 iteration: 4900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21921 FastRCNN class loss: 0.08664 FastRCNN total loss: 0.30585 L1 loss: 0.0000e+00 L2 loss: 1.90096 Learning rate: 0.02 Mask loss: 0.22225 RPN box loss: 0.01399 RPN score loss: 0.01362 RPN total loss: 0.02761 Total loss: 2.45668 timestamp: 1654918987.4310067 iteration: 4905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1622 FastRCNN class loss: 0.09493 FastRCNN total loss: 0.25714 L1 loss: 0.0000e+00 L2 loss: 1.9006 Learning rate: 0.02 Mask loss: 0.18943 RPN box loss: 0.08192 RPN score loss: 0.00687 RPN total loss: 0.08879 Total loss: 2.43596 timestamp: 1654918990.6664464 iteration: 4910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1509 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.20679 L1 loss: 0.0000e+00 L2 loss: 1.90027 Learning rate: 0.02 Mask loss: 0.12673 RPN box loss: 0.02806 RPN score loss: 0.00443 RPN total loss: 0.03249 Total loss: 2.26628 timestamp: 1654918993.912806 iteration: 4915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19331 FastRCNN class loss: 0.09577 FastRCNN total loss: 0.28909 L1 loss: 0.0000e+00 L2 loss: 1.89992 Learning rate: 0.02 Mask loss: 0.23491 RPN box loss: 0.06701 RPN score loss: 0.01273 RPN total loss: 0.07974 Total loss: 2.50365 timestamp: 1654918997.3395996 iteration: 4920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13917 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.1965 L1 loss: 0.0000e+00 L2 loss: 1.89957 Learning rate: 0.02 Mask loss: 0.15431 RPN box loss: 0.01537 RPN score loss: 0.00439 RPN total loss: 0.01976 Total loss: 2.27013 timestamp: 1654919000.512616 iteration: 4925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19048 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.26097 L1 loss: 0.0000e+00 L2 loss: 1.89921 Learning rate: 0.02 Mask loss: 0.13495 RPN box loss: 0.02105 RPN score loss: 0.00736 RPN total loss: 0.02841 Total loss: 2.32354 timestamp: 1654919004.0553348 iteration: 4930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22165 FastRCNN class loss: 0.12679 FastRCNN total loss: 0.34844 L1 loss: 0.0000e+00 L2 loss: 1.89886 Learning rate: 0.02 Mask loss: 0.18402 RPN box loss: 0.06143 RPN score loss: 0.0134 RPN total loss: 0.07483 Total loss: 2.50615 timestamp: 1654919007.2802768 iteration: 4935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13353 FastRCNN class loss: 0.06384 FastRCNN total loss: 0.19737 L1 loss: 0.0000e+00 L2 loss: 1.8985 Learning rate: 0.02 Mask loss: 0.20471 RPN box loss: 0.10288 RPN score loss: 0.00853 RPN total loss: 0.11141 Total loss: 2.41199 timestamp: 1654919010.625228 iteration: 4940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16536 FastRCNN class loss: 0.05933 FastRCNN total loss: 0.22469 L1 loss: 0.0000e+00 L2 loss: 1.89813 Learning rate: 0.02 Mask loss: 0.17294 RPN box loss: 0.06241 RPN score loss: 0.00741 RPN total loss: 0.06982 Total loss: 2.36558 timestamp: 1654919013.7976904 iteration: 4945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17384 FastRCNN class loss: 0.11516 FastRCNN total loss: 0.289 L1 loss: 0.0000e+00 L2 loss: 1.89779 Learning rate: 0.02 Mask loss: 0.20414 RPN box loss: 0.08763 RPN score loss: 0.0137 RPN total loss: 0.10133 Total loss: 2.49226 timestamp: 1654919017.1142528 iteration: 4950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22553 FastRCNN class loss: 0.20703 FastRCNN total loss: 0.43257 L1 loss: 0.0000e+00 L2 loss: 1.89744 Learning rate: 0.02 Mask loss: 0.25946 RPN box loss: 0.10584 RPN score loss: 0.02199 RPN total loss: 0.12782 Total loss: 2.71729 timestamp: 1654919020.4619021 iteration: 4955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2111 FastRCNN class loss: 0.08253 FastRCNN total loss: 0.29363 L1 loss: 0.0000e+00 L2 loss: 1.89709 Learning rate: 0.02 Mask loss: 0.18247 RPN box loss: 0.01955 RPN score loss: 0.00503 RPN total loss: 0.02458 Total loss: 2.39778 timestamp: 1654919023.643371 iteration: 4960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14063 FastRCNN class loss: 0.10617 FastRCNN total loss: 0.24679 L1 loss: 0.0000e+00 L2 loss: 1.89674 Learning rate: 0.02 Mask loss: 0.19046 RPN box loss: 0.02821 RPN score loss: 0.00486 RPN total loss: 0.03307 Total loss: 2.36707 timestamp: 1654919026.8663874 iteration: 4965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20358 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.27043 L1 loss: 0.0000e+00 L2 loss: 1.89638 Learning rate: 0.02 Mask loss: 0.29089 RPN box loss: 0.01602 RPN score loss: 0.00503 RPN total loss: 0.02105 Total loss: 2.47874 timestamp: 1654919030.0473971 iteration: 4970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17915 FastRCNN class loss: 0.12523 FastRCNN total loss: 0.30438 L1 loss: 0.0000e+00 L2 loss: 1.89602 Learning rate: 0.02 Mask loss: 0.17297 RPN box loss: 0.06301 RPN score loss: 0.01285 RPN total loss: 0.07586 Total loss: 2.44923 timestamp: 1654919033.2368793 iteration: 4975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24197 FastRCNN class loss: 0.12703 FastRCNN total loss: 0.369 L1 loss: 0.0000e+00 L2 loss: 1.89567 Learning rate: 0.02 Mask loss: 0.26727 RPN box loss: 0.06151 RPN score loss: 0.01246 RPN total loss: 0.07397 Total loss: 2.60591 timestamp: 1654919036.441653 iteration: 4980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23978 FastRCNN class loss: 0.12167 FastRCNN total loss: 0.36145 L1 loss: 0.0000e+00 L2 loss: 1.89531 Learning rate: 0.02 Mask loss: 0.19674 RPN box loss: 0.05253 RPN score loss: 0.01498 RPN total loss: 0.06751 Total loss: 2.52101 timestamp: 1654919039.6842253 iteration: 4985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12836 FastRCNN class loss: 0.09017 FastRCNN total loss: 0.21852 L1 loss: 0.0000e+00 L2 loss: 1.89493 Learning rate: 0.02 Mask loss: 0.15384 RPN box loss: 0.08271 RPN score loss: 0.0147 RPN total loss: 0.09741 Total loss: 2.36471 timestamp: 1654919042.9418693 iteration: 4990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25663 FastRCNN class loss: 0.11092 FastRCNN total loss: 0.36755 L1 loss: 0.0000e+00 L2 loss: 1.89456 Learning rate: 0.02 Mask loss: 0.18502 RPN box loss: 0.09578 RPN score loss: 0.01086 RPN total loss: 0.10664 Total loss: 2.55378 timestamp: 1654919046.198724 iteration: 4995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20181 FastRCNN class loss: 0.14974 FastRCNN total loss: 0.35155 L1 loss: 0.0000e+00 L2 loss: 1.89423 Learning rate: 0.02 Mask loss: 0.30631 RPN box loss: 0.01933 RPN score loss: 0.00731 RPN total loss: 0.02664 Total loss: 2.57872 timestamp: 1654919049.4251225 iteration: 5000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20135 FastRCNN class loss: 0.12832 FastRCNN total loss: 0.32967 L1 loss: 0.0000e+00 L2 loss: 1.89389 Learning rate: 0.02 Mask loss: 0.19515 RPN box loss: 0.03254 RPN score loss: 0.01427 RPN total loss: 0.04682 Total loss: 2.46553 timestamp: 1654919052.7462468 iteration: 5005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20118 FastRCNN class loss: 0.12494 FastRCNN total loss: 0.32612 L1 loss: 0.0000e+00 L2 loss: 1.89355 Learning rate: 0.02 Mask loss: 0.18783 RPN box loss: 0.05307 RPN score loss: 0.06024 RPN total loss: 0.11331 Total loss: 2.52081 timestamp: 1654919055.8866978 iteration: 5010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19507 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.2761 L1 loss: 0.0000e+00 L2 loss: 1.89317 Learning rate: 0.02 Mask loss: 0.21959 RPN box loss: 0.04502 RPN score loss: 0.0087 RPN total loss: 0.05373 Total loss: 2.44258 timestamp: 1654919059.073826 iteration: 5015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18724 FastRCNN class loss: 0.1121 FastRCNN total loss: 0.29935 L1 loss: 0.0000e+00 L2 loss: 1.89281 Learning rate: 0.02 Mask loss: 0.31664 RPN box loss: 0.10536 RPN score loss: 0.01841 RPN total loss: 0.12377 Total loss: 2.63257 timestamp: 1654919062.4267018 iteration: 5020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15842 FastRCNN class loss: 0.07778 FastRCNN total loss: 0.2362 L1 loss: 0.0000e+00 L2 loss: 1.89245 Learning rate: 0.02 Mask loss: 0.12138 RPN box loss: 0.00692 RPN score loss: 0.00414 RPN total loss: 0.01107 Total loss: 2.26109 timestamp: 1654919065.7230663 iteration: 5025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18372 FastRCNN class loss: 0.12418 FastRCNN total loss: 0.3079 L1 loss: 0.0000e+00 L2 loss: 1.89211 Learning rate: 0.02 Mask loss: 0.28477 RPN box loss: 0.03195 RPN score loss: 0.01605 RPN total loss: 0.04801 Total loss: 2.53279 timestamp: 1654919068.9308429 iteration: 5030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17767 FastRCNN class loss: 0.07207 FastRCNN total loss: 0.24974 L1 loss: 0.0000e+00 L2 loss: 1.89177 Learning rate: 0.02 Mask loss: 0.1403 RPN box loss: 0.01217 RPN score loss: 0.00483 RPN total loss: 0.017 Total loss: 2.2988 timestamp: 1654919072.1229537 iteration: 5035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15933 FastRCNN class loss: 0.07248 FastRCNN total loss: 0.2318 L1 loss: 0.0000e+00 L2 loss: 1.89143 Learning rate: 0.02 Mask loss: 0.20871 RPN box loss: 0.07815 RPN score loss: 0.01212 RPN total loss: 0.09027 Total loss: 2.4222 timestamp: 1654919075.3669374 iteration: 5040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23711 FastRCNN class loss: 0.13662 FastRCNN total loss: 0.37373 L1 loss: 0.0000e+00 L2 loss: 1.89111 Learning rate: 0.02 Mask loss: 0.23322 RPN box loss: 0.06095 RPN score loss: 0.03626 RPN total loss: 0.09722 Total loss: 2.59528 timestamp: 1654919078.5501258 iteration: 5045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12319 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.18958 L1 loss: 0.0000e+00 L2 loss: 1.89076 Learning rate: 0.02 Mask loss: 0.09919 RPN box loss: 0.03083 RPN score loss: 0.00514 RPN total loss: 0.03596 Total loss: 2.21549 timestamp: 1654919081.8654583 iteration: 5050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1399 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.21817 L1 loss: 0.0000e+00 L2 loss: 1.89039 Learning rate: 0.02 Mask loss: 0.16517 RPN box loss: 0.04572 RPN score loss: 0.00442 RPN total loss: 0.05014 Total loss: 2.32387 timestamp: 1654919085.1179075 iteration: 5055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20204 FastRCNN class loss: 0.10297 FastRCNN total loss: 0.30501 L1 loss: 0.0000e+00 L2 loss: 1.89004 Learning rate: 0.02 Mask loss: 0.16157 RPN box loss: 0.02373 RPN score loss: 0.00437 RPN total loss: 0.0281 Total loss: 2.38471 timestamp: 1654919088.3968012 iteration: 5060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12524 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.20855 L1 loss: 0.0000e+00 L2 loss: 1.88968 Learning rate: 0.02 Mask loss: 0.18486 RPN box loss: 0.08471 RPN score loss: 0.00634 RPN total loss: 0.09106 Total loss: 2.37415 timestamp: 1654919091.5392659 iteration: 5065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23147 FastRCNN class loss: 0.088 FastRCNN total loss: 0.31947 L1 loss: 0.0000e+00 L2 loss: 1.88932 Learning rate: 0.02 Mask loss: 0.16408 RPN box loss: 0.04572 RPN score loss: 0.01414 RPN total loss: 0.05986 Total loss: 2.43273 timestamp: 1654919094.9795687 iteration: 5070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19256 FastRCNN class loss: 0.1396 FastRCNN total loss: 0.33216 L1 loss: 0.0000e+00 L2 loss: 1.88898 Learning rate: 0.02 Mask loss: 0.19447 RPN box loss: 0.04381 RPN score loss: 0.00838 RPN total loss: 0.0522 Total loss: 2.46781 timestamp: 1654919098.2158382 iteration: 5075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21632 FastRCNN class loss: 0.10485 FastRCNN total loss: 0.32117 L1 loss: 0.0000e+00 L2 loss: 1.88864 Learning rate: 0.02 Mask loss: 0.43593 RPN box loss: 0.02698 RPN score loss: 0.00711 RPN total loss: 0.03409 Total loss: 2.67983 timestamp: 1654919101.3359826 iteration: 5080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15223 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.2345 L1 loss: 0.0000e+00 L2 loss: 1.88827 Learning rate: 0.02 Mask loss: 0.14283 RPN box loss: 0.02963 RPN score loss: 0.01415 RPN total loss: 0.04378 Total loss: 2.30938 timestamp: 1654919104.6098728 iteration: 5085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19596 FastRCNN class loss: 0.13183 FastRCNN total loss: 0.32779 L1 loss: 0.0000e+00 L2 loss: 1.88791 Learning rate: 0.02 Mask loss: 0.20989 RPN box loss: 0.0239 RPN score loss: 0.01077 RPN total loss: 0.03467 Total loss: 2.46026 timestamp: 1654919107.7846656 iteration: 5090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11659 FastRCNN class loss: 0.08261 FastRCNN total loss: 0.1992 L1 loss: 0.0000e+00 L2 loss: 1.88758 Learning rate: 0.02 Mask loss: 0.21743 RPN box loss: 0.01744 RPN score loss: 0.00792 RPN total loss: 0.02536 Total loss: 2.32957 timestamp: 1654919111.1032152 iteration: 5095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18933 FastRCNN class loss: 0.10721 FastRCNN total loss: 0.29654 L1 loss: 0.0000e+00 L2 loss: 1.88722 Learning rate: 0.02 Mask loss: 0.16269 RPN box loss: 0.06103 RPN score loss: 0.01644 RPN total loss: 0.07747 Total loss: 2.42392 timestamp: 1654919114.348476 iteration: 5100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24311 FastRCNN class loss: 0.11085 FastRCNN total loss: 0.35396 L1 loss: 0.0000e+00 L2 loss: 1.88688 Learning rate: 0.02 Mask loss: 0.14237 RPN box loss: 0.0292 RPN score loss: 0.01088 RPN total loss: 0.04009 Total loss: 2.4233 timestamp: 1654919117.6894882 iteration: 5105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18491 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.2423 L1 loss: 0.0000e+00 L2 loss: 1.88655 Learning rate: 0.02 Mask loss: 0.13205 RPN box loss: 0.01605 RPN score loss: 0.00292 RPN total loss: 0.01897 Total loss: 2.27987 timestamp: 1654919120.925243 iteration: 5110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1876 FastRCNN class loss: 0.10169 FastRCNN total loss: 0.28929 L1 loss: 0.0000e+00 L2 loss: 1.88623 Learning rate: 0.02 Mask loss: 0.21091 RPN box loss: 0.04016 RPN score loss: 0.0097 RPN total loss: 0.04986 Total loss: 2.4363 timestamp: 1654919124.313039 iteration: 5115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22692 FastRCNN class loss: 0.11786 FastRCNN total loss: 0.34478 L1 loss: 0.0000e+00 L2 loss: 1.88588 Learning rate: 0.02 Mask loss: 0.19395 RPN box loss: 0.07014 RPN score loss: 0.00892 RPN total loss: 0.07906 Total loss: 2.50366 timestamp: 1654919127.621997 iteration: 5120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18056 FastRCNN class loss: 0.09162 FastRCNN total loss: 0.27218 L1 loss: 0.0000e+00 L2 loss: 1.88552 Learning rate: 0.02 Mask loss: 0.2306 RPN box loss: 0.01886 RPN score loss: 0.00821 RPN total loss: 0.02707 Total loss: 2.41537 timestamp: 1654919130.7769227 iteration: 5125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13721 FastRCNN class loss: 0.07121 FastRCNN total loss: 0.20842 L1 loss: 0.0000e+00 L2 loss: 1.88517 Learning rate: 0.02 Mask loss: 0.15673 RPN box loss: 0.01052 RPN score loss: 0.00452 RPN total loss: 0.01505 Total loss: 2.26537 timestamp: 1654919134.1862981 iteration: 5130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14852 FastRCNN class loss: 0.09519 FastRCNN total loss: 0.24371 L1 loss: 0.0000e+00 L2 loss: 1.88478 Learning rate: 0.02 Mask loss: 0.15405 RPN box loss: 0.06076 RPN score loss: 0.01134 RPN total loss: 0.07209 Total loss: 2.35463 timestamp: 1654919137.3648403 iteration: 5135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.1109 FastRCNN total loss: 0.26951 L1 loss: 0.0000e+00 L2 loss: 1.88443 Learning rate: 0.02 Mask loss: 0.17371 RPN box loss: 0.08112 RPN score loss: 0.01101 RPN total loss: 0.09213 Total loss: 2.41978 timestamp: 1654919140.7223954 iteration: 5140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20416 FastRCNN class loss: 0.08431 FastRCNN total loss: 0.28847 L1 loss: 0.0000e+00 L2 loss: 1.8841 Learning rate: 0.02 Mask loss: 0.17517 RPN box loss: 0.01351 RPN score loss: 0.00257 RPN total loss: 0.01608 Total loss: 2.36383 timestamp: 1654919143.9398441 iteration: 5145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18656 FastRCNN class loss: 0.10569 FastRCNN total loss: 0.29224 L1 loss: 0.0000e+00 L2 loss: 1.88376 Learning rate: 0.02 Mask loss: 0.18463 RPN box loss: 0.0372 RPN score loss: 0.01004 RPN total loss: 0.04724 Total loss: 2.40788 timestamp: 1654919147.2148452 iteration: 5150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23247 FastRCNN class loss: 0.14674 FastRCNN total loss: 0.37921 L1 loss: 0.0000e+00 L2 loss: 1.88342 Learning rate: 0.02 Mask loss: 0.26895 RPN box loss: 0.02464 RPN score loss: 0.00811 RPN total loss: 0.03275 Total loss: 2.56433 timestamp: 1654919150.4773414 iteration: 5155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16833 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.2389 L1 loss: 0.0000e+00 L2 loss: 1.88305 Learning rate: 0.02 Mask loss: 0.11807 RPN box loss: 0.04168 RPN score loss: 0.01381 RPN total loss: 0.05549 Total loss: 2.29551 timestamp: 1654919153.9158342 iteration: 5160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2347 FastRCNN class loss: 0.12886 FastRCNN total loss: 0.36356 L1 loss: 0.0000e+00 L2 loss: 1.88271 Learning rate: 0.02 Mask loss: 0.13888 RPN box loss: 0.02294 RPN score loss: 0.01036 RPN total loss: 0.0333 Total loss: 2.41844 timestamp: 1654919157.1909685 iteration: 5165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15707 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.25291 L1 loss: 0.0000e+00 L2 loss: 1.88237 Learning rate: 0.02 Mask loss: 0.16289 RPN box loss: 0.02728 RPN score loss: 0.00517 RPN total loss: 0.03245 Total loss: 2.33062 timestamp: 1654919160.5370588 iteration: 5170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24351 FastRCNN class loss: 0.17422 FastRCNN total loss: 0.41774 L1 loss: 0.0000e+00 L2 loss: 1.88203 Learning rate: 0.02 Mask loss: 0.27364 RPN box loss: 0.03197 RPN score loss: 0.01357 RPN total loss: 0.04554 Total loss: 2.61895 timestamp: 1654919163.9658575 iteration: 5175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23379 FastRCNN class loss: 0.11347 FastRCNN total loss: 0.34725 L1 loss: 0.0000e+00 L2 loss: 1.88168 Learning rate: 0.02 Mask loss: 0.16752 RPN box loss: 0.04102 RPN score loss: 0.00958 RPN total loss: 0.0506 Total loss: 2.44705 timestamp: 1654919167.1824555 iteration: 5180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.225 FastRCNN class loss: 0.13977 FastRCNN total loss: 0.36478 L1 loss: 0.0000e+00 L2 loss: 1.88135 Learning rate: 0.02 Mask loss: 0.24442 RPN box loss: 0.03333 RPN score loss: 0.01284 RPN total loss: 0.04617 Total loss: 2.53671 timestamp: 1654919170.4877396 iteration: 5185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18792 FastRCNN class loss: 0.08147 FastRCNN total loss: 0.2694 L1 loss: 0.0000e+00 L2 loss: 1.88099 Learning rate: 0.02 Mask loss: 0.22068 RPN box loss: 0.03122 RPN score loss: 0.01366 RPN total loss: 0.04487 Total loss: 2.41594 timestamp: 1654919173.6345756 iteration: 5190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28176 FastRCNN class loss: 0.13586 FastRCNN total loss: 0.41762 L1 loss: 0.0000e+00 L2 loss: 1.88064 Learning rate: 0.02 Mask loss: 0.31461 RPN box loss: 0.01722 RPN score loss: 0.00511 RPN total loss: 0.02233 Total loss: 2.63521 timestamp: 1654919177.009296 iteration: 5195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15604 FastRCNN class loss: 0.09444 FastRCNN total loss: 0.25047 L1 loss: 0.0000e+00 L2 loss: 1.88028 Learning rate: 0.02 Mask loss: 0.16209 RPN box loss: 0.11107 RPN score loss: 0.00531 RPN total loss: 0.11638 Total loss: 2.40922 timestamp: 1654919180.20297 iteration: 5200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2308 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.32213 L1 loss: 0.0000e+00 L2 loss: 1.87992 Learning rate: 0.02 Mask loss: 0.1986 RPN box loss: 0.02515 RPN score loss: 0.00699 RPN total loss: 0.03214 Total loss: 2.43279 timestamp: 1654919183.4840004 iteration: 5205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12328 FastRCNN class loss: 0.13159 FastRCNN total loss: 0.25487 L1 loss: 0.0000e+00 L2 loss: 1.87956 Learning rate: 0.02 Mask loss: 0.23824 RPN box loss: 0.00981 RPN score loss: 0.00427 RPN total loss: 0.01409 Total loss: 2.38676 timestamp: 1654919186.6772575 iteration: 5210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27859 FastRCNN class loss: 0.10466 FastRCNN total loss: 0.38326 L1 loss: 0.0000e+00 L2 loss: 1.87921 Learning rate: 0.02 Mask loss: 0.18318 RPN box loss: 0.0607 RPN score loss: 0.00881 RPN total loss: 0.0695 Total loss: 2.51515 timestamp: 1654919189.98436 iteration: 5215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29316 FastRCNN class loss: 0.1159 FastRCNN total loss: 0.40906 L1 loss: 0.0000e+00 L2 loss: 1.87886 Learning rate: 0.02 Mask loss: 0.25659 RPN box loss: 0.05435 RPN score loss: 0.0178 RPN total loss: 0.07215 Total loss: 2.61665 timestamp: 1654919193.2366543 iteration: 5220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20406 FastRCNN class loss: 0.09368 FastRCNN total loss: 0.29774 L1 loss: 0.0000e+00 L2 loss: 1.87854 Learning rate: 0.02 Mask loss: 0.15953 RPN box loss: 0.05674 RPN score loss: 0.02591 RPN total loss: 0.08265 Total loss: 2.41846 timestamp: 1654919196.4964454 iteration: 5225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2916 FastRCNN class loss: 0.15694 FastRCNN total loss: 0.44855 L1 loss: 0.0000e+00 L2 loss: 1.87818 Learning rate: 0.02 Mask loss: 0.29437 RPN box loss: 0.06133 RPN score loss: 0.0253 RPN total loss: 0.08662 Total loss: 2.70771 timestamp: 1654919199.727517 iteration: 5230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15987 FastRCNN class loss: 0.11236 FastRCNN total loss: 0.27222 L1 loss: 0.0000e+00 L2 loss: 1.87783 Learning rate: 0.02 Mask loss: 0.29188 RPN box loss: 0.04027 RPN score loss: 0.0216 RPN total loss: 0.06187 Total loss: 2.5038 timestamp: 1654919202.9703379 iteration: 5235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15334 FastRCNN class loss: 0.11423 FastRCNN total loss: 0.26757 L1 loss: 0.0000e+00 L2 loss: 1.87748 Learning rate: 0.02 Mask loss: 0.14945 RPN box loss: 0.04373 RPN score loss: 0.018 RPN total loss: 0.06174 Total loss: 2.35623 timestamp: 1654919206.2980306 iteration: 5240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08256 FastRCNN class loss: 0.08325 FastRCNN total loss: 0.16581 L1 loss: 0.0000e+00 L2 loss: 1.8771 Learning rate: 0.02 Mask loss: 0.14392 RPN box loss: 0.07955 RPN score loss: 0.02195 RPN total loss: 0.1015 Total loss: 2.28832 timestamp: 1654919209.4739938 iteration: 5245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12246 FastRCNN class loss: 0.08746 FastRCNN total loss: 0.20992 L1 loss: 0.0000e+00 L2 loss: 1.87674 Learning rate: 0.02 Mask loss: 0.17735 RPN box loss: 0.06989 RPN score loss: 0.00864 RPN total loss: 0.07853 Total loss: 2.34254 timestamp: 1654919212.7656662 iteration: 5250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21014 FastRCNN class loss: 0.085 FastRCNN total loss: 0.29514 L1 loss: 0.0000e+00 L2 loss: 1.87639 Learning rate: 0.02 Mask loss: 0.20646 RPN box loss: 0.08859 RPN score loss: 0.00955 RPN total loss: 0.09814 Total loss: 2.47614 timestamp: 1654919215.934045 iteration: 5255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.276 FastRCNN class loss: 0.10327 FastRCNN total loss: 0.37927 L1 loss: 0.0000e+00 L2 loss: 1.87606 Learning rate: 0.02 Mask loss: 0.19338 RPN box loss: 0.01071 RPN score loss: 0.00748 RPN total loss: 0.01819 Total loss: 2.4669 timestamp: 1654919219.2752085 iteration: 5260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15153 FastRCNN class loss: 0.11883 FastRCNN total loss: 0.27036 L1 loss: 0.0000e+00 L2 loss: 1.87573 Learning rate: 0.02 Mask loss: 0.20394 RPN box loss: 0.025 RPN score loss: 0.01117 RPN total loss: 0.03617 Total loss: 2.3862 timestamp: 1654919222.4681818 iteration: 5265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11707 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.19203 L1 loss: 0.0000e+00 L2 loss: 1.87538 Learning rate: 0.02 Mask loss: 0.13296 RPN box loss: 0.03541 RPN score loss: 0.0052 RPN total loss: 0.04061 Total loss: 2.24098 timestamp: 1654919225.6726668 iteration: 5270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13324 FastRCNN class loss: 0.09554 FastRCNN total loss: 0.22878 L1 loss: 0.0000e+00 L2 loss: 1.87503 Learning rate: 0.02 Mask loss: 0.25886 RPN box loss: 0.06084 RPN score loss: 0.00663 RPN total loss: 0.06747 Total loss: 2.43014 timestamp: 1654919228.80948 iteration: 5275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23045 FastRCNN class loss: 0.09409 FastRCNN total loss: 0.32453 L1 loss: 0.0000e+00 L2 loss: 1.87468 Learning rate: 0.02 Mask loss: 0.20047 RPN box loss: 0.06139 RPN score loss: 0.009 RPN total loss: 0.07039 Total loss: 2.47008 timestamp: 1654919231.9762263 iteration: 5280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2223 FastRCNN class loss: 0.13212 FastRCNN total loss: 0.35442 L1 loss: 0.0000e+00 L2 loss: 1.87433 Learning rate: 0.02 Mask loss: 0.148 RPN box loss: 0.0623 RPN score loss: 0.01707 RPN total loss: 0.07936 Total loss: 2.45611 timestamp: 1654919235.3491418 iteration: 5285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19971 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.27175 L1 loss: 0.0000e+00 L2 loss: 1.87398 Learning rate: 0.02 Mask loss: 0.16089 RPN box loss: 0.02866 RPN score loss: 0.00604 RPN total loss: 0.0347 Total loss: 2.34132 timestamp: 1654919238.5326822 iteration: 5290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21538 FastRCNN class loss: 0.06418 FastRCNN total loss: 0.27957 L1 loss: 0.0000e+00 L2 loss: 1.87363 Learning rate: 0.02 Mask loss: 0.11707 RPN box loss: 0.01942 RPN score loss: 0.00902 RPN total loss: 0.02844 Total loss: 2.2987 timestamp: 1654919241.8269398 iteration: 5295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20238 FastRCNN class loss: 0.12864 FastRCNN total loss: 0.33102 L1 loss: 0.0000e+00 L2 loss: 1.87329 Learning rate: 0.02 Mask loss: 0.19018 RPN box loss: 0.11667 RPN score loss: 0.00539 RPN total loss: 0.12206 Total loss: 2.51655 timestamp: 1654919245.041643 iteration: 5300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15968 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.23434 L1 loss: 0.0000e+00 L2 loss: 1.87293 Learning rate: 0.02 Mask loss: 0.21609 RPN box loss: 0.02684 RPN score loss: 0.00913 RPN total loss: 0.03597 Total loss: 2.35933 timestamp: 1654919248.3645382 iteration: 5305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19285 FastRCNN class loss: 0.12664 FastRCNN total loss: 0.31949 L1 loss: 0.0000e+00 L2 loss: 1.87261 Learning rate: 0.02 Mask loss: 0.27853 RPN box loss: 0.03443 RPN score loss: 0.01665 RPN total loss: 0.05108 Total loss: 2.52172 timestamp: 1654919251.4944708 iteration: 5310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11192 FastRCNN class loss: 0.07207 FastRCNN total loss: 0.18398 L1 loss: 0.0000e+00 L2 loss: 1.87226 Learning rate: 0.02 Mask loss: 0.18712 RPN box loss: 0.00796 RPN score loss: 0.00901 RPN total loss: 0.01698 Total loss: 2.26034 timestamp: 1654919254.749114 iteration: 5315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16546 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.24553 L1 loss: 0.0000e+00 L2 loss: 1.87192 Learning rate: 0.02 Mask loss: 0.2939 RPN box loss: 0.04946 RPN score loss: 0.00576 RPN total loss: 0.05522 Total loss: 2.46657 timestamp: 1654919257.8575728 iteration: 5320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21196 FastRCNN class loss: 0.09313 FastRCNN total loss: 0.30509 L1 loss: 0.0000e+00 L2 loss: 1.87157 Learning rate: 0.02 Mask loss: 0.23975 RPN box loss: 0.03493 RPN score loss: 0.00719 RPN total loss: 0.04212 Total loss: 2.45853 timestamp: 1654919261.1808786 iteration: 5325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16965 FastRCNN class loss: 0.08257 FastRCNN total loss: 0.25221 L1 loss: 0.0000e+00 L2 loss: 1.87122 Learning rate: 0.02 Mask loss: 0.21405 RPN box loss: 0.0484 RPN score loss: 0.01339 RPN total loss: 0.06178 Total loss: 2.39927 timestamp: 1654919264.399142 iteration: 5330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24464 FastRCNN class loss: 0.14497 FastRCNN total loss: 0.38961 L1 loss: 0.0000e+00 L2 loss: 1.87087 Learning rate: 0.02 Mask loss: 0.26706 RPN box loss: 0.01795 RPN score loss: 0.01926 RPN total loss: 0.0372 Total loss: 2.56474 timestamp: 1654919267.6262286 iteration: 5335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19188 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.28759 L1 loss: 0.0000e+00 L2 loss: 1.87053 Learning rate: 0.02 Mask loss: 0.20781 RPN box loss: 0.03348 RPN score loss: 0.00925 RPN total loss: 0.04273 Total loss: 2.40866 timestamp: 1654919270.7681272 iteration: 5340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1628 FastRCNN class loss: 0.0704 FastRCNN total loss: 0.2332 L1 loss: 0.0000e+00 L2 loss: 1.87019 Learning rate: 0.02 Mask loss: 0.13999 RPN box loss: 0.12874 RPN score loss: 0.00815 RPN total loss: 0.13689 Total loss: 2.38027 timestamp: 1654919274.020718 iteration: 5345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12603 FastRCNN class loss: 0.09022 FastRCNN total loss: 0.21625 L1 loss: 0.0000e+00 L2 loss: 1.86984 Learning rate: 0.02 Mask loss: 0.19698 RPN box loss: 0.04438 RPN score loss: 0.00884 RPN total loss: 0.05322 Total loss: 2.33629 timestamp: 1654919277.272142 iteration: 5350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14749 FastRCNN class loss: 0.09767 FastRCNN total loss: 0.24516 L1 loss: 0.0000e+00 L2 loss: 1.86949 Learning rate: 0.02 Mask loss: 0.16672 RPN box loss: 0.03013 RPN score loss: 0.01112 RPN total loss: 0.04125 Total loss: 2.32262 timestamp: 1654919280.5195453 iteration: 5355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19831 FastRCNN class loss: 0.12711 FastRCNN total loss: 0.32542 L1 loss: 0.0000e+00 L2 loss: 1.86913 Learning rate: 0.02 Mask loss: 0.19057 RPN box loss: 0.04307 RPN score loss: 0.03268 RPN total loss: 0.07575 Total loss: 2.46087 timestamp: 1654919283.8004928 iteration: 5360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21369 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.28338 L1 loss: 0.0000e+00 L2 loss: 1.86878 Learning rate: 0.02 Mask loss: 0.18335 RPN box loss: 0.04349 RPN score loss: 0.0057 RPN total loss: 0.0492 Total loss: 2.3847 timestamp: 1654919287.0414867 iteration: 5365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13001 FastRCNN class loss: 0.06715 FastRCNN total loss: 0.19716 L1 loss: 0.0000e+00 L2 loss: 1.86844 Learning rate: 0.02 Mask loss: 0.26571 RPN box loss: 0.01044 RPN score loss: 0.01144 RPN total loss: 0.02188 Total loss: 2.35319 timestamp: 1654919290.4439025 iteration: 5370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19342 FastRCNN class loss: 0.08243 FastRCNN total loss: 0.27585 L1 loss: 0.0000e+00 L2 loss: 1.86808 Learning rate: 0.02 Mask loss: 0.18037 RPN box loss: 0.02743 RPN score loss: 0.0142 RPN total loss: 0.04162 Total loss: 2.36593 timestamp: 1654919293.6848218 iteration: 5375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25915 FastRCNN class loss: 0.11515 FastRCNN total loss: 0.3743 L1 loss: 0.0000e+00 L2 loss: 1.86776 Learning rate: 0.02 Mask loss: 0.25424 RPN box loss: 0.07447 RPN score loss: 0.01957 RPN total loss: 0.09403 Total loss: 2.59033 timestamp: 1654919296.9212053 iteration: 5380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24209 FastRCNN class loss: 0.09084 FastRCNN total loss: 0.33293 L1 loss: 0.0000e+00 L2 loss: 1.86741 Learning rate: 0.02 Mask loss: 0.23484 RPN box loss: 0.03932 RPN score loss: 0.01058 RPN total loss: 0.0499 Total loss: 2.48508 timestamp: 1654919300.087803 iteration: 5385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13558 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.20591 L1 loss: 0.0000e+00 L2 loss: 1.86706 Learning rate: 0.02 Mask loss: 0.13275 RPN box loss: 0.06818 RPN score loss: 0.00517 RPN total loss: 0.07336 Total loss: 2.27907 timestamp: 1654919303.3395455 iteration: 5390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16666 FastRCNN class loss: 0.11935 FastRCNN total loss: 0.28601 L1 loss: 0.0000e+00 L2 loss: 1.8667 Learning rate: 0.02 Mask loss: 0.19105 RPN box loss: 0.06761 RPN score loss: 0.01839 RPN total loss: 0.08599 Total loss: 2.42975 timestamp: 1654919306.5080826 iteration: 5395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1399 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.20837 L1 loss: 0.0000e+00 L2 loss: 1.86636 Learning rate: 0.02 Mask loss: 0.17876 RPN box loss: 0.09643 RPN score loss: 0.0073 RPN total loss: 0.10373 Total loss: 2.35722 timestamp: 1654919309.7929208 iteration: 5400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19631 FastRCNN class loss: 0.07094 FastRCNN total loss: 0.26725 L1 loss: 0.0000e+00 L2 loss: 1.86604 Learning rate: 0.02 Mask loss: 0.29316 RPN box loss: 0.02292 RPN score loss: 0.00376 RPN total loss: 0.02669 Total loss: 2.45314 timestamp: 1654919313.1432738 iteration: 5405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13335 FastRCNN class loss: 0.13458 FastRCNN total loss: 0.26793 L1 loss: 0.0000e+00 L2 loss: 1.86568 Learning rate: 0.02 Mask loss: 0.15228 RPN box loss: 0.02816 RPN score loss: 0.00762 RPN total loss: 0.03578 Total loss: 2.32168 timestamp: 1654919316.3665745 iteration: 5410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16407 FastRCNN class loss: 0.08031 FastRCNN total loss: 0.24438 L1 loss: 0.0000e+00 L2 loss: 1.86534 Learning rate: 0.02 Mask loss: 0.19681 RPN box loss: 0.0127 RPN score loss: 0.00541 RPN total loss: 0.01811 Total loss: 2.32465 timestamp: 1654919319.7657273 iteration: 5415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17156 FastRCNN class loss: 0.07262 FastRCNN total loss: 0.24419 L1 loss: 0.0000e+00 L2 loss: 1.865 Learning rate: 0.02 Mask loss: 0.23048 RPN box loss: 0.08292 RPN score loss: 0.0073 RPN total loss: 0.09022 Total loss: 2.42989 timestamp: 1654919323.1096182 iteration: 5420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14666 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.20018 L1 loss: 0.0000e+00 L2 loss: 1.86466 Learning rate: 0.02 Mask loss: 0.13539 RPN box loss: 0.02921 RPN score loss: 0.00911 RPN total loss: 0.03832 Total loss: 2.23856 timestamp: 1654919326.4097908 iteration: 5425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12814 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.20361 L1 loss: 0.0000e+00 L2 loss: 1.86431 Learning rate: 0.02 Mask loss: 0.20717 RPN box loss: 0.04314 RPN score loss: 0.03298 RPN total loss: 0.07613 Total loss: 2.35121 timestamp: 1654919329.7176933 iteration: 5430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10926 FastRCNN class loss: 0.05904 FastRCNN total loss: 0.1683 L1 loss: 0.0000e+00 L2 loss: 1.86394 Learning rate: 0.02 Mask loss: 0.17299 RPN box loss: 0.02379 RPN score loss: 0.00384 RPN total loss: 0.02763 Total loss: 2.23287 timestamp: 1654919332.9934874 iteration: 5435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17628 FastRCNN class loss: 0.08918 FastRCNN total loss: 0.26545 L1 loss: 0.0000e+00 L2 loss: 1.86359 Learning rate: 0.02 Mask loss: 0.15694 RPN box loss: 0.06772 RPN score loss: 0.01494 RPN total loss: 0.08266 Total loss: 2.36865 timestamp: 1654919336.2413554 iteration: 5440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20217 FastRCNN class loss: 0.09489 FastRCNN total loss: 0.29707 L1 loss: 0.0000e+00 L2 loss: 1.86323 Learning rate: 0.02 Mask loss: 0.2499 RPN box loss: 0.08207 RPN score loss: 0.01292 RPN total loss: 0.09499 Total loss: 2.50519 timestamp: 1654919339.5477912 iteration: 5445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12779 FastRCNN class loss: 0.05301 FastRCNN total loss: 0.1808 L1 loss: 0.0000e+00 L2 loss: 1.86287 Learning rate: 0.02 Mask loss: 0.167 RPN box loss: 0.02013 RPN score loss: 0.00393 RPN total loss: 0.02406 Total loss: 2.23473 timestamp: 1654919342.8849745 iteration: 5450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15856 FastRCNN class loss: 0.07593 FastRCNN total loss: 0.23449 L1 loss: 0.0000e+00 L2 loss: 1.86255 Learning rate: 0.02 Mask loss: 0.16864 RPN box loss: 0.02628 RPN score loss: 0.0036 RPN total loss: 0.02988 Total loss: 2.29555 timestamp: 1654919346.1724153 iteration: 5455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16218 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.25361 L1 loss: 0.0000e+00 L2 loss: 1.86221 Learning rate: 0.02 Mask loss: 0.17864 RPN box loss: 0.05538 RPN score loss: 0.02029 RPN total loss: 0.07568 Total loss: 2.37014 timestamp: 1654919349.5884395 iteration: 5460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23954 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.35117 L1 loss: 0.0000e+00 L2 loss: 1.86187 Learning rate: 0.02 Mask loss: 0.14057 RPN box loss: 0.02745 RPN score loss: 0.00717 RPN total loss: 0.03462 Total loss: 2.38823 timestamp: 1654919352.7957864 iteration: 5465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19014 FastRCNN class loss: 0.13334 FastRCNN total loss: 0.32348 L1 loss: 0.0000e+00 L2 loss: 1.86153 Learning rate: 0.02 Mask loss: 0.23271 RPN box loss: 0.05116 RPN score loss: 0.00535 RPN total loss: 0.05651 Total loss: 2.47422 timestamp: 1654919356.005677 iteration: 5470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18982 FastRCNN class loss: 0.11092 FastRCNN total loss: 0.30074 L1 loss: 0.0000e+00 L2 loss: 1.86117 Learning rate: 0.02 Mask loss: 0.27604 RPN box loss: 0.09393 RPN score loss: 0.01024 RPN total loss: 0.10417 Total loss: 2.54211 timestamp: 1654919359.2164185 iteration: 5475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1685 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.24884 L1 loss: 0.0000e+00 L2 loss: 1.86081 Learning rate: 0.02 Mask loss: 0.18092 RPN box loss: 0.05071 RPN score loss: 0.00722 RPN total loss: 0.05793 Total loss: 2.34851 timestamp: 1654919362.5586581 iteration: 5480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.05178 FastRCNN total loss: 0.15174 L1 loss: 0.0000e+00 L2 loss: 1.86046 Learning rate: 0.02 Mask loss: 0.15099 RPN box loss: 0.04818 RPN score loss: 0.00526 RPN total loss: 0.05344 Total loss: 2.21664 timestamp: 1654919365.7580552 iteration: 5485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18489 FastRCNN class loss: 0.11894 FastRCNN total loss: 0.30383 L1 loss: 0.0000e+00 L2 loss: 1.86012 Learning rate: 0.02 Mask loss: 0.29138 RPN box loss: 0.01449 RPN score loss: 0.00618 RPN total loss: 0.02067 Total loss: 2.476 timestamp: 1654919369.043366 iteration: 5490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27483 FastRCNN class loss: 0.20898 FastRCNN total loss: 0.48382 L1 loss: 0.0000e+00 L2 loss: 1.85978 Learning rate: 0.02 Mask loss: 0.21991 RPN box loss: 0.028 RPN score loss: 0.00898 RPN total loss: 0.03698 Total loss: 2.60049 timestamp: 1654919372.4037771 iteration: 5495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24199 FastRCNN class loss: 0.14073 FastRCNN total loss: 0.38273 L1 loss: 0.0000e+00 L2 loss: 1.85942 Learning rate: 0.02 Mask loss: 0.21242 RPN box loss: 0.0901 RPN score loss: 0.0132 RPN total loss: 0.1033 Total loss: 2.55787 timestamp: 1654919375.6784065 iteration: 5500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10861 FastRCNN class loss: 0.05425 FastRCNN total loss: 0.16285 L1 loss: 0.0000e+00 L2 loss: 1.85908 Learning rate: 0.02 Mask loss: 0.12627 RPN box loss: 0.01701 RPN score loss: 0.00381 RPN total loss: 0.02082 Total loss: 2.16903 timestamp: 1654919378.9516256 iteration: 5505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13315 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.20852 L1 loss: 0.0000e+00 L2 loss: 1.85873 Learning rate: 0.02 Mask loss: 0.17783 RPN box loss: 0.01076 RPN score loss: 0.00607 RPN total loss: 0.01683 Total loss: 2.26191 timestamp: 1654919382.240936 iteration: 5510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23665 FastRCNN class loss: 0.14978 FastRCNN total loss: 0.38643 L1 loss: 0.0000e+00 L2 loss: 1.85837 Learning rate: 0.02 Mask loss: 0.2341 RPN box loss: 0.04732 RPN score loss: 0.00987 RPN total loss: 0.05719 Total loss: 2.53609 timestamp: 1654919385.5569324 iteration: 5515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18194 FastRCNN class loss: 0.11547 FastRCNN total loss: 0.29741 L1 loss: 0.0000e+00 L2 loss: 1.85804 Learning rate: 0.02 Mask loss: 0.27807 RPN box loss: 0.06628 RPN score loss: 0.01735 RPN total loss: 0.08364 Total loss: 2.51717 timestamp: 1654919388.8187318 iteration: 5520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21551 FastRCNN class loss: 0.11034 FastRCNN total loss: 0.32585 L1 loss: 0.0000e+00 L2 loss: 1.8577 Learning rate: 0.02 Mask loss: 0.21665 RPN box loss: 0.04507 RPN score loss: 0.01997 RPN total loss: 0.06504 Total loss: 2.46524 timestamp: 1654919392.2293155 iteration: 5525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24149 FastRCNN class loss: 0.12312 FastRCNN total loss: 0.36461 L1 loss: 0.0000e+00 L2 loss: 1.85734 Learning rate: 0.02 Mask loss: 0.15677 RPN box loss: 0.02334 RPN score loss: 0.00763 RPN total loss: 0.03097 Total loss: 2.40968 timestamp: 1654919395.3685822 iteration: 5530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19929 FastRCNN class loss: 0.08682 FastRCNN total loss: 0.28612 L1 loss: 0.0000e+00 L2 loss: 1.85697 Learning rate: 0.02 Mask loss: 0.25543 RPN box loss: 0.04354 RPN score loss: 0.00576 RPN total loss: 0.04929 Total loss: 2.44781 timestamp: 1654919398.6826322 iteration: 5535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16042 FastRCNN class loss: 0.1361 FastRCNN total loss: 0.29652 L1 loss: 0.0000e+00 L2 loss: 1.85664 Learning rate: 0.02 Mask loss: 0.23017 RPN box loss: 0.06565 RPN score loss: 0.02919 RPN total loss: 0.09484 Total loss: 2.47818 timestamp: 1654919401.9536822 iteration: 5540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27954 FastRCNN class loss: 0.12476 FastRCNN total loss: 0.4043 L1 loss: 0.0000e+00 L2 loss: 1.85631 Learning rate: 0.02 Mask loss: 0.23346 RPN box loss: 0.10988 RPN score loss: 0.01495 RPN total loss: 0.12483 Total loss: 2.6189 timestamp: 1654919405.2279096 iteration: 5545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31066 FastRCNN class loss: 0.18308 FastRCNN total loss: 0.49374 L1 loss: 0.0000e+00 L2 loss: 1.85597 Learning rate: 0.02 Mask loss: 0.32382 RPN box loss: 0.05754 RPN score loss: 0.01038 RPN total loss: 0.06792 Total loss: 2.74145 timestamp: 1654919408.5976903 iteration: 5550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19879 FastRCNN class loss: 0.08844 FastRCNN total loss: 0.28723 L1 loss: 0.0000e+00 L2 loss: 1.85562 Learning rate: 0.02 Mask loss: 0.1136 RPN box loss: 0.07736 RPN score loss: 0.00594 RPN total loss: 0.0833 Total loss: 2.33974 timestamp: 1654919411.8521502 iteration: 5555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24566 FastRCNN class loss: 0.13935 FastRCNN total loss: 0.38501 L1 loss: 0.0000e+00 L2 loss: 1.85526 Learning rate: 0.02 Mask loss: 0.3068 RPN box loss: 0.07867 RPN score loss: 0.02039 RPN total loss: 0.09906 Total loss: 2.64613 timestamp: 1654919415.217728 iteration: 5560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09188 FastRCNN class loss: 0.04186 FastRCNN total loss: 0.13374 L1 loss: 0.0000e+00 L2 loss: 1.85493 Learning rate: 0.02 Mask loss: 0.13834 RPN box loss: 0.03508 RPN score loss: 0.00928 RPN total loss: 0.04436 Total loss: 2.17137 timestamp: 1654919418.4465864 iteration: 5565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22572 FastRCNN class loss: 0.10233 FastRCNN total loss: 0.32804 L1 loss: 0.0000e+00 L2 loss: 1.85458 Learning rate: 0.02 Mask loss: 0.17489 RPN box loss: 0.04757 RPN score loss: 0.00746 RPN total loss: 0.05503 Total loss: 2.41254 timestamp: 1654919421.6756763 iteration: 5570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13496 FastRCNN class loss: 0.08996 FastRCNN total loss: 0.22492 L1 loss: 0.0000e+00 L2 loss: 1.85424 Learning rate: 0.02 Mask loss: 0.19305 RPN box loss: 0.0366 RPN score loss: 0.02356 RPN total loss: 0.06016 Total loss: 2.33237 timestamp: 1654919424.8707914 iteration: 5575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27953 FastRCNN class loss: 0.15273 FastRCNN total loss: 0.43226 L1 loss: 0.0000e+00 L2 loss: 1.85389 Learning rate: 0.02 Mask loss: 0.14641 RPN box loss: 0.03924 RPN score loss: 0.00982 RPN total loss: 0.04906 Total loss: 2.48162 timestamp: 1654919428.346841 iteration: 5580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12982 FastRCNN class loss: 0.14124 FastRCNN total loss: 0.27106 L1 loss: 0.0000e+00 L2 loss: 1.85354 Learning rate: 0.02 Mask loss: 0.13987 RPN box loss: 0.06446 RPN score loss: 0.00958 RPN total loss: 0.07404 Total loss: 2.3385 timestamp: 1654919431.6343162 iteration: 5585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16428 FastRCNN class loss: 0.05688 FastRCNN total loss: 0.22116 L1 loss: 0.0000e+00 L2 loss: 1.8532 Learning rate: 0.02 Mask loss: 0.14256 RPN box loss: 0.0376 RPN score loss: 0.00477 RPN total loss: 0.04237 Total loss: 2.25929 timestamp: 1654919434.8710477 iteration: 5590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2393 FastRCNN class loss: 0.09342 FastRCNN total loss: 0.33272 L1 loss: 0.0000e+00 L2 loss: 1.85286 Learning rate: 0.02 Mask loss: 0.19046 RPN box loss: 0.0879 RPN score loss: 0.01115 RPN total loss: 0.09905 Total loss: 2.47509 timestamp: 1654919438.2320297 iteration: 5595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14169 FastRCNN class loss: 0.09963 FastRCNN total loss: 0.24133 L1 loss: 0.0000e+00 L2 loss: 1.85251 Learning rate: 0.02 Mask loss: 0.16899 RPN box loss: 0.05938 RPN score loss: 0.01796 RPN total loss: 0.07734 Total loss: 2.34016 timestamp: 1654919441.3919566 iteration: 5600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18464 FastRCNN class loss: 0.15458 FastRCNN total loss: 0.33922 L1 loss: 0.0000e+00 L2 loss: 1.85215 Learning rate: 0.02 Mask loss: 0.21337 RPN box loss: 0.05085 RPN score loss: 0.01217 RPN total loss: 0.06301 Total loss: 2.46775 timestamp: 1654919444.665731 iteration: 5605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11484 FastRCNN class loss: 0.05697 FastRCNN total loss: 0.1718 L1 loss: 0.0000e+00 L2 loss: 1.85185 Learning rate: 0.02 Mask loss: 0.16527 RPN box loss: 0.00574 RPN score loss: 0.00601 RPN total loss: 0.01175 Total loss: 2.20067 timestamp: 1654919447.9051805 iteration: 5610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16082 FastRCNN class loss: 0.09626 FastRCNN total loss: 0.25709 L1 loss: 0.0000e+00 L2 loss: 1.85151 Learning rate: 0.02 Mask loss: 0.17104 RPN box loss: 0.05359 RPN score loss: 0.00953 RPN total loss: 0.06311 Total loss: 2.34275 timestamp: 1654919451.181234 iteration: 5615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18065 FastRCNN class loss: 0.09999 FastRCNN total loss: 0.28063 L1 loss: 0.0000e+00 L2 loss: 1.85117 Learning rate: 0.02 Mask loss: 0.2757 RPN box loss: 0.02901 RPN score loss: 0.00728 RPN total loss: 0.03629 Total loss: 2.44379 timestamp: 1654919454.360692 iteration: 5620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21006 FastRCNN class loss: 0.08503 FastRCNN total loss: 0.29509 L1 loss: 0.0000e+00 L2 loss: 1.85083 Learning rate: 0.02 Mask loss: 0.20637 RPN box loss: 0.0577 RPN score loss: 0.01316 RPN total loss: 0.07086 Total loss: 2.42315 timestamp: 1654919457.7585917 iteration: 5625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18466 FastRCNN class loss: 0.11346 FastRCNN total loss: 0.29812 L1 loss: 0.0000e+00 L2 loss: 1.85049 Learning rate: 0.02 Mask loss: 0.1593 RPN box loss: 0.05459 RPN score loss: 0.00435 RPN total loss: 0.05895 Total loss: 2.36685 timestamp: 1654919461.0363379 iteration: 5630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19468 FastRCNN class loss: 0.11831 FastRCNN total loss: 0.31298 L1 loss: 0.0000e+00 L2 loss: 1.85014 Learning rate: 0.02 Mask loss: 0.16864 RPN box loss: 0.0362 RPN score loss: 0.00808 RPN total loss: 0.04428 Total loss: 2.37603 timestamp: 1654919464.3694935 iteration: 5635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24291 FastRCNN class loss: 0.10118 FastRCNN total loss: 0.34409 L1 loss: 0.0000e+00 L2 loss: 1.84978 Learning rate: 0.02 Mask loss: 0.2364 RPN box loss: 0.02867 RPN score loss: 0.00387 RPN total loss: 0.03253 Total loss: 2.46281 timestamp: 1654919467.8016458 iteration: 5640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11396 FastRCNN class loss: 0.10307 FastRCNN total loss: 0.21703 L1 loss: 0.0000e+00 L2 loss: 1.84943 Learning rate: 0.02 Mask loss: 0.18076 RPN box loss: 0.00841 RPN score loss: 0.00442 RPN total loss: 0.01284 Total loss: 2.26005 timestamp: 1654919470.94961 iteration: 5645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11271 FastRCNN class loss: 0.04493 FastRCNN total loss: 0.15764 L1 loss: 0.0000e+00 L2 loss: 1.8491 Learning rate: 0.02 Mask loss: 0.14714 RPN box loss: 0.01801 RPN score loss: 0.00631 RPN total loss: 0.02432 Total loss: 2.1782 timestamp: 1654919474.2936494 iteration: 5650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13266 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.19672 L1 loss: 0.0000e+00 L2 loss: 1.84875 Learning rate: 0.02 Mask loss: 0.18902 RPN box loss: 0.041 RPN score loss: 0.00938 RPN total loss: 0.05038 Total loss: 2.28487 timestamp: 1654919477.4832287 iteration: 5655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23401 FastRCNN class loss: 0.14944 FastRCNN total loss: 0.38345 L1 loss: 0.0000e+00 L2 loss: 1.8484 Learning rate: 0.02 Mask loss: 0.2671 RPN box loss: 0.03953 RPN score loss: 0.0225 RPN total loss: 0.06203 Total loss: 2.56099 timestamp: 1654919480.818337 iteration: 5660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13534 FastRCNN class loss: 0.08928 FastRCNN total loss: 0.22463 L1 loss: 0.0000e+00 L2 loss: 1.84807 Learning rate: 0.02 Mask loss: 0.15604 RPN box loss: 0.07186 RPN score loss: 0.0092 RPN total loss: 0.08106 Total loss: 2.3098 timestamp: 1654919484.065693 iteration: 5665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19374 FastRCNN class loss: 0.11782 FastRCNN total loss: 0.31156 L1 loss: 0.0000e+00 L2 loss: 1.84772 Learning rate: 0.02 Mask loss: 0.17223 RPN box loss: 0.04161 RPN score loss: 0.02542 RPN total loss: 0.06703 Total loss: 2.39854 timestamp: 1654919487.3445404 iteration: 5670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11281 FastRCNN class loss: 0.05373 FastRCNN total loss: 0.16654 L1 loss: 0.0000e+00 L2 loss: 1.84738 Learning rate: 0.02 Mask loss: 0.11007 RPN box loss: 0.03839 RPN score loss: 0.00328 RPN total loss: 0.04167 Total loss: 2.16567 timestamp: 1654919490.481133 iteration: 5675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1109 FastRCNN class loss: 0.07457 FastRCNN total loss: 0.18547 L1 loss: 0.0000e+00 L2 loss: 1.84704 Learning rate: 0.02 Mask loss: 0.25244 RPN box loss: 0.00897 RPN score loss: 0.00387 RPN total loss: 0.01284 Total loss: 2.29779 timestamp: 1654919493.745024 iteration: 5680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.227 FastRCNN class loss: 0.14278 FastRCNN total loss: 0.36979 L1 loss: 0.0000e+00 L2 loss: 1.84669 Learning rate: 0.02 Mask loss: 0.24032 RPN box loss: 0.06807 RPN score loss: 0.01426 RPN total loss: 0.08233 Total loss: 2.53913 timestamp: 1654919496.9881215 iteration: 5685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21707 FastRCNN class loss: 0.10632 FastRCNN total loss: 0.32339 L1 loss: 0.0000e+00 L2 loss: 1.84634 Learning rate: 0.02 Mask loss: 0.20118 RPN box loss: 0.03862 RPN score loss: 0.00867 RPN total loss: 0.04728 Total loss: 2.41819 timestamp: 1654919500.253594 iteration: 5690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21578 FastRCNN class loss: 0.17125 FastRCNN total loss: 0.38703 L1 loss: 0.0000e+00 L2 loss: 1.84602 Learning rate: 0.02 Mask loss: 0.17444 RPN box loss: 0.07504 RPN score loss: 0.00724 RPN total loss: 0.08228 Total loss: 2.48977 timestamp: 1654919503.5744665 iteration: 5695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13128 FastRCNN class loss: 0.08232 FastRCNN total loss: 0.2136 L1 loss: 0.0000e+00 L2 loss: 1.84568 Learning rate: 0.02 Mask loss: 0.15717 RPN box loss: 0.05414 RPN score loss: 0.01123 RPN total loss: 0.06537 Total loss: 2.28182 timestamp: 1654919506.7900882 iteration: 5700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19592 FastRCNN class loss: 0.10815 FastRCNN total loss: 0.30407 L1 loss: 0.0000e+00 L2 loss: 1.84535 Learning rate: 0.02 Mask loss: 0.19123 RPN box loss: 0.02162 RPN score loss: 0.01358 RPN total loss: 0.0352 Total loss: 2.37585 timestamp: 1654919510.0812333 iteration: 5705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09427 FastRCNN class loss: 0.06001 FastRCNN total loss: 0.15428 L1 loss: 0.0000e+00 L2 loss: 1.845 Learning rate: 0.02 Mask loss: 0.19479 RPN box loss: 0.01001 RPN score loss: 0.00772 RPN total loss: 0.01773 Total loss: 2.21179 timestamp: 1654919513.280061 iteration: 5710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17065 FastRCNN class loss: 0.09895 FastRCNN total loss: 0.2696 L1 loss: 0.0000e+00 L2 loss: 1.84465 Learning rate: 0.02 Mask loss: 0.21539 RPN box loss: 0.04283 RPN score loss: 0.01221 RPN total loss: 0.05504 Total loss: 2.38468 timestamp: 1654919516.4793468 iteration: 5715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19837 FastRCNN class loss: 0.09063 FastRCNN total loss: 0.289 L1 loss: 0.0000e+00 L2 loss: 1.8443 Learning rate: 0.02 Mask loss: 0.19017 RPN box loss: 0.06008 RPN score loss: 0.00646 RPN total loss: 0.06654 Total loss: 2.39001 timestamp: 1654919519.595945 iteration: 5720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15542 FastRCNN class loss: 0.05315 FastRCNN total loss: 0.20857 L1 loss: 0.0000e+00 L2 loss: 1.84399 Learning rate: 0.02 Mask loss: 0.12893 RPN box loss: 0.02182 RPN score loss: 0.00219 RPN total loss: 0.024 Total loss: 2.20549 timestamp: 1654919522.8180058 iteration: 5725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14652 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.21034 L1 loss: 0.0000e+00 L2 loss: 1.84366 Learning rate: 0.02 Mask loss: 0.13104 RPN box loss: 0.03403 RPN score loss: 0.00693 RPN total loss: 0.04096 Total loss: 2.226 timestamp: 1654919526.0756996 iteration: 5730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19593 FastRCNN class loss: 0.12734 FastRCNN total loss: 0.32327 L1 loss: 0.0000e+00 L2 loss: 1.84332 Learning rate: 0.02 Mask loss: 0.23012 RPN box loss: 0.04481 RPN score loss: 0.00747 RPN total loss: 0.05228 Total loss: 2.44899 timestamp: 1654919529.3413885 iteration: 5735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13509 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.21072 L1 loss: 0.0000e+00 L2 loss: 1.84297 Learning rate: 0.02 Mask loss: 0.15904 RPN box loss: 0.06672 RPN score loss: 0.00576 RPN total loss: 0.07248 Total loss: 2.28521 timestamp: 1654919532.7212965 iteration: 5740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19726 FastRCNN class loss: 0.11333 FastRCNN total loss: 0.31059 L1 loss: 0.0000e+00 L2 loss: 1.84263 Learning rate: 0.02 Mask loss: 0.20528 RPN box loss: 0.06408 RPN score loss: 0.02122 RPN total loss: 0.08531 Total loss: 2.4438 timestamp: 1654919535.9402013 iteration: 5745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22437 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.31304 L1 loss: 0.0000e+00 L2 loss: 1.84226 Learning rate: 0.02 Mask loss: 0.29302 RPN box loss: 0.03365 RPN score loss: 0.00834 RPN total loss: 0.04199 Total loss: 2.49032 timestamp: 1654919539.1995838 iteration: 5750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17413 FastRCNN class loss: 0.09944 FastRCNN total loss: 0.27356 L1 loss: 0.0000e+00 L2 loss: 1.84191 Learning rate: 0.02 Mask loss: 0.18021 RPN box loss: 0.03917 RPN score loss: 0.01027 RPN total loss: 0.04944 Total loss: 2.34512 timestamp: 1654919542.4069543 iteration: 5755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14557 FastRCNN class loss: 0.1198 FastRCNN total loss: 0.26537 L1 loss: 0.0000e+00 L2 loss: 1.84158 Learning rate: 0.02 Mask loss: 0.17979 RPN box loss: 0.02975 RPN score loss: 0.00808 RPN total loss: 0.03783 Total loss: 2.32456 timestamp: 1654919545.63701 iteration: 5760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13202 FastRCNN class loss: 0.07903 FastRCNN total loss: 0.21104 L1 loss: 0.0000e+00 L2 loss: 1.84126 Learning rate: 0.02 Mask loss: 0.20128 RPN box loss: 0.04102 RPN score loss: 0.01101 RPN total loss: 0.05202 Total loss: 2.3056 timestamp: 1654919548.8596396 iteration: 5765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18201 FastRCNN class loss: 0.10087 FastRCNN total loss: 0.28289 L1 loss: 0.0000e+00 L2 loss: 1.84091 Learning rate: 0.02 Mask loss: 0.23015 RPN box loss: 0.03477 RPN score loss: 0.01114 RPN total loss: 0.04591 Total loss: 2.39985 timestamp: 1654919552.2161617 iteration: 5770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21507 FastRCNN class loss: 0.17376 FastRCNN total loss: 0.38882 L1 loss: 0.0000e+00 L2 loss: 1.84056 Learning rate: 0.02 Mask loss: 0.25014 RPN box loss: 0.11185 RPN score loss: 0.0121 RPN total loss: 0.12394 Total loss: 2.60347 timestamp: 1654919555.4580286 iteration: 5775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.08695 FastRCNN total loss: 0.23868 L1 loss: 0.0000e+00 L2 loss: 1.84021 Learning rate: 0.02 Mask loss: 0.25537 RPN box loss: 0.05105 RPN score loss: 0.01741 RPN total loss: 0.06846 Total loss: 2.40271 timestamp: 1654919558.766956 iteration: 5780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16877 FastRCNN class loss: 0.13065 FastRCNN total loss: 0.29942 L1 loss: 0.0000e+00 L2 loss: 1.83987 Learning rate: 0.02 Mask loss: 0.17268 RPN box loss: 0.05112 RPN score loss: 0.01181 RPN total loss: 0.06293 Total loss: 2.3749 timestamp: 1654919562.0992765 iteration: 5785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14588 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.22908 L1 loss: 0.0000e+00 L2 loss: 1.83954 Learning rate: 0.02 Mask loss: 0.19172 RPN box loss: 0.0301 RPN score loss: 0.00911 RPN total loss: 0.03921 Total loss: 2.29955 timestamp: 1654919565.346663 iteration: 5790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1944 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.2672 L1 loss: 0.0000e+00 L2 loss: 1.83918 Learning rate: 0.02 Mask loss: 0.19227 RPN box loss: 0.03927 RPN score loss: 0.00944 RPN total loss: 0.04871 Total loss: 2.34736 timestamp: 1654919568.630431 iteration: 5795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08822 FastRCNN class loss: 0.05795 FastRCNN total loss: 0.14617 L1 loss: 0.0000e+00 L2 loss: 1.83885 Learning rate: 0.02 Mask loss: 0.15659 RPN box loss: 0.04633 RPN score loss: 0.0089 RPN total loss: 0.05522 Total loss: 2.19683 timestamp: 1654919571.8434703 iteration: 5800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27094 FastRCNN class loss: 0.1653 FastRCNN total loss: 0.43623 L1 loss: 0.0000e+00 L2 loss: 1.83849 Learning rate: 0.02 Mask loss: 0.33905 RPN box loss: 0.03163 RPN score loss: 0.0192 RPN total loss: 0.05082 Total loss: 2.6646 timestamp: 1654919575.0749624 iteration: 5805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17739 FastRCNN class loss: 0.10643 FastRCNN total loss: 0.28382 L1 loss: 0.0000e+00 L2 loss: 1.83815 Learning rate: 0.02 Mask loss: 0.1925 RPN box loss: 0.07966 RPN score loss: 0.0074 RPN total loss: 0.08706 Total loss: 2.40153 timestamp: 1654919578.358667 iteration: 5810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20052 FastRCNN class loss: 0.13185 FastRCNN total loss: 0.33237 L1 loss: 0.0000e+00 L2 loss: 1.83784 Learning rate: 0.02 Mask loss: 0.21326 RPN box loss: 0.09643 RPN score loss: 0.02153 RPN total loss: 0.11796 Total loss: 2.50143 timestamp: 1654919581.722645 iteration: 5815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19317 FastRCNN class loss: 0.10017 FastRCNN total loss: 0.29334 L1 loss: 0.0000e+00 L2 loss: 1.8375 Learning rate: 0.02 Mask loss: 0.27947 RPN box loss: 0.03903 RPN score loss: 0.01475 RPN total loss: 0.05378 Total loss: 2.46409 timestamp: 1654919584.8525748 iteration: 5820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20664 FastRCNN class loss: 0.11989 FastRCNN total loss: 0.32653 L1 loss: 0.0000e+00 L2 loss: 1.83717 Learning rate: 0.02 Mask loss: 0.18533 RPN box loss: 0.02022 RPN score loss: 0.00652 RPN total loss: 0.02674 Total loss: 2.37577 timestamp: 1654919588.1757262 iteration: 5825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13006 FastRCNN class loss: 0.08376 FastRCNN total loss: 0.21382 L1 loss: 0.0000e+00 L2 loss: 1.83683 Learning rate: 0.02 Mask loss: 0.15704 RPN box loss: 0.01673 RPN score loss: 0.00556 RPN total loss: 0.02229 Total loss: 2.22997 timestamp: 1654919591.3322868 iteration: 5830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15749 FastRCNN class loss: 0.09519 FastRCNN total loss: 0.25268 L1 loss: 0.0000e+00 L2 loss: 1.83648 Learning rate: 0.02 Mask loss: 0.19819 RPN box loss: 0.07066 RPN score loss: 0.00827 RPN total loss: 0.07894 Total loss: 2.36629 timestamp: 1654919594.5319314 iteration: 5835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19986 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.27511 L1 loss: 0.0000e+00 L2 loss: 1.83614 Learning rate: 0.02 Mask loss: 0.16569 RPN box loss: 0.02983 RPN score loss: 0.00508 RPN total loss: 0.03491 Total loss: 2.31185 timestamp: 1654919597.7362263 iteration: 5840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13899 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.2131 L1 loss: 0.0000e+00 L2 loss: 1.83579 Learning rate: 0.02 Mask loss: 0.32292 RPN box loss: 0.08119 RPN score loss: 0.02198 RPN total loss: 0.10317 Total loss: 2.47498 timestamp: 1654919600.9550424 iteration: 5845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16594 FastRCNN class loss: 0.08792 FastRCNN total loss: 0.25386 L1 loss: 0.0000e+00 L2 loss: 1.83544 Learning rate: 0.02 Mask loss: 0.17206 RPN box loss: 0.05071 RPN score loss: 0.00852 RPN total loss: 0.05923 Total loss: 2.32058 timestamp: 1654919604.1120012 iteration: 5850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18805 FastRCNN class loss: 0.17644 FastRCNN total loss: 0.3645 L1 loss: 0.0000e+00 L2 loss: 1.83511 Learning rate: 0.02 Mask loss: 0.21812 RPN box loss: 0.10667 RPN score loss: 0.01119 RPN total loss: 0.11786 Total loss: 2.53559 timestamp: 1654919607.3857977 iteration: 5855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20428 FastRCNN class loss: 0.11144 FastRCNN total loss: 0.31572 L1 loss: 0.0000e+00 L2 loss: 1.83477 Learning rate: 0.02 Mask loss: 0.30784 RPN box loss: 0.03631 RPN score loss: 0.01599 RPN total loss: 0.05229 Total loss: 2.51062 timestamp: 1654919610.776784 iteration: 5860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14601 FastRCNN class loss: 0.05976 FastRCNN total loss: 0.20578 L1 loss: 0.0000e+00 L2 loss: 1.83443 Learning rate: 0.02 Mask loss: 0.16964 RPN box loss: 0.01517 RPN score loss: 0.00229 RPN total loss: 0.01746 Total loss: 2.22731 timestamp: 1654919613.971871 iteration: 5865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10265 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.16307 L1 loss: 0.0000e+00 L2 loss: 1.83413 Learning rate: 0.02 Mask loss: 0.12126 RPN box loss: 0.04801 RPN score loss: 0.0088 RPN total loss: 0.05681 Total loss: 2.17527 timestamp: 1654919617.242489 iteration: 5870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12566 FastRCNN class loss: 0.11645 FastRCNN total loss: 0.24211 L1 loss: 0.0000e+00 L2 loss: 1.83381 Learning rate: 0.02 Mask loss: 0.12497 RPN box loss: 0.08071 RPN score loss: 0.00719 RPN total loss: 0.0879 Total loss: 2.28879 timestamp: 1654919620.3929453 iteration: 5875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10187 FastRCNN class loss: 0.05023 FastRCNN total loss: 0.1521 L1 loss: 0.0000e+00 L2 loss: 1.83346 Learning rate: 0.02 Mask loss: 0.23035 RPN box loss: 0.04636 RPN score loss: 0.01066 RPN total loss: 0.05702 Total loss: 2.27292 timestamp: 1654919623.6505163 iteration: 5880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28534 FastRCNN class loss: 0.08477 FastRCNN total loss: 0.37012 L1 loss: 0.0000e+00 L2 loss: 1.83313 Learning rate: 0.02 Mask loss: 0.17446 RPN box loss: 0.03462 RPN score loss: 0.00559 RPN total loss: 0.04021 Total loss: 2.41792 timestamp: 1654919626.8309627 iteration: 5885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23463 FastRCNN class loss: 0.13505 FastRCNN total loss: 0.36968 L1 loss: 0.0000e+00 L2 loss: 1.83278 Learning rate: 0.02 Mask loss: 0.28313 RPN box loss: 0.02678 RPN score loss: 0.01532 RPN total loss: 0.0421 Total loss: 2.52769 timestamp: 1654919630.2034113 iteration: 5890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20858 FastRCNN class loss: 0.13691 FastRCNN total loss: 0.34549 L1 loss: 0.0000e+00 L2 loss: 1.83244 Learning rate: 0.02 Mask loss: 0.14738 RPN box loss: 0.08763 RPN score loss: 0.01456 RPN total loss: 0.10219 Total loss: 2.42751 timestamp: 1654919633.349353 iteration: 5895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27592 FastRCNN class loss: 0.10245 FastRCNN total loss: 0.37836 L1 loss: 0.0000e+00 L2 loss: 1.8321 Learning rate: 0.02 Mask loss: 0.17544 RPN box loss: 0.03231 RPN score loss: 0.00557 RPN total loss: 0.03788 Total loss: 2.42379 timestamp: 1654919636.6941032 iteration: 5900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24725 FastRCNN class loss: 0.10057 FastRCNN total loss: 0.34782 L1 loss: 0.0000e+00 L2 loss: 1.83176 Learning rate: 0.02 Mask loss: 0.18277 RPN box loss: 0.02217 RPN score loss: 0.00541 RPN total loss: 0.02758 Total loss: 2.38993 timestamp: 1654919639.9194272 iteration: 5905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15191 FastRCNN class loss: 0.07865 FastRCNN total loss: 0.23056 L1 loss: 0.0000e+00 L2 loss: 1.83144 Learning rate: 0.02 Mask loss: 0.23071 RPN box loss: 0.09911 RPN score loss: 0.01418 RPN total loss: 0.11329 Total loss: 2.406 timestamp: 1654919643.160416 iteration: 5910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20372 FastRCNN class loss: 0.10679 FastRCNN total loss: 0.31051 L1 loss: 0.0000e+00 L2 loss: 1.83109 Learning rate: 0.02 Mask loss: 0.17061 RPN box loss: 0.02633 RPN score loss: 0.01407 RPN total loss: 0.04039 Total loss: 2.3526 timestamp: 1654919646.4066637 iteration: 5915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16133 FastRCNN class loss: 0.09095 FastRCNN total loss: 0.25228 L1 loss: 0.0000e+00 L2 loss: 1.83075 Learning rate: 0.02 Mask loss: 0.24388 RPN box loss: 0.04882 RPN score loss: 0.01292 RPN total loss: 0.06174 Total loss: 2.38865 timestamp: 1654919649.6010797 iteration: 5920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16221 FastRCNN class loss: 0.12647 FastRCNN total loss: 0.28868 L1 loss: 0.0000e+00 L2 loss: 1.83041 Learning rate: 0.02 Mask loss: 0.19081 RPN box loss: 0.07215 RPN score loss: 0.0101 RPN total loss: 0.08226 Total loss: 2.39215 timestamp: 1654919652.9512663 iteration: 5925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16619 FastRCNN class loss: 0.12602 FastRCNN total loss: 0.29221 L1 loss: 0.0000e+00 L2 loss: 1.83008 Learning rate: 0.02 Mask loss: 0.16533 RPN box loss: 0.02778 RPN score loss: 0.01019 RPN total loss: 0.03797 Total loss: 2.32559 timestamp: 1654919656.098145 iteration: 5930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23728 FastRCNN class loss: 0.09463 FastRCNN total loss: 0.33191 L1 loss: 0.0000e+00 L2 loss: 1.82974 Learning rate: 0.02 Mask loss: 0.24369 RPN box loss: 0.06688 RPN score loss: 0.0083 RPN total loss: 0.07518 Total loss: 2.48052 timestamp: 1654919659.4130754 iteration: 5935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20218 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.27844 L1 loss: 0.0000e+00 L2 loss: 1.82938 Learning rate: 0.02 Mask loss: 0.16411 RPN box loss: 0.03561 RPN score loss: 0.00955 RPN total loss: 0.04516 Total loss: 2.31708 timestamp: 1654919662.6475394 iteration: 5940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10975 FastRCNN class loss: 0.09706 FastRCNN total loss: 0.20681 L1 loss: 0.0000e+00 L2 loss: 1.82904 Learning rate: 0.02 Mask loss: 0.2 RPN box loss: 0.07885 RPN score loss: 0.01584 RPN total loss: 0.09468 Total loss: 2.33053 timestamp: 1654919666.0178015 iteration: 5945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22278 FastRCNN class loss: 0.14438 FastRCNN total loss: 0.36716 L1 loss: 0.0000e+00 L2 loss: 1.82871 Learning rate: 0.02 Mask loss: 0.24739 RPN box loss: 0.12155 RPN score loss: 0.01899 RPN total loss: 0.14054 Total loss: 2.58379 timestamp: 1654919669.241751 iteration: 5950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16606 FastRCNN class loss: 0.06439 FastRCNN total loss: 0.23045 L1 loss: 0.0000e+00 L2 loss: 1.82836 Learning rate: 0.02 Mask loss: 0.18382 RPN box loss: 0.0515 RPN score loss: 0.00611 RPN total loss: 0.05761 Total loss: 2.30024 timestamp: 1654919672.6153014 iteration: 5955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17132 FastRCNN class loss: 0.08293 FastRCNN total loss: 0.25425 L1 loss: 0.0000e+00 L2 loss: 1.82803 Learning rate: 0.02 Mask loss: 0.1369 RPN box loss: 0.05593 RPN score loss: 0.00636 RPN total loss: 0.06228 Total loss: 2.28146 timestamp: 1654919675.8705764 iteration: 5960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23215 FastRCNN class loss: 0.09473 FastRCNN total loss: 0.32688 L1 loss: 0.0000e+00 L2 loss: 1.82769 Learning rate: 0.02 Mask loss: 0.16138 RPN box loss: 0.01806 RPN score loss: 0.0071 RPN total loss: 0.02515 Total loss: 2.34109 timestamp: 1654919679.1537025 iteration: 5965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21535 FastRCNN class loss: 0.1229 FastRCNN total loss: 0.33824 L1 loss: 0.0000e+00 L2 loss: 1.82736 Learning rate: 0.02 Mask loss: 0.24952 RPN box loss: 0.03398 RPN score loss: 0.0248 RPN total loss: 0.05878 Total loss: 2.4739 timestamp: 1654919682.3942475 iteration: 5970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17906 FastRCNN class loss: 0.06612 FastRCNN total loss: 0.24518 L1 loss: 0.0000e+00 L2 loss: 1.82703 Learning rate: 0.02 Mask loss: 0.17846 RPN box loss: 0.0045 RPN score loss: 0.0043 RPN total loss: 0.0088 Total loss: 2.25947 timestamp: 1654919685.5744689 iteration: 5975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21318 FastRCNN class loss: 0.10118 FastRCNN total loss: 0.31437 L1 loss: 0.0000e+00 L2 loss: 1.82668 Learning rate: 0.02 Mask loss: 0.27445 RPN box loss: 0.12664 RPN score loss: 0.01341 RPN total loss: 0.14005 Total loss: 2.55555 timestamp: 1654919688.8905718 iteration: 5980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14913 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.22803 L1 loss: 0.0000e+00 L2 loss: 1.82634 Learning rate: 0.02 Mask loss: 0.22783 RPN box loss: 0.06466 RPN score loss: 0.00511 RPN total loss: 0.06978 Total loss: 2.35197 timestamp: 1654919692.1097696 iteration: 5985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15879 FastRCNN class loss: 0.09147 FastRCNN total loss: 0.25026 L1 loss: 0.0000e+00 L2 loss: 1.82599 Learning rate: 0.02 Mask loss: 0.23472 RPN box loss: 0.02425 RPN score loss: 0.00748 RPN total loss: 0.03173 Total loss: 2.34271 timestamp: 1654919695.3745213 iteration: 5990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24941 FastRCNN class loss: 0.12321 FastRCNN total loss: 0.37262 L1 loss: 0.0000e+00 L2 loss: 1.82566 Learning rate: 0.02 Mask loss: 0.17766 RPN box loss: 0.03965 RPN score loss: 0.0105 RPN total loss: 0.05015 Total loss: 2.42609 timestamp: 1654919698.5651991 iteration: 5995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.0376 FastRCNN total loss: 0.11745 L1 loss: 0.0000e+00 L2 loss: 1.82532 Learning rate: 0.02 Mask loss: 0.12155 RPN box loss: 0.002 RPN score loss: 0.00238 RPN total loss: 0.00439 Total loss: 2.06872 timestamp: 1654919701.941198 iteration: 6000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12427 FastRCNN class loss: 0.0533 FastRCNN total loss: 0.17757 L1 loss: 0.0000e+00 L2 loss: 1.825 Learning rate: 0.02 Mask loss: 0.18315 RPN box loss: 0.03898 RPN score loss: 0.00364 RPN total loss: 0.04262 Total loss: 2.22834 timestamp: 1654919705.124436 iteration: 6005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18127 FastRCNN class loss: 0.08123 FastRCNN total loss: 0.2625 L1 loss: 0.0000e+00 L2 loss: 1.82466 Learning rate: 0.02 Mask loss: 0.13869 RPN box loss: 0.02963 RPN score loss: 0.00222 RPN total loss: 0.03185 Total loss: 2.2577 timestamp: 1654919708.369504 iteration: 6010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15976 FastRCNN class loss: 0.17945 FastRCNN total loss: 0.3392 L1 loss: 0.0000e+00 L2 loss: 1.8243 Learning rate: 0.02 Mask loss: 0.21991 RPN box loss: 0.03659 RPN score loss: 0.00732 RPN total loss: 0.04391 Total loss: 2.42733 timestamp: 1654919711.6158478 iteration: 6015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18672 FastRCNN class loss: 0.10843 FastRCNN total loss: 0.29515 L1 loss: 0.0000e+00 L2 loss: 1.82396 Learning rate: 0.02 Mask loss: 0.2012 RPN box loss: 0.0498 RPN score loss: 0.00883 RPN total loss: 0.05863 Total loss: 2.37895 timestamp: 1654919714.857286 iteration: 6020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22111 FastRCNN class loss: 0.10378 FastRCNN total loss: 0.32489 L1 loss: 0.0000e+00 L2 loss: 1.82362 Learning rate: 0.02 Mask loss: 0.22176 RPN box loss: 0.02338 RPN score loss: 0.0095 RPN total loss: 0.03288 Total loss: 2.40316 timestamp: 1654919718.257476 iteration: 6025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22661 FastRCNN class loss: 0.06814 FastRCNN total loss: 0.29475 L1 loss: 0.0000e+00 L2 loss: 1.82329 Learning rate: 0.02 Mask loss: 0.15277 RPN box loss: 0.05012 RPN score loss: 0.00578 RPN total loss: 0.0559 Total loss: 2.3267 timestamp: 1654919721.4698157 iteration: 6030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17605 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.25502 L1 loss: 0.0000e+00 L2 loss: 1.82296 Learning rate: 0.02 Mask loss: 0.32082 RPN box loss: 0.04642 RPN score loss: 0.005 RPN total loss: 0.05142 Total loss: 2.45022 timestamp: 1654919724.8246396 iteration: 6035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11602 FastRCNN class loss: 0.11604 FastRCNN total loss: 0.23207 L1 loss: 0.0000e+00 L2 loss: 1.82263 Learning rate: 0.02 Mask loss: 0.17163 RPN box loss: 0.03626 RPN score loss: 0.01507 RPN total loss: 0.05133 Total loss: 2.27765 timestamp: 1654919728.1164324 iteration: 6040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19022 FastRCNN class loss: 0.11277 FastRCNN total loss: 0.30299 L1 loss: 0.0000e+00 L2 loss: 1.82228 Learning rate: 0.02 Mask loss: 0.19306 RPN box loss: 0.01224 RPN score loss: 0.00701 RPN total loss: 0.01924 Total loss: 2.33757 timestamp: 1654919731.373245 iteration: 6045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20801 FastRCNN class loss: 0.13722 FastRCNN total loss: 0.34523 L1 loss: 0.0000e+00 L2 loss: 1.82195 Learning rate: 0.02 Mask loss: 0.32316 RPN box loss: 0.07311 RPN score loss: 0.01097 RPN total loss: 0.08408 Total loss: 2.57441 timestamp: 1654919734.571009 iteration: 6050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09515 FastRCNN class loss: 0.0516 FastRCNN total loss: 0.14674 L1 loss: 0.0000e+00 L2 loss: 1.82161 Learning rate: 0.02 Mask loss: 0.15485 RPN box loss: 0.08845 RPN score loss: 0.00834 RPN total loss: 0.0968 Total loss: 2.22 timestamp: 1654919737.8158896 iteration: 6055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14379 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.20613 L1 loss: 0.0000e+00 L2 loss: 1.82124 Learning rate: 0.02 Mask loss: 0.14906 RPN box loss: 0.0756 RPN score loss: 0.00806 RPN total loss: 0.08366 Total loss: 2.2601 timestamp: 1654919740.983864 iteration: 6060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1606 FastRCNN class loss: 0.11186 FastRCNN total loss: 0.27246 L1 loss: 0.0000e+00 L2 loss: 1.8209 Learning rate: 0.02 Mask loss: 0.18429 RPN box loss: 0.0742 RPN score loss: 0.02662 RPN total loss: 0.10081 Total loss: 2.37845 timestamp: 1654919744.3965256 iteration: 6065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1955 FastRCNN class loss: 0.10268 FastRCNN total loss: 0.29819 L1 loss: 0.0000e+00 L2 loss: 1.82056 Learning rate: 0.02 Mask loss: 0.17393 RPN box loss: 0.03135 RPN score loss: 0.00355 RPN total loss: 0.0349 Total loss: 2.32758 timestamp: 1654919747.6084971 iteration: 6070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1973 FastRCNN class loss: 0.15596 FastRCNN total loss: 0.35326 L1 loss: 0.0000e+00 L2 loss: 1.82021 Learning rate: 0.02 Mask loss: 0.18589 RPN box loss: 0.04793 RPN score loss: 0.01059 RPN total loss: 0.05851 Total loss: 2.41788 timestamp: 1654919750.8329673 iteration: 6075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21005 FastRCNN class loss: 0.09153 FastRCNN total loss: 0.30158 L1 loss: 0.0000e+00 L2 loss: 1.81987 Learning rate: 0.02 Mask loss: 0.21953 RPN box loss: 0.02303 RPN score loss: 0.01099 RPN total loss: 0.03402 Total loss: 2.375 timestamp: 1654919754.0945022 iteration: 6080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13068 FastRCNN class loss: 0.06874 FastRCNN total loss: 0.19942 L1 loss: 0.0000e+00 L2 loss: 1.81954 Learning rate: 0.02 Mask loss: 0.15584 RPN box loss: 0.01119 RPN score loss: 0.00561 RPN total loss: 0.0168 Total loss: 2.19159 timestamp: 1654919757.2462626 iteration: 6085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10038 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.16629 L1 loss: 0.0000e+00 L2 loss: 1.81921 Learning rate: 0.02 Mask loss: 0.1692 RPN box loss: 0.03168 RPN score loss: 0.00866 RPN total loss: 0.04033 Total loss: 2.19503 timestamp: 1654919760.4901686 iteration: 6090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20371 FastRCNN class loss: 0.0892 FastRCNN total loss: 0.29291 L1 loss: 0.0000e+00 L2 loss: 1.8189 Learning rate: 0.02 Mask loss: 0.19505 RPN box loss: 0.05591 RPN score loss: 0.00219 RPN total loss: 0.0581 Total loss: 2.36495 timestamp: 1654919763.6875665 iteration: 6095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.192 FastRCNN class loss: 0.09738 FastRCNN total loss: 0.28939 L1 loss: 0.0000e+00 L2 loss: 1.81855 Learning rate: 0.02 Mask loss: 0.27882 RPN box loss: 0.0572 RPN score loss: 0.01111 RPN total loss: 0.06831 Total loss: 2.45508 timestamp: 1654919767.0916703 iteration: 6100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13032 FastRCNN class loss: 0.07777 FastRCNN total loss: 0.2081 L1 loss: 0.0000e+00 L2 loss: 1.81821 Learning rate: 0.02 Mask loss: 0.15184 RPN box loss: 0.04507 RPN score loss: 0.01221 RPN total loss: 0.05728 Total loss: 2.23542 timestamp: 1654919770.3337717 iteration: 6105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.199 FastRCNN class loss: 0.11131 FastRCNN total loss: 0.31031 L1 loss: 0.0000e+00 L2 loss: 1.81787 Learning rate: 0.02 Mask loss: 0.19494 RPN box loss: 0.02741 RPN score loss: 0.00631 RPN total loss: 0.03372 Total loss: 2.35685 timestamp: 1654919773.6623468 iteration: 6110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16622 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.2288 L1 loss: 0.0000e+00 L2 loss: 1.81754 Learning rate: 0.02 Mask loss: 0.12528 RPN box loss: 0.00999 RPN score loss: 0.00543 RPN total loss: 0.01542 Total loss: 2.18704 timestamp: 1654919776.8121502 iteration: 6115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10117 FastRCNN class loss: 0.04712 FastRCNN total loss: 0.14829 L1 loss: 0.0000e+00 L2 loss: 1.8172 Learning rate: 0.02 Mask loss: 0.17059 RPN box loss: 0.0577 RPN score loss: 0.02544 RPN total loss: 0.08314 Total loss: 2.21922 timestamp: 1654919780.05699 iteration: 6120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21645 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.31739 L1 loss: 0.0000e+00 L2 loss: 1.81685 Learning rate: 0.02 Mask loss: 0.16457 RPN box loss: 0.0516 RPN score loss: 0.00784 RPN total loss: 0.05943 Total loss: 2.35824 timestamp: 1654919783.388935 iteration: 6125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13525 FastRCNN class loss: 0.10514 FastRCNN total loss: 0.24039 L1 loss: 0.0000e+00 L2 loss: 1.81651 Learning rate: 0.02 Mask loss: 0.17319 RPN box loss: 0.02754 RPN score loss: 0.0087 RPN total loss: 0.03624 Total loss: 2.26633 timestamp: 1654919786.52992 iteration: 6130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30238 FastRCNN class loss: 0.10156 FastRCNN total loss: 0.40394 L1 loss: 0.0000e+00 L2 loss: 1.81616 Learning rate: 0.02 Mask loss: 0.31481 RPN box loss: 0.06207 RPN score loss: 0.00974 RPN total loss: 0.07181 Total loss: 2.60673 timestamp: 1654919789.8064744 iteration: 6135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14406 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.22673 L1 loss: 0.0000e+00 L2 loss: 1.81583 Learning rate: 0.02 Mask loss: 0.15781 RPN box loss: 0.03922 RPN score loss: 0.00733 RPN total loss: 0.04655 Total loss: 2.24691 timestamp: 1654919793.0249074 iteration: 6140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1488 FastRCNN class loss: 0.10989 FastRCNN total loss: 0.25869 L1 loss: 0.0000e+00 L2 loss: 1.81548 Learning rate: 0.02 Mask loss: 0.14462 RPN box loss: 0.0154 RPN score loss: 0.00521 RPN total loss: 0.02061 Total loss: 2.2394 timestamp: 1654919796.2948713 iteration: 6145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2214 FastRCNN class loss: 0.10608 FastRCNN total loss: 0.32748 L1 loss: 0.0000e+00 L2 loss: 1.81515 Learning rate: 0.02 Mask loss: 0.16477 RPN box loss: 0.03098 RPN score loss: 0.00708 RPN total loss: 0.03806 Total loss: 2.34547 timestamp: 1654919799.4927971 iteration: 6150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18296 FastRCNN class loss: 0.10779 FastRCNN total loss: 0.29075 L1 loss: 0.0000e+00 L2 loss: 1.81482 Learning rate: 0.02 Mask loss: 0.18998 RPN box loss: 0.02189 RPN score loss: 0.00495 RPN total loss: 0.02685 Total loss: 2.3224 timestamp: 1654919802.9103496 iteration: 6155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15257 FastRCNN class loss: 0.11078 FastRCNN total loss: 0.26335 L1 loss: 0.0000e+00 L2 loss: 1.81447 Learning rate: 0.02 Mask loss: 0.16734 RPN box loss: 0.02629 RPN score loss: 0.00479 RPN total loss: 0.03108 Total loss: 2.27624 timestamp: 1654919806.1338923 iteration: 6160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19583 FastRCNN class loss: 0.07892 FastRCNN total loss: 0.27475 L1 loss: 0.0000e+00 L2 loss: 1.81413 Learning rate: 0.02 Mask loss: 0.15338 RPN box loss: 0.0073 RPN score loss: 0.00133 RPN total loss: 0.00863 Total loss: 2.2509 timestamp: 1654919809.3779328 iteration: 6165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08997 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.17004 L1 loss: 0.0000e+00 L2 loss: 1.81379 Learning rate: 0.02 Mask loss: 0.20671 RPN box loss: 0.0643 RPN score loss: 0.01351 RPN total loss: 0.07782 Total loss: 2.26836 timestamp: 1654919812.6699052 iteration: 6170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19467 FastRCNN class loss: 0.17864 FastRCNN total loss: 0.37332 L1 loss: 0.0000e+00 L2 loss: 1.81346 Learning rate: 0.02 Mask loss: 0.17016 RPN box loss: 0.04895 RPN score loss: 0.01255 RPN total loss: 0.06151 Total loss: 2.41845 timestamp: 1654919816.0166733 iteration: 6175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2159 FastRCNN class loss: 0.11126 FastRCNN total loss: 0.32716 L1 loss: 0.0000e+00 L2 loss: 1.81315 Learning rate: 0.02 Mask loss: 0.26313 RPN box loss: 0.04383 RPN score loss: 0.00515 RPN total loss: 0.04898 Total loss: 2.45242 timestamp: 1654919819.2956572 iteration: 6180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14973 FastRCNN class loss: 0.08561 FastRCNN total loss: 0.23534 L1 loss: 0.0000e+00 L2 loss: 1.8128 Learning rate: 0.02 Mask loss: 0.1405 RPN box loss: 0.01437 RPN score loss: 0.01284 RPN total loss: 0.02721 Total loss: 2.21585 timestamp: 1654919822.4554775 iteration: 6185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22612 FastRCNN class loss: 0.19846 FastRCNN total loss: 0.42458 L1 loss: 0.0000e+00 L2 loss: 1.81244 Learning rate: 0.02 Mask loss: 0.30919 RPN box loss: 0.05065 RPN score loss: 0.01349 RPN total loss: 0.06414 Total loss: 2.61035 timestamp: 1654919825.7837694 iteration: 6190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18894 FastRCNN class loss: 0.10307 FastRCNN total loss: 0.292 L1 loss: 0.0000e+00 L2 loss: 1.8121 Learning rate: 0.02 Mask loss: 0.2195 RPN box loss: 0.04007 RPN score loss: 0.00565 RPN total loss: 0.04572 Total loss: 2.36931 timestamp: 1654919829.0171094 iteration: 6195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14701 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.2159 L1 loss: 0.0000e+00 L2 loss: 1.81176 Learning rate: 0.02 Mask loss: 0.16199 RPN box loss: 0.01386 RPN score loss: 0.0071 RPN total loss: 0.02096 Total loss: 2.21062 timestamp: 1654919832.3106475 iteration: 6200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09302 FastRCNN class loss: 0.07758 FastRCNN total loss: 0.1706 L1 loss: 0.0000e+00 L2 loss: 1.81142 Learning rate: 0.02 Mask loss: 0.13868 RPN box loss: 0.01128 RPN score loss: 0.00336 RPN total loss: 0.01464 Total loss: 2.13534 timestamp: 1654919835.5651965 iteration: 6205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13485 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.20729 L1 loss: 0.0000e+00 L2 loss: 1.8111 Learning rate: 0.02 Mask loss: 0.15341 RPN box loss: 0.04389 RPN score loss: 0.01055 RPN total loss: 0.05443 Total loss: 2.22623 timestamp: 1654919838.8810387 iteration: 6210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11035 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.17926 L1 loss: 0.0000e+00 L2 loss: 1.81077 Learning rate: 0.02 Mask loss: 0.1465 RPN box loss: 0.03531 RPN score loss: 0.01814 RPN total loss: 0.05344 Total loss: 2.18997 timestamp: 1654919842.1097085 iteration: 6215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14325 FastRCNN class loss: 0.07524 FastRCNN total loss: 0.21849 L1 loss: 0.0000e+00 L2 loss: 1.81045 Learning rate: 0.02 Mask loss: 0.15576 RPN box loss: 0.06695 RPN score loss: 0.00988 RPN total loss: 0.07683 Total loss: 2.26153 timestamp: 1654919845.3892465 iteration: 6220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17048 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.25659 L1 loss: 0.0000e+00 L2 loss: 1.8101 Learning rate: 0.02 Mask loss: 0.24488 RPN box loss: 0.04339 RPN score loss: 0.00841 RPN total loss: 0.0518 Total loss: 2.36338 timestamp: 1654919848.7130196 iteration: 6225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19333 FastRCNN class loss: 0.10607 FastRCNN total loss: 0.2994 L1 loss: 0.0000e+00 L2 loss: 1.80976 Learning rate: 0.02 Mask loss: 0.23031 RPN box loss: 0.03595 RPN score loss: 0.0094 RPN total loss: 0.04535 Total loss: 2.38482 timestamp: 1654919851.9350033 iteration: 6230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25368 FastRCNN class loss: 0.10903 FastRCNN total loss: 0.36272 L1 loss: 0.0000e+00 L2 loss: 1.80944 Learning rate: 0.02 Mask loss: 0.22223 RPN box loss: 0.0747 RPN score loss: 0.00806 RPN total loss: 0.08277 Total loss: 2.47716 timestamp: 1654919855.2570305 iteration: 6235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15287 FastRCNN class loss: 0.09631 FastRCNN total loss: 0.24917 L1 loss: 0.0000e+00 L2 loss: 1.80911 Learning rate: 0.02 Mask loss: 0.20289 RPN box loss: 0.0375 RPN score loss: 0.0099 RPN total loss: 0.0474 Total loss: 2.30857 timestamp: 1654919858.3878348 iteration: 6240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22863 FastRCNN class loss: 0.10804 FastRCNN total loss: 0.33667 L1 loss: 0.0000e+00 L2 loss: 1.80878 Learning rate: 0.02 Mask loss: 0.18479 RPN box loss: 0.03599 RPN score loss: 0.02365 RPN total loss: 0.05964 Total loss: 2.38989 timestamp: 1654919861.7299635 iteration: 6245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16145 FastRCNN class loss: 0.06424 FastRCNN total loss: 0.22569 L1 loss: 0.0000e+00 L2 loss: 1.80843 Learning rate: 0.02 Mask loss: 0.15223 RPN box loss: 0.01091 RPN score loss: 0.00252 RPN total loss: 0.01342 Total loss: 2.19977 timestamp: 1654919864.9490623 iteration: 6250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13536 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.20115 L1 loss: 0.0000e+00 L2 loss: 1.80809 Learning rate: 0.02 Mask loss: 0.2006 RPN box loss: 0.01941 RPN score loss: 0.00666 RPN total loss: 0.02607 Total loss: 2.23591 timestamp: 1654919868.1577036 iteration: 6255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18518 FastRCNN class loss: 0.05905 FastRCNN total loss: 0.24424 L1 loss: 0.0000e+00 L2 loss: 1.80776 Learning rate: 0.02 Mask loss: 0.12045 RPN box loss: 0.03146 RPN score loss: 0.00855 RPN total loss: 0.04001 Total loss: 2.21246 timestamp: 1654919871.313962 iteration: 6260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20508 FastRCNN class loss: 0.19042 FastRCNN total loss: 0.39551 L1 loss: 0.0000e+00 L2 loss: 1.80743 Learning rate: 0.02 Mask loss: 0.22493 RPN box loss: 0.03358 RPN score loss: 0.00947 RPN total loss: 0.04306 Total loss: 2.47093 timestamp: 1654919874.6105 iteration: 6265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20979 FastRCNN class loss: 0.10953 FastRCNN total loss: 0.31932 L1 loss: 0.0000e+00 L2 loss: 1.80709 Learning rate: 0.02 Mask loss: 0.1841 RPN box loss: 0.0457 RPN score loss: 0.00826 RPN total loss: 0.05396 Total loss: 2.36447 timestamp: 1654919877.8250105 iteration: 6270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18953 FastRCNN class loss: 0.09024 FastRCNN total loss: 0.27976 L1 loss: 0.0000e+00 L2 loss: 1.80677 Learning rate: 0.02 Mask loss: 0.1741 RPN box loss: 0.07874 RPN score loss: 0.00643 RPN total loss: 0.08517 Total loss: 2.34579 timestamp: 1654919881.1511755 iteration: 6275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16312 FastRCNN class loss: 0.09166 FastRCNN total loss: 0.25477 L1 loss: 0.0000e+00 L2 loss: 1.80644 Learning rate: 0.02 Mask loss: 0.16633 RPN box loss: 0.04242 RPN score loss: 0.00602 RPN total loss: 0.04845 Total loss: 2.27599 timestamp: 1654919884.4490318 iteration: 6280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16811 FastRCNN class loss: 0.09115 FastRCNN total loss: 0.25926 L1 loss: 0.0000e+00 L2 loss: 1.8061 Learning rate: 0.02 Mask loss: 0.19493 RPN box loss: 0.01608 RPN score loss: 0.00677 RPN total loss: 0.02285 Total loss: 2.28315 timestamp: 1654919887.783465 iteration: 6285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17129 FastRCNN class loss: 0.09382 FastRCNN total loss: 0.26511 L1 loss: 0.0000e+00 L2 loss: 1.80578 Learning rate: 0.02 Mask loss: 0.1673 RPN box loss: 0.02539 RPN score loss: 0.01521 RPN total loss: 0.0406 Total loss: 2.27879 timestamp: 1654919891.0015578 iteration: 6290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18188 FastRCNN class loss: 0.06737 FastRCNN total loss: 0.24925 L1 loss: 0.0000e+00 L2 loss: 1.80544 Learning rate: 0.02 Mask loss: 0.24447 RPN box loss: 0.09246 RPN score loss: 0.01356 RPN total loss: 0.10601 Total loss: 2.40518 timestamp: 1654919894.1701949 iteration: 6295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26081 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.33869 L1 loss: 0.0000e+00 L2 loss: 1.8051 Learning rate: 0.02 Mask loss: 0.19703 RPN box loss: 0.09846 RPN score loss: 0.01108 RPN total loss: 0.10954 Total loss: 2.45036 timestamp: 1654919897.489312 iteration: 6300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22768 FastRCNN class loss: 0.10146 FastRCNN total loss: 0.32914 L1 loss: 0.0000e+00 L2 loss: 1.80476 Learning rate: 0.02 Mask loss: 0.25766 RPN box loss: 0.04569 RPN score loss: 0.00619 RPN total loss: 0.05188 Total loss: 2.44344 timestamp: 1654919900.635113 iteration: 6305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18436 FastRCNN class loss: 0.18724 FastRCNN total loss: 0.3716 L1 loss: 0.0000e+00 L2 loss: 1.80443 Learning rate: 0.02 Mask loss: 0.22364 RPN box loss: 0.08422 RPN score loss: 0.01006 RPN total loss: 0.09428 Total loss: 2.49396 timestamp: 1654919903.8613513 iteration: 6310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23862 FastRCNN class loss: 0.15061 FastRCNN total loss: 0.38923 L1 loss: 0.0000e+00 L2 loss: 1.80409 Learning rate: 0.02 Mask loss: 0.29331 RPN box loss: 0.04711 RPN score loss: 0.01405 RPN total loss: 0.06116 Total loss: 2.54779 timestamp: 1654919907.0861547 iteration: 6315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18814 FastRCNN class loss: 0.11533 FastRCNN total loss: 0.30346 L1 loss: 0.0000e+00 L2 loss: 1.80376 Learning rate: 0.02 Mask loss: 0.23691 RPN box loss: 0.0163 RPN score loss: 0.00833 RPN total loss: 0.02463 Total loss: 2.36876 timestamp: 1654919910.302799 iteration: 6320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21251 FastRCNN class loss: 0.15373 FastRCNN total loss: 0.36624 L1 loss: 0.0000e+00 L2 loss: 1.80343 Learning rate: 0.02 Mask loss: 0.18137 RPN box loss: 0.09422 RPN score loss: 0.00977 RPN total loss: 0.104 Total loss: 2.45504 timestamp: 1654919913.5178862 iteration: 6325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19083 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.26068 L1 loss: 0.0000e+00 L2 loss: 1.8031 Learning rate: 0.02 Mask loss: 0.32317 RPN box loss: 0.03304 RPN score loss: 0.00805 RPN total loss: 0.04109 Total loss: 2.42803 timestamp: 1654919916.9042873 iteration: 6330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23946 FastRCNN class loss: 0.10339 FastRCNN total loss: 0.34285 L1 loss: 0.0000e+00 L2 loss: 1.80277 Learning rate: 0.02 Mask loss: 0.23227 RPN box loss: 0.05095 RPN score loss: 0.00614 RPN total loss: 0.05708 Total loss: 2.43497 timestamp: 1654919920.1759074 iteration: 6335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14643 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.21834 L1 loss: 0.0000e+00 L2 loss: 1.80245 Learning rate: 0.02 Mask loss: 0.17457 RPN box loss: 0.05893 RPN score loss: 0.01476 RPN total loss: 0.0737 Total loss: 2.26907 timestamp: 1654919923.43612 iteration: 6340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10208 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.17913 L1 loss: 0.0000e+00 L2 loss: 1.8021 Learning rate: 0.02 Mask loss: 0.14988 RPN box loss: 0.01045 RPN score loss: 0.00515 RPN total loss: 0.0156 Total loss: 2.1467 timestamp: 1654919926.7942376 iteration: 6345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14899 FastRCNN class loss: 0.09976 FastRCNN total loss: 0.24875 L1 loss: 0.0000e+00 L2 loss: 1.80176 Learning rate: 0.02 Mask loss: 0.17855 RPN box loss: 0.04474 RPN score loss: 0.0075 RPN total loss: 0.05224 Total loss: 2.2813 timestamp: 1654919930.0403368 iteration: 6350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13099 FastRCNN class loss: 0.0998 FastRCNN total loss: 0.23079 L1 loss: 0.0000e+00 L2 loss: 1.80141 Learning rate: 0.02 Mask loss: 0.19844 RPN box loss: 0.07149 RPN score loss: 0.01733 RPN total loss: 0.08882 Total loss: 2.31947 timestamp: 1654919933.3412552 iteration: 6355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23218 FastRCNN class loss: 0.20172 FastRCNN total loss: 0.4339 L1 loss: 0.0000e+00 L2 loss: 1.80106 Learning rate: 0.02 Mask loss: 0.18856 RPN box loss: 0.05337 RPN score loss: 0.01909 RPN total loss: 0.07246 Total loss: 2.49597 timestamp: 1654919936.5405684 iteration: 6360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25245 FastRCNN class loss: 0.07967 FastRCNN total loss: 0.33212 L1 loss: 0.0000e+00 L2 loss: 1.80073 Learning rate: 0.02 Mask loss: 0.16269 RPN box loss: 0.02227 RPN score loss: 0.01337 RPN total loss: 0.03563 Total loss: 2.33116 timestamp: 1654919939.8359518 iteration: 6365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16406 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.23273 L1 loss: 0.0000e+00 L2 loss: 1.80041 Learning rate: 0.02 Mask loss: 0.17655 RPN box loss: 0.1099 RPN score loss: 0.00979 RPN total loss: 0.11969 Total loss: 2.32938 timestamp: 1654919943.0293148 iteration: 6370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21739 FastRCNN class loss: 0.14277 FastRCNN total loss: 0.36016 L1 loss: 0.0000e+00 L2 loss: 1.80006 Learning rate: 0.02 Mask loss: 0.28344 RPN box loss: 0.01576 RPN score loss: 0.00443 RPN total loss: 0.02019 Total loss: 2.46386 timestamp: 1654919946.3259294 iteration: 6375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20558 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.28781 L1 loss: 0.0000e+00 L2 loss: 1.79974 Learning rate: 0.02 Mask loss: 0.15001 RPN box loss: 0.01891 RPN score loss: 0.00626 RPN total loss: 0.02516 Total loss: 2.26272 timestamp: 1654919949.5730555 iteration: 6380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18137 FastRCNN class loss: 0.07591 FastRCNN total loss: 0.25728 L1 loss: 0.0000e+00 L2 loss: 1.79941 Learning rate: 0.02 Mask loss: 0.17018 RPN box loss: 0.0377 RPN score loss: 0.00828 RPN total loss: 0.04598 Total loss: 2.27285 timestamp: 1654919952.8411002 iteration: 6385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13671 FastRCNN class loss: 0.0717 FastRCNN total loss: 0.2084 L1 loss: 0.0000e+00 L2 loss: 1.79908 Learning rate: 0.02 Mask loss: 0.24733 RPN box loss: 0.01262 RPN score loss: 0.00432 RPN total loss: 0.01694 Total loss: 2.27174 timestamp: 1654919956.1440482 iteration: 6390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11678 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 1.79875 Learning rate: 0.02 Mask loss: 0.22414 RPN box loss: 0.01983 RPN score loss: 0.00688 RPN total loss: 0.0267 Total loss: 2.22691 timestamp: 1654919959.391312 iteration: 6395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11429 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 1.79842 Learning rate: 0.02 Mask loss: 0.18788 RPN box loss: 0.02722 RPN score loss: 0.02267 RPN total loss: 0.0499 Total loss: 2.23666 timestamp: 1654919962.6208525 iteration: 6400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1658 FastRCNN class loss: 0.09355 FastRCNN total loss: 0.25935 L1 loss: 0.0000e+00 L2 loss: 1.79809 Learning rate: 0.02 Mask loss: 0.15829 RPN box loss: 0.05247 RPN score loss: 0.00946 RPN total loss: 0.06193 Total loss: 2.27766 timestamp: 1654919965.9041946 iteration: 6405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13949 FastRCNN class loss: 0.13174 FastRCNN total loss: 0.27123 L1 loss: 0.0000e+00 L2 loss: 1.79776 Learning rate: 0.02 Mask loss: 0.23348 RPN box loss: 0.0562 RPN score loss: 0.01529 RPN total loss: 0.07148 Total loss: 2.37395 timestamp: 1654919969.2263286 iteration: 6410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14505 FastRCNN class loss: 0.08089 FastRCNN total loss: 0.22593 L1 loss: 0.0000e+00 L2 loss: 1.79743 Learning rate: 0.02 Mask loss: 0.19471 RPN box loss: 0.06281 RPN score loss: 0.01071 RPN total loss: 0.07352 Total loss: 2.29159 timestamp: 1654919972.482975 iteration: 6415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17078 FastRCNN class loss: 0.10286 FastRCNN total loss: 0.27365 L1 loss: 0.0000e+00 L2 loss: 1.79708 Learning rate: 0.02 Mask loss: 0.23738 RPN box loss: 0.04823 RPN score loss: 0.00791 RPN total loss: 0.05614 Total loss: 2.36424 timestamp: 1654919975.841286 iteration: 6420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07439 FastRCNN class loss: 0.06268 FastRCNN total loss: 0.13707 L1 loss: 0.0000e+00 L2 loss: 1.79677 Learning rate: 0.02 Mask loss: 0.10409 RPN box loss: 0.07868 RPN score loss: 0.00838 RPN total loss: 0.08706 Total loss: 2.125 timestamp: 1654919979.07589 iteration: 6425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27149 FastRCNN class loss: 0.14762 FastRCNN total loss: 0.41911 L1 loss: 0.0000e+00 L2 loss: 1.79644 Learning rate: 0.02 Mask loss: 0.33655 RPN box loss: 0.01638 RPN score loss: 0.00574 RPN total loss: 0.02212 Total loss: 2.57422 timestamp: 1654919982.3705478 iteration: 6430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19687 FastRCNN class loss: 0.1076 FastRCNN total loss: 0.30447 L1 loss: 0.0000e+00 L2 loss: 1.79612 Learning rate: 0.02 Mask loss: 0.15421 RPN box loss: 0.02656 RPN score loss: 0.00915 RPN total loss: 0.03571 Total loss: 2.29051 timestamp: 1654919985.614693 iteration: 6435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2131 FastRCNN class loss: 0.15135 FastRCNN total loss: 0.36445 L1 loss: 0.0000e+00 L2 loss: 1.7958 Learning rate: 0.02 Mask loss: 0.22358 RPN box loss: 0.02285 RPN score loss: 0.01338 RPN total loss: 0.03623 Total loss: 2.42006 timestamp: 1654919988.8220298 iteration: 6440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13285 FastRCNN class loss: 0.11182 FastRCNN total loss: 0.24467 L1 loss: 0.0000e+00 L2 loss: 1.79547 Learning rate: 0.02 Mask loss: 0.18082 RPN box loss: 0.02229 RPN score loss: 0.01288 RPN total loss: 0.03517 Total loss: 2.25613 timestamp: 1654919992.2053835 iteration: 6445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22472 FastRCNN class loss: 0.10948 FastRCNN total loss: 0.3342 L1 loss: 0.0000e+00 L2 loss: 1.79515 Learning rate: 0.02 Mask loss: 0.20036 RPN box loss: 0.03244 RPN score loss: 0.0051 RPN total loss: 0.03754 Total loss: 2.36725 timestamp: 1654919995.4145014 iteration: 6450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2289 FastRCNN class loss: 0.16306 FastRCNN total loss: 0.39196 L1 loss: 0.0000e+00 L2 loss: 1.79482 Learning rate: 0.02 Mask loss: 0.2953 RPN box loss: 0.02964 RPN score loss: 0.0109 RPN total loss: 0.04054 Total loss: 2.52262 timestamp: 1654919998.7139113 iteration: 6455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14918 FastRCNN class loss: 0.11704 FastRCNN total loss: 0.26622 L1 loss: 0.0000e+00 L2 loss: 1.79448 Learning rate: 0.02 Mask loss: 0.21046 RPN box loss: 0.03508 RPN score loss: 0.00726 RPN total loss: 0.04234 Total loss: 2.31349 timestamp: 1654920001.9005046 iteration: 6460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25812 FastRCNN class loss: 0.14799 FastRCNN total loss: 0.40612 L1 loss: 0.0000e+00 L2 loss: 1.79414 Learning rate: 0.02 Mask loss: 0.18966 RPN box loss: 0.04104 RPN score loss: 0.0091 RPN total loss: 0.05014 Total loss: 2.44006 timestamp: 1654920005.132531 iteration: 6465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24879 FastRCNN class loss: 0.11918 FastRCNN total loss: 0.36797 L1 loss: 0.0000e+00 L2 loss: 1.79378 Learning rate: 0.02 Mask loss: 0.25781 RPN box loss: 0.02059 RPN score loss: 0.00511 RPN total loss: 0.0257 Total loss: 2.44526 timestamp: 1654920008.4829087 iteration: 6470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17857 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.27174 L1 loss: 0.0000e+00 L2 loss: 1.79345 Learning rate: 0.02 Mask loss: 0.21908 RPN box loss: 0.02262 RPN score loss: 0.00816 RPN total loss: 0.03078 Total loss: 2.31505 timestamp: 1654920011.6997175 iteration: 6475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14455 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.22431 L1 loss: 0.0000e+00 L2 loss: 1.79313 Learning rate: 0.02 Mask loss: 0.1334 RPN box loss: 0.09034 RPN score loss: 0.00843 RPN total loss: 0.09877 Total loss: 2.24961 timestamp: 1654920014.8614614 iteration: 6480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17551 FastRCNN class loss: 0.08222 FastRCNN total loss: 0.25773 L1 loss: 0.0000e+00 L2 loss: 1.7928 Learning rate: 0.02 Mask loss: 0.182 RPN box loss: 0.01994 RPN score loss: 0.00272 RPN total loss: 0.02265 Total loss: 2.25519 timestamp: 1654920018.089397 iteration: 6485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14231 FastRCNN class loss: 0.08485 FastRCNN total loss: 0.22716 L1 loss: 0.0000e+00 L2 loss: 1.79246 Learning rate: 0.02 Mask loss: 0.1765 RPN box loss: 0.04589 RPN score loss: 0.00428 RPN total loss: 0.05017 Total loss: 2.24629 timestamp: 1654920021.4688892 iteration: 6490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20882 FastRCNN class loss: 0.11977 FastRCNN total loss: 0.32859 L1 loss: 0.0000e+00 L2 loss: 1.79214 Learning rate: 0.02 Mask loss: 0.18212 RPN box loss: 0.04232 RPN score loss: 0.01811 RPN total loss: 0.06043 Total loss: 2.36327 timestamp: 1654920024.6530323 iteration: 6495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22313 FastRCNN class loss: 0.10905 FastRCNN total loss: 0.33218 L1 loss: 0.0000e+00 L2 loss: 1.79182 Learning rate: 0.02 Mask loss: 0.20036 RPN box loss: 0.01349 RPN score loss: 0.00848 RPN total loss: 0.02196 Total loss: 2.34632 timestamp: 1654920027.9145255 iteration: 6500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12388 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.17378 L1 loss: 0.0000e+00 L2 loss: 1.7915 Learning rate: 0.02 Mask loss: 0.1715 RPN box loss: 0.02891 RPN score loss: 0.01168 RPN total loss: 0.04059 Total loss: 2.17737 timestamp: 1654920031.121025 iteration: 6505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.09249 FastRCNN total loss: 0.24376 L1 loss: 0.0000e+00 L2 loss: 1.79117 Learning rate: 0.02 Mask loss: 0.22526 RPN box loss: 0.06536 RPN score loss: 0.0129 RPN total loss: 0.07826 Total loss: 2.33845 timestamp: 1654920034.359163 iteration: 6510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22614 FastRCNN class loss: 0.1058 FastRCNN total loss: 0.33195 L1 loss: 0.0000e+00 L2 loss: 1.79085 Learning rate: 0.02 Mask loss: 0.19433 RPN box loss: 0.04452 RPN score loss: 0.01386 RPN total loss: 0.05838 Total loss: 2.37551 timestamp: 1654920037.5139906 iteration: 6515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16978 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.2538 L1 loss: 0.0000e+00 L2 loss: 1.79052 Learning rate: 0.02 Mask loss: 0.1896 RPN box loss: 0.01474 RPN score loss: 0.00655 RPN total loss: 0.02129 Total loss: 2.25522 timestamp: 1654920040.6949232 iteration: 6520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23122 FastRCNN class loss: 0.13299 FastRCNN total loss: 0.36422 L1 loss: 0.0000e+00 L2 loss: 1.79019 Learning rate: 0.02 Mask loss: 0.22073 RPN box loss: 0.0126 RPN score loss: 0.00435 RPN total loss: 0.01696 Total loss: 2.3921 timestamp: 1654920043.8498406 iteration: 6525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22398 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.32492 L1 loss: 0.0000e+00 L2 loss: 1.78984 Learning rate: 0.02 Mask loss: 0.22507 RPN box loss: 0.0276 RPN score loss: 0.00994 RPN total loss: 0.03755 Total loss: 2.37737 timestamp: 1654920047.15571 iteration: 6530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25784 FastRCNN class loss: 0.10388 FastRCNN total loss: 0.36172 L1 loss: 0.0000e+00 L2 loss: 1.78949 Learning rate: 0.02 Mask loss: 0.25031 RPN box loss: 0.02457 RPN score loss: 0.01105 RPN total loss: 0.03562 Total loss: 2.43714 timestamp: 1654920050.3439126 iteration: 6535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19917 FastRCNN class loss: 0.09618 FastRCNN total loss: 0.29535 L1 loss: 0.0000e+00 L2 loss: 1.78918 Learning rate: 0.02 Mask loss: 0.28112 RPN box loss: 0.06718 RPN score loss: 0.0109 RPN total loss: 0.07807 Total loss: 2.44373 timestamp: 1654920053.6994002 iteration: 6540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19741 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.29435 L1 loss: 0.0000e+00 L2 loss: 1.78885 Learning rate: 0.02 Mask loss: 0.21773 RPN box loss: 0.06037 RPN score loss: 0.01668 RPN total loss: 0.07705 Total loss: 2.37798 timestamp: 1654920057.0266314 iteration: 6545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.219 FastRCNN class loss: 0.15181 FastRCNN total loss: 0.37081 L1 loss: 0.0000e+00 L2 loss: 1.78852 Learning rate: 0.02 Mask loss: 0.23192 RPN box loss: 0.08057 RPN score loss: 0.04128 RPN total loss: 0.12185 Total loss: 2.5131 timestamp: 1654920060.2825744 iteration: 6550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09241 FastRCNN class loss: 0.05492 FastRCNN total loss: 0.14733 L1 loss: 0.0000e+00 L2 loss: 1.78818 Learning rate: 0.02 Mask loss: 0.14886 RPN box loss: 0.056 RPN score loss: 0.00774 RPN total loss: 0.06374 Total loss: 2.14811 timestamp: 1654920063.6149085 iteration: 6555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07839 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.13384 L1 loss: 0.0000e+00 L2 loss: 1.78783 Learning rate: 0.02 Mask loss: 0.14389 RPN box loss: 0.02592 RPN score loss: 0.00697 RPN total loss: 0.03289 Total loss: 2.09845 timestamp: 1654920066.8379228 iteration: 6560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12224 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.18691 L1 loss: 0.0000e+00 L2 loss: 1.78751 Learning rate: 0.02 Mask loss: 0.18231 RPN box loss: 0.06522 RPN score loss: 0.00934 RPN total loss: 0.07456 Total loss: 2.23129 timestamp: 1654920070.1384683 iteration: 6565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13367 FastRCNN class loss: 0.08533 FastRCNN total loss: 0.21901 L1 loss: 0.0000e+00 L2 loss: 1.78718 Learning rate: 0.02 Mask loss: 0.16831 RPN box loss: 0.05885 RPN score loss: 0.00646 RPN total loss: 0.06531 Total loss: 2.23981 timestamp: 1654920073.3532917 iteration: 6570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11567 FastRCNN class loss: 0.07278 FastRCNN total loss: 0.18845 L1 loss: 0.0000e+00 L2 loss: 1.78685 Learning rate: 0.02 Mask loss: 0.13181 RPN box loss: 0.01351 RPN score loss: 0.00557 RPN total loss: 0.01908 Total loss: 2.12618 timestamp: 1654920076.619623 iteration: 6575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09121 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.15208 L1 loss: 0.0000e+00 L2 loss: 1.78651 Learning rate: 0.02 Mask loss: 0.13308 RPN box loss: 0.025 RPN score loss: 0.00441 RPN total loss: 0.0294 Total loss: 2.10108 timestamp: 1654920079.8142195 iteration: 6580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09229 FastRCNN class loss: 0.05112 FastRCNN total loss: 0.14342 L1 loss: 0.0000e+00 L2 loss: 1.78617 Learning rate: 0.02 Mask loss: 0.14496 RPN box loss: 0.00562 RPN score loss: 0.00602 RPN total loss: 0.01164 Total loss: 2.08619 timestamp: 1654920083.0960941 iteration: 6585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16722 FastRCNN class loss: 0.13308 FastRCNN total loss: 0.3003 L1 loss: 0.0000e+00 L2 loss: 1.78583 Learning rate: 0.02 Mask loss: 0.17934 RPN box loss: 0.02422 RPN score loss: 0.01102 RPN total loss: 0.03524 Total loss: 2.30071 timestamp: 1654920086.3356566 iteration: 6590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17698 FastRCNN class loss: 0.10448 FastRCNN total loss: 0.28147 L1 loss: 0.0000e+00 L2 loss: 1.78552 Learning rate: 0.02 Mask loss: 0.20351 RPN box loss: 0.06794 RPN score loss: 0.00451 RPN total loss: 0.07245 Total loss: 2.34295 timestamp: 1654920089.7197337 iteration: 6595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17154 FastRCNN class loss: 0.09579 FastRCNN total loss: 0.26733 L1 loss: 0.0000e+00 L2 loss: 1.78519 Learning rate: 0.02 Mask loss: 0.17721 RPN box loss: 0.03906 RPN score loss: 0.00619 RPN total loss: 0.04525 Total loss: 2.27498 timestamp: 1654920093.1305065 iteration: 6600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21068 FastRCNN class loss: 0.11672 FastRCNN total loss: 0.32739 L1 loss: 0.0000e+00 L2 loss: 1.78486 Learning rate: 0.02 Mask loss: 0.19798 RPN box loss: 0.06737 RPN score loss: 0.02329 RPN total loss: 0.09067 Total loss: 2.40091 timestamp: 1654920096.3259366 iteration: 6605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14409 FastRCNN class loss: 0.08549 FastRCNN total loss: 0.22958 L1 loss: 0.0000e+00 L2 loss: 1.78453 Learning rate: 0.02 Mask loss: 0.15766 RPN box loss: 0.0216 RPN score loss: 0.00417 RPN total loss: 0.02577 Total loss: 2.19755 timestamp: 1654920099.6760776 iteration: 6610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26542 FastRCNN class loss: 0.12272 FastRCNN total loss: 0.38814 L1 loss: 0.0000e+00 L2 loss: 1.7842 Learning rate: 0.02 Mask loss: 0.18819 RPN box loss: 0.06794 RPN score loss: 0.00734 RPN total loss: 0.07528 Total loss: 2.43581 timestamp: 1654920102.8429573 iteration: 6615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15286 FastRCNN class loss: 0.13615 FastRCNN total loss: 0.28902 L1 loss: 0.0000e+00 L2 loss: 1.78385 Learning rate: 0.02 Mask loss: 0.16964 RPN box loss: 0.0486 RPN score loss: 0.01819 RPN total loss: 0.06679 Total loss: 2.3093 timestamp: 1654920106.1642385 iteration: 6620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2191 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.29076 L1 loss: 0.0000e+00 L2 loss: 1.78351 Learning rate: 0.02 Mask loss: 0.14478 RPN box loss: 0.09259 RPN score loss: 0.00654 RPN total loss: 0.09913 Total loss: 2.31818 timestamp: 1654920109.3723652 iteration: 6625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16091 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.24939 L1 loss: 0.0000e+00 L2 loss: 1.7832 Learning rate: 0.02 Mask loss: 0.25144 RPN box loss: 0.14222 RPN score loss: 0.01195 RPN total loss: 0.15417 Total loss: 2.4382 timestamp: 1654920112.6857805 iteration: 6630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19653 FastRCNN class loss: 0.08043 FastRCNN total loss: 0.27696 L1 loss: 0.0000e+00 L2 loss: 1.78285 Learning rate: 0.02 Mask loss: 0.25849 RPN box loss: 0.03118 RPN score loss: 0.0041 RPN total loss: 0.03527 Total loss: 2.35357 timestamp: 1654920115.9231503 iteration: 6635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06231 FastRCNN class loss: 0.05431 FastRCNN total loss: 0.11662 L1 loss: 0.0000e+00 L2 loss: 1.78255 Learning rate: 0.02 Mask loss: 0.09675 RPN box loss: 0.0838 RPN score loss: 0.01199 RPN total loss: 0.09579 Total loss: 2.0917 timestamp: 1654920119.238916 iteration: 6640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19569 FastRCNN class loss: 0.10392 FastRCNN total loss: 0.2996 L1 loss: 0.0000e+00 L2 loss: 1.78224 Learning rate: 0.02 Mask loss: 0.2127 RPN box loss: 0.07337 RPN score loss: 0.01665 RPN total loss: 0.09003 Total loss: 2.38457 timestamp: 1654920122.5295117 iteration: 6645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18372 FastRCNN class loss: 0.11482 FastRCNN total loss: 0.29854 L1 loss: 0.0000e+00 L2 loss: 1.78189 Learning rate: 0.02 Mask loss: 0.21467 RPN box loss: 0.05691 RPN score loss: 0.01819 RPN total loss: 0.0751 Total loss: 2.37021 timestamp: 1654920125.700488 iteration: 6650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24408 FastRCNN class loss: 0.06703 FastRCNN total loss: 0.31111 L1 loss: 0.0000e+00 L2 loss: 1.78156 Learning rate: 0.02 Mask loss: 0.13051 RPN box loss: 0.07262 RPN score loss: 0.01746 RPN total loss: 0.09008 Total loss: 2.31325 timestamp: 1654920129.1208737 iteration: 6655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18454 FastRCNN class loss: 0.12014 FastRCNN total loss: 0.30468 L1 loss: 0.0000e+00 L2 loss: 1.78122 Learning rate: 0.02 Mask loss: 0.17949 RPN box loss: 0.0457 RPN score loss: 0.0094 RPN total loss: 0.05509 Total loss: 2.32048 timestamp: 1654920132.353009 iteration: 6660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14009 FastRCNN class loss: 0.04532 FastRCNN total loss: 0.18541 L1 loss: 0.0000e+00 L2 loss: 1.78089 Learning rate: 0.02 Mask loss: 0.16297 RPN box loss: 0.05214 RPN score loss: 0.00207 RPN total loss: 0.05421 Total loss: 2.18349 timestamp: 1654920135.7707446 iteration: 6665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1538 FastRCNN class loss: 0.12293 FastRCNN total loss: 0.27672 L1 loss: 0.0000e+00 L2 loss: 1.78055 Learning rate: 0.02 Mask loss: 0.24816 RPN box loss: 0.01363 RPN score loss: 0.00433 RPN total loss: 0.01796 Total loss: 2.32339 timestamp: 1654920138.9791634 iteration: 6670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21596 FastRCNN class loss: 0.13645 FastRCNN total loss: 0.35241 L1 loss: 0.0000e+00 L2 loss: 1.78021 Learning rate: 0.02 Mask loss: 0.39448 RPN box loss: 0.02459 RPN score loss: 0.00468 RPN total loss: 0.02927 Total loss: 2.55637 timestamp: 1654920142.2172475 iteration: 6675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2321 FastRCNN class loss: 0.13384 FastRCNN total loss: 0.36594 L1 loss: 0.0000e+00 L2 loss: 1.77987 Learning rate: 0.02 Mask loss: 0.23125 RPN box loss: 0.02955 RPN score loss: 0.00775 RPN total loss: 0.0373 Total loss: 2.41435 timestamp: 1654920145.4296718 iteration: 6680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14264 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.21929 L1 loss: 0.0000e+00 L2 loss: 1.77955 Learning rate: 0.02 Mask loss: 0.16029 RPN box loss: 0.03653 RPN score loss: 0.00869 RPN total loss: 0.04523 Total loss: 2.20436 timestamp: 1654920148.7446947 iteration: 6685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.171 FastRCNN class loss: 0.10905 FastRCNN total loss: 0.28005 L1 loss: 0.0000e+00 L2 loss: 1.77924 Learning rate: 0.02 Mask loss: 0.24765 RPN box loss: 0.0435 RPN score loss: 0.01348 RPN total loss: 0.05699 Total loss: 2.36393 timestamp: 1654920151.9014537 iteration: 6690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2143 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.29239 L1 loss: 0.0000e+00 L2 loss: 1.7789 Learning rate: 0.02 Mask loss: 0.12853 RPN box loss: 0.06319 RPN score loss: 0.01335 RPN total loss: 0.07654 Total loss: 2.27636 timestamp: 1654920155.1906495 iteration: 6695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20742 FastRCNN class loss: 0.13641 FastRCNN total loss: 0.34383 L1 loss: 0.0000e+00 L2 loss: 1.77856 Learning rate: 0.02 Mask loss: 0.31943 RPN box loss: 0.02082 RPN score loss: 0.01025 RPN total loss: 0.03107 Total loss: 2.47289 timestamp: 1654920158.5199726 iteration: 6700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13158 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.19826 L1 loss: 0.0000e+00 L2 loss: 1.77824 Learning rate: 0.02 Mask loss: 0.21176 RPN box loss: 0.02535 RPN score loss: 0.00546 RPN total loss: 0.03081 Total loss: 2.21907 timestamp: 1654920161.7815468 iteration: 6705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14966 FastRCNN class loss: 0.08952 FastRCNN total loss: 0.23918 L1 loss: 0.0000e+00 L2 loss: 1.7779 Learning rate: 0.02 Mask loss: 0.13025 RPN box loss: 0.0344 RPN score loss: 0.00559 RPN total loss: 0.03999 Total loss: 2.18733 timestamp: 1654920165.1120374 iteration: 6710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13542 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.20737 L1 loss: 0.0000e+00 L2 loss: 1.77759 Learning rate: 0.02 Mask loss: 0.18224 RPN box loss: 0.23386 RPN score loss: 0.01848 RPN total loss: 0.25234 Total loss: 2.41954 timestamp: 1654920168.2695503 iteration: 6715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10807 FastRCNN class loss: 0.08006 FastRCNN total loss: 0.18814 L1 loss: 0.0000e+00 L2 loss: 1.77727 Learning rate: 0.02 Mask loss: 0.17916 RPN box loss: 0.0586 RPN score loss: 0.00537 RPN total loss: 0.06398 Total loss: 2.20854 timestamp: 1654920171.5995598 iteration: 6720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1684 FastRCNN class loss: 0.11831 FastRCNN total loss: 0.28671 L1 loss: 0.0000e+00 L2 loss: 1.77692 Learning rate: 0.02 Mask loss: 0.17058 RPN box loss: 0.12544 RPN score loss: 0.00629 RPN total loss: 0.13172 Total loss: 2.36593 timestamp: 1654920174.7918959 iteration: 6725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19315 FastRCNN class loss: 0.11323 FastRCNN total loss: 0.30637 L1 loss: 0.0000e+00 L2 loss: 1.77658 Learning rate: 0.02 Mask loss: 0.18045 RPN box loss: 0.03405 RPN score loss: 0.00966 RPN total loss: 0.04371 Total loss: 2.30711 timestamp: 1654920178.1319282 iteration: 6730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2509 FastRCNN class loss: 0.22478 FastRCNN total loss: 0.47568 L1 loss: 0.0000e+00 L2 loss: 1.77625 Learning rate: 0.02 Mask loss: 0.32147 RPN box loss: 0.05972 RPN score loss: 0.02343 RPN total loss: 0.08315 Total loss: 2.65655 timestamp: 1654920181.3015478 iteration: 6735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13695 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.21214 L1 loss: 0.0000e+00 L2 loss: 1.77593 Learning rate: 0.02 Mask loss: 0.10423 RPN box loss: 0.03437 RPN score loss: 0.0095 RPN total loss: 0.04387 Total loss: 2.13618 timestamp: 1654920184.6075487 iteration: 6740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22355 FastRCNN class loss: 0.14297 FastRCNN total loss: 0.36652 L1 loss: 0.0000e+00 L2 loss: 1.7756 Learning rate: 0.02 Mask loss: 0.28928 RPN box loss: 0.03592 RPN score loss: 0.00898 RPN total loss: 0.0449 Total loss: 2.4763 timestamp: 1654920188.051427 iteration: 6745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18105 FastRCNN class loss: 0.05223 FastRCNN total loss: 0.23328 L1 loss: 0.0000e+00 L2 loss: 1.77526 Learning rate: 0.02 Mask loss: 0.11082 RPN box loss: 0.03095 RPN score loss: 0.00561 RPN total loss: 0.03656 Total loss: 2.15592 timestamp: 1654920191.3407881 iteration: 6750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17769 FastRCNN class loss: 0.15972 FastRCNN total loss: 0.3374 L1 loss: 0.0000e+00 L2 loss: 1.77492 Learning rate: 0.02 Mask loss: 0.1767 RPN box loss: 0.03103 RPN score loss: 0.00915 RPN total loss: 0.04017 Total loss: 2.3292 timestamp: 1654920194.7675 iteration: 6755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2044 FastRCNN class loss: 0.12563 FastRCNN total loss: 0.33004 L1 loss: 0.0000e+00 L2 loss: 1.77459 Learning rate: 0.02 Mask loss: 0.17201 RPN box loss: 0.02873 RPN score loss: 0.0141 RPN total loss: 0.04283 Total loss: 2.31947 timestamp: 1654920197.9882133 iteration: 6760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15154 FastRCNN class loss: 0.05798 FastRCNN total loss: 0.20952 L1 loss: 0.0000e+00 L2 loss: 1.77428 Learning rate: 0.02 Mask loss: 0.16187 RPN box loss: 0.00668 RPN score loss: 0.00478 RPN total loss: 0.01146 Total loss: 2.15713 timestamp: 1654920201.299845 iteration: 6765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14109 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.21728 L1 loss: 0.0000e+00 L2 loss: 1.77394 Learning rate: 0.02 Mask loss: 0.14447 RPN box loss: 0.05521 RPN score loss: 0.01208 RPN total loss: 0.06729 Total loss: 2.20297 timestamp: 1654920204.6150124 iteration: 6770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16042 FastRCNN class loss: 0.08299 FastRCNN total loss: 0.24342 L1 loss: 0.0000e+00 L2 loss: 1.77362 Learning rate: 0.02 Mask loss: 0.18215 RPN box loss: 0.04005 RPN score loss: 0.01295 RPN total loss: 0.053 Total loss: 2.25219 timestamp: 1654920207.9116673 iteration: 6775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12921 FastRCNN class loss: 0.09441 FastRCNN total loss: 0.22362 L1 loss: 0.0000e+00 L2 loss: 1.77331 Learning rate: 0.02 Mask loss: 0.19208 RPN box loss: 0.02215 RPN score loss: 0.00937 RPN total loss: 0.03152 Total loss: 2.22053 timestamp: 1654920211.132429 iteration: 6780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09746 FastRCNN class loss: 0.04525 FastRCNN total loss: 0.14271 L1 loss: 0.0000e+00 L2 loss: 1.77298 Learning rate: 0.02 Mask loss: 0.25904 RPN box loss: 0.0296 RPN score loss: 0.00986 RPN total loss: 0.03946 Total loss: 2.21418 timestamp: 1654920214.4602833 iteration: 6785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11361 FastRCNN class loss: 0.11104 FastRCNN total loss: 0.22464 L1 loss: 0.0000e+00 L2 loss: 1.77265 Learning rate: 0.02 Mask loss: 0.10805 RPN box loss: 0.01297 RPN score loss: 0.00606 RPN total loss: 0.01903 Total loss: 2.12438 timestamp: 1654920217.7473288 iteration: 6790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14509 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.21233 L1 loss: 0.0000e+00 L2 loss: 1.77234 Learning rate: 0.02 Mask loss: 0.13038 RPN box loss: 0.01714 RPN score loss: 0.00743 RPN total loss: 0.02457 Total loss: 2.13962 timestamp: 1654920221.047269 iteration: 6795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19603 FastRCNN class loss: 0.12909 FastRCNN total loss: 0.32512 L1 loss: 0.0000e+00 L2 loss: 1.77201 Learning rate: 0.02 Mask loss: 0.14241 RPN box loss: 0.04934 RPN score loss: 0.00836 RPN total loss: 0.0577 Total loss: 2.29725 timestamp: 1654920224.362802 iteration: 6800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15726 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.22373 L1 loss: 0.0000e+00 L2 loss: 1.77169 Learning rate: 0.02 Mask loss: 0.19731 RPN box loss: 0.03732 RPN score loss: 0.00328 RPN total loss: 0.0406 Total loss: 2.23334 timestamp: 1654920227.6195133 iteration: 6805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14051 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.21876 L1 loss: 0.0000e+00 L2 loss: 1.77135 Learning rate: 0.02 Mask loss: 0.20547 RPN box loss: 0.01795 RPN score loss: 0.00364 RPN total loss: 0.02159 Total loss: 2.21717 timestamp: 1654920230.9497094 iteration: 6810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09293 FastRCNN class loss: 0.0531 FastRCNN total loss: 0.14603 L1 loss: 0.0000e+00 L2 loss: 1.77101 Learning rate: 0.02 Mask loss: 0.20452 RPN box loss: 0.04233 RPN score loss: 0.00608 RPN total loss: 0.04841 Total loss: 2.16996 timestamp: 1654920234.1005564 iteration: 6815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19314 FastRCNN class loss: 0.13522 FastRCNN total loss: 0.32836 L1 loss: 0.0000e+00 L2 loss: 1.7707 Learning rate: 0.02 Mask loss: 0.23491 RPN box loss: 0.02957 RPN score loss: 0.01781 RPN total loss: 0.04738 Total loss: 2.38134 timestamp: 1654920237.4420018 iteration: 6820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18664 FastRCNN class loss: 0.09457 FastRCNN total loss: 0.28121 L1 loss: 0.0000e+00 L2 loss: 1.7704 Learning rate: 0.02 Mask loss: 0.14199 RPN box loss: 0.01528 RPN score loss: 0.00337 RPN total loss: 0.01864 Total loss: 2.21224 timestamp: 1654920240.6645706 iteration: 6825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22155 FastRCNN class loss: 0.10557 FastRCNN total loss: 0.32711 L1 loss: 0.0000e+00 L2 loss: 1.7701 Learning rate: 0.02 Mask loss: 0.19048 RPN box loss: 0.03982 RPN score loss: 0.00905 RPN total loss: 0.04886 Total loss: 2.33655 timestamp: 1654920243.938044 iteration: 6830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18732 FastRCNN class loss: 0.1431 FastRCNN total loss: 0.33041 L1 loss: 0.0000e+00 L2 loss: 1.76977 Learning rate: 0.02 Mask loss: 0.18719 RPN box loss: 0.02773 RPN score loss: 0.01414 RPN total loss: 0.04187 Total loss: 2.32924 timestamp: 1654920247.177677 iteration: 6835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17018 FastRCNN class loss: 0.08974 FastRCNN total loss: 0.25992 L1 loss: 0.0000e+00 L2 loss: 1.76944 Learning rate: 0.02 Mask loss: 0.15905 RPN box loss: 0.08523 RPN score loss: 0.01292 RPN total loss: 0.09815 Total loss: 2.28657 timestamp: 1654920250.3832157 iteration: 6840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14032 FastRCNN class loss: 0.0857 FastRCNN total loss: 0.22602 L1 loss: 0.0000e+00 L2 loss: 1.76913 Learning rate: 0.02 Mask loss: 0.23065 RPN box loss: 0.04204 RPN score loss: 0.0111 RPN total loss: 0.05314 Total loss: 2.27892 timestamp: 1654920253.605665 iteration: 6845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15097 FastRCNN class loss: 0.08895 FastRCNN total loss: 0.23991 L1 loss: 0.0000e+00 L2 loss: 1.76879 Learning rate: 0.02 Mask loss: 0.13741 RPN box loss: 0.01714 RPN score loss: 0.00381 RPN total loss: 0.02095 Total loss: 2.16707 timestamp: 1654920256.8424532 iteration: 6850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14855 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.21949 L1 loss: 0.0000e+00 L2 loss: 1.76847 Learning rate: 0.02 Mask loss: 0.16443 RPN box loss: 0.01645 RPN score loss: 0.00798 RPN total loss: 0.02443 Total loss: 2.17683 timestamp: 1654920260.1419702 iteration: 6855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10781 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.17952 L1 loss: 0.0000e+00 L2 loss: 1.76816 Learning rate: 0.02 Mask loss: 0.27953 RPN box loss: 0.03816 RPN score loss: 0.00558 RPN total loss: 0.04374 Total loss: 2.27094 timestamp: 1654920263.2972698 iteration: 6860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14253 FastRCNN class loss: 0.09798 FastRCNN total loss: 0.24051 L1 loss: 0.0000e+00 L2 loss: 1.76783 Learning rate: 0.02 Mask loss: 0.14643 RPN box loss: 0.0235 RPN score loss: 0.00418 RPN total loss: 0.02768 Total loss: 2.18246 timestamp: 1654920266.5739374 iteration: 6865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22648 FastRCNN class loss: 0.1285 FastRCNN total loss: 0.35497 L1 loss: 0.0000e+00 L2 loss: 1.76754 Learning rate: 0.02 Mask loss: 0.24838 RPN box loss: 0.017 RPN score loss: 0.0208 RPN total loss: 0.0378 Total loss: 2.40869 timestamp: 1654920269.7821999 iteration: 6870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1745 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.24465 L1 loss: 0.0000e+00 L2 loss: 1.76721 Learning rate: 0.02 Mask loss: 0.23014 RPN box loss: 0.02848 RPN score loss: 0.00929 RPN total loss: 0.03777 Total loss: 2.27978 timestamp: 1654920273.1745899 iteration: 6875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15225 FastRCNN class loss: 0.08572 FastRCNN total loss: 0.23797 L1 loss: 0.0000e+00 L2 loss: 1.76689 Learning rate: 0.02 Mask loss: 0.18477 RPN box loss: 0.02989 RPN score loss: 0.00291 RPN total loss: 0.03279 Total loss: 2.22243 timestamp: 1654920276.482016 iteration: 6880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15124 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.23843 L1 loss: 0.0000e+00 L2 loss: 1.76657 Learning rate: 0.02 Mask loss: 0.1804 RPN box loss: 0.02838 RPN score loss: 0.01599 RPN total loss: 0.04436 Total loss: 2.22975 timestamp: 1654920279.8132646 iteration: 6885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15609 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.23392 L1 loss: 0.0000e+00 L2 loss: 1.76626 Learning rate: 0.02 Mask loss: 0.1862 RPN box loss: 0.04007 RPN score loss: 0.00612 RPN total loss: 0.04619 Total loss: 2.23257 timestamp: 1654920283.1946838 iteration: 6890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20508 FastRCNN class loss: 0.10964 FastRCNN total loss: 0.31471 L1 loss: 0.0000e+00 L2 loss: 1.76594 Learning rate: 0.02 Mask loss: 0.29426 RPN box loss: 0.06072 RPN score loss: 0.0127 RPN total loss: 0.07341 Total loss: 2.44833 timestamp: 1654920286.456884 iteration: 6895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16016 FastRCNN class loss: 0.11502 FastRCNN total loss: 0.27518 L1 loss: 0.0000e+00 L2 loss: 1.76561 Learning rate: 0.02 Mask loss: 0.24602 RPN box loss: 0.11168 RPN score loss: 0.00937 RPN total loss: 0.12105 Total loss: 2.40787 timestamp: 1654920289.7075286 iteration: 6900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17782 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.27361 L1 loss: 0.0000e+00 L2 loss: 1.76531 Learning rate: 0.02 Mask loss: 0.22509 RPN box loss: 0.08105 RPN score loss: 0.01785 RPN total loss: 0.0989 Total loss: 2.36291 timestamp: 1654920292.913173 iteration: 6905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12943 FastRCNN class loss: 0.08215 FastRCNN total loss: 0.21157 L1 loss: 0.0000e+00 L2 loss: 1.76497 Learning rate: 0.02 Mask loss: 0.15815 RPN box loss: 0.02109 RPN score loss: 0.00431 RPN total loss: 0.0254 Total loss: 2.1601 timestamp: 1654920296.2607665 iteration: 6910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15024 FastRCNN class loss: 0.11275 FastRCNN total loss: 0.26299 L1 loss: 0.0000e+00 L2 loss: 1.76464 Learning rate: 0.02 Mask loss: 0.15512 RPN box loss: 0.02336 RPN score loss: 0.00319 RPN total loss: 0.02656 Total loss: 2.20931 timestamp: 1654920299.4252627 iteration: 6915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20736 FastRCNN class loss: 0.11395 FastRCNN total loss: 0.32131 L1 loss: 0.0000e+00 L2 loss: 1.76431 Learning rate: 0.02 Mask loss: 0.21527 RPN box loss: 0.05751 RPN score loss: 0.01705 RPN total loss: 0.07456 Total loss: 2.37545 timestamp: 1654920302.7199981 iteration: 6920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19297 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.27105 L1 loss: 0.0000e+00 L2 loss: 1.76399 Learning rate: 0.02 Mask loss: 0.17378 RPN box loss: 0.05229 RPN score loss: 0.00866 RPN total loss: 0.06095 Total loss: 2.26977 timestamp: 1654920305.8672209 iteration: 6925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22092 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.29677 L1 loss: 0.0000e+00 L2 loss: 1.76366 Learning rate: 0.02 Mask loss: 0.20852 RPN box loss: 0.01632 RPN score loss: 0.00643 RPN total loss: 0.02275 Total loss: 2.2917 timestamp: 1654920309.107166 iteration: 6930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22802 FastRCNN class loss: 0.13197 FastRCNN total loss: 0.36 L1 loss: 0.0000e+00 L2 loss: 1.76334 Learning rate: 0.02 Mask loss: 0.25404 RPN box loss: 0.02229 RPN score loss: 0.00902 RPN total loss: 0.03131 Total loss: 2.40868 timestamp: 1654920312.3015523 iteration: 6935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15881 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.21501 L1 loss: 0.0000e+00 L2 loss: 1.76301 Learning rate: 0.02 Mask loss: 0.13919 RPN box loss: 0.01068 RPN score loss: 0.00566 RPN total loss: 0.01635 Total loss: 2.13356 timestamp: 1654920315.6010132 iteration: 6940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17566 FastRCNN class loss: 0.08286 FastRCNN total loss: 0.25853 L1 loss: 0.0000e+00 L2 loss: 1.76269 Learning rate: 0.02 Mask loss: 0.24365 RPN box loss: 0.04777 RPN score loss: 0.0104 RPN total loss: 0.05817 Total loss: 2.32304 timestamp: 1654920318.8139157 iteration: 6945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18394 FastRCNN class loss: 0.08943 FastRCNN total loss: 0.27337 L1 loss: 0.0000e+00 L2 loss: 1.76239 Learning rate: 0.02 Mask loss: 0.27214 RPN box loss: 0.10368 RPN score loss: 0.01483 RPN total loss: 0.11851 Total loss: 2.42642 timestamp: 1654920322.0530193 iteration: 6950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17878 FastRCNN class loss: 0.11967 FastRCNN total loss: 0.29846 L1 loss: 0.0000e+00 L2 loss: 1.76207 Learning rate: 0.02 Mask loss: 0.24012 RPN box loss: 0.02423 RPN score loss: 0.00325 RPN total loss: 0.02748 Total loss: 2.32813 timestamp: 1654920325.3445628 iteration: 6955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13008 FastRCNN class loss: 0.07054 FastRCNN total loss: 0.20061 L1 loss: 0.0000e+00 L2 loss: 1.76175 Learning rate: 0.02 Mask loss: 0.18088 RPN box loss: 0.01639 RPN score loss: 0.00952 RPN total loss: 0.02591 Total loss: 2.16915 timestamp: 1654920328.5955126 iteration: 6960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23201 FastRCNN class loss: 0.08108 FastRCNN total loss: 0.31308 L1 loss: 0.0000e+00 L2 loss: 1.7614 Learning rate: 0.02 Mask loss: 0.14872 RPN box loss: 0.03762 RPN score loss: 0.00749 RPN total loss: 0.04511 Total loss: 2.26832 timestamp: 1654920331.9009545 iteration: 6965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24165 FastRCNN class loss: 0.1081 FastRCNN total loss: 0.34974 L1 loss: 0.0000e+00 L2 loss: 1.76108 Learning rate: 0.02 Mask loss: 0.20122 RPN box loss: 0.10297 RPN score loss: 0.01473 RPN total loss: 0.1177 Total loss: 2.42974 timestamp: 1654920335.1237407 iteration: 6970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22987 FastRCNN class loss: 0.14794 FastRCNN total loss: 0.37781 L1 loss: 0.0000e+00 L2 loss: 1.76074 Learning rate: 0.02 Mask loss: 0.22456 RPN box loss: 0.02631 RPN score loss: 0.00535 RPN total loss: 0.03166 Total loss: 2.39477 timestamp: 1654920338.3415778 iteration: 6975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.198 FastRCNN class loss: 0.10489 FastRCNN total loss: 0.30289 L1 loss: 0.0000e+00 L2 loss: 1.76043 Learning rate: 0.02 Mask loss: 0.2714 RPN box loss: 0.06018 RPN score loss: 0.00966 RPN total loss: 0.06984 Total loss: 2.40457 timestamp: 1654920341.5701058 iteration: 6980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13162 FastRCNN class loss: 0.08282 FastRCNN total loss: 0.21444 L1 loss: 0.0000e+00 L2 loss: 1.7601 Learning rate: 0.02 Mask loss: 0.14919 RPN box loss: 0.03781 RPN score loss: 0.00969 RPN total loss: 0.04749 Total loss: 2.17123 timestamp: 1654920344.8328993 iteration: 6985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17623 FastRCNN class loss: 0.08595 FastRCNN total loss: 0.26218 L1 loss: 0.0000e+00 L2 loss: 1.75978 Learning rate: 0.02 Mask loss: 0.18995 RPN box loss: 0.04184 RPN score loss: 0.00639 RPN total loss: 0.04824 Total loss: 2.26014 timestamp: 1654920348.1034358 iteration: 6990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16354 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.23793 L1 loss: 0.0000e+00 L2 loss: 1.75947 Learning rate: 0.02 Mask loss: 0.149 RPN box loss: 0.02796 RPN score loss: 0.00558 RPN total loss: 0.03354 Total loss: 2.17994 timestamp: 1654920351.5209694 iteration: 6995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28595 FastRCNN class loss: 0.08992 FastRCNN total loss: 0.37586 L1 loss: 0.0000e+00 L2 loss: 1.75917 Learning rate: 0.02 Mask loss: 0.17309 RPN box loss: 0.01624 RPN score loss: 0.00272 RPN total loss: 0.01896 Total loss: 2.32708 timestamp: 1654920354.7576017 iteration: 7000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22158 FastRCNN class loss: 0.12739 FastRCNN total loss: 0.34896 L1 loss: 0.0000e+00 L2 loss: 1.75886 Learning rate: 0.02 Mask loss: 0.21054 RPN box loss: 0.02525 RPN score loss: 0.00683 RPN total loss: 0.03208 Total loss: 2.35044 timestamp: 1654920357.9684803 iteration: 7005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1204 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.2032 L1 loss: 0.0000e+00 L2 loss: 1.75856 Learning rate: 0.02 Mask loss: 0.15775 RPN box loss: 0.04129 RPN score loss: 0.00426 RPN total loss: 0.04555 Total loss: 2.16506 timestamp: 1654920361.532515 iteration: 7010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21563 FastRCNN class loss: 0.11325 FastRCNN total loss: 0.32888 L1 loss: 0.0000e+00 L2 loss: 1.75824 Learning rate: 0.02 Mask loss: 0.2338 RPN box loss: 0.03769 RPN score loss: 0.00413 RPN total loss: 0.04182 Total loss: 2.36274 timestamp: 1654920364.941177 iteration: 7015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16762 FastRCNN class loss: 0.07688 FastRCNN total loss: 0.24449 L1 loss: 0.0000e+00 L2 loss: 1.75792 Learning rate: 0.02 Mask loss: 0.12424 RPN box loss: 0.03459 RPN score loss: 0.00875 RPN total loss: 0.04334 Total loss: 2.16999 timestamp: 1654920368.2073565 iteration: 7020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.14593 L1 loss: 0.0000e+00 L2 loss: 1.75761 Learning rate: 0.02 Mask loss: 0.13087 RPN box loss: 0.07289 RPN score loss: 0.00345 RPN total loss: 0.07634 Total loss: 2.11074 timestamp: 1654920371.4014258 iteration: 7025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17044 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.24559 L1 loss: 0.0000e+00 L2 loss: 1.75729 Learning rate: 0.02 Mask loss: 0.10431 RPN box loss: 0.02674 RPN score loss: 0.00311 RPN total loss: 0.02985 Total loss: 2.13704 timestamp: 1654920374.7663686 iteration: 7030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2183 FastRCNN class loss: 0.1158 FastRCNN total loss: 0.3341 L1 loss: 0.0000e+00 L2 loss: 1.75697 Learning rate: 0.02 Mask loss: 0.19786 RPN box loss: 0.03126 RPN score loss: 0.00497 RPN total loss: 0.03623 Total loss: 2.32517 timestamp: 1654920378.0993223 iteration: 7035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20783 FastRCNN class loss: 0.15707 FastRCNN total loss: 0.36491 L1 loss: 0.0000e+00 L2 loss: 1.75667 Learning rate: 0.02 Mask loss: 0.19164 RPN box loss: 0.05737 RPN score loss: 0.01065 RPN total loss: 0.06803 Total loss: 2.38124 timestamp: 1654920381.457076 iteration: 7040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20506 FastRCNN class loss: 0.07207 FastRCNN total loss: 0.27713 L1 loss: 0.0000e+00 L2 loss: 1.75634 Learning rate: 0.02 Mask loss: 0.19871 RPN box loss: 0.04253 RPN score loss: 0.01579 RPN total loss: 0.05832 Total loss: 2.2905 timestamp: 1654920384.8374047 iteration: 7045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22657 FastRCNN class loss: 0.14554 FastRCNN total loss: 0.37211 L1 loss: 0.0000e+00 L2 loss: 1.75602 Learning rate: 0.02 Mask loss: 0.29293 RPN box loss: 0.01548 RPN score loss: 0.02632 RPN total loss: 0.0418 Total loss: 2.46286 timestamp: 1654920388.0237389 iteration: 7050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20882 FastRCNN class loss: 0.10048 FastRCNN total loss: 0.3093 L1 loss: 0.0000e+00 L2 loss: 1.75569 Learning rate: 0.02 Mask loss: 0.21794 RPN box loss: 0.03202 RPN score loss: 0.00846 RPN total loss: 0.04049 Total loss: 2.32342 timestamp: 1654920391.306167 iteration: 7055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16031 FastRCNN class loss: 0.08105 FastRCNN total loss: 0.24136 L1 loss: 0.0000e+00 L2 loss: 1.75535 Learning rate: 0.02 Mask loss: 0.16099 RPN box loss: 0.07154 RPN score loss: 0.00686 RPN total loss: 0.07841 Total loss: 2.23611 timestamp: 1654920394.4707682 iteration: 7060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11642 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.19473 L1 loss: 0.0000e+00 L2 loss: 1.75504 Learning rate: 0.02 Mask loss: 0.20039 RPN box loss: 0.05033 RPN score loss: 0.01397 RPN total loss: 0.06429 Total loss: 2.21445 timestamp: 1654920397.8678944 iteration: 7065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14511 FastRCNN class loss: 0.0792 FastRCNN total loss: 0.22431 L1 loss: 0.0000e+00 L2 loss: 1.75473 Learning rate: 0.02 Mask loss: 0.18339 RPN box loss: 0.03009 RPN score loss: 0.01092 RPN total loss: 0.04102 Total loss: 2.20345 timestamp: 1654920401.1278079 iteration: 7070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18312 FastRCNN class loss: 0.09927 FastRCNN total loss: 0.28239 L1 loss: 0.0000e+00 L2 loss: 1.75441 Learning rate: 0.02 Mask loss: 0.21444 RPN box loss: 0.02017 RPN score loss: 0.00571 RPN total loss: 0.02588 Total loss: 2.27711 timestamp: 1654920404.4504893 iteration: 7075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15536 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.2308 L1 loss: 0.0000e+00 L2 loss: 1.75407 Learning rate: 0.02 Mask loss: 0.23292 RPN box loss: 0.02758 RPN score loss: 0.00623 RPN total loss: 0.03381 Total loss: 2.2516 timestamp: 1654920407.5952535 iteration: 7080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15065 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.21857 L1 loss: 0.0000e+00 L2 loss: 1.75374 Learning rate: 0.02 Mask loss: 0.17719 RPN box loss: 0.01644 RPN score loss: 0.00605 RPN total loss: 0.02249 Total loss: 2.17199 timestamp: 1654920410.8446739 iteration: 7085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30351 FastRCNN class loss: 0.17415 FastRCNN total loss: 0.47766 L1 loss: 0.0000e+00 L2 loss: 1.75343 Learning rate: 0.02 Mask loss: 0.23062 RPN box loss: 0.03073 RPN score loss: 0.00994 RPN total loss: 0.04068 Total loss: 2.50239 timestamp: 1654920414.0116236 iteration: 7090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19465 FastRCNN class loss: 0.12855 FastRCNN total loss: 0.3232 L1 loss: 0.0000e+00 L2 loss: 1.75311 Learning rate: 0.02 Mask loss: 0.15119 RPN box loss: 0.03887 RPN score loss: 0.00423 RPN total loss: 0.0431 Total loss: 2.2706 timestamp: 1654920417.3229582 iteration: 7095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15763 FastRCNN class loss: 0.09675 FastRCNN total loss: 0.25437 L1 loss: 0.0000e+00 L2 loss: 1.75279 Learning rate: 0.02 Mask loss: 0.18002 RPN box loss: 0.03882 RPN score loss: 0.0117 RPN total loss: 0.05052 Total loss: 2.2377 timestamp: 1654920420.6435146 iteration: 7100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1275 FastRCNN class loss: 0.1136 FastRCNN total loss: 0.2411 L1 loss: 0.0000e+00 L2 loss: 1.75246 Learning rate: 0.02 Mask loss: 0.26628 RPN box loss: 0.06588 RPN score loss: 0.02416 RPN total loss: 0.09004 Total loss: 2.34988 timestamp: 1654920423.837498 iteration: 7105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10872 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.18043 L1 loss: 0.0000e+00 L2 loss: 1.75213 Learning rate: 0.02 Mask loss: 0.16795 RPN box loss: 0.0145 RPN score loss: 0.00738 RPN total loss: 0.02187 Total loss: 2.12238 timestamp: 1654920427.13547 iteration: 7110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08246 FastRCNN class loss: 0.0514 FastRCNN total loss: 0.13387 L1 loss: 0.0000e+00 L2 loss: 1.7518 Learning rate: 0.02 Mask loss: 0.11944 RPN box loss: 0.00372 RPN score loss: 0.00642 RPN total loss: 0.01014 Total loss: 2.01525 timestamp: 1654920430.33064 iteration: 7115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22314 FastRCNN class loss: 0.09781 FastRCNN total loss: 0.32095 L1 loss: 0.0000e+00 L2 loss: 1.75147 Learning rate: 0.02 Mask loss: 0.15484 RPN box loss: 0.02623 RPN score loss: 0.00343 RPN total loss: 0.02965 Total loss: 2.25691 timestamp: 1654920433.5704174 iteration: 7120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16399 FastRCNN class loss: 0.11053 FastRCNN total loss: 0.27451 L1 loss: 0.0000e+00 L2 loss: 1.75115 Learning rate: 0.02 Mask loss: 0.15752 RPN box loss: 0.05799 RPN score loss: 0.01476 RPN total loss: 0.07275 Total loss: 2.25594 timestamp: 1654920436.6888978 iteration: 7125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15932 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.24787 L1 loss: 0.0000e+00 L2 loss: 1.75082 Learning rate: 0.02 Mask loss: 0.20874 RPN box loss: 0.0254 RPN score loss: 0.00687 RPN total loss: 0.03227 Total loss: 2.2397 timestamp: 1654920439.994341 iteration: 7130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16634 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.24261 L1 loss: 0.0000e+00 L2 loss: 1.7505 Learning rate: 0.02 Mask loss: 0.15102 RPN box loss: 0.02394 RPN score loss: 0.0052 RPN total loss: 0.02914 Total loss: 2.17327 timestamp: 1654920443.1310687 iteration: 7135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16419 FastRCNN class loss: 0.12119 FastRCNN total loss: 0.28538 L1 loss: 0.0000e+00 L2 loss: 1.75019 Learning rate: 0.02 Mask loss: 0.13402 RPN box loss: 0.12155 RPN score loss: 0.01354 RPN total loss: 0.13509 Total loss: 2.30468 timestamp: 1654920446.3912504 iteration: 7140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20333 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.31487 L1 loss: 0.0000e+00 L2 loss: 1.74986 Learning rate: 0.02 Mask loss: 0.19308 RPN box loss: 0.04655 RPN score loss: 0.00456 RPN total loss: 0.0511 Total loss: 2.30891 timestamp: 1654920449.5862515 iteration: 7145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18244 FastRCNN class loss: 0.13972 FastRCNN total loss: 0.32216 L1 loss: 0.0000e+00 L2 loss: 1.74953 Learning rate: 0.02 Mask loss: 0.22413 RPN box loss: 0.0367 RPN score loss: 0.01105 RPN total loss: 0.04775 Total loss: 2.34358 timestamp: 1654920452.8127813 iteration: 7150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16081 FastRCNN class loss: 0.09072 FastRCNN total loss: 0.25152 L1 loss: 0.0000e+00 L2 loss: 1.74922 Learning rate: 0.02 Mask loss: 0.17286 RPN box loss: 0.02856 RPN score loss: 0.00405 RPN total loss: 0.03261 Total loss: 2.2062 timestamp: 1654920456.0675886 iteration: 7155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17287 FastRCNN class loss: 0.12574 FastRCNN total loss: 0.2986 L1 loss: 0.0000e+00 L2 loss: 1.7489 Learning rate: 0.02 Mask loss: 0.17407 RPN box loss: 0.01129 RPN score loss: 0.00675 RPN total loss: 0.01804 Total loss: 2.23961 timestamp: 1654920459.2601545 iteration: 7160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26623 FastRCNN class loss: 0.18874 FastRCNN total loss: 0.45497 L1 loss: 0.0000e+00 L2 loss: 1.74856 Learning rate: 0.02 Mask loss: 0.25516 RPN box loss: 0.02597 RPN score loss: 0.01154 RPN total loss: 0.03751 Total loss: 2.49621 timestamp: 1654920462.6817298 iteration: 7165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18773 FastRCNN class loss: 0.08959 FastRCNN total loss: 0.27732 L1 loss: 0.0000e+00 L2 loss: 1.74824 Learning rate: 0.02 Mask loss: 0.19945 RPN box loss: 0.05281 RPN score loss: 0.01245 RPN total loss: 0.06526 Total loss: 2.29027 timestamp: 1654920465.8893375 iteration: 7170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21389 FastRCNN class loss: 0.12569 FastRCNN total loss: 0.33957 L1 loss: 0.0000e+00 L2 loss: 1.74792 Learning rate: 0.02 Mask loss: 0.20009 RPN box loss: 0.01649 RPN score loss: 0.0042 RPN total loss: 0.0207 Total loss: 2.30828 timestamp: 1654920469.2172797 iteration: 7175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1467 FastRCNN class loss: 0.10388 FastRCNN total loss: 0.25058 L1 loss: 0.0000e+00 L2 loss: 1.74762 Learning rate: 0.02 Mask loss: 0.18491 RPN box loss: 0.04615 RPN score loss: 0.00658 RPN total loss: 0.05273 Total loss: 2.23584 timestamp: 1654920472.3594124 iteration: 7180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17858 FastRCNN class loss: 0.14222 FastRCNN total loss: 0.3208 L1 loss: 0.0000e+00 L2 loss: 1.74729 Learning rate: 0.02 Mask loss: 0.15697 RPN box loss: 0.0382 RPN score loss: 0.00618 RPN total loss: 0.04438 Total loss: 2.26944 timestamp: 1654920475.6641335 iteration: 7185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1619 FastRCNN class loss: 0.14246 FastRCNN total loss: 0.30435 L1 loss: 0.0000e+00 L2 loss: 1.74697 Learning rate: 0.02 Mask loss: 0.20515 RPN box loss: 0.01968 RPN score loss: 0.00552 RPN total loss: 0.0252 Total loss: 2.28166 timestamp: 1654920478.7915375 iteration: 7190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10779 FastRCNN class loss: 0.11908 FastRCNN total loss: 0.22687 L1 loss: 0.0000e+00 L2 loss: 1.74666 Learning rate: 0.02 Mask loss: 0.13717 RPN box loss: 0.01291 RPN score loss: 0.00234 RPN total loss: 0.01525 Total loss: 2.12595 timestamp: 1654920482.0807142 iteration: 7195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19498 FastRCNN class loss: 0.10432 FastRCNN total loss: 0.2993 L1 loss: 0.0000e+00 L2 loss: 1.74634 Learning rate: 0.02 Mask loss: 0.24801 RPN box loss: 0.01388 RPN score loss: 0.00673 RPN total loss: 0.02061 Total loss: 2.31426 timestamp: 1654920485.2736645 iteration: 7200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15727 FastRCNN class loss: 0.13649 FastRCNN total loss: 0.29376 L1 loss: 0.0000e+00 L2 loss: 1.74603 Learning rate: 0.02 Mask loss: 0.25688 RPN box loss: 0.03862 RPN score loss: 0.00484 RPN total loss: 0.04345 Total loss: 2.34012 timestamp: 1654920488.6031241 iteration: 7205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14073 FastRCNN class loss: 0.14123 FastRCNN total loss: 0.28196 L1 loss: 0.0000e+00 L2 loss: 1.74572 Learning rate: 0.02 Mask loss: 0.13263 RPN box loss: 0.01874 RPN score loss: 0.00407 RPN total loss: 0.0228 Total loss: 2.1831 timestamp: 1654920491.7255726 iteration: 7210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19605 FastRCNN class loss: 0.15312 FastRCNN total loss: 0.34917 L1 loss: 0.0000e+00 L2 loss: 1.7454 Learning rate: 0.02 Mask loss: 0.28528 RPN box loss: 0.06289 RPN score loss: 0.00246 RPN total loss: 0.06535 Total loss: 2.4452 timestamp: 1654920494.9652972 iteration: 7215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20637 FastRCNN class loss: 0.12158 FastRCNN total loss: 0.32795 L1 loss: 0.0000e+00 L2 loss: 1.74507 Learning rate: 0.02 Mask loss: 0.21843 RPN box loss: 0.07796 RPN score loss: 0.0223 RPN total loss: 0.10026 Total loss: 2.39172 timestamp: 1654920498.380641 iteration: 7220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1369 FastRCNN class loss: 0.09545 FastRCNN total loss: 0.23235 L1 loss: 0.0000e+00 L2 loss: 1.74474 Learning rate: 0.02 Mask loss: 0.35318 RPN box loss: 0.02159 RPN score loss: 0.00609 RPN total loss: 0.02769 Total loss: 2.35794 timestamp: 1654920501.5902433 iteration: 7225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20101 FastRCNN class loss: 0.10274 FastRCNN total loss: 0.30374 L1 loss: 0.0000e+00 L2 loss: 1.74441 Learning rate: 0.02 Mask loss: 0.14918 RPN box loss: 0.01394 RPN score loss: 0.00649 RPN total loss: 0.02043 Total loss: 2.21776 timestamp: 1654920504.8790212 iteration: 7230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23461 FastRCNN class loss: 0.12049 FastRCNN total loss: 0.35509 L1 loss: 0.0000e+00 L2 loss: 1.74409 Learning rate: 0.02 Mask loss: 0.29479 RPN box loss: 0.0296 RPN score loss: 0.0093 RPN total loss: 0.0389 Total loss: 2.43288 timestamp: 1654920508.069529 iteration: 7235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16032 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.23211 L1 loss: 0.0000e+00 L2 loss: 1.74377 Learning rate: 0.02 Mask loss: 0.14865 RPN box loss: 0.02338 RPN score loss: 0.00459 RPN total loss: 0.02797 Total loss: 2.15251 timestamp: 1654920511.2517235 iteration: 7240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26122 FastRCNN class loss: 0.22424 FastRCNN total loss: 0.48546 L1 loss: 0.0000e+00 L2 loss: 1.74346 Learning rate: 0.02 Mask loss: 0.28977 RPN box loss: 0.04036 RPN score loss: 0.01321 RPN total loss: 0.05357 Total loss: 2.57225 timestamp: 1654920514.387165 iteration: 7245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11695 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.19202 L1 loss: 0.0000e+00 L2 loss: 1.74314 Learning rate: 0.02 Mask loss: 0.14445 RPN box loss: 0.03985 RPN score loss: 0.01368 RPN total loss: 0.05353 Total loss: 2.13314 timestamp: 1654920517.660966 iteration: 7250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17901 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.25782 L1 loss: 0.0000e+00 L2 loss: 1.74281 Learning rate: 0.02 Mask loss: 0.18476 RPN box loss: 0.04954 RPN score loss: 0.00474 RPN total loss: 0.05428 Total loss: 2.23967 timestamp: 1654920520.8082838 iteration: 7255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12704 FastRCNN class loss: 0.12067 FastRCNN total loss: 0.24771 L1 loss: 0.0000e+00 L2 loss: 1.7425 Learning rate: 0.02 Mask loss: 0.18357 RPN box loss: 0.01808 RPN score loss: 0.00855 RPN total loss: 0.02664 Total loss: 2.20042 timestamp: 1654920523.9984295 iteration: 7260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24691 FastRCNN class loss: 0.16862 FastRCNN total loss: 0.41554 L1 loss: 0.0000e+00 L2 loss: 1.74218 Learning rate: 0.02 Mask loss: 0.27852 RPN box loss: 0.06619 RPN score loss: 0.00881 RPN total loss: 0.075 Total loss: 2.51123 timestamp: 1654920527.1648653 iteration: 7265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13612 FastRCNN class loss: 0.0626 FastRCNN total loss: 0.19872 L1 loss: 0.0000e+00 L2 loss: 1.74186 Learning rate: 0.02 Mask loss: 0.11326 RPN box loss: 0.02765 RPN score loss: 0.00342 RPN total loss: 0.03107 Total loss: 2.0849 timestamp: 1654920530.4630854 iteration: 7270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15042 FastRCNN class loss: 0.10017 FastRCNN total loss: 0.2506 L1 loss: 0.0000e+00 L2 loss: 1.74154 Learning rate: 0.02 Mask loss: 0.22481 RPN box loss: 0.02378 RPN score loss: 0.00499 RPN total loss: 0.02877 Total loss: 2.24571 timestamp: 1654920533.9626632 iteration: 7275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11182 FastRCNN class loss: 0.12863 FastRCNN total loss: 0.24045 L1 loss: 0.0000e+00 L2 loss: 1.74121 Learning rate: 0.02 Mask loss: 0.16359 RPN box loss: 0.00931 RPN score loss: 0.00599 RPN total loss: 0.0153 Total loss: 2.16055 timestamp: 1654920537.2059543 iteration: 7280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17543 FastRCNN class loss: 0.09559 FastRCNN total loss: 0.27103 L1 loss: 0.0000e+00 L2 loss: 1.74091 Learning rate: 0.02 Mask loss: 0.16246 RPN box loss: 0.08657 RPN score loss: 0.01567 RPN total loss: 0.10224 Total loss: 2.27664 timestamp: 1654920540.6404002 iteration: 7285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15616 FastRCNN class loss: 0.07465 FastRCNN total loss: 0.2308 L1 loss: 0.0000e+00 L2 loss: 1.74058 Learning rate: 0.02 Mask loss: 0.12068 RPN box loss: 0.01929 RPN score loss: 0.00284 RPN total loss: 0.02213 Total loss: 2.11419 timestamp: 1654920543.8389997 iteration: 7290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22175 FastRCNN class loss: 0.09022 FastRCNN total loss: 0.31197 L1 loss: 0.0000e+00 L2 loss: 1.74026 Learning rate: 0.02 Mask loss: 0.19029 RPN box loss: 0.04615 RPN score loss: 0.00475 RPN total loss: 0.0509 Total loss: 2.29342 timestamp: 1654920547.0827944 iteration: 7295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14608 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.23874 L1 loss: 0.0000e+00 L2 loss: 1.73992 Learning rate: 0.02 Mask loss: 0.12723 RPN box loss: 0.01587 RPN score loss: 0.00756 RPN total loss: 0.02343 Total loss: 2.12933 timestamp: 1654920550.2857666 iteration: 7300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23957 FastRCNN class loss: 0.10458 FastRCNN total loss: 0.34415 L1 loss: 0.0000e+00 L2 loss: 1.73958 Learning rate: 0.02 Mask loss: 0.18487 RPN box loss: 0.05627 RPN score loss: 0.0094 RPN total loss: 0.06567 Total loss: 2.33428 timestamp: 1654920553.4742432 iteration: 7305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21498 FastRCNN class loss: 0.09637 FastRCNN total loss: 0.31136 L1 loss: 0.0000e+00 L2 loss: 1.73928 Learning rate: 0.02 Mask loss: 0.15192 RPN box loss: 0.03156 RPN score loss: 0.00562 RPN total loss: 0.03718 Total loss: 2.23974 timestamp: 1654920556.7041297 iteration: 7310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25771 FastRCNN class loss: 0.0896 FastRCNN total loss: 0.34731 L1 loss: 0.0000e+00 L2 loss: 1.73898 Learning rate: 0.02 Mask loss: 0.17047 RPN box loss: 0.03435 RPN score loss: 0.00701 RPN total loss: 0.04136 Total loss: 2.29812 timestamp: 1654920560.0845833 iteration: 7315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19078 FastRCNN class loss: 0.07986 FastRCNN total loss: 0.27064 L1 loss: 0.0000e+00 L2 loss: 1.73866 Learning rate: 0.02 Mask loss: 0.21455 RPN box loss: 0.02687 RPN score loss: 0.0065 RPN total loss: 0.03337 Total loss: 2.25722 timestamp: 1654920563.3913484 iteration: 7320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20639 FastRCNN class loss: 0.12694 FastRCNN total loss: 0.33333 L1 loss: 0.0000e+00 L2 loss: 1.73832 Learning rate: 0.02 Mask loss: 0.2421 RPN box loss: 0.04638 RPN score loss: 0.01015 RPN total loss: 0.05654 Total loss: 2.37028 timestamp: 1654920566.6208103 iteration: 7325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18107 FastRCNN class loss: 0.08592 FastRCNN total loss: 0.26699 L1 loss: 0.0000e+00 L2 loss: 1.73801 Learning rate: 0.02 Mask loss: 0.15035 RPN box loss: 0.04569 RPN score loss: 0.00962 RPN total loss: 0.05531 Total loss: 2.21065 timestamp: 1654920569.9558198 iteration: 7330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22634 FastRCNN class loss: 0.171 FastRCNN total loss: 0.39734 L1 loss: 0.0000e+00 L2 loss: 1.73769 Learning rate: 0.02 Mask loss: 0.25483 RPN box loss: 0.04373 RPN score loss: 0.02129 RPN total loss: 0.06502 Total loss: 2.45488 timestamp: 1654920573.0945659 iteration: 7335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13033 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.20971 L1 loss: 0.0000e+00 L2 loss: 1.73738 Learning rate: 0.02 Mask loss: 0.23895 RPN box loss: 0.01736 RPN score loss: 0.00908 RPN total loss: 0.02644 Total loss: 2.21248 timestamp: 1654920576.4057858 iteration: 7340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15199 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.22039 L1 loss: 0.0000e+00 L2 loss: 1.73706 Learning rate: 0.02 Mask loss: 0.19282 RPN box loss: 0.05363 RPN score loss: 0.00723 RPN total loss: 0.06086 Total loss: 2.21113 timestamp: 1654920579.5846727 iteration: 7345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1635 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.24286 L1 loss: 0.0000e+00 L2 loss: 1.73676 Learning rate: 0.02 Mask loss: 0.21042 RPN box loss: 0.02696 RPN score loss: 0.00579 RPN total loss: 0.03274 Total loss: 2.22277 timestamp: 1654920582.886871 iteration: 7350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21045 FastRCNN class loss: 0.11016 FastRCNN total loss: 0.32062 L1 loss: 0.0000e+00 L2 loss: 1.73647 Learning rate: 0.02 Mask loss: 0.24481 RPN box loss: 0.03426 RPN score loss: 0.00783 RPN total loss: 0.04209 Total loss: 2.34399 timestamp: 1654920586.0461018 iteration: 7355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24452 FastRCNN class loss: 0.09462 FastRCNN total loss: 0.33914 L1 loss: 0.0000e+00 L2 loss: 1.73615 Learning rate: 0.02 Mask loss: 0.26798 RPN box loss: 0.04495 RPN score loss: 0.00647 RPN total loss: 0.05141 Total loss: 2.39468 timestamp: 1654920589.3178353 iteration: 7360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17839 FastRCNN class loss: 0.13381 FastRCNN total loss: 0.3122 L1 loss: 0.0000e+00 L2 loss: 1.73583 Learning rate: 0.02 Mask loss: 0.19022 RPN box loss: 0.03094 RPN score loss: 0.0048 RPN total loss: 0.03574 Total loss: 2.27399 timestamp: 1654920592.4439712 iteration: 7365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09001 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.14156 L1 loss: 0.0000e+00 L2 loss: 1.73551 Learning rate: 0.02 Mask loss: 0.16822 RPN box loss: 0.01923 RPN score loss: 0.00671 RPN total loss: 0.02593 Total loss: 2.07122 timestamp: 1654920595.7655869 iteration: 7370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21465 FastRCNN class loss: 0.11091 FastRCNN total loss: 0.32555 L1 loss: 0.0000e+00 L2 loss: 1.73518 Learning rate: 0.02 Mask loss: 0.17914 RPN box loss: 0.05985 RPN score loss: 0.01342 RPN total loss: 0.07327 Total loss: 2.31314 timestamp: 1654920598.9932246 iteration: 7375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09975 FastRCNN class loss: 0.04172 FastRCNN total loss: 0.14147 L1 loss: 0.0000e+00 L2 loss: 1.73485 Learning rate: 0.02 Mask loss: 0.18991 RPN box loss: 0.06778 RPN score loss: 0.02131 RPN total loss: 0.08909 Total loss: 2.15532 timestamp: 1654920602.150973 iteration: 7380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16259 FastRCNN class loss: 0.11841 FastRCNN total loss: 0.28099 L1 loss: 0.0000e+00 L2 loss: 1.73452 Learning rate: 0.02 Mask loss: 0.2585 RPN box loss: 0.04453 RPN score loss: 0.02699 RPN total loss: 0.07152 Total loss: 2.34553 timestamp: 1654920605.5479405 iteration: 7385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13731 FastRCNN class loss: 0.09638 FastRCNN total loss: 0.23369 L1 loss: 0.0000e+00 L2 loss: 1.73421 Learning rate: 0.02 Mask loss: 0.22604 RPN box loss: 0.06863 RPN score loss: 0.01284 RPN total loss: 0.08146 Total loss: 2.27541 timestamp: 1654920608.7683485 iteration: 7390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10178 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.17034 L1 loss: 0.0000e+00 L2 loss: 1.7339 Learning rate: 0.02 Mask loss: 0.20453 RPN box loss: 0.04845 RPN score loss: 0.00659 RPN total loss: 0.05504 Total loss: 2.16381 timestamp: 1654920611.978049 iteration: 7395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10585 FastRCNN class loss: 0.07069 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 1.73358 Learning rate: 0.02 Mask loss: 0.2372 RPN box loss: 0.01158 RPN score loss: 0.0022 RPN total loss: 0.01379 Total loss: 2.1611 timestamp: 1654920615.2443614 iteration: 7400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20573 FastRCNN class loss: 0.09019 FastRCNN total loss: 0.29592 L1 loss: 0.0000e+00 L2 loss: 1.73327 Learning rate: 0.02 Mask loss: 0.18977 RPN box loss: 0.03251 RPN score loss: 0.00967 RPN total loss: 0.04219 Total loss: 2.26115 timestamp: 1654920618.5612252 iteration: 7405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13541 FastRCNN class loss: 0.10954 FastRCNN total loss: 0.24495 L1 loss: 0.0000e+00 L2 loss: 1.73294 Learning rate: 0.02 Mask loss: 0.16987 RPN box loss: 0.09904 RPN score loss: 0.0117 RPN total loss: 0.11074 Total loss: 2.25849 timestamp: 1654920621.7060752 iteration: 7410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18329 FastRCNN class loss: 0.10025 FastRCNN total loss: 0.28354 L1 loss: 0.0000e+00 L2 loss: 1.73263 Learning rate: 0.02 Mask loss: 0.17779 RPN box loss: 0.0377 RPN score loss: 0.02485 RPN total loss: 0.06255 Total loss: 2.2565 timestamp: 1654920625.1573677 iteration: 7415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10273 FastRCNN class loss: 0.04773 FastRCNN total loss: 0.15045 L1 loss: 0.0000e+00 L2 loss: 1.7323 Learning rate: 0.02 Mask loss: 0.12143 RPN box loss: 0.00514 RPN score loss: 0.00266 RPN total loss: 0.0078 Total loss: 2.01199 timestamp: 1654920628.3338816 iteration: 7420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1793 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.24436 L1 loss: 0.0000e+00 L2 loss: 1.73198 Learning rate: 0.02 Mask loss: 0.15544 RPN box loss: 0.03007 RPN score loss: 0.00405 RPN total loss: 0.03412 Total loss: 2.16591 timestamp: 1654920631.6318598 iteration: 7425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05212 FastRCNN class loss: 0.04248 FastRCNN total loss: 0.09461 L1 loss: 0.0000e+00 L2 loss: 1.73168 Learning rate: 0.02 Mask loss: 0.12891 RPN box loss: 0.16065 RPN score loss: 0.01522 RPN total loss: 0.17588 Total loss: 2.13108 timestamp: 1654920634.965621 iteration: 7430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.19313 L1 loss: 0.0000e+00 L2 loss: 1.73136 Learning rate: 0.02 Mask loss: 0.14817 RPN box loss: 0.0238 RPN score loss: 0.01 RPN total loss: 0.0338 Total loss: 2.10645 timestamp: 1654920638.1359043 iteration: 7435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22405 FastRCNN class loss: 0.17526 FastRCNN total loss: 0.39931 L1 loss: 0.0000e+00 L2 loss: 1.73103 Learning rate: 0.02 Mask loss: 0.2126 RPN box loss: 0.04515 RPN score loss: 0.01413 RPN total loss: 0.05928 Total loss: 2.40222 timestamp: 1654920641.4685552 iteration: 7440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12945 FastRCNN class loss: 0.07943 FastRCNN total loss: 0.20888 L1 loss: 0.0000e+00 L2 loss: 1.73073 Learning rate: 0.02 Mask loss: 0.10326 RPN box loss: 0.04825 RPN score loss: 0.00685 RPN total loss: 0.0551 Total loss: 2.09797 timestamp: 1654920644.7122304 iteration: 7445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15863 FastRCNN class loss: 0.06057 FastRCNN total loss: 0.2192 L1 loss: 0.0000e+00 L2 loss: 1.73041 Learning rate: 0.02 Mask loss: 0.11967 RPN box loss: 0.03981 RPN score loss: 0.00658 RPN total loss: 0.04639 Total loss: 2.11567 timestamp: 1654920648.0232348 iteration: 7450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1295 FastRCNN class loss: 0.09263 FastRCNN total loss: 0.22213 L1 loss: 0.0000e+00 L2 loss: 1.7301 Learning rate: 0.02 Mask loss: 0.25084 RPN box loss: 0.05769 RPN score loss: 0.00654 RPN total loss: 0.06422 Total loss: 2.26729 timestamp: 1654920651.2221122 iteration: 7455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20432 FastRCNN class loss: 0.07943 FastRCNN total loss: 0.28375 L1 loss: 0.0000e+00 L2 loss: 1.72976 Learning rate: 0.02 Mask loss: 0.15818 RPN box loss: 0.01344 RPN score loss: 0.00344 RPN total loss: 0.01688 Total loss: 2.18857 timestamp: 1654920654.6414495 iteration: 7460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14029 FastRCNN class loss: 0.08705 FastRCNN total loss: 0.22734 L1 loss: 0.0000e+00 L2 loss: 1.72946 Learning rate: 0.02 Mask loss: 0.12931 RPN box loss: 0.05265 RPN score loss: 0.00787 RPN total loss: 0.06053 Total loss: 2.14664 timestamp: 1654920657.8677826 iteration: 7465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19765 FastRCNN class loss: 0.10833 FastRCNN total loss: 0.30598 L1 loss: 0.0000e+00 L2 loss: 1.72914 Learning rate: 0.02 Mask loss: 0.17916 RPN box loss: 0.01698 RPN score loss: 0.00783 RPN total loss: 0.02481 Total loss: 2.2391 timestamp: 1654920661.1261394 iteration: 7470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23929 FastRCNN class loss: 0.17044 FastRCNN total loss: 0.40973 L1 loss: 0.0000e+00 L2 loss: 1.72884 Learning rate: 0.02 Mask loss: 0.24113 RPN box loss: 0.05438 RPN score loss: 0.01276 RPN total loss: 0.06715 Total loss: 2.44684 timestamp: 1654920664.4568386 iteration: 7475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18459 FastRCNN class loss: 0.15743 FastRCNN total loss: 0.34201 L1 loss: 0.0000e+00 L2 loss: 1.72853 Learning rate: 0.02 Mask loss: 0.20874 RPN box loss: 0.04039 RPN score loss: 0.00985 RPN total loss: 0.05025 Total loss: 2.32953 timestamp: 1654920667.7385204 iteration: 7480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15135 FastRCNN class loss: 0.11387 FastRCNN total loss: 0.26522 L1 loss: 0.0000e+00 L2 loss: 1.7282 Learning rate: 0.02 Mask loss: 0.19717 RPN box loss: 0.07555 RPN score loss: 0.01283 RPN total loss: 0.08838 Total loss: 2.27896 timestamp: 1654920671.0105526 iteration: 7485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16703 FastRCNN class loss: 0.11695 FastRCNN total loss: 0.28399 L1 loss: 0.0000e+00 L2 loss: 1.72788 Learning rate: 0.02 Mask loss: 0.16324 RPN box loss: 0.02825 RPN score loss: 0.00672 RPN total loss: 0.03497 Total loss: 2.21007 timestamp: 1654920674.1874747 iteration: 7490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25713 FastRCNN class loss: 0.13496 FastRCNN total loss: 0.39209 L1 loss: 0.0000e+00 L2 loss: 1.72755 Learning rate: 0.02 Mask loss: 0.24837 RPN box loss: 0.05886 RPN score loss: 0.00858 RPN total loss: 0.06744 Total loss: 2.43544 timestamp: 1654920677.4676888 iteration: 7495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21315 FastRCNN class loss: 0.09177 FastRCNN total loss: 0.30491 L1 loss: 0.0000e+00 L2 loss: 1.72723 Learning rate: 0.02 Mask loss: 0.171 RPN box loss: 0.03535 RPN score loss: 0.01092 RPN total loss: 0.04628 Total loss: 2.24942 timestamp: 1654920680.5967572 iteration: 7500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16794 FastRCNN class loss: 0.0756 FastRCNN total loss: 0.24354 L1 loss: 0.0000e+00 L2 loss: 1.7269 Learning rate: 0.02 Mask loss: 0.1307 RPN box loss: 0.01989 RPN score loss: 0.00999 RPN total loss: 0.02989 Total loss: 2.13103 timestamp: 1654920683.892871 iteration: 7505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20417 FastRCNN class loss: 0.12132 FastRCNN total loss: 0.32549 L1 loss: 0.0000e+00 L2 loss: 1.72657 Learning rate: 0.02 Mask loss: 0.18557 RPN box loss: 0.0342 RPN score loss: 0.01039 RPN total loss: 0.04459 Total loss: 2.28223 timestamp: 1654920687.0930958 iteration: 7510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12431 FastRCNN class loss: 0.0647 FastRCNN total loss: 0.18901 L1 loss: 0.0000e+00 L2 loss: 1.72628 Learning rate: 0.02 Mask loss: 0.13942 RPN box loss: 0.06561 RPN score loss: 0.00481 RPN total loss: 0.07042 Total loss: 2.12514 timestamp: 1654920690.5017323 iteration: 7515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22508 FastRCNN class loss: 0.12486 FastRCNN total loss: 0.34993 L1 loss: 0.0000e+00 L2 loss: 1.72597 Learning rate: 0.02 Mask loss: 0.18614 RPN box loss: 0.03725 RPN score loss: 0.01774 RPN total loss: 0.05499 Total loss: 2.31703 timestamp: 1654920693.704086 iteration: 7520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18683 FastRCNN class loss: 0.11609 FastRCNN total loss: 0.30291 L1 loss: 0.0000e+00 L2 loss: 1.72567 Learning rate: 0.02 Mask loss: 0.14504 RPN box loss: 0.02747 RPN score loss: 0.00733 RPN total loss: 0.0348 Total loss: 2.20842 timestamp: 1654920697.050898 iteration: 7525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15743 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.2168 L1 loss: 0.0000e+00 L2 loss: 1.72533 Learning rate: 0.02 Mask loss: 0.23843 RPN box loss: 0.04675 RPN score loss: 0.01423 RPN total loss: 0.06097 Total loss: 2.24153 timestamp: 1654920700.3285973 iteration: 7530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22817 FastRCNN class loss: 0.14198 FastRCNN total loss: 0.37015 L1 loss: 0.0000e+00 L2 loss: 1.72501 Learning rate: 0.02 Mask loss: 0.26225 RPN box loss: 0.04578 RPN score loss: 0.01681 RPN total loss: 0.0626 Total loss: 2.42001 timestamp: 1654920703.5269165 iteration: 7535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21326 FastRCNN class loss: 0.13697 FastRCNN total loss: 0.35023 L1 loss: 0.0000e+00 L2 loss: 1.72472 Learning rate: 0.02 Mask loss: 0.27159 RPN box loss: 0.04988 RPN score loss: 0.01184 RPN total loss: 0.06173 Total loss: 2.40827 timestamp: 1654920706.7475228 iteration: 7540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14657 FastRCNN class loss: 0.11235 FastRCNN total loss: 0.25891 L1 loss: 0.0000e+00 L2 loss: 1.72441 Learning rate: 0.02 Mask loss: 0.15884 RPN box loss: 0.02972 RPN score loss: 0.00389 RPN total loss: 0.03361 Total loss: 2.17577 timestamp: 1654920709.9231405 iteration: 7545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12611 FastRCNN class loss: 0.08529 FastRCNN total loss: 0.2114 L1 loss: 0.0000e+00 L2 loss: 1.72407 Learning rate: 0.02 Mask loss: 0.25842 RPN box loss: 0.09452 RPN score loss: 0.00607 RPN total loss: 0.10059 Total loss: 2.29448 timestamp: 1654920713.2202988 iteration: 7550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19111 FastRCNN class loss: 0.10927 FastRCNN total loss: 0.30038 L1 loss: 0.0000e+00 L2 loss: 1.72374 Learning rate: 0.02 Mask loss: 0.17078 RPN box loss: 0.05005 RPN score loss: 0.00678 RPN total loss: 0.05682 Total loss: 2.25173 timestamp: 1654920716.4118488 iteration: 7555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1696 FastRCNN class loss: 0.09543 FastRCNN total loss: 0.26503 L1 loss: 0.0000e+00 L2 loss: 1.72345 Learning rate: 0.02 Mask loss: 0.22518 RPN box loss: 0.045 RPN score loss: 0.01819 RPN total loss: 0.06319 Total loss: 2.27685 timestamp: 1654920719.7247176 iteration: 7560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18534 FastRCNN class loss: 0.11334 FastRCNN total loss: 0.29868 L1 loss: 0.0000e+00 L2 loss: 1.72317 Learning rate: 0.02 Mask loss: 0.23311 RPN box loss: 0.06525 RPN score loss: 0.0258 RPN total loss: 0.09105 Total loss: 2.34601 timestamp: 1654920722.978939 iteration: 7565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06008 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.12078 L1 loss: 0.0000e+00 L2 loss: 1.72288 Learning rate: 0.02 Mask loss: 0.13408 RPN box loss: 0.03731 RPN score loss: 0.01734 RPN total loss: 0.05465 Total loss: 2.03239 timestamp: 1654920726.272133 iteration: 7570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11883 FastRCNN class loss: 0.07873 FastRCNN total loss: 0.19756 L1 loss: 0.0000e+00 L2 loss: 1.72255 Learning rate: 0.02 Mask loss: 0.12986 RPN box loss: 0.03496 RPN score loss: 0.00368 RPN total loss: 0.03864 Total loss: 2.08861 timestamp: 1654920729.572238 iteration: 7575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17623 FastRCNN class loss: 0.08801 FastRCNN total loss: 0.26424 L1 loss: 0.0000e+00 L2 loss: 1.72222 Learning rate: 0.02 Mask loss: 0.18057 RPN box loss: 0.07403 RPN score loss: 0.01464 RPN total loss: 0.08867 Total loss: 2.2557 timestamp: 1654920732.9471757 iteration: 7580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20659 FastRCNN class loss: 0.07104 FastRCNN total loss: 0.27762 L1 loss: 0.0000e+00 L2 loss: 1.72191 Learning rate: 0.02 Mask loss: 0.32307 RPN box loss: 0.07993 RPN score loss: 0.00976 RPN total loss: 0.08969 Total loss: 2.4123 timestamp: 1654920736.249103 iteration: 7585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09585 FastRCNN class loss: 0.11953 FastRCNN total loss: 0.21538 L1 loss: 0.0000e+00 L2 loss: 1.72158 Learning rate: 0.02 Mask loss: 0.19517 RPN box loss: 0.05682 RPN score loss: 0.01236 RPN total loss: 0.06917 Total loss: 2.20131 timestamp: 1654920739.530649 iteration: 7590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1535 FastRCNN class loss: 0.08176 FastRCNN total loss: 0.23526 L1 loss: 0.0000e+00 L2 loss: 1.72127 Learning rate: 0.02 Mask loss: 0.14356 RPN box loss: 0.0397 RPN score loss: 0.01867 RPN total loss: 0.05836 Total loss: 2.15845 timestamp: 1654920742.8866694 iteration: 7595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22984 FastRCNN class loss: 0.13784 FastRCNN total loss: 0.36768 L1 loss: 0.0000e+00 L2 loss: 1.72096 Learning rate: 0.02 Mask loss: 0.19601 RPN box loss: 0.03594 RPN score loss: 0.02739 RPN total loss: 0.06333 Total loss: 2.34799 timestamp: 1654920746.0932693 iteration: 7600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19996 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.27194 L1 loss: 0.0000e+00 L2 loss: 1.72065 Learning rate: 0.02 Mask loss: 0.16376 RPN box loss: 0.01155 RPN score loss: 0.00584 RPN total loss: 0.01739 Total loss: 2.17375 timestamp: 1654920749.3550694 iteration: 7605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09554 FastRCNN class loss: 0.06746 FastRCNN total loss: 0.163 L1 loss: 0.0000e+00 L2 loss: 1.72033 Learning rate: 0.02 Mask loss: 0.10095 RPN box loss: 0.02098 RPN score loss: 0.00267 RPN total loss: 0.02365 Total loss: 2.00793 timestamp: 1654920752.6383243 iteration: 7610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14899 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.2219 L1 loss: 0.0000e+00 L2 loss: 1.72001 Learning rate: 0.02 Mask loss: 0.10513 RPN box loss: 0.02183 RPN score loss: 0.00259 RPN total loss: 0.02442 Total loss: 2.07146 timestamp: 1654920755.9460218 iteration: 7615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17531 FastRCNN class loss: 0.13483 FastRCNN total loss: 0.31014 L1 loss: 0.0000e+00 L2 loss: 1.71969 Learning rate: 0.02 Mask loss: 0.19378 RPN box loss: 0.06542 RPN score loss: 0.01246 RPN total loss: 0.07788 Total loss: 2.30149 timestamp: 1654920759.19603 iteration: 7620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08263 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.13627 L1 loss: 0.0000e+00 L2 loss: 1.71937 Learning rate: 0.02 Mask loss: 0.159 RPN box loss: 0.02992 RPN score loss: 0.00852 RPN total loss: 0.03844 Total loss: 2.05308 timestamp: 1654920762.462945 iteration: 7625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21286 FastRCNN class loss: 0.11661 FastRCNN total loss: 0.32946 L1 loss: 0.0000e+00 L2 loss: 1.71906 Learning rate: 0.02 Mask loss: 0.24679 RPN box loss: 0.08177 RPN score loss: 0.01451 RPN total loss: 0.09628 Total loss: 2.39158 timestamp: 1654920765.586278 iteration: 7630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23355 FastRCNN class loss: 0.13086 FastRCNN total loss: 0.36442 L1 loss: 0.0000e+00 L2 loss: 1.71874 Learning rate: 0.02 Mask loss: 0.21072 RPN box loss: 0.05877 RPN score loss: 0.01296 RPN total loss: 0.07173 Total loss: 2.36561 timestamp: 1654920768.9159942 iteration: 7635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25733 FastRCNN class loss: 0.09654 FastRCNN total loss: 0.35387 L1 loss: 0.0000e+00 L2 loss: 1.71845 Learning rate: 0.02 Mask loss: 0.22669 RPN box loss: 0.02247 RPN score loss: 0.01526 RPN total loss: 0.03773 Total loss: 2.33675 timestamp: 1654920772.2753406 iteration: 7640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19573 FastRCNN class loss: 0.10956 FastRCNN total loss: 0.30529 L1 loss: 0.0000e+00 L2 loss: 1.71813 Learning rate: 0.02 Mask loss: 0.18688 RPN box loss: 0.0377 RPN score loss: 0.006 RPN total loss: 0.04369 Total loss: 2.254 timestamp: 1654920775.4346502 iteration: 7645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04947 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.10934 L1 loss: 0.0000e+00 L2 loss: 1.71784 Learning rate: 0.02 Mask loss: 0.19594 RPN box loss: 0.03191 RPN score loss: 0.00393 RPN total loss: 0.03584 Total loss: 2.05897 timestamp: 1654920778.771393 iteration: 7650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08605 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.13091 L1 loss: 0.0000e+00 L2 loss: 1.71753 Learning rate: 0.02 Mask loss: 0.15242 RPN box loss: 0.01447 RPN score loss: 0.0012 RPN total loss: 0.01567 Total loss: 2.01653 timestamp: 1654920782.0228996 iteration: 7655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2001 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.2846 L1 loss: 0.0000e+00 L2 loss: 1.71719 Learning rate: 0.02 Mask loss: 0.13927 RPN box loss: 0.0525 RPN score loss: 0.00291 RPN total loss: 0.05541 Total loss: 2.19646 timestamp: 1654920785.34396 iteration: 7660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23652 FastRCNN class loss: 0.1252 FastRCNN total loss: 0.36172 L1 loss: 0.0000e+00 L2 loss: 1.71688 Learning rate: 0.02 Mask loss: 0.32333 RPN box loss: 0.04145 RPN score loss: 0.00667 RPN total loss: 0.04812 Total loss: 2.45004 timestamp: 1654920788.5647354 iteration: 7665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12739 FastRCNN class loss: 0.06525 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 1.71656 Learning rate: 0.02 Mask loss: 0.14747 RPN box loss: 0.05996 RPN score loss: 0.00817 RPN total loss: 0.06813 Total loss: 2.1248 timestamp: 1654920791.795597 iteration: 7670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1625 FastRCNN class loss: 0.10857 FastRCNN total loss: 0.27107 L1 loss: 0.0000e+00 L2 loss: 1.71625 Learning rate: 0.02 Mask loss: 0.20983 RPN box loss: 0.05245 RPN score loss: 0.01584 RPN total loss: 0.06829 Total loss: 2.26545 timestamp: 1654920795.0033896 iteration: 7675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27702 FastRCNN class loss: 0.13115 FastRCNN total loss: 0.40818 L1 loss: 0.0000e+00 L2 loss: 1.71596 Learning rate: 0.02 Mask loss: 0.3012 RPN box loss: 0.01657 RPN score loss: 0.01099 RPN total loss: 0.02756 Total loss: 2.45289 timestamp: 1654920798.3327458 iteration: 7680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13736 FastRCNN class loss: 0.0575 FastRCNN total loss: 0.19485 L1 loss: 0.0000e+00 L2 loss: 1.71564 Learning rate: 0.02 Mask loss: 0.19301 RPN box loss: 0.05954 RPN score loss: 0.00682 RPN total loss: 0.06636 Total loss: 2.16985 timestamp: 1654920801.5886207 iteration: 7685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.18997 L1 loss: 0.0000e+00 L2 loss: 1.71531 Learning rate: 0.02 Mask loss: 0.15308 RPN box loss: 0.05357 RPN score loss: 0.01175 RPN total loss: 0.06532 Total loss: 2.12368 timestamp: 1654920804.7224581 iteration: 7690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22254 FastRCNN class loss: 0.15663 FastRCNN total loss: 0.37917 L1 loss: 0.0000e+00 L2 loss: 1.715 Learning rate: 0.02 Mask loss: 0.23902 RPN box loss: 0.03908 RPN score loss: 0.0037 RPN total loss: 0.04278 Total loss: 2.37597 timestamp: 1654920808.0009234 iteration: 7695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15946 FastRCNN class loss: 0.11463 FastRCNN total loss: 0.27409 L1 loss: 0.0000e+00 L2 loss: 1.71469 Learning rate: 0.02 Mask loss: 0.21315 RPN box loss: 0.03765 RPN score loss: 0.00811 RPN total loss: 0.04576 Total loss: 2.24769 timestamp: 1654920811.3161128 iteration: 7700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20288 FastRCNN class loss: 0.11043 FastRCNN total loss: 0.31331 L1 loss: 0.0000e+00 L2 loss: 1.71438 Learning rate: 0.02 Mask loss: 0.14117 RPN box loss: 0.02087 RPN score loss: 0.00536 RPN total loss: 0.02623 Total loss: 2.1951 timestamp: 1654920814.641053 iteration: 7705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23503 FastRCNN class loss: 0.11456 FastRCNN total loss: 0.34958 L1 loss: 0.0000e+00 L2 loss: 1.71407 Learning rate: 0.02 Mask loss: 0.22793 RPN box loss: 0.04214 RPN score loss: 0.01132 RPN total loss: 0.05347 Total loss: 2.34505 timestamp: 1654920817.81804 iteration: 7710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14685 FastRCNN class loss: 0.11089 FastRCNN total loss: 0.25774 L1 loss: 0.0000e+00 L2 loss: 1.71376 Learning rate: 0.02 Mask loss: 0.28068 RPN box loss: 0.10163 RPN score loss: 0.01435 RPN total loss: 0.11598 Total loss: 2.36815 timestamp: 1654920821.1224167 iteration: 7715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21403 FastRCNN class loss: 0.10406 FastRCNN total loss: 0.31809 L1 loss: 0.0000e+00 L2 loss: 1.71343 Learning rate: 0.02 Mask loss: 0.29936 RPN box loss: 0.01137 RPN score loss: 0.00631 RPN total loss: 0.01769 Total loss: 2.34857 timestamp: 1654920824.2516909 iteration: 7720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24215 FastRCNN class loss: 0.13478 FastRCNN total loss: 0.37693 L1 loss: 0.0000e+00 L2 loss: 1.71311 Learning rate: 0.02 Mask loss: 0.18456 RPN box loss: 0.05187 RPN score loss: 0.01439 RPN total loss: 0.06626 Total loss: 2.34087 timestamp: 1654920827.592733 iteration: 7725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15202 FastRCNN class loss: 0.08738 FastRCNN total loss: 0.2394 L1 loss: 0.0000e+00 L2 loss: 1.71281 Learning rate: 0.02 Mask loss: 0.13173 RPN box loss: 0.06857 RPN score loss: 0.00781 RPN total loss: 0.07638 Total loss: 2.16032 timestamp: 1654920830.7016592 iteration: 7730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18728 FastRCNN class loss: 0.12278 FastRCNN total loss: 0.31007 L1 loss: 0.0000e+00 L2 loss: 1.7125 Learning rate: 0.02 Mask loss: 0.21881 RPN box loss: 0.02943 RPN score loss: 0.02819 RPN total loss: 0.05762 Total loss: 2.299 timestamp: 1654920834.1078873 iteration: 7735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18305 FastRCNN class loss: 0.06752 FastRCNN total loss: 0.25058 L1 loss: 0.0000e+00 L2 loss: 1.71217 Learning rate: 0.02 Mask loss: 0.11349 RPN box loss: 0.02974 RPN score loss: 0.00461 RPN total loss: 0.03435 Total loss: 2.11059 timestamp: 1654920837.462674 iteration: 7740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22581 FastRCNN class loss: 0.10855 FastRCNN total loss: 0.33436 L1 loss: 0.0000e+00 L2 loss: 1.71186 Learning rate: 0.02 Mask loss: 0.11462 RPN box loss: 0.02129 RPN score loss: 0.00518 RPN total loss: 0.02647 Total loss: 2.18731 timestamp: 1654920840.7020593 iteration: 7745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20304 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.28095 L1 loss: 0.0000e+00 L2 loss: 1.71157 Learning rate: 0.02 Mask loss: 0.17686 RPN box loss: 0.03209 RPN score loss: 0.00487 RPN total loss: 0.03695 Total loss: 2.20632 timestamp: 1654920844.0134835 iteration: 7750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12042 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.18299 L1 loss: 0.0000e+00 L2 loss: 1.71127 Learning rate: 0.02 Mask loss: 0.15717 RPN box loss: 0.03305 RPN score loss: 0.0094 RPN total loss: 0.04245 Total loss: 2.09388 timestamp: 1654920847.2284708 iteration: 7755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23304 FastRCNN class loss: 0.08456 FastRCNN total loss: 0.3176 L1 loss: 0.0000e+00 L2 loss: 1.71095 Learning rate: 0.02 Mask loss: 0.17549 RPN box loss: 0.05121 RPN score loss: 0.00558 RPN total loss: 0.05679 Total loss: 2.26083 timestamp: 1654920850.4983768 iteration: 7760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16586 FastRCNN class loss: 0.11689 FastRCNN total loss: 0.28275 L1 loss: 0.0000e+00 L2 loss: 1.71061 Learning rate: 0.02 Mask loss: 0.22036 RPN box loss: 0.07766 RPN score loss: 0.01262 RPN total loss: 0.09028 Total loss: 2.30401 timestamp: 1654920853.675715 iteration: 7765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17943 FastRCNN class loss: 0.10148 FastRCNN total loss: 0.28091 L1 loss: 0.0000e+00 L2 loss: 1.71032 Learning rate: 0.02 Mask loss: 0.14133 RPN box loss: 0.01219 RPN score loss: 0.00369 RPN total loss: 0.01588 Total loss: 2.14845 timestamp: 1654920856.8511167 iteration: 7770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12363 FastRCNN class loss: 0.08154 FastRCNN total loss: 0.20517 L1 loss: 0.0000e+00 L2 loss: 1.71002 Learning rate: 0.02 Mask loss: 0.10734 RPN box loss: 0.03296 RPN score loss: 0.0082 RPN total loss: 0.04116 Total loss: 2.06369 timestamp: 1654920860.099116 iteration: 7775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1663 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.23024 L1 loss: 0.0000e+00 L2 loss: 1.70972 Learning rate: 0.02 Mask loss: 0.1604 RPN box loss: 0.04379 RPN score loss: 0.00864 RPN total loss: 0.05243 Total loss: 2.1528 timestamp: 1654920863.3428063 iteration: 7780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24797 FastRCNN class loss: 0.08753 FastRCNN total loss: 0.3355 L1 loss: 0.0000e+00 L2 loss: 1.70941 Learning rate: 0.02 Mask loss: 0.18643 RPN box loss: 0.03953 RPN score loss: 0.00563 RPN total loss: 0.04516 Total loss: 2.27649 timestamp: 1654920866.5215867 iteration: 7785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20935 FastRCNN class loss: 0.16158 FastRCNN total loss: 0.37093 L1 loss: 0.0000e+00 L2 loss: 1.70909 Learning rate: 0.02 Mask loss: 0.24335 RPN box loss: 0.03785 RPN score loss: 0.01211 RPN total loss: 0.04997 Total loss: 2.37334 timestamp: 1654920869.8297725 iteration: 7790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17932 FastRCNN class loss: 0.08486 FastRCNN total loss: 0.26418 L1 loss: 0.0000e+00 L2 loss: 1.70877 Learning rate: 0.02 Mask loss: 0.20877 RPN box loss: 0.01942 RPN score loss: 0.00765 RPN total loss: 0.02707 Total loss: 2.2088 timestamp: 1654920873.174814 iteration: 7795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21767 FastRCNN class loss: 0.11321 FastRCNN total loss: 0.33087 L1 loss: 0.0000e+00 L2 loss: 1.70845 Learning rate: 0.02 Mask loss: 0.19634 RPN box loss: 0.01975 RPN score loss: 0.00503 RPN total loss: 0.02478 Total loss: 2.26045 timestamp: 1654920876.3598876 iteration: 7800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1064 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.17041 L1 loss: 0.0000e+00 L2 loss: 1.70814 Learning rate: 0.02 Mask loss: 0.12615 RPN box loss: 0.04073 RPN score loss: 0.00886 RPN total loss: 0.04959 Total loss: 2.05428 timestamp: 1654920879.715173 iteration: 7805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28712 FastRCNN class loss: 0.07661 FastRCNN total loss: 0.36372 L1 loss: 0.0000e+00 L2 loss: 1.70783 Learning rate: 0.02 Mask loss: 0.1618 RPN box loss: 0.0536 RPN score loss: 0.00255 RPN total loss: 0.05614 Total loss: 2.28949 timestamp: 1654920882.9281774 iteration: 7810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10097 FastRCNN class loss: 0.05679 FastRCNN total loss: 0.15776 L1 loss: 0.0000e+00 L2 loss: 1.70752 Learning rate: 0.02 Mask loss: 0.1308 RPN box loss: 0.05433 RPN score loss: 0.00751 RPN total loss: 0.06183 Total loss: 2.05791 timestamp: 1654920886.1567922 iteration: 7815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17359 FastRCNN class loss: 0.08147 FastRCNN total loss: 0.25506 L1 loss: 0.0000e+00 L2 loss: 1.70721 Learning rate: 0.02 Mask loss: 0.1395 RPN box loss: 0.01383 RPN score loss: 0.00647 RPN total loss: 0.0203 Total loss: 2.12206 timestamp: 1654920889.3912754 iteration: 7820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12448 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.18567 L1 loss: 0.0000e+00 L2 loss: 1.7069 Learning rate: 0.02 Mask loss: 0.15006 RPN box loss: 0.03811 RPN score loss: 0.00681 RPN total loss: 0.04492 Total loss: 2.08754 timestamp: 1654920892.5930479 iteration: 7825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20325 FastRCNN class loss: 0.11942 FastRCNN total loss: 0.32267 L1 loss: 0.0000e+00 L2 loss: 1.70657 Learning rate: 0.02 Mask loss: 0.2674 RPN box loss: 0.0302 RPN score loss: 0.00652 RPN total loss: 0.03672 Total loss: 2.33336 timestamp: 1654920895.7827742 iteration: 7830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13496 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.19849 L1 loss: 0.0000e+00 L2 loss: 1.70625 Learning rate: 0.02 Mask loss: 0.15509 RPN box loss: 0.01794 RPN score loss: 0.00555 RPN total loss: 0.02349 Total loss: 2.08332 timestamp: 1654920899.1377864 iteration: 7835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17308 FastRCNN class loss: 0.0952 FastRCNN total loss: 0.26828 L1 loss: 0.0000e+00 L2 loss: 1.70593 Learning rate: 0.02 Mask loss: 0.15102 RPN box loss: 0.028 RPN score loss: 0.00576 RPN total loss: 0.03376 Total loss: 2.15899 timestamp: 1654920902.3470156 iteration: 7840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2076 FastRCNN class loss: 0.07804 FastRCNN total loss: 0.28564 L1 loss: 0.0000e+00 L2 loss: 1.70562 Learning rate: 0.02 Mask loss: 0.19817 RPN box loss: 0.05222 RPN score loss: 0.00887 RPN total loss: 0.06109 Total loss: 2.25052 timestamp: 1654920905.5492039 iteration: 7845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20099 FastRCNN class loss: 0.09031 FastRCNN total loss: 0.2913 L1 loss: 0.0000e+00 L2 loss: 1.70531 Learning rate: 0.02 Mask loss: 0.14438 RPN box loss: 0.02942 RPN score loss: 0.00731 RPN total loss: 0.03673 Total loss: 2.17772 timestamp: 1654920908.749111 iteration: 7850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17933 FastRCNN class loss: 0.11097 FastRCNN total loss: 0.2903 L1 loss: 0.0000e+00 L2 loss: 1.70499 Learning rate: 0.02 Mask loss: 0.16986 RPN box loss: 0.06669 RPN score loss: 0.0149 RPN total loss: 0.0816 Total loss: 2.24675 timestamp: 1654920912.033181 iteration: 7855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18776 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.25868 L1 loss: 0.0000e+00 L2 loss: 1.70468 Learning rate: 0.02 Mask loss: 0.12621 RPN box loss: 0.02212 RPN score loss: 0.00465 RPN total loss: 0.02677 Total loss: 2.11634 timestamp: 1654920915.374146 iteration: 7860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12022 FastRCNN class loss: 0.06835 FastRCNN total loss: 0.18857 L1 loss: 0.0000e+00 L2 loss: 1.70437 Learning rate: 0.02 Mask loss: 0.11969 RPN box loss: 0.0406 RPN score loss: 0.00244 RPN total loss: 0.04303 Total loss: 2.05567 timestamp: 1654920918.55565 iteration: 7865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18485 FastRCNN class loss: 0.12392 FastRCNN total loss: 0.30877 L1 loss: 0.0000e+00 L2 loss: 1.70407 Learning rate: 0.02 Mask loss: 0.16871 RPN box loss: 0.06124 RPN score loss: 0.01249 RPN total loss: 0.07373 Total loss: 2.25528 timestamp: 1654920921.8978143 iteration: 7870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12126 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.20121 L1 loss: 0.0000e+00 L2 loss: 1.70375 Learning rate: 0.02 Mask loss: 0.20149 RPN box loss: 0.03786 RPN score loss: 0.00674 RPN total loss: 0.04461 Total loss: 2.15106 timestamp: 1654920925.136301 iteration: 7875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1527 FastRCNN class loss: 0.0569 FastRCNN total loss: 0.2096 L1 loss: 0.0000e+00 L2 loss: 1.70345 Learning rate: 0.02 Mask loss: 0.17004 RPN box loss: 0.05284 RPN score loss: 0.00577 RPN total loss: 0.0586 Total loss: 2.14169 timestamp: 1654920928.4312592 iteration: 7880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12228 FastRCNN class loss: 0.05483 FastRCNN total loss: 0.1771 L1 loss: 0.0000e+00 L2 loss: 1.70312 Learning rate: 0.02 Mask loss: 0.18887 RPN box loss: 0.0419 RPN score loss: 0.01172 RPN total loss: 0.05362 Total loss: 2.12271 timestamp: 1654920931.6413686 iteration: 7885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14795 FastRCNN class loss: 0.09252 FastRCNN total loss: 0.24047 L1 loss: 0.0000e+00 L2 loss: 1.70281 Learning rate: 0.02 Mask loss: 0.28471 RPN box loss: 0.04676 RPN score loss: 0.0047 RPN total loss: 0.05146 Total loss: 2.27945 timestamp: 1654920934.9695811 iteration: 7890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14903 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.21569 L1 loss: 0.0000e+00 L2 loss: 1.70251 Learning rate: 0.02 Mask loss: 0.1605 RPN box loss: 0.02692 RPN score loss: 0.00449 RPN total loss: 0.03141 Total loss: 2.11011 timestamp: 1654920938.2353878 iteration: 7895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12391 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.18828 L1 loss: 0.0000e+00 L2 loss: 1.7022 Learning rate: 0.02 Mask loss: 0.13995 RPN box loss: 0.05797 RPN score loss: 0.00766 RPN total loss: 0.06563 Total loss: 2.09606 timestamp: 1654920941.416445 iteration: 7900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.09018 FastRCNN total loss: 0.22429 L1 loss: 0.0000e+00 L2 loss: 1.7019 Learning rate: 0.02 Mask loss: 0.20925 RPN box loss: 0.00796 RPN score loss: 0.00524 RPN total loss: 0.01321 Total loss: 2.14864 timestamp: 1654920944.7587917 iteration: 7905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15229 FastRCNN class loss: 0.14188 FastRCNN total loss: 0.29417 L1 loss: 0.0000e+00 L2 loss: 1.70157 Learning rate: 0.02 Mask loss: 0.2017 RPN box loss: 0.06377 RPN score loss: 0.01676 RPN total loss: 0.08052 Total loss: 2.27796 timestamp: 1654920948.0017724 iteration: 7910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12957 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.18246 L1 loss: 0.0000e+00 L2 loss: 1.70127 Learning rate: 0.02 Mask loss: 0.13753 RPN box loss: 0.01996 RPN score loss: 0.00197 RPN total loss: 0.02193 Total loss: 2.0432 timestamp: 1654920951.3576787 iteration: 7915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22376 FastRCNN class loss: 0.09172 FastRCNN total loss: 0.31548 L1 loss: 0.0000e+00 L2 loss: 1.70096 Learning rate: 0.02 Mask loss: 0.18369 RPN box loss: 0.03201 RPN score loss: 0.00503 RPN total loss: 0.03703 Total loss: 2.23716 timestamp: 1654920954.5915244 iteration: 7920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16074 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.23615 L1 loss: 0.0000e+00 L2 loss: 1.70064 Learning rate: 0.02 Mask loss: 0.12433 RPN box loss: 0.01895 RPN score loss: 0.00312 RPN total loss: 0.02207 Total loss: 2.08319 timestamp: 1654920957.9381058 iteration: 7925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1701 FastRCNN class loss: 0.07758 FastRCNN total loss: 0.24768 L1 loss: 0.0000e+00 L2 loss: 1.70034 Learning rate: 0.02 Mask loss: 0.17604 RPN box loss: 0.01199 RPN score loss: 0.00483 RPN total loss: 0.01682 Total loss: 2.14089 timestamp: 1654920961.208971 iteration: 7930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17328 FastRCNN class loss: 0.09848 FastRCNN total loss: 0.27176 L1 loss: 0.0000e+00 L2 loss: 1.70004 Learning rate: 0.02 Mask loss: 0.17851 RPN box loss: 0.02834 RPN score loss: 0.0046 RPN total loss: 0.03294 Total loss: 2.18324 timestamp: 1654920964.5085337 iteration: 7935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12318 FastRCNN class loss: 0.09492 FastRCNN total loss: 0.2181 L1 loss: 0.0000e+00 L2 loss: 1.69973 Learning rate: 0.02 Mask loss: 0.15324 RPN box loss: 0.01816 RPN score loss: 0.00242 RPN total loss: 0.02057 Total loss: 2.09165 timestamp: 1654920967.7453606 iteration: 7940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13941 FastRCNN class loss: 0.10019 FastRCNN total loss: 0.2396 L1 loss: 0.0000e+00 L2 loss: 1.69944 Learning rate: 0.02 Mask loss: 0.18568 RPN box loss: 0.00673 RPN score loss: 0.00418 RPN total loss: 0.01092 Total loss: 2.13564 timestamp: 1654920971.096364 iteration: 7945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16018 FastRCNN class loss: 0.08491 FastRCNN total loss: 0.24509 L1 loss: 0.0000e+00 L2 loss: 1.69913 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.02368 RPN score loss: 0.00507 RPN total loss: 0.02875 Total loss: 2.10507 timestamp: 1654920974.3285668 iteration: 7950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08848 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.13791 L1 loss: 0.0000e+00 L2 loss: 1.69882 Learning rate: 0.02 Mask loss: 0.14143 RPN box loss: 0.01131 RPN score loss: 0.00856 RPN total loss: 0.01987 Total loss: 1.99803 timestamp: 1654920977.4794078 iteration: 7955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20043 FastRCNN class loss: 0.11779 FastRCNN total loss: 0.31822 L1 loss: 0.0000e+00 L2 loss: 1.69853 Learning rate: 0.02 Mask loss: 0.16734 RPN box loss: 0.03838 RPN score loss: 0.01163 RPN total loss: 0.05001 Total loss: 2.2341 timestamp: 1654920980.705329 iteration: 7960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20545 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.28563 L1 loss: 0.0000e+00 L2 loss: 1.69822 Learning rate: 0.02 Mask loss: 0.18244 RPN box loss: 0.15923 RPN score loss: 0.00782 RPN total loss: 0.16706 Total loss: 2.33334 timestamp: 1654920983.9040153 iteration: 7965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12422 FastRCNN class loss: 0.0667 FastRCNN total loss: 0.19093 L1 loss: 0.0000e+00 L2 loss: 1.69792 Learning rate: 0.02 Mask loss: 0.11152 RPN box loss: 0.0281 RPN score loss: 0.00684 RPN total loss: 0.03494 Total loss: 2.0353 timestamp: 1654920987.3183773 iteration: 7970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13838 FastRCNN class loss: 0.0847 FastRCNN total loss: 0.22309 L1 loss: 0.0000e+00 L2 loss: 1.6976 Learning rate: 0.02 Mask loss: 0.16808 RPN box loss: 0.0652 RPN score loss: 0.0091 RPN total loss: 0.07431 Total loss: 2.16308 timestamp: 1654920990.5539613 iteration: 7975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22447 FastRCNN class loss: 0.09709 FastRCNN total loss: 0.32155 L1 loss: 0.0000e+00 L2 loss: 1.69731 Learning rate: 0.02 Mask loss: 0.21847 RPN box loss: 0.06075 RPN score loss: 0.01859 RPN total loss: 0.07934 Total loss: 2.31668 timestamp: 1654920993.8723707 iteration: 7980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13149 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.22099 L1 loss: 0.0000e+00 L2 loss: 1.697 Learning rate: 0.02 Mask loss: 0.15692 RPN box loss: 0.02345 RPN score loss: 0.00408 RPN total loss: 0.02753 Total loss: 2.10243 timestamp: 1654920997.0376003 iteration: 7985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20846 FastRCNN class loss: 0.11381 FastRCNN total loss: 0.32226 L1 loss: 0.0000e+00 L2 loss: 1.69668 Learning rate: 0.02 Mask loss: 0.19933 RPN box loss: 0.03387 RPN score loss: 0.01468 RPN total loss: 0.04855 Total loss: 2.26683 timestamp: 1654921000.2213473 iteration: 7990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19992 FastRCNN class loss: 0.10639 FastRCNN total loss: 0.30631 L1 loss: 0.0000e+00 L2 loss: 1.69636 Learning rate: 0.02 Mask loss: 0.17017 RPN box loss: 0.04254 RPN score loss: 0.01246 RPN total loss: 0.055 Total loss: 2.22785 timestamp: 1654921003.5036335 iteration: 7995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15812 FastRCNN class loss: 0.10375 FastRCNN total loss: 0.26187 L1 loss: 0.0000e+00 L2 loss: 1.69606 Learning rate: 0.02 Mask loss: 0.18173 RPN box loss: 0.04635 RPN score loss: 0.01507 RPN total loss: 0.06143 Total loss: 2.20109 timestamp: 1654921006.7779236 iteration: 8000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11998 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.17344 L1 loss: 0.0000e+00 L2 loss: 1.69577 Learning rate: 0.02 Mask loss: 0.17982 RPN box loss: 0.05686 RPN score loss: 0.00772 RPN total loss: 0.06458 Total loss: 2.11361 timestamp: 1654921010.0293176 iteration: 8005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16352 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.23971 L1 loss: 0.0000e+00 L2 loss: 1.69547 Learning rate: 0.02 Mask loss: 0.10643 RPN box loss: 0.03069 RPN score loss: 0.00784 RPN total loss: 0.03853 Total loss: 2.08014 timestamp: 1654921013.2597425 iteration: 8010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17733 FastRCNN class loss: 0.08742 FastRCNN total loss: 0.26475 L1 loss: 0.0000e+00 L2 loss: 1.69517 Learning rate: 0.02 Mask loss: 0.17362 RPN box loss: 0.08136 RPN score loss: 0.0062 RPN total loss: 0.08756 Total loss: 2.22111 timestamp: 1654921016.4334307 iteration: 8015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18447 FastRCNN class loss: 0.10641 FastRCNN total loss: 0.29088 L1 loss: 0.0000e+00 L2 loss: 1.69486 Learning rate: 0.02 Mask loss: 0.13832 RPN box loss: 0.06566 RPN score loss: 0.00652 RPN total loss: 0.07218 Total loss: 2.19623 timestamp: 1654921019.6758754 iteration: 8020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09589 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.17585 L1 loss: 0.0000e+00 L2 loss: 1.69455 Learning rate: 0.02 Mask loss: 0.18401 RPN box loss: 0.0531 RPN score loss: 0.00693 RPN total loss: 0.06002 Total loss: 2.11443 timestamp: 1654921023.0501056 iteration: 8025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16469 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.23797 L1 loss: 0.0000e+00 L2 loss: 1.69424 Learning rate: 0.02 Mask loss: 0.19052 RPN box loss: 0.07755 RPN score loss: 0.01033 RPN total loss: 0.08789 Total loss: 2.21061 timestamp: 1654921026.1861904 iteration: 8030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22853 FastRCNN class loss: 0.09416 FastRCNN total loss: 0.32269 L1 loss: 0.0000e+00 L2 loss: 1.69393 Learning rate: 0.02 Mask loss: 0.17636 RPN box loss: 0.03643 RPN score loss: 0.01205 RPN total loss: 0.04847 Total loss: 2.24146 timestamp: 1654921029.5600436 iteration: 8035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16011 FastRCNN class loss: 0.15287 FastRCNN total loss: 0.31298 L1 loss: 0.0000e+00 L2 loss: 1.69365 Learning rate: 0.02 Mask loss: 0.21872 RPN box loss: 0.05398 RPN score loss: 0.0145 RPN total loss: 0.06849 Total loss: 2.29384 timestamp: 1654921032.7329912 iteration: 8040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12768 FastRCNN class loss: 0.07073 FastRCNN total loss: 0.1984 L1 loss: 0.0000e+00 L2 loss: 1.69334 Learning rate: 0.02 Mask loss: 0.13375 RPN box loss: 0.00726 RPN score loss: 0.00537 RPN total loss: 0.01263 Total loss: 2.03812 timestamp: 1654921036.0092173 iteration: 8045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22724 FastRCNN class loss: 0.11995 FastRCNN total loss: 0.34719 L1 loss: 0.0000e+00 L2 loss: 1.69302 Learning rate: 0.02 Mask loss: 0.21001 RPN box loss: 0.01903 RPN score loss: 0.00497 RPN total loss: 0.024 Total loss: 2.27422 timestamp: 1654921039.2274177 iteration: 8050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.07424 FastRCNN total loss: 0.2177 L1 loss: 0.0000e+00 L2 loss: 1.69271 Learning rate: 0.02 Mask loss: 0.18323 RPN box loss: 0.01823 RPN score loss: 0.00334 RPN total loss: 0.02156 Total loss: 2.1152 timestamp: 1654921042.653381 iteration: 8055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14888 FastRCNN class loss: 0.08027 FastRCNN total loss: 0.22915 L1 loss: 0.0000e+00 L2 loss: 1.69241 Learning rate: 0.02 Mask loss: 0.20409 RPN box loss: 0.03174 RPN score loss: 0.01148 RPN total loss: 0.04322 Total loss: 2.16887 timestamp: 1654921045.9484088 iteration: 8060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1005 FastRCNN class loss: 0.11914 FastRCNN total loss: 0.21964 L1 loss: 0.0000e+00 L2 loss: 1.69211 Learning rate: 0.02 Mask loss: 0.10115 RPN box loss: 0.00971 RPN score loss: 0.00394 RPN total loss: 0.01364 Total loss: 2.02654 timestamp: 1654921049.186282 iteration: 8065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19773 FastRCNN class loss: 0.14789 FastRCNN total loss: 0.34562 L1 loss: 0.0000e+00 L2 loss: 1.69177 Learning rate: 0.02 Mask loss: 0.17389 RPN box loss: 0.07079 RPN score loss: 0.01365 RPN total loss: 0.08444 Total loss: 2.29572 timestamp: 1654921052.459879 iteration: 8070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11855 FastRCNN class loss: 0.11278 FastRCNN total loss: 0.23133 L1 loss: 0.0000e+00 L2 loss: 1.69144 Learning rate: 0.02 Mask loss: 0.23637 RPN box loss: 0.0336 RPN score loss: 0.00337 RPN total loss: 0.03696 Total loss: 2.19611 timestamp: 1654921055.6534073 iteration: 8075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19651 FastRCNN class loss: 0.15012 FastRCNN total loss: 0.34663 L1 loss: 0.0000e+00 L2 loss: 1.69111 Learning rate: 0.02 Mask loss: 0.22739 RPN box loss: 0.02371 RPN score loss: 0.00656 RPN total loss: 0.03027 Total loss: 2.29539 timestamp: 1654921059.0340729 iteration: 8080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19797 FastRCNN class loss: 0.09919 FastRCNN total loss: 0.29716 L1 loss: 0.0000e+00 L2 loss: 1.6908 Learning rate: 0.02 Mask loss: 0.2307 RPN box loss: 0.05791 RPN score loss: 0.0091 RPN total loss: 0.06701 Total loss: 2.28567 timestamp: 1654921062.2829518 iteration: 8085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16261 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.23504 L1 loss: 0.0000e+00 L2 loss: 1.6905 Learning rate: 0.02 Mask loss: 0.34185 RPN box loss: 0.0312 RPN score loss: 0.00243 RPN total loss: 0.03364 Total loss: 2.30103 timestamp: 1654921065.5863073 iteration: 8090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15408 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.22516 L1 loss: 0.0000e+00 L2 loss: 1.69019 Learning rate: 0.02 Mask loss: 0.15142 RPN box loss: 0.02853 RPN score loss: 0.00456 RPN total loss: 0.03309 Total loss: 2.09986 timestamp: 1654921068.770952 iteration: 8095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10251 FastRCNN class loss: 0.10196 FastRCNN total loss: 0.20446 L1 loss: 0.0000e+00 L2 loss: 1.68988 Learning rate: 0.02 Mask loss: 0.12178 RPN box loss: 0.06214 RPN score loss: 0.00756 RPN total loss: 0.06971 Total loss: 2.08583 timestamp: 1654921072.0772996 iteration: 8100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.161 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.21711 L1 loss: 0.0000e+00 L2 loss: 1.68958 Learning rate: 0.02 Mask loss: 0.16247 RPN box loss: 0.03265 RPN score loss: 0.00542 RPN total loss: 0.03807 Total loss: 2.10722 timestamp: 1654921075.2212775 iteration: 8105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12047 FastRCNN class loss: 0.10693 FastRCNN total loss: 0.2274 L1 loss: 0.0000e+00 L2 loss: 1.68926 Learning rate: 0.02 Mask loss: 0.24319 RPN box loss: 0.06633 RPN score loss: 0.02657 RPN total loss: 0.0929 Total loss: 2.25276 timestamp: 1654921078.4446797 iteration: 8110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1293 FastRCNN class loss: 0.06887 FastRCNN total loss: 0.19817 L1 loss: 0.0000e+00 L2 loss: 1.68894 Learning rate: 0.02 Mask loss: 0.19162 RPN box loss: 0.05378 RPN score loss: 0.00803 RPN total loss: 0.06181 Total loss: 2.14054 timestamp: 1654921081.755237 iteration: 8115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18293 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.28573 L1 loss: 0.0000e+00 L2 loss: 1.68865 Learning rate: 0.02 Mask loss: 0.19986 RPN box loss: 0.05028 RPN score loss: 0.00549 RPN total loss: 0.05577 Total loss: 2.23001 timestamp: 1654921085.027385 iteration: 8120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21133 FastRCNN class loss: 0.11672 FastRCNN total loss: 0.32805 L1 loss: 0.0000e+00 L2 loss: 1.68834 Learning rate: 0.02 Mask loss: 0.19268 RPN box loss: 0.05333 RPN score loss: 0.00289 RPN total loss: 0.05622 Total loss: 2.26529 timestamp: 1654921088.3195908 iteration: 8125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22064 FastRCNN class loss: 0.17773 FastRCNN total loss: 0.39838 L1 loss: 0.0000e+00 L2 loss: 1.68804 Learning rate: 0.02 Mask loss: 0.25144 RPN box loss: 0.06206 RPN score loss: 0.03326 RPN total loss: 0.09533 Total loss: 2.43318 timestamp: 1654921091.539894 iteration: 8130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13933 FastRCNN class loss: 0.05431 FastRCNN total loss: 0.19364 L1 loss: 0.0000e+00 L2 loss: 1.68772 Learning rate: 0.02 Mask loss: 0.12253 RPN box loss: 0.02183 RPN score loss: 0.00357 RPN total loss: 0.0254 Total loss: 2.02928 timestamp: 1654921094.8448763 iteration: 8135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19803 FastRCNN class loss: 0.07704 FastRCNN total loss: 0.27507 L1 loss: 0.0000e+00 L2 loss: 1.68739 Learning rate: 0.02 Mask loss: 0.18447 RPN box loss: 0.04264 RPN score loss: 0.00715 RPN total loss: 0.04979 Total loss: 2.19672 timestamp: 1654921098.0670245 iteration: 8140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11645 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.18969 L1 loss: 0.0000e+00 L2 loss: 1.6871 Learning rate: 0.02 Mask loss: 0.11667 RPN box loss: 0.04071 RPN score loss: 0.00967 RPN total loss: 0.05038 Total loss: 2.04384 timestamp: 1654921101.3141952 iteration: 8145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12951 FastRCNN class loss: 0.07021 FastRCNN total loss: 0.19973 L1 loss: 0.0000e+00 L2 loss: 1.6868 Learning rate: 0.02 Mask loss: 0.33247 RPN box loss: 0.0647 RPN score loss: 0.01353 RPN total loss: 0.07823 Total loss: 2.29722 timestamp: 1654921104.5021718 iteration: 8150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21176 FastRCNN class loss: 0.19946 FastRCNN total loss: 0.41122 L1 loss: 0.0000e+00 L2 loss: 1.6865 Learning rate: 0.02 Mask loss: 0.21291 RPN box loss: 0.0464 RPN score loss: 0.02638 RPN total loss: 0.07279 Total loss: 2.38342 timestamp: 1654921107.8257992 iteration: 8155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09662 FastRCNN class loss: 0.04692 FastRCNN total loss: 0.14354 L1 loss: 0.0000e+00 L2 loss: 1.68621 Learning rate: 0.02 Mask loss: 0.18669 RPN box loss: 0.0337 RPN score loss: 0.00393 RPN total loss: 0.03763 Total loss: 2.05407 timestamp: 1654921111.1110613 iteration: 8160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25746 FastRCNN class loss: 0.12058 FastRCNN total loss: 0.37804 L1 loss: 0.0000e+00 L2 loss: 1.6859 Learning rate: 0.02 Mask loss: 0.15339 RPN box loss: 0.05227 RPN score loss: 0.01153 RPN total loss: 0.06381 Total loss: 2.28113 timestamp: 1654921114.30437 iteration: 8165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18425 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.26342 L1 loss: 0.0000e+00 L2 loss: 1.68558 Learning rate: 0.02 Mask loss: 0.20826 RPN box loss: 0.03216 RPN score loss: 0.01356 RPN total loss: 0.04572 Total loss: 2.20298 timestamp: 1654921117.5306005 iteration: 8170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20338 FastRCNN class loss: 0.11748 FastRCNN total loss: 0.32085 L1 loss: 0.0000e+00 L2 loss: 1.68528 Learning rate: 0.02 Mask loss: 0.22577 RPN box loss: 0.06738 RPN score loss: 0.02702 RPN total loss: 0.0944 Total loss: 2.32629 timestamp: 1654921120.7632515 iteration: 8175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13045 FastRCNN class loss: 0.11355 FastRCNN total loss: 0.244 L1 loss: 0.0000e+00 L2 loss: 1.68498 Learning rate: 0.02 Mask loss: 0.13928 RPN box loss: 0.0229 RPN score loss: 0.00344 RPN total loss: 0.02634 Total loss: 2.09459 timestamp: 1654921123.9388516 iteration: 8180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17645 FastRCNN class loss: 0.13139 FastRCNN total loss: 0.30784 L1 loss: 0.0000e+00 L2 loss: 1.68469 Learning rate: 0.02 Mask loss: 0.16747 RPN box loss: 0.03953 RPN score loss: 0.02568 RPN total loss: 0.06521 Total loss: 2.22521 timestamp: 1654921127.2199774 iteration: 8185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18133 FastRCNN class loss: 0.10186 FastRCNN total loss: 0.28319 L1 loss: 0.0000e+00 L2 loss: 1.6844 Learning rate: 0.02 Mask loss: 0.18323 RPN box loss: 0.01148 RPN score loss: 0.00579 RPN total loss: 0.01727 Total loss: 2.16809 timestamp: 1654921130.57564 iteration: 8190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18901 FastRCNN class loss: 0.10219 FastRCNN total loss: 0.2912 L1 loss: 0.0000e+00 L2 loss: 1.68409 Learning rate: 0.02 Mask loss: 0.16583 RPN box loss: 0.03586 RPN score loss: 0.00593 RPN total loss: 0.04178 Total loss: 2.1829 timestamp: 1654921133.7207246 iteration: 8195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13816 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.1924 L1 loss: 0.0000e+00 L2 loss: 1.68377 Learning rate: 0.02 Mask loss: 0.14855 RPN box loss: 0.05409 RPN score loss: 0.00785 RPN total loss: 0.06194 Total loss: 2.08665 timestamp: 1654921137.0199773 iteration: 8200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11802 FastRCNN class loss: 0.07584 FastRCNN total loss: 0.19387 L1 loss: 0.0000e+00 L2 loss: 1.68345 Learning rate: 0.02 Mask loss: 0.14861 RPN box loss: 0.04951 RPN score loss: 0.01173 RPN total loss: 0.06125 Total loss: 2.08717 timestamp: 1654921140.2312872 iteration: 8205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2024 FastRCNN class loss: 0.10442 FastRCNN total loss: 0.30682 L1 loss: 0.0000e+00 L2 loss: 1.68316 Learning rate: 0.02 Mask loss: 0.21737 RPN box loss: 0.08887 RPN score loss: 0.01584 RPN total loss: 0.10472 Total loss: 2.31206 timestamp: 1654921143.523372 iteration: 8210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1946 FastRCNN class loss: 0.07474 FastRCNN total loss: 0.26933 L1 loss: 0.0000e+00 L2 loss: 1.68284 Learning rate: 0.02 Mask loss: 0.162 RPN box loss: 0.06732 RPN score loss: 0.00992 RPN total loss: 0.07724 Total loss: 2.19142 timestamp: 1654921146.7062726 iteration: 8215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14107 FastRCNN class loss: 0.05709 FastRCNN total loss: 0.19816 L1 loss: 0.0000e+00 L2 loss: 1.68252 Learning rate: 0.02 Mask loss: 0.10843 RPN box loss: 0.03835 RPN score loss: 0.00447 RPN total loss: 0.04281 Total loss: 2.03191 timestamp: 1654921150.0369456 iteration: 8220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14344 FastRCNN class loss: 0.09832 FastRCNN total loss: 0.24175 L1 loss: 0.0000e+00 L2 loss: 1.68223 Learning rate: 0.02 Mask loss: 0.18154 RPN box loss: 0.01743 RPN score loss: 0.00664 RPN total loss: 0.02407 Total loss: 2.12959 timestamp: 1654921153.2854393 iteration: 8225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08425 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.16673 L1 loss: 0.0000e+00 L2 loss: 1.68193 Learning rate: 0.02 Mask loss: 0.16322 RPN box loss: 0.02619 RPN score loss: 0.00727 RPN total loss: 0.03346 Total loss: 2.04533 timestamp: 1654921156.511971 iteration: 8230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15368 FastRCNN class loss: 0.08666 FastRCNN total loss: 0.24034 L1 loss: 0.0000e+00 L2 loss: 1.68163 Learning rate: 0.02 Mask loss: 0.18321 RPN box loss: 0.03028 RPN score loss: 0.00394 RPN total loss: 0.03422 Total loss: 2.1394 timestamp: 1654921159.741215 iteration: 8235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13012 FastRCNN class loss: 0.08388 FastRCNN total loss: 0.214 L1 loss: 0.0000e+00 L2 loss: 1.68133 Learning rate: 0.02 Mask loss: 0.1696 RPN box loss: 0.03907 RPN score loss: 0.00635 RPN total loss: 0.04542 Total loss: 2.11035 timestamp: 1654921162.89977 iteration: 8240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25356 FastRCNN class loss: 0.13817 FastRCNN total loss: 0.39173 L1 loss: 0.0000e+00 L2 loss: 1.68102 Learning rate: 0.02 Mask loss: 0.20728 RPN box loss: 0.01607 RPN score loss: 0.01136 RPN total loss: 0.02743 Total loss: 2.30747 timestamp: 1654921166.2707465 iteration: 8245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16483 FastRCNN class loss: 0.08167 FastRCNN total loss: 0.2465 L1 loss: 0.0000e+00 L2 loss: 1.68072 Learning rate: 0.02 Mask loss: 0.16393 RPN box loss: 0.01292 RPN score loss: 0.00312 RPN total loss: 0.01604 Total loss: 2.10719 timestamp: 1654921169.4073277 iteration: 8250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25024 FastRCNN class loss: 0.13832 FastRCNN total loss: 0.38856 L1 loss: 0.0000e+00 L2 loss: 1.6804 Learning rate: 0.02 Mask loss: 0.22741 RPN box loss: 0.01559 RPN score loss: 0.02014 RPN total loss: 0.03573 Total loss: 2.3321 timestamp: 1654921172.7830083 iteration: 8255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1176 FastRCNN class loss: 0.04601 FastRCNN total loss: 0.16361 L1 loss: 0.0000e+00 L2 loss: 1.68008 Learning rate: 0.02 Mask loss: 0.13363 RPN box loss: 0.04103 RPN score loss: 0.00767 RPN total loss: 0.0487 Total loss: 2.02602 timestamp: 1654921175.9787977 iteration: 8260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19008 FastRCNN class loss: 0.0876 FastRCNN total loss: 0.27769 L1 loss: 0.0000e+00 L2 loss: 1.67977 Learning rate: 0.02 Mask loss: 0.15332 RPN box loss: 0.03365 RPN score loss: 0.00894 RPN total loss: 0.04259 Total loss: 2.15337 timestamp: 1654921179.3326213 iteration: 8265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23765 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.32846 L1 loss: 0.0000e+00 L2 loss: 1.67947 Learning rate: 0.02 Mask loss: 0.21023 RPN box loss: 0.02934 RPN score loss: 0.00568 RPN total loss: 0.03503 Total loss: 2.25318 timestamp: 1654921182.5618289 iteration: 8270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23622 FastRCNN class loss: 0.11946 FastRCNN total loss: 0.35567 L1 loss: 0.0000e+00 L2 loss: 1.67916 Learning rate: 0.02 Mask loss: 0.29097 RPN box loss: 0.03081 RPN score loss: 0.01033 RPN total loss: 0.04114 Total loss: 2.36694 timestamp: 1654921185.9085724 iteration: 8275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17869 FastRCNN class loss: 0.11073 FastRCNN total loss: 0.28942 L1 loss: 0.0000e+00 L2 loss: 1.67885 Learning rate: 0.02 Mask loss: 0.21405 RPN box loss: 0.02598 RPN score loss: 0.0087 RPN total loss: 0.03467 Total loss: 2.217 timestamp: 1654921189.2295027 iteration: 8280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24546 FastRCNN class loss: 0.10043 FastRCNN total loss: 0.3459 L1 loss: 0.0000e+00 L2 loss: 1.67853 Learning rate: 0.02 Mask loss: 0.33397 RPN box loss: 0.02162 RPN score loss: 0.008 RPN total loss: 0.02962 Total loss: 2.38802 timestamp: 1654921192.4316273 iteration: 8285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22263 FastRCNN class loss: 0.09036 FastRCNN total loss: 0.31299 L1 loss: 0.0000e+00 L2 loss: 1.67823 Learning rate: 0.02 Mask loss: 0.17384 RPN box loss: 0.02096 RPN score loss: 0.00422 RPN total loss: 0.02518 Total loss: 2.19024 timestamp: 1654921195.7185056 iteration: 8290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22509 FastRCNN class loss: 0.11911 FastRCNN total loss: 0.3442 L1 loss: 0.0000e+00 L2 loss: 1.67791 Learning rate: 0.02 Mask loss: 0.24716 RPN box loss: 0.03588 RPN score loss: 0.00577 RPN total loss: 0.04165 Total loss: 2.31093 timestamp: 1654921198.8816051 iteration: 8295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15355 FastRCNN class loss: 0.15209 FastRCNN total loss: 0.30564 L1 loss: 0.0000e+00 L2 loss: 1.6776 Learning rate: 0.02 Mask loss: 0.23292 RPN box loss: 0.05163 RPN score loss: 0.01248 RPN total loss: 0.06411 Total loss: 2.28027 timestamp: 1654921202.1929731 iteration: 8300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19251 FastRCNN class loss: 0.1918 FastRCNN total loss: 0.38431 L1 loss: 0.0000e+00 L2 loss: 1.6773 Learning rate: 0.02 Mask loss: 0.2553 RPN box loss: 0.05774 RPN score loss: 0.0194 RPN total loss: 0.07714 Total loss: 2.39405 timestamp: 1654921205.3821182 iteration: 8305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22098 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.28631 L1 loss: 0.0000e+00 L2 loss: 1.67699 Learning rate: 0.02 Mask loss: 0.12002 RPN box loss: 0.09099 RPN score loss: 0.00828 RPN total loss: 0.09928 Total loss: 2.1826 timestamp: 1654921208.7314532 iteration: 8310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24286 FastRCNN class loss: 0.20107 FastRCNN total loss: 0.44393 L1 loss: 0.0000e+00 L2 loss: 1.67669 Learning rate: 0.02 Mask loss: 0.2584 RPN box loss: 0.05457 RPN score loss: 0.02852 RPN total loss: 0.08309 Total loss: 2.46211 timestamp: 1654921212.027029 iteration: 8315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17701 FastRCNN class loss: 0.16629 FastRCNN total loss: 0.34331 L1 loss: 0.0000e+00 L2 loss: 1.67639 Learning rate: 0.02 Mask loss: 0.23324 RPN box loss: 0.06066 RPN score loss: 0.01755 RPN total loss: 0.07821 Total loss: 2.33116 timestamp: 1654921215.3850212 iteration: 8320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15595 FastRCNN class loss: 0.0934 FastRCNN total loss: 0.24935 L1 loss: 0.0000e+00 L2 loss: 1.67609 Learning rate: 0.02 Mask loss: 0.15784 RPN box loss: 0.02817 RPN score loss: 0.01427 RPN total loss: 0.04244 Total loss: 2.12572 timestamp: 1654921218.6483023 iteration: 8325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14962 FastRCNN class loss: 0.09607 FastRCNN total loss: 0.2457 L1 loss: 0.0000e+00 L2 loss: 1.67578 Learning rate: 0.02 Mask loss: 0.12003 RPN box loss: 0.01948 RPN score loss: 0.00663 RPN total loss: 0.02612 Total loss: 2.06762 timestamp: 1654921221.8931892 iteration: 8330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15254 FastRCNN class loss: 0.09597 FastRCNN total loss: 0.2485 L1 loss: 0.0000e+00 L2 loss: 1.67544 Learning rate: 0.02 Mask loss: 0.16622 RPN box loss: 0.01351 RPN score loss: 0.0041 RPN total loss: 0.01761 Total loss: 2.10778 timestamp: 1654921225.1997192 iteration: 8335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.09369 FastRCNN total loss: 0.21257 L1 loss: 0.0000e+00 L2 loss: 1.67514 Learning rate: 0.02 Mask loss: 0.17047 RPN box loss: 0.04712 RPN score loss: 0.01202 RPN total loss: 0.05913 Total loss: 2.11731 timestamp: 1654921228.3823426 iteration: 8340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19699 FastRCNN class loss: 0.12227 FastRCNN total loss: 0.31927 L1 loss: 0.0000e+00 L2 loss: 1.67486 Learning rate: 0.02 Mask loss: 0.24208 RPN box loss: 0.03404 RPN score loss: 0.00849 RPN total loss: 0.04253 Total loss: 2.27873 timestamp: 1654921231.7388692 iteration: 8345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17874 FastRCNN class loss: 0.08728 FastRCNN total loss: 0.26602 L1 loss: 0.0000e+00 L2 loss: 1.67457 Learning rate: 0.02 Mask loss: 0.17659 RPN box loss: 0.06692 RPN score loss: 0.00574 RPN total loss: 0.07266 Total loss: 2.18985 timestamp: 1654921234.9981446 iteration: 8350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2538 FastRCNN class loss: 0.11685 FastRCNN total loss: 0.37065 L1 loss: 0.0000e+00 L2 loss: 1.67427 Learning rate: 0.02 Mask loss: 0.24649 RPN box loss: 0.03368 RPN score loss: 0.00428 RPN total loss: 0.03795 Total loss: 2.32936 timestamp: 1654921238.345206 iteration: 8355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21708 FastRCNN class loss: 0.1022 FastRCNN total loss: 0.31928 L1 loss: 0.0000e+00 L2 loss: 1.67396 Learning rate: 0.02 Mask loss: 0.18564 RPN box loss: 0.06518 RPN score loss: 0.0043 RPN total loss: 0.06948 Total loss: 2.24835 timestamp: 1654921241.588179 iteration: 8360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16757 FastRCNN class loss: 0.12051 FastRCNN total loss: 0.28808 L1 loss: 0.0000e+00 L2 loss: 1.67363 Learning rate: 0.02 Mask loss: 0.18477 RPN box loss: 0.02023 RPN score loss: 0.00504 RPN total loss: 0.02527 Total loss: 2.17175 timestamp: 1654921244.7914875 iteration: 8365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11164 FastRCNN class loss: 0.0681 FastRCNN total loss: 0.17974 L1 loss: 0.0000e+00 L2 loss: 1.67332 Learning rate: 0.02 Mask loss: 0.18971 RPN box loss: 0.00757 RPN score loss: 0.0044 RPN total loss: 0.01197 Total loss: 2.05474 timestamp: 1654921248.0016735 iteration: 8370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1739 FastRCNN class loss: 0.13905 FastRCNN total loss: 0.31295 L1 loss: 0.0000e+00 L2 loss: 1.67301 Learning rate: 0.02 Mask loss: 0.16069 RPN box loss: 0.0144 RPN score loss: 0.00584 RPN total loss: 0.02024 Total loss: 2.16688 timestamp: 1654921251.3020413 iteration: 8375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18892 FastRCNN class loss: 0.0654 FastRCNN total loss: 0.25432 L1 loss: 0.0000e+00 L2 loss: 1.67271 Learning rate: 0.02 Mask loss: 0.16757 RPN box loss: 0.01558 RPN score loss: 0.00662 RPN total loss: 0.02219 Total loss: 2.1168 timestamp: 1654921254.578017 iteration: 8380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15932 FastRCNN class loss: 0.10986 FastRCNN total loss: 0.26918 L1 loss: 0.0000e+00 L2 loss: 1.67242 Learning rate: 0.02 Mask loss: 0.17156 RPN box loss: 0.06979 RPN score loss: 0.01343 RPN total loss: 0.08322 Total loss: 2.19638 timestamp: 1654921257.8757184 iteration: 8385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24163 FastRCNN class loss: 0.10107 FastRCNN total loss: 0.3427 L1 loss: 0.0000e+00 L2 loss: 1.67211 Learning rate: 0.02 Mask loss: 0.20928 RPN box loss: 0.02318 RPN score loss: 0.00584 RPN total loss: 0.02903 Total loss: 2.25312 timestamp: 1654921261.1173263 iteration: 8390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18503 FastRCNN class loss: 0.1025 FastRCNN total loss: 0.28753 L1 loss: 0.0000e+00 L2 loss: 1.67184 Learning rate: 0.02 Mask loss: 0.187 RPN box loss: 0.03338 RPN score loss: 0.01143 RPN total loss: 0.04481 Total loss: 2.19117 timestamp: 1654921264.3475404 iteration: 8395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11811 FastRCNN class loss: 0.05538 FastRCNN total loss: 0.17349 L1 loss: 0.0000e+00 L2 loss: 1.67154 Learning rate: 0.02 Mask loss: 0.11156 RPN box loss: 0.0495 RPN score loss: 0.00872 RPN total loss: 0.05823 Total loss: 2.01482 timestamp: 1654921267.6424828 iteration: 8400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2247 FastRCNN class loss: 0.11685 FastRCNN total loss: 0.34155 L1 loss: 0.0000e+00 L2 loss: 1.67123 Learning rate: 0.02 Mask loss: 0.20118 RPN box loss: 0.0979 RPN score loss: 0.0175 RPN total loss: 0.11541 Total loss: 2.32937 timestamp: 1654921270.8535595 iteration: 8405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20015 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.29243 L1 loss: 0.0000e+00 L2 loss: 1.67093 Learning rate: 0.02 Mask loss: 0.22255 RPN box loss: 0.00752 RPN score loss: 0.00471 RPN total loss: 0.01223 Total loss: 2.19814 timestamp: 1654921274.0928798 iteration: 8410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21346 FastRCNN class loss: 0.14439 FastRCNN total loss: 0.35786 L1 loss: 0.0000e+00 L2 loss: 1.67063 Learning rate: 0.02 Mask loss: 0.22317 RPN box loss: 0.03225 RPN score loss: 0.02184 RPN total loss: 0.0541 Total loss: 2.30576 timestamp: 1654921277.3282974 iteration: 8415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20028 FastRCNN class loss: 0.15107 FastRCNN total loss: 0.35135 L1 loss: 0.0000e+00 L2 loss: 1.67031 Learning rate: 0.02 Mask loss: 0.26163 RPN box loss: 0.0569 RPN score loss: 0.01341 RPN total loss: 0.07031 Total loss: 2.3536 timestamp: 1654921280.6681828 iteration: 8420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12143 FastRCNN class loss: 0.09101 FastRCNN total loss: 0.21244 L1 loss: 0.0000e+00 L2 loss: 1.67 Learning rate: 0.02 Mask loss: 0.18196 RPN box loss: 0.07852 RPN score loss: 0.01997 RPN total loss: 0.0985 Total loss: 2.1629 timestamp: 1654921284.1090724 iteration: 8425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10138 FastRCNN class loss: 0.07124 FastRCNN total loss: 0.17262 L1 loss: 0.0000e+00 L2 loss: 1.66971 Learning rate: 0.02 Mask loss: 0.09384 RPN box loss: 0.05147 RPN score loss: 0.00428 RPN total loss: 0.05575 Total loss: 1.99193 timestamp: 1654921287.3445253 iteration: 8430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16863 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.25424 L1 loss: 0.0000e+00 L2 loss: 1.66939 Learning rate: 0.02 Mask loss: 0.2401 RPN box loss: 0.03892 RPN score loss: 0.01383 RPN total loss: 0.05275 Total loss: 2.21649 timestamp: 1654921290.6487014 iteration: 8435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22501 FastRCNN class loss: 0.12105 FastRCNN total loss: 0.34606 L1 loss: 0.0000e+00 L2 loss: 1.6691 Learning rate: 0.02 Mask loss: 0.21849 RPN box loss: 0.04096 RPN score loss: 0.00969 RPN total loss: 0.05064 Total loss: 2.2843 timestamp: 1654921293.84314 iteration: 8440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09926 FastRCNN class loss: 0.05186 FastRCNN total loss: 0.15111 L1 loss: 0.0000e+00 L2 loss: 1.66882 Learning rate: 0.02 Mask loss: 0.14414 RPN box loss: 0.02544 RPN score loss: 0.00812 RPN total loss: 0.03356 Total loss: 1.99764 timestamp: 1654921297.121799 iteration: 8445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18349 FastRCNN class loss: 0.08763 FastRCNN total loss: 0.27112 L1 loss: 0.0000e+00 L2 loss: 1.6685 Learning rate: 0.02 Mask loss: 0.12846 RPN box loss: 0.02236 RPN score loss: 0.00591 RPN total loss: 0.02827 Total loss: 2.09636 timestamp: 1654921300.3022196 iteration: 8450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20861 FastRCNN class loss: 0.09178 FastRCNN total loss: 0.30039 L1 loss: 0.0000e+00 L2 loss: 1.66819 Learning rate: 0.02 Mask loss: 0.21409 RPN box loss: 0.04048 RPN score loss: 0.00662 RPN total loss: 0.0471 Total loss: 2.22977 timestamp: 1654921303.6371047 iteration: 8455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16797 FastRCNN class loss: 0.10619 FastRCNN total loss: 0.27416 L1 loss: 0.0000e+00 L2 loss: 1.66788 Learning rate: 0.02 Mask loss: 0.14377 RPN box loss: 0.07459 RPN score loss: 0.01198 RPN total loss: 0.08657 Total loss: 2.17237 timestamp: 1654921306.8764238 iteration: 8460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16198 FastRCNN class loss: 0.12522 FastRCNN total loss: 0.28719 L1 loss: 0.0000e+00 L2 loss: 1.66758 Learning rate: 0.02 Mask loss: 0.30404 RPN box loss: 0.04214 RPN score loss: 0.00699 RPN total loss: 0.04914 Total loss: 2.30796 timestamp: 1654921310.1020775 iteration: 8465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11478 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.17555 L1 loss: 0.0000e+00 L2 loss: 1.66727 Learning rate: 0.02 Mask loss: 0.12969 RPN box loss: 0.02406 RPN score loss: 0.00484 RPN total loss: 0.0289 Total loss: 2.00141 timestamp: 1654921313.265683 iteration: 8470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16763 FastRCNN class loss: 0.0851 FastRCNN total loss: 0.25273 L1 loss: 0.0000e+00 L2 loss: 1.66694 Learning rate: 0.02 Mask loss: 0.21382 RPN box loss: 0.03442 RPN score loss: 0.01096 RPN total loss: 0.04538 Total loss: 2.17887 timestamp: 1654921316.5151083 iteration: 8475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09279 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.17534 L1 loss: 0.0000e+00 L2 loss: 1.66663 Learning rate: 0.02 Mask loss: 0.12357 RPN box loss: 0.03412 RPN score loss: 0.00398 RPN total loss: 0.03811 Total loss: 2.00364 timestamp: 1654921319.751309 iteration: 8480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23793 FastRCNN class loss: 0.11153 FastRCNN total loss: 0.34946 L1 loss: 0.0000e+00 L2 loss: 1.66631 Learning rate: 0.02 Mask loss: 0.23777 RPN box loss: 0.02203 RPN score loss: 0.01957 RPN total loss: 0.0416 Total loss: 2.29514 timestamp: 1654921322.9581852 iteration: 8485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11741 FastRCNN class loss: 0.06866 FastRCNN total loss: 0.18607 L1 loss: 0.0000e+00 L2 loss: 1.666 Learning rate: 0.02 Mask loss: 0.15135 RPN box loss: 0.06587 RPN score loss: 0.00599 RPN total loss: 0.07186 Total loss: 2.07527 timestamp: 1654921326.280606 iteration: 8490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13959 FastRCNN class loss: 0.08984 FastRCNN total loss: 0.22943 L1 loss: 0.0000e+00 L2 loss: 1.6657 Learning rate: 0.02 Mask loss: 0.18907 RPN box loss: 0.05435 RPN score loss: 0.00498 RPN total loss: 0.05933 Total loss: 2.14353 timestamp: 1654921329.5258808 iteration: 8495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16515 FastRCNN class loss: 0.09205 FastRCNN total loss: 0.2572 L1 loss: 0.0000e+00 L2 loss: 1.66539 Learning rate: 0.02 Mask loss: 0.10156 RPN box loss: 0.03227 RPN score loss: 0.00432 RPN total loss: 0.03659 Total loss: 2.06074 timestamp: 1654921332.817891 iteration: 8500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18286 FastRCNN class loss: 0.10616 FastRCNN total loss: 0.28902 L1 loss: 0.0000e+00 L2 loss: 1.66508 Learning rate: 0.02 Mask loss: 0.27644 RPN box loss: 0.05479 RPN score loss: 0.00632 RPN total loss: 0.06111 Total loss: 2.29165 timestamp: 1654921335.9801393 iteration: 8505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12637 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.1953 L1 loss: 0.0000e+00 L2 loss: 1.66479 Learning rate: 0.02 Mask loss: 0.17432 RPN box loss: 0.03763 RPN score loss: 0.00952 RPN total loss: 0.04715 Total loss: 2.08156 timestamp: 1654921339.2951634 iteration: 8510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18366 FastRCNN class loss: 0.10312 FastRCNN total loss: 0.28678 L1 loss: 0.0000e+00 L2 loss: 1.66452 Learning rate: 0.02 Mask loss: 0.25591 RPN box loss: 0.01951 RPN score loss: 0.00664 RPN total loss: 0.02614 Total loss: 2.23335 timestamp: 1654921342.44273 iteration: 8515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15663 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.22452 L1 loss: 0.0000e+00 L2 loss: 1.66422 Learning rate: 0.02 Mask loss: 0.12509 RPN box loss: 0.05613 RPN score loss: 0.00727 RPN total loss: 0.06339 Total loss: 2.07722 timestamp: 1654921345.8179495 iteration: 8520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18445 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.25406 L1 loss: 0.0000e+00 L2 loss: 1.66394 Learning rate: 0.02 Mask loss: 0.21405 RPN box loss: 0.01032 RPN score loss: 0.00327 RPN total loss: 0.01359 Total loss: 2.14564 timestamp: 1654921349.0629623 iteration: 8525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17798 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.25563 L1 loss: 0.0000e+00 L2 loss: 1.66363 Learning rate: 0.02 Mask loss: 0.13295 RPN box loss: 0.01658 RPN score loss: 0.0032 RPN total loss: 0.01977 Total loss: 2.07199 timestamp: 1654921352.3932498 iteration: 8530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21585 FastRCNN class loss: 0.12157 FastRCNN total loss: 0.33741 L1 loss: 0.0000e+00 L2 loss: 1.66333 Learning rate: 0.02 Mask loss: 0.15598 RPN box loss: 0.02626 RPN score loss: 0.00712 RPN total loss: 0.03338 Total loss: 2.19011 timestamp: 1654921355.695113 iteration: 8535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1373 FastRCNN class loss: 0.11583 FastRCNN total loss: 0.25313 L1 loss: 0.0000e+00 L2 loss: 1.66301 Learning rate: 0.02 Mask loss: 0.27159 RPN box loss: 0.02576 RPN score loss: 0.0024 RPN total loss: 0.02815 Total loss: 2.21589 timestamp: 1654921358.8892837 iteration: 8540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30702 FastRCNN class loss: 0.14324 FastRCNN total loss: 0.45026 L1 loss: 0.0000e+00 L2 loss: 1.66269 Learning rate: 0.02 Mask loss: 0.17428 RPN box loss: 0.0174 RPN score loss: 0.00298 RPN total loss: 0.02038 Total loss: 2.30762 timestamp: 1654921362.1625621 iteration: 8545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17353 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.25556 L1 loss: 0.0000e+00 L2 loss: 1.66239 Learning rate: 0.02 Mask loss: 0.17336 RPN box loss: 0.02624 RPN score loss: 0.0092 RPN total loss: 0.03544 Total loss: 2.12675 timestamp: 1654921365.47592 iteration: 8550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16029 FastRCNN class loss: 0.08908 FastRCNN total loss: 0.24937 L1 loss: 0.0000e+00 L2 loss: 1.6621 Learning rate: 0.02 Mask loss: 0.20282 RPN box loss: 0.03162 RPN score loss: 0.00931 RPN total loss: 0.04093 Total loss: 2.15522 timestamp: 1654921368.7371721 iteration: 8555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18779 FastRCNN class loss: 0.16089 FastRCNN total loss: 0.34868 L1 loss: 0.0000e+00 L2 loss: 1.6618 Learning rate: 0.02 Mask loss: 0.2446 RPN box loss: 0.09037 RPN score loss: 0.01655 RPN total loss: 0.10693 Total loss: 2.36201 timestamp: 1654921372.0009975 iteration: 8560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23059 FastRCNN class loss: 0.1157 FastRCNN total loss: 0.34629 L1 loss: 0.0000e+00 L2 loss: 1.66149 Learning rate: 0.02 Mask loss: 0.27322 RPN box loss: 0.04649 RPN score loss: 0.02109 RPN total loss: 0.06759 Total loss: 2.34859 timestamp: 1654921375.2397618 iteration: 8565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15569 FastRCNN class loss: 0.08241 FastRCNN total loss: 0.23809 L1 loss: 0.0000e+00 L2 loss: 1.6612 Learning rate: 0.02 Mask loss: 0.15439 RPN box loss: 0.0151 RPN score loss: 0.00268 RPN total loss: 0.01778 Total loss: 2.07146 timestamp: 1654921378.5374665 iteration: 8570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1393 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.20856 L1 loss: 0.0000e+00 L2 loss: 1.66091 Learning rate: 0.02 Mask loss: 0.15771 RPN box loss: 0.13191 RPN score loss: 0.00675 RPN total loss: 0.13866 Total loss: 2.16584 timestamp: 1654921381.8005614 iteration: 8575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16278 FastRCNN class loss: 0.10977 FastRCNN total loss: 0.27255 L1 loss: 0.0000e+00 L2 loss: 1.66059 Learning rate: 0.02 Mask loss: 0.15932 RPN box loss: 0.03048 RPN score loss: 0.01268 RPN total loss: 0.04316 Total loss: 2.13562 timestamp: 1654921385.1528304 iteration: 8580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19555 FastRCNN class loss: 0.12916 FastRCNN total loss: 0.3247 L1 loss: 0.0000e+00 L2 loss: 1.66028 Learning rate: 0.02 Mask loss: 0.19897 RPN box loss: 0.01707 RPN score loss: 0.01065 RPN total loss: 0.02771 Total loss: 2.21166 timestamp: 1654921388.388325 iteration: 8585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14528 FastRCNN class loss: 0.10618 FastRCNN total loss: 0.25146 L1 loss: 0.0000e+00 L2 loss: 1.65998 Learning rate: 0.02 Mask loss: 0.20157 RPN box loss: 0.1023 RPN score loss: 0.0177 RPN total loss: 0.12 Total loss: 2.23302 timestamp: 1654921391.679391 iteration: 8590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20928 FastRCNN class loss: 0.13331 FastRCNN total loss: 0.34259 L1 loss: 0.0000e+00 L2 loss: 1.65969 Learning rate: 0.02 Mask loss: 0.27972 RPN box loss: 0.06682 RPN score loss: 0.0067 RPN total loss: 0.07352 Total loss: 2.35554 timestamp: 1654921394.929207 iteration: 8595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11773 FastRCNN class loss: 0.08121 FastRCNN total loss: 0.19893 L1 loss: 0.0000e+00 L2 loss: 1.6594 Learning rate: 0.02 Mask loss: 0.18695 RPN box loss: 0.01071 RPN score loss: 0.00596 RPN total loss: 0.01667 Total loss: 2.06196 timestamp: 1654921398.2974107 iteration: 8600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22209 FastRCNN class loss: 0.1888 FastRCNN total loss: 0.41089 L1 loss: 0.0000e+00 L2 loss: 1.65911 Learning rate: 0.02 Mask loss: 0.24498 RPN box loss: 0.04295 RPN score loss: 0.01957 RPN total loss: 0.06252 Total loss: 2.37749 timestamp: 1654921401.5239537 iteration: 8605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13665 FastRCNN class loss: 0.12373 FastRCNN total loss: 0.26037 L1 loss: 0.0000e+00 L2 loss: 1.65877 Learning rate: 0.02 Mask loss: 0.17663 RPN box loss: 0.02429 RPN score loss: 0.01101 RPN total loss: 0.0353 Total loss: 2.13108 timestamp: 1654921404.879268 iteration: 8610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10747 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.18036 L1 loss: 0.0000e+00 L2 loss: 1.65848 Learning rate: 0.02 Mask loss: 0.18208 RPN box loss: 0.06815 RPN score loss: 0.00992 RPN total loss: 0.07807 Total loss: 2.09899 timestamp: 1654921408.098737 iteration: 8615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12603 FastRCNN class loss: 0.08775 FastRCNN total loss: 0.21378 L1 loss: 0.0000e+00 L2 loss: 1.65819 Learning rate: 0.02 Mask loss: 0.15228 RPN box loss: 0.05624 RPN score loss: 0.01318 RPN total loss: 0.06942 Total loss: 2.09368 timestamp: 1654921411.3520043 iteration: 8620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13693 FastRCNN class loss: 0.10072 FastRCNN total loss: 0.23764 L1 loss: 0.0000e+00 L2 loss: 1.65787 Learning rate: 0.02 Mask loss: 0.1294 RPN box loss: 0.08771 RPN score loss: 0.0102 RPN total loss: 0.09791 Total loss: 2.12283 timestamp: 1654921414.5832171 iteration: 8625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18225 FastRCNN class loss: 0.09098 FastRCNN total loss: 0.27323 L1 loss: 0.0000e+00 L2 loss: 1.65757 Learning rate: 0.02 Mask loss: 0.23444 RPN box loss: 0.03362 RPN score loss: 0.0069 RPN total loss: 0.04053 Total loss: 2.20577 timestamp: 1654921417.7761433 iteration: 8630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1081 FastRCNN class loss: 0.08143 FastRCNN total loss: 0.18953 L1 loss: 0.0000e+00 L2 loss: 1.65724 Learning rate: 0.02 Mask loss: 0.16861 RPN box loss: 0.01278 RPN score loss: 0.00535 RPN total loss: 0.01812 Total loss: 2.03351 timestamp: 1654921421.1022482 iteration: 8635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19992 FastRCNN class loss: 0.13331 FastRCNN total loss: 0.33323 L1 loss: 0.0000e+00 L2 loss: 1.65693 Learning rate: 0.02 Mask loss: 0.20717 RPN box loss: 0.11003 RPN score loss: 0.02385 RPN total loss: 0.13388 Total loss: 2.3312 timestamp: 1654921424.3320358 iteration: 8640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19613 FastRCNN class loss: 0.10327 FastRCNN total loss: 0.2994 L1 loss: 0.0000e+00 L2 loss: 1.65663 Learning rate: 0.02 Mask loss: 0.17643 RPN box loss: 0.01658 RPN score loss: 0.00822 RPN total loss: 0.0248 Total loss: 2.15727 timestamp: 1654921427.5521188 iteration: 8645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17448 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.23596 L1 loss: 0.0000e+00 L2 loss: 1.65633 Learning rate: 0.02 Mask loss: 0.14209 RPN box loss: 0.06211 RPN score loss: 0.01003 RPN total loss: 0.07214 Total loss: 2.10653 timestamp: 1654921430.7587636 iteration: 8650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18193 FastRCNN class loss: 0.12127 FastRCNN total loss: 0.3032 L1 loss: 0.0000e+00 L2 loss: 1.65605 Learning rate: 0.02 Mask loss: 0.22029 RPN box loss: 0.01935 RPN score loss: 0.0081 RPN total loss: 0.02744 Total loss: 2.20698 timestamp: 1654921434.1218548 iteration: 8655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19787 FastRCNN class loss: 0.13264 FastRCNN total loss: 0.33051 L1 loss: 0.0000e+00 L2 loss: 1.65573 Learning rate: 0.02 Mask loss: 0.23587 RPN box loss: 0.0642 RPN score loss: 0.01515 RPN total loss: 0.07935 Total loss: 2.30147 timestamp: 1654921437.3073308 iteration: 8660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21215 FastRCNN class loss: 0.2003 FastRCNN total loss: 0.41245 L1 loss: 0.0000e+00 L2 loss: 1.65544 Learning rate: 0.02 Mask loss: 0.23888 RPN box loss: 0.03446 RPN score loss: 0.01601 RPN total loss: 0.05047 Total loss: 2.35724 timestamp: 1654921440.5669756 iteration: 8665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14039 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.19567 L1 loss: 0.0000e+00 L2 loss: 1.65514 Learning rate: 0.02 Mask loss: 0.16822 RPN box loss: 0.03366 RPN score loss: 0.008 RPN total loss: 0.04166 Total loss: 2.06069 timestamp: 1654921443.7931736 iteration: 8670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23307 FastRCNN class loss: 0.14019 FastRCNN total loss: 0.37325 L1 loss: 0.0000e+00 L2 loss: 1.65483 Learning rate: 0.02 Mask loss: 0.25025 RPN box loss: 0.05228 RPN score loss: 0.0078 RPN total loss: 0.06008 Total loss: 2.33841 timestamp: 1654921447.1218312 iteration: 8675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15121 FastRCNN class loss: 0.0696 FastRCNN total loss: 0.22081 L1 loss: 0.0000e+00 L2 loss: 1.65452 Learning rate: 0.02 Mask loss: 0.14389 RPN box loss: 0.05498 RPN score loss: 0.0082 RPN total loss: 0.06319 Total loss: 2.08241 timestamp: 1654921450.3414185 iteration: 8680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16109 FastRCNN class loss: 0.05881 FastRCNN total loss: 0.2199 L1 loss: 0.0000e+00 L2 loss: 1.65425 Learning rate: 0.02 Mask loss: 0.09439 RPN box loss: 0.02315 RPN score loss: 0.00258 RPN total loss: 0.02573 Total loss: 1.99428 timestamp: 1654921453.681598 iteration: 8685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20153 FastRCNN class loss: 0.15135 FastRCNN total loss: 0.35288 L1 loss: 0.0000e+00 L2 loss: 1.65397 Learning rate: 0.02 Mask loss: 0.19226 RPN box loss: 0.04625 RPN score loss: 0.0115 RPN total loss: 0.05776 Total loss: 2.25687 timestamp: 1654921457.0431752 iteration: 8690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16602 FastRCNN class loss: 0.11135 FastRCNN total loss: 0.27737 L1 loss: 0.0000e+00 L2 loss: 1.65369 Learning rate: 0.02 Mask loss: 0.18586 RPN box loss: 0.01584 RPN score loss: 0.00234 RPN total loss: 0.01818 Total loss: 2.13509 timestamp: 1654921460.2774763 iteration: 8695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1607 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.23741 L1 loss: 0.0000e+00 L2 loss: 1.65337 Learning rate: 0.02 Mask loss: 0.16574 RPN box loss: 0.01461 RPN score loss: 0.00513 RPN total loss: 0.01975 Total loss: 2.07627 timestamp: 1654921463.5646741 iteration: 8700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19565 FastRCNN class loss: 0.09984 FastRCNN total loss: 0.29549 L1 loss: 0.0000e+00 L2 loss: 1.65305 Learning rate: 0.02 Mask loss: 0.21058 RPN box loss: 0.01649 RPN score loss: 0.01113 RPN total loss: 0.02761 Total loss: 2.18674 timestamp: 1654921466.8034253 iteration: 8705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15965 FastRCNN class loss: 0.09832 FastRCNN total loss: 0.25797 L1 loss: 0.0000e+00 L2 loss: 1.65275 Learning rate: 0.02 Mask loss: 0.15935 RPN box loss: 0.02576 RPN score loss: 0.00302 RPN total loss: 0.02878 Total loss: 2.09885 timestamp: 1654921469.995663 iteration: 8710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14773 FastRCNN class loss: 0.05682 FastRCNN total loss: 0.20455 L1 loss: 0.0000e+00 L2 loss: 1.65246 Learning rate: 0.02 Mask loss: 0.14343 RPN box loss: 0.00574 RPN score loss: 0.00394 RPN total loss: 0.00968 Total loss: 2.01012 timestamp: 1654921473.145433 iteration: 8715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16128 FastRCNN class loss: 0.11971 FastRCNN total loss: 0.28099 L1 loss: 0.0000e+00 L2 loss: 1.65216 Learning rate: 0.02 Mask loss: 0.18902 RPN box loss: 0.03802 RPN score loss: 0.01748 RPN total loss: 0.0555 Total loss: 2.17767 timestamp: 1654921476.3729918 iteration: 8720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25869 FastRCNN class loss: 0.13147 FastRCNN total loss: 0.39016 L1 loss: 0.0000e+00 L2 loss: 1.65186 Learning rate: 0.02 Mask loss: 0.19157 RPN box loss: 0.03382 RPN score loss: 0.01286 RPN total loss: 0.04668 Total loss: 2.28026 timestamp: 1654921479.590454 iteration: 8725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0931 FastRCNN class loss: 0.07859 FastRCNN total loss: 0.17169 L1 loss: 0.0000e+00 L2 loss: 1.65157 Learning rate: 0.02 Mask loss: 0.11383 RPN box loss: 0.01411 RPN score loss: 0.00293 RPN total loss: 0.01704 Total loss: 1.95413 timestamp: 1654921483.0129354 iteration: 8730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26317 FastRCNN class loss: 0.18956 FastRCNN total loss: 0.45272 L1 loss: 0.0000e+00 L2 loss: 1.65126 Learning rate: 0.02 Mask loss: 0.31702 RPN box loss: 0.0392 RPN score loss: 0.01198 RPN total loss: 0.05119 Total loss: 2.47219 timestamp: 1654921486.3174992 iteration: 8735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14701 FastRCNN class loss: 0.10165 FastRCNN total loss: 0.24866 L1 loss: 0.0000e+00 L2 loss: 1.65094 Learning rate: 0.02 Mask loss: 0.22411 RPN box loss: 0.04747 RPN score loss: 0.01637 RPN total loss: 0.06384 Total loss: 2.18755 timestamp: 1654921489.5721083 iteration: 8740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23872 FastRCNN class loss: 0.10614 FastRCNN total loss: 0.34486 L1 loss: 0.0000e+00 L2 loss: 1.65064 Learning rate: 0.02 Mask loss: 0.2751 RPN box loss: 0.07253 RPN score loss: 0.00929 RPN total loss: 0.08182 Total loss: 2.35243 timestamp: 1654921492.8587708 iteration: 8745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13017 FastRCNN class loss: 0.04903 FastRCNN total loss: 0.1792 L1 loss: 0.0000e+00 L2 loss: 1.65033 Learning rate: 0.02 Mask loss: 0.15008 RPN box loss: 0.01181 RPN score loss: 0.00621 RPN total loss: 0.01802 Total loss: 1.99763 timestamp: 1654921496.065043 iteration: 8750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14191 FastRCNN class loss: 0.12732 FastRCNN total loss: 0.26924 L1 loss: 0.0000e+00 L2 loss: 1.65002 Learning rate: 0.02 Mask loss: 0.22927 RPN box loss: 0.07516 RPN score loss: 0.00845 RPN total loss: 0.08361 Total loss: 2.23213 timestamp: 1654921499.3085024 iteration: 8755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13745 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.23008 L1 loss: 0.0000e+00 L2 loss: 1.64972 Learning rate: 0.02 Mask loss: 0.14828 RPN box loss: 0.01693 RPN score loss: 0.00351 RPN total loss: 0.02044 Total loss: 2.04852 timestamp: 1654921502.5692441 iteration: 8760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14646 FastRCNN class loss: 0.0655 FastRCNN total loss: 0.21197 L1 loss: 0.0000e+00 L2 loss: 1.64942 Learning rate: 0.02 Mask loss: 0.12761 RPN box loss: 0.01877 RPN score loss: 0.00185 RPN total loss: 0.02062 Total loss: 2.00961 timestamp: 1654921505.8522215 iteration: 8765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2651 FastRCNN class loss: 0.17155 FastRCNN total loss: 0.43664 L1 loss: 0.0000e+00 L2 loss: 1.64912 Learning rate: 0.02 Mask loss: 0.16608 RPN box loss: 0.03763 RPN score loss: 0.01384 RPN total loss: 0.05147 Total loss: 2.30331 timestamp: 1654921509.1095917 iteration: 8770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1044 FastRCNN class loss: 0.08024 FastRCNN total loss: 0.18464 L1 loss: 0.0000e+00 L2 loss: 1.64881 Learning rate: 0.02 Mask loss: 0.12405 RPN box loss: 0.057 RPN score loss: 0.00754 RPN total loss: 0.06454 Total loss: 2.02203 timestamp: 1654921512.4323223 iteration: 8775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14575 FastRCNN class loss: 0.12761 FastRCNN total loss: 0.27336 L1 loss: 0.0000e+00 L2 loss: 1.64851 Learning rate: 0.02 Mask loss: 0.18696 RPN box loss: 0.05616 RPN score loss: 0.01394 RPN total loss: 0.0701 Total loss: 2.17893 timestamp: 1654921515.7659538 iteration: 8780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18606 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.27167 L1 loss: 0.0000e+00 L2 loss: 1.64822 Learning rate: 0.02 Mask loss: 0.12157 RPN box loss: 0.04373 RPN score loss: 0.00912 RPN total loss: 0.05284 Total loss: 2.0943 timestamp: 1654921518.9781427 iteration: 8785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1449 FastRCNN class loss: 0.08324 FastRCNN total loss: 0.22814 L1 loss: 0.0000e+00 L2 loss: 1.64791 Learning rate: 0.02 Mask loss: 0.11636 RPN box loss: 0.05484 RPN score loss: 0.00697 RPN total loss: 0.06181 Total loss: 2.05422 timestamp: 1654921522.2665722 iteration: 8790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16232 FastRCNN class loss: 0.10296 FastRCNN total loss: 0.26528 L1 loss: 0.0000e+00 L2 loss: 1.64762 Learning rate: 0.02 Mask loss: 0.18188 RPN box loss: 0.05063 RPN score loss: 0.01107 RPN total loss: 0.0617 Total loss: 2.15647 timestamp: 1654921525.47654 iteration: 8795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13687 FastRCNN class loss: 0.09454 FastRCNN total loss: 0.23141 L1 loss: 0.0000e+00 L2 loss: 1.64731 Learning rate: 0.02 Mask loss: 0.17327 RPN box loss: 0.13088 RPN score loss: 0.01149 RPN total loss: 0.14238 Total loss: 2.19437 timestamp: 1654921528.6538482 iteration: 8800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17407 FastRCNN class loss: 0.07315 FastRCNN total loss: 0.24722 L1 loss: 0.0000e+00 L2 loss: 1.64701 Learning rate: 0.02 Mask loss: 0.13569 RPN box loss: 0.01696 RPN score loss: 0.00596 RPN total loss: 0.02292 Total loss: 2.05285 timestamp: 1654921531.9279623 iteration: 8805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16271 FastRCNN class loss: 0.08518 FastRCNN total loss: 0.24789 L1 loss: 0.0000e+00 L2 loss: 1.64671 Learning rate: 0.02 Mask loss: 0.19095 RPN box loss: 0.05683 RPN score loss: 0.0049 RPN total loss: 0.06172 Total loss: 2.14728 timestamp: 1654921535.4308462 iteration: 8810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11197 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.17536 L1 loss: 0.0000e+00 L2 loss: 1.6464 Learning rate: 0.02 Mask loss: 0.21465 RPN box loss: 0.01601 RPN score loss: 0.00483 RPN total loss: 0.02085 Total loss: 2.05725 timestamp: 1654921538.7360306 iteration: 8815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1865 FastRCNN class loss: 0.10767 FastRCNN total loss: 0.29417 L1 loss: 0.0000e+00 L2 loss: 1.6461 Learning rate: 0.02 Mask loss: 0.22888 RPN box loss: 0.02831 RPN score loss: 0.02279 RPN total loss: 0.05111 Total loss: 2.22025 timestamp: 1654921542.1454234 iteration: 8820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21508 FastRCNN class loss: 0.13655 FastRCNN total loss: 0.35162 L1 loss: 0.0000e+00 L2 loss: 1.64579 Learning rate: 0.02 Mask loss: 0.26149 RPN box loss: 0.02382 RPN score loss: 0.04823 RPN total loss: 0.07205 Total loss: 2.33095 timestamp: 1654921545.4731667 iteration: 8825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15624 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.24934 L1 loss: 0.0000e+00 L2 loss: 1.64548 Learning rate: 0.02 Mask loss: 0.30879 RPN box loss: 0.00646 RPN score loss: 0.00172 RPN total loss: 0.00818 Total loss: 2.21179 timestamp: 1654921548.6969228 iteration: 8830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17531 FastRCNN class loss: 0.05238 FastRCNN total loss: 0.22769 L1 loss: 0.0000e+00 L2 loss: 1.64518 Learning rate: 0.02 Mask loss: 0.17895 RPN box loss: 0.0146 RPN score loss: 0.00214 RPN total loss: 0.01674 Total loss: 2.06856 timestamp: 1654921552.0487835 iteration: 8835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17053 FastRCNN class loss: 0.12016 FastRCNN total loss: 0.29069 L1 loss: 0.0000e+00 L2 loss: 1.64487 Learning rate: 0.02 Mask loss: 0.20072 RPN box loss: 0.0167 RPN score loss: 0.00924 RPN total loss: 0.02594 Total loss: 2.16223 timestamp: 1654921555.261787 iteration: 8840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25122 FastRCNN class loss: 0.11088 FastRCNN total loss: 0.3621 L1 loss: 0.0000e+00 L2 loss: 1.64457 Learning rate: 0.02 Mask loss: 0.17948 RPN box loss: 0.04423 RPN score loss: 0.01056 RPN total loss: 0.05479 Total loss: 2.24094 timestamp: 1654921558.6243145 iteration: 8845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10845 FastRCNN class loss: 0.07821 FastRCNN total loss: 0.18666 L1 loss: 0.0000e+00 L2 loss: 1.6443 Learning rate: 0.02 Mask loss: 0.18452 RPN box loss: 0.10603 RPN score loss: 0.01123 RPN total loss: 0.11726 Total loss: 2.13274 timestamp: 1654921561.8370068 iteration: 8850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17609 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.2433 L1 loss: 0.0000e+00 L2 loss: 1.64398 Learning rate: 0.02 Mask loss: 0.12096 RPN box loss: 0.06875 RPN score loss: 0.00671 RPN total loss: 0.07546 Total loss: 2.0837 timestamp: 1654921565.311682 iteration: 8855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22559 FastRCNN class loss: 0.0841 FastRCNN total loss: 0.30969 L1 loss: 0.0000e+00 L2 loss: 1.64368 Learning rate: 0.02 Mask loss: 0.1876 RPN box loss: 0.08181 RPN score loss: 0.01334 RPN total loss: 0.09515 Total loss: 2.23612 timestamp: 1654921568.6016443 iteration: 8860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1237 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.18363 L1 loss: 0.0000e+00 L2 loss: 1.64338 Learning rate: 0.02 Mask loss: 0.16928 RPN box loss: 0.06454 RPN score loss: 0.00721 RPN total loss: 0.07175 Total loss: 2.06803 timestamp: 1654921571.9664197 iteration: 8865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18487 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.24881 L1 loss: 0.0000e+00 L2 loss: 1.64308 Learning rate: 0.02 Mask loss: 0.19982 RPN box loss: 0.04952 RPN score loss: 0.00913 RPN total loss: 0.05865 Total loss: 2.15036 timestamp: 1654921575.337287 iteration: 8870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18602 FastRCNN class loss: 0.13508 FastRCNN total loss: 0.32111 L1 loss: 0.0000e+00 L2 loss: 1.64279 Learning rate: 0.02 Mask loss: 0.21848 RPN box loss: 0.08744 RPN score loss: 0.03007 RPN total loss: 0.11751 Total loss: 2.29989 timestamp: 1654921578.685163 iteration: 8875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13392 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.19998 L1 loss: 0.0000e+00 L2 loss: 1.64251 Learning rate: 0.02 Mask loss: 0.13576 RPN box loss: 0.02881 RPN score loss: 0.0047 RPN total loss: 0.0335 Total loss: 2.01174 timestamp: 1654921582.204959 iteration: 8880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16375 FastRCNN class loss: 0.14859 FastRCNN total loss: 0.31234 L1 loss: 0.0000e+00 L2 loss: 1.64221 Learning rate: 0.02 Mask loss: 0.2086 RPN box loss: 0.06255 RPN score loss: 0.01784 RPN total loss: 0.08039 Total loss: 2.24354 timestamp: 1654921585.392057 iteration: 8885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20006 FastRCNN class loss: 0.07773 FastRCNN total loss: 0.2778 L1 loss: 0.0000e+00 L2 loss: 1.64191 Learning rate: 0.02 Mask loss: 0.1185 RPN box loss: 0.06009 RPN score loss: 0.01011 RPN total loss: 0.0702 Total loss: 2.10841 timestamp: 1654921588.8739448 iteration: 8890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.133 FastRCNN class loss: 0.0763 FastRCNN total loss: 0.2093 L1 loss: 0.0000e+00 L2 loss: 1.64162 Learning rate: 0.02 Mask loss: 0.26324 RPN box loss: 0.04483 RPN score loss: 0.00625 RPN total loss: 0.05107 Total loss: 2.16524 timestamp: 1654921592.1337397 iteration: 8895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18674 FastRCNN class loss: 0.07266 FastRCNN total loss: 0.25941 L1 loss: 0.0000e+00 L2 loss: 1.64131 Learning rate: 0.02 Mask loss: 0.16531 RPN box loss: 0.08525 RPN score loss: 0.01068 RPN total loss: 0.09593 Total loss: 2.16195 timestamp: 1654921595.4975817 iteration: 8900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10691 FastRCNN class loss: 0.09707 FastRCNN total loss: 0.20398 L1 loss: 0.0000e+00 L2 loss: 1.64099 Learning rate: 0.02 Mask loss: 0.15174 RPN box loss: 0.00878 RPN score loss: 0.00383 RPN total loss: 0.01262 Total loss: 2.00934 timestamp: 1654921598.739108 iteration: 8905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14609 FastRCNN class loss: 0.11879 FastRCNN total loss: 0.26488 L1 loss: 0.0000e+00 L2 loss: 1.6407 Learning rate: 0.02 Mask loss: 0.1647 RPN box loss: 0.04443 RPN score loss: 0.00843 RPN total loss: 0.05286 Total loss: 2.12315 timestamp: 1654921602.1259546 iteration: 8910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16851 FastRCNN class loss: 0.12334 FastRCNN total loss: 0.29185 L1 loss: 0.0000e+00 L2 loss: 1.6404 Learning rate: 0.02 Mask loss: 0.19612 RPN box loss: 0.07592 RPN score loss: 0.03062 RPN total loss: 0.10655 Total loss: 2.23492 timestamp: 1654921605.533188 iteration: 8915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24099 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.31025 L1 loss: 0.0000e+00 L2 loss: 1.64008 Learning rate: 0.02 Mask loss: 0.16451 RPN box loss: 0.04301 RPN score loss: 0.0077 RPN total loss: 0.05071 Total loss: 2.16555 timestamp: 1654921608.7707012 iteration: 8920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17063 FastRCNN class loss: 0.12387 FastRCNN total loss: 0.2945 L1 loss: 0.0000e+00 L2 loss: 1.63977 Learning rate: 0.02 Mask loss: 0.17219 RPN box loss: 0.0443 RPN score loss: 0.00695 RPN total loss: 0.05125 Total loss: 2.15771 timestamp: 1654921612.034164 iteration: 8925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.14461 L1 loss: 0.0000e+00 L2 loss: 1.63946 Learning rate: 0.02 Mask loss: 0.11198 RPN box loss: 0.00483 RPN score loss: 0.00327 RPN total loss: 0.0081 Total loss: 1.90415 timestamp: 1654921615.1742089 iteration: 8930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13574 FastRCNN class loss: 0.10216 FastRCNN total loss: 0.2379 L1 loss: 0.0000e+00 L2 loss: 1.63916 Learning rate: 0.02 Mask loss: 0.14331 RPN box loss: 0.07196 RPN score loss: 0.00332 RPN total loss: 0.07528 Total loss: 2.09565 timestamp: 1654921618.4315605 iteration: 8935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22342 FastRCNN class loss: 0.13045 FastRCNN total loss: 0.35387 L1 loss: 0.0000e+00 L2 loss: 1.63889 Learning rate: 0.02 Mask loss: 0.34738 RPN box loss: 0.05583 RPN score loss: 0.0166 RPN total loss: 0.07243 Total loss: 2.41257 timestamp: 1654921621.6676018 iteration: 8940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17324 FastRCNN class loss: 0.15697 FastRCNN total loss: 0.33021 L1 loss: 0.0000e+00 L2 loss: 1.63862 Learning rate: 0.02 Mask loss: 0.22891 RPN box loss: 0.0317 RPN score loss: 0.00546 RPN total loss: 0.03715 Total loss: 2.23489 timestamp: 1654921625.03405 iteration: 8945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2251 FastRCNN class loss: 0.11908 FastRCNN total loss: 0.34418 L1 loss: 0.0000e+00 L2 loss: 1.63831 Learning rate: 0.02 Mask loss: 0.39162 RPN box loss: 0.02086 RPN score loss: 0.00858 RPN total loss: 0.02944 Total loss: 2.40355 timestamp: 1654921628.236416 iteration: 8950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.08538 FastRCNN total loss: 0.23279 L1 loss: 0.0000e+00 L2 loss: 1.63804 Learning rate: 0.02 Mask loss: 0.15716 RPN box loss: 0.0429 RPN score loss: 0.01099 RPN total loss: 0.0539 Total loss: 2.08188 timestamp: 1654921631.540898 iteration: 8955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17695 FastRCNN class loss: 0.10347 FastRCNN total loss: 0.28042 L1 loss: 0.0000e+00 L2 loss: 1.63775 Learning rate: 0.02 Mask loss: 0.18534 RPN box loss: 0.02184 RPN score loss: 0.01091 RPN total loss: 0.03275 Total loss: 2.13625 timestamp: 1654921634.713732 iteration: 8960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2527 FastRCNN class loss: 0.0981 FastRCNN total loss: 0.3508 L1 loss: 0.0000e+00 L2 loss: 1.63746 Learning rate: 0.02 Mask loss: 0.18028 RPN box loss: 0.04735 RPN score loss: 0.00664 RPN total loss: 0.054 Total loss: 2.22252 timestamp: 1654921637.9801688 iteration: 8965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16206 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.22192 L1 loss: 0.0000e+00 L2 loss: 1.63717 Learning rate: 0.02 Mask loss: 0.17778 RPN box loss: 0.07609 RPN score loss: 0.00665 RPN total loss: 0.08274 Total loss: 2.11961 timestamp: 1654921641.3173406 iteration: 8970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14488 FastRCNN class loss: 0.09237 FastRCNN total loss: 0.23726 L1 loss: 0.0000e+00 L2 loss: 1.63686 Learning rate: 0.02 Mask loss: 0.18944 RPN box loss: 0.0385 RPN score loss: 0.0054 RPN total loss: 0.0439 Total loss: 2.10746 timestamp: 1654921644.68023 iteration: 8975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23384 FastRCNN class loss: 0.14392 FastRCNN total loss: 0.37776 L1 loss: 0.0000e+00 L2 loss: 1.63657 Learning rate: 0.02 Mask loss: 0.20157 RPN box loss: 0.02175 RPN score loss: 0.00473 RPN total loss: 0.02648 Total loss: 2.24238 timestamp: 1654921648.0052733 iteration: 8980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14312 FastRCNN class loss: 0.07914 FastRCNN total loss: 0.22226 L1 loss: 0.0000e+00 L2 loss: 1.63628 Learning rate: 0.02 Mask loss: 0.1168 RPN box loss: 0.01366 RPN score loss: 0.00612 RPN total loss: 0.01979 Total loss: 1.99512 timestamp: 1654921651.2400632 iteration: 8985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10592 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.1791 L1 loss: 0.0000e+00 L2 loss: 1.63599 Learning rate: 0.02 Mask loss: 0.12458 RPN box loss: 0.02715 RPN score loss: 0.00679 RPN total loss: 0.03394 Total loss: 1.97361 timestamp: 1654921654.4773903 iteration: 8990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15928 FastRCNN class loss: 0.12512 FastRCNN total loss: 0.2844 L1 loss: 0.0000e+00 L2 loss: 1.63569 Learning rate: 0.02 Mask loss: 0.19204 RPN box loss: 0.04734 RPN score loss: 0.01032 RPN total loss: 0.05766 Total loss: 2.16979 timestamp: 1654921657.62376 iteration: 8995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11828 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.20911 L1 loss: 0.0000e+00 L2 loss: 1.63538 Learning rate: 0.02 Mask loss: 0.12717 RPN box loss: 0.05412 RPN score loss: 0.01504 RPN total loss: 0.06916 Total loss: 2.04082 timestamp: 1654921660.9441159 iteration: 9000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10732 FastRCNN class loss: 0.03921 FastRCNN total loss: 0.14653 L1 loss: 0.0000e+00 L2 loss: 1.63507 Learning rate: 0.02 Mask loss: 0.12052 RPN box loss: 0.03458 RPN score loss: 0.0014 RPN total loss: 0.03598 Total loss: 1.9381 timestamp: 1654921664.107251 iteration: 9005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25368 FastRCNN class loss: 0.10169 FastRCNN total loss: 0.35537 L1 loss: 0.0000e+00 L2 loss: 1.6348 Learning rate: 0.02 Mask loss: 0.20172 RPN box loss: 0.02489 RPN score loss: 0.00668 RPN total loss: 0.03157 Total loss: 2.22345 timestamp: 1654921667.4329538 iteration: 9010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13834 FastRCNN class loss: 0.10519 FastRCNN total loss: 0.24353 L1 loss: 0.0000e+00 L2 loss: 1.63451 Learning rate: 0.02 Mask loss: 0.14282 RPN box loss: 0.01789 RPN score loss: 0.00581 RPN total loss: 0.02369 Total loss: 2.04455 timestamp: 1654921670.7038527 iteration: 9015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1293 FastRCNN class loss: 0.11685 FastRCNN total loss: 0.24615 L1 loss: 0.0000e+00 L2 loss: 1.63421 Learning rate: 0.02 Mask loss: 0.41603 RPN box loss: 0.05174 RPN score loss: 0.00623 RPN total loss: 0.05797 Total loss: 2.35435 timestamp: 1654921673.8902435 iteration: 9020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1614 FastRCNN class loss: 0.07729 FastRCNN total loss: 0.23869 L1 loss: 0.0000e+00 L2 loss: 1.63391 Learning rate: 0.02 Mask loss: 0.20293 RPN box loss: 0.08595 RPN score loss: 0.00473 RPN total loss: 0.09068 Total loss: 2.1662 timestamp: 1654921677.2246525 iteration: 9025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15395 FastRCNN class loss: 0.12209 FastRCNN total loss: 0.27604 L1 loss: 0.0000e+00 L2 loss: 1.63359 Learning rate: 0.02 Mask loss: 0.23057 RPN box loss: 0.01988 RPN score loss: 0.01256 RPN total loss: 0.03244 Total loss: 2.17264 timestamp: 1654921680.44945 iteration: 9030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09104 FastRCNN class loss: 0.04668 FastRCNN total loss: 0.13772 L1 loss: 0.0000e+00 L2 loss: 1.63328 Learning rate: 0.02 Mask loss: 0.13189 RPN box loss: 0.07973 RPN score loss: 0.00828 RPN total loss: 0.088 Total loss: 1.99089 timestamp: 1654921683.7718458 iteration: 9035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24731 FastRCNN class loss: 0.1944 FastRCNN total loss: 0.4417 L1 loss: 0.0000e+00 L2 loss: 1.633 Learning rate: 0.02 Mask loss: 0.26793 RPN box loss: 0.05995 RPN score loss: 0.01367 RPN total loss: 0.07362 Total loss: 2.41626 timestamp: 1654921686.9778316 iteration: 9040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20767 FastRCNN class loss: 0.17587 FastRCNN total loss: 0.38354 L1 loss: 0.0000e+00 L2 loss: 1.6327 Learning rate: 0.02 Mask loss: 0.21029 RPN box loss: 0.03328 RPN score loss: 0.0089 RPN total loss: 0.04218 Total loss: 2.26871 timestamp: 1654921690.304858 iteration: 9045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22551 FastRCNN class loss: 0.09644 FastRCNN total loss: 0.32195 L1 loss: 0.0000e+00 L2 loss: 1.63241 Learning rate: 0.02 Mask loss: 0.20026 RPN box loss: 0.03414 RPN score loss: 0.00908 RPN total loss: 0.04322 Total loss: 2.19784 timestamp: 1654921693.4870193 iteration: 9050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.167 FastRCNN class loss: 0.13118 FastRCNN total loss: 0.29818 L1 loss: 0.0000e+00 L2 loss: 1.63212 Learning rate: 0.02 Mask loss: 0.22738 RPN box loss: 0.05739 RPN score loss: 0.00817 RPN total loss: 0.06555 Total loss: 2.22324 timestamp: 1654921696.795493 iteration: 9055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15391 FastRCNN class loss: 0.12274 FastRCNN total loss: 0.27666 L1 loss: 0.0000e+00 L2 loss: 1.63184 Learning rate: 0.02 Mask loss: 0.19817 RPN box loss: 0.02032 RPN score loss: 0.01126 RPN total loss: 0.03158 Total loss: 2.13824 timestamp: 1654921700.0517862 iteration: 9060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18694 FastRCNN class loss: 0.12719 FastRCNN total loss: 0.31413 L1 loss: 0.0000e+00 L2 loss: 1.63154 Learning rate: 0.02 Mask loss: 0.14984 RPN box loss: 0.03435 RPN score loss: 0.00986 RPN total loss: 0.04421 Total loss: 2.13972 timestamp: 1654921703.3874025 iteration: 9065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12736 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.21887 L1 loss: 0.0000e+00 L2 loss: 1.63125 Learning rate: 0.02 Mask loss: 0.14119 RPN box loss: 0.04791 RPN score loss: 0.00617 RPN total loss: 0.05408 Total loss: 2.04538 timestamp: 1654921706.6898694 iteration: 9070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15175 FastRCNN class loss: 0.082 FastRCNN total loss: 0.23375 L1 loss: 0.0000e+00 L2 loss: 1.63097 Learning rate: 0.02 Mask loss: 0.18304 RPN box loss: 0.02278 RPN score loss: 0.00353 RPN total loss: 0.02631 Total loss: 2.07406 timestamp: 1654921709.9404292 iteration: 9075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15716 FastRCNN class loss: 0.10895 FastRCNN total loss: 0.26611 L1 loss: 0.0000e+00 L2 loss: 1.63066 Learning rate: 0.02 Mask loss: 0.14555 RPN box loss: 0.03172 RPN score loss: 0.00622 RPN total loss: 0.03794 Total loss: 2.08025 timestamp: 1654921713.2144861 iteration: 9080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15481 FastRCNN class loss: 0.09946 FastRCNN total loss: 0.25427 L1 loss: 0.0000e+00 L2 loss: 1.63037 Learning rate: 0.02 Mask loss: 0.16585 RPN box loss: 0.00809 RPN score loss: 0.01583 RPN total loss: 0.02392 Total loss: 2.07441 timestamp: 1654921716.4363282 iteration: 9085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17786 FastRCNN class loss: 0.07884 FastRCNN total loss: 0.2567 L1 loss: 0.0000e+00 L2 loss: 1.6301 Learning rate: 0.02 Mask loss: 0.19968 RPN box loss: 0.14015 RPN score loss: 0.01341 RPN total loss: 0.15355 Total loss: 2.24002 timestamp: 1654921719.807818 iteration: 9090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15659 FastRCNN class loss: 0.0643 FastRCNN total loss: 0.22089 L1 loss: 0.0000e+00 L2 loss: 1.62981 Learning rate: 0.02 Mask loss: 0.18186 RPN box loss: 0.04886 RPN score loss: 0.00283 RPN total loss: 0.05169 Total loss: 2.08425 timestamp: 1654921722.9769392 iteration: 9095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18316 FastRCNN class loss: 0.09914 FastRCNN total loss: 0.2823 L1 loss: 0.0000e+00 L2 loss: 1.62952 Learning rate: 0.02 Mask loss: 0.1176 RPN box loss: 0.02531 RPN score loss: 0.00378 RPN total loss: 0.0291 Total loss: 2.05852 timestamp: 1654921726.3758695 iteration: 9100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11469 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.18747 L1 loss: 0.0000e+00 L2 loss: 1.62924 Learning rate: 0.02 Mask loss: 0.12116 RPN box loss: 0.01553 RPN score loss: 0.0024 RPN total loss: 0.01793 Total loss: 1.9558 timestamp: 1654921729.5700557 iteration: 9105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25066 FastRCNN class loss: 0.11563 FastRCNN total loss: 0.36629 L1 loss: 0.0000e+00 L2 loss: 1.62891 Learning rate: 0.02 Mask loss: 0.21606 RPN box loss: 0.09317 RPN score loss: 0.01349 RPN total loss: 0.10666 Total loss: 2.31792 timestamp: 1654921732.8626113 iteration: 9110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16196 FastRCNN class loss: 0.18215 FastRCNN total loss: 0.34411 L1 loss: 0.0000e+00 L2 loss: 1.62861 Learning rate: 0.02 Mask loss: 0.17407 RPN box loss: 0.09717 RPN score loss: 0.01477 RPN total loss: 0.11195 Total loss: 2.25874 timestamp: 1654921736.3453696 iteration: 9115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20439 FastRCNN class loss: 0.10966 FastRCNN total loss: 0.31405 L1 loss: 0.0000e+00 L2 loss: 1.62833 Learning rate: 0.02 Mask loss: 0.14488 RPN box loss: 0.05924 RPN score loss: 0.00903 RPN total loss: 0.06827 Total loss: 2.15553 timestamp: 1654921739.5714176 iteration: 9120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15662 FastRCNN class loss: 0.08615 FastRCNN total loss: 0.24277 L1 loss: 0.0000e+00 L2 loss: 1.62803 Learning rate: 0.02 Mask loss: 0.14241 RPN box loss: 0.03453 RPN score loss: 0.0081 RPN total loss: 0.04263 Total loss: 2.05584 timestamp: 1654921742.975495 iteration: 9125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21574 FastRCNN class loss: 0.07266 FastRCNN total loss: 0.2884 L1 loss: 0.0000e+00 L2 loss: 1.62774 Learning rate: 0.02 Mask loss: 0.19455 RPN box loss: 0.0291 RPN score loss: 0.00732 RPN total loss: 0.03642 Total loss: 2.14712 timestamp: 1654921746.252418 iteration: 9130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16261 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.24948 L1 loss: 0.0000e+00 L2 loss: 1.62744 Learning rate: 0.02 Mask loss: 0.25627 RPN box loss: 0.02558 RPN score loss: 0.0135 RPN total loss: 0.03907 Total loss: 2.17227 timestamp: 1654921749.4541132 iteration: 9135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16403 FastRCNN class loss: 0.12232 FastRCNN total loss: 0.28635 L1 loss: 0.0000e+00 L2 loss: 1.62715 Learning rate: 0.02 Mask loss: 0.21013 RPN box loss: 0.06391 RPN score loss: 0.00628 RPN total loss: 0.07019 Total loss: 2.19381 timestamp: 1654921752.5643034 iteration: 9140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19819 FastRCNN class loss: 0.10461 FastRCNN total loss: 0.3028 L1 loss: 0.0000e+00 L2 loss: 1.62684 Learning rate: 0.02 Mask loss: 0.15803 RPN box loss: 0.0239 RPN score loss: 0.00822 RPN total loss: 0.03212 Total loss: 2.11979 timestamp: 1654921755.7927372 iteration: 9145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15149 FastRCNN class loss: 0.1022 FastRCNN total loss: 0.25369 L1 loss: 0.0000e+00 L2 loss: 1.62656 Learning rate: 0.02 Mask loss: 0.2162 RPN box loss: 0.09886 RPN score loss: 0.0042 RPN total loss: 0.10306 Total loss: 2.19951 timestamp: 1654921758.9563463 iteration: 9150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13778 FastRCNN class loss: 0.06707 FastRCNN total loss: 0.20484 L1 loss: 0.0000e+00 L2 loss: 1.62627 Learning rate: 0.02 Mask loss: 0.19981 RPN box loss: 0.05845 RPN score loss: 0.02659 RPN total loss: 0.08505 Total loss: 2.11598 timestamp: 1654921762.2276309 iteration: 9155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24983 FastRCNN class loss: 0.12072 FastRCNN total loss: 0.37055 L1 loss: 0.0000e+00 L2 loss: 1.62598 Learning rate: 0.02 Mask loss: 0.20267 RPN box loss: 0.00947 RPN score loss: 0.00611 RPN total loss: 0.01558 Total loss: 2.21479 timestamp: 1654921765.4275851 iteration: 9160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.122 FastRCNN class loss: 0.09009 FastRCNN total loss: 0.21209 L1 loss: 0.0000e+00 L2 loss: 1.62569 Learning rate: 0.02 Mask loss: 0.16641 RPN box loss: 0.0281 RPN score loss: 0.00404 RPN total loss: 0.03214 Total loss: 2.03633 timestamp: 1654921768.6672964 iteration: 9165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14826 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.21843 L1 loss: 0.0000e+00 L2 loss: 1.6254 Learning rate: 0.02 Mask loss: 0.15058 RPN box loss: 0.08622 RPN score loss: 0.02717 RPN total loss: 0.11339 Total loss: 2.1078 timestamp: 1654921771.9381008 iteration: 9170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.17249 L1 loss: 0.0000e+00 L2 loss: 1.62511 Learning rate: 0.02 Mask loss: 0.10049 RPN box loss: 0.01154 RPN score loss: 0.00388 RPN total loss: 0.01543 Total loss: 1.91352 timestamp: 1654921775.1761255 iteration: 9175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18367 FastRCNN class loss: 0.08654 FastRCNN total loss: 0.2702 L1 loss: 0.0000e+00 L2 loss: 1.62482 Learning rate: 0.02 Mask loss: 0.10701 RPN box loss: 0.0298 RPN score loss: 0.00905 RPN total loss: 0.03884 Total loss: 2.04088 timestamp: 1654921778.584065 iteration: 9180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09672 FastRCNN class loss: 0.11362 FastRCNN total loss: 0.21034 L1 loss: 0.0000e+00 L2 loss: 1.62453 Learning rate: 0.02 Mask loss: 0.1184 RPN box loss: 0.03158 RPN score loss: 0.00476 RPN total loss: 0.03634 Total loss: 1.98961 timestamp: 1654921781.7877078 iteration: 9185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.137 FastRCNN class loss: 0.08368 FastRCNN total loss: 0.22069 L1 loss: 0.0000e+00 L2 loss: 1.62423 Learning rate: 0.02 Mask loss: 0.20511 RPN box loss: 0.1063 RPN score loss: 0.02072 RPN total loss: 0.12701 Total loss: 2.17704 timestamp: 1654921785.064199 iteration: 9190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11514 FastRCNN class loss: 0.0943 FastRCNN total loss: 0.20944 L1 loss: 0.0000e+00 L2 loss: 1.62396 Learning rate: 0.02 Mask loss: 0.23595 RPN box loss: 0.02658 RPN score loss: 0.00764 RPN total loss: 0.03422 Total loss: 2.10357 timestamp: 1654921788.2444723 iteration: 9195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1191 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.18777 L1 loss: 0.0000e+00 L2 loss: 1.62364 Learning rate: 0.02 Mask loss: 0.21947 RPN box loss: 0.02607 RPN score loss: 0.01038 RPN total loss: 0.03644 Total loss: 2.06732 timestamp: 1654921791.4492836 iteration: 9200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16758 FastRCNN class loss: 0.20284 FastRCNN total loss: 0.37041 L1 loss: 0.0000e+00 L2 loss: 1.62335 Learning rate: 0.02 Mask loss: 0.15075 RPN box loss: 0.04776 RPN score loss: 0.01103 RPN total loss: 0.05879 Total loss: 2.20332 timestamp: 1654921794.6063268 iteration: 9205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1459 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.21701 L1 loss: 0.0000e+00 L2 loss: 1.62305 Learning rate: 0.02 Mask loss: 0.15071 RPN box loss: 0.09228 RPN score loss: 0.00795 RPN total loss: 0.10023 Total loss: 2.091 timestamp: 1654921797.8364036 iteration: 9210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10869 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.16314 L1 loss: 0.0000e+00 L2 loss: 1.62275 Learning rate: 0.02 Mask loss: 0.09041 RPN box loss: 0.02427 RPN score loss: 0.00656 RPN total loss: 0.03084 Total loss: 1.90714 timestamp: 1654921801.0300164 iteration: 9215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13579 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.22545 L1 loss: 0.0000e+00 L2 loss: 1.62246 Learning rate: 0.02 Mask loss: 0.11306 RPN box loss: 0.00828 RPN score loss: 0.0065 RPN total loss: 0.01477 Total loss: 1.97573 timestamp: 1654921804.316864 iteration: 9220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19969 FastRCNN class loss: 0.086 FastRCNN total loss: 0.28569 L1 loss: 0.0000e+00 L2 loss: 1.62219 Learning rate: 0.02 Mask loss: 0.17376 RPN box loss: 0.02205 RPN score loss: 0.00581 RPN total loss: 0.02786 Total loss: 2.10951 timestamp: 1654921807.641512 iteration: 9225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14318 FastRCNN class loss: 0.08989 FastRCNN total loss: 0.23307 L1 loss: 0.0000e+00 L2 loss: 1.62191 Learning rate: 0.02 Mask loss: 0.20882 RPN box loss: 0.01569 RPN score loss: 0.0056 RPN total loss: 0.0213 Total loss: 2.08509 timestamp: 1654921810.914009 iteration: 9230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12106 FastRCNN class loss: 0.08437 FastRCNN total loss: 0.20543 L1 loss: 0.0000e+00 L2 loss: 1.6216 Learning rate: 0.02 Mask loss: 0.13031 RPN box loss: 0.09939 RPN score loss: 0.01019 RPN total loss: 0.10958 Total loss: 2.06691 timestamp: 1654921814.210995 iteration: 9235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12893 FastRCNN class loss: 0.05863 FastRCNN total loss: 0.18756 L1 loss: 0.0000e+00 L2 loss: 1.62127 Learning rate: 0.02 Mask loss: 0.13671 RPN box loss: 0.0177 RPN score loss: 0.00523 RPN total loss: 0.02293 Total loss: 1.96848 timestamp: 1654921817.399115 iteration: 9240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15593 FastRCNN class loss: 0.15785 FastRCNN total loss: 0.31378 L1 loss: 0.0000e+00 L2 loss: 1.62099 Learning rate: 0.02 Mask loss: 0.25169 RPN box loss: 0.05231 RPN score loss: 0.04043 RPN total loss: 0.09274 Total loss: 2.2792 timestamp: 1654921820.7010305 iteration: 9245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15926 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.26116 L1 loss: 0.0000e+00 L2 loss: 1.6207 Learning rate: 0.02 Mask loss: 0.21192 RPN box loss: 0.06916 RPN score loss: 0.00797 RPN total loss: 0.07713 Total loss: 2.17092 timestamp: 1654921823.920331 iteration: 9250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22002 FastRCNN class loss: 0.16855 FastRCNN total loss: 0.38857 L1 loss: 0.0000e+00 L2 loss: 1.62039 Learning rate: 0.02 Mask loss: 0.20889 RPN box loss: 0.09377 RPN score loss: 0.00862 RPN total loss: 0.10238 Total loss: 2.32024 timestamp: 1654921827.2210684 iteration: 9255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13393 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.21106 L1 loss: 0.0000e+00 L2 loss: 1.6201 Learning rate: 0.02 Mask loss: 0.17332 RPN box loss: 0.05216 RPN score loss: 0.01019 RPN total loss: 0.06236 Total loss: 2.06684 timestamp: 1654921830.4307747 iteration: 9260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14857 FastRCNN class loss: 0.11464 FastRCNN total loss: 0.26321 L1 loss: 0.0000e+00 L2 loss: 1.61983 Learning rate: 0.02 Mask loss: 0.21108 RPN box loss: 0.02532 RPN score loss: 0.01169 RPN total loss: 0.03701 Total loss: 2.13112 timestamp: 1654921833.674384 iteration: 9265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13727 FastRCNN class loss: 0.08128 FastRCNN total loss: 0.21855 L1 loss: 0.0000e+00 L2 loss: 1.61956 Learning rate: 0.02 Mask loss: 0.20718 RPN box loss: 0.05581 RPN score loss: 0.01342 RPN total loss: 0.06923 Total loss: 2.11451 timestamp: 1654921836.9293485 iteration: 9270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15297 FastRCNN class loss: 0.13124 FastRCNN total loss: 0.28421 L1 loss: 0.0000e+00 L2 loss: 1.61925 Learning rate: 0.02 Mask loss: 0.17956 RPN box loss: 0.03067 RPN score loss: 0.00254 RPN total loss: 0.03322 Total loss: 2.11624 timestamp: 1654921840.2188265 iteration: 9275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13843 FastRCNN class loss: 0.08369 FastRCNN total loss: 0.22212 L1 loss: 0.0000e+00 L2 loss: 1.61893 Learning rate: 0.02 Mask loss: 0.13359 RPN box loss: 0.02278 RPN score loss: 0.00623 RPN total loss: 0.02901 Total loss: 2.00365 timestamp: 1654921843.499777 iteration: 9280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17455 FastRCNN class loss: 0.07073 FastRCNN total loss: 0.24528 L1 loss: 0.0000e+00 L2 loss: 1.61861 Learning rate: 0.02 Mask loss: 0.12816 RPN box loss: 0.02673 RPN score loss: 0.00515 RPN total loss: 0.03188 Total loss: 2.02392 timestamp: 1654921846.6798038 iteration: 9285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23792 FastRCNN class loss: 0.08595 FastRCNN total loss: 0.32386 L1 loss: 0.0000e+00 L2 loss: 1.61832 Learning rate: 0.02 Mask loss: 0.14604 RPN box loss: 0.0595 RPN score loss: 0.00462 RPN total loss: 0.06411 Total loss: 2.15234 timestamp: 1654921849.9504583 iteration: 9290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19151 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.27508 L1 loss: 0.0000e+00 L2 loss: 1.61806 Learning rate: 0.02 Mask loss: 0.1252 RPN box loss: 0.01196 RPN score loss: 0.00384 RPN total loss: 0.0158 Total loss: 2.03413 timestamp: 1654921853.139806 iteration: 9295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14483 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.21152 L1 loss: 0.0000e+00 L2 loss: 1.61776 Learning rate: 0.02 Mask loss: 0.13322 RPN box loss: 0.04629 RPN score loss: 0.00726 RPN total loss: 0.05355 Total loss: 2.01605 timestamp: 1654921856.5548825 iteration: 9300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10611 FastRCNN class loss: 0.1208 FastRCNN total loss: 0.22691 L1 loss: 0.0000e+00 L2 loss: 1.61746 Learning rate: 0.02 Mask loss: 0.15551 RPN box loss: 0.06982 RPN score loss: 0.00825 RPN total loss: 0.07808 Total loss: 2.07795 timestamp: 1654921859.8097315 iteration: 9305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14057 FastRCNN class loss: 0.08458 FastRCNN total loss: 0.22515 L1 loss: 0.0000e+00 L2 loss: 1.61716 Learning rate: 0.02 Mask loss: 0.16516 RPN box loss: 0.03421 RPN score loss: 0.00495 RPN total loss: 0.03916 Total loss: 2.04663 timestamp: 1654921863.2222993 iteration: 9310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16261 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.22792 L1 loss: 0.0000e+00 L2 loss: 1.61685 Learning rate: 0.02 Mask loss: 0.14918 RPN box loss: 0.10406 RPN score loss: 0.00434 RPN total loss: 0.1084 Total loss: 2.10235 timestamp: 1654921866.4079487 iteration: 9315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20049 FastRCNN class loss: 0.13907 FastRCNN total loss: 0.33955 L1 loss: 0.0000e+00 L2 loss: 1.61657 Learning rate: 0.02 Mask loss: 0.19564 RPN box loss: 0.07755 RPN score loss: 0.01929 RPN total loss: 0.09684 Total loss: 2.24861 timestamp: 1654921869.7828043 iteration: 9320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14298 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.21726 L1 loss: 0.0000e+00 L2 loss: 1.61629 Learning rate: 0.02 Mask loss: 0.14705 RPN box loss: 0.0126 RPN score loss: 0.00695 RPN total loss: 0.01955 Total loss: 2.00014 timestamp: 1654921873.0709896 iteration: 9325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18872 FastRCNN class loss: 0.09699 FastRCNN total loss: 0.2857 L1 loss: 0.0000e+00 L2 loss: 1.616 Learning rate: 0.02 Mask loss: 0.37809 RPN box loss: 0.0528 RPN score loss: 0.01358 RPN total loss: 0.06638 Total loss: 2.34618 timestamp: 1654921876.3354518 iteration: 9330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15191 FastRCNN class loss: 0.07876 FastRCNN total loss: 0.23067 L1 loss: 0.0000e+00 L2 loss: 1.6157 Learning rate: 0.02 Mask loss: 0.22887 RPN box loss: 0.03426 RPN score loss: 0.00797 RPN total loss: 0.04223 Total loss: 2.11746 timestamp: 1654921879.6336906 iteration: 9335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15195 FastRCNN class loss: 0.10164 FastRCNN total loss: 0.25359 L1 loss: 0.0000e+00 L2 loss: 1.61541 Learning rate: 0.02 Mask loss: 0.11514 RPN box loss: 0.04933 RPN score loss: 0.00319 RPN total loss: 0.05253 Total loss: 2.03667 timestamp: 1654921882.7935798 iteration: 9340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14873 FastRCNN class loss: 0.08531 FastRCNN total loss: 0.23404 L1 loss: 0.0000e+00 L2 loss: 1.61512 Learning rate: 0.02 Mask loss: 0.1896 RPN box loss: 0.08553 RPN score loss: 0.01211 RPN total loss: 0.09764 Total loss: 2.1364 timestamp: 1654921886.118296 iteration: 9345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22219 FastRCNN class loss: 0.11232 FastRCNN total loss: 0.33451 L1 loss: 0.0000e+00 L2 loss: 1.61482 Learning rate: 0.02 Mask loss: 0.27254 RPN box loss: 0.02832 RPN score loss: 0.00656 RPN total loss: 0.03488 Total loss: 2.25675 timestamp: 1654921889.3361642 iteration: 9350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22405 FastRCNN class loss: 0.08546 FastRCNN total loss: 0.3095 L1 loss: 0.0000e+00 L2 loss: 1.61453 Learning rate: 0.02 Mask loss: 0.16371 RPN box loss: 0.03758 RPN score loss: 0.00372 RPN total loss: 0.0413 Total loss: 2.12904 timestamp: 1654921892.702403 iteration: 9355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15991 FastRCNN class loss: 0.12366 FastRCNN total loss: 0.28356 L1 loss: 0.0000e+00 L2 loss: 1.61423 Learning rate: 0.02 Mask loss: 0.218 RPN box loss: 0.06539 RPN score loss: 0.01195 RPN total loss: 0.07734 Total loss: 2.19313 timestamp: 1654921895.9173856 iteration: 9360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12891 FastRCNN class loss: 0.06515 FastRCNN total loss: 0.19406 L1 loss: 0.0000e+00 L2 loss: 1.61394 Learning rate: 0.02 Mask loss: 0.10112 RPN box loss: 0.03817 RPN score loss: 0.00974 RPN total loss: 0.04791 Total loss: 1.95703 timestamp: 1654921899.192165 iteration: 9365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15316 FastRCNN class loss: 0.11332 FastRCNN total loss: 0.26647 L1 loss: 0.0000e+00 L2 loss: 1.61366 Learning rate: 0.02 Mask loss: 0.19945 RPN box loss: 0.02022 RPN score loss: 0.00455 RPN total loss: 0.02477 Total loss: 2.10435 timestamp: 1654921902.396866 iteration: 9370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16294 FastRCNN class loss: 0.10921 FastRCNN total loss: 0.27215 L1 loss: 0.0000e+00 L2 loss: 1.61339 Learning rate: 0.02 Mask loss: 0.24139 RPN box loss: 0.0683 RPN score loss: 0.01 RPN total loss: 0.07831 Total loss: 2.20524 timestamp: 1654921905.7448297 iteration: 9375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16818 FastRCNN class loss: 0.15726 FastRCNN total loss: 0.32544 L1 loss: 0.0000e+00 L2 loss: 1.61311 Learning rate: 0.02 Mask loss: 0.2411 RPN box loss: 0.04466 RPN score loss: 0.02088 RPN total loss: 0.06555 Total loss: 2.2452 timestamp: 1654921909.0446908 iteration: 9380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21703 FastRCNN class loss: 0.12453 FastRCNN total loss: 0.34156 L1 loss: 0.0000e+00 L2 loss: 1.6128 Learning rate: 0.02 Mask loss: 0.18319 RPN box loss: 0.01929 RPN score loss: 0.02088 RPN total loss: 0.04017 Total loss: 2.17773 timestamp: 1654921912.2889202 iteration: 9385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14615 FastRCNN class loss: 0.16375 FastRCNN total loss: 0.3099 L1 loss: 0.0000e+00 L2 loss: 1.61251 Learning rate: 0.02 Mask loss: 0.23934 RPN box loss: 0.05047 RPN score loss: 0.00826 RPN total loss: 0.05873 Total loss: 2.22049 timestamp: 1654921915.6025271 iteration: 9390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16901 FastRCNN class loss: 0.0734 FastRCNN total loss: 0.24241 L1 loss: 0.0000e+00 L2 loss: 1.6122 Learning rate: 0.02 Mask loss: 0.15293 RPN box loss: 0.0389 RPN score loss: 0.005 RPN total loss: 0.0439 Total loss: 2.05143 timestamp: 1654921918.8075352 iteration: 9395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22136 FastRCNN class loss: 0.12524 FastRCNN total loss: 0.34661 L1 loss: 0.0000e+00 L2 loss: 1.61189 Learning rate: 0.02 Mask loss: 0.17492 RPN box loss: 0.05899 RPN score loss: 0.03626 RPN total loss: 0.09525 Total loss: 2.22867 timestamp: 1654921922.0828724 iteration: 9400 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16374 FastRCNN class loss: 0.10946 FastRCNN total loss: 0.2732 L1 loss: 0.0000e+00 L2 loss: 1.61156 Learning rate: 0.02 Mask loss: 0.1932 RPN box loss: 0.0338 RPN score loss: 0.00583 RPN total loss: 0.03963 Total loss: 2.1176 timestamp: 1654921925.252734 iteration: 9405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10726 FastRCNN class loss: 0.0899 FastRCNN total loss: 0.19716 L1 loss: 0.0000e+00 L2 loss: 1.61128 Learning rate: 0.02 Mask loss: 0.16833 RPN box loss: 0.03807 RPN score loss: 0.01097 RPN total loss: 0.04903 Total loss: 2.0258 timestamp: 1654921928.5269506 iteration: 9410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13607 FastRCNN class loss: 0.09422 FastRCNN total loss: 0.23029 L1 loss: 0.0000e+00 L2 loss: 1.61101 Learning rate: 0.02 Mask loss: 0.15002 RPN box loss: 0.04138 RPN score loss: 0.00684 RPN total loss: 0.04822 Total loss: 2.03953 timestamp: 1654921931.8360443 iteration: 9415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12496 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.18781 L1 loss: 0.0000e+00 L2 loss: 1.61072 Learning rate: 0.02 Mask loss: 0.16511 RPN box loss: 0.01147 RPN score loss: 0.00606 RPN total loss: 0.01753 Total loss: 1.98117 timestamp: 1654921935.1576312 iteration: 9420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16745 FastRCNN class loss: 0.12789 FastRCNN total loss: 0.29534 L1 loss: 0.0000e+00 L2 loss: 1.61043 Learning rate: 0.02 Mask loss: 0.19983 RPN box loss: 0.03926 RPN score loss: 0.01473 RPN total loss: 0.05399 Total loss: 2.15959 timestamp: 1654921938.469178 iteration: 9425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14897 FastRCNN class loss: 0.10046 FastRCNN total loss: 0.24943 L1 loss: 0.0000e+00 L2 loss: 1.61014 Learning rate: 0.02 Mask loss: 0.1992 RPN box loss: 0.08008 RPN score loss: 0.01329 RPN total loss: 0.09337 Total loss: 2.15213 timestamp: 1654921941.6721914 iteration: 9430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2103 FastRCNN class loss: 0.09702 FastRCNN total loss: 0.30732 L1 loss: 0.0000e+00 L2 loss: 1.60984 Learning rate: 0.02 Mask loss: 0.17262 RPN box loss: 0.09136 RPN score loss: 0.0113 RPN total loss: 0.10266 Total loss: 2.19244 timestamp: 1654921944.974124 iteration: 9435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20872 FastRCNN class loss: 0.12327 FastRCNN total loss: 0.33199 L1 loss: 0.0000e+00 L2 loss: 1.60956 Learning rate: 0.02 Mask loss: 0.18312 RPN box loss: 0.03256 RPN score loss: 0.01479 RPN total loss: 0.04735 Total loss: 2.17203 timestamp: 1654921948.1720834 iteration: 9440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.09329 FastRCNN total loss: 0.22085 L1 loss: 0.0000e+00 L2 loss: 1.60925 Learning rate: 0.02 Mask loss: 0.15267 RPN box loss: 0.04051 RPN score loss: 0.00677 RPN total loss: 0.04728 Total loss: 2.03005 timestamp: 1654921951.4294064 iteration: 9445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17702 FastRCNN class loss: 0.07237 FastRCNN total loss: 0.24939 L1 loss: 0.0000e+00 L2 loss: 1.60894 Learning rate: 0.02 Mask loss: 0.20339 RPN box loss: 0.07484 RPN score loss: 0.01466 RPN total loss: 0.08951 Total loss: 2.15123 timestamp: 1654921954.674668 iteration: 9450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06783 FastRCNN class loss: 0.08097 FastRCNN total loss: 0.1488 L1 loss: 0.0000e+00 L2 loss: 1.60866 Learning rate: 0.02 Mask loss: 0.12047 RPN box loss: 0.04912 RPN score loss: 0.00331 RPN total loss: 0.05243 Total loss: 1.93036 timestamp: 1654921957.9430268 iteration: 9455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20988 FastRCNN class loss: 0.10203 FastRCNN total loss: 0.31191 L1 loss: 0.0000e+00 L2 loss: 1.60839 Learning rate: 0.02 Mask loss: 0.23785 RPN box loss: 0.04296 RPN score loss: 0.01794 RPN total loss: 0.0609 Total loss: 2.21905 timestamp: 1654921961.138756 iteration: 9460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16482 FastRCNN class loss: 0.10833 FastRCNN total loss: 0.27315 L1 loss: 0.0000e+00 L2 loss: 1.6081 Learning rate: 0.02 Mask loss: 0.16408 RPN box loss: 0.05446 RPN score loss: 0.0079 RPN total loss: 0.06236 Total loss: 2.10769 timestamp: 1654921964.3890998 iteration: 9465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09313 FastRCNN class loss: 0.05537 FastRCNN total loss: 0.1485 L1 loss: 0.0000e+00 L2 loss: 1.60781 Learning rate: 0.02 Mask loss: 0.12898 RPN box loss: 0.07506 RPN score loss: 0.02296 RPN total loss: 0.09803 Total loss: 1.98332 timestamp: 1654921967.607478 iteration: 9470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.17759 L1 loss: 0.0000e+00 L2 loss: 1.60753 Learning rate: 0.02 Mask loss: 0.10735 RPN box loss: 0.03149 RPN score loss: 0.00503 RPN total loss: 0.03652 Total loss: 1.92897 timestamp: 1654921970.8960466 iteration: 9475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18703 FastRCNN class loss: 0.18405 FastRCNN total loss: 0.37107 L1 loss: 0.0000e+00 L2 loss: 1.60722 Learning rate: 0.02 Mask loss: 0.31678 RPN box loss: 0.06006 RPN score loss: 0.07654 RPN total loss: 0.13661 Total loss: 2.43169 timestamp: 1654921974.1549828 iteration: 9480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12134 FastRCNN class loss: 0.06015 FastRCNN total loss: 0.18148 L1 loss: 0.0000e+00 L2 loss: 1.60692 Learning rate: 0.02 Mask loss: 0.18207 RPN box loss: 0.04251 RPN score loss: 0.01325 RPN total loss: 0.05576 Total loss: 2.02623 timestamp: 1654921977.3148878 iteration: 9485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16707 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.264 L1 loss: 0.0000e+00 L2 loss: 1.60663 Learning rate: 0.02 Mask loss: 0.23194 RPN box loss: 0.02554 RPN score loss: 0.01035 RPN total loss: 0.0359 Total loss: 2.13847 timestamp: 1654921980.5873816 iteration: 9490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20715 FastRCNN class loss: 0.08669 FastRCNN total loss: 0.29384 L1 loss: 0.0000e+00 L2 loss: 1.60634 Learning rate: 0.02 Mask loss: 0.20067 RPN box loss: 0.03001 RPN score loss: 0.00559 RPN total loss: 0.03559 Total loss: 2.13644 timestamp: 1654921983.7503812 iteration: 9495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27806 FastRCNN class loss: 0.13717 FastRCNN total loss: 0.41522 L1 loss: 0.0000e+00 L2 loss: 1.60605 Learning rate: 0.02 Mask loss: 0.21151 RPN box loss: 0.03768 RPN score loss: 0.00918 RPN total loss: 0.04687 Total loss: 2.27965 timestamp: 1654921986.9864395 iteration: 9500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23388 FastRCNN class loss: 0.10592 FastRCNN total loss: 0.3398 L1 loss: 0.0000e+00 L2 loss: 1.60577 Learning rate: 0.02 Mask loss: 0.18355 RPN box loss: 0.04275 RPN score loss: 0.01165 RPN total loss: 0.05439 Total loss: 2.18351 timestamp: 1654921990.1697404 iteration: 9505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17921 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.25982 L1 loss: 0.0000e+00 L2 loss: 1.60549 Learning rate: 0.02 Mask loss: 0.11564 RPN box loss: 0.04455 RPN score loss: 0.00752 RPN total loss: 0.05206 Total loss: 2.03301 timestamp: 1654921993.5315168 iteration: 9510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27638 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.35389 L1 loss: 0.0000e+00 L2 loss: 1.60521 Learning rate: 0.02 Mask loss: 0.18455 RPN box loss: 0.01706 RPN score loss: 0.00702 RPN total loss: 0.02408 Total loss: 2.16773 timestamp: 1654921996.7287068 iteration: 9515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21697 FastRCNN class loss: 0.11524 FastRCNN total loss: 0.33221 L1 loss: 0.0000e+00 L2 loss: 1.60492 Learning rate: 0.02 Mask loss: 0.21441 RPN box loss: 0.03335 RPN score loss: 0.00516 RPN total loss: 0.03851 Total loss: 2.19005 timestamp: 1654921999.9428387 iteration: 9520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12927 FastRCNN class loss: 0.07678 FastRCNN total loss: 0.20605 L1 loss: 0.0000e+00 L2 loss: 1.60462 Learning rate: 0.02 Mask loss: 0.20154 RPN box loss: 0.03422 RPN score loss: 0.00995 RPN total loss: 0.04417 Total loss: 2.05639 timestamp: 1654922003.159947 iteration: 9525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12369 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.20371 L1 loss: 0.0000e+00 L2 loss: 1.60434 Learning rate: 0.02 Mask loss: 0.14078 RPN box loss: 0.04784 RPN score loss: 0.0043 RPN total loss: 0.05215 Total loss: 2.00097 timestamp: 1654922006.4883597 iteration: 9530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18916 FastRCNN class loss: 0.09196 FastRCNN total loss: 0.28112 L1 loss: 0.0000e+00 L2 loss: 1.60405 Learning rate: 0.02 Mask loss: 0.1747 RPN box loss: 0.07215 RPN score loss: 0.00847 RPN total loss: 0.08063 Total loss: 2.14049 timestamp: 1654922009.7224731 iteration: 9535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11914 FastRCNN class loss: 0.10078 FastRCNN total loss: 0.21992 L1 loss: 0.0000e+00 L2 loss: 1.60375 Learning rate: 0.02 Mask loss: 0.21805 RPN box loss: 0.04364 RPN score loss: 0.01864 RPN total loss: 0.06228 Total loss: 2.104 timestamp: 1654922013.0019057 iteration: 9540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14649 FastRCNN class loss: 0.10302 FastRCNN total loss: 0.24951 L1 loss: 0.0000e+00 L2 loss: 1.60345 Learning rate: 0.02 Mask loss: 0.19432 RPN box loss: 0.01739 RPN score loss: 0.00524 RPN total loss: 0.02263 Total loss: 2.06991 timestamp: 1654922016.3334067 iteration: 9545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18651 FastRCNN class loss: 0.1198 FastRCNN total loss: 0.30631 L1 loss: 0.0000e+00 L2 loss: 1.60315 Learning rate: 0.02 Mask loss: 0.23212 RPN box loss: 0.05916 RPN score loss: 0.00998 RPN total loss: 0.06914 Total loss: 2.21072 timestamp: 1654922019.5291846 iteration: 9550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15625 FastRCNN class loss: 0.10586 FastRCNN total loss: 0.26211 L1 loss: 0.0000e+00 L2 loss: 1.60286 Learning rate: 0.02 Mask loss: 0.19031 RPN box loss: 0.02759 RPN score loss: 0.01079 RPN total loss: 0.03838 Total loss: 2.09365 timestamp: 1654922022.7360735 iteration: 9555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19821 FastRCNN class loss: 0.10169 FastRCNN total loss: 0.2999 L1 loss: 0.0000e+00 L2 loss: 1.60259 Learning rate: 0.02 Mask loss: 0.16871 RPN box loss: 0.09318 RPN score loss: 0.00826 RPN total loss: 0.10144 Total loss: 2.17264 timestamp: 1654922025.9853418 iteration: 9560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15109 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.24562 L1 loss: 0.0000e+00 L2 loss: 1.60231 Learning rate: 0.02 Mask loss: 0.15036 RPN box loss: 0.02221 RPN score loss: 0.00638 RPN total loss: 0.02859 Total loss: 2.02687 timestamp: 1654922029.1888096 iteration: 9565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10345 FastRCNN class loss: 0.05335 FastRCNN total loss: 0.1568 L1 loss: 0.0000e+00 L2 loss: 1.60201 Learning rate: 0.02 Mask loss: 0.11136 RPN box loss: 0.01796 RPN score loss: 0.00346 RPN total loss: 0.02142 Total loss: 1.89158 timestamp: 1654922032.3703957 iteration: 9570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17761 FastRCNN class loss: 0.12612 FastRCNN total loss: 0.30374 L1 loss: 0.0000e+00 L2 loss: 1.60172 Learning rate: 0.02 Mask loss: 0.17937 RPN box loss: 0.03567 RPN score loss: 0.01019 RPN total loss: 0.04586 Total loss: 2.13069 timestamp: 1654922035.63322 iteration: 9575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13677 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.22395 L1 loss: 0.0000e+00 L2 loss: 1.60144 Learning rate: 0.02 Mask loss: 0.14687 RPN box loss: 0.04722 RPN score loss: 0.00981 RPN total loss: 0.05704 Total loss: 2.0293 timestamp: 1654922038.7943761 iteration: 9580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16174 FastRCNN class loss: 0.07242 FastRCNN total loss: 0.23415 L1 loss: 0.0000e+00 L2 loss: 1.60114 Learning rate: 0.02 Mask loss: 0.15113 RPN box loss: 0.09129 RPN score loss: 0.01177 RPN total loss: 0.10305 Total loss: 2.08947 timestamp: 1654922042.1070979 iteration: 9585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26961 FastRCNN class loss: 0.11104 FastRCNN total loss: 0.38065 L1 loss: 0.0000e+00 L2 loss: 1.60085 Learning rate: 0.02 Mask loss: 0.23801 RPN box loss: 0.02666 RPN score loss: 0.01596 RPN total loss: 0.04261 Total loss: 2.26212 timestamp: 1654922045.2952995 iteration: 9590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1604 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.22795 L1 loss: 0.0000e+00 L2 loss: 1.60055 Learning rate: 0.02 Mask loss: 0.13126 RPN box loss: 0.01007 RPN score loss: 0.00817 RPN total loss: 0.01824 Total loss: 1.978 timestamp: 1654922048.5376842 iteration: 9595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26303 FastRCNN class loss: 0.09254 FastRCNN total loss: 0.35557 L1 loss: 0.0000e+00 L2 loss: 1.60025 Learning rate: 0.02 Mask loss: 0.1807 RPN box loss: 0.05549 RPN score loss: 0.00802 RPN total loss: 0.06351 Total loss: 2.20002 timestamp: 1654922051.8436718 iteration: 9600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11684 FastRCNN class loss: 0.08195 FastRCNN total loss: 0.19879 L1 loss: 0.0000e+00 L2 loss: 1.59996 Learning rate: 0.02 Mask loss: 0.16654 RPN box loss: 0.0464 RPN score loss: 0.00546 RPN total loss: 0.05186 Total loss: 2.01715 timestamp: 1654922055.0872347 iteration: 9605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16955 FastRCNN class loss: 0.07677 FastRCNN total loss: 0.24632 L1 loss: 0.0000e+00 L2 loss: 1.59967 Learning rate: 0.02 Mask loss: 0.18222 RPN box loss: 0.07512 RPN score loss: 0.00578 RPN total loss: 0.08091 Total loss: 2.10912 timestamp: 1654922058.411079 iteration: 9610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24663 FastRCNN class loss: 0.15923 FastRCNN total loss: 0.40586 L1 loss: 0.0000e+00 L2 loss: 1.59938 Learning rate: 0.02 Mask loss: 0.20976 RPN box loss: 0.06882 RPN score loss: 0.02359 RPN total loss: 0.09241 Total loss: 2.30741 timestamp: 1654922061.6734285 iteration: 9615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10908 FastRCNN class loss: 0.05357 FastRCNN total loss: 0.16265 L1 loss: 0.0000e+00 L2 loss: 1.59909 Learning rate: 0.02 Mask loss: 0.1102 RPN box loss: 0.02364 RPN score loss: 0.00402 RPN total loss: 0.02766 Total loss: 1.89959 timestamp: 1654922064.863722 iteration: 9620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.03767 FastRCNN total loss: 0.12169 L1 loss: 0.0000e+00 L2 loss: 1.59881 Learning rate: 0.02 Mask loss: 0.10106 RPN box loss: 0.02686 RPN score loss: 0.00368 RPN total loss: 0.03054 Total loss: 1.85211 timestamp: 1654922068.07716 iteration: 9625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16907 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.22864 L1 loss: 0.0000e+00 L2 loss: 1.59852 Learning rate: 0.02 Mask loss: 0.1566 RPN box loss: 0.01583 RPN score loss: 0.00563 RPN total loss: 0.02146 Total loss: 2.00522 timestamp: 1654922071.4232981 iteration: 9630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27497 FastRCNN class loss: 0.11286 FastRCNN total loss: 0.38782 L1 loss: 0.0000e+00 L2 loss: 1.59823 Learning rate: 0.02 Mask loss: 0.23394 RPN box loss: 0.05585 RPN score loss: 0.0105 RPN total loss: 0.06635 Total loss: 2.28634 timestamp: 1654922074.6638489 iteration: 9635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14017 FastRCNN class loss: 0.08653 FastRCNN total loss: 0.2267 L1 loss: 0.0000e+00 L2 loss: 1.59795 Learning rate: 0.02 Mask loss: 0.19605 RPN box loss: 0.01234 RPN score loss: 0.01058 RPN total loss: 0.02292 Total loss: 2.04361 timestamp: 1654922077.8974125 iteration: 9640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16339 FastRCNN class loss: 0.04906 FastRCNN total loss: 0.21245 L1 loss: 0.0000e+00 L2 loss: 1.59766 Learning rate: 0.02 Mask loss: 0.14595 RPN box loss: 0.04847 RPN score loss: 0.00689 RPN total loss: 0.05536 Total loss: 2.01141 timestamp: 1654922081.1840878 iteration: 9645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17445 FastRCNN class loss: 0.11484 FastRCNN total loss: 0.28929 L1 loss: 0.0000e+00 L2 loss: 1.59735 Learning rate: 0.02 Mask loss: 0.15377 RPN box loss: 0.03249 RPN score loss: 0.008 RPN total loss: 0.04049 Total loss: 2.08089 timestamp: 1654922084.5802562 iteration: 9650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13578 FastRCNN class loss: 0.08818 FastRCNN total loss: 0.22395 L1 loss: 0.0000e+00 L2 loss: 1.59706 Learning rate: 0.02 Mask loss: 0.18559 RPN box loss: 0.03789 RPN score loss: 0.01608 RPN total loss: 0.05397 Total loss: 2.06057 timestamp: 1654922087.9132679 iteration: 9655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.157 FastRCNN class loss: 0.09224 FastRCNN total loss: 0.24924 L1 loss: 0.0000e+00 L2 loss: 1.59678 Learning rate: 0.02 Mask loss: 0.21907 RPN box loss: 0.0298 RPN score loss: 0.00798 RPN total loss: 0.03778 Total loss: 2.10287 timestamp: 1654922091.1888802 iteration: 9660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17374 FastRCNN class loss: 0.14339 FastRCNN total loss: 0.31713 L1 loss: 0.0000e+00 L2 loss: 1.59649 Learning rate: 0.02 Mask loss: 0.18818 RPN box loss: 0.04207 RPN score loss: 0.00383 RPN total loss: 0.0459 Total loss: 2.14769 timestamp: 1654922094.4932463 iteration: 9665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15693 FastRCNN class loss: 0.11721 FastRCNN total loss: 0.27414 L1 loss: 0.0000e+00 L2 loss: 1.59621 Learning rate: 0.02 Mask loss: 0.21675 RPN box loss: 0.06776 RPN score loss: 0.00813 RPN total loss: 0.07589 Total loss: 2.16299 timestamp: 1654922097.7471802 iteration: 9670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13634 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.21219 L1 loss: 0.0000e+00 L2 loss: 1.59592 Learning rate: 0.02 Mask loss: 0.14134 RPN box loss: 0.02823 RPN score loss: 0.00914 RPN total loss: 0.03737 Total loss: 1.98682 timestamp: 1654922101.0629914 iteration: 9675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12236 FastRCNN class loss: 0.0718 FastRCNN total loss: 0.19416 L1 loss: 0.0000e+00 L2 loss: 1.59562 Learning rate: 0.02 Mask loss: 0.17277 RPN box loss: 0.03161 RPN score loss: 0.00373 RPN total loss: 0.03534 Total loss: 1.99789 timestamp: 1654922104.2806628 iteration: 9680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17043 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.22898 L1 loss: 0.0000e+00 L2 loss: 1.59532 Learning rate: 0.02 Mask loss: 0.14699 RPN box loss: 0.02217 RPN score loss: 0.00663 RPN total loss: 0.0288 Total loss: 2.00009 timestamp: 1654922107.5777116 iteration: 9685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18207 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.26624 L1 loss: 0.0000e+00 L2 loss: 1.59501 Learning rate: 0.02 Mask loss: 0.16012 RPN box loss: 0.04048 RPN score loss: 0.00373 RPN total loss: 0.04421 Total loss: 2.06558 timestamp: 1654922110.8275716 iteration: 9690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11273 FastRCNN class loss: 0.08836 FastRCNN total loss: 0.20109 L1 loss: 0.0000e+00 L2 loss: 1.59473 Learning rate: 0.02 Mask loss: 0.18195 RPN box loss: 0.02752 RPN score loss: 0.0056 RPN total loss: 0.03312 Total loss: 2.0109 timestamp: 1654922114.1343787 iteration: 9695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15749 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.21477 L1 loss: 0.0000e+00 L2 loss: 1.59445 Learning rate: 0.02 Mask loss: 0.17775 RPN box loss: 0.00615 RPN score loss: 0.00323 RPN total loss: 0.00939 Total loss: 1.99635 timestamp: 1654922117.4095824 iteration: 9700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16258 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.25235 L1 loss: 0.0000e+00 L2 loss: 1.59417 Learning rate: 0.02 Mask loss: 0.09549 RPN box loss: 0.01846 RPN score loss: 0.00222 RPN total loss: 0.02068 Total loss: 1.96269 timestamp: 1654922120.6147318 iteration: 9705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09535 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.16669 L1 loss: 0.0000e+00 L2 loss: 1.59388 Learning rate: 0.02 Mask loss: 0.15972 RPN box loss: 0.03098 RPN score loss: 0.00773 RPN total loss: 0.03871 Total loss: 1.95899 timestamp: 1654922123.9319623 iteration: 9710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16833 FastRCNN class loss: 0.08651 FastRCNN total loss: 0.25484 L1 loss: 0.0000e+00 L2 loss: 1.59357 Learning rate: 0.02 Mask loss: 0.12735 RPN box loss: 0.05947 RPN score loss: 0.00932 RPN total loss: 0.06879 Total loss: 2.04456 timestamp: 1654922127.1026173 iteration: 9715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17429 FastRCNN class loss: 0.13065 FastRCNN total loss: 0.30494 L1 loss: 0.0000e+00 L2 loss: 1.59327 Learning rate: 0.02 Mask loss: 0.20873 RPN box loss: 0.03357 RPN score loss: 0.01433 RPN total loss: 0.0479 Total loss: 2.15484 timestamp: 1654922130.5130882 iteration: 9720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22653 FastRCNN class loss: 0.10266 FastRCNN total loss: 0.32919 L1 loss: 0.0000e+00 L2 loss: 1.59299 Learning rate: 0.02 Mask loss: 0.21128 RPN box loss: 0.10608 RPN score loss: 0.00684 RPN total loss: 0.11292 Total loss: 2.24637 timestamp: 1654922133.7517157 iteration: 9725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19223 FastRCNN class loss: 0.09561 FastRCNN total loss: 0.28784 L1 loss: 0.0000e+00 L2 loss: 1.5927 Learning rate: 0.02 Mask loss: 0.19687 RPN box loss: 0.03159 RPN score loss: 0.00853 RPN total loss: 0.04013 Total loss: 2.11755 timestamp: 1654922136.9361196 iteration: 9730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09588 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.15686 L1 loss: 0.0000e+00 L2 loss: 1.59244 Learning rate: 0.02 Mask loss: 0.12292 RPN box loss: 0.00411 RPN score loss: 0.0019 RPN total loss: 0.00601 Total loss: 1.87822 timestamp: 1654922140.119519 iteration: 9735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08103 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.136 L1 loss: 0.0000e+00 L2 loss: 1.59216 Learning rate: 0.02 Mask loss: 0.16029 RPN box loss: 0.02149 RPN score loss: 0.00379 RPN total loss: 0.02528 Total loss: 1.91373 timestamp: 1654922143.4029145 iteration: 9740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11688 FastRCNN class loss: 0.12168 FastRCNN total loss: 0.23856 L1 loss: 0.0000e+00 L2 loss: 1.59189 Learning rate: 0.02 Mask loss: 0.19501 RPN box loss: 0.11947 RPN score loss: 0.05805 RPN total loss: 0.17752 Total loss: 2.20298 timestamp: 1654922146.60659 iteration: 9745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15322 FastRCNN class loss: 0.08063 FastRCNN total loss: 0.23385 L1 loss: 0.0000e+00 L2 loss: 1.5916 Learning rate: 0.02 Mask loss: 0.24311 RPN box loss: 0.03228 RPN score loss: 0.01064 RPN total loss: 0.04292 Total loss: 2.11148 timestamp: 1654922149.9393299 iteration: 9750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13864 FastRCNN class loss: 0.11924 FastRCNN total loss: 0.25788 L1 loss: 0.0000e+00 L2 loss: 1.59132 Learning rate: 0.02 Mask loss: 0.20179 RPN box loss: 0.03199 RPN score loss: 0.01189 RPN total loss: 0.04388 Total loss: 2.09488 timestamp: 1654922153.2026331 iteration: 9755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07545 FastRCNN class loss: 0.09543 FastRCNN total loss: 0.17088 L1 loss: 0.0000e+00 L2 loss: 1.59103 Learning rate: 0.02 Mask loss: 0.15319 RPN box loss: 0.05392 RPN score loss: 0.00557 RPN total loss: 0.05949 Total loss: 1.97459 timestamp: 1654922156.3878715 iteration: 9760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09007 FastRCNN class loss: 0.08559 FastRCNN total loss: 0.17566 L1 loss: 0.0000e+00 L2 loss: 1.59073 Learning rate: 0.02 Mask loss: 0.13894 RPN box loss: 0.05343 RPN score loss: 0.00677 RPN total loss: 0.0602 Total loss: 1.96553 timestamp: 1654922159.7115886 iteration: 9765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18437 FastRCNN class loss: 0.12168 FastRCNN total loss: 0.30605 L1 loss: 0.0000e+00 L2 loss: 1.59045 Learning rate: 0.02 Mask loss: 0.22542 RPN box loss: 0.05217 RPN score loss: 0.02146 RPN total loss: 0.07363 Total loss: 2.19556 timestamp: 1654922162.9021614 iteration: 9770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19383 FastRCNN class loss: 0.08765 FastRCNN total loss: 0.28147 L1 loss: 0.0000e+00 L2 loss: 1.59019 Learning rate: 0.02 Mask loss: 0.16352 RPN box loss: 0.02029 RPN score loss: 0.00818 RPN total loss: 0.02847 Total loss: 2.06365 timestamp: 1654922166.134038 iteration: 9775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23942 FastRCNN class loss: 0.10186 FastRCNN total loss: 0.34128 L1 loss: 0.0000e+00 L2 loss: 1.58991 Learning rate: 0.02 Mask loss: 0.20325 RPN box loss: 0.08054 RPN score loss: 0.01177 RPN total loss: 0.09231 Total loss: 2.22675 timestamp: 1654922169.30945 iteration: 9780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14601 FastRCNN class loss: 0.12766 FastRCNN total loss: 0.27367 L1 loss: 0.0000e+00 L2 loss: 1.58962 Learning rate: 0.02 Mask loss: 0.15784 RPN box loss: 0.06557 RPN score loss: 0.00939 RPN total loss: 0.07496 Total loss: 2.09609 timestamp: 1654922172.5636513 iteration: 9785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1873 FastRCNN class loss: 0.13884 FastRCNN total loss: 0.32613 L1 loss: 0.0000e+00 L2 loss: 1.58933 Learning rate: 0.02 Mask loss: 0.31799 RPN box loss: 0.05666 RPN score loss: 0.00856 RPN total loss: 0.06522 Total loss: 2.29868 timestamp: 1654922175.836064 iteration: 9790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15194 FastRCNN class loss: 0.0694 FastRCNN total loss: 0.22134 L1 loss: 0.0000e+00 L2 loss: 1.58903 Learning rate: 0.02 Mask loss: 0.17636 RPN box loss: 0.01012 RPN score loss: 0.00306 RPN total loss: 0.01318 Total loss: 1.99991 timestamp: 1654922179.0410004 iteration: 9795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24933 FastRCNN class loss: 0.21981 FastRCNN total loss: 0.46914 L1 loss: 0.0000e+00 L2 loss: 1.58872 Learning rate: 0.02 Mask loss: 0.26843 RPN box loss: 0.10393 RPN score loss: 0.01905 RPN total loss: 0.12299 Total loss: 2.44928 timestamp: 1654922182.2424653 iteration: 9800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1874 FastRCNN class loss: 0.09798 FastRCNN total loss: 0.28539 L1 loss: 0.0000e+00 L2 loss: 1.58844 Learning rate: 0.02 Mask loss: 0.14959 RPN box loss: 0.0403 RPN score loss: 0.00649 RPN total loss: 0.04678 Total loss: 2.0702 timestamp: 1654922185.6249955 iteration: 9805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14704 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.2144 L1 loss: 0.0000e+00 L2 loss: 1.58815 Learning rate: 0.02 Mask loss: 0.13082 RPN box loss: 0.00359 RPN score loss: 0.00391 RPN total loss: 0.00751 Total loss: 1.94087 timestamp: 1654922188.9751532 iteration: 9810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16057 FastRCNN class loss: 0.08944 FastRCNN total loss: 0.25001 L1 loss: 0.0000e+00 L2 loss: 1.58786 Learning rate: 0.02 Mask loss: 0.13553 RPN box loss: 0.06795 RPN score loss: 0.00391 RPN total loss: 0.07186 Total loss: 2.04525 timestamp: 1654922192.1202855 iteration: 9815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13259 FastRCNN class loss: 0.09998 FastRCNN total loss: 0.23257 L1 loss: 0.0000e+00 L2 loss: 1.5876 Learning rate: 0.02 Mask loss: 0.12389 RPN box loss: 0.05715 RPN score loss: 0.02027 RPN total loss: 0.07742 Total loss: 2.02148 timestamp: 1654922195.289966 iteration: 9820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21282 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.30972 L1 loss: 0.0000e+00 L2 loss: 1.58731 Learning rate: 0.02 Mask loss: 0.24856 RPN box loss: 0.04275 RPN score loss: 0.00778 RPN total loss: 0.05054 Total loss: 2.19612 timestamp: 1654922198.5108228 iteration: 9825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24024 FastRCNN class loss: 0.09651 FastRCNN total loss: 0.33676 L1 loss: 0.0000e+00 L2 loss: 1.58703 Learning rate: 0.02 Mask loss: 0.17907 RPN box loss: 0.03243 RPN score loss: 0.01158 RPN total loss: 0.04401 Total loss: 2.14686 timestamp: 1654922201.8939776 iteration: 9830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10004 FastRCNN class loss: 0.05018 FastRCNN total loss: 0.15023 L1 loss: 0.0000e+00 L2 loss: 1.58674 Learning rate: 0.02 Mask loss: 0.11025 RPN box loss: 0.02118 RPN score loss: 0.00916 RPN total loss: 0.03035 Total loss: 1.87756 timestamp: 1654922205.038186 iteration: 9835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23607 FastRCNN class loss: 0.135 FastRCNN total loss: 0.37107 L1 loss: 0.0000e+00 L2 loss: 1.58645 Learning rate: 0.02 Mask loss: 0.27916 RPN box loss: 0.01795 RPN score loss: 0.00581 RPN total loss: 0.02376 Total loss: 2.26044 timestamp: 1654922208.3050425 iteration: 9840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0948 FastRCNN class loss: 0.07852 FastRCNN total loss: 0.17332 L1 loss: 0.0000e+00 L2 loss: 1.58616 Learning rate: 0.02 Mask loss: 0.19591 RPN box loss: 0.02589 RPN score loss: 0.00758 RPN total loss: 0.03348 Total loss: 1.98887 timestamp: 1654922211.5130377 iteration: 9845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1387 FastRCNN class loss: 0.08419 FastRCNN total loss: 0.22289 L1 loss: 0.0000e+00 L2 loss: 1.58586 Learning rate: 0.02 Mask loss: 0.11641 RPN box loss: 0.03117 RPN score loss: 0.01535 RPN total loss: 0.04651 Total loss: 1.97166 timestamp: 1654922214.7232184 iteration: 9850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14254 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.22042 L1 loss: 0.0000e+00 L2 loss: 1.58556 Learning rate: 0.02 Mask loss: 0.16182 RPN box loss: 0.13847 RPN score loss: 0.00667 RPN total loss: 0.14514 Total loss: 2.11295 timestamp: 1654922217.938759 iteration: 9855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20266 FastRCNN class loss: 0.1065 FastRCNN total loss: 0.30917 L1 loss: 0.0000e+00 L2 loss: 1.58527 Learning rate: 0.02 Mask loss: 0.13834 RPN box loss: 0.03474 RPN score loss: 0.00846 RPN total loss: 0.0432 Total loss: 2.07598 timestamp: 1654922221.1055703 iteration: 9860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10588 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.17372 L1 loss: 0.0000e+00 L2 loss: 1.58497 Learning rate: 0.02 Mask loss: 0.13553 RPN box loss: 0.08283 RPN score loss: 0.00924 RPN total loss: 0.09208 Total loss: 1.98631 timestamp: 1654922224.3424335 iteration: 9865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17782 FastRCNN class loss: 0.11667 FastRCNN total loss: 0.29449 L1 loss: 0.0000e+00 L2 loss: 1.58469 Learning rate: 0.02 Mask loss: 0.21596 RPN box loss: 0.02907 RPN score loss: 0.01213 RPN total loss: 0.0412 Total loss: 2.13634 timestamp: 1654922227.6212347 iteration: 9870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16168 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.24591 L1 loss: 0.0000e+00 L2 loss: 1.58441 Learning rate: 0.02 Mask loss: 0.15754 RPN box loss: 0.03442 RPN score loss: 0.01739 RPN total loss: 0.05181 Total loss: 2.03968 timestamp: 1654922230.9069893 iteration: 9875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23321 FastRCNN class loss: 0.10598 FastRCNN total loss: 0.33918 L1 loss: 0.0000e+00 L2 loss: 1.58413 Learning rate: 0.02 Mask loss: 0.19615 RPN box loss: 0.07591 RPN score loss: 0.01258 RPN total loss: 0.08849 Total loss: 2.20795 timestamp: 1654922234.1654382 iteration: 9880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19297 FastRCNN class loss: 0.09212 FastRCNN total loss: 0.28509 L1 loss: 0.0000e+00 L2 loss: 1.58386 Learning rate: 0.02 Mask loss: 0.23009 RPN box loss: 0.02535 RPN score loss: 0.01006 RPN total loss: 0.03541 Total loss: 2.13445 timestamp: 1654922237.434687 iteration: 9885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18013 FastRCNN class loss: 0.09578 FastRCNN total loss: 0.27591 L1 loss: 0.0000e+00 L2 loss: 1.5836 Learning rate: 0.02 Mask loss: 0.17507 RPN box loss: 0.05212 RPN score loss: 0.00743 RPN total loss: 0.05955 Total loss: 2.09412 timestamp: 1654922240.7414675 iteration: 9890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15937 FastRCNN class loss: 0.12789 FastRCNN total loss: 0.28726 L1 loss: 0.0000e+00 L2 loss: 1.58332 Learning rate: 0.02 Mask loss: 0.1578 RPN box loss: 0.05388 RPN score loss: 0.0161 RPN total loss: 0.06998 Total loss: 2.09836 timestamp: 1654922244.1328437 iteration: 9895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16301 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.22244 L1 loss: 0.0000e+00 L2 loss: 1.58303 Learning rate: 0.02 Mask loss: 0.19598 RPN box loss: 0.04205 RPN score loss: 0.00582 RPN total loss: 0.04787 Total loss: 2.04931 timestamp: 1654922247.337335 iteration: 9900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13471 FastRCNN class loss: 0.12093 FastRCNN total loss: 0.25565 L1 loss: 0.0000e+00 L2 loss: 1.58273 Learning rate: 0.02 Mask loss: 0.1912 RPN box loss: 0.02322 RPN score loss: 0.00642 RPN total loss: 0.02964 Total loss: 2.05922 timestamp: 1654922250.7091343 iteration: 9905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3035 FastRCNN class loss: 0.19471 FastRCNN total loss: 0.49821 L1 loss: 0.0000e+00 L2 loss: 1.58245 Learning rate: 0.02 Mask loss: 0.38014 RPN box loss: 0.03759 RPN score loss: 0.01757 RPN total loss: 0.05515 Total loss: 2.51595 timestamp: 1654922254.0121891 iteration: 9910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15254 FastRCNN class loss: 0.08953 FastRCNN total loss: 0.24207 L1 loss: 0.0000e+00 L2 loss: 1.58215 Learning rate: 0.02 Mask loss: 0.20717 RPN box loss: 0.03848 RPN score loss: 0.01051 RPN total loss: 0.04898 Total loss: 2.08037 timestamp: 1654922257.3365629 iteration: 9915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19701 FastRCNN class loss: 0.07929 FastRCNN total loss: 0.2763 L1 loss: 0.0000e+00 L2 loss: 1.58185 Learning rate: 0.02 Mask loss: 0.21985 RPN box loss: 0.05831 RPN score loss: 0.01542 RPN total loss: 0.07373 Total loss: 2.15173 timestamp: 1654922260.5579624 iteration: 9920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11882 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.18831 L1 loss: 0.0000e+00 L2 loss: 1.58157 Learning rate: 0.02 Mask loss: 0.12032 RPN box loss: 0.0412 RPN score loss: 0.01333 RPN total loss: 0.05453 Total loss: 1.94473 timestamp: 1654922263.8549416 iteration: 9925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23525 FastRCNN class loss: 0.13146 FastRCNN total loss: 0.36671 L1 loss: 0.0000e+00 L2 loss: 1.58129 Learning rate: 0.02 Mask loss: 0.26526 RPN box loss: 0.08781 RPN score loss: 0.00976 RPN total loss: 0.09757 Total loss: 2.31083 timestamp: 1654922267.1166139 iteration: 9930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2076 FastRCNN class loss: 0.10891 FastRCNN total loss: 0.31651 L1 loss: 0.0000e+00 L2 loss: 1.58102 Learning rate: 0.02 Mask loss: 0.22456 RPN box loss: 0.02936 RPN score loss: 0.00901 RPN total loss: 0.03837 Total loss: 2.16046 timestamp: 1654922270.3195295 iteration: 9935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17263 FastRCNN class loss: 0.05736 FastRCNN total loss: 0.22999 L1 loss: 0.0000e+00 L2 loss: 1.58075 Learning rate: 0.02 Mask loss: 0.18583 RPN box loss: 0.09121 RPN score loss: 0.00549 RPN total loss: 0.09669 Total loss: 2.09326 timestamp: 1654922273.614044 iteration: 9940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20627 FastRCNN class loss: 0.13177 FastRCNN total loss: 0.33804 L1 loss: 0.0000e+00 L2 loss: 1.58049 Learning rate: 0.02 Mask loss: 0.2407 RPN box loss: 0.02386 RPN score loss: 0.01018 RPN total loss: 0.03404 Total loss: 2.19327 timestamp: 1654922276.8011162 iteration: 9945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13707 FastRCNN class loss: 0.08154 FastRCNN total loss: 0.21861 L1 loss: 0.0000e+00 L2 loss: 1.58023 Learning rate: 0.02 Mask loss: 0.15412 RPN box loss: 0.04188 RPN score loss: 0.00236 RPN total loss: 0.04424 Total loss: 1.99721 timestamp: 1654922280.0458858 iteration: 9950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19178 FastRCNN class loss: 0.10472 FastRCNN total loss: 0.2965 L1 loss: 0.0000e+00 L2 loss: 1.57995 Learning rate: 0.02 Mask loss: 0.18518 RPN box loss: 0.02611 RPN score loss: 0.00926 RPN total loss: 0.03537 Total loss: 2.097 timestamp: 1654922283.269912 iteration: 9955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13861 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.2187 L1 loss: 0.0000e+00 L2 loss: 1.57965 Learning rate: 0.02 Mask loss: 0.175 RPN box loss: 0.00667 RPN score loss: 0.0059 RPN total loss: 0.01257 Total loss: 1.98593 timestamp: 1654922286.5563622 iteration: 9960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1642 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.23055 L1 loss: 0.0000e+00 L2 loss: 1.57936 Learning rate: 0.02 Mask loss: 0.14312 RPN box loss: 0.04897 RPN score loss: 0.00663 RPN total loss: 0.0556 Total loss: 2.00863 timestamp: 1654922289.8201191 iteration: 9965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11488 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.16612 L1 loss: 0.0000e+00 L2 loss: 1.57906 Learning rate: 0.02 Mask loss: 0.11311 RPN box loss: 0.05003 RPN score loss: 0.00437 RPN total loss: 0.0544 Total loss: 1.91269 timestamp: 1654922293.0976279 iteration: 9970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1538 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.23628 L1 loss: 0.0000e+00 L2 loss: 1.57876 Learning rate: 0.02 Mask loss: 0.18459 RPN box loss: 0.07238 RPN score loss: 0.00634 RPN total loss: 0.07872 Total loss: 2.07835 timestamp: 1654922296.3680532 iteration: 9975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10103 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.16536 L1 loss: 0.0000e+00 L2 loss: 1.57844 Learning rate: 0.02 Mask loss: 0.1188 RPN box loss: 0.01577 RPN score loss: 0.00519 RPN total loss: 0.02095 Total loss: 1.88355 timestamp: 1654922299.6405616 iteration: 9980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1575 FastRCNN class loss: 0.10076 FastRCNN total loss: 0.25826 L1 loss: 0.0000e+00 L2 loss: 1.57814 Learning rate: 0.02 Mask loss: 0.14715 RPN box loss: 0.10548 RPN score loss: 0.00871 RPN total loss: 0.11419 Total loss: 2.09774 timestamp: 1654922302.9713483 iteration: 9985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16051 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.25962 L1 loss: 0.0000e+00 L2 loss: 1.57785 Learning rate: 0.02 Mask loss: 0.24301 RPN box loss: 0.0404 RPN score loss: 0.00801 RPN total loss: 0.04841 Total loss: 2.12889 timestamp: 1654922306.1019127 iteration: 9990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16148 FastRCNN class loss: 0.0938 FastRCNN total loss: 0.25528 L1 loss: 0.0000e+00 L2 loss: 1.57758 Learning rate: 0.02 Mask loss: 0.11265 RPN box loss: 0.00997 RPN score loss: 0.00262 RPN total loss: 0.01259 Total loss: 1.9581 timestamp: 1654922309.3980742 iteration: 9995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25394 FastRCNN class loss: 0.14103 FastRCNN total loss: 0.39497 L1 loss: 0.0000e+00 L2 loss: 1.57731 Learning rate: 0.02 Mask loss: 0.31157 RPN box loss: 0.07295 RPN score loss: 0.01124 RPN total loss: 0.08419 Total loss: 2.36804 timestamp: 1654922312.6327083 iteration: 10000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13703 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.22847 L1 loss: 0.0000e+00 L2 loss: 1.57701 Learning rate: 0.02 Mask loss: 0.21497 RPN box loss: 0.03936 RPN score loss: 0.0063 RPN total loss: 0.04567 Total loss: 2.06612 Saving checkpoints for 10000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-10000.tlt. ================================= Start evaluation cycle 01 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-10000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 7.4776s - Throughput: 0.5 imgs/s Running inference on batch 002/125... - Step Time: 0.3375s - Throughput: 11.9 imgs/s Running inference on batch 003/125... - Step Time: 0.3300s - Throughput: 12.1 imgs/s Running inference on batch 004/125... - Step Time: 0.3514s - Throughput: 11.4 imgs/s Running inference on batch 005/125... - Step Time: 0.3247s - Throughput: 12.3 imgs/s Running inference on batch 006/125... - Step Time: 0.3407s - Throughput: 11.7 imgs/s Running inference on batch 007/125... - Step Time: 0.3220s - Throughput: 12.4 imgs/s Running inference on batch 008/125... - Step Time: 0.3237s - Throughput: 12.4 imgs/s Running inference on batch 009/125... - Step Time: 0.3386s - Throughput: 11.8 imgs/s Running inference on batch 010/125... - Step Time: 0.3320s - Throughput: 12.0 imgs/s Running inference on batch 011/125... - Step Time: 0.3330s - Throughput: 12.0 imgs/s Running inference on batch 012/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 013/125... - Step Time: 0.3427s - Throughput: 11.7 imgs/s Running inference on batch 014/125... - Step Time: 0.3276s - Throughput: 12.2 imgs/s Running inference on batch 015/125... - Step Time: 0.3390s - Throughput: 11.8 imgs/s Running inference on batch 016/125... - Step Time: 0.3313s - Throughput: 12.1 imgs/s Running inference on batch 017/125... - Step Time: 0.3296s - Throughput: 12.1 imgs/s Running inference on batch 018/125... - Step Time: 0.3241s - Throughput: 12.3 imgs/s Running inference on batch 019/125... - Step Time: 0.3310s - Throughput: 12.1 imgs/s Running inference on batch 020/125... - Step Time: 0.3288s - Throughput: 12.2 imgs/s Running inference on batch 021/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 022/125... - Step Time: 0.3283s - Throughput: 12.2 imgs/s Running inference on batch 023/125... - Step Time: 0.3689s - Throughput: 10.8 imgs/s Running inference on batch 024/125... - Step Time: 0.3259s - Throughput: 12.3 imgs/s Running inference on batch 025/125... - Step Time: 0.3328s - Throughput: 12.0 imgs/s Running inference on batch 026/125... - Step Time: 0.3332s - Throughput: 12.0 imgs/s Running inference on batch 027/125... - Step Time: 0.3190s - Throughput: 12.5 imgs/s Running inference on batch 028/125... - Step Time: 0.3313s - Throughput: 12.1 imgs/s Running inference on batch 029/125... - Step Time: 0.3255s - Throughput: 12.3 imgs/s Running inference on batch 030/125... - Step Time: 0.3383s - Throughput: 11.8 imgs/s Running inference on batch 031/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 032/125... - Step Time: 0.3302s - Throughput: 12.1 imgs/s Running inference on batch 033/125... - Step Time: 0.3269s - Throughput: 12.2 imgs/s Running inference on batch 034/125... - Step Time: 0.3305s - Throughput: 12.1 imgs/s Running inference on batch 035/125... - Step Time: 0.3236s - Throughput: 12.4 imgs/s Running inference on batch 036/125... - Step Time: 0.3326s - Throughput: 12.0 imgs/s Running inference on batch 037/125... - Step Time: 0.3299s - Throughput: 12.1 imgs/s Running inference on batch 038/125... - Step Time: 0.3311s - Throughput: 12.1 imgs/s Running inference on batch 039/125... - Step Time: 0.3228s - Throughput: 12.4 imgs/s Running inference on batch 040/125... - Step Time: 0.3530s - Throughput: 11.3 imgs/s Running inference on batch 041/125... - Step Time: 0.3398s - Throughput: 11.8 imgs/s Running inference on batch 042/125... - Step Time: 0.3275s - Throughput: 12.2 imgs/s Running inference on batch 043/125... - Step Time: 0.3259s - Throughput: 12.3 imgs/s Running inference on batch 044/125... - Step Time: 0.3275s - Throughput: 12.2 imgs/s Running inference on batch 045/125... - Step Time: 0.3260s - Throughput: 12.3 imgs/s Running inference on batch 046/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 047/125... - Step Time: 0.3243s - Throughput: 12.3 imgs/s Running inference on batch 048/125... - Step Time: 0.3417s - Throughput: 11.7 imgs/s Running inference on batch 049/125... - Step Time: 0.3362s - Throughput: 11.9 imgs/s Running inference on batch 050/125... - Step Time: 0.3309s - Throughput: 12.1 imgs/s Running inference on batch 051/125... - Step Time: 0.3299s - Throughput: 12.1 imgs/s Running inference on batch 052/125... - Step Time: 0.3247s - Throughput: 12.3 imgs/s Running inference on batch 053/125... - Step Time: 0.3341s - Throughput: 12.0 imgs/s Running inference on batch 054/125... - Step Time: 0.3219s - Throughput: 12.4 imgs/s Running inference on batch 055/125... - Step Time: 0.3184s - Throughput: 12.6 imgs/s Running inference on batch 056/125... - Step Time: 0.3277s - Throughput: 12.2 imgs/s Running inference on batch 057/125... - Step Time: 0.3322s - Throughput: 12.0 imgs/s Running inference on batch 058/125... - Step Time: 0.3254s - Throughput: 12.3 imgs/s Running inference on batch 059/125... - Step Time: 0.3257s - Throughput: 12.3 imgs/s Running inference on batch 060/125... - Step Time: 0.3298s - Throughput: 12.1 imgs/s Running inference on batch 061/125... - Step Time: 0.3174s - Throughput: 12.6 imgs/s Running inference on batch 062/125... - Step Time: 0.3253s - Throughput: 12.3 imgs/s Running inference on batch 063/125... - Step Time: 0.3184s - Throughput: 12.6 imgs/s Running inference on batch 064/125... - Step Time: 0.3285s - Throughput: 12.2 imgs/s Running inference on batch 065/125... - Step Time: 0.3178s - Throughput: 12.6 imgs/s Running inference on batch 066/125... - Step Time: 0.3286s - Throughput: 12.2 imgs/s Running inference on batch 067/125... - Step Time: 0.3204s - Throughput: 12.5 imgs/s Running inference on batch 068/125... - Step Time: 0.3244s - Throughput: 12.3 imgs/s Running inference on batch 069/125... - Step Time: 0.3319s - Throughput: 12.1 imgs/s Running inference on batch 070/125... - Step Time: 0.3305s - Throughput: 12.1 imgs/s Running inference on batch 071/125... - Step Time: 0.3268s - Throughput: 12.2 imgs/s Running inference on batch 072/125... - Step Time: 0.3389s - Throughput: 11.8 imgs/s Running inference on batch 073/125... - Step Time: 0.3311s - Throughput: 12.1 imgs/s Running inference on batch 074/125... - Step Time: 0.3211s - Throughput: 12.5 imgs/s Running inference on batch 075/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 076/125... - Step Time: 0.3362s - Throughput: 11.9 imgs/s Running inference on batch 077/125... - Step Time: 0.3293s - Throughput: 12.1 imgs/s Running inference on batch 078/125... - Step Time: 0.3306s - Throughput: 12.1 imgs/s Running inference on batch 079/125... - Step Time: 0.3297s - Throughput: 12.1 imgs/s Running inference on batch 080/125... - Step Time: 0.3340s - Throughput: 12.0 imgs/s Running inference on batch 081/125... - Step Time: 0.3223s - Throughput: 12.4 imgs/s Running inference on batch 082/125... - Step Time: 0.3203s - Throughput: 12.5 imgs/s Running inference on batch 083/125... - Step Time: 0.3263s - Throughput: 12.3 imgs/s Running inference on batch 084/125... - Step Time: 0.3304s - Throughput: 12.1 imgs/s Running inference on batch 085/125... - Step Time: 0.3299s - Throughput: 12.1 imgs/s Running inference on batch 086/125... - Step Time: 0.3189s - Throughput: 12.5 imgs/s Running inference on batch 087/125... - Step Time: 0.3252s - Throughput: 12.3 imgs/s Running inference on batch 088/125... - Step Time: 0.3326s - Throughput: 12.0 imgs/s Running inference on batch 089/125... - Step Time: 0.3301s - Throughput: 12.1 imgs/s Running inference on batch 090/125... - Step Time: 0.3075s - Throughput: 13.0 imgs/s Running inference on batch 091/125... - Step Time: 0.3240s - Throughput: 12.3 imgs/s Running inference on batch 092/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 093/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 094/125... - Step Time: 0.3399s - Throughput: 11.8 imgs/s Running inference on batch 095/125... - Step Time: 0.3355s - Throughput: 11.9 imgs/s Running inference on batch 096/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 097/125... - Step Time: 0.3306s - Throughput: 12.1 imgs/s Running inference on batch 098/125... - Step Time: 0.3228s - Throughput: 12.4 imgs/s Running inference on batch 099/125... - Step Time: 0.3151s - Throughput: 12.7 imgs/s Running inference on batch 100/125... - Step Time: 0.2899s - Throughput: 13.8 imgs/s Running inference on batch 101/125... - Step Time: 0.3220s - Throughput: 12.4 imgs/s Running inference on batch 102/125... - Step Time: 0.3230s - Throughput: 12.4 imgs/s Running inference on batch 103/125... - Step Time: 0.3212s - Throughput: 12.5 imgs/s Running inference on batch 104/125... - Step Time: 0.3273s - Throughput: 12.2 imgs/s Running inference on batch 105/125... - Step Time: 0.3185s - Throughput: 12.6 imgs/s Running inference on batch 106/125... - Step Time: 0.3252s - Throughput: 12.3 imgs/s Running inference on batch 107/125... - Step Time: 0.3339s - Throughput: 12.0 imgs/s Running inference on batch 108/125... - Step Time: 0.3295s - Throughput: 12.1 imgs/s Running inference on batch 109/125... - Step Time: 0.2839s - Throughput: 14.1 imgs/s Running inference on batch 110/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 111/125... - Step Time: 0.3261s - Throughput: 12.3 imgs/s Running inference on batch 112/125... - Step Time: 0.3238s - Throughput: 12.4 imgs/s Running inference on batch 113/125... - Step Time: 0.3196s - Throughput: 12.5 imgs/s Running inference on batch 114/125... - Step Time: 0.3311s - Throughput: 12.1 imgs/s Running inference on batch 115/125... - Step Time: 0.3233s - Throughput: 12.4 imgs/s Running inference on batch 116/125... - Step Time: 0.3314s - Throughput: 12.1 imgs/s Running inference on batch 117/125... - Step Time: 0.3213s - Throughput: 12.4 imgs/s Running inference on batch 118/125... - Step Time: 0.3377s - Throughput: 11.8 imgs/s Running inference on batch 119/125... - Step Time: 0.3325s - Throughput: 12.0 imgs/s Running inference on batch 120/125... - Step Time: 0.3270s - Throughput: 12.2 imgs/s Running inference on batch 121/125... - Step Time: 0.3356s - Throughput: 11.9 imgs/s Running inference on batch 122/125... - Step Time: 0.3268s - Throughput: 12.2 imgs/s Running inference on batch 123/125... - Step Time: 0.3339s - Throughput: 12.0 imgs/s Running inference on batch 124/125... - Step Time: 0.3402s - Throughput: 11.8 imgs/s Running inference on batch 125/125... - Step Time: 0.3185s - Throughput: 12.6 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 12.3 samples/sec Total processed steps: 125 Total processing time: 0.0h 25m 11s ==================== Metrics ==================== AP: 0.163599581 AP50: 0.263321221 AP75: 0.159928292 APl: 0.187593281 APm: 0.047336511 APs: 0.009478965 ARl: 0.402090251 ARm: 0.088934541 ARmax1: 0.263308048 ARmax10: 0.344652414 ARmax100: 0.349276185 ARs: 0.014699793 mask_AP: 0.132669196 mask_AP50: 0.222352564 mask_AP75: 0.132935762 mask_APl: 0.152175367 mask_APm: 0.022516387 mask_APs: 0.000146863 mask_ARl: 0.270540506 mask_ARm: 0.045093168 mask_ARmax1: 0.191814199 mask_ARmax10: 0.225330129 mask_ARmax100: 0.227793515 mask_ARs: 0.003381643 ================================= Start training cycle 02 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654923510.688843 iteration: 10005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14759 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.21164 L1 loss: 0.0000e+00 L2 loss: 1.57672 Learning rate: 0.02 Mask loss: 0.1517 RPN box loss: 0.02328 RPN score loss: 0.00234 RPN total loss: 0.02562 Total loss: 1.96569 timestamp: 1654923514.031705 iteration: 10010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12855 FastRCNN class loss: 0.08579 FastRCNN total loss: 0.21434 L1 loss: 0.0000e+00 L2 loss: 1.57645 Learning rate: 0.02 Mask loss: 0.16029 RPN box loss: 0.02493 RPN score loss: 0.00342 RPN total loss: 0.02835 Total loss: 1.97944 timestamp: 1654923517.2042232 iteration: 10015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12951 FastRCNN class loss: 0.06199 FastRCNN total loss: 0.1915 L1 loss: 0.0000e+00 L2 loss: 1.57619 Learning rate: 0.02 Mask loss: 0.1928 RPN box loss: 0.00949 RPN score loss: 0.00786 RPN total loss: 0.01735 Total loss: 1.97783 timestamp: 1654923520.4792507 iteration: 10020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25871 FastRCNN class loss: 0.09447 FastRCNN total loss: 0.35318 L1 loss: 0.0000e+00 L2 loss: 1.5759 Learning rate: 0.02 Mask loss: 0.21781 RPN box loss: 0.03212 RPN score loss: 0.00749 RPN total loss: 0.03961 Total loss: 2.18651 timestamp: 1654923523.7445517 iteration: 10025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1163 FastRCNN class loss: 0.06046 FastRCNN total loss: 0.17676 L1 loss: 0.0000e+00 L2 loss: 1.57562 Learning rate: 0.02 Mask loss: 0.17214 RPN box loss: 0.10452 RPN score loss: 0.0062 RPN total loss: 0.11072 Total loss: 2.03525 timestamp: 1654923527.0818224 iteration: 10030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17986 FastRCNN class loss: 0.08487 FastRCNN total loss: 0.26473 L1 loss: 0.0000e+00 L2 loss: 1.57533 Learning rate: 0.02 Mask loss: 0.1089 RPN box loss: 0.01295 RPN score loss: 0.0023 RPN total loss: 0.01526 Total loss: 1.96422 timestamp: 1654923530.410047 iteration: 10035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12267 FastRCNN class loss: 0.08304 FastRCNN total loss: 0.20571 L1 loss: 0.0000e+00 L2 loss: 1.57505 Learning rate: 0.02 Mask loss: 0.20422 RPN box loss: 0.01352 RPN score loss: 0.00546 RPN total loss: 0.01898 Total loss: 2.00397 timestamp: 1654923533.6992707 iteration: 10040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16784 FastRCNN class loss: 0.09192 FastRCNN total loss: 0.25976 L1 loss: 0.0000e+00 L2 loss: 1.5748 Learning rate: 0.02 Mask loss: 0.20239 RPN box loss: 0.01344 RPN score loss: 0.00285 RPN total loss: 0.01629 Total loss: 2.05324 timestamp: 1654923536.964382 iteration: 10045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22884 FastRCNN class loss: 0.10678 FastRCNN total loss: 0.33561 L1 loss: 0.0000e+00 L2 loss: 1.57451 Learning rate: 0.02 Mask loss: 0.12212 RPN box loss: 0.02038 RPN score loss: 0.00622 RPN total loss: 0.0266 Total loss: 2.05884 timestamp: 1654923540.32412 iteration: 10050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18684 FastRCNN class loss: 0.12132 FastRCNN total loss: 0.30817 L1 loss: 0.0000e+00 L2 loss: 1.5742 Learning rate: 0.02 Mask loss: 0.16607 RPN box loss: 0.01915 RPN score loss: 0.00667 RPN total loss: 0.02582 Total loss: 2.07426 timestamp: 1654923543.5841782 iteration: 10055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14944 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.22133 L1 loss: 0.0000e+00 L2 loss: 1.57393 Learning rate: 0.02 Mask loss: 0.14212 RPN box loss: 0.05393 RPN score loss: 0.00755 RPN total loss: 0.06147 Total loss: 1.99885 timestamp: 1654923546.816033 iteration: 10060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20411 FastRCNN class loss: 0.19295 FastRCNN total loss: 0.39706 L1 loss: 0.0000e+00 L2 loss: 1.57366 Learning rate: 0.02 Mask loss: 0.30507 RPN box loss: 0.04586 RPN score loss: 0.00978 RPN total loss: 0.05564 Total loss: 2.33143 timestamp: 1654923550.0736003 iteration: 10065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.09112 FastRCNN total loss: 0.20111 L1 loss: 0.0000e+00 L2 loss: 1.57337 Learning rate: 0.02 Mask loss: 0.16605 RPN box loss: 0.0678 RPN score loss: 0.00442 RPN total loss: 0.07222 Total loss: 2.01275 timestamp: 1654923553.2993925 iteration: 10070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17944 FastRCNN class loss: 0.11762 FastRCNN total loss: 0.29706 L1 loss: 0.0000e+00 L2 loss: 1.57308 Learning rate: 0.02 Mask loss: 0.13633 RPN box loss: 0.06504 RPN score loss: 0.00537 RPN total loss: 0.07041 Total loss: 2.07688 timestamp: 1654923556.667162 iteration: 10075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2741 FastRCNN class loss: 0.12645 FastRCNN total loss: 0.40054 L1 loss: 0.0000e+00 L2 loss: 1.57278 Learning rate: 0.02 Mask loss: 0.2245 RPN box loss: 0.03654 RPN score loss: 0.00895 RPN total loss: 0.04549 Total loss: 2.24331 timestamp: 1654923559.8493462 iteration: 10080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09287 FastRCNN class loss: 0.03971 FastRCNN total loss: 0.13257 L1 loss: 0.0000e+00 L2 loss: 1.5725 Learning rate: 0.02 Mask loss: 0.13642 RPN box loss: 0.03997 RPN score loss: 0.00523 RPN total loss: 0.0452 Total loss: 1.88669 timestamp: 1654923563.2953987 iteration: 10085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19902 FastRCNN class loss: 0.12432 FastRCNN total loss: 0.32335 L1 loss: 0.0000e+00 L2 loss: 1.57221 Learning rate: 0.02 Mask loss: 0.23639 RPN box loss: 0.03579 RPN score loss: 0.00538 RPN total loss: 0.04117 Total loss: 2.17312 timestamp: 1654923566.562824 iteration: 10090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22882 FastRCNN class loss: 0.08352 FastRCNN total loss: 0.31234 L1 loss: 0.0000e+00 L2 loss: 1.57192 Learning rate: 0.02 Mask loss: 0.17819 RPN box loss: 0.03658 RPN score loss: 0.0077 RPN total loss: 0.04428 Total loss: 2.10674 timestamp: 1654923569.9123077 iteration: 10095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11124 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.17178 L1 loss: 0.0000e+00 L2 loss: 1.57164 Learning rate: 0.02 Mask loss: 0.09723 RPN box loss: 0.03847 RPN score loss: 0.00459 RPN total loss: 0.04306 Total loss: 1.88371 timestamp: 1654923573.3532484 iteration: 10100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13761 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.19256 L1 loss: 0.0000e+00 L2 loss: 1.57134 Learning rate: 0.02 Mask loss: 0.10782 RPN box loss: 0.01587 RPN score loss: 0.00651 RPN total loss: 0.02238 Total loss: 1.8941 timestamp: 1654923576.5042026 iteration: 10105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21099 FastRCNN class loss: 0.10744 FastRCNN total loss: 0.31843 L1 loss: 0.0000e+00 L2 loss: 1.57106 Learning rate: 0.02 Mask loss: 0.14996 RPN box loss: 0.0442 RPN score loss: 0.01033 RPN total loss: 0.05453 Total loss: 2.09399 timestamp: 1654923579.698916 iteration: 10110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16115 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.22363 L1 loss: 0.0000e+00 L2 loss: 1.57079 Learning rate: 0.02 Mask loss: 0.1408 RPN box loss: 0.01497 RPN score loss: 0.00782 RPN total loss: 0.02279 Total loss: 1.958 timestamp: 1654923582.9379263 iteration: 10115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17988 FastRCNN class loss: 0.08499 FastRCNN total loss: 0.26487 L1 loss: 0.0000e+00 L2 loss: 1.57053 Learning rate: 0.02 Mask loss: 0.20805 RPN box loss: 0.02885 RPN score loss: 0.00739 RPN total loss: 0.03624 Total loss: 2.07969 timestamp: 1654923586.2605903 iteration: 10120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07646 FastRCNN class loss: 0.04329 FastRCNN total loss: 0.11974 L1 loss: 0.0000e+00 L2 loss: 1.57024 Learning rate: 0.02 Mask loss: 0.12776 RPN box loss: 0.00382 RPN score loss: 0.00195 RPN total loss: 0.00577 Total loss: 1.82351 timestamp: 1654923589.4393005 iteration: 10125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15883 FastRCNN class loss: 0.08543 FastRCNN total loss: 0.24426 L1 loss: 0.0000e+00 L2 loss: 1.56995 Learning rate: 0.02 Mask loss: 0.15556 RPN box loss: 0.01576 RPN score loss: 0.00299 RPN total loss: 0.01875 Total loss: 1.98852 timestamp: 1654923592.7409728 iteration: 10130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11646 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.18761 L1 loss: 0.0000e+00 L2 loss: 1.56968 Learning rate: 0.02 Mask loss: 0.19392 RPN box loss: 0.10511 RPN score loss: 0.01083 RPN total loss: 0.11594 Total loss: 2.06715 timestamp: 1654923595.9740393 iteration: 10135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14113 FastRCNN class loss: 0.10295 FastRCNN total loss: 0.24408 L1 loss: 0.0000e+00 L2 loss: 1.56938 Learning rate: 0.02 Mask loss: 0.16083 RPN box loss: 0.02322 RPN score loss: 0.00925 RPN total loss: 0.03248 Total loss: 2.00676 timestamp: 1654923599.2719908 iteration: 10140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13847 FastRCNN class loss: 0.10888 FastRCNN total loss: 0.24735 L1 loss: 0.0000e+00 L2 loss: 1.56909 Learning rate: 0.02 Mask loss: 0.13131 RPN box loss: 0.02782 RPN score loss: 0.00763 RPN total loss: 0.03546 Total loss: 1.98321 timestamp: 1654923602.6045287 iteration: 10145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13928 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.20534 L1 loss: 0.0000e+00 L2 loss: 1.56881 Learning rate: 0.02 Mask loss: 0.10744 RPN box loss: 0.00557 RPN score loss: 0.00583 RPN total loss: 0.0114 Total loss: 1.89299 timestamp: 1654923605.7931826 iteration: 10150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13636 FastRCNN class loss: 0.12492 FastRCNN total loss: 0.26128 L1 loss: 0.0000e+00 L2 loss: 1.56853 Learning rate: 0.02 Mask loss: 0.15138 RPN box loss: 0.04516 RPN score loss: 0.00784 RPN total loss: 0.053 Total loss: 2.0342 timestamp: 1654923609.1278427 iteration: 10155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10982 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.17209 L1 loss: 0.0000e+00 L2 loss: 1.56828 Learning rate: 0.02 Mask loss: 0.10308 RPN box loss: 0.01088 RPN score loss: 0.00437 RPN total loss: 0.01525 Total loss: 1.8587 timestamp: 1654923612.3141043 iteration: 10160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12971 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.21505 L1 loss: 0.0000e+00 L2 loss: 1.56799 Learning rate: 0.02 Mask loss: 0.24293 RPN box loss: 0.01577 RPN score loss: 0.00738 RPN total loss: 0.02315 Total loss: 2.04912 timestamp: 1654923615.6016238 iteration: 10165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.17103 L1 loss: 0.0000e+00 L2 loss: 1.56772 Learning rate: 0.02 Mask loss: 0.15914 RPN box loss: 0.03584 RPN score loss: 0.00518 RPN total loss: 0.04102 Total loss: 1.93891 timestamp: 1654923618.7878988 iteration: 10170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12385 FastRCNN class loss: 0.08472 FastRCNN total loss: 0.20857 L1 loss: 0.0000e+00 L2 loss: 1.56744 Learning rate: 0.02 Mask loss: 0.26299 RPN box loss: 0.07887 RPN score loss: 0.00823 RPN total loss: 0.0871 Total loss: 2.12609 timestamp: 1654923622.0903087 iteration: 10175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13552 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.21334 L1 loss: 0.0000e+00 L2 loss: 1.56716 Learning rate: 0.02 Mask loss: 0.14363 RPN box loss: 0.00816 RPN score loss: 0.01387 RPN total loss: 0.02203 Total loss: 1.94615 timestamp: 1654923625.2748003 iteration: 10180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18486 FastRCNN class loss: 0.09175 FastRCNN total loss: 0.27661 L1 loss: 0.0000e+00 L2 loss: 1.56689 Learning rate: 0.02 Mask loss: 0.18681 RPN box loss: 0.04126 RPN score loss: 0.01168 RPN total loss: 0.05294 Total loss: 2.08325 timestamp: 1654923628.6146777 iteration: 10185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12266 FastRCNN class loss: 0.14993 FastRCNN total loss: 0.27259 L1 loss: 0.0000e+00 L2 loss: 1.56658 Learning rate: 0.02 Mask loss: 0.20371 RPN box loss: 0.06046 RPN score loss: 0.02364 RPN total loss: 0.0841 Total loss: 2.12698 timestamp: 1654923631.8620818 iteration: 10190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15604 FastRCNN class loss: 0.10877 FastRCNN total loss: 0.2648 L1 loss: 0.0000e+00 L2 loss: 1.5663 Learning rate: 0.02 Mask loss: 0.16969 RPN box loss: 0.06315 RPN score loss: 0.00393 RPN total loss: 0.06709 Total loss: 2.06787 timestamp: 1654923635.1235697 iteration: 10195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15521 FastRCNN class loss: 0.11932 FastRCNN total loss: 0.27453 L1 loss: 0.0000e+00 L2 loss: 1.56602 Learning rate: 0.02 Mask loss: 0.28052 RPN box loss: 0.08636 RPN score loss: 0.00758 RPN total loss: 0.09394 Total loss: 2.21501 timestamp: 1654923638.4762032 iteration: 10200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21311 FastRCNN class loss: 0.11918 FastRCNN total loss: 0.33229 L1 loss: 0.0000e+00 L2 loss: 1.56574 Learning rate: 0.02 Mask loss: 0.1882 RPN box loss: 0.0835 RPN score loss: 0.00584 RPN total loss: 0.08934 Total loss: 2.17556 timestamp: 1654923641.7027829 iteration: 10205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11373 FastRCNN class loss: 0.11373 FastRCNN total loss: 0.22746 L1 loss: 0.0000e+00 L2 loss: 1.56547 Learning rate: 0.02 Mask loss: 0.15753 RPN box loss: 0.07276 RPN score loss: 0.00744 RPN total loss: 0.0802 Total loss: 2.03067 timestamp: 1654923645.0520194 iteration: 10210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18659 FastRCNN class loss: 0.10658 FastRCNN total loss: 0.29316 L1 loss: 0.0000e+00 L2 loss: 1.5652 Learning rate: 0.02 Mask loss: 0.27974 RPN box loss: 0.02372 RPN score loss: 0.00946 RPN total loss: 0.03319 Total loss: 2.17128 timestamp: 1654923648.2571597 iteration: 10215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15706 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.24655 L1 loss: 0.0000e+00 L2 loss: 1.5649 Learning rate: 0.02 Mask loss: 0.22577 RPN box loss: 0.02142 RPN score loss: 0.00568 RPN total loss: 0.0271 Total loss: 2.06433 timestamp: 1654923651.5930893 iteration: 10220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.05075 FastRCNN total loss: 0.13472 L1 loss: 0.0000e+00 L2 loss: 1.56461 Learning rate: 0.02 Mask loss: 0.11377 RPN box loss: 0.04367 RPN score loss: 0.0066 RPN total loss: 0.05027 Total loss: 1.86337 timestamp: 1654923654.907628 iteration: 10225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09795 FastRCNN class loss: 0.05404 FastRCNN total loss: 0.15199 L1 loss: 0.0000e+00 L2 loss: 1.56435 Learning rate: 0.02 Mask loss: 0.12201 RPN box loss: 0.02709 RPN score loss: 0.00732 RPN total loss: 0.03441 Total loss: 1.87275 timestamp: 1654923658.1737 iteration: 10230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17785 FastRCNN class loss: 0.09614 FastRCNN total loss: 0.27399 L1 loss: 0.0000e+00 L2 loss: 1.56407 Learning rate: 0.02 Mask loss: 0.27102 RPN box loss: 0.03071 RPN score loss: 0.0093 RPN total loss: 0.04001 Total loss: 2.14909 timestamp: 1654923661.3949382 iteration: 10235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16883 FastRCNN class loss: 0.06773 FastRCNN total loss: 0.23656 L1 loss: 0.0000e+00 L2 loss: 1.5638 Learning rate: 0.02 Mask loss: 0.13792 RPN box loss: 0.01564 RPN score loss: 0.00667 RPN total loss: 0.02231 Total loss: 1.9606 timestamp: 1654923664.6826787 iteration: 10240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12484 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.18823 L1 loss: 0.0000e+00 L2 loss: 1.56352 Learning rate: 0.02 Mask loss: 0.13727 RPN box loss: 0.02317 RPN score loss: 0.00785 RPN total loss: 0.03102 Total loss: 1.92004 timestamp: 1654923667.8973353 iteration: 10245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16751 FastRCNN class loss: 0.09068 FastRCNN total loss: 0.25819 L1 loss: 0.0000e+00 L2 loss: 1.56324 Learning rate: 0.02 Mask loss: 0.18279 RPN box loss: 0.0334 RPN score loss: 0.00978 RPN total loss: 0.04318 Total loss: 2.0474 timestamp: 1654923671.3877835 iteration: 10250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11386 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.1806 L1 loss: 0.0000e+00 L2 loss: 1.56295 Learning rate: 0.02 Mask loss: 0.12414 RPN box loss: 0.03223 RPN score loss: 0.00399 RPN total loss: 0.03621 Total loss: 1.90391 timestamp: 1654923674.5948324 iteration: 10255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17298 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.24403 L1 loss: 0.0000e+00 L2 loss: 1.56267 Learning rate: 0.02 Mask loss: 0.10976 RPN box loss: 0.00982 RPN score loss: 0.0048 RPN total loss: 0.01462 Total loss: 1.93108 timestamp: 1654923677.8628612 iteration: 10260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16115 FastRCNN class loss: 0.10412 FastRCNN total loss: 0.26528 L1 loss: 0.0000e+00 L2 loss: 1.56239 Learning rate: 0.02 Mask loss: 0.18384 RPN box loss: 0.00791 RPN score loss: 0.00259 RPN total loss: 0.0105 Total loss: 2.02201 timestamp: 1654923681.1411798 iteration: 10265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18182 FastRCNN class loss: 0.09508 FastRCNN total loss: 0.2769 L1 loss: 0.0000e+00 L2 loss: 1.5621 Learning rate: 0.02 Mask loss: 0.15402 RPN box loss: 0.05378 RPN score loss: 0.01082 RPN total loss: 0.0646 Total loss: 2.05762 timestamp: 1654923684.2957098 iteration: 10270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20444 FastRCNN class loss: 0.10832 FastRCNN total loss: 0.31276 L1 loss: 0.0000e+00 L2 loss: 1.56181 Learning rate: 0.02 Mask loss: 0.21201 RPN box loss: 0.01767 RPN score loss: 0.01089 RPN total loss: 0.02855 Total loss: 2.11513 timestamp: 1654923687.7263756 iteration: 10275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19487 FastRCNN class loss: 0.12856 FastRCNN total loss: 0.32343 L1 loss: 0.0000e+00 L2 loss: 1.56152 Learning rate: 0.02 Mask loss: 0.18621 RPN box loss: 0.04009 RPN score loss: 0.00422 RPN total loss: 0.04431 Total loss: 2.11547 timestamp: 1654923690.8970225 iteration: 10280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18398 FastRCNN class loss: 0.10001 FastRCNN total loss: 0.28399 L1 loss: 0.0000e+00 L2 loss: 1.56123 Learning rate: 0.02 Mask loss: 0.19466 RPN box loss: 0.01286 RPN score loss: 0.00298 RPN total loss: 0.01584 Total loss: 2.05572 timestamp: 1654923694.1994867 iteration: 10285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1506 FastRCNN class loss: 0.05378 FastRCNN total loss: 0.20438 L1 loss: 0.0000e+00 L2 loss: 1.56096 Learning rate: 0.02 Mask loss: 0.10349 RPN box loss: 0.04891 RPN score loss: 0.00782 RPN total loss: 0.05673 Total loss: 1.92557 timestamp: 1654923697.4557955 iteration: 10290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1244 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.2014 L1 loss: 0.0000e+00 L2 loss: 1.56069 Learning rate: 0.02 Mask loss: 0.14249 RPN box loss: 0.03644 RPN score loss: 0.00756 RPN total loss: 0.044 Total loss: 1.94858 timestamp: 1654923700.747111 iteration: 10295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11582 FastRCNN class loss: 0.07308 FastRCNN total loss: 0.1889 L1 loss: 0.0000e+00 L2 loss: 1.56041 Learning rate: 0.02 Mask loss: 0.15193 RPN box loss: 0.09806 RPN score loss: 0.01135 RPN total loss: 0.10941 Total loss: 2.01065 timestamp: 1654923704.1270316 iteration: 10300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20806 FastRCNN class loss: 0.12676 FastRCNN total loss: 0.33483 L1 loss: 0.0000e+00 L2 loss: 1.56014 Learning rate: 0.02 Mask loss: 0.19432 RPN box loss: 0.04359 RPN score loss: 0.00672 RPN total loss: 0.0503 Total loss: 2.13959 timestamp: 1654923707.286036 iteration: 10305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1796 FastRCNN class loss: 0.09084 FastRCNN total loss: 0.27044 L1 loss: 0.0000e+00 L2 loss: 1.55985 Learning rate: 0.02 Mask loss: 0.16687 RPN box loss: 0.01778 RPN score loss: 0.00965 RPN total loss: 0.02743 Total loss: 2.02459 timestamp: 1654923710.6041589 iteration: 10310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18116 FastRCNN class loss: 0.10507 FastRCNN total loss: 0.28623 L1 loss: 0.0000e+00 L2 loss: 1.55958 Learning rate: 0.02 Mask loss: 0.16112 RPN box loss: 0.04593 RPN score loss: 0.00476 RPN total loss: 0.05069 Total loss: 2.05762 timestamp: 1654923713.7755563 iteration: 10315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13168 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.19231 L1 loss: 0.0000e+00 L2 loss: 1.5593 Learning rate: 0.02 Mask loss: 0.18268 RPN box loss: 0.03927 RPN score loss: 0.0041 RPN total loss: 0.04337 Total loss: 1.97765 timestamp: 1654923717.116841 iteration: 10320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1618 FastRCNN class loss: 0.10234 FastRCNN total loss: 0.26414 L1 loss: 0.0000e+00 L2 loss: 1.55902 Learning rate: 0.02 Mask loss: 0.24383 RPN box loss: 0.02041 RPN score loss: 0.00321 RPN total loss: 0.02362 Total loss: 2.09062 timestamp: 1654923720.3365169 iteration: 10325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09705 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.15754 L1 loss: 0.0000e+00 L2 loss: 1.55875 Learning rate: 0.02 Mask loss: 0.13865 RPN box loss: 0.06721 RPN score loss: 0.00587 RPN total loss: 0.07308 Total loss: 1.92802 timestamp: 1654923723.732943 iteration: 10330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15478 FastRCNN class loss: 0.08062 FastRCNN total loss: 0.2354 L1 loss: 0.0000e+00 L2 loss: 1.55846 Learning rate: 0.02 Mask loss: 0.16189 RPN box loss: 0.0373 RPN score loss: 0.0064 RPN total loss: 0.0437 Total loss: 1.99946 timestamp: 1654923727.008946 iteration: 10335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1734 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.24696 L1 loss: 0.0000e+00 L2 loss: 1.55818 Learning rate: 0.02 Mask loss: 0.14806 RPN box loss: 0.05399 RPN score loss: 0.0283 RPN total loss: 0.08228 Total loss: 2.03548 timestamp: 1654923730.2390351 iteration: 10340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12666 FastRCNN class loss: 0.09309 FastRCNN total loss: 0.21975 L1 loss: 0.0000e+00 L2 loss: 1.55789 Learning rate: 0.02 Mask loss: 0.23528 RPN box loss: 0.0374 RPN score loss: 0.00374 RPN total loss: 0.04114 Total loss: 2.05405 timestamp: 1654923733.5724008 iteration: 10345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12952 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.1965 L1 loss: 0.0000e+00 L2 loss: 1.5576 Learning rate: 0.02 Mask loss: 0.1573 RPN box loss: 0.01114 RPN score loss: 0.00939 RPN total loss: 0.02052 Total loss: 1.93192 timestamp: 1654923736.754912 iteration: 10350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19069 FastRCNN class loss: 0.12917 FastRCNN total loss: 0.31986 L1 loss: 0.0000e+00 L2 loss: 1.55732 Learning rate: 0.02 Mask loss: 0.24481 RPN box loss: 0.04408 RPN score loss: 0.03981 RPN total loss: 0.08389 Total loss: 2.20587 timestamp: 1654923740.0159457 iteration: 10355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18301 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.25246 L1 loss: 0.0000e+00 L2 loss: 1.55703 Learning rate: 0.02 Mask loss: 0.12699 RPN box loss: 0.0364 RPN score loss: 0.00783 RPN total loss: 0.04423 Total loss: 1.98071 timestamp: 1654923743.1967952 iteration: 10360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18398 FastRCNN class loss: 0.14977 FastRCNN total loss: 0.33375 L1 loss: 0.0000e+00 L2 loss: 1.55675 Learning rate: 0.02 Mask loss: 0.20787 RPN box loss: 0.05042 RPN score loss: 0.0102 RPN total loss: 0.06062 Total loss: 2.159 timestamp: 1654923746.4701366 iteration: 10365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12223 FastRCNN class loss: 0.08378 FastRCNN total loss: 0.20601 L1 loss: 0.0000e+00 L2 loss: 1.55647 Learning rate: 0.02 Mask loss: 0.1315 RPN box loss: 0.03863 RPN score loss: 0.00894 RPN total loss: 0.04757 Total loss: 1.94156 timestamp: 1654923749.7596223 iteration: 10370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15276 FastRCNN class loss: 0.09674 FastRCNN total loss: 0.24949 L1 loss: 0.0000e+00 L2 loss: 1.55619 Learning rate: 0.02 Mask loss: 0.13437 RPN box loss: 0.02913 RPN score loss: 0.0027 RPN total loss: 0.03183 Total loss: 1.97188 timestamp: 1654923753.1702657 iteration: 10375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13018 FastRCNN class loss: 0.09781 FastRCNN total loss: 0.22799 L1 loss: 0.0000e+00 L2 loss: 1.55593 Learning rate: 0.02 Mask loss: 0.27373 RPN box loss: 0.03429 RPN score loss: 0.00471 RPN total loss: 0.03901 Total loss: 2.09665 timestamp: 1654923756.2887063 iteration: 10380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13403 FastRCNN class loss: 0.13005 FastRCNN total loss: 0.26408 L1 loss: 0.0000e+00 L2 loss: 1.55566 Learning rate: 0.02 Mask loss: 0.23264 RPN box loss: 0.02747 RPN score loss: 0.00791 RPN total loss: 0.03538 Total loss: 2.08776 timestamp: 1654923759.62911 iteration: 10385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33296 FastRCNN class loss: 0.17007 FastRCNN total loss: 0.50303 L1 loss: 0.0000e+00 L2 loss: 1.55537 Learning rate: 0.02 Mask loss: 0.23136 RPN box loss: 0.07279 RPN score loss: 0.0523 RPN total loss: 0.12509 Total loss: 2.41485 timestamp: 1654923762.7498953 iteration: 10390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13444 FastRCNN class loss: 0.06728 FastRCNN total loss: 0.20173 L1 loss: 0.0000e+00 L2 loss: 1.55508 Learning rate: 0.02 Mask loss: 0.29546 RPN box loss: 0.01856 RPN score loss: 0.00431 RPN total loss: 0.02287 Total loss: 2.07513 timestamp: 1654923766.1067326 iteration: 10395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16911 FastRCNN class loss: 0.15428 FastRCNN total loss: 0.32339 L1 loss: 0.0000e+00 L2 loss: 1.55481 Learning rate: 0.02 Mask loss: 0.15757 RPN box loss: 0.04147 RPN score loss: 0.00915 RPN total loss: 0.05062 Total loss: 2.08638 timestamp: 1654923769.3695543 iteration: 10400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1164 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.18579 L1 loss: 0.0000e+00 L2 loss: 1.55453 Learning rate: 0.02 Mask loss: 0.14043 RPN box loss: 0.00789 RPN score loss: 0.00423 RPN total loss: 0.01212 Total loss: 1.89287 timestamp: 1654923772.59667 iteration: 10405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12295 FastRCNN class loss: 0.07717 FastRCNN total loss: 0.20012 L1 loss: 0.0000e+00 L2 loss: 1.55425 Learning rate: 0.02 Mask loss: 0.14134 RPN box loss: 0.00952 RPN score loss: 0.00518 RPN total loss: 0.0147 Total loss: 1.91041 timestamp: 1654923775.8082886 iteration: 10410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24103 FastRCNN class loss: 0.14503 FastRCNN total loss: 0.38606 L1 loss: 0.0000e+00 L2 loss: 1.55397 Learning rate: 0.02 Mask loss: 0.15931 RPN box loss: 0.0267 RPN score loss: 0.00753 RPN total loss: 0.03424 Total loss: 2.13358 timestamp: 1654923779.0209157 iteration: 10415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1528 FastRCNN class loss: 0.09268 FastRCNN total loss: 0.24548 L1 loss: 0.0000e+00 L2 loss: 1.55369 Learning rate: 0.02 Mask loss: 0.14169 RPN box loss: 0.02744 RPN score loss: 0.00728 RPN total loss: 0.03472 Total loss: 1.97558 timestamp: 1654923782.3667133 iteration: 10420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10467 FastRCNN class loss: 0.05548 FastRCNN total loss: 0.16016 L1 loss: 0.0000e+00 L2 loss: 1.5534 Learning rate: 0.02 Mask loss: 0.1729 RPN box loss: 0.03913 RPN score loss: 0.00678 RPN total loss: 0.04591 Total loss: 1.93236 timestamp: 1654923785.4918115 iteration: 10425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16228 FastRCNN class loss: 0.08806 FastRCNN total loss: 0.25034 L1 loss: 0.0000e+00 L2 loss: 1.55312 Learning rate: 0.02 Mask loss: 0.23821 RPN box loss: 0.08035 RPN score loss: 0.01154 RPN total loss: 0.0919 Total loss: 2.13357 timestamp: 1654923788.7748644 iteration: 10430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24788 FastRCNN class loss: 0.11316 FastRCNN total loss: 0.36104 L1 loss: 0.0000e+00 L2 loss: 1.55285 Learning rate: 0.02 Mask loss: 0.21317 RPN box loss: 0.03766 RPN score loss: 0.00468 RPN total loss: 0.04234 Total loss: 2.1694 timestamp: 1654923791.9448147 iteration: 10435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15874 FastRCNN class loss: 0.10996 FastRCNN total loss: 0.2687 L1 loss: 0.0000e+00 L2 loss: 1.55256 Learning rate: 0.02 Mask loss: 0.24749 RPN box loss: 0.04443 RPN score loss: 0.01262 RPN total loss: 0.05706 Total loss: 2.12581 timestamp: 1654923795.24403 iteration: 10440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17228 FastRCNN class loss: 0.06865 FastRCNN total loss: 0.24093 L1 loss: 0.0000e+00 L2 loss: 1.55229 Learning rate: 0.02 Mask loss: 0.20311 RPN box loss: 0.03182 RPN score loss: 0.00471 RPN total loss: 0.03652 Total loss: 2.03285 timestamp: 1654923798.3975883 iteration: 10445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14215 FastRCNN class loss: 0.08424 FastRCNN total loss: 0.22639 L1 loss: 0.0000e+00 L2 loss: 1.55201 Learning rate: 0.02 Mask loss: 0.15863 RPN box loss: 0.03875 RPN score loss: 0.0059 RPN total loss: 0.04465 Total loss: 1.98168 timestamp: 1654923801.7241762 iteration: 10450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14325 FastRCNN class loss: 0.09509 FastRCNN total loss: 0.23834 L1 loss: 0.0000e+00 L2 loss: 1.55172 Learning rate: 0.02 Mask loss: 0.20773 RPN box loss: 0.01812 RPN score loss: 0.00931 RPN total loss: 0.02743 Total loss: 2.02522 timestamp: 1654923804.872034 iteration: 10455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23785 FastRCNN class loss: 0.1938 FastRCNN total loss: 0.43165 L1 loss: 0.0000e+00 L2 loss: 1.55143 Learning rate: 0.02 Mask loss: 0.2102 RPN box loss: 0.05923 RPN score loss: 0.01353 RPN total loss: 0.07276 Total loss: 2.26604 timestamp: 1654923808.1075366 iteration: 10460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14984 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.23119 L1 loss: 0.0000e+00 L2 loss: 1.55114 Learning rate: 0.02 Mask loss: 0.17128 RPN box loss: 0.08284 RPN score loss: 0.00878 RPN total loss: 0.09162 Total loss: 2.04523 timestamp: 1654923811.3291872 iteration: 10465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17303 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.23449 L1 loss: 0.0000e+00 L2 loss: 1.55087 Learning rate: 0.02 Mask loss: 0.1362 RPN box loss: 0.0038 RPN score loss: 0.00312 RPN total loss: 0.00692 Total loss: 1.92848 timestamp: 1654923814.6124098 iteration: 10470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13355 FastRCNN class loss: 0.11894 FastRCNN total loss: 0.25249 L1 loss: 0.0000e+00 L2 loss: 1.55061 Learning rate: 0.02 Mask loss: 0.18366 RPN box loss: 0.0687 RPN score loss: 0.0161 RPN total loss: 0.0848 Total loss: 2.07157 timestamp: 1654923817.9311504 iteration: 10475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21584 FastRCNN class loss: 0.10134 FastRCNN total loss: 0.31717 L1 loss: 0.0000e+00 L2 loss: 1.55034 Learning rate: 0.02 Mask loss: 0.18031 RPN box loss: 0.02253 RPN score loss: 0.00683 RPN total loss: 0.02937 Total loss: 2.07719 timestamp: 1654923821.200279 iteration: 10480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1805 FastRCNN class loss: 0.15055 FastRCNN total loss: 0.33105 L1 loss: 0.0000e+00 L2 loss: 1.55007 Learning rate: 0.02 Mask loss: 0.17223 RPN box loss: 0.04839 RPN score loss: 0.00512 RPN total loss: 0.05351 Total loss: 2.10685 timestamp: 1654923824.4761047 iteration: 10485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1382 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.21345 L1 loss: 0.0000e+00 L2 loss: 1.54978 Learning rate: 0.02 Mask loss: 0.14998 RPN box loss: 0.03839 RPN score loss: 0.016 RPN total loss: 0.0544 Total loss: 1.96761 timestamp: 1654923827.739146 iteration: 10490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10563 FastRCNN class loss: 0.0712 FastRCNN total loss: 0.17683 L1 loss: 0.0000e+00 L2 loss: 1.54949 Learning rate: 0.02 Mask loss: 0.17711 RPN box loss: 0.03775 RPN score loss: 0.00954 RPN total loss: 0.04729 Total loss: 1.95072 timestamp: 1654923831.0294912 iteration: 10495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19125 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.28455 L1 loss: 0.0000e+00 L2 loss: 1.54922 Learning rate: 0.02 Mask loss: 0.17941 RPN box loss: 0.03785 RPN score loss: 0.00479 RPN total loss: 0.04264 Total loss: 2.05583 timestamp: 1654923834.2184355 iteration: 10500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20525 FastRCNN class loss: 0.09818 FastRCNN total loss: 0.30343 L1 loss: 0.0000e+00 L2 loss: 1.54895 Learning rate: 0.02 Mask loss: 0.16918 RPN box loss: 0.02068 RPN score loss: 0.00358 RPN total loss: 0.02427 Total loss: 2.04582 timestamp: 1654923837.4416409 iteration: 10505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11147 FastRCNN class loss: 0.05112 FastRCNN total loss: 0.16259 L1 loss: 0.0000e+00 L2 loss: 1.54867 Learning rate: 0.02 Mask loss: 0.15896 RPN box loss: 0.00421 RPN score loss: 0.00454 RPN total loss: 0.00875 Total loss: 1.87897 timestamp: 1654923840.678375 iteration: 10510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15696 FastRCNN class loss: 0.10703 FastRCNN total loss: 0.26399 L1 loss: 0.0000e+00 L2 loss: 1.5484 Learning rate: 0.02 Mask loss: 0.1623 RPN box loss: 0.01531 RPN score loss: 0.00473 RPN total loss: 0.02004 Total loss: 1.99473 timestamp: 1654923843.9653137 iteration: 10515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17162 FastRCNN class loss: 0.10787 FastRCNN total loss: 0.27949 L1 loss: 0.0000e+00 L2 loss: 1.54811 Learning rate: 0.02 Mask loss: 0.17472 RPN box loss: 0.03514 RPN score loss: 0.0056 RPN total loss: 0.04075 Total loss: 2.04307 timestamp: 1654923847.2698767 iteration: 10520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0943 FastRCNN class loss: 0.04658 FastRCNN total loss: 0.14088 L1 loss: 0.0000e+00 L2 loss: 1.54782 Learning rate: 0.02 Mask loss: 0.1554 RPN box loss: 0.02321 RPN score loss: 0.0063 RPN total loss: 0.02951 Total loss: 1.87361 timestamp: 1654923850.4420595 iteration: 10525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16829 FastRCNN class loss: 0.07878 FastRCNN total loss: 0.24706 L1 loss: 0.0000e+00 L2 loss: 1.54752 Learning rate: 0.02 Mask loss: 0.14359 RPN box loss: 0.06773 RPN score loss: 0.00762 RPN total loss: 0.07535 Total loss: 2.01352 timestamp: 1654923853.6887884 iteration: 10530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10889 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.18446 L1 loss: 0.0000e+00 L2 loss: 1.54726 Learning rate: 0.02 Mask loss: 0.2098 RPN box loss: 0.04957 RPN score loss: 0.00744 RPN total loss: 0.05701 Total loss: 1.99853 timestamp: 1654923856.969155 iteration: 10535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15225 FastRCNN class loss: 0.08535 FastRCNN total loss: 0.2376 L1 loss: 0.0000e+00 L2 loss: 1.54701 Learning rate: 0.02 Mask loss: 0.16279 RPN box loss: 0.02727 RPN score loss: 0.00765 RPN total loss: 0.03492 Total loss: 1.98232 timestamp: 1654923860.396386 iteration: 10540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09159 FastRCNN class loss: 0.05625 FastRCNN total loss: 0.14784 L1 loss: 0.0000e+00 L2 loss: 1.54675 Learning rate: 0.02 Mask loss: 0.08049 RPN box loss: 0.01114 RPN score loss: 0.00212 RPN total loss: 0.01325 Total loss: 1.78833 timestamp: 1654923863.6735692 iteration: 10545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25096 FastRCNN class loss: 0.11736 FastRCNN total loss: 0.36833 L1 loss: 0.0000e+00 L2 loss: 1.54648 Learning rate: 0.02 Mask loss: 0.18889 RPN box loss: 0.07076 RPN score loss: 0.02068 RPN total loss: 0.09143 Total loss: 2.19513 timestamp: 1654923867.0833144 iteration: 10550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17271 FastRCNN class loss: 0.11735 FastRCNN total loss: 0.29006 L1 loss: 0.0000e+00 L2 loss: 1.54622 Learning rate: 0.02 Mask loss: 0.20633 RPN box loss: 0.02851 RPN score loss: 0.01639 RPN total loss: 0.0449 Total loss: 2.08751 timestamp: 1654923870.2769094 iteration: 10555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11946 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.18901 L1 loss: 0.0000e+00 L2 loss: 1.54593 Learning rate: 0.02 Mask loss: 0.16428 RPN box loss: 0.03324 RPN score loss: 0.01011 RPN total loss: 0.04334 Total loss: 1.94256 timestamp: 1654923873.5361023 iteration: 10560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2443 FastRCNN class loss: 0.12858 FastRCNN total loss: 0.37287 L1 loss: 0.0000e+00 L2 loss: 1.54566 Learning rate: 0.02 Mask loss: 0.26357 RPN box loss: 0.0278 RPN score loss: 0.0193 RPN total loss: 0.0471 Total loss: 2.2292 timestamp: 1654923876.8014758 iteration: 10565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1019 FastRCNN class loss: 0.08558 FastRCNN total loss: 0.18748 L1 loss: 0.0000e+00 L2 loss: 1.54539 Learning rate: 0.02 Mask loss: 0.19215 RPN box loss: 0.02024 RPN score loss: 0.00433 RPN total loss: 0.02457 Total loss: 1.94958 timestamp: 1654923880.043141 iteration: 10570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16908 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.26601 L1 loss: 0.0000e+00 L2 loss: 1.5451 Learning rate: 0.02 Mask loss: 0.30719 RPN box loss: 0.03063 RPN score loss: 0.00796 RPN total loss: 0.03858 Total loss: 2.15689 timestamp: 1654923883.3007746 iteration: 10575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13502 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.20307 L1 loss: 0.0000e+00 L2 loss: 1.5448 Learning rate: 0.02 Mask loss: 0.17736 RPN box loss: 0.05084 RPN score loss: 0.00287 RPN total loss: 0.05371 Total loss: 1.97894 timestamp: 1654923886.549807 iteration: 10580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15887 FastRCNN class loss: 0.13105 FastRCNN total loss: 0.28992 L1 loss: 0.0000e+00 L2 loss: 1.54452 Learning rate: 0.02 Mask loss: 0.14499 RPN box loss: 0.02043 RPN score loss: 0.00879 RPN total loss: 0.02922 Total loss: 2.00865 timestamp: 1654923889.888966 iteration: 10585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22564 FastRCNN class loss: 0.14593 FastRCNN total loss: 0.37157 L1 loss: 0.0000e+00 L2 loss: 1.54424 Learning rate: 0.02 Mask loss: 0.31855 RPN box loss: 0.01345 RPN score loss: 0.01098 RPN total loss: 0.02444 Total loss: 2.2588 timestamp: 1654923893.1719859 iteration: 10590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17267 FastRCNN class loss: 0.0888 FastRCNN total loss: 0.26147 L1 loss: 0.0000e+00 L2 loss: 1.54395 Learning rate: 0.02 Mask loss: 0.19956 RPN box loss: 0.01963 RPN score loss: 0.00638 RPN total loss: 0.02601 Total loss: 2.03099 timestamp: 1654923896.473208 iteration: 10595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17465 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.26042 L1 loss: 0.0000e+00 L2 loss: 1.5437 Learning rate: 0.02 Mask loss: 0.152 RPN box loss: 0.05107 RPN score loss: 0.01129 RPN total loss: 0.06237 Total loss: 2.01849 timestamp: 1654923899.6644802 iteration: 10600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25972 FastRCNN class loss: 0.09791 FastRCNN total loss: 0.35763 L1 loss: 0.0000e+00 L2 loss: 1.54341 Learning rate: 0.02 Mask loss: 0.14112 RPN box loss: 0.07104 RPN score loss: 0.00974 RPN total loss: 0.08078 Total loss: 2.12294 timestamp: 1654923902.9481282 iteration: 10605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21549 FastRCNN class loss: 0.08398 FastRCNN total loss: 0.29947 L1 loss: 0.0000e+00 L2 loss: 1.54312 Learning rate: 0.02 Mask loss: 0.13068 RPN box loss: 0.04625 RPN score loss: 0.00913 RPN total loss: 0.05538 Total loss: 2.02865 timestamp: 1654923906.1225076 iteration: 10610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16579 FastRCNN class loss: 0.0812 FastRCNN total loss: 0.24699 L1 loss: 0.0000e+00 L2 loss: 1.54285 Learning rate: 0.02 Mask loss: 0.13554 RPN box loss: 0.05637 RPN score loss: 0.01071 RPN total loss: 0.06708 Total loss: 1.99246 timestamp: 1654923909.4437528 iteration: 10615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17402 FastRCNN class loss: 0.10018 FastRCNN total loss: 0.2742 L1 loss: 0.0000e+00 L2 loss: 1.54258 Learning rate: 0.02 Mask loss: 0.19785 RPN box loss: 0.05249 RPN score loss: 0.00853 RPN total loss: 0.06102 Total loss: 2.07565 timestamp: 1654923912.7564895 iteration: 10620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16125 FastRCNN class loss: 0.10114 FastRCNN total loss: 0.26239 L1 loss: 0.0000e+00 L2 loss: 1.54231 Learning rate: 0.02 Mask loss: 0.19335 RPN box loss: 0.01526 RPN score loss: 0.00466 RPN total loss: 0.01992 Total loss: 2.01798 timestamp: 1654923916.0079477 iteration: 10625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16704 FastRCNN class loss: 0.09073 FastRCNN total loss: 0.25777 L1 loss: 0.0000e+00 L2 loss: 1.54204 Learning rate: 0.02 Mask loss: 0.18778 RPN box loss: 0.02507 RPN score loss: 0.00715 RPN total loss: 0.03222 Total loss: 2.01981 timestamp: 1654923919.4193625 iteration: 10630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11596 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.17744 L1 loss: 0.0000e+00 L2 loss: 1.54175 Learning rate: 0.02 Mask loss: 0.12362 RPN box loss: 0.04354 RPN score loss: 0.01771 RPN total loss: 0.06125 Total loss: 1.90406 timestamp: 1654923922.6336007 iteration: 10635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13424 FastRCNN class loss: 0.07695 FastRCNN total loss: 0.21119 L1 loss: 0.0000e+00 L2 loss: 1.54147 Learning rate: 0.02 Mask loss: 0.14295 RPN box loss: 0.01637 RPN score loss: 0.00205 RPN total loss: 0.01841 Total loss: 1.91402 timestamp: 1654923925.8477113 iteration: 10640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21762 FastRCNN class loss: 0.12545 FastRCNN total loss: 0.34307 L1 loss: 0.0000e+00 L2 loss: 1.5412 Learning rate: 0.02 Mask loss: 0.19514 RPN box loss: 0.06235 RPN score loss: 0.00737 RPN total loss: 0.06972 Total loss: 2.14913 timestamp: 1654923929.0522866 iteration: 10645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23071 FastRCNN class loss: 0.10964 FastRCNN total loss: 0.34035 L1 loss: 0.0000e+00 L2 loss: 1.54094 Learning rate: 0.02 Mask loss: 0.18295 RPN box loss: 0.0408 RPN score loss: 0.00419 RPN total loss: 0.04499 Total loss: 2.10924 timestamp: 1654923932.2704778 iteration: 10650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11966 FastRCNN class loss: 0.07389 FastRCNN total loss: 0.19354 L1 loss: 0.0000e+00 L2 loss: 1.54067 Learning rate: 0.02 Mask loss: 0.16436 RPN box loss: 0.06494 RPN score loss: 0.00985 RPN total loss: 0.07479 Total loss: 1.97337 timestamp: 1654923935.4959102 iteration: 10655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13331 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.21826 L1 loss: 0.0000e+00 L2 loss: 1.5404 Learning rate: 0.02 Mask loss: 0.17834 RPN box loss: 0.02754 RPN score loss: 0.0016 RPN total loss: 0.02914 Total loss: 1.96613 timestamp: 1654923938.8448818 iteration: 10660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16825 FastRCNN class loss: 0.12014 FastRCNN total loss: 0.28839 L1 loss: 0.0000e+00 L2 loss: 1.54015 Learning rate: 0.02 Mask loss: 0.29254 RPN box loss: 0.11862 RPN score loss: 0.00661 RPN total loss: 0.12523 Total loss: 2.24631 timestamp: 1654923942.1652853 iteration: 10665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13603 FastRCNN class loss: 0.07477 FastRCNN total loss: 0.21079 L1 loss: 0.0000e+00 L2 loss: 1.53986 Learning rate: 0.02 Mask loss: 0.17678 RPN box loss: 0.01567 RPN score loss: 0.00754 RPN total loss: 0.02321 Total loss: 1.95065 timestamp: 1654923945.4156754 iteration: 10670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17232 FastRCNN class loss: 0.11954 FastRCNN total loss: 0.29186 L1 loss: 0.0000e+00 L2 loss: 1.53958 Learning rate: 0.02 Mask loss: 0.1957 RPN box loss: 0.03073 RPN score loss: 0.00619 RPN total loss: 0.03693 Total loss: 2.06407 timestamp: 1654923948.6614451 iteration: 10675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16785 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.22854 L1 loss: 0.0000e+00 L2 loss: 1.53931 Learning rate: 0.02 Mask loss: 0.17554 RPN box loss: 0.00628 RPN score loss: 0.0028 RPN total loss: 0.00908 Total loss: 1.95247 timestamp: 1654923951.862502 iteration: 10680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25815 FastRCNN class loss: 0.07514 FastRCNN total loss: 0.33329 L1 loss: 0.0000e+00 L2 loss: 1.53904 Learning rate: 0.02 Mask loss: 0.11346 RPN box loss: 0.05533 RPN score loss: 0.00859 RPN total loss: 0.06392 Total loss: 2.0497 timestamp: 1654923955.1868253 iteration: 10685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18407 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.2686 L1 loss: 0.0000e+00 L2 loss: 1.53875 Learning rate: 0.02 Mask loss: 0.20471 RPN box loss: 0.06411 RPN score loss: 0.00771 RPN total loss: 0.07182 Total loss: 2.08388 timestamp: 1654923958.444499 iteration: 10690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22076 FastRCNN class loss: 0.13548 FastRCNN total loss: 0.35625 L1 loss: 0.0000e+00 L2 loss: 1.53847 Learning rate: 0.02 Mask loss: 0.25439 RPN box loss: 0.03397 RPN score loss: 0.00774 RPN total loss: 0.04171 Total loss: 2.19082 timestamp: 1654923961.808757 iteration: 10695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21012 FastRCNN class loss: 0.14352 FastRCNN total loss: 0.35365 L1 loss: 0.0000e+00 L2 loss: 1.53821 Learning rate: 0.02 Mask loss: 0.32934 RPN box loss: 0.06978 RPN score loss: 0.00863 RPN total loss: 0.07841 Total loss: 2.29961 timestamp: 1654923964.9693985 iteration: 10700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21835 FastRCNN class loss: 0.0909 FastRCNN total loss: 0.30924 L1 loss: 0.0000e+00 L2 loss: 1.5379 Learning rate: 0.02 Mask loss: 0.19231 RPN box loss: 0.04127 RPN score loss: 0.0099 RPN total loss: 0.05117 Total loss: 2.09062 timestamp: 1654923968.284369 iteration: 10705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12999 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.18927 L1 loss: 0.0000e+00 L2 loss: 1.53763 Learning rate: 0.02 Mask loss: 0.10115 RPN box loss: 0.00682 RPN score loss: 0.00199 RPN total loss: 0.0088 Total loss: 1.83686 timestamp: 1654923971.5838337 iteration: 10710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09675 FastRCNN class loss: 0.05867 FastRCNN total loss: 0.15542 L1 loss: 0.0000e+00 L2 loss: 1.53736 Learning rate: 0.02 Mask loss: 0.14438 RPN box loss: 0.00984 RPN score loss: 0.00254 RPN total loss: 0.01238 Total loss: 1.84955 timestamp: 1654923974.7308328 iteration: 10715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12976 FastRCNN class loss: 0.06236 FastRCNN total loss: 0.19213 L1 loss: 0.0000e+00 L2 loss: 1.53711 Learning rate: 0.02 Mask loss: 0.12787 RPN box loss: 0.02735 RPN score loss: 0.00323 RPN total loss: 0.03058 Total loss: 1.88769 timestamp: 1654923978.0321376 iteration: 10720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27862 FastRCNN class loss: 0.09464 FastRCNN total loss: 0.37327 L1 loss: 0.0000e+00 L2 loss: 1.53685 Learning rate: 0.02 Mask loss: 0.12407 RPN box loss: 0.06232 RPN score loss: 0.0161 RPN total loss: 0.07843 Total loss: 2.11262 timestamp: 1654923981.2786975 iteration: 10725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09687 FastRCNN class loss: 0.0556 FastRCNN total loss: 0.15247 L1 loss: 0.0000e+00 L2 loss: 1.53656 Learning rate: 0.02 Mask loss: 0.1538 RPN box loss: 0.02 RPN score loss: 0.00639 RPN total loss: 0.02639 Total loss: 1.86922 timestamp: 1654923984.6592603 iteration: 10730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13364 FastRCNN class loss: 0.06424 FastRCNN total loss: 0.19788 L1 loss: 0.0000e+00 L2 loss: 1.53627 Learning rate: 0.02 Mask loss: 0.15476 RPN box loss: 0.04832 RPN score loss: 0.00742 RPN total loss: 0.05573 Total loss: 1.94463 timestamp: 1654923987.890934 iteration: 10735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15487 FastRCNN class loss: 0.10464 FastRCNN total loss: 0.25952 L1 loss: 0.0000e+00 L2 loss: 1.536 Learning rate: 0.02 Mask loss: 0.12898 RPN box loss: 0.03604 RPN score loss: 0.00435 RPN total loss: 0.04039 Total loss: 1.96489 timestamp: 1654923991.151673 iteration: 10740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11063 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.17536 L1 loss: 0.0000e+00 L2 loss: 1.53573 Learning rate: 0.02 Mask loss: 0.12116 RPN box loss: 0.01308 RPN score loss: 0.00339 RPN total loss: 0.01648 Total loss: 1.84873 timestamp: 1654923994.2776015 iteration: 10745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14977 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.2228 L1 loss: 0.0000e+00 L2 loss: 1.53546 Learning rate: 0.02 Mask loss: 0.20659 RPN box loss: 0.02438 RPN score loss: 0.0034 RPN total loss: 0.02778 Total loss: 1.99263 timestamp: 1654923997.5697656 iteration: 10750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23004 FastRCNN class loss: 0.12233 FastRCNN total loss: 0.35237 L1 loss: 0.0000e+00 L2 loss: 1.53519 Learning rate: 0.02 Mask loss: 0.17298 RPN box loss: 0.06197 RPN score loss: 0.01917 RPN total loss: 0.08114 Total loss: 2.14168 timestamp: 1654924000.7102675 iteration: 10755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15074 FastRCNN class loss: 0.13443 FastRCNN total loss: 0.28517 L1 loss: 0.0000e+00 L2 loss: 1.53491 Learning rate: 0.02 Mask loss: 0.18578 RPN box loss: 0.02908 RPN score loss: 0.01097 RPN total loss: 0.04005 Total loss: 2.04591 timestamp: 1654924003.980616 iteration: 10760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18006 FastRCNN class loss: 0.07874 FastRCNN total loss: 0.2588 L1 loss: 0.0000e+00 L2 loss: 1.53462 Learning rate: 0.02 Mask loss: 0.1534 RPN box loss: 0.03202 RPN score loss: 0.00363 RPN total loss: 0.03565 Total loss: 1.98246 timestamp: 1654924007.3147326 iteration: 10765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23491 FastRCNN class loss: 0.09237 FastRCNN total loss: 0.32728 L1 loss: 0.0000e+00 L2 loss: 1.53434 Learning rate: 0.02 Mask loss: 0.20082 RPN box loss: 0.02562 RPN score loss: 0.01086 RPN total loss: 0.03648 Total loss: 2.09891 timestamp: 1654924010.6723516 iteration: 10770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21774 FastRCNN class loss: 0.11297 FastRCNN total loss: 0.33071 L1 loss: 0.0000e+00 L2 loss: 1.53406 Learning rate: 0.02 Mask loss: 0.19686 RPN box loss: 0.03436 RPN score loss: 0.00472 RPN total loss: 0.03908 Total loss: 2.1007 timestamp: 1654924014.0118577 iteration: 10775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12312 FastRCNN class loss: 0.0792 FastRCNN total loss: 0.20232 L1 loss: 0.0000e+00 L2 loss: 1.53378 Learning rate: 0.02 Mask loss: 0.13873 RPN box loss: 0.0463 RPN score loss: 0.00672 RPN total loss: 0.05302 Total loss: 1.92786 timestamp: 1654924017.2526567 iteration: 10780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0693 FastRCNN class loss: 0.05525 FastRCNN total loss: 0.12454 L1 loss: 0.0000e+00 L2 loss: 1.53349 Learning rate: 0.02 Mask loss: 0.22927 RPN box loss: 0.00903 RPN score loss: 0.00553 RPN total loss: 0.01455 Total loss: 1.90185 timestamp: 1654924020.5720475 iteration: 10785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17134 FastRCNN class loss: 0.08744 FastRCNN total loss: 0.25878 L1 loss: 0.0000e+00 L2 loss: 1.53322 Learning rate: 0.02 Mask loss: 0.18231 RPN box loss: 0.06125 RPN score loss: 0.01213 RPN total loss: 0.07338 Total loss: 2.04769 timestamp: 1654924023.7612684 iteration: 10790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10976 FastRCNN class loss: 0.11039 FastRCNN total loss: 0.22015 L1 loss: 0.0000e+00 L2 loss: 1.53295 Learning rate: 0.02 Mask loss: 0.14253 RPN box loss: 0.03139 RPN score loss: 0.00615 RPN total loss: 0.03754 Total loss: 1.93317 timestamp: 1654924027.0113864 iteration: 10795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08275 FastRCNN class loss: 0.07926 FastRCNN total loss: 0.16201 L1 loss: 0.0000e+00 L2 loss: 1.53268 Learning rate: 0.02 Mask loss: 0.15106 RPN box loss: 0.0482 RPN score loss: 0.00393 RPN total loss: 0.05213 Total loss: 1.89789 timestamp: 1654924030.2031746 iteration: 10800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27587 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.35335 L1 loss: 0.0000e+00 L2 loss: 1.5324 Learning rate: 0.02 Mask loss: 0.18173 RPN box loss: 0.03328 RPN score loss: 0.00557 RPN total loss: 0.03885 Total loss: 2.10633 timestamp: 1654924033.4798932 iteration: 10805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20971 FastRCNN class loss: 0.09526 FastRCNN total loss: 0.30498 L1 loss: 0.0000e+00 L2 loss: 1.53214 Learning rate: 0.02 Mask loss: 0.24238 RPN box loss: 0.08239 RPN score loss: 0.00708 RPN total loss: 0.08946 Total loss: 2.16896 timestamp: 1654924036.7658162 iteration: 10810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13109 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.17852 L1 loss: 0.0000e+00 L2 loss: 1.53186 Learning rate: 0.02 Mask loss: 0.19228 RPN box loss: 0.00657 RPN score loss: 0.00246 RPN total loss: 0.00903 Total loss: 1.91169 timestamp: 1654924040.0170567 iteration: 10815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13862 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.2271 L1 loss: 0.0000e+00 L2 loss: 1.53156 Learning rate: 0.02 Mask loss: 0.23084 RPN box loss: 0.09385 RPN score loss: 0.01013 RPN total loss: 0.10398 Total loss: 2.09347 timestamp: 1654924043.3737211 iteration: 10820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20112 FastRCNN class loss: 0.13485 FastRCNN total loss: 0.33597 L1 loss: 0.0000e+00 L2 loss: 1.53129 Learning rate: 0.02 Mask loss: 0.20432 RPN box loss: 0.01476 RPN score loss: 0.00736 RPN total loss: 0.02212 Total loss: 2.09369 timestamp: 1654924046.6003463 iteration: 10825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15826 FastRCNN class loss: 0.10894 FastRCNN total loss: 0.2672 L1 loss: 0.0000e+00 L2 loss: 1.53101 Learning rate: 0.02 Mask loss: 0.23343 RPN box loss: 0.02736 RPN score loss: 0.01057 RPN total loss: 0.03794 Total loss: 2.06958 timestamp: 1654924049.8398912 iteration: 10830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16317 FastRCNN class loss: 0.13455 FastRCNN total loss: 0.29773 L1 loss: 0.0000e+00 L2 loss: 1.53071 Learning rate: 0.02 Mask loss: 0.18155 RPN box loss: 0.01811 RPN score loss: 0.00594 RPN total loss: 0.02405 Total loss: 2.03403 timestamp: 1654924053.0955772 iteration: 10835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11841 FastRCNN class loss: 0.12042 FastRCNN total loss: 0.23883 L1 loss: 0.0000e+00 L2 loss: 1.53043 Learning rate: 0.02 Mask loss: 0.12139 RPN box loss: 0.04275 RPN score loss: 0.00962 RPN total loss: 0.05237 Total loss: 1.94302 timestamp: 1654924056.4275696 iteration: 10840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18649 FastRCNN class loss: 0.08912 FastRCNN total loss: 0.27561 L1 loss: 0.0000e+00 L2 loss: 1.53016 Learning rate: 0.02 Mask loss: 0.15155 RPN box loss: 0.02318 RPN score loss: 0.00367 RPN total loss: 0.02685 Total loss: 1.98416 timestamp: 1654924059.6450615 iteration: 10845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14002 FastRCNN class loss: 0.1045 FastRCNN total loss: 0.24451 L1 loss: 0.0000e+00 L2 loss: 1.52991 Learning rate: 0.02 Mask loss: 0.14114 RPN box loss: 0.01507 RPN score loss: 0.00361 RPN total loss: 0.01867 Total loss: 1.93423 timestamp: 1654924062.8294907 iteration: 10850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.07346 FastRCNN total loss: 0.17854 L1 loss: 0.0000e+00 L2 loss: 1.52964 Learning rate: 0.02 Mask loss: 0.1203 RPN box loss: 0.04541 RPN score loss: 0.00652 RPN total loss: 0.05193 Total loss: 1.88041 timestamp: 1654924066.0369215 iteration: 10855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12122 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.20733 L1 loss: 0.0000e+00 L2 loss: 1.52938 Learning rate: 0.02 Mask loss: 0.13386 RPN box loss: 0.03647 RPN score loss: 0.00499 RPN total loss: 0.04146 Total loss: 1.91203 timestamp: 1654924069.240511 iteration: 10860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12648 FastRCNN class loss: 0.12344 FastRCNN total loss: 0.24993 L1 loss: 0.0000e+00 L2 loss: 1.52911 Learning rate: 0.02 Mask loss: 0.17791 RPN box loss: 0.05179 RPN score loss: 0.00885 RPN total loss: 0.06064 Total loss: 2.01758 timestamp: 1654924072.4862258 iteration: 10865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11801 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.1964 L1 loss: 0.0000e+00 L2 loss: 1.52884 Learning rate: 0.02 Mask loss: 0.15819 RPN box loss: 0.02907 RPN score loss: 0.00286 RPN total loss: 0.03193 Total loss: 1.91537 timestamp: 1654924075.8031235 iteration: 10870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1755 FastRCNN class loss: 0.10816 FastRCNN total loss: 0.28366 L1 loss: 0.0000e+00 L2 loss: 1.52857 Learning rate: 0.02 Mask loss: 0.17227 RPN box loss: 0.10055 RPN score loss: 0.01604 RPN total loss: 0.11659 Total loss: 2.10109 timestamp: 1654924078.9859705 iteration: 10875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20583 FastRCNN class loss: 0.1459 FastRCNN total loss: 0.35174 L1 loss: 0.0000e+00 L2 loss: 1.52828 Learning rate: 0.02 Mask loss: 0.18611 RPN box loss: 0.03349 RPN score loss: 0.01157 RPN total loss: 0.04506 Total loss: 2.11118 timestamp: 1654924082.3855019 iteration: 10880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25448 FastRCNN class loss: 0.13735 FastRCNN total loss: 0.39183 L1 loss: 0.0000e+00 L2 loss: 1.52799 Learning rate: 0.02 Mask loss: 0.33166 RPN box loss: 0.0536 RPN score loss: 0.0164 RPN total loss: 0.06999 Total loss: 2.32147 timestamp: 1654924085.7536738 iteration: 10885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14907 FastRCNN class loss: 0.1228 FastRCNN total loss: 0.27186 L1 loss: 0.0000e+00 L2 loss: 1.5277 Learning rate: 0.02 Mask loss: 0.15768 RPN box loss: 0.03541 RPN score loss: 0.01045 RPN total loss: 0.04586 Total loss: 2.0031 timestamp: 1654924088.9569323 iteration: 10890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15166 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.23541 L1 loss: 0.0000e+00 L2 loss: 1.52743 Learning rate: 0.02 Mask loss: 0.2336 RPN box loss: 0.0581 RPN score loss: 0.00878 RPN total loss: 0.06688 Total loss: 2.06332 timestamp: 1654924092.244167 iteration: 10895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12912 FastRCNN class loss: 0.063 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 1.52721 Learning rate: 0.02 Mask loss: 0.10135 RPN box loss: 0.04071 RPN score loss: 0.00441 RPN total loss: 0.04512 Total loss: 1.8658 timestamp: 1654924095.4203787 iteration: 10900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13872 FastRCNN class loss: 0.0934 FastRCNN total loss: 0.23212 L1 loss: 0.0000e+00 L2 loss: 1.52695 Learning rate: 0.02 Mask loss: 0.27051 RPN box loss: 0.04092 RPN score loss: 0.02914 RPN total loss: 0.07006 Total loss: 2.09963 timestamp: 1654924098.8407066 iteration: 10905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18391 FastRCNN class loss: 0.06481 FastRCNN total loss: 0.24872 L1 loss: 0.0000e+00 L2 loss: 1.52667 Learning rate: 0.02 Mask loss: 0.10513 RPN box loss: 0.04601 RPN score loss: 0.00742 RPN total loss: 0.05343 Total loss: 1.93395 timestamp: 1654924102.0839572 iteration: 10910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15544 FastRCNN class loss: 0.10129 FastRCNN total loss: 0.25673 L1 loss: 0.0000e+00 L2 loss: 1.52638 Learning rate: 0.02 Mask loss: 0.22674 RPN box loss: 0.05794 RPN score loss: 0.02274 RPN total loss: 0.08068 Total loss: 2.09054 timestamp: 1654924105.548964 iteration: 10915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16116 FastRCNN class loss: 0.08799 FastRCNN total loss: 0.24915 L1 loss: 0.0000e+00 L2 loss: 1.5261 Learning rate: 0.02 Mask loss: 0.14302 RPN box loss: 0.09222 RPN score loss: 0.01348 RPN total loss: 0.10571 Total loss: 2.02398 timestamp: 1654924108.8570044 iteration: 10920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12339 FastRCNN class loss: 0.07789 FastRCNN total loss: 0.20129 L1 loss: 0.0000e+00 L2 loss: 1.52583 Learning rate: 0.02 Mask loss: 0.12896 RPN box loss: 0.03456 RPN score loss: 0.00566 RPN total loss: 0.04022 Total loss: 1.89629 timestamp: 1654924112.0990114 iteration: 10925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09465 FastRCNN class loss: 0.05526 FastRCNN total loss: 0.14991 L1 loss: 0.0000e+00 L2 loss: 1.52558 Learning rate: 0.02 Mask loss: 0.17101 RPN box loss: 0.01453 RPN score loss: 0.00641 RPN total loss: 0.02094 Total loss: 1.86744 timestamp: 1654924115.36062 iteration: 10930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13862 FastRCNN class loss: 0.063 FastRCNN total loss: 0.20163 L1 loss: 0.0000e+00 L2 loss: 1.52532 Learning rate: 0.02 Mask loss: 0.13791 RPN box loss: 0.0269 RPN score loss: 0.01315 RPN total loss: 0.04005 Total loss: 1.9049 timestamp: 1654924118.6210756 iteration: 10935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32309 FastRCNN class loss: 0.11616 FastRCNN total loss: 0.43925 L1 loss: 0.0000e+00 L2 loss: 1.52502 Learning rate: 0.02 Mask loss: 0.24547 RPN box loss: 0.0302 RPN score loss: 0.01663 RPN total loss: 0.04682 Total loss: 2.25656 timestamp: 1654924122.0222225 iteration: 10940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17984 FastRCNN class loss: 0.10716 FastRCNN total loss: 0.28699 L1 loss: 0.0000e+00 L2 loss: 1.52474 Learning rate: 0.02 Mask loss: 0.1652 RPN box loss: 0.0216 RPN score loss: 0.00639 RPN total loss: 0.028 Total loss: 2.00493 timestamp: 1654924125.2846067 iteration: 10945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1268 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.17823 L1 loss: 0.0000e+00 L2 loss: 1.52446 Learning rate: 0.02 Mask loss: 0.1577 RPN box loss: 0.01533 RPN score loss: 0.00579 RPN total loss: 0.02113 Total loss: 1.88152 timestamp: 1654924128.561578 iteration: 10950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18369 FastRCNN class loss: 0.12022 FastRCNN total loss: 0.30391 L1 loss: 0.0000e+00 L2 loss: 1.5242 Learning rate: 0.02 Mask loss: 0.19974 RPN box loss: 0.04291 RPN score loss: 0.01818 RPN total loss: 0.06109 Total loss: 2.08894 timestamp: 1654924131.7822373 iteration: 10955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2095 FastRCNN class loss: 0.109 FastRCNN total loss: 0.3185 L1 loss: 0.0000e+00 L2 loss: 1.52393 Learning rate: 0.02 Mask loss: 0.13113 RPN box loss: 0.03653 RPN score loss: 0.01531 RPN total loss: 0.05184 Total loss: 2.02541 timestamp: 1654924135.0440087 iteration: 10960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17203 FastRCNN class loss: 0.10137 FastRCNN total loss: 0.2734 L1 loss: 0.0000e+00 L2 loss: 1.52365 Learning rate: 0.02 Mask loss: 0.17763 RPN box loss: 0.02183 RPN score loss: 0.00984 RPN total loss: 0.03167 Total loss: 2.00635 timestamp: 1654924138.2880564 iteration: 10965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16562 FastRCNN class loss: 0.08819 FastRCNN total loss: 0.25381 L1 loss: 0.0000e+00 L2 loss: 1.52337 Learning rate: 0.02 Mask loss: 0.20742 RPN box loss: 0.03928 RPN score loss: 0.00756 RPN total loss: 0.04684 Total loss: 2.03144 timestamp: 1654924141.6748896 iteration: 10970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16043 FastRCNN class loss: 0.092 FastRCNN total loss: 0.25243 L1 loss: 0.0000e+00 L2 loss: 1.52309 Learning rate: 0.02 Mask loss: 0.16199 RPN box loss: 0.03865 RPN score loss: 0.008 RPN total loss: 0.04664 Total loss: 1.98415 timestamp: 1654924144.8905213 iteration: 10975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16132 FastRCNN class loss: 0.10607 FastRCNN total loss: 0.26739 L1 loss: 0.0000e+00 L2 loss: 1.52281 Learning rate: 0.02 Mask loss: 0.1448 RPN box loss: 0.0399 RPN score loss: 0.00459 RPN total loss: 0.04449 Total loss: 1.97949 timestamp: 1654924148.1564605 iteration: 10980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15028 FastRCNN class loss: 0.09486 FastRCNN total loss: 0.24513 L1 loss: 0.0000e+00 L2 loss: 1.52251 Learning rate: 0.02 Mask loss: 0.1453 RPN box loss: 0.02773 RPN score loss: 0.00537 RPN total loss: 0.0331 Total loss: 1.94605 timestamp: 1654924151.5829751 iteration: 10985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07859 FastRCNN class loss: 0.06029 FastRCNN total loss: 0.13888 L1 loss: 0.0000e+00 L2 loss: 1.52223 Learning rate: 0.02 Mask loss: 0.25988 RPN box loss: 0.00517 RPN score loss: 0.00382 RPN total loss: 0.00898 Total loss: 1.92997 timestamp: 1654924154.7958663 iteration: 10990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12487 FastRCNN class loss: 0.09321 FastRCNN total loss: 0.21808 L1 loss: 0.0000e+00 L2 loss: 1.52197 Learning rate: 0.02 Mask loss: 0.14358 RPN box loss: 0.03808 RPN score loss: 0.00689 RPN total loss: 0.04498 Total loss: 1.9286 timestamp: 1654924158.0353305 iteration: 10995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14687 FastRCNN class loss: 0.08937 FastRCNN total loss: 0.23624 L1 loss: 0.0000e+00 L2 loss: 1.5217 Learning rate: 0.02 Mask loss: 0.15418 RPN box loss: 0.09853 RPN score loss: 0.01873 RPN total loss: 0.11727 Total loss: 2.02939 timestamp: 1654924161.2834256 iteration: 11000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18505 FastRCNN class loss: 0.0643 FastRCNN total loss: 0.24934 L1 loss: 0.0000e+00 L2 loss: 1.52143 Learning rate: 0.02 Mask loss: 0.12659 RPN box loss: 0.06686 RPN score loss: 0.00594 RPN total loss: 0.07281 Total loss: 1.97017 timestamp: 1654924164.5792513 iteration: 11005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11366 FastRCNN class loss: 0.0577 FastRCNN total loss: 0.17136 L1 loss: 0.0000e+00 L2 loss: 1.52116 Learning rate: 0.02 Mask loss: 0.14729 RPN box loss: 0.05033 RPN score loss: 0.00667 RPN total loss: 0.05701 Total loss: 1.89682 timestamp: 1654924167.8121414 iteration: 11010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18356 FastRCNN class loss: 0.07342 FastRCNN total loss: 0.25698 L1 loss: 0.0000e+00 L2 loss: 1.52088 Learning rate: 0.02 Mask loss: 0.1628 RPN box loss: 0.04725 RPN score loss: 0.00559 RPN total loss: 0.05284 Total loss: 1.9935 timestamp: 1654924171.158681 iteration: 11015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08893 FastRCNN class loss: 0.04278 FastRCNN total loss: 0.13171 L1 loss: 0.0000e+00 L2 loss: 1.52061 Learning rate: 0.02 Mask loss: 0.17097 RPN box loss: 0.01509 RPN score loss: 0.00532 RPN total loss: 0.02041 Total loss: 1.8437 timestamp: 1654924174.5564685 iteration: 11020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23872 FastRCNN class loss: 0.13776 FastRCNN total loss: 0.37648 L1 loss: 0.0000e+00 L2 loss: 1.52034 Learning rate: 0.02 Mask loss: 0.32809 RPN box loss: 0.04274 RPN score loss: 0.02305 RPN total loss: 0.06578 Total loss: 2.29069 timestamp: 1654924177.84908 iteration: 11025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07968 FastRCNN class loss: 0.08241 FastRCNN total loss: 0.16209 L1 loss: 0.0000e+00 L2 loss: 1.52007 Learning rate: 0.02 Mask loss: 0.14039 RPN box loss: 0.01612 RPN score loss: 0.00881 RPN total loss: 0.02493 Total loss: 1.84749 timestamp: 1654924181.1259847 iteration: 11030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11064 FastRCNN class loss: 0.09414 FastRCNN total loss: 0.20478 L1 loss: 0.0000e+00 L2 loss: 1.51979 Learning rate: 0.02 Mask loss: 0.21277 RPN box loss: 0.14955 RPN score loss: 0.01237 RPN total loss: 0.16192 Total loss: 2.09927 timestamp: 1654924184.3769288 iteration: 11035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13382 FastRCNN class loss: 0.10704 FastRCNN total loss: 0.24086 L1 loss: 0.0000e+00 L2 loss: 1.51951 Learning rate: 0.02 Mask loss: 0.17283 RPN box loss: 0.0298 RPN score loss: 0.01217 RPN total loss: 0.04198 Total loss: 1.97518 timestamp: 1654924187.6524792 iteration: 11040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21708 FastRCNN class loss: 0.11392 FastRCNN total loss: 0.331 L1 loss: 0.0000e+00 L2 loss: 1.51924 Learning rate: 0.02 Mask loss: 0.29798 RPN box loss: 0.02797 RPN score loss: 0.01237 RPN total loss: 0.04034 Total loss: 2.18855 timestamp: 1654924190.813139 iteration: 11045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.23763 L1 loss: 0.0000e+00 L2 loss: 1.51896 Learning rate: 0.02 Mask loss: 0.14476 RPN box loss: 0.05056 RPN score loss: 0.00975 RPN total loss: 0.06031 Total loss: 1.96165 timestamp: 1654924194.0142086 iteration: 11050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10271 FastRCNN class loss: 0.09098 FastRCNN total loss: 0.19369 L1 loss: 0.0000e+00 L2 loss: 1.51869 Learning rate: 0.02 Mask loss: 0.15857 RPN box loss: 0.06226 RPN score loss: 0.00697 RPN total loss: 0.06923 Total loss: 1.94019 timestamp: 1654924197.2378132 iteration: 11055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12937 FastRCNN class loss: 0.0632 FastRCNN total loss: 0.19257 L1 loss: 0.0000e+00 L2 loss: 1.51844 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.03022 RPN score loss: 0.00624 RPN total loss: 0.03646 Total loss: 1.87957 timestamp: 1654924200.47922 iteration: 11060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15635 FastRCNN class loss: 0.10959 FastRCNN total loss: 0.26594 L1 loss: 0.0000e+00 L2 loss: 1.51817 Learning rate: 0.02 Mask loss: 0.14647 RPN box loss: 0.02327 RPN score loss: 0.00531 RPN total loss: 0.02857 Total loss: 1.95915 timestamp: 1654924203.6808507 iteration: 11065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.148 FastRCNN class loss: 0.08995 FastRCNN total loss: 0.23795 L1 loss: 0.0000e+00 L2 loss: 1.5179 Learning rate: 0.02 Mask loss: 0.18235 RPN box loss: 0.05932 RPN score loss: 0.00893 RPN total loss: 0.06826 Total loss: 2.00646 timestamp: 1654924206.9962134 iteration: 11070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16033 FastRCNN class loss: 0.11269 FastRCNN total loss: 0.27302 L1 loss: 0.0000e+00 L2 loss: 1.51764 Learning rate: 0.02 Mask loss: 0.17227 RPN box loss: 0.06168 RPN score loss: 0.00832 RPN total loss: 0.06999 Total loss: 2.03293 timestamp: 1654924210.2978842 iteration: 11075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1732 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.25389 L1 loss: 0.0000e+00 L2 loss: 1.51738 Learning rate: 0.02 Mask loss: 0.18341 RPN box loss: 0.03874 RPN score loss: 0.00784 RPN total loss: 0.04658 Total loss: 2.00126 timestamp: 1654924213.5386796 iteration: 11080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.18324 L1 loss: 0.0000e+00 L2 loss: 1.5171 Learning rate: 0.02 Mask loss: 0.14215 RPN box loss: 0.01333 RPN score loss: 0.00727 RPN total loss: 0.0206 Total loss: 1.86308 timestamp: 1654924216.8713045 iteration: 11085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2213 FastRCNN class loss: 0.13401 FastRCNN total loss: 0.3553 L1 loss: 0.0000e+00 L2 loss: 1.51682 Learning rate: 0.02 Mask loss: 0.21417 RPN box loss: 0.03596 RPN score loss: 0.00692 RPN total loss: 0.04288 Total loss: 2.12918 timestamp: 1654924220.108952 iteration: 11090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17098 FastRCNN class loss: 0.09455 FastRCNN total loss: 0.26552 L1 loss: 0.0000e+00 L2 loss: 1.51657 Learning rate: 0.02 Mask loss: 0.15351 RPN box loss: 0.01802 RPN score loss: 0.0052 RPN total loss: 0.02322 Total loss: 1.95882 timestamp: 1654924223.3607235 iteration: 11095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17045 FastRCNN class loss: 0.11411 FastRCNN total loss: 0.28456 L1 loss: 0.0000e+00 L2 loss: 1.51628 Learning rate: 0.02 Mask loss: 0.20063 RPN box loss: 0.06744 RPN score loss: 0.00558 RPN total loss: 0.07303 Total loss: 2.0745 timestamp: 1654924226.6017609 iteration: 11100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16456 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.22838 L1 loss: 0.0000e+00 L2 loss: 1.51601 Learning rate: 0.02 Mask loss: 0.2222 RPN box loss: 0.13121 RPN score loss: 0.01019 RPN total loss: 0.14139 Total loss: 2.10798 timestamp: 1654924229.9314919 iteration: 11105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12786 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.18644 L1 loss: 0.0000e+00 L2 loss: 1.51576 Learning rate: 0.02 Mask loss: 0.17755 RPN box loss: 0.04747 RPN score loss: 0.00578 RPN total loss: 0.05325 Total loss: 1.933 timestamp: 1654924233.1635864 iteration: 11110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19484 FastRCNN class loss: 0.09046 FastRCNN total loss: 0.2853 L1 loss: 0.0000e+00 L2 loss: 1.51548 Learning rate: 0.02 Mask loss: 0.17195 RPN box loss: 0.02854 RPN score loss: 0.02417 RPN total loss: 0.05271 Total loss: 2.02544 timestamp: 1654924236.44981 iteration: 11115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20561 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.29463 L1 loss: 0.0000e+00 L2 loss: 1.51518 Learning rate: 0.02 Mask loss: 0.16737 RPN box loss: 0.07253 RPN score loss: 0.00517 RPN total loss: 0.07769 Total loss: 2.05488 timestamp: 1654924239.7272632 iteration: 11120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12114 FastRCNN class loss: 0.08016 FastRCNN total loss: 0.2013 L1 loss: 0.0000e+00 L2 loss: 1.51494 Learning rate: 0.02 Mask loss: 0.13232 RPN box loss: 0.04626 RPN score loss: 0.00568 RPN total loss: 0.05194 Total loss: 1.9005 timestamp: 1654924243.0136435 iteration: 11125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14271 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.20905 L1 loss: 0.0000e+00 L2 loss: 1.51467 Learning rate: 0.02 Mask loss: 0.15897 RPN box loss: 0.06137 RPN score loss: 0.01077 RPN total loss: 0.07214 Total loss: 1.95483 timestamp: 1654924246.3256896 iteration: 11130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20772 FastRCNN class loss: 0.04751 FastRCNN total loss: 0.25524 L1 loss: 0.0000e+00 L2 loss: 1.51439 Learning rate: 0.02 Mask loss: 0.20161 RPN box loss: 0.00615 RPN score loss: 0.00385 RPN total loss: 0.01 Total loss: 1.98124 timestamp: 1654924249.5123477 iteration: 11135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12689 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.19777 L1 loss: 0.0000e+00 L2 loss: 1.51414 Learning rate: 0.02 Mask loss: 0.20016 RPN box loss: 0.02233 RPN score loss: 0.0038 RPN total loss: 0.02613 Total loss: 1.9382 timestamp: 1654924252.9204562 iteration: 11140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07841 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.14982 L1 loss: 0.0000e+00 L2 loss: 1.51386 Learning rate: 0.02 Mask loss: 0.1111 RPN box loss: 0.00499 RPN score loss: 0.00165 RPN total loss: 0.00664 Total loss: 1.78142 timestamp: 1654924256.0819848 iteration: 11145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1876 FastRCNN class loss: 0.10514 FastRCNN total loss: 0.29274 L1 loss: 0.0000e+00 L2 loss: 1.5136 Learning rate: 0.02 Mask loss: 0.10801 RPN box loss: 0.07264 RPN score loss: 0.00367 RPN total loss: 0.07631 Total loss: 1.99066 timestamp: 1654924259.356852 iteration: 11150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19903 FastRCNN class loss: 0.12459 FastRCNN total loss: 0.32363 L1 loss: 0.0000e+00 L2 loss: 1.51333 Learning rate: 0.02 Mask loss: 0.23321 RPN box loss: 0.03209 RPN score loss: 0.0092 RPN total loss: 0.04129 Total loss: 2.11145 timestamp: 1654924262.517663 iteration: 11155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16256 FastRCNN class loss: 0.07569 FastRCNN total loss: 0.23826 L1 loss: 0.0000e+00 L2 loss: 1.51307 Learning rate: 0.02 Mask loss: 0.14249 RPN box loss: 0.01951 RPN score loss: 0.00666 RPN total loss: 0.02618 Total loss: 1.91999 timestamp: 1654924265.7000802 iteration: 11160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17948 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.23652 L1 loss: 0.0000e+00 L2 loss: 1.51281 Learning rate: 0.02 Mask loss: 0.13144 RPN box loss: 0.02163 RPN score loss: 0.00369 RPN total loss: 0.02532 Total loss: 1.90609 timestamp: 1654924268.935975 iteration: 11165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17803 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.26954 L1 loss: 0.0000e+00 L2 loss: 1.51255 Learning rate: 0.02 Mask loss: 0.18616 RPN box loss: 0.02403 RPN score loss: 0.00383 RPN total loss: 0.02785 Total loss: 1.9961 timestamp: 1654924272.19321 iteration: 11170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12765 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.21016 L1 loss: 0.0000e+00 L2 loss: 1.51228 Learning rate: 0.02 Mask loss: 0.18091 RPN box loss: 0.0338 RPN score loss: 0.00513 RPN total loss: 0.03893 Total loss: 1.94228 timestamp: 1654924275.5252564 iteration: 11175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2242 FastRCNN class loss: 0.10817 FastRCNN total loss: 0.33237 L1 loss: 0.0000e+00 L2 loss: 1.512 Learning rate: 0.02 Mask loss: 0.16955 RPN box loss: 0.02252 RPN score loss: 0.01768 RPN total loss: 0.0402 Total loss: 2.05413 timestamp: 1654924278.7365868 iteration: 11180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16438 FastRCNN class loss: 0.08866 FastRCNN total loss: 0.25304 L1 loss: 0.0000e+00 L2 loss: 1.51173 Learning rate: 0.02 Mask loss: 0.20313 RPN box loss: 0.08784 RPN score loss: 0.0118 RPN total loss: 0.09965 Total loss: 2.06755 timestamp: 1654924282.0187018 iteration: 11185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13343 FastRCNN class loss: 0.10183 FastRCNN total loss: 0.23526 L1 loss: 0.0000e+00 L2 loss: 1.51145 Learning rate: 0.02 Mask loss: 0.2201 RPN box loss: 0.03115 RPN score loss: 0.00596 RPN total loss: 0.03711 Total loss: 2.00392 timestamp: 1654924285.225545 iteration: 11190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18538 FastRCNN class loss: 0.11433 FastRCNN total loss: 0.29971 L1 loss: 0.0000e+00 L2 loss: 1.51117 Learning rate: 0.02 Mask loss: 0.1343 RPN box loss: 0.02143 RPN score loss: 0.00867 RPN total loss: 0.03009 Total loss: 1.97528 timestamp: 1654924288.4428232 iteration: 11195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16494 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.23336 L1 loss: 0.0000e+00 L2 loss: 1.51092 Learning rate: 0.02 Mask loss: 0.17739 RPN box loss: 0.03754 RPN score loss: 0.01244 RPN total loss: 0.04997 Total loss: 1.97164 timestamp: 1654924291.6005917 iteration: 11200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14147 FastRCNN class loss: 0.08017 FastRCNN total loss: 0.22164 L1 loss: 0.0000e+00 L2 loss: 1.51065 Learning rate: 0.02 Mask loss: 0.14398 RPN box loss: 0.01536 RPN score loss: 0.00323 RPN total loss: 0.01859 Total loss: 1.89486 timestamp: 1654924294.7963 iteration: 11205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14195 FastRCNN class loss: 0.14923 FastRCNN total loss: 0.29117 L1 loss: 0.0000e+00 L2 loss: 1.51039 Learning rate: 0.02 Mask loss: 0.2427 RPN box loss: 0.07524 RPN score loss: 0.01176 RPN total loss: 0.087 Total loss: 2.13126 timestamp: 1654924298.0183294 iteration: 11210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07741 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.13087 L1 loss: 0.0000e+00 L2 loss: 1.51013 Learning rate: 0.02 Mask loss: 0.13789 RPN box loss: 0.04142 RPN score loss: 0.00969 RPN total loss: 0.05111 Total loss: 1.83 timestamp: 1654924301.2805493 iteration: 11215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.137 FastRCNN class loss: 0.09648 FastRCNN total loss: 0.23347 L1 loss: 0.0000e+00 L2 loss: 1.50984 Learning rate: 0.02 Mask loss: 0.17229 RPN box loss: 0.03653 RPN score loss: 0.00577 RPN total loss: 0.0423 Total loss: 1.9579 timestamp: 1654924304.486957 iteration: 11220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15418 FastRCNN class loss: 0.0883 FastRCNN total loss: 0.24248 L1 loss: 0.0000e+00 L2 loss: 1.50958 Learning rate: 0.02 Mask loss: 0.17987 RPN box loss: 0.03061 RPN score loss: 0.00969 RPN total loss: 0.04029 Total loss: 1.97223 timestamp: 1654924307.6961327 iteration: 11225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17348 FastRCNN class loss: 0.06415 FastRCNN total loss: 0.23763 L1 loss: 0.0000e+00 L2 loss: 1.5093 Learning rate: 0.02 Mask loss: 0.13907 RPN box loss: 0.04543 RPN score loss: 0.00301 RPN total loss: 0.04844 Total loss: 1.93444 timestamp: 1654924310.8731952 iteration: 11230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12827 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.21031 L1 loss: 0.0000e+00 L2 loss: 1.50906 Learning rate: 0.02 Mask loss: 0.16262 RPN box loss: 0.03234 RPN score loss: 0.0094 RPN total loss: 0.04174 Total loss: 1.92373 timestamp: 1654924314.0741415 iteration: 11235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17842 FastRCNN class loss: 0.12199 FastRCNN total loss: 0.30041 L1 loss: 0.0000e+00 L2 loss: 1.50878 Learning rate: 0.02 Mask loss: 0.20855 RPN box loss: 0.04185 RPN score loss: 0.01026 RPN total loss: 0.05211 Total loss: 2.06985 timestamp: 1654924317.3653233 iteration: 11240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22113 FastRCNN class loss: 0.10597 FastRCNN total loss: 0.3271 L1 loss: 0.0000e+00 L2 loss: 1.5085 Learning rate: 0.02 Mask loss: 0.27691 RPN box loss: 0.04102 RPN score loss: 0.01004 RPN total loss: 0.05106 Total loss: 2.16357 timestamp: 1654924320.6734903 iteration: 11245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24661 FastRCNN class loss: 0.10298 FastRCNN total loss: 0.3496 L1 loss: 0.0000e+00 L2 loss: 1.50823 Learning rate: 0.02 Mask loss: 0.1684 RPN box loss: 0.0452 RPN score loss: 0.00643 RPN total loss: 0.05163 Total loss: 2.07786 timestamp: 1654924323.907143 iteration: 11250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1265 FastRCNN class loss: 0.06735 FastRCNN total loss: 0.19385 L1 loss: 0.0000e+00 L2 loss: 1.50796 Learning rate: 0.02 Mask loss: 0.16574 RPN box loss: 0.02745 RPN score loss: 0.00378 RPN total loss: 0.03123 Total loss: 1.89878 timestamp: 1654924327.0068774 iteration: 11255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17785 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.26461 L1 loss: 0.0000e+00 L2 loss: 1.50769 Learning rate: 0.02 Mask loss: 0.15646 RPN box loss: 0.04913 RPN score loss: 0.0064 RPN total loss: 0.05553 Total loss: 1.98429 timestamp: 1654924330.2780924 iteration: 11260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18884 FastRCNN class loss: 0.09757 FastRCNN total loss: 0.28641 L1 loss: 0.0000e+00 L2 loss: 1.50743 Learning rate: 0.02 Mask loss: 0.209 RPN box loss: 0.02474 RPN score loss: 0.00802 RPN total loss: 0.03276 Total loss: 2.0356 timestamp: 1654924333.5390625 iteration: 11265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1876 FastRCNN class loss: 0.11945 FastRCNN total loss: 0.30705 L1 loss: 0.0000e+00 L2 loss: 1.50716 Learning rate: 0.02 Mask loss: 0.17131 RPN box loss: 0.05553 RPN score loss: 0.00393 RPN total loss: 0.05945 Total loss: 2.04497 timestamp: 1654924336.841349 iteration: 11270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10735 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.1768 L1 loss: 0.0000e+00 L2 loss: 1.50691 Learning rate: 0.02 Mask loss: 0.09174 RPN box loss: 0.0057 RPN score loss: 0.00415 RPN total loss: 0.00984 Total loss: 1.78529 timestamp: 1654924340.1269088 iteration: 11275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20364 FastRCNN class loss: 0.10645 FastRCNN total loss: 0.31009 L1 loss: 0.0000e+00 L2 loss: 1.50662 Learning rate: 0.02 Mask loss: 0.12523 RPN box loss: 0.03932 RPN score loss: 0.0057 RPN total loss: 0.04502 Total loss: 1.98696 timestamp: 1654924343.3964624 iteration: 11280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18244 FastRCNN class loss: 0.08622 FastRCNN total loss: 0.26866 L1 loss: 0.0000e+00 L2 loss: 1.50636 Learning rate: 0.02 Mask loss: 0.20371 RPN box loss: 0.04632 RPN score loss: 0.00432 RPN total loss: 0.05064 Total loss: 2.02937 timestamp: 1654924346.5417125 iteration: 11285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13449 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.21717 L1 loss: 0.0000e+00 L2 loss: 1.50611 Learning rate: 0.02 Mask loss: 0.21361 RPN box loss: 0.01116 RPN score loss: 0.00656 RPN total loss: 0.01772 Total loss: 1.95461 timestamp: 1654924349.8021824 iteration: 11290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14756 FastRCNN class loss: 0.06739 FastRCNN total loss: 0.21495 L1 loss: 0.0000e+00 L2 loss: 1.50583 Learning rate: 0.02 Mask loss: 0.145 RPN box loss: 0.01456 RPN score loss: 0.00479 RPN total loss: 0.01935 Total loss: 1.88512 timestamp: 1654924353.0650177 iteration: 11295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20495 FastRCNN class loss: 0.08415 FastRCNN total loss: 0.2891 L1 loss: 0.0000e+00 L2 loss: 1.50554 Learning rate: 0.02 Mask loss: 0.13246 RPN box loss: 0.04154 RPN score loss: 0.00991 RPN total loss: 0.05145 Total loss: 1.97855 timestamp: 1654924356.314281 iteration: 11300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19794 FastRCNN class loss: 0.09657 FastRCNN total loss: 0.29451 L1 loss: 0.0000e+00 L2 loss: 1.50529 Learning rate: 0.02 Mask loss: 0.12363 RPN box loss: 0.02523 RPN score loss: 0.00546 RPN total loss: 0.03069 Total loss: 1.95411 timestamp: 1654924359.6725101 iteration: 11305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14124 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.20361 L1 loss: 0.0000e+00 L2 loss: 1.50503 Learning rate: 0.02 Mask loss: 0.12016 RPN box loss: 0.01984 RPN score loss: 0.00389 RPN total loss: 0.02372 Total loss: 1.85253 timestamp: 1654924362.9657218 iteration: 11310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15829 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.2281 L1 loss: 0.0000e+00 L2 loss: 1.50476 Learning rate: 0.02 Mask loss: 0.13132 RPN box loss: 0.04231 RPN score loss: 0.01285 RPN total loss: 0.05516 Total loss: 1.91934 timestamp: 1654924366.278838 iteration: 11315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2098 FastRCNN class loss: 0.10848 FastRCNN total loss: 0.31829 L1 loss: 0.0000e+00 L2 loss: 1.50448 Learning rate: 0.02 Mask loss: 0.18047 RPN box loss: 0.0699 RPN score loss: 0.01006 RPN total loss: 0.07996 Total loss: 2.0832 timestamp: 1654924369.4998896 iteration: 11320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1071 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.18408 L1 loss: 0.0000e+00 L2 loss: 1.50421 Learning rate: 0.02 Mask loss: 0.09238 RPN box loss: 0.01869 RPN score loss: 0.00288 RPN total loss: 0.02156 Total loss: 1.80223 timestamp: 1654924372.8581266 iteration: 11325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19176 FastRCNN class loss: 0.12213 FastRCNN total loss: 0.31389 L1 loss: 0.0000e+00 L2 loss: 1.50394 Learning rate: 0.02 Mask loss: 0.27041 RPN box loss: 0.06251 RPN score loss: 0.01023 RPN total loss: 0.07275 Total loss: 2.16098 timestamp: 1654924376.068458 iteration: 11330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20095 FastRCNN class loss: 0.20605 FastRCNN total loss: 0.40701 L1 loss: 0.0000e+00 L2 loss: 1.50368 Learning rate: 0.02 Mask loss: 0.20749 RPN box loss: 0.01579 RPN score loss: 0.00407 RPN total loss: 0.01986 Total loss: 2.13804 timestamp: 1654924379.3229208 iteration: 11335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11335 FastRCNN class loss: 0.06411 FastRCNN total loss: 0.17746 L1 loss: 0.0000e+00 L2 loss: 1.50339 Learning rate: 0.02 Mask loss: 0.14284 RPN box loss: 0.01024 RPN score loss: 0.00126 RPN total loss: 0.01151 Total loss: 1.83521 timestamp: 1654924382.5093107 iteration: 11340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10423 FastRCNN class loss: 0.07421 FastRCNN total loss: 0.17844 L1 loss: 0.0000e+00 L2 loss: 1.50312 Learning rate: 0.02 Mask loss: 0.11562 RPN box loss: 0.03094 RPN score loss: 0.00587 RPN total loss: 0.03681 Total loss: 1.83399 timestamp: 1654924385.796742 iteration: 11345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16901 FastRCNN class loss: 0.11573 FastRCNN total loss: 0.28474 L1 loss: 0.0000e+00 L2 loss: 1.50288 Learning rate: 0.02 Mask loss: 0.27849 RPN box loss: 0.03517 RPN score loss: 0.00984 RPN total loss: 0.04501 Total loss: 2.11111 timestamp: 1654924389.158293 iteration: 11350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10073 FastRCNN class loss: 0.05877 FastRCNN total loss: 0.15951 L1 loss: 0.0000e+00 L2 loss: 1.50259 Learning rate: 0.02 Mask loss: 0.12586 RPN box loss: 0.03711 RPN score loss: 0.00561 RPN total loss: 0.04273 Total loss: 1.83069 timestamp: 1654924392.3278816 iteration: 11355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14557 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.20124 L1 loss: 0.0000e+00 L2 loss: 1.50233 Learning rate: 0.02 Mask loss: 0.1236 RPN box loss: 0.01971 RPN score loss: 0.00576 RPN total loss: 0.02547 Total loss: 1.85264 timestamp: 1654924395.5496886 iteration: 11360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16692 FastRCNN class loss: 0.08923 FastRCNN total loss: 0.25615 L1 loss: 0.0000e+00 L2 loss: 1.50208 Learning rate: 0.02 Mask loss: 0.1483 RPN box loss: 0.02073 RPN score loss: 0.00269 RPN total loss: 0.02342 Total loss: 1.92995 timestamp: 1654924398.6841438 iteration: 11365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05109 FastRCNN class loss: 0.03925 FastRCNN total loss: 0.09034 L1 loss: 0.0000e+00 L2 loss: 1.50182 Learning rate: 0.02 Mask loss: 0.10218 RPN box loss: 0.02429 RPN score loss: 0.00432 RPN total loss: 0.02861 Total loss: 1.72294 timestamp: 1654924401.9699821 iteration: 11370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19321 FastRCNN class loss: 0.1081 FastRCNN total loss: 0.3013 L1 loss: 0.0000e+00 L2 loss: 1.50155 Learning rate: 0.02 Mask loss: 0.1618 RPN box loss: 0.03482 RPN score loss: 0.00409 RPN total loss: 0.03891 Total loss: 2.00356 timestamp: 1654924405.1509857 iteration: 11375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17482 FastRCNN class loss: 0.08211 FastRCNN total loss: 0.25694 L1 loss: 0.0000e+00 L2 loss: 1.50127 Learning rate: 0.02 Mask loss: 0.21298 RPN box loss: 0.05299 RPN score loss: 0.00734 RPN total loss: 0.06033 Total loss: 2.03152 timestamp: 1654924408.347133 iteration: 11380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18793 FastRCNN class loss: 0.08542 FastRCNN total loss: 0.27335 L1 loss: 0.0000e+00 L2 loss: 1.50098 Learning rate: 0.02 Mask loss: 0.14575 RPN box loss: 0.0275 RPN score loss: 0.0106 RPN total loss: 0.03809 Total loss: 1.95817 timestamp: 1654924411.5079868 iteration: 11385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14983 FastRCNN class loss: 0.06331 FastRCNN total loss: 0.21314 L1 loss: 0.0000e+00 L2 loss: 1.5007 Learning rate: 0.02 Mask loss: 0.12332 RPN box loss: 0.00902 RPN score loss: 0.0023 RPN total loss: 0.01132 Total loss: 1.84849 timestamp: 1654924414.7892447 iteration: 11390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12883 FastRCNN class loss: 0.06024 FastRCNN total loss: 0.18907 L1 loss: 0.0000e+00 L2 loss: 1.50044 Learning rate: 0.02 Mask loss: 0.14891 RPN box loss: 0.03922 RPN score loss: 0.00458 RPN total loss: 0.0438 Total loss: 1.88222 timestamp: 1654924417.937171 iteration: 11395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14561 FastRCNN class loss: 0.09377 FastRCNN total loss: 0.23938 L1 loss: 0.0000e+00 L2 loss: 1.50018 Learning rate: 0.02 Mask loss: 0.16033 RPN box loss: 0.01438 RPN score loss: 0.00563 RPN total loss: 0.02001 Total loss: 1.9199 timestamp: 1654924421.2800128 iteration: 11400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16499 FastRCNN class loss: 0.06108 FastRCNN total loss: 0.22607 L1 loss: 0.0000e+00 L2 loss: 1.49991 Learning rate: 0.02 Mask loss: 0.14331 RPN box loss: 0.08822 RPN score loss: 0.00455 RPN total loss: 0.09277 Total loss: 1.96207 timestamp: 1654924424.650295 iteration: 11405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14103 FastRCNN class loss: 0.09985 FastRCNN total loss: 0.24088 L1 loss: 0.0000e+00 L2 loss: 1.49964 Learning rate: 0.02 Mask loss: 0.20895 RPN box loss: 0.07665 RPN score loss: 0.01404 RPN total loss: 0.09068 Total loss: 2.04015 timestamp: 1654924427.865692 iteration: 11410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21478 FastRCNN class loss: 0.12219 FastRCNN total loss: 0.33697 L1 loss: 0.0000e+00 L2 loss: 1.49938 Learning rate: 0.02 Mask loss: 0.1347 RPN box loss: 0.01317 RPN score loss: 0.00766 RPN total loss: 0.02083 Total loss: 1.99188 timestamp: 1654924431.21941 iteration: 11415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16245 FastRCNN class loss: 0.15397 FastRCNN total loss: 0.31642 L1 loss: 0.0000e+00 L2 loss: 1.49914 Learning rate: 0.02 Mask loss: 0.1846 RPN box loss: 0.05745 RPN score loss: 0.00887 RPN total loss: 0.06633 Total loss: 2.06649 timestamp: 1654924434.4098341 iteration: 11420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14342 FastRCNN class loss: 0.07053 FastRCNN total loss: 0.21395 L1 loss: 0.0000e+00 L2 loss: 1.49889 Learning rate: 0.02 Mask loss: 0.13134 RPN box loss: 0.03197 RPN score loss: 0.00509 RPN total loss: 0.03706 Total loss: 1.88124 timestamp: 1654924437.7683089 iteration: 11425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20598 FastRCNN class loss: 0.12555 FastRCNN total loss: 0.33153 L1 loss: 0.0000e+00 L2 loss: 1.49861 Learning rate: 0.02 Mask loss: 0.20597 RPN box loss: 0.06653 RPN score loss: 0.02141 RPN total loss: 0.08794 Total loss: 2.12404 timestamp: 1654924441.0668328 iteration: 11430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23706 FastRCNN class loss: 0.12333 FastRCNN total loss: 0.36039 L1 loss: 0.0000e+00 L2 loss: 1.49833 Learning rate: 0.02 Mask loss: 0.22862 RPN box loss: 0.02223 RPN score loss: 0.00571 RPN total loss: 0.02795 Total loss: 2.11528 timestamp: 1654924444.301484 iteration: 11435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14512 FastRCNN class loss: 0.08398 FastRCNN total loss: 0.2291 L1 loss: 0.0000e+00 L2 loss: 1.49805 Learning rate: 0.02 Mask loss: 0.15106 RPN box loss: 0.07592 RPN score loss: 0.00712 RPN total loss: 0.08304 Total loss: 1.96125 timestamp: 1654924447.5162778 iteration: 11440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13988 FastRCNN class loss: 0.0808 FastRCNN total loss: 0.22068 L1 loss: 0.0000e+00 L2 loss: 1.4978 Learning rate: 0.02 Mask loss: 0.13675 RPN box loss: 0.02179 RPN score loss: 0.00455 RPN total loss: 0.02634 Total loss: 1.88157 timestamp: 1654924450.9262555 iteration: 11445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1623 FastRCNN class loss: 0.11285 FastRCNN total loss: 0.27515 L1 loss: 0.0000e+00 L2 loss: 1.49753 Learning rate: 0.02 Mask loss: 0.20629 RPN box loss: 0.01377 RPN score loss: 0.00892 RPN total loss: 0.02269 Total loss: 2.00167 timestamp: 1654924454.0779746 iteration: 11450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11021 FastRCNN class loss: 0.09913 FastRCNN total loss: 0.20934 L1 loss: 0.0000e+00 L2 loss: 1.49725 Learning rate: 0.02 Mask loss: 0.1966 RPN box loss: 0.03707 RPN score loss: 0.00717 RPN total loss: 0.04424 Total loss: 1.94744 timestamp: 1654924457.4228039 iteration: 11455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16726 FastRCNN class loss: 0.12349 FastRCNN total loss: 0.29074 L1 loss: 0.0000e+00 L2 loss: 1.49698 Learning rate: 0.02 Mask loss: 0.19204 RPN box loss: 0.04018 RPN score loss: 0.01242 RPN total loss: 0.0526 Total loss: 2.03236 timestamp: 1654924460.7191029 iteration: 11460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14526 FastRCNN class loss: 0.09812 FastRCNN total loss: 0.24338 L1 loss: 0.0000e+00 L2 loss: 1.49672 Learning rate: 0.02 Mask loss: 0.12918 RPN box loss: 0.0399 RPN score loss: 0.00566 RPN total loss: 0.04555 Total loss: 1.91483 timestamp: 1654924463.9596713 iteration: 11465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12865 FastRCNN class loss: 0.09423 FastRCNN total loss: 0.22288 L1 loss: 0.0000e+00 L2 loss: 1.49646 Learning rate: 0.02 Mask loss: 0.17426 RPN box loss: 0.04874 RPN score loss: 0.01147 RPN total loss: 0.06021 Total loss: 1.9538 timestamp: 1654924467.3454869 iteration: 11470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22695 FastRCNN class loss: 0.19837 FastRCNN total loss: 0.42532 L1 loss: 0.0000e+00 L2 loss: 1.4962 Learning rate: 0.02 Mask loss: 0.25677 RPN box loss: 0.03694 RPN score loss: 0.01678 RPN total loss: 0.05371 Total loss: 2.23201 timestamp: 1654924470.625805 iteration: 11475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21756 FastRCNN class loss: 0.09478 FastRCNN total loss: 0.31234 L1 loss: 0.0000e+00 L2 loss: 1.49593 Learning rate: 0.02 Mask loss: 0.21656 RPN box loss: 0.02134 RPN score loss: 0.00918 RPN total loss: 0.03051 Total loss: 2.05534 timestamp: 1654924473.9983888 iteration: 11480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1339 FastRCNN class loss: 0.0886 FastRCNN total loss: 0.2225 L1 loss: 0.0000e+00 L2 loss: 1.49567 Learning rate: 0.02 Mask loss: 0.13269 RPN box loss: 0.0426 RPN score loss: 0.00606 RPN total loss: 0.04866 Total loss: 1.89951 timestamp: 1654924477.1721056 iteration: 11485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16388 FastRCNN class loss: 0.11243 FastRCNN total loss: 0.27631 L1 loss: 0.0000e+00 L2 loss: 1.49541 Learning rate: 0.02 Mask loss: 0.17273 RPN box loss: 0.06311 RPN score loss: 0.01429 RPN total loss: 0.0774 Total loss: 2.02185 timestamp: 1654924480.5079038 iteration: 11490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13447 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.20266 L1 loss: 0.0000e+00 L2 loss: 1.49515 Learning rate: 0.02 Mask loss: 0.11881 RPN box loss: 0.02511 RPN score loss: 0.00467 RPN total loss: 0.02978 Total loss: 1.8464 timestamp: 1654924483.669815 iteration: 11495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12048 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.2131 L1 loss: 0.0000e+00 L2 loss: 1.49489 Learning rate: 0.02 Mask loss: 0.16864 RPN box loss: 0.03739 RPN score loss: 0.01371 RPN total loss: 0.05111 Total loss: 1.92773 timestamp: 1654924486.943933 iteration: 11500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2134 FastRCNN class loss: 0.15092 FastRCNN total loss: 0.36432 L1 loss: 0.0000e+00 L2 loss: 1.49464 Learning rate: 0.02 Mask loss: 0.27666 RPN box loss: 0.04925 RPN score loss: 0.01297 RPN total loss: 0.06222 Total loss: 2.19784 timestamp: 1654924490.1733341 iteration: 11505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07608 FastRCNN class loss: 0.04384 FastRCNN total loss: 0.11992 L1 loss: 0.0000e+00 L2 loss: 1.4944 Learning rate: 0.02 Mask loss: 0.156 RPN box loss: 0.02874 RPN score loss: 0.00394 RPN total loss: 0.03267 Total loss: 1.80299 timestamp: 1654924493.402191 iteration: 11510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11402 FastRCNN class loss: 0.07703 FastRCNN total loss: 0.19106 L1 loss: 0.0000e+00 L2 loss: 1.49412 Learning rate: 0.02 Mask loss: 0.1971 RPN box loss: 0.06014 RPN score loss: 0.01821 RPN total loss: 0.07835 Total loss: 1.96064 timestamp: 1654924496.699971 iteration: 11515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18584 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.26769 L1 loss: 0.0000e+00 L2 loss: 1.49385 Learning rate: 0.02 Mask loss: 0.12768 RPN box loss: 0.01973 RPN score loss: 0.00416 RPN total loss: 0.02389 Total loss: 1.91311 timestamp: 1654924499.9397433 iteration: 11520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13788 FastRCNN class loss: 0.10238 FastRCNN total loss: 0.24025 L1 loss: 0.0000e+00 L2 loss: 1.49358 Learning rate: 0.02 Mask loss: 0.16243 RPN box loss: 0.05054 RPN score loss: 0.00906 RPN total loss: 0.0596 Total loss: 1.95585 timestamp: 1654924503.167788 iteration: 11525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08808 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.13751 L1 loss: 0.0000e+00 L2 loss: 1.49333 Learning rate: 0.02 Mask loss: 0.16861 RPN box loss: 0.03292 RPN score loss: 0.00771 RPN total loss: 0.04064 Total loss: 1.84009 timestamp: 1654924506.4316723 iteration: 11530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11404 FastRCNN class loss: 0.0786 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 1.49306 Learning rate: 0.02 Mask loss: 0.14858 RPN box loss: 0.05799 RPN score loss: 0.01033 RPN total loss: 0.06832 Total loss: 1.9026 timestamp: 1654924509.7178133 iteration: 11535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14287 FastRCNN class loss: 0.10188 FastRCNN total loss: 0.24475 L1 loss: 0.0000e+00 L2 loss: 1.49277 Learning rate: 0.02 Mask loss: 0.20856 RPN box loss: 0.05279 RPN score loss: 0.00672 RPN total loss: 0.05951 Total loss: 2.00559 timestamp: 1654924512.8917782 iteration: 11540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1404 FastRCNN class loss: 0.06774 FastRCNN total loss: 0.20815 L1 loss: 0.0000e+00 L2 loss: 1.49248 Learning rate: 0.02 Mask loss: 0.23269 RPN box loss: 0.0097 RPN score loss: 0.00423 RPN total loss: 0.01393 Total loss: 1.94725 timestamp: 1654924516.2645497 iteration: 11545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12943 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.18249 L1 loss: 0.0000e+00 L2 loss: 1.49221 Learning rate: 0.02 Mask loss: 0.18958 RPN box loss: 0.01475 RPN score loss: 0.00303 RPN total loss: 0.01778 Total loss: 1.88206 timestamp: 1654924519.506248 iteration: 11550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.03572 FastRCNN total loss: 0.10863 L1 loss: 0.0000e+00 L2 loss: 1.49196 Learning rate: 0.02 Mask loss: 0.11601 RPN box loss: 0.04656 RPN score loss: 0.00384 RPN total loss: 0.0504 Total loss: 1.76699 timestamp: 1654924522.7389047 iteration: 11555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16586 FastRCNN class loss: 0.06778 FastRCNN total loss: 0.23364 L1 loss: 0.0000e+00 L2 loss: 1.49169 Learning rate: 0.02 Mask loss: 0.13292 RPN box loss: 0.01798 RPN score loss: 0.00889 RPN total loss: 0.02686 Total loss: 1.88512 timestamp: 1654924525.9945574 iteration: 11560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10996 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.17103 L1 loss: 0.0000e+00 L2 loss: 1.49144 Learning rate: 0.02 Mask loss: 0.1308 RPN box loss: 0.03239 RPN score loss: 0.00363 RPN total loss: 0.03603 Total loss: 1.8293 timestamp: 1654924529.2055733 iteration: 11565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10827 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.19792 L1 loss: 0.0000e+00 L2 loss: 1.49117 Learning rate: 0.02 Mask loss: 0.14182 RPN box loss: 0.03477 RPN score loss: 0.00907 RPN total loss: 0.04384 Total loss: 1.87475 timestamp: 1654924532.5516367 iteration: 11570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21995 FastRCNN class loss: 0.11138 FastRCNN total loss: 0.33133 L1 loss: 0.0000e+00 L2 loss: 1.49091 Learning rate: 0.02 Mask loss: 0.22861 RPN box loss: 0.04141 RPN score loss: 0.00954 RPN total loss: 0.05095 Total loss: 2.1018 timestamp: 1654924535.7535846 iteration: 11575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1816 FastRCNN class loss: 0.17574 FastRCNN total loss: 0.35734 L1 loss: 0.0000e+00 L2 loss: 1.49063 Learning rate: 0.02 Mask loss: 0.20454 RPN box loss: 0.03779 RPN score loss: 0.00713 RPN total loss: 0.04492 Total loss: 2.09744 timestamp: 1654924539.1971734 iteration: 11580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10594 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.16901 L1 loss: 0.0000e+00 L2 loss: 1.49035 Learning rate: 0.02 Mask loss: 0.13323 RPN box loss: 0.03045 RPN score loss: 0.00924 RPN total loss: 0.03969 Total loss: 1.83228 timestamp: 1654924542.4014864 iteration: 11585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17547 FastRCNN class loss: 0.07063 FastRCNN total loss: 0.2461 L1 loss: 0.0000e+00 L2 loss: 1.49011 Learning rate: 0.02 Mask loss: 0.1376 RPN box loss: 0.08192 RPN score loss: 0.00835 RPN total loss: 0.09027 Total loss: 1.96408 timestamp: 1654924545.674284 iteration: 11590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16141 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.23225 L1 loss: 0.0000e+00 L2 loss: 1.48984 Learning rate: 0.02 Mask loss: 0.205 RPN box loss: 0.03729 RPN score loss: 0.01346 RPN total loss: 0.05074 Total loss: 1.97783 timestamp: 1654924548.8353238 iteration: 11595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11305 FastRCNN class loss: 0.11602 FastRCNN total loss: 0.22907 L1 loss: 0.0000e+00 L2 loss: 1.48956 Learning rate: 0.02 Mask loss: 0.24014 RPN box loss: 0.01174 RPN score loss: 0.00117 RPN total loss: 0.01292 Total loss: 1.97169 timestamp: 1654924552.081737 iteration: 11600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15622 FastRCNN class loss: 0.13363 FastRCNN total loss: 0.28986 L1 loss: 0.0000e+00 L2 loss: 1.48932 Learning rate: 0.02 Mask loss: 0.23246 RPN box loss: 0.03859 RPN score loss: 0.00355 RPN total loss: 0.04215 Total loss: 2.05378 timestamp: 1654924555.4534867 iteration: 11605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24336 FastRCNN class loss: 0.15288 FastRCNN total loss: 0.39625 L1 loss: 0.0000e+00 L2 loss: 1.48904 Learning rate: 0.02 Mask loss: 0.22329 RPN box loss: 0.04768 RPN score loss: 0.01029 RPN total loss: 0.05797 Total loss: 2.16654 timestamp: 1654924558.7196279 iteration: 11610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19148 FastRCNN class loss: 0.10478 FastRCNN total loss: 0.29626 L1 loss: 0.0000e+00 L2 loss: 1.48877 Learning rate: 0.02 Mask loss: 0.18414 RPN box loss: 0.03593 RPN score loss: 0.01042 RPN total loss: 0.04636 Total loss: 2.01552 timestamp: 1654924561.9925408 iteration: 11615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15686 FastRCNN class loss: 0.12414 FastRCNN total loss: 0.28099 L1 loss: 0.0000e+00 L2 loss: 1.48851 Learning rate: 0.02 Mask loss: 0.20335 RPN box loss: 0.03488 RPN score loss: 0.00741 RPN total loss: 0.04229 Total loss: 2.01514 timestamp: 1654924565.2188199 iteration: 11620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18058 FastRCNN class loss: 0.09647 FastRCNN total loss: 0.27705 L1 loss: 0.0000e+00 L2 loss: 1.48826 Learning rate: 0.02 Mask loss: 0.12841 RPN box loss: 0.05301 RPN score loss: 0.00898 RPN total loss: 0.06199 Total loss: 1.95572 timestamp: 1654924568.6166937 iteration: 11625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1515 FastRCNN class loss: 0.10819 FastRCNN total loss: 0.25969 L1 loss: 0.0000e+00 L2 loss: 1.48799 Learning rate: 0.02 Mask loss: 0.17422 RPN box loss: 0.16459 RPN score loss: 0.0087 RPN total loss: 0.1733 Total loss: 2.09521 timestamp: 1654924571.785561 iteration: 11630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11006 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.17738 L1 loss: 0.0000e+00 L2 loss: 1.48777 Learning rate: 0.02 Mask loss: 0.16492 RPN box loss: 0.0571 RPN score loss: 0.01054 RPN total loss: 0.06764 Total loss: 1.89771 timestamp: 1654924575.1084511 iteration: 11635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11707 FastRCNN class loss: 0.16157 FastRCNN total loss: 0.27865 L1 loss: 0.0000e+00 L2 loss: 1.4875 Learning rate: 0.02 Mask loss: 0.24724 RPN box loss: 0.04469 RPN score loss: 0.07335 RPN total loss: 0.11804 Total loss: 2.13142 timestamp: 1654924578.3005989 iteration: 11640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14924 FastRCNN class loss: 0.1298 FastRCNN total loss: 0.27904 L1 loss: 0.0000e+00 L2 loss: 1.48721 Learning rate: 0.02 Mask loss: 0.21066 RPN box loss: 0.02784 RPN score loss: 0.01199 RPN total loss: 0.03983 Total loss: 2.01675 timestamp: 1654924581.6613226 iteration: 11645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2399 FastRCNN class loss: 0.07907 FastRCNN total loss: 0.31897 L1 loss: 0.0000e+00 L2 loss: 1.48698 Learning rate: 0.02 Mask loss: 0.21064 RPN box loss: 0.03662 RPN score loss: 0.00808 RPN total loss: 0.0447 Total loss: 2.06128 timestamp: 1654924584.855492 iteration: 11650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15453 FastRCNN class loss: 0.09064 FastRCNN total loss: 0.24517 L1 loss: 0.0000e+00 L2 loss: 1.48672 Learning rate: 0.02 Mask loss: 0.15847 RPN box loss: 0.02101 RPN score loss: 0.00962 RPN total loss: 0.03063 Total loss: 1.92099 timestamp: 1654924588.3129017 iteration: 11655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16762 FastRCNN class loss: 0.08741 FastRCNN total loss: 0.25504 L1 loss: 0.0000e+00 L2 loss: 1.48644 Learning rate: 0.02 Mask loss: 0.15038 RPN box loss: 0.02191 RPN score loss: 0.00595 RPN total loss: 0.02786 Total loss: 1.91972 timestamp: 1654924591.6198962 iteration: 11660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21711 FastRCNN class loss: 0.10957 FastRCNN total loss: 0.32668 L1 loss: 0.0000e+00 L2 loss: 1.4862 Learning rate: 0.02 Mask loss: 0.21924 RPN box loss: 0.03092 RPN score loss: 0.01277 RPN total loss: 0.04369 Total loss: 2.07581 timestamp: 1654924594.7378109 iteration: 11665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13223 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.19663 L1 loss: 0.0000e+00 L2 loss: 1.48595 Learning rate: 0.02 Mask loss: 0.11951 RPN box loss: 0.02408 RPN score loss: 0.0052 RPN total loss: 0.02928 Total loss: 1.83138 timestamp: 1654924598.0325935 iteration: 11670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10474 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 1.48569 Learning rate: 0.02 Mask loss: 0.15001 RPN box loss: 0.03597 RPN score loss: 0.00475 RPN total loss: 0.04072 Total loss: 1.86802 timestamp: 1654924601.2325532 iteration: 11675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16646 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.23182 L1 loss: 0.0000e+00 L2 loss: 1.48543 Learning rate: 0.02 Mask loss: 0.1383 RPN box loss: 0.11028 RPN score loss: 0.00866 RPN total loss: 0.11894 Total loss: 1.9745 timestamp: 1654924604.6166506 iteration: 11680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12723 FastRCNN class loss: 0.05853 FastRCNN total loss: 0.18576 L1 loss: 0.0000e+00 L2 loss: 1.48517 Learning rate: 0.02 Mask loss: 0.13277 RPN box loss: 0.02159 RPN score loss: 0.0042 RPN total loss: 0.02578 Total loss: 1.82949 timestamp: 1654924607.91937 iteration: 11685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17396 FastRCNN class loss: 0.12803 FastRCNN total loss: 0.30199 L1 loss: 0.0000e+00 L2 loss: 1.4849 Learning rate: 0.02 Mask loss: 0.19762 RPN box loss: 0.02425 RPN score loss: 0.00571 RPN total loss: 0.02996 Total loss: 2.01447 timestamp: 1654924611.3162441 iteration: 11690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15079 FastRCNN class loss: 0.09651 FastRCNN total loss: 0.2473 L1 loss: 0.0000e+00 L2 loss: 1.48463 Learning rate: 0.02 Mask loss: 0.17413 RPN box loss: 0.03784 RPN score loss: 0.00802 RPN total loss: 0.04587 Total loss: 1.95193 timestamp: 1654924614.523969 iteration: 11695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12132 FastRCNN class loss: 0.09716 FastRCNN total loss: 0.21848 L1 loss: 0.0000e+00 L2 loss: 1.48435 Learning rate: 0.02 Mask loss: 0.16249 RPN box loss: 0.00831 RPN score loss: 0.00573 RPN total loss: 0.01404 Total loss: 1.87937 timestamp: 1654924617.8585281 iteration: 11700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18997 FastRCNN class loss: 0.10464 FastRCNN total loss: 0.29461 L1 loss: 0.0000e+00 L2 loss: 1.48411 Learning rate: 0.02 Mask loss: 0.16472 RPN box loss: 0.01302 RPN score loss: 0.00412 RPN total loss: 0.01714 Total loss: 1.96056 timestamp: 1654924621.1386554 iteration: 11705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21415 FastRCNN class loss: 0.1392 FastRCNN total loss: 0.35335 L1 loss: 0.0000e+00 L2 loss: 1.48384 Learning rate: 0.02 Mask loss: 0.19706 RPN box loss: 0.05586 RPN score loss: 0.01745 RPN total loss: 0.07332 Total loss: 2.10756 timestamp: 1654924624.3264852 iteration: 11710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14222 FastRCNN class loss: 0.12194 FastRCNN total loss: 0.26416 L1 loss: 0.0000e+00 L2 loss: 1.48356 Learning rate: 0.02 Mask loss: 0.17131 RPN box loss: 0.08059 RPN score loss: 0.01246 RPN total loss: 0.09304 Total loss: 2.01208 timestamp: 1654924627.7038393 iteration: 11715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1914 FastRCNN class loss: 0.11232 FastRCNN total loss: 0.30372 L1 loss: 0.0000e+00 L2 loss: 1.48329 Learning rate: 0.02 Mask loss: 0.20831 RPN box loss: 0.03461 RPN score loss: 0.00909 RPN total loss: 0.0437 Total loss: 2.03902 timestamp: 1654924630.8895216 iteration: 11720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16293 FastRCNN class loss: 0.06536 FastRCNN total loss: 0.2283 L1 loss: 0.0000e+00 L2 loss: 1.48303 Learning rate: 0.02 Mask loss: 0.11897 RPN box loss: 0.05933 RPN score loss: 0.00765 RPN total loss: 0.06698 Total loss: 1.89727 timestamp: 1654924634.105664 iteration: 11725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21337 FastRCNN class loss: 0.13205 FastRCNN total loss: 0.34543 L1 loss: 0.0000e+00 L2 loss: 1.48278 Learning rate: 0.02 Mask loss: 0.25421 RPN box loss: 0.06677 RPN score loss: 0.01961 RPN total loss: 0.08638 Total loss: 2.1688 timestamp: 1654924637.3203008 iteration: 11730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16564 FastRCNN class loss: 0.10136 FastRCNN total loss: 0.267 L1 loss: 0.0000e+00 L2 loss: 1.48254 Learning rate: 0.02 Mask loss: 0.21016 RPN box loss: 0.01828 RPN score loss: 0.00318 RPN total loss: 0.02146 Total loss: 1.98116 timestamp: 1654924640.6566057 iteration: 11735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16084 FastRCNN class loss: 0.12344 FastRCNN total loss: 0.28428 L1 loss: 0.0000e+00 L2 loss: 1.48227 Learning rate: 0.02 Mask loss: 0.1451 RPN box loss: 0.04122 RPN score loss: 0.01391 RPN total loss: 0.05513 Total loss: 1.96678 timestamp: 1654924643.8714473 iteration: 11740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18488 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.25974 L1 loss: 0.0000e+00 L2 loss: 1.48201 Learning rate: 0.02 Mask loss: 0.15587 RPN box loss: 0.01557 RPN score loss: 0.00456 RPN total loss: 0.02013 Total loss: 1.91776 timestamp: 1654924647.21862 iteration: 11745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16107 FastRCNN class loss: 0.08518 FastRCNN total loss: 0.24625 L1 loss: 0.0000e+00 L2 loss: 1.48174 Learning rate: 0.02 Mask loss: 0.14502 RPN box loss: 0.03354 RPN score loss: 0.0031 RPN total loss: 0.03663 Total loss: 1.90965 timestamp: 1654924650.4118109 iteration: 11750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12358 FastRCNN class loss: 0.05642 FastRCNN total loss: 0.18 L1 loss: 0.0000e+00 L2 loss: 1.48146 Learning rate: 0.02 Mask loss: 0.16133 RPN box loss: 0.03759 RPN score loss: 0.00246 RPN total loss: 0.04005 Total loss: 1.86284 timestamp: 1654924653.6435852 iteration: 11755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09368 FastRCNN class loss: 0.05436 FastRCNN total loss: 0.14804 L1 loss: 0.0000e+00 L2 loss: 1.48119 Learning rate: 0.02 Mask loss: 0.14316 RPN box loss: 0.0166 RPN score loss: 0.00238 RPN total loss: 0.01897 Total loss: 1.79137 timestamp: 1654924657.0269477 iteration: 11760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25529 FastRCNN class loss: 0.17919 FastRCNN total loss: 0.43449 L1 loss: 0.0000e+00 L2 loss: 1.48095 Learning rate: 0.02 Mask loss: 0.14817 RPN box loss: 0.02788 RPN score loss: 0.01329 RPN total loss: 0.04117 Total loss: 2.10479 timestamp: 1654924660.2994547 iteration: 11765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19972 FastRCNN class loss: 0.09507 FastRCNN total loss: 0.29479 L1 loss: 0.0000e+00 L2 loss: 1.48069 Learning rate: 0.02 Mask loss: 0.24273 RPN box loss: 0.08263 RPN score loss: 0.01812 RPN total loss: 0.10075 Total loss: 2.11896 timestamp: 1654924663.522101 iteration: 11770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19344 FastRCNN class loss: 0.10011 FastRCNN total loss: 0.29354 L1 loss: 0.0000e+00 L2 loss: 1.48044 Learning rate: 0.02 Mask loss: 0.17605 RPN box loss: 0.04762 RPN score loss: 0.01192 RPN total loss: 0.05954 Total loss: 2.00957 timestamp: 1654924666.7177863 iteration: 11775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15115 FastRCNN class loss: 0.08107 FastRCNN total loss: 0.23222 L1 loss: 0.0000e+00 L2 loss: 1.48016 Learning rate: 0.02 Mask loss: 0.1791 RPN box loss: 0.06235 RPN score loss: 0.00606 RPN total loss: 0.06841 Total loss: 1.95988 timestamp: 1654924669.9287531 iteration: 11780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21161 FastRCNN class loss: 0.07934 FastRCNN total loss: 0.29095 L1 loss: 0.0000e+00 L2 loss: 1.47988 Learning rate: 0.02 Mask loss: 0.15276 RPN box loss: 0.07127 RPN score loss: 0.00602 RPN total loss: 0.07729 Total loss: 2.00087 timestamp: 1654924673.1816947 iteration: 11785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12022 FastRCNN class loss: 0.0604 FastRCNN total loss: 0.18062 L1 loss: 0.0000e+00 L2 loss: 1.47961 Learning rate: 0.02 Mask loss: 0.13024 RPN box loss: 0.00855 RPN score loss: 0.00537 RPN total loss: 0.01392 Total loss: 1.80438 timestamp: 1654924676.44824 iteration: 11790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29207 FastRCNN class loss: 0.10992 FastRCNN total loss: 0.402 L1 loss: 0.0000e+00 L2 loss: 1.47935 Learning rate: 0.02 Mask loss: 0.21385 RPN box loss: 0.0588 RPN score loss: 0.01977 RPN total loss: 0.07857 Total loss: 2.17377 timestamp: 1654924679.6513612 iteration: 11795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.14325 L1 loss: 0.0000e+00 L2 loss: 1.47907 Learning rate: 0.02 Mask loss: 0.17865 RPN box loss: 0.02389 RPN score loss: 0.00319 RPN total loss: 0.02707 Total loss: 1.82804 timestamp: 1654924682.9307032 iteration: 11800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24363 FastRCNN class loss: 0.12494 FastRCNN total loss: 0.36856 L1 loss: 0.0000e+00 L2 loss: 1.4788 Learning rate: 0.02 Mask loss: 0.36733 RPN box loss: 0.09792 RPN score loss: 0.01357 RPN total loss: 0.11149 Total loss: 2.32618 timestamp: 1654924686.1245253 iteration: 11805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1347 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.20643 L1 loss: 0.0000e+00 L2 loss: 1.47854 Learning rate: 0.02 Mask loss: 0.14831 RPN box loss: 0.0136 RPN score loss: 0.00891 RPN total loss: 0.02251 Total loss: 1.85579 timestamp: 1654924689.3950946 iteration: 11810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15822 FastRCNN class loss: 0.07467 FastRCNN total loss: 0.2329 L1 loss: 0.0000e+00 L2 loss: 1.47829 Learning rate: 0.02 Mask loss: 0.12052 RPN box loss: 0.00939 RPN score loss: 0.00373 RPN total loss: 0.01312 Total loss: 1.84483 timestamp: 1654924692.7146368 iteration: 11815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20029 FastRCNN class loss: 0.09052 FastRCNN total loss: 0.29081 L1 loss: 0.0000e+00 L2 loss: 1.47801 Learning rate: 0.02 Mask loss: 0.20306 RPN box loss: 0.06248 RPN score loss: 0.01008 RPN total loss: 0.07256 Total loss: 2.04444 timestamp: 1654924695.9613962 iteration: 11820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23489 FastRCNN class loss: 0.10006 FastRCNN total loss: 0.33495 L1 loss: 0.0000e+00 L2 loss: 1.47776 Learning rate: 0.02 Mask loss: 0.15278 RPN box loss: 0.02904 RPN score loss: 0.00765 RPN total loss: 0.0367 Total loss: 2.00219 timestamp: 1654924699.3759687 iteration: 11825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19041 FastRCNN class loss: 0.13871 FastRCNN total loss: 0.32912 L1 loss: 0.0000e+00 L2 loss: 1.47752 Learning rate: 0.02 Mask loss: 0.22436 RPN box loss: 0.06765 RPN score loss: 0.01161 RPN total loss: 0.07926 Total loss: 2.11027 timestamp: 1654924702.558297 iteration: 11830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11899 FastRCNN class loss: 0.04686 FastRCNN total loss: 0.16585 L1 loss: 0.0000e+00 L2 loss: 1.47726 Learning rate: 0.02 Mask loss: 0.11955 RPN box loss: 0.045 RPN score loss: 0.008 RPN total loss: 0.053 Total loss: 1.81565 timestamp: 1654924705.7873788 iteration: 11835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23068 FastRCNN class loss: 0.09948 FastRCNN total loss: 0.33016 L1 loss: 0.0000e+00 L2 loss: 1.47699 Learning rate: 0.02 Mask loss: 0.14508 RPN box loss: 0.02606 RPN score loss: 0.00532 RPN total loss: 0.03137 Total loss: 1.9836 timestamp: 1654924708.9874325 iteration: 11840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08144 FastRCNN class loss: 0.06852 FastRCNN total loss: 0.14996 L1 loss: 0.0000e+00 L2 loss: 1.47672 Learning rate: 0.02 Mask loss: 0.11063 RPN box loss: 0.0237 RPN score loss: 0.00544 RPN total loss: 0.02914 Total loss: 1.76645 timestamp: 1654924712.2507844 iteration: 11845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09034 FastRCNN class loss: 0.09759 FastRCNN total loss: 0.18793 L1 loss: 0.0000e+00 L2 loss: 1.47644 Learning rate: 0.02 Mask loss: 0.1226 RPN box loss: 0.02796 RPN score loss: 0.01002 RPN total loss: 0.03798 Total loss: 1.82494 timestamp: 1654924715.37211 iteration: 11850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11337 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.18092 L1 loss: 0.0000e+00 L2 loss: 1.47617 Learning rate: 0.02 Mask loss: 0.15597 RPN box loss: 0.12383 RPN score loss: 0.00889 RPN total loss: 0.13272 Total loss: 1.94577 timestamp: 1654924718.6987853 iteration: 11855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17397 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.26809 L1 loss: 0.0000e+00 L2 loss: 1.4759 Learning rate: 0.02 Mask loss: 0.15013 RPN box loss: 0.05467 RPN score loss: 0.006 RPN total loss: 0.06067 Total loss: 1.9548 timestamp: 1654924721.9642465 iteration: 11860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16349 FastRCNN class loss: 0.09821 FastRCNN total loss: 0.2617 L1 loss: 0.0000e+00 L2 loss: 1.47566 Learning rate: 0.02 Mask loss: 0.19691 RPN box loss: 0.05007 RPN score loss: 0.00463 RPN total loss: 0.0547 Total loss: 1.98896 timestamp: 1654924725.1473093 iteration: 11865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18971 FastRCNN class loss: 0.12609 FastRCNN total loss: 0.3158 L1 loss: 0.0000e+00 L2 loss: 1.47541 Learning rate: 0.02 Mask loss: 0.17149 RPN box loss: 0.04144 RPN score loss: 0.02206 RPN total loss: 0.06351 Total loss: 2.0262 timestamp: 1654924728.3912508 iteration: 11870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23295 FastRCNN class loss: 0.11671 FastRCNN total loss: 0.34966 L1 loss: 0.0000e+00 L2 loss: 1.47513 Learning rate: 0.02 Mask loss: 0.18941 RPN box loss: 0.07623 RPN score loss: 0.00779 RPN total loss: 0.08402 Total loss: 2.09822 timestamp: 1654924731.6182313 iteration: 11875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14024 FastRCNN class loss: 0.06305 FastRCNN total loss: 0.20329 L1 loss: 0.0000e+00 L2 loss: 1.47488 Learning rate: 0.02 Mask loss: 0.19442 RPN box loss: 0.02918 RPN score loss: 0.0054 RPN total loss: 0.03458 Total loss: 1.90717 timestamp: 1654924734.7213674 iteration: 11880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08809 FastRCNN class loss: 0.06092 FastRCNN total loss: 0.14901 L1 loss: 0.0000e+00 L2 loss: 1.47462 Learning rate: 0.02 Mask loss: 0.1847 RPN box loss: 0.02534 RPN score loss: 0.00692 RPN total loss: 0.03226 Total loss: 1.84059 timestamp: 1654924737.9694593 iteration: 11885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16686 FastRCNN class loss: 0.08812 FastRCNN total loss: 0.25498 L1 loss: 0.0000e+00 L2 loss: 1.47435 Learning rate: 0.02 Mask loss: 0.24056 RPN box loss: 0.0273 RPN score loss: 0.00265 RPN total loss: 0.02995 Total loss: 1.99985 timestamp: 1654924741.337112 iteration: 11890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10772 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.18074 L1 loss: 0.0000e+00 L2 loss: 1.47408 Learning rate: 0.02 Mask loss: 0.16285 RPN box loss: 0.0137 RPN score loss: 0.00894 RPN total loss: 0.02265 Total loss: 1.84032 timestamp: 1654924744.602909 iteration: 11895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16594 FastRCNN class loss: 0.09996 FastRCNN total loss: 0.2659 L1 loss: 0.0000e+00 L2 loss: 1.47383 Learning rate: 0.02 Mask loss: 0.18672 RPN box loss: 0.07545 RPN score loss: 0.00854 RPN total loss: 0.08398 Total loss: 2.01043 timestamp: 1654924747.8086135 iteration: 11900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10705 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.16408 L1 loss: 0.0000e+00 L2 loss: 1.47356 Learning rate: 0.02 Mask loss: 0.15776 RPN box loss: 0.06979 RPN score loss: 0.01284 RPN total loss: 0.08263 Total loss: 1.87804 timestamp: 1654924751.050258 iteration: 11905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13777 FastRCNN class loss: 0.07128 FastRCNN total loss: 0.20906 L1 loss: 0.0000e+00 L2 loss: 1.47331 Learning rate: 0.02 Mask loss: 0.16125 RPN box loss: 0.08097 RPN score loss: 0.00916 RPN total loss: 0.09012 Total loss: 1.93374 timestamp: 1654924754.2847424 iteration: 11910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26872 FastRCNN class loss: 0.18526 FastRCNN total loss: 0.45397 L1 loss: 0.0000e+00 L2 loss: 1.47304 Learning rate: 0.02 Mask loss: 0.28853 RPN box loss: 0.08893 RPN score loss: 0.01084 RPN total loss: 0.09977 Total loss: 2.31531 timestamp: 1654924757.4649453 iteration: 11915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1309 FastRCNN class loss: 0.05342 FastRCNN total loss: 0.18432 L1 loss: 0.0000e+00 L2 loss: 1.47278 Learning rate: 0.02 Mask loss: 0.13827 RPN box loss: 0.13851 RPN score loss: 0.01086 RPN total loss: 0.14937 Total loss: 1.94475 timestamp: 1654924760.856659 iteration: 11920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18719 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.26753 L1 loss: 0.0000e+00 L2 loss: 1.47254 Learning rate: 0.02 Mask loss: 0.16732 RPN box loss: 0.01125 RPN score loss: 0.00374 RPN total loss: 0.01499 Total loss: 1.92238 timestamp: 1654924764.097597 iteration: 11925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15216 FastRCNN class loss: 0.07488 FastRCNN total loss: 0.22704 L1 loss: 0.0000e+00 L2 loss: 1.47226 Learning rate: 0.02 Mask loss: 0.23532 RPN box loss: 0.03738 RPN score loss: 0.01085 RPN total loss: 0.04823 Total loss: 1.98285 timestamp: 1654924767.3218136 iteration: 11930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20793 FastRCNN class loss: 0.10634 FastRCNN total loss: 0.31428 L1 loss: 0.0000e+00 L2 loss: 1.472 Learning rate: 0.02 Mask loss: 0.18575 RPN box loss: 0.01211 RPN score loss: 0.00634 RPN total loss: 0.01845 Total loss: 1.99048 timestamp: 1654924770.6150954 iteration: 11935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2076 FastRCNN class loss: 0.13326 FastRCNN total loss: 0.34087 L1 loss: 0.0000e+00 L2 loss: 1.47175 Learning rate: 0.02 Mask loss: 0.22227 RPN box loss: 0.0854 RPN score loss: 0.02132 RPN total loss: 0.10672 Total loss: 2.14161 timestamp: 1654924773.7810135 iteration: 11940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17363 FastRCNN class loss: 0.09797 FastRCNN total loss: 0.27161 L1 loss: 0.0000e+00 L2 loss: 1.47149 Learning rate: 0.02 Mask loss: 0.19533 RPN box loss: 0.02152 RPN score loss: 0.00418 RPN total loss: 0.0257 Total loss: 1.96412 timestamp: 1654924777.044534 iteration: 11945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10833 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.18616 L1 loss: 0.0000e+00 L2 loss: 1.47123 Learning rate: 0.02 Mask loss: 0.12901 RPN box loss: 0.0156 RPN score loss: 0.00286 RPN total loss: 0.01846 Total loss: 1.80487 timestamp: 1654924780.2316537 iteration: 11950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17751 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.24419 L1 loss: 0.0000e+00 L2 loss: 1.47101 Learning rate: 0.02 Mask loss: 0.18881 RPN box loss: 0.06978 RPN score loss: 0.00535 RPN total loss: 0.07513 Total loss: 1.97914 timestamp: 1654924783.502688 iteration: 11955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18351 FastRCNN class loss: 0.08802 FastRCNN total loss: 0.27152 L1 loss: 0.0000e+00 L2 loss: 1.47074 Learning rate: 0.02 Mask loss: 0.13277 RPN box loss: 0.05534 RPN score loss: 0.00887 RPN total loss: 0.06421 Total loss: 1.93925 timestamp: 1654924786.720848 iteration: 11960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.18822 L1 loss: 0.0000e+00 L2 loss: 1.47049 Learning rate: 0.02 Mask loss: 0.13235 RPN box loss: 0.02844 RPN score loss: 0.00547 RPN total loss: 0.03392 Total loss: 1.82498 timestamp: 1654924790.0043736 iteration: 11965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14263 FastRCNN class loss: 0.11194 FastRCNN total loss: 0.25456 L1 loss: 0.0000e+00 L2 loss: 1.47023 Learning rate: 0.02 Mask loss: 0.17864 RPN box loss: 0.05594 RPN score loss: 0.00649 RPN total loss: 0.06244 Total loss: 1.96586 timestamp: 1654924793.1363804 iteration: 11970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12592 FastRCNN class loss: 0.1178 FastRCNN total loss: 0.24372 L1 loss: 0.0000e+00 L2 loss: 1.46996 Learning rate: 0.02 Mask loss: 0.19716 RPN box loss: 0.01217 RPN score loss: 0.00468 RPN total loss: 0.01684 Total loss: 1.92768 timestamp: 1654924796.5765858 iteration: 11975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17398 FastRCNN class loss: 0.16627 FastRCNN total loss: 0.34026 L1 loss: 0.0000e+00 L2 loss: 1.46971 Learning rate: 0.02 Mask loss: 0.23852 RPN box loss: 0.02326 RPN score loss: 0.01527 RPN total loss: 0.03853 Total loss: 2.08702 timestamp: 1654924799.7547777 iteration: 11980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09941 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.16584 L1 loss: 0.0000e+00 L2 loss: 1.46947 Learning rate: 0.02 Mask loss: 0.16478 RPN box loss: 0.02785 RPN score loss: 0.01306 RPN total loss: 0.04091 Total loss: 1.841 timestamp: 1654924803.0091128 iteration: 11985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18874 FastRCNN class loss: 0.09937 FastRCNN total loss: 0.28811 L1 loss: 0.0000e+00 L2 loss: 1.4692 Learning rate: 0.02 Mask loss: 0.18759 RPN box loss: 0.05929 RPN score loss: 0.0151 RPN total loss: 0.07439 Total loss: 2.01929 timestamp: 1654924806.25013 iteration: 11990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18061 FastRCNN class loss: 0.09489 FastRCNN total loss: 0.2755 L1 loss: 0.0000e+00 L2 loss: 1.46894 Learning rate: 0.02 Mask loss: 0.24051 RPN box loss: 0.04165 RPN score loss: 0.00572 RPN total loss: 0.04738 Total loss: 2.03233 timestamp: 1654924809.519937 iteration: 11995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11918 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.19152 L1 loss: 0.0000e+00 L2 loss: 1.46867 Learning rate: 0.02 Mask loss: 0.16238 RPN box loss: 0.04673 RPN score loss: 0.00447 RPN total loss: 0.0512 Total loss: 1.87378 timestamp: 1654924812.7804384 iteration: 12000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18698 FastRCNN class loss: 0.12111 FastRCNN total loss: 0.3081 L1 loss: 0.0000e+00 L2 loss: 1.46842 Learning rate: 0.02 Mask loss: 0.15791 RPN box loss: 0.01688 RPN score loss: 0.00802 RPN total loss: 0.02491 Total loss: 1.95933 timestamp: 1654924816.0612829 iteration: 12005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1162 FastRCNN class loss: 0.0512 FastRCNN total loss: 0.1674 L1 loss: 0.0000e+00 L2 loss: 1.46816 Learning rate: 0.02 Mask loss: 0.18789 RPN box loss: 0.00457 RPN score loss: 0.00351 RPN total loss: 0.00808 Total loss: 1.83153 timestamp: 1654924819.3346524 iteration: 12010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22711 FastRCNN class loss: 0.09691 FastRCNN total loss: 0.32401 L1 loss: 0.0000e+00 L2 loss: 1.46789 Learning rate: 0.02 Mask loss: 0.26455 RPN box loss: 0.02728 RPN score loss: 0.00806 RPN total loss: 0.03534 Total loss: 2.0918 timestamp: 1654924822.588479 iteration: 12015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20709 FastRCNN class loss: 0.12181 FastRCNN total loss: 0.3289 L1 loss: 0.0000e+00 L2 loss: 1.46765 Learning rate: 0.02 Mask loss: 0.16381 RPN box loss: 0.04893 RPN score loss: 0.01213 RPN total loss: 0.06106 Total loss: 2.02143 timestamp: 1654924825.8974848 iteration: 12020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19942 FastRCNN class loss: 0.11558 FastRCNN total loss: 0.31501 L1 loss: 0.0000e+00 L2 loss: 1.4674 Learning rate: 0.02 Mask loss: 0.1888 RPN box loss: 0.07018 RPN score loss: 0.01323 RPN total loss: 0.08341 Total loss: 2.05461 timestamp: 1654924829.1915941 iteration: 12025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19472 FastRCNN class loss: 0.13463 FastRCNN total loss: 0.32935 L1 loss: 0.0000e+00 L2 loss: 1.46715 Learning rate: 0.02 Mask loss: 0.15454 RPN box loss: 0.10282 RPN score loss: 0.01127 RPN total loss: 0.11409 Total loss: 2.06512 timestamp: 1654924832.6269302 iteration: 12030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16712 FastRCNN class loss: 0.1059 FastRCNN total loss: 0.27301 L1 loss: 0.0000e+00 L2 loss: 1.4669 Learning rate: 0.02 Mask loss: 0.20116 RPN box loss: 0.02998 RPN score loss: 0.00823 RPN total loss: 0.0382 Total loss: 1.97927 timestamp: 1654924835.8454642 iteration: 12035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10545 FastRCNN class loss: 0.06035 FastRCNN total loss: 0.1658 L1 loss: 0.0000e+00 L2 loss: 1.46662 Learning rate: 0.02 Mask loss: 0.13833 RPN box loss: 0.10206 RPN score loss: 0.00566 RPN total loss: 0.10772 Total loss: 1.87846 timestamp: 1654924839.084589 iteration: 12040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14296 FastRCNN class loss: 0.0632 FastRCNN total loss: 0.20616 L1 loss: 0.0000e+00 L2 loss: 1.46636 Learning rate: 0.02 Mask loss: 0.10557 RPN box loss: 0.04177 RPN score loss: 0.00873 RPN total loss: 0.0505 Total loss: 1.8286 timestamp: 1654924842.425844 iteration: 12045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17611 FastRCNN class loss: 0.10686 FastRCNN total loss: 0.28296 L1 loss: 0.0000e+00 L2 loss: 1.46611 Learning rate: 0.02 Mask loss: 0.17733 RPN box loss: 0.08115 RPN score loss: 0.0133 RPN total loss: 0.09445 Total loss: 2.02086 timestamp: 1654924845.654245 iteration: 12050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16688 FastRCNN class loss: 0.04538 FastRCNN total loss: 0.21226 L1 loss: 0.0000e+00 L2 loss: 1.46583 Learning rate: 0.02 Mask loss: 0.23953 RPN box loss: 0.0323 RPN score loss: 0.00394 RPN total loss: 0.03624 Total loss: 1.95385 timestamp: 1654924849.0063508 iteration: 12055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17139 FastRCNN class loss: 0.10738 FastRCNN total loss: 0.27877 L1 loss: 0.0000e+00 L2 loss: 1.46559 Learning rate: 0.02 Mask loss: 0.16773 RPN box loss: 0.02356 RPN score loss: 0.00816 RPN total loss: 0.03172 Total loss: 1.94381 timestamp: 1654924852.1406262 iteration: 12060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19132 FastRCNN class loss: 0.0995 FastRCNN total loss: 0.29082 L1 loss: 0.0000e+00 L2 loss: 1.46534 Learning rate: 0.02 Mask loss: 0.13364 RPN box loss: 0.02351 RPN score loss: 0.00755 RPN total loss: 0.03106 Total loss: 1.92085 timestamp: 1654924855.4295902 iteration: 12065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1594 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.25976 L1 loss: 0.0000e+00 L2 loss: 1.46507 Learning rate: 0.02 Mask loss: 0.17677 RPN box loss: 0.05262 RPN score loss: 0.0112 RPN total loss: 0.06382 Total loss: 1.96542 timestamp: 1654924858.6588004 iteration: 12070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16327 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.21967 L1 loss: 0.0000e+00 L2 loss: 1.4648 Learning rate: 0.02 Mask loss: 0.13561 RPN box loss: 0.02232 RPN score loss: 0.00519 RPN total loss: 0.02751 Total loss: 1.84759 timestamp: 1654924861.9145267 iteration: 12075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09047 FastRCNN class loss: 0.04857 FastRCNN total loss: 0.13904 L1 loss: 0.0000e+00 L2 loss: 1.46451 Learning rate: 0.02 Mask loss: 0.15595 RPN box loss: 0.02099 RPN score loss: 0.01606 RPN total loss: 0.03704 Total loss: 1.79653 timestamp: 1654924865.0744643 iteration: 12080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09695 FastRCNN class loss: 0.04192 FastRCNN total loss: 0.13887 L1 loss: 0.0000e+00 L2 loss: 1.46427 Learning rate: 0.02 Mask loss: 0.10698 RPN box loss: 0.04041 RPN score loss: 0.00177 RPN total loss: 0.04218 Total loss: 1.75229 timestamp: 1654924868.4217415 iteration: 12085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14583 FastRCNN class loss: 0.07719 FastRCNN total loss: 0.22302 L1 loss: 0.0000e+00 L2 loss: 1.46403 Learning rate: 0.02 Mask loss: 0.18845 RPN box loss: 0.01471 RPN score loss: 0.00325 RPN total loss: 0.01796 Total loss: 1.89347 timestamp: 1654924871.5738804 iteration: 12090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14504 FastRCNN class loss: 0.06812 FastRCNN total loss: 0.21316 L1 loss: 0.0000e+00 L2 loss: 1.46374 Learning rate: 0.02 Mask loss: 0.15833 RPN box loss: 0.07538 RPN score loss: 0.01284 RPN total loss: 0.08821 Total loss: 1.92345 timestamp: 1654924874.7391384 iteration: 12095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13957 FastRCNN class loss: 0.11239 FastRCNN total loss: 0.25196 L1 loss: 0.0000e+00 L2 loss: 1.46349 Learning rate: 0.02 Mask loss: 0.19671 RPN box loss: 0.02348 RPN score loss: 0.0022 RPN total loss: 0.02568 Total loss: 1.93784 timestamp: 1654924878.0641482 iteration: 12100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14055 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.22194 L1 loss: 0.0000e+00 L2 loss: 1.46324 Learning rate: 0.02 Mask loss: 0.1148 RPN box loss: 0.09135 RPN score loss: 0.01211 RPN total loss: 0.10346 Total loss: 1.90344 timestamp: 1654924881.286231 iteration: 12105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.10545 FastRCNN total loss: 0.24501 L1 loss: 0.0000e+00 L2 loss: 1.46297 Learning rate: 0.02 Mask loss: 0.19314 RPN box loss: 0.03674 RPN score loss: 0.00886 RPN total loss: 0.0456 Total loss: 1.94672 timestamp: 1654924884.581267 iteration: 12110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19349 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.27099 L1 loss: 0.0000e+00 L2 loss: 1.46268 Learning rate: 0.02 Mask loss: 0.13129 RPN box loss: 0.04699 RPN score loss: 0.00883 RPN total loss: 0.05582 Total loss: 1.92078 timestamp: 1654924887.7647796 iteration: 12115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20675 FastRCNN class loss: 0.12612 FastRCNN total loss: 0.33287 L1 loss: 0.0000e+00 L2 loss: 1.4624 Learning rate: 0.02 Mask loss: 0.15262 RPN box loss: 0.03783 RPN score loss: 0.00971 RPN total loss: 0.04753 Total loss: 1.99543 timestamp: 1654924891.0474901 iteration: 12120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1634 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.25715 L1 loss: 0.0000e+00 L2 loss: 1.46216 Learning rate: 0.02 Mask loss: 0.1941 RPN box loss: 0.04566 RPN score loss: 0.00746 RPN total loss: 0.05312 Total loss: 1.96653 timestamp: 1654924894.2786348 iteration: 12125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10135 FastRCNN class loss: 0.08808 FastRCNN total loss: 0.18943 L1 loss: 0.0000e+00 L2 loss: 1.46193 Learning rate: 0.02 Mask loss: 0.13504 RPN box loss: 0.04233 RPN score loss: 0.01013 RPN total loss: 0.05246 Total loss: 1.83886 timestamp: 1654924897.4016857 iteration: 12130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10697 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.163 L1 loss: 0.0000e+00 L2 loss: 1.46168 Learning rate: 0.02 Mask loss: 0.09752 RPN box loss: 0.02203 RPN score loss: 0.00285 RPN total loss: 0.02489 Total loss: 1.74707 timestamp: 1654924900.5684793 iteration: 12135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15617 FastRCNN class loss: 0.07376 FastRCNN total loss: 0.22994 L1 loss: 0.0000e+00 L2 loss: 1.46141 Learning rate: 0.02 Mask loss: 0.13578 RPN box loss: 0.02216 RPN score loss: 0.00747 RPN total loss: 0.02964 Total loss: 1.85677 timestamp: 1654924903.861211 iteration: 12140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15368 FastRCNN class loss: 0.116 FastRCNN total loss: 0.26969 L1 loss: 0.0000e+00 L2 loss: 1.46113 Learning rate: 0.02 Mask loss: 0.16447 RPN box loss: 0.02796 RPN score loss: 0.00527 RPN total loss: 0.03323 Total loss: 1.92852 timestamp: 1654924907.1243236 iteration: 12145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22363 FastRCNN class loss: 0.12506 FastRCNN total loss: 0.3487 L1 loss: 0.0000e+00 L2 loss: 1.46086 Learning rate: 0.02 Mask loss: 0.25403 RPN box loss: 0.07793 RPN score loss: 0.01325 RPN total loss: 0.09118 Total loss: 2.15476 timestamp: 1654924910.4603105 iteration: 12150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17966 FastRCNN class loss: 0.09858 FastRCNN total loss: 0.27824 L1 loss: 0.0000e+00 L2 loss: 1.4606 Learning rate: 0.02 Mask loss: 0.19342 RPN box loss: 0.06233 RPN score loss: 0.02604 RPN total loss: 0.08837 Total loss: 2.02063 timestamp: 1654924913.7452652 iteration: 12155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18186 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.26492 L1 loss: 0.0000e+00 L2 loss: 1.46033 Learning rate: 0.02 Mask loss: 0.19217 RPN box loss: 0.06051 RPN score loss: 0.01159 RPN total loss: 0.07211 Total loss: 1.98952 timestamp: 1654924916.9198642 iteration: 12160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1156 FastRCNN class loss: 0.12474 FastRCNN total loss: 0.24033 L1 loss: 0.0000e+00 L2 loss: 1.46011 Learning rate: 0.02 Mask loss: 0.11786 RPN box loss: 0.0323 RPN score loss: 0.01165 RPN total loss: 0.04395 Total loss: 1.86226 timestamp: 1654924920.2189195 iteration: 12165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20884 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.28505 L1 loss: 0.0000e+00 L2 loss: 1.45987 Learning rate: 0.02 Mask loss: 0.17172 RPN box loss: 0.01392 RPN score loss: 0.00965 RPN total loss: 0.02357 Total loss: 1.9402 timestamp: 1654924923.465413 iteration: 12170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19875 FastRCNN class loss: 0.08544 FastRCNN total loss: 0.28419 L1 loss: 0.0000e+00 L2 loss: 1.4596 Learning rate: 0.02 Mask loss: 0.13494 RPN box loss: 0.08116 RPN score loss: 0.00706 RPN total loss: 0.08822 Total loss: 1.96696 timestamp: 1654924926.6257982 iteration: 12175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14326 FastRCNN class loss: 0.08737 FastRCNN total loss: 0.23062 L1 loss: 0.0000e+00 L2 loss: 1.45936 Learning rate: 0.02 Mask loss: 0.14433 RPN box loss: 0.03441 RPN score loss: 0.01175 RPN total loss: 0.04616 Total loss: 1.88047 timestamp: 1654924929.814999 iteration: 12180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21781 FastRCNN class loss: 0.16922 FastRCNN total loss: 0.38702 L1 loss: 0.0000e+00 L2 loss: 1.45909 Learning rate: 0.02 Mask loss: 0.14904 RPN box loss: 0.01731 RPN score loss: 0.00811 RPN total loss: 0.02542 Total loss: 2.02058 timestamp: 1654924933.0727754 iteration: 12185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09431 FastRCNN class loss: 0.05692 FastRCNN total loss: 0.15123 L1 loss: 0.0000e+00 L2 loss: 1.45883 Learning rate: 0.02 Mask loss: 0.12578 RPN box loss: 0.0387 RPN score loss: 0.00658 RPN total loss: 0.04528 Total loss: 1.78112 timestamp: 1654924936.2769163 iteration: 12190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16587 FastRCNN class loss: 0.09271 FastRCNN total loss: 0.25858 L1 loss: 0.0000e+00 L2 loss: 1.45855 Learning rate: 0.02 Mask loss: 0.15622 RPN box loss: 0.04572 RPN score loss: 0.0102 RPN total loss: 0.05592 Total loss: 1.92927 timestamp: 1654924939.4876218 iteration: 12195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19045 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.27418 L1 loss: 0.0000e+00 L2 loss: 1.45828 Learning rate: 0.02 Mask loss: 0.3151 RPN box loss: 0.02369 RPN score loss: 0.00953 RPN total loss: 0.03323 Total loss: 2.08079 timestamp: 1654924942.8314486 iteration: 12200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1189 FastRCNN class loss: 0.10067 FastRCNN total loss: 0.21958 L1 loss: 0.0000e+00 L2 loss: 1.45803 Learning rate: 0.02 Mask loss: 0.13273 RPN box loss: 0.03579 RPN score loss: 0.00506 RPN total loss: 0.04084 Total loss: 1.85118 timestamp: 1654924946.0834906 iteration: 12205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11532 FastRCNN class loss: 0.05153 FastRCNN total loss: 0.16685 L1 loss: 0.0000e+00 L2 loss: 1.45778 Learning rate: 0.02 Mask loss: 0.13544 RPN box loss: 0.0203 RPN score loss: 0.00615 RPN total loss: 0.02645 Total loss: 1.78652 timestamp: 1654924949.34906 iteration: 12210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19091 FastRCNN class loss: 0.13975 FastRCNN total loss: 0.33066 L1 loss: 0.0000e+00 L2 loss: 1.45753 Learning rate: 0.02 Mask loss: 0.24749 RPN box loss: 0.03813 RPN score loss: 0.02032 RPN total loss: 0.05846 Total loss: 2.09414 timestamp: 1654924952.5497394 iteration: 12215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18033 FastRCNN class loss: 0.11412 FastRCNN total loss: 0.29445 L1 loss: 0.0000e+00 L2 loss: 1.45728 Learning rate: 0.02 Mask loss: 0.2195 RPN box loss: 0.03272 RPN score loss: 0.00875 RPN total loss: 0.04148 Total loss: 2.0127 timestamp: 1654924955.924832 iteration: 12220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16235 FastRCNN class loss: 0.09492 FastRCNN total loss: 0.25727 L1 loss: 0.0000e+00 L2 loss: 1.457 Learning rate: 0.02 Mask loss: 0.1438 RPN box loss: 0.01481 RPN score loss: 0.00321 RPN total loss: 0.01802 Total loss: 1.8761 timestamp: 1654924959.1093569 iteration: 12225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22639 FastRCNN class loss: 0.10621 FastRCNN total loss: 0.33261 L1 loss: 0.0000e+00 L2 loss: 1.45674 Learning rate: 0.02 Mask loss: 0.1691 RPN box loss: 0.06248 RPN score loss: 0.00962 RPN total loss: 0.0721 Total loss: 2.03055 timestamp: 1654924962.2945995 iteration: 12230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20106 FastRCNN class loss: 0.06658 FastRCNN total loss: 0.26765 L1 loss: 0.0000e+00 L2 loss: 1.45649 Learning rate: 0.02 Mask loss: 0.16494 RPN box loss: 0.03272 RPN score loss: 0.0054 RPN total loss: 0.03812 Total loss: 1.9272 timestamp: 1654924965.4830353 iteration: 12235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13623 FastRCNN class loss: 0.09709 FastRCNN total loss: 0.23333 L1 loss: 0.0000e+00 L2 loss: 1.45623 Learning rate: 0.02 Mask loss: 0.1156 RPN box loss: 0.04323 RPN score loss: 0.01133 RPN total loss: 0.05456 Total loss: 1.85971 timestamp: 1654924968.7128375 iteration: 12240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1355 FastRCNN class loss: 0.1067 FastRCNN total loss: 0.2422 L1 loss: 0.0000e+00 L2 loss: 1.45596 Learning rate: 0.02 Mask loss: 0.23679 RPN box loss: 0.03768 RPN score loss: 0.00672 RPN total loss: 0.0444 Total loss: 1.97935 timestamp: 1654924971.8546968 iteration: 12245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13019 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.21739 L1 loss: 0.0000e+00 L2 loss: 1.45571 Learning rate: 0.02 Mask loss: 0.18993 RPN box loss: 0.0159 RPN score loss: 0.00416 RPN total loss: 0.02006 Total loss: 1.8831 timestamp: 1654924975.075059 iteration: 12250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22343 FastRCNN class loss: 0.11679 FastRCNN total loss: 0.34022 L1 loss: 0.0000e+00 L2 loss: 1.45544 Learning rate: 0.02 Mask loss: 0.14504 RPN box loss: 0.08929 RPN score loss: 0.01125 RPN total loss: 0.10054 Total loss: 2.04124 timestamp: 1654924978.2712317 iteration: 12255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.113 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.17145 L1 loss: 0.0000e+00 L2 loss: 1.45516 Learning rate: 0.02 Mask loss: 0.17557 RPN box loss: 0.02997 RPN score loss: 0.00643 RPN total loss: 0.03641 Total loss: 1.83858 timestamp: 1654924981.5970612 iteration: 12260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21552 FastRCNN class loss: 0.17212 FastRCNN total loss: 0.38765 L1 loss: 0.0000e+00 L2 loss: 1.45488 Learning rate: 0.02 Mask loss: 0.23467 RPN box loss: 0.04684 RPN score loss: 0.01461 RPN total loss: 0.06145 Total loss: 2.13865 timestamp: 1654924984.9590847 iteration: 12265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15392 FastRCNN class loss: 0.11182 FastRCNN total loss: 0.26573 L1 loss: 0.0000e+00 L2 loss: 1.45462 Learning rate: 0.02 Mask loss: 0.13295 RPN box loss: 0.08535 RPN score loss: 0.01013 RPN total loss: 0.09548 Total loss: 1.94878 timestamp: 1654924988.2215521 iteration: 12270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15391 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.21844 L1 loss: 0.0000e+00 L2 loss: 1.45438 Learning rate: 0.02 Mask loss: 0.13536 RPN box loss: 0.06989 RPN score loss: 0.00629 RPN total loss: 0.07618 Total loss: 1.88436 timestamp: 1654924991.4743671 iteration: 12275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08506 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.15146 L1 loss: 0.0000e+00 L2 loss: 1.45413 Learning rate: 0.02 Mask loss: 0.11233 RPN box loss: 0.03665 RPN score loss: 0.01321 RPN total loss: 0.04986 Total loss: 1.76778 timestamp: 1654924994.6507375 iteration: 12280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1645 FastRCNN class loss: 0.07927 FastRCNN total loss: 0.24377 L1 loss: 0.0000e+00 L2 loss: 1.45389 Learning rate: 0.02 Mask loss: 0.12972 RPN box loss: 0.0218 RPN score loss: 0.00477 RPN total loss: 0.02657 Total loss: 1.85394 timestamp: 1654924997.9842348 iteration: 12285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17768 FastRCNN class loss: 0.16195 FastRCNN total loss: 0.33963 L1 loss: 0.0000e+00 L2 loss: 1.45363 Learning rate: 0.02 Mask loss: 0.18586 RPN box loss: 0.01761 RPN score loss: 0.00777 RPN total loss: 0.02538 Total loss: 2.0045 timestamp: 1654925001.159315 iteration: 12290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20072 FastRCNN class loss: 0.06633 FastRCNN total loss: 0.26704 L1 loss: 0.0000e+00 L2 loss: 1.45336 Learning rate: 0.02 Mask loss: 0.13206 RPN box loss: 0.01842 RPN score loss: 0.00671 RPN total loss: 0.02513 Total loss: 1.87759 timestamp: 1654925004.5245645 iteration: 12295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24875 FastRCNN class loss: 0.09715 FastRCNN total loss: 0.3459 L1 loss: 0.0000e+00 L2 loss: 1.45311 Learning rate: 0.02 Mask loss: 0.22522 RPN box loss: 0.02255 RPN score loss: 0.01076 RPN total loss: 0.03331 Total loss: 2.05754 timestamp: 1654925007.7167969 iteration: 12300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1848 FastRCNN class loss: 0.09094 FastRCNN total loss: 0.27574 L1 loss: 0.0000e+00 L2 loss: 1.45283 Learning rate: 0.02 Mask loss: 0.12473 RPN box loss: 0.01121 RPN score loss: 0.00284 RPN total loss: 0.01405 Total loss: 1.86736 timestamp: 1654925010.991954 iteration: 12305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14192 FastRCNN class loss: 0.1038 FastRCNN total loss: 0.24572 L1 loss: 0.0000e+00 L2 loss: 1.45259 Learning rate: 0.02 Mask loss: 0.20134 RPN box loss: 0.05071 RPN score loss: 0.01142 RPN total loss: 0.06213 Total loss: 1.96178 timestamp: 1654925014.280921 iteration: 12310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05938 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.12813 L1 loss: 0.0000e+00 L2 loss: 1.45234 Learning rate: 0.02 Mask loss: 0.12647 RPN box loss: 0.04653 RPN score loss: 0.00962 RPN total loss: 0.05614 Total loss: 1.76308 timestamp: 1654925017.4979095 iteration: 12315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17481 FastRCNN class loss: 0.08574 FastRCNN total loss: 0.26055 L1 loss: 0.0000e+00 L2 loss: 1.45209 Learning rate: 0.02 Mask loss: 0.1298 RPN box loss: 0.04191 RPN score loss: 0.00567 RPN total loss: 0.04758 Total loss: 1.89002 timestamp: 1654925020.709519 iteration: 12320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18927 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.28591 L1 loss: 0.0000e+00 L2 loss: 1.45184 Learning rate: 0.02 Mask loss: 0.15362 RPN box loss: 0.0441 RPN score loss: 0.02073 RPN total loss: 0.06483 Total loss: 1.9562 timestamp: 1654925023.955557 iteration: 12325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14865 FastRCNN class loss: 0.07472 FastRCNN total loss: 0.22337 L1 loss: 0.0000e+00 L2 loss: 1.45159 Learning rate: 0.02 Mask loss: 0.16537 RPN box loss: 0.02542 RPN score loss: 0.00427 RPN total loss: 0.02968 Total loss: 1.87001 timestamp: 1654925027.2524142 iteration: 12330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1364 FastRCNN class loss: 0.11633 FastRCNN total loss: 0.25272 L1 loss: 0.0000e+00 L2 loss: 1.45134 Learning rate: 0.02 Mask loss: 0.16091 RPN box loss: 0.06427 RPN score loss: 0.00763 RPN total loss: 0.0719 Total loss: 1.93687 timestamp: 1654925030.4534476 iteration: 12335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11292 FastRCNN class loss: 0.04821 FastRCNN total loss: 0.16113 L1 loss: 0.0000e+00 L2 loss: 1.45109 Learning rate: 0.02 Mask loss: 0.13345 RPN box loss: 0.04216 RPN score loss: 0.01442 RPN total loss: 0.05658 Total loss: 1.80225 timestamp: 1654925033.8641124 iteration: 12340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12919 FastRCNN class loss: 0.1064 FastRCNN total loss: 0.23558 L1 loss: 0.0000e+00 L2 loss: 1.45083 Learning rate: 0.02 Mask loss: 0.14693 RPN box loss: 0.01105 RPN score loss: 0.00352 RPN total loss: 0.01457 Total loss: 1.84792 timestamp: 1654925037.0397525 iteration: 12345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14688 FastRCNN class loss: 0.08597 FastRCNN total loss: 0.23285 L1 loss: 0.0000e+00 L2 loss: 1.45057 Learning rate: 0.02 Mask loss: 0.17666 RPN box loss: 0.04097 RPN score loss: 0.00912 RPN total loss: 0.05009 Total loss: 1.91016 timestamp: 1654925040.3469534 iteration: 12350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19032 FastRCNN class loss: 0.09103 FastRCNN total loss: 0.28135 L1 loss: 0.0000e+00 L2 loss: 1.4503 Learning rate: 0.02 Mask loss: 0.13877 RPN box loss: 0.03229 RPN score loss: 0.01078 RPN total loss: 0.04307 Total loss: 1.91349 timestamp: 1654925043.5849078 iteration: 12355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28142 FastRCNN class loss: 0.10394 FastRCNN total loss: 0.38537 L1 loss: 0.0000e+00 L2 loss: 1.45004 Learning rate: 0.02 Mask loss: 0.17649 RPN box loss: 0.04369 RPN score loss: 0.01961 RPN total loss: 0.06329 Total loss: 2.07519 timestamp: 1654925046.840648 iteration: 12360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08904 FastRCNN class loss: 0.04552 FastRCNN total loss: 0.13456 L1 loss: 0.0000e+00 L2 loss: 1.44979 Learning rate: 0.02 Mask loss: 0.31508 RPN box loss: 0.01216 RPN score loss: 0.00543 RPN total loss: 0.01759 Total loss: 1.91702 timestamp: 1654925050.182043 iteration: 12365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09455 FastRCNN class loss: 0.09436 FastRCNN total loss: 0.18891 L1 loss: 0.0000e+00 L2 loss: 1.44954 Learning rate: 0.02 Mask loss: 0.13075 RPN box loss: 0.02548 RPN score loss: 0.00665 RPN total loss: 0.03214 Total loss: 1.80134 timestamp: 1654925053.4714823 iteration: 12370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11596 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.19103 L1 loss: 0.0000e+00 L2 loss: 1.44931 Learning rate: 0.02 Mask loss: 0.16384 RPN box loss: 0.03562 RPN score loss: 0.0094 RPN total loss: 0.04502 Total loss: 1.8492 timestamp: 1654925056.7179825 iteration: 12375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11059 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.19451 L1 loss: 0.0000e+00 L2 loss: 1.44904 Learning rate: 0.02 Mask loss: 0.18251 RPN box loss: 0.03796 RPN score loss: 0.00331 RPN total loss: 0.04127 Total loss: 1.86734 timestamp: 1654925059.9359565 iteration: 12380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16397 FastRCNN class loss: 0.09902 FastRCNN total loss: 0.26299 L1 loss: 0.0000e+00 L2 loss: 1.44877 Learning rate: 0.02 Mask loss: 0.13236 RPN box loss: 0.0216 RPN score loss: 0.0018 RPN total loss: 0.02339 Total loss: 1.86751 timestamp: 1654925063.1418135 iteration: 12385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17265 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.26416 L1 loss: 0.0000e+00 L2 loss: 1.44851 Learning rate: 0.02 Mask loss: 0.14789 RPN box loss: 0.05619 RPN score loss: 0.01078 RPN total loss: 0.06697 Total loss: 1.92752 timestamp: 1654925066.3001218 iteration: 12390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1366 FastRCNN class loss: 0.07822 FastRCNN total loss: 0.21481 L1 loss: 0.0000e+00 L2 loss: 1.44825 Learning rate: 0.02 Mask loss: 0.14823 RPN box loss: 0.02624 RPN score loss: 0.00369 RPN total loss: 0.02993 Total loss: 1.84123 timestamp: 1654925069.5371897 iteration: 12395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.127 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.18822 L1 loss: 0.0000e+00 L2 loss: 1.44799 Learning rate: 0.02 Mask loss: 0.10909 RPN box loss: 0.07299 RPN score loss: 0.00455 RPN total loss: 0.07754 Total loss: 1.82283 timestamp: 1654925072.769279 iteration: 12400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15655 FastRCNN class loss: 0.07566 FastRCNN total loss: 0.23221 L1 loss: 0.0000e+00 L2 loss: 1.44773 Learning rate: 0.02 Mask loss: 0.12607 RPN box loss: 0.06755 RPN score loss: 0.00751 RPN total loss: 0.07507 Total loss: 1.88108 timestamp: 1654925076.1585894 iteration: 12405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21861 FastRCNN class loss: 0.13094 FastRCNN total loss: 0.34956 L1 loss: 0.0000e+00 L2 loss: 1.44747 Learning rate: 0.02 Mask loss: 0.21546 RPN box loss: 0.01826 RPN score loss: 0.00873 RPN total loss: 0.02699 Total loss: 2.03948 timestamp: 1654925079.3728538 iteration: 12410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15756 FastRCNN class loss: 0.09909 FastRCNN total loss: 0.25666 L1 loss: 0.0000e+00 L2 loss: 1.44723 Learning rate: 0.02 Mask loss: 0.18536 RPN box loss: 0.07153 RPN score loss: 0.00753 RPN total loss: 0.07906 Total loss: 1.96831 timestamp: 1654925082.6850893 iteration: 12415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12234 FastRCNN class loss: 0.06775 FastRCNN total loss: 0.1901 L1 loss: 0.0000e+00 L2 loss: 1.44696 Learning rate: 0.02 Mask loss: 0.13226 RPN box loss: 0.0516 RPN score loss: 0.00704 RPN total loss: 0.05864 Total loss: 1.82795 timestamp: 1654925085.8094935 iteration: 12420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11193 FastRCNN class loss: 0.0821 FastRCNN total loss: 0.19403 L1 loss: 0.0000e+00 L2 loss: 1.44669 Learning rate: 0.02 Mask loss: 0.16384 RPN box loss: 0.02222 RPN score loss: 0.01929 RPN total loss: 0.04151 Total loss: 1.84607 timestamp: 1654925089.1186018 iteration: 12425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12583 FastRCNN class loss: 0.09889 FastRCNN total loss: 0.22472 L1 loss: 0.0000e+00 L2 loss: 1.44644 Learning rate: 0.02 Mask loss: 0.18428 RPN box loss: 0.06885 RPN score loss: 0.01426 RPN total loss: 0.0831 Total loss: 1.93855 timestamp: 1654925092.3355649 iteration: 12430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15483 FastRCNN class loss: 0.09235 FastRCNN total loss: 0.24718 L1 loss: 0.0000e+00 L2 loss: 1.44621 Learning rate: 0.02 Mask loss: 0.15267 RPN box loss: 0.02601 RPN score loss: 0.00398 RPN total loss: 0.02999 Total loss: 1.87604 timestamp: 1654925095.5832722 iteration: 12435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11482 FastRCNN class loss: 0.05812 FastRCNN total loss: 0.17294 L1 loss: 0.0000e+00 L2 loss: 1.44594 Learning rate: 0.02 Mask loss: 0.11374 RPN box loss: 0.01635 RPN score loss: 0.00434 RPN total loss: 0.02069 Total loss: 1.75331 timestamp: 1654925098.9317288 iteration: 12440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16859 FastRCNN class loss: 0.10089 FastRCNN total loss: 0.26947 L1 loss: 0.0000e+00 L2 loss: 1.44568 Learning rate: 0.02 Mask loss: 0.25869 RPN box loss: 0.0974 RPN score loss: 0.00965 RPN total loss: 0.10706 Total loss: 2.0809 timestamp: 1654925102.1198878 iteration: 12445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21965 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.31655 L1 loss: 0.0000e+00 L2 loss: 1.44542 Learning rate: 0.02 Mask loss: 0.20618 RPN box loss: 0.04699 RPN score loss: 0.00862 RPN total loss: 0.05561 Total loss: 2.02376 timestamp: 1654925105.3915322 iteration: 12450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12103 FastRCNN class loss: 0.07593 FastRCNN total loss: 0.19696 L1 loss: 0.0000e+00 L2 loss: 1.44518 Learning rate: 0.02 Mask loss: 0.16708 RPN box loss: 0.04079 RPN score loss: 0.03768 RPN total loss: 0.07847 Total loss: 1.88769 timestamp: 1654925108.5719383 iteration: 12455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16623 FastRCNN class loss: 0.08851 FastRCNN total loss: 0.25474 L1 loss: 0.0000e+00 L2 loss: 1.44494 Learning rate: 0.02 Mask loss: 0.21416 RPN box loss: 0.02197 RPN score loss: 0.00656 RPN total loss: 0.02853 Total loss: 1.94238 timestamp: 1654925111.8887148 iteration: 12460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19397 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.29359 L1 loss: 0.0000e+00 L2 loss: 1.44467 Learning rate: 0.02 Mask loss: 0.27852 RPN box loss: 0.02437 RPN score loss: 0.00975 RPN total loss: 0.03412 Total loss: 2.0509 timestamp: 1654925115.1139886 iteration: 12465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20867 FastRCNN class loss: 0.09094 FastRCNN total loss: 0.29961 L1 loss: 0.0000e+00 L2 loss: 1.44442 Learning rate: 0.02 Mask loss: 0.13901 RPN box loss: 0.04411 RPN score loss: 0.00638 RPN total loss: 0.05049 Total loss: 1.93353 timestamp: 1654925118.3474555 iteration: 12470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1497 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.24404 L1 loss: 0.0000e+00 L2 loss: 1.44417 Learning rate: 0.02 Mask loss: 0.15476 RPN box loss: 0.02248 RPN score loss: 0.00557 RPN total loss: 0.02805 Total loss: 1.87103 timestamp: 1654925121.5769117 iteration: 12475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17366 FastRCNN class loss: 0.10295 FastRCNN total loss: 0.27661 L1 loss: 0.0000e+00 L2 loss: 1.44391 Learning rate: 0.02 Mask loss: 0.19102 RPN box loss: 0.03165 RPN score loss: 0.00734 RPN total loss: 0.03899 Total loss: 1.95053 timestamp: 1654925124.9385374 iteration: 12480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15007 FastRCNN class loss: 0.10525 FastRCNN total loss: 0.25532 L1 loss: 0.0000e+00 L2 loss: 1.44365 Learning rate: 0.02 Mask loss: 0.16195 RPN box loss: 0.0566 RPN score loss: 0.01449 RPN total loss: 0.0711 Total loss: 1.93201 timestamp: 1654925128.3266501 iteration: 12485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10965 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.1782 L1 loss: 0.0000e+00 L2 loss: 1.44341 Learning rate: 0.02 Mask loss: 0.1144 RPN box loss: 0.04283 RPN score loss: 0.00749 RPN total loss: 0.05031 Total loss: 1.78632 timestamp: 1654925131.5818038 iteration: 12490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13502 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.22441 L1 loss: 0.0000e+00 L2 loss: 1.44316 Learning rate: 0.02 Mask loss: 0.09548 RPN box loss: 0.01041 RPN score loss: 0.0058 RPN total loss: 0.01621 Total loss: 1.77926 timestamp: 1654925134.7853665 iteration: 12495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10012 FastRCNN class loss: 0.05898 FastRCNN total loss: 0.1591 L1 loss: 0.0000e+00 L2 loss: 1.44291 Learning rate: 0.02 Mask loss: 0.1136 RPN box loss: 0.01574 RPN score loss: 0.00571 RPN total loss: 0.02144 Total loss: 1.73704 timestamp: 1654925138.0158854 iteration: 12500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11373 FastRCNN class loss: 0.08314 FastRCNN total loss: 0.19687 L1 loss: 0.0000e+00 L2 loss: 1.44265 Learning rate: 0.02 Mask loss: 0.09761 RPN box loss: 0.07697 RPN score loss: 0.00641 RPN total loss: 0.08338 Total loss: 1.82052 timestamp: 1654925141.3527327 iteration: 12505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16365 FastRCNN class loss: 0.09507 FastRCNN total loss: 0.25872 L1 loss: 0.0000e+00 L2 loss: 1.4424 Learning rate: 0.02 Mask loss: 0.16476 RPN box loss: 0.0411 RPN score loss: 0.00439 RPN total loss: 0.04549 Total loss: 1.91138 timestamp: 1654925144.5239334 iteration: 12510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.108 FastRCNN class loss: 0.09715 FastRCNN total loss: 0.20515 L1 loss: 0.0000e+00 L2 loss: 1.44214 Learning rate: 0.02 Mask loss: 0.16156 RPN box loss: 0.05243 RPN score loss: 0.00576 RPN total loss: 0.05819 Total loss: 1.86703 timestamp: 1654925147.8003137 iteration: 12515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22309 FastRCNN class loss: 0.1562 FastRCNN total loss: 0.37929 L1 loss: 0.0000e+00 L2 loss: 1.44188 Learning rate: 0.02 Mask loss: 0.25249 RPN box loss: 0.07651 RPN score loss: 0.01352 RPN total loss: 0.09003 Total loss: 2.16369 timestamp: 1654925150.9751282 iteration: 12520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13731 FastRCNN class loss: 0.07568 FastRCNN total loss: 0.21298 L1 loss: 0.0000e+00 L2 loss: 1.44163 Learning rate: 0.02 Mask loss: 0.18835 RPN box loss: 0.02951 RPN score loss: 0.01329 RPN total loss: 0.0428 Total loss: 1.88576 timestamp: 1654925154.27111 iteration: 12525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15495 FastRCNN class loss: 0.06419 FastRCNN total loss: 0.21914 L1 loss: 0.0000e+00 L2 loss: 1.44139 Learning rate: 0.02 Mask loss: 0.25035 RPN box loss: 0.04124 RPN score loss: 0.01842 RPN total loss: 0.05966 Total loss: 1.97054 timestamp: 1654925157.5003607 iteration: 12530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10617 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.16918 L1 loss: 0.0000e+00 L2 loss: 1.44113 Learning rate: 0.02 Mask loss: 0.1397 RPN box loss: 0.01718 RPN score loss: 0.00327 RPN total loss: 0.02044 Total loss: 1.77046 timestamp: 1654925160.757975 iteration: 12535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11064 FastRCNN class loss: 0.08649 FastRCNN total loss: 0.19713 L1 loss: 0.0000e+00 L2 loss: 1.44086 Learning rate: 0.02 Mask loss: 0.19775 RPN box loss: 0.02555 RPN score loss: 0.01178 RPN total loss: 0.03733 Total loss: 1.87307 timestamp: 1654925164.1775596 iteration: 12540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15257 FastRCNN class loss: 0.10606 FastRCNN total loss: 0.25863 L1 loss: 0.0000e+00 L2 loss: 1.4406 Learning rate: 0.02 Mask loss: 0.23514 RPN box loss: 0.04107 RPN score loss: 0.00869 RPN total loss: 0.04976 Total loss: 1.98414 timestamp: 1654925167.301934 iteration: 12545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16794 FastRCNN class loss: 0.05364 FastRCNN total loss: 0.22159 L1 loss: 0.0000e+00 L2 loss: 1.44035 Learning rate: 0.02 Mask loss: 0.18871 RPN box loss: 0.06363 RPN score loss: 0.00759 RPN total loss: 0.07121 Total loss: 1.92186 timestamp: 1654925170.6141858 iteration: 12550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15154 FastRCNN class loss: 0.09354 FastRCNN total loss: 0.24508 L1 loss: 0.0000e+00 L2 loss: 1.44011 Learning rate: 0.02 Mask loss: 0.17313 RPN box loss: 0.01522 RPN score loss: 0.00336 RPN total loss: 0.01858 Total loss: 1.87689 timestamp: 1654925173.849918 iteration: 12555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20619 FastRCNN class loss: 0.09515 FastRCNN total loss: 0.30134 L1 loss: 0.0000e+00 L2 loss: 1.43983 Learning rate: 0.02 Mask loss: 0.31061 RPN box loss: 0.07969 RPN score loss: 0.01536 RPN total loss: 0.09506 Total loss: 2.14684 timestamp: 1654925177.042018 iteration: 12560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15826 FastRCNN class loss: 0.19525 FastRCNN total loss: 0.35351 L1 loss: 0.0000e+00 L2 loss: 1.43958 Learning rate: 0.02 Mask loss: 0.19023 RPN box loss: 0.03977 RPN score loss: 0.01052 RPN total loss: 0.05029 Total loss: 2.03362 timestamp: 1654925180.286012 iteration: 12565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19917 FastRCNN class loss: 0.17254 FastRCNN total loss: 0.3717 L1 loss: 0.0000e+00 L2 loss: 1.43934 Learning rate: 0.02 Mask loss: 0.19071 RPN box loss: 0.04837 RPN score loss: 0.01258 RPN total loss: 0.06095 Total loss: 2.06271 timestamp: 1654925183.6148744 iteration: 12570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14885 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.21774 L1 loss: 0.0000e+00 L2 loss: 1.43907 Learning rate: 0.02 Mask loss: 0.11662 RPN box loss: 0.00513 RPN score loss: 0.00449 RPN total loss: 0.00962 Total loss: 1.78305 timestamp: 1654925186.804228 iteration: 12575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14142 FastRCNN class loss: 0.09542 FastRCNN total loss: 0.23684 L1 loss: 0.0000e+00 L2 loss: 1.43881 Learning rate: 0.02 Mask loss: 0.2325 RPN box loss: 0.01421 RPN score loss: 0.00456 RPN total loss: 0.01877 Total loss: 1.92692 timestamp: 1654925190.1287491 iteration: 12580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12192 FastRCNN class loss: 0.10538 FastRCNN total loss: 0.2273 L1 loss: 0.0000e+00 L2 loss: 1.43857 Learning rate: 0.02 Mask loss: 0.22981 RPN box loss: 0.06709 RPN score loss: 0.01231 RPN total loss: 0.07939 Total loss: 1.97507 timestamp: 1654925193.4437385 iteration: 12585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14555 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.20317 L1 loss: 0.0000e+00 L2 loss: 1.43833 Learning rate: 0.02 Mask loss: 0.20378 RPN box loss: 0.0344 RPN score loss: 0.00337 RPN total loss: 0.03778 Total loss: 1.88305 timestamp: 1654925196.5935156 iteration: 12590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15456 FastRCNN class loss: 0.06829 FastRCNN total loss: 0.22285 L1 loss: 0.0000e+00 L2 loss: 1.43805 Learning rate: 0.02 Mask loss: 0.12219 RPN box loss: 0.01946 RPN score loss: 0.00452 RPN total loss: 0.02398 Total loss: 1.80707 timestamp: 1654925199.8964646 iteration: 12595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25076 FastRCNN class loss: 0.12135 FastRCNN total loss: 0.37212 L1 loss: 0.0000e+00 L2 loss: 1.43779 Learning rate: 0.02 Mask loss: 0.18864 RPN box loss: 0.10732 RPN score loss: 0.01927 RPN total loss: 0.12659 Total loss: 2.12513 timestamp: 1654925203.067935 iteration: 12600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12219 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.18407 L1 loss: 0.0000e+00 L2 loss: 1.43754 Learning rate: 0.02 Mask loss: 0.17614 RPN box loss: 0.03692 RPN score loss: 0.0041 RPN total loss: 0.04103 Total loss: 1.83878 timestamp: 1654925206.3991766 iteration: 12605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20232 FastRCNN class loss: 0.07507 FastRCNN total loss: 0.27739 L1 loss: 0.0000e+00 L2 loss: 1.4373 Learning rate: 0.02 Mask loss: 0.21348 RPN box loss: 0.00895 RPN score loss: 0.00287 RPN total loss: 0.01182 Total loss: 1.93998 timestamp: 1654925209.5445676 iteration: 12610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17015 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.24795 L1 loss: 0.0000e+00 L2 loss: 1.43704 Learning rate: 0.02 Mask loss: 0.10061 RPN box loss: 0.03562 RPN score loss: 0.00421 RPN total loss: 0.03983 Total loss: 1.82543 timestamp: 1654925212.841421 iteration: 12615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12617 FastRCNN class loss: 0.08767 FastRCNN total loss: 0.21384 L1 loss: 0.0000e+00 L2 loss: 1.43678 Learning rate: 0.02 Mask loss: 0.24415 RPN box loss: 0.03034 RPN score loss: 0.01449 RPN total loss: 0.04483 Total loss: 1.9396 timestamp: 1654925216.0476887 iteration: 12620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1659 FastRCNN class loss: 0.09362 FastRCNN total loss: 0.25952 L1 loss: 0.0000e+00 L2 loss: 1.43653 Learning rate: 0.02 Mask loss: 0.29214 RPN box loss: 0.01265 RPN score loss: 0.00289 RPN total loss: 0.01554 Total loss: 2.00373 timestamp: 1654925219.2718716 iteration: 12625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.06917 FastRCNN total loss: 0.23161 L1 loss: 0.0000e+00 L2 loss: 1.43626 Learning rate: 0.02 Mask loss: 0.13792 RPN box loss: 0.01971 RPN score loss: 0.00567 RPN total loss: 0.02538 Total loss: 1.83117 timestamp: 1654925222.4708185 iteration: 12630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11408 FastRCNN class loss: 0.07855 FastRCNN total loss: 0.19263 L1 loss: 0.0000e+00 L2 loss: 1.436 Learning rate: 0.02 Mask loss: 0.14271 RPN box loss: 0.04846 RPN score loss: 0.00554 RPN total loss: 0.05401 Total loss: 1.82534 timestamp: 1654925225.8070874 iteration: 12635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09866 FastRCNN class loss: 0.06813 FastRCNN total loss: 0.16678 L1 loss: 0.0000e+00 L2 loss: 1.43575 Learning rate: 0.02 Mask loss: 0.10559 RPN box loss: 0.00866 RPN score loss: 0.00779 RPN total loss: 0.01645 Total loss: 1.72457 timestamp: 1654925229.0722878 iteration: 12640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22877 FastRCNN class loss: 0.10031 FastRCNN total loss: 0.32908 L1 loss: 0.0000e+00 L2 loss: 1.4355 Learning rate: 0.02 Mask loss: 0.17131 RPN box loss: 0.03648 RPN score loss: 0.00888 RPN total loss: 0.04536 Total loss: 1.98125 timestamp: 1654925232.2639241 iteration: 12645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10939 FastRCNN class loss: 0.04703 FastRCNN total loss: 0.15642 L1 loss: 0.0000e+00 L2 loss: 1.43524 Learning rate: 0.02 Mask loss: 0.10339 RPN box loss: 0.02016 RPN score loss: 0.0089 RPN total loss: 0.02906 Total loss: 1.7241 timestamp: 1654925235.4757986 iteration: 12650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13646 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.20667 L1 loss: 0.0000e+00 L2 loss: 1.43499 Learning rate: 0.02 Mask loss: 0.1276 RPN box loss: 0.01096 RPN score loss: 0.00588 RPN total loss: 0.01684 Total loss: 1.7861 timestamp: 1654925238.6999233 iteration: 12655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14671 FastRCNN class loss: 0.07128 FastRCNN total loss: 0.21799 L1 loss: 0.0000e+00 L2 loss: 1.43475 Learning rate: 0.02 Mask loss: 0.16244 RPN box loss: 0.02483 RPN score loss: 0.00381 RPN total loss: 0.02864 Total loss: 1.84382 timestamp: 1654925242.0081096 iteration: 12660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22106 FastRCNN class loss: 0.11387 FastRCNN total loss: 0.33493 L1 loss: 0.0000e+00 L2 loss: 1.4345 Learning rate: 0.02 Mask loss: 0.23038 RPN box loss: 0.02106 RPN score loss: 0.00403 RPN total loss: 0.02509 Total loss: 2.0249 timestamp: 1654925245.2079365 iteration: 12665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14816 FastRCNN class loss: 0.09701 FastRCNN total loss: 0.24517 L1 loss: 0.0000e+00 L2 loss: 1.43423 Learning rate: 0.02 Mask loss: 0.17684 RPN box loss: 0.04732 RPN score loss: 0.01182 RPN total loss: 0.05913 Total loss: 1.91537 timestamp: 1654925248.463489 iteration: 12670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16477 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.24476 L1 loss: 0.0000e+00 L2 loss: 1.43397 Learning rate: 0.02 Mask loss: 0.16684 RPN box loss: 0.05809 RPN score loss: 0.00805 RPN total loss: 0.06614 Total loss: 1.91171 timestamp: 1654925251.6070642 iteration: 12675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17775 FastRCNN class loss: 0.07046 FastRCNN total loss: 0.24821 L1 loss: 0.0000e+00 L2 loss: 1.4337 Learning rate: 0.02 Mask loss: 0.18439 RPN box loss: 0.01869 RPN score loss: 0.0085 RPN total loss: 0.02719 Total loss: 1.89349 timestamp: 1654925254.8612158 iteration: 12680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14997 FastRCNN class loss: 0.10458 FastRCNN total loss: 0.25455 L1 loss: 0.0000e+00 L2 loss: 1.43345 Learning rate: 0.02 Mask loss: 0.27402 RPN box loss: 0.05189 RPN score loss: 0.00727 RPN total loss: 0.05917 Total loss: 2.02119 timestamp: 1654925258.0785675 iteration: 12685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10553 FastRCNN class loss: 0.0962 FastRCNN total loss: 0.20173 L1 loss: 0.0000e+00 L2 loss: 1.4332 Learning rate: 0.02 Mask loss: 0.15915 RPN box loss: 0.08794 RPN score loss: 0.01065 RPN total loss: 0.09859 Total loss: 1.89268 timestamp: 1654925261.4876814 iteration: 12690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14252 FastRCNN class loss: 0.15442 FastRCNN total loss: 0.29694 L1 loss: 0.0000e+00 L2 loss: 1.43297 Learning rate: 0.02 Mask loss: 0.22074 RPN box loss: 0.07987 RPN score loss: 0.01818 RPN total loss: 0.09805 Total loss: 2.0487 timestamp: 1654925264.7676597 iteration: 12695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05088 FastRCNN class loss: 0.04576 FastRCNN total loss: 0.09663 L1 loss: 0.0000e+00 L2 loss: 1.43271 Learning rate: 0.02 Mask loss: 0.15905 RPN box loss: 0.04552 RPN score loss: 0.00565 RPN total loss: 0.05117 Total loss: 1.73956 timestamp: 1654925267.98687 iteration: 12700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10313 FastRCNN class loss: 0.05654 FastRCNN total loss: 0.15967 L1 loss: 0.0000e+00 L2 loss: 1.43244 Learning rate: 0.02 Mask loss: 0.16856 RPN box loss: 0.08415 RPN score loss: 0.00482 RPN total loss: 0.08897 Total loss: 1.84964 timestamp: 1654925271.425087 iteration: 12705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16763 FastRCNN class loss: 0.12605 FastRCNN total loss: 0.29369 L1 loss: 0.0000e+00 L2 loss: 1.43217 Learning rate: 0.02 Mask loss: 0.18652 RPN box loss: 0.0494 RPN score loss: 0.01293 RPN total loss: 0.06233 Total loss: 1.97471 timestamp: 1654925274.685825 iteration: 12710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11009 FastRCNN class loss: 0.05713 FastRCNN total loss: 0.16722 L1 loss: 0.0000e+00 L2 loss: 1.43191 Learning rate: 0.02 Mask loss: 0.13839 RPN box loss: 0.02062 RPN score loss: 0.00488 RPN total loss: 0.0255 Total loss: 1.76302 timestamp: 1654925278.0910275 iteration: 12715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16777 FastRCNN class loss: 0.11762 FastRCNN total loss: 0.28539 L1 loss: 0.0000e+00 L2 loss: 1.43167 Learning rate: 0.02 Mask loss: 0.12753 RPN box loss: 0.01902 RPN score loss: 0.00897 RPN total loss: 0.02798 Total loss: 1.87257 timestamp: 1654925281.294636 iteration: 12720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16285 FastRCNN class loss: 0.10485 FastRCNN total loss: 0.2677 L1 loss: 0.0000e+00 L2 loss: 1.43143 Learning rate: 0.02 Mask loss: 0.22862 RPN box loss: 0.04407 RPN score loss: 0.0131 RPN total loss: 0.05717 Total loss: 1.98491 timestamp: 1654925284.5649984 iteration: 12725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09348 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.18116 L1 loss: 0.0000e+00 L2 loss: 1.4312 Learning rate: 0.02 Mask loss: 0.16769 RPN box loss: 0.04127 RPN score loss: 0.01081 RPN total loss: 0.05208 Total loss: 1.83213 timestamp: 1654925287.7868347 iteration: 12730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1562 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.21589 L1 loss: 0.0000e+00 L2 loss: 1.43096 Learning rate: 0.02 Mask loss: 0.10471 RPN box loss: 0.03169 RPN score loss: 0.00649 RPN total loss: 0.03819 Total loss: 1.78974 timestamp: 1654925291.138165 iteration: 12735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11392 FastRCNN class loss: 0.09186 FastRCNN total loss: 0.20578 L1 loss: 0.0000e+00 L2 loss: 1.4307 Learning rate: 0.02 Mask loss: 0.18666 RPN box loss: 0.02008 RPN score loss: 0.00474 RPN total loss: 0.02482 Total loss: 1.84796 timestamp: 1654925294.5018408 iteration: 12740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20554 FastRCNN class loss: 0.10068 FastRCNN total loss: 0.30621 L1 loss: 0.0000e+00 L2 loss: 1.43045 Learning rate: 0.02 Mask loss: 0.17365 RPN box loss: 0.04058 RPN score loss: 0.00781 RPN total loss: 0.04839 Total loss: 1.9587 timestamp: 1654925297.7451546 iteration: 12745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18177 FastRCNN class loss: 0.11608 FastRCNN total loss: 0.29785 L1 loss: 0.0000e+00 L2 loss: 1.43019 Learning rate: 0.02 Mask loss: 0.15777 RPN box loss: 0.13783 RPN score loss: 0.00739 RPN total loss: 0.14522 Total loss: 2.03102 timestamp: 1654925301.0059252 iteration: 12750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15924 FastRCNN class loss: 0.08302 FastRCNN total loss: 0.24226 L1 loss: 0.0000e+00 L2 loss: 1.42993 Learning rate: 0.02 Mask loss: 0.17032 RPN box loss: 0.06691 RPN score loss: 0.0036 RPN total loss: 0.07051 Total loss: 1.91302 timestamp: 1654925304.2855985 iteration: 12755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21163 FastRCNN class loss: 0.0874 FastRCNN total loss: 0.29903 L1 loss: 0.0000e+00 L2 loss: 1.42967 Learning rate: 0.02 Mask loss: 0.2232 RPN box loss: 0.04402 RPN score loss: 0.02053 RPN total loss: 0.06455 Total loss: 2.01646 timestamp: 1654925307.6594577 iteration: 12760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16907 FastRCNN class loss: 0.12389 FastRCNN total loss: 0.29296 L1 loss: 0.0000e+00 L2 loss: 1.42943 Learning rate: 0.02 Mask loss: 0.165 RPN box loss: 0.04024 RPN score loss: 0.01393 RPN total loss: 0.05417 Total loss: 1.94156 timestamp: 1654925310.845356 iteration: 12765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19084 FastRCNN class loss: 0.09881 FastRCNN total loss: 0.28965 L1 loss: 0.0000e+00 L2 loss: 1.4292 Learning rate: 0.02 Mask loss: 0.21155 RPN box loss: 0.06499 RPN score loss: 0.00423 RPN total loss: 0.06923 Total loss: 1.99962 timestamp: 1654925314.17887 iteration: 12770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09415 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.17467 L1 loss: 0.0000e+00 L2 loss: 1.42895 Learning rate: 0.02 Mask loss: 0.13371 RPN box loss: 0.03581 RPN score loss: 0.0051 RPN total loss: 0.0409 Total loss: 1.77823 timestamp: 1654925317.350257 iteration: 12775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19067 FastRCNN class loss: 0.17645 FastRCNN total loss: 0.36712 L1 loss: 0.0000e+00 L2 loss: 1.42871 Learning rate: 0.02 Mask loss: 0.23367 RPN box loss: 0.01961 RPN score loss: 0.0059 RPN total loss: 0.0255 Total loss: 2.05501 timestamp: 1654925320.8207102 iteration: 12780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11332 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.17111 L1 loss: 0.0000e+00 L2 loss: 1.42847 Learning rate: 0.02 Mask loss: 0.13216 RPN box loss: 0.01991 RPN score loss: 0.00199 RPN total loss: 0.0219 Total loss: 1.75363 timestamp: 1654925324.2221828 iteration: 12785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13157 FastRCNN class loss: 0.07161 FastRCNN total loss: 0.20318 L1 loss: 0.0000e+00 L2 loss: 1.42821 Learning rate: 0.02 Mask loss: 0.16077 RPN box loss: 0.06663 RPN score loss: 0.00625 RPN total loss: 0.07288 Total loss: 1.86504 timestamp: 1654925327.603841 iteration: 12790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19857 FastRCNN class loss: 0.07892 FastRCNN total loss: 0.2775 L1 loss: 0.0000e+00 L2 loss: 1.42797 Learning rate: 0.02 Mask loss: 0.17311 RPN box loss: 0.01681 RPN score loss: 0.00746 RPN total loss: 0.02427 Total loss: 1.90285 timestamp: 1654925330.9667609 iteration: 12795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14963 FastRCNN class loss: 0.0486 FastRCNN total loss: 0.19823 L1 loss: 0.0000e+00 L2 loss: 1.42772 Learning rate: 0.02 Mask loss: 0.13825 RPN box loss: 0.00874 RPN score loss: 0.00324 RPN total loss: 0.01197 Total loss: 1.77617 timestamp: 1654925334.214278 iteration: 12800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2046 FastRCNN class loss: 0.11846 FastRCNN total loss: 0.32306 L1 loss: 0.0000e+00 L2 loss: 1.42748 Learning rate: 0.02 Mask loss: 0.19896 RPN box loss: 0.04151 RPN score loss: 0.008 RPN total loss: 0.04951 Total loss: 1.99901 timestamp: 1654925337.547057 iteration: 12805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10037 FastRCNN class loss: 0.07693 FastRCNN total loss: 0.1773 L1 loss: 0.0000e+00 L2 loss: 1.42721 Learning rate: 0.02 Mask loss: 0.119 RPN box loss: 0.01709 RPN score loss: 0.00295 RPN total loss: 0.02005 Total loss: 1.74356 timestamp: 1654925340.8055747 iteration: 12810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14532 FastRCNN class loss: 0.09806 FastRCNN total loss: 0.24338 L1 loss: 0.0000e+00 L2 loss: 1.42696 Learning rate: 0.02 Mask loss: 0.22727 RPN box loss: 0.04336 RPN score loss: 0.00651 RPN total loss: 0.04988 Total loss: 1.94748 timestamp: 1654925344.1430955 iteration: 12815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15944 FastRCNN class loss: 0.07816 FastRCNN total loss: 0.23759 L1 loss: 0.0000e+00 L2 loss: 1.42671 Learning rate: 0.02 Mask loss: 0.16631 RPN box loss: 0.01781 RPN score loss: 0.00595 RPN total loss: 0.02376 Total loss: 1.85438 timestamp: 1654925347.3739474 iteration: 12820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18165 FastRCNN class loss: 0.07627 FastRCNN total loss: 0.25792 L1 loss: 0.0000e+00 L2 loss: 1.42647 Learning rate: 0.02 Mask loss: 0.12759 RPN box loss: 0.0326 RPN score loss: 0.00427 RPN total loss: 0.03688 Total loss: 1.84887 timestamp: 1654925350.5812352 iteration: 12825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13835 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.21175 L1 loss: 0.0000e+00 L2 loss: 1.42621 Learning rate: 0.02 Mask loss: 0.19012 RPN box loss: 0.02235 RPN score loss: 0.00849 RPN total loss: 0.03084 Total loss: 1.85891 timestamp: 1654925353.9253783 iteration: 12830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13777 FastRCNN class loss: 0.08901 FastRCNN total loss: 0.22679 L1 loss: 0.0000e+00 L2 loss: 1.42595 Learning rate: 0.02 Mask loss: 0.1844 RPN box loss: 0.03131 RPN score loss: 0.00408 RPN total loss: 0.03539 Total loss: 1.87253 timestamp: 1654925357.0986636 iteration: 12835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12927 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.22237 L1 loss: 0.0000e+00 L2 loss: 1.42569 Learning rate: 0.02 Mask loss: 0.12029 RPN box loss: 0.04597 RPN score loss: 0.00545 RPN total loss: 0.05142 Total loss: 1.81978 timestamp: 1654925360.3808577 iteration: 12840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29384 FastRCNN class loss: 0.16825 FastRCNN total loss: 0.46209 L1 loss: 0.0000e+00 L2 loss: 1.42544 Learning rate: 0.02 Mask loss: 0.21688 RPN box loss: 0.03907 RPN score loss: 0.01791 RPN total loss: 0.05698 Total loss: 2.16139 timestamp: 1654925363.5812223 iteration: 12845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10879 FastRCNN class loss: 0.06794 FastRCNN total loss: 0.17673 L1 loss: 0.0000e+00 L2 loss: 1.4252 Learning rate: 0.02 Mask loss: 0.13869 RPN box loss: 0.05259 RPN score loss: 0.00583 RPN total loss: 0.05843 Total loss: 1.79904 timestamp: 1654925366.8057458 iteration: 12850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15375 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.23003 L1 loss: 0.0000e+00 L2 loss: 1.42495 Learning rate: 0.02 Mask loss: 0.14123 RPN box loss: 0.02537 RPN score loss: 0.00617 RPN total loss: 0.03154 Total loss: 1.82775 timestamp: 1654925370.0802429 iteration: 12855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15983 FastRCNN class loss: 0.13395 FastRCNN total loss: 0.29378 L1 loss: 0.0000e+00 L2 loss: 1.42472 Learning rate: 0.02 Mask loss: 0.18658 RPN box loss: 0.11056 RPN score loss: 0.01317 RPN total loss: 0.12372 Total loss: 2.02881 timestamp: 1654925373.3984373 iteration: 12860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17938 FastRCNN class loss: 0.08826 FastRCNN total loss: 0.26765 L1 loss: 0.0000e+00 L2 loss: 1.42446 Learning rate: 0.02 Mask loss: 0.11183 RPN box loss: 0.01821 RPN score loss: 0.00414 RPN total loss: 0.02236 Total loss: 1.8263 timestamp: 1654925376.6576438 iteration: 12865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0946 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.15354 L1 loss: 0.0000e+00 L2 loss: 1.42421 Learning rate: 0.02 Mask loss: 0.13796 RPN box loss: 0.03547 RPN score loss: 0.00284 RPN total loss: 0.03831 Total loss: 1.75403 timestamp: 1654925379.958389 iteration: 12870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16204 FastRCNN class loss: 0.09067 FastRCNN total loss: 0.25271 L1 loss: 0.0000e+00 L2 loss: 1.42399 Learning rate: 0.02 Mask loss: 0.16772 RPN box loss: 0.0742 RPN score loss: 0.00338 RPN total loss: 0.07758 Total loss: 1.92199 timestamp: 1654925383.1478238 iteration: 12875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14795 FastRCNN class loss: 0.07182 FastRCNN total loss: 0.21976 L1 loss: 0.0000e+00 L2 loss: 1.42373 Learning rate: 0.02 Mask loss: 0.12565 RPN box loss: 0.02927 RPN score loss: 0.00622 RPN total loss: 0.03549 Total loss: 1.80463 timestamp: 1654925386.346744 iteration: 12880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09786 FastRCNN class loss: 0.04405 FastRCNN total loss: 0.14191 L1 loss: 0.0000e+00 L2 loss: 1.42348 Learning rate: 0.02 Mask loss: 0.11313 RPN box loss: 0.01044 RPN score loss: 0.00473 RPN total loss: 0.01518 Total loss: 1.6937 timestamp: 1654925389.580317 iteration: 12885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13676 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.20336 L1 loss: 0.0000e+00 L2 loss: 1.42324 Learning rate: 0.02 Mask loss: 0.18721 RPN box loss: 0.01772 RPN score loss: 0.00462 RPN total loss: 0.02233 Total loss: 1.83615 timestamp: 1654925392.849885 iteration: 12890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23197 FastRCNN class loss: 0.1069 FastRCNN total loss: 0.33886 L1 loss: 0.0000e+00 L2 loss: 1.42299 Learning rate: 0.02 Mask loss: 0.22505 RPN box loss: 0.05026 RPN score loss: 0.00459 RPN total loss: 0.05485 Total loss: 2.04176 timestamp: 1654925396.1557384 iteration: 12895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15908 FastRCNN class loss: 0.09383 FastRCNN total loss: 0.25291 L1 loss: 0.0000e+00 L2 loss: 1.42276 Learning rate: 0.02 Mask loss: 0.13852 RPN box loss: 0.13689 RPN score loss: 0.01255 RPN total loss: 0.14944 Total loss: 1.96363 timestamp: 1654925399.4852026 iteration: 12900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12919 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.21079 L1 loss: 0.0000e+00 L2 loss: 1.42249 Learning rate: 0.02 Mask loss: 0.152 RPN box loss: 0.08335 RPN score loss: 0.01043 RPN total loss: 0.09378 Total loss: 1.87905 timestamp: 1654925402.7323282 iteration: 12905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19039 FastRCNN class loss: 0.09512 FastRCNN total loss: 0.28551 L1 loss: 0.0000e+00 L2 loss: 1.42222 Learning rate: 0.02 Mask loss: 0.15319 RPN box loss: 0.05481 RPN score loss: 0.01057 RPN total loss: 0.06538 Total loss: 1.92629 timestamp: 1654925405.9528694 iteration: 12910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16186 FastRCNN class loss: 0.10695 FastRCNN total loss: 0.26881 L1 loss: 0.0000e+00 L2 loss: 1.42197 Learning rate: 0.02 Mask loss: 0.21977 RPN box loss: 0.05416 RPN score loss: 0.01261 RPN total loss: 0.06677 Total loss: 1.9773 timestamp: 1654925409.1768374 iteration: 12915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.04036 FastRCNN total loss: 0.13678 L1 loss: 0.0000e+00 L2 loss: 1.42172 Learning rate: 0.02 Mask loss: 0.10992 RPN box loss: 0.01059 RPN score loss: 0.00203 RPN total loss: 0.01262 Total loss: 1.68104 timestamp: 1654925412.3805165 iteration: 12920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14135 FastRCNN class loss: 0.09599 FastRCNN total loss: 0.23733 L1 loss: 0.0000e+00 L2 loss: 1.42146 Learning rate: 0.02 Mask loss: 0.2076 RPN box loss: 0.03894 RPN score loss: 0.01497 RPN total loss: 0.05391 Total loss: 1.92031 timestamp: 1654925415.7218497 iteration: 12925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2465 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.35036 L1 loss: 0.0000e+00 L2 loss: 1.4212 Learning rate: 0.02 Mask loss: 0.24197 RPN box loss: 0.04881 RPN score loss: 0.00365 RPN total loss: 0.05246 Total loss: 2.066 timestamp: 1654925418.9055579 iteration: 12930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14176 FastRCNN class loss: 0.09628 FastRCNN total loss: 0.23804 L1 loss: 0.0000e+00 L2 loss: 1.42096 Learning rate: 0.02 Mask loss: 0.25924 RPN box loss: 0.06205 RPN score loss: 0.00445 RPN total loss: 0.0665 Total loss: 1.98474 timestamp: 1654925422.2583256 iteration: 12935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16241 FastRCNN class loss: 0.1137 FastRCNN total loss: 0.27611 L1 loss: 0.0000e+00 L2 loss: 1.4207 Learning rate: 0.02 Mask loss: 0.14524 RPN box loss: 0.02771 RPN score loss: 0.0044 RPN total loss: 0.03211 Total loss: 1.87416 timestamp: 1654925425.5971441 iteration: 12940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08938 FastRCNN class loss: 0.04418 FastRCNN total loss: 0.13356 L1 loss: 0.0000e+00 L2 loss: 1.42042 Learning rate: 0.02 Mask loss: 0.29569 RPN box loss: 0.04674 RPN score loss: 0.00317 RPN total loss: 0.04991 Total loss: 1.89957 timestamp: 1654925428.7672937 iteration: 12945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18206 FastRCNN class loss: 0.11123 FastRCNN total loss: 0.29329 L1 loss: 0.0000e+00 L2 loss: 1.42014 Learning rate: 0.02 Mask loss: 0.20798 RPN box loss: 0.03965 RPN score loss: 0.02215 RPN total loss: 0.0618 Total loss: 1.98321 timestamp: 1654925431.9434056 iteration: 12950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12087 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.19035 L1 loss: 0.0000e+00 L2 loss: 1.41989 Learning rate: 0.02 Mask loss: 0.12923 RPN box loss: 0.09142 RPN score loss: 0.01071 RPN total loss: 0.10213 Total loss: 1.8416 timestamp: 1654925435.2132196 iteration: 12955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13675 FastRCNN class loss: 0.10493 FastRCNN total loss: 0.24168 L1 loss: 0.0000e+00 L2 loss: 1.41967 Learning rate: 0.02 Mask loss: 0.14631 RPN box loss: 0.0068 RPN score loss: 0.00795 RPN total loss: 0.01474 Total loss: 1.82241 timestamp: 1654925438.576814 iteration: 12960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08169 FastRCNN class loss: 0.06332 FastRCNN total loss: 0.14501 L1 loss: 0.0000e+00 L2 loss: 1.41942 Learning rate: 0.02 Mask loss: 0.13457 RPN box loss: 0.01734 RPN score loss: 0.00566 RPN total loss: 0.023 Total loss: 1.722 timestamp: 1654925441.7523978 iteration: 12965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.156 FastRCNN class loss: 0.10773 FastRCNN total loss: 0.26373 L1 loss: 0.0000e+00 L2 loss: 1.41917 Learning rate: 0.02 Mask loss: 0.25063 RPN box loss: 0.02913 RPN score loss: 0.00389 RPN total loss: 0.03302 Total loss: 1.96655 timestamp: 1654925445.0666325 iteration: 12970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17167 FastRCNN class loss: 0.09591 FastRCNN total loss: 0.26759 L1 loss: 0.0000e+00 L2 loss: 1.41893 Learning rate: 0.02 Mask loss: 0.16934 RPN box loss: 0.02757 RPN score loss: 0.01451 RPN total loss: 0.04208 Total loss: 1.89793 timestamp: 1654925448.3281465 iteration: 12975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10519 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.15655 L1 loss: 0.0000e+00 L2 loss: 1.4187 Learning rate: 0.02 Mask loss: 0.13367 RPN box loss: 0.00476 RPN score loss: 0.00299 RPN total loss: 0.00775 Total loss: 1.71667 timestamp: 1654925451.6374233 iteration: 12980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31297 FastRCNN class loss: 0.09538 FastRCNN total loss: 0.40835 L1 loss: 0.0000e+00 L2 loss: 1.41845 Learning rate: 0.02 Mask loss: 0.23754 RPN box loss: 0.01072 RPN score loss: 0.00298 RPN total loss: 0.0137 Total loss: 2.07803 timestamp: 1654925454.8208768 iteration: 12985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14577 FastRCNN class loss: 0.09043 FastRCNN total loss: 0.2362 L1 loss: 0.0000e+00 L2 loss: 1.41818 Learning rate: 0.02 Mask loss: 0.18311 RPN box loss: 0.03565 RPN score loss: 0.00407 RPN total loss: 0.03972 Total loss: 1.87721 timestamp: 1654925458.160713 iteration: 12990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16257 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.23414 L1 loss: 0.0000e+00 L2 loss: 1.41793 Learning rate: 0.02 Mask loss: 0.17938 RPN box loss: 0.02476 RPN score loss: 0.00612 RPN total loss: 0.03088 Total loss: 1.86233 timestamp: 1654925461.421241 iteration: 12995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09872 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.16082 L1 loss: 0.0000e+00 L2 loss: 1.41769 Learning rate: 0.02 Mask loss: 0.13871 RPN box loss: 0.0808 RPN score loss: 0.00494 RPN total loss: 0.08574 Total loss: 1.80296 timestamp: 1654925464.594579 iteration: 13000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15946 FastRCNN class loss: 0.10616 FastRCNN total loss: 0.26562 L1 loss: 0.0000e+00 L2 loss: 1.41746 Learning rate: 0.02 Mask loss: 0.1578 RPN box loss: 0.03765 RPN score loss: 0.01211 RPN total loss: 0.04976 Total loss: 1.89064 timestamp: 1654925467.9884117 iteration: 13005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1384 FastRCNN class loss: 0.07982 FastRCNN total loss: 0.21822 L1 loss: 0.0000e+00 L2 loss: 1.41721 Learning rate: 0.02 Mask loss: 0.17658 RPN box loss: 0.01159 RPN score loss: 0.01032 RPN total loss: 0.02191 Total loss: 1.83392 timestamp: 1654925471.186572 iteration: 13010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18758 FastRCNN class loss: 0.20007 FastRCNN total loss: 0.38765 L1 loss: 0.0000e+00 L2 loss: 1.41695 Learning rate: 0.02 Mask loss: 0.33979 RPN box loss: 0.03708 RPN score loss: 0.01101 RPN total loss: 0.04809 Total loss: 2.19248 timestamp: 1654925474.6080322 iteration: 13015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16881 FastRCNN class loss: 0.10251 FastRCNN total loss: 0.27133 L1 loss: 0.0000e+00 L2 loss: 1.4167 Learning rate: 0.02 Mask loss: 0.14763 RPN box loss: 0.03497 RPN score loss: 0.00817 RPN total loss: 0.04314 Total loss: 1.8788 timestamp: 1654925477.8441877 iteration: 13020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09229 FastRCNN class loss: 0.0488 FastRCNN total loss: 0.14109 L1 loss: 0.0000e+00 L2 loss: 1.41646 Learning rate: 0.02 Mask loss: 0.14083 RPN box loss: 0.02111 RPN score loss: 0.00299 RPN total loss: 0.0241 Total loss: 1.72247 timestamp: 1654925481.021566 iteration: 13025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20762 FastRCNN class loss: 0.11764 FastRCNN total loss: 0.32526 L1 loss: 0.0000e+00 L2 loss: 1.41618 Learning rate: 0.02 Mask loss: 0.17593 RPN box loss: 0.03854 RPN score loss: 0.00639 RPN total loss: 0.04492 Total loss: 1.9623 timestamp: 1654925484.2966924 iteration: 13030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11053 FastRCNN class loss: 0.05991 FastRCNN total loss: 0.17044 L1 loss: 0.0000e+00 L2 loss: 1.41594 Learning rate: 0.02 Mask loss: 0.16552 RPN box loss: 0.03501 RPN score loss: 0.01147 RPN total loss: 0.04648 Total loss: 1.79838 timestamp: 1654925487.5295637 iteration: 13035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15467 FastRCNN class loss: 0.07341 FastRCNN total loss: 0.22808 L1 loss: 0.0000e+00 L2 loss: 1.4157 Learning rate: 0.02 Mask loss: 0.14513 RPN box loss: 0.01217 RPN score loss: 0.00324 RPN total loss: 0.0154 Total loss: 1.80431 timestamp: 1654925490.7450092 iteration: 13040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18676 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.25257 L1 loss: 0.0000e+00 L2 loss: 1.41545 Learning rate: 0.02 Mask loss: 0.16883 RPN box loss: 0.05773 RPN score loss: 0.00999 RPN total loss: 0.06772 Total loss: 1.90458 timestamp: 1654925494.0210075 iteration: 13045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2119 FastRCNN class loss: 0.06203 FastRCNN total loss: 0.27392 L1 loss: 0.0000e+00 L2 loss: 1.41519 Learning rate: 0.02 Mask loss: 0.161 RPN box loss: 0.06163 RPN score loss: 0.00432 RPN total loss: 0.06595 Total loss: 1.91606 timestamp: 1654925497.4075015 iteration: 13050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12361 FastRCNN class loss: 0.07373 FastRCNN total loss: 0.19734 L1 loss: 0.0000e+00 L2 loss: 1.41493 Learning rate: 0.02 Mask loss: 0.17001 RPN box loss: 0.0714 RPN score loss: 0.00758 RPN total loss: 0.07898 Total loss: 1.86127 timestamp: 1654925500.6311789 iteration: 13055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11711 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.17494 L1 loss: 0.0000e+00 L2 loss: 1.41468 Learning rate: 0.02 Mask loss: 0.13581 RPN box loss: 0.04037 RPN score loss: 0.02156 RPN total loss: 0.06194 Total loss: 1.78736 timestamp: 1654925503.9818492 iteration: 13060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1647 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.22744 L1 loss: 0.0000e+00 L2 loss: 1.41442 Learning rate: 0.02 Mask loss: 0.14334 RPN box loss: 0.02152 RPN score loss: 0.00683 RPN total loss: 0.02835 Total loss: 1.81356 timestamp: 1654925507.1445715 iteration: 13065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2287 FastRCNN class loss: 0.09835 FastRCNN total loss: 0.32705 L1 loss: 0.0000e+00 L2 loss: 1.41419 Learning rate: 0.02 Mask loss: 0.15335 RPN box loss: 0.02626 RPN score loss: 0.00698 RPN total loss: 0.03324 Total loss: 1.92782 timestamp: 1654925510.4511385 iteration: 13070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19387 FastRCNN class loss: 0.10226 FastRCNN total loss: 0.29613 L1 loss: 0.0000e+00 L2 loss: 1.41394 Learning rate: 0.02 Mask loss: 0.18949 RPN box loss: 0.06229 RPN score loss: 0.01004 RPN total loss: 0.07232 Total loss: 1.97189 timestamp: 1654925513.637169 iteration: 13075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1468 FastRCNN class loss: 0.09988 FastRCNN total loss: 0.24669 L1 loss: 0.0000e+00 L2 loss: 1.4137 Learning rate: 0.02 Mask loss: 0.15275 RPN box loss: 0.04859 RPN score loss: 0.00733 RPN total loss: 0.05592 Total loss: 1.86906 timestamp: 1654925516.9351428 iteration: 13080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14023 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.20496 L1 loss: 0.0000e+00 L2 loss: 1.41346 Learning rate: 0.02 Mask loss: 0.16965 RPN box loss: 0.04091 RPN score loss: 0.00515 RPN total loss: 0.04606 Total loss: 1.83414 timestamp: 1654925520.1397598 iteration: 13085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12209 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.20543 L1 loss: 0.0000e+00 L2 loss: 1.41321 Learning rate: 0.02 Mask loss: 0.18999 RPN box loss: 0.03899 RPN score loss: 0.00698 RPN total loss: 0.04597 Total loss: 1.8546 timestamp: 1654925523.3311744 iteration: 13090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11789 FastRCNN class loss: 0.05956 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 1.41297 Learning rate: 0.02 Mask loss: 0.14001 RPN box loss: 0.04093 RPN score loss: 0.00306 RPN total loss: 0.04399 Total loss: 1.77443 timestamp: 1654925526.5889273 iteration: 13095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20424 FastRCNN class loss: 0.14478 FastRCNN total loss: 0.34902 L1 loss: 0.0000e+00 L2 loss: 1.41273 Learning rate: 0.02 Mask loss: 0.2989 RPN box loss: 0.02088 RPN score loss: 0.00447 RPN total loss: 0.02535 Total loss: 2.086 timestamp: 1654925529.8219204 iteration: 13100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10377 FastRCNN class loss: 0.1098 FastRCNN total loss: 0.21357 L1 loss: 0.0000e+00 L2 loss: 1.41247 Learning rate: 0.02 Mask loss: 0.1972 RPN box loss: 0.03377 RPN score loss: 0.01936 RPN total loss: 0.05313 Total loss: 1.87637 timestamp: 1654925533.054878 iteration: 13105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20672 FastRCNN class loss: 0.12488 FastRCNN total loss: 0.33161 L1 loss: 0.0000e+00 L2 loss: 1.4122 Learning rate: 0.02 Mask loss: 0.18915 RPN box loss: 0.08393 RPN score loss: 0.00833 RPN total loss: 0.09226 Total loss: 2.02522 timestamp: 1654925536.2578287 iteration: 13110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22225 FastRCNN class loss: 0.12353 FastRCNN total loss: 0.34577 L1 loss: 0.0000e+00 L2 loss: 1.41194 Learning rate: 0.02 Mask loss: 0.16835 RPN box loss: 0.04758 RPN score loss: 0.00637 RPN total loss: 0.05395 Total loss: 1.98001 timestamp: 1654925539.4664245 iteration: 13115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16427 FastRCNN class loss: 0.09156 FastRCNN total loss: 0.25583 L1 loss: 0.0000e+00 L2 loss: 1.41169 Learning rate: 0.02 Mask loss: 0.16923 RPN box loss: 0.07214 RPN score loss: 0.01065 RPN total loss: 0.08279 Total loss: 1.91955 timestamp: 1654925542.6809547 iteration: 13120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17058 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.25931 L1 loss: 0.0000e+00 L2 loss: 1.41145 Learning rate: 0.02 Mask loss: 0.1469 RPN box loss: 0.02699 RPN score loss: 0.01065 RPN total loss: 0.03764 Total loss: 1.8553 timestamp: 1654925545.912593 iteration: 13125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10875 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.18927 L1 loss: 0.0000e+00 L2 loss: 1.41122 Learning rate: 0.02 Mask loss: 0.11294 RPN box loss: 0.06302 RPN score loss: 0.00307 RPN total loss: 0.06609 Total loss: 1.77952 timestamp: 1654925549.1461744 iteration: 13130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06704 FastRCNN class loss: 0.03939 FastRCNN total loss: 0.10643 L1 loss: 0.0000e+00 L2 loss: 1.41096 Learning rate: 0.02 Mask loss: 0.10417 RPN box loss: 0.02626 RPN score loss: 0.00195 RPN total loss: 0.02821 Total loss: 1.64977 timestamp: 1654925552.4510427 iteration: 13135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11622 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.17056 L1 loss: 0.0000e+00 L2 loss: 1.41072 Learning rate: 0.02 Mask loss: 0.21182 RPN box loss: 0.04778 RPN score loss: 0.01063 RPN total loss: 0.05841 Total loss: 1.85151 timestamp: 1654925555.659929 iteration: 13140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18711 FastRCNN class loss: 0.10404 FastRCNN total loss: 0.29115 L1 loss: 0.0000e+00 L2 loss: 1.41047 Learning rate: 0.02 Mask loss: 0.20595 RPN box loss: 0.05227 RPN score loss: 0.01608 RPN total loss: 0.06835 Total loss: 1.97591 timestamp: 1654925558.9867282 iteration: 13145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21738 FastRCNN class loss: 0.11835 FastRCNN total loss: 0.33573 L1 loss: 0.0000e+00 L2 loss: 1.41021 Learning rate: 0.02 Mask loss: 0.24008 RPN box loss: 0.04811 RPN score loss: 0.01218 RPN total loss: 0.06029 Total loss: 2.04632 timestamp: 1654925562.219129 iteration: 13150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1728 FastRCNN class loss: 0.1248 FastRCNN total loss: 0.2976 L1 loss: 0.0000e+00 L2 loss: 1.40997 Learning rate: 0.02 Mask loss: 0.20988 RPN box loss: 0.06136 RPN score loss: 0.00869 RPN total loss: 0.07005 Total loss: 1.9875 timestamp: 1654925565.5786524 iteration: 13155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16372 FastRCNN class loss: 0.0971 FastRCNN total loss: 0.26082 L1 loss: 0.0000e+00 L2 loss: 1.40974 Learning rate: 0.02 Mask loss: 0.14797 RPN box loss: 0.03302 RPN score loss: 0.01129 RPN total loss: 0.04431 Total loss: 1.86283 timestamp: 1654925568.8640876 iteration: 13160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11096 FastRCNN class loss: 0.14217 FastRCNN total loss: 0.25314 L1 loss: 0.0000e+00 L2 loss: 1.40949 Learning rate: 0.02 Mask loss: 0.17392 RPN box loss: 0.0541 RPN score loss: 0.0234 RPN total loss: 0.07749 Total loss: 1.91404 timestamp: 1654925572.070453 iteration: 13165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19025 FastRCNN class loss: 0.0878 FastRCNN total loss: 0.27805 L1 loss: 0.0000e+00 L2 loss: 1.40924 Learning rate: 0.02 Mask loss: 0.17451 RPN box loss: 0.05133 RPN score loss: 0.00925 RPN total loss: 0.06057 Total loss: 1.92237 timestamp: 1654925575.3438864 iteration: 13170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16429 FastRCNN class loss: 0.10136 FastRCNN total loss: 0.26566 L1 loss: 0.0000e+00 L2 loss: 1.40897 Learning rate: 0.02 Mask loss: 0.14269 RPN box loss: 0.06527 RPN score loss: 0.01821 RPN total loss: 0.08347 Total loss: 1.9008 timestamp: 1654925578.5043142 iteration: 13175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11862 FastRCNN class loss: 0.07651 FastRCNN total loss: 0.19512 L1 loss: 0.0000e+00 L2 loss: 1.40874 Learning rate: 0.02 Mask loss: 0.16009 RPN box loss: 0.03802 RPN score loss: 0.01127 RPN total loss: 0.0493 Total loss: 1.81325 timestamp: 1654925581.9066217 iteration: 13180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16834 FastRCNN class loss: 0.12479 FastRCNN total loss: 0.29314 L1 loss: 0.0000e+00 L2 loss: 1.4085 Learning rate: 0.02 Mask loss: 0.23954 RPN box loss: 0.04082 RPN score loss: 0.01427 RPN total loss: 0.05509 Total loss: 1.99627 timestamp: 1654925585.1444223 iteration: 13185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16141 FastRCNN class loss: 0.12185 FastRCNN total loss: 0.28326 L1 loss: 0.0000e+00 L2 loss: 1.40826 Learning rate: 0.02 Mask loss: 0.18399 RPN box loss: 0.07032 RPN score loss: 0.01222 RPN total loss: 0.08253 Total loss: 1.95805 timestamp: 1654925588.427562 iteration: 13190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20721 FastRCNN class loss: 0.15024 FastRCNN total loss: 0.35745 L1 loss: 0.0000e+00 L2 loss: 1.40802 Learning rate: 0.02 Mask loss: 0.20379 RPN box loss: 0.06416 RPN score loss: 0.03195 RPN total loss: 0.09611 Total loss: 2.06538 timestamp: 1654925591.5500736 iteration: 13195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18041 FastRCNN class loss: 0.10661 FastRCNN total loss: 0.28702 L1 loss: 0.0000e+00 L2 loss: 1.40775 Learning rate: 0.02 Mask loss: 0.16501 RPN box loss: 0.00969 RPN score loss: 0.00359 RPN total loss: 0.01327 Total loss: 1.87306 timestamp: 1654925594.7634664 iteration: 13200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22784 FastRCNN class loss: 0.11535 FastRCNN total loss: 0.34318 L1 loss: 0.0000e+00 L2 loss: 1.40751 Learning rate: 0.02 Mask loss: 0.22282 RPN box loss: 0.0464 RPN score loss: 0.0073 RPN total loss: 0.0537 Total loss: 2.02721 timestamp: 1654925597.915434 iteration: 13205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14418 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.21664 L1 loss: 0.0000e+00 L2 loss: 1.40728 Learning rate: 0.02 Mask loss: 0.20806 RPN box loss: 0.02432 RPN score loss: 0.00471 RPN total loss: 0.02903 Total loss: 1.86101 timestamp: 1654925601.1669965 iteration: 13210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10219 FastRCNN class loss: 0.06393 FastRCNN total loss: 0.16612 L1 loss: 0.0000e+00 L2 loss: 1.40704 Learning rate: 0.02 Mask loss: 0.12473 RPN box loss: 0.01276 RPN score loss: 0.00562 RPN total loss: 0.01838 Total loss: 1.71627 timestamp: 1654925604.3585787 iteration: 13215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20564 FastRCNN class loss: 0.129 FastRCNN total loss: 0.33465 L1 loss: 0.0000e+00 L2 loss: 1.40681 Learning rate: 0.02 Mask loss: 0.16862 RPN box loss: 0.02275 RPN score loss: 0.00424 RPN total loss: 0.027 Total loss: 1.93707 timestamp: 1654925607.6786785 iteration: 13220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21217 FastRCNN class loss: 0.12177 FastRCNN total loss: 0.33394 L1 loss: 0.0000e+00 L2 loss: 1.40655 Learning rate: 0.02 Mask loss: 0.24098 RPN box loss: 0.05991 RPN score loss: 0.01314 RPN total loss: 0.07305 Total loss: 2.05451 timestamp: 1654925610.9218786 iteration: 13225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11198 FastRCNN class loss: 0.05676 FastRCNN total loss: 0.16874 L1 loss: 0.0000e+00 L2 loss: 1.4063 Learning rate: 0.02 Mask loss: 0.17574 RPN box loss: 0.02395 RPN score loss: 0.0028 RPN total loss: 0.02675 Total loss: 1.77753 timestamp: 1654925614.193253 iteration: 13230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18792 FastRCNN class loss: 0.09129 FastRCNN total loss: 0.27921 L1 loss: 0.0000e+00 L2 loss: 1.40607 Learning rate: 0.02 Mask loss: 0.10388 RPN box loss: 0.02289 RPN score loss: 0.00403 RPN total loss: 0.02693 Total loss: 1.81608 timestamp: 1654925617.4857876 iteration: 13235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14007 FastRCNN class loss: 0.08941 FastRCNN total loss: 0.22948 L1 loss: 0.0000e+00 L2 loss: 1.40583 Learning rate: 0.02 Mask loss: 0.28195 RPN box loss: 0.04798 RPN score loss: 0.00499 RPN total loss: 0.05297 Total loss: 1.97023 timestamp: 1654925620.7024941 iteration: 13240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18315 FastRCNN class loss: 0.10686 FastRCNN total loss: 0.29001 L1 loss: 0.0000e+00 L2 loss: 1.40556 Learning rate: 0.02 Mask loss: 0.25747 RPN box loss: 0.04816 RPN score loss: 0.01043 RPN total loss: 0.0586 Total loss: 2.01164 timestamp: 1654925623.9694076 iteration: 13245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16486 FastRCNN class loss: 0.10481 FastRCNN total loss: 0.26967 L1 loss: 0.0000e+00 L2 loss: 1.40531 Learning rate: 0.02 Mask loss: 0.14443 RPN box loss: 0.0557 RPN score loss: 0.01571 RPN total loss: 0.07141 Total loss: 1.89082 timestamp: 1654925627.2175558 iteration: 13250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15228 FastRCNN class loss: 0.11357 FastRCNN total loss: 0.26584 L1 loss: 0.0000e+00 L2 loss: 1.40508 Learning rate: 0.02 Mask loss: 0.15578 RPN box loss: 0.02843 RPN score loss: 0.00928 RPN total loss: 0.03771 Total loss: 1.86441 timestamp: 1654925630.4922338 iteration: 13255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15918 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.24198 L1 loss: 0.0000e+00 L2 loss: 1.40483 Learning rate: 0.02 Mask loss: 0.18972 RPN box loss: 0.02169 RPN score loss: 0.00983 RPN total loss: 0.03152 Total loss: 1.86805 timestamp: 1654925633.5849988 iteration: 13260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11193 FastRCNN class loss: 0.06543 FastRCNN total loss: 0.17736 L1 loss: 0.0000e+00 L2 loss: 1.40459 Learning rate: 0.02 Mask loss: 0.10778 RPN box loss: 0.02797 RPN score loss: 0.0074 RPN total loss: 0.03537 Total loss: 1.7251 timestamp: 1654925636.8462029 iteration: 13265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13534 FastRCNN class loss: 0.06708 FastRCNN total loss: 0.20241 L1 loss: 0.0000e+00 L2 loss: 1.40435 Learning rate: 0.02 Mask loss: 0.1341 RPN box loss: 0.02303 RPN score loss: 0.00507 RPN total loss: 0.02811 Total loss: 1.76897 timestamp: 1654925640.0575671 iteration: 13270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12353 FastRCNN class loss: 0.09487 FastRCNN total loss: 0.21841 L1 loss: 0.0000e+00 L2 loss: 1.4041 Learning rate: 0.02 Mask loss: 0.19684 RPN box loss: 0.03122 RPN score loss: 0.0148 RPN total loss: 0.04602 Total loss: 1.86537 timestamp: 1654925643.2845001 iteration: 13275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18358 FastRCNN class loss: 0.11004 FastRCNN total loss: 0.29362 L1 loss: 0.0000e+00 L2 loss: 1.40386 Learning rate: 0.02 Mask loss: 0.22689 RPN box loss: 0.04771 RPN score loss: 0.01578 RPN total loss: 0.06349 Total loss: 1.98786 timestamp: 1654925646.5480494 iteration: 13280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12074 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.19306 L1 loss: 0.0000e+00 L2 loss: 1.40361 Learning rate: 0.02 Mask loss: 0.10194 RPN box loss: 0.03721 RPN score loss: 0.00662 RPN total loss: 0.04383 Total loss: 1.74244 timestamp: 1654925649.724923 iteration: 13285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13619 FastRCNN class loss: 0.09038 FastRCNN total loss: 0.22656 L1 loss: 0.0000e+00 L2 loss: 1.40336 Learning rate: 0.02 Mask loss: 0.18724 RPN box loss: 0.06618 RPN score loss: 0.01406 RPN total loss: 0.08023 Total loss: 1.8974 timestamp: 1654925653.0801446 iteration: 13290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15452 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.23521 L1 loss: 0.0000e+00 L2 loss: 1.40308 Learning rate: 0.02 Mask loss: 0.14959 RPN box loss: 0.05547 RPN score loss: 0.01478 RPN total loss: 0.07025 Total loss: 1.85813 timestamp: 1654925656.267069 iteration: 13295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17924 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.27234 L1 loss: 0.0000e+00 L2 loss: 1.40283 Learning rate: 0.02 Mask loss: 0.16657 RPN box loss: 0.04273 RPN score loss: 0.00247 RPN total loss: 0.0452 Total loss: 1.88694 timestamp: 1654925659.511579 iteration: 13300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16681 FastRCNN class loss: 0.11274 FastRCNN total loss: 0.27955 L1 loss: 0.0000e+00 L2 loss: 1.4026 Learning rate: 0.02 Mask loss: 0.12881 RPN box loss: 0.03056 RPN score loss: 0.01288 RPN total loss: 0.04344 Total loss: 1.85441 timestamp: 1654925662.7195501 iteration: 13305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16087 FastRCNN class loss: 0.12096 FastRCNN total loss: 0.28183 L1 loss: 0.0000e+00 L2 loss: 1.40235 Learning rate: 0.02 Mask loss: 0.17304 RPN box loss: 0.0291 RPN score loss: 0.01033 RPN total loss: 0.03943 Total loss: 1.89666 timestamp: 1654925666.08701 iteration: 13310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18343 FastRCNN class loss: 0.11109 FastRCNN total loss: 0.29453 L1 loss: 0.0000e+00 L2 loss: 1.40214 Learning rate: 0.02 Mask loss: 0.2675 RPN box loss: 0.03345 RPN score loss: 0.00861 RPN total loss: 0.04206 Total loss: 2.00621 timestamp: 1654925669.249061 iteration: 13315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16506 FastRCNN class loss: 0.09835 FastRCNN total loss: 0.26341 L1 loss: 0.0000e+00 L2 loss: 1.40188 Learning rate: 0.02 Mask loss: 0.19798 RPN box loss: 0.02969 RPN score loss: 0.00775 RPN total loss: 0.03744 Total loss: 1.90072 timestamp: 1654925672.514026 iteration: 13320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15573 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.23626 L1 loss: 0.0000e+00 L2 loss: 1.40163 Learning rate: 0.02 Mask loss: 0.18597 RPN box loss: 0.00813 RPN score loss: 0.00532 RPN total loss: 0.01344 Total loss: 1.8373 timestamp: 1654925675.719034 iteration: 13325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1532 FastRCNN class loss: 0.09241 FastRCNN total loss: 0.24561 L1 loss: 0.0000e+00 L2 loss: 1.4014 Learning rate: 0.02 Mask loss: 0.17877 RPN box loss: 0.00942 RPN score loss: 0.0062 RPN total loss: 0.01562 Total loss: 1.84141 timestamp: 1654925679.0781305 iteration: 13330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21575 FastRCNN class loss: 0.1131 FastRCNN total loss: 0.32885 L1 loss: 0.0000e+00 L2 loss: 1.40116 Learning rate: 0.02 Mask loss: 0.14379 RPN box loss: 0.05715 RPN score loss: 0.00364 RPN total loss: 0.06079 Total loss: 1.93459 timestamp: 1654925682.282773 iteration: 13335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11757 FastRCNN class loss: 0.09869 FastRCNN total loss: 0.21626 L1 loss: 0.0000e+00 L2 loss: 1.40091 Learning rate: 0.02 Mask loss: 0.15113 RPN box loss: 0.02692 RPN score loss: 0.00998 RPN total loss: 0.0369 Total loss: 1.8052 timestamp: 1654925685.5162525 iteration: 13340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10764 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.16661 L1 loss: 0.0000e+00 L2 loss: 1.40065 Learning rate: 0.02 Mask loss: 0.12837 RPN box loss: 0.0205 RPN score loss: 0.01218 RPN total loss: 0.03268 Total loss: 1.72831 timestamp: 1654925688.9189672 iteration: 13345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17331 FastRCNN class loss: 0.09412 FastRCNN total loss: 0.26743 L1 loss: 0.0000e+00 L2 loss: 1.40042 Learning rate: 0.02 Mask loss: 0.16619 RPN box loss: 0.0145 RPN score loss: 0.00803 RPN total loss: 0.02253 Total loss: 1.85657 timestamp: 1654925692.1519237 iteration: 13350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18367 FastRCNN class loss: 0.11842 FastRCNN total loss: 0.30209 L1 loss: 0.0000e+00 L2 loss: 1.40019 Learning rate: 0.02 Mask loss: 0.17969 RPN box loss: 0.0366 RPN score loss: 0.0081 RPN total loss: 0.0447 Total loss: 1.92667 timestamp: 1654925695.4131303 iteration: 13355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1604 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.23676 L1 loss: 0.0000e+00 L2 loss: 1.39995 Learning rate: 0.02 Mask loss: 0.26285 RPN box loss: 0.04868 RPN score loss: 0.01514 RPN total loss: 0.06381 Total loss: 1.96338 timestamp: 1654925698.6390338 iteration: 13360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1497 FastRCNN class loss: 0.09999 FastRCNN total loss: 0.24969 L1 loss: 0.0000e+00 L2 loss: 1.39973 Learning rate: 0.02 Mask loss: 0.12654 RPN box loss: 0.07053 RPN score loss: 0.01304 RPN total loss: 0.08357 Total loss: 1.85953 timestamp: 1654925702.0238645 iteration: 13365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18906 FastRCNN class loss: 0.10918 FastRCNN total loss: 0.29824 L1 loss: 0.0000e+00 L2 loss: 1.39948 Learning rate: 0.02 Mask loss: 0.21895 RPN box loss: 0.04476 RPN score loss: 0.00901 RPN total loss: 0.05378 Total loss: 1.97045 timestamp: 1654925705.2110202 iteration: 13370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19629 FastRCNN class loss: 0.15411 FastRCNN total loss: 0.35041 L1 loss: 0.0000e+00 L2 loss: 1.39921 Learning rate: 0.02 Mask loss: 0.19773 RPN box loss: 0.04732 RPN score loss: 0.01118 RPN total loss: 0.0585 Total loss: 2.00585 timestamp: 1654925708.4777472 iteration: 13375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14301 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.21644 L1 loss: 0.0000e+00 L2 loss: 1.39898 Learning rate: 0.02 Mask loss: 0.12367 RPN box loss: 0.02914 RPN score loss: 0.00366 RPN total loss: 0.0328 Total loss: 1.7719 timestamp: 1654925711.7603798 iteration: 13380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15039 FastRCNN class loss: 0.06208 FastRCNN total loss: 0.21247 L1 loss: 0.0000e+00 L2 loss: 1.39872 Learning rate: 0.02 Mask loss: 0.24024 RPN box loss: 0.01021 RPN score loss: 0.0031 RPN total loss: 0.01331 Total loss: 1.86474 timestamp: 1654925715.033636 iteration: 13385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14183 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.23015 L1 loss: 0.0000e+00 L2 loss: 1.39847 Learning rate: 0.02 Mask loss: 0.13691 RPN box loss: 0.02233 RPN score loss: 0.00489 RPN total loss: 0.02723 Total loss: 1.79276 timestamp: 1654925718.4042962 iteration: 13390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21444 FastRCNN class loss: 0.11988 FastRCNN total loss: 0.33432 L1 loss: 0.0000e+00 L2 loss: 1.39823 Learning rate: 0.02 Mask loss: 0.15175 RPN box loss: 0.01268 RPN score loss: 0.00378 RPN total loss: 0.01646 Total loss: 1.90076 timestamp: 1654925721.6033957 iteration: 13395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20278 FastRCNN class loss: 0.13155 FastRCNN total loss: 0.33433 L1 loss: 0.0000e+00 L2 loss: 1.39802 Learning rate: 0.02 Mask loss: 0.25954 RPN box loss: 0.02511 RPN score loss: 0.00764 RPN total loss: 0.03275 Total loss: 2.02464 timestamp: 1654925724.8754613 iteration: 13400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15226 FastRCNN class loss: 0.08172 FastRCNN total loss: 0.23398 L1 loss: 0.0000e+00 L2 loss: 1.39778 Learning rate: 0.02 Mask loss: 0.18711 RPN box loss: 0.01199 RPN score loss: 0.00367 RPN total loss: 0.01566 Total loss: 1.83452 timestamp: 1654925728.14269 iteration: 13405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12431 FastRCNN class loss: 0.07777 FastRCNN total loss: 0.20208 L1 loss: 0.0000e+00 L2 loss: 1.39754 Learning rate: 0.02 Mask loss: 0.1573 RPN box loss: 0.08553 RPN score loss: 0.00592 RPN total loss: 0.09145 Total loss: 1.84837 timestamp: 1654925731.49452 iteration: 13410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15504 FastRCNN class loss: 0.06532 FastRCNN total loss: 0.22035 L1 loss: 0.0000e+00 L2 loss: 1.39731 Learning rate: 0.02 Mask loss: 0.17031 RPN box loss: 0.05013 RPN score loss: 0.00537 RPN total loss: 0.0555 Total loss: 1.84347 timestamp: 1654925734.8016942 iteration: 13415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12942 FastRCNN class loss: 0.08703 FastRCNN total loss: 0.21644 L1 loss: 0.0000e+00 L2 loss: 1.39704 Learning rate: 0.02 Mask loss: 0.1927 RPN box loss: 0.02787 RPN score loss: 0.02066 RPN total loss: 0.04854 Total loss: 1.85473 timestamp: 1654925738.0575817 iteration: 13420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14153 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.23847 L1 loss: 0.0000e+00 L2 loss: 1.39678 Learning rate: 0.02 Mask loss: 0.23784 RPN box loss: 0.01237 RPN score loss: 0.00785 RPN total loss: 0.02022 Total loss: 1.8933 timestamp: 1654925741.2958152 iteration: 13425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15508 FastRCNN class loss: 0.11504 FastRCNN total loss: 0.27013 L1 loss: 0.0000e+00 L2 loss: 1.39654 Learning rate: 0.02 Mask loss: 0.18965 RPN box loss: 0.04022 RPN score loss: 0.0156 RPN total loss: 0.05583 Total loss: 1.91214 timestamp: 1654925744.5631056 iteration: 13430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12443 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.17912 L1 loss: 0.0000e+00 L2 loss: 1.39629 Learning rate: 0.02 Mask loss: 0.10946 RPN box loss: 0.04194 RPN score loss: 0.00416 RPN total loss: 0.04609 Total loss: 1.73096 timestamp: 1654925747.8896914 iteration: 13435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12828 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.21961 L1 loss: 0.0000e+00 L2 loss: 1.39605 Learning rate: 0.02 Mask loss: 0.15342 RPN box loss: 0.07895 RPN score loss: 0.01177 RPN total loss: 0.09072 Total loss: 1.8598 timestamp: 1654925751.1022654 iteration: 13440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17644 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.28798 L1 loss: 0.0000e+00 L2 loss: 1.39582 Learning rate: 0.02 Mask loss: 0.21714 RPN box loss: 0.02385 RPN score loss: 0.00472 RPN total loss: 0.02856 Total loss: 1.9295 timestamp: 1654925754.3971658 iteration: 13445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14482 FastRCNN class loss: 0.10658 FastRCNN total loss: 0.2514 L1 loss: 0.0000e+00 L2 loss: 1.39558 Learning rate: 0.02 Mask loss: 0.19285 RPN box loss: 0.01413 RPN score loss: 0.00829 RPN total loss: 0.02242 Total loss: 1.86225 timestamp: 1654925757.560507 iteration: 13450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13387 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.18621 L1 loss: 0.0000e+00 L2 loss: 1.39534 Learning rate: 0.02 Mask loss: 0.14156 RPN box loss: 0.0382 RPN score loss: 0.00356 RPN total loss: 0.04176 Total loss: 1.76486 timestamp: 1654925760.9278524 iteration: 13455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12576 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 1.39511 Learning rate: 0.02 Mask loss: 0.10372 RPN box loss: 0.01782 RPN score loss: 0.00444 RPN total loss: 0.02226 Total loss: 1.71114 timestamp: 1654925764.1619549 iteration: 13460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1846 FastRCNN class loss: 0.10956 FastRCNN total loss: 0.29416 L1 loss: 0.0000e+00 L2 loss: 1.39486 Learning rate: 0.02 Mask loss: 0.15952 RPN box loss: 0.04889 RPN score loss: 0.00764 RPN total loss: 0.05652 Total loss: 1.90506 timestamp: 1654925767.4689646 iteration: 13465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17695 FastRCNN class loss: 0.1135 FastRCNN total loss: 0.29045 L1 loss: 0.0000e+00 L2 loss: 1.39461 Learning rate: 0.02 Mask loss: 0.18815 RPN box loss: 0.0389 RPN score loss: 0.01101 RPN total loss: 0.04991 Total loss: 1.92312 timestamp: 1654925770.6722424 iteration: 13470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14626 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.22053 L1 loss: 0.0000e+00 L2 loss: 1.39435 Learning rate: 0.02 Mask loss: 0.18893 RPN box loss: 0.03757 RPN score loss: 0.00317 RPN total loss: 0.04075 Total loss: 1.84456 timestamp: 1654925773.9814487 iteration: 13475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16483 FastRCNN class loss: 0.12483 FastRCNN total loss: 0.28965 L1 loss: 0.0000e+00 L2 loss: 1.3941 Learning rate: 0.02 Mask loss: 0.22892 RPN box loss: 0.05622 RPN score loss: 0.01069 RPN total loss: 0.06692 Total loss: 1.97959 timestamp: 1654925777.376883 iteration: 13480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1619 FastRCNN class loss: 0.09979 FastRCNN total loss: 0.26169 L1 loss: 0.0000e+00 L2 loss: 1.39385 Learning rate: 0.02 Mask loss: 0.18056 RPN box loss: 0.07453 RPN score loss: 0.01578 RPN total loss: 0.09031 Total loss: 1.92641 timestamp: 1654925780.608745 iteration: 13485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16965 FastRCNN class loss: 0.12294 FastRCNN total loss: 0.29259 L1 loss: 0.0000e+00 L2 loss: 1.39361 Learning rate: 0.02 Mask loss: 0.16218 RPN box loss: 0.02388 RPN score loss: 0.00742 RPN total loss: 0.0313 Total loss: 1.87968 timestamp: 1654925783.9456835 iteration: 13490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1659 FastRCNN class loss: 0.10171 FastRCNN total loss: 0.26761 L1 loss: 0.0000e+00 L2 loss: 1.39336 Learning rate: 0.02 Mask loss: 0.1759 RPN box loss: 0.01101 RPN score loss: 0.0073 RPN total loss: 0.01831 Total loss: 1.85519 timestamp: 1654925787.18283 iteration: 13495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10395 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.17743 L1 loss: 0.0000e+00 L2 loss: 1.39311 Learning rate: 0.02 Mask loss: 0.12458 RPN box loss: 0.0156 RPN score loss: 0.0044 RPN total loss: 0.02 Total loss: 1.71512 timestamp: 1654925790.5081272 iteration: 13500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13476 FastRCNN class loss: 0.10405 FastRCNN total loss: 0.23881 L1 loss: 0.0000e+00 L2 loss: 1.39288 Learning rate: 0.02 Mask loss: 0.16999 RPN box loss: 0.02241 RPN score loss: 0.00678 RPN total loss: 0.02919 Total loss: 1.83087 timestamp: 1654925793.7360413 iteration: 13505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11598 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.17673 L1 loss: 0.0000e+00 L2 loss: 1.39263 Learning rate: 0.02 Mask loss: 0.12675 RPN box loss: 0.02246 RPN score loss: 0.00665 RPN total loss: 0.02911 Total loss: 1.72522 timestamp: 1654925797.1031787 iteration: 13510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21312 FastRCNN class loss: 0.12216 FastRCNN total loss: 0.33528 L1 loss: 0.0000e+00 L2 loss: 1.39237 Learning rate: 0.02 Mask loss: 0.19029 RPN box loss: 0.07506 RPN score loss: 0.01206 RPN total loss: 0.08713 Total loss: 2.00507 timestamp: 1654925800.284751 iteration: 13515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20574 FastRCNN class loss: 0.10552 FastRCNN total loss: 0.31126 L1 loss: 0.0000e+00 L2 loss: 1.39211 Learning rate: 0.02 Mask loss: 0.21312 RPN box loss: 0.02408 RPN score loss: 0.0075 RPN total loss: 0.03158 Total loss: 1.94807 timestamp: 1654925803.6038852 iteration: 13520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10353 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.17486 L1 loss: 0.0000e+00 L2 loss: 1.39187 Learning rate: 0.02 Mask loss: 0.1837 RPN box loss: 0.01814 RPN score loss: 0.00308 RPN total loss: 0.02122 Total loss: 1.77165 timestamp: 1654925806.7624779 iteration: 13525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09982 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.16235 L1 loss: 0.0000e+00 L2 loss: 1.39164 Learning rate: 0.02 Mask loss: 0.10728 RPN box loss: 0.02996 RPN score loss: 0.0046 RPN total loss: 0.03456 Total loss: 1.69584 timestamp: 1654925810.0724664 iteration: 13530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17033 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.24306 L1 loss: 0.0000e+00 L2 loss: 1.39141 Learning rate: 0.02 Mask loss: 0.16276 RPN box loss: 0.03984 RPN score loss: 0.0067 RPN total loss: 0.04654 Total loss: 1.84377 timestamp: 1654925813.3812568 iteration: 13535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15084 FastRCNN class loss: 0.14287 FastRCNN total loss: 0.29372 L1 loss: 0.0000e+00 L2 loss: 1.39116 Learning rate: 0.02 Mask loss: 0.15702 RPN box loss: 0.05007 RPN score loss: 0.01402 RPN total loss: 0.06409 Total loss: 1.90599 timestamp: 1654925816.602747 iteration: 13540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21232 FastRCNN class loss: 0.11016 FastRCNN total loss: 0.32248 L1 loss: 0.0000e+00 L2 loss: 1.39092 Learning rate: 0.02 Mask loss: 0.22605 RPN box loss: 0.02866 RPN score loss: 0.00591 RPN total loss: 0.03457 Total loss: 1.97402 timestamp: 1654925819.9364188 iteration: 13545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08967 FastRCNN class loss: 0.06996 FastRCNN total loss: 0.15963 L1 loss: 0.0000e+00 L2 loss: 1.39067 Learning rate: 0.02 Mask loss: 0.11906 RPN box loss: 0.01424 RPN score loss: 0.00574 RPN total loss: 0.01997 Total loss: 1.68933 timestamp: 1654925823.1857502 iteration: 13550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16666 FastRCNN class loss: 0.07955 FastRCNN total loss: 0.2462 L1 loss: 0.0000e+00 L2 loss: 1.39044 Learning rate: 0.02 Mask loss: 0.14845 RPN box loss: 0.02394 RPN score loss: 0.00484 RPN total loss: 0.02878 Total loss: 1.81387 timestamp: 1654925826.4516068 iteration: 13555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0845 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.15166 L1 loss: 0.0000e+00 L2 loss: 1.39021 Learning rate: 0.02 Mask loss: 0.2079 RPN box loss: 0.02902 RPN score loss: 0.00577 RPN total loss: 0.03479 Total loss: 1.78457 timestamp: 1654925829.6437893 iteration: 13560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13119 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.20276 L1 loss: 0.0000e+00 L2 loss: 1.38997 Learning rate: 0.02 Mask loss: 0.11254 RPN box loss: 0.01267 RPN score loss: 0.00669 RPN total loss: 0.01936 Total loss: 1.72463 timestamp: 1654925832.8993082 iteration: 13565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17279 FastRCNN class loss: 0.08985 FastRCNN total loss: 0.26263 L1 loss: 0.0000e+00 L2 loss: 1.38971 Learning rate: 0.02 Mask loss: 0.12836 RPN box loss: 0.05554 RPN score loss: 0.00637 RPN total loss: 0.06191 Total loss: 1.84262 timestamp: 1654925836.0887587 iteration: 13570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.19141 L1 loss: 0.0000e+00 L2 loss: 1.38947 Learning rate: 0.02 Mask loss: 0.12115 RPN box loss: 0.06751 RPN score loss: 0.00459 RPN total loss: 0.0721 Total loss: 1.77413 timestamp: 1654925839.4063513 iteration: 13575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15504 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.21978 L1 loss: 0.0000e+00 L2 loss: 1.38924 Learning rate: 0.02 Mask loss: 0.11574 RPN box loss: 0.01246 RPN score loss: 0.00839 RPN total loss: 0.02085 Total loss: 1.7456 timestamp: 1654925842.6057541 iteration: 13580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17558 FastRCNN class loss: 0.08882 FastRCNN total loss: 0.26439 L1 loss: 0.0000e+00 L2 loss: 1.38901 Learning rate: 0.02 Mask loss: 0.12698 RPN box loss: 0.04171 RPN score loss: 0.00466 RPN total loss: 0.04637 Total loss: 1.82675 timestamp: 1654925845.8427236 iteration: 13585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14257 FastRCNN class loss: 0.06761 FastRCNN total loss: 0.21018 L1 loss: 0.0000e+00 L2 loss: 1.38878 Learning rate: 0.02 Mask loss: 0.09665 RPN box loss: 0.03299 RPN score loss: 0.00405 RPN total loss: 0.03704 Total loss: 1.73265 timestamp: 1654925849.161195 iteration: 13590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12543 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.18826 L1 loss: 0.0000e+00 L2 loss: 1.38855 Learning rate: 0.02 Mask loss: 0.19776 RPN box loss: 0.00763 RPN score loss: 0.00385 RPN total loss: 0.01148 Total loss: 1.78605 timestamp: 1654925852.399876 iteration: 13595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20304 FastRCNN class loss: 0.20316 FastRCNN total loss: 0.4062 L1 loss: 0.0000e+00 L2 loss: 1.38829 Learning rate: 0.02 Mask loss: 0.28352 RPN box loss: 0.02898 RPN score loss: 0.01152 RPN total loss: 0.04049 Total loss: 2.1185 timestamp: 1654925855.7378445 iteration: 13600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14694 FastRCNN class loss: 0.08133 FastRCNN total loss: 0.22827 L1 loss: 0.0000e+00 L2 loss: 1.38804 Learning rate: 0.02 Mask loss: 0.17529 RPN box loss: 0.03167 RPN score loss: 0.02163 RPN total loss: 0.0533 Total loss: 1.84489 timestamp: 1654925858.909563 iteration: 13605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12731 FastRCNN class loss: 0.05478 FastRCNN total loss: 0.18209 L1 loss: 0.0000e+00 L2 loss: 1.38778 Learning rate: 0.02 Mask loss: 0.08434 RPN box loss: 0.00944 RPN score loss: 0.00396 RPN total loss: 0.0134 Total loss: 1.6676 timestamp: 1654925862.2576988 iteration: 13610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12944 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.19891 L1 loss: 0.0000e+00 L2 loss: 1.38753 Learning rate: 0.02 Mask loss: 0.16291 RPN box loss: 0.02169 RPN score loss: 0.00253 RPN total loss: 0.02421 Total loss: 1.77357 timestamp: 1654925865.4914143 iteration: 13615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15653 FastRCNN class loss: 0.1217 FastRCNN total loss: 0.27823 L1 loss: 0.0000e+00 L2 loss: 1.38729 Learning rate: 0.02 Mask loss: 0.171 RPN box loss: 0.04312 RPN score loss: 0.00642 RPN total loss: 0.04954 Total loss: 1.88605 timestamp: 1654925868.7904172 iteration: 13620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21103 FastRCNN class loss: 0.08803 FastRCNN total loss: 0.29906 L1 loss: 0.0000e+00 L2 loss: 1.38705 Learning rate: 0.02 Mask loss: 0.14148 RPN box loss: 0.06436 RPN score loss: 0.01069 RPN total loss: 0.07505 Total loss: 1.90264 timestamp: 1654925871.928172 iteration: 13625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14882 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.21618 L1 loss: 0.0000e+00 L2 loss: 1.38682 Learning rate: 0.02 Mask loss: 0.15498 RPN box loss: 0.02883 RPN score loss: 0.00563 RPN total loss: 0.03445 Total loss: 1.79243 timestamp: 1654925875.290698 iteration: 13630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14 FastRCNN class loss: 0.1025 FastRCNN total loss: 0.24251 L1 loss: 0.0000e+00 L2 loss: 1.38658 Learning rate: 0.02 Mask loss: 0.17643 RPN box loss: 0.01356 RPN score loss: 0.00803 RPN total loss: 0.02159 Total loss: 1.8271 timestamp: 1654925878.5219662 iteration: 13635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19978 FastRCNN class loss: 0.13773 FastRCNN total loss: 0.3375 L1 loss: 0.0000e+00 L2 loss: 1.38634 Learning rate: 0.02 Mask loss: 0.22605 RPN box loss: 0.11708 RPN score loss: 0.01794 RPN total loss: 0.13502 Total loss: 2.08492 timestamp: 1654925881.7555485 iteration: 13640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13028 FastRCNN class loss: 0.0656 FastRCNN total loss: 0.19587 L1 loss: 0.0000e+00 L2 loss: 1.3861 Learning rate: 0.02 Mask loss: 0.11788 RPN box loss: 0.03411 RPN score loss: 0.00561 RPN total loss: 0.03972 Total loss: 1.73958 timestamp: 1654925885.0577464 iteration: 13645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15002 FastRCNN class loss: 0.10627 FastRCNN total loss: 0.25629 L1 loss: 0.0000e+00 L2 loss: 1.38586 Learning rate: 0.02 Mask loss: 0.17879 RPN box loss: 0.05827 RPN score loss: 0.0152 RPN total loss: 0.07347 Total loss: 1.8944 timestamp: 1654925888.326096 iteration: 13650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10869 FastRCNN class loss: 0.06264 FastRCNN total loss: 0.17134 L1 loss: 0.0000e+00 L2 loss: 1.38561 Learning rate: 0.02 Mask loss: 0.15667 RPN box loss: 0.02913 RPN score loss: 0.0081 RPN total loss: 0.03723 Total loss: 1.75085 timestamp: 1654925891.639447 iteration: 13655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16221 FastRCNN class loss: 0.17965 FastRCNN total loss: 0.34186 L1 loss: 0.0000e+00 L2 loss: 1.38537 Learning rate: 0.02 Mask loss: 0.23994 RPN box loss: 0.03387 RPN score loss: 0.00803 RPN total loss: 0.04191 Total loss: 2.00907 timestamp: 1654925894.8795106 iteration: 13660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21444 FastRCNN class loss: 0.11783 FastRCNN total loss: 0.33227 L1 loss: 0.0000e+00 L2 loss: 1.38511 Learning rate: 0.02 Mask loss: 0.13371 RPN box loss: 0.07361 RPN score loss: 0.0233 RPN total loss: 0.09691 Total loss: 1.94799 timestamp: 1654925898.0700052 iteration: 13665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17562 FastRCNN class loss: 0.14989 FastRCNN total loss: 0.32551 L1 loss: 0.0000e+00 L2 loss: 1.38488 Learning rate: 0.02 Mask loss: 0.15213 RPN box loss: 0.03235 RPN score loss: 0.00557 RPN total loss: 0.03792 Total loss: 1.90043 timestamp: 1654925901.2768884 iteration: 13670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19079 FastRCNN class loss: 0.04447 FastRCNN total loss: 0.23526 L1 loss: 0.0000e+00 L2 loss: 1.38465 Learning rate: 0.02 Mask loss: 0.11378 RPN box loss: 0.02022 RPN score loss: 0.00271 RPN total loss: 0.02293 Total loss: 1.75662 timestamp: 1654925904.545006 iteration: 13675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17751 FastRCNN class loss: 0.13343 FastRCNN total loss: 0.31095 L1 loss: 0.0000e+00 L2 loss: 1.38441 Learning rate: 0.02 Mask loss: 0.1657 RPN box loss: 0.03315 RPN score loss: 0.01393 RPN total loss: 0.04709 Total loss: 1.90814 timestamp: 1654925907.7157638 iteration: 13680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11733 FastRCNN class loss: 0.05538 FastRCNN total loss: 0.17271 L1 loss: 0.0000e+00 L2 loss: 1.38419 Learning rate: 0.02 Mask loss: 0.17399 RPN box loss: 0.02611 RPN score loss: 0.0015 RPN total loss: 0.02761 Total loss: 1.75851 timestamp: 1654925910.9521265 iteration: 13685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07822 FastRCNN class loss: 0.06567 FastRCNN total loss: 0.14389 L1 loss: 0.0000e+00 L2 loss: 1.38396 Learning rate: 0.02 Mask loss: 0.15294 RPN box loss: 0.02595 RPN score loss: 0.02431 RPN total loss: 0.05026 Total loss: 1.73104 timestamp: 1654925914.2099967 iteration: 13690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19057 FastRCNN class loss: 0.11612 FastRCNN total loss: 0.30669 L1 loss: 0.0000e+00 L2 loss: 1.38369 Learning rate: 0.02 Mask loss: 0.18939 RPN box loss: 0.02363 RPN score loss: 0.00232 RPN total loss: 0.02595 Total loss: 1.90572 timestamp: 1654925917.4356592 iteration: 13695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09997 FastRCNN class loss: 0.06458 FastRCNN total loss: 0.16455 L1 loss: 0.0000e+00 L2 loss: 1.38346 Learning rate: 0.02 Mask loss: 0.12509 RPN box loss: 0.01593 RPN score loss: 0.00614 RPN total loss: 0.02208 Total loss: 1.69518 timestamp: 1654925920.8126273 iteration: 13700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16105 FastRCNN class loss: 0.12143 FastRCNN total loss: 0.28248 L1 loss: 0.0000e+00 L2 loss: 1.38323 Learning rate: 0.02 Mask loss: 0.24416 RPN box loss: 0.06869 RPN score loss: 0.01389 RPN total loss: 0.08258 Total loss: 1.99246 timestamp: 1654925924.0036495 iteration: 13705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16726 FastRCNN class loss: 0.06296 FastRCNN total loss: 0.23022 L1 loss: 0.0000e+00 L2 loss: 1.38299 Learning rate: 0.02 Mask loss: 0.10097 RPN box loss: 0.02305 RPN score loss: 0.00575 RPN total loss: 0.0288 Total loss: 1.74299 timestamp: 1654925927.3011386 iteration: 13710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18336 FastRCNN class loss: 0.09551 FastRCNN total loss: 0.27887 L1 loss: 0.0000e+00 L2 loss: 1.38274 Learning rate: 0.02 Mask loss: 0.28769 RPN box loss: 0.02368 RPN score loss: 0.0082 RPN total loss: 0.03188 Total loss: 1.98118 timestamp: 1654925930.5164495 iteration: 13715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12575 FastRCNN class loss: 0.06526 FastRCNN total loss: 0.19101 L1 loss: 0.0000e+00 L2 loss: 1.38251 Learning rate: 0.02 Mask loss: 0.14883 RPN box loss: 0.03469 RPN score loss: 0.00732 RPN total loss: 0.04201 Total loss: 1.76436 timestamp: 1654925933.7928755 iteration: 13720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.084 FastRCNN total loss: 0.23141 L1 loss: 0.0000e+00 L2 loss: 1.38228 Learning rate: 0.02 Mask loss: 0.12858 RPN box loss: 0.08538 RPN score loss: 0.00706 RPN total loss: 0.09244 Total loss: 1.83471 timestamp: 1654925936.9556978 iteration: 13725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14603 FastRCNN class loss: 0.0868 FastRCNN total loss: 0.23282 L1 loss: 0.0000e+00 L2 loss: 1.38204 Learning rate: 0.02 Mask loss: 0.23238 RPN box loss: 0.03307 RPN score loss: 0.01606 RPN total loss: 0.04913 Total loss: 1.89637 timestamp: 1654925940.2644677 iteration: 13730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18595 FastRCNN class loss: 0.11218 FastRCNN total loss: 0.29812 L1 loss: 0.0000e+00 L2 loss: 1.3818 Learning rate: 0.02 Mask loss: 0.26855 RPN box loss: 0.02751 RPN score loss: 0.00476 RPN total loss: 0.03227 Total loss: 1.98074 timestamp: 1654925943.4221542 iteration: 13735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12205 FastRCNN class loss: 0.09837 FastRCNN total loss: 0.22042 L1 loss: 0.0000e+00 L2 loss: 1.38157 Learning rate: 0.02 Mask loss: 0.18411 RPN box loss: 0.03254 RPN score loss: 0.00382 RPN total loss: 0.03636 Total loss: 1.82246 timestamp: 1654925946.7309384 iteration: 13740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18482 FastRCNN class loss: 0.08222 FastRCNN total loss: 0.26705 L1 loss: 0.0000e+00 L2 loss: 1.38132 Learning rate: 0.02 Mask loss: 0.1407 RPN box loss: 0.0088 RPN score loss: 0.003 RPN total loss: 0.0118 Total loss: 1.80087 timestamp: 1654925949.9460495 iteration: 13745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14069 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.21505 L1 loss: 0.0000e+00 L2 loss: 1.38108 Learning rate: 0.02 Mask loss: 0.20191 RPN box loss: 0.01815 RPN score loss: 0.00928 RPN total loss: 0.02743 Total loss: 1.82547 timestamp: 1654925953.205552 iteration: 13750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21355 FastRCNN class loss: 0.07443 FastRCNN total loss: 0.28798 L1 loss: 0.0000e+00 L2 loss: 1.38085 Learning rate: 0.02 Mask loss: 0.18091 RPN box loss: 0.02986 RPN score loss: 0.01199 RPN total loss: 0.04185 Total loss: 1.89159 timestamp: 1654925956.4913979 iteration: 13755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17028 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.23512 L1 loss: 0.0000e+00 L2 loss: 1.38059 Learning rate: 0.02 Mask loss: 0.16746 RPN box loss: 0.01656 RPN score loss: 0.00296 RPN total loss: 0.01951 Total loss: 1.80268 timestamp: 1654925959.769284 iteration: 13760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1148 FastRCNN class loss: 0.06958 FastRCNN total loss: 0.18438 L1 loss: 0.0000e+00 L2 loss: 1.38037 Learning rate: 0.02 Mask loss: 0.17226 RPN box loss: 0.05641 RPN score loss: 0.00683 RPN total loss: 0.06324 Total loss: 1.80024 timestamp: 1654925963.0445354 iteration: 13765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19803 FastRCNN class loss: 0.07991 FastRCNN total loss: 0.27794 L1 loss: 0.0000e+00 L2 loss: 1.38014 Learning rate: 0.02 Mask loss: 0.15294 RPN box loss: 0.02646 RPN score loss: 0.00612 RPN total loss: 0.03258 Total loss: 1.8436 timestamp: 1654925966.229154 iteration: 13770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14663 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.22487 L1 loss: 0.0000e+00 L2 loss: 1.37988 Learning rate: 0.02 Mask loss: 0.22982 RPN box loss: 0.03698 RPN score loss: 0.00492 RPN total loss: 0.0419 Total loss: 1.87648 timestamp: 1654925969.5003126 iteration: 13775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15056 FastRCNN class loss: 0.07069 FastRCNN total loss: 0.22125 L1 loss: 0.0000e+00 L2 loss: 1.37965 Learning rate: 0.02 Mask loss: 0.16953 RPN box loss: 0.02621 RPN score loss: 0.01017 RPN total loss: 0.03639 Total loss: 1.80681 timestamp: 1654925972.7329612 iteration: 13780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12148 FastRCNN class loss: 0.08137 FastRCNN total loss: 0.20285 L1 loss: 0.0000e+00 L2 loss: 1.37941 Learning rate: 0.02 Mask loss: 0.09975 RPN box loss: 0.02096 RPN score loss: 0.00387 RPN total loss: 0.02483 Total loss: 1.70684 timestamp: 1654925976.123809 iteration: 13785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21541 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.30773 L1 loss: 0.0000e+00 L2 loss: 1.37915 Learning rate: 0.02 Mask loss: 0.21755 RPN box loss: 0.03275 RPN score loss: 0.00769 RPN total loss: 0.04044 Total loss: 1.94487 timestamp: 1654925979.3505163 iteration: 13790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20826 FastRCNN class loss: 0.11482 FastRCNN total loss: 0.32308 L1 loss: 0.0000e+00 L2 loss: 1.37892 Learning rate: 0.02 Mask loss: 0.2366 RPN box loss: 0.04587 RPN score loss: 0.0142 RPN total loss: 0.06007 Total loss: 1.99867 timestamp: 1654925982.6128993 iteration: 13795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23758 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.32048 L1 loss: 0.0000e+00 L2 loss: 1.37866 Learning rate: 0.02 Mask loss: 0.12609 RPN box loss: 0.02887 RPN score loss: 0.01239 RPN total loss: 0.04126 Total loss: 1.8665 timestamp: 1654925985.8181155 iteration: 13800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2308 FastRCNN class loss: 0.10019 FastRCNN total loss: 0.33099 L1 loss: 0.0000e+00 L2 loss: 1.37845 Learning rate: 0.02 Mask loss: 0.17371 RPN box loss: 0.02968 RPN score loss: 0.00436 RPN total loss: 0.03404 Total loss: 1.91719 timestamp: 1654925989.029972 iteration: 13805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1864 FastRCNN class loss: 0.15943 FastRCNN total loss: 0.34584 L1 loss: 0.0000e+00 L2 loss: 1.37821 Learning rate: 0.02 Mask loss: 0.33494 RPN box loss: 0.07209 RPN score loss: 0.0104 RPN total loss: 0.0825 Total loss: 2.14149 timestamp: 1654925992.4072492 iteration: 13810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2 FastRCNN class loss: 0.16556 FastRCNN total loss: 0.36556 L1 loss: 0.0000e+00 L2 loss: 1.37796 Learning rate: 0.02 Mask loss: 0.16782 RPN box loss: 0.03915 RPN score loss: 0.01509 RPN total loss: 0.05424 Total loss: 1.96558 timestamp: 1654925995.6508126 iteration: 13815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14988 FastRCNN class loss: 0.09716 FastRCNN total loss: 0.24705 L1 loss: 0.0000e+00 L2 loss: 1.37776 Learning rate: 0.02 Mask loss: 0.1338 RPN box loss: 0.0403 RPN score loss: 0.00433 RPN total loss: 0.04464 Total loss: 1.80324 timestamp: 1654925998.9236193 iteration: 13820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15299 FastRCNN class loss: 0.09613 FastRCNN total loss: 0.24912 L1 loss: 0.0000e+00 L2 loss: 1.37751 Learning rate: 0.02 Mask loss: 0.18101 RPN box loss: 0.03957 RPN score loss: 0.00522 RPN total loss: 0.04478 Total loss: 1.85242 timestamp: 1654926002.1096208 iteration: 13825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18593 FastRCNN class loss: 0.12845 FastRCNN total loss: 0.31438 L1 loss: 0.0000e+00 L2 loss: 1.37724 Learning rate: 0.02 Mask loss: 0.16261 RPN box loss: 0.12904 RPN score loss: 0.02411 RPN total loss: 0.15315 Total loss: 2.00738 timestamp: 1654926005.479251 iteration: 13830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12228 FastRCNN class loss: 0.07948 FastRCNN total loss: 0.20176 L1 loss: 0.0000e+00 L2 loss: 1.37701 Learning rate: 0.02 Mask loss: 0.08699 RPN box loss: 0.03678 RPN score loss: 0.00641 RPN total loss: 0.04319 Total loss: 1.70895 timestamp: 1654926008.7148802 iteration: 13835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.171 FastRCNN class loss: 0.10737 FastRCNN total loss: 0.27837 L1 loss: 0.0000e+00 L2 loss: 1.37677 Learning rate: 0.02 Mask loss: 0.14305 RPN box loss: 0.01122 RPN score loss: 0.00472 RPN total loss: 0.01594 Total loss: 1.81413 timestamp: 1654926012.0026042 iteration: 13840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10329 FastRCNN class loss: 0.03973 FastRCNN total loss: 0.14303 L1 loss: 0.0000e+00 L2 loss: 1.37655 Learning rate: 0.02 Mask loss: 0.12381 RPN box loss: 0.01267 RPN score loss: 0.00633 RPN total loss: 0.01901 Total loss: 1.66239 timestamp: 1654926015.237668 iteration: 13845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16338 FastRCNN class loss: 0.10116 FastRCNN total loss: 0.26454 L1 loss: 0.0000e+00 L2 loss: 1.37633 Learning rate: 0.02 Mask loss: 0.19126 RPN box loss: 0.02502 RPN score loss: 0.00379 RPN total loss: 0.02881 Total loss: 1.86094 timestamp: 1654926018.5135207 iteration: 13850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19676 FastRCNN class loss: 0.0431 FastRCNN total loss: 0.23986 L1 loss: 0.0000e+00 L2 loss: 1.37609 Learning rate: 0.02 Mask loss: 0.08355 RPN box loss: 0.02947 RPN score loss: 0.00512 RPN total loss: 0.03459 Total loss: 1.73409 timestamp: 1654926021.8817441 iteration: 13855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16579 FastRCNN class loss: 0.08431 FastRCNN total loss: 0.2501 L1 loss: 0.0000e+00 L2 loss: 1.37583 Learning rate: 0.02 Mask loss: 0.19823 RPN box loss: 0.00575 RPN score loss: 0.00404 RPN total loss: 0.00979 Total loss: 1.83395 timestamp: 1654926025.0953994 iteration: 13860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10931 FastRCNN class loss: 0.08922 FastRCNN total loss: 0.19853 L1 loss: 0.0000e+00 L2 loss: 1.37558 Learning rate: 0.02 Mask loss: 0.20086 RPN box loss: 0.02249 RPN score loss: 0.00714 RPN total loss: 0.02963 Total loss: 1.8046 timestamp: 1654926028.415755 iteration: 13865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12213 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.19239 L1 loss: 0.0000e+00 L2 loss: 1.37536 Learning rate: 0.02 Mask loss: 0.14163 RPN box loss: 0.03647 RPN score loss: 0.00226 RPN total loss: 0.03873 Total loss: 1.7481 timestamp: 1654926031.6840694 iteration: 13870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1571 FastRCNN class loss: 0.08436 FastRCNN total loss: 0.24146 L1 loss: 0.0000e+00 L2 loss: 1.3751 Learning rate: 0.02 Mask loss: 0.17969 RPN box loss: 0.01796 RPN score loss: 0.00727 RPN total loss: 0.02523 Total loss: 1.82148 timestamp: 1654926034.9759996 iteration: 13875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17351 FastRCNN class loss: 0.10052 FastRCNN total loss: 0.27403 L1 loss: 0.0000e+00 L2 loss: 1.37484 Learning rate: 0.02 Mask loss: 0.2109 RPN box loss: 0.05127 RPN score loss: 0.01663 RPN total loss: 0.0679 Total loss: 1.92767 timestamp: 1654926038.1863554 iteration: 13880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15408 FastRCNN class loss: 0.07845 FastRCNN total loss: 0.23253 L1 loss: 0.0000e+00 L2 loss: 1.37462 Learning rate: 0.02 Mask loss: 0.24033 RPN box loss: 0.04405 RPN score loss: 0.01282 RPN total loss: 0.05688 Total loss: 1.90437 timestamp: 1654926041.458659 iteration: 13885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10692 FastRCNN class loss: 0.08107 FastRCNN total loss: 0.18799 L1 loss: 0.0000e+00 L2 loss: 1.37441 Learning rate: 0.02 Mask loss: 0.21896 RPN box loss: 0.0256 RPN score loss: 0.00443 RPN total loss: 0.03003 Total loss: 1.8114 timestamp: 1654926044.594435 iteration: 13890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14383 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.2193 L1 loss: 0.0000e+00 L2 loss: 1.37416 Learning rate: 0.02 Mask loss: 0.23725 RPN box loss: 0.02857 RPN score loss: 0.01291 RPN total loss: 0.04147 Total loss: 1.87219 timestamp: 1654926047.7514818 iteration: 13895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15857 FastRCNN class loss: 0.09353 FastRCNN total loss: 0.2521 L1 loss: 0.0000e+00 L2 loss: 1.37391 Learning rate: 0.02 Mask loss: 0.18238 RPN box loss: 0.04533 RPN score loss: 0.0068 RPN total loss: 0.05213 Total loss: 1.86052 timestamp: 1654926050.9367018 iteration: 13900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13702 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.23407 L1 loss: 0.0000e+00 L2 loss: 1.37368 Learning rate: 0.02 Mask loss: 0.16297 RPN box loss: 0.05934 RPN score loss: 0.01421 RPN total loss: 0.07354 Total loss: 1.84426 timestamp: 1654926054.1748219 iteration: 13905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19014 FastRCNN class loss: 0.11766 FastRCNN total loss: 0.3078 L1 loss: 0.0000e+00 L2 loss: 1.37344 Learning rate: 0.02 Mask loss: 0.12575 RPN box loss: 0.01019 RPN score loss: 0.00618 RPN total loss: 0.01637 Total loss: 1.82337 timestamp: 1654926057.2558177 iteration: 13910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14491 FastRCNN class loss: 0.10897 FastRCNN total loss: 0.25387 L1 loss: 0.0000e+00 L2 loss: 1.3732 Learning rate: 0.02 Mask loss: 0.18077 RPN box loss: 0.05961 RPN score loss: 0.00931 RPN total loss: 0.06892 Total loss: 1.87677 timestamp: 1654926060.4709992 iteration: 13915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16767 FastRCNN class loss: 0.09178 FastRCNN total loss: 0.25945 L1 loss: 0.0000e+00 L2 loss: 1.37297 Learning rate: 0.02 Mask loss: 0.1239 RPN box loss: 0.02408 RPN score loss: 0.00936 RPN total loss: 0.03344 Total loss: 1.78976 timestamp: 1654926063.824902 iteration: 13920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21546 FastRCNN class loss: 0.07685 FastRCNN total loss: 0.29231 L1 loss: 0.0000e+00 L2 loss: 1.37271 Learning rate: 0.02 Mask loss: 0.20814 RPN box loss: 0.02611 RPN score loss: 0.00538 RPN total loss: 0.0315 Total loss: 1.90466 timestamp: 1654926067.0455878 iteration: 13925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13895 FastRCNN class loss: 0.06449 FastRCNN total loss: 0.20343 L1 loss: 0.0000e+00 L2 loss: 1.37246 Learning rate: 0.02 Mask loss: 0.11819 RPN box loss: 0.02263 RPN score loss: 0.00663 RPN total loss: 0.02926 Total loss: 1.72335 timestamp: 1654926070.3388164 iteration: 13930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12924 FastRCNN class loss: 0.07081 FastRCNN total loss: 0.20005 L1 loss: 0.0000e+00 L2 loss: 1.37223 Learning rate: 0.02 Mask loss: 0.1046 RPN box loss: 0.03108 RPN score loss: 0.00454 RPN total loss: 0.03562 Total loss: 1.7125 timestamp: 1654926073.606746 iteration: 13935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19811 FastRCNN class loss: 0.09671 FastRCNN total loss: 0.29482 L1 loss: 0.0000e+00 L2 loss: 1.37201 Learning rate: 0.02 Mask loss: 0.21737 RPN box loss: 0.01309 RPN score loss: 0.00841 RPN total loss: 0.0215 Total loss: 1.9057 timestamp: 1654926076.854882 iteration: 13940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1369 FastRCNN class loss: 0.07532 FastRCNN total loss: 0.21221 L1 loss: 0.0000e+00 L2 loss: 1.37175 Learning rate: 0.02 Mask loss: 0.15735 RPN box loss: 0.04927 RPN score loss: 0.00971 RPN total loss: 0.05898 Total loss: 1.8003 timestamp: 1654926080.0239682 iteration: 13945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15337 FastRCNN class loss: 0.11102 FastRCNN total loss: 0.26439 L1 loss: 0.0000e+00 L2 loss: 1.37151 Learning rate: 0.02 Mask loss: 0.19089 RPN box loss: 0.0341 RPN score loss: 0.00619 RPN total loss: 0.04029 Total loss: 1.86708 timestamp: 1654926083.358186 iteration: 13950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17266 FastRCNN class loss: 0.16825 FastRCNN total loss: 0.34091 L1 loss: 0.0000e+00 L2 loss: 1.37128 Learning rate: 0.02 Mask loss: 0.22065 RPN box loss: 0.02584 RPN score loss: 0.01184 RPN total loss: 0.03768 Total loss: 1.97052 timestamp: 1654926086.509027 iteration: 13955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16735 FastRCNN class loss: 0.10436 FastRCNN total loss: 0.27172 L1 loss: 0.0000e+00 L2 loss: 1.37102 Learning rate: 0.02 Mask loss: 0.20714 RPN box loss: 0.00877 RPN score loss: 0.00849 RPN total loss: 0.01726 Total loss: 1.86713 timestamp: 1654926089.817747 iteration: 13960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18948 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.27017 L1 loss: 0.0000e+00 L2 loss: 1.37078 Learning rate: 0.02 Mask loss: 0.14412 RPN box loss: 0.04687 RPN score loss: 0.00748 RPN total loss: 0.05435 Total loss: 1.83942 timestamp: 1654926093.0234807 iteration: 13965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25394 FastRCNN class loss: 0.111 FastRCNN total loss: 0.36494 L1 loss: 0.0000e+00 L2 loss: 1.37056 Learning rate: 0.02 Mask loss: 0.21682 RPN box loss: 0.0432 RPN score loss: 0.02056 RPN total loss: 0.06376 Total loss: 2.01609 timestamp: 1654926096.233931 iteration: 13970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12491 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.20007 L1 loss: 0.0000e+00 L2 loss: 1.37031 Learning rate: 0.02 Mask loss: 0.27238 RPN box loss: 0.02824 RPN score loss: 0.00887 RPN total loss: 0.03711 Total loss: 1.87988 timestamp: 1654926099.4804852 iteration: 13975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17219 FastRCNN class loss: 0.12946 FastRCNN total loss: 0.30165 L1 loss: 0.0000e+00 L2 loss: 1.37007 Learning rate: 0.02 Mask loss: 0.20741 RPN box loss: 0.04096 RPN score loss: 0.01191 RPN total loss: 0.05287 Total loss: 1.93201 timestamp: 1654926102.662809 iteration: 13980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14816 FastRCNN class loss: 0.09154 FastRCNN total loss: 0.2397 L1 loss: 0.0000e+00 L2 loss: 1.36983 Learning rate: 0.02 Mask loss: 0.23053 RPN box loss: 0.04127 RPN score loss: 0.00868 RPN total loss: 0.04995 Total loss: 1.89001 timestamp: 1654926106.028799 iteration: 13985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18693 FastRCNN class loss: 0.06492 FastRCNN total loss: 0.25185 L1 loss: 0.0000e+00 L2 loss: 1.36962 Learning rate: 0.02 Mask loss: 0.11163 RPN box loss: 0.01314 RPN score loss: 0.00259 RPN total loss: 0.01573 Total loss: 1.74883 timestamp: 1654926109.2195916 iteration: 13990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2434 FastRCNN class loss: 0.11899 FastRCNN total loss: 0.36239 L1 loss: 0.0000e+00 L2 loss: 1.36935 Learning rate: 0.02 Mask loss: 0.23956 RPN box loss: 0.01388 RPN score loss: 0.00558 RPN total loss: 0.01946 Total loss: 1.99076 timestamp: 1654926112.3419127 iteration: 13995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10637 FastRCNN class loss: 0.0787 FastRCNN total loss: 0.18507 L1 loss: 0.0000e+00 L2 loss: 1.36913 Learning rate: 0.02 Mask loss: 0.12522 RPN box loss: 0.05982 RPN score loss: 0.00961 RPN total loss: 0.06943 Total loss: 1.74885 timestamp: 1654926115.5240068 iteration: 14000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22488 FastRCNN class loss: 0.09702 FastRCNN total loss: 0.3219 L1 loss: 0.0000e+00 L2 loss: 1.36891 Learning rate: 0.02 Mask loss: 0.14846 RPN box loss: 0.02894 RPN score loss: 0.00665 RPN total loss: 0.03559 Total loss: 1.87486 timestamp: 1654926118.84603 iteration: 14005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16357 FastRCNN class loss: 0.13701 FastRCNN total loss: 0.30059 L1 loss: 0.0000e+00 L2 loss: 1.36869 Learning rate: 0.02 Mask loss: 0.16293 RPN box loss: 0.01958 RPN score loss: 0.00544 RPN total loss: 0.02502 Total loss: 1.85722 timestamp: 1654926122.1336412 iteration: 14010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15989 FastRCNN class loss: 0.07542 FastRCNN total loss: 0.23532 L1 loss: 0.0000e+00 L2 loss: 1.36844 Learning rate: 0.02 Mask loss: 0.12475 RPN box loss: 0.03815 RPN score loss: 0.01325 RPN total loss: 0.0514 Total loss: 1.77991 timestamp: 1654926125.4911764 iteration: 14015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13452 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.20871 L1 loss: 0.0000e+00 L2 loss: 1.36818 Learning rate: 0.02 Mask loss: 0.14312 RPN box loss: 0.03657 RPN score loss: 0.00842 RPN total loss: 0.04499 Total loss: 1.76499 timestamp: 1654926128.6308088 iteration: 14020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18208 FastRCNN class loss: 0.10539 FastRCNN total loss: 0.28747 L1 loss: 0.0000e+00 L2 loss: 1.36793 Learning rate: 0.02 Mask loss: 0.19117 RPN box loss: 0.05983 RPN score loss: 0.00983 RPN total loss: 0.06966 Total loss: 1.91623 timestamp: 1654926131.9308453 iteration: 14025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1723 FastRCNN class loss: 0.08076 FastRCNN total loss: 0.25306 L1 loss: 0.0000e+00 L2 loss: 1.36768 Learning rate: 0.02 Mask loss: 0.21613 RPN box loss: 0.02377 RPN score loss: 0.00725 RPN total loss: 0.03102 Total loss: 1.8679 timestamp: 1654926135.2339582 iteration: 14030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20742 FastRCNN class loss: 0.09515 FastRCNN total loss: 0.30257 L1 loss: 0.0000e+00 L2 loss: 1.36743 Learning rate: 0.02 Mask loss: 0.191 RPN box loss: 0.02877 RPN score loss: 0.0078 RPN total loss: 0.03657 Total loss: 1.89757 timestamp: 1654926138.4335446 iteration: 14035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16369 FastRCNN class loss: 0.08476 FastRCNN total loss: 0.24845 L1 loss: 0.0000e+00 L2 loss: 1.36721 Learning rate: 0.02 Mask loss: 0.17936 RPN box loss: 0.03877 RPN score loss: 0.01111 RPN total loss: 0.04988 Total loss: 1.8449 timestamp: 1654926141.69485 iteration: 14040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18653 FastRCNN class loss: 0.15141 FastRCNN total loss: 0.33795 L1 loss: 0.0000e+00 L2 loss: 1.36696 Learning rate: 0.02 Mask loss: 0.24157 RPN box loss: 0.04291 RPN score loss: 0.01101 RPN total loss: 0.05392 Total loss: 2.0004 timestamp: 1654926144.8588765 iteration: 14045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11726 FastRCNN class loss: 0.05432 FastRCNN total loss: 0.17158 L1 loss: 0.0000e+00 L2 loss: 1.3667 Learning rate: 0.02 Mask loss: 0.26629 RPN box loss: 0.02627 RPN score loss: 0.01023 RPN total loss: 0.0365 Total loss: 1.84107 timestamp: 1654926148.141385 iteration: 14050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09466 FastRCNN class loss: 0.05478 FastRCNN total loss: 0.14944 L1 loss: 0.0000e+00 L2 loss: 1.36645 Learning rate: 0.02 Mask loss: 0.10459 RPN box loss: 0.02816 RPN score loss: 0.00301 RPN total loss: 0.03117 Total loss: 1.65165 timestamp: 1654926151.2987711 iteration: 14055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10433 FastRCNN class loss: 0.06517 FastRCNN total loss: 0.16951 L1 loss: 0.0000e+00 L2 loss: 1.36621 Learning rate: 0.02 Mask loss: 0.13972 RPN box loss: 0.05241 RPN score loss: 0.00957 RPN total loss: 0.06198 Total loss: 1.73742 timestamp: 1654926154.6012776 iteration: 14060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22094 FastRCNN class loss: 0.11173 FastRCNN total loss: 0.33267 L1 loss: 0.0000e+00 L2 loss: 1.36599 Learning rate: 0.02 Mask loss: 0.19034 RPN box loss: 0.04739 RPN score loss: 0.00524 RPN total loss: 0.05263 Total loss: 1.94163 timestamp: 1654926157.7982483 iteration: 14065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16303 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.25039 L1 loss: 0.0000e+00 L2 loss: 1.36574 Learning rate: 0.02 Mask loss: 0.15682 RPN box loss: 0.01602 RPN score loss: 0.00497 RPN total loss: 0.021 Total loss: 1.79395 timestamp: 1654926161.0320613 iteration: 14070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13215 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.20828 L1 loss: 0.0000e+00 L2 loss: 1.3655 Learning rate: 0.02 Mask loss: 0.15323 RPN box loss: 0.01126 RPN score loss: 0.00413 RPN total loss: 0.01539 Total loss: 1.7424 timestamp: 1654926164.2325044 iteration: 14075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11258 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.18728 L1 loss: 0.0000e+00 L2 loss: 1.36528 Learning rate: 0.02 Mask loss: 0.15886 RPN box loss: 0.03049 RPN score loss: 0.00873 RPN total loss: 0.03921 Total loss: 1.75064 timestamp: 1654926167.5402892 iteration: 14080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15767 FastRCNN class loss: 0.10631 FastRCNN total loss: 0.26398 L1 loss: 0.0000e+00 L2 loss: 1.36506 Learning rate: 0.02 Mask loss: 0.23675 RPN box loss: 0.05087 RPN score loss: 0.00874 RPN total loss: 0.05961 Total loss: 1.9254 timestamp: 1654926170.8173668 iteration: 14085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22126 FastRCNN class loss: 0.10988 FastRCNN total loss: 0.33114 L1 loss: 0.0000e+00 L2 loss: 1.36482 Learning rate: 0.02 Mask loss: 0.25108 RPN box loss: 0.06736 RPN score loss: 0.01264 RPN total loss: 0.08 Total loss: 2.02704 timestamp: 1654926174.0372217 iteration: 14090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17677 FastRCNN class loss: 0.12387 FastRCNN total loss: 0.30064 L1 loss: 0.0000e+00 L2 loss: 1.3646 Learning rate: 0.02 Mask loss: 0.17199 RPN box loss: 0.05367 RPN score loss: 0.01171 RPN total loss: 0.06538 Total loss: 1.90261 timestamp: 1654926177.2893112 iteration: 14095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13912 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.2111 L1 loss: 0.0000e+00 L2 loss: 1.36435 Learning rate: 0.02 Mask loss: 0.11519 RPN box loss: 0.01027 RPN score loss: 0.00466 RPN total loss: 0.01493 Total loss: 1.70557 timestamp: 1654926180.5055928 iteration: 14100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24081 FastRCNN class loss: 0.10642 FastRCNN total loss: 0.34724 L1 loss: 0.0000e+00 L2 loss: 1.36411 Learning rate: 0.02 Mask loss: 0.16177 RPN box loss: 0.05561 RPN score loss: 0.00822 RPN total loss: 0.06383 Total loss: 1.93696 timestamp: 1654926183.8044124 iteration: 14105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20311 FastRCNN class loss: 0.10544 FastRCNN total loss: 0.30855 L1 loss: 0.0000e+00 L2 loss: 1.36391 Learning rate: 0.02 Mask loss: 0.18656 RPN box loss: 0.02202 RPN score loss: 0.00427 RPN total loss: 0.02629 Total loss: 1.88531 timestamp: 1654926187.0211198 iteration: 14110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20248 FastRCNN class loss: 0.11612 FastRCNN total loss: 0.3186 L1 loss: 0.0000e+00 L2 loss: 1.36369 Learning rate: 0.02 Mask loss: 0.15123 RPN box loss: 0.0295 RPN score loss: 0.00982 RPN total loss: 0.03932 Total loss: 1.87284 timestamp: 1654926190.4406931 iteration: 14115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13942 FastRCNN class loss: 0.10998 FastRCNN total loss: 0.2494 L1 loss: 0.0000e+00 L2 loss: 1.36346 Learning rate: 0.02 Mask loss: 0.1412 RPN box loss: 0.04166 RPN score loss: 0.01227 RPN total loss: 0.05394 Total loss: 1.80799 timestamp: 1654926193.6723127 iteration: 14120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18125 FastRCNN class loss: 0.09245 FastRCNN total loss: 0.27369 L1 loss: 0.0000e+00 L2 loss: 1.36324 Learning rate: 0.02 Mask loss: 0.18151 RPN box loss: 0.0489 RPN score loss: 0.01128 RPN total loss: 0.06018 Total loss: 1.87862 timestamp: 1654926196.9137895 iteration: 14125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27688 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.356 L1 loss: 0.0000e+00 L2 loss: 1.36298 Learning rate: 0.02 Mask loss: 0.18113 RPN box loss: 0.04074 RPN score loss: 0.01454 RPN total loss: 0.05529 Total loss: 1.9554 timestamp: 1654926200.2325945 iteration: 14130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15378 FastRCNN class loss: 0.16918 FastRCNN total loss: 0.32296 L1 loss: 0.0000e+00 L2 loss: 1.36272 Learning rate: 0.02 Mask loss: 0.25804 RPN box loss: 0.05893 RPN score loss: 0.09362 RPN total loss: 0.15255 Total loss: 2.09627 timestamp: 1654926203.4485064 iteration: 14135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.15101 L1 loss: 0.0000e+00 L2 loss: 1.3625 Learning rate: 0.02 Mask loss: 0.12515 RPN box loss: 0.06296 RPN score loss: 0.01083 RPN total loss: 0.07378 Total loss: 1.71244 timestamp: 1654926206.6863832 iteration: 14140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21526 FastRCNN class loss: 0.09603 FastRCNN total loss: 0.3113 L1 loss: 0.0000e+00 L2 loss: 1.36227 Learning rate: 0.02 Mask loss: 0.14047 RPN box loss: 0.0529 RPN score loss: 0.00734 RPN total loss: 0.06024 Total loss: 1.87428 timestamp: 1654926209.9283946 iteration: 14145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13696 FastRCNN class loss: 0.07586 FastRCNN total loss: 0.21281 L1 loss: 0.0000e+00 L2 loss: 1.36203 Learning rate: 0.02 Mask loss: 0.16472 RPN box loss: 0.09276 RPN score loss: 0.01088 RPN total loss: 0.10364 Total loss: 1.84319 timestamp: 1654926213.2192297 iteration: 14150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14134 FastRCNN class loss: 0.07128 FastRCNN total loss: 0.21262 L1 loss: 0.0000e+00 L2 loss: 1.36179 Learning rate: 0.02 Mask loss: 0.19148 RPN box loss: 0.04602 RPN score loss: 0.01058 RPN total loss: 0.0566 Total loss: 1.82249 timestamp: 1654926216.478836 iteration: 14155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15052 FastRCNN class loss: 0.09437 FastRCNN total loss: 0.2449 L1 loss: 0.0000e+00 L2 loss: 1.36155 Learning rate: 0.02 Mask loss: 0.19107 RPN box loss: 0.07603 RPN score loss: 0.00585 RPN total loss: 0.08188 Total loss: 1.87939 timestamp: 1654926219.7942038 iteration: 14160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10205 FastRCNN class loss: 0.05792 FastRCNN total loss: 0.15997 L1 loss: 0.0000e+00 L2 loss: 1.3613 Learning rate: 0.02 Mask loss: 0.10227 RPN box loss: 0.02049 RPN score loss: 0.00369 RPN total loss: 0.02418 Total loss: 1.64772 timestamp: 1654926223.0343919 iteration: 14165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10549 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.15844 L1 loss: 0.0000e+00 L2 loss: 1.36106 Learning rate: 0.02 Mask loss: 0.23753 RPN box loss: 0.05913 RPN score loss: 0.01006 RPN total loss: 0.06919 Total loss: 1.82622 timestamp: 1654926226.352001 iteration: 14170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14885 FastRCNN class loss: 0.11908 FastRCNN total loss: 0.26793 L1 loss: 0.0000e+00 L2 loss: 1.36082 Learning rate: 0.02 Mask loss: 0.20382 RPN box loss: 0.02297 RPN score loss: 0.01 RPN total loss: 0.03298 Total loss: 1.86554 timestamp: 1654926229.6325996 iteration: 14175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09566 FastRCNN class loss: 0.06633 FastRCNN total loss: 0.162 L1 loss: 0.0000e+00 L2 loss: 1.36057 Learning rate: 0.02 Mask loss: 0.11668 RPN box loss: 0.04016 RPN score loss: 0.00569 RPN total loss: 0.04584 Total loss: 1.68509 timestamp: 1654926232.9137394 iteration: 14180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19869 FastRCNN class loss: 0.07872 FastRCNN total loss: 0.27741 L1 loss: 0.0000e+00 L2 loss: 1.36033 Learning rate: 0.02 Mask loss: 0.1875 RPN box loss: 0.08319 RPN score loss: 0.00719 RPN total loss: 0.09038 Total loss: 1.91562 timestamp: 1654926236.280991 iteration: 14185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08524 FastRCNN class loss: 0.04061 FastRCNN total loss: 0.12584 L1 loss: 0.0000e+00 L2 loss: 1.36009 Learning rate: 0.02 Mask loss: 0.15543 RPN box loss: 0.00462 RPN score loss: 0.00123 RPN total loss: 0.00584 Total loss: 1.6472 timestamp: 1654926239.4789748 iteration: 14190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1661 FastRCNN class loss: 0.12412 FastRCNN total loss: 0.29021 L1 loss: 0.0000e+00 L2 loss: 1.35987 Learning rate: 0.02 Mask loss: 0.20352 RPN box loss: 0.03802 RPN score loss: 0.01083 RPN total loss: 0.04885 Total loss: 1.90245 timestamp: 1654926242.790986 iteration: 14195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21133 FastRCNN class loss: 0.16818 FastRCNN total loss: 0.3795 L1 loss: 0.0000e+00 L2 loss: 1.35966 Learning rate: 0.02 Mask loss: 0.24596 RPN box loss: 0.04911 RPN score loss: 0.0117 RPN total loss: 0.06081 Total loss: 2.04594 timestamp: 1654926245.9194934 iteration: 14200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17073 FastRCNN class loss: 0.09857 FastRCNN total loss: 0.2693 L1 loss: 0.0000e+00 L2 loss: 1.35942 Learning rate: 0.02 Mask loss: 0.13947 RPN box loss: 0.03505 RPN score loss: 0.03013 RPN total loss: 0.06518 Total loss: 1.83337 timestamp: 1654926249.1875265 iteration: 14205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15651 FastRCNN class loss: 0.09726 FastRCNN total loss: 0.25377 L1 loss: 0.0000e+00 L2 loss: 1.35916 Learning rate: 0.02 Mask loss: 0.19986 RPN box loss: 0.01292 RPN score loss: 0.00442 RPN total loss: 0.01734 Total loss: 1.83013 timestamp: 1654926252.3765085 iteration: 14210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10655 FastRCNN class loss: 0.05851 FastRCNN total loss: 0.16506 L1 loss: 0.0000e+00 L2 loss: 1.35892 Learning rate: 0.02 Mask loss: 0.11791 RPN box loss: 0.02451 RPN score loss: 0.00669 RPN total loss: 0.0312 Total loss: 1.67309 timestamp: 1654926255.6134262 iteration: 14215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09168 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.14943 L1 loss: 0.0000e+00 L2 loss: 1.35869 Learning rate: 0.02 Mask loss: 0.20006 RPN box loss: 0.00935 RPN score loss: 0.00225 RPN total loss: 0.0116 Total loss: 1.71978 timestamp: 1654926258.788401 iteration: 14220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12564 FastRCNN class loss: 0.06707 FastRCNN total loss: 0.19271 L1 loss: 0.0000e+00 L2 loss: 1.35845 Learning rate: 0.02 Mask loss: 0.14632 RPN box loss: 0.05945 RPN score loss: 0.00242 RPN total loss: 0.06188 Total loss: 1.75937 timestamp: 1654926262.0095797 iteration: 14225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17578 FastRCNN class loss: 0.0708 FastRCNN total loss: 0.24658 L1 loss: 0.0000e+00 L2 loss: 1.35821 Learning rate: 0.02 Mask loss: 0.15489 RPN box loss: 0.0657 RPN score loss: 0.01042 RPN total loss: 0.07612 Total loss: 1.83581 timestamp: 1654926265.2560565 iteration: 14230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16707 FastRCNN class loss: 0.09214 FastRCNN total loss: 0.25921 L1 loss: 0.0000e+00 L2 loss: 1.35797 Learning rate: 0.02 Mask loss: 0.15175 RPN box loss: 0.01682 RPN score loss: 0.00384 RPN total loss: 0.02066 Total loss: 1.78959 timestamp: 1654926268.4778056 iteration: 14235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22408 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.31674 L1 loss: 0.0000e+00 L2 loss: 1.35774 Learning rate: 0.02 Mask loss: 0.17457 RPN box loss: 0.0481 RPN score loss: 0.00507 RPN total loss: 0.05318 Total loss: 1.90223 timestamp: 1654926271.669566 iteration: 14240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16309 FastRCNN class loss: 0.1004 FastRCNN total loss: 0.26349 L1 loss: 0.0000e+00 L2 loss: 1.35751 Learning rate: 0.02 Mask loss: 0.20057 RPN box loss: 0.01612 RPN score loss: 0.00298 RPN total loss: 0.0191 Total loss: 1.84067 timestamp: 1654926274.941345 iteration: 14245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12843 FastRCNN class loss: 0.05064 FastRCNN total loss: 0.17906 L1 loss: 0.0000e+00 L2 loss: 1.35727 Learning rate: 0.02 Mask loss: 0.1517 RPN box loss: 0.0225 RPN score loss: 0.00768 RPN total loss: 0.03018 Total loss: 1.71821 timestamp: 1654926278.1997008 iteration: 14250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0824 FastRCNN class loss: 0.09477 FastRCNN total loss: 0.17717 L1 loss: 0.0000e+00 L2 loss: 1.35704 Learning rate: 0.02 Mask loss: 0.13479 RPN box loss: 0.01324 RPN score loss: 0.00658 RPN total loss: 0.01982 Total loss: 1.68882 timestamp: 1654926281.4248257 iteration: 14255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.165 FastRCNN class loss: 0.05759 FastRCNN total loss: 0.22259 L1 loss: 0.0000e+00 L2 loss: 1.35681 Learning rate: 0.02 Mask loss: 0.10486 RPN box loss: 0.05488 RPN score loss: 0.00384 RPN total loss: 0.05872 Total loss: 1.74297 timestamp: 1654926284.7857792 iteration: 14260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14215 FastRCNN class loss: 0.12148 FastRCNN total loss: 0.26363 L1 loss: 0.0000e+00 L2 loss: 1.35656 Learning rate: 0.02 Mask loss: 0.23717 RPN box loss: 0.0226 RPN score loss: 0.00548 RPN total loss: 0.02808 Total loss: 1.88544 timestamp: 1654926288.0071108 iteration: 14265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11817 FastRCNN class loss: 0.11987 FastRCNN total loss: 0.23804 L1 loss: 0.0000e+00 L2 loss: 1.35633 Learning rate: 0.02 Mask loss: 0.13445 RPN box loss: 0.04303 RPN score loss: 0.02352 RPN total loss: 0.06654 Total loss: 1.79536 timestamp: 1654926291.3901136 iteration: 14270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19224 FastRCNN class loss: 0.11156 FastRCNN total loss: 0.3038 L1 loss: 0.0000e+00 L2 loss: 1.35611 Learning rate: 0.02 Mask loss: 0.18087 RPN box loss: 0.01953 RPN score loss: 0.01256 RPN total loss: 0.03209 Total loss: 1.87287 timestamp: 1654926294.583325 iteration: 14275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14152 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.23272 L1 loss: 0.0000e+00 L2 loss: 1.35588 Learning rate: 0.02 Mask loss: 0.1504 RPN box loss: 0.02786 RPN score loss: 0.00398 RPN total loss: 0.03184 Total loss: 1.77084 timestamp: 1654926297.8709934 iteration: 14280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1172 FastRCNN class loss: 0.04804 FastRCNN total loss: 0.16524 L1 loss: 0.0000e+00 L2 loss: 1.35562 Learning rate: 0.02 Mask loss: 0.15229 RPN box loss: 0.03976 RPN score loss: 0.00902 RPN total loss: 0.04878 Total loss: 1.72193 timestamp: 1654926301.1293285 iteration: 14285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15312 FastRCNN class loss: 0.09872 FastRCNN total loss: 0.25184 L1 loss: 0.0000e+00 L2 loss: 1.35539 Learning rate: 0.02 Mask loss: 0.20594 RPN box loss: 0.04197 RPN score loss: 0.00385 RPN total loss: 0.04582 Total loss: 1.859 timestamp: 1654926304.5908062 iteration: 14290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13769 FastRCNN class loss: 0.07997 FastRCNN total loss: 0.21766 L1 loss: 0.0000e+00 L2 loss: 1.35515 Learning rate: 0.02 Mask loss: 0.17306 RPN box loss: 0.03272 RPN score loss: 0.00738 RPN total loss: 0.04009 Total loss: 1.78596 timestamp: 1654926307.8706276 iteration: 14295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19683 FastRCNN class loss: 0.08235 FastRCNN total loss: 0.27918 L1 loss: 0.0000e+00 L2 loss: 1.3549 Learning rate: 0.02 Mask loss: 0.1832 RPN box loss: 0.06842 RPN score loss: 0.00164 RPN total loss: 0.07006 Total loss: 1.88734 timestamp: 1654926310.9555216 iteration: 14300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11358 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.17896 L1 loss: 0.0000e+00 L2 loss: 1.35467 Learning rate: 0.02 Mask loss: 0.14897 RPN box loss: 0.04948 RPN score loss: 0.00889 RPN total loss: 0.05837 Total loss: 1.74098 timestamp: 1654926314.1789777 iteration: 14305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10893 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.20236 L1 loss: 0.0000e+00 L2 loss: 1.35442 Learning rate: 0.02 Mask loss: 0.12581 RPN box loss: 0.02371 RPN score loss: 0.00619 RPN total loss: 0.0299 Total loss: 1.71249 timestamp: 1654926317.4019794 iteration: 14310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14126 FastRCNN class loss: 0.09564 FastRCNN total loss: 0.23689 L1 loss: 0.0000e+00 L2 loss: 1.35417 Learning rate: 0.02 Mask loss: 0.14399 RPN box loss: 0.11655 RPN score loss: 0.00445 RPN total loss: 0.121 Total loss: 1.85605 timestamp: 1654926320.5902467 iteration: 14315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1677 FastRCNN class loss: 0.10734 FastRCNN total loss: 0.27504 L1 loss: 0.0000e+00 L2 loss: 1.35393 Learning rate: 0.02 Mask loss: 0.18617 RPN box loss: 0.10309 RPN score loss: 0.0066 RPN total loss: 0.10969 Total loss: 1.92483 timestamp: 1654926323.6892743 iteration: 14320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.187 FastRCNN class loss: 0.11217 FastRCNN total loss: 0.29917 L1 loss: 0.0000e+00 L2 loss: 1.3537 Learning rate: 0.02 Mask loss: 0.15446 RPN box loss: 0.07651 RPN score loss: 0.02337 RPN total loss: 0.09988 Total loss: 1.90721 timestamp: 1654926326.9753308 iteration: 14325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18551 FastRCNN class loss: 0.06773 FastRCNN total loss: 0.25324 L1 loss: 0.0000e+00 L2 loss: 1.35348 Learning rate: 0.02 Mask loss: 0.12071 RPN box loss: 0.06976 RPN score loss: 0.03473 RPN total loss: 0.10449 Total loss: 1.83193 timestamp: 1654926330.221472 iteration: 14330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15787 FastRCNN class loss: 0.09713 FastRCNN total loss: 0.255 L1 loss: 0.0000e+00 L2 loss: 1.35325 Learning rate: 0.02 Mask loss: 0.14692 RPN box loss: 0.04187 RPN score loss: 0.00199 RPN total loss: 0.04386 Total loss: 1.79903 timestamp: 1654926333.5114622 iteration: 14335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18182 FastRCNN class loss: 0.0779 FastRCNN total loss: 0.25973 L1 loss: 0.0000e+00 L2 loss: 1.35302 Learning rate: 0.02 Mask loss: 0.14237 RPN box loss: 0.04487 RPN score loss: 0.00754 RPN total loss: 0.05241 Total loss: 1.80753 timestamp: 1654926336.7467966 iteration: 14340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18003 FastRCNN class loss: 0.0522 FastRCNN total loss: 0.23223 L1 loss: 0.0000e+00 L2 loss: 1.3528 Learning rate: 0.02 Mask loss: 0.11486 RPN box loss: 0.01337 RPN score loss: 0.00281 RPN total loss: 0.01618 Total loss: 1.71607 timestamp: 1654926340.0672941 iteration: 14345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12761 FastRCNN class loss: 0.08542 FastRCNN total loss: 0.21302 L1 loss: 0.0000e+00 L2 loss: 1.35255 Learning rate: 0.02 Mask loss: 0.11234 RPN box loss: 0.02272 RPN score loss: 0.00558 RPN total loss: 0.02831 Total loss: 1.70621 timestamp: 1654926343.2393837 iteration: 14350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28559 FastRCNN class loss: 0.20072 FastRCNN total loss: 0.48631 L1 loss: 0.0000e+00 L2 loss: 1.35231 Learning rate: 0.02 Mask loss: 0.33021 RPN box loss: 0.03457 RPN score loss: 0.01031 RPN total loss: 0.04487 Total loss: 2.21371 timestamp: 1654926346.4763703 iteration: 14355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11585 FastRCNN class loss: 0.07943 FastRCNN total loss: 0.19529 L1 loss: 0.0000e+00 L2 loss: 1.35207 Learning rate: 0.02 Mask loss: 0.17335 RPN box loss: 0.04163 RPN score loss: 0.00429 RPN total loss: 0.04592 Total loss: 1.76663 timestamp: 1654926349.753142 iteration: 14360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10153 FastRCNN class loss: 0.0582 FastRCNN total loss: 0.15973 L1 loss: 0.0000e+00 L2 loss: 1.35185 Learning rate: 0.02 Mask loss: 0.11106 RPN box loss: 0.02641 RPN score loss: 0.00264 RPN total loss: 0.02905 Total loss: 1.65168 timestamp: 1654926353.0013983 iteration: 14365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13114 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.18957 L1 loss: 0.0000e+00 L2 loss: 1.35162 Learning rate: 0.02 Mask loss: 0.12884 RPN box loss: 0.03358 RPN score loss: 0.00481 RPN total loss: 0.0384 Total loss: 1.70843 timestamp: 1654926356.3690608 iteration: 14370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12173 FastRCNN class loss: 0.13518 FastRCNN total loss: 0.25691 L1 loss: 0.0000e+00 L2 loss: 1.35137 Learning rate: 0.02 Mask loss: 0.23568 RPN box loss: 0.04352 RPN score loss: 0.00322 RPN total loss: 0.04674 Total loss: 1.8907 timestamp: 1654926359.5584528 iteration: 14375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22388 FastRCNN class loss: 0.11203 FastRCNN total loss: 0.33591 L1 loss: 0.0000e+00 L2 loss: 1.35112 Learning rate: 0.02 Mask loss: 0.20833 RPN box loss: 0.05151 RPN score loss: 0.00761 RPN total loss: 0.05912 Total loss: 1.95448 timestamp: 1654926362.836577 iteration: 14380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12942 FastRCNN class loss: 0.09666 FastRCNN total loss: 0.22608 L1 loss: 0.0000e+00 L2 loss: 1.35089 Learning rate: 0.02 Mask loss: 0.1373 RPN box loss: 0.03766 RPN score loss: 0.01843 RPN total loss: 0.05608 Total loss: 1.77035 timestamp: 1654926366.0640655 iteration: 14385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23625 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.31694 L1 loss: 0.0000e+00 L2 loss: 1.35065 Learning rate: 0.02 Mask loss: 0.14616 RPN box loss: 0.05493 RPN score loss: 0.00474 RPN total loss: 0.05967 Total loss: 1.87341 timestamp: 1654926369.381574 iteration: 14390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12604 FastRCNN class loss: 0.07866 FastRCNN total loss: 0.2047 L1 loss: 0.0000e+00 L2 loss: 1.35041 Learning rate: 0.02 Mask loss: 0.13214 RPN box loss: 0.02514 RPN score loss: 0.00508 RPN total loss: 0.03022 Total loss: 1.71747 timestamp: 1654926372.5491269 iteration: 14395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18169 FastRCNN class loss: 0.12598 FastRCNN total loss: 0.30767 L1 loss: 0.0000e+00 L2 loss: 1.35021 Learning rate: 0.02 Mask loss: 0.1794 RPN box loss: 0.04416 RPN score loss: 0.01686 RPN total loss: 0.06102 Total loss: 1.8983 timestamp: 1654926375.8664224 iteration: 14400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19676 FastRCNN class loss: 0.1471 FastRCNN total loss: 0.34386 L1 loss: 0.0000e+00 L2 loss: 1.34995 Learning rate: 0.02 Mask loss: 0.15234 RPN box loss: 0.02213 RPN score loss: 0.01191 RPN total loss: 0.03404 Total loss: 1.88019 timestamp: 1654926379.0662084 iteration: 14405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1022 FastRCNN class loss: 0.065 FastRCNN total loss: 0.16721 L1 loss: 0.0000e+00 L2 loss: 1.34974 Learning rate: 0.02 Mask loss: 0.29322 RPN box loss: 0.02629 RPN score loss: 0.00363 RPN total loss: 0.02992 Total loss: 1.8401 timestamp: 1654926382.4631202 iteration: 14410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2241 FastRCNN class loss: 0.12833 FastRCNN total loss: 0.35243 L1 loss: 0.0000e+00 L2 loss: 1.3495 Learning rate: 0.02 Mask loss: 0.17113 RPN box loss: 0.038 RPN score loss: 0.00456 RPN total loss: 0.04256 Total loss: 1.91562 timestamp: 1654926385.7907674 iteration: 14415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15782 FastRCNN class loss: 0.11848 FastRCNN total loss: 0.27631 L1 loss: 0.0000e+00 L2 loss: 1.34924 Learning rate: 0.02 Mask loss: 0.20991 RPN box loss: 0.07613 RPN score loss: 0.0184 RPN total loss: 0.09453 Total loss: 1.92999 timestamp: 1654926388.9855776 iteration: 14420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22504 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.30586 L1 loss: 0.0000e+00 L2 loss: 1.34902 Learning rate: 0.02 Mask loss: 0.15907 RPN box loss: 0.01613 RPN score loss: 0.00218 RPN total loss: 0.01831 Total loss: 1.83227 timestamp: 1654926392.296951 iteration: 14425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14791 FastRCNN class loss: 0.08243 FastRCNN total loss: 0.23034 L1 loss: 0.0000e+00 L2 loss: 1.34878 Learning rate: 0.02 Mask loss: 0.15753 RPN box loss: 0.03387 RPN score loss: 0.01193 RPN total loss: 0.0458 Total loss: 1.78245 timestamp: 1654926395.5531113 iteration: 14430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17153 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.22441 L1 loss: 0.0000e+00 L2 loss: 1.34856 Learning rate: 0.02 Mask loss: 0.13329 RPN box loss: 0.03529 RPN score loss: 0.00682 RPN total loss: 0.0421 Total loss: 1.74836 timestamp: 1654926398.8847876 iteration: 14435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18837 FastRCNN class loss: 0.09886 FastRCNN total loss: 0.28722 L1 loss: 0.0000e+00 L2 loss: 1.34832 Learning rate: 0.02 Mask loss: 0.1881 RPN box loss: 0.0621 RPN score loss: 0.01351 RPN total loss: 0.07561 Total loss: 1.89925 timestamp: 1654926402.1098855 iteration: 14440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15251 FastRCNN class loss: 0.13658 FastRCNN total loss: 0.28909 L1 loss: 0.0000e+00 L2 loss: 1.34808 Learning rate: 0.02 Mask loss: 0.21324 RPN box loss: 0.02943 RPN score loss: 0.00683 RPN total loss: 0.03626 Total loss: 1.88667 timestamp: 1654926405.4410217 iteration: 14445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1844 FastRCNN class loss: 0.09272 FastRCNN total loss: 0.27712 L1 loss: 0.0000e+00 L2 loss: 1.34786 Learning rate: 0.02 Mask loss: 0.21931 RPN box loss: 0.05511 RPN score loss: 0.01147 RPN total loss: 0.06658 Total loss: 1.91086 timestamp: 1654926408.5430582 iteration: 14450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10669 FastRCNN class loss: 0.13457 FastRCNN total loss: 0.24125 L1 loss: 0.0000e+00 L2 loss: 1.34765 Learning rate: 0.02 Mask loss: 0.18801 RPN box loss: 0.05626 RPN score loss: 0.01536 RPN total loss: 0.07162 Total loss: 1.84853 timestamp: 1654926411.904325 iteration: 14455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16938 FastRCNN class loss: 0.07452 FastRCNN total loss: 0.24389 L1 loss: 0.0000e+00 L2 loss: 1.34742 Learning rate: 0.02 Mask loss: 0.20019 RPN box loss: 0.05575 RPN score loss: 0.00948 RPN total loss: 0.06522 Total loss: 1.85672 timestamp: 1654926415.0833616 iteration: 14460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16294 FastRCNN class loss: 0.0962 FastRCNN total loss: 0.25914 L1 loss: 0.0000e+00 L2 loss: 1.34721 Learning rate: 0.02 Mask loss: 0.17239 RPN box loss: 0.0304 RPN score loss: 0.00557 RPN total loss: 0.03596 Total loss: 1.8147 timestamp: 1654926418.407665 iteration: 14465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10202 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.17435 L1 loss: 0.0000e+00 L2 loss: 1.34697 Learning rate: 0.02 Mask loss: 0.12449 RPN box loss: 0.08676 RPN score loss: 0.00982 RPN total loss: 0.09658 Total loss: 1.74239 timestamp: 1654926421.6281247 iteration: 14470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16798 FastRCNN class loss: 0.14964 FastRCNN total loss: 0.31762 L1 loss: 0.0000e+00 L2 loss: 1.34671 Learning rate: 0.02 Mask loss: 0.22802 RPN box loss: 0.01662 RPN score loss: 0.00478 RPN total loss: 0.0214 Total loss: 1.91376 timestamp: 1654926424.8583198 iteration: 14475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16731 FastRCNN class loss: 0.1314 FastRCNN total loss: 0.29872 L1 loss: 0.0000e+00 L2 loss: 1.34648 Learning rate: 0.02 Mask loss: 0.16649 RPN box loss: 0.02212 RPN score loss: 0.00987 RPN total loss: 0.03199 Total loss: 1.84368 timestamp: 1654926428.2009964 iteration: 14480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17473 FastRCNN class loss: 0.10104 FastRCNN total loss: 0.27577 L1 loss: 0.0000e+00 L2 loss: 1.34625 Learning rate: 0.02 Mask loss: 0.18569 RPN box loss: 0.01819 RPN score loss: 0.00767 RPN total loss: 0.02585 Total loss: 1.83356 timestamp: 1654926431.367036 iteration: 14485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10472 FastRCNN class loss: 0.05051 FastRCNN total loss: 0.15523 L1 loss: 0.0000e+00 L2 loss: 1.34602 Learning rate: 0.02 Mask loss: 0.08766 RPN box loss: 0.01381 RPN score loss: 0.0032 RPN total loss: 0.01701 Total loss: 1.60592 timestamp: 1654926434.6347084 iteration: 14490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08721 FastRCNN class loss: 0.0567 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 1.34582 Learning rate: 0.02 Mask loss: 0.07977 RPN box loss: 0.07195 RPN score loss: 0.00556 RPN total loss: 0.0775 Total loss: 1.647 timestamp: 1654926437.8062704 iteration: 14495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0968 FastRCNN class loss: 0.0479 FastRCNN total loss: 0.1447 L1 loss: 0.0000e+00 L2 loss: 1.34558 Learning rate: 0.02 Mask loss: 0.12901 RPN box loss: 0.06107 RPN score loss: 0.0084 RPN total loss: 0.06947 Total loss: 1.68876 timestamp: 1654926441.1076915 iteration: 14500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13484 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.19605 L1 loss: 0.0000e+00 L2 loss: 1.34534 Learning rate: 0.02 Mask loss: 0.12562 RPN box loss: 0.03288 RPN score loss: 0.00317 RPN total loss: 0.03605 Total loss: 1.70306 timestamp: 1654926444.3294983 iteration: 14505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15496 FastRCNN class loss: 0.11624 FastRCNN total loss: 0.2712 L1 loss: 0.0000e+00 L2 loss: 1.34509 Learning rate: 0.02 Mask loss: 0.24582 RPN box loss: 0.02552 RPN score loss: 0.00486 RPN total loss: 0.03039 Total loss: 1.89248 timestamp: 1654926447.699291 iteration: 14510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21206 FastRCNN class loss: 0.08345 FastRCNN total loss: 0.2955 L1 loss: 0.0000e+00 L2 loss: 1.34483 Learning rate: 0.02 Mask loss: 0.22812 RPN box loss: 0.01515 RPN score loss: 0.0041 RPN total loss: 0.01924 Total loss: 1.88771 timestamp: 1654926451.0385542 iteration: 14515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16355 FastRCNN class loss: 0.11149 FastRCNN total loss: 0.27504 L1 loss: 0.0000e+00 L2 loss: 1.34459 Learning rate: 0.02 Mask loss: 0.22997 RPN box loss: 0.04833 RPN score loss: 0.00732 RPN total loss: 0.05564 Total loss: 1.90524 timestamp: 1654926454.3205178 iteration: 14520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16272 FastRCNN class loss: 0.09461 FastRCNN total loss: 0.25733 L1 loss: 0.0000e+00 L2 loss: 1.34434 Learning rate: 0.02 Mask loss: 0.18782 RPN box loss: 0.03338 RPN score loss: 0.01259 RPN total loss: 0.04597 Total loss: 1.83545 timestamp: 1654926457.6409876 iteration: 14525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13769 FastRCNN class loss: 0.08054 FastRCNN total loss: 0.21823 L1 loss: 0.0000e+00 L2 loss: 1.34415 Learning rate: 0.02 Mask loss: 0.18257 RPN box loss: 0.01504 RPN score loss: 0.00485 RPN total loss: 0.01989 Total loss: 1.76484 timestamp: 1654926460.8715992 iteration: 14530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1509 FastRCNN class loss: 0.04766 FastRCNN total loss: 0.19856 L1 loss: 0.0000e+00 L2 loss: 1.34394 Learning rate: 0.02 Mask loss: 0.09739 RPN box loss: 0.00723 RPN score loss: 0.0012 RPN total loss: 0.00843 Total loss: 1.64832 timestamp: 1654926464.1638694 iteration: 14535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.09837 FastRCNN total loss: 0.23436 L1 loss: 0.0000e+00 L2 loss: 1.34371 Learning rate: 0.02 Mask loss: 0.15325 RPN box loss: 0.02926 RPN score loss: 0.00654 RPN total loss: 0.0358 Total loss: 1.76712 timestamp: 1654926467.2578676 iteration: 14540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15015 FastRCNN class loss: 0.13106 FastRCNN total loss: 0.28121 L1 loss: 0.0000e+00 L2 loss: 1.34349 Learning rate: 0.02 Mask loss: 0.24189 RPN box loss: 0.05108 RPN score loss: 0.027 RPN total loss: 0.07808 Total loss: 1.94466 timestamp: 1654926470.5844915 iteration: 14545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1662 FastRCNN class loss: 0.0876 FastRCNN total loss: 0.2538 L1 loss: 0.0000e+00 L2 loss: 1.34326 Learning rate: 0.02 Mask loss: 0.13728 RPN box loss: 0.02003 RPN score loss: 0.00504 RPN total loss: 0.02507 Total loss: 1.75941 timestamp: 1654926473.802396 iteration: 14550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17406 FastRCNN class loss: 0.0566 FastRCNN total loss: 0.23066 L1 loss: 0.0000e+00 L2 loss: 1.34303 Learning rate: 0.02 Mask loss: 0.14588 RPN box loss: 0.0128 RPN score loss: 0.00557 RPN total loss: 0.01837 Total loss: 1.73795 timestamp: 1654926477.1686468 iteration: 14555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12391 FastRCNN class loss: 0.10887 FastRCNN total loss: 0.23278 L1 loss: 0.0000e+00 L2 loss: 1.34283 Learning rate: 0.02 Mask loss: 0.14523 RPN box loss: 0.04741 RPN score loss: 0.00408 RPN total loss: 0.05149 Total loss: 1.77233 timestamp: 1654926480.4055421 iteration: 14560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24506 FastRCNN class loss: 0.15961 FastRCNN total loss: 0.40466 L1 loss: 0.0000e+00 L2 loss: 1.34259 Learning rate: 0.02 Mask loss: 0.27089 RPN box loss: 0.06985 RPN score loss: 0.01562 RPN total loss: 0.08548 Total loss: 2.10363 timestamp: 1654926483.6896381 iteration: 14565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10537 FastRCNN class loss: 0.10729 FastRCNN total loss: 0.21266 L1 loss: 0.0000e+00 L2 loss: 1.34237 Learning rate: 0.02 Mask loss: 0.19532 RPN box loss: 0.02699 RPN score loss: 0.0071 RPN total loss: 0.0341 Total loss: 1.78445 timestamp: 1654926487.001593 iteration: 14570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16713 FastRCNN class loss: 0.07643 FastRCNN total loss: 0.24355 L1 loss: 0.0000e+00 L2 loss: 1.34213 Learning rate: 0.02 Mask loss: 0.10357 RPN box loss: 0.0533 RPN score loss: 0.008 RPN total loss: 0.06129 Total loss: 1.75055 timestamp: 1654926490.176593 iteration: 14575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11586 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.18132 L1 loss: 0.0000e+00 L2 loss: 1.3419 Learning rate: 0.02 Mask loss: 0.15277 RPN box loss: 0.01508 RPN score loss: 0.00945 RPN total loss: 0.02454 Total loss: 1.70053 timestamp: 1654926493.525523 iteration: 14580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15686 FastRCNN class loss: 0.10165 FastRCNN total loss: 0.25851 L1 loss: 0.0000e+00 L2 loss: 1.34169 Learning rate: 0.02 Mask loss: 0.16443 RPN box loss: 0.03523 RPN score loss: 0.00606 RPN total loss: 0.04129 Total loss: 1.80592 timestamp: 1654926496.7919943 iteration: 14585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08423 FastRCNN class loss: 0.05037 FastRCNN total loss: 0.1346 L1 loss: 0.0000e+00 L2 loss: 1.34146 Learning rate: 0.02 Mask loss: 0.09786 RPN box loss: 0.00278 RPN score loss: 0.00249 RPN total loss: 0.00527 Total loss: 1.57919 timestamp: 1654926500.1469278 iteration: 14590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06279 FastRCNN class loss: 0.03997 FastRCNN total loss: 0.10276 L1 loss: 0.0000e+00 L2 loss: 1.34122 Learning rate: 0.02 Mask loss: 0.10126 RPN box loss: 0.00934 RPN score loss: 0.00135 RPN total loss: 0.01069 Total loss: 1.55592 timestamp: 1654926503.3820386 iteration: 14595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16497 FastRCNN class loss: 0.09646 FastRCNN total loss: 0.26143 L1 loss: 0.0000e+00 L2 loss: 1.34099 Learning rate: 0.02 Mask loss: 0.15542 RPN box loss: 0.02024 RPN score loss: 0.00644 RPN total loss: 0.02668 Total loss: 1.78452 timestamp: 1654926506.8284688 iteration: 14600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11188 FastRCNN class loss: 0.08095 FastRCNN total loss: 0.19284 L1 loss: 0.0000e+00 L2 loss: 1.34074 Learning rate: 0.02 Mask loss: 0.14192 RPN box loss: 0.03486 RPN score loss: 0.00905 RPN total loss: 0.0439 Total loss: 1.7194 timestamp: 1654926510.0090778 iteration: 14605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11976 FastRCNN class loss: 0.1022 FastRCNN total loss: 0.22196 L1 loss: 0.0000e+00 L2 loss: 1.34051 Learning rate: 0.02 Mask loss: 0.14863 RPN box loss: 0.03741 RPN score loss: 0.01759 RPN total loss: 0.055 Total loss: 1.7661 timestamp: 1654926513.3753011 iteration: 14610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18289 FastRCNN class loss: 0.08221 FastRCNN total loss: 0.2651 L1 loss: 0.0000e+00 L2 loss: 1.34029 Learning rate: 0.02 Mask loss: 0.12855 RPN box loss: 0.01706 RPN score loss: 0.01343 RPN total loss: 0.03049 Total loss: 1.76443 timestamp: 1654926516.6410425 iteration: 14615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13336 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.2247 L1 loss: 0.0000e+00 L2 loss: 1.34006 Learning rate: 0.02 Mask loss: 0.19032 RPN box loss: 0.03369 RPN score loss: 0.01446 RPN total loss: 0.04816 Total loss: 1.80325 timestamp: 1654926519.8941772 iteration: 14620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16446 FastRCNN class loss: 0.10234 FastRCNN total loss: 0.2668 L1 loss: 0.0000e+00 L2 loss: 1.3398 Learning rate: 0.02 Mask loss: 0.17447 RPN box loss: 0.02495 RPN score loss: 0.00578 RPN total loss: 0.03072 Total loss: 1.8118 timestamp: 1654926523.2784743 iteration: 14625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23567 FastRCNN class loss: 0.15718 FastRCNN total loss: 0.39285 L1 loss: 0.0000e+00 L2 loss: 1.33958 Learning rate: 0.02 Mask loss: 0.18964 RPN box loss: 0.02864 RPN score loss: 0.0051 RPN total loss: 0.03374 Total loss: 1.95581 timestamp: 1654926526.5212445 iteration: 14630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18147 FastRCNN class loss: 0.11016 FastRCNN total loss: 0.29163 L1 loss: 0.0000e+00 L2 loss: 1.33936 Learning rate: 0.02 Mask loss: 0.22489 RPN box loss: 0.0298 RPN score loss: 0.00757 RPN total loss: 0.03738 Total loss: 1.89325 timestamp: 1654926529.7612672 iteration: 14635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16431 FastRCNN class loss: 0.07472 FastRCNN total loss: 0.23904 L1 loss: 0.0000e+00 L2 loss: 1.3391 Learning rate: 0.02 Mask loss: 0.21378 RPN box loss: 0.02759 RPN score loss: 0.00847 RPN total loss: 0.03606 Total loss: 1.82798 timestamp: 1654926533.0357685 iteration: 14640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14184 FastRCNN class loss: 0.08792 FastRCNN total loss: 0.22976 L1 loss: 0.0000e+00 L2 loss: 1.33888 Learning rate: 0.02 Mask loss: 0.14963 RPN box loss: 0.01828 RPN score loss: 0.00527 RPN total loss: 0.02355 Total loss: 1.74181 timestamp: 1654926536.3000891 iteration: 14645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13141 FastRCNN class loss: 0.11345 FastRCNN total loss: 0.24486 L1 loss: 0.0000e+00 L2 loss: 1.33866 Learning rate: 0.02 Mask loss: 0.139 RPN box loss: 0.04246 RPN score loss: 0.00445 RPN total loss: 0.04691 Total loss: 1.76943 timestamp: 1654926539.4795325 iteration: 14650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14766 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.23165 L1 loss: 0.0000e+00 L2 loss: 1.33843 Learning rate: 0.02 Mask loss: 0.14345 RPN box loss: 0.05808 RPN score loss: 0.00451 RPN total loss: 0.06259 Total loss: 1.77612 timestamp: 1654926542.74771 iteration: 14655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14271 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.19556 L1 loss: 0.0000e+00 L2 loss: 1.33823 Learning rate: 0.02 Mask loss: 0.16042 RPN box loss: 0.01106 RPN score loss: 0.00554 RPN total loss: 0.01659 Total loss: 1.7108 timestamp: 1654926545.934671 iteration: 14660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19922 FastRCNN class loss: 0.13173 FastRCNN total loss: 0.33095 L1 loss: 0.0000e+00 L2 loss: 1.338 Learning rate: 0.02 Mask loss: 0.12919 RPN box loss: 0.05399 RPN score loss: 0.00965 RPN total loss: 0.06364 Total loss: 1.86178 timestamp: 1654926549.1604204 iteration: 14665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1584 FastRCNN class loss: 0.17575 FastRCNN total loss: 0.33415 L1 loss: 0.0000e+00 L2 loss: 1.33778 Learning rate: 0.02 Mask loss: 0.18337 RPN box loss: 0.03623 RPN score loss: 0.0077 RPN total loss: 0.04393 Total loss: 1.89923 timestamp: 1654926552.4644377 iteration: 14670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06022 FastRCNN class loss: 0.03919 FastRCNN total loss: 0.09941 L1 loss: 0.0000e+00 L2 loss: 1.33756 Learning rate: 0.02 Mask loss: 0.10063 RPN box loss: 0.01509 RPN score loss: 0.00102 RPN total loss: 0.0161 Total loss: 1.5537 timestamp: 1654926555.764448 iteration: 14675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16344 FastRCNN class loss: 0.12062 FastRCNN total loss: 0.28406 L1 loss: 0.0000e+00 L2 loss: 1.33731 Learning rate: 0.02 Mask loss: 0.17593 RPN box loss: 0.07527 RPN score loss: 0.00667 RPN total loss: 0.08194 Total loss: 1.87925 timestamp: 1654926558.9597714 iteration: 14680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22918 FastRCNN class loss: 0.12315 FastRCNN total loss: 0.35233 L1 loss: 0.0000e+00 L2 loss: 1.33708 Learning rate: 0.02 Mask loss: 0.16405 RPN box loss: 0.05258 RPN score loss: 0.00993 RPN total loss: 0.06252 Total loss: 1.91597 timestamp: 1654926562.1462073 iteration: 14685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16564 FastRCNN class loss: 0.10199 FastRCNN total loss: 0.26763 L1 loss: 0.0000e+00 L2 loss: 1.33684 Learning rate: 0.02 Mask loss: 0.22617 RPN box loss: 0.03132 RPN score loss: 0.01456 RPN total loss: 0.04588 Total loss: 1.87652 timestamp: 1654926565.440356 iteration: 14690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11182 FastRCNN class loss: 0.07457 FastRCNN total loss: 0.18638 L1 loss: 0.0000e+00 L2 loss: 1.33662 Learning rate: 0.02 Mask loss: 0.17629 RPN box loss: 0.04207 RPN score loss: 0.00538 RPN total loss: 0.04745 Total loss: 1.74675 timestamp: 1654926568.6818671 iteration: 14695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13454 FastRCNN class loss: 0.09383 FastRCNN total loss: 0.22837 L1 loss: 0.0000e+00 L2 loss: 1.33641 Learning rate: 0.02 Mask loss: 0.16071 RPN box loss: 0.01874 RPN score loss: 0.00469 RPN total loss: 0.02343 Total loss: 1.74892 timestamp: 1654926572.059393 iteration: 14700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29024 FastRCNN class loss: 0.12718 FastRCNN total loss: 0.41742 L1 loss: 0.0000e+00 L2 loss: 1.33618 Learning rate: 0.02 Mask loss: 0.21947 RPN box loss: 0.03467 RPN score loss: 0.02166 RPN total loss: 0.05633 Total loss: 2.0294 timestamp: 1654926575.2640061 iteration: 14705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12462 FastRCNN class loss: 0.05706 FastRCNN total loss: 0.18168 L1 loss: 0.0000e+00 L2 loss: 1.33594 Learning rate: 0.02 Mask loss: 0.2043 RPN box loss: 0.02571 RPN score loss: 0.00417 RPN total loss: 0.02988 Total loss: 1.7518 timestamp: 1654926578.5097218 iteration: 14710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19524 FastRCNN class loss: 0.11622 FastRCNN total loss: 0.31146 L1 loss: 0.0000e+00 L2 loss: 1.33571 Learning rate: 0.02 Mask loss: 0.13959 RPN box loss: 0.06135 RPN score loss: 0.01137 RPN total loss: 0.07272 Total loss: 1.85948 timestamp: 1654926581.7279687 iteration: 14715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12012 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.18621 L1 loss: 0.0000e+00 L2 loss: 1.33548 Learning rate: 0.02 Mask loss: 0.15265 RPN box loss: 0.02875 RPN score loss: 0.00389 RPN total loss: 0.03264 Total loss: 1.70697 timestamp: 1654926585.0037155 iteration: 14720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.157 FastRCNN class loss: 0.06481 FastRCNN total loss: 0.22181 L1 loss: 0.0000e+00 L2 loss: 1.33525 Learning rate: 0.02 Mask loss: 0.17219 RPN box loss: 0.02433 RPN score loss: 0.01023 RPN total loss: 0.03456 Total loss: 1.7638 timestamp: 1654926588.2580664 iteration: 14725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17528 FastRCNN class loss: 0.09198 FastRCNN total loss: 0.26726 L1 loss: 0.0000e+00 L2 loss: 1.33502 Learning rate: 0.02 Mask loss: 0.14516 RPN box loss: 0.02988 RPN score loss: 0.00642 RPN total loss: 0.0363 Total loss: 1.78374 timestamp: 1654926591.4748898 iteration: 14730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17571 FastRCNN class loss: 0.18797 FastRCNN total loss: 0.36367 L1 loss: 0.0000e+00 L2 loss: 1.33477 Learning rate: 0.02 Mask loss: 0.20513 RPN box loss: 0.02866 RPN score loss: 0.01142 RPN total loss: 0.04008 Total loss: 1.94366 timestamp: 1654926594.7604923 iteration: 14735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.097 FastRCNN class loss: 0.0517 FastRCNN total loss: 0.1487 L1 loss: 0.0000e+00 L2 loss: 1.33452 Learning rate: 0.02 Mask loss: 0.15666 RPN box loss: 0.0126 RPN score loss: 0.00392 RPN total loss: 0.01652 Total loss: 1.65641 timestamp: 1654926597.9589105 iteration: 14740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19711 FastRCNN class loss: 0.11363 FastRCNN total loss: 0.31074 L1 loss: 0.0000e+00 L2 loss: 1.33429 Learning rate: 0.02 Mask loss: 0.13925 RPN box loss: 0.0416 RPN score loss: 0.00393 RPN total loss: 0.04552 Total loss: 1.8298 timestamp: 1654926601.3451598 iteration: 14745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13688 FastRCNN class loss: 0.10507 FastRCNN total loss: 0.24195 L1 loss: 0.0000e+00 L2 loss: 1.33405 Learning rate: 0.02 Mask loss: 0.19089 RPN box loss: 0.02007 RPN score loss: 0.00391 RPN total loss: 0.02398 Total loss: 1.79087 timestamp: 1654926604.4754174 iteration: 14750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15095 FastRCNN class loss: 0.08324 FastRCNN total loss: 0.23419 L1 loss: 0.0000e+00 L2 loss: 1.33382 Learning rate: 0.02 Mask loss: 0.13055 RPN box loss: 0.04025 RPN score loss: 0.00583 RPN total loss: 0.04608 Total loss: 1.74464 timestamp: 1654926607.7216976 iteration: 14755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13096 FastRCNN class loss: 0.10119 FastRCNN total loss: 0.23215 L1 loss: 0.0000e+00 L2 loss: 1.3336 Learning rate: 0.02 Mask loss: 0.21458 RPN box loss: 0.0333 RPN score loss: 0.01961 RPN total loss: 0.05291 Total loss: 1.83324 timestamp: 1654926610.899567 iteration: 14760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15048 FastRCNN class loss: 0.0871 FastRCNN total loss: 0.23758 L1 loss: 0.0000e+00 L2 loss: 1.33337 Learning rate: 0.02 Mask loss: 0.21984 RPN box loss: 0.02619 RPN score loss: 0.00399 RPN total loss: 0.03018 Total loss: 1.82098 timestamp: 1654926614.201924 iteration: 14765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07255 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.14431 L1 loss: 0.0000e+00 L2 loss: 1.33314 Learning rate: 0.02 Mask loss: 0.10162 RPN box loss: 0.02268 RPN score loss: 0.00894 RPN total loss: 0.03162 Total loss: 1.61069 timestamp: 1654926617.4532545 iteration: 14770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18366 FastRCNN class loss: 0.14552 FastRCNN total loss: 0.32917 L1 loss: 0.0000e+00 L2 loss: 1.33291 Learning rate: 0.02 Mask loss: 0.24102 RPN box loss: 0.04874 RPN score loss: 0.00801 RPN total loss: 0.05675 Total loss: 1.95985 timestamp: 1654926620.7030058 iteration: 14775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19291 FastRCNN class loss: 0.09514 FastRCNN total loss: 0.28805 L1 loss: 0.0000e+00 L2 loss: 1.33267 Learning rate: 0.02 Mask loss: 0.33001 RPN box loss: 0.05361 RPN score loss: 0.01092 RPN total loss: 0.06453 Total loss: 2.01526 timestamp: 1654926623.9521058 iteration: 14780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12835 FastRCNN class loss: 0.09937 FastRCNN total loss: 0.22772 L1 loss: 0.0000e+00 L2 loss: 1.33242 Learning rate: 0.02 Mask loss: 0.16501 RPN box loss: 0.02516 RPN score loss: 0.00666 RPN total loss: 0.03182 Total loss: 1.75697 timestamp: 1654926627.1206768 iteration: 14785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16496 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.24001 L1 loss: 0.0000e+00 L2 loss: 1.33218 Learning rate: 0.02 Mask loss: 0.14745 RPN box loss: 0.09813 RPN score loss: 0.00821 RPN total loss: 0.10633 Total loss: 1.82597 timestamp: 1654926630.5415707 iteration: 14790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.0598 FastRCNN total loss: 0.16711 L1 loss: 0.0000e+00 L2 loss: 1.33194 Learning rate: 0.02 Mask loss: 0.17387 RPN box loss: 0.03141 RPN score loss: 0.00146 RPN total loss: 0.03287 Total loss: 1.70578 timestamp: 1654926633.7990098 iteration: 14795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16385 FastRCNN class loss: 0.10523 FastRCNN total loss: 0.26909 L1 loss: 0.0000e+00 L2 loss: 1.33171 Learning rate: 0.02 Mask loss: 0.23043 RPN box loss: 0.02295 RPN score loss: 0.00795 RPN total loss: 0.0309 Total loss: 1.86213 timestamp: 1654926637.047251 iteration: 14800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15336 FastRCNN class loss: 0.09012 FastRCNN total loss: 0.24348 L1 loss: 0.0000e+00 L2 loss: 1.3315 Learning rate: 0.02 Mask loss: 0.19228 RPN box loss: 0.03954 RPN score loss: 0.01248 RPN total loss: 0.05202 Total loss: 1.81928 timestamp: 1654926640.3046367 iteration: 14805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15965 FastRCNN class loss: 0.11079 FastRCNN total loss: 0.27044 L1 loss: 0.0000e+00 L2 loss: 1.33127 Learning rate: 0.02 Mask loss: 0.17651 RPN box loss: 0.06272 RPN score loss: 0.00734 RPN total loss: 0.07007 Total loss: 1.84829 timestamp: 1654926643.6961117 iteration: 14810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23042 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.31204 L1 loss: 0.0000e+00 L2 loss: 1.33103 Learning rate: 0.02 Mask loss: 0.14098 RPN box loss: 0.01287 RPN score loss: 0.00432 RPN total loss: 0.01719 Total loss: 1.80123 timestamp: 1654926646.9331007 iteration: 14815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07425 FastRCNN class loss: 0.0594 FastRCNN total loss: 0.13365 L1 loss: 0.0000e+00 L2 loss: 1.33081 Learning rate: 0.02 Mask loss: 0.13004 RPN box loss: 0.01812 RPN score loss: 0.01509 RPN total loss: 0.03321 Total loss: 1.62771 timestamp: 1654926650.3009737 iteration: 14820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0926 FastRCNN class loss: 0.05256 FastRCNN total loss: 0.14516 L1 loss: 0.0000e+00 L2 loss: 1.33058 Learning rate: 0.02 Mask loss: 0.1062 RPN box loss: 0.01624 RPN score loss: 0.00487 RPN total loss: 0.0211 Total loss: 1.60304 timestamp: 1654926653.592842 iteration: 14825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24602 FastRCNN class loss: 0.15803 FastRCNN total loss: 0.40405 L1 loss: 0.0000e+00 L2 loss: 1.33035 Learning rate: 0.02 Mask loss: 0.28453 RPN box loss: 0.08388 RPN score loss: 0.00872 RPN total loss: 0.0926 Total loss: 2.11152 timestamp: 1654926656.7479947 iteration: 14830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16577 FastRCNN class loss: 0.06562 FastRCNN total loss: 0.23139 L1 loss: 0.0000e+00 L2 loss: 1.33012 Learning rate: 0.02 Mask loss: 0.13274 RPN box loss: 0.01678 RPN score loss: 0.0051 RPN total loss: 0.02188 Total loss: 1.71613 timestamp: 1654926659.9647117 iteration: 14835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.09118 FastRCNN total loss: 0.22717 L1 loss: 0.0000e+00 L2 loss: 1.32989 Learning rate: 0.02 Mask loss: 0.1424 RPN box loss: 0.04186 RPN score loss: 0.01652 RPN total loss: 0.05838 Total loss: 1.75784 timestamp: 1654926663.180741 iteration: 14840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12912 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.18653 L1 loss: 0.0000e+00 L2 loss: 1.32966 Learning rate: 0.02 Mask loss: 0.13783 RPN box loss: 0.03481 RPN score loss: 0.00372 RPN total loss: 0.03853 Total loss: 1.69254 timestamp: 1654926666.450271 iteration: 14845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.04794 FastRCNN total loss: 0.16143 L1 loss: 0.0000e+00 L2 loss: 1.32943 Learning rate: 0.02 Mask loss: 0.12858 RPN box loss: 0.00817 RPN score loss: 0.00288 RPN total loss: 0.01105 Total loss: 1.63049 timestamp: 1654926669.6127195 iteration: 14850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16625 FastRCNN class loss: 0.09797 FastRCNN total loss: 0.26422 L1 loss: 0.0000e+00 L2 loss: 1.3292 Learning rate: 0.02 Mask loss: 0.14599 RPN box loss: 0.01134 RPN score loss: 0.00939 RPN total loss: 0.02073 Total loss: 1.76013 timestamp: 1654926672.9807749 iteration: 14855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09024 FastRCNN class loss: 0.05422 FastRCNN total loss: 0.14447 L1 loss: 0.0000e+00 L2 loss: 1.32898 Learning rate: 0.02 Mask loss: 0.19107 RPN box loss: 0.03216 RPN score loss: 0.00567 RPN total loss: 0.03783 Total loss: 1.70234 timestamp: 1654926676.1770887 iteration: 14860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.10566 FastRCNN total loss: 0.25736 L1 loss: 0.0000e+00 L2 loss: 1.32875 Learning rate: 0.02 Mask loss: 0.15604 RPN box loss: 0.02513 RPN score loss: 0.0139 RPN total loss: 0.03903 Total loss: 1.78117 timestamp: 1654926679.3921402 iteration: 14865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17341 FastRCNN class loss: 0.10292 FastRCNN total loss: 0.27633 L1 loss: 0.0000e+00 L2 loss: 1.32851 Learning rate: 0.02 Mask loss: 0.18348 RPN box loss: 0.01465 RPN score loss: 0.02249 RPN total loss: 0.03714 Total loss: 1.82546 timestamp: 1654926682.6309032 iteration: 14870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11212 FastRCNN class loss: 0.09007 FastRCNN total loss: 0.20219 L1 loss: 0.0000e+00 L2 loss: 1.3283 Learning rate: 0.02 Mask loss: 0.12414 RPN box loss: 0.02708 RPN score loss: 0.00439 RPN total loss: 0.03147 Total loss: 1.6861 timestamp: 1654926685.9664068 iteration: 14875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17084 FastRCNN class loss: 0.11488 FastRCNN total loss: 0.28573 L1 loss: 0.0000e+00 L2 loss: 1.32807 Learning rate: 0.02 Mask loss: 0.17627 RPN box loss: 0.03576 RPN score loss: 0.00644 RPN total loss: 0.0422 Total loss: 1.83226 timestamp: 1654926689.1313353 iteration: 14880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16993 FastRCNN class loss: 0.11275 FastRCNN total loss: 0.28268 L1 loss: 0.0000e+00 L2 loss: 1.32784 Learning rate: 0.02 Mask loss: 0.2964 RPN box loss: 0.03439 RPN score loss: 0.00834 RPN total loss: 0.04273 Total loss: 1.94965 timestamp: 1654926692.4153624 iteration: 14885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23044 FastRCNN class loss: 0.1074 FastRCNN total loss: 0.33784 L1 loss: 0.0000e+00 L2 loss: 1.3276 Learning rate: 0.02 Mask loss: 0.14206 RPN box loss: 0.06414 RPN score loss: 0.00681 RPN total loss: 0.07095 Total loss: 1.87845 timestamp: 1654926695.754858 iteration: 14890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1219 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.1856 L1 loss: 0.0000e+00 L2 loss: 1.32735 Learning rate: 0.02 Mask loss: 0.08251 RPN box loss: 0.01113 RPN score loss: 0.00393 RPN total loss: 0.01506 Total loss: 1.61052 timestamp: 1654926698.9904287 iteration: 14895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13217 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.20683 L1 loss: 0.0000e+00 L2 loss: 1.32711 Learning rate: 0.02 Mask loss: 0.15504 RPN box loss: 0.0248 RPN score loss: 0.00727 RPN total loss: 0.03207 Total loss: 1.72106 timestamp: 1654926702.3930387 iteration: 14900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20645 FastRCNN class loss: 0.09792 FastRCNN total loss: 0.30437 L1 loss: 0.0000e+00 L2 loss: 1.3269 Learning rate: 0.02 Mask loss: 0.17562 RPN box loss: 0.016 RPN score loss: 0.00587 RPN total loss: 0.02187 Total loss: 1.82877 timestamp: 1654926705.60655 iteration: 14905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16168 FastRCNN class loss: 0.10112 FastRCNN total loss: 0.2628 L1 loss: 0.0000e+00 L2 loss: 1.32667 Learning rate: 0.02 Mask loss: 0.1555 RPN box loss: 0.03164 RPN score loss: 0.00457 RPN total loss: 0.03622 Total loss: 1.78119 timestamp: 1654926708.88999 iteration: 14910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11145 FastRCNN class loss: 0.05291 FastRCNN total loss: 0.16436 L1 loss: 0.0000e+00 L2 loss: 1.32644 Learning rate: 0.02 Mask loss: 0.11783 RPN box loss: 0.01468 RPN score loss: 0.00157 RPN total loss: 0.01625 Total loss: 1.62488 timestamp: 1654926712.0441604 iteration: 14915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18591 FastRCNN class loss: 0.11665 FastRCNN total loss: 0.30256 L1 loss: 0.0000e+00 L2 loss: 1.3262 Learning rate: 0.02 Mask loss: 0.21676 RPN box loss: 0.07481 RPN score loss: 0.00878 RPN total loss: 0.08358 Total loss: 1.92911 timestamp: 1654926715.2930152 iteration: 14920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08849 FastRCNN class loss: 0.04278 FastRCNN total loss: 0.13127 L1 loss: 0.0000e+00 L2 loss: 1.32597 Learning rate: 0.02 Mask loss: 0.12972 RPN box loss: 0.00784 RPN score loss: 0.00308 RPN total loss: 0.01092 Total loss: 1.59788 timestamp: 1654926718.4611433 iteration: 14925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17005 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.22606 L1 loss: 0.0000e+00 L2 loss: 1.32575 Learning rate: 0.02 Mask loss: 0.11916 RPN box loss: 0.02205 RPN score loss: 0.00501 RPN total loss: 0.02706 Total loss: 1.69803 timestamp: 1654926721.833517 iteration: 14930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14964 FastRCNN class loss: 0.12763 FastRCNN total loss: 0.27728 L1 loss: 0.0000e+00 L2 loss: 1.32551 Learning rate: 0.02 Mask loss: 0.17306 RPN box loss: 0.04378 RPN score loss: 0.00911 RPN total loss: 0.0529 Total loss: 1.82875 timestamp: 1654926725.1162224 iteration: 14935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12223 FastRCNN class loss: 0.05743 FastRCNN total loss: 0.17966 L1 loss: 0.0000e+00 L2 loss: 1.32528 Learning rate: 0.02 Mask loss: 0.13438 RPN box loss: 0.07655 RPN score loss: 0.00513 RPN total loss: 0.08168 Total loss: 1.721 timestamp: 1654926728.3811703 iteration: 14940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16804 FastRCNN class loss: 0.04774 FastRCNN total loss: 0.21578 L1 loss: 0.0000e+00 L2 loss: 1.32505 Learning rate: 0.02 Mask loss: 0.14965 RPN box loss: 0.05311 RPN score loss: 0.00336 RPN total loss: 0.05648 Total loss: 1.74695 timestamp: 1654926731.6308155 iteration: 14945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14989 FastRCNN class loss: 0.13687 FastRCNN total loss: 0.28675 L1 loss: 0.0000e+00 L2 loss: 1.32484 Learning rate: 0.02 Mask loss: 0.18556 RPN box loss: 0.08168 RPN score loss: 0.00782 RPN total loss: 0.0895 Total loss: 1.88665 timestamp: 1654926734.8344932 iteration: 14950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2349 FastRCNN class loss: 0.20622 FastRCNN total loss: 0.44112 L1 loss: 0.0000e+00 L2 loss: 1.32461 Learning rate: 0.02 Mask loss: 0.27848 RPN box loss: 0.09251 RPN score loss: 0.01797 RPN total loss: 0.11048 Total loss: 2.15469 timestamp: 1654926738.1098096 iteration: 14955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20436 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.28471 L1 loss: 0.0000e+00 L2 loss: 1.32439 Learning rate: 0.02 Mask loss: 0.17947 RPN box loss: 0.00962 RPN score loss: 0.00274 RPN total loss: 0.01237 Total loss: 1.80093 timestamp: 1654926741.3250444 iteration: 14960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11915 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.20492 L1 loss: 0.0000e+00 L2 loss: 1.32414 Learning rate: 0.02 Mask loss: 0.1584 RPN box loss: 0.0185 RPN score loss: 0.00237 RPN total loss: 0.02087 Total loss: 1.70833 timestamp: 1654926744.632346 iteration: 14965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14698 FastRCNN class loss: 0.04591 FastRCNN total loss: 0.19289 L1 loss: 0.0000e+00 L2 loss: 1.3239 Learning rate: 0.02 Mask loss: 0.20427 RPN box loss: 0.01188 RPN score loss: 0.0058 RPN total loss: 0.01768 Total loss: 1.73873 timestamp: 1654926747.783033 iteration: 14970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14184 FastRCNN class loss: 0.11279 FastRCNN total loss: 0.25464 L1 loss: 0.0000e+00 L2 loss: 1.32367 Learning rate: 0.02 Mask loss: 0.15183 RPN box loss: 0.04442 RPN score loss: 0.0099 RPN total loss: 0.05432 Total loss: 1.78446 timestamp: 1654926751.1069825 iteration: 14975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15748 FastRCNN class loss: 0.10159 FastRCNN total loss: 0.25906 L1 loss: 0.0000e+00 L2 loss: 1.32345 Learning rate: 0.02 Mask loss: 0.21077 RPN box loss: 0.03469 RPN score loss: 0.0132 RPN total loss: 0.04789 Total loss: 1.84118 timestamp: 1654926754.2648041 iteration: 14980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17095 FastRCNN class loss: 0.12655 FastRCNN total loss: 0.2975 L1 loss: 0.0000e+00 L2 loss: 1.32323 Learning rate: 0.02 Mask loss: 0.16811 RPN box loss: 0.06395 RPN score loss: 0.0088 RPN total loss: 0.07275 Total loss: 1.8616 timestamp: 1654926757.508852 iteration: 14985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10006 FastRCNN class loss: 0.08308 FastRCNN total loss: 0.18313 L1 loss: 0.0000e+00 L2 loss: 1.323 Learning rate: 0.02 Mask loss: 0.13402 RPN box loss: 0.06878 RPN score loss: 0.01545 RPN total loss: 0.08424 Total loss: 1.72438 timestamp: 1654926760.7413313 iteration: 14990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17236 FastRCNN class loss: 0.14111 FastRCNN total loss: 0.31347 L1 loss: 0.0000e+00 L2 loss: 1.32277 Learning rate: 0.02 Mask loss: 0.14511 RPN box loss: 0.02421 RPN score loss: 0.01206 RPN total loss: 0.03628 Total loss: 1.81762 timestamp: 1654926763.9955878 iteration: 14995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14127 FastRCNN class loss: 0.11475 FastRCNN total loss: 0.25602 L1 loss: 0.0000e+00 L2 loss: 1.32256 Learning rate: 0.02 Mask loss: 0.17119 RPN box loss: 0.01344 RPN score loss: 0.00395 RPN total loss: 0.01739 Total loss: 1.76716 timestamp: 1654926767.3933198 iteration: 15000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20869 FastRCNN class loss: 0.11126 FastRCNN total loss: 0.31995 L1 loss: 0.0000e+00 L2 loss: 1.32234 Learning rate: 0.02 Mask loss: 0.19876 RPN box loss: 0.03835 RPN score loss: 0.00488 RPN total loss: 0.04322 Total loss: 1.88427 timestamp: 1654926770.6361623 iteration: 15005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17807 FastRCNN class loss: 0.12903 FastRCNN total loss: 0.3071 L1 loss: 0.0000e+00 L2 loss: 1.32211 Learning rate: 0.02 Mask loss: 0.18371 RPN box loss: 0.03366 RPN score loss: 0.04872 RPN total loss: 0.08238 Total loss: 1.89531 timestamp: 1654926773.8630104 iteration: 15010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14562 FastRCNN class loss: 0.07267 FastRCNN total loss: 0.21829 L1 loss: 0.0000e+00 L2 loss: 1.32187 Learning rate: 0.02 Mask loss: 0.1624 RPN box loss: 0.03137 RPN score loss: 0.00537 RPN total loss: 0.03674 Total loss: 1.7393 timestamp: 1654926777.0263968 iteration: 15015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13734 FastRCNN class loss: 0.08216 FastRCNN total loss: 0.2195 L1 loss: 0.0000e+00 L2 loss: 1.32166 Learning rate: 0.02 Mask loss: 0.24158 RPN box loss: 0.10586 RPN score loss: 0.01677 RPN total loss: 0.12264 Total loss: 1.90537 timestamp: 1654926780.3021417 iteration: 15020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12262 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.19083 L1 loss: 0.0000e+00 L2 loss: 1.32143 Learning rate: 0.02 Mask loss: 0.10528 RPN box loss: 0.00589 RPN score loss: 0.00348 RPN total loss: 0.00936 Total loss: 1.62691 timestamp: 1654926783.4835944 iteration: 15025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17342 FastRCNN class loss: 0.1089 FastRCNN total loss: 0.28232 L1 loss: 0.0000e+00 L2 loss: 1.3212 Learning rate: 0.02 Mask loss: 0.24929 RPN box loss: 0.03679 RPN score loss: 0.01769 RPN total loss: 0.05447 Total loss: 1.90728 timestamp: 1654926786.8051262 iteration: 15030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16303 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.22086 L1 loss: 0.0000e+00 L2 loss: 1.32097 Learning rate: 0.02 Mask loss: 0.12507 RPN box loss: 0.00924 RPN score loss: 0.00332 RPN total loss: 0.01256 Total loss: 1.67946 timestamp: 1654926789.8969734 iteration: 15035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14813 FastRCNN class loss: 0.06778 FastRCNN total loss: 0.21591 L1 loss: 0.0000e+00 L2 loss: 1.32071 Learning rate: 0.02 Mask loss: 0.15758 RPN box loss: 0.05422 RPN score loss: 0.00668 RPN total loss: 0.0609 Total loss: 1.7551 timestamp: 1654926793.2568643 iteration: 15040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20355 FastRCNN class loss: 0.12735 FastRCNN total loss: 0.3309 L1 loss: 0.0000e+00 L2 loss: 1.32051 Learning rate: 0.02 Mask loss: 0.21849 RPN box loss: 0.03443 RPN score loss: 0.02063 RPN total loss: 0.05506 Total loss: 1.92495 timestamp: 1654926796.511293 iteration: 15045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11105 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.17013 L1 loss: 0.0000e+00 L2 loss: 1.32027 Learning rate: 0.02 Mask loss: 0.07914 RPN box loss: 0.0132 RPN score loss: 0.00764 RPN total loss: 0.02084 Total loss: 1.59039 timestamp: 1654926799.827756 iteration: 15050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.16683 L1 loss: 0.0000e+00 L2 loss: 1.32002 Learning rate: 0.02 Mask loss: 0.14367 RPN box loss: 0.02808 RPN score loss: 0.00292 RPN total loss: 0.03101 Total loss: 1.66153 timestamp: 1654926803.1234229 iteration: 15055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17456 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.26343 L1 loss: 0.0000e+00 L2 loss: 1.31981 Learning rate: 0.02 Mask loss: 0.12907 RPN box loss: 0.0119 RPN score loss: 0.00204 RPN total loss: 0.01395 Total loss: 1.72626 timestamp: 1654926806.3663268 iteration: 15060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13294 FastRCNN class loss: 0.09738 FastRCNN total loss: 0.23032 L1 loss: 0.0000e+00 L2 loss: 1.31959 Learning rate: 0.02 Mask loss: 0.14807 RPN box loss: 0.04955 RPN score loss: 0.00834 RPN total loss: 0.05789 Total loss: 1.75587 timestamp: 1654926809.64161 iteration: 15065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15575 FastRCNN class loss: 0.09618 FastRCNN total loss: 0.25193 L1 loss: 0.0000e+00 L2 loss: 1.31935 Learning rate: 0.02 Mask loss: 0.12959 RPN box loss: 0.03709 RPN score loss: 0.01446 RPN total loss: 0.05155 Total loss: 1.75242 timestamp: 1654926812.8490095 iteration: 15070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15803 FastRCNN class loss: 0.08922 FastRCNN total loss: 0.24726 L1 loss: 0.0000e+00 L2 loss: 1.31912 Learning rate: 0.02 Mask loss: 0.16174 RPN box loss: 0.0706 RPN score loss: 0.00785 RPN total loss: 0.07846 Total loss: 1.80658 timestamp: 1654926816.2705145 iteration: 15075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13707 FastRCNN class loss: 0.10953 FastRCNN total loss: 0.2466 L1 loss: 0.0000e+00 L2 loss: 1.31892 Learning rate: 0.02 Mask loss: 0.32247 RPN box loss: 0.01795 RPN score loss: 0.00337 RPN total loss: 0.02131 Total loss: 1.9093 timestamp: 1654926819.4985359 iteration: 15080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1226 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.18066 L1 loss: 0.0000e+00 L2 loss: 1.31869 Learning rate: 0.02 Mask loss: 0.10301 RPN box loss: 0.03902 RPN score loss: 0.00981 RPN total loss: 0.04884 Total loss: 1.65119 timestamp: 1654926822.8689573 iteration: 15085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09431 FastRCNN class loss: 0.10932 FastRCNN total loss: 0.20363 L1 loss: 0.0000e+00 L2 loss: 1.31846 Learning rate: 0.02 Mask loss: 0.14185 RPN box loss: 0.0249 RPN score loss: 0.00535 RPN total loss: 0.03025 Total loss: 1.69419 timestamp: 1654926826.0522325 iteration: 15090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.18158 L1 loss: 0.0000e+00 L2 loss: 1.31825 Learning rate: 0.02 Mask loss: 0.20826 RPN box loss: 0.01451 RPN score loss: 0.00253 RPN total loss: 0.01705 Total loss: 1.72513 timestamp: 1654926829.2741003 iteration: 15095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1402 FastRCNN class loss: 0.08996 FastRCNN total loss: 0.23016 L1 loss: 0.0000e+00 L2 loss: 1.31804 Learning rate: 0.02 Mask loss: 0.14719 RPN box loss: 0.02958 RPN score loss: 0.01393 RPN total loss: 0.04351 Total loss: 1.73891 timestamp: 1654926832.3844595 iteration: 15100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15219 FastRCNN class loss: 0.07627 FastRCNN total loss: 0.22846 L1 loss: 0.0000e+00 L2 loss: 1.31781 Learning rate: 0.02 Mask loss: 0.10115 RPN box loss: 0.03591 RPN score loss: 0.00898 RPN total loss: 0.04489 Total loss: 1.69231 timestamp: 1654926835.591003 iteration: 15105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11433 FastRCNN class loss: 0.04675 FastRCNN total loss: 0.16108 L1 loss: 0.0000e+00 L2 loss: 1.3176 Learning rate: 0.02 Mask loss: 0.10605 RPN box loss: 0.00932 RPN score loss: 0.004 RPN total loss: 0.01333 Total loss: 1.59806 timestamp: 1654926838.8364155 iteration: 15110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.09876 FastRCNN total loss: 0.23281 L1 loss: 0.0000e+00 L2 loss: 1.31739 Learning rate: 0.02 Mask loss: 0.17618 RPN box loss: 0.03409 RPN score loss: 0.00598 RPN total loss: 0.04007 Total loss: 1.76645 timestamp: 1654926842.0809026 iteration: 15115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17768 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.26278 L1 loss: 0.0000e+00 L2 loss: 1.31716 Learning rate: 0.02 Mask loss: 0.15819 RPN box loss: 0.08293 RPN score loss: 0.00803 RPN total loss: 0.09096 Total loss: 1.82909 timestamp: 1654926845.3894854 iteration: 15120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19744 FastRCNN class loss: 0.09046 FastRCNN total loss: 0.2879 L1 loss: 0.0000e+00 L2 loss: 1.31693 Learning rate: 0.02 Mask loss: 0.1813 RPN box loss: 0.00871 RPN score loss: 0.00421 RPN total loss: 0.01292 Total loss: 1.79906 timestamp: 1654926848.615821 iteration: 15125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.0614 FastRCNN total loss: 0.15134 L1 loss: 0.0000e+00 L2 loss: 1.31671 Learning rate: 0.02 Mask loss: 0.15012 RPN box loss: 0.0097 RPN score loss: 0.00527 RPN total loss: 0.01497 Total loss: 1.63313 timestamp: 1654926851.9195263 iteration: 15130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13178 FastRCNN class loss: 0.07965 FastRCNN total loss: 0.21142 L1 loss: 0.0000e+00 L2 loss: 1.31645 Learning rate: 0.02 Mask loss: 0.12822 RPN box loss: 0.04163 RPN score loss: 0.00606 RPN total loss: 0.04769 Total loss: 1.70379 timestamp: 1654926855.076461 iteration: 15135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.11488 FastRCNN total loss: 0.20807 L1 loss: 0.0000e+00 L2 loss: 1.31624 Learning rate: 0.02 Mask loss: 0.14967 RPN box loss: 0.0589 RPN score loss: 0.00705 RPN total loss: 0.06596 Total loss: 1.73993 timestamp: 1654926858.347036 iteration: 15140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18658 FastRCNN class loss: 0.07371 FastRCNN total loss: 0.26029 L1 loss: 0.0000e+00 L2 loss: 1.31603 Learning rate: 0.02 Mask loss: 0.13675 RPN box loss: 0.00941 RPN score loss: 0.00185 RPN total loss: 0.01126 Total loss: 1.72433 timestamp: 1654926861.4711208 iteration: 15145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11607 FastRCNN class loss: 0.0812 FastRCNN total loss: 0.19726 L1 loss: 0.0000e+00 L2 loss: 1.31581 Learning rate: 0.02 Mask loss: 0.13581 RPN box loss: 0.03822 RPN score loss: 0.00642 RPN total loss: 0.04464 Total loss: 1.69352 timestamp: 1654926864.8397877 iteration: 15150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15855 FastRCNN class loss: 0.09105 FastRCNN total loss: 0.2496 L1 loss: 0.0000e+00 L2 loss: 1.31558 Learning rate: 0.02 Mask loss: 0.21476 RPN box loss: 0.02058 RPN score loss: 0.00605 RPN total loss: 0.02662 Total loss: 1.80656 timestamp: 1654926868.0673792 iteration: 15155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16217 FastRCNN class loss: 0.08197 FastRCNN total loss: 0.24414 L1 loss: 0.0000e+00 L2 loss: 1.31537 Learning rate: 0.02 Mask loss: 0.10458 RPN box loss: 0.01699 RPN score loss: 0.00632 RPN total loss: 0.02331 Total loss: 1.6874 timestamp: 1654926871.3761237 iteration: 15160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16908 FastRCNN class loss: 0.09419 FastRCNN total loss: 0.26327 L1 loss: 0.0000e+00 L2 loss: 1.31514 Learning rate: 0.02 Mask loss: 0.10294 RPN box loss: 0.02948 RPN score loss: 0.0034 RPN total loss: 0.03288 Total loss: 1.71423 timestamp: 1654926874.6088972 iteration: 15165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12377 FastRCNN class loss: 0.06899 FastRCNN total loss: 0.19275 L1 loss: 0.0000e+00 L2 loss: 1.31492 Learning rate: 0.02 Mask loss: 0.12917 RPN box loss: 0.02225 RPN score loss: 0.00178 RPN total loss: 0.02404 Total loss: 1.66088 timestamp: 1654926877.8368282 iteration: 15170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19387 FastRCNN class loss: 0.1499 FastRCNN total loss: 0.34377 L1 loss: 0.0000e+00 L2 loss: 1.31469 Learning rate: 0.02 Mask loss: 0.26477 RPN box loss: 0.03275 RPN score loss: 0.01138 RPN total loss: 0.04413 Total loss: 1.96737 timestamp: 1654926881.1599216 iteration: 15175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1534 FastRCNN class loss: 0.08733 FastRCNN total loss: 0.24073 L1 loss: 0.0000e+00 L2 loss: 1.31443 Learning rate: 0.02 Mask loss: 0.12176 RPN box loss: 0.01246 RPN score loss: 0.00759 RPN total loss: 0.02005 Total loss: 1.69697 timestamp: 1654926884.3288662 iteration: 15180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22391 FastRCNN class loss: 0.14249 FastRCNN total loss: 0.3664 L1 loss: 0.0000e+00 L2 loss: 1.31421 Learning rate: 0.02 Mask loss: 0.1935 RPN box loss: 0.02161 RPN score loss: 0.00587 RPN total loss: 0.02748 Total loss: 1.90159 timestamp: 1654926887.5434852 iteration: 15185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12506 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.21352 L1 loss: 0.0000e+00 L2 loss: 1.31401 Learning rate: 0.02 Mask loss: 0.15199 RPN box loss: 0.01611 RPN score loss: 0.00617 RPN total loss: 0.02228 Total loss: 1.7018 timestamp: 1654926890.7118037 iteration: 15190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1396 FastRCNN class loss: 0.08798 FastRCNN total loss: 0.22758 L1 loss: 0.0000e+00 L2 loss: 1.31379 Learning rate: 0.02 Mask loss: 0.22475 RPN box loss: 0.02581 RPN score loss: 0.00268 RPN total loss: 0.02849 Total loss: 1.79461 timestamp: 1654926893.9447381 iteration: 15195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1627 FastRCNN class loss: 0.08473 FastRCNN total loss: 0.24743 L1 loss: 0.0000e+00 L2 loss: 1.31358 Learning rate: 0.02 Mask loss: 0.12871 RPN box loss: 0.11075 RPN score loss: 0.00499 RPN total loss: 0.11574 Total loss: 1.80546 timestamp: 1654926897.1794965 iteration: 15200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19462 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.28073 L1 loss: 0.0000e+00 L2 loss: 1.31333 Learning rate: 0.02 Mask loss: 0.19701 RPN box loss: 0.02265 RPN score loss: 0.0052 RPN total loss: 0.02785 Total loss: 1.81892 timestamp: 1654926900.589137 iteration: 15205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.10857 FastRCNN total loss: 0.22154 L1 loss: 0.0000e+00 L2 loss: 1.3131 Learning rate: 0.02 Mask loss: 0.17892 RPN box loss: 0.01345 RPN score loss: 0.00494 RPN total loss: 0.01838 Total loss: 1.73194 timestamp: 1654926903.7740786 iteration: 15210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21012 FastRCNN class loss: 0.09563 FastRCNN total loss: 0.30575 L1 loss: 0.0000e+00 L2 loss: 1.31287 Learning rate: 0.02 Mask loss: 0.15997 RPN box loss: 0.03883 RPN score loss: 0.00661 RPN total loss: 0.04544 Total loss: 1.82403 timestamp: 1654926907.14776 iteration: 15215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24726 FastRCNN class loss: 0.1069 FastRCNN total loss: 0.35417 L1 loss: 0.0000e+00 L2 loss: 1.31265 Learning rate: 0.02 Mask loss: 0.20679 RPN box loss: 0.05507 RPN score loss: 0.01737 RPN total loss: 0.07244 Total loss: 1.94604 timestamp: 1654926910.4041672 iteration: 15220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25288 FastRCNN class loss: 0.10967 FastRCNN total loss: 0.36255 L1 loss: 0.0000e+00 L2 loss: 1.31244 Learning rate: 0.02 Mask loss: 0.1374 RPN box loss: 0.04591 RPN score loss: 0.02274 RPN total loss: 0.06865 Total loss: 1.88104 timestamp: 1654926913.6226447 iteration: 15225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18102 FastRCNN class loss: 0.1127 FastRCNN total loss: 0.29372 L1 loss: 0.0000e+00 L2 loss: 1.31221 Learning rate: 0.02 Mask loss: 0.21304 RPN box loss: 0.05968 RPN score loss: 0.02126 RPN total loss: 0.08094 Total loss: 1.89991 timestamp: 1654926916.8575175 iteration: 15230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.21475 L1 loss: 0.0000e+00 L2 loss: 1.31196 Learning rate: 0.02 Mask loss: 0.22387 RPN box loss: 0.02862 RPN score loss: 0.01493 RPN total loss: 0.04354 Total loss: 1.79413 timestamp: 1654926920.0358484 iteration: 15235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13576 FastRCNN class loss: 0.09556 FastRCNN total loss: 0.23132 L1 loss: 0.0000e+00 L2 loss: 1.31173 Learning rate: 0.02 Mask loss: 0.12963 RPN box loss: 0.0185 RPN score loss: 0.00878 RPN total loss: 0.02728 Total loss: 1.69996 timestamp: 1654926923.3814297 iteration: 15240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11701 FastRCNN class loss: 0.09117 FastRCNN total loss: 0.20818 L1 loss: 0.0000e+00 L2 loss: 1.31149 Learning rate: 0.02 Mask loss: 0.13571 RPN box loss: 0.04034 RPN score loss: 0.01754 RPN total loss: 0.05788 Total loss: 1.71325 timestamp: 1654926926.5874233 iteration: 15245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11369 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.19661 L1 loss: 0.0000e+00 L2 loss: 1.31127 Learning rate: 0.02 Mask loss: 0.14391 RPN box loss: 0.06429 RPN score loss: 0.00762 RPN total loss: 0.07191 Total loss: 1.7237 timestamp: 1654926929.8072348 iteration: 15250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14907 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.22583 L1 loss: 0.0000e+00 L2 loss: 1.31104 Learning rate: 0.02 Mask loss: 0.1793 RPN box loss: 0.03804 RPN score loss: 0.01317 RPN total loss: 0.05121 Total loss: 1.76738 timestamp: 1654926932.9949207 iteration: 15255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23242 FastRCNN class loss: 0.07745 FastRCNN total loss: 0.30986 L1 loss: 0.0000e+00 L2 loss: 1.31081 Learning rate: 0.02 Mask loss: 0.16442 RPN box loss: 0.00838 RPN score loss: 0.00529 RPN total loss: 0.01367 Total loss: 1.79877 timestamp: 1654926936.1689293 iteration: 15260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12797 FastRCNN class loss: 0.08042 FastRCNN total loss: 0.20839 L1 loss: 0.0000e+00 L2 loss: 1.31061 Learning rate: 0.02 Mask loss: 0.17276 RPN box loss: 0.0324 RPN score loss: 0.00511 RPN total loss: 0.03752 Total loss: 1.72928 timestamp: 1654926939.3025358 iteration: 15265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.15406 L1 loss: 0.0000e+00 L2 loss: 1.31038 Learning rate: 0.02 Mask loss: 0.10287 RPN box loss: 0.01148 RPN score loss: 0.00358 RPN total loss: 0.01506 Total loss: 1.58237 timestamp: 1654926942.5128312 iteration: 15270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10069 FastRCNN class loss: 0.08743 FastRCNN total loss: 0.18812 L1 loss: 0.0000e+00 L2 loss: 1.31016 Learning rate: 0.02 Mask loss: 0.23033 RPN box loss: 0.03975 RPN score loss: 0.00293 RPN total loss: 0.04267 Total loss: 1.77128 timestamp: 1654926945.767085 iteration: 15275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22181 FastRCNN class loss: 0.10207 FastRCNN total loss: 0.32388 L1 loss: 0.0000e+00 L2 loss: 1.30993 Learning rate: 0.02 Mask loss: 0.16529 RPN box loss: 0.04918 RPN score loss: 0.00774 RPN total loss: 0.05693 Total loss: 1.85602 timestamp: 1654926949.0838842 iteration: 15280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18206 FastRCNN class loss: 0.15253 FastRCNN total loss: 0.33459 L1 loss: 0.0000e+00 L2 loss: 1.30972 Learning rate: 0.02 Mask loss: 0.12406 RPN box loss: 0.04805 RPN score loss: 0.01736 RPN total loss: 0.06541 Total loss: 1.83378 timestamp: 1654926952.3044124 iteration: 15285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22965 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.29967 L1 loss: 0.0000e+00 L2 loss: 1.30949 Learning rate: 0.02 Mask loss: 0.12799 RPN box loss: 0.02301 RPN score loss: 0.00369 RPN total loss: 0.02669 Total loss: 1.76383 timestamp: 1654926955.5111573 iteration: 15290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20083 FastRCNN class loss: 0.05098 FastRCNN total loss: 0.25181 L1 loss: 0.0000e+00 L2 loss: 1.30924 Learning rate: 0.02 Mask loss: 0.10114 RPN box loss: 0.01757 RPN score loss: 0.00575 RPN total loss: 0.02333 Total loss: 1.68552 timestamp: 1654926958.7658353 iteration: 15295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.08448 FastRCNN total loss: 0.23575 L1 loss: 0.0000e+00 L2 loss: 1.30902 Learning rate: 0.02 Mask loss: 0.16201 RPN box loss: 0.04577 RPN score loss: 0.00436 RPN total loss: 0.05013 Total loss: 1.75691 timestamp: 1654926961.941165 iteration: 15300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12079 FastRCNN class loss: 0.06254 FastRCNN total loss: 0.18334 L1 loss: 0.0000e+00 L2 loss: 1.3088 Learning rate: 0.02 Mask loss: 0.16846 RPN box loss: 0.01852 RPN score loss: 0.0027 RPN total loss: 0.02122 Total loss: 1.68181 timestamp: 1654926965.1766105 iteration: 15305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16114 FastRCNN class loss: 0.10803 FastRCNN total loss: 0.26916 L1 loss: 0.0000e+00 L2 loss: 1.30859 Learning rate: 0.02 Mask loss: 0.25293 RPN box loss: 0.02375 RPN score loss: 0.01417 RPN total loss: 0.03791 Total loss: 1.86859 timestamp: 1654926968.4265778 iteration: 15310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08067 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.14205 L1 loss: 0.0000e+00 L2 loss: 1.30836 Learning rate: 0.02 Mask loss: 0.11745 RPN box loss: 0.00401 RPN score loss: 0.00234 RPN total loss: 0.00635 Total loss: 1.57421 timestamp: 1654926971.7495046 iteration: 15315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11327 FastRCNN class loss: 0.07041 FastRCNN total loss: 0.18368 L1 loss: 0.0000e+00 L2 loss: 1.30814 Learning rate: 0.02 Mask loss: 0.18636 RPN box loss: 0.0533 RPN score loss: 0.00432 RPN total loss: 0.05762 Total loss: 1.73581 timestamp: 1654926974.8898935 iteration: 15320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15678 FastRCNN class loss: 0.09257 FastRCNN total loss: 0.24935 L1 loss: 0.0000e+00 L2 loss: 1.30792 Learning rate: 0.02 Mask loss: 0.18228 RPN box loss: 0.03711 RPN score loss: 0.00292 RPN total loss: 0.04003 Total loss: 1.77959 timestamp: 1654926978.2057285 iteration: 15325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18555 FastRCNN class loss: 0.08349 FastRCNN total loss: 0.26904 L1 loss: 0.0000e+00 L2 loss: 1.3077 Learning rate: 0.02 Mask loss: 0.16164 RPN box loss: 0.06583 RPN score loss: 0.00761 RPN total loss: 0.07344 Total loss: 1.81183 timestamp: 1654926981.466586 iteration: 15330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21263 FastRCNN class loss: 0.13359 FastRCNN total loss: 0.34622 L1 loss: 0.0000e+00 L2 loss: 1.30746 Learning rate: 0.02 Mask loss: 0.21088 RPN box loss: 0.01285 RPN score loss: 0.00631 RPN total loss: 0.01915 Total loss: 1.88372 timestamp: 1654926984.8124895 iteration: 15335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12116 FastRCNN class loss: 0.0841 FastRCNN total loss: 0.20526 L1 loss: 0.0000e+00 L2 loss: 1.30723 Learning rate: 0.02 Mask loss: 0.16695 RPN box loss: 0.03122 RPN score loss: 0.00631 RPN total loss: 0.03753 Total loss: 1.71697 timestamp: 1654926988.0889752 iteration: 15340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1195 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 1.30702 Learning rate: 0.02 Mask loss: 0.12425 RPN box loss: 0.07987 RPN score loss: 0.01093 RPN total loss: 0.0908 Total loss: 1.71268 timestamp: 1654926991.2454257 iteration: 15345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09216 FastRCNN class loss: 0.05898 FastRCNN total loss: 0.15114 L1 loss: 0.0000e+00 L2 loss: 1.30678 Learning rate: 0.02 Mask loss: 0.15919 RPN box loss: 0.04422 RPN score loss: 0.00527 RPN total loss: 0.04949 Total loss: 1.66659 timestamp: 1654926994.4266813 iteration: 15350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12817 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.20178 L1 loss: 0.0000e+00 L2 loss: 1.30654 Learning rate: 0.02 Mask loss: 0.13967 RPN box loss: 0.03545 RPN score loss: 0.01189 RPN total loss: 0.04733 Total loss: 1.69532 timestamp: 1654926997.6815553 iteration: 15355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17874 FastRCNN class loss: 0.11343 FastRCNN total loss: 0.29217 L1 loss: 0.0000e+00 L2 loss: 1.30629 Learning rate: 0.02 Mask loss: 0.22344 RPN box loss: 0.04021 RPN score loss: 0.02494 RPN total loss: 0.06515 Total loss: 1.88706 timestamp: 1654927000.9636137 iteration: 15360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18849 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.25483 L1 loss: 0.0000e+00 L2 loss: 1.30606 Learning rate: 0.02 Mask loss: 0.17519 RPN box loss: 0.04332 RPN score loss: 0.00246 RPN total loss: 0.04579 Total loss: 1.78187 timestamp: 1654927004.1234624 iteration: 15365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08611 FastRCNN class loss: 0.04657 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 1.30585 Learning rate: 0.02 Mask loss: 0.16179 RPN box loss: 0.01916 RPN score loss: 0.00774 RPN total loss: 0.02689 Total loss: 1.62721 timestamp: 1654927007.4300904 iteration: 15370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14009 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.21515 L1 loss: 0.0000e+00 L2 loss: 1.30563 Learning rate: 0.02 Mask loss: 0.15617 RPN box loss: 0.02826 RPN score loss: 0.00733 RPN total loss: 0.03559 Total loss: 1.71254 timestamp: 1654927010.5795085 iteration: 15375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18368 FastRCNN class loss: 0.09383 FastRCNN total loss: 0.27751 L1 loss: 0.0000e+00 L2 loss: 1.3054 Learning rate: 0.02 Mask loss: 0.25013 RPN box loss: 0.05864 RPN score loss: 0.01201 RPN total loss: 0.07065 Total loss: 1.9037 timestamp: 1654927013.8455245 iteration: 15380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25179 FastRCNN class loss: 0.09153 FastRCNN total loss: 0.34332 L1 loss: 0.0000e+00 L2 loss: 1.30518 Learning rate: 0.02 Mask loss: 0.15849 RPN box loss: 0.05695 RPN score loss: 0.01144 RPN total loss: 0.06839 Total loss: 1.87538 timestamp: 1654927017.0471203 iteration: 15385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1307 FastRCNN class loss: 0.08005 FastRCNN total loss: 0.21075 L1 loss: 0.0000e+00 L2 loss: 1.30498 Learning rate: 0.02 Mask loss: 0.11537 RPN box loss: 0.0465 RPN score loss: 0.00345 RPN total loss: 0.04995 Total loss: 1.68106 timestamp: 1654927020.3246548 iteration: 15390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14296 FastRCNN class loss: 0.12577 FastRCNN total loss: 0.26873 L1 loss: 0.0000e+00 L2 loss: 1.30474 Learning rate: 0.02 Mask loss: 0.16217 RPN box loss: 0.06753 RPN score loss: 0.01308 RPN total loss: 0.08061 Total loss: 1.81625 timestamp: 1654927023.5862749 iteration: 15395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09474 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.13926 L1 loss: 0.0000e+00 L2 loss: 1.30452 Learning rate: 0.02 Mask loss: 0.12961 RPN box loss: 0.05044 RPN score loss: 0.00372 RPN total loss: 0.05416 Total loss: 1.62755 timestamp: 1654927026.8116996 iteration: 15400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1478 FastRCNN class loss: 0.06366 FastRCNN total loss: 0.21146 L1 loss: 0.0000e+00 L2 loss: 1.30432 Learning rate: 0.02 Mask loss: 0.17965 RPN box loss: 0.02139 RPN score loss: 0.0035 RPN total loss: 0.02488 Total loss: 1.72032 timestamp: 1654927030.049882 iteration: 15405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10146 FastRCNN class loss: 0.11358 FastRCNN total loss: 0.21503 L1 loss: 0.0000e+00 L2 loss: 1.30409 Learning rate: 0.02 Mask loss: 0.12683 RPN box loss: 0.02383 RPN score loss: 0.00361 RPN total loss: 0.02744 Total loss: 1.6734 timestamp: 1654927033.238859 iteration: 15410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17508 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.23092 L1 loss: 0.0000e+00 L2 loss: 1.30385 Learning rate: 0.02 Mask loss: 0.1436 RPN box loss: 0.01492 RPN score loss: 0.0027 RPN total loss: 0.01762 Total loss: 1.69599 timestamp: 1654927036.4623995 iteration: 15415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16562 FastRCNN class loss: 0.07312 FastRCNN total loss: 0.23874 L1 loss: 0.0000e+00 L2 loss: 1.30365 Learning rate: 0.02 Mask loss: 0.18907 RPN box loss: 0.05456 RPN score loss: 0.00328 RPN total loss: 0.05783 Total loss: 1.78929 timestamp: 1654927039.6359794 iteration: 15420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09758 FastRCNN class loss: 0.04265 FastRCNN total loss: 0.14023 L1 loss: 0.0000e+00 L2 loss: 1.30343 Learning rate: 0.02 Mask loss: 0.09578 RPN box loss: 0.0268 RPN score loss: 0.00808 RPN total loss: 0.03488 Total loss: 1.57432 timestamp: 1654927042.907346 iteration: 15425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10459 FastRCNN class loss: 0.07731 FastRCNN total loss: 0.1819 L1 loss: 0.0000e+00 L2 loss: 1.30319 Learning rate: 0.02 Mask loss: 0.16783 RPN box loss: 0.03844 RPN score loss: 0.0321 RPN total loss: 0.07054 Total loss: 1.72347 timestamp: 1654927046.2017388 iteration: 15430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10489 FastRCNN class loss: 0.05203 FastRCNN total loss: 0.15692 L1 loss: 0.0000e+00 L2 loss: 1.30295 Learning rate: 0.02 Mask loss: 0.13023 RPN box loss: 0.02293 RPN score loss: 0.0054 RPN total loss: 0.02834 Total loss: 1.61844 timestamp: 1654927049.5448065 iteration: 15435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10083 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.17647 L1 loss: 0.0000e+00 L2 loss: 1.30273 Learning rate: 0.02 Mask loss: 0.12222 RPN box loss: 0.03788 RPN score loss: 0.00637 RPN total loss: 0.04425 Total loss: 1.64567 timestamp: 1654927052.7750251 iteration: 15440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.0973 FastRCNN total loss: 0.24075 L1 loss: 0.0000e+00 L2 loss: 1.30252 Learning rate: 0.02 Mask loss: 0.20487 RPN box loss: 0.06371 RPN score loss: 0.01838 RPN total loss: 0.08209 Total loss: 1.83023 timestamp: 1654927056.0986485 iteration: 15445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11213 FastRCNN class loss: 0.05565 FastRCNN total loss: 0.16778 L1 loss: 0.0000e+00 L2 loss: 1.3023 Learning rate: 0.02 Mask loss: 0.15301 RPN box loss: 0.01523 RPN score loss: 0.0019 RPN total loss: 0.01714 Total loss: 1.64023 timestamp: 1654927059.38574 iteration: 15450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13436 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.19794 L1 loss: 0.0000e+00 L2 loss: 1.30209 Learning rate: 0.02 Mask loss: 0.13297 RPN box loss: 0.00991 RPN score loss: 0.0018 RPN total loss: 0.01171 Total loss: 1.6447 timestamp: 1654927062.5609524 iteration: 15455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15678 FastRCNN class loss: 0.07078 FastRCNN total loss: 0.22757 L1 loss: 0.0000e+00 L2 loss: 1.30185 Learning rate: 0.02 Mask loss: 0.14943 RPN box loss: 0.05392 RPN score loss: 0.02049 RPN total loss: 0.0744 Total loss: 1.75325 timestamp: 1654927065.7851472 iteration: 15460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18136 FastRCNN class loss: 0.07027 FastRCNN total loss: 0.25163 L1 loss: 0.0000e+00 L2 loss: 1.30162 Learning rate: 0.02 Mask loss: 0.11029 RPN box loss: 0.03107 RPN score loss: 0.00455 RPN total loss: 0.03562 Total loss: 1.69915 timestamp: 1654927069.0302866 iteration: 15465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12065 FastRCNN class loss: 0.11603 FastRCNN total loss: 0.23668 L1 loss: 0.0000e+00 L2 loss: 1.30141 Learning rate: 0.02 Mask loss: 0.19911 RPN box loss: 0.04726 RPN score loss: 0.00654 RPN total loss: 0.0538 Total loss: 1.791 timestamp: 1654927072.2533925 iteration: 15470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18414 FastRCNN class loss: 0.10066 FastRCNN total loss: 0.2848 L1 loss: 0.0000e+00 L2 loss: 1.30118 Learning rate: 0.02 Mask loss: 0.1635 RPN box loss: 0.02218 RPN score loss: 0.00659 RPN total loss: 0.02877 Total loss: 1.77825 timestamp: 1654927075.4761677 iteration: 15475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13531 FastRCNN class loss: 0.05744 FastRCNN total loss: 0.19275 L1 loss: 0.0000e+00 L2 loss: 1.30096 Learning rate: 0.02 Mask loss: 0.14058 RPN box loss: 0.04387 RPN score loss: 0.00748 RPN total loss: 0.05135 Total loss: 1.68564 timestamp: 1654927078.8308408 iteration: 15480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09102 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.14256 L1 loss: 0.0000e+00 L2 loss: 1.30074 Learning rate: 0.02 Mask loss: 0.13325 RPN box loss: 0.04403 RPN score loss: 0.00124 RPN total loss: 0.04527 Total loss: 1.62182 timestamp: 1654927082.045724 iteration: 15485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12552 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.20881 L1 loss: 0.0000e+00 L2 loss: 1.30051 Learning rate: 0.02 Mask loss: 0.21764 RPN box loss: 0.01281 RPN score loss: 0.0024 RPN total loss: 0.01521 Total loss: 1.74217 timestamp: 1654927085.3000345 iteration: 15490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20598 FastRCNN class loss: 0.15311 FastRCNN total loss: 0.3591 L1 loss: 0.0000e+00 L2 loss: 1.3003 Learning rate: 0.02 Mask loss: 0.16254 RPN box loss: 0.05275 RPN score loss: 0.00763 RPN total loss: 0.06038 Total loss: 1.88232 timestamp: 1654927088.4789457 iteration: 15495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19196 FastRCNN class loss: 0.12372 FastRCNN total loss: 0.31568 L1 loss: 0.0000e+00 L2 loss: 1.30006 Learning rate: 0.02 Mask loss: 0.20551 RPN box loss: 0.06251 RPN score loss: 0.01452 RPN total loss: 0.07703 Total loss: 1.89828 timestamp: 1654927091.8102326 iteration: 15500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09935 FastRCNN class loss: 0.03962 FastRCNN total loss: 0.13897 L1 loss: 0.0000e+00 L2 loss: 1.29984 Learning rate: 0.02 Mask loss: 0.10451 RPN box loss: 0.01847 RPN score loss: 0.00465 RPN total loss: 0.02312 Total loss: 1.56643 timestamp: 1654927095.0428348 iteration: 15505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08604 FastRCNN class loss: 0.05926 FastRCNN total loss: 0.1453 L1 loss: 0.0000e+00 L2 loss: 1.29962 Learning rate: 0.02 Mask loss: 0.15736 RPN box loss: 0.01797 RPN score loss: 0.00212 RPN total loss: 0.02009 Total loss: 1.62236 timestamp: 1654927098.309563 iteration: 15510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18555 FastRCNN class loss: 0.13398 FastRCNN total loss: 0.31953 L1 loss: 0.0000e+00 L2 loss: 1.29937 Learning rate: 0.02 Mask loss: 0.25047 RPN box loss: 0.04852 RPN score loss: 0.00914 RPN total loss: 0.05767 Total loss: 1.92704 timestamp: 1654927101.4982042 iteration: 15515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13209 FastRCNN class loss: 0.10916 FastRCNN total loss: 0.24125 L1 loss: 0.0000e+00 L2 loss: 1.29915 Learning rate: 0.02 Mask loss: 0.22993 RPN box loss: 0.05922 RPN score loss: 0.01364 RPN total loss: 0.07286 Total loss: 1.84319 timestamp: 1654927104.8193805 iteration: 15520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14223 FastRCNN class loss: 0.10491 FastRCNN total loss: 0.24714 L1 loss: 0.0000e+00 L2 loss: 1.29893 Learning rate: 0.02 Mask loss: 0.19616 RPN box loss: 0.03467 RPN score loss: 0.01908 RPN total loss: 0.05375 Total loss: 1.79598 timestamp: 1654927108.0258527 iteration: 15525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19345 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.28158 L1 loss: 0.0000e+00 L2 loss: 1.2987 Learning rate: 0.02 Mask loss: 0.12211 RPN box loss: 0.02517 RPN score loss: 0.01094 RPN total loss: 0.03611 Total loss: 1.7385 timestamp: 1654927111.332906 iteration: 15530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16742 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.25554 L1 loss: 0.0000e+00 L2 loss: 1.29848 Learning rate: 0.02 Mask loss: 0.23382 RPN box loss: 0.0371 RPN score loss: 0.00471 RPN total loss: 0.04181 Total loss: 1.82965 timestamp: 1654927114.6293244 iteration: 15535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17778 FastRCNN class loss: 0.13506 FastRCNN total loss: 0.31284 L1 loss: 0.0000e+00 L2 loss: 1.29827 Learning rate: 0.02 Mask loss: 0.21023 RPN box loss: 0.06109 RPN score loss: 0.01902 RPN total loss: 0.0801 Total loss: 1.90144 timestamp: 1654927117.9148653 iteration: 15540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21115 FastRCNN class loss: 0.13524 FastRCNN total loss: 0.3464 L1 loss: 0.0000e+00 L2 loss: 1.29806 Learning rate: 0.02 Mask loss: 0.1602 RPN box loss: 0.04679 RPN score loss: 0.01011 RPN total loss: 0.05689 Total loss: 1.86154 timestamp: 1654927121.2340539 iteration: 15545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26511 FastRCNN class loss: 0.14816 FastRCNN total loss: 0.41327 L1 loss: 0.0000e+00 L2 loss: 1.29784 Learning rate: 0.02 Mask loss: 0.25651 RPN box loss: 0.04078 RPN score loss: 0.00963 RPN total loss: 0.05041 Total loss: 2.01803 timestamp: 1654927124.4937303 iteration: 15550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12232 FastRCNN class loss: 0.06501 FastRCNN total loss: 0.18732 L1 loss: 0.0000e+00 L2 loss: 1.2976 Learning rate: 0.02 Mask loss: 0.09558 RPN box loss: 0.06762 RPN score loss: 0.00266 RPN total loss: 0.07028 Total loss: 1.65078 timestamp: 1654927127.9076831 iteration: 15555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19876 FastRCNN class loss: 0.15572 FastRCNN total loss: 0.35449 L1 loss: 0.0000e+00 L2 loss: 1.29737 Learning rate: 0.02 Mask loss: 0.28976 RPN box loss: 0.06735 RPN score loss: 0.01737 RPN total loss: 0.08471 Total loss: 2.02633 timestamp: 1654927131.1661084 iteration: 15560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10129 FastRCNN class loss: 0.05525 FastRCNN total loss: 0.15654 L1 loss: 0.0000e+00 L2 loss: 1.29716 Learning rate: 0.02 Mask loss: 0.11223 RPN box loss: 0.04598 RPN score loss: 0.00702 RPN total loss: 0.053 Total loss: 1.61893 timestamp: 1654927134.3867018 iteration: 15565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16721 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.24913 L1 loss: 0.0000e+00 L2 loss: 1.29694 Learning rate: 0.02 Mask loss: 0.1618 RPN box loss: 0.03877 RPN score loss: 0.00514 RPN total loss: 0.0439 Total loss: 1.75177 timestamp: 1654927137.72097 iteration: 15570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10379 FastRCNN class loss: 0.07286 FastRCNN total loss: 0.17665 L1 loss: 0.0000e+00 L2 loss: 1.29673 Learning rate: 0.02 Mask loss: 0.17764 RPN box loss: 0.03892 RPN score loss: 0.01355 RPN total loss: 0.05246 Total loss: 1.70348 timestamp: 1654927140.9627023 iteration: 15575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23375 FastRCNN class loss: 0.1686 FastRCNN total loss: 0.40235 L1 loss: 0.0000e+00 L2 loss: 1.2965 Learning rate: 0.02 Mask loss: 0.14997 RPN box loss: 0.03841 RPN score loss: 0.00474 RPN total loss: 0.04314 Total loss: 1.89196 timestamp: 1654927144.2642705 iteration: 15580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.14092 FastRCNN total loss: 0.24624 L1 loss: 0.0000e+00 L2 loss: 1.29626 Learning rate: 0.02 Mask loss: 0.13675 RPN box loss: 0.05428 RPN score loss: 0.00694 RPN total loss: 0.06122 Total loss: 1.74047 timestamp: 1654927147.5281765 iteration: 15585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12244 FastRCNN class loss: 0.06132 FastRCNN total loss: 0.18376 L1 loss: 0.0000e+00 L2 loss: 1.29603 Learning rate: 0.02 Mask loss: 0.11881 RPN box loss: 0.01355 RPN score loss: 0.00594 RPN total loss: 0.01949 Total loss: 1.61808 timestamp: 1654927150.779181 iteration: 15590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15134 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.24073 L1 loss: 0.0000e+00 L2 loss: 1.29583 Learning rate: 0.02 Mask loss: 0.16754 RPN box loss: 0.05166 RPN score loss: 0.01338 RPN total loss: 0.06504 Total loss: 1.76914 timestamp: 1654927153.9778728 iteration: 15595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11921 FastRCNN class loss: 0.08604 FastRCNN total loss: 0.20525 L1 loss: 0.0000e+00 L2 loss: 1.29561 Learning rate: 0.02 Mask loss: 0.13241 RPN box loss: 0.06195 RPN score loss: 0.01411 RPN total loss: 0.07605 Total loss: 1.70932 timestamp: 1654927157.2346132 iteration: 15600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15003 FastRCNN class loss: 0.12473 FastRCNN total loss: 0.27475 L1 loss: 0.0000e+00 L2 loss: 1.29538 Learning rate: 0.02 Mask loss: 0.16172 RPN box loss: 0.07314 RPN score loss: 0.00868 RPN total loss: 0.08182 Total loss: 1.81367 timestamp: 1654927160.4971833 iteration: 15605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08407 FastRCNN class loss: 0.04638 FastRCNN total loss: 0.13045 L1 loss: 0.0000e+00 L2 loss: 1.29518 Learning rate: 0.02 Mask loss: 0.12243 RPN box loss: 0.00942 RPN score loss: 0.00325 RPN total loss: 0.01266 Total loss: 1.56073 timestamp: 1654927163.760001 iteration: 15610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11461 FastRCNN class loss: 0.10493 FastRCNN total loss: 0.21954 L1 loss: 0.0000e+00 L2 loss: 1.29495 Learning rate: 0.02 Mask loss: 0.19294 RPN box loss: 0.03445 RPN score loss: 0.00659 RPN total loss: 0.04104 Total loss: 1.74847 timestamp: 1654927167.0473547 iteration: 15615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16058 FastRCNN class loss: 0.07773 FastRCNN total loss: 0.23831 L1 loss: 0.0000e+00 L2 loss: 1.29471 Learning rate: 0.02 Mask loss: 0.25546 RPN box loss: 0.03191 RPN score loss: 0.00786 RPN total loss: 0.03976 Total loss: 1.82824 timestamp: 1654927170.1906998 iteration: 15620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14129 FastRCNN class loss: 0.0685 FastRCNN total loss: 0.20979 L1 loss: 0.0000e+00 L2 loss: 1.29449 Learning rate: 0.02 Mask loss: 0.16414 RPN box loss: 0.0709 RPN score loss: 0.0044 RPN total loss: 0.07529 Total loss: 1.74372 timestamp: 1654927173.423476 iteration: 15625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18976 FastRCNN class loss: 0.10412 FastRCNN total loss: 0.29388 L1 loss: 0.0000e+00 L2 loss: 1.29426 Learning rate: 0.02 Mask loss: 0.15915 RPN box loss: 0.05024 RPN score loss: 0.0031 RPN total loss: 0.05334 Total loss: 1.80062 timestamp: 1654927176.6028147 iteration: 15630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15155 FastRCNN class loss: 0.10018 FastRCNN total loss: 0.25173 L1 loss: 0.0000e+00 L2 loss: 1.29402 Learning rate: 0.02 Mask loss: 0.14892 RPN box loss: 0.02146 RPN score loss: 0.00885 RPN total loss: 0.03031 Total loss: 1.72498 timestamp: 1654927179.9107077 iteration: 15635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25442 FastRCNN class loss: 0.08564 FastRCNN total loss: 0.34007 L1 loss: 0.0000e+00 L2 loss: 1.2938 Learning rate: 0.02 Mask loss: 0.21654 RPN box loss: 0.03184 RPN score loss: 0.00571 RPN total loss: 0.03755 Total loss: 1.88797 timestamp: 1654927183.1354554 iteration: 15640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10041 FastRCNN class loss: 0.08221 FastRCNN total loss: 0.18262 L1 loss: 0.0000e+00 L2 loss: 1.29357 Learning rate: 0.02 Mask loss: 0.13338 RPN box loss: 0.0073 RPN score loss: 0.00234 RPN total loss: 0.00965 Total loss: 1.61922 timestamp: 1654927186.4192727 iteration: 15645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10345 FastRCNN class loss: 0.03843 FastRCNN total loss: 0.14188 L1 loss: 0.0000e+00 L2 loss: 1.29335 Learning rate: 0.02 Mask loss: 0.13735 RPN box loss: 0.01936 RPN score loss: 0.00275 RPN total loss: 0.02211 Total loss: 1.59469 timestamp: 1654927189.5824282 iteration: 15650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13382 FastRCNN class loss: 0.05972 FastRCNN total loss: 0.19354 L1 loss: 0.0000e+00 L2 loss: 1.29314 Learning rate: 0.02 Mask loss: 0.18131 RPN box loss: 0.03207 RPN score loss: 0.0052 RPN total loss: 0.03727 Total loss: 1.70526 timestamp: 1654927192.806477 iteration: 15655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22597 FastRCNN class loss: 0.14312 FastRCNN total loss: 0.36909 L1 loss: 0.0000e+00 L2 loss: 1.29291 Learning rate: 0.02 Mask loss: 0.21472 RPN box loss: 0.02917 RPN score loss: 0.00539 RPN total loss: 0.03456 Total loss: 1.91128 timestamp: 1654927196.0081596 iteration: 15660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15035 FastRCNN class loss: 0.10096 FastRCNN total loss: 0.25132 L1 loss: 0.0000e+00 L2 loss: 1.29271 Learning rate: 0.02 Mask loss: 0.13176 RPN box loss: 0.05007 RPN score loss: 0.00937 RPN total loss: 0.05944 Total loss: 1.73522 timestamp: 1654927199.330837 iteration: 15665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15649 FastRCNN class loss: 0.09268 FastRCNN total loss: 0.24917 L1 loss: 0.0000e+00 L2 loss: 1.29248 Learning rate: 0.02 Mask loss: 0.15884 RPN box loss: 0.06205 RPN score loss: 0.02398 RPN total loss: 0.08604 Total loss: 1.78652 timestamp: 1654927202.6562939 iteration: 15670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12528 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.18113 L1 loss: 0.0000e+00 L2 loss: 1.29225 Learning rate: 0.02 Mask loss: 0.10993 RPN box loss: 0.03962 RPN score loss: 0.0039 RPN total loss: 0.04353 Total loss: 1.62684 timestamp: 1654927205.8230927 iteration: 15675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04655 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.11652 L1 loss: 0.0000e+00 L2 loss: 1.29203 Learning rate: 0.02 Mask loss: 0.16023 RPN box loss: 0.00918 RPN score loss: 0.00673 RPN total loss: 0.01592 Total loss: 1.5847 timestamp: 1654927209.080299 iteration: 15680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.205 FastRCNN class loss: 0.12669 FastRCNN total loss: 0.33169 L1 loss: 0.0000e+00 L2 loss: 1.2918 Learning rate: 0.02 Mask loss: 0.21303 RPN box loss: 0.04032 RPN score loss: 0.01207 RPN total loss: 0.05239 Total loss: 1.88892 timestamp: 1654927212.230141 iteration: 15685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21608 FastRCNN class loss: 0.12709 FastRCNN total loss: 0.34317 L1 loss: 0.0000e+00 L2 loss: 1.29157 Learning rate: 0.02 Mask loss: 0.17842 RPN box loss: 0.03781 RPN score loss: 0.00713 RPN total loss: 0.04494 Total loss: 1.85809 timestamp: 1654927215.5243447 iteration: 15690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14661 FastRCNN class loss: 0.11236 FastRCNN total loss: 0.25897 L1 loss: 0.0000e+00 L2 loss: 1.29135 Learning rate: 0.02 Mask loss: 0.14228 RPN box loss: 0.02999 RPN score loss: 0.00551 RPN total loss: 0.0355 Total loss: 1.72809 timestamp: 1654927218.7525513 iteration: 15695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13874 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.22091 L1 loss: 0.0000e+00 L2 loss: 1.29111 Learning rate: 0.02 Mask loss: 0.12315 RPN box loss: 0.03056 RPN score loss: 0.00969 RPN total loss: 0.04025 Total loss: 1.67542 timestamp: 1654927221.9733787 iteration: 15700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22968 FastRCNN class loss: 0.10911 FastRCNN total loss: 0.33879 L1 loss: 0.0000e+00 L2 loss: 1.2909 Learning rate: 0.02 Mask loss: 0.23771 RPN box loss: 0.01177 RPN score loss: 0.01102 RPN total loss: 0.02279 Total loss: 1.8902 timestamp: 1654927225.1414566 iteration: 15705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07293 FastRCNN class loss: 0.06466 FastRCNN total loss: 0.13759 L1 loss: 0.0000e+00 L2 loss: 1.29068 Learning rate: 0.02 Mask loss: 0.1758 RPN box loss: 0.00671 RPN score loss: 0.005 RPN total loss: 0.01171 Total loss: 1.61577 timestamp: 1654927228.401308 iteration: 15710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15208 FastRCNN class loss: 0.08908 FastRCNN total loss: 0.24117 L1 loss: 0.0000e+00 L2 loss: 1.29047 Learning rate: 0.02 Mask loss: 0.24079 RPN box loss: 0.0437 RPN score loss: 0.01513 RPN total loss: 0.05883 Total loss: 1.83126 timestamp: 1654927231.591224 iteration: 15715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15015 FastRCNN class loss: 0.08393 FastRCNN total loss: 0.23407 L1 loss: 0.0000e+00 L2 loss: 1.29025 Learning rate: 0.02 Mask loss: 0.1685 RPN box loss: 0.04155 RPN score loss: 0.00452 RPN total loss: 0.04607 Total loss: 1.73889 timestamp: 1654927234.933877 iteration: 15720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12103 FastRCNN class loss: 0.04968 FastRCNN total loss: 0.17071 L1 loss: 0.0000e+00 L2 loss: 1.29007 Learning rate: 0.02 Mask loss: 0.10892 RPN box loss: 0.01862 RPN score loss: 0.00087 RPN total loss: 0.01948 Total loss: 1.58919 timestamp: 1654927238.1556118 iteration: 15725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11505 FastRCNN class loss: 0.04855 FastRCNN total loss: 0.1636 L1 loss: 0.0000e+00 L2 loss: 1.28988 Learning rate: 0.02 Mask loss: 0.12644 RPN box loss: 0.02358 RPN score loss: 0.00377 RPN total loss: 0.02735 Total loss: 1.60727 timestamp: 1654927241.48434 iteration: 15730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15935 FastRCNN class loss: 0.1047 FastRCNN total loss: 0.26405 L1 loss: 0.0000e+00 L2 loss: 1.28968 Learning rate: 0.02 Mask loss: 0.15381 RPN box loss: 0.02386 RPN score loss: 0.00458 RPN total loss: 0.02844 Total loss: 1.73598 timestamp: 1654927244.7651813 iteration: 15735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08651 FastRCNN class loss: 0.04707 FastRCNN total loss: 0.13357 L1 loss: 0.0000e+00 L2 loss: 1.28943 Learning rate: 0.02 Mask loss: 0.13688 RPN box loss: 0.07882 RPN score loss: 0.0027 RPN total loss: 0.08152 Total loss: 1.6414 timestamp: 1654927247.981563 iteration: 15740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14519 FastRCNN class loss: 0.08418 FastRCNN total loss: 0.22936 L1 loss: 0.0000e+00 L2 loss: 1.28918 Learning rate: 0.02 Mask loss: 0.1915 RPN box loss: 0.05463 RPN score loss: 0.02025 RPN total loss: 0.07488 Total loss: 1.78492 timestamp: 1654927251.3294525 iteration: 15745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18763 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.26986 L1 loss: 0.0000e+00 L2 loss: 1.28892 Learning rate: 0.02 Mask loss: 0.26678 RPN box loss: 0.02387 RPN score loss: 0.00614 RPN total loss: 0.03001 Total loss: 1.85557 timestamp: 1654927254.5302033 iteration: 15750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13272 FastRCNN class loss: 0.09613 FastRCNN total loss: 0.22885 L1 loss: 0.0000e+00 L2 loss: 1.28868 Learning rate: 0.02 Mask loss: 0.17398 RPN box loss: 0.03978 RPN score loss: 0.00872 RPN total loss: 0.0485 Total loss: 1.74002 timestamp: 1654927257.8482249 iteration: 15755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12078 FastRCNN class loss: 0.10465 FastRCNN total loss: 0.22543 L1 loss: 0.0000e+00 L2 loss: 1.28848 Learning rate: 0.02 Mask loss: 0.12869 RPN box loss: 0.01796 RPN score loss: 0.00615 RPN total loss: 0.02411 Total loss: 1.66671 timestamp: 1654927261.06139 iteration: 15760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14067 FastRCNN class loss: 0.08296 FastRCNN total loss: 0.22362 L1 loss: 0.0000e+00 L2 loss: 1.2883 Learning rate: 0.02 Mask loss: 0.18171 RPN box loss: 0.04904 RPN score loss: 0.01044 RPN total loss: 0.05948 Total loss: 1.75311 timestamp: 1654927264.323975 iteration: 15765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15466 FastRCNN class loss: 0.08059 FastRCNN total loss: 0.23525 L1 loss: 0.0000e+00 L2 loss: 1.28807 Learning rate: 0.02 Mask loss: 0.19294 RPN box loss: 0.01532 RPN score loss: 0.0059 RPN total loss: 0.02122 Total loss: 1.73749 timestamp: 1654927267.60106 iteration: 15770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15616 FastRCNN class loss: 0.11688 FastRCNN total loss: 0.27304 L1 loss: 0.0000e+00 L2 loss: 1.28788 Learning rate: 0.02 Mask loss: 0.21885 RPN box loss: 0.04988 RPN score loss: 0.01085 RPN total loss: 0.06072 Total loss: 1.84049 timestamp: 1654927270.8764443 iteration: 15775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1043 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.17605 L1 loss: 0.0000e+00 L2 loss: 1.28766 Learning rate: 0.02 Mask loss: 0.2015 RPN box loss: 0.02086 RPN score loss: 0.00854 RPN total loss: 0.0294 Total loss: 1.69462 timestamp: 1654927274.1944551 iteration: 15780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13091 FastRCNN class loss: 0.11339 FastRCNN total loss: 0.2443 L1 loss: 0.0000e+00 L2 loss: 1.28743 Learning rate: 0.02 Mask loss: 0.13043 RPN box loss: 0.02124 RPN score loss: 0.00342 RPN total loss: 0.02466 Total loss: 1.68682 timestamp: 1654927277.422663 iteration: 15785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11632 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.19035 L1 loss: 0.0000e+00 L2 loss: 1.28721 Learning rate: 0.02 Mask loss: 0.18152 RPN box loss: 0.02148 RPN score loss: 0.00614 RPN total loss: 0.02762 Total loss: 1.6867 timestamp: 1654927280.7538333 iteration: 15790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18546 FastRCNN class loss: 0.06024 FastRCNN total loss: 0.2457 L1 loss: 0.0000e+00 L2 loss: 1.28698 Learning rate: 0.02 Mask loss: 0.15071 RPN box loss: 0.03468 RPN score loss: 0.01048 RPN total loss: 0.04516 Total loss: 1.72855 timestamp: 1654927284.0255127 iteration: 15795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.15594 L1 loss: 0.0000e+00 L2 loss: 1.28674 Learning rate: 0.02 Mask loss: 0.16689 RPN box loss: 0.03342 RPN score loss: 0.00274 RPN total loss: 0.03616 Total loss: 1.64574 timestamp: 1654927287.4190009 iteration: 15800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24608 FastRCNN class loss: 0.10936 FastRCNN total loss: 0.35544 L1 loss: 0.0000e+00 L2 loss: 1.28651 Learning rate: 0.02 Mask loss: 0.25626 RPN box loss: 0.04255 RPN score loss: 0.00892 RPN total loss: 0.05147 Total loss: 1.94968 timestamp: 1654927290.6225028 iteration: 15805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13728 FastRCNN class loss: 0.10299 FastRCNN total loss: 0.24026 L1 loss: 0.0000e+00 L2 loss: 1.2863 Learning rate: 0.02 Mask loss: 0.15408 RPN box loss: 0.05803 RPN score loss: 0.0064 RPN total loss: 0.06443 Total loss: 1.74508 timestamp: 1654927293.9925983 iteration: 15810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15233 FastRCNN class loss: 0.1154 FastRCNN total loss: 0.26773 L1 loss: 0.0000e+00 L2 loss: 1.2861 Learning rate: 0.02 Mask loss: 0.19627 RPN box loss: 0.0586 RPN score loss: 0.01886 RPN total loss: 0.07745 Total loss: 1.82755 timestamp: 1654927297.2206492 iteration: 15815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13926 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.22516 L1 loss: 0.0000e+00 L2 loss: 1.28589 Learning rate: 0.02 Mask loss: 0.22277 RPN box loss: 0.03303 RPN score loss: 0.01488 RPN total loss: 0.04791 Total loss: 1.78172 timestamp: 1654927300.4447925 iteration: 15820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18591 FastRCNN class loss: 0.1029 FastRCNN total loss: 0.28881 L1 loss: 0.0000e+00 L2 loss: 1.28569 Learning rate: 0.02 Mask loss: 0.18739 RPN box loss: 0.01202 RPN score loss: 0.00347 RPN total loss: 0.01548 Total loss: 1.77737 timestamp: 1654927303.6302392 iteration: 15825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08741 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.14517 L1 loss: 0.0000e+00 L2 loss: 1.28549 Learning rate: 0.02 Mask loss: 0.14608 RPN box loss: 0.01798 RPN score loss: 0.00243 RPN total loss: 0.02042 Total loss: 1.59716 timestamp: 1654927306.9763844 iteration: 15830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13814 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.21064 L1 loss: 0.0000e+00 L2 loss: 1.28528 Learning rate: 0.02 Mask loss: 0.16471 RPN box loss: 0.06169 RPN score loss: 0.00541 RPN total loss: 0.0671 Total loss: 1.72773 timestamp: 1654927310.3279128 iteration: 15835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15377 FastRCNN class loss: 0.07712 FastRCNN total loss: 0.23089 L1 loss: 0.0000e+00 L2 loss: 1.28507 Learning rate: 0.02 Mask loss: 0.15954 RPN box loss: 0.04314 RPN score loss: 0.00171 RPN total loss: 0.04485 Total loss: 1.72035 timestamp: 1654927313.544569 iteration: 15840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12479 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.19122 L1 loss: 0.0000e+00 L2 loss: 1.28485 Learning rate: 0.02 Mask loss: 0.31131 RPN box loss: 0.06086 RPN score loss: 0.01382 RPN total loss: 0.07468 Total loss: 1.86206 timestamp: 1654927316.9449537 iteration: 15845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11499 FastRCNN class loss: 0.08689 FastRCNN total loss: 0.20189 L1 loss: 0.0000e+00 L2 loss: 1.28462 Learning rate: 0.02 Mask loss: 0.14628 RPN box loss: 0.04471 RPN score loss: 0.00483 RPN total loss: 0.04953 Total loss: 1.68233 timestamp: 1654927320.0829628 iteration: 15850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15563 FastRCNN class loss: 0.15366 FastRCNN total loss: 0.30928 L1 loss: 0.0000e+00 L2 loss: 1.28443 Learning rate: 0.02 Mask loss: 0.2217 RPN box loss: 0.09126 RPN score loss: 0.01158 RPN total loss: 0.10285 Total loss: 1.91826 timestamp: 1654927323.4088726 iteration: 15855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16299 FastRCNN class loss: 0.10518 FastRCNN total loss: 0.26818 L1 loss: 0.0000e+00 L2 loss: 1.2842 Learning rate: 0.02 Mask loss: 0.28007 RPN box loss: 0.02017 RPN score loss: 0.01346 RPN total loss: 0.03363 Total loss: 1.86608 timestamp: 1654927326.6613154 iteration: 15860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17076 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.23013 L1 loss: 0.0000e+00 L2 loss: 1.28396 Learning rate: 0.02 Mask loss: 0.14456 RPN box loss: 0.01256 RPN score loss: 0.00213 RPN total loss: 0.01469 Total loss: 1.67334 timestamp: 1654927329.8698063 iteration: 15865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09917 FastRCNN class loss: 0.05328 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 1.28377 Learning rate: 0.02 Mask loss: 0.10376 RPN box loss: 0.03366 RPN score loss: 0.00787 RPN total loss: 0.04154 Total loss: 1.58153 timestamp: 1654927333.1092756 iteration: 15870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11232 FastRCNN class loss: 0.11232 FastRCNN total loss: 0.22464 L1 loss: 0.0000e+00 L2 loss: 1.2836 Learning rate: 0.02 Mask loss: 0.11707 RPN box loss: 0.02027 RPN score loss: 0.0042 RPN total loss: 0.02447 Total loss: 1.64977 timestamp: 1654927336.3874223 iteration: 15875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06797 FastRCNN class loss: 0.04571 FastRCNN total loss: 0.11368 L1 loss: 0.0000e+00 L2 loss: 1.28337 Learning rate: 0.02 Mask loss: 0.16563 RPN box loss: 0.0365 RPN score loss: 0.00776 RPN total loss: 0.04426 Total loss: 1.60695 timestamp: 1654927339.633579 iteration: 15880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14453 FastRCNN class loss: 0.0667 FastRCNN total loss: 0.21123 L1 loss: 0.0000e+00 L2 loss: 1.28315 Learning rate: 0.02 Mask loss: 0.12669 RPN box loss: 0.02233 RPN score loss: 0.00278 RPN total loss: 0.02511 Total loss: 1.64618 timestamp: 1654927342.807002 iteration: 15885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20034 FastRCNN class loss: 0.12292 FastRCNN total loss: 0.32326 L1 loss: 0.0000e+00 L2 loss: 1.28294 Learning rate: 0.02 Mask loss: 0.23334 RPN box loss: 0.02373 RPN score loss: 0.01328 RPN total loss: 0.03701 Total loss: 1.87655 timestamp: 1654927346.0172424 iteration: 15890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15426 FastRCNN class loss: 0.14949 FastRCNN total loss: 0.30375 L1 loss: 0.0000e+00 L2 loss: 1.28272 Learning rate: 0.02 Mask loss: 0.14978 RPN box loss: 0.0577 RPN score loss: 0.01418 RPN total loss: 0.07188 Total loss: 1.80814 timestamp: 1654927349.202703 iteration: 15895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22669 FastRCNN class loss: 0.09003 FastRCNN total loss: 0.31672 L1 loss: 0.0000e+00 L2 loss: 1.28251 Learning rate: 0.02 Mask loss: 0.13818 RPN box loss: 0.02557 RPN score loss: 0.0027 RPN total loss: 0.02826 Total loss: 1.76568 timestamp: 1654927352.4699852 iteration: 15900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14539 FastRCNN class loss: 0.08587 FastRCNN total loss: 0.23126 L1 loss: 0.0000e+00 L2 loss: 1.28229 Learning rate: 0.02 Mask loss: 0.15116 RPN box loss: 0.01673 RPN score loss: 0.00332 RPN total loss: 0.02004 Total loss: 1.68474 timestamp: 1654927355.6554646 iteration: 15905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13626 FastRCNN class loss: 0.08207 FastRCNN total loss: 0.21834 L1 loss: 0.0000e+00 L2 loss: 1.28207 Learning rate: 0.02 Mask loss: 0.20969 RPN box loss: 0.08969 RPN score loss: 0.00834 RPN total loss: 0.09803 Total loss: 1.80813 timestamp: 1654927358.95584 iteration: 15910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22051 FastRCNN class loss: 0.14351 FastRCNN total loss: 0.36403 L1 loss: 0.0000e+00 L2 loss: 1.28185 Learning rate: 0.02 Mask loss: 0.13892 RPN box loss: 0.02997 RPN score loss: 0.0086 RPN total loss: 0.03856 Total loss: 1.82336 timestamp: 1654927362.1804326 iteration: 15915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16224 FastRCNN class loss: 0.07804 FastRCNN total loss: 0.24027 L1 loss: 0.0000e+00 L2 loss: 1.28164 Learning rate: 0.02 Mask loss: 0.17856 RPN box loss: 0.02789 RPN score loss: 0.01188 RPN total loss: 0.03977 Total loss: 1.74025 timestamp: 1654927365.4902916 iteration: 15920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13439 FastRCNN class loss: 0.10731 FastRCNN total loss: 0.2417 L1 loss: 0.0000e+00 L2 loss: 1.28143 Learning rate: 0.02 Mask loss: 0.16793 RPN box loss: 0.05611 RPN score loss: 0.00617 RPN total loss: 0.06228 Total loss: 1.75334 timestamp: 1654927368.6598804 iteration: 15925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13301 FastRCNN class loss: 0.11216 FastRCNN total loss: 0.24517 L1 loss: 0.0000e+00 L2 loss: 1.28121 Learning rate: 0.02 Mask loss: 0.13453 RPN box loss: 0.04284 RPN score loss: 0.01304 RPN total loss: 0.05588 Total loss: 1.71679 timestamp: 1654927371.9698827 iteration: 15930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19637 FastRCNN class loss: 0.11849 FastRCNN total loss: 0.31487 L1 loss: 0.0000e+00 L2 loss: 1.28099 Learning rate: 0.02 Mask loss: 0.23998 RPN box loss: 0.04822 RPN score loss: 0.0067 RPN total loss: 0.05492 Total loss: 1.89075 timestamp: 1654927375.1277308 iteration: 15935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20438 FastRCNN class loss: 0.0737 FastRCNN total loss: 0.27808 L1 loss: 0.0000e+00 L2 loss: 1.28075 Learning rate: 0.02 Mask loss: 0.14579 RPN box loss: 0.02402 RPN score loss: 0.00798 RPN total loss: 0.032 Total loss: 1.73662 timestamp: 1654927378.385201 iteration: 15940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0884 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.1753 L1 loss: 0.0000e+00 L2 loss: 1.28052 Learning rate: 0.02 Mask loss: 0.16626 RPN box loss: 0.04417 RPN score loss: 0.01867 RPN total loss: 0.06283 Total loss: 1.68491 timestamp: 1654927381.5929966 iteration: 15945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23876 FastRCNN class loss: 0.11691 FastRCNN total loss: 0.35566 L1 loss: 0.0000e+00 L2 loss: 1.28029 Learning rate: 0.02 Mask loss: 0.19078 RPN box loss: 0.08616 RPN score loss: 0.02254 RPN total loss: 0.1087 Total loss: 1.93543 timestamp: 1654927384.7817605 iteration: 15950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17088 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.23903 L1 loss: 0.0000e+00 L2 loss: 1.28008 Learning rate: 0.02 Mask loss: 0.14455 RPN box loss: 0.04952 RPN score loss: 0.00359 RPN total loss: 0.05311 Total loss: 1.71677 timestamp: 1654927388.087885 iteration: 15955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21043 FastRCNN class loss: 0.10005 FastRCNN total loss: 0.31048 L1 loss: 0.0000e+00 L2 loss: 1.27986 Learning rate: 0.02 Mask loss: 0.14323 RPN box loss: 0.03774 RPN score loss: 0.00538 RPN total loss: 0.04312 Total loss: 1.77668 timestamp: 1654927391.3191059 iteration: 15960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18797 FastRCNN class loss: 0.09525 FastRCNN total loss: 0.28322 L1 loss: 0.0000e+00 L2 loss: 1.27963 Learning rate: 0.02 Mask loss: 0.13947 RPN box loss: 0.01644 RPN score loss: 0.00428 RPN total loss: 0.02072 Total loss: 1.72305 timestamp: 1654927394.6025753 iteration: 15965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22116 FastRCNN class loss: 0.11267 FastRCNN total loss: 0.33382 L1 loss: 0.0000e+00 L2 loss: 1.27941 Learning rate: 0.02 Mask loss: 0.20335 RPN box loss: 0.03015 RPN score loss: 0.02274 RPN total loss: 0.05289 Total loss: 1.86947 timestamp: 1654927397.878076 iteration: 15970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15284 FastRCNN class loss: 0.05161 FastRCNN total loss: 0.20446 L1 loss: 0.0000e+00 L2 loss: 1.2792 Learning rate: 0.02 Mask loss: 0.15254 RPN box loss: 0.00903 RPN score loss: 0.00613 RPN total loss: 0.01517 Total loss: 1.65136 timestamp: 1654927401.1610043 iteration: 15975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17782 FastRCNN class loss: 0.11892 FastRCNN total loss: 0.29674 L1 loss: 0.0000e+00 L2 loss: 1.27898 Learning rate: 0.02 Mask loss: 0.248 RPN box loss: 0.04357 RPN score loss: 0.01086 RPN total loss: 0.05444 Total loss: 1.87816 timestamp: 1654927404.2984934 iteration: 15980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08079 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.1389 L1 loss: 0.0000e+00 L2 loss: 1.27876 Learning rate: 0.02 Mask loss: 0.17096 RPN box loss: 0.03527 RPN score loss: 0.00604 RPN total loss: 0.04131 Total loss: 1.62993 timestamp: 1654927407.5816665 iteration: 15985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17904 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.25634 L1 loss: 0.0000e+00 L2 loss: 1.27855 Learning rate: 0.02 Mask loss: 0.22 RPN box loss: 0.04437 RPN score loss: 0.0051 RPN total loss: 0.04947 Total loss: 1.80436 timestamp: 1654927410.7935898 iteration: 15990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20029 FastRCNN class loss: 0.0928 FastRCNN total loss: 0.29309 L1 loss: 0.0000e+00 L2 loss: 1.27833 Learning rate: 0.02 Mask loss: 0.14363 RPN box loss: 0.02677 RPN score loss: 0.00665 RPN total loss: 0.03342 Total loss: 1.74848 timestamp: 1654927414.068222 iteration: 15995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04674 FastRCNN class loss: 0.02667 FastRCNN total loss: 0.07341 L1 loss: 0.0000e+00 L2 loss: 1.27812 Learning rate: 0.02 Mask loss: 0.14404 RPN box loss: 0.00115 RPN score loss: 0.00635 RPN total loss: 0.0075 Total loss: 1.50307 timestamp: 1654927417.3931422 iteration: 16000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11859 FastRCNN class loss: 0.05829 FastRCNN total loss: 0.17688 L1 loss: 0.0000e+00 L2 loss: 1.27791 Learning rate: 0.02 Mask loss: 0.14384 RPN box loss: 0.02368 RPN score loss: 0.00437 RPN total loss: 0.02805 Total loss: 1.62668 timestamp: 1654927420.6168044 iteration: 16005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12859 FastRCNN class loss: 0.06145 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 1.27769 Learning rate: 0.02 Mask loss: 0.11193 RPN box loss: 0.02101 RPN score loss: 0.00397 RPN total loss: 0.02498 Total loss: 1.60464 timestamp: 1654927423.859585 iteration: 16010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17738 FastRCNN class loss: 0.16845 FastRCNN total loss: 0.34584 L1 loss: 0.0000e+00 L2 loss: 1.27743 Learning rate: 0.02 Mask loss: 0.18596 RPN box loss: 0.04474 RPN score loss: 0.00812 RPN total loss: 0.05286 Total loss: 1.86209 timestamp: 1654927427.0844855 iteration: 16015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18373 FastRCNN class loss: 0.10002 FastRCNN total loss: 0.28375 L1 loss: 0.0000e+00 L2 loss: 1.27722 Learning rate: 0.02 Mask loss: 0.15688 RPN box loss: 0.04462 RPN score loss: 0.0124 RPN total loss: 0.05702 Total loss: 1.77487 timestamp: 1654927430.3428257 iteration: 16020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19397 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.28365 L1 loss: 0.0000e+00 L2 loss: 1.27702 Learning rate: 0.02 Mask loss: 0.16748 RPN box loss: 0.0188 RPN score loss: 0.00813 RPN total loss: 0.02693 Total loss: 1.75508 timestamp: 1654927433.5861526 iteration: 16025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17776 FastRCNN class loss: 0.04887 FastRCNN total loss: 0.22663 L1 loss: 0.0000e+00 L2 loss: 1.27682 Learning rate: 0.02 Mask loss: 0.13597 RPN box loss: 0.04828 RPN score loss: 0.00294 RPN total loss: 0.05122 Total loss: 1.69064 timestamp: 1654927436.7286212 iteration: 16030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12319 FastRCNN class loss: 0.06057 FastRCNN total loss: 0.18377 L1 loss: 0.0000e+00 L2 loss: 1.27659 Learning rate: 0.02 Mask loss: 0.32069 RPN box loss: 0.04897 RPN score loss: 0.00625 RPN total loss: 0.05523 Total loss: 1.83628 timestamp: 1654927439.899101 iteration: 16035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.12222 FastRCNN total loss: 0.23321 L1 loss: 0.0000e+00 L2 loss: 1.27637 Learning rate: 0.02 Mask loss: 0.14908 RPN box loss: 0.02242 RPN score loss: 0.01409 RPN total loss: 0.03651 Total loss: 1.69517 timestamp: 1654927443.127469 iteration: 16040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13278 FastRCNN class loss: 0.10249 FastRCNN total loss: 0.23527 L1 loss: 0.0000e+00 L2 loss: 1.27614 Learning rate: 0.02 Mask loss: 0.16546 RPN box loss: 0.00836 RPN score loss: 0.00471 RPN total loss: 0.01307 Total loss: 1.68995 timestamp: 1654927446.2204316 iteration: 16045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17341 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.26059 L1 loss: 0.0000e+00 L2 loss: 1.27592 Learning rate: 0.02 Mask loss: 0.24562 RPN box loss: 0.06077 RPN score loss: 0.01321 RPN total loss: 0.07398 Total loss: 1.85611 timestamp: 1654927449.4627678 iteration: 16050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10709 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.1638 L1 loss: 0.0000e+00 L2 loss: 1.27571 Learning rate: 0.02 Mask loss: 0.17597 RPN box loss: 0.0681 RPN score loss: 0.00608 RPN total loss: 0.07418 Total loss: 1.68966 timestamp: 1654927452.6759973 iteration: 16055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10123 FastRCNN class loss: 0.0587 FastRCNN total loss: 0.15993 L1 loss: 0.0000e+00 L2 loss: 1.27549 Learning rate: 0.02 Mask loss: 0.11428 RPN box loss: 0.05358 RPN score loss: 0.00611 RPN total loss: 0.05969 Total loss: 1.60939 timestamp: 1654927455.9429896 iteration: 16060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1174 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.19325 L1 loss: 0.0000e+00 L2 loss: 1.27526 Learning rate: 0.02 Mask loss: 0.14573 RPN box loss: 0.05471 RPN score loss: 0.02354 RPN total loss: 0.07825 Total loss: 1.6925 timestamp: 1654927459.299572 iteration: 16065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16773 FastRCNN class loss: 0.09006 FastRCNN total loss: 0.25779 L1 loss: 0.0000e+00 L2 loss: 1.27505 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.03281 RPN score loss: 0.00298 RPN total loss: 0.0358 Total loss: 1.70695 timestamp: 1654927462.505308 iteration: 16070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18061 FastRCNN class loss: 0.15253 FastRCNN total loss: 0.33314 L1 loss: 0.0000e+00 L2 loss: 1.27484 Learning rate: 0.02 Mask loss: 0.16286 RPN box loss: 0.04434 RPN score loss: 0.00907 RPN total loss: 0.05341 Total loss: 1.82426 timestamp: 1654927465.9813893 iteration: 16075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16626 FastRCNN class loss: 0.08068 FastRCNN total loss: 0.24694 L1 loss: 0.0000e+00 L2 loss: 1.27462 Learning rate: 0.02 Mask loss: 0.17631 RPN box loss: 0.01667 RPN score loss: 0.01509 RPN total loss: 0.03176 Total loss: 1.72962 timestamp: 1654927469.1965284 iteration: 16080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1182 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.17676 L1 loss: 0.0000e+00 L2 loss: 1.27443 Learning rate: 0.02 Mask loss: 0.13768 RPN box loss: 0.01956 RPN score loss: 0.00291 RPN total loss: 0.02247 Total loss: 1.61134 timestamp: 1654927472.5146499 iteration: 16085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08659 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.14109 L1 loss: 0.0000e+00 L2 loss: 1.27418 Learning rate: 0.02 Mask loss: 0.14602 RPN box loss: 0.03986 RPN score loss: 0.00628 RPN total loss: 0.04614 Total loss: 1.60744 timestamp: 1654927475.7130976 iteration: 16090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1411 FastRCNN class loss: 0.07145 FastRCNN total loss: 0.21255 L1 loss: 0.0000e+00 L2 loss: 1.27397 Learning rate: 0.02 Mask loss: 0.16416 RPN box loss: 0.03876 RPN score loss: 0.00316 RPN total loss: 0.04193 Total loss: 1.69261 timestamp: 1654927479.0826712 iteration: 16095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17816 FastRCNN class loss: 0.08814 FastRCNN total loss: 0.26631 L1 loss: 0.0000e+00 L2 loss: 1.27376 Learning rate: 0.02 Mask loss: 0.32982 RPN box loss: 0.04244 RPN score loss: 0.00393 RPN total loss: 0.04637 Total loss: 1.91626 timestamp: 1654927482.3404891 iteration: 16100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14826 FastRCNN class loss: 0.0906 FastRCNN total loss: 0.23886 L1 loss: 0.0000e+00 L2 loss: 1.27354 Learning rate: 0.02 Mask loss: 0.16697 RPN box loss: 0.03241 RPN score loss: 0.00895 RPN total loss: 0.04136 Total loss: 1.72072 timestamp: 1654927485.6180742 iteration: 16105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17321 FastRCNN class loss: 0.10045 FastRCNN total loss: 0.27366 L1 loss: 0.0000e+00 L2 loss: 1.27333 Learning rate: 0.02 Mask loss: 0.1938 RPN box loss: 0.0276 RPN score loss: 0.00827 RPN total loss: 0.03587 Total loss: 1.77666 timestamp: 1654927488.9737852 iteration: 16110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10605 FastRCNN class loss: 0.0532 FastRCNN total loss: 0.15925 L1 loss: 0.0000e+00 L2 loss: 1.27312 Learning rate: 0.02 Mask loss: 0.08432 RPN box loss: 0.00642 RPN score loss: 0.00508 RPN total loss: 0.0115 Total loss: 1.52819 timestamp: 1654927492.2939315 iteration: 16115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.05775 FastRCNN total loss: 0.16422 L1 loss: 0.0000e+00 L2 loss: 1.27289 Learning rate: 0.02 Mask loss: 0.1511 RPN box loss: 0.03404 RPN score loss: 0.01039 RPN total loss: 0.04443 Total loss: 1.63264 timestamp: 1654927495.4970171 iteration: 16120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18434 FastRCNN class loss: 0.12139 FastRCNN total loss: 0.30573 L1 loss: 0.0000e+00 L2 loss: 1.27266 Learning rate: 0.02 Mask loss: 0.15274 RPN box loss: 0.02629 RPN score loss: 0.00738 RPN total loss: 0.03367 Total loss: 1.76481 timestamp: 1654927498.6223736 iteration: 16125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1507 FastRCNN class loss: 0.11263 FastRCNN total loss: 0.26333 L1 loss: 0.0000e+00 L2 loss: 1.27244 Learning rate: 0.02 Mask loss: 0.15918 RPN box loss: 0.02261 RPN score loss: 0.00451 RPN total loss: 0.02712 Total loss: 1.72207 timestamp: 1654927501.8459787 iteration: 16130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28459 FastRCNN class loss: 0.11595 FastRCNN total loss: 0.40054 L1 loss: 0.0000e+00 L2 loss: 1.27222 Learning rate: 0.02 Mask loss: 0.21286 RPN box loss: 0.04335 RPN score loss: 0.00754 RPN total loss: 0.05089 Total loss: 1.93651 timestamp: 1654927505.0137556 iteration: 16135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10683 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.18416 L1 loss: 0.0000e+00 L2 loss: 1.272 Learning rate: 0.02 Mask loss: 0.14429 RPN box loss: 0.03738 RPN score loss: 0.0041 RPN total loss: 0.04148 Total loss: 1.64193 timestamp: 1654927508.2807937 iteration: 16140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13005 FastRCNN class loss: 0.0731 FastRCNN total loss: 0.20315 L1 loss: 0.0000e+00 L2 loss: 1.27178 Learning rate: 0.02 Mask loss: 0.10621 RPN box loss: 0.01369 RPN score loss: 0.0028 RPN total loss: 0.01649 Total loss: 1.59763 timestamp: 1654927511.455069 iteration: 16145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18391 FastRCNN class loss: 0.1177 FastRCNN total loss: 0.30161 L1 loss: 0.0000e+00 L2 loss: 1.27157 Learning rate: 0.02 Mask loss: 0.1588 RPN box loss: 0.01418 RPN score loss: 0.00403 RPN total loss: 0.01822 Total loss: 1.7502 timestamp: 1654927514.6789527 iteration: 16150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12551 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.20717 L1 loss: 0.0000e+00 L2 loss: 1.27135 Learning rate: 0.02 Mask loss: 0.14608 RPN box loss: 0.01998 RPN score loss: 0.00664 RPN total loss: 0.02663 Total loss: 1.65123 timestamp: 1654927517.869273 iteration: 16155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13807 FastRCNN class loss: 0.11142 FastRCNN total loss: 0.24949 L1 loss: 0.0000e+00 L2 loss: 1.27112 Learning rate: 0.02 Mask loss: 0.15964 RPN box loss: 0.02215 RPN score loss: 0.01201 RPN total loss: 0.03416 Total loss: 1.71441 timestamp: 1654927521.1695426 iteration: 16160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16435 FastRCNN class loss: 0.07392 FastRCNN total loss: 0.23827 L1 loss: 0.0000e+00 L2 loss: 1.27092 Learning rate: 0.02 Mask loss: 0.11497 RPN box loss: 0.00809 RPN score loss: 0.00206 RPN total loss: 0.01014 Total loss: 1.63431 timestamp: 1654927524.3312454 iteration: 16165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10804 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.19762 L1 loss: 0.0000e+00 L2 loss: 1.27071 Learning rate: 0.02 Mask loss: 0.17123 RPN box loss: 0.0397 RPN score loss: 0.00985 RPN total loss: 0.04955 Total loss: 1.68911 timestamp: 1654927527.5185444 iteration: 16170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20008 FastRCNN class loss: 0.15879 FastRCNN total loss: 0.35887 L1 loss: 0.0000e+00 L2 loss: 1.2705 Learning rate: 0.02 Mask loss: 0.14298 RPN box loss: 0.06414 RPN score loss: 0.0081 RPN total loss: 0.07224 Total loss: 1.8446 timestamp: 1654927530.7827454 iteration: 16175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.192 FastRCNN class loss: 0.10356 FastRCNN total loss: 0.29555 L1 loss: 0.0000e+00 L2 loss: 1.2703 Learning rate: 0.02 Mask loss: 0.25502 RPN box loss: 0.02971 RPN score loss: 0.00558 RPN total loss: 0.03529 Total loss: 1.85616 timestamp: 1654927534.0538282 iteration: 16180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13184 FastRCNN class loss: 0.07855 FastRCNN total loss: 0.21039 L1 loss: 0.0000e+00 L2 loss: 1.27007 Learning rate: 0.02 Mask loss: 0.15766 RPN box loss: 0.00791 RPN score loss: 0.0069 RPN total loss: 0.01481 Total loss: 1.65294 timestamp: 1654927537.345176 iteration: 16185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18074 FastRCNN class loss: 0.17049 FastRCNN total loss: 0.35123 L1 loss: 0.0000e+00 L2 loss: 1.26982 Learning rate: 0.02 Mask loss: 0.27684 RPN box loss: 0.04631 RPN score loss: 0.00569 RPN total loss: 0.05199 Total loss: 1.94989 timestamp: 1654927540.58391 iteration: 16190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14351 FastRCNN class loss: 0.08656 FastRCNN total loss: 0.23007 L1 loss: 0.0000e+00 L2 loss: 1.26962 Learning rate: 0.02 Mask loss: 0.21216 RPN box loss: 0.03689 RPN score loss: 0.00278 RPN total loss: 0.03967 Total loss: 1.75152 timestamp: 1654927543.8053107 iteration: 16195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14384 FastRCNN class loss: 0.05696 FastRCNN total loss: 0.2008 L1 loss: 0.0000e+00 L2 loss: 1.26943 Learning rate: 0.02 Mask loss: 0.14756 RPN box loss: 0.02368 RPN score loss: 0.00329 RPN total loss: 0.02697 Total loss: 1.64476 timestamp: 1654927547.021361 iteration: 16200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10561 FastRCNN class loss: 0.04611 FastRCNN total loss: 0.15172 L1 loss: 0.0000e+00 L2 loss: 1.26922 Learning rate: 0.02 Mask loss: 0.13306 RPN box loss: 0.01057 RPN score loss: 0.00136 RPN total loss: 0.01193 Total loss: 1.56593 timestamp: 1654927550.328232 iteration: 16205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.097 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.15695 L1 loss: 0.0000e+00 L2 loss: 1.269 Learning rate: 0.02 Mask loss: 0.12599 RPN box loss: 0.04611 RPN score loss: 0.00991 RPN total loss: 0.05602 Total loss: 1.60797 timestamp: 1654927553.5859914 iteration: 16210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14676 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.23575 L1 loss: 0.0000e+00 L2 loss: 1.2688 Learning rate: 0.02 Mask loss: 0.16815 RPN box loss: 0.03283 RPN score loss: 0.00975 RPN total loss: 0.04258 Total loss: 1.71527 timestamp: 1654927556.8690417 iteration: 16215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10908 FastRCNN class loss: 0.07221 FastRCNN total loss: 0.18129 L1 loss: 0.0000e+00 L2 loss: 1.26859 Learning rate: 0.02 Mask loss: 0.15002 RPN box loss: 0.0546 RPN score loss: 0.01198 RPN total loss: 0.06658 Total loss: 1.66648 timestamp: 1654927560.078361 iteration: 16220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13921 FastRCNN class loss: 0.10643 FastRCNN total loss: 0.24564 L1 loss: 0.0000e+00 L2 loss: 1.26835 Learning rate: 0.02 Mask loss: 0.18785 RPN box loss: 0.04135 RPN score loss: 0.00665 RPN total loss: 0.048 Total loss: 1.74984 timestamp: 1654927563.3915203 iteration: 16225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15114 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.23026 L1 loss: 0.0000e+00 L2 loss: 1.26813 Learning rate: 0.02 Mask loss: 0.17805 RPN box loss: 0.02763 RPN score loss: 0.00597 RPN total loss: 0.03359 Total loss: 1.71003 timestamp: 1654927566.7000437 iteration: 16230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1864 FastRCNN class loss: 0.11481 FastRCNN total loss: 0.30121 L1 loss: 0.0000e+00 L2 loss: 1.26792 Learning rate: 0.02 Mask loss: 0.17147 RPN box loss: 0.0582 RPN score loss: 0.00947 RPN total loss: 0.06767 Total loss: 1.80827 timestamp: 1654927569.9126034 iteration: 16235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10532 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.19615 L1 loss: 0.0000e+00 L2 loss: 1.2677 Learning rate: 0.02 Mask loss: 0.1852 RPN box loss: 0.03669 RPN score loss: 0.0078 RPN total loss: 0.04448 Total loss: 1.69353 timestamp: 1654927573.119492 iteration: 16240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20026 FastRCNN class loss: 0.13147 FastRCNN total loss: 0.33173 L1 loss: 0.0000e+00 L2 loss: 1.26749 Learning rate: 0.02 Mask loss: 0.17605 RPN box loss: 0.02592 RPN score loss: 0.01961 RPN total loss: 0.04553 Total loss: 1.8208 timestamp: 1654927576.314629 iteration: 16245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12993 FastRCNN class loss: 0.05277 FastRCNN total loss: 0.1827 L1 loss: 0.0000e+00 L2 loss: 1.26726 Learning rate: 0.02 Mask loss: 0.12302 RPN box loss: 0.00816 RPN score loss: 0.00118 RPN total loss: 0.00934 Total loss: 1.58232 timestamp: 1654927579.6255405 iteration: 16250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11561 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.17546 L1 loss: 0.0000e+00 L2 loss: 1.26705 Learning rate: 0.02 Mask loss: 0.1858 RPN box loss: 0.01396 RPN score loss: 0.00292 RPN total loss: 0.01688 Total loss: 1.64519 timestamp: 1654927582.7837322 iteration: 16255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15878 FastRCNN class loss: 0.06672 FastRCNN total loss: 0.22551 L1 loss: 0.0000e+00 L2 loss: 1.26684 Learning rate: 0.02 Mask loss: 0.12718 RPN box loss: 0.02855 RPN score loss: 0.00439 RPN total loss: 0.03294 Total loss: 1.65247 timestamp: 1654927586.0034359 iteration: 16260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19647 FastRCNN class loss: 0.17574 FastRCNN total loss: 0.37221 L1 loss: 0.0000e+00 L2 loss: 1.26662 Learning rate: 0.02 Mask loss: 0.22001 RPN box loss: 0.04561 RPN score loss: 0.00381 RPN total loss: 0.04941 Total loss: 1.90826 timestamp: 1654927589.1510448 iteration: 16265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14621 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.22404 L1 loss: 0.0000e+00 L2 loss: 1.26641 Learning rate: 0.02 Mask loss: 0.17137 RPN box loss: 0.03841 RPN score loss: 0.00613 RPN total loss: 0.04455 Total loss: 1.70636 timestamp: 1654927592.4338112 iteration: 16270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15392 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.23356 L1 loss: 0.0000e+00 L2 loss: 1.26618 Learning rate: 0.02 Mask loss: 0.14811 RPN box loss: 0.06772 RPN score loss: 0.00547 RPN total loss: 0.07318 Total loss: 1.72104 timestamp: 1654927595.6276045 iteration: 16275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17431 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.25662 L1 loss: 0.0000e+00 L2 loss: 1.26596 Learning rate: 0.02 Mask loss: 0.12026 RPN box loss: 0.01855 RPN score loss: 0.00981 RPN total loss: 0.02835 Total loss: 1.6712 timestamp: 1654927598.8324 iteration: 16280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09128 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.15037 L1 loss: 0.0000e+00 L2 loss: 1.26575 Learning rate: 0.02 Mask loss: 0.13421 RPN box loss: 0.00898 RPN score loss: 0.00583 RPN total loss: 0.01481 Total loss: 1.56513 timestamp: 1654927602.1767335 iteration: 16285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13815 FastRCNN class loss: 0.09661 FastRCNN total loss: 0.23476 L1 loss: 0.0000e+00 L2 loss: 1.26554 Learning rate: 0.02 Mask loss: 0.15448 RPN box loss: 0.022 RPN score loss: 0.00952 RPN total loss: 0.03152 Total loss: 1.6863 timestamp: 1654927605.3547752 iteration: 16290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12083 FastRCNN class loss: 0.06645 FastRCNN total loss: 0.18729 L1 loss: 0.0000e+00 L2 loss: 1.26532 Learning rate: 0.02 Mask loss: 0.21426 RPN box loss: 0.06859 RPN score loss: 0.00791 RPN total loss: 0.0765 Total loss: 1.74336 timestamp: 1654927608.7103977 iteration: 16295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17014 FastRCNN class loss: 0.09059 FastRCNN total loss: 0.26074 L1 loss: 0.0000e+00 L2 loss: 1.2651 Learning rate: 0.02 Mask loss: 0.15434 RPN box loss: 0.05718 RPN score loss: 0.00993 RPN total loss: 0.0671 Total loss: 1.74727 timestamp: 1654927611.9365115 iteration: 16300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19404 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.28371 L1 loss: 0.0000e+00 L2 loss: 1.26489 Learning rate: 0.02 Mask loss: 0.21849 RPN box loss: 0.03246 RPN score loss: 0.0055 RPN total loss: 0.03796 Total loss: 1.80503 timestamp: 1654927615.2729518 iteration: 16305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16527 FastRCNN class loss: 0.15781 FastRCNN total loss: 0.32308 L1 loss: 0.0000e+00 L2 loss: 1.26467 Learning rate: 0.02 Mask loss: 0.20094 RPN box loss: 0.05006 RPN score loss: 0.00921 RPN total loss: 0.05927 Total loss: 1.84796 timestamp: 1654927618.497444 iteration: 16310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18462 FastRCNN class loss: 0.12013 FastRCNN total loss: 0.30475 L1 loss: 0.0000e+00 L2 loss: 1.26446 Learning rate: 0.02 Mask loss: 0.26127 RPN box loss: 0.05837 RPN score loss: 0.0106 RPN total loss: 0.06896 Total loss: 1.89945 timestamp: 1654927621.8200002 iteration: 16315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15033 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.23311 L1 loss: 0.0000e+00 L2 loss: 1.26427 Learning rate: 0.02 Mask loss: 0.24393 RPN box loss: 0.0383 RPN score loss: 0.00792 RPN total loss: 0.04622 Total loss: 1.78753 timestamp: 1654927625.139369 iteration: 16320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18356 FastRCNN class loss: 0.14058 FastRCNN total loss: 0.32414 L1 loss: 0.0000e+00 L2 loss: 1.26405 Learning rate: 0.02 Mask loss: 0.14986 RPN box loss: 0.06717 RPN score loss: 0.00468 RPN total loss: 0.07186 Total loss: 1.80991 timestamp: 1654927628.4456813 iteration: 16325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14143 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.21138 L1 loss: 0.0000e+00 L2 loss: 1.26383 Learning rate: 0.02 Mask loss: 0.29025 RPN box loss: 0.01493 RPN score loss: 0.01154 RPN total loss: 0.02647 Total loss: 1.79192 timestamp: 1654927631.7278817 iteration: 16330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20187 FastRCNN class loss: 0.10775 FastRCNN total loss: 0.30963 L1 loss: 0.0000e+00 L2 loss: 1.2636 Learning rate: 0.02 Mask loss: 0.18552 RPN box loss: 0.05083 RPN score loss: 0.00535 RPN total loss: 0.05619 Total loss: 1.81493 timestamp: 1654927634.9189453 iteration: 16335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13399 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.22266 L1 loss: 0.0000e+00 L2 loss: 1.2634 Learning rate: 0.02 Mask loss: 0.14502 RPN box loss: 0.05619 RPN score loss: 0.00808 RPN total loss: 0.06427 Total loss: 1.69535 timestamp: 1654927638.1678796 iteration: 16340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06875 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.12757 L1 loss: 0.0000e+00 L2 loss: 1.26318 Learning rate: 0.02 Mask loss: 0.13587 RPN box loss: 0.01367 RPN score loss: 0.00293 RPN total loss: 0.01659 Total loss: 1.54321 timestamp: 1654927641.3424475 iteration: 16345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14012 FastRCNN class loss: 0.10008 FastRCNN total loss: 0.2402 L1 loss: 0.0000e+00 L2 loss: 1.26297 Learning rate: 0.02 Mask loss: 0.18102 RPN box loss: 0.04866 RPN score loss: 0.00646 RPN total loss: 0.05512 Total loss: 1.73931 timestamp: 1654927644.604102 iteration: 16350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13108 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.22679 L1 loss: 0.0000e+00 L2 loss: 1.26275 Learning rate: 0.02 Mask loss: 0.15275 RPN box loss: 0.0772 RPN score loss: 0.01175 RPN total loss: 0.08895 Total loss: 1.73123 timestamp: 1654927647.821324 iteration: 16355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19606 FastRCNN class loss: 0.18036 FastRCNN total loss: 0.37642 L1 loss: 0.0000e+00 L2 loss: 1.26251 Learning rate: 0.02 Mask loss: 0.19315 RPN box loss: 0.04314 RPN score loss: 0.01397 RPN total loss: 0.05711 Total loss: 1.88919 timestamp: 1654927651.2054703 iteration: 16360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2398 FastRCNN class loss: 0.0737 FastRCNN total loss: 0.3135 L1 loss: 0.0000e+00 L2 loss: 1.26228 Learning rate: 0.02 Mask loss: 0.14582 RPN box loss: 0.03311 RPN score loss: 0.00644 RPN total loss: 0.03956 Total loss: 1.76116 timestamp: 1654927654.4069633 iteration: 16365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11752 FastRCNN class loss: 0.05797 FastRCNN total loss: 0.17549 L1 loss: 0.0000e+00 L2 loss: 1.26208 Learning rate: 0.02 Mask loss: 0.14649 RPN box loss: 0.06749 RPN score loss: 0.00615 RPN total loss: 0.07365 Total loss: 1.65772 timestamp: 1654927657.7430835 iteration: 16370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15226 FastRCNN class loss: 0.09715 FastRCNN total loss: 0.24941 L1 loss: 0.0000e+00 L2 loss: 1.26186 Learning rate: 0.02 Mask loss: 0.2207 RPN box loss: 0.02013 RPN score loss: 0.0067 RPN total loss: 0.02683 Total loss: 1.75879 timestamp: 1654927660.9510937 iteration: 16375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16932 FastRCNN class loss: 0.06768 FastRCNN total loss: 0.237 L1 loss: 0.0000e+00 L2 loss: 1.26165 Learning rate: 0.02 Mask loss: 0.12992 RPN box loss: 0.01049 RPN score loss: 0.00657 RPN total loss: 0.01706 Total loss: 1.64563 timestamp: 1654927664.166067 iteration: 16380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11614 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.19063 L1 loss: 0.0000e+00 L2 loss: 1.26144 Learning rate: 0.02 Mask loss: 0.12547 RPN box loss: 0.03058 RPN score loss: 0.00732 RPN total loss: 0.0379 Total loss: 1.61544 timestamp: 1654927667.5430205 iteration: 16385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1162 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.18012 L1 loss: 0.0000e+00 L2 loss: 1.26122 Learning rate: 0.02 Mask loss: 0.2131 RPN box loss: 0.01001 RPN score loss: 0.00454 RPN total loss: 0.01455 Total loss: 1.66899 timestamp: 1654927670.8138926 iteration: 16390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.05397 FastRCNN total loss: 0.15457 L1 loss: 0.0000e+00 L2 loss: 1.261 Learning rate: 0.02 Mask loss: 0.19247 RPN box loss: 0.01642 RPN score loss: 0.00664 RPN total loss: 0.02306 Total loss: 1.6311 timestamp: 1654927674.1787488 iteration: 16395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11168 FastRCNN class loss: 0.09981 FastRCNN total loss: 0.21149 L1 loss: 0.0000e+00 L2 loss: 1.26078 Learning rate: 0.02 Mask loss: 0.18725 RPN box loss: 0.02345 RPN score loss: 0.01768 RPN total loss: 0.04112 Total loss: 1.70065 timestamp: 1654927677.4145184 iteration: 16400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15921 FastRCNN class loss: 0.08542 FastRCNN total loss: 0.24463 L1 loss: 0.0000e+00 L2 loss: 1.26057 Learning rate: 0.02 Mask loss: 0.15707 RPN box loss: 0.03132 RPN score loss: 0.00891 RPN total loss: 0.04023 Total loss: 1.7025 timestamp: 1654927680.8307123 iteration: 16405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09989 FastRCNN class loss: 0.12044 FastRCNN total loss: 0.22032 L1 loss: 0.0000e+00 L2 loss: 1.26035 Learning rate: 0.02 Mask loss: 0.19656 RPN box loss: 0.03958 RPN score loss: 0.01451 RPN total loss: 0.05409 Total loss: 1.73131 timestamp: 1654927684.0527127 iteration: 16410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12994 FastRCNN class loss: 0.08911 FastRCNN total loss: 0.21905 L1 loss: 0.0000e+00 L2 loss: 1.26016 Learning rate: 0.02 Mask loss: 0.17004 RPN box loss: 0.04216 RPN score loss: 0.00826 RPN total loss: 0.05041 Total loss: 1.69966 timestamp: 1654927687.2500215 iteration: 16415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12365 FastRCNN class loss: 0.09491 FastRCNN total loss: 0.21856 L1 loss: 0.0000e+00 L2 loss: 1.25993 Learning rate: 0.02 Mask loss: 0.20623 RPN box loss: 0.03531 RPN score loss: 0.00571 RPN total loss: 0.04102 Total loss: 1.72574 timestamp: 1654927690.478796 iteration: 16420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09811 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.15855 L1 loss: 0.0000e+00 L2 loss: 1.25972 Learning rate: 0.02 Mask loss: 0.10833 RPN box loss: 0.03677 RPN score loss: 0.00791 RPN total loss: 0.04467 Total loss: 1.57128 timestamp: 1654927693.798818 iteration: 16425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19887 FastRCNN class loss: 0.13402 FastRCNN total loss: 0.33288 L1 loss: 0.0000e+00 L2 loss: 1.2595 Learning rate: 0.02 Mask loss: 0.2308 RPN box loss: 0.02389 RPN score loss: 0.00416 RPN total loss: 0.02805 Total loss: 1.85123 timestamp: 1654927697.2000253 iteration: 16430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18382 FastRCNN class loss: 0.08071 FastRCNN total loss: 0.26453 L1 loss: 0.0000e+00 L2 loss: 1.25929 Learning rate: 0.02 Mask loss: 0.1354 RPN box loss: 0.032 RPN score loss: 0.00392 RPN total loss: 0.03592 Total loss: 1.69513 timestamp: 1654927700.4066145 iteration: 16435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17089 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.27272 L1 loss: 0.0000e+00 L2 loss: 1.25908 Learning rate: 0.02 Mask loss: 0.18883 RPN box loss: 0.02504 RPN score loss: 0.01124 RPN total loss: 0.03628 Total loss: 1.75691 timestamp: 1654927703.7808654 iteration: 16440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13395 FastRCNN class loss: 0.09207 FastRCNN total loss: 0.22602 L1 loss: 0.0000e+00 L2 loss: 1.25887 Learning rate: 0.02 Mask loss: 0.15936 RPN box loss: 0.01716 RPN score loss: 0.00741 RPN total loss: 0.02458 Total loss: 1.66882 timestamp: 1654927707.0701513 iteration: 16445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21708 FastRCNN class loss: 0.09714 FastRCNN total loss: 0.31421 L1 loss: 0.0000e+00 L2 loss: 1.25864 Learning rate: 0.02 Mask loss: 0.16076 RPN box loss: 0.03363 RPN score loss: 0.00617 RPN total loss: 0.0398 Total loss: 1.77341 timestamp: 1654927710.4048834 iteration: 16450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19387 FastRCNN class loss: 0.1337 FastRCNN total loss: 0.32757 L1 loss: 0.0000e+00 L2 loss: 1.25844 Learning rate: 0.02 Mask loss: 0.22445 RPN box loss: 0.0378 RPN score loss: 0.00751 RPN total loss: 0.0453 Total loss: 1.85576 timestamp: 1654927713.629983 iteration: 16455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12607 FastRCNN class loss: 0.09031 FastRCNN total loss: 0.21638 L1 loss: 0.0000e+00 L2 loss: 1.25822 Learning rate: 0.02 Mask loss: 0.18875 RPN box loss: 0.03239 RPN score loss: 0.00405 RPN total loss: 0.03645 Total loss: 1.6998 timestamp: 1654927716.9282103 iteration: 16460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21371 FastRCNN class loss: 0.10145 FastRCNN total loss: 0.31516 L1 loss: 0.0000e+00 L2 loss: 1.25799 Learning rate: 0.02 Mask loss: 0.1515 RPN box loss: 0.03361 RPN score loss: 0.00826 RPN total loss: 0.04187 Total loss: 1.76652 timestamp: 1654927720.1420193 iteration: 16465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20677 FastRCNN class loss: 0.09428 FastRCNN total loss: 0.30105 L1 loss: 0.0000e+00 L2 loss: 1.25777 Learning rate: 0.02 Mask loss: 0.2173 RPN box loss: 0.0311 RPN score loss: 0.00447 RPN total loss: 0.03557 Total loss: 1.81168 timestamp: 1654927723.4880729 iteration: 16470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13825 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.21631 L1 loss: 0.0000e+00 L2 loss: 1.25753 Learning rate: 0.02 Mask loss: 0.19168 RPN box loss: 0.0179 RPN score loss: 0.00242 RPN total loss: 0.02032 Total loss: 1.68585 timestamp: 1654927726.8070028 iteration: 16475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.17691 L1 loss: 0.0000e+00 L2 loss: 1.25731 Learning rate: 0.02 Mask loss: 0.12474 RPN box loss: 0.05084 RPN score loss: 0.00474 RPN total loss: 0.05558 Total loss: 1.61454 timestamp: 1654927730.1080174 iteration: 16480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13182 FastRCNN class loss: 0.0674 FastRCNN total loss: 0.19921 L1 loss: 0.0000e+00 L2 loss: 1.25711 Learning rate: 0.02 Mask loss: 0.1314 RPN box loss: 0.01047 RPN score loss: 0.00496 RPN total loss: 0.01542 Total loss: 1.60314 timestamp: 1654927733.3152802 iteration: 16485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11796 FastRCNN class loss: 0.09244 FastRCNN total loss: 0.2104 L1 loss: 0.0000e+00 L2 loss: 1.2569 Learning rate: 0.02 Mask loss: 0.15884 RPN box loss: 0.02837 RPN score loss: 0.0059 RPN total loss: 0.03427 Total loss: 1.66041 timestamp: 1654927736.457092 iteration: 16490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1698 FastRCNN class loss: 0.09628 FastRCNN total loss: 0.26608 L1 loss: 0.0000e+00 L2 loss: 1.25669 Learning rate: 0.02 Mask loss: 0.16558 RPN box loss: 0.03792 RPN score loss: 0.01472 RPN total loss: 0.05264 Total loss: 1.74098 timestamp: 1654927739.7113976 iteration: 16495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20898 FastRCNN class loss: 0.08767 FastRCNN total loss: 0.29665 L1 loss: 0.0000e+00 L2 loss: 1.2565 Learning rate: 0.02 Mask loss: 0.17073 RPN box loss: 0.02567 RPN score loss: 0.00593 RPN total loss: 0.0316 Total loss: 1.75549 timestamp: 1654927742.9778876 iteration: 16500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17939 FastRCNN class loss: 0.04922 FastRCNN total loss: 0.2286 L1 loss: 0.0000e+00 L2 loss: 1.2563 Learning rate: 0.02 Mask loss: 0.14079 RPN box loss: 0.03205 RPN score loss: 0.00843 RPN total loss: 0.04048 Total loss: 1.66618 timestamp: 1654927746.2205005 iteration: 16505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11508 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.18454 L1 loss: 0.0000e+00 L2 loss: 1.25607 Learning rate: 0.02 Mask loss: 0.20167 RPN box loss: 0.05603 RPN score loss: 0.00618 RPN total loss: 0.06221 Total loss: 1.70449 timestamp: 1654927749.471339 iteration: 16510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18254 FastRCNN class loss: 0.09751 FastRCNN total loss: 0.28004 L1 loss: 0.0000e+00 L2 loss: 1.25586 Learning rate: 0.02 Mask loss: 0.13018 RPN box loss: 0.03457 RPN score loss: 0.01016 RPN total loss: 0.04473 Total loss: 1.71082 timestamp: 1654927752.8095326 iteration: 16515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1384 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.20869 L1 loss: 0.0000e+00 L2 loss: 1.25566 Learning rate: 0.02 Mask loss: 0.16282 RPN box loss: 0.01636 RPN score loss: 0.00503 RPN total loss: 0.0214 Total loss: 1.64857 timestamp: 1654927755.9869843 iteration: 16520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18984 FastRCNN class loss: 0.10816 FastRCNN total loss: 0.298 L1 loss: 0.0000e+00 L2 loss: 1.25545 Learning rate: 0.02 Mask loss: 0.17452 RPN box loss: 0.01475 RPN score loss: 0.00177 RPN total loss: 0.01651 Total loss: 1.74449 timestamp: 1654927759.3902578 iteration: 16525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15015 FastRCNN class loss: 0.09192 FastRCNN total loss: 0.24207 L1 loss: 0.0000e+00 L2 loss: 1.2552 Learning rate: 0.02 Mask loss: 0.18089 RPN box loss: 0.01606 RPN score loss: 0.0049 RPN total loss: 0.02096 Total loss: 1.69913 timestamp: 1654927762.7077572 iteration: 16530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14773 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.24037 L1 loss: 0.0000e+00 L2 loss: 1.25502 Learning rate: 0.02 Mask loss: 0.17838 RPN box loss: 0.03061 RPN score loss: 0.01119 RPN total loss: 0.0418 Total loss: 1.71556 timestamp: 1654927765.983863 iteration: 16535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14033 FastRCNN class loss: 0.1051 FastRCNN total loss: 0.24543 L1 loss: 0.0000e+00 L2 loss: 1.25482 Learning rate: 0.02 Mask loss: 0.23634 RPN box loss: 0.0547 RPN score loss: 0.00754 RPN total loss: 0.06224 Total loss: 1.79884 timestamp: 1654927769.1885386 iteration: 16540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20062 FastRCNN class loss: 0.09033 FastRCNN total loss: 0.29095 L1 loss: 0.0000e+00 L2 loss: 1.25462 Learning rate: 0.02 Mask loss: 0.20753 RPN box loss: 0.04596 RPN score loss: 0.01442 RPN total loss: 0.06038 Total loss: 1.81348 timestamp: 1654927772.4689932 iteration: 16545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18904 FastRCNN class loss: 0.16729 FastRCNN total loss: 0.35633 L1 loss: 0.0000e+00 L2 loss: 1.25438 Learning rate: 0.02 Mask loss: 0.21647 RPN box loss: 0.07482 RPN score loss: 0.04059 RPN total loss: 0.11541 Total loss: 1.94259 timestamp: 1654927775.7412593 iteration: 16550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0746 FastRCNN class loss: 0.05091 FastRCNN total loss: 0.12551 L1 loss: 0.0000e+00 L2 loss: 1.25416 Learning rate: 0.02 Mask loss: 0.14861 RPN box loss: 0.04516 RPN score loss: 0.00645 RPN total loss: 0.05161 Total loss: 1.57989 timestamp: 1654927778.9433577 iteration: 16555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0976 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.15287 L1 loss: 0.0000e+00 L2 loss: 1.25395 Learning rate: 0.02 Mask loss: 0.14921 RPN box loss: 0.01741 RPN score loss: 0.00332 RPN total loss: 0.02072 Total loss: 1.57675 timestamp: 1654927782.2806916 iteration: 16560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14445 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.22358 L1 loss: 0.0000e+00 L2 loss: 1.25376 Learning rate: 0.02 Mask loss: 0.16458 RPN box loss: 0.0583 RPN score loss: 0.00593 RPN total loss: 0.06424 Total loss: 1.70616 timestamp: 1654927785.4592054 iteration: 16565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07973 FastRCNN class loss: 0.04885 FastRCNN total loss: 0.12858 L1 loss: 0.0000e+00 L2 loss: 1.25355 Learning rate: 0.02 Mask loss: 0.14647 RPN box loss: 0.03154 RPN score loss: 0.01052 RPN total loss: 0.04206 Total loss: 1.57066 timestamp: 1654927788.8577304 iteration: 16570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09629 FastRCNN class loss: 0.06419 FastRCNN total loss: 0.16047 L1 loss: 0.0000e+00 L2 loss: 1.25332 Learning rate: 0.02 Mask loss: 0.10954 RPN box loss: 0.01081 RPN score loss: 0.00473 RPN total loss: 0.01554 Total loss: 1.53887 timestamp: 1654927792.0479481 iteration: 16575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08557 FastRCNN class loss: 0.06355 FastRCNN total loss: 0.14912 L1 loss: 0.0000e+00 L2 loss: 1.2531 Learning rate: 0.02 Mask loss: 0.12331 RPN box loss: 0.02453 RPN score loss: 0.00324 RPN total loss: 0.02776 Total loss: 1.5533 timestamp: 1654927795.3040729 iteration: 16580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08249 FastRCNN class loss: 0.03797 FastRCNN total loss: 0.12046 L1 loss: 0.0000e+00 L2 loss: 1.25288 Learning rate: 0.02 Mask loss: 0.12661 RPN box loss: 0.00618 RPN score loss: 0.00484 RPN total loss: 0.01102 Total loss: 1.51098 timestamp: 1654927798.551951 iteration: 16585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13777 FastRCNN class loss: 0.10328 FastRCNN total loss: 0.24105 L1 loss: 0.0000e+00 L2 loss: 1.25267 Learning rate: 0.02 Mask loss: 0.13469 RPN box loss: 0.02875 RPN score loss: 0.00763 RPN total loss: 0.03638 Total loss: 1.6648 timestamp: 1654927801.7193387 iteration: 16590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12339 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 1.25246 Learning rate: 0.02 Mask loss: 0.16857 RPN box loss: 0.0599 RPN score loss: 0.00342 RPN total loss: 0.06332 Total loss: 1.67431 timestamp: 1654927804.9921188 iteration: 16595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16719 FastRCNN class loss: 0.0859 FastRCNN total loss: 0.25309 L1 loss: 0.0000e+00 L2 loss: 1.25224 Learning rate: 0.02 Mask loss: 0.16987 RPN box loss: 0.043 RPN score loss: 0.00556 RPN total loss: 0.04855 Total loss: 1.72375 timestamp: 1654927808.1577835 iteration: 16600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15435 FastRCNN class loss: 0.12995 FastRCNN total loss: 0.2843 L1 loss: 0.0000e+00 L2 loss: 1.25203 Learning rate: 0.02 Mask loss: 0.14948 RPN box loss: 0.03764 RPN score loss: 0.02074 RPN total loss: 0.05839 Total loss: 1.74419 timestamp: 1654927811.406353 iteration: 16605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12621 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 1.25181 Learning rate: 0.02 Mask loss: 0.13161 RPN box loss: 0.01687 RPN score loss: 0.00489 RPN total loss: 0.02175 Total loss: 1.59874 timestamp: 1654927814.6623333 iteration: 16610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20999 FastRCNN class loss: 0.10233 FastRCNN total loss: 0.31232 L1 loss: 0.0000e+00 L2 loss: 1.25158 Learning rate: 0.02 Mask loss: 0.16878 RPN box loss: 0.05515 RPN score loss: 0.00714 RPN total loss: 0.06229 Total loss: 1.79497 timestamp: 1654927817.9417746 iteration: 16615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1292 FastRCNN class loss: 0.13369 FastRCNN total loss: 0.2629 L1 loss: 0.0000e+00 L2 loss: 1.25135 Learning rate: 0.02 Mask loss: 0.1746 RPN box loss: 0.03468 RPN score loss: 0.01401 RPN total loss: 0.04869 Total loss: 1.73754 timestamp: 1654927821.1468444 iteration: 16620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17512 FastRCNN class loss: 0.07266 FastRCNN total loss: 0.24778 L1 loss: 0.0000e+00 L2 loss: 1.25114 Learning rate: 0.02 Mask loss: 0.13215 RPN box loss: 0.073 RPN score loss: 0.00554 RPN total loss: 0.07854 Total loss: 1.70961 timestamp: 1654927824.3947496 iteration: 16625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12063 FastRCNN class loss: 0.08801 FastRCNN total loss: 0.20864 L1 loss: 0.0000e+00 L2 loss: 1.25092 Learning rate: 0.02 Mask loss: 0.20105 RPN box loss: 0.1085 RPN score loss: 0.01446 RPN total loss: 0.12296 Total loss: 1.78357 timestamp: 1654927827.6475422 iteration: 16630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14198 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.21452 L1 loss: 0.0000e+00 L2 loss: 1.25071 Learning rate: 0.02 Mask loss: 0.21584 RPN box loss: 0.02666 RPN score loss: 0.00218 RPN total loss: 0.02884 Total loss: 1.70991 timestamp: 1654927830.8830125 iteration: 16635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07996 FastRCNN class loss: 0.0462 FastRCNN total loss: 0.12615 L1 loss: 0.0000e+00 L2 loss: 1.2505 Learning rate: 0.02 Mask loss: 0.08822 RPN box loss: 0.057 RPN score loss: 0.00791 RPN total loss: 0.06492 Total loss: 1.5298 timestamp: 1654927834.1583219 iteration: 16640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15257 FastRCNN class loss: 0.08528 FastRCNN total loss: 0.23785 L1 loss: 0.0000e+00 L2 loss: 1.25031 Learning rate: 0.02 Mask loss: 0.20723 RPN box loss: 0.07585 RPN score loss: 0.01734 RPN total loss: 0.09319 Total loss: 1.78858 timestamp: 1654927837.407516 iteration: 16645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14939 FastRCNN class loss: 0.11569 FastRCNN total loss: 0.26508 L1 loss: 0.0000e+00 L2 loss: 1.25009 Learning rate: 0.02 Mask loss: 0.1702 RPN box loss: 0.04608 RPN score loss: 0.01181 RPN total loss: 0.05789 Total loss: 1.74326 timestamp: 1654927840.712103 iteration: 16650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25406 FastRCNN class loss: 0.08215 FastRCNN total loss: 0.33621 L1 loss: 0.0000e+00 L2 loss: 1.24987 Learning rate: 0.02 Mask loss: 0.11858 RPN box loss: 0.0559 RPN score loss: 0.0165 RPN total loss: 0.07239 Total loss: 1.77705 timestamp: 1654927843.8577566 iteration: 16655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09945 FastRCNN class loss: 0.0902 FastRCNN total loss: 0.18964 L1 loss: 0.0000e+00 L2 loss: 1.24965 Learning rate: 0.02 Mask loss: 0.14848 RPN box loss: 0.03111 RPN score loss: 0.01059 RPN total loss: 0.0417 Total loss: 1.62948 timestamp: 1654927847.1812036 iteration: 16660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.04721 FastRCNN total loss: 0.1663 L1 loss: 0.0000e+00 L2 loss: 1.24944 Learning rate: 0.02 Mask loss: 0.15344 RPN box loss: 0.03472 RPN score loss: 0.00232 RPN total loss: 0.03704 Total loss: 1.6062 timestamp: 1654927850.3641577 iteration: 16665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15243 FastRCNN class loss: 0.10419 FastRCNN total loss: 0.25662 L1 loss: 0.0000e+00 L2 loss: 1.24919 Learning rate: 0.02 Mask loss: 0.18616 RPN box loss: 0.01111 RPN score loss: 0.00321 RPN total loss: 0.01432 Total loss: 1.70629 timestamp: 1654927853.7623262 iteration: 16670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21812 FastRCNN class loss: 0.1536 FastRCNN total loss: 0.37172 L1 loss: 0.0000e+00 L2 loss: 1.24898 Learning rate: 0.02 Mask loss: 0.28473 RPN box loss: 0.00909 RPN score loss: 0.00263 RPN total loss: 0.01172 Total loss: 1.91715 timestamp: 1654927856.9603055 iteration: 16675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24215 FastRCNN class loss: 0.14677 FastRCNN total loss: 0.38892 L1 loss: 0.0000e+00 L2 loss: 1.24879 Learning rate: 0.02 Mask loss: 0.25811 RPN box loss: 0.02073 RPN score loss: 0.00402 RPN total loss: 0.02474 Total loss: 1.92056 timestamp: 1654927860.239754 iteration: 16680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15522 FastRCNN class loss: 0.05612 FastRCNN total loss: 0.21134 L1 loss: 0.0000e+00 L2 loss: 1.24859 Learning rate: 0.02 Mask loss: 0.14792 RPN box loss: 0.0798 RPN score loss: 0.01107 RPN total loss: 0.09087 Total loss: 1.69872 timestamp: 1654927863.449358 iteration: 16685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17357 FastRCNN class loss: 0.12361 FastRCNN total loss: 0.29719 L1 loss: 0.0000e+00 L2 loss: 1.24839 Learning rate: 0.02 Mask loss: 0.22334 RPN box loss: 0.02837 RPN score loss: 0.01141 RPN total loss: 0.03977 Total loss: 1.80869 timestamp: 1654927866.6917684 iteration: 16690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19695 FastRCNN class loss: 0.08338 FastRCNN total loss: 0.28034 L1 loss: 0.0000e+00 L2 loss: 1.24818 Learning rate: 0.02 Mask loss: 0.10227 RPN box loss: 0.03964 RPN score loss: 0.00997 RPN total loss: 0.04961 Total loss: 1.68039 timestamp: 1654927869.9290328 iteration: 16695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16063 FastRCNN class loss: 0.10485 FastRCNN total loss: 0.26548 L1 loss: 0.0000e+00 L2 loss: 1.24796 Learning rate: 0.02 Mask loss: 0.27908 RPN box loss: 0.04309 RPN score loss: 0.01206 RPN total loss: 0.05515 Total loss: 1.84767 timestamp: 1654927873.1330435 iteration: 16700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09641 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.1704 L1 loss: 0.0000e+00 L2 loss: 1.24775 Learning rate: 0.02 Mask loss: 0.17763 RPN box loss: 0.0313 RPN score loss: 0.00381 RPN total loss: 0.03511 Total loss: 1.63089 timestamp: 1654927876.4285803 iteration: 16705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12552 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.20321 L1 loss: 0.0000e+00 L2 loss: 1.24754 Learning rate: 0.02 Mask loss: 0.11037 RPN box loss: 0.047 RPN score loss: 0.00547 RPN total loss: 0.05247 Total loss: 1.61359 timestamp: 1654927879.63051 iteration: 16710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.20936 L1 loss: 0.0000e+00 L2 loss: 1.24734 Learning rate: 0.02 Mask loss: 0.18959 RPN box loss: 0.21987 RPN score loss: 0.01612 RPN total loss: 0.23599 Total loss: 1.88227 timestamp: 1654927882.981381 iteration: 16715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11172 FastRCNN class loss: 0.08426 FastRCNN total loss: 0.19598 L1 loss: 0.0000e+00 L2 loss: 1.24714 Learning rate: 0.02 Mask loss: 0.16245 RPN box loss: 0.0573 RPN score loss: 0.00677 RPN total loss: 0.06407 Total loss: 1.66964 timestamp: 1654927886.1461976 iteration: 16720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11742 FastRCNN class loss: 0.11139 FastRCNN total loss: 0.22881 L1 loss: 0.0000e+00 L2 loss: 1.24692 Learning rate: 0.02 Mask loss: 0.14908 RPN box loss: 0.07611 RPN score loss: 0.00292 RPN total loss: 0.07903 Total loss: 1.70383 timestamp: 1654927889.4135935 iteration: 16725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16956 FastRCNN class loss: 0.10999 FastRCNN total loss: 0.27955 L1 loss: 0.0000e+00 L2 loss: 1.24669 Learning rate: 0.02 Mask loss: 0.18537 RPN box loss: 0.03478 RPN score loss: 0.00813 RPN total loss: 0.04291 Total loss: 1.75452 timestamp: 1654927892.622 iteration: 16730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19232 FastRCNN class loss: 0.12672 FastRCNN total loss: 0.31904 L1 loss: 0.0000e+00 L2 loss: 1.24648 Learning rate: 0.02 Mask loss: 0.26395 RPN box loss: 0.05103 RPN score loss: 0.01132 RPN total loss: 0.06235 Total loss: 1.89182 timestamp: 1654927895.93212 iteration: 16735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.121 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.18788 L1 loss: 0.0000e+00 L2 loss: 1.24629 Learning rate: 0.02 Mask loss: 0.08104 RPN box loss: 0.03675 RPN score loss: 0.00735 RPN total loss: 0.0441 Total loss: 1.55931 timestamp: 1654927899.0979807 iteration: 16740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15849 FastRCNN class loss: 0.10653 FastRCNN total loss: 0.26501 L1 loss: 0.0000e+00 L2 loss: 1.24608 Learning rate: 0.02 Mask loss: 0.23969 RPN box loss: 0.03448 RPN score loss: 0.0091 RPN total loss: 0.04358 Total loss: 1.79436 timestamp: 1654927902.4882324 iteration: 16745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19195 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.23954 L1 loss: 0.0000e+00 L2 loss: 1.24586 Learning rate: 0.02 Mask loss: 0.09828 RPN box loss: 0.04561 RPN score loss: 0.00318 RPN total loss: 0.04879 Total loss: 1.63247 timestamp: 1654927905.8598933 iteration: 16750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20289 FastRCNN class loss: 0.13083 FastRCNN total loss: 0.33372 L1 loss: 0.0000e+00 L2 loss: 1.24564 Learning rate: 0.02 Mask loss: 0.15797 RPN box loss: 0.01834 RPN score loss: 0.00543 RPN total loss: 0.02377 Total loss: 1.76111 timestamp: 1654927909.0652344 iteration: 16755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15105 FastRCNN class loss: 0.09278 FastRCNN total loss: 0.24384 L1 loss: 0.0000e+00 L2 loss: 1.24543 Learning rate: 0.02 Mask loss: 0.13117 RPN box loss: 0.03806 RPN score loss: 0.01942 RPN total loss: 0.05748 Total loss: 1.67791 timestamp: 1654927912.4102554 iteration: 16760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13845 FastRCNN class loss: 0.04917 FastRCNN total loss: 0.18762 L1 loss: 0.0000e+00 L2 loss: 1.24521 Learning rate: 0.02 Mask loss: 0.11968 RPN box loss: 0.01153 RPN score loss: 0.00298 RPN total loss: 0.01452 Total loss: 1.56703 timestamp: 1654927915.6478949 iteration: 16765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10475 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.16372 L1 loss: 0.0000e+00 L2 loss: 1.245 Learning rate: 0.02 Mask loss: 0.12583 RPN box loss: 0.06137 RPN score loss: 0.00844 RPN total loss: 0.06981 Total loss: 1.60436 timestamp: 1654927919.011968 iteration: 16770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14723 FastRCNN class loss: 0.08668 FastRCNN total loss: 0.23391 L1 loss: 0.0000e+00 L2 loss: 1.2448 Learning rate: 0.02 Mask loss: 0.16171 RPN box loss: 0.04409 RPN score loss: 0.00769 RPN total loss: 0.05178 Total loss: 1.69221 timestamp: 1654927922.2835674 iteration: 16775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10264 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.19611 L1 loss: 0.0000e+00 L2 loss: 1.2446 Learning rate: 0.02 Mask loss: 0.21673 RPN box loss: 0.01948 RPN score loss: 0.00328 RPN total loss: 0.02277 Total loss: 1.68022 timestamp: 1654927925.6174896 iteration: 16780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05654 FastRCNN class loss: 0.04153 FastRCNN total loss: 0.09807 L1 loss: 0.0000e+00 L2 loss: 1.2444 Learning rate: 0.02 Mask loss: 0.26964 RPN box loss: 0.0264 RPN score loss: 0.00258 RPN total loss: 0.02899 Total loss: 1.64109 timestamp: 1654927928.8313155 iteration: 16785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10818 FastRCNN class loss: 0.10209 FastRCNN total loss: 0.21027 L1 loss: 0.0000e+00 L2 loss: 1.24418 Learning rate: 0.02 Mask loss: 0.09465 RPN box loss: 0.01618 RPN score loss: 0.00706 RPN total loss: 0.02324 Total loss: 1.57234 timestamp: 1654927932.1452894 iteration: 16790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14698 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.22554 L1 loss: 0.0000e+00 L2 loss: 1.24399 Learning rate: 0.02 Mask loss: 0.12926 RPN box loss: 0.02335 RPN score loss: 0.00592 RPN total loss: 0.02927 Total loss: 1.62805 timestamp: 1654927935.3924208 iteration: 16795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14702 FastRCNN class loss: 0.10122 FastRCNN total loss: 0.24824 L1 loss: 0.0000e+00 L2 loss: 1.24377 Learning rate: 0.02 Mask loss: 0.15635 RPN box loss: 0.06289 RPN score loss: 0.00591 RPN total loss: 0.0688 Total loss: 1.71716 timestamp: 1654927938.584334 iteration: 16800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1152 FastRCNN class loss: 0.05436 FastRCNN total loss: 0.16956 L1 loss: 0.0000e+00 L2 loss: 1.24355 Learning rate: 0.02 Mask loss: 0.18392 RPN box loss: 0.02204 RPN score loss: 0.00345 RPN total loss: 0.02549 Total loss: 1.62253 timestamp: 1654927941.8144805 iteration: 16805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14128 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.21021 L1 loss: 0.0000e+00 L2 loss: 1.24332 Learning rate: 0.02 Mask loss: 0.15748 RPN box loss: 0.0276 RPN score loss: 0.00131 RPN total loss: 0.02892 Total loss: 1.63994 timestamp: 1654927945.0304024 iteration: 16810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08045 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.132 L1 loss: 0.0000e+00 L2 loss: 1.24312 Learning rate: 0.02 Mask loss: 0.13978 RPN box loss: 0.02973 RPN score loss: 0.00147 RPN total loss: 0.0312 Total loss: 1.5461 timestamp: 1654927948.3971338 iteration: 16815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13505 FastRCNN class loss: 0.11604 FastRCNN total loss: 0.25109 L1 loss: 0.0000e+00 L2 loss: 1.24293 Learning rate: 0.02 Mask loss: 0.19976 RPN box loss: 0.03035 RPN score loss: 0.01307 RPN total loss: 0.04341 Total loss: 1.73719 timestamp: 1654927951.5957382 iteration: 16820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15159 FastRCNN class loss: 0.06612 FastRCNN total loss: 0.21771 L1 loss: 0.0000e+00 L2 loss: 1.2427 Learning rate: 0.02 Mask loss: 0.11168 RPN box loss: 0.01719 RPN score loss: 0.00479 RPN total loss: 0.02198 Total loss: 1.59407 timestamp: 1654927954.8985052 iteration: 16825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16201 FastRCNN class loss: 0.08239 FastRCNN total loss: 0.2444 L1 loss: 0.0000e+00 L2 loss: 1.24252 Learning rate: 0.02 Mask loss: 0.17043 RPN box loss: 0.05017 RPN score loss: 0.0029 RPN total loss: 0.05308 Total loss: 1.71043 timestamp: 1654927958.05817 iteration: 16830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16252 FastRCNN class loss: 0.13491 FastRCNN total loss: 0.29743 L1 loss: 0.0000e+00 L2 loss: 1.2423 Learning rate: 0.02 Mask loss: 0.15472 RPN box loss: 0.02101 RPN score loss: 0.01252 RPN total loss: 0.03353 Total loss: 1.72798 timestamp: 1654927961.322285 iteration: 16835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1575 FastRCNN class loss: 0.10614 FastRCNN total loss: 0.26364 L1 loss: 0.0000e+00 L2 loss: 1.24208 Learning rate: 0.02 Mask loss: 0.13765 RPN box loss: 0.04875 RPN score loss: 0.01262 RPN total loss: 0.06137 Total loss: 1.70475 timestamp: 1654927964.5338311 iteration: 16840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10561 FastRCNN class loss: 0.08546 FastRCNN total loss: 0.19108 L1 loss: 0.0000e+00 L2 loss: 1.24189 Learning rate: 0.02 Mask loss: 0.18116 RPN box loss: 0.02654 RPN score loss: 0.00563 RPN total loss: 0.03217 Total loss: 1.64629 timestamp: 1654927967.7891526 iteration: 16845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14175 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.22625 L1 loss: 0.0000e+00 L2 loss: 1.24166 Learning rate: 0.02 Mask loss: 0.12342 RPN box loss: 0.01615 RPN score loss: 0.00596 RPN total loss: 0.02211 Total loss: 1.61344 timestamp: 1654927970.9338706 iteration: 16850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1374 FastRCNN class loss: 0.05048 FastRCNN total loss: 0.18788 L1 loss: 0.0000e+00 L2 loss: 1.24145 Learning rate: 0.02 Mask loss: 0.11209 RPN box loss: 0.00793 RPN score loss: 0.00505 RPN total loss: 0.01298 Total loss: 1.5544 timestamp: 1654927974.3037474 iteration: 16855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09213 FastRCNN class loss: 0.04134 FastRCNN total loss: 0.13347 L1 loss: 0.0000e+00 L2 loss: 1.24125 Learning rate: 0.02 Mask loss: 0.19794 RPN box loss: 0.04599 RPN score loss: 0.00591 RPN total loss: 0.0519 Total loss: 1.62457 timestamp: 1654927977.6686141 iteration: 16860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09352 FastRCNN class loss: 0.06087 FastRCNN total loss: 0.15439 L1 loss: 0.0000e+00 L2 loss: 1.24104 Learning rate: 0.02 Mask loss: 0.13124 RPN box loss: 0.02867 RPN score loss: 0.00291 RPN total loss: 0.03158 Total loss: 1.55825 timestamp: 1654927980.8980012 iteration: 16865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18526 FastRCNN class loss: 0.10423 FastRCNN total loss: 0.2895 L1 loss: 0.0000e+00 L2 loss: 1.24084 Learning rate: 0.02 Mask loss: 0.19503 RPN box loss: 0.015 RPN score loss: 0.00902 RPN total loss: 0.02402 Total loss: 1.74939 timestamp: 1654927984.2447171 iteration: 16870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14701 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.20228 L1 loss: 0.0000e+00 L2 loss: 1.24064 Learning rate: 0.02 Mask loss: 0.17314 RPN box loss: 0.02641 RPN score loss: 0.00717 RPN total loss: 0.03358 Total loss: 1.64963 timestamp: 1654927987.4207509 iteration: 16875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11589 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.1847 L1 loss: 0.0000e+00 L2 loss: 1.24041 Learning rate: 0.02 Mask loss: 0.1622 RPN box loss: 0.01439 RPN score loss: 0.00637 RPN total loss: 0.02076 Total loss: 1.60807 timestamp: 1654927990.6456754 iteration: 16880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16634 FastRCNN class loss: 0.08733 FastRCNN total loss: 0.25366 L1 loss: 0.0000e+00 L2 loss: 1.24022 Learning rate: 0.02 Mask loss: 0.15049 RPN box loss: 0.01998 RPN score loss: 0.01034 RPN total loss: 0.03032 Total loss: 1.67469 timestamp: 1654927993.9069421 iteration: 16885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16223 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.22352 L1 loss: 0.0000e+00 L2 loss: 1.24003 Learning rate: 0.02 Mask loss: 0.14634 RPN box loss: 0.02783 RPN score loss: 0.00698 RPN total loss: 0.03481 Total loss: 1.64469 timestamp: 1654927997.164062 iteration: 16890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18434 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.26946 L1 loss: 0.0000e+00 L2 loss: 1.23982 Learning rate: 0.02 Mask loss: 0.19406 RPN box loss: 0.06628 RPN score loss: 0.01324 RPN total loss: 0.07952 Total loss: 1.78285 timestamp: 1654928000.3130534 iteration: 16895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11126 FastRCNN class loss: 0.09895 FastRCNN total loss: 0.21021 L1 loss: 0.0000e+00 L2 loss: 1.2396 Learning rate: 0.02 Mask loss: 0.19315 RPN box loss: 0.09427 RPN score loss: 0.00488 RPN total loss: 0.09915 Total loss: 1.74211 timestamp: 1654928003.6582077 iteration: 16900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20459 FastRCNN class loss: 0.08906 FastRCNN total loss: 0.29365 L1 loss: 0.0000e+00 L2 loss: 1.23939 Learning rate: 0.02 Mask loss: 0.17353 RPN box loss: 0.06264 RPN score loss: 0.01556 RPN total loss: 0.0782 Total loss: 1.78477 timestamp: 1654928006.9787786 iteration: 16905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11456 FastRCNN class loss: 0.07076 FastRCNN total loss: 0.18532 L1 loss: 0.0000e+00 L2 loss: 1.23918 Learning rate: 0.02 Mask loss: 0.11805 RPN box loss: 0.02396 RPN score loss: 0.00664 RPN total loss: 0.0306 Total loss: 1.57315 timestamp: 1654928010.0951085 iteration: 16910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14193 FastRCNN class loss: 0.10529 FastRCNN total loss: 0.24722 L1 loss: 0.0000e+00 L2 loss: 1.23896 Learning rate: 0.02 Mask loss: 0.14087 RPN box loss: 0.01496 RPN score loss: 0.00469 RPN total loss: 0.01965 Total loss: 1.6467 timestamp: 1654928013.2982163 iteration: 16915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17758 FastRCNN class loss: 0.11779 FastRCNN total loss: 0.29536 L1 loss: 0.0000e+00 L2 loss: 1.23872 Learning rate: 0.02 Mask loss: 0.20951 RPN box loss: 0.04623 RPN score loss: 0.01102 RPN total loss: 0.05725 Total loss: 1.80084 timestamp: 1654928016.5605268 iteration: 16920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17408 FastRCNN class loss: 0.07182 FastRCNN total loss: 0.2459 L1 loss: 0.0000e+00 L2 loss: 1.23851 Learning rate: 0.02 Mask loss: 0.1473 RPN box loss: 0.03252 RPN score loss: 0.00676 RPN total loss: 0.03928 Total loss: 1.67099 timestamp: 1654928019.8482597 iteration: 16925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.17896 L1 loss: 0.0000e+00 L2 loss: 1.23831 Learning rate: 0.02 Mask loss: 0.16687 RPN box loss: 0.01251 RPN score loss: 0.00486 RPN total loss: 0.01737 Total loss: 1.60151 timestamp: 1654928023.0286775 iteration: 16930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17091 FastRCNN class loss: 0.12103 FastRCNN total loss: 0.29193 L1 loss: 0.0000e+00 L2 loss: 1.2381 Learning rate: 0.02 Mask loss: 0.22338 RPN box loss: 0.02314 RPN score loss: 0.0074 RPN total loss: 0.03054 Total loss: 1.78396 timestamp: 1654928026.3111165 iteration: 16935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16182 FastRCNN class loss: 0.05696 FastRCNN total loss: 0.21879 L1 loss: 0.0000e+00 L2 loss: 1.2379 Learning rate: 0.02 Mask loss: 0.11755 RPN box loss: 0.01419 RPN score loss: 0.00461 RPN total loss: 0.01881 Total loss: 1.59304 timestamp: 1654928029.5086994 iteration: 16940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15962 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.24782 L1 loss: 0.0000e+00 L2 loss: 1.23774 Learning rate: 0.02 Mask loss: 0.22855 RPN box loss: 0.06127 RPN score loss: 0.00678 RPN total loss: 0.06805 Total loss: 1.78216 timestamp: 1654928032.7809122 iteration: 16945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1728 FastRCNN class loss: 0.12334 FastRCNN total loss: 0.29614 L1 loss: 0.0000e+00 L2 loss: 1.23752 Learning rate: 0.02 Mask loss: 0.18771 RPN box loss: 0.04181 RPN score loss: 0.01251 RPN total loss: 0.05432 Total loss: 1.77568 timestamp: 1654928036.0699413 iteration: 16950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17377 FastRCNN class loss: 0.1132 FastRCNN total loss: 0.28696 L1 loss: 0.0000e+00 L2 loss: 1.2373 Learning rate: 0.02 Mask loss: 0.21315 RPN box loss: 0.02367 RPN score loss: 0.00516 RPN total loss: 0.02883 Total loss: 1.76623 timestamp: 1654928039.314889 iteration: 16955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09307 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.18175 L1 loss: 0.0000e+00 L2 loss: 1.23709 Learning rate: 0.02 Mask loss: 0.18638 RPN box loss: 0.01005 RPN score loss: 0.00767 RPN total loss: 0.01771 Total loss: 1.62293 timestamp: 1654928042.497254 iteration: 16960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19494 FastRCNN class loss: 0.07704 FastRCNN total loss: 0.27198 L1 loss: 0.0000e+00 L2 loss: 1.23687 Learning rate: 0.02 Mask loss: 0.14233 RPN box loss: 0.02541 RPN score loss: 0.00626 RPN total loss: 0.03167 Total loss: 1.68285 timestamp: 1654928045.7024374 iteration: 16965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17553 FastRCNN class loss: 0.09624 FastRCNN total loss: 0.27177 L1 loss: 0.0000e+00 L2 loss: 1.23667 Learning rate: 0.02 Mask loss: 0.1697 RPN box loss: 0.04914 RPN score loss: 0.01532 RPN total loss: 0.06446 Total loss: 1.7426 timestamp: 1654928049.0771868 iteration: 16970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17498 FastRCNN class loss: 0.12706 FastRCNN total loss: 0.30204 L1 loss: 0.0000e+00 L2 loss: 1.23646 Learning rate: 0.02 Mask loss: 0.20338 RPN box loss: 0.01875 RPN score loss: 0.00555 RPN total loss: 0.0243 Total loss: 1.76617 timestamp: 1654928052.298086 iteration: 16975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14913 FastRCNN class loss: 0.09558 FastRCNN total loss: 0.24471 L1 loss: 0.0000e+00 L2 loss: 1.23624 Learning rate: 0.02 Mask loss: 0.22047 RPN box loss: 0.03718 RPN score loss: 0.00595 RPN total loss: 0.04313 Total loss: 1.74455 timestamp: 1654928055.5708969 iteration: 16980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11413 FastRCNN class loss: 0.06627 FastRCNN total loss: 0.1804 L1 loss: 0.0000e+00 L2 loss: 1.23602 Learning rate: 0.02 Mask loss: 0.13955 RPN box loss: 0.04779 RPN score loss: 0.00655 RPN total loss: 0.05434 Total loss: 1.61031 timestamp: 1654928058.7420642 iteration: 16985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11449 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.18815 L1 loss: 0.0000e+00 L2 loss: 1.23581 Learning rate: 0.02 Mask loss: 0.15587 RPN box loss: 0.01625 RPN score loss: 0.00297 RPN total loss: 0.01922 Total loss: 1.59905 timestamp: 1654928062.065384 iteration: 16990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1189 FastRCNN class loss: 0.04674 FastRCNN total loss: 0.16564 L1 loss: 0.0000e+00 L2 loss: 1.23561 Learning rate: 0.02 Mask loss: 0.12276 RPN box loss: 0.038 RPN score loss: 0.00294 RPN total loss: 0.04094 Total loss: 1.56494 timestamp: 1654928065.2510633 iteration: 16995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1867 FastRCNN class loss: 0.06191 FastRCNN total loss: 0.24862 L1 loss: 0.0000e+00 L2 loss: 1.23542 Learning rate: 0.02 Mask loss: 0.13848 RPN box loss: 0.04183 RPN score loss: 0.00514 RPN total loss: 0.04697 Total loss: 1.66949 timestamp: 1654928068.513063 iteration: 17000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16513 FastRCNN class loss: 0.10957 FastRCNN total loss: 0.2747 L1 loss: 0.0000e+00 L2 loss: 1.23524 Learning rate: 0.02 Mask loss: 0.14688 RPN box loss: 0.02852 RPN score loss: 0.0067 RPN total loss: 0.03521 Total loss: 1.69203 timestamp: 1654928071.68075 iteration: 17005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08583 FastRCNN class loss: 0.0761 FastRCNN total loss: 0.16193 L1 loss: 0.0000e+00 L2 loss: 1.23505 Learning rate: 0.02 Mask loss: 0.13032 RPN box loss: 0.0304 RPN score loss: 0.00401 RPN total loss: 0.03441 Total loss: 1.56171 timestamp: 1654928074.927657 iteration: 17010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13264 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.2149 L1 loss: 0.0000e+00 L2 loss: 1.23482 Learning rate: 0.02 Mask loss: 0.14498 RPN box loss: 0.04126 RPN score loss: 0.0048 RPN total loss: 0.04607 Total loss: 1.64076 timestamp: 1654928078.111028 iteration: 17015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13702 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.20491 L1 loss: 0.0000e+00 L2 loss: 1.23459 Learning rate: 0.02 Mask loss: 0.09393 RPN box loss: 0.034 RPN score loss: 0.00787 RPN total loss: 0.04187 Total loss: 1.57529 timestamp: 1654928081.2891035 iteration: 17020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0818 FastRCNN class loss: 0.04669 FastRCNN total loss: 0.12849 L1 loss: 0.0000e+00 L2 loss: 1.23438 Learning rate: 0.02 Mask loss: 0.15251 RPN box loss: 0.0493 RPN score loss: 0.0019 RPN total loss: 0.0512 Total loss: 1.56658 timestamp: 1654928084.4961877 iteration: 17025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17241 FastRCNN class loss: 0.06316 FastRCNN total loss: 0.23557 L1 loss: 0.0000e+00 L2 loss: 1.23418 Learning rate: 0.02 Mask loss: 0.08827 RPN box loss: 0.00813 RPN score loss: 0.00187 RPN total loss: 0.01 Total loss: 1.56802 timestamp: 1654928087.728792 iteration: 17030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23451 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.3284 L1 loss: 0.0000e+00 L2 loss: 1.23397 Learning rate: 0.02 Mask loss: 0.14255 RPN box loss: 0.01894 RPN score loss: 0.00472 RPN total loss: 0.02367 Total loss: 1.72859 timestamp: 1654928091.1595438 iteration: 17035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18847 FastRCNN class loss: 0.13113 FastRCNN total loss: 0.31959 L1 loss: 0.0000e+00 L2 loss: 1.23378 Learning rate: 0.02 Mask loss: 0.18267 RPN box loss: 0.04642 RPN score loss: 0.00668 RPN total loss: 0.0531 Total loss: 1.78914 timestamp: 1654928094.4431787 iteration: 17040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23137 FastRCNN class loss: 0.07382 FastRCNN total loss: 0.30519 L1 loss: 0.0000e+00 L2 loss: 1.23355 Learning rate: 0.02 Mask loss: 0.17284 RPN box loss: 0.02541 RPN score loss: 0.00863 RPN total loss: 0.03404 Total loss: 1.74562 timestamp: 1654928097.791374 iteration: 17045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20544 FastRCNN class loss: 0.12509 FastRCNN total loss: 0.33053 L1 loss: 0.0000e+00 L2 loss: 1.23334 Learning rate: 0.02 Mask loss: 0.26743 RPN box loss: 0.01085 RPN score loss: 0.01693 RPN total loss: 0.02778 Total loss: 1.85908 timestamp: 1654928100.9480898 iteration: 17050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14961 FastRCNN class loss: 0.08821 FastRCNN total loss: 0.23782 L1 loss: 0.0000e+00 L2 loss: 1.23313 Learning rate: 0.02 Mask loss: 0.18284 RPN box loss: 0.05799 RPN score loss: 0.00617 RPN total loss: 0.06415 Total loss: 1.71794 timestamp: 1654928104.2940865 iteration: 17055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13721 FastRCNN class loss: 0.08276 FastRCNN total loss: 0.21997 L1 loss: 0.0000e+00 L2 loss: 1.23292 Learning rate: 0.02 Mask loss: 0.13698 RPN box loss: 0.05136 RPN score loss: 0.00421 RPN total loss: 0.05558 Total loss: 1.64545 timestamp: 1654928107.5138001 iteration: 17060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09603 FastRCNN class loss: 0.08778 FastRCNN total loss: 0.18381 L1 loss: 0.0000e+00 L2 loss: 1.23273 Learning rate: 0.02 Mask loss: 0.17796 RPN box loss: 0.04961 RPN score loss: 0.00848 RPN total loss: 0.05809 Total loss: 1.65258 timestamp: 1654928110.7658474 iteration: 17065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07758 FastRCNN class loss: 0.06002 FastRCNN total loss: 0.1376 L1 loss: 0.0000e+00 L2 loss: 1.23252 Learning rate: 0.02 Mask loss: 0.17052 RPN box loss: 0.01747 RPN score loss: 0.00664 RPN total loss: 0.02411 Total loss: 1.56475 timestamp: 1654928114.197959 iteration: 17070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14843 FastRCNN class loss: 0.0875 FastRCNN total loss: 0.23593 L1 loss: 0.0000e+00 L2 loss: 1.23231 Learning rate: 0.02 Mask loss: 0.20946 RPN box loss: 0.03017 RPN score loss: 0.00393 RPN total loss: 0.03409 Total loss: 1.71179 timestamp: 1654928117.3386576 iteration: 17075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.06275 FastRCNN total loss: 0.17314 L1 loss: 0.0000e+00 L2 loss: 1.23208 Learning rate: 0.02 Mask loss: 0.22762 RPN box loss: 0.03236 RPN score loss: 0.00313 RPN total loss: 0.0355 Total loss: 1.66834 timestamp: 1654928120.6356227 iteration: 17080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10097 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.18495 L1 loss: 0.0000e+00 L2 loss: 1.23186 Learning rate: 0.02 Mask loss: 0.17803 RPN box loss: 0.01054 RPN score loss: 0.00237 RPN total loss: 0.01291 Total loss: 1.60776 timestamp: 1654928123.8469236 iteration: 17085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2227 FastRCNN class loss: 0.16984 FastRCNN total loss: 0.39254 L1 loss: 0.0000e+00 L2 loss: 1.23167 Learning rate: 0.02 Mask loss: 0.19736 RPN box loss: 0.02344 RPN score loss: 0.00959 RPN total loss: 0.03303 Total loss: 1.85461 timestamp: 1654928127.1511388 iteration: 17090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17402 FastRCNN class loss: 0.08926 FastRCNN total loss: 0.26328 L1 loss: 0.0000e+00 L2 loss: 1.23146 Learning rate: 0.02 Mask loss: 0.13406 RPN box loss: 0.04057 RPN score loss: 0.00297 RPN total loss: 0.04355 Total loss: 1.67234 timestamp: 1654928130.3467865 iteration: 17095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09749 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.16142 L1 loss: 0.0000e+00 L2 loss: 1.23125 Learning rate: 0.02 Mask loss: 0.1614 RPN box loss: 0.05908 RPN score loss: 0.01081 RPN total loss: 0.06989 Total loss: 1.62396 timestamp: 1654928133.602098 iteration: 17100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11306 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.20289 L1 loss: 0.0000e+00 L2 loss: 1.23104 Learning rate: 0.02 Mask loss: 0.23382 RPN box loss: 0.06078 RPN score loss: 0.01772 RPN total loss: 0.0785 Total loss: 1.74626 timestamp: 1654928136.8444777 iteration: 17105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09208 FastRCNN class loss: 0.04931 FastRCNN total loss: 0.1414 L1 loss: 0.0000e+00 L2 loss: 1.23082 Learning rate: 0.02 Mask loss: 0.15804 RPN box loss: 0.0153 RPN score loss: 0.00476 RPN total loss: 0.02006 Total loss: 1.55032 timestamp: 1654928140.0706124 iteration: 17110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07005 FastRCNN class loss: 0.04011 FastRCNN total loss: 0.11016 L1 loss: 0.0000e+00 L2 loss: 1.23059 Learning rate: 0.02 Mask loss: 0.12421 RPN box loss: 0.00449 RPN score loss: 0.00361 RPN total loss: 0.0081 Total loss: 1.47306 timestamp: 1654928143.273317 iteration: 17115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19344 FastRCNN class loss: 0.09718 FastRCNN total loss: 0.29062 L1 loss: 0.0000e+00 L2 loss: 1.23038 Learning rate: 0.02 Mask loss: 0.14489 RPN box loss: 0.01927 RPN score loss: 0.00611 RPN total loss: 0.02538 Total loss: 1.69126 timestamp: 1654928146.467831 iteration: 17120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12415 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.21895 L1 loss: 0.0000e+00 L2 loss: 1.23019 Learning rate: 0.02 Mask loss: 0.1465 RPN box loss: 0.05395 RPN score loss: 0.01342 RPN total loss: 0.06737 Total loss: 1.66301 timestamp: 1654928149.6622128 iteration: 17125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08006 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.15302 L1 loss: 0.0000e+00 L2 loss: 1.22998 Learning rate: 0.02 Mask loss: 0.16556 RPN box loss: 0.02178 RPN score loss: 0.00936 RPN total loss: 0.03114 Total loss: 1.5797 timestamp: 1654928153.0308528 iteration: 17130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12666 FastRCNN class loss: 0.0685 FastRCNN total loss: 0.19516 L1 loss: 0.0000e+00 L2 loss: 1.22979 Learning rate: 0.02 Mask loss: 0.14116 RPN box loss: 0.02353 RPN score loss: 0.006 RPN total loss: 0.02953 Total loss: 1.59564 timestamp: 1654928156.2684073 iteration: 17135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15765 FastRCNN class loss: 0.10482 FastRCNN total loss: 0.26247 L1 loss: 0.0000e+00 L2 loss: 1.22957 Learning rate: 0.02 Mask loss: 0.12638 RPN box loss: 0.06035 RPN score loss: 0.01272 RPN total loss: 0.07307 Total loss: 1.69149 timestamp: 1654928159.4476767 iteration: 17140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17269 FastRCNN class loss: 0.10225 FastRCNN total loss: 0.27495 L1 loss: 0.0000e+00 L2 loss: 1.22935 Learning rate: 0.02 Mask loss: 0.15486 RPN box loss: 0.04332 RPN score loss: 0.00447 RPN total loss: 0.04779 Total loss: 1.70695 timestamp: 1654928162.7837996 iteration: 17145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14757 FastRCNN class loss: 0.11446 FastRCNN total loss: 0.26202 L1 loss: 0.0000e+00 L2 loss: 1.22913 Learning rate: 0.02 Mask loss: 0.19268 RPN box loss: 0.02052 RPN score loss: 0.01088 RPN total loss: 0.0314 Total loss: 1.71524 timestamp: 1654928165.9482074 iteration: 17150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11192 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.18093 L1 loss: 0.0000e+00 L2 loss: 1.22892 Learning rate: 0.02 Mask loss: 0.14607 RPN box loss: 0.04456 RPN score loss: 0.00576 RPN total loss: 0.05032 Total loss: 1.60624 timestamp: 1654928169.2711625 iteration: 17155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13201 FastRCNN class loss: 0.089 FastRCNN total loss: 0.22101 L1 loss: 0.0000e+00 L2 loss: 1.22872 Learning rate: 0.02 Mask loss: 0.13582 RPN box loss: 0.01322 RPN score loss: 0.00255 RPN total loss: 0.01577 Total loss: 1.60132 timestamp: 1654928172.4715667 iteration: 17160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21869 FastRCNN class loss: 0.20142 FastRCNN total loss: 0.42011 L1 loss: 0.0000e+00 L2 loss: 1.2285 Learning rate: 0.02 Mask loss: 0.23429 RPN box loss: 0.01905 RPN score loss: 0.00836 RPN total loss: 0.0274 Total loss: 1.9103 timestamp: 1654928175.773044 iteration: 17165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1472 FastRCNN class loss: 0.0803 FastRCNN total loss: 0.2275 L1 loss: 0.0000e+00 L2 loss: 1.22829 Learning rate: 0.02 Mask loss: 0.1824 RPN box loss: 0.03532 RPN score loss: 0.00954 RPN total loss: 0.04486 Total loss: 1.68304 timestamp: 1654928178.9458718 iteration: 17170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18918 FastRCNN class loss: 0.10625 FastRCNN total loss: 0.29543 L1 loss: 0.0000e+00 L2 loss: 1.22808 Learning rate: 0.02 Mask loss: 0.19376 RPN box loss: 0.01268 RPN score loss: 0.00484 RPN total loss: 0.01752 Total loss: 1.7348 timestamp: 1654928182.2441444 iteration: 17175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1425 FastRCNN class loss: 0.11835 FastRCNN total loss: 0.26085 L1 loss: 0.0000e+00 L2 loss: 1.22788 Learning rate: 0.02 Mask loss: 0.15735 RPN box loss: 0.03713 RPN score loss: 0.00548 RPN total loss: 0.04262 Total loss: 1.68869 timestamp: 1654928185.6431568 iteration: 17180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15929 FastRCNN class loss: 0.12435 FastRCNN total loss: 0.28364 L1 loss: 0.0000e+00 L2 loss: 1.22768 Learning rate: 0.02 Mask loss: 0.13142 RPN box loss: 0.03785 RPN score loss: 0.00749 RPN total loss: 0.04534 Total loss: 1.68808 timestamp: 1654928188.800991 iteration: 17185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17353 FastRCNN class loss: 0.1194 FastRCNN total loss: 0.29293 L1 loss: 0.0000e+00 L2 loss: 1.22748 Learning rate: 0.02 Mask loss: 0.16179 RPN box loss: 0.02733 RPN score loss: 0.00219 RPN total loss: 0.02952 Total loss: 1.71171 timestamp: 1654928192.0570557 iteration: 17190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10599 FastRCNN class loss: 0.09906 FastRCNN total loss: 0.20505 L1 loss: 0.0000e+00 L2 loss: 1.22729 Learning rate: 0.02 Mask loss: 0.12176 RPN box loss: 0.00931 RPN score loss: 0.00238 RPN total loss: 0.01169 Total loss: 1.56579 timestamp: 1654928195.2770784 iteration: 17195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15115 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.24053 L1 loss: 0.0000e+00 L2 loss: 1.22708 Learning rate: 0.02 Mask loss: 0.20745 RPN box loss: 0.01061 RPN score loss: 0.00928 RPN total loss: 0.01989 Total loss: 1.69496 timestamp: 1654928198.575592 iteration: 17200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13218 FastRCNN class loss: 0.11579 FastRCNN total loss: 0.24797 L1 loss: 0.0000e+00 L2 loss: 1.22686 Learning rate: 0.02 Mask loss: 0.24948 RPN box loss: 0.03979 RPN score loss: 0.00422 RPN total loss: 0.04402 Total loss: 1.76833 timestamp: 1654928201.7356293 iteration: 17205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14152 FastRCNN class loss: 0.15524 FastRCNN total loss: 0.29676 L1 loss: 0.0000e+00 L2 loss: 1.22665 Learning rate: 0.02 Mask loss: 0.12215 RPN box loss: 0.02368 RPN score loss: 0.00443 RPN total loss: 0.0281 Total loss: 1.67366 timestamp: 1654928205.042867 iteration: 17210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14789 FastRCNN class loss: 0.11447 FastRCNN total loss: 0.26235 L1 loss: 0.0000e+00 L2 loss: 1.22645 Learning rate: 0.02 Mask loss: 0.17644 RPN box loss: 0.019 RPN score loss: 0.00239 RPN total loss: 0.02139 Total loss: 1.68663 timestamp: 1654928208.2125592 iteration: 17215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19512 FastRCNN class loss: 0.12614 FastRCNN total loss: 0.32126 L1 loss: 0.0000e+00 L2 loss: 1.22625 Learning rate: 0.02 Mask loss: 0.20711 RPN box loss: 0.05403 RPN score loss: 0.01624 RPN total loss: 0.07027 Total loss: 1.82489 timestamp: 1654928211.4938757 iteration: 17220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.0697 FastRCNN total loss: 0.17758 L1 loss: 0.0000e+00 L2 loss: 1.22602 Learning rate: 0.02 Mask loss: 0.3239 RPN box loss: 0.02648 RPN score loss: 0.00563 RPN total loss: 0.03211 Total loss: 1.75962 timestamp: 1654928214.7102442 iteration: 17225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16965 FastRCNN class loss: 0.08646 FastRCNN total loss: 0.25611 L1 loss: 0.0000e+00 L2 loss: 1.22581 Learning rate: 0.02 Mask loss: 0.12931 RPN box loss: 0.02206 RPN score loss: 0.00457 RPN total loss: 0.02663 Total loss: 1.63785 timestamp: 1654928218.0492916 iteration: 17230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20071 FastRCNN class loss: 0.11747 FastRCNN total loss: 0.31817 L1 loss: 0.0000e+00 L2 loss: 1.2256 Learning rate: 0.02 Mask loss: 0.23863 RPN box loss: 0.03984 RPN score loss: 0.00464 RPN total loss: 0.04448 Total loss: 1.82688 timestamp: 1654928221.213798 iteration: 17235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1643 FastRCNN class loss: 0.07038 FastRCNN total loss: 0.23467 L1 loss: 0.0000e+00 L2 loss: 1.22539 Learning rate: 0.02 Mask loss: 0.12819 RPN box loss: 0.03806 RPN score loss: 0.00547 RPN total loss: 0.04353 Total loss: 1.63178 timestamp: 1654928224.5442905 iteration: 17240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19404 FastRCNN class loss: 0.20995 FastRCNN total loss: 0.40399 L1 loss: 0.0000e+00 L2 loss: 1.2252 Learning rate: 0.02 Mask loss: 0.23533 RPN box loss: 0.03488 RPN score loss: 0.00941 RPN total loss: 0.04429 Total loss: 1.9088 timestamp: 1654928227.8816617 iteration: 17245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15846 FastRCNN class loss: 0.08911 FastRCNN total loss: 0.24757 L1 loss: 0.0000e+00 L2 loss: 1.22502 Learning rate: 0.02 Mask loss: 0.13191 RPN box loss: 0.01954 RPN score loss: 0.00959 RPN total loss: 0.02913 Total loss: 1.63363 timestamp: 1654928231.0472586 iteration: 17250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20776 FastRCNN class loss: 0.09324 FastRCNN total loss: 0.301 L1 loss: 0.0000e+00 L2 loss: 1.22481 Learning rate: 0.02 Mask loss: 0.20208 RPN box loss: 0.04655 RPN score loss: 0.00982 RPN total loss: 0.05637 Total loss: 1.78426 timestamp: 1654928234.3136606 iteration: 17255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12136 FastRCNN class loss: 0.11117 FastRCNN total loss: 0.23254 L1 loss: 0.0000e+00 L2 loss: 1.22459 Learning rate: 0.02 Mask loss: 0.14516 RPN box loss: 0.01315 RPN score loss: 0.0089 RPN total loss: 0.02205 Total loss: 1.62434 timestamp: 1654928237.4758198 iteration: 17260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21853 FastRCNN class loss: 0.13625 FastRCNN total loss: 0.35477 L1 loss: 0.0000e+00 L2 loss: 1.22438 Learning rate: 0.02 Mask loss: 0.22604 RPN box loss: 0.06236 RPN score loss: 0.00595 RPN total loss: 0.06831 Total loss: 1.87351 timestamp: 1654928240.7862594 iteration: 17265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11787 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.1798 L1 loss: 0.0000e+00 L2 loss: 1.22418 Learning rate: 0.02 Mask loss: 0.10504 RPN box loss: 0.01917 RPN score loss: 0.00438 RPN total loss: 0.02355 Total loss: 1.53258 timestamp: 1654928244.0287943 iteration: 17270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14217 FastRCNN class loss: 0.09355 FastRCNN total loss: 0.23572 L1 loss: 0.0000e+00 L2 loss: 1.22399 Learning rate: 0.02 Mask loss: 0.16963 RPN box loss: 0.01099 RPN score loss: 0.00794 RPN total loss: 0.01893 Total loss: 1.64826 timestamp: 1654928247.3273273 iteration: 17275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1147 FastRCNN class loss: 0.12069 FastRCNN total loss: 0.23538 L1 loss: 0.0000e+00 L2 loss: 1.22378 Learning rate: 0.02 Mask loss: 0.16339 RPN box loss: 0.01294 RPN score loss: 0.0031 RPN total loss: 0.01604 Total loss: 1.6386 timestamp: 1654928250.5262134 iteration: 17280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16859 FastRCNN class loss: 0.09174 FastRCNN total loss: 0.26032 L1 loss: 0.0000e+00 L2 loss: 1.22359 Learning rate: 0.02 Mask loss: 0.16524 RPN box loss: 0.03949 RPN score loss: 0.01424 RPN total loss: 0.05373 Total loss: 1.70288 timestamp: 1654928253.9051888 iteration: 17285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13701 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.2008 L1 loss: 0.0000e+00 L2 loss: 1.22339 Learning rate: 0.02 Mask loss: 0.12053 RPN box loss: 0.0215 RPN score loss: 0.00227 RPN total loss: 0.02377 Total loss: 1.56849 timestamp: 1654928257.2619557 iteration: 17290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1753 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.24868 L1 loss: 0.0000e+00 L2 loss: 1.22317 Learning rate: 0.02 Mask loss: 0.15993 RPN box loss: 0.04535 RPN score loss: 0.00288 RPN total loss: 0.04823 Total loss: 1.68001 timestamp: 1654928260.4824967 iteration: 17295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1203 FastRCNN class loss: 0.106 FastRCNN total loss: 0.2263 L1 loss: 0.0000e+00 L2 loss: 1.22296 Learning rate: 0.02 Mask loss: 0.10216 RPN box loss: 0.03151 RPN score loss: 0.009 RPN total loss: 0.04051 Total loss: 1.59193 timestamp: 1654928263.7866385 iteration: 17300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24244 FastRCNN class loss: 0.0922 FastRCNN total loss: 0.33464 L1 loss: 0.0000e+00 L2 loss: 1.22272 Learning rate: 0.02 Mask loss: 0.23875 RPN box loss: 0.03276 RPN score loss: 0.00685 RPN total loss: 0.03961 Total loss: 1.83573 timestamp: 1654928266.9940982 iteration: 17305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18964 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.27215 L1 loss: 0.0000e+00 L2 loss: 1.22253 Learning rate: 0.02 Mask loss: 0.14164 RPN box loss: 0.03547 RPN score loss: 0.00567 RPN total loss: 0.04114 Total loss: 1.67747 timestamp: 1654928270.3015122 iteration: 17310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17994 FastRCNN class loss: 0.05439 FastRCNN total loss: 0.23433 L1 loss: 0.0000e+00 L2 loss: 1.22235 Learning rate: 0.02 Mask loss: 0.12955 RPN box loss: 0.04052 RPN score loss: 0.00818 RPN total loss: 0.0487 Total loss: 1.63493 timestamp: 1654928273.5065444 iteration: 17315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13863 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.19959 L1 loss: 0.0000e+00 L2 loss: 1.22215 Learning rate: 0.02 Mask loss: 0.20405 RPN box loss: 0.02773 RPN score loss: 0.00407 RPN total loss: 0.03179 Total loss: 1.65759 timestamp: 1654928276.754671 iteration: 17320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21007 FastRCNN class loss: 0.09009 FastRCNN total loss: 0.30016 L1 loss: 0.0000e+00 L2 loss: 1.22194 Learning rate: 0.02 Mask loss: 0.2073 RPN box loss: 0.05406 RPN score loss: 0.00638 RPN total loss: 0.06043 Total loss: 1.78983 timestamp: 1654928279.9113936 iteration: 17325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11752 FastRCNN class loss: 0.09827 FastRCNN total loss: 0.21579 L1 loss: 0.0000e+00 L2 loss: 1.22172 Learning rate: 0.02 Mask loss: 0.13699 RPN box loss: 0.03685 RPN score loss: 0.01138 RPN total loss: 0.04823 Total loss: 1.62273 timestamp: 1654928283.1856647 iteration: 17330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23804 FastRCNN class loss: 0.15695 FastRCNN total loss: 0.39499 L1 loss: 0.0000e+00 L2 loss: 1.22149 Learning rate: 0.02 Mask loss: 0.21037 RPN box loss: 0.04789 RPN score loss: 0.0364 RPN total loss: 0.08429 Total loss: 1.91114 timestamp: 1654928286.4173682 iteration: 17335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10979 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.1886 L1 loss: 0.0000e+00 L2 loss: 1.2213 Learning rate: 0.02 Mask loss: 0.2042 RPN box loss: 0.0146 RPN score loss: 0.00714 RPN total loss: 0.02174 Total loss: 1.63584 timestamp: 1654928289.685042 iteration: 17340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12516 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.20057 L1 loss: 0.0000e+00 L2 loss: 1.2211 Learning rate: 0.02 Mask loss: 0.15657 RPN box loss: 0.05542 RPN score loss: 0.00605 RPN total loss: 0.06147 Total loss: 1.63971 timestamp: 1654928292.8006258 iteration: 17345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.07121 FastRCNN total loss: 0.17852 L1 loss: 0.0000e+00 L2 loss: 1.22091 Learning rate: 0.02 Mask loss: 0.16969 RPN box loss: 0.03293 RPN score loss: 0.00209 RPN total loss: 0.03502 Total loss: 1.60414 timestamp: 1654928295.9992428 iteration: 17350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1647 FastRCNN class loss: 0.09274 FastRCNN total loss: 0.25745 L1 loss: 0.0000e+00 L2 loss: 1.22072 Learning rate: 0.02 Mask loss: 0.18744 RPN box loss: 0.04752 RPN score loss: 0.00477 RPN total loss: 0.05229 Total loss: 1.7179 timestamp: 1654928299.2756498 iteration: 17355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16012 FastRCNN class loss: 0.09573 FastRCNN total loss: 0.25584 L1 loss: 0.0000e+00 L2 loss: 1.22052 Learning rate: 0.02 Mask loss: 0.19408 RPN box loss: 0.04748 RPN score loss: 0.00302 RPN total loss: 0.0505 Total loss: 1.72094 timestamp: 1654928302.4716594 iteration: 17360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10472 FastRCNN class loss: 0.0941 FastRCNN total loss: 0.19881 L1 loss: 0.0000e+00 L2 loss: 1.22028 Learning rate: 0.02 Mask loss: 0.17475 RPN box loss: 0.03541 RPN score loss: 0.0035 RPN total loss: 0.03892 Total loss: 1.63277 timestamp: 1654928305.6379278 iteration: 17365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10759 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.16525 L1 loss: 0.0000e+00 L2 loss: 1.22008 Learning rate: 0.02 Mask loss: 0.15884 RPN box loss: 0.01487 RPN score loss: 0.00302 RPN total loss: 0.01789 Total loss: 1.56206 timestamp: 1654928308.8100533 iteration: 17370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20777 FastRCNN class loss: 0.11786 FastRCNN total loss: 0.32563 L1 loss: 0.0000e+00 L2 loss: 1.21987 Learning rate: 0.02 Mask loss: 0.15793 RPN box loss: 0.05262 RPN score loss: 0.00831 RPN total loss: 0.06093 Total loss: 1.76435 timestamp: 1654928312.117444 iteration: 17375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13921 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.18955 L1 loss: 0.0000e+00 L2 loss: 1.21966 Learning rate: 0.02 Mask loss: 0.18231 RPN box loss: 0.04604 RPN score loss: 0.01104 RPN total loss: 0.05707 Total loss: 1.64858 timestamp: 1654928315.2656844 iteration: 17380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17289 FastRCNN class loss: 0.11834 FastRCNN total loss: 0.29123 L1 loss: 0.0000e+00 L2 loss: 1.21946 Learning rate: 0.02 Mask loss: 0.21254 RPN box loss: 0.05129 RPN score loss: 0.027 RPN total loss: 0.07829 Total loss: 1.80153 timestamp: 1654928318.413237 iteration: 17385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11334 FastRCNN class loss: 0.07737 FastRCNN total loss: 0.19071 L1 loss: 0.0000e+00 L2 loss: 1.2193 Learning rate: 0.02 Mask loss: 0.15565 RPN box loss: 0.04289 RPN score loss: 0.01335 RPN total loss: 0.05624 Total loss: 1.6219 timestamp: 1654928321.604 iteration: 17390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06246 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.13094 L1 loss: 0.0000e+00 L2 loss: 1.21912 Learning rate: 0.02 Mask loss: 0.21924 RPN box loss: 0.0284 RPN score loss: 0.00397 RPN total loss: 0.03237 Total loss: 1.60167 timestamp: 1654928324.954868 iteration: 17395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07108 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.13326 L1 loss: 0.0000e+00 L2 loss: 1.21892 Learning rate: 0.02 Mask loss: 0.17371 RPN box loss: 0.00497 RPN score loss: 0.00623 RPN total loss: 0.0112 Total loss: 1.5371 timestamp: 1654928328.1800075 iteration: 17400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16588 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.25021 L1 loss: 0.0000e+00 L2 loss: 1.21871 Learning rate: 0.02 Mask loss: 0.16419 RPN box loss: 0.01917 RPN score loss: 0.0084 RPN total loss: 0.02756 Total loss: 1.66067 timestamp: 1654928331.4217253 iteration: 17405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10008 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.18725 L1 loss: 0.0000e+00 L2 loss: 1.21849 Learning rate: 0.02 Mask loss: 0.14429 RPN box loss: 0.0614 RPN score loss: 0.01482 RPN total loss: 0.07621 Total loss: 1.62626 timestamp: 1654928334.5572772 iteration: 17410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16997 FastRCNN class loss: 0.09283 FastRCNN total loss: 0.26281 L1 loss: 0.0000e+00 L2 loss: 1.21828 Learning rate: 0.02 Mask loss: 0.17766 RPN box loss: 0.02482 RPN score loss: 0.02171 RPN total loss: 0.04653 Total loss: 1.70528 timestamp: 1654928337.8217096 iteration: 17415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06009 FastRCNN class loss: 0.04287 FastRCNN total loss: 0.10296 L1 loss: 0.0000e+00 L2 loss: 1.21808 Learning rate: 0.02 Mask loss: 0.1068 RPN box loss: 0.00451 RPN score loss: 0.00221 RPN total loss: 0.00672 Total loss: 1.43456 timestamp: 1654928341.0521436 iteration: 17420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15305 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.22094 L1 loss: 0.0000e+00 L2 loss: 1.21787 Learning rate: 0.02 Mask loss: 0.14052 RPN box loss: 0.02768 RPN score loss: 0.00346 RPN total loss: 0.03114 Total loss: 1.61048 timestamp: 1654928344.2484727 iteration: 17425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.04084 FastRCNN total loss: 0.11938 L1 loss: 0.0000e+00 L2 loss: 1.21767 Learning rate: 0.02 Mask loss: 0.13282 RPN box loss: 0.04002 RPN score loss: 0.00908 RPN total loss: 0.0491 Total loss: 1.51897 timestamp: 1654928347.4220006 iteration: 17430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11497 FastRCNN class loss: 0.05734 FastRCNN total loss: 0.17231 L1 loss: 0.0000e+00 L2 loss: 1.21745 Learning rate: 0.02 Mask loss: 0.13454 RPN box loss: 0.01867 RPN score loss: 0.00687 RPN total loss: 0.02554 Total loss: 1.54984 timestamp: 1654928350.6451306 iteration: 17435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1723 FastRCNN class loss: 0.12517 FastRCNN total loss: 0.29747 L1 loss: 0.0000e+00 L2 loss: 1.21725 Learning rate: 0.02 Mask loss: 0.18642 RPN box loss: 0.05143 RPN score loss: 0.00944 RPN total loss: 0.06087 Total loss: 1.76201 timestamp: 1654928353.9130824 iteration: 17440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07922 FastRCNN class loss: 0.05948 FastRCNN total loss: 0.1387 L1 loss: 0.0000e+00 L2 loss: 1.21705 Learning rate: 0.02 Mask loss: 0.09306 RPN box loss: 0.04818 RPN score loss: 0.01083 RPN total loss: 0.05901 Total loss: 1.50783 timestamp: 1654928357.1116297 iteration: 17445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18557 FastRCNN class loss: 0.06796 FastRCNN total loss: 0.25353 L1 loss: 0.0000e+00 L2 loss: 1.21683 Learning rate: 0.02 Mask loss: 0.1272 RPN box loss: 0.04628 RPN score loss: 0.00353 RPN total loss: 0.04981 Total loss: 1.64737 timestamp: 1654928360.360664 iteration: 17450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12754 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.20868 L1 loss: 0.0000e+00 L2 loss: 1.21661 Learning rate: 0.02 Mask loss: 0.23078 RPN box loss: 0.06419 RPN score loss: 0.0097 RPN total loss: 0.07389 Total loss: 1.72997 timestamp: 1654928363.4650872 iteration: 17455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15313 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.21437 L1 loss: 0.0000e+00 L2 loss: 1.21639 Learning rate: 0.02 Mask loss: 0.10993 RPN box loss: 0.01218 RPN score loss: 0.00237 RPN total loss: 0.01455 Total loss: 1.55523 timestamp: 1654928366.6836705 iteration: 17460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16594 FastRCNN class loss: 0.09224 FastRCNN total loss: 0.25818 L1 loss: 0.0000e+00 L2 loss: 1.21617 Learning rate: 0.02 Mask loss: 0.12528 RPN box loss: 0.02193 RPN score loss: 0.0041 RPN total loss: 0.02603 Total loss: 1.62567 timestamp: 1654928369.9008238 iteration: 17465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20782 FastRCNN class loss: 0.10578 FastRCNN total loss: 0.3136 L1 loss: 0.0000e+00 L2 loss: 1.21596 Learning rate: 0.02 Mask loss: 0.16393 RPN box loss: 0.01545 RPN score loss: 0.002 RPN total loss: 0.01745 Total loss: 1.71093 timestamp: 1654928373.1406484 iteration: 17470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16337 FastRCNN class loss: 0.13109 FastRCNN total loss: 0.29446 L1 loss: 0.0000e+00 L2 loss: 1.21577 Learning rate: 0.02 Mask loss: 0.20715 RPN box loss: 0.06399 RPN score loss: 0.00854 RPN total loss: 0.07253 Total loss: 1.78991 timestamp: 1654928376.4142318 iteration: 17475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16835 FastRCNN class loss: 0.13529 FastRCNN total loss: 0.30364 L1 loss: 0.0000e+00 L2 loss: 1.21557 Learning rate: 0.02 Mask loss: 0.14447 RPN box loss: 0.02539 RPN score loss: 0.01287 RPN total loss: 0.03826 Total loss: 1.70194 timestamp: 1654928379.7180977 iteration: 17480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13428 FastRCNN class loss: 0.11267 FastRCNN total loss: 0.24695 L1 loss: 0.0000e+00 L2 loss: 1.21535 Learning rate: 0.02 Mask loss: 0.16703 RPN box loss: 0.06617 RPN score loss: 0.01682 RPN total loss: 0.08299 Total loss: 1.71231 timestamp: 1654928383.0961456 iteration: 17485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11737 FastRCNN class loss: 0.09135 FastRCNN total loss: 0.20873 L1 loss: 0.0000e+00 L2 loss: 1.21515 Learning rate: 0.02 Mask loss: 0.14538 RPN box loss: 0.02295 RPN score loss: 0.00775 RPN total loss: 0.0307 Total loss: 1.59996 timestamp: 1654928386.304437 iteration: 17490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21744 FastRCNN class loss: 0.11441 FastRCNN total loss: 0.33185 L1 loss: 0.0000e+00 L2 loss: 1.21494 Learning rate: 0.02 Mask loss: 0.23573 RPN box loss: 0.05728 RPN score loss: 0.0055 RPN total loss: 0.06279 Total loss: 1.84531 timestamp: 1654928389.7349749 iteration: 17495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19157 FastRCNN class loss: 0.10661 FastRCNN total loss: 0.29818 L1 loss: 0.0000e+00 L2 loss: 1.21472 Learning rate: 0.02 Mask loss: 0.13733 RPN box loss: 0.03774 RPN score loss: 0.00712 RPN total loss: 0.04486 Total loss: 1.69509 timestamp: 1654928392.9340777 iteration: 17500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14661 FastRCNN class loss: 0.07512 FastRCNN total loss: 0.22173 L1 loss: 0.0000e+00 L2 loss: 1.21449 Learning rate: 0.02 Mask loss: 0.10511 RPN box loss: 0.02227 RPN score loss: 0.00644 RPN total loss: 0.02871 Total loss: 1.57004 timestamp: 1654928396.291651 iteration: 17505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16164 FastRCNN class loss: 0.09617 FastRCNN total loss: 0.25781 L1 loss: 0.0000e+00 L2 loss: 1.21428 Learning rate: 0.02 Mask loss: 0.16969 RPN box loss: 0.03739 RPN score loss: 0.0074 RPN total loss: 0.04479 Total loss: 1.68657 timestamp: 1654928399.499663 iteration: 17510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09331 FastRCNN class loss: 0.05231 FastRCNN total loss: 0.14561 L1 loss: 0.0000e+00 L2 loss: 1.21408 Learning rate: 0.02 Mask loss: 0.11499 RPN box loss: 0.0383 RPN score loss: 0.00467 RPN total loss: 0.04297 Total loss: 1.51766 timestamp: 1654928402.739792 iteration: 17515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19137 FastRCNN class loss: 0.11048 FastRCNN total loss: 0.30184 L1 loss: 0.0000e+00 L2 loss: 1.21388 Learning rate: 0.02 Mask loss: 0.15601 RPN box loss: 0.026 RPN score loss: 0.01345 RPN total loss: 0.03945 Total loss: 1.71119 timestamp: 1654928406.0606477 iteration: 17520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.22476 L1 loss: 0.0000e+00 L2 loss: 1.2137 Learning rate: 0.02 Mask loss: 0.14246 RPN box loss: 0.03608 RPN score loss: 0.00581 RPN total loss: 0.04189 Total loss: 1.6228 timestamp: 1654928409.3667114 iteration: 17525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15721 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.22705 L1 loss: 0.0000e+00 L2 loss: 1.21348 Learning rate: 0.02 Mask loss: 0.24177 RPN box loss: 0.03269 RPN score loss: 0.0117 RPN total loss: 0.04438 Total loss: 1.7267 timestamp: 1654928412.6125493 iteration: 17530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18462 FastRCNN class loss: 0.14429 FastRCNN total loss: 0.32891 L1 loss: 0.0000e+00 L2 loss: 1.21328 Learning rate: 0.02 Mask loss: 0.24941 RPN box loss: 0.0578 RPN score loss: 0.01255 RPN total loss: 0.07035 Total loss: 1.86195 timestamp: 1654928415.874799 iteration: 17535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17862 FastRCNN class loss: 0.13832 FastRCNN total loss: 0.31693 L1 loss: 0.0000e+00 L2 loss: 1.21309 Learning rate: 0.02 Mask loss: 0.26935 RPN box loss: 0.03418 RPN score loss: 0.00669 RPN total loss: 0.04087 Total loss: 1.84025 timestamp: 1654928419.1575437 iteration: 17540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12145 FastRCNN class loss: 0.08556 FastRCNN total loss: 0.20701 L1 loss: 0.0000e+00 L2 loss: 1.21291 Learning rate: 0.02 Mask loss: 0.14108 RPN box loss: 0.02406 RPN score loss: 0.00272 RPN total loss: 0.02679 Total loss: 1.58778 timestamp: 1654928422.305459 iteration: 17545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10564 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.18184 L1 loss: 0.0000e+00 L2 loss: 1.21267 Learning rate: 0.02 Mask loss: 0.22622 RPN box loss: 0.08374 RPN score loss: 0.00577 RPN total loss: 0.08951 Total loss: 1.71023 timestamp: 1654928425.5906665 iteration: 17550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14384 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.22006 L1 loss: 0.0000e+00 L2 loss: 1.21246 Learning rate: 0.02 Mask loss: 0.11341 RPN box loss: 0.04564 RPN score loss: 0.00566 RPN total loss: 0.0513 Total loss: 1.59723 timestamp: 1654928428.764704 iteration: 17555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16187 FastRCNN class loss: 0.11412 FastRCNN total loss: 0.27599 L1 loss: 0.0000e+00 L2 loss: 1.21227 Learning rate: 0.02 Mask loss: 0.2166 RPN box loss: 0.04381 RPN score loss: 0.01187 RPN total loss: 0.05568 Total loss: 1.76055 timestamp: 1654928431.991747 iteration: 17560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13494 FastRCNN class loss: 0.09225 FastRCNN total loss: 0.22719 L1 loss: 0.0000e+00 L2 loss: 1.21208 Learning rate: 0.02 Mask loss: 0.22511 RPN box loss: 0.07525 RPN score loss: 0.0388 RPN total loss: 0.11405 Total loss: 1.77843 timestamp: 1654928435.2140224 iteration: 17565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0826 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.15556 L1 loss: 0.0000e+00 L2 loss: 1.21188 Learning rate: 0.02 Mask loss: 0.12682 RPN box loss: 0.02909 RPN score loss: 0.0098 RPN total loss: 0.03889 Total loss: 1.53315 timestamp: 1654928438.5229802 iteration: 17570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12812 FastRCNN class loss: 0.06919 FastRCNN total loss: 0.19731 L1 loss: 0.0000e+00 L2 loss: 1.21167 Learning rate: 0.02 Mask loss: 0.10629 RPN box loss: 0.04756 RPN score loss: 0.00278 RPN total loss: 0.05035 Total loss: 1.56562 timestamp: 1654928441.781859 iteration: 17575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1585 FastRCNN class loss: 0.08437 FastRCNN total loss: 0.24287 L1 loss: 0.0000e+00 L2 loss: 1.21146 Learning rate: 0.02 Mask loss: 0.1571 RPN box loss: 0.05315 RPN score loss: 0.01408 RPN total loss: 0.06723 Total loss: 1.67866 timestamp: 1654928445.0057006 iteration: 17580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20634 FastRCNN class loss: 0.09654 FastRCNN total loss: 0.30288 L1 loss: 0.0000e+00 L2 loss: 1.21126 Learning rate: 0.02 Mask loss: 0.32169 RPN box loss: 0.07705 RPN score loss: 0.011 RPN total loss: 0.08805 Total loss: 1.92388 timestamp: 1654928448.2962148 iteration: 17585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13061 FastRCNN class loss: 0.11392 FastRCNN total loss: 0.24453 L1 loss: 0.0000e+00 L2 loss: 1.21106 Learning rate: 0.02 Mask loss: 0.18566 RPN box loss: 0.0298 RPN score loss: 0.01114 RPN total loss: 0.04094 Total loss: 1.68219 timestamp: 1654928451.5744176 iteration: 17590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15218 FastRCNN class loss: 0.1005 FastRCNN total loss: 0.25268 L1 loss: 0.0000e+00 L2 loss: 1.21086 Learning rate: 0.02 Mask loss: 0.14321 RPN box loss: 0.05313 RPN score loss: 0.01464 RPN total loss: 0.06777 Total loss: 1.67452 timestamp: 1654928454.820475 iteration: 17595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21554 FastRCNN class loss: 0.14039 FastRCNN total loss: 0.35593 L1 loss: 0.0000e+00 L2 loss: 1.21067 Learning rate: 0.02 Mask loss: 0.22482 RPN box loss: 0.0324 RPN score loss: 0.01776 RPN total loss: 0.05015 Total loss: 1.84157 timestamp: 1654928458.0429611 iteration: 17600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1893 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.24761 L1 loss: 0.0000e+00 L2 loss: 1.21043 Learning rate: 0.02 Mask loss: 0.15484 RPN box loss: 0.0144 RPN score loss: 0.00433 RPN total loss: 0.01874 Total loss: 1.63162 timestamp: 1654928461.449687 iteration: 17605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08403 FastRCNN class loss: 0.06798 FastRCNN total loss: 0.15201 L1 loss: 0.0000e+00 L2 loss: 1.21022 Learning rate: 0.02 Mask loss: 0.09019 RPN box loss: 0.01622 RPN score loss: 0.00368 RPN total loss: 0.0199 Total loss: 1.47232 timestamp: 1654928464.6954608 iteration: 17610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11765 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.18298 L1 loss: 0.0000e+00 L2 loss: 1.21003 Learning rate: 0.02 Mask loss: 0.08398 RPN box loss: 0.01771 RPN score loss: 0.0015 RPN total loss: 0.01921 Total loss: 1.4962 timestamp: 1654928467.9682698 iteration: 17615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15434 FastRCNN class loss: 0.13076 FastRCNN total loss: 0.2851 L1 loss: 0.0000e+00 L2 loss: 1.20985 Learning rate: 0.02 Mask loss: 0.16417 RPN box loss: 0.04554 RPN score loss: 0.01844 RPN total loss: 0.06399 Total loss: 1.72311 timestamp: 1654928471.1353126 iteration: 17620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07889 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.1287 L1 loss: 0.0000e+00 L2 loss: 1.20968 Learning rate: 0.02 Mask loss: 0.15368 RPN box loss: 0.06835 RPN score loss: 0.00728 RPN total loss: 0.07563 Total loss: 1.56768 timestamp: 1654928474.3887079 iteration: 17625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12966 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.20398 L1 loss: 0.0000e+00 L2 loss: 1.20947 Learning rate: 0.02 Mask loss: 0.1891 RPN box loss: 0.07682 RPN score loss: 0.00776 RPN total loss: 0.08458 Total loss: 1.68713 timestamp: 1654928477.6807163 iteration: 17630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21596 FastRCNN class loss: 0.108 FastRCNN total loss: 0.32395 L1 loss: 0.0000e+00 L2 loss: 1.20927 Learning rate: 0.02 Mask loss: 0.18622 RPN box loss: 0.04953 RPN score loss: 0.01218 RPN total loss: 0.06171 Total loss: 1.78116 timestamp: 1654928480.8858933 iteration: 17635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19282 FastRCNN class loss: 0.08906 FastRCNN total loss: 0.28188 L1 loss: 0.0000e+00 L2 loss: 1.20909 Learning rate: 0.02 Mask loss: 0.18746 RPN box loss: 0.02474 RPN score loss: 0.00446 RPN total loss: 0.0292 Total loss: 1.70763 timestamp: 1654928484.191466 iteration: 17640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19048 FastRCNN class loss: 0.11168 FastRCNN total loss: 0.30216 L1 loss: 0.0000e+00 L2 loss: 1.20888 Learning rate: 0.02 Mask loss: 0.16823 RPN box loss: 0.02483 RPN score loss: 0.00932 RPN total loss: 0.03415 Total loss: 1.71342 timestamp: 1654928487.4624548 iteration: 17645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05515 FastRCNN class loss: 0.04945 FastRCNN total loss: 0.1046 L1 loss: 0.0000e+00 L2 loss: 1.2087 Learning rate: 0.02 Mask loss: 0.15354 RPN box loss: 0.0081 RPN score loss: 0.00591 RPN total loss: 0.01401 Total loss: 1.48084 timestamp: 1654928490.8114371 iteration: 17650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05006 FastRCNN class loss: 0.03649 FastRCNN total loss: 0.08655 L1 loss: 0.0000e+00 L2 loss: 1.2085 Learning rate: 0.02 Mask loss: 0.11403 RPN box loss: 0.00253 RPN score loss: 0.00257 RPN total loss: 0.0051 Total loss: 1.41419 timestamp: 1654928493.9979343 iteration: 17655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19433 FastRCNN class loss: 0.06592 FastRCNN total loss: 0.26025 L1 loss: 0.0000e+00 L2 loss: 1.20828 Learning rate: 0.02 Mask loss: 0.1215 RPN box loss: 0.03285 RPN score loss: 0.0037 RPN total loss: 0.03655 Total loss: 1.62658 timestamp: 1654928497.2847168 iteration: 17660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17469 FastRCNN class loss: 0.08901 FastRCNN total loss: 0.2637 L1 loss: 0.0000e+00 L2 loss: 1.20807 Learning rate: 0.02 Mask loss: 0.20833 RPN box loss: 0.05152 RPN score loss: 0.00502 RPN total loss: 0.05654 Total loss: 1.73664 timestamp: 1654928500.5261524 iteration: 17665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11896 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.17672 L1 loss: 0.0000e+00 L2 loss: 1.20784 Learning rate: 0.02 Mask loss: 0.13642 RPN box loss: 0.03615 RPN score loss: 0.00365 RPN total loss: 0.0398 Total loss: 1.56078 timestamp: 1654928503.9775052 iteration: 17670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16163 FastRCNN class loss: 0.0923 FastRCNN total loss: 0.25393 L1 loss: 0.0000e+00 L2 loss: 1.20762 Learning rate: 0.02 Mask loss: 0.18865 RPN box loss: 0.05306 RPN score loss: 0.01865 RPN total loss: 0.07171 Total loss: 1.72191 timestamp: 1654928507.2435756 iteration: 17675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23385 FastRCNN class loss: 0.10967 FastRCNN total loss: 0.34352 L1 loss: 0.0000e+00 L2 loss: 1.20741 Learning rate: 0.02 Mask loss: 0.19698 RPN box loss: 0.03134 RPN score loss: 0.00631 RPN total loss: 0.03765 Total loss: 1.78556 timestamp: 1654928510.398776 iteration: 17680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12235 FastRCNN class loss: 0.03839 FastRCNN total loss: 0.16074 L1 loss: 0.0000e+00 L2 loss: 1.20721 Learning rate: 0.02 Mask loss: 0.16726 RPN box loss: 0.08294 RPN score loss: 0.00757 RPN total loss: 0.09051 Total loss: 1.62573 timestamp: 1654928513.8046145 iteration: 17685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1003 FastRCNN class loss: 0.06344 FastRCNN total loss: 0.16374 L1 loss: 0.0000e+00 L2 loss: 1.207 Learning rate: 0.02 Mask loss: 0.1639 RPN box loss: 0.03936 RPN score loss: 0.00491 RPN total loss: 0.04427 Total loss: 1.57892 timestamp: 1654928517.0141165 iteration: 17690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18856 FastRCNN class loss: 0.12157 FastRCNN total loss: 0.31013 L1 loss: 0.0000e+00 L2 loss: 1.20681 Learning rate: 0.02 Mask loss: 0.23252 RPN box loss: 0.04495 RPN score loss: 0.00276 RPN total loss: 0.04771 Total loss: 1.79716 timestamp: 1654928520.3534884 iteration: 17695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16236 FastRCNN class loss: 0.11864 FastRCNN total loss: 0.281 L1 loss: 0.0000e+00 L2 loss: 1.20663 Learning rate: 0.02 Mask loss: 0.20199 RPN box loss: 0.01946 RPN score loss: 0.00619 RPN total loss: 0.02565 Total loss: 1.71527 timestamp: 1654928523.592904 iteration: 17700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1501 FastRCNN class loss: 0.08864 FastRCNN total loss: 0.23873 L1 loss: 0.0000e+00 L2 loss: 1.20645 Learning rate: 0.02 Mask loss: 0.1343 RPN box loss: 0.03053 RPN score loss: 0.00337 RPN total loss: 0.03389 Total loss: 1.61337 timestamp: 1654928526.8790298 iteration: 17705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18147 FastRCNN class loss: 0.10226 FastRCNN total loss: 0.28373 L1 loss: 0.0000e+00 L2 loss: 1.20626 Learning rate: 0.02 Mask loss: 0.17443 RPN box loss: 0.03773 RPN score loss: 0.00772 RPN total loss: 0.04545 Total loss: 1.70987 timestamp: 1654928530.0230246 iteration: 17710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14256 FastRCNN class loss: 0.09892 FastRCNN total loss: 0.24148 L1 loss: 0.0000e+00 L2 loss: 1.20604 Learning rate: 0.02 Mask loss: 0.25759 RPN box loss: 0.0895 RPN score loss: 0.01076 RPN total loss: 0.10026 Total loss: 1.80538 timestamp: 1654928533.3296473 iteration: 17715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17832 FastRCNN class loss: 0.09047 FastRCNN total loss: 0.26878 L1 loss: 0.0000e+00 L2 loss: 1.20583 Learning rate: 0.02 Mask loss: 0.23972 RPN box loss: 0.01449 RPN score loss: 0.0087 RPN total loss: 0.02319 Total loss: 1.73753 timestamp: 1654928536.5290785 iteration: 17720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21179 FastRCNN class loss: 0.11468 FastRCNN total loss: 0.32648 L1 loss: 0.0000e+00 L2 loss: 1.20563 Learning rate: 0.02 Mask loss: 0.21265 RPN box loss: 0.05071 RPN score loss: 0.01117 RPN total loss: 0.06188 Total loss: 1.80663 timestamp: 1654928539.7876863 iteration: 17725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10658 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.16805 L1 loss: 0.0000e+00 L2 loss: 1.20541 Learning rate: 0.02 Mask loss: 0.11829 RPN box loss: 0.04054 RPN score loss: 0.00904 RPN total loss: 0.04958 Total loss: 1.54134 timestamp: 1654928543.1376748 iteration: 17730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10548 FastRCNN class loss: 0.09469 FastRCNN total loss: 0.20017 L1 loss: 0.0000e+00 L2 loss: 1.2052 Learning rate: 0.02 Mask loss: 0.19081 RPN box loss: 0.03094 RPN score loss: 0.02422 RPN total loss: 0.05517 Total loss: 1.65134 timestamp: 1654928546.3463202 iteration: 17735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16718 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.23278 L1 loss: 0.0000e+00 L2 loss: 1.20498 Learning rate: 0.02 Mask loss: 0.10838 RPN box loss: 0.02706 RPN score loss: 0.00483 RPN total loss: 0.03189 Total loss: 1.57802 timestamp: 1654928549.697693 iteration: 17740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22892 FastRCNN class loss: 0.08228 FastRCNN total loss: 0.3112 L1 loss: 0.0000e+00 L2 loss: 1.20475 Learning rate: 0.02 Mask loss: 0.09879 RPN box loss: 0.00978 RPN score loss: 0.00465 RPN total loss: 0.01443 Total loss: 1.62917 timestamp: 1654928552.985332 iteration: 17745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16189 FastRCNN class loss: 0.06918 FastRCNN total loss: 0.23106 L1 loss: 0.0000e+00 L2 loss: 1.20455 Learning rate: 0.02 Mask loss: 0.12656 RPN box loss: 0.0243 RPN score loss: 0.00539 RPN total loss: 0.02969 Total loss: 1.59186 timestamp: 1654928556.2471662 iteration: 17750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14523 FastRCNN class loss: 0.07064 FastRCNN total loss: 0.21587 L1 loss: 0.0000e+00 L2 loss: 1.20435 Learning rate: 0.02 Mask loss: 0.13578 RPN box loss: 0.03336 RPN score loss: 0.00378 RPN total loss: 0.03714 Total loss: 1.59314 timestamp: 1654928559.4316516 iteration: 17755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19019 FastRCNN class loss: 0.10446 FastRCNN total loss: 0.29465 L1 loss: 0.0000e+00 L2 loss: 1.20416 Learning rate: 0.02 Mask loss: 0.1667 RPN box loss: 0.05683 RPN score loss: 0.00879 RPN total loss: 0.06562 Total loss: 1.73113 timestamp: 1654928562.7425056 iteration: 17760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16322 FastRCNN class loss: 0.12401 FastRCNN total loss: 0.28724 L1 loss: 0.0000e+00 L2 loss: 1.20394 Learning rate: 0.02 Mask loss: 0.20749 RPN box loss: 0.06202 RPN score loss: 0.01032 RPN total loss: 0.07233 Total loss: 1.771 timestamp: 1654928565.9021444 iteration: 17765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18341 FastRCNN class loss: 0.07068 FastRCNN total loss: 0.25409 L1 loss: 0.0000e+00 L2 loss: 1.20376 Learning rate: 0.02 Mask loss: 0.13025 RPN box loss: 0.01165 RPN score loss: 0.00246 RPN total loss: 0.01411 Total loss: 1.60222 timestamp: 1654928569.306582 iteration: 17770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10669 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.17914 L1 loss: 0.0000e+00 L2 loss: 1.20357 Learning rate: 0.02 Mask loss: 0.09724 RPN box loss: 0.02386 RPN score loss: 0.00662 RPN total loss: 0.03049 Total loss: 1.51042 timestamp: 1654928572.619668 iteration: 17775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14779 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.20349 L1 loss: 0.0000e+00 L2 loss: 1.20338 Learning rate: 0.02 Mask loss: 0.14939 RPN box loss: 0.01762 RPN score loss: 0.00558 RPN total loss: 0.0232 Total loss: 1.57946 timestamp: 1654928575.823711 iteration: 17780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2526 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.33561 L1 loss: 0.0000e+00 L2 loss: 1.20317 Learning rate: 0.02 Mask loss: 0.16271 RPN box loss: 0.00997 RPN score loss: 0.00417 RPN total loss: 0.01414 Total loss: 1.71564 timestamp: 1654928579.0383513 iteration: 17785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14225 FastRCNN class loss: 0.11827 FastRCNN total loss: 0.26052 L1 loss: 0.0000e+00 L2 loss: 1.20294 Learning rate: 0.02 Mask loss: 0.17973 RPN box loss: 0.03248 RPN score loss: 0.01036 RPN total loss: 0.04284 Total loss: 1.68603 timestamp: 1654928582.292189 iteration: 17790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12604 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.19872 L1 loss: 0.0000e+00 L2 loss: 1.20276 Learning rate: 0.02 Mask loss: 0.19607 RPN box loss: 0.01842 RPN score loss: 0.00826 RPN total loss: 0.02668 Total loss: 1.62422 timestamp: 1654928585.5952353 iteration: 17795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17886 FastRCNN class loss: 0.09082 FastRCNN total loss: 0.26967 L1 loss: 0.0000e+00 L2 loss: 1.20257 Learning rate: 0.02 Mask loss: 0.13491 RPN box loss: 0.02387 RPN score loss: 0.00612 RPN total loss: 0.02999 Total loss: 1.63714 timestamp: 1654928588.824933 iteration: 17800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09637 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.15494 L1 loss: 0.0000e+00 L2 loss: 1.20235 Learning rate: 0.02 Mask loss: 0.12299 RPN box loss: 0.03196 RPN score loss: 0.0091 RPN total loss: 0.04106 Total loss: 1.52134 timestamp: 1654928592.1008914 iteration: 17805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21783 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.28177 L1 loss: 0.0000e+00 L2 loss: 1.20216 Learning rate: 0.02 Mask loss: 0.14334 RPN box loss: 0.0483 RPN score loss: 0.00371 RPN total loss: 0.05201 Total loss: 1.67927 timestamp: 1654928595.2062643 iteration: 17810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08308 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.13725 L1 loss: 0.0000e+00 L2 loss: 1.20197 Learning rate: 0.02 Mask loss: 0.12821 RPN box loss: 0.04296 RPN score loss: 0.00921 RPN total loss: 0.05217 Total loss: 1.51959 timestamp: 1654928598.590944 iteration: 17815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.19223 L1 loss: 0.0000e+00 L2 loss: 1.20176 Learning rate: 0.02 Mask loss: 0.12966 RPN box loss: 0.01294 RPN score loss: 0.00573 RPN total loss: 0.01867 Total loss: 1.54233 timestamp: 1654928601.7197678 iteration: 17820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15592 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.22837 L1 loss: 0.0000e+00 L2 loss: 1.20154 Learning rate: 0.02 Mask loss: 0.14628 RPN box loss: 0.01515 RPN score loss: 0.00282 RPN total loss: 0.01797 Total loss: 1.59417 timestamp: 1654928605.0512345 iteration: 17825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14458 FastRCNN class loss: 0.10347 FastRCNN total loss: 0.24805 L1 loss: 0.0000e+00 L2 loss: 1.20132 Learning rate: 0.02 Mask loss: 0.28519 RPN box loss: 0.02273 RPN score loss: 0.00378 RPN total loss: 0.02651 Total loss: 1.76107 timestamp: 1654928608.4140496 iteration: 17830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15854 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.21966 L1 loss: 0.0000e+00 L2 loss: 1.20111 Learning rate: 0.02 Mask loss: 0.13802 RPN box loss: 0.01735 RPN score loss: 0.01066 RPN total loss: 0.02801 Total loss: 1.5868 timestamp: 1654928611.5975225 iteration: 17835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11762 FastRCNN class loss: 0.08394 FastRCNN total loss: 0.20156 L1 loss: 0.0000e+00 L2 loss: 1.20093 Learning rate: 0.02 Mask loss: 0.13201 RPN box loss: 0.03043 RPN score loss: 0.00353 RPN total loss: 0.03396 Total loss: 1.56845 timestamp: 1654928614.8135657 iteration: 17840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13921 FastRCNN class loss: 0.07028 FastRCNN total loss: 0.20949 L1 loss: 0.0000e+00 L2 loss: 1.20074 Learning rate: 0.02 Mask loss: 0.16304 RPN box loss: 0.03156 RPN score loss: 0.00412 RPN total loss: 0.03567 Total loss: 1.60894 timestamp: 1654928617.9985473 iteration: 17845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18008 FastRCNN class loss: 0.09401 FastRCNN total loss: 0.27408 L1 loss: 0.0000e+00 L2 loss: 1.20054 Learning rate: 0.02 Mask loss: 0.13144 RPN box loss: 0.01964 RPN score loss: 0.00354 RPN total loss: 0.02319 Total loss: 1.62925 timestamp: 1654928621.2387178 iteration: 17850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19971 FastRCNN class loss: 0.10701 FastRCNN total loss: 0.30673 L1 loss: 0.0000e+00 L2 loss: 1.20033 Learning rate: 0.02 Mask loss: 0.16548 RPN box loss: 0.05395 RPN score loss: 0.00979 RPN total loss: 0.06374 Total loss: 1.73627 timestamp: 1654928624.4523642 iteration: 17855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18245 FastRCNN class loss: 0.05598 FastRCNN total loss: 0.23843 L1 loss: 0.0000e+00 L2 loss: 1.20011 Learning rate: 0.02 Mask loss: 0.11858 RPN box loss: 0.01866 RPN score loss: 0.00623 RPN total loss: 0.0249 Total loss: 1.58202 timestamp: 1654928627.819676 iteration: 17860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09956 FastRCNN class loss: 0.0454 FastRCNN total loss: 0.14496 L1 loss: 0.0000e+00 L2 loss: 1.19993 Learning rate: 0.02 Mask loss: 0.11876 RPN box loss: 0.02617 RPN score loss: 0.00212 RPN total loss: 0.02829 Total loss: 1.49194 timestamp: 1654928631.054212 iteration: 17865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16243 FastRCNN class loss: 0.10704 FastRCNN total loss: 0.26947 L1 loss: 0.0000e+00 L2 loss: 1.19975 Learning rate: 0.02 Mask loss: 0.14446 RPN box loss: 0.0352 RPN score loss: 0.01034 RPN total loss: 0.04554 Total loss: 1.65922 timestamp: 1654928634.3177395 iteration: 17870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11376 FastRCNN class loss: 0.07009 FastRCNN total loss: 0.18385 L1 loss: 0.0000e+00 L2 loss: 1.19954 Learning rate: 0.02 Mask loss: 0.18662 RPN box loss: 0.02663 RPN score loss: 0.0032 RPN total loss: 0.02983 Total loss: 1.59983 timestamp: 1654928637.5839796 iteration: 17875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14309 FastRCNN class loss: 0.06113 FastRCNN total loss: 0.20422 L1 loss: 0.0000e+00 L2 loss: 1.19934 Learning rate: 0.02 Mask loss: 0.1483 RPN box loss: 0.0322 RPN score loss: 0.00664 RPN total loss: 0.03884 Total loss: 1.5907 timestamp: 1654928640.8489761 iteration: 17880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08536 FastRCNN class loss: 0.04921 FastRCNN total loss: 0.13457 L1 loss: 0.0000e+00 L2 loss: 1.19913 Learning rate: 0.02 Mask loss: 0.16927 RPN box loss: 0.0283 RPN score loss: 0.00589 RPN total loss: 0.0342 Total loss: 1.53717 timestamp: 1654928644.1056442 iteration: 17885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10332 FastRCNN class loss: 0.07973 FastRCNN total loss: 0.18305 L1 loss: 0.0000e+00 L2 loss: 1.19893 Learning rate: 0.02 Mask loss: 0.23086 RPN box loss: 0.05129 RPN score loss: 0.00348 RPN total loss: 0.05477 Total loss: 1.6676 timestamp: 1654928647.393814 iteration: 17890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14553 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.22061 L1 loss: 0.0000e+00 L2 loss: 1.19875 Learning rate: 0.02 Mask loss: 0.14726 RPN box loss: 0.02818 RPN score loss: 0.00321 RPN total loss: 0.0314 Total loss: 1.59801 timestamp: 1654928650.6933494 iteration: 17895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15806 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.21883 L1 loss: 0.0000e+00 L2 loss: 1.19854 Learning rate: 0.02 Mask loss: 0.12362 RPN box loss: 0.04344 RPN score loss: 0.00539 RPN total loss: 0.04883 Total loss: 1.58983 timestamp: 1654928653.901941 iteration: 17900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08836 FastRCNN class loss: 0.09194 FastRCNN total loss: 0.1803 L1 loss: 0.0000e+00 L2 loss: 1.19834 Learning rate: 0.02 Mask loss: 0.15358 RPN box loss: 0.00652 RPN score loss: 0.00495 RPN total loss: 0.01147 Total loss: 1.54368 timestamp: 1654928657.153513 iteration: 17905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15188 FastRCNN class loss: 0.12511 FastRCNN total loss: 0.27699 L1 loss: 0.0000e+00 L2 loss: 1.19813 Learning rate: 0.02 Mask loss: 0.16048 RPN box loss: 0.04509 RPN score loss: 0.01359 RPN total loss: 0.05868 Total loss: 1.69427 timestamp: 1654928660.3091795 iteration: 17910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.04862 FastRCNN total loss: 0.15943 L1 loss: 0.0000e+00 L2 loss: 1.19793 Learning rate: 0.02 Mask loss: 0.12273 RPN box loss: 0.01373 RPN score loss: 0.00147 RPN total loss: 0.0152 Total loss: 1.49529 timestamp: 1654928663.5631542 iteration: 17915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17528 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.25011 L1 loss: 0.0000e+00 L2 loss: 1.19773 Learning rate: 0.02 Mask loss: 0.15906 RPN box loss: 0.01248 RPN score loss: 0.00637 RPN total loss: 0.01885 Total loss: 1.62574 timestamp: 1654928666.7141845 iteration: 17920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15218 FastRCNN class loss: 0.0602 FastRCNN total loss: 0.21238 L1 loss: 0.0000e+00 L2 loss: 1.19754 Learning rate: 0.02 Mask loss: 0.12437 RPN box loss: 0.01704 RPN score loss: 0.00305 RPN total loss: 0.0201 Total loss: 1.55438 timestamp: 1654928670.0834265 iteration: 17925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14639 FastRCNN class loss: 0.07858 FastRCNN total loss: 0.22496 L1 loss: 0.0000e+00 L2 loss: 1.19735 Learning rate: 0.02 Mask loss: 0.1549 RPN box loss: 0.00848 RPN score loss: 0.00444 RPN total loss: 0.01292 Total loss: 1.59013 timestamp: 1654928673.3560781 iteration: 17930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1275 FastRCNN class loss: 0.09372 FastRCNN total loss: 0.22122 L1 loss: 0.0000e+00 L2 loss: 1.19714 Learning rate: 0.02 Mask loss: 0.14657 RPN box loss: 0.01269 RPN score loss: 0.00318 RPN total loss: 0.01587 Total loss: 1.5808 timestamp: 1654928676.5806038 iteration: 17935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1088 FastRCNN class loss: 0.08478 FastRCNN total loss: 0.19358 L1 loss: 0.0000e+00 L2 loss: 1.19694 Learning rate: 0.02 Mask loss: 0.1325 RPN box loss: 0.01653 RPN score loss: 0.00395 RPN total loss: 0.02048 Total loss: 1.5435 timestamp: 1654928679.7837536 iteration: 17940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13634 FastRCNN class loss: 0.0878 FastRCNN total loss: 0.22414 L1 loss: 0.0000e+00 L2 loss: 1.19676 Learning rate: 0.02 Mask loss: 0.13928 RPN box loss: 0.00979 RPN score loss: 0.00199 RPN total loss: 0.01177 Total loss: 1.57196 timestamp: 1654928683.0818663 iteration: 17945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14129 FastRCNN class loss: 0.05792 FastRCNN total loss: 0.19921 L1 loss: 0.0000e+00 L2 loss: 1.19654 Learning rate: 0.02 Mask loss: 0.1068 RPN box loss: 0.03518 RPN score loss: 0.00388 RPN total loss: 0.03906 Total loss: 1.54161 timestamp: 1654928686.4505444 iteration: 17950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08206 FastRCNN class loss: 0.04823 FastRCNN total loss: 0.13029 L1 loss: 0.0000e+00 L2 loss: 1.19633 Learning rate: 0.02 Mask loss: 0.12355 RPN box loss: 0.01924 RPN score loss: 0.00224 RPN total loss: 0.02148 Total loss: 1.47165 timestamp: 1654928689.626475 iteration: 17955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16631 FastRCNN class loss: 0.10375 FastRCNN total loss: 0.27006 L1 loss: 0.0000e+00 L2 loss: 1.19615 Learning rate: 0.02 Mask loss: 0.16872 RPN box loss: 0.05102 RPN score loss: 0.00807 RPN total loss: 0.05909 Total loss: 1.69401 timestamp: 1654928692.7581906 iteration: 17960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18484 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.2734 L1 loss: 0.0000e+00 L2 loss: 1.19594 Learning rate: 0.02 Mask loss: 0.17334 RPN box loss: 0.18319 RPN score loss: 0.01005 RPN total loss: 0.19324 Total loss: 1.83592 timestamp: 1654928695.9527175 iteration: 17965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11316 FastRCNN class loss: 0.04555 FastRCNN total loss: 0.15871 L1 loss: 0.0000e+00 L2 loss: 1.19574 Learning rate: 0.02 Mask loss: 0.10586 RPN box loss: 0.01519 RPN score loss: 0.00872 RPN total loss: 0.0239 Total loss: 1.48422 timestamp: 1654928699.2084975 iteration: 17970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1666 FastRCNN class loss: 0.07886 FastRCNN total loss: 0.24546 L1 loss: 0.0000e+00 L2 loss: 1.19554 Learning rate: 0.02 Mask loss: 0.16598 RPN box loss: 0.05133 RPN score loss: 0.00259 RPN total loss: 0.05392 Total loss: 1.6609 timestamp: 1654928702.4278874 iteration: 17975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14377 FastRCNN class loss: 0.09732 FastRCNN total loss: 0.24108 L1 loss: 0.0000e+00 L2 loss: 1.19532 Learning rate: 0.02 Mask loss: 0.15812 RPN box loss: 0.0534 RPN score loss: 0.01366 RPN total loss: 0.06706 Total loss: 1.66158 timestamp: 1654928705.7001035 iteration: 17980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.07551 FastRCNN total loss: 0.18799 L1 loss: 0.0000e+00 L2 loss: 1.19512 Learning rate: 0.02 Mask loss: 0.14443 RPN box loss: 0.01447 RPN score loss: 0.00466 RPN total loss: 0.01914 Total loss: 1.54669 timestamp: 1654928708.8367841 iteration: 17985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20517 FastRCNN class loss: 0.10608 FastRCNN total loss: 0.31125 L1 loss: 0.0000e+00 L2 loss: 1.19496 Learning rate: 0.02 Mask loss: 0.179 RPN box loss: 0.02627 RPN score loss: 0.00759 RPN total loss: 0.03386 Total loss: 1.71907 timestamp: 1654928712.085082 iteration: 17990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.10943 FastRCNN total loss: 0.25223 L1 loss: 0.0000e+00 L2 loss: 1.19477 Learning rate: 0.02 Mask loss: 0.15053 RPN box loss: 0.03299 RPN score loss: 0.00821 RPN total loss: 0.0412 Total loss: 1.63872 timestamp: 1654928715.3000538 iteration: 17995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17039 FastRCNN class loss: 0.08508 FastRCNN total loss: 0.25547 L1 loss: 0.0000e+00 L2 loss: 1.19458 Learning rate: 0.02 Mask loss: 0.17649 RPN box loss: 0.04864 RPN score loss: 0.01317 RPN total loss: 0.06181 Total loss: 1.68834 timestamp: 1654928718.5477347 iteration: 18000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14082 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.19569 L1 loss: 0.0000e+00 L2 loss: 1.19438 Learning rate: 0.02 Mask loss: 0.17108 RPN box loss: 0.04 RPN score loss: 0.0086 RPN total loss: 0.0486 Total loss: 1.60975 timestamp: 1654928721.7970347 iteration: 18005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1345 FastRCNN class loss: 0.07654 FastRCNN total loss: 0.21104 L1 loss: 0.0000e+00 L2 loss: 1.1942 Learning rate: 0.02 Mask loss: 0.10087 RPN box loss: 0.01907 RPN score loss: 0.00592 RPN total loss: 0.02498 Total loss: 1.53109 timestamp: 1654928724.9895427 iteration: 18010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15796 FastRCNN class loss: 0.07261 FastRCNN total loss: 0.23056 L1 loss: 0.0000e+00 L2 loss: 1.19401 Learning rate: 0.02 Mask loss: 0.15578 RPN box loss: 0.05947 RPN score loss: 0.00488 RPN total loss: 0.06435 Total loss: 1.64471 timestamp: 1654928728.2813947 iteration: 18015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1316 FastRCNN class loss: 0.12298 FastRCNN total loss: 0.25458 L1 loss: 0.0000e+00 L2 loss: 1.19378 Learning rate: 0.02 Mask loss: 0.11986 RPN box loss: 0.05188 RPN score loss: 0.00364 RPN total loss: 0.05552 Total loss: 1.62374 timestamp: 1654928731.5424702 iteration: 18020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09816 FastRCNN class loss: 0.07951 FastRCNN total loss: 0.17768 L1 loss: 0.0000e+00 L2 loss: 1.19358 Learning rate: 0.02 Mask loss: 0.16255 RPN box loss: 0.05289 RPN score loss: 0.00593 RPN total loss: 0.05882 Total loss: 1.59262 timestamp: 1654928734.866354 iteration: 18025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18398 FastRCNN class loss: 0.08329 FastRCNN total loss: 0.26727 L1 loss: 0.0000e+00 L2 loss: 1.19339 Learning rate: 0.02 Mask loss: 0.17892 RPN box loss: 0.06056 RPN score loss: 0.01148 RPN total loss: 0.07204 Total loss: 1.71162 timestamp: 1654928738.0477495 iteration: 18030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23667 FastRCNN class loss: 0.10349 FastRCNN total loss: 0.34015 L1 loss: 0.0000e+00 L2 loss: 1.19318 Learning rate: 0.02 Mask loss: 0.14563 RPN box loss: 0.01733 RPN score loss: 0.01005 RPN total loss: 0.02738 Total loss: 1.70634 timestamp: 1654928741.2837057 iteration: 18035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1024 FastRCNN class loss: 0.12549 FastRCNN total loss: 0.22789 L1 loss: 0.0000e+00 L2 loss: 1.19299 Learning rate: 0.02 Mask loss: 0.18664 RPN box loss: 0.04669 RPN score loss: 0.01257 RPN total loss: 0.05926 Total loss: 1.66678 timestamp: 1654928744.556827 iteration: 18040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.05556 FastRCNN total loss: 0.13352 L1 loss: 0.0000e+00 L2 loss: 1.19278 Learning rate: 0.02 Mask loss: 0.0996 RPN box loss: 0.01357 RPN score loss: 0.00452 RPN total loss: 0.01809 Total loss: 1.44399 timestamp: 1654928747.9181135 iteration: 18045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27285 FastRCNN class loss: 0.13216 FastRCNN total loss: 0.40501 L1 loss: 0.0000e+00 L2 loss: 1.19257 Learning rate: 0.02 Mask loss: 0.23391 RPN box loss: 0.01795 RPN score loss: 0.00597 RPN total loss: 0.02391 Total loss: 1.8554 timestamp: 1654928751.1689756 iteration: 18050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10544 FastRCNN class loss: 0.05819 FastRCNN total loss: 0.16363 L1 loss: 0.0000e+00 L2 loss: 1.19238 Learning rate: 0.02 Mask loss: 0.15251 RPN box loss: 0.00869 RPN score loss: 0.00463 RPN total loss: 0.01332 Total loss: 1.52183 timestamp: 1654928754.4168537 iteration: 18055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12659 FastRCNN class loss: 0.06644 FastRCNN total loss: 0.19303 L1 loss: 0.0000e+00 L2 loss: 1.19218 Learning rate: 0.02 Mask loss: 0.17372 RPN box loss: 0.02516 RPN score loss: 0.00287 RPN total loss: 0.02803 Total loss: 1.58696 timestamp: 1654928757.6694508 iteration: 18060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.08102 FastRCNN total loss: 0.14969 L1 loss: 0.0000e+00 L2 loss: 1.192 Learning rate: 0.02 Mask loss: 0.08642 RPN box loss: 0.01115 RPN score loss: 0.00762 RPN total loss: 0.01877 Total loss: 1.44687 timestamp: 1654928760.8695314 iteration: 18065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22267 FastRCNN class loss: 0.15893 FastRCNN total loss: 0.3816 L1 loss: 0.0000e+00 L2 loss: 1.19178 Learning rate: 0.02 Mask loss: 0.15292 RPN box loss: 0.0343 RPN score loss: 0.0124 RPN total loss: 0.0467 Total loss: 1.773 timestamp: 1654928764.148218 iteration: 18070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12007 FastRCNN class loss: 0.1154 FastRCNN total loss: 0.23547 L1 loss: 0.0000e+00 L2 loss: 1.19157 Learning rate: 0.02 Mask loss: 0.21512 RPN box loss: 0.02926 RPN score loss: 0.00543 RPN total loss: 0.03469 Total loss: 1.67685 timestamp: 1654928767.3193905 iteration: 18075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18894 FastRCNN class loss: 0.11328 FastRCNN total loss: 0.30223 L1 loss: 0.0000e+00 L2 loss: 1.19136 Learning rate: 0.02 Mask loss: 0.21763 RPN box loss: 0.01831 RPN score loss: 0.00193 RPN total loss: 0.02025 Total loss: 1.73147 timestamp: 1654928770.5782244 iteration: 18080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21687 FastRCNN class loss: 0.11056 FastRCNN total loss: 0.32743 L1 loss: 0.0000e+00 L2 loss: 1.19117 Learning rate: 0.02 Mask loss: 0.20473 RPN box loss: 0.02921 RPN score loss: 0.009 RPN total loss: 0.03821 Total loss: 1.76154 timestamp: 1654928773.7338164 iteration: 18085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13825 FastRCNN class loss: 0.05661 FastRCNN total loss: 0.19486 L1 loss: 0.0000e+00 L2 loss: 1.191 Learning rate: 0.02 Mask loss: 0.27576 RPN box loss: 0.0267 RPN score loss: 0.00436 RPN total loss: 0.03106 Total loss: 1.69268 timestamp: 1654928777.1037683 iteration: 18090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14678 FastRCNN class loss: 0.05959 FastRCNN total loss: 0.20637 L1 loss: 0.0000e+00 L2 loss: 1.19079 Learning rate: 0.02 Mask loss: 0.11731 RPN box loss: 0.03032 RPN score loss: 0.00411 RPN total loss: 0.03443 Total loss: 1.5489 timestamp: 1654928780.2804031 iteration: 18095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08865 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.17733 L1 loss: 0.0000e+00 L2 loss: 1.19057 Learning rate: 0.02 Mask loss: 0.11214 RPN box loss: 0.05055 RPN score loss: 0.00331 RPN total loss: 0.05387 Total loss: 1.5339 timestamp: 1654928783.6113825 iteration: 18100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07732 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.12777 L1 loss: 0.0000e+00 L2 loss: 1.19038 Learning rate: 0.02 Mask loss: 0.12804 RPN box loss: 0.02034 RPN score loss: 0.002 RPN total loss: 0.02234 Total loss: 1.46853 timestamp: 1654928786.7637932 iteration: 18105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11143 FastRCNN class loss: 0.10897 FastRCNN total loss: 0.2204 L1 loss: 0.0000e+00 L2 loss: 1.19016 Learning rate: 0.02 Mask loss: 0.26759 RPN box loss: 0.04867 RPN score loss: 0.01055 RPN total loss: 0.05922 Total loss: 1.73737 timestamp: 1654928790.0161836 iteration: 18110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11068 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.16892 L1 loss: 0.0000e+00 L2 loss: 1.18996 Learning rate: 0.02 Mask loss: 0.15406 RPN box loss: 0.05284 RPN score loss: 0.00445 RPN total loss: 0.05729 Total loss: 1.57024 timestamp: 1654928793.303948 iteration: 18115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15617 FastRCNN class loss: 0.0853 FastRCNN total loss: 0.24147 L1 loss: 0.0000e+00 L2 loss: 1.18978 Learning rate: 0.02 Mask loss: 0.1409 RPN box loss: 0.02347 RPN score loss: 0.00381 RPN total loss: 0.02728 Total loss: 1.59943 timestamp: 1654928796.4239218 iteration: 18120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15891 FastRCNN class loss: 0.07762 FastRCNN total loss: 0.23653 L1 loss: 0.0000e+00 L2 loss: 1.18958 Learning rate: 0.02 Mask loss: 0.15137 RPN box loss: 0.0305 RPN score loss: 0.00366 RPN total loss: 0.03415 Total loss: 1.61163 timestamp: 1654928799.6490586 iteration: 18125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19634 FastRCNN class loss: 0.16965 FastRCNN total loss: 0.36599 L1 loss: 0.0000e+00 L2 loss: 1.18938 Learning rate: 0.02 Mask loss: 0.21407 RPN box loss: 0.04837 RPN score loss: 0.02231 RPN total loss: 0.07068 Total loss: 1.84013 timestamp: 1654928802.839788 iteration: 18130 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11519 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.16808 L1 loss: 0.0000e+00 L2 loss: 1.18919 Learning rate: 0.02 Mask loss: 0.10384 RPN box loss: 0.06491 RPN score loss: 0.0064 RPN total loss: 0.07131 Total loss: 1.53241 timestamp: 1654928806.2327545 iteration: 18135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11181 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.16686 L1 loss: 0.0000e+00 L2 loss: 1.18898 Learning rate: 0.02 Mask loss: 0.16493 RPN box loss: 0.03836 RPN score loss: 0.00365 RPN total loss: 0.04202 Total loss: 1.56278 timestamp: 1654928809.4638429 iteration: 18140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09513 FastRCNN class loss: 0.05976 FastRCNN total loss: 0.15489 L1 loss: 0.0000e+00 L2 loss: 1.18877 Learning rate: 0.02 Mask loss: 0.10285 RPN box loss: 0.05111 RPN score loss: 0.00964 RPN total loss: 0.06074 Total loss: 1.50724 timestamp: 1654928812.7837937 iteration: 18145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14809 FastRCNN class loss: 0.0875 FastRCNN total loss: 0.23559 L1 loss: 0.0000e+00 L2 loss: 1.18857 Learning rate: 0.02 Mask loss: 0.29973 RPN box loss: 0.04034 RPN score loss: 0.0053 RPN total loss: 0.04564 Total loss: 1.76953 timestamp: 1654928816.0629318 iteration: 18150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17415 FastRCNN class loss: 0.21321 FastRCNN total loss: 0.38735 L1 loss: 0.0000e+00 L2 loss: 1.18837 Learning rate: 0.02 Mask loss: 0.18056 RPN box loss: 0.03914 RPN score loss: 0.0217 RPN total loss: 0.06084 Total loss: 1.81713 timestamp: 1654928819.302841 iteration: 18155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09967 FastRCNN class loss: 0.03963 FastRCNN total loss: 0.13929 L1 loss: 0.0000e+00 L2 loss: 1.18819 Learning rate: 0.02 Mask loss: 0.1392 RPN box loss: 0.03159 RPN score loss: 0.00829 RPN total loss: 0.03988 Total loss: 1.50655 timestamp: 1654928822.5535483 iteration: 18160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24728 FastRCNN class loss: 0.11338 FastRCNN total loss: 0.36067 L1 loss: 0.0000e+00 L2 loss: 1.18798 Learning rate: 0.02 Mask loss: 0.14634 RPN box loss: 0.03999 RPN score loss: 0.0091 RPN total loss: 0.04909 Total loss: 1.74407 timestamp: 1654928825.814646 iteration: 18165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12813 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.20435 L1 loss: 0.0000e+00 L2 loss: 1.18777 Learning rate: 0.02 Mask loss: 0.17771 RPN box loss: 0.02668 RPN score loss: 0.00681 RPN total loss: 0.0335 Total loss: 1.60332 timestamp: 1654928829.0753965 iteration: 18170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16383 FastRCNN class loss: 0.0873 FastRCNN total loss: 0.25113 L1 loss: 0.0000e+00 L2 loss: 1.18758 Learning rate: 0.02 Mask loss: 0.17929 RPN box loss: 0.04037 RPN score loss: 0.02409 RPN total loss: 0.06446 Total loss: 1.68246 timestamp: 1654928832.3611681 iteration: 18175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.09491 FastRCNN total loss: 0.19709 L1 loss: 0.0000e+00 L2 loss: 1.18741 Learning rate: 0.02 Mask loss: 0.1425 RPN box loss: 0.01229 RPN score loss: 0.00232 RPN total loss: 0.01462 Total loss: 1.54162 timestamp: 1654928835.6889484 iteration: 18180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16636 FastRCNN class loss: 0.13721 FastRCNN total loss: 0.30357 L1 loss: 0.0000e+00 L2 loss: 1.18722 Learning rate: 0.02 Mask loss: 0.17029 RPN box loss: 0.02994 RPN score loss: 0.0148 RPN total loss: 0.04474 Total loss: 1.70582 timestamp: 1654928838.9501238 iteration: 18185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13609 FastRCNN class loss: 0.07716 FastRCNN total loss: 0.21326 L1 loss: 0.0000e+00 L2 loss: 1.18702 Learning rate: 0.02 Mask loss: 0.1571 RPN box loss: 0.02056 RPN score loss: 0.004 RPN total loss: 0.02456 Total loss: 1.58194 timestamp: 1654928842.273278 iteration: 18190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17742 FastRCNN class loss: 0.08485 FastRCNN total loss: 0.26227 L1 loss: 0.0000e+00 L2 loss: 1.18682 Learning rate: 0.02 Mask loss: 0.1427 RPN box loss: 0.02156 RPN score loss: 0.00575 RPN total loss: 0.02731 Total loss: 1.61911 timestamp: 1654928845.5349066 iteration: 18195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06487 FastRCNN class loss: 0.04771 FastRCNN total loss: 0.11258 L1 loss: 0.0000e+00 L2 loss: 1.18662 Learning rate: 0.02 Mask loss: 0.13182 RPN box loss: 0.03321 RPN score loss: 0.00436 RPN total loss: 0.03757 Total loss: 1.46858 timestamp: 1654928848.7121577 iteration: 18200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.08025 FastRCNN total loss: 0.17431 L1 loss: 0.0000e+00 L2 loss: 1.18642 Learning rate: 0.02 Mask loss: 0.14571 RPN box loss: 0.03505 RPN score loss: 0.01207 RPN total loss: 0.04711 Total loss: 1.55356 timestamp: 1654928851.8577197 iteration: 18205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10389 FastRCNN class loss: 0.07993 FastRCNN total loss: 0.18382 L1 loss: 0.0000e+00 L2 loss: 1.18623 Learning rate: 0.02 Mask loss: 0.16389 RPN box loss: 0.10795 RPN score loss: 0.01084 RPN total loss: 0.11879 Total loss: 1.65272 timestamp: 1654928855.1672852 iteration: 18210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20363 FastRCNN class loss: 0.09482 FastRCNN total loss: 0.29845 L1 loss: 0.0000e+00 L2 loss: 1.18603 Learning rate: 0.02 Mask loss: 0.13723 RPN box loss: 0.04959 RPN score loss: 0.00508 RPN total loss: 0.05467 Total loss: 1.67638 timestamp: 1654928858.5388002 iteration: 18215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10645 FastRCNN class loss: 0.04368 FastRCNN total loss: 0.15013 L1 loss: 0.0000e+00 L2 loss: 1.18583 Learning rate: 0.02 Mask loss: 0.08603 RPN box loss: 0.03966 RPN score loss: 0.00348 RPN total loss: 0.04314 Total loss: 1.46513 timestamp: 1654928861.7196043 iteration: 18220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1217 FastRCNN class loss: 0.08136 FastRCNN total loss: 0.20305 L1 loss: 0.0000e+00 L2 loss: 1.18565 Learning rate: 0.02 Mask loss: 0.14721 RPN box loss: 0.02863 RPN score loss: 0.00386 RPN total loss: 0.03249 Total loss: 1.5684 timestamp: 1654928864.9718506 iteration: 18225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1026 FastRCNN class loss: 0.0673 FastRCNN total loss: 0.1699 L1 loss: 0.0000e+00 L2 loss: 1.18547 Learning rate: 0.02 Mask loss: 0.1593 RPN box loss: 0.02425 RPN score loss: 0.00635 RPN total loss: 0.0306 Total loss: 1.54527 timestamp: 1654928868.2145617 iteration: 18230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08638 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.1472 L1 loss: 0.0000e+00 L2 loss: 1.18527 Learning rate: 0.02 Mask loss: 0.15191 RPN box loss: 0.0408 RPN score loss: 0.00454 RPN total loss: 0.04534 Total loss: 1.52972 timestamp: 1654928871.4654272 iteration: 18235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10042 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.17539 L1 loss: 0.0000e+00 L2 loss: 1.18507 Learning rate: 0.02 Mask loss: 0.14324 RPN box loss: 0.02516 RPN score loss: 0.00435 RPN total loss: 0.02952 Total loss: 1.53321 timestamp: 1654928874.7641802 iteration: 18240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19807 FastRCNN class loss: 0.11435 FastRCNN total loss: 0.31242 L1 loss: 0.0000e+00 L2 loss: 1.18488 Learning rate: 0.02 Mask loss: 0.19871 RPN box loss: 0.0266 RPN score loss: 0.0032 RPN total loss: 0.02979 Total loss: 1.72581 timestamp: 1654928878.0629547 iteration: 18245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12613 FastRCNN class loss: 0.09035 FastRCNN total loss: 0.21648 L1 loss: 0.0000e+00 L2 loss: 1.18469 Learning rate: 0.02 Mask loss: 0.16422 RPN box loss: 0.01054 RPN score loss: 0.00532 RPN total loss: 0.01586 Total loss: 1.58124 timestamp: 1654928881.2175224 iteration: 18250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26144 FastRCNN class loss: 0.16273 FastRCNN total loss: 0.42417 L1 loss: 0.0000e+00 L2 loss: 1.18446 Learning rate: 0.02 Mask loss: 0.22596 RPN box loss: 0.02929 RPN score loss: 0.01588 RPN total loss: 0.04517 Total loss: 1.87976 timestamp: 1654928884.4293084 iteration: 18255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0976 FastRCNN class loss: 0.05113 FastRCNN total loss: 0.14873 L1 loss: 0.0000e+00 L2 loss: 1.18425 Learning rate: 0.02 Mask loss: 0.12393 RPN box loss: 0.03473 RPN score loss: 0.00616 RPN total loss: 0.0409 Total loss: 1.4978 timestamp: 1654928887.746222 iteration: 18260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2387 FastRCNN class loss: 0.09051 FastRCNN total loss: 0.3292 L1 loss: 0.0000e+00 L2 loss: 1.18404 Learning rate: 0.02 Mask loss: 0.13405 RPN box loss: 0.03059 RPN score loss: 0.00408 RPN total loss: 0.03467 Total loss: 1.68197 timestamp: 1654928891.0080924 iteration: 18265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1171 FastRCNN class loss: 0.06215 FastRCNN total loss: 0.17925 L1 loss: 0.0000e+00 L2 loss: 1.18384 Learning rate: 0.02 Mask loss: 0.16721 RPN box loss: 0.01697 RPN score loss: 0.00531 RPN total loss: 0.02229 Total loss: 1.55258 timestamp: 1654928894.241386 iteration: 18270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2319 FastRCNN class loss: 0.1126 FastRCNN total loss: 0.3445 L1 loss: 0.0000e+00 L2 loss: 1.18364 Learning rate: 0.02 Mask loss: 0.28289 RPN box loss: 0.02195 RPN score loss: 0.00929 RPN total loss: 0.03124 Total loss: 1.84227 timestamp: 1654928897.4299624 iteration: 18275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15491 FastRCNN class loss: 0.1045 FastRCNN total loss: 0.25941 L1 loss: 0.0000e+00 L2 loss: 1.18344 Learning rate: 0.02 Mask loss: 0.18812 RPN box loss: 0.03349 RPN score loss: 0.00611 RPN total loss: 0.0396 Total loss: 1.67057 timestamp: 1654928900.7123075 iteration: 18280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17668 FastRCNN class loss: 0.08838 FastRCNN total loss: 0.26506 L1 loss: 0.0000e+00 L2 loss: 1.18325 Learning rate: 0.02 Mask loss: 0.35131 RPN box loss: 0.0177 RPN score loss: 0.0036 RPN total loss: 0.0213 Total loss: 1.82092 timestamp: 1654928903.8861873 iteration: 18285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17529 FastRCNN class loss: 0.08633 FastRCNN total loss: 0.26162 L1 loss: 0.0000e+00 L2 loss: 1.18304 Learning rate: 0.02 Mask loss: 0.14069 RPN box loss: 0.01599 RPN score loss: 0.00398 RPN total loss: 0.01997 Total loss: 1.60533 timestamp: 1654928907.169776 iteration: 18290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19455 FastRCNN class loss: 0.10898 FastRCNN total loss: 0.30354 L1 loss: 0.0000e+00 L2 loss: 1.18284 Learning rate: 0.02 Mask loss: 0.2127 RPN box loss: 0.02786 RPN score loss: 0.00527 RPN total loss: 0.03314 Total loss: 1.73222 timestamp: 1654928910.3632674 iteration: 18295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1317 FastRCNN class loss: 0.11058 FastRCNN total loss: 0.24228 L1 loss: 0.0000e+00 L2 loss: 1.18265 Learning rate: 0.02 Mask loss: 0.27814 RPN box loss: 0.07446 RPN score loss: 0.01405 RPN total loss: 0.08852 Total loss: 1.79159 timestamp: 1654928913.5960572 iteration: 18300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15548 FastRCNN class loss: 0.19499 FastRCNN total loss: 0.35047 L1 loss: 0.0000e+00 L2 loss: 1.18244 Learning rate: 0.02 Mask loss: 0.19965 RPN box loss: 0.06371 RPN score loss: 0.02139 RPN total loss: 0.0851 Total loss: 1.81766 timestamp: 1654928916.8598864 iteration: 18305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16544 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.24886 L1 loss: 0.0000e+00 L2 loss: 1.18224 Learning rate: 0.02 Mask loss: 0.11228 RPN box loss: 0.06354 RPN score loss: 0.00593 RPN total loss: 0.06947 Total loss: 1.61285 timestamp: 1654928920.1307123 iteration: 18310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20794 FastRCNN class loss: 0.16669 FastRCNN total loss: 0.37463 L1 loss: 0.0000e+00 L2 loss: 1.18205 Learning rate: 0.02 Mask loss: 0.21507 RPN box loss: 0.07283 RPN score loss: 0.02395 RPN total loss: 0.09677 Total loss: 1.86852 timestamp: 1654928923.3353357 iteration: 18315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16043 FastRCNN class loss: 0.15089 FastRCNN total loss: 0.31132 L1 loss: 0.0000e+00 L2 loss: 1.18187 Learning rate: 0.02 Mask loss: 0.20045 RPN box loss: 0.07305 RPN score loss: 0.01701 RPN total loss: 0.09006 Total loss: 1.7837 timestamp: 1654928926.7065098 iteration: 18320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10407 FastRCNN class loss: 0.08588 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 1.18166 Learning rate: 0.02 Mask loss: 0.13776 RPN box loss: 0.02005 RPN score loss: 0.01325 RPN total loss: 0.0333 Total loss: 1.54267 timestamp: 1654928929.9614055 iteration: 18325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10812 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.18429 L1 loss: 0.0000e+00 L2 loss: 1.18146 Learning rate: 0.02 Mask loss: 0.10925 RPN box loss: 0.02428 RPN score loss: 0.00493 RPN total loss: 0.02921 Total loss: 1.50421 timestamp: 1654928933.162161 iteration: 18330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12194 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.21584 L1 loss: 0.0000e+00 L2 loss: 1.18126 Learning rate: 0.02 Mask loss: 0.14903 RPN box loss: 0.00586 RPN score loss: 0.00174 RPN total loss: 0.0076 Total loss: 1.55372 timestamp: 1654928936.4686575 iteration: 18335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11445 FastRCNN class loss: 0.09528 FastRCNN total loss: 0.20973 L1 loss: 0.0000e+00 L2 loss: 1.18107 Learning rate: 0.02 Mask loss: 0.16996 RPN box loss: 0.0406 RPN score loss: 0.00816 RPN total loss: 0.04876 Total loss: 1.60951 timestamp: 1654928939.7183957 iteration: 18340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1254 FastRCNN class loss: 0.10406 FastRCNN total loss: 0.22945 L1 loss: 0.0000e+00 L2 loss: 1.18087 Learning rate: 0.02 Mask loss: 0.16016 RPN box loss: 0.01585 RPN score loss: 0.00315 RPN total loss: 0.019 Total loss: 1.58948 timestamp: 1654928942.9825842 iteration: 18345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15248 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.24207 L1 loss: 0.0000e+00 L2 loss: 1.18067 Learning rate: 0.02 Mask loss: 0.19157 RPN box loss: 0.0282 RPN score loss: 0.00422 RPN total loss: 0.03242 Total loss: 1.64672 timestamp: 1654928946.1628237 iteration: 18350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18089 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.26956 L1 loss: 0.0000e+00 L2 loss: 1.18046 Learning rate: 0.02 Mask loss: 0.20052 RPN box loss: 0.01564 RPN score loss: 0.00811 RPN total loss: 0.02375 Total loss: 1.67429 timestamp: 1654928949.520205 iteration: 18355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17727 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.24946 L1 loss: 0.0000e+00 L2 loss: 1.18025 Learning rate: 0.02 Mask loss: 0.16118 RPN box loss: 0.03537 RPN score loss: 0.0051 RPN total loss: 0.04047 Total loss: 1.63137 timestamp: 1654928952.7416883 iteration: 18360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13236 FastRCNN class loss: 0.08772 FastRCNN total loss: 0.22008 L1 loss: 0.0000e+00 L2 loss: 1.18003 Learning rate: 0.02 Mask loss: 0.13485 RPN box loss: 0.0093 RPN score loss: 0.00331 RPN total loss: 0.01261 Total loss: 1.54757 timestamp: 1654928956.0686126 iteration: 18365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08519 FastRCNN class loss: 0.05165 FastRCNN total loss: 0.13684 L1 loss: 0.0000e+00 L2 loss: 1.17984 Learning rate: 0.02 Mask loss: 0.13791 RPN box loss: 0.02252 RPN score loss: 0.00275 RPN total loss: 0.02527 Total loss: 1.47986 timestamp: 1654928959.3050334 iteration: 18370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16118 FastRCNN class loss: 0.13442 FastRCNN total loss: 0.2956 L1 loss: 0.0000e+00 L2 loss: 1.17966 Learning rate: 0.02 Mask loss: 0.12582 RPN box loss: 0.02046 RPN score loss: 0.00393 RPN total loss: 0.02439 Total loss: 1.62547 timestamp: 1654928962.563787 iteration: 18375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14064 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.18952 L1 loss: 0.0000e+00 L2 loss: 1.17946 Learning rate: 0.02 Mask loss: 0.14031 RPN box loss: 0.0097 RPN score loss: 0.004 RPN total loss: 0.0137 Total loss: 1.523 timestamp: 1654928965.9635198 iteration: 18380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12892 FastRCNN class loss: 0.09587 FastRCNN total loss: 0.22478 L1 loss: 0.0000e+00 L2 loss: 1.17926 Learning rate: 0.02 Mask loss: 0.173 RPN box loss: 0.02342 RPN score loss: 0.0125 RPN total loss: 0.03592 Total loss: 1.61296 timestamp: 1654928969.1711428 iteration: 18385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22645 FastRCNN class loss: 0.08803 FastRCNN total loss: 0.31448 L1 loss: 0.0000e+00 L2 loss: 1.17905 Learning rate: 0.02 Mask loss: 0.18621 RPN box loss: 0.01599 RPN score loss: 0.00666 RPN total loss: 0.02265 Total loss: 1.70239 timestamp: 1654928972.4588516 iteration: 18390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11499 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.20774 L1 loss: 0.0000e+00 L2 loss: 1.17888 Learning rate: 0.02 Mask loss: 0.15832 RPN box loss: 0.0302 RPN score loss: 0.00615 RPN total loss: 0.03636 Total loss: 1.58129 timestamp: 1654928975.6952267 iteration: 18395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08246 FastRCNN class loss: 0.04679 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 1.17868 Learning rate: 0.02 Mask loss: 0.10599 RPN box loss: 0.02339 RPN score loss: 0.00358 RPN total loss: 0.02696 Total loss: 1.44088 timestamp: 1654928978.9864936 iteration: 18400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16413 FastRCNN class loss: 0.10772 FastRCNN total loss: 0.27185 L1 loss: 0.0000e+00 L2 loss: 1.17849 Learning rate: 0.02 Mask loss: 0.18908 RPN box loss: 0.06845 RPN score loss: 0.01867 RPN total loss: 0.08712 Total loss: 1.72655 timestamp: 1654928982.210401 iteration: 18405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1074 FastRCNN class loss: 0.08512 FastRCNN total loss: 0.19252 L1 loss: 0.0000e+00 L2 loss: 1.17831 Learning rate: 0.02 Mask loss: 0.1192 RPN box loss: 0.00603 RPN score loss: 0.00421 RPN total loss: 0.01025 Total loss: 1.50028 timestamp: 1654928985.5620818 iteration: 18410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17114 FastRCNN class loss: 0.13844 FastRCNN total loss: 0.30958 L1 loss: 0.0000e+00 L2 loss: 1.17811 Learning rate: 0.02 Mask loss: 0.18708 RPN box loss: 0.01884 RPN score loss: 0.01947 RPN total loss: 0.03832 Total loss: 1.71309 timestamp: 1654928988.8601718 iteration: 18415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1566 FastRCNN class loss: 0.12681 FastRCNN total loss: 0.28341 L1 loss: 0.0000e+00 L2 loss: 1.17789 Learning rate: 0.02 Mask loss: 0.24063 RPN box loss: 0.05244 RPN score loss: 0.00909 RPN total loss: 0.06153 Total loss: 1.76346 timestamp: 1654928992.1104631 iteration: 18420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12296 FastRCNN class loss: 0.09939 FastRCNN total loss: 0.22234 L1 loss: 0.0000e+00 L2 loss: 1.17769 Learning rate: 0.02 Mask loss: 0.16451 RPN box loss: 0.03872 RPN score loss: 0.01818 RPN total loss: 0.05691 Total loss: 1.62145 timestamp: 1654928995.3374162 iteration: 18425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08366 FastRCNN class loss: 0.05308 FastRCNN total loss: 0.13674 L1 loss: 0.0000e+00 L2 loss: 1.1775 Learning rate: 0.02 Mask loss: 0.07217 RPN box loss: 0.04517 RPN score loss: 0.00173 RPN total loss: 0.0469 Total loss: 1.4333 timestamp: 1654928998.524939 iteration: 18430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16746 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.25718 L1 loss: 0.0000e+00 L2 loss: 1.17732 Learning rate: 0.02 Mask loss: 0.22229 RPN box loss: 0.04369 RPN score loss: 0.00867 RPN total loss: 0.05236 Total loss: 1.70915 timestamp: 1654929001.8072422 iteration: 18435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19054 FastRCNN class loss: 0.10169 FastRCNN total loss: 0.29224 L1 loss: 0.0000e+00 L2 loss: 1.17715 Learning rate: 0.02 Mask loss: 0.1978 RPN box loss: 0.03233 RPN score loss: 0.01164 RPN total loss: 0.04397 Total loss: 1.71116 timestamp: 1654929005.007491 iteration: 18440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08444 FastRCNN class loss: 0.06263 FastRCNN total loss: 0.14707 L1 loss: 0.0000e+00 L2 loss: 1.17697 Learning rate: 0.02 Mask loss: 0.13221 RPN box loss: 0.0192 RPN score loss: 0.0081 RPN total loss: 0.02731 Total loss: 1.48355 timestamp: 1654929008.4131386 iteration: 18445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13827 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.21879 L1 loss: 0.0000e+00 L2 loss: 1.17675 Learning rate: 0.02 Mask loss: 0.10339 RPN box loss: 0.0287 RPN score loss: 0.00619 RPN total loss: 0.03489 Total loss: 1.53382 timestamp: 1654929011.6275468 iteration: 18450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24301 FastRCNN class loss: 0.09674 FastRCNN total loss: 0.33975 L1 loss: 0.0000e+00 L2 loss: 1.17655 Learning rate: 0.02 Mask loss: 0.21222 RPN box loss: 0.04209 RPN score loss: 0.00629 RPN total loss: 0.04839 Total loss: 1.77691 timestamp: 1654929014.8135114 iteration: 18455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14098 FastRCNN class loss: 0.09993 FastRCNN total loss: 0.24091 L1 loss: 0.0000e+00 L2 loss: 1.17633 Learning rate: 0.02 Mask loss: 0.13613 RPN box loss: 0.04924 RPN score loss: 0.01576 RPN total loss: 0.065 Total loss: 1.61836 timestamp: 1654929018.0105965 iteration: 18460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14286 FastRCNN class loss: 0.09621 FastRCNN total loss: 0.23907 L1 loss: 0.0000e+00 L2 loss: 1.17612 Learning rate: 0.02 Mask loss: 0.27407 RPN box loss: 0.03151 RPN score loss: 0.01024 RPN total loss: 0.04175 Total loss: 1.73102 timestamp: 1654929021.386431 iteration: 18465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09685 FastRCNN class loss: 0.05552 FastRCNN total loss: 0.15237 L1 loss: 0.0000e+00 L2 loss: 1.17592 Learning rate: 0.02 Mask loss: 0.10767 RPN box loss: 0.01859 RPN score loss: 0.00704 RPN total loss: 0.02563 Total loss: 1.46159 timestamp: 1654929024.6028216 iteration: 18470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11863 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.19097 L1 loss: 0.0000e+00 L2 loss: 1.17571 Learning rate: 0.02 Mask loss: 0.24711 RPN box loss: 0.01808 RPN score loss: 0.00532 RPN total loss: 0.0234 Total loss: 1.63719 timestamp: 1654929027.9104626 iteration: 18475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09927 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.17444 L1 loss: 0.0000e+00 L2 loss: 1.1755 Learning rate: 0.02 Mask loss: 0.11491 RPN box loss: 0.02082 RPN score loss: 0.00828 RPN total loss: 0.0291 Total loss: 1.49395 timestamp: 1654929031.1768928 iteration: 18480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15115 FastRCNN class loss: 0.0811 FastRCNN total loss: 0.23225 L1 loss: 0.0000e+00 L2 loss: 1.1753 Learning rate: 0.02 Mask loss: 0.21771 RPN box loss: 0.01773 RPN score loss: 0.01878 RPN total loss: 0.03651 Total loss: 1.66177 timestamp: 1654929034.4086082 iteration: 18485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12615 FastRCNN class loss: 0.06602 FastRCNN total loss: 0.19218 L1 loss: 0.0000e+00 L2 loss: 1.1751 Learning rate: 0.02 Mask loss: 0.14343 RPN box loss: 0.077 RPN score loss: 0.00448 RPN total loss: 0.08148 Total loss: 1.59219 timestamp: 1654929037.7427995 iteration: 18490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1099 FastRCNN class loss: 0.10422 FastRCNN total loss: 0.21412 L1 loss: 0.0000e+00 L2 loss: 1.17491 Learning rate: 0.02 Mask loss: 0.13466 RPN box loss: 0.02683 RPN score loss: 0.00509 RPN total loss: 0.03192 Total loss: 1.55561 timestamp: 1654929041.0066624 iteration: 18495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09717 FastRCNN class loss: 0.06318 FastRCNN total loss: 0.16035 L1 loss: 0.0000e+00 L2 loss: 1.1747 Learning rate: 0.02 Mask loss: 0.08251 RPN box loss: 0.01707 RPN score loss: 0.00459 RPN total loss: 0.02166 Total loss: 1.43922 timestamp: 1654929044.3147793 iteration: 18500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16701 FastRCNN class loss: 0.12095 FastRCNN total loss: 0.28795 L1 loss: 0.0000e+00 L2 loss: 1.1745 Learning rate: 0.02 Mask loss: 0.2248 RPN box loss: 0.04874 RPN score loss: 0.00767 RPN total loss: 0.0564 Total loss: 1.74366 timestamp: 1654929047.515019 iteration: 18505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13654 FastRCNN class loss: 0.07611 FastRCNN total loss: 0.21266 L1 loss: 0.0000e+00 L2 loss: 1.17432 Learning rate: 0.02 Mask loss: 0.14596 RPN box loss: 0.02777 RPN score loss: 0.01359 RPN total loss: 0.04135 Total loss: 1.57429 timestamp: 1654929050.7684388 iteration: 18510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17719 FastRCNN class loss: 0.10272 FastRCNN total loss: 0.27992 L1 loss: 0.0000e+00 L2 loss: 1.17413 Learning rate: 0.02 Mask loss: 0.22699 RPN box loss: 0.01071 RPN score loss: 0.01306 RPN total loss: 0.02377 Total loss: 1.70481 timestamp: 1654929053.980357 iteration: 18515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12465 FastRCNN class loss: 0.0566 FastRCNN total loss: 0.18124 L1 loss: 0.0000e+00 L2 loss: 1.17394 Learning rate: 0.02 Mask loss: 0.0961 RPN box loss: 0.02945 RPN score loss: 0.00786 RPN total loss: 0.0373 Total loss: 1.48858 timestamp: 1654929057.3065891 iteration: 18520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15787 FastRCNN class loss: 0.06959 FastRCNN total loss: 0.22747 L1 loss: 0.0000e+00 L2 loss: 1.17376 Learning rate: 0.02 Mask loss: 0.1421 RPN box loss: 0.00783 RPN score loss: 0.00385 RPN total loss: 0.01168 Total loss: 1.555 timestamp: 1654929060.5077229 iteration: 18525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12111 FastRCNN class loss: 0.05829 FastRCNN total loss: 0.1794 L1 loss: 0.0000e+00 L2 loss: 1.17355 Learning rate: 0.02 Mask loss: 0.11929 RPN box loss: 0.0205 RPN score loss: 0.0046 RPN total loss: 0.0251 Total loss: 1.49734 timestamp: 1654929063.861289 iteration: 18530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16021 FastRCNN class loss: 0.09316 FastRCNN total loss: 0.25336 L1 loss: 0.0000e+00 L2 loss: 1.17336 Learning rate: 0.02 Mask loss: 0.15574 RPN box loss: 0.01642 RPN score loss: 0.00723 RPN total loss: 0.02364 Total loss: 1.60611 timestamp: 1654929067.2560852 iteration: 18535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11865 FastRCNN class loss: 0.11083 FastRCNN total loss: 0.22947 L1 loss: 0.0000e+00 L2 loss: 1.17316 Learning rate: 0.02 Mask loss: 0.28647 RPN box loss: 0.02476 RPN score loss: 0.00355 RPN total loss: 0.02831 Total loss: 1.7174 timestamp: 1654929070.5093217 iteration: 18540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24872 FastRCNN class loss: 0.10246 FastRCNN total loss: 0.35118 L1 loss: 0.0000e+00 L2 loss: 1.17295 Learning rate: 0.02 Mask loss: 0.14042 RPN box loss: 0.01317 RPN score loss: 0.00317 RPN total loss: 0.01634 Total loss: 1.68089 timestamp: 1654929073.7225108 iteration: 18545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08622 FastRCNN class loss: 0.07014 FastRCNN total loss: 0.15636 L1 loss: 0.0000e+00 L2 loss: 1.17276 Learning rate: 0.02 Mask loss: 0.16998 RPN box loss: 0.01479 RPN score loss: 0.00614 RPN total loss: 0.02093 Total loss: 1.52002 timestamp: 1654929076.9290552 iteration: 18550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14202 FastRCNN class loss: 0.0674 FastRCNN total loss: 0.20943 L1 loss: 0.0000e+00 L2 loss: 1.17257 Learning rate: 0.02 Mask loss: 0.17776 RPN box loss: 0.02127 RPN score loss: 0.01342 RPN total loss: 0.03469 Total loss: 1.59446 timestamp: 1654929080.3191128 iteration: 18555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16625 FastRCNN class loss: 0.13153 FastRCNN total loss: 0.29778 L1 loss: 0.0000e+00 L2 loss: 1.17238 Learning rate: 0.02 Mask loss: 0.21307 RPN box loss: 0.12485 RPN score loss: 0.01381 RPN total loss: 0.13866 Total loss: 1.82189 timestamp: 1654929083.5560174 iteration: 18560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15143 FastRCNN class loss: 0.11149 FastRCNN total loss: 0.26292 L1 loss: 0.0000e+00 L2 loss: 1.17219 Learning rate: 0.02 Mask loss: 0.225 RPN box loss: 0.04885 RPN score loss: 0.01587 RPN total loss: 0.06472 Total loss: 1.72483 timestamp: 1654929086.8849807 iteration: 18565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10368 FastRCNN class loss: 0.07226 FastRCNN total loss: 0.17594 L1 loss: 0.0000e+00 L2 loss: 1.172 Learning rate: 0.02 Mask loss: 0.12283 RPN box loss: 0.02153 RPN score loss: 0.0029 RPN total loss: 0.02443 Total loss: 1.4952 timestamp: 1654929090.0753841 iteration: 18570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15463 FastRCNN class loss: 0.07378 FastRCNN total loss: 0.22841 L1 loss: 0.0000e+00 L2 loss: 1.1718 Learning rate: 0.02 Mask loss: 0.1225 RPN box loss: 0.05936 RPN score loss: 0.00539 RPN total loss: 0.06475 Total loss: 1.58746 timestamp: 1654929093.396855 iteration: 18575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16168 FastRCNN class loss: 0.10003 FastRCNN total loss: 0.26172 L1 loss: 0.0000e+00 L2 loss: 1.17159 Learning rate: 0.02 Mask loss: 0.13421 RPN box loss: 0.04577 RPN score loss: 0.00869 RPN total loss: 0.05446 Total loss: 1.62198 timestamp: 1654929096.6950133 iteration: 18580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12737 FastRCNN class loss: 0.07706 FastRCNN total loss: 0.20443 L1 loss: 0.0000e+00 L2 loss: 1.17139 Learning rate: 0.02 Mask loss: 0.1512 RPN box loss: 0.0275 RPN score loss: 0.00662 RPN total loss: 0.03412 Total loss: 1.56114 timestamp: 1654929099.918007 iteration: 18585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12576 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.22599 L1 loss: 0.0000e+00 L2 loss: 1.1712 Learning rate: 0.02 Mask loss: 0.1764 RPN box loss: 0.06562 RPN score loss: 0.01985 RPN total loss: 0.08547 Total loss: 1.65906 timestamp: 1654929103.254434 iteration: 18590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17172 FastRCNN class loss: 0.12591 FastRCNN total loss: 0.29763 L1 loss: 0.0000e+00 L2 loss: 1.17104 Learning rate: 0.02 Mask loss: 0.25299 RPN box loss: 0.05876 RPN score loss: 0.0047 RPN total loss: 0.06346 Total loss: 1.78512 timestamp: 1654929106.430545 iteration: 18595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11314 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 1.17085 Learning rate: 0.02 Mask loss: 0.17697 RPN box loss: 0.00576 RPN score loss: 0.00637 RPN total loss: 0.01212 Total loss: 1.53995 timestamp: 1654929109.7105696 iteration: 18600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18546 FastRCNN class loss: 0.15222 FastRCNN total loss: 0.33769 L1 loss: 0.0000e+00 L2 loss: 1.17064 Learning rate: 0.02 Mask loss: 0.24789 RPN box loss: 0.06058 RPN score loss: 0.01028 RPN total loss: 0.07086 Total loss: 1.82708 timestamp: 1654929112.884249 iteration: 18605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11389 FastRCNN class loss: 0.1177 FastRCNN total loss: 0.23159 L1 loss: 0.0000e+00 L2 loss: 1.17042 Learning rate: 0.02 Mask loss: 0.19788 RPN box loss: 0.01439 RPN score loss: 0.01572 RPN total loss: 0.03011 Total loss: 1.62999 timestamp: 1654929116.1831412 iteration: 18610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09929 FastRCNN class loss: 0.04652 FastRCNN total loss: 0.14581 L1 loss: 0.0000e+00 L2 loss: 1.17024 Learning rate: 0.02 Mask loss: 0.14879 RPN box loss: 0.09997 RPN score loss: 0.00834 RPN total loss: 0.10831 Total loss: 1.57314 timestamp: 1654929119.3118958 iteration: 18615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13307 FastRCNN class loss: 0.09443 FastRCNN total loss: 0.2275 L1 loss: 0.0000e+00 L2 loss: 1.17004 Learning rate: 0.02 Mask loss: 0.14894 RPN box loss: 0.03085 RPN score loss: 0.00787 RPN total loss: 0.03872 Total loss: 1.58521 timestamp: 1654929122.5514874 iteration: 18620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09779 FastRCNN class loss: 0.09032 FastRCNN total loss: 0.18811 L1 loss: 0.0000e+00 L2 loss: 1.16984 Learning rate: 0.02 Mask loss: 0.10614 RPN box loss: 0.05042 RPN score loss: 0.00845 RPN total loss: 0.05888 Total loss: 1.52297 timestamp: 1654929125.8154151 iteration: 18625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14616 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.21939 L1 loss: 0.0000e+00 L2 loss: 1.16966 Learning rate: 0.02 Mask loss: 0.19047 RPN box loss: 0.01236 RPN score loss: 0.00646 RPN total loss: 0.01882 Total loss: 1.59834 timestamp: 1654929129.0209217 iteration: 18630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09949 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.16875 L1 loss: 0.0000e+00 L2 loss: 1.16943 Learning rate: 0.02 Mask loss: 0.1231 RPN box loss: 0.01461 RPN score loss: 0.00437 RPN total loss: 0.01899 Total loss: 1.48026 timestamp: 1654929132.1888077 iteration: 18635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19933 FastRCNN class loss: 0.12245 FastRCNN total loss: 0.32178 L1 loss: 0.0000e+00 L2 loss: 1.16924 Learning rate: 0.02 Mask loss: 0.19259 RPN box loss: 0.04938 RPN score loss: 0.02228 RPN total loss: 0.07166 Total loss: 1.75527 timestamp: 1654929135.379708 iteration: 18640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18953 FastRCNN class loss: 0.10685 FastRCNN total loss: 0.29638 L1 loss: 0.0000e+00 L2 loss: 1.16905 Learning rate: 0.02 Mask loss: 0.15528 RPN box loss: 0.01598 RPN score loss: 0.00893 RPN total loss: 0.02491 Total loss: 1.64562 timestamp: 1654929138.6368468 iteration: 18645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14766 FastRCNN class loss: 0.04984 FastRCNN total loss: 0.1975 L1 loss: 0.0000e+00 L2 loss: 1.16887 Learning rate: 0.02 Mask loss: 0.12049 RPN box loss: 0.07062 RPN score loss: 0.00944 RPN total loss: 0.08006 Total loss: 1.56691 timestamp: 1654929141.800151 iteration: 18650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18081 FastRCNN class loss: 0.09677 FastRCNN total loss: 0.27758 L1 loss: 0.0000e+00 L2 loss: 1.1687 Learning rate: 0.02 Mask loss: 0.16296 RPN box loss: 0.02064 RPN score loss: 0.00396 RPN total loss: 0.0246 Total loss: 1.63385 timestamp: 1654929145.1246407 iteration: 18655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19686 FastRCNN class loss: 0.13335 FastRCNN total loss: 0.33021 L1 loss: 0.0000e+00 L2 loss: 1.16847 Learning rate: 0.02 Mask loss: 0.22449 RPN box loss: 0.04171 RPN score loss: 0.01358 RPN total loss: 0.05529 Total loss: 1.77847 timestamp: 1654929148.368118 iteration: 18660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18223 FastRCNN class loss: 0.15989 FastRCNN total loss: 0.34212 L1 loss: 0.0000e+00 L2 loss: 1.16826 Learning rate: 0.02 Mask loss: 0.18645 RPN box loss: 0.02566 RPN score loss: 0.01753 RPN total loss: 0.04319 Total loss: 1.74002 timestamp: 1654929151.6755745 iteration: 18665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14766 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.20954 L1 loss: 0.0000e+00 L2 loss: 1.16806 Learning rate: 0.02 Mask loss: 0.1202 RPN box loss: 0.01981 RPN score loss: 0.00408 RPN total loss: 0.02389 Total loss: 1.52169 timestamp: 1654929154.8553753 iteration: 18670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17075 FastRCNN class loss: 0.12491 FastRCNN total loss: 0.29566 L1 loss: 0.0000e+00 L2 loss: 1.16787 Learning rate: 0.02 Mask loss: 0.21271 RPN box loss: 0.03848 RPN score loss: 0.00468 RPN total loss: 0.04317 Total loss: 1.7194 timestamp: 1654929158.1545644 iteration: 18675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13037 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.19542 L1 loss: 0.0000e+00 L2 loss: 1.16766 Learning rate: 0.02 Mask loss: 0.13194 RPN box loss: 0.04013 RPN score loss: 0.00867 RPN total loss: 0.0488 Total loss: 1.54383 timestamp: 1654929161.3417165 iteration: 18680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.04342 FastRCNN total loss: 0.15702 L1 loss: 0.0000e+00 L2 loss: 1.1675 Learning rate: 0.02 Mask loss: 0.08946 RPN box loss: 0.01384 RPN score loss: 0.00268 RPN total loss: 0.01652 Total loss: 1.43049 timestamp: 1654929164.681603 iteration: 18685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22426 FastRCNN class loss: 0.14827 FastRCNN total loss: 0.37254 L1 loss: 0.0000e+00 L2 loss: 1.16734 Learning rate: 0.02 Mask loss: 0.1859 RPN box loss: 0.03302 RPN score loss: 0.01032 RPN total loss: 0.04333 Total loss: 1.76911 timestamp: 1654929167.8916216 iteration: 18690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13212 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.21489 L1 loss: 0.0000e+00 L2 loss: 1.16714 Learning rate: 0.02 Mask loss: 0.13245 RPN box loss: 0.00849 RPN score loss: 0.00161 RPN total loss: 0.0101 Total loss: 1.52459 timestamp: 1654929171.112622 iteration: 18695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14206 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.20975 L1 loss: 0.0000e+00 L2 loss: 1.16694 Learning rate: 0.02 Mask loss: 0.15964 RPN box loss: 0.0131 RPN score loss: 0.00205 RPN total loss: 0.01515 Total loss: 1.55149 timestamp: 1654929174.359671 iteration: 18700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18681 FastRCNN class loss: 0.08235 FastRCNN total loss: 0.26915 L1 loss: 0.0000e+00 L2 loss: 1.16674 Learning rate: 0.02 Mask loss: 0.20935 RPN box loss: 0.01243 RPN score loss: 0.00887 RPN total loss: 0.0213 Total loss: 1.66654 timestamp: 1654929177.5226083 iteration: 18705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18344 FastRCNN class loss: 0.09046 FastRCNN total loss: 0.2739 L1 loss: 0.0000e+00 L2 loss: 1.16656 Learning rate: 0.02 Mask loss: 0.14644 RPN box loss: 0.02034 RPN score loss: 0.00222 RPN total loss: 0.02256 Total loss: 1.60946 timestamp: 1654929180.7641177 iteration: 18710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1066 FastRCNN class loss: 0.04581 FastRCNN total loss: 0.15242 L1 loss: 0.0000e+00 L2 loss: 1.16638 Learning rate: 0.02 Mask loss: 0.1215 RPN box loss: 0.00534 RPN score loss: 0.00448 RPN total loss: 0.00982 Total loss: 1.45012 timestamp: 1654929183.9989698 iteration: 18715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18026 FastRCNN class loss: 0.10353 FastRCNN total loss: 0.28378 L1 loss: 0.0000e+00 L2 loss: 1.16619 Learning rate: 0.02 Mask loss: 0.172 RPN box loss: 0.03097 RPN score loss: 0.01358 RPN total loss: 0.04455 Total loss: 1.66652 timestamp: 1654929187.2176907 iteration: 18720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23565 FastRCNN class loss: 0.12079 FastRCNN total loss: 0.35645 L1 loss: 0.0000e+00 L2 loss: 1.16599 Learning rate: 0.02 Mask loss: 0.1744 RPN box loss: 0.03758 RPN score loss: 0.00755 RPN total loss: 0.04513 Total loss: 1.74197 timestamp: 1654929190.437764 iteration: 18725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06158 FastRCNN class loss: 0.05872 FastRCNN total loss: 0.1203 L1 loss: 0.0000e+00 L2 loss: 1.1658 Learning rate: 0.02 Mask loss: 0.09566 RPN box loss: 0.01325 RPN score loss: 0.0024 RPN total loss: 0.01565 Total loss: 1.39741 timestamp: 1654929193.6733632 iteration: 18730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22577 FastRCNN class loss: 0.14676 FastRCNN total loss: 0.37253 L1 loss: 0.0000e+00 L2 loss: 1.16559 Learning rate: 0.02 Mask loss: 0.15748 RPN box loss: 0.03989 RPN score loss: 0.00657 RPN total loss: 0.04646 Total loss: 1.74206 timestamp: 1654929196.8476596 iteration: 18735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1397 FastRCNN class loss: 0.11206 FastRCNN total loss: 0.25176 L1 loss: 0.0000e+00 L2 loss: 1.16536 Learning rate: 0.02 Mask loss: 0.19089 RPN box loss: 0.05188 RPN score loss: 0.01498 RPN total loss: 0.06685 Total loss: 1.67487 timestamp: 1654929200.137061 iteration: 18740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21511 FastRCNN class loss: 0.10945 FastRCNN total loss: 0.32456 L1 loss: 0.0000e+00 L2 loss: 1.16517 Learning rate: 0.02 Mask loss: 0.24478 RPN box loss: 0.06982 RPN score loss: 0.00883 RPN total loss: 0.07865 Total loss: 1.81316 timestamp: 1654929203.2745063 iteration: 18745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10054 FastRCNN class loss: 0.04797 FastRCNN total loss: 0.1485 L1 loss: 0.0000e+00 L2 loss: 1.16497 Learning rate: 0.02 Mask loss: 0.14007 RPN box loss: 0.00892 RPN score loss: 0.00505 RPN total loss: 0.01397 Total loss: 1.46752 timestamp: 1654929206.5618718 iteration: 18750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12247 FastRCNN class loss: 0.11527 FastRCNN total loss: 0.23774 L1 loss: 0.0000e+00 L2 loss: 1.16478 Learning rate: 0.02 Mask loss: 0.21859 RPN box loss: 0.05965 RPN score loss: 0.012 RPN total loss: 0.07164 Total loss: 1.69275 timestamp: 1654929209.7901237 iteration: 18755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12492 FastRCNN class loss: 0.0855 FastRCNN total loss: 0.21042 L1 loss: 0.0000e+00 L2 loss: 1.16458 Learning rate: 0.02 Mask loss: 0.11609 RPN box loss: 0.01471 RPN score loss: 0.00166 RPN total loss: 0.01637 Total loss: 1.50746 timestamp: 1654929213.0006208 iteration: 18760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14297 FastRCNN class loss: 0.05712 FastRCNN total loss: 0.20009 L1 loss: 0.0000e+00 L2 loss: 1.16439 Learning rate: 0.02 Mask loss: 0.12916 RPN box loss: 0.00738 RPN score loss: 0.00351 RPN total loss: 0.01089 Total loss: 1.50454 timestamp: 1654929216.35801 iteration: 18765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18349 FastRCNN class loss: 0.16178 FastRCNN total loss: 0.34527 L1 loss: 0.0000e+00 L2 loss: 1.16422 Learning rate: 0.02 Mask loss: 0.16625 RPN box loss: 0.03619 RPN score loss: 0.00708 RPN total loss: 0.04328 Total loss: 1.71902 timestamp: 1654929219.6131318 iteration: 18770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09169 FastRCNN class loss: 0.05521 FastRCNN total loss: 0.1469 L1 loss: 0.0000e+00 L2 loss: 1.16403 Learning rate: 0.02 Mask loss: 0.11212 RPN box loss: 0.02414 RPN score loss: 0.00629 RPN total loss: 0.03043 Total loss: 1.45348 timestamp: 1654929222.8308766 iteration: 18775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13536 FastRCNN class loss: 0.10833 FastRCNN total loss: 0.24368 L1 loss: 0.0000e+00 L2 loss: 1.16382 Learning rate: 0.02 Mask loss: 0.16978 RPN box loss: 0.04705 RPN score loss: 0.01354 RPN total loss: 0.06059 Total loss: 1.63788 timestamp: 1654929226.026315 iteration: 18780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13926 FastRCNN class loss: 0.07709 FastRCNN total loss: 0.21634 L1 loss: 0.0000e+00 L2 loss: 1.16363 Learning rate: 0.02 Mask loss: 0.09657 RPN box loss: 0.02467 RPN score loss: 0.01085 RPN total loss: 0.03552 Total loss: 1.51207 timestamp: 1654929229.351846 iteration: 18785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10185 FastRCNN class loss: 0.06633 FastRCNN total loss: 0.16818 L1 loss: 0.0000e+00 L2 loss: 1.16343 Learning rate: 0.02 Mask loss: 0.09209 RPN box loss: 0.04802 RPN score loss: 0.0067 RPN total loss: 0.05472 Total loss: 1.47842 timestamp: 1654929232.5379791 iteration: 18790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12478 FastRCNN class loss: 0.09605 FastRCNN total loss: 0.22082 L1 loss: 0.0000e+00 L2 loss: 1.16322 Learning rate: 0.02 Mask loss: 0.18347 RPN box loss: 0.04602 RPN score loss: 0.0123 RPN total loss: 0.05832 Total loss: 1.62583 timestamp: 1654929235.7907512 iteration: 18795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13651 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.21882 L1 loss: 0.0000e+00 L2 loss: 1.16301 Learning rate: 0.02 Mask loss: 0.17868 RPN box loss: 0.07495 RPN score loss: 0.01737 RPN total loss: 0.09232 Total loss: 1.65284 timestamp: 1654929238.9759305 iteration: 18800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1645 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.24206 L1 loss: 0.0000e+00 L2 loss: 1.16285 Learning rate: 0.02 Mask loss: 0.10944 RPN box loss: 0.01438 RPN score loss: 0.00558 RPN total loss: 0.01996 Total loss: 1.53431 timestamp: 1654929242.1664438 iteration: 18805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16452 FastRCNN class loss: 0.07309 FastRCNN total loss: 0.23761 L1 loss: 0.0000e+00 L2 loss: 1.16268 Learning rate: 0.02 Mask loss: 0.17537 RPN box loss: 0.03472 RPN score loss: 0.00889 RPN total loss: 0.0436 Total loss: 1.61926 timestamp: 1654929245.323936 iteration: 18810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08859 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.15007 L1 loss: 0.0000e+00 L2 loss: 1.16248 Learning rate: 0.02 Mask loss: 0.19928 RPN box loss: 0.01877 RPN score loss: 0.00482 RPN total loss: 0.0236 Total loss: 1.53543 timestamp: 1654929248.7777498 iteration: 18815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16096 FastRCNN class loss: 0.11242 FastRCNN total loss: 0.27338 L1 loss: 0.0000e+00 L2 loss: 1.16229 Learning rate: 0.02 Mask loss: 0.23445 RPN box loss: 0.02694 RPN score loss: 0.01584 RPN total loss: 0.04277 Total loss: 1.71289 timestamp: 1654929252.0483763 iteration: 18820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15925 FastRCNN class loss: 0.14844 FastRCNN total loss: 0.30769 L1 loss: 0.0000e+00 L2 loss: 1.16207 Learning rate: 0.02 Mask loss: 0.22511 RPN box loss: 0.01999 RPN score loss: 0.03035 RPN total loss: 0.05034 Total loss: 1.74521 timestamp: 1654929255.2864933 iteration: 18825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.19966 L1 loss: 0.0000e+00 L2 loss: 1.16188 Learning rate: 0.02 Mask loss: 0.23687 RPN box loss: 0.0048 RPN score loss: 0.00193 RPN total loss: 0.00672 Total loss: 1.60514 timestamp: 1654929258.6617634 iteration: 18830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14957 FastRCNN class loss: 0.05413 FastRCNN total loss: 0.2037 L1 loss: 0.0000e+00 L2 loss: 1.16169 Learning rate: 0.02 Mask loss: 0.15843 RPN box loss: 0.01633 RPN score loss: 0.00189 RPN total loss: 0.01822 Total loss: 1.54203 timestamp: 1654929261.7962892 iteration: 18835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09433 FastRCNN class loss: 0.07269 FastRCNN total loss: 0.16702 L1 loss: 0.0000e+00 L2 loss: 1.16149 Learning rate: 0.02 Mask loss: 0.18082 RPN box loss: 0.06246 RPN score loss: 0.00528 RPN total loss: 0.06773 Total loss: 1.57706 timestamp: 1654929265.1546555 iteration: 18840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20076 FastRCNN class loss: 0.08658 FastRCNN total loss: 0.28734 L1 loss: 0.0000e+00 L2 loss: 1.16129 Learning rate: 0.02 Mask loss: 0.15462 RPN box loss: 0.03132 RPN score loss: 0.00717 RPN total loss: 0.03848 Total loss: 1.64174 timestamp: 1654929268.3432696 iteration: 18845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1049 FastRCNN class loss: 0.07582 FastRCNN total loss: 0.18071 L1 loss: 0.0000e+00 L2 loss: 1.16111 Learning rate: 0.02 Mask loss: 0.17138 RPN box loss: 0.06142 RPN score loss: 0.00524 RPN total loss: 0.06666 Total loss: 1.57986 timestamp: 1654929271.6689928 iteration: 18850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22303 FastRCNN class loss: 0.07577 FastRCNN total loss: 0.2988 L1 loss: 0.0000e+00 L2 loss: 1.16091 Learning rate: 0.02 Mask loss: 0.11428 RPN box loss: 0.0974 RPN score loss: 0.00318 RPN total loss: 0.10058 Total loss: 1.67457 timestamp: 1654929274.8667982 iteration: 18855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21396 FastRCNN class loss: 0.08136 FastRCNN total loss: 0.29532 L1 loss: 0.0000e+00 L2 loss: 1.16073 Learning rate: 0.02 Mask loss: 0.16626 RPN box loss: 0.07999 RPN score loss: 0.00864 RPN total loss: 0.08864 Total loss: 1.71095 timestamp: 1654929278.1934948 iteration: 18860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11297 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.18608 L1 loss: 0.0000e+00 L2 loss: 1.16053 Learning rate: 0.02 Mask loss: 0.149 RPN box loss: 0.01473 RPN score loss: 0.00459 RPN total loss: 0.01932 Total loss: 1.51493 timestamp: 1654929281.5025804 iteration: 18865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13671 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.18428 L1 loss: 0.0000e+00 L2 loss: 1.16034 Learning rate: 0.02 Mask loss: 0.17672 RPN box loss: 0.04257 RPN score loss: 0.00467 RPN total loss: 0.04724 Total loss: 1.56858 timestamp: 1654929284.7588675 iteration: 18870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23885 FastRCNN class loss: 0.12849 FastRCNN total loss: 0.36735 L1 loss: 0.0000e+00 L2 loss: 1.16017 Learning rate: 0.02 Mask loss: 0.181 RPN box loss: 0.06254 RPN score loss: 0.01508 RPN total loss: 0.07762 Total loss: 1.78613 timestamp: 1654929287.9514537 iteration: 18875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10859 FastRCNN class loss: 0.05142 FastRCNN total loss: 0.16001 L1 loss: 0.0000e+00 L2 loss: 1.15998 Learning rate: 0.02 Mask loss: 0.12468 RPN box loss: 0.03571 RPN score loss: 0.00393 RPN total loss: 0.03964 Total loss: 1.48432 timestamp: 1654929291.143172 iteration: 18880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14045 FastRCNN class loss: 0.16105 FastRCNN total loss: 0.3015 L1 loss: 0.0000e+00 L2 loss: 1.15979 Learning rate: 0.02 Mask loss: 0.20218 RPN box loss: 0.05267 RPN score loss: 0.01469 RPN total loss: 0.06737 Total loss: 1.73083 timestamp: 1654929294.3510358 iteration: 18885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16717 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.23197 L1 loss: 0.0000e+00 L2 loss: 1.1596 Learning rate: 0.02 Mask loss: 0.11647 RPN box loss: 0.05264 RPN score loss: 0.00988 RPN total loss: 0.06252 Total loss: 1.57056 timestamp: 1654929297.59158 iteration: 18890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13321 FastRCNN class loss: 0.08352 FastRCNN total loss: 0.21674 L1 loss: 0.0000e+00 L2 loss: 1.15941 Learning rate: 0.02 Mask loss: 0.16143 RPN box loss: 0.03045 RPN score loss: 0.00768 RPN total loss: 0.03812 Total loss: 1.5757 timestamp: 1654929300.9297218 iteration: 18895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1411 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.21112 L1 loss: 0.0000e+00 L2 loss: 1.15918 Learning rate: 0.02 Mask loss: 0.15277 RPN box loss: 0.07645 RPN score loss: 0.01045 RPN total loss: 0.0869 Total loss: 1.60998 timestamp: 1654929304.121979 iteration: 18900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10709 FastRCNN class loss: 0.10602 FastRCNN total loss: 0.2131 L1 loss: 0.0000e+00 L2 loss: 1.15897 Learning rate: 0.02 Mask loss: 0.12933 RPN box loss: 0.00721 RPN score loss: 0.00268 RPN total loss: 0.00989 Total loss: 1.5113 timestamp: 1654929307.4170299 iteration: 18905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17171 FastRCNN class loss: 0.13661 FastRCNN total loss: 0.30832 L1 loss: 0.0000e+00 L2 loss: 1.15878 Learning rate: 0.02 Mask loss: 0.16745 RPN box loss: 0.02573 RPN score loss: 0.00683 RPN total loss: 0.03256 Total loss: 1.66711 timestamp: 1654929310.6832883 iteration: 18910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12537 FastRCNN class loss: 0.12672 FastRCNN total loss: 0.25209 L1 loss: 0.0000e+00 L2 loss: 1.15859 Learning rate: 0.02 Mask loss: 0.17801 RPN box loss: 0.06077 RPN score loss: 0.01991 RPN total loss: 0.08068 Total loss: 1.66938 timestamp: 1654929313.939366 iteration: 18915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18848 FastRCNN class loss: 0.0781 FastRCNN total loss: 0.26657 L1 loss: 0.0000e+00 L2 loss: 1.15839 Learning rate: 0.02 Mask loss: 0.15637 RPN box loss: 0.04326 RPN score loss: 0.01147 RPN total loss: 0.05473 Total loss: 1.63606 timestamp: 1654929317.1013205 iteration: 18920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.12718 FastRCNN total loss: 0.27889 L1 loss: 0.0000e+00 L2 loss: 1.15821 Learning rate: 0.02 Mask loss: 0.15788 RPN box loss: 0.03542 RPN score loss: 0.00393 RPN total loss: 0.03935 Total loss: 1.63432 timestamp: 1654929320.3866544 iteration: 18925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06325 FastRCNN class loss: 0.04481 FastRCNN total loss: 0.10807 L1 loss: 0.0000e+00 L2 loss: 1.15801 Learning rate: 0.02 Mask loss: 0.10077 RPN box loss: 0.02228 RPN score loss: 0.00599 RPN total loss: 0.02827 Total loss: 1.39512 timestamp: 1654929323.8075454 iteration: 18930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13681 FastRCNN class loss: 0.08414 FastRCNN total loss: 0.22096 L1 loss: 0.0000e+00 L2 loss: 1.15781 Learning rate: 0.02 Mask loss: 0.11288 RPN box loss: 0.03203 RPN score loss: 0.00276 RPN total loss: 0.03479 Total loss: 1.52644 timestamp: 1654929327.0528836 iteration: 18935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21314 FastRCNN class loss: 0.12608 FastRCNN total loss: 0.33921 L1 loss: 0.0000e+00 L2 loss: 1.15763 Learning rate: 0.02 Mask loss: 0.31539 RPN box loss: 0.04996 RPN score loss: 0.01912 RPN total loss: 0.06909 Total loss: 1.88131 timestamp: 1654929330.4806414 iteration: 18940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12764 FastRCNN class loss: 0.16035 FastRCNN total loss: 0.288 L1 loss: 0.0000e+00 L2 loss: 1.15744 Learning rate: 0.02 Mask loss: 0.20028 RPN box loss: 0.04544 RPN score loss: 0.00198 RPN total loss: 0.04741 Total loss: 1.69314 timestamp: 1654929333.6582797 iteration: 18945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15434 FastRCNN class loss: 0.09558 FastRCNN total loss: 0.24992 L1 loss: 0.0000e+00 L2 loss: 1.15726 Learning rate: 0.02 Mask loss: 0.34217 RPN box loss: 0.01766 RPN score loss: 0.00789 RPN total loss: 0.02556 Total loss: 1.77491 timestamp: 1654929337.074489 iteration: 18950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12687 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.21767 L1 loss: 0.0000e+00 L2 loss: 1.15709 Learning rate: 0.02 Mask loss: 0.14711 RPN box loss: 0.01926 RPN score loss: 0.01247 RPN total loss: 0.03174 Total loss: 1.55361 timestamp: 1654929340.1910455 iteration: 18955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14239 FastRCNN class loss: 0.0928 FastRCNN total loss: 0.23519 L1 loss: 0.0000e+00 L2 loss: 1.1569 Learning rate: 0.02 Mask loss: 0.16709 RPN box loss: 0.018 RPN score loss: 0.00886 RPN total loss: 0.02686 Total loss: 1.58603 timestamp: 1654929343.5264463 iteration: 18960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18618 FastRCNN class loss: 0.08817 FastRCNN total loss: 0.27434 L1 loss: 0.0000e+00 L2 loss: 1.15671 Learning rate: 0.02 Mask loss: 0.18977 RPN box loss: 0.03734 RPN score loss: 0.00298 RPN total loss: 0.04033 Total loss: 1.66115 timestamp: 1654929346.7502406 iteration: 18965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16899 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.24502 L1 loss: 0.0000e+00 L2 loss: 1.15653 Learning rate: 0.02 Mask loss: 0.17156 RPN box loss: 0.03963 RPN score loss: 0.00564 RPN total loss: 0.04527 Total loss: 1.61838 timestamp: 1654929350.0608025 iteration: 18970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14251 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.2018 L1 loss: 0.0000e+00 L2 loss: 1.15635 Learning rate: 0.02 Mask loss: 0.16338 RPN box loss: 0.02939 RPN score loss: 0.00548 RPN total loss: 0.03487 Total loss: 1.5564 timestamp: 1654929353.5078416 iteration: 18975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18881 FastRCNN class loss: 0.14435 FastRCNN total loss: 0.33316 L1 loss: 0.0000e+00 L2 loss: 1.15616 Learning rate: 0.02 Mask loss: 0.18433 RPN box loss: 0.01914 RPN score loss: 0.00278 RPN total loss: 0.02191 Total loss: 1.69557 timestamp: 1654929356.77797 iteration: 18980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17708 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.24133 L1 loss: 0.0000e+00 L2 loss: 1.15596 Learning rate: 0.02 Mask loss: 0.11599 RPN box loss: 0.01294 RPN score loss: 0.00319 RPN total loss: 0.01613 Total loss: 1.52941 timestamp: 1654929359.9613686 iteration: 18985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12955 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.19294 L1 loss: 0.0000e+00 L2 loss: 1.15578 Learning rate: 0.02 Mask loss: 0.11129 RPN box loss: 0.03074 RPN score loss: 0.00641 RPN total loss: 0.03716 Total loss: 1.49716 timestamp: 1654929363.192185 iteration: 18990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11579 FastRCNN class loss: 0.08359 FastRCNN total loss: 0.19938 L1 loss: 0.0000e+00 L2 loss: 1.15558 Learning rate: 0.02 Mask loss: 0.1203 RPN box loss: 0.05321 RPN score loss: 0.00822 RPN total loss: 0.06143 Total loss: 1.53669 timestamp: 1654929366.4427912 iteration: 18995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09947 FastRCNN class loss: 0.08586 FastRCNN total loss: 0.18534 L1 loss: 0.0000e+00 L2 loss: 1.15538 Learning rate: 0.02 Mask loss: 0.11606 RPN box loss: 0.04347 RPN score loss: 0.0141 RPN total loss: 0.05758 Total loss: 1.51435 timestamp: 1654929369.59762 iteration: 19000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10438 FastRCNN class loss: 0.03431 FastRCNN total loss: 0.13869 L1 loss: 0.0000e+00 L2 loss: 1.15518 Learning rate: 0.02 Mask loss: 0.12136 RPN box loss: 0.04371 RPN score loss: 0.00167 RPN total loss: 0.04538 Total loss: 1.46061 timestamp: 1654929372.8594818 iteration: 19005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1795 FastRCNN class loss: 0.08727 FastRCNN total loss: 0.26677 L1 loss: 0.0000e+00 L2 loss: 1.15501 Learning rate: 0.02 Mask loss: 0.18208 RPN box loss: 0.01557 RPN score loss: 0.00879 RPN total loss: 0.02436 Total loss: 1.62822 timestamp: 1654929376.079247 iteration: 19010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13604 FastRCNN class loss: 0.09602 FastRCNN total loss: 0.23206 L1 loss: 0.0000e+00 L2 loss: 1.15484 Learning rate: 0.02 Mask loss: 0.12221 RPN box loss: 0.05218 RPN score loss: 0.00505 RPN total loss: 0.05722 Total loss: 1.56634 timestamp: 1654929379.2835026 iteration: 19015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11726 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.21502 L1 loss: 0.0000e+00 L2 loss: 1.15464 Learning rate: 0.02 Mask loss: 0.34811 RPN box loss: 0.02096 RPN score loss: 0.0067 RPN total loss: 0.02766 Total loss: 1.74544 timestamp: 1654929382.4605753 iteration: 19020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09671 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.15926 L1 loss: 0.0000e+00 L2 loss: 1.15445 Learning rate: 0.02 Mask loss: 0.17634 RPN box loss: 0.07811 RPN score loss: 0.0037 RPN total loss: 0.08181 Total loss: 1.57187 timestamp: 1654929385.7309847 iteration: 19025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16911 FastRCNN class loss: 0.1307 FastRCNN total loss: 0.29982 L1 loss: 0.0000e+00 L2 loss: 1.15425 Learning rate: 0.02 Mask loss: 0.2211 RPN box loss: 0.02159 RPN score loss: 0.00901 RPN total loss: 0.0306 Total loss: 1.70577 timestamp: 1654929388.9854393 iteration: 19030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06215 FastRCNN class loss: 0.04719 FastRCNN total loss: 0.10934 L1 loss: 0.0000e+00 L2 loss: 1.15406 Learning rate: 0.02 Mask loss: 0.11129 RPN box loss: 0.0488 RPN score loss: 0.00306 RPN total loss: 0.05185 Total loss: 1.42654 timestamp: 1654929392.1890478 iteration: 19035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21881 FastRCNN class loss: 0.18042 FastRCNN total loss: 0.39923 L1 loss: 0.0000e+00 L2 loss: 1.15388 Learning rate: 0.02 Mask loss: 0.25285 RPN box loss: 0.06464 RPN score loss: 0.01352 RPN total loss: 0.07816 Total loss: 1.88412 timestamp: 1654929395.4477353 iteration: 19040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16663 FastRCNN class loss: 0.18163 FastRCNN total loss: 0.34826 L1 loss: 0.0000e+00 L2 loss: 1.15368 Learning rate: 0.02 Mask loss: 0.18615 RPN box loss: 0.03045 RPN score loss: 0.0095 RPN total loss: 0.03995 Total loss: 1.72804 timestamp: 1654929398.669688 iteration: 19045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18331 FastRCNN class loss: 0.09293 FastRCNN total loss: 0.27624 L1 loss: 0.0000e+00 L2 loss: 1.1535 Learning rate: 0.02 Mask loss: 0.19465 RPN box loss: 0.04097 RPN score loss: 0.01198 RPN total loss: 0.05295 Total loss: 1.67734 timestamp: 1654929401.945169 iteration: 19050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15337 FastRCNN class loss: 0.11242 FastRCNN total loss: 0.26579 L1 loss: 0.0000e+00 L2 loss: 1.1533 Learning rate: 0.02 Mask loss: 0.20784 RPN box loss: 0.03672 RPN score loss: 0.0123 RPN total loss: 0.04902 Total loss: 1.67595 timestamp: 1654929405.0667505 iteration: 19055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.10322 FastRCNN total loss: 0.19333 L1 loss: 0.0000e+00 L2 loss: 1.1531 Learning rate: 0.02 Mask loss: 0.16871 RPN box loss: 0.01474 RPN score loss: 0.01365 RPN total loss: 0.02838 Total loss: 1.54353 timestamp: 1654929408.2789428 iteration: 19060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18166 FastRCNN class loss: 0.12229 FastRCNN total loss: 0.30395 L1 loss: 0.0000e+00 L2 loss: 1.15292 Learning rate: 0.02 Mask loss: 0.13948 RPN box loss: 0.03672 RPN score loss: 0.00797 RPN total loss: 0.04469 Total loss: 1.64105 timestamp: 1654929411.4547899 iteration: 19065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15723 FastRCNN class loss: 0.08685 FastRCNN total loss: 0.24408 L1 loss: 0.0000e+00 L2 loss: 1.15273 Learning rate: 0.02 Mask loss: 0.12988 RPN box loss: 0.04479 RPN score loss: 0.00412 RPN total loss: 0.04891 Total loss: 1.5756 timestamp: 1654929414.6225212 iteration: 19070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11387 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.17922 L1 loss: 0.0000e+00 L2 loss: 1.15255 Learning rate: 0.02 Mask loss: 0.13393 RPN box loss: 0.01645 RPN score loss: 0.00404 RPN total loss: 0.0205 Total loss: 1.4862 timestamp: 1654929417.7594025 iteration: 19075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16069 FastRCNN class loss: 0.09345 FastRCNN total loss: 0.25414 L1 loss: 0.0000e+00 L2 loss: 1.15236 Learning rate: 0.02 Mask loss: 0.14757 RPN box loss: 0.02377 RPN score loss: 0.00716 RPN total loss: 0.03093 Total loss: 1.585 timestamp: 1654929421.0814438 iteration: 19080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14237 FastRCNN class loss: 0.09226 FastRCNN total loss: 0.23464 L1 loss: 0.0000e+00 L2 loss: 1.15217 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.00868 RPN score loss: 0.01769 RPN total loss: 0.02636 Total loss: 1.55149 timestamp: 1654929424.437332 iteration: 19085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16616 FastRCNN class loss: 0.0685 FastRCNN total loss: 0.23465 L1 loss: 0.0000e+00 L2 loss: 1.152 Learning rate: 0.02 Mask loss: 0.17953 RPN box loss: 0.09588 RPN score loss: 0.0053 RPN total loss: 0.10118 Total loss: 1.66736 timestamp: 1654929427.7067993 iteration: 19090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16606 FastRCNN class loss: 0.05575 FastRCNN total loss: 0.22181 L1 loss: 0.0000e+00 L2 loss: 1.15181 Learning rate: 0.02 Mask loss: 0.17423 RPN box loss: 0.0464 RPN score loss: 0.0016 RPN total loss: 0.048 Total loss: 1.59586 timestamp: 1654929430.9962606 iteration: 19095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14571 FastRCNN class loss: 0.08465 FastRCNN total loss: 0.23036 L1 loss: 0.0000e+00 L2 loss: 1.15164 Learning rate: 0.02 Mask loss: 0.0936 RPN box loss: 0.01716 RPN score loss: 0.00259 RPN total loss: 0.01975 Total loss: 1.49534 timestamp: 1654929434.1834133 iteration: 19100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07458 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.13415 L1 loss: 0.0000e+00 L2 loss: 1.15146 Learning rate: 0.02 Mask loss: 0.09818 RPN box loss: 0.01281 RPN score loss: 0.00485 RPN total loss: 0.01766 Total loss: 1.40144 timestamp: 1654929437.434452 iteration: 19105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20683 FastRCNN class loss: 0.07941 FastRCNN total loss: 0.28624 L1 loss: 0.0000e+00 L2 loss: 1.15125 Learning rate: 0.02 Mask loss: 0.18329 RPN box loss: 0.07691 RPN score loss: 0.0107 RPN total loss: 0.08761 Total loss: 1.7084 timestamp: 1654929440.5384572 iteration: 19110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12096 FastRCNN class loss: 0.12671 FastRCNN total loss: 0.24767 L1 loss: 0.0000e+00 L2 loss: 1.15105 Learning rate: 0.02 Mask loss: 0.16518 RPN box loss: 0.07511 RPN score loss: 0.01338 RPN total loss: 0.08849 Total loss: 1.65239 timestamp: 1654929443.9237428 iteration: 19115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17472 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.27567 L1 loss: 0.0000e+00 L2 loss: 1.15086 Learning rate: 0.02 Mask loss: 0.1376 RPN box loss: 0.03011 RPN score loss: 0.00468 RPN total loss: 0.03478 Total loss: 1.59891 timestamp: 1654929447.1764894 iteration: 19120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09887 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.16548 L1 loss: 0.0000e+00 L2 loss: 1.15066 Learning rate: 0.02 Mask loss: 0.13045 RPN box loss: 0.01457 RPN score loss: 0.0034 RPN total loss: 0.01797 Total loss: 1.46456 timestamp: 1654929450.6554332 iteration: 19125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16252 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.21251 L1 loss: 0.0000e+00 L2 loss: 1.15046 Learning rate: 0.02 Mask loss: 0.14032 RPN box loss: 0.02691 RPN score loss: 0.00396 RPN total loss: 0.03087 Total loss: 1.53416 timestamp: 1654929453.8469627 iteration: 19130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17021 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.24827 L1 loss: 0.0000e+00 L2 loss: 1.15029 Learning rate: 0.02 Mask loss: 0.19936 RPN box loss: 0.02969 RPN score loss: 0.01184 RPN total loss: 0.04153 Total loss: 1.63944 timestamp: 1654929457.1337504 iteration: 19135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14038 FastRCNN class loss: 0.10719 FastRCNN total loss: 0.24757 L1 loss: 0.0000e+00 L2 loss: 1.15009 Learning rate: 0.02 Mask loss: 0.18204 RPN box loss: 0.06966 RPN score loss: 0.00633 RPN total loss: 0.07599 Total loss: 1.65568 timestamp: 1654929460.5003355 iteration: 19140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18377 FastRCNN class loss: 0.11057 FastRCNN total loss: 0.29434 L1 loss: 0.0000e+00 L2 loss: 1.1499 Learning rate: 0.02 Mask loss: 0.12738 RPN box loss: 0.01588 RPN score loss: 0.00306 RPN total loss: 0.01894 Total loss: 1.59056 timestamp: 1654929463.751916 iteration: 19145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08661 FastRCNN class loss: 0.07745 FastRCNN total loss: 0.16406 L1 loss: 0.0000e+00 L2 loss: 1.14971 Learning rate: 0.02 Mask loss: 0.17201 RPN box loss: 0.09935 RPN score loss: 0.00487 RPN total loss: 0.10422 Total loss: 1.59 timestamp: 1654929466.98331 iteration: 19150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13304 FastRCNN class loss: 0.08528 FastRCNN total loss: 0.21832 L1 loss: 0.0000e+00 L2 loss: 1.14953 Learning rate: 0.02 Mask loss: 0.19969 RPN box loss: 0.02356 RPN score loss: 0.01896 RPN total loss: 0.04253 Total loss: 1.61006 timestamp: 1654929470.2090063 iteration: 19155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16482 FastRCNN class loss: 0.0802 FastRCNN total loss: 0.24502 L1 loss: 0.0000e+00 L2 loss: 1.14933 Learning rate: 0.02 Mask loss: 0.17276 RPN box loss: 0.01102 RPN score loss: 0.00629 RPN total loss: 0.01731 Total loss: 1.58442 timestamp: 1654929473.480345 iteration: 19160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11488 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.18886 L1 loss: 0.0000e+00 L2 loss: 1.14913 Learning rate: 0.02 Mask loss: 0.15931 RPN box loss: 0.02528 RPN score loss: 0.00291 RPN total loss: 0.02819 Total loss: 1.5255 timestamp: 1654929476.670826 iteration: 19165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12837 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.21045 L1 loss: 0.0000e+00 L2 loss: 1.14897 Learning rate: 0.02 Mask loss: 0.12567 RPN box loss: 0.06105 RPN score loss: 0.01088 RPN total loss: 0.07193 Total loss: 1.55702 timestamp: 1654929479.9465625 iteration: 19170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1092 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.16129 L1 loss: 0.0000e+00 L2 loss: 1.14878 Learning rate: 0.02 Mask loss: 0.11801 RPN box loss: 0.00834 RPN score loss: 0.00256 RPN total loss: 0.0109 Total loss: 1.43898 timestamp: 1654929483.1463566 iteration: 19175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12423 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.19412 L1 loss: 0.0000e+00 L2 loss: 1.14858 Learning rate: 0.02 Mask loss: 0.08525 RPN box loss: 0.03099 RPN score loss: 0.00473 RPN total loss: 0.03573 Total loss: 1.46367 timestamp: 1654929486.439126 iteration: 19180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09991 FastRCNN class loss: 0.08993 FastRCNN total loss: 0.18984 L1 loss: 0.0000e+00 L2 loss: 1.1484 Learning rate: 0.02 Mask loss: 0.10247 RPN box loss: 0.03257 RPN score loss: 0.00319 RPN total loss: 0.03576 Total loss: 1.47646 timestamp: 1654929489.6561573 iteration: 19185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13389 FastRCNN class loss: 0.07612 FastRCNN total loss: 0.21002 L1 loss: 0.0000e+00 L2 loss: 1.1482 Learning rate: 0.02 Mask loss: 0.19046 RPN box loss: 0.08862 RPN score loss: 0.01236 RPN total loss: 0.10098 Total loss: 1.64965 timestamp: 1654929492.9089103 iteration: 19190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.19287 L1 loss: 0.0000e+00 L2 loss: 1.148 Learning rate: 0.02 Mask loss: 0.17136 RPN box loss: 0.04182 RPN score loss: 0.00797 RPN total loss: 0.04978 Total loss: 1.56202 timestamp: 1654929496.2518106 iteration: 19195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11896 FastRCNN class loss: 0.06544 FastRCNN total loss: 0.18441 L1 loss: 0.0000e+00 L2 loss: 1.1478 Learning rate: 0.02 Mask loss: 0.16051 RPN box loss: 0.025 RPN score loss: 0.01274 RPN total loss: 0.03773 Total loss: 1.53045 timestamp: 1654929499.5408084 iteration: 19200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17562 FastRCNN class loss: 0.20583 FastRCNN total loss: 0.38145 L1 loss: 0.0000e+00 L2 loss: 1.14761 Learning rate: 0.02 Mask loss: 0.13489 RPN box loss: 0.03804 RPN score loss: 0.01027 RPN total loss: 0.04831 Total loss: 1.71226 timestamp: 1654929502.810563 iteration: 19205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1104 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.1731 L1 loss: 0.0000e+00 L2 loss: 1.14742 Learning rate: 0.02 Mask loss: 0.12373 RPN box loss: 0.06711 RPN score loss: 0.01015 RPN total loss: 0.07726 Total loss: 1.5215 timestamp: 1654929506.0631077 iteration: 19210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07977 FastRCNN class loss: 0.05208 FastRCNN total loss: 0.13186 L1 loss: 0.0000e+00 L2 loss: 1.14721 Learning rate: 0.02 Mask loss: 0.08865 RPN box loss: 0.01491 RPN score loss: 0.00503 RPN total loss: 0.01993 Total loss: 1.38765 timestamp: 1654929509.3717182 iteration: 19215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12525 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.21338 L1 loss: 0.0000e+00 L2 loss: 1.14703 Learning rate: 0.02 Mask loss: 0.10362 RPN box loss: 0.00822 RPN score loss: 0.00438 RPN total loss: 0.0126 Total loss: 1.47663 timestamp: 1654929512.5704103 iteration: 19220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16126 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.22895 L1 loss: 0.0000e+00 L2 loss: 1.14686 Learning rate: 0.02 Mask loss: 0.15853 RPN box loss: 0.01787 RPN score loss: 0.00512 RPN total loss: 0.02299 Total loss: 1.55733 timestamp: 1654929515.880428 iteration: 19225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12387 FastRCNN class loss: 0.09467 FastRCNN total loss: 0.21855 L1 loss: 0.0000e+00 L2 loss: 1.14667 Learning rate: 0.02 Mask loss: 0.20692 RPN box loss: 0.01145 RPN score loss: 0.00502 RPN total loss: 0.01647 Total loss: 1.58861 timestamp: 1654929519.0589461 iteration: 19230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13806 FastRCNN class loss: 0.13377 FastRCNN total loss: 0.27182 L1 loss: 0.0000e+00 L2 loss: 1.14648 Learning rate: 0.02 Mask loss: 0.11133 RPN box loss: 0.06556 RPN score loss: 0.00692 RPN total loss: 0.07248 Total loss: 1.60211 timestamp: 1654929522.4176269 iteration: 19235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11802 FastRCNN class loss: 0.0482 FastRCNN total loss: 0.16622 L1 loss: 0.0000e+00 L2 loss: 1.14629 Learning rate: 0.02 Mask loss: 0.15203 RPN box loss: 0.01161 RPN score loss: 0.00376 RPN total loss: 0.01537 Total loss: 1.47991 timestamp: 1654929525.6595078 iteration: 19240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14641 FastRCNN class loss: 0.16626 FastRCNN total loss: 0.31267 L1 loss: 0.0000e+00 L2 loss: 1.1461 Learning rate: 0.02 Mask loss: 0.25016 RPN box loss: 0.0466 RPN score loss: 0.04504 RPN total loss: 0.09163 Total loss: 1.80056 timestamp: 1654929528.8928268 iteration: 19245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14042 FastRCNN class loss: 0.10214 FastRCNN total loss: 0.24256 L1 loss: 0.0000e+00 L2 loss: 1.1459 Learning rate: 0.02 Mask loss: 0.20274 RPN box loss: 0.05762 RPN score loss: 0.00633 RPN total loss: 0.06395 Total loss: 1.65515 timestamp: 1654929532.234071 iteration: 19250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1641 FastRCNN class loss: 0.11884 FastRCNN total loss: 0.28294 L1 loss: 0.0000e+00 L2 loss: 1.14568 Learning rate: 0.02 Mask loss: 0.1594 RPN box loss: 0.05736 RPN score loss: 0.0065 RPN total loss: 0.06387 Total loss: 1.65188 timestamp: 1654929535.5361586 iteration: 19255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.2097 L1 loss: 0.0000e+00 L2 loss: 1.14549 Learning rate: 0.02 Mask loss: 0.1725 RPN box loss: 0.03111 RPN score loss: 0.01041 RPN total loss: 0.04152 Total loss: 1.56921 timestamp: 1654929538.8471603 iteration: 19260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11189 FastRCNN class loss: 0.11194 FastRCNN total loss: 0.22384 L1 loss: 0.0000e+00 L2 loss: 1.14531 Learning rate: 0.02 Mask loss: 0.18091 RPN box loss: 0.02332 RPN score loss: 0.01122 RPN total loss: 0.03453 Total loss: 1.58459 timestamp: 1654929542.050409 iteration: 19265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11966 FastRCNN class loss: 0.07868 FastRCNN total loss: 0.19834 L1 loss: 0.0000e+00 L2 loss: 1.14516 Learning rate: 0.02 Mask loss: 0.17546 RPN box loss: 0.04959 RPN score loss: 0.01651 RPN total loss: 0.06609 Total loss: 1.58506 timestamp: 1654929545.31582 iteration: 19270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11672 FastRCNN class loss: 0.10884 FastRCNN total loss: 0.22556 L1 loss: 0.0000e+00 L2 loss: 1.14496 Learning rate: 0.02 Mask loss: 0.14761 RPN box loss: 0.02985 RPN score loss: 0.0012 RPN total loss: 0.03104 Total loss: 1.54917 timestamp: 1654929548.5988567 iteration: 19275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12015 FastRCNN class loss: 0.08313 FastRCNN total loss: 0.20328 L1 loss: 0.0000e+00 L2 loss: 1.14477 Learning rate: 0.02 Mask loss: 0.12054 RPN box loss: 0.01998 RPN score loss: 0.00575 RPN total loss: 0.02573 Total loss: 1.49432 timestamp: 1654929552.0744448 iteration: 19280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16016 FastRCNN class loss: 0.06299 FastRCNN total loss: 0.22315 L1 loss: 0.0000e+00 L2 loss: 1.14457 Learning rate: 0.02 Mask loss: 0.11592 RPN box loss: 0.02382 RPN score loss: 0.00355 RPN total loss: 0.02738 Total loss: 1.51101 timestamp: 1654929555.287384 iteration: 19285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2337 FastRCNN class loss: 0.0966 FastRCNN total loss: 0.3303 L1 loss: 0.0000e+00 L2 loss: 1.1444 Learning rate: 0.02 Mask loss: 0.1511 RPN box loss: 0.0276 RPN score loss: 0.01022 RPN total loss: 0.03781 Total loss: 1.66361 timestamp: 1654929558.6078458 iteration: 19290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16277 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.23192 L1 loss: 0.0000e+00 L2 loss: 1.14424 Learning rate: 0.02 Mask loss: 0.12314 RPN box loss: 0.00654 RPN score loss: 0.00182 RPN total loss: 0.00836 Total loss: 1.50766 timestamp: 1654929561.9354274 iteration: 19295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.16628 L1 loss: 0.0000e+00 L2 loss: 1.14405 Learning rate: 0.02 Mask loss: 0.11621 RPN box loss: 0.03962 RPN score loss: 0.00596 RPN total loss: 0.04558 Total loss: 1.47212 timestamp: 1654929565.0775332 iteration: 19300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.12934 FastRCNN total loss: 0.23169 L1 loss: 0.0000e+00 L2 loss: 1.14385 Learning rate: 0.02 Mask loss: 0.13656 RPN box loss: 0.06654 RPN score loss: 0.00522 RPN total loss: 0.07176 Total loss: 1.58386 timestamp: 1654929568.3363292 iteration: 19305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12123 FastRCNN class loss: 0.07589 FastRCNN total loss: 0.19712 L1 loss: 0.0000e+00 L2 loss: 1.14366 Learning rate: 0.02 Mask loss: 0.15922 RPN box loss: 0.03326 RPN score loss: 0.00213 RPN total loss: 0.0354 Total loss: 1.5354 timestamp: 1654929571.6052456 iteration: 19310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08634 FastRCNN class loss: 0.05349 FastRCNN total loss: 0.13983 L1 loss: 0.0000e+00 L2 loss: 1.14347 Learning rate: 0.02 Mask loss: 0.11547 RPN box loss: 0.0674 RPN score loss: 0.00483 RPN total loss: 0.07223 Total loss: 1.471 timestamp: 1654929574.8738084 iteration: 19315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15163 FastRCNN class loss: 0.12348 FastRCNN total loss: 0.27511 L1 loss: 0.0000e+00 L2 loss: 1.14329 Learning rate: 0.02 Mask loss: 0.18487 RPN box loss: 0.06541 RPN score loss: 0.01241 RPN total loss: 0.07781 Total loss: 1.68107 timestamp: 1654929578.0595834 iteration: 19320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16907 FastRCNN class loss: 0.05903 FastRCNN total loss: 0.22811 L1 loss: 0.0000e+00 L2 loss: 1.14312 Learning rate: 0.02 Mask loss: 0.14091 RPN box loss: 0.01382 RPN score loss: 0.00631 RPN total loss: 0.02014 Total loss: 1.53227 timestamp: 1654929581.333069 iteration: 19325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14849 FastRCNN class loss: 0.10797 FastRCNN total loss: 0.25647 L1 loss: 0.0000e+00 L2 loss: 1.14293 Learning rate: 0.02 Mask loss: 0.23899 RPN box loss: 0.01893 RPN score loss: 0.00799 RPN total loss: 0.02692 Total loss: 1.66532 timestamp: 1654929584.5133207 iteration: 19330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12135 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.19901 L1 loss: 0.0000e+00 L2 loss: 1.14272 Learning rate: 0.02 Mask loss: 0.1637 RPN box loss: 0.03252 RPN score loss: 0.00915 RPN total loss: 0.04166 Total loss: 1.54709 timestamp: 1654929587.899265 iteration: 19335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18111 FastRCNN class loss: 0.09815 FastRCNN total loss: 0.27926 L1 loss: 0.0000e+00 L2 loss: 1.14254 Learning rate: 0.02 Mask loss: 0.10237 RPN box loss: 0.03702 RPN score loss: 0.00339 RPN total loss: 0.04041 Total loss: 1.56459 timestamp: 1654929591.092531 iteration: 19340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14625 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.22466 L1 loss: 0.0000e+00 L2 loss: 1.14235 Learning rate: 0.02 Mask loss: 0.18582 RPN box loss: 0.0967 RPN score loss: 0.00754 RPN total loss: 0.10424 Total loss: 1.65707 timestamp: 1654929594.3670862 iteration: 19345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2474 FastRCNN class loss: 0.12275 FastRCNN total loss: 0.37015 L1 loss: 0.0000e+00 L2 loss: 1.14216 Learning rate: 0.02 Mask loss: 0.2494 RPN box loss: 0.01744 RPN score loss: 0.0091 RPN total loss: 0.02654 Total loss: 1.78825 timestamp: 1654929597.6121604 iteration: 19350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19339 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.27712 L1 loss: 0.0000e+00 L2 loss: 1.14197 Learning rate: 0.02 Mask loss: 0.13348 RPN box loss: 0.02826 RPN score loss: 0.00265 RPN total loss: 0.03091 Total loss: 1.58348 timestamp: 1654929600.7952533 iteration: 19355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13914 FastRCNN class loss: 0.13446 FastRCNN total loss: 0.2736 L1 loss: 0.0000e+00 L2 loss: 1.14177 Learning rate: 0.02 Mask loss: 0.19211 RPN box loss: 0.06275 RPN score loss: 0.0116 RPN total loss: 0.07435 Total loss: 1.68184 timestamp: 1654929604.0705252 iteration: 19360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13371 FastRCNN class loss: 0.06642 FastRCNN total loss: 0.20013 L1 loss: 0.0000e+00 L2 loss: 1.14158 Learning rate: 0.02 Mask loss: 0.08806 RPN box loss: 0.0388 RPN score loss: 0.00958 RPN total loss: 0.04837 Total loss: 1.47815 timestamp: 1654929607.2414267 iteration: 19365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14713 FastRCNN class loss: 0.09302 FastRCNN total loss: 0.24016 L1 loss: 0.0000e+00 L2 loss: 1.14141 Learning rate: 0.02 Mask loss: 0.17808 RPN box loss: 0.01977 RPN score loss: 0.00393 RPN total loss: 0.0237 Total loss: 1.58334 timestamp: 1654929610.5655243 iteration: 19370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14762 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.23294 L1 loss: 0.0000e+00 L2 loss: 1.14123 Learning rate: 0.02 Mask loss: 0.25356 RPN box loss: 0.04906 RPN score loss: 0.01194 RPN total loss: 0.061 Total loss: 1.68873 timestamp: 1654929613.7786536 iteration: 19375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15321 FastRCNN class loss: 0.13763 FastRCNN total loss: 0.29084 L1 loss: 0.0000e+00 L2 loss: 1.14105 Learning rate: 0.02 Mask loss: 0.22814 RPN box loss: 0.02894 RPN score loss: 0.01791 RPN total loss: 0.04685 Total loss: 1.70688 timestamp: 1654929617.0619757 iteration: 19380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18776 FastRCNN class loss: 0.11254 FastRCNN total loss: 0.3003 L1 loss: 0.0000e+00 L2 loss: 1.14086 Learning rate: 0.02 Mask loss: 0.18968 RPN box loss: 0.0282 RPN score loss: 0.01471 RPN total loss: 0.04291 Total loss: 1.67375 timestamp: 1654929620.2254653 iteration: 19385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13733 FastRCNN class loss: 0.13093 FastRCNN total loss: 0.26826 L1 loss: 0.0000e+00 L2 loss: 1.14065 Learning rate: 0.02 Mask loss: 0.19348 RPN box loss: 0.02774 RPN score loss: 0.0059 RPN total loss: 0.03364 Total loss: 1.63603 timestamp: 1654929623.5930696 iteration: 19390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11634 FastRCNN class loss: 0.07543 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 1.14046 Learning rate: 0.02 Mask loss: 0.14407 RPN box loss: 0.03227 RPN score loss: 0.00594 RPN total loss: 0.03821 Total loss: 1.51451 timestamp: 1654929626.8885527 iteration: 19395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17773 FastRCNN class loss: 0.10442 FastRCNN total loss: 0.28215 L1 loss: 0.0000e+00 L2 loss: 1.14027 Learning rate: 0.02 Mask loss: 0.14105 RPN box loss: 0.05602 RPN score loss: 0.03874 RPN total loss: 0.09476 Total loss: 1.65824 timestamp: 1654929630.230316 iteration: 19400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.18693 L1 loss: 0.0000e+00 L2 loss: 1.14007 Learning rate: 0.02 Mask loss: 0.20684 RPN box loss: 0.02 RPN score loss: 0.00461 RPN total loss: 0.02461 Total loss: 1.55844 timestamp: 1654929633.519279 iteration: 19405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.09977 FastRCNN total loss: 0.21449 L1 loss: 0.0000e+00 L2 loss: 1.13989 Learning rate: 0.02 Mask loss: 0.16773 RPN box loss: 0.0231 RPN score loss: 0.00974 RPN total loss: 0.03284 Total loss: 1.55494 timestamp: 1654929636.6646383 iteration: 19410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10572 FastRCNN class loss: 0.08628 FastRCNN total loss: 0.192 L1 loss: 0.0000e+00 L2 loss: 1.13971 Learning rate: 0.02 Mask loss: 0.12264 RPN box loss: 0.02423 RPN score loss: 0.00366 RPN total loss: 0.02789 Total loss: 1.48224 timestamp: 1654929639.942732 iteration: 19415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.2359 L1 loss: 0.0000e+00 L2 loss: 1.13951 Learning rate: 0.02 Mask loss: 0.1422 RPN box loss: 0.01735 RPN score loss: 0.00559 RPN total loss: 0.02294 Total loss: 1.54055 timestamp: 1654929643.0565355 iteration: 19420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15828 FastRCNN class loss: 0.10151 FastRCNN total loss: 0.25979 L1 loss: 0.0000e+00 L2 loss: 1.13932 Learning rate: 0.02 Mask loss: 0.17581 RPN box loss: 0.03119 RPN score loss: 0.01528 RPN total loss: 0.04647 Total loss: 1.62139 timestamp: 1654929646.336802 iteration: 19425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14866 FastRCNN class loss: 0.09679 FastRCNN total loss: 0.24545 L1 loss: 0.0000e+00 L2 loss: 1.13912 Learning rate: 0.02 Mask loss: 0.16147 RPN box loss: 0.07846 RPN score loss: 0.013 RPN total loss: 0.09146 Total loss: 1.6375 timestamp: 1654929649.52544 iteration: 19430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1652 FastRCNN class loss: 0.10436 FastRCNN total loss: 0.26956 L1 loss: 0.0000e+00 L2 loss: 1.13894 Learning rate: 0.02 Mask loss: 0.15713 RPN box loss: 0.08029 RPN score loss: 0.00891 RPN total loss: 0.08919 Total loss: 1.65482 timestamp: 1654929652.8818161 iteration: 19435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20133 FastRCNN class loss: 0.11694 FastRCNN total loss: 0.31827 L1 loss: 0.0000e+00 L2 loss: 1.13876 Learning rate: 0.02 Mask loss: 0.15748 RPN box loss: 0.03687 RPN score loss: 0.00694 RPN total loss: 0.0438 Total loss: 1.65831 timestamp: 1654929656.059417 iteration: 19440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08784 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 1.13855 Learning rate: 0.02 Mask loss: 0.14744 RPN box loss: 0.03162 RPN score loss: 0.00449 RPN total loss: 0.03611 Total loss: 1.48217 timestamp: 1654929659.265913 iteration: 19445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15084 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.21985 L1 loss: 0.0000e+00 L2 loss: 1.13835 Learning rate: 0.02 Mask loss: 0.18163 RPN box loss: 0.06343 RPN score loss: 0.00918 RPN total loss: 0.0726 Total loss: 1.61244 timestamp: 1654929662.5334008 iteration: 19450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06501 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.12629 L1 loss: 0.0000e+00 L2 loss: 1.13816 Learning rate: 0.02 Mask loss: 0.09541 RPN box loss: 0.01379 RPN score loss: 0.00355 RPN total loss: 0.01734 Total loss: 1.3772 timestamp: 1654929665.9273381 iteration: 19455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15722 FastRCNN class loss: 0.10034 FastRCNN total loss: 0.25757 L1 loss: 0.0000e+00 L2 loss: 1.13798 Learning rate: 0.02 Mask loss: 0.239 RPN box loss: 0.02441 RPN score loss: 0.01798 RPN total loss: 0.04239 Total loss: 1.67693 timestamp: 1654929669.1801388 iteration: 19460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1538 FastRCNN class loss: 0.10617 FastRCNN total loss: 0.25997 L1 loss: 0.0000e+00 L2 loss: 1.13779 Learning rate: 0.02 Mask loss: 0.13106 RPN box loss: 0.04418 RPN score loss: 0.00632 RPN total loss: 0.0505 Total loss: 1.57932 timestamp: 1654929672.364886 iteration: 19465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13397 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.20745 L1 loss: 0.0000e+00 L2 loss: 1.1376 Learning rate: 0.02 Mask loss: 0.13164 RPN box loss: 0.05545 RPN score loss: 0.01735 RPN total loss: 0.0728 Total loss: 1.54948 timestamp: 1654929675.6817026 iteration: 19470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.06835 FastRCNN total loss: 0.15531 L1 loss: 0.0000e+00 L2 loss: 1.13741 Learning rate: 0.02 Mask loss: 0.08485 RPN box loss: 0.03184 RPN score loss: 0.00289 RPN total loss: 0.03473 Total loss: 1.4123 timestamp: 1654929678.8673942 iteration: 19475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17475 FastRCNN class loss: 0.17694 FastRCNN total loss: 0.35169 L1 loss: 0.0000e+00 L2 loss: 1.13719 Learning rate: 0.02 Mask loss: 0.27463 RPN box loss: 0.04857 RPN score loss: 0.10813 RPN total loss: 0.1567 Total loss: 1.92021 timestamp: 1654929682.12254 iteration: 19480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11417 FastRCNN class loss: 0.06456 FastRCNN total loss: 0.17873 L1 loss: 0.0000e+00 L2 loss: 1.13701 Learning rate: 0.02 Mask loss: 0.15426 RPN box loss: 0.02488 RPN score loss: 0.00814 RPN total loss: 0.03302 Total loss: 1.50302 timestamp: 1654929685.2751706 iteration: 19485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15673 FastRCNN class loss: 0.08537 FastRCNN total loss: 0.2421 L1 loss: 0.0000e+00 L2 loss: 1.13683 Learning rate: 0.02 Mask loss: 0.24631 RPN box loss: 0.02791 RPN score loss: 0.00526 RPN total loss: 0.03317 Total loss: 1.65842 timestamp: 1654929688.531385 iteration: 19490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19725 FastRCNN class loss: 0.06985 FastRCNN total loss: 0.2671 L1 loss: 0.0000e+00 L2 loss: 1.13666 Learning rate: 0.02 Mask loss: 0.18702 RPN box loss: 0.0389 RPN score loss: 0.00654 RPN total loss: 0.04544 Total loss: 1.63622 timestamp: 1654929691.7779083 iteration: 19495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21214 FastRCNN class loss: 0.11887 FastRCNN total loss: 0.33101 L1 loss: 0.0000e+00 L2 loss: 1.13648 Learning rate: 0.02 Mask loss: 0.20441 RPN box loss: 0.02695 RPN score loss: 0.00747 RPN total loss: 0.03442 Total loss: 1.70633 timestamp: 1654929695.0513484 iteration: 19500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22628 FastRCNN class loss: 0.10304 FastRCNN total loss: 0.32933 L1 loss: 0.0000e+00 L2 loss: 1.1363 Learning rate: 0.02 Mask loss: 0.17253 RPN box loss: 0.02527 RPN score loss: 0.00758 RPN total loss: 0.03284 Total loss: 1.671 timestamp: 1654929698.253917 iteration: 19505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1417 FastRCNN class loss: 0.0793 FastRCNN total loss: 0.22099 L1 loss: 0.0000e+00 L2 loss: 1.13613 Learning rate: 0.02 Mask loss: 0.13529 RPN box loss: 0.03018 RPN score loss: 0.00348 RPN total loss: 0.03366 Total loss: 1.52608 timestamp: 1654929701.6204603 iteration: 19510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20249 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.27164 L1 loss: 0.0000e+00 L2 loss: 1.13597 Learning rate: 0.02 Mask loss: 0.15349 RPN box loss: 0.02779 RPN score loss: 0.00182 RPN total loss: 0.02961 Total loss: 1.59071 timestamp: 1654929704.8823037 iteration: 19515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19676 FastRCNN class loss: 0.1396 FastRCNN total loss: 0.33636 L1 loss: 0.0000e+00 L2 loss: 1.1358 Learning rate: 0.02 Mask loss: 0.2031 RPN box loss: 0.01608 RPN score loss: 0.00725 RPN total loss: 0.02333 Total loss: 1.69859 timestamp: 1654929708.077128 iteration: 19520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11893 FastRCNN class loss: 0.07328 FastRCNN total loss: 0.19221 L1 loss: 0.0000e+00 L2 loss: 1.13561 Learning rate: 0.02 Mask loss: 0.1767 RPN box loss: 0.02925 RPN score loss: 0.00562 RPN total loss: 0.03487 Total loss: 1.53939 timestamp: 1654929711.315364 iteration: 19525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09307 FastRCNN class loss: 0.06365 FastRCNN total loss: 0.15672 L1 loss: 0.0000e+00 L2 loss: 1.13543 Learning rate: 0.02 Mask loss: 0.12953 RPN box loss: 0.0562 RPN score loss: 0.00519 RPN total loss: 0.06139 Total loss: 1.48306 timestamp: 1654929714.59049 iteration: 19530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.138 FastRCNN class loss: 0.06086 FastRCNN total loss: 0.19886 L1 loss: 0.0000e+00 L2 loss: 1.13526 Learning rate: 0.02 Mask loss: 0.1294 RPN box loss: 0.08849 RPN score loss: 0.00752 RPN total loss: 0.09601 Total loss: 1.55952 timestamp: 1654929717.8544836 iteration: 19535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13326 FastRCNN class loss: 0.09809 FastRCNN total loss: 0.23135 L1 loss: 0.0000e+00 L2 loss: 1.13509 Learning rate: 0.02 Mask loss: 0.16054 RPN box loss: 0.01401 RPN score loss: 0.00921 RPN total loss: 0.02322 Total loss: 1.5502 timestamp: 1654929721.058066 iteration: 19540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11438 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.1979 L1 loss: 0.0000e+00 L2 loss: 1.13489 Learning rate: 0.02 Mask loss: 0.14533 RPN box loss: 0.01302 RPN score loss: 0.00352 RPN total loss: 0.01653 Total loss: 1.49465 timestamp: 1654929724.3649805 iteration: 19545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20699 FastRCNN class loss: 0.13105 FastRCNN total loss: 0.33804 L1 loss: 0.0000e+00 L2 loss: 1.13467 Learning rate: 0.02 Mask loss: 0.19836 RPN box loss: 0.07791 RPN score loss: 0.00749 RPN total loss: 0.0854 Total loss: 1.75647 timestamp: 1654929727.5579548 iteration: 19550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13751 FastRCNN class loss: 0.09291 FastRCNN total loss: 0.23042 L1 loss: 0.0000e+00 L2 loss: 1.13448 Learning rate: 0.02 Mask loss: 0.18247 RPN box loss: 0.0252 RPN score loss: 0.01431 RPN total loss: 0.03951 Total loss: 1.58689 timestamp: 1654929730.8198235 iteration: 19555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18265 FastRCNN class loss: 0.09252 FastRCNN total loss: 0.27517 L1 loss: 0.0000e+00 L2 loss: 1.1343 Learning rate: 0.02 Mask loss: 0.15661 RPN box loss: 0.05608 RPN score loss: 0.00821 RPN total loss: 0.06429 Total loss: 1.63037 timestamp: 1654929733.9993072 iteration: 19560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12149 FastRCNN class loss: 0.08686 FastRCNN total loss: 0.20835 L1 loss: 0.0000e+00 L2 loss: 1.13412 Learning rate: 0.02 Mask loss: 0.13952 RPN box loss: 0.02408 RPN score loss: 0.00786 RPN total loss: 0.03193 Total loss: 1.51392 timestamp: 1654929737.405192 iteration: 19565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09267 FastRCNN class loss: 0.04963 FastRCNN total loss: 0.14231 L1 loss: 0.0000e+00 L2 loss: 1.13392 Learning rate: 0.02 Mask loss: 0.1048 RPN box loss: 0.01581 RPN score loss: 0.00271 RPN total loss: 0.01851 Total loss: 1.39954 timestamp: 1654929740.551134 iteration: 19570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15697 FastRCNN class loss: 0.13539 FastRCNN total loss: 0.29236 L1 loss: 0.0000e+00 L2 loss: 1.13371 Learning rate: 0.02 Mask loss: 0.18124 RPN box loss: 0.02753 RPN score loss: 0.00771 RPN total loss: 0.03524 Total loss: 1.64255 timestamp: 1654929743.8043156 iteration: 19575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09549 FastRCNN class loss: 0.07634 FastRCNN total loss: 0.17183 L1 loss: 0.0000e+00 L2 loss: 1.13355 Learning rate: 0.02 Mask loss: 0.12643 RPN box loss: 0.06301 RPN score loss: 0.00808 RPN total loss: 0.07109 Total loss: 1.5029 timestamp: 1654929747.0313067 iteration: 19580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14862 FastRCNN class loss: 0.0909 FastRCNN total loss: 0.23952 L1 loss: 0.0000e+00 L2 loss: 1.13334 Learning rate: 0.02 Mask loss: 0.15491 RPN box loss: 0.02809 RPN score loss: 0.00689 RPN total loss: 0.03498 Total loss: 1.56274 timestamp: 1654929750.2933698 iteration: 19585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21184 FastRCNN class loss: 0.08625 FastRCNN total loss: 0.2981 L1 loss: 0.0000e+00 L2 loss: 1.13315 Learning rate: 0.02 Mask loss: 0.19391 RPN box loss: 0.0145 RPN score loss: 0.01042 RPN total loss: 0.02492 Total loss: 1.65007 timestamp: 1654929753.6023967 iteration: 19590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1223 FastRCNN class loss: 0.0583 FastRCNN total loss: 0.1806 L1 loss: 0.0000e+00 L2 loss: 1.13297 Learning rate: 0.02 Mask loss: 0.111 RPN box loss: 0.01976 RPN score loss: 0.00786 RPN total loss: 0.02762 Total loss: 1.45219 timestamp: 1654929756.7706103 iteration: 19595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21974 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.3124 L1 loss: 0.0000e+00 L2 loss: 1.13277 Learning rate: 0.02 Mask loss: 0.15163 RPN box loss: 0.01436 RPN score loss: 0.00907 RPN total loss: 0.02343 Total loss: 1.62023 timestamp: 1654929760.0869796 iteration: 19600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11674 FastRCNN class loss: 0.06889 FastRCNN total loss: 0.18563 L1 loss: 0.0000e+00 L2 loss: 1.13259 Learning rate: 0.02 Mask loss: 0.15854 RPN box loss: 0.03025 RPN score loss: 0.00599 RPN total loss: 0.03624 Total loss: 1.513 timestamp: 1654929763.2513554 iteration: 19605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16833 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.25019 L1 loss: 0.0000e+00 L2 loss: 1.13243 Learning rate: 0.02 Mask loss: 0.17766 RPN box loss: 0.04229 RPN score loss: 0.00558 RPN total loss: 0.04787 Total loss: 1.60814 timestamp: 1654929766.5065792 iteration: 19610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20967 FastRCNN class loss: 0.15286 FastRCNN total loss: 0.36254 L1 loss: 0.0000e+00 L2 loss: 1.13224 Learning rate: 0.02 Mask loss: 0.19094 RPN box loss: 0.06466 RPN score loss: 0.01507 RPN total loss: 0.07973 Total loss: 1.76545 timestamp: 1654929769.7450824 iteration: 19615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14884 FastRCNN class loss: 0.0603 FastRCNN total loss: 0.20914 L1 loss: 0.0000e+00 L2 loss: 1.13204 Learning rate: 0.02 Mask loss: 0.10115 RPN box loss: 0.0247 RPN score loss: 0.00168 RPN total loss: 0.02638 Total loss: 1.46871 timestamp: 1654929773.0403197 iteration: 19620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06526 FastRCNN class loss: 0.02793 FastRCNN total loss: 0.09319 L1 loss: 0.0000e+00 L2 loss: 1.13186 Learning rate: 0.02 Mask loss: 0.0899 RPN box loss: 0.03666 RPN score loss: 0.00379 RPN total loss: 0.04045 Total loss: 1.3554 timestamp: 1654929776.2774131 iteration: 19625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16336 FastRCNN class loss: 0.04766 FastRCNN total loss: 0.21103 L1 loss: 0.0000e+00 L2 loss: 1.13166 Learning rate: 0.02 Mask loss: 0.17299 RPN box loss: 0.02904 RPN score loss: 0.00478 RPN total loss: 0.03382 Total loss: 1.54949 timestamp: 1654929779.642688 iteration: 19630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22819 FastRCNN class loss: 0.11186 FastRCNN total loss: 0.34005 L1 loss: 0.0000e+00 L2 loss: 1.13148 Learning rate: 0.02 Mask loss: 0.21303 RPN box loss: 0.0204 RPN score loss: 0.0074 RPN total loss: 0.02781 Total loss: 1.71236 timestamp: 1654929782.999999 iteration: 19635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13847 FastRCNN class loss: 0.08293 FastRCNN total loss: 0.22141 L1 loss: 0.0000e+00 L2 loss: 1.13129 Learning rate: 0.02 Mask loss: 0.16653 RPN box loss: 0.01492 RPN score loss: 0.0088 RPN total loss: 0.02372 Total loss: 1.54294 timestamp: 1654929786.181737 iteration: 19640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13774 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.20126 L1 loss: 0.0000e+00 L2 loss: 1.13111 Learning rate: 0.02 Mask loss: 0.15595 RPN box loss: 0.03169 RPN score loss: 0.0051 RPN total loss: 0.03679 Total loss: 1.52511 timestamp: 1654929789.543627 iteration: 19645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17249 FastRCNN class loss: 0.11438 FastRCNN total loss: 0.28687 L1 loss: 0.0000e+00 L2 loss: 1.13091 Learning rate: 0.02 Mask loss: 0.14785 RPN box loss: 0.02568 RPN score loss: 0.00506 RPN total loss: 0.03074 Total loss: 1.59637 timestamp: 1654929792.819835 iteration: 19650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09251 FastRCNN class loss: 0.08388 FastRCNN total loss: 0.17639 L1 loss: 0.0000e+00 L2 loss: 1.13072 Learning rate: 0.02 Mask loss: 0.16519 RPN box loss: 0.02987 RPN score loss: 0.0099 RPN total loss: 0.03978 Total loss: 1.51207 timestamp: 1654929796.0710142 iteration: 19655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12954 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.20072 L1 loss: 0.0000e+00 L2 loss: 1.13055 Learning rate: 0.02 Mask loss: 0.16775 RPN box loss: 0.02696 RPN score loss: 0.00413 RPN total loss: 0.03108 Total loss: 1.53011 timestamp: 1654929799.3772256 iteration: 19660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15669 FastRCNN class loss: 0.14247 FastRCNN total loss: 0.29916 L1 loss: 0.0000e+00 L2 loss: 1.13037 Learning rate: 0.02 Mask loss: 0.15728 RPN box loss: 0.03389 RPN score loss: 0.00336 RPN total loss: 0.03725 Total loss: 1.62407 timestamp: 1654929802.6761694 iteration: 19665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14176 FastRCNN class loss: 0.09563 FastRCNN total loss: 0.23739 L1 loss: 0.0000e+00 L2 loss: 1.1302 Learning rate: 0.02 Mask loss: 0.15901 RPN box loss: 0.05356 RPN score loss: 0.005 RPN total loss: 0.05856 Total loss: 1.58516 timestamp: 1654929805.8367946 iteration: 19670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18931 FastRCNN class loss: 0.07968 FastRCNN total loss: 0.26899 L1 loss: 0.0000e+00 L2 loss: 1.13001 Learning rate: 0.02 Mask loss: 0.11506 RPN box loss: 0.03116 RPN score loss: 0.00531 RPN total loss: 0.03647 Total loss: 1.55052 timestamp: 1654929809.19144 iteration: 19675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09654 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.16931 L1 loss: 0.0000e+00 L2 loss: 1.12982 Learning rate: 0.02 Mask loss: 0.27149 RPN box loss: 0.0148 RPN score loss: 0.00146 RPN total loss: 0.01626 Total loss: 1.58688 timestamp: 1654929812.4465144 iteration: 19680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29584 FastRCNN class loss: 0.05614 FastRCNN total loss: 0.35198 L1 loss: 0.0000e+00 L2 loss: 1.12963 Learning rate: 0.02 Mask loss: 0.176 RPN box loss: 0.01155 RPN score loss: 0.00293 RPN total loss: 0.01448 Total loss: 1.67209 timestamp: 1654929815.6475186 iteration: 19685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10154 FastRCNN class loss: 0.04358 FastRCNN total loss: 0.14512 L1 loss: 0.0000e+00 L2 loss: 1.12943 Learning rate: 0.02 Mask loss: 0.12242 RPN box loss: 0.04443 RPN score loss: 0.00302 RPN total loss: 0.04745 Total loss: 1.44443 timestamp: 1654929819.0131164 iteration: 19690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09534 FastRCNN class loss: 0.09073 FastRCNN total loss: 0.18607 L1 loss: 0.0000e+00 L2 loss: 1.12924 Learning rate: 0.02 Mask loss: 0.15754 RPN box loss: 0.02547 RPN score loss: 0.00475 RPN total loss: 0.03021 Total loss: 1.50306 timestamp: 1654929822.227135 iteration: 19695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13221 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.19293 L1 loss: 0.0000e+00 L2 loss: 1.12906 Learning rate: 0.02 Mask loss: 0.14868 RPN box loss: 0.00646 RPN score loss: 0.00414 RPN total loss: 0.0106 Total loss: 1.48127 timestamp: 1654929825.7159333 iteration: 19700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.25012 L1 loss: 0.0000e+00 L2 loss: 1.12889 Learning rate: 0.02 Mask loss: 0.07805 RPN box loss: 0.01598 RPN score loss: 0.00448 RPN total loss: 0.02046 Total loss: 1.47751 timestamp: 1654929828.882018 iteration: 19705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08464 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.16249 L1 loss: 0.0000e+00 L2 loss: 1.12871 Learning rate: 0.02 Mask loss: 0.13353 RPN box loss: 0.01043 RPN score loss: 0.00435 RPN total loss: 0.01478 Total loss: 1.43951 timestamp: 1654929832.2047782 iteration: 19710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20952 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.28353 L1 loss: 0.0000e+00 L2 loss: 1.12853 Learning rate: 0.02 Mask loss: 0.11737 RPN box loss: 0.04435 RPN score loss: 0.00789 RPN total loss: 0.05224 Total loss: 1.58168 timestamp: 1654929835.384189 iteration: 19715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16531 FastRCNN class loss: 0.13406 FastRCNN total loss: 0.29938 L1 loss: 0.0000e+00 L2 loss: 1.12833 Learning rate: 0.02 Mask loss: 0.18828 RPN box loss: 0.02396 RPN score loss: 0.01245 RPN total loss: 0.03641 Total loss: 1.6524 timestamp: 1654929838.7119746 iteration: 19720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16384 FastRCNN class loss: 0.11832 FastRCNN total loss: 0.28216 L1 loss: 0.0000e+00 L2 loss: 1.12814 Learning rate: 0.02 Mask loss: 0.18993 RPN box loss: 0.04587 RPN score loss: 0.01175 RPN total loss: 0.05762 Total loss: 1.65785 timestamp: 1654929842.0306387 iteration: 19725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19056 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.25899 L1 loss: 0.0000e+00 L2 loss: 1.12798 Learning rate: 0.02 Mask loss: 0.22701 RPN box loss: 0.03558 RPN score loss: 0.01031 RPN total loss: 0.04589 Total loss: 1.65987 timestamp: 1654929845.3832586 iteration: 19730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07841 FastRCNN class loss: 0.05722 FastRCNN total loss: 0.13564 L1 loss: 0.0000e+00 L2 loss: 1.12779 Learning rate: 0.02 Mask loss: 0.10526 RPN box loss: 0.00448 RPN score loss: 0.00135 RPN total loss: 0.00584 Total loss: 1.37453 timestamp: 1654929848.7014358 iteration: 19735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08141 FastRCNN class loss: 0.05226 FastRCNN total loss: 0.13368 L1 loss: 0.0000e+00 L2 loss: 1.12762 Learning rate: 0.02 Mask loss: 0.14216 RPN box loss: 0.02776 RPN score loss: 0.00309 RPN total loss: 0.03085 Total loss: 1.43431 timestamp: 1654929851.8691654 iteration: 19740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09947 FastRCNN class loss: 0.10769 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 1.12745 Learning rate: 0.02 Mask loss: 0.1637 RPN box loss: 0.09634 RPN score loss: 0.03709 RPN total loss: 0.13342 Total loss: 1.63174 timestamp: 1654929855.0898018 iteration: 19745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12165 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.18703 L1 loss: 0.0000e+00 L2 loss: 1.12725 Learning rate: 0.02 Mask loss: 0.22284 RPN box loss: 0.02568 RPN score loss: 0.00735 RPN total loss: 0.03303 Total loss: 1.57015 timestamp: 1654929858.262091 iteration: 19750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13077 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.21944 L1 loss: 0.0000e+00 L2 loss: 1.12707 Learning rate: 0.02 Mask loss: 0.1759 RPN box loss: 0.03643 RPN score loss: 0.01091 RPN total loss: 0.04734 Total loss: 1.56975 timestamp: 1654929861.554939 iteration: 19755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05407 FastRCNN class loss: 0.09322 FastRCNN total loss: 0.14729 L1 loss: 0.0000e+00 L2 loss: 1.1269 Learning rate: 0.02 Mask loss: 0.12908 RPN box loss: 0.03573 RPN score loss: 0.01198 RPN total loss: 0.04771 Total loss: 1.45098 timestamp: 1654929864.7080445 iteration: 19760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09067 FastRCNN class loss: 0.08201 FastRCNN total loss: 0.17268 L1 loss: 0.0000e+00 L2 loss: 1.12669 Learning rate: 0.02 Mask loss: 0.12656 RPN box loss: 0.04873 RPN score loss: 0.00988 RPN total loss: 0.05862 Total loss: 1.48455 timestamp: 1654929868.0053368 iteration: 19765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1353 FastRCNN class loss: 0.13582 FastRCNN total loss: 0.27113 L1 loss: 0.0000e+00 L2 loss: 1.1265 Learning rate: 0.02 Mask loss: 0.22627 RPN box loss: 0.04813 RPN score loss: 0.01529 RPN total loss: 0.06342 Total loss: 1.68731 timestamp: 1654929871.2866154 iteration: 19770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16994 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.24056 L1 loss: 0.0000e+00 L2 loss: 1.12633 Learning rate: 0.02 Mask loss: 0.14072 RPN box loss: 0.02639 RPN score loss: 0.00578 RPN total loss: 0.03217 Total loss: 1.53978 timestamp: 1654929874.5712316 iteration: 19775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18747 FastRCNN class loss: 0.09975 FastRCNN total loss: 0.28721 L1 loss: 0.0000e+00 L2 loss: 1.12617 Learning rate: 0.02 Mask loss: 0.20855 RPN box loss: 0.05589 RPN score loss: 0.00646 RPN total loss: 0.06235 Total loss: 1.68428 timestamp: 1654929877.8406096 iteration: 19780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.16864 L1 loss: 0.0000e+00 L2 loss: 1.12596 Learning rate: 0.02 Mask loss: 0.12298 RPN box loss: 0.06283 RPN score loss: 0.00512 RPN total loss: 0.06795 Total loss: 1.48553 timestamp: 1654929881.060281 iteration: 19785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15968 FastRCNN class loss: 0.1206 FastRCNN total loss: 0.28028 L1 loss: 0.0000e+00 L2 loss: 1.12578 Learning rate: 0.02 Mask loss: 0.30226 RPN box loss: 0.03909 RPN score loss: 0.00769 RPN total loss: 0.04678 Total loss: 1.7551 timestamp: 1654929884.3887095 iteration: 19790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17441 FastRCNN class loss: 0.07024 FastRCNN total loss: 0.24465 L1 loss: 0.0000e+00 L2 loss: 1.1256 Learning rate: 0.02 Mask loss: 0.15819 RPN box loss: 0.00629 RPN score loss: 0.00447 RPN total loss: 0.01077 Total loss: 1.5392 timestamp: 1654929887.6266453 iteration: 19795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22353 FastRCNN class loss: 0.19752 FastRCNN total loss: 0.42105 L1 loss: 0.0000e+00 L2 loss: 1.12538 Learning rate: 0.02 Mask loss: 0.22792 RPN box loss: 0.08146 RPN score loss: 0.01991 RPN total loss: 0.10137 Total loss: 1.87572 timestamp: 1654929890.8889334 iteration: 19800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07406 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.14045 L1 loss: 0.0000e+00 L2 loss: 1.12519 Learning rate: 0.02 Mask loss: 0.12613 RPN box loss: 0.02415 RPN score loss: 0.00531 RPN total loss: 0.02946 Total loss: 1.42123 timestamp: 1654929894.1233265 iteration: 19805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14179 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.20402 L1 loss: 0.0000e+00 L2 loss: 1.12502 Learning rate: 0.02 Mask loss: 0.13043 RPN box loss: 0.00491 RPN score loss: 0.00241 RPN total loss: 0.00732 Total loss: 1.46679 timestamp: 1654929897.40643 iteration: 19810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09983 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.16459 L1 loss: 0.0000e+00 L2 loss: 1.12483 Learning rate: 0.02 Mask loss: 0.10355 RPN box loss: 0.03771 RPN score loss: 0.00485 RPN total loss: 0.04256 Total loss: 1.43552 timestamp: 1654929900.5509667 iteration: 19815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10187 FastRCNN class loss: 0.10253 FastRCNN total loss: 0.20441 L1 loss: 0.0000e+00 L2 loss: 1.12465 Learning rate: 0.02 Mask loss: 0.12155 RPN box loss: 0.04536 RPN score loss: 0.0183 RPN total loss: 0.06366 Total loss: 1.51427 timestamp: 1654929904.0331724 iteration: 19820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.07848 FastRCNN total loss: 0.21259 L1 loss: 0.0000e+00 L2 loss: 1.12448 Learning rate: 0.02 Mask loss: 0.19755 RPN box loss: 0.03752 RPN score loss: 0.01082 RPN total loss: 0.04834 Total loss: 1.58295 timestamp: 1654929907.3881078 iteration: 19825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19874 FastRCNN class loss: 0.09104 FastRCNN total loss: 0.28978 L1 loss: 0.0000e+00 L2 loss: 1.12429 Learning rate: 0.02 Mask loss: 0.1772 RPN box loss: 0.02308 RPN score loss: 0.00869 RPN total loss: 0.03177 Total loss: 1.62304 timestamp: 1654929910.6434352 iteration: 19830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05572 FastRCNN class loss: 0.03684 FastRCNN total loss: 0.09256 L1 loss: 0.0000e+00 L2 loss: 1.12408 Learning rate: 0.02 Mask loss: 0.09664 RPN box loss: 0.01568 RPN score loss: 0.00712 RPN total loss: 0.0228 Total loss: 1.33609 timestamp: 1654929913.942734 iteration: 19835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20378 FastRCNN class loss: 0.10185 FastRCNN total loss: 0.30563 L1 loss: 0.0000e+00 L2 loss: 1.1239 Learning rate: 0.02 Mask loss: 0.24451 RPN box loss: 0.01558 RPN score loss: 0.0065 RPN total loss: 0.02207 Total loss: 1.69611 timestamp: 1654929917.133898 iteration: 19840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10189 FastRCNN class loss: 0.07389 FastRCNN total loss: 0.17579 L1 loss: 0.0000e+00 L2 loss: 1.12373 Learning rate: 0.02 Mask loss: 0.16656 RPN box loss: 0.02237 RPN score loss: 0.00842 RPN total loss: 0.03078 Total loss: 1.49686 timestamp: 1654929920.4986665 iteration: 19845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12373 FastRCNN class loss: 0.08996 FastRCNN total loss: 0.2137 L1 loss: 0.0000e+00 L2 loss: 1.12354 Learning rate: 0.02 Mask loss: 0.11398 RPN box loss: 0.02671 RPN score loss: 0.01651 RPN total loss: 0.04322 Total loss: 1.49444 timestamp: 1654929923.6769912 iteration: 19850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12146 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.19531 L1 loss: 0.0000e+00 L2 loss: 1.12335 Learning rate: 0.02 Mask loss: 0.16385 RPN box loss: 0.10505 RPN score loss: 0.00409 RPN total loss: 0.10913 Total loss: 1.59164 timestamp: 1654929926.9508111 iteration: 19855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1566 FastRCNN class loss: 0.11606 FastRCNN total loss: 0.27266 L1 loss: 0.0000e+00 L2 loss: 1.12317 Learning rate: 0.02 Mask loss: 0.14218 RPN box loss: 0.01861 RPN score loss: 0.00545 RPN total loss: 0.02406 Total loss: 1.56207 timestamp: 1654929930.2078311 iteration: 19860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.17599 L1 loss: 0.0000e+00 L2 loss: 1.12297 Learning rate: 0.02 Mask loss: 0.14844 RPN box loss: 0.01841 RPN score loss: 0.00281 RPN total loss: 0.02121 Total loss: 1.46862 timestamp: 1654929933.5867186 iteration: 19865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17096 FastRCNN class loss: 0.09415 FastRCNN total loss: 0.26511 L1 loss: 0.0000e+00 L2 loss: 1.12278 Learning rate: 0.02 Mask loss: 0.21074 RPN box loss: 0.02271 RPN score loss: 0.00283 RPN total loss: 0.02554 Total loss: 1.62417 timestamp: 1654929936.8010936 iteration: 19870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1572 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.22833 L1 loss: 0.0000e+00 L2 loss: 1.1226 Learning rate: 0.02 Mask loss: 0.1612 RPN box loss: 0.04036 RPN score loss: 0.01526 RPN total loss: 0.05562 Total loss: 1.56774 timestamp: 1654929940.0096338 iteration: 19875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19087 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.27451 L1 loss: 0.0000e+00 L2 loss: 1.12241 Learning rate: 0.02 Mask loss: 0.15781 RPN box loss: 0.07154 RPN score loss: 0.0113 RPN total loss: 0.08284 Total loss: 1.63758 timestamp: 1654929943.2577333 iteration: 19880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12865 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.20003 L1 loss: 0.0000e+00 L2 loss: 1.12223 Learning rate: 0.02 Mask loss: 0.20383 RPN box loss: 0.01935 RPN score loss: 0.01101 RPN total loss: 0.03036 Total loss: 1.55645 timestamp: 1654929946.4142542 iteration: 19885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13383 FastRCNN class loss: 0.08265 FastRCNN total loss: 0.21647 L1 loss: 0.0000e+00 L2 loss: 1.12204 Learning rate: 0.02 Mask loss: 0.15366 RPN box loss: 0.04833 RPN score loss: 0.00595 RPN total loss: 0.05429 Total loss: 1.54647 timestamp: 1654929949.7669866 iteration: 19890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15888 FastRCNN class loss: 0.10664 FastRCNN total loss: 0.26552 L1 loss: 0.0000e+00 L2 loss: 1.12186 Learning rate: 0.02 Mask loss: 0.15894 RPN box loss: 0.03265 RPN score loss: 0.01371 RPN total loss: 0.04636 Total loss: 1.59268 timestamp: 1654929952.9954414 iteration: 19895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14877 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.20195 L1 loss: 0.0000e+00 L2 loss: 1.12167 Learning rate: 0.02 Mask loss: 0.15645 RPN box loss: 0.04541 RPN score loss: 0.00139 RPN total loss: 0.0468 Total loss: 1.52687 timestamp: 1654929956.2554035 iteration: 19900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11074 FastRCNN class loss: 0.09471 FastRCNN total loss: 0.20545 L1 loss: 0.0000e+00 L2 loss: 1.12147 Learning rate: 0.02 Mask loss: 0.19179 RPN box loss: 0.01352 RPN score loss: 0.00499 RPN total loss: 0.01851 Total loss: 1.53723 timestamp: 1654929959.4028919 iteration: 19905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28689 FastRCNN class loss: 0.19372 FastRCNN total loss: 0.48061 L1 loss: 0.0000e+00 L2 loss: 1.12128 Learning rate: 0.02 Mask loss: 0.36086 RPN box loss: 0.02994 RPN score loss: 0.01691 RPN total loss: 0.04685 Total loss: 2.00959 timestamp: 1654929962.7348738 iteration: 19910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15933 FastRCNN class loss: 0.09071 FastRCNN total loss: 0.25005 L1 loss: 0.0000e+00 L2 loss: 1.12108 Learning rate: 0.02 Mask loss: 0.18592 RPN box loss: 0.02668 RPN score loss: 0.00591 RPN total loss: 0.03259 Total loss: 1.58964 timestamp: 1654929965.9097385 iteration: 19915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17527 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.25146 L1 loss: 0.0000e+00 L2 loss: 1.1209 Learning rate: 0.02 Mask loss: 0.17995 RPN box loss: 0.04939 RPN score loss: 0.01378 RPN total loss: 0.06317 Total loss: 1.61548 timestamp: 1654929969.2038963 iteration: 19920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09332 FastRCNN class loss: 0.05128 FastRCNN total loss: 0.14459 L1 loss: 0.0000e+00 L2 loss: 1.12072 Learning rate: 0.02 Mask loss: 0.10253 RPN box loss: 0.04307 RPN score loss: 0.00627 RPN total loss: 0.04934 Total loss: 1.41718 timestamp: 1654929972.4242265 iteration: 19925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17803 FastRCNN class loss: 0.12106 FastRCNN total loss: 0.29909 L1 loss: 0.0000e+00 L2 loss: 1.12053 Learning rate: 0.02 Mask loss: 0.23737 RPN box loss: 0.05272 RPN score loss: 0.0113 RPN total loss: 0.06403 Total loss: 1.72102 timestamp: 1654929975.8499684 iteration: 19930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24906 FastRCNN class loss: 0.10576 FastRCNN total loss: 0.35482 L1 loss: 0.0000e+00 L2 loss: 1.12037 Learning rate: 0.02 Mask loss: 0.21709 RPN box loss: 0.03771 RPN score loss: 0.00833 RPN total loss: 0.04605 Total loss: 1.73833 timestamp: 1654929979.175699 iteration: 19935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17781 FastRCNN class loss: 0.05393 FastRCNN total loss: 0.23174 L1 loss: 0.0000e+00 L2 loss: 1.12019 Learning rate: 0.02 Mask loss: 0.16578 RPN box loss: 0.05715 RPN score loss: 0.00385 RPN total loss: 0.061 Total loss: 1.57871 timestamp: 1654929982.3254182 iteration: 19940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17674 FastRCNN class loss: 0.15704 FastRCNN total loss: 0.33377 L1 loss: 0.0000e+00 L2 loss: 1.12002 Learning rate: 0.02 Mask loss: 0.22646 RPN box loss: 0.02654 RPN score loss: 0.00604 RPN total loss: 0.03258 Total loss: 1.71283 timestamp: 1654929985.6260443 iteration: 19945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13123 FastRCNN class loss: 0.06157 FastRCNN total loss: 0.19281 L1 loss: 0.0000e+00 L2 loss: 1.11984 Learning rate: 0.02 Mask loss: 0.13282 RPN box loss: 0.0278 RPN score loss: 0.00384 RPN total loss: 0.03164 Total loss: 1.4771 timestamp: 1654929988.8061326 iteration: 19950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22739 FastRCNN class loss: 0.09471 FastRCNN total loss: 0.32211 L1 loss: 0.0000e+00 L2 loss: 1.11964 Learning rate: 0.02 Mask loss: 0.15964 RPN box loss: 0.02748 RPN score loss: 0.00463 RPN total loss: 0.03211 Total loss: 1.63349 timestamp: 1654929992.0484135 iteration: 19955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11726 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.17713 L1 loss: 0.0000e+00 L2 loss: 1.11945 Learning rate: 0.02 Mask loss: 0.13964 RPN box loss: 0.00786 RPN score loss: 0.0034 RPN total loss: 0.01125 Total loss: 1.44747 timestamp: 1654929995.18865 iteration: 19960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16771 FastRCNN class loss: 0.06835 FastRCNN total loss: 0.23606 L1 loss: 0.0000e+00 L2 loss: 1.11925 Learning rate: 0.02 Mask loss: 0.14746 RPN box loss: 0.05265 RPN score loss: 0.00382 RPN total loss: 0.05647 Total loss: 1.55924 timestamp: 1654929998.4841175 iteration: 19965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13084 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.1894 L1 loss: 0.0000e+00 L2 loss: 1.11907 Learning rate: 0.02 Mask loss: 0.12238 RPN box loss: 0.04335 RPN score loss: 0.00216 RPN total loss: 0.04551 Total loss: 1.47635 timestamp: 1654930001.6250727 iteration: 19970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1444 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.23002 L1 loss: 0.0000e+00 L2 loss: 1.1189 Learning rate: 0.02 Mask loss: 0.18315 RPN box loss: 0.02207 RPN score loss: 0.00808 RPN total loss: 0.03015 Total loss: 1.56223 timestamp: 1654930004.8365471 iteration: 19975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07044 FastRCNN class loss: 0.04762 FastRCNN total loss: 0.11806 L1 loss: 0.0000e+00 L2 loss: 1.11871 Learning rate: 0.02 Mask loss: 0.11385 RPN box loss: 0.01433 RPN score loss: 0.00524 RPN total loss: 0.01957 Total loss: 1.37019 timestamp: 1654930008.0788126 iteration: 19980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17753 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.29754 L1 loss: 0.0000e+00 L2 loss: 1.11853 Learning rate: 0.02 Mask loss: 0.14206 RPN box loss: 0.09519 RPN score loss: 0.00436 RPN total loss: 0.09955 Total loss: 1.65767 timestamp: 1654930011.3539774 iteration: 19985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13331 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.2085 L1 loss: 0.0000e+00 L2 loss: 1.11834 Learning rate: 0.02 Mask loss: 0.21561 RPN box loss: 0.04802 RPN score loss: 0.01161 RPN total loss: 0.05963 Total loss: 1.60208 timestamp: 1654930014.6924787 iteration: 19990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14338 FastRCNN class loss: 0.0915 FastRCNN total loss: 0.23487 L1 loss: 0.0000e+00 L2 loss: 1.11817 Learning rate: 0.02 Mask loss: 0.10573 RPN box loss: 0.00792 RPN score loss: 0.00183 RPN total loss: 0.00975 Total loss: 1.46853 timestamp: 1654930017.8932357 iteration: 19995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16174 FastRCNN class loss: 0.10092 FastRCNN total loss: 0.26266 L1 loss: 0.0000e+00 L2 loss: 1.11801 Learning rate: 0.02 Mask loss: 0.27395 RPN box loss: 0.04476 RPN score loss: 0.0131 RPN total loss: 0.05786 Total loss: 1.71247 timestamp: 1654930021.236114 iteration: 20000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17035 FastRCNN class loss: 0.10975 FastRCNN total loss: 0.28009 L1 loss: 0.0000e+00 L2 loss: 1.11781 Learning rate: 0.02 Mask loss: 0.22186 RPN box loss: 0.03392 RPN score loss: 0.00364 RPN total loss: 0.03756 Total loss: 1.65732 Saving checkpoints for 20000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-20000.tlt. ================================= Start evaluation cycle 02 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-20000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.6176s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.3311s - Throughput: 12.1 imgs/s Running inference on batch 003/125... - Step Time: 0.3249s - Throughput: 12.3 imgs/s Running inference on batch 004/125... - Step Time: 0.3377s - Throughput: 11.8 imgs/s Running inference on batch 005/125... - Step Time: 0.3205s - Throughput: 12.5 imgs/s Running inference on batch 006/125... - Step Time: 0.3215s - Throughput: 12.4 imgs/s Running inference on batch 007/125... - Step Time: 0.3352s - Throughput: 11.9 imgs/s Running inference on batch 008/125... - Step Time: 0.3280s - Throughput: 12.2 imgs/s Running inference on batch 009/125... - Step Time: 0.3456s - Throughput: 11.6 imgs/s Running inference on batch 010/125... - Step Time: 0.3273s - Throughput: 12.2 imgs/s Running inference on batch 011/125... - Step Time: 0.3352s - Throughput: 11.9 imgs/s Running inference on batch 012/125... - Step Time: 0.3312s - Throughput: 12.1 imgs/s Running inference on batch 013/125... - Step Time: 0.3301s - Throughput: 12.1 imgs/s Running inference on batch 014/125... - Step Time: 0.3243s - Throughput: 12.3 imgs/s Running inference on batch 015/125... - Step Time: 0.3301s - Throughput: 12.1 imgs/s Running inference on batch 016/125... - Step Time: 0.3237s - Throughput: 12.4 imgs/s Running inference on batch 017/125... - Step Time: 0.3280s - Throughput: 12.2 imgs/s Running inference on batch 018/125... - Step Time: 0.2606s - Throughput: 15.3 imgs/s Running inference on batch 019/125... - Step Time: 0.3040s - Throughput: 13.2 imgs/s Running inference on batch 020/125... - Step Time: 0.3275s - Throughput: 12.2 imgs/s Running inference on batch 021/125... - Step Time: 0.3181s - Throughput: 12.6 imgs/s Running inference on batch 022/125... - Step Time: 0.3347s - Throughput: 12.0 imgs/s Running inference on batch 023/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 024/125... - Step Time: 0.3188s - Throughput: 12.5 imgs/s Running inference on batch 025/125... - Step Time: 0.3285s - Throughput: 12.2 imgs/s Running inference on batch 026/125... - Step Time: 0.3221s - Throughput: 12.4 imgs/s Running inference on batch 027/125... - Step Time: 0.3315s - Throughput: 12.1 imgs/s Running inference on batch 028/125... - Step Time: 0.3231s - Throughput: 12.4 imgs/s Running inference on batch 029/125... - Step Time: 0.3254s - Throughput: 12.3 imgs/s Running inference on batch 030/125... - Step Time: 0.3255s - Throughput: 12.3 imgs/s Running inference on batch 031/125... - Step Time: 0.3341s - Throughput: 12.0 imgs/s Running inference on batch 032/125... - Step Time: 0.3234s - Throughput: 12.4 imgs/s Running inference on batch 033/125... - Step Time: 0.3367s - Throughput: 11.9 imgs/s Running inference on batch 034/125... - Step Time: 0.3388s - Throughput: 11.8 imgs/s Running inference on batch 035/125... - Step Time: 0.3169s - Throughput: 12.6 imgs/s Running inference on batch 036/125... - Step Time: 0.3277s - Throughput: 12.2 imgs/s Running inference on batch 037/125... - Step Time: 0.3396s - Throughput: 11.8 imgs/s Running inference on batch 038/125... - Step Time: 0.3195s - Throughput: 12.5 imgs/s Running inference on batch 039/125... - Step Time: 0.3222s - Throughput: 12.4 imgs/s Running inference on batch 040/125... - Step Time: 0.3357s - Throughput: 11.9 imgs/s Running inference on batch 041/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 042/125... - Step Time: 0.3298s - Throughput: 12.1 imgs/s Running inference on batch 043/125... - Step Time: 0.3548s - Throughput: 11.3 imgs/s Running inference on batch 044/125... - Step Time: 0.3290s - Throughput: 12.2 imgs/s Running inference on batch 045/125... - Step Time: 0.3392s - Throughput: 11.8 imgs/s Running inference on batch 046/125... - Step Time: 0.3344s - Throughput: 12.0 imgs/s Running inference on batch 047/125... - Step Time: 0.3271s - Throughput: 12.2 imgs/s Running inference on batch 048/125... - Step Time: 0.3270s - Throughput: 12.2 imgs/s Running inference on batch 049/125... - Step Time: 0.3186s - Throughput: 12.6 imgs/s Running inference on batch 050/125... - Step Time: 0.3247s - Throughput: 12.3 imgs/s Running inference on batch 051/125... - Step Time: 0.3273s - Throughput: 12.2 imgs/s Running inference on batch 052/125... - Step Time: 0.3161s - Throughput: 12.7 imgs/s Running inference on batch 053/125... - Step Time: 0.3431s - Throughput: 11.7 imgs/s Running inference on batch 054/125... - Step Time: 0.3234s - Throughput: 12.4 imgs/s Running inference on batch 055/125... - Step Time: 0.3398s - Throughput: 11.8 imgs/s Running inference on batch 056/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 057/125... - Step Time: 0.3414s - Throughput: 11.7 imgs/s Running inference on batch 058/125... - Step Time: 0.3275s - Throughput: 12.2 imgs/s Running inference on batch 059/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 060/125... - Step Time: 0.3485s - Throughput: 11.5 imgs/s Running inference on batch 061/125... - Step Time: 0.3304s - Throughput: 12.1 imgs/s Running inference on batch 062/125... - Step Time: 0.3423s - Throughput: 11.7 imgs/s Running inference on batch 063/125... - Step Time: 0.2785s - Throughput: 14.4 imgs/s Running inference on batch 064/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 065/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 066/125... - Step Time: 0.2645s - Throughput: 15.1 imgs/s Running inference on batch 067/125... - Step Time: 0.3087s - Throughput: 13.0 imgs/s Running inference on batch 068/125... - Step Time: 0.3226s - Throughput: 12.4 imgs/s Running inference on batch 069/125... - Step Time: 0.3452s - Throughput: 11.6 imgs/s Running inference on batch 070/125... - Step Time: 0.3387s - Throughput: 11.8 imgs/s Running inference on batch 071/125... - Step Time: 0.2902s - Throughput: 13.8 imgs/s Running inference on batch 072/125... - Step Time: 0.3296s - Throughput: 12.1 imgs/s Running inference on batch 073/125... - Step Time: 0.3256s - Throughput: 12.3 imgs/s Running inference on batch 074/125... - Step Time: 0.3296s - Throughput: 12.1 imgs/s Running inference on batch 075/125... - Step Time: 0.3458s - Throughput: 11.6 imgs/s Running inference on batch 076/125... - Step Time: 0.3391s - Throughput: 11.8 imgs/s Running inference on batch 077/125... - Step Time: 0.3299s - Throughput: 12.1 imgs/s Running inference on batch 078/125... - Step Time: 0.3389s - Throughput: 11.8 imgs/s Running inference on batch 079/125... - Step Time: 0.3267s - Throughput: 12.2 imgs/s Running inference on batch 080/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 081/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 082/125... - Step Time: 0.3260s - Throughput: 12.3 imgs/s Running inference on batch 083/125... - Step Time: 0.3238s - Throughput: 12.4 imgs/s Running inference on batch 084/125... - Step Time: 0.3349s - Throughput: 11.9 imgs/s Running inference on batch 085/125... - Step Time: 0.3214s - Throughput: 12.4 imgs/s Running inference on batch 086/125... - Step Time: 0.3245s - Throughput: 12.3 imgs/s Running inference on batch 087/125... - Step Time: 0.3007s - Throughput: 13.3 imgs/s Running inference on batch 088/125... - Step Time: 0.3371s - Throughput: 11.9 imgs/s Running inference on batch 089/125... - Step Time: 0.3332s - Throughput: 12.0 imgs/s Running inference on batch 090/125... - Step Time: 0.2611s - Throughput: 15.3 imgs/s Running inference on batch 091/125... - Step Time: 0.2702s - Throughput: 14.8 imgs/s Running inference on batch 092/125... - Step Time: 0.3383s - Throughput: 11.8 imgs/s Running inference on batch 093/125... - Step Time: 0.3046s - Throughput: 13.1 imgs/s Running inference on batch 094/125... - Step Time: 0.3269s - Throughput: 12.2 imgs/s Running inference on batch 095/125... - Step Time: 0.3193s - Throughput: 12.5 imgs/s Running inference on batch 096/125... - Step Time: 0.3227s - Throughput: 12.4 imgs/s Running inference on batch 097/125... - Step Time: 0.3309s - Throughput: 12.1 imgs/s Running inference on batch 098/125... - Step Time: 0.3265s - Throughput: 12.3 imgs/s Running inference on batch 099/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 100/125... - Step Time: 0.3118s - Throughput: 12.8 imgs/s Running inference on batch 101/125... - Step Time: 0.3249s - Throughput: 12.3 imgs/s Running inference on batch 102/125... - Step Time: 0.3226s - Throughput: 12.4 imgs/s Running inference on batch 103/125... - Step Time: 0.3258s - Throughput: 12.3 imgs/s Running inference on batch 104/125... - Step Time: 0.3498s - Throughput: 11.4 imgs/s Running inference on batch 105/125... - Step Time: 0.3223s - Throughput: 12.4 imgs/s Running inference on batch 106/125... - Step Time: 0.3298s - Throughput: 12.1 imgs/s Running inference on batch 107/125... - Step Time: 0.3252s - Throughput: 12.3 imgs/s Running inference on batch 108/125... - Step Time: 0.3325s - Throughput: 12.0 imgs/s Running inference on batch 109/125... - Step Time: 0.3304s - Throughput: 12.1 imgs/s Running inference on batch 110/125... - Step Time: 0.3370s - Throughput: 11.9 imgs/s Running inference on batch 111/125... - Step Time: 0.3284s - Throughput: 12.2 imgs/s Running inference on batch 112/125... - Step Time: 0.3366s - Throughput: 11.9 imgs/s Running inference on batch 113/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 114/125... - Step Time: 0.3237s - Throughput: 12.4 imgs/s Running inference on batch 115/125... - Step Time: 0.3330s - Throughput: 12.0 imgs/s Running inference on batch 116/125... - Step Time: 0.3283s - Throughput: 12.2 imgs/s Running inference on batch 117/125... - Step Time: 0.3239s - Throughput: 12.3 imgs/s Running inference on batch 118/125... - Step Time: 0.3437s - Throughput: 11.6 imgs/s Running inference on batch 119/125... - Step Time: 0.3410s - Throughput: 11.7 imgs/s Running inference on batch 120/125... - Step Time: 0.3290s - Throughput: 12.2 imgs/s Running inference on batch 121/125... - Step Time: 0.3289s - Throughput: 12.2 imgs/s Running inference on batch 122/125... - Step Time: 0.3251s - Throughput: 12.3 imgs/s Running inference on batch 123/125... - Step Time: 0.3268s - Throughput: 12.2 imgs/s Running inference on batch 124/125... - Step Time: 0.3376s - Throughput: 11.8 imgs/s Running inference on batch 125/125... - Step Time: 0.3253s - Throughput: 12.3 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 12.1 samples/sec Total processed steps: 125 Total processing time: 0.0h 25m 23s ==================== Metrics ==================== AP: 0.185595542 AP50: 0.293133706 AP75: 0.195121065 APl: 0.215516388 APm: 0.054809149 APs: 0.000993499 ARl: 0.417310536 ARm: 0.123322181 ARmax1: 0.268304735 ARmax10: 0.356456786 ARmax100: 0.361048669 ARs: 0.021819646 mask_AP: 0.141965225 mask_AP50: 0.240727514 mask_AP75: 0.146134049 mask_APl: 0.165906668 mask_APm: 0.024838414 mask_APs: 0.004213084 mask_ARl: 0.287216604 mask_ARm: 0.069704570 mask_ARmax1: 0.201236039 mask_ARmax10: 0.241098359 mask_ARmax100: 0.243917614 mask_ARs: 0.018196458 ================================= Start training cycle 03 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654931256.0173376 iteration: 20005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14109 FastRCNN class loss: 0.05604 FastRCNN total loss: 0.19713 L1 loss: 0.0000e+00 L2 loss: 1.11762 Learning rate: 0.02 Mask loss: 0.13079 RPN box loss: 0.04934 RPN score loss: 0.00208 RPN total loss: 0.05143 Total loss: 1.49697 timestamp: 1654931259.228239 iteration: 20010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10899 FastRCNN class loss: 0.07221 FastRCNN total loss: 0.1812 L1 loss: 0.0000e+00 L2 loss: 1.11746 Learning rate: 0.02 Mask loss: 0.13689 RPN box loss: 0.02313 RPN score loss: 0.00473 RPN total loss: 0.02785 Total loss: 1.4634 timestamp: 1654931262.451397 iteration: 20015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0792 FastRCNN class loss: 0.06024 FastRCNN total loss: 0.13944 L1 loss: 0.0000e+00 L2 loss: 1.11728 Learning rate: 0.02 Mask loss: 0.19081 RPN box loss: 0.00872 RPN score loss: 0.00792 RPN total loss: 0.01664 Total loss: 1.46417 timestamp: 1654931265.6553793 iteration: 20020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19403 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.26804 L1 loss: 0.0000e+00 L2 loss: 1.11708 Learning rate: 0.02 Mask loss: 0.20395 RPN box loss: 0.02731 RPN score loss: 0.00317 RPN total loss: 0.03048 Total loss: 1.61955 timestamp: 1654931268.9386122 iteration: 20025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10483 FastRCNN class loss: 0.06408 FastRCNN total loss: 0.1689 L1 loss: 0.0000e+00 L2 loss: 1.11689 Learning rate: 0.02 Mask loss: 0.16053 RPN box loss: 0.05141 RPN score loss: 0.00235 RPN total loss: 0.05376 Total loss: 1.50009 timestamp: 1654931272.141263 iteration: 20030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11452 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.18947 L1 loss: 0.0000e+00 L2 loss: 1.11671 Learning rate: 0.02 Mask loss: 0.09774 RPN box loss: 0.01339 RPN score loss: 0.00421 RPN total loss: 0.0176 Total loss: 1.42152 timestamp: 1654931275.4078586 iteration: 20035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.15701 L1 loss: 0.0000e+00 L2 loss: 1.11653 Learning rate: 0.02 Mask loss: 0.20207 RPN box loss: 0.00689 RPN score loss: 0.00345 RPN total loss: 0.01033 Total loss: 1.48594 timestamp: 1654931278.6146235 iteration: 20040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12497 FastRCNN class loss: 0.07554 FastRCNN total loss: 0.20051 L1 loss: 0.0000e+00 L2 loss: 1.11638 Learning rate: 0.02 Mask loss: 0.19311 RPN box loss: 0.00992 RPN score loss: 0.0015 RPN total loss: 0.01142 Total loss: 1.52142 timestamp: 1654931281.717648 iteration: 20045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18264 FastRCNN class loss: 0.08429 FastRCNN total loss: 0.26692 L1 loss: 0.0000e+00 L2 loss: 1.11618 Learning rate: 0.02 Mask loss: 0.11546 RPN box loss: 0.01959 RPN score loss: 0.00771 RPN total loss: 0.0273 Total loss: 1.52586 timestamp: 1654931284.9691644 iteration: 20050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14383 FastRCNN class loss: 0.08865 FastRCNN total loss: 0.23247 L1 loss: 0.0000e+00 L2 loss: 1.11598 Learning rate: 0.02 Mask loss: 0.1366 RPN box loss: 0.01425 RPN score loss: 0.00495 RPN total loss: 0.0192 Total loss: 1.50426 timestamp: 1654931288.1876497 iteration: 20055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11665 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.2093 L1 loss: 0.0000e+00 L2 loss: 1.11582 Learning rate: 0.02 Mask loss: 0.14244 RPN box loss: 0.03787 RPN score loss: 0.00463 RPN total loss: 0.0425 Total loss: 1.51005 timestamp: 1654931291.3868117 iteration: 20060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17223 FastRCNN class loss: 0.15058 FastRCNN total loss: 0.32282 L1 loss: 0.0000e+00 L2 loss: 1.11564 Learning rate: 0.02 Mask loss: 0.24375 RPN box loss: 0.045 RPN score loss: 0.01496 RPN total loss: 0.05996 Total loss: 1.74216 timestamp: 1654931294.5689156 iteration: 20065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15216 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.22929 L1 loss: 0.0000e+00 L2 loss: 1.11546 Learning rate: 0.02 Mask loss: 0.16278 RPN box loss: 0.05992 RPN score loss: 0.00379 RPN total loss: 0.06371 Total loss: 1.57124 timestamp: 1654931297.7939126 iteration: 20070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14426 FastRCNN class loss: 0.10345 FastRCNN total loss: 0.2477 L1 loss: 0.0000e+00 L2 loss: 1.11529 Learning rate: 0.02 Mask loss: 0.12708 RPN box loss: 0.03079 RPN score loss: 0.00492 RPN total loss: 0.03572 Total loss: 1.52578 timestamp: 1654931301.0197172 iteration: 20075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17084 FastRCNN class loss: 0.09358 FastRCNN total loss: 0.26443 L1 loss: 0.0000e+00 L2 loss: 1.1151 Learning rate: 0.02 Mask loss: 0.17214 RPN box loss: 0.02571 RPN score loss: 0.00983 RPN total loss: 0.03554 Total loss: 1.5872 timestamp: 1654931304.1699374 iteration: 20080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09378 FastRCNN class loss: 0.03711 FastRCNN total loss: 0.13089 L1 loss: 0.0000e+00 L2 loss: 1.11493 Learning rate: 0.02 Mask loss: 0.12628 RPN box loss: 0.01402 RPN score loss: 0.0037 RPN total loss: 0.01771 Total loss: 1.38982 timestamp: 1654931307.3763115 iteration: 20085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15175 FastRCNN class loss: 0.1064 FastRCNN total loss: 0.25815 L1 loss: 0.0000e+00 L2 loss: 1.11476 Learning rate: 0.02 Mask loss: 0.20536 RPN box loss: 0.02663 RPN score loss: 0.00587 RPN total loss: 0.0325 Total loss: 1.61077 timestamp: 1654931310.5921237 iteration: 20090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23129 FastRCNN class loss: 0.11301 FastRCNN total loss: 0.3443 L1 loss: 0.0000e+00 L2 loss: 1.11458 Learning rate: 0.02 Mask loss: 0.16474 RPN box loss: 0.03825 RPN score loss: 0.00832 RPN total loss: 0.04657 Total loss: 1.6702 timestamp: 1654931313.8044236 iteration: 20095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11753 FastRCNN class loss: 0.05235 FastRCNN total loss: 0.16988 L1 loss: 0.0000e+00 L2 loss: 1.11439 Learning rate: 0.02 Mask loss: 0.08878 RPN box loss: 0.02133 RPN score loss: 0.00307 RPN total loss: 0.0244 Total loss: 1.39744 timestamp: 1654931317.0917459 iteration: 20100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09773 FastRCNN class loss: 0.0485 FastRCNN total loss: 0.14623 L1 loss: 0.0000e+00 L2 loss: 1.11419 Learning rate: 0.02 Mask loss: 0.10588 RPN box loss: 0.02927 RPN score loss: 0.0078 RPN total loss: 0.03708 Total loss: 1.40338 timestamp: 1654931320.3542476 iteration: 20105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20068 FastRCNN class loss: 0.08928 FastRCNN total loss: 0.28996 L1 loss: 0.0000e+00 L2 loss: 1.11401 Learning rate: 0.02 Mask loss: 0.15993 RPN box loss: 0.05909 RPN score loss: 0.00915 RPN total loss: 0.06824 Total loss: 1.63215 timestamp: 1654931323.5670922 iteration: 20110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15051 FastRCNN class loss: 0.07864 FastRCNN total loss: 0.22915 L1 loss: 0.0000e+00 L2 loss: 1.11385 Learning rate: 0.02 Mask loss: 0.13581 RPN box loss: 0.01248 RPN score loss: 0.00535 RPN total loss: 0.01783 Total loss: 1.49664 timestamp: 1654931326.8484082 iteration: 20115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14109 FastRCNN class loss: 0.06824 FastRCNN total loss: 0.20933 L1 loss: 0.0000e+00 L2 loss: 1.11369 Learning rate: 0.02 Mask loss: 0.18122 RPN box loss: 0.03383 RPN score loss: 0.00682 RPN total loss: 0.04065 Total loss: 1.54489 timestamp: 1654931330.0523286 iteration: 20120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09296 FastRCNN class loss: 0.04125 FastRCNN total loss: 0.13421 L1 loss: 0.0000e+00 L2 loss: 1.11352 Learning rate: 0.02 Mask loss: 0.11833 RPN box loss: 0.00316 RPN score loss: 0.00277 RPN total loss: 0.00593 Total loss: 1.372 timestamp: 1654931333.2692044 iteration: 20125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10785 FastRCNN class loss: 0.0766 FastRCNN total loss: 0.18446 L1 loss: 0.0000e+00 L2 loss: 1.11334 Learning rate: 0.02 Mask loss: 0.144 RPN box loss: 0.01855 RPN score loss: 0.00288 RPN total loss: 0.02144 Total loss: 1.46323 timestamp: 1654931336.4842253 iteration: 20130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14975 FastRCNN class loss: 0.08769 FastRCNN total loss: 0.23744 L1 loss: 0.0000e+00 L2 loss: 1.11316 Learning rate: 0.02 Mask loss: 0.196 RPN box loss: 0.07745 RPN score loss: 0.00755 RPN total loss: 0.085 Total loss: 1.63161 timestamp: 1654931339.743761 iteration: 20135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18793 FastRCNN class loss: 0.08954 FastRCNN total loss: 0.27747 L1 loss: 0.0000e+00 L2 loss: 1.11296 Learning rate: 0.02 Mask loss: 0.15468 RPN box loss: 0.02615 RPN score loss: 0.00942 RPN total loss: 0.03557 Total loss: 1.58067 timestamp: 1654931342.9522946 iteration: 20140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17767 FastRCNN class loss: 0.1033 FastRCNN total loss: 0.28097 L1 loss: 0.0000e+00 L2 loss: 1.11277 Learning rate: 0.02 Mask loss: 0.14509 RPN box loss: 0.02048 RPN score loss: 0.00529 RPN total loss: 0.02577 Total loss: 1.5646 timestamp: 1654931346.1408832 iteration: 20145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12627 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.18745 L1 loss: 0.0000e+00 L2 loss: 1.11258 Learning rate: 0.02 Mask loss: 0.09449 RPN box loss: 0.00567 RPN score loss: 0.00399 RPN total loss: 0.00966 Total loss: 1.40417 timestamp: 1654931349.320653 iteration: 20150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14343 FastRCNN class loss: 0.10879 FastRCNN total loss: 0.25221 L1 loss: 0.0000e+00 L2 loss: 1.11239 Learning rate: 0.02 Mask loss: 0.13644 RPN box loss: 0.03746 RPN score loss: 0.00621 RPN total loss: 0.04367 Total loss: 1.54472 timestamp: 1654931352.562579 iteration: 20155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.05592 FastRCNN total loss: 0.17546 L1 loss: 0.0000e+00 L2 loss: 1.11222 Learning rate: 0.02 Mask loss: 0.09709 RPN box loss: 0.00963 RPN score loss: 0.00173 RPN total loss: 0.01136 Total loss: 1.39614 timestamp: 1654931355.8284695 iteration: 20160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1414 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.22371 L1 loss: 0.0000e+00 L2 loss: 1.11203 Learning rate: 0.02 Mask loss: 0.23775 RPN box loss: 0.0103 RPN score loss: 0.00384 RPN total loss: 0.01414 Total loss: 1.58763 timestamp: 1654931359.0731037 iteration: 20165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0969 FastRCNN class loss: 0.0582 FastRCNN total loss: 0.1551 L1 loss: 0.0000e+00 L2 loss: 1.11187 Learning rate: 0.02 Mask loss: 0.1247 RPN box loss: 0.02596 RPN score loss: 0.00492 RPN total loss: 0.03088 Total loss: 1.42255 timestamp: 1654931362.2886436 iteration: 20170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14787 FastRCNN class loss: 0.09476 FastRCNN total loss: 0.24263 L1 loss: 0.0000e+00 L2 loss: 1.11168 Learning rate: 0.02 Mask loss: 0.26368 RPN box loss: 0.05303 RPN score loss: 0.01238 RPN total loss: 0.06541 Total loss: 1.68339 timestamp: 1654931365.4475625 iteration: 20175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13194 FastRCNN class loss: 0.0722 FastRCNN total loss: 0.20415 L1 loss: 0.0000e+00 L2 loss: 1.11149 Learning rate: 0.02 Mask loss: 0.13825 RPN box loss: 0.00919 RPN score loss: 0.00316 RPN total loss: 0.01235 Total loss: 1.46623 timestamp: 1654931368.6809037 iteration: 20180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17233 FastRCNN class loss: 0.09147 FastRCNN total loss: 0.2638 L1 loss: 0.0000e+00 L2 loss: 1.11133 Learning rate: 0.02 Mask loss: 0.18541 RPN box loss: 0.03749 RPN score loss: 0.00469 RPN total loss: 0.04218 Total loss: 1.60272 timestamp: 1654931371.8826902 iteration: 20185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10503 FastRCNN class loss: 0.13928 FastRCNN total loss: 0.24431 L1 loss: 0.0000e+00 L2 loss: 1.11114 Learning rate: 0.02 Mask loss: 0.17739 RPN box loss: 0.03797 RPN score loss: 0.0189 RPN total loss: 0.05687 Total loss: 1.58971 timestamp: 1654931375.0921073 iteration: 20190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14141 FastRCNN class loss: 0.09647 FastRCNN total loss: 0.23788 L1 loss: 0.0000e+00 L2 loss: 1.11095 Learning rate: 0.02 Mask loss: 0.14555 RPN box loss: 0.05345 RPN score loss: 0.00888 RPN total loss: 0.06234 Total loss: 1.55671 timestamp: 1654931378.3219125 iteration: 20195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16093 FastRCNN class loss: 0.11862 FastRCNN total loss: 0.27955 L1 loss: 0.0000e+00 L2 loss: 1.11076 Learning rate: 0.02 Mask loss: 0.22365 RPN box loss: 0.05866 RPN score loss: 0.00877 RPN total loss: 0.06742 Total loss: 1.68139 timestamp: 1654931381.4348016 iteration: 20200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18298 FastRCNN class loss: 0.09388 FastRCNN total loss: 0.27686 L1 loss: 0.0000e+00 L2 loss: 1.1106 Learning rate: 0.02 Mask loss: 0.14745 RPN box loss: 0.07063 RPN score loss: 0.00516 RPN total loss: 0.07579 Total loss: 1.6107 timestamp: 1654931384.655628 iteration: 20205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12499 FastRCNN class loss: 0.1316 FastRCNN total loss: 0.25659 L1 loss: 0.0000e+00 L2 loss: 1.11044 Learning rate: 0.02 Mask loss: 0.1522 RPN box loss: 0.04107 RPN score loss: 0.00456 RPN total loss: 0.04563 Total loss: 1.56485 timestamp: 1654931387.8581743 iteration: 20210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13718 FastRCNN class loss: 0.10958 FastRCNN total loss: 0.24676 L1 loss: 0.0000e+00 L2 loss: 1.11027 Learning rate: 0.02 Mask loss: 0.23665 RPN box loss: 0.0288 RPN score loss: 0.00864 RPN total loss: 0.03744 Total loss: 1.63112 timestamp: 1654931391.1387262 iteration: 20215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14117 FastRCNN class loss: 0.09913 FastRCNN total loss: 0.24029 L1 loss: 0.0000e+00 L2 loss: 1.11007 Learning rate: 0.02 Mask loss: 0.22683 RPN box loss: 0.02083 RPN score loss: 0.00771 RPN total loss: 0.02855 Total loss: 1.60574 timestamp: 1654931394.38571 iteration: 20220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06862 FastRCNN class loss: 0.06562 FastRCNN total loss: 0.13424 L1 loss: 0.0000e+00 L2 loss: 1.1099 Learning rate: 0.02 Mask loss: 0.10497 RPN box loss: 0.02594 RPN score loss: 0.00372 RPN total loss: 0.02966 Total loss: 1.37877 timestamp: 1654931397.5372434 iteration: 20225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06591 FastRCNN class loss: 0.05385 FastRCNN total loss: 0.11976 L1 loss: 0.0000e+00 L2 loss: 1.10973 Learning rate: 0.02 Mask loss: 0.12574 RPN box loss: 0.02432 RPN score loss: 0.00703 RPN total loss: 0.03135 Total loss: 1.38658 timestamp: 1654931400.7754915 iteration: 20230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14764 FastRCNN class loss: 0.10989 FastRCNN total loss: 0.25753 L1 loss: 0.0000e+00 L2 loss: 1.10955 Learning rate: 0.02 Mask loss: 0.26497 RPN box loss: 0.03126 RPN score loss: 0.00916 RPN total loss: 0.04043 Total loss: 1.67248 timestamp: 1654931403.9685824 iteration: 20235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17084 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.2429 L1 loss: 0.0000e+00 L2 loss: 1.10938 Learning rate: 0.02 Mask loss: 0.10945 RPN box loss: 0.00896 RPN score loss: 0.00179 RPN total loss: 0.01075 Total loss: 1.47247 timestamp: 1654931407.2023838 iteration: 20240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14808 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.20745 L1 loss: 0.0000e+00 L2 loss: 1.1092 Learning rate: 0.02 Mask loss: 0.12935 RPN box loss: 0.02183 RPN score loss: 0.00541 RPN total loss: 0.02724 Total loss: 1.47324 timestamp: 1654931410.419051 iteration: 20245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14477 FastRCNN class loss: 0.10044 FastRCNN total loss: 0.24521 L1 loss: 0.0000e+00 L2 loss: 1.10902 Learning rate: 0.02 Mask loss: 0.18741 RPN box loss: 0.02651 RPN score loss: 0.00895 RPN total loss: 0.03546 Total loss: 1.57711 timestamp: 1654931413.5617805 iteration: 20250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12604 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.18444 L1 loss: 0.0000e+00 L2 loss: 1.10883 Learning rate: 0.02 Mask loss: 0.11717 RPN box loss: 0.02287 RPN score loss: 0.00168 RPN total loss: 0.02455 Total loss: 1.43499 timestamp: 1654931416.7980943 iteration: 20255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13866 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.20845 L1 loss: 0.0000e+00 L2 loss: 1.10865 Learning rate: 0.02 Mask loss: 0.09999 RPN box loss: 0.00962 RPN score loss: 0.00255 RPN total loss: 0.01216 Total loss: 1.42925 timestamp: 1654931420.0373368 iteration: 20260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.10177 FastRCNN total loss: 0.25314 L1 loss: 0.0000e+00 L2 loss: 1.10847 Learning rate: 0.02 Mask loss: 0.15804 RPN box loss: 0.01095 RPN score loss: 0.00302 RPN total loss: 0.01397 Total loss: 1.53363 timestamp: 1654931423.284289 iteration: 20265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15405 FastRCNN class loss: 0.08988 FastRCNN total loss: 0.24393 L1 loss: 0.0000e+00 L2 loss: 1.10829 Learning rate: 0.02 Mask loss: 0.13076 RPN box loss: 0.04826 RPN score loss: 0.01027 RPN total loss: 0.05854 Total loss: 1.54152 timestamp: 1654931426.5239668 iteration: 20270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15617 FastRCNN class loss: 0.09268 FastRCNN total loss: 0.24885 L1 loss: 0.0000e+00 L2 loss: 1.1081 Learning rate: 0.02 Mask loss: 0.18963 RPN box loss: 0.02189 RPN score loss: 0.00738 RPN total loss: 0.02926 Total loss: 1.57584 timestamp: 1654931429.7559414 iteration: 20275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13852 FastRCNN class loss: 0.11248 FastRCNN total loss: 0.251 L1 loss: 0.0000e+00 L2 loss: 1.10792 Learning rate: 0.02 Mask loss: 0.15471 RPN box loss: 0.02889 RPN score loss: 0.00484 RPN total loss: 0.03373 Total loss: 1.54736 timestamp: 1654931432.900849 iteration: 20280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18765 FastRCNN class loss: 0.08586 FastRCNN total loss: 0.27352 L1 loss: 0.0000e+00 L2 loss: 1.10772 Learning rate: 0.02 Mask loss: 0.16742 RPN box loss: 0.00797 RPN score loss: 0.00291 RPN total loss: 0.01088 Total loss: 1.55953 timestamp: 1654931436.1703157 iteration: 20285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19905 FastRCNN class loss: 0.05861 FastRCNN total loss: 0.25766 L1 loss: 0.0000e+00 L2 loss: 1.10754 Learning rate: 0.02 Mask loss: 0.09004 RPN box loss: 0.01954 RPN score loss: 0.00533 RPN total loss: 0.02486 Total loss: 1.4801 timestamp: 1654931439.4095929 iteration: 20290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.08792 FastRCNN total loss: 0.20474 L1 loss: 0.0000e+00 L2 loss: 1.10737 Learning rate: 0.02 Mask loss: 0.13197 RPN box loss: 0.02244 RPN score loss: 0.0037 RPN total loss: 0.02614 Total loss: 1.47022 timestamp: 1654931442.5993469 iteration: 20295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12885 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.20633 L1 loss: 0.0000e+00 L2 loss: 1.10719 Learning rate: 0.02 Mask loss: 0.13272 RPN box loss: 0.08419 RPN score loss: 0.01048 RPN total loss: 0.09467 Total loss: 1.54091 timestamp: 1654931445.8711083 iteration: 20300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17754 FastRCNN class loss: 0.1002 FastRCNN total loss: 0.27774 L1 loss: 0.0000e+00 L2 loss: 1.10701 Learning rate: 0.02 Mask loss: 0.1688 RPN box loss: 0.03397 RPN score loss: 0.00695 RPN total loss: 0.04093 Total loss: 1.59448 timestamp: 1654931449.0768814 iteration: 20305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13827 FastRCNN class loss: 0.08388 FastRCNN total loss: 0.22215 L1 loss: 0.0000e+00 L2 loss: 1.10683 Learning rate: 0.02 Mask loss: 0.14566 RPN box loss: 0.01786 RPN score loss: 0.00417 RPN total loss: 0.02202 Total loss: 1.49666 timestamp: 1654931452.2879357 iteration: 20310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14493 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.22915 L1 loss: 0.0000e+00 L2 loss: 1.10665 Learning rate: 0.02 Mask loss: 0.15266 RPN box loss: 0.0425 RPN score loss: 0.00627 RPN total loss: 0.04877 Total loss: 1.53724 timestamp: 1654931455.5149353 iteration: 20315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09603 FastRCNN class loss: 0.06145 FastRCNN total loss: 0.15748 L1 loss: 0.0000e+00 L2 loss: 1.10647 Learning rate: 0.02 Mask loss: 0.1696 RPN box loss: 0.03825 RPN score loss: 0.00163 RPN total loss: 0.03988 Total loss: 1.47343 timestamp: 1654931458.6908996 iteration: 20320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15384 FastRCNN class loss: 0.08699 FastRCNN total loss: 0.24083 L1 loss: 0.0000e+00 L2 loss: 1.10628 Learning rate: 0.02 Mask loss: 0.22176 RPN box loss: 0.01867 RPN score loss: 0.00495 RPN total loss: 0.02361 Total loss: 1.59248 timestamp: 1654931461.9531476 iteration: 20325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11388 FastRCNN class loss: 0.05233 FastRCNN total loss: 0.16621 L1 loss: 0.0000e+00 L2 loss: 1.1061 Learning rate: 0.02 Mask loss: 0.13404 RPN box loss: 0.03081 RPN score loss: 0.00393 RPN total loss: 0.03474 Total loss: 1.4411 timestamp: 1654931465.1085176 iteration: 20330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12412 FastRCNN class loss: 0.07717 FastRCNN total loss: 0.2013 L1 loss: 0.0000e+00 L2 loss: 1.10591 Learning rate: 0.02 Mask loss: 0.13052 RPN box loss: 0.04426 RPN score loss: 0.00392 RPN total loss: 0.04818 Total loss: 1.48591 timestamp: 1654931468.384081 iteration: 20335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14873 FastRCNN class loss: 0.07577 FastRCNN total loss: 0.2245 L1 loss: 0.0000e+00 L2 loss: 1.10574 Learning rate: 0.02 Mask loss: 0.13657 RPN box loss: 0.0585 RPN score loss: 0.02088 RPN total loss: 0.07938 Total loss: 1.54619 timestamp: 1654931471.5340245 iteration: 20340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10627 FastRCNN class loss: 0.07452 FastRCNN total loss: 0.18079 L1 loss: 0.0000e+00 L2 loss: 1.10554 Learning rate: 0.02 Mask loss: 0.20957 RPN box loss: 0.03927 RPN score loss: 0.00342 RPN total loss: 0.0427 Total loss: 1.53861 timestamp: 1654931474.7920961 iteration: 20345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13498 FastRCNN class loss: 0.0822 FastRCNN total loss: 0.21718 L1 loss: 0.0000e+00 L2 loss: 1.10535 Learning rate: 0.02 Mask loss: 0.14303 RPN box loss: 0.01296 RPN score loss: 0.00754 RPN total loss: 0.02051 Total loss: 1.48607 timestamp: 1654931477.9920883 iteration: 20350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18872 FastRCNN class loss: 0.13347 FastRCNN total loss: 0.32219 L1 loss: 0.0000e+00 L2 loss: 1.10518 Learning rate: 0.02 Mask loss: 0.26795 RPN box loss: 0.05676 RPN score loss: 0.01468 RPN total loss: 0.07144 Total loss: 1.76675 timestamp: 1654931481.1635134 iteration: 20355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18756 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.23862 L1 loss: 0.0000e+00 L2 loss: 1.105 Learning rate: 0.02 Mask loss: 0.14235 RPN box loss: 0.0193 RPN score loss: 0.00597 RPN total loss: 0.02528 Total loss: 1.51125 timestamp: 1654931484.3027573 iteration: 20360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15972 FastRCNN class loss: 0.13418 FastRCNN total loss: 0.2939 L1 loss: 0.0000e+00 L2 loss: 1.10482 Learning rate: 0.02 Mask loss: 0.17485 RPN box loss: 0.04621 RPN score loss: 0.00911 RPN total loss: 0.05532 Total loss: 1.62888 timestamp: 1654931487.5229845 iteration: 20365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11895 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.21076 L1 loss: 0.0000e+00 L2 loss: 1.10465 Learning rate: 0.02 Mask loss: 0.11854 RPN box loss: 0.03529 RPN score loss: 0.00681 RPN total loss: 0.0421 Total loss: 1.47604 timestamp: 1654931490.7346776 iteration: 20370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12312 FastRCNN class loss: 0.08191 FastRCNN total loss: 0.20503 L1 loss: 0.0000e+00 L2 loss: 1.10446 Learning rate: 0.02 Mask loss: 0.12062 RPN box loss: 0.0353 RPN score loss: 0.00625 RPN total loss: 0.04155 Total loss: 1.47166 timestamp: 1654931493.9929352 iteration: 20375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15398 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.24134 L1 loss: 0.0000e+00 L2 loss: 1.10429 Learning rate: 0.02 Mask loss: 0.24284 RPN box loss: 0.03272 RPN score loss: 0.0046 RPN total loss: 0.03732 Total loss: 1.62579 timestamp: 1654931497.1613455 iteration: 20380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12854 FastRCNN class loss: 0.11001 FastRCNN total loss: 0.23855 L1 loss: 0.0000e+00 L2 loss: 1.1041 Learning rate: 0.02 Mask loss: 0.20541 RPN box loss: 0.02462 RPN score loss: 0.00818 RPN total loss: 0.0328 Total loss: 1.58087 timestamp: 1654931500.4541364 iteration: 20385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30464 FastRCNN class loss: 0.15985 FastRCNN total loss: 0.46449 L1 loss: 0.0000e+00 L2 loss: 1.10391 Learning rate: 0.02 Mask loss: 0.22151 RPN box loss: 0.04636 RPN score loss: 0.04062 RPN total loss: 0.08698 Total loss: 1.87688 timestamp: 1654931503.681273 iteration: 20390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10154 FastRCNN class loss: 0.065 FastRCNN total loss: 0.16654 L1 loss: 0.0000e+00 L2 loss: 1.10374 Learning rate: 0.02 Mask loss: 0.26872 RPN box loss: 0.0146 RPN score loss: 0.0056 RPN total loss: 0.0202 Total loss: 1.5592 timestamp: 1654931506.8281093 iteration: 20395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12725 FastRCNN class loss: 0.122 FastRCNN total loss: 0.24926 L1 loss: 0.0000e+00 L2 loss: 1.10357 Learning rate: 0.02 Mask loss: 0.14098 RPN box loss: 0.02787 RPN score loss: 0.0077 RPN total loss: 0.03557 Total loss: 1.52937 timestamp: 1654931510.029124 iteration: 20400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10248 FastRCNN class loss: 0.06941 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 1.10337 Learning rate: 0.02 Mask loss: 0.13281 RPN box loss: 0.01151 RPN score loss: 0.00502 RPN total loss: 0.01653 Total loss: 1.4246 timestamp: 1654931513.213732 iteration: 20405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09684 FastRCNN class loss: 0.08021 FastRCNN total loss: 0.17706 L1 loss: 0.0000e+00 L2 loss: 1.1032 Learning rate: 0.02 Mask loss: 0.14315 RPN box loss: 0.00775 RPN score loss: 0.00239 RPN total loss: 0.01014 Total loss: 1.43355 timestamp: 1654931516.4511514 iteration: 20410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15539 FastRCNN class loss: 0.14084 FastRCNN total loss: 0.29624 L1 loss: 0.0000e+00 L2 loss: 1.10303 Learning rate: 0.02 Mask loss: 0.1531 RPN box loss: 0.03914 RPN score loss: 0.00877 RPN total loss: 0.04791 Total loss: 1.60028 timestamp: 1654931519.6440003 iteration: 20415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15436 FastRCNN class loss: 0.08903 FastRCNN total loss: 0.24339 L1 loss: 0.0000e+00 L2 loss: 1.10285 Learning rate: 0.02 Mask loss: 0.13779 RPN box loss: 0.02056 RPN score loss: 0.00653 RPN total loss: 0.02709 Total loss: 1.51112 timestamp: 1654931522.892934 iteration: 20420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12742 FastRCNN class loss: 0.0522 FastRCNN total loss: 0.17962 L1 loss: 0.0000e+00 L2 loss: 1.10266 Learning rate: 0.02 Mask loss: 0.15323 RPN box loss: 0.0477 RPN score loss: 0.00367 RPN total loss: 0.05137 Total loss: 1.48687 timestamp: 1654931526.2063854 iteration: 20425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14793 FastRCNN class loss: 0.08741 FastRCNN total loss: 0.23534 L1 loss: 0.0000e+00 L2 loss: 1.10247 Learning rate: 0.02 Mask loss: 0.19591 RPN box loss: 0.0323 RPN score loss: 0.01702 RPN total loss: 0.04933 Total loss: 1.58304 timestamp: 1654931529.422745 iteration: 20430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23908 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.33049 L1 loss: 0.0000e+00 L2 loss: 1.1023 Learning rate: 0.02 Mask loss: 0.22973 RPN box loss: 0.02129 RPN score loss: 0.00525 RPN total loss: 0.02654 Total loss: 1.68906 timestamp: 1654931532.6338449 iteration: 20435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13117 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.21134 L1 loss: 0.0000e+00 L2 loss: 1.10214 Learning rate: 0.02 Mask loss: 0.21131 RPN box loss: 0.04065 RPN score loss: 0.0101 RPN total loss: 0.05075 Total loss: 1.57555 timestamp: 1654931535.8738604 iteration: 20440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17589 FastRCNN class loss: 0.06738 FastRCNN total loss: 0.24328 L1 loss: 0.0000e+00 L2 loss: 1.10195 Learning rate: 0.02 Mask loss: 0.18699 RPN box loss: 0.0227 RPN score loss: 0.00287 RPN total loss: 0.02557 Total loss: 1.55778 timestamp: 1654931539.1304975 iteration: 20445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11289 FastRCNN class loss: 0.08897 FastRCNN total loss: 0.20185 L1 loss: 0.0000e+00 L2 loss: 1.10178 Learning rate: 0.02 Mask loss: 0.16675 RPN box loss: 0.05608 RPN score loss: 0.00585 RPN total loss: 0.06193 Total loss: 1.53231 timestamp: 1654931542.2885802 iteration: 20450 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14787 FastRCNN class loss: 0.0875 FastRCNN total loss: 0.23536 L1 loss: 0.0000e+00 L2 loss: 1.10159 Learning rate: 0.02 Mask loss: 0.19526 RPN box loss: 0.01401 RPN score loss: 0.00621 RPN total loss: 0.02023 Total loss: 1.55244 timestamp: 1654931545.457991 iteration: 20455 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18216 FastRCNN class loss: 0.22105 FastRCNN total loss: 0.40322 L1 loss: 0.0000e+00 L2 loss: 1.10141 Learning rate: 0.02 Mask loss: 0.20254 RPN box loss: 0.06004 RPN score loss: 0.01345 RPN total loss: 0.0735 Total loss: 1.78067 timestamp: 1654931548.7043586 iteration: 20460 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13961 FastRCNN class loss: 0.08897 FastRCNN total loss: 0.22858 L1 loss: 0.0000e+00 L2 loss: 1.10123 Learning rate: 0.02 Mask loss: 0.15925 RPN box loss: 0.05444 RPN score loss: 0.00831 RPN total loss: 0.06275 Total loss: 1.55181 timestamp: 1654931551.8651552 iteration: 20465 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.04741 FastRCNN total loss: 0.1699 L1 loss: 0.0000e+00 L2 loss: 1.10104 Learning rate: 0.02 Mask loss: 0.11988 RPN box loss: 0.00398 RPN score loss: 0.00247 RPN total loss: 0.00645 Total loss: 1.39728 timestamp: 1654931555.0711224 iteration: 20470 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12427 FastRCNN class loss: 0.12147 FastRCNN total loss: 0.24574 L1 loss: 0.0000e+00 L2 loss: 1.10086 Learning rate: 0.02 Mask loss: 0.17275 RPN box loss: 0.04742 RPN score loss: 0.01834 RPN total loss: 0.06577 Total loss: 1.58512 timestamp: 1654931558.2873387 iteration: 20475 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20713 FastRCNN class loss: 0.0817 FastRCNN total loss: 0.28884 L1 loss: 0.0000e+00 L2 loss: 1.10067 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.01877 RPN score loss: 0.00503 RPN total loss: 0.0238 Total loss: 1.56756 timestamp: 1654931561.5759544 iteration: 20480 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18285 FastRCNN class loss: 0.13158 FastRCNN total loss: 0.31442 L1 loss: 0.0000e+00 L2 loss: 1.10051 Learning rate: 0.02 Mask loss: 0.16305 RPN box loss: 0.04318 RPN score loss: 0.0046 RPN total loss: 0.04778 Total loss: 1.62576 timestamp: 1654931564.8006947 iteration: 20485 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15751 FastRCNN class loss: 0.0731 FastRCNN total loss: 0.23062 L1 loss: 0.0000e+00 L2 loss: 1.10033 Learning rate: 0.02 Mask loss: 0.13048 RPN box loss: 0.04132 RPN score loss: 0.00723 RPN total loss: 0.04855 Total loss: 1.50998 timestamp: 1654931567.9894156 iteration: 20490 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.15149 L1 loss: 0.0000e+00 L2 loss: 1.10015 Learning rate: 0.02 Mask loss: 0.12104 RPN box loss: 0.03118 RPN score loss: 0.01047 RPN total loss: 0.04166 Total loss: 1.41433 timestamp: 1654931571.208253 iteration: 20495 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14754 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.22939 L1 loss: 0.0000e+00 L2 loss: 1.09998 Learning rate: 0.02 Mask loss: 0.22901 RPN box loss: 0.023 RPN score loss: 0.00549 RPN total loss: 0.02849 Total loss: 1.58688 timestamp: 1654931574.3468359 iteration: 20500 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16918 FastRCNN class loss: 0.07872 FastRCNN total loss: 0.24789 L1 loss: 0.0000e+00 L2 loss: 1.09981 Learning rate: 0.02 Mask loss: 0.15497 RPN box loss: 0.00993 RPN score loss: 0.00238 RPN total loss: 0.01231 Total loss: 1.51499 timestamp: 1654931577.5361931 iteration: 20505 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09558 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.15023 L1 loss: 0.0000e+00 L2 loss: 1.0996 Learning rate: 0.02 Mask loss: 0.15957 RPN box loss: 0.0094 RPN score loss: 0.00235 RPN total loss: 0.01175 Total loss: 1.42115 timestamp: 1654931580.8240507 iteration: 20510 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.06371 FastRCNN total loss: 0.18087 L1 loss: 0.0000e+00 L2 loss: 1.09943 Learning rate: 0.02 Mask loss: 0.13634 RPN box loss: 0.02268 RPN score loss: 0.0027 RPN total loss: 0.02539 Total loss: 1.44203 timestamp: 1654931584.0081537 iteration: 20515 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14266 FastRCNN class loss: 0.10644 FastRCNN total loss: 0.2491 L1 loss: 0.0000e+00 L2 loss: 1.09925 Learning rate: 0.02 Mask loss: 0.17117 RPN box loss: 0.03284 RPN score loss: 0.00291 RPN total loss: 0.03575 Total loss: 1.55526 timestamp: 1654931587.2696617 iteration: 20520 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08278 FastRCNN class loss: 0.04972 FastRCNN total loss: 0.13251 L1 loss: 0.0000e+00 L2 loss: 1.09906 Learning rate: 0.02 Mask loss: 0.16233 RPN box loss: 0.02443 RPN score loss: 0.00278 RPN total loss: 0.02721 Total loss: 1.4211 timestamp: 1654931590.4473662 iteration: 20525 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14386 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.22592 L1 loss: 0.0000e+00 L2 loss: 1.09885 Learning rate: 0.02 Mask loss: 0.13767 RPN box loss: 0.03448 RPN score loss: 0.00601 RPN total loss: 0.04049 Total loss: 1.50292 timestamp: 1654931593.5921187 iteration: 20530 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1204 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.1932 L1 loss: 0.0000e+00 L2 loss: 1.0987 Learning rate: 0.02 Mask loss: 0.17713 RPN box loss: 0.06241 RPN score loss: 0.00342 RPN total loss: 0.06583 Total loss: 1.53486 timestamp: 1654931596.8136563 iteration: 20535 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17374 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.2409 L1 loss: 0.0000e+00 L2 loss: 1.09854 Learning rate: 0.02 Mask loss: 0.15834 RPN box loss: 0.01556 RPN score loss: 0.00559 RPN total loss: 0.02115 Total loss: 1.51893 timestamp: 1654931600.0055525 iteration: 20540 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.0495 FastRCNN total loss: 0.12746 L1 loss: 0.0000e+00 L2 loss: 1.09836 Learning rate: 0.02 Mask loss: 0.08134 RPN box loss: 0.00559 RPN score loss: 0.00152 RPN total loss: 0.00712 Total loss: 1.31427 timestamp: 1654931603.227163 iteration: 20545 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20037 FastRCNN class loss: 0.1369 FastRCNN total loss: 0.33727 L1 loss: 0.0000e+00 L2 loss: 1.09816 Learning rate: 0.02 Mask loss: 0.19399 RPN box loss: 0.10123 RPN score loss: 0.01684 RPN total loss: 0.11807 Total loss: 1.7475 timestamp: 1654931606.4916565 iteration: 20550 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15176 FastRCNN class loss: 0.09986 FastRCNN total loss: 0.25163 L1 loss: 0.0000e+00 L2 loss: 1.09798 Learning rate: 0.02 Mask loss: 0.15447 RPN box loss: 0.01949 RPN score loss: 0.00967 RPN total loss: 0.02916 Total loss: 1.53323 timestamp: 1654931609.6931272 iteration: 20555 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11898 FastRCNN class loss: 0.06814 FastRCNN total loss: 0.18711 L1 loss: 0.0000e+00 L2 loss: 1.09781 Learning rate: 0.02 Mask loss: 0.1574 RPN box loss: 0.01952 RPN score loss: 0.01133 RPN total loss: 0.03085 Total loss: 1.47318 timestamp: 1654931612.8774455 iteration: 20560 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28585 FastRCNN class loss: 0.1204 FastRCNN total loss: 0.40625 L1 loss: 0.0000e+00 L2 loss: 1.09762 Learning rate: 0.02 Mask loss: 0.26598 RPN box loss: 0.02192 RPN score loss: 0.0123 RPN total loss: 0.03422 Total loss: 1.80407 timestamp: 1654931616.1046524 iteration: 20565 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09374 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.18247 L1 loss: 0.0000e+00 L2 loss: 1.09746 Learning rate: 0.02 Mask loss: 0.15704 RPN box loss: 0.01863 RPN score loss: 0.00774 RPN total loss: 0.02637 Total loss: 1.46334 timestamp: 1654931619.3450363 iteration: 20570 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17672 FastRCNN class loss: 0.09493 FastRCNN total loss: 0.27165 L1 loss: 0.0000e+00 L2 loss: 1.09728 Learning rate: 0.02 Mask loss: 0.29341 RPN box loss: 0.02106 RPN score loss: 0.0037 RPN total loss: 0.02476 Total loss: 1.6871 timestamp: 1654931622.5895042 iteration: 20575 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11772 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.17342 L1 loss: 0.0000e+00 L2 loss: 1.0971 Learning rate: 0.02 Mask loss: 0.14981 RPN box loss: 0.0065 RPN score loss: 0.00312 RPN total loss: 0.00962 Total loss: 1.42995 timestamp: 1654931625.8063138 iteration: 20580 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12113 FastRCNN class loss: 0.1051 FastRCNN total loss: 0.22623 L1 loss: 0.0000e+00 L2 loss: 1.09693 Learning rate: 0.02 Mask loss: 0.13395 RPN box loss: 0.02282 RPN score loss: 0.00493 RPN total loss: 0.02775 Total loss: 1.48485 timestamp: 1654931629.0435646 iteration: 20585 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19906 FastRCNN class loss: 0.12783 FastRCNN total loss: 0.32689 L1 loss: 0.0000e+00 L2 loss: 1.09673 Learning rate: 0.02 Mask loss: 0.29917 RPN box loss: 0.011 RPN score loss: 0.00873 RPN total loss: 0.01974 Total loss: 1.74252 timestamp: 1654931632.248494 iteration: 20590 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15384 FastRCNN class loss: 0.08064 FastRCNN total loss: 0.23448 L1 loss: 0.0000e+00 L2 loss: 1.09654 Learning rate: 0.02 Mask loss: 0.16583 RPN box loss: 0.01897 RPN score loss: 0.00549 RPN total loss: 0.02445 Total loss: 1.5213 timestamp: 1654931635.4449763 iteration: 20595 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18116 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.26018 L1 loss: 0.0000e+00 L2 loss: 1.09638 Learning rate: 0.02 Mask loss: 0.15422 RPN box loss: 0.02135 RPN score loss: 0.01182 RPN total loss: 0.03317 Total loss: 1.54396 timestamp: 1654931638.6206024 iteration: 20600 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20066 FastRCNN class loss: 0.07498 FastRCNN total loss: 0.27564 L1 loss: 0.0000e+00 L2 loss: 1.09621 Learning rate: 0.02 Mask loss: 0.12035 RPN box loss: 0.03772 RPN score loss: 0.01037 RPN total loss: 0.04809 Total loss: 1.54028 timestamp: 1654931641.85187 iteration: 20605 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18235 FastRCNN class loss: 0.08631 FastRCNN total loss: 0.26866 L1 loss: 0.0000e+00 L2 loss: 1.09603 Learning rate: 0.02 Mask loss: 0.10599 RPN box loss: 0.03464 RPN score loss: 0.00814 RPN total loss: 0.04278 Total loss: 1.51346 timestamp: 1654931645.1007288 iteration: 20610 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12777 FastRCNN class loss: 0.06822 FastRCNN total loss: 0.19599 L1 loss: 0.0000e+00 L2 loss: 1.09584 Learning rate: 0.02 Mask loss: 0.12549 RPN box loss: 0.06841 RPN score loss: 0.01037 RPN total loss: 0.07877 Total loss: 1.4961 timestamp: 1654931648.3565586 iteration: 20615 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15945 FastRCNN class loss: 0.07879 FastRCNN total loss: 0.23824 L1 loss: 0.0000e+00 L2 loss: 1.09567 Learning rate: 0.02 Mask loss: 0.16513 RPN box loss: 0.03764 RPN score loss: 0.01261 RPN total loss: 0.05025 Total loss: 1.54929 timestamp: 1654931651.567244 iteration: 20620 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16878 FastRCNN class loss: 0.09677 FastRCNN total loss: 0.26554 L1 loss: 0.0000e+00 L2 loss: 1.09551 Learning rate: 0.02 Mask loss: 0.19098 RPN box loss: 0.0154 RPN score loss: 0.00408 RPN total loss: 0.01948 Total loss: 1.57151 timestamp: 1654931654.7298727 iteration: 20625 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12815 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.18974 L1 loss: 0.0000e+00 L2 loss: 1.09533 Learning rate: 0.02 Mask loss: 0.1373 RPN box loss: 0.03754 RPN score loss: 0.00933 RPN total loss: 0.04687 Total loss: 1.46924 timestamp: 1654931657.9158695 iteration: 20630 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08651 FastRCNN class loss: 0.04584 FastRCNN total loss: 0.13235 L1 loss: 0.0000e+00 L2 loss: 1.09516 Learning rate: 0.02 Mask loss: 0.10711 RPN box loss: 0.05861 RPN score loss: 0.01454 RPN total loss: 0.07314 Total loss: 1.40777 timestamp: 1654931661.1073382 iteration: 20635 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14201 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.22479 L1 loss: 0.0000e+00 L2 loss: 1.095 Learning rate: 0.02 Mask loss: 0.13067 RPN box loss: 0.01076 RPN score loss: 0.00402 RPN total loss: 0.01477 Total loss: 1.46523 timestamp: 1654931664.3713706 iteration: 20640 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20207 FastRCNN class loss: 0.10197 FastRCNN total loss: 0.30404 L1 loss: 0.0000e+00 L2 loss: 1.09484 Learning rate: 0.02 Mask loss: 0.17912 RPN box loss: 0.04758 RPN score loss: 0.00511 RPN total loss: 0.0527 Total loss: 1.6307 timestamp: 1654931667.6471393 iteration: 20645 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24726 FastRCNN class loss: 0.10929 FastRCNN total loss: 0.35655 L1 loss: 0.0000e+00 L2 loss: 1.09468 Learning rate: 0.02 Mask loss: 0.23811 RPN box loss: 0.04086 RPN score loss: 0.0054 RPN total loss: 0.04626 Total loss: 1.7356 timestamp: 1654931670.8425763 iteration: 20650 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09162 FastRCNN class loss: 0.07473 FastRCNN total loss: 0.16635 L1 loss: 0.0000e+00 L2 loss: 1.09449 Learning rate: 0.02 Mask loss: 0.18638 RPN box loss: 0.02146 RPN score loss: 0.00974 RPN total loss: 0.03119 Total loss: 1.47842 timestamp: 1654931674.0947483 iteration: 20655 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11044 FastRCNN class loss: 0.06832 FastRCNN total loss: 0.17877 L1 loss: 0.0000e+00 L2 loss: 1.09432 Learning rate: 0.02 Mask loss: 0.15542 RPN box loss: 0.0269 RPN score loss: 0.00587 RPN total loss: 0.03278 Total loss: 1.46128 timestamp: 1654931677.327389 iteration: 20660 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1833 FastRCNN class loss: 0.12827 FastRCNN total loss: 0.31157 L1 loss: 0.0000e+00 L2 loss: 1.09414 Learning rate: 0.02 Mask loss: 0.2191 RPN box loss: 0.06099 RPN score loss: 0.00733 RPN total loss: 0.06831 Total loss: 1.69313 timestamp: 1654931680.5533156 iteration: 20665 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12338 FastRCNN class loss: 0.06127 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 1.09396 Learning rate: 0.02 Mask loss: 0.16296 RPN box loss: 0.00937 RPN score loss: 0.00581 RPN total loss: 0.01517 Total loss: 1.45674 timestamp: 1654931683.7024348 iteration: 20670 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16288 FastRCNN class loss: 0.12795 FastRCNN total loss: 0.29083 L1 loss: 0.0000e+00 L2 loss: 1.09378 Learning rate: 0.02 Mask loss: 0.16157 RPN box loss: 0.0177 RPN score loss: 0.00639 RPN total loss: 0.02409 Total loss: 1.57026 timestamp: 1654931686.9517298 iteration: 20675 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13615 FastRCNN class loss: 0.05702 FastRCNN total loss: 0.19317 L1 loss: 0.0000e+00 L2 loss: 1.09358 Learning rate: 0.02 Mask loss: 0.18617 RPN box loss: 0.0049 RPN score loss: 0.00354 RPN total loss: 0.00844 Total loss: 1.48136 timestamp: 1654931690.2121716 iteration: 20680 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19107 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.27745 L1 loss: 0.0000e+00 L2 loss: 1.09343 Learning rate: 0.02 Mask loss: 0.11562 RPN box loss: 0.04032 RPN score loss: 0.00897 RPN total loss: 0.04929 Total loss: 1.53579 timestamp: 1654931693.3918352 iteration: 20685 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16608 FastRCNN class loss: 0.08542 FastRCNN total loss: 0.25151 L1 loss: 0.0000e+00 L2 loss: 1.09324 Learning rate: 0.02 Mask loss: 0.22993 RPN box loss: 0.04826 RPN score loss: 0.01083 RPN total loss: 0.05909 Total loss: 1.63377 timestamp: 1654931696.5324285 iteration: 20690 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20748 FastRCNN class loss: 0.13353 FastRCNN total loss: 0.34101 L1 loss: 0.0000e+00 L2 loss: 1.09305 Learning rate: 0.02 Mask loss: 0.21336 RPN box loss: 0.03332 RPN score loss: 0.00544 RPN total loss: 0.03876 Total loss: 1.68618 timestamp: 1654931699.7677615 iteration: 20695 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19223 FastRCNN class loss: 0.11031 FastRCNN total loss: 0.30254 L1 loss: 0.0000e+00 L2 loss: 1.0929 Learning rate: 0.02 Mask loss: 0.26552 RPN box loss: 0.0311 RPN score loss: 0.00805 RPN total loss: 0.03915 Total loss: 1.70011 timestamp: 1654931703.026603 iteration: 20700 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19441 FastRCNN class loss: 0.09054 FastRCNN total loss: 0.28496 L1 loss: 0.0000e+00 L2 loss: 1.09271 Learning rate: 0.02 Mask loss: 0.18206 RPN box loss: 0.02595 RPN score loss: 0.00771 RPN total loss: 0.03366 Total loss: 1.59339 timestamp: 1654931706.246564 iteration: 20705 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10365 FastRCNN class loss: 0.06349 FastRCNN total loss: 0.16713 L1 loss: 0.0000e+00 L2 loss: 1.09254 Learning rate: 0.02 Mask loss: 0.10144 RPN box loss: 0.00545 RPN score loss: 0.00279 RPN total loss: 0.00824 Total loss: 1.36936 timestamp: 1654931709.4466057 iteration: 20710 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.05786 FastRCNN total loss: 0.16323 L1 loss: 0.0000e+00 L2 loss: 1.09237 Learning rate: 0.02 Mask loss: 0.12719 RPN box loss: 0.01109 RPN score loss: 0.00465 RPN total loss: 0.01573 Total loss: 1.39853 timestamp: 1654931712.7357216 iteration: 20715 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10548 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.17233 L1 loss: 0.0000e+00 L2 loss: 1.0922 Learning rate: 0.02 Mask loss: 0.12638 RPN box loss: 0.02693 RPN score loss: 0.00363 RPN total loss: 0.03056 Total loss: 1.42147 timestamp: 1654931715.9948208 iteration: 20720 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25439 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.34594 L1 loss: 0.0000e+00 L2 loss: 1.09202 Learning rate: 0.02 Mask loss: 0.12249 RPN box loss: 0.05202 RPN score loss: 0.01048 RPN total loss: 0.0625 Total loss: 1.62295 timestamp: 1654931719.2172976 iteration: 20725 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.04648 FastRCNN total loss: 0.1413 L1 loss: 0.0000e+00 L2 loss: 1.09183 Learning rate: 0.02 Mask loss: 0.17124 RPN box loss: 0.02363 RPN score loss: 0.00165 RPN total loss: 0.02528 Total loss: 1.42964 timestamp: 1654931722.4433823 iteration: 20730 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12474 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 1.09165 Learning rate: 0.02 Mask loss: 0.14712 RPN box loss: 0.03149 RPN score loss: 0.00487 RPN total loss: 0.03637 Total loss: 1.45514 timestamp: 1654931725.6554842 iteration: 20735 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12878 FastRCNN class loss: 0.08876 FastRCNN total loss: 0.21754 L1 loss: 0.0000e+00 L2 loss: 1.09148 Learning rate: 0.02 Mask loss: 0.11024 RPN box loss: 0.02352 RPN score loss: 0.0047 RPN total loss: 0.02822 Total loss: 1.44748 timestamp: 1654931728.951646 iteration: 20740 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08358 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.13834 L1 loss: 0.0000e+00 L2 loss: 1.0913 Learning rate: 0.02 Mask loss: 0.11167 RPN box loss: 0.00746 RPN score loss: 0.008 RPN total loss: 0.01545 Total loss: 1.35676 timestamp: 1654931732.1787171 iteration: 20745 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1437 FastRCNN class loss: 0.09539 FastRCNN total loss: 0.23909 L1 loss: 0.0000e+00 L2 loss: 1.09113 Learning rate: 0.02 Mask loss: 0.17244 RPN box loss: 0.01407 RPN score loss: 0.00628 RPN total loss: 0.02035 Total loss: 1.523 timestamp: 1654931735.4032817 iteration: 20750 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20517 FastRCNN class loss: 0.15542 FastRCNN total loss: 0.36059 L1 loss: 0.0000e+00 L2 loss: 1.09095 Learning rate: 0.02 Mask loss: 0.1663 RPN box loss: 0.02931 RPN score loss: 0.01577 RPN total loss: 0.04508 Total loss: 1.66292 timestamp: 1654931738.560886 iteration: 20755 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.11708 FastRCNN total loss: 0.22706 L1 loss: 0.0000e+00 L2 loss: 1.09076 Learning rate: 0.02 Mask loss: 0.14355 RPN box loss: 0.02815 RPN score loss: 0.00589 RPN total loss: 0.03404 Total loss: 1.49542 timestamp: 1654931741.718656 iteration: 20760 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13968 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.21911 L1 loss: 0.0000e+00 L2 loss: 1.09059 Learning rate: 0.02 Mask loss: 0.15053 RPN box loss: 0.02796 RPN score loss: 0.00398 RPN total loss: 0.03194 Total loss: 1.49217 timestamp: 1654931744.9285088 iteration: 20765 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27059 FastRCNN class loss: 0.10037 FastRCNN total loss: 0.37096 L1 loss: 0.0000e+00 L2 loss: 1.09041 Learning rate: 0.02 Mask loss: 0.20866 RPN box loss: 0.0394 RPN score loss: 0.00309 RPN total loss: 0.04249 Total loss: 1.71252 timestamp: 1654931748.1577518 iteration: 20770 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19232 FastRCNN class loss: 0.09132 FastRCNN total loss: 0.28364 L1 loss: 0.0000e+00 L2 loss: 1.09021 Learning rate: 0.02 Mask loss: 0.16461 RPN box loss: 0.04098 RPN score loss: 0.0067 RPN total loss: 0.04768 Total loss: 1.58614 timestamp: 1654931751.352264 iteration: 20775 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08369 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.15503 L1 loss: 0.0000e+00 L2 loss: 1.09005 Learning rate: 0.02 Mask loss: 0.12556 RPN box loss: 0.03651 RPN score loss: 0.00495 RPN total loss: 0.04146 Total loss: 1.4121 timestamp: 1654931754.5758731 iteration: 20780 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.078 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.13087 L1 loss: 0.0000e+00 L2 loss: 1.08987 Learning rate: 0.02 Mask loss: 0.18556 RPN box loss: 0.01025 RPN score loss: 0.00302 RPN total loss: 0.01326 Total loss: 1.41956 timestamp: 1654931757.8453033 iteration: 20785 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16642 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.24693 L1 loss: 0.0000e+00 L2 loss: 1.0897 Learning rate: 0.02 Mask loss: 0.18047 RPN box loss: 0.02864 RPN score loss: 0.01383 RPN total loss: 0.04246 Total loss: 1.55956 timestamp: 1654931761.0220768 iteration: 20790 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11698 FastRCNN class loss: 0.09994 FastRCNN total loss: 0.21691 L1 loss: 0.0000e+00 L2 loss: 1.08953 Learning rate: 0.02 Mask loss: 0.12038 RPN box loss: 0.02539 RPN score loss: 0.00733 RPN total loss: 0.03273 Total loss: 1.45955 timestamp: 1654931764.235663 iteration: 20795 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.16581 L1 loss: 0.0000e+00 L2 loss: 1.08937 Learning rate: 0.02 Mask loss: 0.1623 RPN box loss: 0.02888 RPN score loss: 0.00514 RPN total loss: 0.03402 Total loss: 1.4515 timestamp: 1654931767.361573 iteration: 20800 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26988 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.3372 L1 loss: 0.0000e+00 L2 loss: 1.08918 Learning rate: 0.02 Mask loss: 0.16438 RPN box loss: 0.02621 RPN score loss: 0.00433 RPN total loss: 0.03054 Total loss: 1.6213 timestamp: 1654931770.5796096 iteration: 20805 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12611 FastRCNN class loss: 0.09186 FastRCNN total loss: 0.21797 L1 loss: 0.0000e+00 L2 loss: 1.08901 Learning rate: 0.02 Mask loss: 0.16757 RPN box loss: 0.05451 RPN score loss: 0.00712 RPN total loss: 0.06162 Total loss: 1.53618 timestamp: 1654931773.9096742 iteration: 20810 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1215 FastRCNN class loss: 0.03812 FastRCNN total loss: 0.15962 L1 loss: 0.0000e+00 L2 loss: 1.08883 Learning rate: 0.02 Mask loss: 0.15586 RPN box loss: 0.00522 RPN score loss: 0.00121 RPN total loss: 0.00643 Total loss: 1.41075 timestamp: 1654931777.1138184 iteration: 20815 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11868 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.20321 L1 loss: 0.0000e+00 L2 loss: 1.08863 Learning rate: 0.02 Mask loss: 0.20135 RPN box loss: 0.05164 RPN score loss: 0.01155 RPN total loss: 0.06319 Total loss: 1.55638 timestamp: 1654931780.3145075 iteration: 20820 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17991 FastRCNN class loss: 0.12963 FastRCNN total loss: 0.30954 L1 loss: 0.0000e+00 L2 loss: 1.08843 Learning rate: 0.02 Mask loss: 0.18491 RPN box loss: 0.01422 RPN score loss: 0.00546 RPN total loss: 0.01968 Total loss: 1.60256 timestamp: 1654931783.5009563 iteration: 20825 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16792 FastRCNN class loss: 0.09454 FastRCNN total loss: 0.26246 L1 loss: 0.0000e+00 L2 loss: 1.08828 Learning rate: 0.02 Mask loss: 0.22033 RPN box loss: 0.02564 RPN score loss: 0.0074 RPN total loss: 0.03304 Total loss: 1.60411 timestamp: 1654931786.7378068 iteration: 20830 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16062 FastRCNN class loss: 0.12375 FastRCNN total loss: 0.28437 L1 loss: 0.0000e+00 L2 loss: 1.08809 Learning rate: 0.02 Mask loss: 0.157 RPN box loss: 0.0231 RPN score loss: 0.00672 RPN total loss: 0.02983 Total loss: 1.55928 timestamp: 1654931789.9950366 iteration: 20835 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09044 FastRCNN class loss: 0.11951 FastRCNN total loss: 0.20994 L1 loss: 0.0000e+00 L2 loss: 1.08791 Learning rate: 0.02 Mask loss: 0.11393 RPN box loss: 0.03018 RPN score loss: 0.00885 RPN total loss: 0.03903 Total loss: 1.45081 timestamp: 1654931793.1756704 iteration: 20840 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16531 FastRCNN class loss: 0.08122 FastRCNN total loss: 0.24654 L1 loss: 0.0000e+00 L2 loss: 1.08774 Learning rate: 0.02 Mask loss: 0.14925 RPN box loss: 0.02046 RPN score loss: 0.00603 RPN total loss: 0.02649 Total loss: 1.51002 timestamp: 1654931796.3675063 iteration: 20845 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10633 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.18999 L1 loss: 0.0000e+00 L2 loss: 1.08758 Learning rate: 0.02 Mask loss: 0.12296 RPN box loss: 0.01513 RPN score loss: 0.00411 RPN total loss: 0.01924 Total loss: 1.41976 timestamp: 1654931799.5477238 iteration: 20850 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.07614 FastRCNN total loss: 0.17707 L1 loss: 0.0000e+00 L2 loss: 1.08739 Learning rate: 0.02 Mask loss: 0.10999 RPN box loss: 0.04556 RPN score loss: 0.00501 RPN total loss: 0.05057 Total loss: 1.42503 timestamp: 1654931802.760846 iteration: 20855 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12432 FastRCNN class loss: 0.08647 FastRCNN total loss: 0.2108 L1 loss: 0.0000e+00 L2 loss: 1.08722 Learning rate: 0.02 Mask loss: 0.12694 RPN box loss: 0.0286 RPN score loss: 0.0062 RPN total loss: 0.03481 Total loss: 1.45976 timestamp: 1654931806.0027704 iteration: 20860 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11836 FastRCNN class loss: 0.11853 FastRCNN total loss: 0.23689 L1 loss: 0.0000e+00 L2 loss: 1.08703 Learning rate: 0.02 Mask loss: 0.16425 RPN box loss: 0.03711 RPN score loss: 0.0081 RPN total loss: 0.04521 Total loss: 1.53339 timestamp: 1654931809.169539 iteration: 20865 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1251 FastRCNN class loss: 0.07972 FastRCNN total loss: 0.20481 L1 loss: 0.0000e+00 L2 loss: 1.08686 Learning rate: 0.02 Mask loss: 0.16158 RPN box loss: 0.03778 RPN score loss: 0.00431 RPN total loss: 0.04209 Total loss: 1.49534 timestamp: 1654931812.3930793 iteration: 20870 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16082 FastRCNN class loss: 0.11741 FastRCNN total loss: 0.27823 L1 loss: 0.0000e+00 L2 loss: 1.08669 Learning rate: 0.02 Mask loss: 0.16645 RPN box loss: 0.04644 RPN score loss: 0.0122 RPN total loss: 0.05865 Total loss: 1.59001 timestamp: 1654931815.5542722 iteration: 20875 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15998 FastRCNN class loss: 0.11551 FastRCNN total loss: 0.27549 L1 loss: 0.0000e+00 L2 loss: 1.08652 Learning rate: 0.02 Mask loss: 0.16464 RPN box loss: 0.02821 RPN score loss: 0.0133 RPN total loss: 0.04151 Total loss: 1.56816 timestamp: 1654931818.7669625 iteration: 20880 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21545 FastRCNN class loss: 0.11809 FastRCNN total loss: 0.33353 L1 loss: 0.0000e+00 L2 loss: 1.08633 Learning rate: 0.02 Mask loss: 0.28317 RPN box loss: 0.044 RPN score loss: 0.01353 RPN total loss: 0.05754 Total loss: 1.76057 timestamp: 1654931822.0105557 iteration: 20885 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16557 FastRCNN class loss: 0.10936 FastRCNN total loss: 0.27492 L1 loss: 0.0000e+00 L2 loss: 1.08613 Learning rate: 0.02 Mask loss: 0.1431 RPN box loss: 0.03236 RPN score loss: 0.01107 RPN total loss: 0.04343 Total loss: 1.54759 timestamp: 1654931825.1999443 iteration: 20890 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1541 FastRCNN class loss: 0.06885 FastRCNN total loss: 0.22295 L1 loss: 0.0000e+00 L2 loss: 1.08595 Learning rate: 0.02 Mask loss: 0.18688 RPN box loss: 0.03504 RPN score loss: 0.00939 RPN total loss: 0.04442 Total loss: 1.5402 timestamp: 1654931828.4530554 iteration: 20895 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11889 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.17178 L1 loss: 0.0000e+00 L2 loss: 1.08581 Learning rate: 0.02 Mask loss: 0.08885 RPN box loss: 0.04387 RPN score loss: 0.00291 RPN total loss: 0.04678 Total loss: 1.39321 timestamp: 1654931831.636919 iteration: 20900 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1207 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.19842 L1 loss: 0.0000e+00 L2 loss: 1.08563 Learning rate: 0.02 Mask loss: 0.23222 RPN box loss: 0.03389 RPN score loss: 0.02061 RPN total loss: 0.0545 Total loss: 1.57077 timestamp: 1654931834.7455103 iteration: 20905 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11612 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.16627 L1 loss: 0.0000e+00 L2 loss: 1.08543 Learning rate: 0.02 Mask loss: 0.09545 RPN box loss: 0.03382 RPN score loss: 0.00693 RPN total loss: 0.04075 Total loss: 1.38791 timestamp: 1654931837.9828439 iteration: 20910 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13528 FastRCNN class loss: 0.10519 FastRCNN total loss: 0.24047 L1 loss: 0.0000e+00 L2 loss: 1.08526 Learning rate: 0.02 Mask loss: 0.19119 RPN box loss: 0.04457 RPN score loss: 0.02056 RPN total loss: 0.06513 Total loss: 1.58205 timestamp: 1654931841.2486126 iteration: 20915 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10962 FastRCNN class loss: 0.08444 FastRCNN total loss: 0.19407 L1 loss: 0.0000e+00 L2 loss: 1.08506 Learning rate: 0.02 Mask loss: 0.10752 RPN box loss: 0.05596 RPN score loss: 0.0094 RPN total loss: 0.06537 Total loss: 1.45202 timestamp: 1654931844.4348116 iteration: 20920 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0586 FastRCNN class loss: 0.05617 FastRCNN total loss: 0.11477 L1 loss: 0.0000e+00 L2 loss: 1.08491 Learning rate: 0.02 Mask loss: 0.12825 RPN box loss: 0.02354 RPN score loss: 0.00974 RPN total loss: 0.03328 Total loss: 1.36121 timestamp: 1654931847.6319606 iteration: 20925 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07652 FastRCNN class loss: 0.05368 FastRCNN total loss: 0.13019 L1 loss: 0.0000e+00 L2 loss: 1.08476 Learning rate: 0.02 Mask loss: 0.13214 RPN box loss: 0.01115 RPN score loss: 0.00414 RPN total loss: 0.01528 Total loss: 1.36237 timestamp: 1654931850.8017259 iteration: 20930 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10483 FastRCNN class loss: 0.05068 FastRCNN total loss: 0.15551 L1 loss: 0.0000e+00 L2 loss: 1.08459 Learning rate: 0.02 Mask loss: 0.12722 RPN box loss: 0.02942 RPN score loss: 0.00854 RPN total loss: 0.03796 Total loss: 1.40528 timestamp: 1654931853.9495358 iteration: 20935 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26037 FastRCNN class loss: 0.11181 FastRCNN total loss: 0.37218 L1 loss: 0.0000e+00 L2 loss: 1.0844 Learning rate: 0.02 Mask loss: 0.24479 RPN box loss: 0.02246 RPN score loss: 0.00825 RPN total loss: 0.03072 Total loss: 1.73209 timestamp: 1654931857.1759038 iteration: 20940 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12701 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.20046 L1 loss: 0.0000e+00 L2 loss: 1.08421 Learning rate: 0.02 Mask loss: 0.11788 RPN box loss: 0.02795 RPN score loss: 0.00745 RPN total loss: 0.03539 Total loss: 1.43794 timestamp: 1654931860.3658988 iteration: 20945 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10723 FastRCNN class loss: 0.05397 FastRCNN total loss: 0.1612 L1 loss: 0.0000e+00 L2 loss: 1.084 Learning rate: 0.02 Mask loss: 0.14553 RPN box loss: 0.01965 RPN score loss: 0.00403 RPN total loss: 0.02368 Total loss: 1.41442 timestamp: 1654931863.5911725 iteration: 20950 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1525 FastRCNN class loss: 0.14747 FastRCNN total loss: 0.29997 L1 loss: 0.0000e+00 L2 loss: 1.08382 Learning rate: 0.02 Mask loss: 0.20437 RPN box loss: 0.03272 RPN score loss: 0.01272 RPN total loss: 0.04544 Total loss: 1.6336 timestamp: 1654931866.7675996 iteration: 20955 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15216 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.23748 L1 loss: 0.0000e+00 L2 loss: 1.08366 Learning rate: 0.02 Mask loss: 0.11914 RPN box loss: 0.05156 RPN score loss: 0.00962 RPN total loss: 0.06117 Total loss: 1.50145 timestamp: 1654931870.0605595 iteration: 20960 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18461 FastRCNN class loss: 0.12335 FastRCNN total loss: 0.30795 L1 loss: 0.0000e+00 L2 loss: 1.08348 Learning rate: 0.02 Mask loss: 0.1714 RPN box loss: 0.02191 RPN score loss: 0.00689 RPN total loss: 0.0288 Total loss: 1.59164 timestamp: 1654931873.2649593 iteration: 20965 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14448 FastRCNN class loss: 0.08005 FastRCNN total loss: 0.22452 L1 loss: 0.0000e+00 L2 loss: 1.08328 Learning rate: 0.02 Mask loss: 0.19483 RPN box loss: 0.05548 RPN score loss: 0.00525 RPN total loss: 0.06073 Total loss: 1.56337 timestamp: 1654931876.494981 iteration: 20970 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15065 FastRCNN class loss: 0.0808 FastRCNN total loss: 0.23145 L1 loss: 0.0000e+00 L2 loss: 1.0831 Learning rate: 0.02 Mask loss: 0.16289 RPN box loss: 0.03743 RPN score loss: 0.00996 RPN total loss: 0.04739 Total loss: 1.52483 timestamp: 1654931879.7858906 iteration: 20975 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15524 FastRCNN class loss: 0.1139 FastRCNN total loss: 0.26914 L1 loss: 0.0000e+00 L2 loss: 1.08292 Learning rate: 0.02 Mask loss: 0.13049 RPN box loss: 0.04705 RPN score loss: 0.00376 RPN total loss: 0.0508 Total loss: 1.53335 timestamp: 1654931883.0140746 iteration: 20980 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13546 FastRCNN class loss: 0.09261 FastRCNN total loss: 0.22806 L1 loss: 0.0000e+00 L2 loss: 1.08272 Learning rate: 0.02 Mask loss: 0.13579 RPN box loss: 0.03445 RPN score loss: 0.00586 RPN total loss: 0.04031 Total loss: 1.48688 timestamp: 1654931886.101894 iteration: 20985 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04271 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.10419 L1 loss: 0.0000e+00 L2 loss: 1.08251 Learning rate: 0.02 Mask loss: 0.26156 RPN box loss: 0.00649 RPN score loss: 0.00532 RPN total loss: 0.01181 Total loss: 1.46008 timestamp: 1654931889.3094547 iteration: 20990 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13857 FastRCNN class loss: 0.10833 FastRCNN total loss: 0.2469 L1 loss: 0.0000e+00 L2 loss: 1.08236 Learning rate: 0.02 Mask loss: 0.14315 RPN box loss: 0.03411 RPN score loss: 0.00712 RPN total loss: 0.04122 Total loss: 1.51363 timestamp: 1654931892.5532813 iteration: 20995 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11302 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.18263 L1 loss: 0.0000e+00 L2 loss: 1.08218 Learning rate: 0.02 Mask loss: 0.15595 RPN box loss: 0.07575 RPN score loss: 0.01978 RPN total loss: 0.09553 Total loss: 1.51628 timestamp: 1654931895.7605712 iteration: 21000 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15449 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.21894 L1 loss: 0.0000e+00 L2 loss: 1.082 Learning rate: 0.02 Mask loss: 0.13644 RPN box loss: 0.02969 RPN score loss: 0.00836 RPN total loss: 0.03805 Total loss: 1.47544 timestamp: 1654931898.983083 iteration: 21005 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09598 FastRCNN class loss: 0.03499 FastRCNN total loss: 0.13097 L1 loss: 0.0000e+00 L2 loss: 1.08183 Learning rate: 0.02 Mask loss: 0.15056 RPN box loss: 0.0586 RPN score loss: 0.00465 RPN total loss: 0.06325 Total loss: 1.42662 timestamp: 1654931902.2218714 iteration: 21010 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17672 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.25104 L1 loss: 0.0000e+00 L2 loss: 1.08166 Learning rate: 0.02 Mask loss: 0.15979 RPN box loss: 0.03862 RPN score loss: 0.00421 RPN total loss: 0.04283 Total loss: 1.53532 timestamp: 1654931905.5220945 iteration: 21015 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08078 FastRCNN class loss: 0.04494 FastRCNN total loss: 0.12572 L1 loss: 0.0000e+00 L2 loss: 1.08148 Learning rate: 0.02 Mask loss: 0.155 RPN box loss: 0.01639 RPN score loss: 0.00406 RPN total loss: 0.02045 Total loss: 1.38265 timestamp: 1654931908.7851713 iteration: 21020 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20094 FastRCNN class loss: 0.11898 FastRCNN total loss: 0.31992 L1 loss: 0.0000e+00 L2 loss: 1.08132 Learning rate: 0.02 Mask loss: 0.30235 RPN box loss: 0.03151 RPN score loss: 0.01432 RPN total loss: 0.04583 Total loss: 1.74942 timestamp: 1654931912.0208683 iteration: 21025 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12816 FastRCNN class loss: 0.0781 FastRCNN total loss: 0.20626 L1 loss: 0.0000e+00 L2 loss: 1.08114 Learning rate: 0.02 Mask loss: 0.10432 RPN box loss: 0.03808 RPN score loss: 0.00496 RPN total loss: 0.04304 Total loss: 1.43477 timestamp: 1654931915.2310622 iteration: 21030 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12549 FastRCNN class loss: 0.09836 FastRCNN total loss: 0.22384 L1 loss: 0.0000e+00 L2 loss: 1.08095 Learning rate: 0.02 Mask loss: 0.17857 RPN box loss: 0.11105 RPN score loss: 0.01444 RPN total loss: 0.12549 Total loss: 1.60886 timestamp: 1654931918.4284725 iteration: 21035 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12198 FastRCNN class loss: 0.10797 FastRCNN total loss: 0.22996 L1 loss: 0.0000e+00 L2 loss: 1.08077 Learning rate: 0.02 Mask loss: 0.15322 RPN box loss: 0.04469 RPN score loss: 0.00861 RPN total loss: 0.05329 Total loss: 1.51724 timestamp: 1654931921.6568427 iteration: 21040 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23596 FastRCNN class loss: 0.11362 FastRCNN total loss: 0.34958 L1 loss: 0.0000e+00 L2 loss: 1.08062 Learning rate: 0.02 Mask loss: 0.23692 RPN box loss: 0.06051 RPN score loss: 0.00822 RPN total loss: 0.06873 Total loss: 1.73584 timestamp: 1654931924.8201098 iteration: 21045 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14019 FastRCNN class loss: 0.05667 FastRCNN total loss: 0.19686 L1 loss: 0.0000e+00 L2 loss: 1.08042 Learning rate: 0.02 Mask loss: 0.13027 RPN box loss: 0.026 RPN score loss: 0.00772 RPN total loss: 0.03373 Total loss: 1.44127 timestamp: 1654931928.0517237 iteration: 21050 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13528 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.21694 L1 loss: 0.0000e+00 L2 loss: 1.08024 Learning rate: 0.02 Mask loss: 0.14684 RPN box loss: 0.06892 RPN score loss: 0.01014 RPN total loss: 0.07906 Total loss: 1.52307 timestamp: 1654931931.2371142 iteration: 21055 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10462 FastRCNN class loss: 0.05446 FastRCNN total loss: 0.15908 L1 loss: 0.0000e+00 L2 loss: 1.08009 Learning rate: 0.02 Mask loss: 0.10482 RPN box loss: 0.01419 RPN score loss: 0.0068 RPN total loss: 0.02099 Total loss: 1.36498 timestamp: 1654931934.4574203 iteration: 21060 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13996 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.22717 L1 loss: 0.0000e+00 L2 loss: 1.07991 Learning rate: 0.02 Mask loss: 0.13552 RPN box loss: 0.02217 RPN score loss: 0.00693 RPN total loss: 0.0291 Total loss: 1.47169 timestamp: 1654931937.6578343 iteration: 21065 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15704 FastRCNN class loss: 0.07068 FastRCNN total loss: 0.22772 L1 loss: 0.0000e+00 L2 loss: 1.07974 Learning rate: 0.02 Mask loss: 0.14367 RPN box loss: 0.04578 RPN score loss: 0.00696 RPN total loss: 0.05274 Total loss: 1.50387 timestamp: 1654931940.8695283 iteration: 21070 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15559 FastRCNN class loss: 0.09657 FastRCNN total loss: 0.25216 L1 loss: 0.0000e+00 L2 loss: 1.07957 Learning rate: 0.02 Mask loss: 0.1672 RPN box loss: 0.04671 RPN score loss: 0.00707 RPN total loss: 0.05378 Total loss: 1.55271 timestamp: 1654931944.1160247 iteration: 21075 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16015 FastRCNN class loss: 0.06595 FastRCNN total loss: 0.2261 L1 loss: 0.0000e+00 L2 loss: 1.07939 Learning rate: 0.02 Mask loss: 0.14892 RPN box loss: 0.02931 RPN score loss: 0.00346 RPN total loss: 0.03277 Total loss: 1.48718 timestamp: 1654931947.3440073 iteration: 21080 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10528 FastRCNN class loss: 0.04518 FastRCNN total loss: 0.15046 L1 loss: 0.0000e+00 L2 loss: 1.07921 Learning rate: 0.02 Mask loss: 0.1233 RPN box loss: 0.02098 RPN score loss: 0.0062 RPN total loss: 0.02717 Total loss: 1.38016 timestamp: 1654931950.5324216 iteration: 21085 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20096 FastRCNN class loss: 0.09868 FastRCNN total loss: 0.29964 L1 loss: 0.0000e+00 L2 loss: 1.07902 Learning rate: 0.02 Mask loss: 0.20922 RPN box loss: 0.00912 RPN score loss: 0.00592 RPN total loss: 0.01504 Total loss: 1.60293 timestamp: 1654931953.7690518 iteration: 21090 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18172 FastRCNN class loss: 0.085 FastRCNN total loss: 0.26672 L1 loss: 0.0000e+00 L2 loss: 1.07887 Learning rate: 0.02 Mask loss: 0.15747 RPN box loss: 0.02004 RPN score loss: 0.00283 RPN total loss: 0.02287 Total loss: 1.52592 timestamp: 1654931956.9738731 iteration: 21095 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12031 FastRCNN class loss: 0.09338 FastRCNN total loss: 0.21369 L1 loss: 0.0000e+00 L2 loss: 1.07869 Learning rate: 0.02 Mask loss: 0.1772 RPN box loss: 0.07026 RPN score loss: 0.00573 RPN total loss: 0.07599 Total loss: 1.54557 timestamp: 1654931960.1873336 iteration: 21100 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18015 FastRCNN class loss: 0.05956 FastRCNN total loss: 0.23971 L1 loss: 0.0000e+00 L2 loss: 1.07849 Learning rate: 0.02 Mask loss: 0.20939 RPN box loss: 0.0492 RPN score loss: 0.01135 RPN total loss: 0.06056 Total loss: 1.58815 timestamp: 1654931963.414936 iteration: 21105 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10721 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 1.07835 Learning rate: 0.02 Mask loss: 0.16267 RPN box loss: 0.03293 RPN score loss: 0.00254 RPN total loss: 0.03547 Total loss: 1.43865 timestamp: 1654931966.5708103 iteration: 21110 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20791 FastRCNN class loss: 0.10554 FastRCNN total loss: 0.31345 L1 loss: 0.0000e+00 L2 loss: 1.07819 Learning rate: 0.02 Mask loss: 0.19361 RPN box loss: 0.02301 RPN score loss: 0.01471 RPN total loss: 0.03772 Total loss: 1.62296 timestamp: 1654931969.8084018 iteration: 21115 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18437 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.28473 L1 loss: 0.0000e+00 L2 loss: 1.078 Learning rate: 0.02 Mask loss: 0.14812 RPN box loss: 0.06076 RPN score loss: 0.0036 RPN total loss: 0.06436 Total loss: 1.57522 timestamp: 1654931973.0805147 iteration: 21120 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11711 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.20157 L1 loss: 0.0000e+00 L2 loss: 1.07784 Learning rate: 0.02 Mask loss: 0.11557 RPN box loss: 0.04223 RPN score loss: 0.00393 RPN total loss: 0.04617 Total loss: 1.44115 timestamp: 1654931976.2659829 iteration: 21125 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.18134 L1 loss: 0.0000e+00 L2 loss: 1.07768 Learning rate: 0.02 Mask loss: 0.15332 RPN box loss: 0.07065 RPN score loss: 0.01152 RPN total loss: 0.08217 Total loss: 1.49452 timestamp: 1654931979.4397242 iteration: 21130 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14549 FastRCNN class loss: 0.03546 FastRCNN total loss: 0.18095 L1 loss: 0.0000e+00 L2 loss: 1.07751 Learning rate: 0.02 Mask loss: 0.11077 RPN box loss: 0.00728 RPN score loss: 0.00532 RPN total loss: 0.01261 Total loss: 1.38184 timestamp: 1654931982.6073563 iteration: 21135 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13516 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.20393 L1 loss: 0.0000e+00 L2 loss: 1.07734 Learning rate: 0.02 Mask loss: 0.17242 RPN box loss: 0.0213 RPN score loss: 0.00389 RPN total loss: 0.02519 Total loss: 1.47888 timestamp: 1654931985.7648327 iteration: 21140 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.04527 FastRCNN total loss: 0.14098 L1 loss: 0.0000e+00 L2 loss: 1.07714 Learning rate: 0.02 Mask loss: 0.10323 RPN box loss: 0.00475 RPN score loss: 0.00334 RPN total loss: 0.00809 Total loss: 1.32944 timestamp: 1654931988.9789684 iteration: 21145 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1348 FastRCNN class loss: 0.07451 FastRCNN total loss: 0.2093 L1 loss: 0.0000e+00 L2 loss: 1.07698 Learning rate: 0.02 Mask loss: 0.09681 RPN box loss: 0.05564 RPN score loss: 0.00341 RPN total loss: 0.05905 Total loss: 1.44215 timestamp: 1654931992.2331302 iteration: 21150 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17072 FastRCNN class loss: 0.11178 FastRCNN total loss: 0.2825 L1 loss: 0.0000e+00 L2 loss: 1.0768 Learning rate: 0.02 Mask loss: 0.19194 RPN box loss: 0.0259 RPN score loss: 0.00625 RPN total loss: 0.03214 Total loss: 1.58339 timestamp: 1654931995.3407016 iteration: 21155 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17485 FastRCNN class loss: 0.05508 FastRCNN total loss: 0.22993 L1 loss: 0.0000e+00 L2 loss: 1.07662 Learning rate: 0.02 Mask loss: 0.14577 RPN box loss: 0.02772 RPN score loss: 0.00634 RPN total loss: 0.03406 Total loss: 1.48637 timestamp: 1654931998.5092607 iteration: 21160 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12248 FastRCNN class loss: 0.04998 FastRCNN total loss: 0.17246 L1 loss: 0.0000e+00 L2 loss: 1.07646 Learning rate: 0.02 Mask loss: 0.11346 RPN box loss: 0.02475 RPN score loss: 0.00402 RPN total loss: 0.02877 Total loss: 1.39115 timestamp: 1654932001.6785822 iteration: 21165 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15925 FastRCNN class loss: 0.07074 FastRCNN total loss: 0.22999 L1 loss: 0.0000e+00 L2 loss: 1.07628 Learning rate: 0.02 Mask loss: 0.15891 RPN box loss: 0.01297 RPN score loss: 0.0032 RPN total loss: 0.01617 Total loss: 1.48134 timestamp: 1654932004.9145267 iteration: 21170 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10057 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.17963 L1 loss: 0.0000e+00 L2 loss: 1.07612 Learning rate: 0.02 Mask loss: 0.16662 RPN box loss: 0.03211 RPN score loss: 0.00464 RPN total loss: 0.03675 Total loss: 1.45912 timestamp: 1654932008.072363 iteration: 21175 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.219 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.31162 L1 loss: 0.0000e+00 L2 loss: 1.07595 Learning rate: 0.02 Mask loss: 0.17425 RPN box loss: 0.01762 RPN score loss: 0.00564 RPN total loss: 0.02326 Total loss: 1.58508 timestamp: 1654932011.3563662 iteration: 21180 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13763 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.22789 L1 loss: 0.0000e+00 L2 loss: 1.07576 Learning rate: 0.02 Mask loss: 0.17467 RPN box loss: 0.06846 RPN score loss: 0.01163 RPN total loss: 0.08008 Total loss: 1.5584 timestamp: 1654932014.4885623 iteration: 21185 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12362 FastRCNN class loss: 0.09502 FastRCNN total loss: 0.21865 L1 loss: 0.0000e+00 L2 loss: 1.07559 Learning rate: 0.02 Mask loss: 0.19692 RPN box loss: 0.03846 RPN score loss: 0.01209 RPN total loss: 0.05055 Total loss: 1.54171 timestamp: 1654932017.6727734 iteration: 21190 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1631 FastRCNN class loss: 0.09403 FastRCNN total loss: 0.25713 L1 loss: 0.0000e+00 L2 loss: 1.07541 Learning rate: 0.02 Mask loss: 0.11305 RPN box loss: 0.01672 RPN score loss: 0.00778 RPN total loss: 0.0245 Total loss: 1.4701 timestamp: 1654932020.8766809 iteration: 21195 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16412 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.22399 L1 loss: 0.0000e+00 L2 loss: 1.07524 Learning rate: 0.02 Mask loss: 0.13913 RPN box loss: 0.04437 RPN score loss: 0.00396 RPN total loss: 0.04833 Total loss: 1.4867 timestamp: 1654932024.0272722 iteration: 21200 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.18514 L1 loss: 0.0000e+00 L2 loss: 1.07507 Learning rate: 0.02 Mask loss: 0.12149 RPN box loss: 0.01567 RPN score loss: 0.0023 RPN total loss: 0.01797 Total loss: 1.39967 timestamp: 1654932027.1973836 iteration: 21205 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11364 FastRCNN class loss: 0.10797 FastRCNN total loss: 0.22161 L1 loss: 0.0000e+00 L2 loss: 1.07489 Learning rate: 0.02 Mask loss: 0.24308 RPN box loss: 0.04657 RPN score loss: 0.0124 RPN total loss: 0.05897 Total loss: 1.59854 timestamp: 1654932030.3250556 iteration: 21210 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.089 FastRCNN class loss: 0.04461 FastRCNN total loss: 0.13361 L1 loss: 0.0000e+00 L2 loss: 1.07471 Learning rate: 0.02 Mask loss: 0.11933 RPN box loss: 0.04907 RPN score loss: 0.00639 RPN total loss: 0.05546 Total loss: 1.38311 timestamp: 1654932033.5574706 iteration: 21215 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09369 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.16988 L1 loss: 0.0000e+00 L2 loss: 1.07452 Learning rate: 0.02 Mask loss: 0.14974 RPN box loss: 0.04063 RPN score loss: 0.00666 RPN total loss: 0.04729 Total loss: 1.44143 timestamp: 1654932036.8016477 iteration: 21220 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15502 FastRCNN class loss: 0.08134 FastRCNN total loss: 0.23636 L1 loss: 0.0000e+00 L2 loss: 1.07437 Learning rate: 0.02 Mask loss: 0.17493 RPN box loss: 0.03659 RPN score loss: 0.00822 RPN total loss: 0.04481 Total loss: 1.53046 timestamp: 1654932039.9974034 iteration: 21225 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15283 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.21142 L1 loss: 0.0000e+00 L2 loss: 1.0742 Learning rate: 0.02 Mask loss: 0.13553 RPN box loss: 0.01162 RPN score loss: 0.00269 RPN total loss: 0.01431 Total loss: 1.43545 timestamp: 1654932043.2363486 iteration: 21230 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12837 FastRCNN class loss: 0.08438 FastRCNN total loss: 0.21275 L1 loss: 0.0000e+00 L2 loss: 1.07403 Learning rate: 0.02 Mask loss: 0.15667 RPN box loss: 0.02342 RPN score loss: 0.00531 RPN total loss: 0.02873 Total loss: 1.47218 timestamp: 1654932046.4808912 iteration: 21235 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16722 FastRCNN class loss: 0.11453 FastRCNN total loss: 0.28176 L1 loss: 0.0000e+00 L2 loss: 1.07386 Learning rate: 0.02 Mask loss: 0.22598 RPN box loss: 0.01349 RPN score loss: 0.00843 RPN total loss: 0.02191 Total loss: 1.60352 timestamp: 1654932049.7378235 iteration: 21240 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17656 FastRCNN class loss: 0.10808 FastRCNN total loss: 0.28464 L1 loss: 0.0000e+00 L2 loss: 1.07368 Learning rate: 0.02 Mask loss: 0.24296 RPN box loss: 0.0451 RPN score loss: 0.00936 RPN total loss: 0.05446 Total loss: 1.65574 timestamp: 1654932052.965013 iteration: 21245 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15752 FastRCNN class loss: 0.10114 FastRCNN total loss: 0.25866 L1 loss: 0.0000e+00 L2 loss: 1.0735 Learning rate: 0.02 Mask loss: 0.16088 RPN box loss: 0.0572 RPN score loss: 0.00756 RPN total loss: 0.06476 Total loss: 1.55781 timestamp: 1654932056.1962204 iteration: 21250 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14055 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.20614 L1 loss: 0.0000e+00 L2 loss: 1.07332 Learning rate: 0.02 Mask loss: 0.15397 RPN box loss: 0.02054 RPN score loss: 0.003 RPN total loss: 0.02354 Total loss: 1.45697 timestamp: 1654932059.4082398 iteration: 21255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14871 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.22059 L1 loss: 0.0000e+00 L2 loss: 1.07313 Learning rate: 0.02 Mask loss: 0.13844 RPN box loss: 0.05817 RPN score loss: 0.00735 RPN total loss: 0.06552 Total loss: 1.49768 timestamp: 1654932062.5186002 iteration: 21260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18494 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.27824 L1 loss: 0.0000e+00 L2 loss: 1.07297 Learning rate: 0.02 Mask loss: 0.18223 RPN box loss: 0.01908 RPN score loss: 0.00579 RPN total loss: 0.02488 Total loss: 1.55832 timestamp: 1654932065.7127693 iteration: 21265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16258 FastRCNN class loss: 0.11268 FastRCNN total loss: 0.27527 L1 loss: 0.0000e+00 L2 loss: 1.0728 Learning rate: 0.02 Mask loss: 0.14628 RPN box loss: 0.0447 RPN score loss: 0.00282 RPN total loss: 0.04752 Total loss: 1.54186 timestamp: 1654932068.9396818 iteration: 21270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06934 FastRCNN class loss: 0.05634 FastRCNN total loss: 0.12568 L1 loss: 0.0000e+00 L2 loss: 1.07263 Learning rate: 0.02 Mask loss: 0.09074 RPN box loss: 0.00767 RPN score loss: 0.00408 RPN total loss: 0.01175 Total loss: 1.3008 timestamp: 1654932072.0604324 iteration: 21275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16694 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.25228 L1 loss: 0.0000e+00 L2 loss: 1.07246 Learning rate: 0.02 Mask loss: 0.12542 RPN box loss: 0.03578 RPN score loss: 0.00443 RPN total loss: 0.04021 Total loss: 1.49037 timestamp: 1654932075.2755866 iteration: 21280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13762 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.21315 L1 loss: 0.0000e+00 L2 loss: 1.07228 Learning rate: 0.02 Mask loss: 0.17967 RPN box loss: 0.05117 RPN score loss: 0.00267 RPN total loss: 0.05384 Total loss: 1.51894 timestamp: 1654932078.4721718 iteration: 21285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12104 FastRCNN class loss: 0.06544 FastRCNN total loss: 0.18648 L1 loss: 0.0000e+00 L2 loss: 1.07212 Learning rate: 0.02 Mask loss: 0.17585 RPN box loss: 0.011 RPN score loss: 0.00339 RPN total loss: 0.01439 Total loss: 1.44884 timestamp: 1654932081.658449 iteration: 21290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12115 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.18712 L1 loss: 0.0000e+00 L2 loss: 1.07194 Learning rate: 0.02 Mask loss: 0.17703 RPN box loss: 0.01041 RPN score loss: 0.00226 RPN total loss: 0.01267 Total loss: 1.44876 timestamp: 1654932084.8508868 iteration: 21295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18987 FastRCNN class loss: 0.10177 FastRCNN total loss: 0.29163 L1 loss: 0.0000e+00 L2 loss: 1.07176 Learning rate: 0.02 Mask loss: 0.13853 RPN box loss: 0.01296 RPN score loss: 0.00451 RPN total loss: 0.01747 Total loss: 1.51939 timestamp: 1654932088.0480244 iteration: 21300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19144 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.2722 L1 loss: 0.0000e+00 L2 loss: 1.07158 Learning rate: 0.02 Mask loss: 0.11212 RPN box loss: 0.01473 RPN score loss: 0.00659 RPN total loss: 0.02132 Total loss: 1.47722 timestamp: 1654932091.2045166 iteration: 21305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11563 FastRCNN class loss: 0.049 FastRCNN total loss: 0.16463 L1 loss: 0.0000e+00 L2 loss: 1.0714 Learning rate: 0.02 Mask loss: 0.10506 RPN box loss: 0.02656 RPN score loss: 0.0023 RPN total loss: 0.02886 Total loss: 1.36995 timestamp: 1654932094.354367 iteration: 21310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12517 FastRCNN class loss: 0.07388 FastRCNN total loss: 0.19905 L1 loss: 0.0000e+00 L2 loss: 1.07122 Learning rate: 0.02 Mask loss: 0.13452 RPN box loss: 0.03136 RPN score loss: 0.00883 RPN total loss: 0.04019 Total loss: 1.44497 timestamp: 1654932097.5430155 iteration: 21315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19097 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.2819 L1 loss: 0.0000e+00 L2 loss: 1.07104 Learning rate: 0.02 Mask loss: 0.16389 RPN box loss: 0.04657 RPN score loss: 0.0103 RPN total loss: 0.05687 Total loss: 1.5737 timestamp: 1654932100.7573571 iteration: 21320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08582 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.15806 L1 loss: 0.0000e+00 L2 loss: 1.07086 Learning rate: 0.02 Mask loss: 0.09896 RPN box loss: 0.01386 RPN score loss: 0.00456 RPN total loss: 0.01842 Total loss: 1.3463 timestamp: 1654932104.043052 iteration: 21325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18127 FastRCNN class loss: 0.11829 FastRCNN total loss: 0.29956 L1 loss: 0.0000e+00 L2 loss: 1.07067 Learning rate: 0.02 Mask loss: 0.26277 RPN box loss: 0.06859 RPN score loss: 0.00783 RPN total loss: 0.07642 Total loss: 1.70942 timestamp: 1654932107.1791718 iteration: 21330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16027 FastRCNN class loss: 0.16954 FastRCNN total loss: 0.32982 L1 loss: 0.0000e+00 L2 loss: 1.07051 Learning rate: 0.02 Mask loss: 0.20018 RPN box loss: 0.02779 RPN score loss: 0.00402 RPN total loss: 0.03181 Total loss: 1.63231 timestamp: 1654932110.3338718 iteration: 21335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0875 FastRCNN class loss: 0.0604 FastRCNN total loss: 0.14789 L1 loss: 0.0000e+00 L2 loss: 1.07033 Learning rate: 0.02 Mask loss: 0.12396 RPN box loss: 0.01121 RPN score loss: 0.00085 RPN total loss: 0.01206 Total loss: 1.35425 timestamp: 1654932113.5181613 iteration: 21340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09665 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.18268 L1 loss: 0.0000e+00 L2 loss: 1.07014 Learning rate: 0.02 Mask loss: 0.11187 RPN box loss: 0.02054 RPN score loss: 0.00551 RPN total loss: 0.02605 Total loss: 1.39074 timestamp: 1654932116.7597187 iteration: 21345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1674 FastRCNN class loss: 0.11268 FastRCNN total loss: 0.28009 L1 loss: 0.0000e+00 L2 loss: 1.06999 Learning rate: 0.02 Mask loss: 0.27631 RPN box loss: 0.03417 RPN score loss: 0.00821 RPN total loss: 0.04238 Total loss: 1.66877 timestamp: 1654932119.9174342 iteration: 21350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10002 FastRCNN class loss: 0.05794 FastRCNN total loss: 0.15796 L1 loss: 0.0000e+00 L2 loss: 1.06982 Learning rate: 0.02 Mask loss: 0.10616 RPN box loss: 0.03125 RPN score loss: 0.00532 RPN total loss: 0.03656 Total loss: 1.37051 timestamp: 1654932123.2033193 iteration: 21355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17874 FastRCNN class loss: 0.0655 FastRCNN total loss: 0.24424 L1 loss: 0.0000e+00 L2 loss: 1.06967 Learning rate: 0.02 Mask loss: 0.12184 RPN box loss: 0.02184 RPN score loss: 0.01017 RPN total loss: 0.03201 Total loss: 1.46776 timestamp: 1654932126.4704754 iteration: 21360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11835 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.21016 L1 loss: 0.0000e+00 L2 loss: 1.06951 Learning rate: 0.02 Mask loss: 0.13387 RPN box loss: 0.01856 RPN score loss: 0.00343 RPN total loss: 0.02198 Total loss: 1.43553 timestamp: 1654932129.6774971 iteration: 21365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10887 FastRCNN class loss: 0.0441 FastRCNN total loss: 0.15297 L1 loss: 0.0000e+00 L2 loss: 1.06934 Learning rate: 0.02 Mask loss: 0.10153 RPN box loss: 0.00982 RPN score loss: 0.006 RPN total loss: 0.01582 Total loss: 1.33966 timestamp: 1654932132.9597101 iteration: 21370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1317 FastRCNN class loss: 0.09001 FastRCNN total loss: 0.22171 L1 loss: 0.0000e+00 L2 loss: 1.06916 Learning rate: 0.02 Mask loss: 0.15571 RPN box loss: 0.01538 RPN score loss: 0.00294 RPN total loss: 0.01832 Total loss: 1.4649 timestamp: 1654932136.146727 iteration: 21375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16242 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.24278 L1 loss: 0.0000e+00 L2 loss: 1.06896 Learning rate: 0.02 Mask loss: 0.18244 RPN box loss: 0.023 RPN score loss: 0.00733 RPN total loss: 0.03032 Total loss: 1.5245 timestamp: 1654932139.3691301 iteration: 21380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13927 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.20815 L1 loss: 0.0000e+00 L2 loss: 1.06876 Learning rate: 0.02 Mask loss: 0.15594 RPN box loss: 0.03442 RPN score loss: 0.01387 RPN total loss: 0.04828 Total loss: 1.48114 timestamp: 1654932142.7081106 iteration: 21385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14905 FastRCNN class loss: 0.06342 FastRCNN total loss: 0.21246 L1 loss: 0.0000e+00 L2 loss: 1.06859 Learning rate: 0.02 Mask loss: 0.11428 RPN box loss: 0.00835 RPN score loss: 0.00377 RPN total loss: 0.01211 Total loss: 1.40744 timestamp: 1654932146.0067031 iteration: 21390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10469 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.17718 L1 loss: 0.0000e+00 L2 loss: 1.06844 Learning rate: 0.02 Mask loss: 0.14505 RPN box loss: 0.02024 RPN score loss: 0.00438 RPN total loss: 0.02462 Total loss: 1.41528 timestamp: 1654932149.161567 iteration: 21395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14333 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.23266 L1 loss: 0.0000e+00 L2 loss: 1.06827 Learning rate: 0.02 Mask loss: 0.15197 RPN box loss: 0.01361 RPN score loss: 0.00607 RPN total loss: 0.01969 Total loss: 1.47258 timestamp: 1654932152.3377728 iteration: 21400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16777 FastRCNN class loss: 0.06966 FastRCNN total loss: 0.23743 L1 loss: 0.0000e+00 L2 loss: 1.06812 Learning rate: 0.02 Mask loss: 0.1381 RPN box loss: 0.06241 RPN score loss: 0.00837 RPN total loss: 0.07078 Total loss: 1.51443 timestamp: 1654932155.6063132 iteration: 21405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12798 FastRCNN class loss: 0.1015 FastRCNN total loss: 0.22948 L1 loss: 0.0000e+00 L2 loss: 1.06796 Learning rate: 0.02 Mask loss: 0.19389 RPN box loss: 0.05978 RPN score loss: 0.01196 RPN total loss: 0.07174 Total loss: 1.56306 timestamp: 1654932158.7853644 iteration: 21410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1581 FastRCNN class loss: 0.10086 FastRCNN total loss: 0.25896 L1 loss: 0.0000e+00 L2 loss: 1.06778 Learning rate: 0.02 Mask loss: 0.123 RPN box loss: 0.01464 RPN score loss: 0.00864 RPN total loss: 0.02328 Total loss: 1.47302 timestamp: 1654932161.968144 iteration: 21415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14587 FastRCNN class loss: 0.13536 FastRCNN total loss: 0.28123 L1 loss: 0.0000e+00 L2 loss: 1.06762 Learning rate: 0.02 Mask loss: 0.16046 RPN box loss: 0.06412 RPN score loss: 0.00707 RPN total loss: 0.0712 Total loss: 1.58051 timestamp: 1654932165.1199033 iteration: 21420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12418 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.18341 L1 loss: 0.0000e+00 L2 loss: 1.06747 Learning rate: 0.02 Mask loss: 0.13199 RPN box loss: 0.01775 RPN score loss: 0.00213 RPN total loss: 0.01988 Total loss: 1.40275 timestamp: 1654932168.3317947 iteration: 21425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16976 FastRCNN class loss: 0.11229 FastRCNN total loss: 0.28205 L1 loss: 0.0000e+00 L2 loss: 1.06728 Learning rate: 0.02 Mask loss: 0.17977 RPN box loss: 0.05775 RPN score loss: 0.01976 RPN total loss: 0.07752 Total loss: 1.60662 timestamp: 1654932171.5199442 iteration: 21430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17707 FastRCNN class loss: 0.10846 FastRCNN total loss: 0.28553 L1 loss: 0.0000e+00 L2 loss: 1.06709 Learning rate: 0.02 Mask loss: 0.23541 RPN box loss: 0.02099 RPN score loss: 0.00544 RPN total loss: 0.02643 Total loss: 1.61446 timestamp: 1654932174.714087 iteration: 21435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17973 FastRCNN class loss: 0.08091 FastRCNN total loss: 0.26064 L1 loss: 0.0000e+00 L2 loss: 1.06691 Learning rate: 0.02 Mask loss: 0.15299 RPN box loss: 0.01679 RPN score loss: 0.0034 RPN total loss: 0.02019 Total loss: 1.50073 timestamp: 1654932177.9552941 iteration: 21440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1154 FastRCNN class loss: 0.07716 FastRCNN total loss: 0.19256 L1 loss: 0.0000e+00 L2 loss: 1.06676 Learning rate: 0.02 Mask loss: 0.13035 RPN box loss: 0.01858 RPN score loss: 0.00407 RPN total loss: 0.02265 Total loss: 1.41233 timestamp: 1654932181.1854112 iteration: 21445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14577 FastRCNN class loss: 0.09769 FastRCNN total loss: 0.24346 L1 loss: 0.0000e+00 L2 loss: 1.0666 Learning rate: 0.02 Mask loss: 0.17624 RPN box loss: 0.0208 RPN score loss: 0.00649 RPN total loss: 0.0273 Total loss: 1.5136 timestamp: 1654932184.3435512 iteration: 21450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09398 FastRCNN class loss: 0.078 FastRCNN total loss: 0.17199 L1 loss: 0.0000e+00 L2 loss: 1.06643 Learning rate: 0.02 Mask loss: 0.16288 RPN box loss: 0.02604 RPN score loss: 0.00703 RPN total loss: 0.03307 Total loss: 1.43436 timestamp: 1654932187.4688137 iteration: 21455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17507 FastRCNN class loss: 0.12968 FastRCNN total loss: 0.30475 L1 loss: 0.0000e+00 L2 loss: 1.06626 Learning rate: 0.02 Mask loss: 0.19342 RPN box loss: 0.02655 RPN score loss: 0.00978 RPN total loss: 0.03633 Total loss: 1.60076 timestamp: 1654932190.6665487 iteration: 21460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14231 FastRCNN class loss: 0.08254 FastRCNN total loss: 0.22484 L1 loss: 0.0000e+00 L2 loss: 1.06607 Learning rate: 0.02 Mask loss: 0.13844 RPN box loss: 0.03573 RPN score loss: 0.0049 RPN total loss: 0.04063 Total loss: 1.46999 timestamp: 1654932193.8478491 iteration: 21465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12739 FastRCNN class loss: 0.09516 FastRCNN total loss: 0.22255 L1 loss: 0.0000e+00 L2 loss: 1.06591 Learning rate: 0.02 Mask loss: 0.15041 RPN box loss: 0.0381 RPN score loss: 0.00855 RPN total loss: 0.04665 Total loss: 1.48553 timestamp: 1654932197.0859637 iteration: 21470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18417 FastRCNN class loss: 0.18056 FastRCNN total loss: 0.36473 L1 loss: 0.0000e+00 L2 loss: 1.06574 Learning rate: 0.02 Mask loss: 0.26372 RPN box loss: 0.03365 RPN score loss: 0.01465 RPN total loss: 0.0483 Total loss: 1.74249 timestamp: 1654932200.2972095 iteration: 21475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19137 FastRCNN class loss: 0.08826 FastRCNN total loss: 0.27962 L1 loss: 0.0000e+00 L2 loss: 1.06556 Learning rate: 0.02 Mask loss: 0.2084 RPN box loss: 0.01752 RPN score loss: 0.00527 RPN total loss: 0.02279 Total loss: 1.57638 timestamp: 1654932203.5134559 iteration: 21480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.07811 FastRCNN total loss: 0.18154 L1 loss: 0.0000e+00 L2 loss: 1.0654 Learning rate: 0.02 Mask loss: 0.12565 RPN box loss: 0.02751 RPN score loss: 0.00837 RPN total loss: 0.03588 Total loss: 1.40846 timestamp: 1654932206.690245 iteration: 21485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13676 FastRCNN class loss: 0.09142 FastRCNN total loss: 0.22818 L1 loss: 0.0000e+00 L2 loss: 1.06523 Learning rate: 0.02 Mask loss: 0.16544 RPN box loss: 0.04851 RPN score loss: 0.01006 RPN total loss: 0.05857 Total loss: 1.51742 timestamp: 1654932209.9090528 iteration: 21490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10863 FastRCNN class loss: 0.06913 FastRCNN total loss: 0.17777 L1 loss: 0.0000e+00 L2 loss: 1.06507 Learning rate: 0.02 Mask loss: 0.10216 RPN box loss: 0.04465 RPN score loss: 0.00246 RPN total loss: 0.04711 Total loss: 1.39211 timestamp: 1654932213.0930064 iteration: 21495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11262 FastRCNN class loss: 0.08886 FastRCNN total loss: 0.20148 L1 loss: 0.0000e+00 L2 loss: 1.06489 Learning rate: 0.02 Mask loss: 0.15048 RPN box loss: 0.02396 RPN score loss: 0.00762 RPN total loss: 0.03159 Total loss: 1.44844 timestamp: 1654932216.2790377 iteration: 21500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15397 FastRCNN class loss: 0.12187 FastRCNN total loss: 0.27584 L1 loss: 0.0000e+00 L2 loss: 1.06473 Learning rate: 0.02 Mask loss: 0.26578 RPN box loss: 0.04373 RPN score loss: 0.01373 RPN total loss: 0.05745 Total loss: 1.66381 timestamp: 1654932219.465036 iteration: 21505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06177 FastRCNN class loss: 0.04437 FastRCNN total loss: 0.10614 L1 loss: 0.0000e+00 L2 loss: 1.06456 Learning rate: 0.02 Mask loss: 0.14423 RPN box loss: 0.02649 RPN score loss: 0.00127 RPN total loss: 0.02776 Total loss: 1.3427 timestamp: 1654932222.6966288 iteration: 21510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13476 FastRCNN class loss: 0.09329 FastRCNN total loss: 0.22804 L1 loss: 0.0000e+00 L2 loss: 1.06437 Learning rate: 0.02 Mask loss: 0.18322 RPN box loss: 0.04804 RPN score loss: 0.0134 RPN total loss: 0.06144 Total loss: 1.53708 timestamp: 1654932225.9058316 iteration: 21515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17803 FastRCNN class loss: 0.07986 FastRCNN total loss: 0.25789 L1 loss: 0.0000e+00 L2 loss: 1.0642 Learning rate: 0.02 Mask loss: 0.12625 RPN box loss: 0.00904 RPN score loss: 0.0044 RPN total loss: 0.01344 Total loss: 1.46178 timestamp: 1654932229.127138 iteration: 21520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13014 FastRCNN class loss: 0.08951 FastRCNN total loss: 0.21965 L1 loss: 0.0000e+00 L2 loss: 1.06403 Learning rate: 0.02 Mask loss: 0.15963 RPN box loss: 0.04476 RPN score loss: 0.00735 RPN total loss: 0.0521 Total loss: 1.49541 timestamp: 1654932232.3399317 iteration: 21525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.16958 L1 loss: 0.0000e+00 L2 loss: 1.06386 Learning rate: 0.02 Mask loss: 0.19985 RPN box loss: 0.03097 RPN score loss: 0.00827 RPN total loss: 0.03924 Total loss: 1.47254 timestamp: 1654932235.4526517 iteration: 21530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12148 FastRCNN class loss: 0.07558 FastRCNN total loss: 0.19706 L1 loss: 0.0000e+00 L2 loss: 1.06367 Learning rate: 0.02 Mask loss: 0.14951 RPN box loss: 0.04526 RPN score loss: 0.00764 RPN total loss: 0.05291 Total loss: 1.46315 timestamp: 1654932238.6385877 iteration: 21535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10464 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.19583 L1 loss: 0.0000e+00 L2 loss: 1.06349 Learning rate: 0.02 Mask loss: 0.17336 RPN box loss: 0.02979 RPN score loss: 0.00569 RPN total loss: 0.03548 Total loss: 1.46817 timestamp: 1654932241.8311522 iteration: 21540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11968 FastRCNN class loss: 0.05435 FastRCNN total loss: 0.17403 L1 loss: 0.0000e+00 L2 loss: 1.06329 Learning rate: 0.02 Mask loss: 0.23789 RPN box loss: 0.01831 RPN score loss: 0.00625 RPN total loss: 0.02456 Total loss: 1.49977 timestamp: 1654932245.0523562 iteration: 21545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12729 FastRCNN class loss: 0.05245 FastRCNN total loss: 0.17975 L1 loss: 0.0000e+00 L2 loss: 1.06312 Learning rate: 0.02 Mask loss: 0.15978 RPN box loss: 0.01052 RPN score loss: 0.00227 RPN total loss: 0.01279 Total loss: 1.41544 timestamp: 1654932248.2540934 iteration: 21550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05052 FastRCNN class loss: 0.03203 FastRCNN total loss: 0.08255 L1 loss: 0.0000e+00 L2 loss: 1.06297 Learning rate: 0.02 Mask loss: 0.12339 RPN box loss: 0.06408 RPN score loss: 0.0052 RPN total loss: 0.06928 Total loss: 1.33819 timestamp: 1654932251.472011 iteration: 21555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18052 FastRCNN class loss: 0.0906 FastRCNN total loss: 0.27112 L1 loss: 0.0000e+00 L2 loss: 1.06279 Learning rate: 0.02 Mask loss: 0.14979 RPN box loss: 0.01134 RPN score loss: 0.00302 RPN total loss: 0.01436 Total loss: 1.49806 timestamp: 1654932254.6151304 iteration: 21560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.16718 L1 loss: 0.0000e+00 L2 loss: 1.06261 Learning rate: 0.02 Mask loss: 0.14305 RPN box loss: 0.01624 RPN score loss: 0.00591 RPN total loss: 0.02214 Total loss: 1.39498 timestamp: 1654932257.8217196 iteration: 21565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12175 FastRCNN class loss: 0.10332 FastRCNN total loss: 0.22508 L1 loss: 0.0000e+00 L2 loss: 1.06243 Learning rate: 0.02 Mask loss: 0.13317 RPN box loss: 0.03974 RPN score loss: 0.00734 RPN total loss: 0.04708 Total loss: 1.46775 timestamp: 1654932260.9842153 iteration: 21570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16108 FastRCNN class loss: 0.07239 FastRCNN total loss: 0.23347 L1 loss: 0.0000e+00 L2 loss: 1.06226 Learning rate: 0.02 Mask loss: 0.23573 RPN box loss: 0.02681 RPN score loss: 0.00956 RPN total loss: 0.03638 Total loss: 1.56785 timestamp: 1654932264.1737309 iteration: 21575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16005 FastRCNN class loss: 0.12546 FastRCNN total loss: 0.2855 L1 loss: 0.0000e+00 L2 loss: 1.06208 Learning rate: 0.02 Mask loss: 0.17272 RPN box loss: 0.03173 RPN score loss: 0.00666 RPN total loss: 0.03838 Total loss: 1.55869 timestamp: 1654932267.40237 iteration: 21580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13803 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.20432 L1 loss: 0.0000e+00 L2 loss: 1.0619 Learning rate: 0.02 Mask loss: 0.14591 RPN box loss: 0.02879 RPN score loss: 0.01 RPN total loss: 0.03879 Total loss: 1.45091 timestamp: 1654932270.5387843 iteration: 21585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1726 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.24807 L1 loss: 0.0000e+00 L2 loss: 1.06176 Learning rate: 0.02 Mask loss: 0.13384 RPN box loss: 0.03983 RPN score loss: 0.00799 RPN total loss: 0.04782 Total loss: 1.49149 timestamp: 1654932273.7655528 iteration: 21590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15536 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.23606 L1 loss: 0.0000e+00 L2 loss: 1.06159 Learning rate: 0.02 Mask loss: 0.20187 RPN box loss: 0.05929 RPN score loss: 0.00857 RPN total loss: 0.06786 Total loss: 1.56738 timestamp: 1654932276.922452 iteration: 21595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09508 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.1701 L1 loss: 0.0000e+00 L2 loss: 1.06142 Learning rate: 0.02 Mask loss: 0.19178 RPN box loss: 0.01081 RPN score loss: 0.0031 RPN total loss: 0.01391 Total loss: 1.43721 timestamp: 1654932280.1201344 iteration: 21600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15568 FastRCNN class loss: 0.1319 FastRCNN total loss: 0.28758 L1 loss: 0.0000e+00 L2 loss: 1.06128 Learning rate: 0.02 Mask loss: 0.19406 RPN box loss: 0.02702 RPN score loss: 0.00464 RPN total loss: 0.03166 Total loss: 1.57457 timestamp: 1654932283.4044108 iteration: 21605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29315 FastRCNN class loss: 0.14855 FastRCNN total loss: 0.4417 L1 loss: 0.0000e+00 L2 loss: 1.06111 Learning rate: 0.02 Mask loss: 0.24142 RPN box loss: 0.04779 RPN score loss: 0.01087 RPN total loss: 0.05865 Total loss: 1.80288 timestamp: 1654932286.5620832 iteration: 21610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1891 FastRCNN class loss: 0.10417 FastRCNN total loss: 0.29327 L1 loss: 0.0000e+00 L2 loss: 1.06092 Learning rate: 0.02 Mask loss: 0.17375 RPN box loss: 0.03772 RPN score loss: 0.01095 RPN total loss: 0.04866 Total loss: 1.57661 timestamp: 1654932289.7903018 iteration: 21615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11658 FastRCNN class loss: 0.09103 FastRCNN total loss: 0.20761 L1 loss: 0.0000e+00 L2 loss: 1.06076 Learning rate: 0.02 Mask loss: 0.15886 RPN box loss: 0.05007 RPN score loss: 0.00287 RPN total loss: 0.05294 Total loss: 1.48016 timestamp: 1654932293.0640423 iteration: 21620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15667 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.23704 L1 loss: 0.0000e+00 L2 loss: 1.06061 Learning rate: 0.02 Mask loss: 0.1265 RPN box loss: 0.03412 RPN score loss: 0.00467 RPN total loss: 0.03879 Total loss: 1.46294 timestamp: 1654932296.3252037 iteration: 21625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16892 FastRCNN class loss: 0.13797 FastRCNN total loss: 0.30689 L1 loss: 0.0000e+00 L2 loss: 1.06043 Learning rate: 0.02 Mask loss: 0.15469 RPN box loss: 0.18432 RPN score loss: 0.00889 RPN total loss: 0.19322 Total loss: 1.71523 timestamp: 1654932299.5793138 iteration: 21630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09316 FastRCNN class loss: 0.06032 FastRCNN total loss: 0.15348 L1 loss: 0.0000e+00 L2 loss: 1.06029 Learning rate: 0.02 Mask loss: 0.1596 RPN box loss: 0.03586 RPN score loss: 0.00872 RPN total loss: 0.04458 Total loss: 1.41794 timestamp: 1654932302.8122022 iteration: 21635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11396 FastRCNN class loss: 0.15508 FastRCNN total loss: 0.26904 L1 loss: 0.0000e+00 L2 loss: 1.0601 Learning rate: 0.02 Mask loss: 0.25158 RPN box loss: 0.04254 RPN score loss: 0.07464 RPN total loss: 0.11718 Total loss: 1.6979 timestamp: 1654932305.9895148 iteration: 21640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11093 FastRCNN class loss: 0.11266 FastRCNN total loss: 0.22358 L1 loss: 0.0000e+00 L2 loss: 1.05993 Learning rate: 0.02 Mask loss: 0.18459 RPN box loss: 0.04202 RPN score loss: 0.01102 RPN total loss: 0.05305 Total loss: 1.52115 timestamp: 1654932309.1710157 iteration: 21645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20903 FastRCNN class loss: 0.07635 FastRCNN total loss: 0.28538 L1 loss: 0.0000e+00 L2 loss: 1.0598 Learning rate: 0.02 Mask loss: 0.19358 RPN box loss: 0.03055 RPN score loss: 0.00886 RPN total loss: 0.0394 Total loss: 1.57816 timestamp: 1654932312.3969584 iteration: 21650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13233 FastRCNN class loss: 0.07978 FastRCNN total loss: 0.21211 L1 loss: 0.0000e+00 L2 loss: 1.05964 Learning rate: 0.02 Mask loss: 0.16177 RPN box loss: 0.03332 RPN score loss: 0.00983 RPN total loss: 0.04314 Total loss: 1.47666 timestamp: 1654932315.5613863 iteration: 21655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15999 FastRCNN class loss: 0.07714 FastRCNN total loss: 0.23713 L1 loss: 0.0000e+00 L2 loss: 1.05945 Learning rate: 0.02 Mask loss: 0.12625 RPN box loss: 0.02075 RPN score loss: 0.00428 RPN total loss: 0.02504 Total loss: 1.44787 timestamp: 1654932318.7458727 iteration: 21660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19839 FastRCNN class loss: 0.11275 FastRCNN total loss: 0.31114 L1 loss: 0.0000e+00 L2 loss: 1.05929 Learning rate: 0.02 Mask loss: 0.191 RPN box loss: 0.02602 RPN score loss: 0.00823 RPN total loss: 0.03425 Total loss: 1.59568 timestamp: 1654932321.918778 iteration: 21665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11146 FastRCNN class loss: 0.04695 FastRCNN total loss: 0.15841 L1 loss: 0.0000e+00 L2 loss: 1.05912 Learning rate: 0.02 Mask loss: 0.12478 RPN box loss: 0.02409 RPN score loss: 0.00257 RPN total loss: 0.02666 Total loss: 1.36897 timestamp: 1654932325.0929964 iteration: 21670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13978 FastRCNN class loss: 0.08798 FastRCNN total loss: 0.22776 L1 loss: 0.0000e+00 L2 loss: 1.05895 Learning rate: 0.02 Mask loss: 0.13585 RPN box loss: 0.0267 RPN score loss: 0.00743 RPN total loss: 0.03413 Total loss: 1.4567 timestamp: 1654932328.2577548 iteration: 21675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16029 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.23413 L1 loss: 0.0000e+00 L2 loss: 1.0588 Learning rate: 0.02 Mask loss: 0.11939 RPN box loss: 0.11857 RPN score loss: 0.00673 RPN total loss: 0.1253 Total loss: 1.53762 timestamp: 1654932331.5149095 iteration: 21680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13291 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.19951 L1 loss: 0.0000e+00 L2 loss: 1.05864 Learning rate: 0.02 Mask loss: 0.12345 RPN box loss: 0.02526 RPN score loss: 0.00261 RPN total loss: 0.02787 Total loss: 1.40947 timestamp: 1654932334.6937914 iteration: 21685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13528 FastRCNN class loss: 0.1235 FastRCNN total loss: 0.25878 L1 loss: 0.0000e+00 L2 loss: 1.05848 Learning rate: 0.02 Mask loss: 0.17643 RPN box loss: 0.02354 RPN score loss: 0.00327 RPN total loss: 0.02682 Total loss: 1.52049 timestamp: 1654932337.9750159 iteration: 21690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15929 FastRCNN class loss: 0.08809 FastRCNN total loss: 0.24738 L1 loss: 0.0000e+00 L2 loss: 1.0583 Learning rate: 0.02 Mask loss: 0.14982 RPN box loss: 0.03917 RPN score loss: 0.00699 RPN total loss: 0.04616 Total loss: 1.50166 timestamp: 1654932341.1793325 iteration: 21695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12222 FastRCNN class loss: 0.0913 FastRCNN total loss: 0.21353 L1 loss: 0.0000e+00 L2 loss: 1.05811 Learning rate: 0.02 Mask loss: 0.1452 RPN box loss: 0.00861 RPN score loss: 0.00257 RPN total loss: 0.01117 Total loss: 1.42801 timestamp: 1654932344.358237 iteration: 21700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15941 FastRCNN class loss: 0.09412 FastRCNN total loss: 0.25353 L1 loss: 0.0000e+00 L2 loss: 1.05794 Learning rate: 0.02 Mask loss: 0.13391 RPN box loss: 0.01659 RPN score loss: 0.00422 RPN total loss: 0.02081 Total loss: 1.46619 timestamp: 1654932347.5635624 iteration: 21705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21062 FastRCNN class loss: 0.1329 FastRCNN total loss: 0.34352 L1 loss: 0.0000e+00 L2 loss: 1.05777 Learning rate: 0.02 Mask loss: 0.21271 RPN box loss: 0.03662 RPN score loss: 0.01383 RPN total loss: 0.05045 Total loss: 1.66446 timestamp: 1654932350.8001308 iteration: 21710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11244 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.21433 L1 loss: 0.0000e+00 L2 loss: 1.0576 Learning rate: 0.02 Mask loss: 0.14024 RPN box loss: 0.06971 RPN score loss: 0.0165 RPN total loss: 0.08621 Total loss: 1.49839 timestamp: 1654932353.9959567 iteration: 21715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1866 FastRCNN class loss: 0.0971 FastRCNN total loss: 0.2837 L1 loss: 0.0000e+00 L2 loss: 1.05742 Learning rate: 0.02 Mask loss: 0.19701 RPN box loss: 0.01639 RPN score loss: 0.00577 RPN total loss: 0.02216 Total loss: 1.56029 timestamp: 1654932357.168045 iteration: 21720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14404 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.21044 L1 loss: 0.0000e+00 L2 loss: 1.05725 Learning rate: 0.02 Mask loss: 0.10228 RPN box loss: 0.03587 RPN score loss: 0.0061 RPN total loss: 0.04197 Total loss: 1.41194 timestamp: 1654932360.3376245 iteration: 21725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2141 FastRCNN class loss: 0.12485 FastRCNN total loss: 0.33895 L1 loss: 0.0000e+00 L2 loss: 1.0571 Learning rate: 0.02 Mask loss: 0.23567 RPN box loss: 0.05336 RPN score loss: 0.01707 RPN total loss: 0.07043 Total loss: 1.70214 timestamp: 1654932363.53479 iteration: 21730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08006 FastRCNN class loss: 0.05227 FastRCNN total loss: 0.13233 L1 loss: 0.0000e+00 L2 loss: 1.05694 Learning rate: 0.02 Mask loss: 0.17833 RPN box loss: 0.02797 RPN score loss: 0.0025 RPN total loss: 0.03047 Total loss: 1.39808 timestamp: 1654932366.704112 iteration: 21735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16943 FastRCNN class loss: 0.11095 FastRCNN total loss: 0.28038 L1 loss: 0.0000e+00 L2 loss: 1.05678 Learning rate: 0.02 Mask loss: 0.12568 RPN box loss: 0.03915 RPN score loss: 0.00428 RPN total loss: 0.04343 Total loss: 1.50626 timestamp: 1654932369.9435668 iteration: 21740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16209 FastRCNN class loss: 0.0632 FastRCNN total loss: 0.22528 L1 loss: 0.0000e+00 L2 loss: 1.05662 Learning rate: 0.02 Mask loss: 0.13026 RPN box loss: 0.01979 RPN score loss: 0.00276 RPN total loss: 0.02255 Total loss: 1.43472 timestamp: 1654932373.2549057 iteration: 21745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14348 FastRCNN class loss: 0.05798 FastRCNN total loss: 0.20147 L1 loss: 0.0000e+00 L2 loss: 1.05643 Learning rate: 0.02 Mask loss: 0.12256 RPN box loss: 0.01516 RPN score loss: 0.00403 RPN total loss: 0.01919 Total loss: 1.39965 timestamp: 1654932376.4427009 iteration: 21750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11537 FastRCNN class loss: 0.0577 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 1.05624 Learning rate: 0.02 Mask loss: 0.13603 RPN box loss: 0.02901 RPN score loss: 0.00396 RPN total loss: 0.03297 Total loss: 1.39832 timestamp: 1654932379.6496327 iteration: 21755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10118 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.16167 L1 loss: 0.0000e+00 L2 loss: 1.05608 Learning rate: 0.02 Mask loss: 0.1147 RPN box loss: 0.00549 RPN score loss: 0.00226 RPN total loss: 0.00775 Total loss: 1.3402 timestamp: 1654932382.8969262 iteration: 21760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18488 FastRCNN class loss: 0.17803 FastRCNN total loss: 0.36291 L1 loss: 0.0000e+00 L2 loss: 1.05593 Learning rate: 0.02 Mask loss: 0.1369 RPN box loss: 0.03246 RPN score loss: 0.00805 RPN total loss: 0.04051 Total loss: 1.59625 timestamp: 1654932386.084697 iteration: 21765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17908 FastRCNN class loss: 0.09816 FastRCNN total loss: 0.27724 L1 loss: 0.0000e+00 L2 loss: 1.05578 Learning rate: 0.02 Mask loss: 0.22586 RPN box loss: 0.0699 RPN score loss: 0.02065 RPN total loss: 0.09055 Total loss: 1.64943 timestamp: 1654932389.2745934 iteration: 21770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1714 FastRCNN class loss: 0.08555 FastRCNN total loss: 0.25695 L1 loss: 0.0000e+00 L2 loss: 1.05563 Learning rate: 0.02 Mask loss: 0.15767 RPN box loss: 0.02385 RPN score loss: 0.0137 RPN total loss: 0.03755 Total loss: 1.5078 timestamp: 1654932392.4968204 iteration: 21775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19548 FastRCNN class loss: 0.08575 FastRCNN total loss: 0.28123 L1 loss: 0.0000e+00 L2 loss: 1.05545 Learning rate: 0.02 Mask loss: 0.22879 RPN box loss: 0.04594 RPN score loss: 0.00643 RPN total loss: 0.05238 Total loss: 1.61784 timestamp: 1654932395.7278855 iteration: 21780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18298 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.25175 L1 loss: 0.0000e+00 L2 loss: 1.05525 Learning rate: 0.02 Mask loss: 0.13164 RPN box loss: 0.04197 RPN score loss: 0.00706 RPN total loss: 0.04904 Total loss: 1.48768 timestamp: 1654932398.8762045 iteration: 21785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07734 FastRCNN class loss: 0.05268 FastRCNN total loss: 0.13002 L1 loss: 0.0000e+00 L2 loss: 1.05508 Learning rate: 0.02 Mask loss: 0.12678 RPN box loss: 0.00939 RPN score loss: 0.00202 RPN total loss: 0.0114 Total loss: 1.32329 timestamp: 1654932402.057843 iteration: 21790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28129 FastRCNN class loss: 0.10793 FastRCNN total loss: 0.38922 L1 loss: 0.0000e+00 L2 loss: 1.05492 Learning rate: 0.02 Mask loss: 0.19799 RPN box loss: 0.05214 RPN score loss: 0.01369 RPN total loss: 0.06583 Total loss: 1.70797 timestamp: 1654932405.2729526 iteration: 21795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07936 FastRCNN class loss: 0.05079 FastRCNN total loss: 0.13015 L1 loss: 0.0000e+00 L2 loss: 1.05473 Learning rate: 0.02 Mask loss: 0.16699 RPN box loss: 0.01779 RPN score loss: 0.00512 RPN total loss: 0.02291 Total loss: 1.37478 timestamp: 1654932408.495812 iteration: 21800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22979 FastRCNN class loss: 0.12482 FastRCNN total loss: 0.35461 L1 loss: 0.0000e+00 L2 loss: 1.05453 Learning rate: 0.02 Mask loss: 0.22524 RPN box loss: 0.0482 RPN score loss: 0.00992 RPN total loss: 0.05812 Total loss: 1.6925 timestamp: 1654932411.6948316 iteration: 21805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11096 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.17547 L1 loss: 0.0000e+00 L2 loss: 1.05436 Learning rate: 0.02 Mask loss: 0.13282 RPN box loss: 0.01904 RPN score loss: 0.00277 RPN total loss: 0.0218 Total loss: 1.38444 timestamp: 1654932414.9307907 iteration: 21810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.23967 L1 loss: 0.0000e+00 L2 loss: 1.05419 Learning rate: 0.02 Mask loss: 0.10766 RPN box loss: 0.01298 RPN score loss: 0.00372 RPN total loss: 0.0167 Total loss: 1.41823 timestamp: 1654932418.0850632 iteration: 21815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18826 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.25925 L1 loss: 0.0000e+00 L2 loss: 1.05402 Learning rate: 0.02 Mask loss: 0.1653 RPN box loss: 0.05076 RPN score loss: 0.01037 RPN total loss: 0.06114 Total loss: 1.53971 timestamp: 1654932421.2828534 iteration: 21820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17457 FastRCNN class loss: 0.07692 FastRCNN total loss: 0.25149 L1 loss: 0.0000e+00 L2 loss: 1.05387 Learning rate: 0.02 Mask loss: 0.12482 RPN box loss: 0.01741 RPN score loss: 0.00651 RPN total loss: 0.02391 Total loss: 1.4541 timestamp: 1654932424.4942386 iteration: 21825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1713 FastRCNN class loss: 0.11542 FastRCNN total loss: 0.28672 L1 loss: 0.0000e+00 L2 loss: 1.05371 Learning rate: 0.02 Mask loss: 0.21124 RPN box loss: 0.02271 RPN score loss: 0.00925 RPN total loss: 0.03197 Total loss: 1.58364 timestamp: 1654932427.7203717 iteration: 21830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10095 FastRCNN class loss: 0.04753 FastRCNN total loss: 0.14847 L1 loss: 0.0000e+00 L2 loss: 1.05353 Learning rate: 0.02 Mask loss: 0.10775 RPN box loss: 0.04375 RPN score loss: 0.00467 RPN total loss: 0.04842 Total loss: 1.35818 timestamp: 1654932430.9827495 iteration: 21835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21313 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.30186 L1 loss: 0.0000e+00 L2 loss: 1.05336 Learning rate: 0.02 Mask loss: 0.1311 RPN box loss: 0.01756 RPN score loss: 0.01029 RPN total loss: 0.02785 Total loss: 1.51417 timestamp: 1654932434.2497191 iteration: 21840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10926 FastRCNN class loss: 0.07132 FastRCNN total loss: 0.18058 L1 loss: 0.0000e+00 L2 loss: 1.05318 Learning rate: 0.02 Mask loss: 0.09748 RPN box loss: 0.02254 RPN score loss: 0.00237 RPN total loss: 0.0249 Total loss: 1.35614 timestamp: 1654932437.4713428 iteration: 21845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08974 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.17201 L1 loss: 0.0000e+00 L2 loss: 1.053 Learning rate: 0.02 Mask loss: 0.11002 RPN box loss: 0.01515 RPN score loss: 0.00164 RPN total loss: 0.01679 Total loss: 1.35182 timestamp: 1654932440.6091835 iteration: 21850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11421 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.18192 L1 loss: 0.0000e+00 L2 loss: 1.05283 Learning rate: 0.02 Mask loss: 0.12931 RPN box loss: 0.11266 RPN score loss: 0.00691 RPN total loss: 0.11958 Total loss: 1.48364 timestamp: 1654932443.837788 iteration: 21855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16909 FastRCNN class loss: 0.10118 FastRCNN total loss: 0.27027 L1 loss: 0.0000e+00 L2 loss: 1.05266 Learning rate: 0.02 Mask loss: 0.13236 RPN box loss: 0.04203 RPN score loss: 0.00576 RPN total loss: 0.04779 Total loss: 1.50308 timestamp: 1654932447.034336 iteration: 21860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15193 FastRCNN class loss: 0.08726 FastRCNN total loss: 0.23919 L1 loss: 0.0000e+00 L2 loss: 1.05248 Learning rate: 0.02 Mask loss: 0.16134 RPN box loss: 0.05221 RPN score loss: 0.00274 RPN total loss: 0.05494 Total loss: 1.50796 timestamp: 1654932450.1797287 iteration: 21865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24929 FastRCNN class loss: 0.15443 FastRCNN total loss: 0.40372 L1 loss: 0.0000e+00 L2 loss: 1.05232 Learning rate: 0.02 Mask loss: 0.17404 RPN box loss: 0.03406 RPN score loss: 0.0107 RPN total loss: 0.04476 Total loss: 1.67484 timestamp: 1654932453.342726 iteration: 21870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14652 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.22919 L1 loss: 0.0000e+00 L2 loss: 1.05214 Learning rate: 0.02 Mask loss: 0.18406 RPN box loss: 0.04227 RPN score loss: 0.00754 RPN total loss: 0.04981 Total loss: 1.51522 timestamp: 1654932456.4776697 iteration: 21875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1131 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.17039 L1 loss: 0.0000e+00 L2 loss: 1.05198 Learning rate: 0.02 Mask loss: 0.15183 RPN box loss: 0.01671 RPN score loss: 0.00304 RPN total loss: 0.01974 Total loss: 1.39394 timestamp: 1654932459.630835 iteration: 21880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0883 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.15825 L1 loss: 0.0000e+00 L2 loss: 1.05182 Learning rate: 0.02 Mask loss: 0.19759 RPN box loss: 0.02515 RPN score loss: 0.00218 RPN total loss: 0.02733 Total loss: 1.435 timestamp: 1654932462.8930352 iteration: 21885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13265 FastRCNN class loss: 0.07855 FastRCNN total loss: 0.21121 L1 loss: 0.0000e+00 L2 loss: 1.05164 Learning rate: 0.02 Mask loss: 0.21919 RPN box loss: 0.01939 RPN score loss: 0.00596 RPN total loss: 0.02535 Total loss: 1.50739 timestamp: 1654932466.068326 iteration: 21890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09723 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 1.05145 Learning rate: 0.02 Mask loss: 0.15039 RPN box loss: 0.01496 RPN score loss: 0.00629 RPN total loss: 0.02125 Total loss: 1.40041 timestamp: 1654932469.3481512 iteration: 21895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11302 FastRCNN class loss: 0.08021 FastRCNN total loss: 0.19323 L1 loss: 0.0000e+00 L2 loss: 1.05129 Learning rate: 0.02 Mask loss: 0.16698 RPN box loss: 0.05381 RPN score loss: 0.00675 RPN total loss: 0.06056 Total loss: 1.47206 timestamp: 1654932472.5294652 iteration: 21900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10785 FastRCNN class loss: 0.06336 FastRCNN total loss: 0.1712 L1 loss: 0.0000e+00 L2 loss: 1.05111 Learning rate: 0.02 Mask loss: 0.14629 RPN box loss: 0.03326 RPN score loss: 0.01556 RPN total loss: 0.04883 Total loss: 1.41743 timestamp: 1654932475.692966 iteration: 21905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07157 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.12754 L1 loss: 0.0000e+00 L2 loss: 1.05096 Learning rate: 0.02 Mask loss: 0.12884 RPN box loss: 0.09835 RPN score loss: 0.00839 RPN total loss: 0.10675 Total loss: 1.41409 timestamp: 1654932478.926476 iteration: 21910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16709 FastRCNN class loss: 0.16297 FastRCNN total loss: 0.33005 L1 loss: 0.0000e+00 L2 loss: 1.05079 Learning rate: 0.02 Mask loss: 0.27745 RPN box loss: 0.03456 RPN score loss: 0.00879 RPN total loss: 0.04335 Total loss: 1.70164 timestamp: 1654932482.1733592 iteration: 21915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13067 FastRCNN class loss: 0.05093 FastRCNN total loss: 0.18159 L1 loss: 0.0000e+00 L2 loss: 1.05063 Learning rate: 0.02 Mask loss: 0.11804 RPN box loss: 0.08275 RPN score loss: 0.00421 RPN total loss: 0.08696 Total loss: 1.43723 timestamp: 1654932485.3914053 iteration: 21920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15647 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.22359 L1 loss: 0.0000e+00 L2 loss: 1.05048 Learning rate: 0.02 Mask loss: 0.11647 RPN box loss: 0.00955 RPN score loss: 0.00464 RPN total loss: 0.01419 Total loss: 1.40473 timestamp: 1654932488.6472929 iteration: 21925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16446 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.23281 L1 loss: 0.0000e+00 L2 loss: 1.05028 Learning rate: 0.02 Mask loss: 0.18559 RPN box loss: 0.03816 RPN score loss: 0.00261 RPN total loss: 0.04076 Total loss: 1.50945 timestamp: 1654932491.8563707 iteration: 21930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16408 FastRCNN class loss: 0.1073 FastRCNN total loss: 0.27138 L1 loss: 0.0000e+00 L2 loss: 1.05012 Learning rate: 0.02 Mask loss: 0.19057 RPN box loss: 0.00667 RPN score loss: 0.00611 RPN total loss: 0.01278 Total loss: 1.52485 timestamp: 1654932494.9976523 iteration: 21935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17164 FastRCNN class loss: 0.11429 FastRCNN total loss: 0.28594 L1 loss: 0.0000e+00 L2 loss: 1.04997 Learning rate: 0.02 Mask loss: 0.19954 RPN box loss: 0.0737 RPN score loss: 0.02395 RPN total loss: 0.09765 Total loss: 1.6331 timestamp: 1654932498.1600304 iteration: 21940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15472 FastRCNN class loss: 0.09259 FastRCNN total loss: 0.2473 L1 loss: 0.0000e+00 L2 loss: 1.04979 Learning rate: 0.02 Mask loss: 0.16703 RPN box loss: 0.0289 RPN score loss: 0.00454 RPN total loss: 0.03344 Total loss: 1.49757 timestamp: 1654932501.3967812 iteration: 21945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12725 FastRCNN class loss: 0.0726 FastRCNN total loss: 0.19985 L1 loss: 0.0000e+00 L2 loss: 1.04964 Learning rate: 0.02 Mask loss: 0.11389 RPN box loss: 0.01632 RPN score loss: 0.00722 RPN total loss: 0.02354 Total loss: 1.38692 timestamp: 1654932504.5681574 iteration: 21950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11856 FastRCNN class loss: 0.05369 FastRCNN total loss: 0.17225 L1 loss: 0.0000e+00 L2 loss: 1.04947 Learning rate: 0.02 Mask loss: 0.14735 RPN box loss: 0.06873 RPN score loss: 0.0052 RPN total loss: 0.07394 Total loss: 1.44301 timestamp: 1654932507.7961922 iteration: 21955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14346 FastRCNN class loss: 0.07342 FastRCNN total loss: 0.21689 L1 loss: 0.0000e+00 L2 loss: 1.04927 Learning rate: 0.02 Mask loss: 0.12989 RPN box loss: 0.03949 RPN score loss: 0.01419 RPN total loss: 0.05368 Total loss: 1.44973 timestamp: 1654932510.9994981 iteration: 21960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08253 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.14422 L1 loss: 0.0000e+00 L2 loss: 1.04913 Learning rate: 0.02 Mask loss: 0.11318 RPN box loss: 0.01597 RPN score loss: 0.00486 RPN total loss: 0.02083 Total loss: 1.32736 timestamp: 1654932514.3093493 iteration: 21965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.10635 FastRCNN total loss: 0.2476 L1 loss: 0.0000e+00 L2 loss: 1.04896 Learning rate: 0.02 Mask loss: 0.14536 RPN box loss: 0.03701 RPN score loss: 0.00889 RPN total loss: 0.04589 Total loss: 1.48781 timestamp: 1654932517.5663762 iteration: 21970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11302 FastRCNN class loss: 0.07864 FastRCNN total loss: 0.19166 L1 loss: 0.0000e+00 L2 loss: 1.04877 Learning rate: 0.02 Mask loss: 0.14451 RPN box loss: 0.01773 RPN score loss: 0.00509 RPN total loss: 0.02282 Total loss: 1.40776 timestamp: 1654932520.8182032 iteration: 21975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15589 FastRCNN class loss: 0.14659 FastRCNN total loss: 0.30248 L1 loss: 0.0000e+00 L2 loss: 1.04863 Learning rate: 0.02 Mask loss: 0.206 RPN box loss: 0.01941 RPN score loss: 0.01302 RPN total loss: 0.03243 Total loss: 1.58954 timestamp: 1654932524.0226877 iteration: 21980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09623 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.16277 L1 loss: 0.0000e+00 L2 loss: 1.04848 Learning rate: 0.02 Mask loss: 0.15394 RPN box loss: 0.01341 RPN score loss: 0.00886 RPN total loss: 0.02227 Total loss: 1.38747 timestamp: 1654932527.2759907 iteration: 21985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15236 FastRCNN class loss: 0.07823 FastRCNN total loss: 0.23059 L1 loss: 0.0000e+00 L2 loss: 1.0483 Learning rate: 0.02 Mask loss: 0.14871 RPN box loss: 0.05791 RPN score loss: 0.01335 RPN total loss: 0.07126 Total loss: 1.49886 timestamp: 1654932530.4570432 iteration: 21990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17531 FastRCNN class loss: 0.08705 FastRCNN total loss: 0.26236 L1 loss: 0.0000e+00 L2 loss: 1.04813 Learning rate: 0.02 Mask loss: 0.22845 RPN box loss: 0.03983 RPN score loss: 0.00417 RPN total loss: 0.044 Total loss: 1.58295 timestamp: 1654932533.702026 iteration: 21995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10518 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.16491 L1 loss: 0.0000e+00 L2 loss: 1.04796 Learning rate: 0.02 Mask loss: 0.15429 RPN box loss: 0.04167 RPN score loss: 0.00848 RPN total loss: 0.05016 Total loss: 1.41732 timestamp: 1654932536.9688592 iteration: 22000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12356 FastRCNN class loss: 0.09628 FastRCNN total loss: 0.21985 L1 loss: 0.0000e+00 L2 loss: 1.04778 Learning rate: 0.02 Mask loss: 0.1331 RPN box loss: 0.01962 RPN score loss: 0.00607 RPN total loss: 0.02569 Total loss: 1.42642 timestamp: 1654932540.233317 iteration: 22005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13001 FastRCNN class loss: 0.05103 FastRCNN total loss: 0.18103 L1 loss: 0.0000e+00 L2 loss: 1.0476 Learning rate: 0.02 Mask loss: 0.17392 RPN box loss: 0.00392 RPN score loss: 0.00338 RPN total loss: 0.00729 Total loss: 1.40984 timestamp: 1654932543.4681506 iteration: 22010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19498 FastRCNN class loss: 0.09163 FastRCNN total loss: 0.28661 L1 loss: 0.0000e+00 L2 loss: 1.04741 Learning rate: 0.02 Mask loss: 0.28539 RPN box loss: 0.01781 RPN score loss: 0.00563 RPN total loss: 0.02344 Total loss: 1.64285 timestamp: 1654932546.6677089 iteration: 22015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16702 FastRCNN class loss: 0.1047 FastRCNN total loss: 0.27172 L1 loss: 0.0000e+00 L2 loss: 1.04726 Learning rate: 0.02 Mask loss: 0.15944 RPN box loss: 0.04239 RPN score loss: 0.01735 RPN total loss: 0.05975 Total loss: 1.53817 timestamp: 1654932549.840224 iteration: 22020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17365 FastRCNN class loss: 0.12121 FastRCNN total loss: 0.29485 L1 loss: 0.0000e+00 L2 loss: 1.0471 Learning rate: 0.02 Mask loss: 0.18109 RPN box loss: 0.04079 RPN score loss: 0.00734 RPN total loss: 0.04813 Total loss: 1.57117 timestamp: 1654932553.0404117 iteration: 22025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15785 FastRCNN class loss: 0.11509 FastRCNN total loss: 0.27294 L1 loss: 0.0000e+00 L2 loss: 1.04694 Learning rate: 0.02 Mask loss: 0.14248 RPN box loss: 0.09424 RPN score loss: 0.00871 RPN total loss: 0.10295 Total loss: 1.56531 timestamp: 1654932556.3790164 iteration: 22030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15917 FastRCNN class loss: 0.10908 FastRCNN total loss: 0.26825 L1 loss: 0.0000e+00 L2 loss: 1.04678 Learning rate: 0.02 Mask loss: 0.17291 RPN box loss: 0.02475 RPN score loss: 0.00744 RPN total loss: 0.03219 Total loss: 1.52014 timestamp: 1654932559.5979562 iteration: 22035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.15457 L1 loss: 0.0000e+00 L2 loss: 1.04659 Learning rate: 0.02 Mask loss: 0.12275 RPN box loss: 0.07607 RPN score loss: 0.00404 RPN total loss: 0.08011 Total loss: 1.40402 timestamp: 1654932562.7934077 iteration: 22040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14315 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.2014 L1 loss: 0.0000e+00 L2 loss: 1.04645 Learning rate: 0.02 Mask loss: 0.10431 RPN box loss: 0.02673 RPN score loss: 0.00586 RPN total loss: 0.03259 Total loss: 1.38475 timestamp: 1654932565.968172 iteration: 22045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17498 FastRCNN class loss: 0.1059 FastRCNN total loss: 0.28088 L1 loss: 0.0000e+00 L2 loss: 1.04628 Learning rate: 0.02 Mask loss: 0.15723 RPN box loss: 0.08236 RPN score loss: 0.00975 RPN total loss: 0.09211 Total loss: 1.57651 timestamp: 1654932569.1287978 iteration: 22050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14001 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.18844 L1 loss: 0.0000e+00 L2 loss: 1.04612 Learning rate: 0.02 Mask loss: 0.18907 RPN box loss: 0.02902 RPN score loss: 0.00333 RPN total loss: 0.03235 Total loss: 1.45598 timestamp: 1654932572.3374333 iteration: 22055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13759 FastRCNN class loss: 0.10726 FastRCNN total loss: 0.24486 L1 loss: 0.0000e+00 L2 loss: 1.04595 Learning rate: 0.02 Mask loss: 0.18634 RPN box loss: 0.02646 RPN score loss: 0.00893 RPN total loss: 0.03539 Total loss: 1.51254 timestamp: 1654932575.5911794 iteration: 22060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14892 FastRCNN class loss: 0.11007 FastRCNN total loss: 0.25898 L1 loss: 0.0000e+00 L2 loss: 1.04578 Learning rate: 0.02 Mask loss: 0.12199 RPN box loss: 0.03041 RPN score loss: 0.00808 RPN total loss: 0.03849 Total loss: 1.46525 timestamp: 1654932578.7393293 iteration: 22065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11425 FastRCNN class loss: 0.09283 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 1.0456 Learning rate: 0.02 Mask loss: 0.14505 RPN box loss: 0.03467 RPN score loss: 0.01272 RPN total loss: 0.04739 Total loss: 1.44513 timestamp: 1654932581.9375865 iteration: 22070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1671 FastRCNN class loss: 0.06212 FastRCNN total loss: 0.22921 L1 loss: 0.0000e+00 L2 loss: 1.04545 Learning rate: 0.02 Mask loss: 0.12485 RPN box loss: 0.00628 RPN score loss: 0.00359 RPN total loss: 0.00987 Total loss: 1.40937 timestamp: 1654932585.1273415 iteration: 22075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12986 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.19242 L1 loss: 0.0000e+00 L2 loss: 1.04527 Learning rate: 0.02 Mask loss: 0.14991 RPN box loss: 0.02191 RPN score loss: 0.01066 RPN total loss: 0.03258 Total loss: 1.42018 timestamp: 1654932588.3925512 iteration: 22080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10106 FastRCNN class loss: 0.04649 FastRCNN total loss: 0.14755 L1 loss: 0.0000e+00 L2 loss: 1.04512 Learning rate: 0.02 Mask loss: 0.0978 RPN box loss: 0.05353 RPN score loss: 0.00373 RPN total loss: 0.05726 Total loss: 1.34773 timestamp: 1654932591.6316013 iteration: 22085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11497 FastRCNN class loss: 0.07626 FastRCNN total loss: 0.19124 L1 loss: 0.0000e+00 L2 loss: 1.04495 Learning rate: 0.02 Mask loss: 0.17472 RPN box loss: 0.0132 RPN score loss: 0.00213 RPN total loss: 0.01534 Total loss: 1.42624 timestamp: 1654932594.8540719 iteration: 22090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14288 FastRCNN class loss: 0.07489 FastRCNN total loss: 0.21777 L1 loss: 0.0000e+00 L2 loss: 1.04476 Learning rate: 0.02 Mask loss: 0.16219 RPN box loss: 0.0674 RPN score loss: 0.00954 RPN total loss: 0.07694 Total loss: 1.50166 timestamp: 1654932598.0559185 iteration: 22095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12173 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.21523 L1 loss: 0.0000e+00 L2 loss: 1.04459 Learning rate: 0.02 Mask loss: 0.19661 RPN box loss: 0.02084 RPN score loss: 0.0039 RPN total loss: 0.02473 Total loss: 1.48115 timestamp: 1654932601.1983387 iteration: 22100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1288 FastRCNN class loss: 0.07393 FastRCNN total loss: 0.20273 L1 loss: 0.0000e+00 L2 loss: 1.04442 Learning rate: 0.02 Mask loss: 0.11109 RPN box loss: 0.05645 RPN score loss: 0.01135 RPN total loss: 0.0678 Total loss: 1.42603 timestamp: 1654932604.4388204 iteration: 22105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19905 FastRCNN class loss: 0.10804 FastRCNN total loss: 0.30709 L1 loss: 0.0000e+00 L2 loss: 1.04424 Learning rate: 0.02 Mask loss: 0.17465 RPN box loss: 0.04302 RPN score loss: 0.00436 RPN total loss: 0.04738 Total loss: 1.57336 timestamp: 1654932607.6485767 iteration: 22110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12298 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.1931 L1 loss: 0.0000e+00 L2 loss: 1.04405 Learning rate: 0.02 Mask loss: 0.10536 RPN box loss: 0.04562 RPN score loss: 0.00967 RPN total loss: 0.05529 Total loss: 1.39779 timestamp: 1654932610.7443123 iteration: 22115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23142 FastRCNN class loss: 0.11742 FastRCNN total loss: 0.34884 L1 loss: 0.0000e+00 L2 loss: 1.04388 Learning rate: 0.02 Mask loss: 0.14054 RPN box loss: 0.03308 RPN score loss: 0.00659 RPN total loss: 0.03967 Total loss: 1.57294 timestamp: 1654932613.9394517 iteration: 22120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1473 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.22091 L1 loss: 0.0000e+00 L2 loss: 1.04373 Learning rate: 0.02 Mask loss: 0.1718 RPN box loss: 0.03373 RPN score loss: 0.01102 RPN total loss: 0.04475 Total loss: 1.48119 timestamp: 1654932617.1483884 iteration: 22125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12866 FastRCNN class loss: 0.09104 FastRCNN total loss: 0.2197 L1 loss: 0.0000e+00 L2 loss: 1.04358 Learning rate: 0.02 Mask loss: 0.12969 RPN box loss: 0.04497 RPN score loss: 0.00305 RPN total loss: 0.04802 Total loss: 1.441 timestamp: 1654932620.365967 iteration: 22130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13195 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.18513 L1 loss: 0.0000e+00 L2 loss: 1.04342 Learning rate: 0.02 Mask loss: 0.09911 RPN box loss: 0.01068 RPN score loss: 0.0023 RPN total loss: 0.01299 Total loss: 1.34064 timestamp: 1654932623.5347857 iteration: 22135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16387 FastRCNN class loss: 0.06293 FastRCNN total loss: 0.2268 L1 loss: 0.0000e+00 L2 loss: 1.04325 Learning rate: 0.02 Mask loss: 0.14768 RPN box loss: 0.00998 RPN score loss: 0.0076 RPN total loss: 0.01759 Total loss: 1.43532 timestamp: 1654932626.7481353 iteration: 22140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12224 FastRCNN class loss: 0.11402 FastRCNN total loss: 0.23626 L1 loss: 0.0000e+00 L2 loss: 1.04307 Learning rate: 0.02 Mask loss: 0.15214 RPN box loss: 0.02747 RPN score loss: 0.00731 RPN total loss: 0.03477 Total loss: 1.46625 timestamp: 1654932629.9058573 iteration: 22145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24772 FastRCNN class loss: 0.16813 FastRCNN total loss: 0.41584 L1 loss: 0.0000e+00 L2 loss: 1.04291 Learning rate: 0.02 Mask loss: 0.26568 RPN box loss: 0.05362 RPN score loss: 0.02146 RPN total loss: 0.07509 Total loss: 1.79952 timestamp: 1654932633.1503775 iteration: 22150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14881 FastRCNN class loss: 0.08903 FastRCNN total loss: 0.23783 L1 loss: 0.0000e+00 L2 loss: 1.04274 Learning rate: 0.02 Mask loss: 0.15431 RPN box loss: 0.06933 RPN score loss: 0.01284 RPN total loss: 0.08217 Total loss: 1.51706 timestamp: 1654932636.3151364 iteration: 22155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13672 FastRCNN class loss: 0.07736 FastRCNN total loss: 0.21409 L1 loss: 0.0000e+00 L2 loss: 1.04256 Learning rate: 0.02 Mask loss: 0.16816 RPN box loss: 0.07063 RPN score loss: 0.00955 RPN total loss: 0.08018 Total loss: 1.50499 timestamp: 1654932639.5616086 iteration: 22160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08234 FastRCNN class loss: 0.0722 FastRCNN total loss: 0.15454 L1 loss: 0.0000e+00 L2 loss: 1.04242 Learning rate: 0.02 Mask loss: 0.10475 RPN box loss: 0.0407 RPN score loss: 0.01045 RPN total loss: 0.05114 Total loss: 1.35285 timestamp: 1654932642.7984138 iteration: 22165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19163 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.27294 L1 loss: 0.0000e+00 L2 loss: 1.04226 Learning rate: 0.02 Mask loss: 0.14464 RPN box loss: 0.00878 RPN score loss: 0.00489 RPN total loss: 0.01367 Total loss: 1.47352 timestamp: 1654932645.9565725 iteration: 22170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18295 FastRCNN class loss: 0.08894 FastRCNN total loss: 0.27189 L1 loss: 0.0000e+00 L2 loss: 1.04209 Learning rate: 0.02 Mask loss: 0.1656 RPN box loss: 0.06049 RPN score loss: 0.00823 RPN total loss: 0.06872 Total loss: 1.5483 timestamp: 1654932649.0497177 iteration: 22175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09861 FastRCNN class loss: 0.084 FastRCNN total loss: 0.18261 L1 loss: 0.0000e+00 L2 loss: 1.04194 Learning rate: 0.02 Mask loss: 0.15186 RPN box loss: 0.02548 RPN score loss: 0.00384 RPN total loss: 0.02932 Total loss: 1.40573 timestamp: 1654932652.2013295 iteration: 22180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22982 FastRCNN class loss: 0.17129 FastRCNN total loss: 0.40111 L1 loss: 0.0000e+00 L2 loss: 1.04177 Learning rate: 0.02 Mask loss: 0.14678 RPN box loss: 0.02642 RPN score loss: 0.01175 RPN total loss: 0.03817 Total loss: 1.62782 timestamp: 1654932655.4729602 iteration: 22185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09657 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.14672 L1 loss: 0.0000e+00 L2 loss: 1.04161 Learning rate: 0.02 Mask loss: 0.13234 RPN box loss: 0.01192 RPN score loss: 0.00569 RPN total loss: 0.01761 Total loss: 1.33828 timestamp: 1654932658.6799166 iteration: 22190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12692 FastRCNN class loss: 0.07412 FastRCNN total loss: 0.20103 L1 loss: 0.0000e+00 L2 loss: 1.04143 Learning rate: 0.02 Mask loss: 0.15347 RPN box loss: 0.05531 RPN score loss: 0.0141 RPN total loss: 0.06941 Total loss: 1.46535 timestamp: 1654932661.8094356 iteration: 22195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20138 FastRCNN class loss: 0.07566 FastRCNN total loss: 0.27704 L1 loss: 0.0000e+00 L2 loss: 1.04125 Learning rate: 0.02 Mask loss: 0.30661 RPN box loss: 0.02162 RPN score loss: 0.00507 RPN total loss: 0.02669 Total loss: 1.65159 timestamp: 1654932665.0456567 iteration: 22200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11138 FastRCNN class loss: 0.10362 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 1.04109 Learning rate: 0.02 Mask loss: 0.11798 RPN box loss: 0.02887 RPN score loss: 0.00466 RPN total loss: 0.03353 Total loss: 1.40759 timestamp: 1654932668.2896795 iteration: 22205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.05341 FastRCNN total loss: 0.16306 L1 loss: 0.0000e+00 L2 loss: 1.04092 Learning rate: 0.02 Mask loss: 0.1265 RPN box loss: 0.02178 RPN score loss: 0.00386 RPN total loss: 0.02564 Total loss: 1.35613 timestamp: 1654932671.4482813 iteration: 22210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20246 FastRCNN class loss: 0.13267 FastRCNN total loss: 0.33513 L1 loss: 0.0000e+00 L2 loss: 1.04078 Learning rate: 0.02 Mask loss: 0.2454 RPN box loss: 0.0469 RPN score loss: 0.02008 RPN total loss: 0.06699 Total loss: 1.6883 timestamp: 1654932674.6508741 iteration: 22215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13528 FastRCNN class loss: 0.1329 FastRCNN total loss: 0.26818 L1 loss: 0.0000e+00 L2 loss: 1.04062 Learning rate: 0.02 Mask loss: 0.21151 RPN box loss: 0.01825 RPN score loss: 0.01415 RPN total loss: 0.0324 Total loss: 1.55271 timestamp: 1654932677.8578267 iteration: 22220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1454 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.23246 L1 loss: 0.0000e+00 L2 loss: 1.04044 Learning rate: 0.02 Mask loss: 0.13704 RPN box loss: 0.01652 RPN score loss: 0.00245 RPN total loss: 0.01896 Total loss: 1.42891 timestamp: 1654932681.078012 iteration: 22225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16949 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.24519 L1 loss: 0.0000e+00 L2 loss: 1.04026 Learning rate: 0.02 Mask loss: 0.14273 RPN box loss: 0.06889 RPN score loss: 0.01097 RPN total loss: 0.07987 Total loss: 1.50805 timestamp: 1654932684.2888207 iteration: 22230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20261 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.26858 L1 loss: 0.0000e+00 L2 loss: 1.0401 Learning rate: 0.02 Mask loss: 0.14516 RPN box loss: 0.0334 RPN score loss: 0.00469 RPN total loss: 0.03809 Total loss: 1.49193 timestamp: 1654932687.3788948 iteration: 22235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12738 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.21494 L1 loss: 0.0000e+00 L2 loss: 1.03992 Learning rate: 0.02 Mask loss: 0.11291 RPN box loss: 0.03748 RPN score loss: 0.00962 RPN total loss: 0.0471 Total loss: 1.41487 timestamp: 1654932690.6202931 iteration: 22240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12603 FastRCNN class loss: 0.11091 FastRCNN total loss: 0.23695 L1 loss: 0.0000e+00 L2 loss: 1.03977 Learning rate: 0.02 Mask loss: 0.20674 RPN box loss: 0.02273 RPN score loss: 0.00861 RPN total loss: 0.03134 Total loss: 1.5148 timestamp: 1654932693.8747823 iteration: 22245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11947 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.19922 L1 loss: 0.0000e+00 L2 loss: 1.03963 Learning rate: 0.02 Mask loss: 0.18304 RPN box loss: 0.02391 RPN score loss: 0.00355 RPN total loss: 0.02746 Total loss: 1.44935 timestamp: 1654932697.1130595 iteration: 22250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21637 FastRCNN class loss: 0.0973 FastRCNN total loss: 0.31367 L1 loss: 0.0000e+00 L2 loss: 1.03945 Learning rate: 0.02 Mask loss: 0.13579 RPN box loss: 0.05051 RPN score loss: 0.00792 RPN total loss: 0.05843 Total loss: 1.54734 timestamp: 1654932700.2591357 iteration: 22255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07478 FastRCNN class loss: 0.04887 FastRCNN total loss: 0.12365 L1 loss: 0.0000e+00 L2 loss: 1.03925 Learning rate: 0.02 Mask loss: 0.14074 RPN box loss: 0.03534 RPN score loss: 0.00691 RPN total loss: 0.04225 Total loss: 1.34589 timestamp: 1654932703.5033486 iteration: 22260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15438 FastRCNN class loss: 0.13015 FastRCNN total loss: 0.28453 L1 loss: 0.0000e+00 L2 loss: 1.03908 Learning rate: 0.02 Mask loss: 0.20935 RPN box loss: 0.05256 RPN score loss: 0.01202 RPN total loss: 0.06459 Total loss: 1.59755 timestamp: 1654932706.663681 iteration: 22265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.143 FastRCNN class loss: 0.0906 FastRCNN total loss: 0.2336 L1 loss: 0.0000e+00 L2 loss: 1.03891 Learning rate: 0.02 Mask loss: 0.13064 RPN box loss: 0.06677 RPN score loss: 0.0091 RPN total loss: 0.07586 Total loss: 1.47902 timestamp: 1654932709.918027 iteration: 22270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1178 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.17723 L1 loss: 0.0000e+00 L2 loss: 1.03876 Learning rate: 0.02 Mask loss: 0.12837 RPN box loss: 0.04589 RPN score loss: 0.00695 RPN total loss: 0.05284 Total loss: 1.39721 timestamp: 1654932713.060206 iteration: 22275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08893 FastRCNN class loss: 0.07868 FastRCNN total loss: 0.16761 L1 loss: 0.0000e+00 L2 loss: 1.03858 Learning rate: 0.02 Mask loss: 0.1082 RPN box loss: 0.03781 RPN score loss: 0.00715 RPN total loss: 0.04496 Total loss: 1.35935 timestamp: 1654932716.1987257 iteration: 22280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10598 FastRCNN class loss: 0.06373 FastRCNN total loss: 0.16971 L1 loss: 0.0000e+00 L2 loss: 1.03842 Learning rate: 0.02 Mask loss: 0.11655 RPN box loss: 0.02226 RPN score loss: 0.0081 RPN total loss: 0.03035 Total loss: 1.35504 timestamp: 1654932719.3965335 iteration: 22285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18789 FastRCNN class loss: 0.13497 FastRCNN total loss: 0.32286 L1 loss: 0.0000e+00 L2 loss: 1.03828 Learning rate: 0.02 Mask loss: 0.16237 RPN box loss: 0.02139 RPN score loss: 0.01074 RPN total loss: 0.03212 Total loss: 1.55564 timestamp: 1654932722.6243994 iteration: 22290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17285 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.24322 L1 loss: 0.0000e+00 L2 loss: 1.03811 Learning rate: 0.02 Mask loss: 0.12157 RPN box loss: 0.01499 RPN score loss: 0.00414 RPN total loss: 0.01913 Total loss: 1.42204 timestamp: 1654932725.8982277 iteration: 22295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25804 FastRCNN class loss: 0.08913 FastRCNN total loss: 0.34718 L1 loss: 0.0000e+00 L2 loss: 1.03793 Learning rate: 0.02 Mask loss: 0.18867 RPN box loss: 0.01948 RPN score loss: 0.00299 RPN total loss: 0.02247 Total loss: 1.59625 timestamp: 1654932729.131566 iteration: 22300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12913 FastRCNN class loss: 0.08875 FastRCNN total loss: 0.21788 L1 loss: 0.0000e+00 L2 loss: 1.03774 Learning rate: 0.02 Mask loss: 0.12562 RPN box loss: 0.00871 RPN score loss: 0.01107 RPN total loss: 0.01979 Total loss: 1.40104 timestamp: 1654932732.349706 iteration: 22305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14871 FastRCNN class loss: 0.09279 FastRCNN total loss: 0.2415 L1 loss: 0.0000e+00 L2 loss: 1.03761 Learning rate: 0.02 Mask loss: 0.18581 RPN box loss: 0.06631 RPN score loss: 0.0052 RPN total loss: 0.0715 Total loss: 1.53642 timestamp: 1654932735.5158906 iteration: 22310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05644 FastRCNN class loss: 0.05988 FastRCNN total loss: 0.11632 L1 loss: 0.0000e+00 L2 loss: 1.03746 Learning rate: 0.02 Mask loss: 0.1137 RPN box loss: 0.03454 RPN score loss: 0.00455 RPN total loss: 0.03909 Total loss: 1.30657 timestamp: 1654932738.7411199 iteration: 22315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.136 FastRCNN class loss: 0.08918 FastRCNN total loss: 0.22517 L1 loss: 0.0000e+00 L2 loss: 1.03731 Learning rate: 0.02 Mask loss: 0.11287 RPN box loss: 0.04133 RPN score loss: 0.00582 RPN total loss: 0.04715 Total loss: 1.4225 timestamp: 1654932741.9601047 iteration: 22320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19822 FastRCNN class loss: 0.08554 FastRCNN total loss: 0.28377 L1 loss: 0.0000e+00 L2 loss: 1.03715 Learning rate: 0.02 Mask loss: 0.15841 RPN box loss: 0.04425 RPN score loss: 0.01585 RPN total loss: 0.0601 Total loss: 1.53943 timestamp: 1654932745.2070625 iteration: 22325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1379 FastRCNN class loss: 0.05706 FastRCNN total loss: 0.19496 L1 loss: 0.0000e+00 L2 loss: 1.03699 Learning rate: 0.02 Mask loss: 0.12843 RPN box loss: 0.01244 RPN score loss: 0.00565 RPN total loss: 0.01809 Total loss: 1.37847 timestamp: 1654932748.4806988 iteration: 22330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1415 FastRCNN class loss: 0.08897 FastRCNN total loss: 0.23047 L1 loss: 0.0000e+00 L2 loss: 1.03684 Learning rate: 0.02 Mask loss: 0.15926 RPN box loss: 0.05526 RPN score loss: 0.0051 RPN total loss: 0.06036 Total loss: 1.48693 timestamp: 1654932751.7187684 iteration: 22335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.04205 FastRCNN total loss: 0.12271 L1 loss: 0.0000e+00 L2 loss: 1.03669 Learning rate: 0.02 Mask loss: 0.14241 RPN box loss: 0.05167 RPN score loss: 0.01021 RPN total loss: 0.06189 Total loss: 1.3637 timestamp: 1654932754.9610474 iteration: 22340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08206 FastRCNN class loss: 0.08195 FastRCNN total loss: 0.16401 L1 loss: 0.0000e+00 L2 loss: 1.03651 Learning rate: 0.02 Mask loss: 0.11063 RPN box loss: 0.0108 RPN score loss: 0.00417 RPN total loss: 0.01498 Total loss: 1.32612 timestamp: 1654932758.1454108 iteration: 22345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1528 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.21256 L1 loss: 0.0000e+00 L2 loss: 1.03633 Learning rate: 0.02 Mask loss: 0.16968 RPN box loss: 0.0553 RPN score loss: 0.00716 RPN total loss: 0.06246 Total loss: 1.48103 timestamp: 1654932761.388018 iteration: 22350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15206 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.22957 L1 loss: 0.0000e+00 L2 loss: 1.03616 Learning rate: 0.02 Mask loss: 0.11839 RPN box loss: 0.0175 RPN score loss: 0.00998 RPN total loss: 0.02748 Total loss: 1.41159 timestamp: 1654932764.7071023 iteration: 22355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30314 FastRCNN class loss: 0.11742 FastRCNN total loss: 0.42056 L1 loss: 0.0000e+00 L2 loss: 1.03601 Learning rate: 0.02 Mask loss: 0.16841 RPN box loss: 0.0264 RPN score loss: 0.01539 RPN total loss: 0.04179 Total loss: 1.66677 timestamp: 1654932767.9454577 iteration: 22360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08765 FastRCNN class loss: 0.04187 FastRCNN total loss: 0.12953 L1 loss: 0.0000e+00 L2 loss: 1.03585 Learning rate: 0.02 Mask loss: 0.25371 RPN box loss: 0.04176 RPN score loss: 0.00243 RPN total loss: 0.04419 Total loss: 1.46327 timestamp: 1654932771.236101 iteration: 22365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06903 FastRCNN class loss: 0.06231 FastRCNN total loss: 0.13134 L1 loss: 0.0000e+00 L2 loss: 1.0357 Learning rate: 0.02 Mask loss: 0.09955 RPN box loss: 0.07177 RPN score loss: 0.00339 RPN total loss: 0.07516 Total loss: 1.34175 timestamp: 1654932774.4138906 iteration: 22370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07786 FastRCNN class loss: 0.07038 FastRCNN total loss: 0.14824 L1 loss: 0.0000e+00 L2 loss: 1.03552 Learning rate: 0.02 Mask loss: 0.12706 RPN box loss: 0.0235 RPN score loss: 0.01215 RPN total loss: 0.03565 Total loss: 1.34647 timestamp: 1654932777.7355945 iteration: 22375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11822 FastRCNN class loss: 0.06764 FastRCNN total loss: 0.18585 L1 loss: 0.0000e+00 L2 loss: 1.03533 Learning rate: 0.02 Mask loss: 0.16007 RPN box loss: 0.02049 RPN score loss: 0.00335 RPN total loss: 0.02384 Total loss: 1.40509 timestamp: 1654932780.9375808 iteration: 22380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12244 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.2007 L1 loss: 0.0000e+00 L2 loss: 1.03515 Learning rate: 0.02 Mask loss: 0.12404 RPN box loss: 0.01999 RPN score loss: 0.00114 RPN total loss: 0.02113 Total loss: 1.38103 timestamp: 1654932784.0951605 iteration: 22385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12186 FastRCNN class loss: 0.08688 FastRCNN total loss: 0.20874 L1 loss: 0.0000e+00 L2 loss: 1.03497 Learning rate: 0.02 Mask loss: 0.13203 RPN box loss: 0.06131 RPN score loss: 0.01 RPN total loss: 0.07131 Total loss: 1.44705 timestamp: 1654932787.24667 iteration: 22390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10786 FastRCNN class loss: 0.05734 FastRCNN total loss: 0.1652 L1 loss: 0.0000e+00 L2 loss: 1.0348 Learning rate: 0.02 Mask loss: 0.14263 RPN box loss: 0.01324 RPN score loss: 0.00536 RPN total loss: 0.01861 Total loss: 1.36125 timestamp: 1654932790.4763284 iteration: 22395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10589 FastRCNN class loss: 0.05232 FastRCNN total loss: 0.15821 L1 loss: 0.0000e+00 L2 loss: 1.03465 Learning rate: 0.02 Mask loss: 0.0993 RPN box loss: 0.02729 RPN score loss: 0.00769 RPN total loss: 0.03498 Total loss: 1.32714 timestamp: 1654932793.7314155 iteration: 22400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16699 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.24751 L1 loss: 0.0000e+00 L2 loss: 1.03449 Learning rate: 0.02 Mask loss: 0.12114 RPN box loss: 0.0759 RPN score loss: 0.00796 RPN total loss: 0.08386 Total loss: 1.48701 timestamp: 1654932796.94967 iteration: 22405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20029 FastRCNN class loss: 0.10675 FastRCNN total loss: 0.30704 L1 loss: 0.0000e+00 L2 loss: 1.03433 Learning rate: 0.02 Mask loss: 0.16188 RPN box loss: 0.01365 RPN score loss: 0.00541 RPN total loss: 0.01906 Total loss: 1.5223 timestamp: 1654932800.1937122 iteration: 22410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1465 FastRCNN class loss: 0.10428 FastRCNN total loss: 0.25078 L1 loss: 0.0000e+00 L2 loss: 1.03415 Learning rate: 0.02 Mask loss: 0.1751 RPN box loss: 0.03444 RPN score loss: 0.01075 RPN total loss: 0.04519 Total loss: 1.50522 timestamp: 1654932803.4287415 iteration: 22415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18552 FastRCNN class loss: 0.08651 FastRCNN total loss: 0.27203 L1 loss: 0.0000e+00 L2 loss: 1.03396 Learning rate: 0.02 Mask loss: 0.12706 RPN box loss: 0.05725 RPN score loss: 0.00549 RPN total loss: 0.06273 Total loss: 1.49578 timestamp: 1654932806.7454588 iteration: 22420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14947 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.23886 L1 loss: 0.0000e+00 L2 loss: 1.0338 Learning rate: 0.02 Mask loss: 0.17746 RPN box loss: 0.03285 RPN score loss: 0.01506 RPN total loss: 0.04791 Total loss: 1.49804 timestamp: 1654932809.957458 iteration: 22425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13209 FastRCNN class loss: 0.12941 FastRCNN total loss: 0.2615 L1 loss: 0.0000e+00 L2 loss: 1.03364 Learning rate: 0.02 Mask loss: 0.1797 RPN box loss: 0.0688 RPN score loss: 0.01483 RPN total loss: 0.08363 Total loss: 1.55848 timestamp: 1654932813.122163 iteration: 22430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17062 FastRCNN class loss: 0.10435 FastRCNN total loss: 0.27497 L1 loss: 0.0000e+00 L2 loss: 1.0335 Learning rate: 0.02 Mask loss: 0.15719 RPN box loss: 0.04319 RPN score loss: 0.00591 RPN total loss: 0.04909 Total loss: 1.51475 timestamp: 1654932816.3249068 iteration: 22435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10903 FastRCNN class loss: 0.05679 FastRCNN total loss: 0.16582 L1 loss: 0.0000e+00 L2 loss: 1.03334 Learning rate: 0.02 Mask loss: 0.11055 RPN box loss: 0.01771 RPN score loss: 0.00253 RPN total loss: 0.02024 Total loss: 1.32995 timestamp: 1654932819.4852283 iteration: 22440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.09536 FastRCNN total loss: 0.24678 L1 loss: 0.0000e+00 L2 loss: 1.03318 Learning rate: 0.02 Mask loss: 0.24584 RPN box loss: 0.11537 RPN score loss: 0.00817 RPN total loss: 0.12354 Total loss: 1.64934 timestamp: 1654932822.75102 iteration: 22445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20267 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.29961 L1 loss: 0.0000e+00 L2 loss: 1.03302 Learning rate: 0.02 Mask loss: 0.19019 RPN box loss: 0.03353 RPN score loss: 0.00712 RPN total loss: 0.04065 Total loss: 1.56347 timestamp: 1654932825.9322894 iteration: 22450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1119 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.18811 L1 loss: 0.0000e+00 L2 loss: 1.03286 Learning rate: 0.02 Mask loss: 0.15965 RPN box loss: 0.03394 RPN score loss: 0.02884 RPN total loss: 0.06278 Total loss: 1.4434 timestamp: 1654932829.0801797 iteration: 22455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13395 FastRCNN class loss: 0.08614 FastRCNN total loss: 0.22009 L1 loss: 0.0000e+00 L2 loss: 1.03271 Learning rate: 0.02 Mask loss: 0.23371 RPN box loss: 0.02607 RPN score loss: 0.00264 RPN total loss: 0.02871 Total loss: 1.51522 timestamp: 1654932832.2873662 iteration: 22460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20854 FastRCNN class loss: 0.12072 FastRCNN total loss: 0.32926 L1 loss: 0.0000e+00 L2 loss: 1.03254 Learning rate: 0.02 Mask loss: 0.25422 RPN box loss: 0.02159 RPN score loss: 0.00533 RPN total loss: 0.02692 Total loss: 1.64293 timestamp: 1654932835.4546854 iteration: 22465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12188 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.19796 L1 loss: 0.0000e+00 L2 loss: 1.03239 Learning rate: 0.02 Mask loss: 0.11863 RPN box loss: 0.02121 RPN score loss: 0.00549 RPN total loss: 0.0267 Total loss: 1.37567 timestamp: 1654932838.6939714 iteration: 22470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11708 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.19238 L1 loss: 0.0000e+00 L2 loss: 1.03223 Learning rate: 0.02 Mask loss: 0.14553 RPN box loss: 0.02779 RPN score loss: 0.00731 RPN total loss: 0.0351 Total loss: 1.40525 timestamp: 1654932841.873021 iteration: 22475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12895 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.19843 L1 loss: 0.0000e+00 L2 loss: 1.03206 Learning rate: 0.02 Mask loss: 0.15029 RPN box loss: 0.04662 RPN score loss: 0.00173 RPN total loss: 0.04835 Total loss: 1.42912 timestamp: 1654932845.0782351 iteration: 22480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13441 FastRCNN class loss: 0.10655 FastRCNN total loss: 0.24096 L1 loss: 0.0000e+00 L2 loss: 1.03189 Learning rate: 0.02 Mask loss: 0.15139 RPN box loss: 0.0774 RPN score loss: 0.0086 RPN total loss: 0.086 Total loss: 1.51024 timestamp: 1654932848.3304808 iteration: 22485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09323 FastRCNN class loss: 0.07374 FastRCNN total loss: 0.16696 L1 loss: 0.0000e+00 L2 loss: 1.03173 Learning rate: 0.02 Mask loss: 0.10527 RPN box loss: 0.04156 RPN score loss: 0.00355 RPN total loss: 0.04511 Total loss: 1.34908 timestamp: 1654932851.542648 iteration: 22490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12618 FastRCNN class loss: 0.0707 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 1.03157 Learning rate: 0.02 Mask loss: 0.09495 RPN box loss: 0.01175 RPN score loss: 0.00321 RPN total loss: 0.01496 Total loss: 1.33836 timestamp: 1654932854.7452898 iteration: 22495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09601 FastRCNN class loss: 0.06299 FastRCNN total loss: 0.159 L1 loss: 0.0000e+00 L2 loss: 1.03142 Learning rate: 0.02 Mask loss: 0.09319 RPN box loss: 0.00873 RPN score loss: 0.00396 RPN total loss: 0.01269 Total loss: 1.2963 timestamp: 1654932857.9522014 iteration: 22500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10277 FastRCNN class loss: 0.10119 FastRCNN total loss: 0.20396 L1 loss: 0.0000e+00 L2 loss: 1.03124 Learning rate: 0.02 Mask loss: 0.08324 RPN box loss: 0.07993 RPN score loss: 0.01383 RPN total loss: 0.09376 Total loss: 1.41219 timestamp: 1654932861.1147244 iteration: 22505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15374 FastRCNN class loss: 0.0853 FastRCNN total loss: 0.23904 L1 loss: 0.0000e+00 L2 loss: 1.03108 Learning rate: 0.02 Mask loss: 0.15704 RPN box loss: 0.03247 RPN score loss: 0.00602 RPN total loss: 0.03849 Total loss: 1.46565 timestamp: 1654932864.3718746 iteration: 22510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10644 FastRCNN class loss: 0.09449 FastRCNN total loss: 0.20093 L1 loss: 0.0000e+00 L2 loss: 1.03091 Learning rate: 0.02 Mask loss: 0.13803 RPN box loss: 0.03802 RPN score loss: 0.00385 RPN total loss: 0.04187 Total loss: 1.41174 timestamp: 1654932867.6642947 iteration: 22515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17651 FastRCNN class loss: 0.12642 FastRCNN total loss: 0.30293 L1 loss: 0.0000e+00 L2 loss: 1.03076 Learning rate: 0.02 Mask loss: 0.22472 RPN box loss: 0.06239 RPN score loss: 0.01214 RPN total loss: 0.07453 Total loss: 1.63294 timestamp: 1654932870.8335848 iteration: 22520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11713 FastRCNN class loss: 0.07008 FastRCNN total loss: 0.18721 L1 loss: 0.0000e+00 L2 loss: 1.03061 Learning rate: 0.02 Mask loss: 0.1753 RPN box loss: 0.05516 RPN score loss: 0.00856 RPN total loss: 0.06372 Total loss: 1.45684 timestamp: 1654932874.0782464 iteration: 22525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10368 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.1927 L1 loss: 0.0000e+00 L2 loss: 1.03044 Learning rate: 0.02 Mask loss: 0.20318 RPN box loss: 0.0506 RPN score loss: 0.00755 RPN total loss: 0.05815 Total loss: 1.48446 timestamp: 1654932877.2627294 iteration: 22530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11217 FastRCNN class loss: 0.05962 FastRCNN total loss: 0.17179 L1 loss: 0.0000e+00 L2 loss: 1.03027 Learning rate: 0.02 Mask loss: 0.13367 RPN box loss: 0.01654 RPN score loss: 0.00317 RPN total loss: 0.01971 Total loss: 1.35543 timestamp: 1654932880.5220866 iteration: 22535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12072 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.19573 L1 loss: 0.0000e+00 L2 loss: 1.03011 Learning rate: 0.02 Mask loss: 0.1743 RPN box loss: 0.0114 RPN score loss: 0.01084 RPN total loss: 0.02224 Total loss: 1.42238 timestamp: 1654932883.7522652 iteration: 22540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1261 FastRCNN class loss: 0.11715 FastRCNN total loss: 0.24325 L1 loss: 0.0000e+00 L2 loss: 1.02996 Learning rate: 0.02 Mask loss: 0.20482 RPN box loss: 0.05558 RPN score loss: 0.00755 RPN total loss: 0.06312 Total loss: 1.54114 timestamp: 1654932886.9821603 iteration: 22545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09183 FastRCNN class loss: 0.04487 FastRCNN total loss: 0.13671 L1 loss: 0.0000e+00 L2 loss: 1.0298 Learning rate: 0.02 Mask loss: 0.1831 RPN box loss: 0.04757 RPN score loss: 0.00687 RPN total loss: 0.05444 Total loss: 1.40405 timestamp: 1654932890.1818278 iteration: 22550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1778 FastRCNN class loss: 0.09387 FastRCNN total loss: 0.27167 L1 loss: 0.0000e+00 L2 loss: 1.02965 Learning rate: 0.02 Mask loss: 0.15022 RPN box loss: 0.0114 RPN score loss: 0.00466 RPN total loss: 0.01606 Total loss: 1.4676 timestamp: 1654932893.3495464 iteration: 22555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17344 FastRCNN class loss: 0.07416 FastRCNN total loss: 0.2476 L1 loss: 0.0000e+00 L2 loss: 1.02947 Learning rate: 0.02 Mask loss: 0.27555 RPN box loss: 0.04108 RPN score loss: 0.00916 RPN total loss: 0.05025 Total loss: 1.60286 timestamp: 1654932896.633275 iteration: 22560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11285 FastRCNN class loss: 0.159 FastRCNN total loss: 0.27185 L1 loss: 0.0000e+00 L2 loss: 1.0293 Learning rate: 0.02 Mask loss: 0.17923 RPN box loss: 0.03805 RPN score loss: 0.01054 RPN total loss: 0.04859 Total loss: 1.52898 timestamp: 1654932899.802463 iteration: 22565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17187 FastRCNN class loss: 0.13776 FastRCNN total loss: 0.30962 L1 loss: 0.0000e+00 L2 loss: 1.02913 Learning rate: 0.02 Mask loss: 0.16839 RPN box loss: 0.04211 RPN score loss: 0.00945 RPN total loss: 0.05156 Total loss: 1.55871 timestamp: 1654932902.9623306 iteration: 22570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1146 FastRCNN class loss: 0.06367 FastRCNN total loss: 0.17827 L1 loss: 0.0000e+00 L2 loss: 1.02896 Learning rate: 0.02 Mask loss: 0.10695 RPN box loss: 0.01528 RPN score loss: 0.00231 RPN total loss: 0.01759 Total loss: 1.33176 timestamp: 1654932906.135659 iteration: 22575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12079 FastRCNN class loss: 0.08724 FastRCNN total loss: 0.20803 L1 loss: 0.0000e+00 L2 loss: 1.02879 Learning rate: 0.02 Mask loss: 0.23427 RPN box loss: 0.0088 RPN score loss: 0.00857 RPN total loss: 0.01737 Total loss: 1.48846 timestamp: 1654932909.2750828 iteration: 22580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15114 FastRCNN class loss: 0.12657 FastRCNN total loss: 0.27771 L1 loss: 0.0000e+00 L2 loss: 1.02863 Learning rate: 0.02 Mask loss: 0.22656 RPN box loss: 0.06523 RPN score loss: 0.01499 RPN total loss: 0.08022 Total loss: 1.61312 timestamp: 1654932912.4737673 iteration: 22585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13983 FastRCNN class loss: 0.04518 FastRCNN total loss: 0.18501 L1 loss: 0.0000e+00 L2 loss: 1.02846 Learning rate: 0.02 Mask loss: 0.18008 RPN box loss: 0.03423 RPN score loss: 0.00175 RPN total loss: 0.03598 Total loss: 1.42953 timestamp: 1654932915.6302369 iteration: 22590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14526 FastRCNN class loss: 0.07646 FastRCNN total loss: 0.22171 L1 loss: 0.0000e+00 L2 loss: 1.02831 Learning rate: 0.02 Mask loss: 0.10392 RPN box loss: 0.02001 RPN score loss: 0.00221 RPN total loss: 0.02222 Total loss: 1.37616 timestamp: 1654932918.9114394 iteration: 22595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19615 FastRCNN class loss: 0.10747 FastRCNN total loss: 0.30362 L1 loss: 0.0000e+00 L2 loss: 1.02812 Learning rate: 0.02 Mask loss: 0.17319 RPN box loss: 0.06936 RPN score loss: 0.01098 RPN total loss: 0.08034 Total loss: 1.58527 timestamp: 1654932922.0908017 iteration: 22600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14636 FastRCNN class loss: 0.07569 FastRCNN total loss: 0.22204 L1 loss: 0.0000e+00 L2 loss: 1.02796 Learning rate: 0.02 Mask loss: 0.17429 RPN box loss: 0.05173 RPN score loss: 0.00194 RPN total loss: 0.05367 Total loss: 1.47796 timestamp: 1654932925.305812 iteration: 22605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10101 FastRCNN class loss: 0.05047 FastRCNN total loss: 0.15148 L1 loss: 0.0000e+00 L2 loss: 1.02782 Learning rate: 0.02 Mask loss: 0.17076 RPN box loss: 0.00797 RPN score loss: 0.00391 RPN total loss: 0.01188 Total loss: 1.36194 timestamp: 1654932928.4645581 iteration: 22610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07557 FastRCNN class loss: 0.06199 FastRCNN total loss: 0.13756 L1 loss: 0.0000e+00 L2 loss: 1.02764 Learning rate: 0.02 Mask loss: 0.08717 RPN box loss: 0.03228 RPN score loss: 0.00412 RPN total loss: 0.0364 Total loss: 1.28878 timestamp: 1654932931.7262068 iteration: 22615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12196 FastRCNN class loss: 0.09348 FastRCNN total loss: 0.21544 L1 loss: 0.0000e+00 L2 loss: 1.02747 Learning rate: 0.02 Mask loss: 0.20579 RPN box loss: 0.02493 RPN score loss: 0.01006 RPN total loss: 0.03499 Total loss: 1.48368 timestamp: 1654932934.9565785 iteration: 22620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17032 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.23688 L1 loss: 0.0000e+00 L2 loss: 1.02732 Learning rate: 0.02 Mask loss: 0.28166 RPN box loss: 0.0267 RPN score loss: 0.00389 RPN total loss: 0.03059 Total loss: 1.57645 timestamp: 1654932938.1334414 iteration: 22625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13364 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.19979 L1 loss: 0.0000e+00 L2 loss: 1.02716 Learning rate: 0.02 Mask loss: 0.12261 RPN box loss: 0.01722 RPN score loss: 0.00773 RPN total loss: 0.02495 Total loss: 1.3745 timestamp: 1654932941.3955104 iteration: 22630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11408 FastRCNN class loss: 0.09456 FastRCNN total loss: 0.20864 L1 loss: 0.0000e+00 L2 loss: 1.027 Learning rate: 0.02 Mask loss: 0.13011 RPN box loss: 0.04792 RPN score loss: 0.01063 RPN total loss: 0.05855 Total loss: 1.4243 timestamp: 1654932944.6025443 iteration: 22635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10689 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.17018 L1 loss: 0.0000e+00 L2 loss: 1.02683 Learning rate: 0.02 Mask loss: 0.10462 RPN box loss: 0.00996 RPN score loss: 0.00471 RPN total loss: 0.01467 Total loss: 1.3163 timestamp: 1654932947.8799624 iteration: 22640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20793 FastRCNN class loss: 0.10839 FastRCNN total loss: 0.31633 L1 loss: 0.0000e+00 L2 loss: 1.02665 Learning rate: 0.02 Mask loss: 0.16293 RPN box loss: 0.03208 RPN score loss: 0.00537 RPN total loss: 0.03745 Total loss: 1.54336 timestamp: 1654932951.120005 iteration: 22645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10401 FastRCNN class loss: 0.0542 FastRCNN total loss: 0.15821 L1 loss: 0.0000e+00 L2 loss: 1.02651 Learning rate: 0.02 Mask loss: 0.09937 RPN box loss: 0.07973 RPN score loss: 0.00789 RPN total loss: 0.08762 Total loss: 1.37172 timestamp: 1654932954.295462 iteration: 22650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12435 FastRCNN class loss: 0.06829 FastRCNN total loss: 0.19265 L1 loss: 0.0000e+00 L2 loss: 1.02636 Learning rate: 0.02 Mask loss: 0.11459 RPN box loss: 0.01747 RPN score loss: 0.00185 RPN total loss: 0.01931 Total loss: 1.35291 timestamp: 1654932957.4877543 iteration: 22655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13197 FastRCNN class loss: 0.08072 FastRCNN total loss: 0.21269 L1 loss: 0.0000e+00 L2 loss: 1.02619 Learning rate: 0.02 Mask loss: 0.15866 RPN box loss: 0.02068 RPN score loss: 0.00599 RPN total loss: 0.02667 Total loss: 1.42422 timestamp: 1654932960.652156 iteration: 22660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2013 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.28344 L1 loss: 0.0000e+00 L2 loss: 1.02602 Learning rate: 0.02 Mask loss: 0.15151 RPN box loss: 0.02363 RPN score loss: 0.00744 RPN total loss: 0.03107 Total loss: 1.49203 timestamp: 1654932963.883972 iteration: 22665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16697 FastRCNN class loss: 0.10895 FastRCNN total loss: 0.27592 L1 loss: 0.0000e+00 L2 loss: 1.02585 Learning rate: 0.02 Mask loss: 0.13702 RPN box loss: 0.04858 RPN score loss: 0.01314 RPN total loss: 0.06172 Total loss: 1.50052 timestamp: 1654932967.0522768 iteration: 22670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13108 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.20841 L1 loss: 0.0000e+00 L2 loss: 1.02569 Learning rate: 0.02 Mask loss: 0.15492 RPN box loss: 0.06699 RPN score loss: 0.00761 RPN total loss: 0.0746 Total loss: 1.46362 timestamp: 1654932970.2042003 iteration: 22675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15361 FastRCNN class loss: 0.08743 FastRCNN total loss: 0.24104 L1 loss: 0.0000e+00 L2 loss: 1.02553 Learning rate: 0.02 Mask loss: 0.15507 RPN box loss: 0.01414 RPN score loss: 0.00738 RPN total loss: 0.02152 Total loss: 1.44316 timestamp: 1654932973.4152315 iteration: 22680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12969 FastRCNN class loss: 0.10146 FastRCNN total loss: 0.23114 L1 loss: 0.0000e+00 L2 loss: 1.02536 Learning rate: 0.02 Mask loss: 0.20609 RPN box loss: 0.02375 RPN score loss: 0.00952 RPN total loss: 0.03327 Total loss: 1.49587 timestamp: 1654932976.6254866 iteration: 22685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09385 FastRCNN class loss: 0.09976 FastRCNN total loss: 0.19361 L1 loss: 0.0000e+00 L2 loss: 1.02519 Learning rate: 0.02 Mask loss: 0.13964 RPN box loss: 0.0682 RPN score loss: 0.00927 RPN total loss: 0.07747 Total loss: 1.4359 timestamp: 1654932979.8132322 iteration: 22690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15172 FastRCNN class loss: 0.14839 FastRCNN total loss: 0.30011 L1 loss: 0.0000e+00 L2 loss: 1.02502 Learning rate: 0.02 Mask loss: 0.18084 RPN box loss: 0.06523 RPN score loss: 0.01434 RPN total loss: 0.07957 Total loss: 1.58553 timestamp: 1654932983.031347 iteration: 22695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06129 FastRCNN class loss: 0.04765 FastRCNN total loss: 0.10894 L1 loss: 0.0000e+00 L2 loss: 1.02484 Learning rate: 0.02 Mask loss: 0.14383 RPN box loss: 0.03141 RPN score loss: 0.00848 RPN total loss: 0.03989 Total loss: 1.3175 timestamp: 1654932986.2696629 iteration: 22700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10277 FastRCNN class loss: 0.05712 FastRCNN total loss: 0.15989 L1 loss: 0.0000e+00 L2 loss: 1.02466 Learning rate: 0.02 Mask loss: 0.14547 RPN box loss: 0.05473 RPN score loss: 0.00562 RPN total loss: 0.06034 Total loss: 1.39037 timestamp: 1654932989.5068402 iteration: 22705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12025 FastRCNN class loss: 0.10203 FastRCNN total loss: 0.22229 L1 loss: 0.0000e+00 L2 loss: 1.02451 Learning rate: 0.02 Mask loss: 0.14708 RPN box loss: 0.046 RPN score loss: 0.01166 RPN total loss: 0.05766 Total loss: 1.45153 timestamp: 1654932992.7239242 iteration: 22710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08276 FastRCNN class loss: 0.045 FastRCNN total loss: 0.12776 L1 loss: 0.0000e+00 L2 loss: 1.02435 Learning rate: 0.02 Mask loss: 0.12907 RPN box loss: 0.02557 RPN score loss: 0.00372 RPN total loss: 0.0293 Total loss: 1.31048 timestamp: 1654932995.9322407 iteration: 22715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15446 FastRCNN class loss: 0.13222 FastRCNN total loss: 0.28668 L1 loss: 0.0000e+00 L2 loss: 1.0242 Learning rate: 0.02 Mask loss: 0.11073 RPN box loss: 0.03404 RPN score loss: 0.00711 RPN total loss: 0.04115 Total loss: 1.46275 timestamp: 1654932999.128531 iteration: 22720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11782 FastRCNN class loss: 0.0989 FastRCNN total loss: 0.21672 L1 loss: 0.0000e+00 L2 loss: 1.02404 Learning rate: 0.02 Mask loss: 0.15525 RPN box loss: 0.04398 RPN score loss: 0.01377 RPN total loss: 0.05776 Total loss: 1.45377 timestamp: 1654933002.27338 iteration: 22725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10849 FastRCNN class loss: 0.08512 FastRCNN total loss: 0.19361 L1 loss: 0.0000e+00 L2 loss: 1.02386 Learning rate: 0.02 Mask loss: 0.15077 RPN box loss: 0.03667 RPN score loss: 0.00802 RPN total loss: 0.0447 Total loss: 1.41294 timestamp: 1654933005.4629226 iteration: 22730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09775 FastRCNN class loss: 0.04926 FastRCNN total loss: 0.14701 L1 loss: 0.0000e+00 L2 loss: 1.02371 Learning rate: 0.02 Mask loss: 0.09208 RPN box loss: 0.03928 RPN score loss: 0.0103 RPN total loss: 0.04958 Total loss: 1.31237 timestamp: 1654933008.6807334 iteration: 22735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12141 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.19983 L1 loss: 0.0000e+00 L2 loss: 1.02355 Learning rate: 0.02 Mask loss: 0.1704 RPN box loss: 0.02517 RPN score loss: 0.00357 RPN total loss: 0.02874 Total loss: 1.42251 timestamp: 1654933011.9203277 iteration: 22740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18678 FastRCNN class loss: 0.09444 FastRCNN total loss: 0.28122 L1 loss: 0.0000e+00 L2 loss: 1.02338 Learning rate: 0.02 Mask loss: 0.18001 RPN box loss: 0.04316 RPN score loss: 0.00917 RPN total loss: 0.05232 Total loss: 1.53693 timestamp: 1654933015.0683413 iteration: 22745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16228 FastRCNN class loss: 0.10171 FastRCNN total loss: 0.26399 L1 loss: 0.0000e+00 L2 loss: 1.02324 Learning rate: 0.02 Mask loss: 0.14793 RPN box loss: 0.12841 RPN score loss: 0.00634 RPN total loss: 0.13475 Total loss: 1.56991 timestamp: 1654933018.3005514 iteration: 22750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17089 FastRCNN class loss: 0.07583 FastRCNN total loss: 0.24673 L1 loss: 0.0000e+00 L2 loss: 1.02308 Learning rate: 0.02 Mask loss: 0.12948 RPN box loss: 0.05241 RPN score loss: 0.00259 RPN total loss: 0.055 Total loss: 1.45429 timestamp: 1654933021.485361 iteration: 22755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14451 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.21998 L1 loss: 0.0000e+00 L2 loss: 1.02293 Learning rate: 0.02 Mask loss: 0.23504 RPN box loss: 0.02396 RPN score loss: 0.01954 RPN total loss: 0.0435 Total loss: 1.52144 timestamp: 1654933024.7029114 iteration: 22760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15202 FastRCNN class loss: 0.11618 FastRCNN total loss: 0.2682 L1 loss: 0.0000e+00 L2 loss: 1.02279 Learning rate: 0.02 Mask loss: 0.16506 RPN box loss: 0.03091 RPN score loss: 0.00959 RPN total loss: 0.04049 Total loss: 1.49654 timestamp: 1654933027.895126 iteration: 22765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19979 FastRCNN class loss: 0.10049 FastRCNN total loss: 0.30028 L1 loss: 0.0000e+00 L2 loss: 1.02264 Learning rate: 0.02 Mask loss: 0.16503 RPN box loss: 0.05704 RPN score loss: 0.00333 RPN total loss: 0.06037 Total loss: 1.54833 timestamp: 1654933031.1281066 iteration: 22770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07596 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.14766 L1 loss: 0.0000e+00 L2 loss: 1.02247 Learning rate: 0.02 Mask loss: 0.11446 RPN box loss: 0.03297 RPN score loss: 0.00495 RPN total loss: 0.03792 Total loss: 1.32251 timestamp: 1654933034.3435178 iteration: 22775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14564 FastRCNN class loss: 0.13959 FastRCNN total loss: 0.28524 L1 loss: 0.0000e+00 L2 loss: 1.02232 Learning rate: 0.02 Mask loss: 0.17515 RPN box loss: 0.02321 RPN score loss: 0.00753 RPN total loss: 0.03074 Total loss: 1.51345 timestamp: 1654933037.5566552 iteration: 22780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1088 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.17248 L1 loss: 0.0000e+00 L2 loss: 1.02215 Learning rate: 0.02 Mask loss: 0.13349 RPN box loss: 0.02107 RPN score loss: 0.00084 RPN total loss: 0.02191 Total loss: 1.35004 timestamp: 1654933040.775129 iteration: 22785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13794 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.21199 L1 loss: 0.0000e+00 L2 loss: 1.02201 Learning rate: 0.02 Mask loss: 0.15313 RPN box loss: 0.06032 RPN score loss: 0.00423 RPN total loss: 0.06455 Total loss: 1.45168 timestamp: 1654933044.0161908 iteration: 22790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09989 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.1606 L1 loss: 0.0000e+00 L2 loss: 1.02186 Learning rate: 0.02 Mask loss: 0.16433 RPN box loss: 0.01878 RPN score loss: 0.00603 RPN total loss: 0.02481 Total loss: 1.3716 timestamp: 1654933047.2255912 iteration: 22795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14331 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.20122 L1 loss: 0.0000e+00 L2 loss: 1.0217 Learning rate: 0.02 Mask loss: 0.14789 RPN box loss: 0.00627 RPN score loss: 0.00416 RPN total loss: 0.01043 Total loss: 1.38124 timestamp: 1654933050.4552062 iteration: 22800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16584 FastRCNN class loss: 0.13154 FastRCNN total loss: 0.29738 L1 loss: 0.0000e+00 L2 loss: 1.02155 Learning rate: 0.02 Mask loss: 0.20617 RPN box loss: 0.03532 RPN score loss: 0.00398 RPN total loss: 0.0393 Total loss: 1.56441 timestamp: 1654933053.6822562 iteration: 22805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08676 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.16319 L1 loss: 0.0000e+00 L2 loss: 1.02138 Learning rate: 0.02 Mask loss: 0.11038 RPN box loss: 0.00689 RPN score loss: 0.0042 RPN total loss: 0.01109 Total loss: 1.30603 timestamp: 1654933056.9228706 iteration: 22810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15588 FastRCNN class loss: 0.1025 FastRCNN total loss: 0.25838 L1 loss: 0.0000e+00 L2 loss: 1.02121 Learning rate: 0.02 Mask loss: 0.19711 RPN box loss: 0.03866 RPN score loss: 0.00472 RPN total loss: 0.04337 Total loss: 1.52007 timestamp: 1654933060.1270251 iteration: 22815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16857 FastRCNN class loss: 0.081 FastRCNN total loss: 0.24957 L1 loss: 0.0000e+00 L2 loss: 1.02106 Learning rate: 0.02 Mask loss: 0.13571 RPN box loss: 0.02527 RPN score loss: 0.00239 RPN total loss: 0.02766 Total loss: 1.434 timestamp: 1654933063.353274 iteration: 22820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14259 FastRCNN class loss: 0.07041 FastRCNN total loss: 0.213 L1 loss: 0.0000e+00 L2 loss: 1.0209 Learning rate: 0.02 Mask loss: 0.12793 RPN box loss: 0.01829 RPN score loss: 0.00643 RPN total loss: 0.02472 Total loss: 1.38655 timestamp: 1654933066.6120002 iteration: 22825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13604 FastRCNN class loss: 0.0743 FastRCNN total loss: 0.21034 L1 loss: 0.0000e+00 L2 loss: 1.02073 Learning rate: 0.02 Mask loss: 0.19766 RPN box loss: 0.03479 RPN score loss: 0.00928 RPN total loss: 0.04407 Total loss: 1.4728 timestamp: 1654933069.860177 iteration: 22830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11472 FastRCNN class loss: 0.07427 FastRCNN total loss: 0.18899 L1 loss: 0.0000e+00 L2 loss: 1.02054 Learning rate: 0.02 Mask loss: 0.17322 RPN box loss: 0.03942 RPN score loss: 0.00416 RPN total loss: 0.04358 Total loss: 1.42634 timestamp: 1654933073.0710416 iteration: 22835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13572 FastRCNN class loss: 0.09415 FastRCNN total loss: 0.22987 L1 loss: 0.0000e+00 L2 loss: 1.02037 Learning rate: 0.02 Mask loss: 0.10637 RPN box loss: 0.03832 RPN score loss: 0.00446 RPN total loss: 0.04278 Total loss: 1.39939 timestamp: 1654933076.267317 iteration: 22840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24475 FastRCNN class loss: 0.15383 FastRCNN total loss: 0.39859 L1 loss: 0.0000e+00 L2 loss: 1.02019 Learning rate: 0.02 Mask loss: 0.1955 RPN box loss: 0.04093 RPN score loss: 0.01973 RPN total loss: 0.06066 Total loss: 1.67494 timestamp: 1654933079.4708438 iteration: 22845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08369 FastRCNN class loss: 0.05708 FastRCNN total loss: 0.14077 L1 loss: 0.0000e+00 L2 loss: 1.02002 Learning rate: 0.02 Mask loss: 0.11821 RPN box loss: 0.04177 RPN score loss: 0.00644 RPN total loss: 0.04821 Total loss: 1.32722 timestamp: 1654933082.6642187 iteration: 22850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1473 FastRCNN class loss: 0.06944 FastRCNN total loss: 0.21674 L1 loss: 0.0000e+00 L2 loss: 1.01987 Learning rate: 0.02 Mask loss: 0.13791 RPN box loss: 0.01889 RPN score loss: 0.00687 RPN total loss: 0.02576 Total loss: 1.40029 timestamp: 1654933085.8622127 iteration: 22855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13577 FastRCNN class loss: 0.11964 FastRCNN total loss: 0.2554 L1 loss: 0.0000e+00 L2 loss: 1.01972 Learning rate: 0.02 Mask loss: 0.17021 RPN box loss: 0.04067 RPN score loss: 0.01039 RPN total loss: 0.05105 Total loss: 1.49639 timestamp: 1654933089.072712 iteration: 22860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12177 FastRCNN class loss: 0.07847 FastRCNN total loss: 0.20024 L1 loss: 0.0000e+00 L2 loss: 1.01955 Learning rate: 0.02 Mask loss: 0.0993 RPN box loss: 0.03322 RPN score loss: 0.00427 RPN total loss: 0.03748 Total loss: 1.35657 timestamp: 1654933092.2842548 iteration: 22865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12475 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.19197 L1 loss: 0.0000e+00 L2 loss: 1.01939 Learning rate: 0.02 Mask loss: 0.13676 RPN box loss: 0.02856 RPN score loss: 0.0035 RPN total loss: 0.03206 Total loss: 1.38017 timestamp: 1654933095.468149 iteration: 22870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14245 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.21469 L1 loss: 0.0000e+00 L2 loss: 1.01924 Learning rate: 0.02 Mask loss: 0.17923 RPN box loss: 0.03233 RPN score loss: 0.01266 RPN total loss: 0.04499 Total loss: 1.45814 timestamp: 1654933098.7251334 iteration: 22875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13424 FastRCNN class loss: 0.0885 FastRCNN total loss: 0.22274 L1 loss: 0.0000e+00 L2 loss: 1.01908 Learning rate: 0.02 Mask loss: 0.13298 RPN box loss: 0.03485 RPN score loss: 0.00292 RPN total loss: 0.03777 Total loss: 1.41258 timestamp: 1654933101.9104548 iteration: 22880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08424 FastRCNN class loss: 0.05521 FastRCNN total loss: 0.13946 L1 loss: 0.0000e+00 L2 loss: 1.01892 Learning rate: 0.02 Mask loss: 0.10583 RPN box loss: 0.01188 RPN score loss: 0.00145 RPN total loss: 0.01333 Total loss: 1.27754 timestamp: 1654933105.1103313 iteration: 22885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11736 FastRCNN class loss: 0.05201 FastRCNN total loss: 0.16937 L1 loss: 0.0000e+00 L2 loss: 1.01877 Learning rate: 0.02 Mask loss: 0.16384 RPN box loss: 0.02774 RPN score loss: 0.00332 RPN total loss: 0.03105 Total loss: 1.38304 timestamp: 1654933108.3325605 iteration: 22890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19122 FastRCNN class loss: 0.1016 FastRCNN total loss: 0.29281 L1 loss: 0.0000e+00 L2 loss: 1.01861 Learning rate: 0.02 Mask loss: 0.18819 RPN box loss: 0.03888 RPN score loss: 0.00241 RPN total loss: 0.04129 Total loss: 1.54091 timestamp: 1654933111.4911063 iteration: 22895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12246 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.21215 L1 loss: 0.0000e+00 L2 loss: 1.01846 Learning rate: 0.02 Mask loss: 0.13303 RPN box loss: 0.07467 RPN score loss: 0.00868 RPN total loss: 0.08335 Total loss: 1.44698 timestamp: 1654933114.644702 iteration: 22900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.08239 FastRCNN total loss: 0.19791 L1 loss: 0.0000e+00 L2 loss: 1.01829 Learning rate: 0.02 Mask loss: 0.14745 RPN box loss: 0.0662 RPN score loss: 0.0106 RPN total loss: 0.0768 Total loss: 1.44045 timestamp: 1654933117.8919086 iteration: 22905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16157 FastRCNN class loss: 0.10009 FastRCNN total loss: 0.26166 L1 loss: 0.0000e+00 L2 loss: 1.01811 Learning rate: 0.02 Mask loss: 0.15681 RPN box loss: 0.06439 RPN score loss: 0.01279 RPN total loss: 0.07717 Total loss: 1.51376 timestamp: 1654933121.0800745 iteration: 22910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1603 FastRCNN class loss: 0.10764 FastRCNN total loss: 0.26794 L1 loss: 0.0000e+00 L2 loss: 1.01796 Learning rate: 0.02 Mask loss: 0.18951 RPN box loss: 0.03554 RPN score loss: 0.00754 RPN total loss: 0.04309 Total loss: 1.5185 timestamp: 1654933124.3716342 iteration: 22915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09088 FastRCNN class loss: 0.03898 FastRCNN total loss: 0.12986 L1 loss: 0.0000e+00 L2 loss: 1.01782 Learning rate: 0.02 Mask loss: 0.11697 RPN box loss: 0.00808 RPN score loss: 0.00171 RPN total loss: 0.00979 Total loss: 1.27444 timestamp: 1654933127.5980752 iteration: 22920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18387 FastRCNN class loss: 0.08752 FastRCNN total loss: 0.27139 L1 loss: 0.0000e+00 L2 loss: 1.01763 Learning rate: 0.02 Mask loss: 0.19958 RPN box loss: 0.0514 RPN score loss: 0.00813 RPN total loss: 0.05953 Total loss: 1.54814 timestamp: 1654933130.8105314 iteration: 22925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24997 FastRCNN class loss: 0.11318 FastRCNN total loss: 0.36314 L1 loss: 0.0000e+00 L2 loss: 1.01747 Learning rate: 0.02 Mask loss: 0.27669 RPN box loss: 0.04478 RPN score loss: 0.00255 RPN total loss: 0.04733 Total loss: 1.70463 timestamp: 1654933133.9769537 iteration: 22930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11006 FastRCNN class loss: 0.07899 FastRCNN total loss: 0.18905 L1 loss: 0.0000e+00 L2 loss: 1.01733 Learning rate: 0.02 Mask loss: 0.23714 RPN box loss: 0.05369 RPN score loss: 0.00727 RPN total loss: 0.06096 Total loss: 1.50449 timestamp: 1654933137.230168 iteration: 22935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13362 FastRCNN class loss: 0.10514 FastRCNN total loss: 0.23876 L1 loss: 0.0000e+00 L2 loss: 1.01717 Learning rate: 0.02 Mask loss: 0.14672 RPN box loss: 0.02633 RPN score loss: 0.00362 RPN total loss: 0.02995 Total loss: 1.4326 timestamp: 1654933140.4574704 iteration: 22940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0932 FastRCNN class loss: 0.04262 FastRCNN total loss: 0.13582 L1 loss: 0.0000e+00 L2 loss: 1.017 Learning rate: 0.02 Mask loss: 0.26268 RPN box loss: 0.05075 RPN score loss: 0.00198 RPN total loss: 0.05273 Total loss: 1.46823 timestamp: 1654933143.6087918 iteration: 22945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16291 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.26206 L1 loss: 0.0000e+00 L2 loss: 1.01683 Learning rate: 0.02 Mask loss: 0.18405 RPN box loss: 0.02913 RPN score loss: 0.02306 RPN total loss: 0.05219 Total loss: 1.51512 timestamp: 1654933146.8479555 iteration: 22950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10367 FastRCNN class loss: 0.06002 FastRCNN total loss: 0.16368 L1 loss: 0.0000e+00 L2 loss: 1.01666 Learning rate: 0.02 Mask loss: 0.11466 RPN box loss: 0.02356 RPN score loss: 0.00523 RPN total loss: 0.02879 Total loss: 1.32379 timestamp: 1654933150.0652313 iteration: 22955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18913 FastRCNN class loss: 0.08322 FastRCNN total loss: 0.27235 L1 loss: 0.0000e+00 L2 loss: 1.0165 Learning rate: 0.02 Mask loss: 0.13713 RPN box loss: 0.00899 RPN score loss: 0.00549 RPN total loss: 0.01448 Total loss: 1.44046 timestamp: 1654933153.1860776 iteration: 22960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08695 FastRCNN class loss: 0.07764 FastRCNN total loss: 0.16459 L1 loss: 0.0000e+00 L2 loss: 1.01632 Learning rate: 0.02 Mask loss: 0.12872 RPN box loss: 0.0092 RPN score loss: 0.00342 RPN total loss: 0.01262 Total loss: 1.32226 timestamp: 1654933156.4202092 iteration: 22965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16698 FastRCNN class loss: 0.12936 FastRCNN total loss: 0.29633 L1 loss: 0.0000e+00 L2 loss: 1.01616 Learning rate: 0.02 Mask loss: 0.1753 RPN box loss: 0.02783 RPN score loss: 0.00654 RPN total loss: 0.03437 Total loss: 1.52216 timestamp: 1654933159.577977 iteration: 22970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16993 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.24755 L1 loss: 0.0000e+00 L2 loss: 1.01601 Learning rate: 0.02 Mask loss: 0.16487 RPN box loss: 0.02876 RPN score loss: 0.00819 RPN total loss: 0.03695 Total loss: 1.46538 timestamp: 1654933162.7555826 iteration: 22975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1248 FastRCNN class loss: 0.05253 FastRCNN total loss: 0.17733 L1 loss: 0.0000e+00 L2 loss: 1.01589 Learning rate: 0.02 Mask loss: 0.13964 RPN box loss: 0.00845 RPN score loss: 0.00176 RPN total loss: 0.01021 Total loss: 1.34306 timestamp: 1654933165.9064891 iteration: 22980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25106 FastRCNN class loss: 0.09806 FastRCNN total loss: 0.34912 L1 loss: 0.0000e+00 L2 loss: 1.01572 Learning rate: 0.02 Mask loss: 0.23717 RPN box loss: 0.01207 RPN score loss: 0.00327 RPN total loss: 0.01533 Total loss: 1.61734 timestamp: 1654933169.1334393 iteration: 22985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10801 FastRCNN class loss: 0.07376 FastRCNN total loss: 0.18176 L1 loss: 0.0000e+00 L2 loss: 1.01553 Learning rate: 0.02 Mask loss: 0.18106 RPN box loss: 0.01448 RPN score loss: 0.00302 RPN total loss: 0.01749 Total loss: 1.39584 timestamp: 1654933172.328186 iteration: 22990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16488 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.23365 L1 loss: 0.0000e+00 L2 loss: 1.01538 Learning rate: 0.02 Mask loss: 0.15692 RPN box loss: 0.0234 RPN score loss: 0.00424 RPN total loss: 0.02765 Total loss: 1.4336 timestamp: 1654933175.5034206 iteration: 22995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08693 FastRCNN class loss: 0.06959 FastRCNN total loss: 0.15652 L1 loss: 0.0000e+00 L2 loss: 1.01523 Learning rate: 0.02 Mask loss: 0.12344 RPN box loss: 0.07706 RPN score loss: 0.00629 RPN total loss: 0.08335 Total loss: 1.37854 timestamp: 1654933178.7263834 iteration: 23000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1307 FastRCNN class loss: 0.11584 FastRCNN total loss: 0.24654 L1 loss: 0.0000e+00 L2 loss: 1.01509 Learning rate: 0.02 Mask loss: 0.15096 RPN box loss: 0.02022 RPN score loss: 0.00777 RPN total loss: 0.02798 Total loss: 1.44057 timestamp: 1654933181.9069533 iteration: 23005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10794 FastRCNN class loss: 0.07739 FastRCNN total loss: 0.18533 L1 loss: 0.0000e+00 L2 loss: 1.01493 Learning rate: 0.02 Mask loss: 0.17789 RPN box loss: 0.00942 RPN score loss: 0.00625 RPN total loss: 0.01567 Total loss: 1.39383 timestamp: 1654933185.154926 iteration: 23010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13857 FastRCNN class loss: 0.14815 FastRCNN total loss: 0.28672 L1 loss: 0.0000e+00 L2 loss: 1.01476 Learning rate: 0.02 Mask loss: 0.28448 RPN box loss: 0.03137 RPN score loss: 0.01194 RPN total loss: 0.04331 Total loss: 1.62928 timestamp: 1654933188.3512332 iteration: 23015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15269 FastRCNN class loss: 0.10098 FastRCNN total loss: 0.25366 L1 loss: 0.0000e+00 L2 loss: 1.0146 Learning rate: 0.02 Mask loss: 0.14713 RPN box loss: 0.03096 RPN score loss: 0.00419 RPN total loss: 0.03515 Total loss: 1.45054 timestamp: 1654933191.508515 iteration: 23020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09624 FastRCNN class loss: 0.04997 FastRCNN total loss: 0.14621 L1 loss: 0.0000e+00 L2 loss: 1.01444 Learning rate: 0.02 Mask loss: 0.12853 RPN box loss: 0.00843 RPN score loss: 0.00234 RPN total loss: 0.01077 Total loss: 1.29996 timestamp: 1654933194.701734 iteration: 23025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19962 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.29194 L1 loss: 0.0000e+00 L2 loss: 1.01426 Learning rate: 0.02 Mask loss: 0.14568 RPN box loss: 0.02999 RPN score loss: 0.00637 RPN total loss: 0.03636 Total loss: 1.48823 timestamp: 1654933197.9540424 iteration: 23030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.16265 L1 loss: 0.0000e+00 L2 loss: 1.01411 Learning rate: 0.02 Mask loss: 0.1386 RPN box loss: 0.03402 RPN score loss: 0.00983 RPN total loss: 0.04385 Total loss: 1.35921 timestamp: 1654933201.1623683 iteration: 23035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12706 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.20003 L1 loss: 0.0000e+00 L2 loss: 1.01398 Learning rate: 0.02 Mask loss: 0.12333 RPN box loss: 0.01094 RPN score loss: 0.00144 RPN total loss: 0.01238 Total loss: 1.34971 timestamp: 1654933204.3240762 iteration: 23040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1959 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.2723 L1 loss: 0.0000e+00 L2 loss: 1.0138 Learning rate: 0.02 Mask loss: 0.11375 RPN box loss: 0.06057 RPN score loss: 0.00596 RPN total loss: 0.06652 Total loss: 1.46638 timestamp: 1654933207.613104 iteration: 23045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26003 FastRCNN class loss: 0.09623 FastRCNN total loss: 0.35626 L1 loss: 0.0000e+00 L2 loss: 1.01362 Learning rate: 0.02 Mask loss: 0.15444 RPN box loss: 0.03303 RPN score loss: 0.00602 RPN total loss: 0.03905 Total loss: 1.56337 timestamp: 1654933210.8157115 iteration: 23050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14529 FastRCNN class loss: 0.08653 FastRCNN total loss: 0.23182 L1 loss: 0.0000e+00 L2 loss: 1.01346 Learning rate: 0.02 Mask loss: 0.17986 RPN box loss: 0.03395 RPN score loss: 0.00871 RPN total loss: 0.04266 Total loss: 1.4678 timestamp: 1654933214.0641682 iteration: 23055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0977 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.15916 L1 loss: 0.0000e+00 L2 loss: 1.0133 Learning rate: 0.02 Mask loss: 0.1379 RPN box loss: 0.02996 RPN score loss: 0.02482 RPN total loss: 0.05478 Total loss: 1.36513 timestamp: 1654933217.296285 iteration: 23060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19557 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.28003 L1 loss: 0.0000e+00 L2 loss: 1.01311 Learning rate: 0.02 Mask loss: 0.13328 RPN box loss: 0.01887 RPN score loss: 0.00649 RPN total loss: 0.02535 Total loss: 1.45177 timestamp: 1654933220.4710126 iteration: 23065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17472 FastRCNN class loss: 0.08674 FastRCNN total loss: 0.26146 L1 loss: 0.0000e+00 L2 loss: 1.01297 Learning rate: 0.02 Mask loss: 0.144 RPN box loss: 0.01934 RPN score loss: 0.00366 RPN total loss: 0.023 Total loss: 1.44143 timestamp: 1654933223.6524942 iteration: 23070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14533 FastRCNN class loss: 0.11377 FastRCNN total loss: 0.2591 L1 loss: 0.0000e+00 L2 loss: 1.01279 Learning rate: 0.02 Mask loss: 0.1816 RPN box loss: 0.05145 RPN score loss: 0.00831 RPN total loss: 0.05976 Total loss: 1.51325 timestamp: 1654933226.8156545 iteration: 23075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14688 FastRCNN class loss: 0.08305 FastRCNN total loss: 0.22993 L1 loss: 0.0000e+00 L2 loss: 1.01267 Learning rate: 0.02 Mask loss: 0.1365 RPN box loss: 0.05241 RPN score loss: 0.00423 RPN total loss: 0.05664 Total loss: 1.43575 timestamp: 1654933230.0022855 iteration: 23080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14032 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.20672 L1 loss: 0.0000e+00 L2 loss: 1.01252 Learning rate: 0.02 Mask loss: 0.16694 RPN box loss: 0.0257 RPN score loss: 0.0025 RPN total loss: 0.0282 Total loss: 1.41438 timestamp: 1654933233.2272756 iteration: 23085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15551 FastRCNN class loss: 0.08748 FastRCNN total loss: 0.24299 L1 loss: 0.0000e+00 L2 loss: 1.01235 Learning rate: 0.02 Mask loss: 0.16868 RPN box loss: 0.04573 RPN score loss: 0.00649 RPN total loss: 0.05222 Total loss: 1.47624 timestamp: 1654933236.4705198 iteration: 23090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09743 FastRCNN class loss: 0.05122 FastRCNN total loss: 0.14865 L1 loss: 0.0000e+00 L2 loss: 1.01219 Learning rate: 0.02 Mask loss: 0.13365 RPN box loss: 0.0259 RPN score loss: 0.00648 RPN total loss: 0.03238 Total loss: 1.32686 timestamp: 1654933239.7535129 iteration: 23095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16574 FastRCNN class loss: 0.1131 FastRCNN total loss: 0.27884 L1 loss: 0.0000e+00 L2 loss: 1.01204 Learning rate: 0.02 Mask loss: 0.28386 RPN box loss: 0.01047 RPN score loss: 0.00907 RPN total loss: 0.01954 Total loss: 1.59428 timestamp: 1654933242.98678 iteration: 23100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08792 FastRCNN class loss: 0.08584 FastRCNN total loss: 0.17376 L1 loss: 0.0000e+00 L2 loss: 1.01186 Learning rate: 0.02 Mask loss: 0.19897 RPN box loss: 0.02796 RPN score loss: 0.02303 RPN total loss: 0.051 Total loss: 1.43559 timestamp: 1654933246.2659917 iteration: 23105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18564 FastRCNN class loss: 0.11352 FastRCNN total loss: 0.29916 L1 loss: 0.0000e+00 L2 loss: 1.01169 Learning rate: 0.02 Mask loss: 0.18257 RPN box loss: 0.059 RPN score loss: 0.01177 RPN total loss: 0.07077 Total loss: 1.56419 timestamp: 1654933249.4402013 iteration: 23110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2047 FastRCNN class loss: 0.12174 FastRCNN total loss: 0.32643 L1 loss: 0.0000e+00 L2 loss: 1.01153 Learning rate: 0.02 Mask loss: 0.15637 RPN box loss: 0.04244 RPN score loss: 0.00661 RPN total loss: 0.04905 Total loss: 1.54338 timestamp: 1654933252.6502872 iteration: 23115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17853 FastRCNN class loss: 0.07385 FastRCNN total loss: 0.25239 L1 loss: 0.0000e+00 L2 loss: 1.01139 Learning rate: 0.02 Mask loss: 0.12523 RPN box loss: 0.07648 RPN score loss: 0.00888 RPN total loss: 0.08536 Total loss: 1.47436 timestamp: 1654933255.7943363 iteration: 23120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12603 FastRCNN class loss: 0.08332 FastRCNN total loss: 0.20935 L1 loss: 0.0000e+00 L2 loss: 1.01123 Learning rate: 0.02 Mask loss: 0.14079 RPN box loss: 0.01662 RPN score loss: 0.009 RPN total loss: 0.02562 Total loss: 1.38699 timestamp: 1654933258.9451907 iteration: 23125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09037 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.16484 L1 loss: 0.0000e+00 L2 loss: 1.01106 Learning rate: 0.02 Mask loss: 0.09612 RPN box loss: 0.0349 RPN score loss: 0.00462 RPN total loss: 0.03952 Total loss: 1.31154 timestamp: 1654933262.1821244 iteration: 23130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04012 FastRCNN class loss: 0.03495 FastRCNN total loss: 0.07508 L1 loss: 0.0000e+00 L2 loss: 1.01091 Learning rate: 0.02 Mask loss: 0.08229 RPN box loss: 0.03146 RPN score loss: 0.00544 RPN total loss: 0.0369 Total loss: 1.20517 timestamp: 1654933265.390887 iteration: 23135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12728 FastRCNN class loss: 0.0651 FastRCNN total loss: 0.19238 L1 loss: 0.0000e+00 L2 loss: 1.01076 Learning rate: 0.02 Mask loss: 0.20372 RPN box loss: 0.03443 RPN score loss: 0.0086 RPN total loss: 0.04303 Total loss: 1.4499 timestamp: 1654933268.646379 iteration: 23140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1859 FastRCNN class loss: 0.10677 FastRCNN total loss: 0.29267 L1 loss: 0.0000e+00 L2 loss: 1.0106 Learning rate: 0.02 Mask loss: 0.18983 RPN box loss: 0.05442 RPN score loss: 0.01315 RPN total loss: 0.06757 Total loss: 1.56067 timestamp: 1654933271.8042822 iteration: 23145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1887 FastRCNN class loss: 0.11436 FastRCNN total loss: 0.30306 L1 loss: 0.0000e+00 L2 loss: 1.01044 Learning rate: 0.02 Mask loss: 0.21476 RPN box loss: 0.04072 RPN score loss: 0.01155 RPN total loss: 0.05227 Total loss: 1.58054 timestamp: 1654933274.9624865 iteration: 23150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16532 FastRCNN class loss: 0.13178 FastRCNN total loss: 0.2971 L1 loss: 0.0000e+00 L2 loss: 1.0103 Learning rate: 0.02 Mask loss: 0.16809 RPN box loss: 0.02943 RPN score loss: 0.00927 RPN total loss: 0.03869 Total loss: 1.51418 timestamp: 1654933278.183637 iteration: 23155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12361 FastRCNN class loss: 0.09761 FastRCNN total loss: 0.22122 L1 loss: 0.0000e+00 L2 loss: 1.01016 Learning rate: 0.02 Mask loss: 0.13905 RPN box loss: 0.05555 RPN score loss: 0.01 RPN total loss: 0.06555 Total loss: 1.43598 timestamp: 1654933281.262766 iteration: 23160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11154 FastRCNN class loss: 0.12748 FastRCNN total loss: 0.23902 L1 loss: 0.0000e+00 L2 loss: 1.01 Learning rate: 0.02 Mask loss: 0.1762 RPN box loss: 0.05701 RPN score loss: 0.01476 RPN total loss: 0.07177 Total loss: 1.497 timestamp: 1654933284.431286 iteration: 23165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1958 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.26456 L1 loss: 0.0000e+00 L2 loss: 1.00985 Learning rate: 0.02 Mask loss: 0.15639 RPN box loss: 0.04152 RPN score loss: 0.00601 RPN total loss: 0.04753 Total loss: 1.47833 timestamp: 1654933287.6910777 iteration: 23170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15354 FastRCNN class loss: 0.12346 FastRCNN total loss: 0.277 L1 loss: 0.0000e+00 L2 loss: 1.00969 Learning rate: 0.02 Mask loss: 0.15112 RPN box loss: 0.05588 RPN score loss: 0.01657 RPN total loss: 0.07246 Total loss: 1.51026 timestamp: 1654933290.8712587 iteration: 23175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13455 FastRCNN class loss: 0.09913 FastRCNN total loss: 0.23368 L1 loss: 0.0000e+00 L2 loss: 1.00953 Learning rate: 0.02 Mask loss: 0.16119 RPN box loss: 0.02292 RPN score loss: 0.01083 RPN total loss: 0.03375 Total loss: 1.43816 timestamp: 1654933294.1464999 iteration: 23180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16402 FastRCNN class loss: 0.11337 FastRCNN total loss: 0.27739 L1 loss: 0.0000e+00 L2 loss: 1.00938 Learning rate: 0.02 Mask loss: 0.21241 RPN box loss: 0.02765 RPN score loss: 0.01097 RPN total loss: 0.03862 Total loss: 1.53781 timestamp: 1654933297.370945 iteration: 23185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13712 FastRCNN class loss: 0.10946 FastRCNN total loss: 0.24657 L1 loss: 0.0000e+00 L2 loss: 1.00922 Learning rate: 0.02 Mask loss: 0.16597 RPN box loss: 0.07182 RPN score loss: 0.01302 RPN total loss: 0.08484 Total loss: 1.5066 timestamp: 1654933300.5759344 iteration: 23190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19762 FastRCNN class loss: 0.15702 FastRCNN total loss: 0.35464 L1 loss: 0.0000e+00 L2 loss: 1.00905 Learning rate: 0.02 Mask loss: 0.22169 RPN box loss: 0.04284 RPN score loss: 0.01826 RPN total loss: 0.0611 Total loss: 1.64648 timestamp: 1654933303.760672 iteration: 23195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1479 FastRCNN class loss: 0.09199 FastRCNN total loss: 0.23989 L1 loss: 0.0000e+00 L2 loss: 1.00887 Learning rate: 0.02 Mask loss: 0.14791 RPN box loss: 0.01008 RPN score loss: 0.00512 RPN total loss: 0.0152 Total loss: 1.41188 timestamp: 1654933306.8939993 iteration: 23200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15883 FastRCNN class loss: 0.08389 FastRCNN total loss: 0.24272 L1 loss: 0.0000e+00 L2 loss: 1.00872 Learning rate: 0.02 Mask loss: 0.18562 RPN box loss: 0.04484 RPN score loss: 0.01122 RPN total loss: 0.05606 Total loss: 1.49312 timestamp: 1654933310.1238942 iteration: 23205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1482 FastRCNN class loss: 0.07875 FastRCNN total loss: 0.22695 L1 loss: 0.0000e+00 L2 loss: 1.00856 Learning rate: 0.02 Mask loss: 0.203 RPN box loss: 0.02781 RPN score loss: 0.00321 RPN total loss: 0.03102 Total loss: 1.46953 timestamp: 1654933313.27331 iteration: 23210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.0596 FastRCNN total loss: 0.14025 L1 loss: 0.0000e+00 L2 loss: 1.0084 Learning rate: 0.02 Mask loss: 0.10843 RPN box loss: 0.0095 RPN score loss: 0.00171 RPN total loss: 0.01121 Total loss: 1.26829 timestamp: 1654933316.4417934 iteration: 23215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1758 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.27465 L1 loss: 0.0000e+00 L2 loss: 1.00824 Learning rate: 0.02 Mask loss: 0.17034 RPN box loss: 0.02019 RPN score loss: 0.00428 RPN total loss: 0.02446 Total loss: 1.47769 timestamp: 1654933319.6115189 iteration: 23220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15799 FastRCNN class loss: 0.10647 FastRCNN total loss: 0.26446 L1 loss: 0.0000e+00 L2 loss: 1.00807 Learning rate: 0.02 Mask loss: 0.2234 RPN box loss: 0.0466 RPN score loss: 0.00855 RPN total loss: 0.05515 Total loss: 1.55108 timestamp: 1654933322.7253776 iteration: 23225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.06254 FastRCNN total loss: 0.17499 L1 loss: 0.0000e+00 L2 loss: 1.00792 Learning rate: 0.02 Mask loss: 0.19877 RPN box loss: 0.01448 RPN score loss: 0.00554 RPN total loss: 0.02002 Total loss: 1.40169 timestamp: 1654933325.9545417 iteration: 23230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15575 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.2308 L1 loss: 0.0000e+00 L2 loss: 1.00776 Learning rate: 0.02 Mask loss: 0.08891 RPN box loss: 0.01481 RPN score loss: 0.00298 RPN total loss: 0.01779 Total loss: 1.34526 timestamp: 1654933329.1619647 iteration: 23235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12212 FastRCNN class loss: 0.09653 FastRCNN total loss: 0.21865 L1 loss: 0.0000e+00 L2 loss: 1.0076 Learning rate: 0.02 Mask loss: 0.24337 RPN box loss: 0.04788 RPN score loss: 0.0052 RPN total loss: 0.05308 Total loss: 1.52269 timestamp: 1654933332.3589535 iteration: 23240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15837 FastRCNN class loss: 0.10311 FastRCNN total loss: 0.26148 L1 loss: 0.0000e+00 L2 loss: 1.00744 Learning rate: 0.02 Mask loss: 0.23521 RPN box loss: 0.03172 RPN score loss: 0.01482 RPN total loss: 0.04654 Total loss: 1.55067 timestamp: 1654933335.5142915 iteration: 23245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17715 FastRCNN class loss: 0.10832 FastRCNN total loss: 0.28547 L1 loss: 0.0000e+00 L2 loss: 1.00728 Learning rate: 0.02 Mask loss: 0.13719 RPN box loss: 0.02425 RPN score loss: 0.01053 RPN total loss: 0.03477 Total loss: 1.46471 timestamp: 1654933338.6362724 iteration: 23250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14786 FastRCNN class loss: 0.09516 FastRCNN total loss: 0.24302 L1 loss: 0.0000e+00 L2 loss: 1.00714 Learning rate: 0.02 Mask loss: 0.12953 RPN box loss: 0.02746 RPN score loss: 0.00755 RPN total loss: 0.03501 Total loss: 1.4147 timestamp: 1654933341.8650334 iteration: 23255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18978 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.28119 L1 loss: 0.0000e+00 L2 loss: 1.00699 Learning rate: 0.02 Mask loss: 0.17004 RPN box loss: 0.02548 RPN score loss: 0.0077 RPN total loss: 0.03318 Total loss: 1.4914 timestamp: 1654933345.0830894 iteration: 23260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07242 FastRCNN class loss: 0.04796 FastRCNN total loss: 0.12038 L1 loss: 0.0000e+00 L2 loss: 1.00684 Learning rate: 0.02 Mask loss: 0.08992 RPN box loss: 0.02224 RPN score loss: 0.00932 RPN total loss: 0.03156 Total loss: 1.24871 timestamp: 1654933348.2838829 iteration: 23265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13947 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.21349 L1 loss: 0.0000e+00 L2 loss: 1.00668 Learning rate: 0.02 Mask loss: 0.11688 RPN box loss: 0.0204 RPN score loss: 0.0025 RPN total loss: 0.0229 Total loss: 1.35994 timestamp: 1654933351.4783847 iteration: 23270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15842 FastRCNN class loss: 0.08555 FastRCNN total loss: 0.24398 L1 loss: 0.0000e+00 L2 loss: 1.0065 Learning rate: 0.02 Mask loss: 0.19722 RPN box loss: 0.0194 RPN score loss: 0.0103 RPN total loss: 0.0297 Total loss: 1.4774 timestamp: 1654933354.6953912 iteration: 23275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17167 FastRCNN class loss: 0.10739 FastRCNN total loss: 0.27906 L1 loss: 0.0000e+00 L2 loss: 1.00633 Learning rate: 0.02 Mask loss: 0.21557 RPN box loss: 0.02684 RPN score loss: 0.01706 RPN total loss: 0.0439 Total loss: 1.54486 timestamp: 1654933357.8086603 iteration: 23280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07057 FastRCNN class loss: 0.06165 FastRCNN total loss: 0.13223 L1 loss: 0.0000e+00 L2 loss: 1.00619 Learning rate: 0.02 Mask loss: 0.09516 RPN box loss: 0.03069 RPN score loss: 0.00689 RPN total loss: 0.03758 Total loss: 1.27116 timestamp: 1654933361.0068002 iteration: 23285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13407 FastRCNN class loss: 0.10234 FastRCNN total loss: 0.23641 L1 loss: 0.0000e+00 L2 loss: 1.00604 Learning rate: 0.02 Mask loss: 0.17595 RPN box loss: 0.04278 RPN score loss: 0.01114 RPN total loss: 0.05392 Total loss: 1.47231 timestamp: 1654933364.2527845 iteration: 23290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.16757 L1 loss: 0.0000e+00 L2 loss: 1.00586 Learning rate: 0.02 Mask loss: 0.12635 RPN box loss: 0.04278 RPN score loss: 0.02029 RPN total loss: 0.06307 Total loss: 1.36285 timestamp: 1654933367.3739111 iteration: 23295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1578 FastRCNN class loss: 0.11214 FastRCNN total loss: 0.26994 L1 loss: 0.0000e+00 L2 loss: 1.00571 Learning rate: 0.02 Mask loss: 0.14043 RPN box loss: 0.02128 RPN score loss: 0.00542 RPN total loss: 0.0267 Total loss: 1.44277 timestamp: 1654933370.5134184 iteration: 23300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1639 FastRCNN class loss: 0.11775 FastRCNN total loss: 0.28165 L1 loss: 0.0000e+00 L2 loss: 1.00557 Learning rate: 0.02 Mask loss: 0.12299 RPN box loss: 0.05286 RPN score loss: 0.00803 RPN total loss: 0.06088 Total loss: 1.4711 timestamp: 1654933373.7246816 iteration: 23305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15317 FastRCNN class loss: 0.11554 FastRCNN total loss: 0.26871 L1 loss: 0.0000e+00 L2 loss: 1.00541 Learning rate: 0.02 Mask loss: 0.14438 RPN box loss: 0.01872 RPN score loss: 0.00852 RPN total loss: 0.02724 Total loss: 1.44574 timestamp: 1654933376.883391 iteration: 23310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17157 FastRCNN class loss: 0.10939 FastRCNN total loss: 0.28096 L1 loss: 0.0000e+00 L2 loss: 1.00526 Learning rate: 0.02 Mask loss: 0.24114 RPN box loss: 0.05594 RPN score loss: 0.00885 RPN total loss: 0.06479 Total loss: 1.59214 timestamp: 1654933380.1097085 iteration: 23315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1679 FastRCNN class loss: 0.10599 FastRCNN total loss: 0.27389 L1 loss: 0.0000e+00 L2 loss: 1.00508 Learning rate: 0.02 Mask loss: 0.18581 RPN box loss: 0.02041 RPN score loss: 0.00368 RPN total loss: 0.02409 Total loss: 1.48887 timestamp: 1654933383.261014 iteration: 23320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16506 FastRCNN class loss: 0.08923 FastRCNN total loss: 0.25429 L1 loss: 0.0000e+00 L2 loss: 1.00491 Learning rate: 0.02 Mask loss: 0.17984 RPN box loss: 0.00775 RPN score loss: 0.00308 RPN total loss: 0.01084 Total loss: 1.44988 timestamp: 1654933386.5018873 iteration: 23325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20823 FastRCNN class loss: 0.0987 FastRCNN total loss: 0.30693 L1 loss: 0.0000e+00 L2 loss: 1.00476 Learning rate: 0.02 Mask loss: 0.19333 RPN box loss: 0.00655 RPN score loss: 0.00516 RPN total loss: 0.01171 Total loss: 1.51672 timestamp: 1654933389.7349546 iteration: 23330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17762 FastRCNN class loss: 0.10581 FastRCNN total loss: 0.28344 L1 loss: 0.0000e+00 L2 loss: 1.00462 Learning rate: 0.02 Mask loss: 0.14786 RPN box loss: 0.02927 RPN score loss: 0.00693 RPN total loss: 0.03619 Total loss: 1.4721 timestamp: 1654933393.0184712 iteration: 23335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12924 FastRCNN class loss: 0.10117 FastRCNN total loss: 0.23041 L1 loss: 0.0000e+00 L2 loss: 1.00447 Learning rate: 0.02 Mask loss: 0.15758 RPN box loss: 0.02304 RPN score loss: 0.00877 RPN total loss: 0.0318 Total loss: 1.42426 timestamp: 1654933396.1701102 iteration: 23340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0972 FastRCNN class loss: 0.05952 FastRCNN total loss: 0.15672 L1 loss: 0.0000e+00 L2 loss: 1.00433 Learning rate: 0.02 Mask loss: 0.11529 RPN box loss: 0.02192 RPN score loss: 0.00678 RPN total loss: 0.0287 Total loss: 1.30504 timestamp: 1654933399.4562793 iteration: 23345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18449 FastRCNN class loss: 0.08628 FastRCNN total loss: 0.27076 L1 loss: 0.0000e+00 L2 loss: 1.0042 Learning rate: 0.02 Mask loss: 0.14626 RPN box loss: 0.01527 RPN score loss: 0.00598 RPN total loss: 0.02125 Total loss: 1.44247 timestamp: 1654933402.7188594 iteration: 23350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15364 FastRCNN class loss: 0.11606 FastRCNN total loss: 0.2697 L1 loss: 0.0000e+00 L2 loss: 1.00405 Learning rate: 0.02 Mask loss: 0.15336 RPN box loss: 0.03917 RPN score loss: 0.01059 RPN total loss: 0.04976 Total loss: 1.47687 timestamp: 1654933405.9210286 iteration: 23355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14143 FastRCNN class loss: 0.08249 FastRCNN total loss: 0.22391 L1 loss: 0.0000e+00 L2 loss: 1.00389 Learning rate: 0.02 Mask loss: 0.22866 RPN box loss: 0.0653 RPN score loss: 0.01929 RPN total loss: 0.08459 Total loss: 1.54105 timestamp: 1654933409.1140122 iteration: 23360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11474 FastRCNN class loss: 0.08326 FastRCNN total loss: 0.198 L1 loss: 0.0000e+00 L2 loss: 1.00374 Learning rate: 0.02 Mask loss: 0.12345 RPN box loss: 0.05726 RPN score loss: 0.0126 RPN total loss: 0.06985 Total loss: 1.39504 timestamp: 1654933412.3530357 iteration: 23365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09764 FastRCNN class loss: 0.10774 FastRCNN total loss: 0.20538 L1 loss: 0.0000e+00 L2 loss: 1.00356 Learning rate: 0.02 Mask loss: 0.18973 RPN box loss: 0.03626 RPN score loss: 0.01382 RPN total loss: 0.05008 Total loss: 1.44875 timestamp: 1654933415.5360847 iteration: 23370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15858 FastRCNN class loss: 0.1295 FastRCNN total loss: 0.28808 L1 loss: 0.0000e+00 L2 loss: 1.00341 Learning rate: 0.02 Mask loss: 0.22824 RPN box loss: 0.03481 RPN score loss: 0.00912 RPN total loss: 0.04393 Total loss: 1.56365 timestamp: 1654933418.7138708 iteration: 23375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.15875 L1 loss: 0.0000e+00 L2 loss: 1.00325 Learning rate: 0.02 Mask loss: 0.12602 RPN box loss: 0.03403 RPN score loss: 0.00296 RPN total loss: 0.037 Total loss: 1.32502 timestamp: 1654933421.9489043 iteration: 23380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13398 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.18843 L1 loss: 0.0000e+00 L2 loss: 1.00308 Learning rate: 0.02 Mask loss: 0.17302 RPN box loss: 0.01101 RPN score loss: 0.00152 RPN total loss: 0.01253 Total loss: 1.37706 timestamp: 1654933425.1289802 iteration: 23385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1286 FastRCNN class loss: 0.08121 FastRCNN total loss: 0.20981 L1 loss: 0.0000e+00 L2 loss: 1.00295 Learning rate: 0.02 Mask loss: 0.12308 RPN box loss: 0.02732 RPN score loss: 0.00419 RPN total loss: 0.03151 Total loss: 1.36736 timestamp: 1654933428.344763 iteration: 23390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15632 FastRCNN class loss: 0.1038 FastRCNN total loss: 0.26013 L1 loss: 0.0000e+00 L2 loss: 1.00279 Learning rate: 0.02 Mask loss: 0.13794 RPN box loss: 0.03028 RPN score loss: 0.00581 RPN total loss: 0.03609 Total loss: 1.43695 timestamp: 1654933431.5690587 iteration: 23395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19805 FastRCNN class loss: 0.12959 FastRCNN total loss: 0.32764 L1 loss: 0.0000e+00 L2 loss: 1.00263 Learning rate: 0.02 Mask loss: 0.22929 RPN box loss: 0.02626 RPN score loss: 0.00544 RPN total loss: 0.0317 Total loss: 1.59127 timestamp: 1654933434.8154979 iteration: 23400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16034 FastRCNN class loss: 0.08645 FastRCNN total loss: 0.2468 L1 loss: 0.0000e+00 L2 loss: 1.00248 Learning rate: 0.02 Mask loss: 0.23492 RPN box loss: 0.00996 RPN score loss: 0.00227 RPN total loss: 0.01223 Total loss: 1.49643 timestamp: 1654933438.0887728 iteration: 23405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0956 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.16962 L1 loss: 0.0000e+00 L2 loss: 1.00231 Learning rate: 0.02 Mask loss: 0.13484 RPN box loss: 0.06216 RPN score loss: 0.00689 RPN total loss: 0.06905 Total loss: 1.37582 timestamp: 1654933441.3697083 iteration: 23410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10013 FastRCNN class loss: 0.065 FastRCNN total loss: 0.16514 L1 loss: 0.0000e+00 L2 loss: 1.00216 Learning rate: 0.02 Mask loss: 0.14312 RPN box loss: 0.03958 RPN score loss: 0.00345 RPN total loss: 0.04303 Total loss: 1.35345 timestamp: 1654933444.4880638 iteration: 23415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.135 FastRCNN class loss: 0.10099 FastRCNN total loss: 0.23599 L1 loss: 0.0000e+00 L2 loss: 1.002 Learning rate: 0.02 Mask loss: 0.18962 RPN box loss: 0.0233 RPN score loss: 0.01197 RPN total loss: 0.03528 Total loss: 1.46289 timestamp: 1654933447.6537874 iteration: 23420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10196 FastRCNN class loss: 0.0909 FastRCNN total loss: 0.19286 L1 loss: 0.0000e+00 L2 loss: 1.00183 Learning rate: 0.02 Mask loss: 0.23564 RPN box loss: 0.01983 RPN score loss: 0.00362 RPN total loss: 0.02344 Total loss: 1.45377 timestamp: 1654933450.8820503 iteration: 23425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19957 FastRCNN class loss: 0.09539 FastRCNN total loss: 0.29496 L1 loss: 0.0000e+00 L2 loss: 1.00167 Learning rate: 0.02 Mask loss: 0.18505 RPN box loss: 0.01699 RPN score loss: 0.01236 RPN total loss: 0.02935 Total loss: 1.51104 timestamp: 1654933454.0149872 iteration: 23430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1065 FastRCNN class loss: 0.05001 FastRCNN total loss: 0.1565 L1 loss: 0.0000e+00 L2 loss: 1.00152 Learning rate: 0.02 Mask loss: 0.10353 RPN box loss: 0.04579 RPN score loss: 0.00819 RPN total loss: 0.05397 Total loss: 1.31553 timestamp: 1654933457.1488962 iteration: 23435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13873 FastRCNN class loss: 0.08964 FastRCNN total loss: 0.22838 L1 loss: 0.0000e+00 L2 loss: 1.00136 Learning rate: 0.02 Mask loss: 0.1159 RPN box loss: 0.03559 RPN score loss: 0.01032 RPN total loss: 0.04591 Total loss: 1.39155 timestamp: 1654933460.3555331 iteration: 23440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12306 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.20641 L1 loss: 0.0000e+00 L2 loss: 1.0012 Learning rate: 0.02 Mask loss: 0.20541 RPN box loss: 0.0192 RPN score loss: 0.00386 RPN total loss: 0.02306 Total loss: 1.43607 timestamp: 1654933463.5514686 iteration: 23445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12221 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.19026 L1 loss: 0.0000e+00 L2 loss: 1.00103 Learning rate: 0.02 Mask loss: 0.18857 RPN box loss: 0.01006 RPN score loss: 0.00546 RPN total loss: 0.01552 Total loss: 1.39538 timestamp: 1654933466.6545227 iteration: 23450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1084 FastRCNN class loss: 0.05764 FastRCNN total loss: 0.16604 L1 loss: 0.0000e+00 L2 loss: 1.00089 Learning rate: 0.02 Mask loss: 0.14487 RPN box loss: 0.02835 RPN score loss: 0.00211 RPN total loss: 0.03046 Total loss: 1.34225 timestamp: 1654933469.90217 iteration: 23455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0854 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.15531 L1 loss: 0.0000e+00 L2 loss: 1.00075 Learning rate: 0.02 Mask loss: 0.09304 RPN box loss: 0.01161 RPN score loss: 0.00532 RPN total loss: 0.01694 Total loss: 1.26604 timestamp: 1654933473.0219138 iteration: 23460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12236 FastRCNN class loss: 0.08788 FastRCNN total loss: 0.21024 L1 loss: 0.0000e+00 L2 loss: 1.00059 Learning rate: 0.02 Mask loss: 0.14785 RPN box loss: 0.03576 RPN score loss: 0.00492 RPN total loss: 0.04068 Total loss: 1.39935 timestamp: 1654933476.3117185 iteration: 23465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16605 FastRCNN class loss: 0.10404 FastRCNN total loss: 0.27009 L1 loss: 0.0000e+00 L2 loss: 1.00042 Learning rate: 0.02 Mask loss: 0.19047 RPN box loss: 0.02704 RPN score loss: 0.0121 RPN total loss: 0.03914 Total loss: 1.50012 timestamp: 1654933479.598519 iteration: 23470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13778 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.20918 L1 loss: 0.0000e+00 L2 loss: 1.00024 Learning rate: 0.02 Mask loss: 0.17726 RPN box loss: 0.0162 RPN score loss: 0.00542 RPN total loss: 0.02162 Total loss: 1.4083 timestamp: 1654933482.7331712 iteration: 23475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13984 FastRCNN class loss: 0.10979 FastRCNN total loss: 0.24963 L1 loss: 0.0000e+00 L2 loss: 1.00009 Learning rate: 0.02 Mask loss: 0.19556 RPN box loss: 0.05818 RPN score loss: 0.01552 RPN total loss: 0.0737 Total loss: 1.51897 timestamp: 1654933485.9766717 iteration: 23480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15962 FastRCNN class loss: 0.1143 FastRCNN total loss: 0.27392 L1 loss: 0.0000e+00 L2 loss: 0.99991 Learning rate: 0.02 Mask loss: 0.15887 RPN box loss: 0.04448 RPN score loss: 0.01322 RPN total loss: 0.0577 Total loss: 1.4904 timestamp: 1654933489.1295848 iteration: 23485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16438 FastRCNN class loss: 0.10969 FastRCNN total loss: 0.27407 L1 loss: 0.0000e+00 L2 loss: 0.99975 Learning rate: 0.02 Mask loss: 0.14256 RPN box loss: 0.03474 RPN score loss: 0.00563 RPN total loss: 0.04037 Total loss: 1.45675 timestamp: 1654933492.3296556 iteration: 23490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12894 FastRCNN class loss: 0.08901 FastRCNN total loss: 0.21795 L1 loss: 0.0000e+00 L2 loss: 0.9996 Learning rate: 0.02 Mask loss: 0.15221 RPN box loss: 0.00529 RPN score loss: 0.00388 RPN total loss: 0.00916 Total loss: 1.37892 timestamp: 1654933495.6064613 iteration: 23495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08358 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.15608 L1 loss: 0.0000e+00 L2 loss: 0.99944 Learning rate: 0.02 Mask loss: 0.10342 RPN box loss: 0.02406 RPN score loss: 0.00608 RPN total loss: 0.03015 Total loss: 1.28908 timestamp: 1654933498.8359725 iteration: 23500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15511 FastRCNN class loss: 0.08585 FastRCNN total loss: 0.24095 L1 loss: 0.0000e+00 L2 loss: 0.99928 Learning rate: 0.02 Mask loss: 0.16287 RPN box loss: 0.02124 RPN score loss: 0.00615 RPN total loss: 0.02739 Total loss: 1.43049 timestamp: 1654933502.050212 iteration: 23505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11583 FastRCNN class loss: 0.05163 FastRCNN total loss: 0.16746 L1 loss: 0.0000e+00 L2 loss: 0.99914 Learning rate: 0.02 Mask loss: 0.1265 RPN box loss: 0.0448 RPN score loss: 0.00583 RPN total loss: 0.05062 Total loss: 1.34372 timestamp: 1654933505.261506 iteration: 23510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2024 FastRCNN class loss: 0.11639 FastRCNN total loss: 0.31879 L1 loss: 0.0000e+00 L2 loss: 0.99897 Learning rate: 0.02 Mask loss: 0.17956 RPN box loss: 0.06688 RPN score loss: 0.01453 RPN total loss: 0.08141 Total loss: 1.57872 timestamp: 1654933508.4709554 iteration: 23515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16625 FastRCNN class loss: 0.08304 FastRCNN total loss: 0.2493 L1 loss: 0.0000e+00 L2 loss: 0.99881 Learning rate: 0.02 Mask loss: 0.17963 RPN box loss: 0.01642 RPN score loss: 0.00265 RPN total loss: 0.01907 Total loss: 1.4468 timestamp: 1654933511.6834278 iteration: 23520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11222 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.18447 L1 loss: 0.0000e+00 L2 loss: 0.99866 Learning rate: 0.02 Mask loss: 0.17632 RPN box loss: 0.01719 RPN score loss: 0.00492 RPN total loss: 0.02211 Total loss: 1.38155 timestamp: 1654933514.8544064 iteration: 23525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09379 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.16001 L1 loss: 0.0000e+00 L2 loss: 0.99849 Learning rate: 0.02 Mask loss: 0.10285 RPN box loss: 0.02398 RPN score loss: 0.00245 RPN total loss: 0.02643 Total loss: 1.28778 timestamp: 1654933518.0751164 iteration: 23530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15878 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.23065 L1 loss: 0.0000e+00 L2 loss: 0.99833 Learning rate: 0.02 Mask loss: 0.18151 RPN box loss: 0.02876 RPN score loss: 0.00491 RPN total loss: 0.03368 Total loss: 1.44418 timestamp: 1654933521.2422621 iteration: 23535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14317 FastRCNN class loss: 0.13364 FastRCNN total loss: 0.2768 L1 loss: 0.0000e+00 L2 loss: 0.99819 Learning rate: 0.02 Mask loss: 0.15137 RPN box loss: 0.04249 RPN score loss: 0.01068 RPN total loss: 0.05317 Total loss: 1.47953 timestamp: 1654933524.4180572 iteration: 23540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19084 FastRCNN class loss: 0.10187 FastRCNN total loss: 0.2927 L1 loss: 0.0000e+00 L2 loss: 0.99805 Learning rate: 0.02 Mask loss: 0.20236 RPN box loss: 0.02072 RPN score loss: 0.00404 RPN total loss: 0.02475 Total loss: 1.51787 timestamp: 1654933527.5565462 iteration: 23545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09246 FastRCNN class loss: 0.06752 FastRCNN total loss: 0.15998 L1 loss: 0.0000e+00 L2 loss: 0.9979 Learning rate: 0.02 Mask loss: 0.12005 RPN box loss: 0.04746 RPN score loss: 0.00326 RPN total loss: 0.05072 Total loss: 1.32864 timestamp: 1654933530.7819507 iteration: 23550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13562 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.21681 L1 loss: 0.0000e+00 L2 loss: 0.99776 Learning rate: 0.02 Mask loss: 0.12727 RPN box loss: 0.01344 RPN score loss: 0.00584 RPN total loss: 0.01928 Total loss: 1.36111 timestamp: 1654933534.0126042 iteration: 23555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07531 FastRCNN class loss: 0.04991 FastRCNN total loss: 0.12522 L1 loss: 0.0000e+00 L2 loss: 0.99763 Learning rate: 0.02 Mask loss: 0.1933 RPN box loss: 0.02561 RPN score loss: 0.0062 RPN total loss: 0.03181 Total loss: 1.34796 timestamp: 1654933537.1594653 iteration: 23560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12401 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.19344 L1 loss: 0.0000e+00 L2 loss: 0.99747 Learning rate: 0.02 Mask loss: 0.10574 RPN box loss: 0.00722 RPN score loss: 0.00696 RPN total loss: 0.01418 Total loss: 1.31082 timestamp: 1654933540.3677044 iteration: 23565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16866 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.25721 L1 loss: 0.0000e+00 L2 loss: 0.99729 Learning rate: 0.02 Mask loss: 0.1202 RPN box loss: 0.03721 RPN score loss: 0.00742 RPN total loss: 0.04463 Total loss: 1.41932 timestamp: 1654933543.5554554 iteration: 23570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13728 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.20408 L1 loss: 0.0000e+00 L2 loss: 0.99713 Learning rate: 0.02 Mask loss: 0.14029 RPN box loss: 0.07913 RPN score loss: 0.00612 RPN total loss: 0.08525 Total loss: 1.42675 timestamp: 1654933546.7736688 iteration: 23575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1093 FastRCNN class loss: 0.07363 FastRCNN total loss: 0.18294 L1 loss: 0.0000e+00 L2 loss: 0.99697 Learning rate: 0.02 Mask loss: 0.10643 RPN box loss: 0.03632 RPN score loss: 0.00335 RPN total loss: 0.03967 Total loss: 1.32601 timestamp: 1654933550.0212715 iteration: 23580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16016 FastRCNN class loss: 0.09371 FastRCNN total loss: 0.25387 L1 loss: 0.0000e+00 L2 loss: 0.99682 Learning rate: 0.02 Mask loss: 0.12073 RPN box loss: 0.02247 RPN score loss: 0.00423 RPN total loss: 0.02671 Total loss: 1.39813 timestamp: 1654933553.2220826 iteration: 23585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12528 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.19059 L1 loss: 0.0000e+00 L2 loss: 0.99668 Learning rate: 0.02 Mask loss: 0.09479 RPN box loss: 0.06519 RPN score loss: 0.00504 RPN total loss: 0.07023 Total loss: 1.3523 timestamp: 1654933556.4693193 iteration: 23590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.16179 L1 loss: 0.0000e+00 L2 loss: 0.99654 Learning rate: 0.02 Mask loss: 0.20957 RPN box loss: 0.01266 RPN score loss: 0.0028 RPN total loss: 0.01546 Total loss: 1.38336 timestamp: 1654933559.657807 iteration: 23595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1833 FastRCNN class loss: 0.17645 FastRCNN total loss: 0.35975 L1 loss: 0.0000e+00 L2 loss: 0.99636 Learning rate: 0.02 Mask loss: 0.25866 RPN box loss: 0.04593 RPN score loss: 0.01365 RPN total loss: 0.05957 Total loss: 1.67435 timestamp: 1654933562.8894186 iteration: 23600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13216 FastRCNN class loss: 0.08418 FastRCNN total loss: 0.21634 L1 loss: 0.0000e+00 L2 loss: 0.9962 Learning rate: 0.02 Mask loss: 0.19263 RPN box loss: 0.04159 RPN score loss: 0.0117 RPN total loss: 0.05329 Total loss: 1.45846 timestamp: 1654933566.1025567 iteration: 23605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08467 FastRCNN class loss: 0.04576 FastRCNN total loss: 0.13044 L1 loss: 0.0000e+00 L2 loss: 0.99604 Learning rate: 0.02 Mask loss: 0.07794 RPN box loss: 0.00618 RPN score loss: 0.00155 RPN total loss: 0.00773 Total loss: 1.21215 timestamp: 1654933569.3199513 iteration: 23610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10246 FastRCNN class loss: 0.06496 FastRCNN total loss: 0.16742 L1 loss: 0.0000e+00 L2 loss: 0.99589 Learning rate: 0.02 Mask loss: 0.15611 RPN box loss: 0.0156 RPN score loss: 0.00234 RPN total loss: 0.01794 Total loss: 1.33737 timestamp: 1654933572.5603917 iteration: 23615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16605 FastRCNN class loss: 0.14837 FastRCNN total loss: 0.31442 L1 loss: 0.0000e+00 L2 loss: 0.99575 Learning rate: 0.02 Mask loss: 0.18503 RPN box loss: 0.02027 RPN score loss: 0.00354 RPN total loss: 0.02381 Total loss: 1.51901 timestamp: 1654933575.7497537 iteration: 23620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20516 FastRCNN class loss: 0.07882 FastRCNN total loss: 0.28398 L1 loss: 0.0000e+00 L2 loss: 0.99557 Learning rate: 0.02 Mask loss: 0.12653 RPN box loss: 0.03753 RPN score loss: 0.01286 RPN total loss: 0.05038 Total loss: 1.45646 timestamp: 1654933578.8745227 iteration: 23625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1465 FastRCNN class loss: 0.07659 FastRCNN total loss: 0.22309 L1 loss: 0.0000e+00 L2 loss: 0.99544 Learning rate: 0.02 Mask loss: 0.15003 RPN box loss: 0.04518 RPN score loss: 0.00638 RPN total loss: 0.05156 Total loss: 1.42013 timestamp: 1654933582.0037506 iteration: 23630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13417 FastRCNN class loss: 0.10405 FastRCNN total loss: 0.23822 L1 loss: 0.0000e+00 L2 loss: 0.99529 Learning rate: 0.02 Mask loss: 0.1663 RPN box loss: 0.01096 RPN score loss: 0.0049 RPN total loss: 0.01587 Total loss: 1.41567 timestamp: 1654933585.2142723 iteration: 23635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1585 FastRCNN class loss: 0.13552 FastRCNN total loss: 0.29402 L1 loss: 0.0000e+00 L2 loss: 0.99512 Learning rate: 0.02 Mask loss: 0.24023 RPN box loss: 0.0835 RPN score loss: 0.0151 RPN total loss: 0.09859 Total loss: 1.62796 timestamp: 1654933588.4255311 iteration: 23640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11315 FastRCNN class loss: 0.07039 FastRCNN total loss: 0.18354 L1 loss: 0.0000e+00 L2 loss: 0.99496 Learning rate: 0.02 Mask loss: 0.12062 RPN box loss: 0.02708 RPN score loss: 0.00432 RPN total loss: 0.0314 Total loss: 1.33052 timestamp: 1654933591.7108366 iteration: 23645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11945 FastRCNN class loss: 0.09725 FastRCNN total loss: 0.21671 L1 loss: 0.0000e+00 L2 loss: 0.99482 Learning rate: 0.02 Mask loss: 0.15807 RPN box loss: 0.05175 RPN score loss: 0.01497 RPN total loss: 0.06671 Total loss: 1.43631 timestamp: 1654933594.9152324 iteration: 23650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11304 FastRCNN class loss: 0.06397 FastRCNN total loss: 0.17701 L1 loss: 0.0000e+00 L2 loss: 0.99466 Learning rate: 0.02 Mask loss: 0.17522 RPN box loss: 0.03802 RPN score loss: 0.00576 RPN total loss: 0.04378 Total loss: 1.39067 timestamp: 1654933598.1248872 iteration: 23655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.1656 FastRCNN total loss: 0.31771 L1 loss: 0.0000e+00 L2 loss: 0.99451 Learning rate: 0.02 Mask loss: 0.21257 RPN box loss: 0.03034 RPN score loss: 0.00939 RPN total loss: 0.03973 Total loss: 1.56451 timestamp: 1654933601.310315 iteration: 23660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18212 FastRCNN class loss: 0.09848 FastRCNN total loss: 0.28059 L1 loss: 0.0000e+00 L2 loss: 0.99434 Learning rate: 0.02 Mask loss: 0.10691 RPN box loss: 0.05831 RPN score loss: 0.01772 RPN total loss: 0.07604 Total loss: 1.45788 timestamp: 1654933604.5044432 iteration: 23665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16308 FastRCNN class loss: 0.14998 FastRCNN total loss: 0.31306 L1 loss: 0.0000e+00 L2 loss: 0.99421 Learning rate: 0.02 Mask loss: 0.14114 RPN box loss: 0.04826 RPN score loss: 0.00366 RPN total loss: 0.05193 Total loss: 1.50033 timestamp: 1654933607.7360487 iteration: 23670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1999 FastRCNN class loss: 0.06318 FastRCNN total loss: 0.26308 L1 loss: 0.0000e+00 L2 loss: 0.99404 Learning rate: 0.02 Mask loss: 0.11501 RPN box loss: 0.00859 RPN score loss: 0.00168 RPN total loss: 0.01026 Total loss: 1.3824 timestamp: 1654933610.966525 iteration: 23675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14218 FastRCNN class loss: 0.14201 FastRCNN total loss: 0.28419 L1 loss: 0.0000e+00 L2 loss: 0.99389 Learning rate: 0.02 Mask loss: 0.17506 RPN box loss: 0.03108 RPN score loss: 0.00956 RPN total loss: 0.04064 Total loss: 1.49378 timestamp: 1654933614.1668122 iteration: 23680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0942 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.15277 L1 loss: 0.0000e+00 L2 loss: 0.99374 Learning rate: 0.02 Mask loss: 0.16624 RPN box loss: 0.02026 RPN score loss: 0.00155 RPN total loss: 0.02181 Total loss: 1.33456 timestamp: 1654933617.3433466 iteration: 23685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0754 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.13478 L1 loss: 0.0000e+00 L2 loss: 0.99358 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.03858 RPN score loss: 0.02604 RPN total loss: 0.06462 Total loss: 1.3313 timestamp: 1654933620.5607147 iteration: 23690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21633 FastRCNN class loss: 0.13031 FastRCNN total loss: 0.34664 L1 loss: 0.0000e+00 L2 loss: 0.9934 Learning rate: 0.02 Mask loss: 0.19358 RPN box loss: 0.0233 RPN score loss: 0.00513 RPN total loss: 0.02844 Total loss: 1.56206 timestamp: 1654933623.7603273 iteration: 23695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13303 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.20413 L1 loss: 0.0000e+00 L2 loss: 0.99324 Learning rate: 0.02 Mask loss: 0.12939 RPN box loss: 0.01528 RPN score loss: 0.0037 RPN total loss: 0.01898 Total loss: 1.34574 timestamp: 1654933626.983598 iteration: 23700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16185 FastRCNN class loss: 0.12171 FastRCNN total loss: 0.28356 L1 loss: 0.0000e+00 L2 loss: 0.99309 Learning rate: 0.02 Mask loss: 0.25546 RPN box loss: 0.03773 RPN score loss: 0.0171 RPN total loss: 0.05483 Total loss: 1.58694 timestamp: 1654933630.173701 iteration: 23705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15663 FastRCNN class loss: 0.072 FastRCNN total loss: 0.22863 L1 loss: 0.0000e+00 L2 loss: 0.99294 Learning rate: 0.02 Mask loss: 0.09177 RPN box loss: 0.02138 RPN score loss: 0.00659 RPN total loss: 0.02797 Total loss: 1.3413 timestamp: 1654933633.3304331 iteration: 23710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16667 FastRCNN class loss: 0.10203 FastRCNN total loss: 0.2687 L1 loss: 0.0000e+00 L2 loss: 0.99277 Learning rate: 0.02 Mask loss: 0.268 RPN box loss: 0.01887 RPN score loss: 0.00518 RPN total loss: 0.02405 Total loss: 1.55352 timestamp: 1654933636.5481887 iteration: 23715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09566 FastRCNN class loss: 0.07379 FastRCNN total loss: 0.16945 L1 loss: 0.0000e+00 L2 loss: 0.99263 Learning rate: 0.02 Mask loss: 0.13877 RPN box loss: 0.0125 RPN score loss: 0.00896 RPN total loss: 0.02146 Total loss: 1.32231 timestamp: 1654933639.717127 iteration: 23720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15814 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.23832 L1 loss: 0.0000e+00 L2 loss: 0.99247 Learning rate: 0.02 Mask loss: 0.13284 RPN box loss: 0.07843 RPN score loss: 0.00596 RPN total loss: 0.08439 Total loss: 1.44802 timestamp: 1654933642.8818672 iteration: 23725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14679 FastRCNN class loss: 0.09741 FastRCNN total loss: 0.2442 L1 loss: 0.0000e+00 L2 loss: 0.99232 Learning rate: 0.02 Mask loss: 0.20777 RPN box loss: 0.02723 RPN score loss: 0.01826 RPN total loss: 0.04549 Total loss: 1.48978 timestamp: 1654933646.0379848 iteration: 23730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15715 FastRCNN class loss: 0.08723 FastRCNN total loss: 0.24439 L1 loss: 0.0000e+00 L2 loss: 0.99218 Learning rate: 0.02 Mask loss: 0.23468 RPN box loss: 0.02598 RPN score loss: 0.00655 RPN total loss: 0.03252 Total loss: 1.50377 timestamp: 1654933649.232981 iteration: 23735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09815 FastRCNN class loss: 0.09001 FastRCNN total loss: 0.18816 L1 loss: 0.0000e+00 L2 loss: 0.99204 Learning rate: 0.02 Mask loss: 0.18739 RPN box loss: 0.02872 RPN score loss: 0.00632 RPN total loss: 0.03504 Total loss: 1.40262 timestamp: 1654933652.4553316 iteration: 23740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11454 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.18751 L1 loss: 0.0000e+00 L2 loss: 0.99187 Learning rate: 0.02 Mask loss: 0.13797 RPN box loss: 0.00997 RPN score loss: 0.00198 RPN total loss: 0.01195 Total loss: 1.3293 timestamp: 1654933655.6531715 iteration: 23745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14464 FastRCNN class loss: 0.09456 FastRCNN total loss: 0.23921 L1 loss: 0.0000e+00 L2 loss: 0.99172 Learning rate: 0.02 Mask loss: 0.2407 RPN box loss: 0.0153 RPN score loss: 0.00503 RPN total loss: 0.02033 Total loss: 1.49196 timestamp: 1654933658.8658948 iteration: 23750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18481 FastRCNN class loss: 0.07362 FastRCNN total loss: 0.25843 L1 loss: 0.0000e+00 L2 loss: 0.99157 Learning rate: 0.02 Mask loss: 0.15885 RPN box loss: 0.05665 RPN score loss: 0.00603 RPN total loss: 0.06268 Total loss: 1.47153 timestamp: 1654933662.064914 iteration: 23755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12771 FastRCNN class loss: 0.04626 FastRCNN total loss: 0.17397 L1 loss: 0.0000e+00 L2 loss: 0.99141 Learning rate: 0.02 Mask loss: 0.14245 RPN box loss: 0.01374 RPN score loss: 0.0038 RPN total loss: 0.01754 Total loss: 1.32537 timestamp: 1654933665.3013055 iteration: 23760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11103 FastRCNN class loss: 0.06587 FastRCNN total loss: 0.1769 L1 loss: 0.0000e+00 L2 loss: 0.99128 Learning rate: 0.02 Mask loss: 0.14533 RPN box loss: 0.0349 RPN score loss: 0.00578 RPN total loss: 0.04068 Total loss: 1.35419 timestamp: 1654933668.5105665 iteration: 23765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12202 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.19389 L1 loss: 0.0000e+00 L2 loss: 0.99114 Learning rate: 0.02 Mask loss: 0.15338 RPN box loss: 0.03692 RPN score loss: 0.00527 RPN total loss: 0.04219 Total loss: 1.38059 timestamp: 1654933671.6719713 iteration: 23770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14621 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.2141 L1 loss: 0.0000e+00 L2 loss: 0.99097 Learning rate: 0.02 Mask loss: 0.19286 RPN box loss: 0.04398 RPN score loss: 0.00636 RPN total loss: 0.05034 Total loss: 1.44827 timestamp: 1654933674.824395 iteration: 23775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17376 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.2411 L1 loss: 0.0000e+00 L2 loss: 0.99082 Learning rate: 0.02 Mask loss: 0.14411 RPN box loss: 0.03313 RPN score loss: 0.0098 RPN total loss: 0.04293 Total loss: 1.41895 timestamp: 1654933678.0753481 iteration: 23780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12135 FastRCNN class loss: 0.10039 FastRCNN total loss: 0.22174 L1 loss: 0.0000e+00 L2 loss: 0.99065 Learning rate: 0.02 Mask loss: 0.09428 RPN box loss: 0.01498 RPN score loss: 0.00259 RPN total loss: 0.01757 Total loss: 1.32425 timestamp: 1654933681.3121836 iteration: 23785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16838 FastRCNN class loss: 0.09881 FastRCNN total loss: 0.26719 L1 loss: 0.0000e+00 L2 loss: 0.9905 Learning rate: 0.02 Mask loss: 0.20796 RPN box loss: 0.02182 RPN score loss: 0.00691 RPN total loss: 0.02874 Total loss: 1.49438 timestamp: 1654933684.4964852 iteration: 23790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16231 FastRCNN class loss: 0.10519 FastRCNN total loss: 0.2675 L1 loss: 0.0000e+00 L2 loss: 0.99035 Learning rate: 0.02 Mask loss: 0.21633 RPN box loss: 0.03664 RPN score loss: 0.01175 RPN total loss: 0.04838 Total loss: 1.52257 timestamp: 1654933687.690514 iteration: 23795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20067 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.29299 L1 loss: 0.0000e+00 L2 loss: 0.99018 Learning rate: 0.02 Mask loss: 0.14836 RPN box loss: 0.02956 RPN score loss: 0.00735 RPN total loss: 0.03692 Total loss: 1.46844 timestamp: 1654933690.9008112 iteration: 23800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17658 FastRCNN class loss: 0.08805 FastRCNN total loss: 0.26464 L1 loss: 0.0000e+00 L2 loss: 0.99004 Learning rate: 0.02 Mask loss: 0.15569 RPN box loss: 0.01542 RPN score loss: 0.00353 RPN total loss: 0.01895 Total loss: 1.42931 timestamp: 1654933694.1409307 iteration: 23805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17585 FastRCNN class loss: 0.14397 FastRCNN total loss: 0.31983 L1 loss: 0.0000e+00 L2 loss: 0.98989 Learning rate: 0.02 Mask loss: 0.29932 RPN box loss: 0.05225 RPN score loss: 0.00804 RPN total loss: 0.06028 Total loss: 1.66932 timestamp: 1654933697.3162546 iteration: 23810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17626 FastRCNN class loss: 0.16889 FastRCNN total loss: 0.34515 L1 loss: 0.0000e+00 L2 loss: 0.98973 Learning rate: 0.02 Mask loss: 0.15289 RPN box loss: 0.0409 RPN score loss: 0.01108 RPN total loss: 0.05198 Total loss: 1.53976 timestamp: 1654933700.4472196 iteration: 23815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12729 FastRCNN class loss: 0.08504 FastRCNN total loss: 0.21232 L1 loss: 0.0000e+00 L2 loss: 0.98959 Learning rate: 0.02 Mask loss: 0.10709 RPN box loss: 0.03446 RPN score loss: 0.00787 RPN total loss: 0.04233 Total loss: 1.35133 timestamp: 1654933703.726526 iteration: 23820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12868 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.2148 L1 loss: 0.0000e+00 L2 loss: 0.98941 Learning rate: 0.02 Mask loss: 0.14878 RPN box loss: 0.06166 RPN score loss: 0.00267 RPN total loss: 0.06433 Total loss: 1.41732 timestamp: 1654933706.9436781 iteration: 23825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13649 FastRCNN class loss: 0.11587 FastRCNN total loss: 0.25236 L1 loss: 0.0000e+00 L2 loss: 0.98925 Learning rate: 0.02 Mask loss: 0.16337 RPN box loss: 0.11427 RPN score loss: 0.02362 RPN total loss: 0.13788 Total loss: 1.54287 timestamp: 1654933710.1324313 iteration: 23830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.19143 L1 loss: 0.0000e+00 L2 loss: 0.9891 Learning rate: 0.02 Mask loss: 0.09988 RPN box loss: 0.02026 RPN score loss: 0.00804 RPN total loss: 0.02831 Total loss: 1.30872 timestamp: 1654933713.3192809 iteration: 23835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15122 FastRCNN class loss: 0.08352 FastRCNN total loss: 0.23474 L1 loss: 0.0000e+00 L2 loss: 0.98896 Learning rate: 0.02 Mask loss: 0.11125 RPN box loss: 0.00772 RPN score loss: 0.00441 RPN total loss: 0.01213 Total loss: 1.34708 timestamp: 1654933716.449285 iteration: 23840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09018 FastRCNN class loss: 0.04444 FastRCNN total loss: 0.13462 L1 loss: 0.0000e+00 L2 loss: 0.9888 Learning rate: 0.02 Mask loss: 0.11597 RPN box loss: 0.02461 RPN score loss: 0.00849 RPN total loss: 0.03309 Total loss: 1.27248 timestamp: 1654933719.7920947 iteration: 23845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15144 FastRCNN class loss: 0.10066 FastRCNN total loss: 0.2521 L1 loss: 0.0000e+00 L2 loss: 0.98865 Learning rate: 0.02 Mask loss: 0.20772 RPN box loss: 0.02156 RPN score loss: 0.0027 RPN total loss: 0.02426 Total loss: 1.47272 timestamp: 1654933723.0272684 iteration: 23850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23544 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.29497 L1 loss: 0.0000e+00 L2 loss: 0.98849 Learning rate: 0.02 Mask loss: 0.09366 RPN box loss: 0.03763 RPN score loss: 0.00391 RPN total loss: 0.04154 Total loss: 1.41865 timestamp: 1654933726.2050827 iteration: 23855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13384 FastRCNN class loss: 0.065 FastRCNN total loss: 0.19885 L1 loss: 0.0000e+00 L2 loss: 0.98831 Learning rate: 0.02 Mask loss: 0.17455 RPN box loss: 0.0054 RPN score loss: 0.00424 RPN total loss: 0.00964 Total loss: 1.37135 timestamp: 1654933729.4390016 iteration: 23860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11784 FastRCNN class loss: 0.10545 FastRCNN total loss: 0.22329 L1 loss: 0.0000e+00 L2 loss: 0.98815 Learning rate: 0.02 Mask loss: 0.1878 RPN box loss: 0.0172 RPN score loss: 0.00312 RPN total loss: 0.02032 Total loss: 1.41955 timestamp: 1654933732.6442652 iteration: 23865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13781 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.20759 L1 loss: 0.0000e+00 L2 loss: 0.98801 Learning rate: 0.02 Mask loss: 0.13289 RPN box loss: 0.03711 RPN score loss: 0.00464 RPN total loss: 0.04174 Total loss: 1.37023 timestamp: 1654933735.8888044 iteration: 23870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12281 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.18715 L1 loss: 0.0000e+00 L2 loss: 0.98785 Learning rate: 0.02 Mask loss: 0.1659 RPN box loss: 0.01651 RPN score loss: 0.0061 RPN total loss: 0.02261 Total loss: 1.36351 timestamp: 1654933739.0276258 iteration: 23875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17229 FastRCNN class loss: 0.09103 FastRCNN total loss: 0.26332 L1 loss: 0.0000e+00 L2 loss: 0.98769 Learning rate: 0.02 Mask loss: 0.21334 RPN box loss: 0.04403 RPN score loss: 0.0126 RPN total loss: 0.05664 Total loss: 1.52098 timestamp: 1654933742.2213762 iteration: 23880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13331 FastRCNN class loss: 0.0727 FastRCNN total loss: 0.206 L1 loss: 0.0000e+00 L2 loss: 0.98754 Learning rate: 0.02 Mask loss: 0.22098 RPN box loss: 0.02867 RPN score loss: 0.01057 RPN total loss: 0.03924 Total loss: 1.45377 timestamp: 1654933745.4142497 iteration: 23885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1101 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.17751 L1 loss: 0.0000e+00 L2 loss: 0.9874 Learning rate: 0.02 Mask loss: 0.19093 RPN box loss: 0.01115 RPN score loss: 0.00311 RPN total loss: 0.01427 Total loss: 1.37011 timestamp: 1654933748.5938537 iteration: 23890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14616 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.22785 L1 loss: 0.0000e+00 L2 loss: 0.98725 Learning rate: 0.02 Mask loss: 0.22313 RPN box loss: 0.01973 RPN score loss: 0.01065 RPN total loss: 0.03039 Total loss: 1.46861 timestamp: 1654933751.8164437 iteration: 23895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14378 FastRCNN class loss: 0.07741 FastRCNN total loss: 0.22119 L1 loss: 0.0000e+00 L2 loss: 0.98708 Learning rate: 0.02 Mask loss: 0.15753 RPN box loss: 0.04053 RPN score loss: 0.00963 RPN total loss: 0.05017 Total loss: 1.41597 timestamp: 1654933755.027422 iteration: 23900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12265 FastRCNN class loss: 0.08634 FastRCNN total loss: 0.20899 L1 loss: 0.0000e+00 L2 loss: 0.98692 Learning rate: 0.02 Mask loss: 0.14716 RPN box loss: 0.04101 RPN score loss: 0.00745 RPN total loss: 0.04846 Total loss: 1.39153 timestamp: 1654933758.2312233 iteration: 23905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15169 FastRCNN class loss: 0.10639 FastRCNN total loss: 0.25808 L1 loss: 0.0000e+00 L2 loss: 0.98677 Learning rate: 0.02 Mask loss: 0.11877 RPN box loss: 0.02014 RPN score loss: 0.00649 RPN total loss: 0.02662 Total loss: 1.39025 timestamp: 1654933761.4498055 iteration: 23910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.10302 FastRCNN total loss: 0.25439 L1 loss: 0.0000e+00 L2 loss: 0.98661 Learning rate: 0.02 Mask loss: 0.16062 RPN box loss: 0.06421 RPN score loss: 0.01421 RPN total loss: 0.07842 Total loss: 1.48004 timestamp: 1654933764.718769 iteration: 23915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17097 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.26138 L1 loss: 0.0000e+00 L2 loss: 0.98647 Learning rate: 0.02 Mask loss: 0.11167 RPN box loss: 0.01876 RPN score loss: 0.00803 RPN total loss: 0.02679 Total loss: 1.38631 timestamp: 1654933767.93601 iteration: 23920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18744 FastRCNN class loss: 0.07801 FastRCNN total loss: 0.26545 L1 loss: 0.0000e+00 L2 loss: 0.98631 Learning rate: 0.02 Mask loss: 0.20556 RPN box loss: 0.02287 RPN score loss: 0.01073 RPN total loss: 0.0336 Total loss: 1.49092 timestamp: 1654933771.202852 iteration: 23925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1156 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.18097 L1 loss: 0.0000e+00 L2 loss: 0.98616 Learning rate: 0.02 Mask loss: 0.11681 RPN box loss: 0.02121 RPN score loss: 0.00801 RPN total loss: 0.02922 Total loss: 1.31316 timestamp: 1654933774.4164412 iteration: 23930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08151 FastRCNN class loss: 0.05748 FastRCNN total loss: 0.13899 L1 loss: 0.0000e+00 L2 loss: 0.98601 Learning rate: 0.02 Mask loss: 0.09245 RPN box loss: 0.02879 RPN score loss: 0.00311 RPN total loss: 0.03191 Total loss: 1.24935 timestamp: 1654933777.6506188 iteration: 23935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1952 FastRCNN class loss: 0.08849 FastRCNN total loss: 0.28369 L1 loss: 0.0000e+00 L2 loss: 0.98585 Learning rate: 0.02 Mask loss: 0.21502 RPN box loss: 0.00693 RPN score loss: 0.01059 RPN total loss: 0.01752 Total loss: 1.50208 timestamp: 1654933780.828556 iteration: 23940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13601 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.21012 L1 loss: 0.0000e+00 L2 loss: 0.98568 Learning rate: 0.02 Mask loss: 0.13415 RPN box loss: 0.0533 RPN score loss: 0.00862 RPN total loss: 0.06192 Total loss: 1.39187 timestamp: 1654933784.0350928 iteration: 23945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15894 FastRCNN class loss: 0.10495 FastRCNN total loss: 0.26389 L1 loss: 0.0000e+00 L2 loss: 0.98553 Learning rate: 0.02 Mask loss: 0.17134 RPN box loss: 0.03529 RPN score loss: 0.00806 RPN total loss: 0.04335 Total loss: 1.46411 timestamp: 1654933787.1504164 iteration: 23950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16154 FastRCNN class loss: 0.1608 FastRCNN total loss: 0.32234 L1 loss: 0.0000e+00 L2 loss: 0.98538 Learning rate: 0.02 Mask loss: 0.19142 RPN box loss: 0.01688 RPN score loss: 0.01525 RPN total loss: 0.03213 Total loss: 1.53127 timestamp: 1654933790.3429768 iteration: 23955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1648 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.24728 L1 loss: 0.0000e+00 L2 loss: 0.9852 Learning rate: 0.02 Mask loss: 0.1904 RPN box loss: 0.01528 RPN score loss: 0.0046 RPN total loss: 0.01988 Total loss: 1.44275 timestamp: 1654933793.5899131 iteration: 23960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14021 FastRCNN class loss: 0.07491 FastRCNN total loss: 0.21512 L1 loss: 0.0000e+00 L2 loss: 0.98506 Learning rate: 0.02 Mask loss: 0.1251 RPN box loss: 0.03588 RPN score loss: 0.00449 RPN total loss: 0.04038 Total loss: 1.36566 timestamp: 1654933796.8214567 iteration: 23965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20964 FastRCNN class loss: 0.10507 FastRCNN total loss: 0.31471 L1 loss: 0.0000e+00 L2 loss: 0.98492 Learning rate: 0.02 Mask loss: 0.23367 RPN box loss: 0.04702 RPN score loss: 0.01777 RPN total loss: 0.06479 Total loss: 1.5981 timestamp: 1654933799.9536328 iteration: 23970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12722 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.20773 L1 loss: 0.0000e+00 L2 loss: 0.98475 Learning rate: 0.02 Mask loss: 0.2169 RPN box loss: 0.02886 RPN score loss: 0.00948 RPN total loss: 0.03835 Total loss: 1.44773 timestamp: 1654933803.176047 iteration: 23975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17178 FastRCNN class loss: 0.12218 FastRCNN total loss: 0.29396 L1 loss: 0.0000e+00 L2 loss: 0.9846 Learning rate: 0.02 Mask loss: 0.16514 RPN box loss: 0.04942 RPN score loss: 0.01087 RPN total loss: 0.06029 Total loss: 1.50398 timestamp: 1654933806.3871696 iteration: 23980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16848 FastRCNN class loss: 0.08043 FastRCNN total loss: 0.24891 L1 loss: 0.0000e+00 L2 loss: 0.98444 Learning rate: 0.02 Mask loss: 0.18494 RPN box loss: 0.02765 RPN score loss: 0.00958 RPN total loss: 0.03723 Total loss: 1.45552 timestamp: 1654933809.5348566 iteration: 23985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18462 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.24634 L1 loss: 0.0000e+00 L2 loss: 0.98427 Learning rate: 0.02 Mask loss: 0.09794 RPN box loss: 0.00671 RPN score loss: 0.00216 RPN total loss: 0.00886 Total loss: 1.33741 timestamp: 1654933812.7497225 iteration: 23990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18445 FastRCNN class loss: 0.11077 FastRCNN total loss: 0.29522 L1 loss: 0.0000e+00 L2 loss: 0.9841 Learning rate: 0.02 Mask loss: 0.17438 RPN box loss: 0.01241 RPN score loss: 0.00625 RPN total loss: 0.01866 Total loss: 1.47236 timestamp: 1654933815.9590478 iteration: 23995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06868 FastRCNN class loss: 0.06916 FastRCNN total loss: 0.13784 L1 loss: 0.0000e+00 L2 loss: 0.98398 Learning rate: 0.02 Mask loss: 0.10718 RPN box loss: 0.04465 RPN score loss: 0.0114 RPN total loss: 0.05605 Total loss: 1.28506 timestamp: 1654933819.162394 iteration: 24000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25564 FastRCNN class loss: 0.0967 FastRCNN total loss: 0.35234 L1 loss: 0.0000e+00 L2 loss: 0.98383 Learning rate: 0.02 Mask loss: 0.14275 RPN box loss: 0.02517 RPN score loss: 0.0088 RPN total loss: 0.03398 Total loss: 1.51289 timestamp: 1654933822.3765087 iteration: 24005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16202 FastRCNN class loss: 0.13281 FastRCNN total loss: 0.29483 L1 loss: 0.0000e+00 L2 loss: 0.98369 Learning rate: 0.02 Mask loss: 0.13467 RPN box loss: 0.01614 RPN score loss: 0.0076 RPN total loss: 0.02374 Total loss: 1.43693 timestamp: 1654933825.471704 iteration: 24010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17556 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.25441 L1 loss: 0.0000e+00 L2 loss: 0.98352 Learning rate: 0.02 Mask loss: 0.13354 RPN box loss: 0.03683 RPN score loss: 0.00814 RPN total loss: 0.04497 Total loss: 1.41643 timestamp: 1654933828.7135205 iteration: 24015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12173 FastRCNN class loss: 0.06941 FastRCNN total loss: 0.19113 L1 loss: 0.0000e+00 L2 loss: 0.98336 Learning rate: 0.02 Mask loss: 0.11452 RPN box loss: 0.02664 RPN score loss: 0.01087 RPN total loss: 0.03751 Total loss: 1.32652 timestamp: 1654933831.9153693 iteration: 24020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15743 FastRCNN class loss: 0.08995 FastRCNN total loss: 0.24738 L1 loss: 0.0000e+00 L2 loss: 0.98322 Learning rate: 0.02 Mask loss: 0.15419 RPN box loss: 0.07381 RPN score loss: 0.00919 RPN total loss: 0.083 Total loss: 1.46779 timestamp: 1654933835.1894686 iteration: 24025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20068 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.2769 L1 loss: 0.0000e+00 L2 loss: 0.98307 Learning rate: 0.02 Mask loss: 0.21488 RPN box loss: 0.02517 RPN score loss: 0.00495 RPN total loss: 0.03012 Total loss: 1.50497 timestamp: 1654933838.3675833 iteration: 24030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19437 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.29212 L1 loss: 0.0000e+00 L2 loss: 0.9829 Learning rate: 0.02 Mask loss: 0.1505 RPN box loss: 0.01483 RPN score loss: 0.00165 RPN total loss: 0.01648 Total loss: 1.44201 timestamp: 1654933841.5519066 iteration: 24035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18598 FastRCNN class loss: 0.07927 FastRCNN total loss: 0.26526 L1 loss: 0.0000e+00 L2 loss: 0.98277 Learning rate: 0.02 Mask loss: 0.1435 RPN box loss: 0.04519 RPN score loss: 0.00517 RPN total loss: 0.05036 Total loss: 1.44189 timestamp: 1654933844.797859 iteration: 24040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16074 FastRCNN class loss: 0.14669 FastRCNN total loss: 0.30743 L1 loss: 0.0000e+00 L2 loss: 0.9826 Learning rate: 0.02 Mask loss: 0.2158 RPN box loss: 0.04136 RPN score loss: 0.0124 RPN total loss: 0.05376 Total loss: 1.55959 timestamp: 1654933848.052771 iteration: 24045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08283 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.1412 L1 loss: 0.0000e+00 L2 loss: 0.98242 Learning rate: 0.02 Mask loss: 0.21314 RPN box loss: 0.02576 RPN score loss: 0.00321 RPN total loss: 0.02898 Total loss: 1.36573 timestamp: 1654933851.263407 iteration: 24050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08471 FastRCNN class loss: 0.03921 FastRCNN total loss: 0.12392 L1 loss: 0.0000e+00 L2 loss: 0.98227 Learning rate: 0.02 Mask loss: 0.09479 RPN box loss: 0.02752 RPN score loss: 0.00204 RPN total loss: 0.02956 Total loss: 1.23054 timestamp: 1654933854.4695358 iteration: 24055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14893 FastRCNN class loss: 0.06207 FastRCNN total loss: 0.211 L1 loss: 0.0000e+00 L2 loss: 0.98212 Learning rate: 0.02 Mask loss: 0.13211 RPN box loss: 0.05295 RPN score loss: 0.01299 RPN total loss: 0.06595 Total loss: 1.39117 timestamp: 1654933857.6424513 iteration: 24060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21418 FastRCNN class loss: 0.09755 FastRCNN total loss: 0.31172 L1 loss: 0.0000e+00 L2 loss: 0.98196 Learning rate: 0.02 Mask loss: 0.166 RPN box loss: 0.06179 RPN score loss: 0.00517 RPN total loss: 0.06696 Total loss: 1.52665 timestamp: 1654933860.849258 iteration: 24065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11812 FastRCNN class loss: 0.06155 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.9818 Learning rate: 0.02 Mask loss: 0.13415 RPN box loss: 0.02269 RPN score loss: 0.00573 RPN total loss: 0.02841 Total loss: 1.32404 timestamp: 1654933863.9785793 iteration: 24070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10929 FastRCNN class loss: 0.0722 FastRCNN total loss: 0.18149 L1 loss: 0.0000e+00 L2 loss: 0.98165 Learning rate: 0.02 Mask loss: 0.14426 RPN box loss: 0.02097 RPN score loss: 0.00729 RPN total loss: 0.02826 Total loss: 1.33566 timestamp: 1654933867.1490936 iteration: 24075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11058 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 0.9815 Learning rate: 0.02 Mask loss: 0.17288 RPN box loss: 0.01432 RPN score loss: 0.00586 RPN total loss: 0.02018 Total loss: 1.36632 timestamp: 1654933870.285184 iteration: 24080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1708 FastRCNN class loss: 0.08794 FastRCNN total loss: 0.25874 L1 loss: 0.0000e+00 L2 loss: 0.98136 Learning rate: 0.02 Mask loss: 0.20416 RPN box loss: 0.02742 RPN score loss: 0.00297 RPN total loss: 0.03038 Total loss: 1.47465 timestamp: 1654933873.5001855 iteration: 24085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18815 FastRCNN class loss: 0.11898 FastRCNN total loss: 0.30713 L1 loss: 0.0000e+00 L2 loss: 0.9812 Learning rate: 0.02 Mask loss: 0.24548 RPN box loss: 0.04679 RPN score loss: 0.0098 RPN total loss: 0.05659 Total loss: 1.5904 timestamp: 1654933876.7362154 iteration: 24090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18419 FastRCNN class loss: 0.10858 FastRCNN total loss: 0.29277 L1 loss: 0.0000e+00 L2 loss: 0.98105 Learning rate: 0.02 Mask loss: 0.16835 RPN box loss: 0.01162 RPN score loss: 0.01156 RPN total loss: 0.02318 Total loss: 1.46535 timestamp: 1654933879.9232817 iteration: 24095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13883 FastRCNN class loss: 0.08386 FastRCNN total loss: 0.2227 L1 loss: 0.0000e+00 L2 loss: 0.98091 Learning rate: 0.02 Mask loss: 0.11123 RPN box loss: 0.01065 RPN score loss: 0.00341 RPN total loss: 0.01406 Total loss: 1.3289 timestamp: 1654933883.111001 iteration: 24100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17577 FastRCNN class loss: 0.08092 FastRCNN total loss: 0.25669 L1 loss: 0.0000e+00 L2 loss: 0.98076 Learning rate: 0.02 Mask loss: 0.13912 RPN box loss: 0.03753 RPN score loss: 0.00916 RPN total loss: 0.04669 Total loss: 1.42325 timestamp: 1654933886.2867556 iteration: 24105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23778 FastRCNN class loss: 0.11477 FastRCNN total loss: 0.35254 L1 loss: 0.0000e+00 L2 loss: 0.98062 Learning rate: 0.02 Mask loss: 0.18311 RPN box loss: 0.01423 RPN score loss: 0.01296 RPN total loss: 0.02719 Total loss: 1.54346 timestamp: 1654933889.4584975 iteration: 24110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17097 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.26141 L1 loss: 0.0000e+00 L2 loss: 0.98048 Learning rate: 0.02 Mask loss: 0.14651 RPN box loss: 0.02157 RPN score loss: 0.00491 RPN total loss: 0.02649 Total loss: 1.41489 timestamp: 1654933892.6772778 iteration: 24115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.10439 FastRCNN total loss: 0.23211 L1 loss: 0.0000e+00 L2 loss: 0.98033 Learning rate: 0.02 Mask loss: 0.13139 RPN box loss: 0.03411 RPN score loss: 0.01257 RPN total loss: 0.04668 Total loss: 1.3905 timestamp: 1654933895.9206731 iteration: 24120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1714 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.2465 L1 loss: 0.0000e+00 L2 loss: 0.98017 Learning rate: 0.02 Mask loss: 0.1699 RPN box loss: 0.04222 RPN score loss: 0.00628 RPN total loss: 0.0485 Total loss: 1.44508 timestamp: 1654933899.1377292 iteration: 24125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22154 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.30714 L1 loss: 0.0000e+00 L2 loss: 0.98 Learning rate: 0.02 Mask loss: 0.15155 RPN box loss: 0.03043 RPN score loss: 0.00626 RPN total loss: 0.03669 Total loss: 1.47538 timestamp: 1654933902.2870994 iteration: 24130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15158 FastRCNN class loss: 0.20607 FastRCNN total loss: 0.35764 L1 loss: 0.0000e+00 L2 loss: 0.97984 Learning rate: 0.02 Mask loss: 0.23572 RPN box loss: 0.04582 RPN score loss: 0.06652 RPN total loss: 0.11234 Total loss: 1.68555 timestamp: 1654933905.4468892 iteration: 24135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06338 FastRCNN class loss: 0.05815 FastRCNN total loss: 0.12152 L1 loss: 0.0000e+00 L2 loss: 0.97969 Learning rate: 0.02 Mask loss: 0.13478 RPN box loss: 0.06243 RPN score loss: 0.00741 RPN total loss: 0.06984 Total loss: 1.30584 timestamp: 1654933908.662282 iteration: 24140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1913 FastRCNN class loss: 0.08157 FastRCNN total loss: 0.27287 L1 loss: 0.0000e+00 L2 loss: 0.97953 Learning rate: 0.02 Mask loss: 0.13874 RPN box loss: 0.05085 RPN score loss: 0.00625 RPN total loss: 0.05709 Total loss: 1.44823 timestamp: 1654933911.9002495 iteration: 24145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1387 FastRCNN class loss: 0.08006 FastRCNN total loss: 0.21876 L1 loss: 0.0000e+00 L2 loss: 0.97937 Learning rate: 0.02 Mask loss: 0.15267 RPN box loss: 0.06787 RPN score loss: 0.00977 RPN total loss: 0.07764 Total loss: 1.42844 timestamp: 1654933915.1273782 iteration: 24150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12368 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.19035 L1 loss: 0.0000e+00 L2 loss: 0.97921 Learning rate: 0.02 Mask loss: 0.17049 RPN box loss: 0.02795 RPN score loss: 0.00998 RPN total loss: 0.03792 Total loss: 1.37796 timestamp: 1654933918.3841283 iteration: 24155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12692 FastRCNN class loss: 0.09156 FastRCNN total loss: 0.21849 L1 loss: 0.0000e+00 L2 loss: 0.97906 Learning rate: 0.02 Mask loss: 0.18764 RPN box loss: 0.08561 RPN score loss: 0.00578 RPN total loss: 0.09139 Total loss: 1.47657 timestamp: 1654933921.601425 iteration: 24160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09158 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.1448 L1 loss: 0.0000e+00 L2 loss: 0.9789 Learning rate: 0.02 Mask loss: 0.08997 RPN box loss: 0.01657 RPN score loss: 0.00278 RPN total loss: 0.01935 Total loss: 1.23302 timestamp: 1654933924.7478235 iteration: 24165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0759 FastRCNN class loss: 0.05349 FastRCNN total loss: 0.12939 L1 loss: 0.0000e+00 L2 loss: 0.97875 Learning rate: 0.02 Mask loss: 0.20195 RPN box loss: 0.04836 RPN score loss: 0.01006 RPN total loss: 0.05842 Total loss: 1.36852 timestamp: 1654933927.9941633 iteration: 24170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15547 FastRCNN class loss: 0.09494 FastRCNN total loss: 0.25041 L1 loss: 0.0000e+00 L2 loss: 0.97859 Learning rate: 0.02 Mask loss: 0.18699 RPN box loss: 0.02962 RPN score loss: 0.00907 RPN total loss: 0.03869 Total loss: 1.45468 timestamp: 1654933931.186831 iteration: 24175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08897 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.1506 L1 loss: 0.0000e+00 L2 loss: 0.97842 Learning rate: 0.02 Mask loss: 0.10907 RPN box loss: 0.02993 RPN score loss: 0.00351 RPN total loss: 0.03345 Total loss: 1.27154 timestamp: 1654933934.3995674 iteration: 24180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19418 FastRCNN class loss: 0.07264 FastRCNN total loss: 0.26682 L1 loss: 0.0000e+00 L2 loss: 0.97825 Learning rate: 0.02 Mask loss: 0.15824 RPN box loss: 0.07253 RPN score loss: 0.00534 RPN total loss: 0.07787 Total loss: 1.48118 timestamp: 1654933937.5498285 iteration: 24185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07124 FastRCNN class loss: 0.03096 FastRCNN total loss: 0.10221 L1 loss: 0.0000e+00 L2 loss: 0.97811 Learning rate: 0.02 Mask loss: 0.15293 RPN box loss: 0.00481 RPN score loss: 0.00111 RPN total loss: 0.00592 Total loss: 1.23917 timestamp: 1654933940.7779894 iteration: 24190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16755 FastRCNN class loss: 0.11603 FastRCNN total loss: 0.28358 L1 loss: 0.0000e+00 L2 loss: 0.97795 Learning rate: 0.02 Mask loss: 0.19361 RPN box loss: 0.03755 RPN score loss: 0.00874 RPN total loss: 0.04629 Total loss: 1.50143 timestamp: 1654933943.9944458 iteration: 24195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15596 FastRCNN class loss: 0.14806 FastRCNN total loss: 0.30402 L1 loss: 0.0000e+00 L2 loss: 0.97781 Learning rate: 0.02 Mask loss: 0.19425 RPN box loss: 0.03797 RPN score loss: 0.00972 RPN total loss: 0.04768 Total loss: 1.52378 timestamp: 1654933947.177533 iteration: 24200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13354 FastRCNN class loss: 0.09699 FastRCNN total loss: 0.23053 L1 loss: 0.0000e+00 L2 loss: 0.97766 Learning rate: 0.02 Mask loss: 0.1407 RPN box loss: 0.02481 RPN score loss: 0.02623 RPN total loss: 0.05103 Total loss: 1.39993 timestamp: 1654933950.2869387 iteration: 24205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14951 FastRCNN class loss: 0.09023 FastRCNN total loss: 0.23974 L1 loss: 0.0000e+00 L2 loss: 0.97749 Learning rate: 0.02 Mask loss: 0.16473 RPN box loss: 0.02033 RPN score loss: 0.00268 RPN total loss: 0.02302 Total loss: 1.40497 timestamp: 1654933953.5308824 iteration: 24210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1132 FastRCNN class loss: 0.04411 FastRCNN total loss: 0.15731 L1 loss: 0.0000e+00 L2 loss: 0.97734 Learning rate: 0.02 Mask loss: 0.1181 RPN box loss: 0.02738 RPN score loss: 0.00661 RPN total loss: 0.03399 Total loss: 1.28674 timestamp: 1654933956.673347 iteration: 24215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10808 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.15781 L1 loss: 0.0000e+00 L2 loss: 0.97719 Learning rate: 0.02 Mask loss: 0.24391 RPN box loss: 0.00422 RPN score loss: 0.00177 RPN total loss: 0.00599 Total loss: 1.3849 timestamp: 1654933959.899429 iteration: 24220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12038 FastRCNN class loss: 0.05217 FastRCNN total loss: 0.17255 L1 loss: 0.0000e+00 L2 loss: 0.97702 Learning rate: 0.02 Mask loss: 0.14757 RPN box loss: 0.04869 RPN score loss: 0.00498 RPN total loss: 0.05367 Total loss: 1.3508 timestamp: 1654933963.135628 iteration: 24225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11946 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.17674 L1 loss: 0.0000e+00 L2 loss: 0.97687 Learning rate: 0.02 Mask loss: 0.13484 RPN box loss: 0.0481 RPN score loss: 0.00837 RPN total loss: 0.05647 Total loss: 1.34491 timestamp: 1654933966.3116531 iteration: 24230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16257 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.22088 L1 loss: 0.0000e+00 L2 loss: 0.97674 Learning rate: 0.02 Mask loss: 0.13813 RPN box loss: 0.01544 RPN score loss: 0.00426 RPN total loss: 0.0197 Total loss: 1.35545 timestamp: 1654933969.5029268 iteration: 24235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17816 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.26136 L1 loss: 0.0000e+00 L2 loss: 0.97658 Learning rate: 0.02 Mask loss: 0.16865 RPN box loss: 0.04393 RPN score loss: 0.00554 RPN total loss: 0.04947 Total loss: 1.45605 timestamp: 1654933972.748915 iteration: 24240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16623 FastRCNN class loss: 0.1046 FastRCNN total loss: 0.27084 L1 loss: 0.0000e+00 L2 loss: 0.97644 Learning rate: 0.02 Mask loss: 0.1852 RPN box loss: 0.02087 RPN score loss: 0.00185 RPN total loss: 0.02272 Total loss: 1.4552 timestamp: 1654933975.9957256 iteration: 24245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0907 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.14499 L1 loss: 0.0000e+00 L2 loss: 0.9763 Learning rate: 0.02 Mask loss: 0.14426 RPN box loss: 0.02733 RPN score loss: 0.00532 RPN total loss: 0.03266 Total loss: 1.29821 timestamp: 1654933979.262049 iteration: 24250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08669 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.16752 L1 loss: 0.0000e+00 L2 loss: 0.97614 Learning rate: 0.02 Mask loss: 0.13098 RPN box loss: 0.01411 RPN score loss: 0.00471 RPN total loss: 0.01882 Total loss: 1.29346 timestamp: 1654933982.4782171 iteration: 24255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18089 FastRCNN class loss: 0.08228 FastRCNN total loss: 0.26317 L1 loss: 0.0000e+00 L2 loss: 0.976 Learning rate: 0.02 Mask loss: 0.10095 RPN box loss: 0.04841 RPN score loss: 0.0063 RPN total loss: 0.05471 Total loss: 1.39484 timestamp: 1654933985.6539593 iteration: 24260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.12023 FastRCNN total loss: 0.2334 L1 loss: 0.0000e+00 L2 loss: 0.97586 Learning rate: 0.02 Mask loss: 0.20563 RPN box loss: 0.01521 RPN score loss: 0.00393 RPN total loss: 0.01914 Total loss: 1.43404 timestamp: 1654933988.8723876 iteration: 24265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08866 FastRCNN class loss: 0.12263 FastRCNN total loss: 0.21129 L1 loss: 0.0000e+00 L2 loss: 0.97571 Learning rate: 0.02 Mask loss: 0.12245 RPN box loss: 0.02345 RPN score loss: 0.01311 RPN total loss: 0.03656 Total loss: 1.34602 timestamp: 1654933992.0844667 iteration: 24270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14666 FastRCNN class loss: 0.10913 FastRCNN total loss: 0.25579 L1 loss: 0.0000e+00 L2 loss: 0.97557 Learning rate: 0.02 Mask loss: 0.14881 RPN box loss: 0.01863 RPN score loss: 0.00825 RPN total loss: 0.02688 Total loss: 1.40704 timestamp: 1654933995.2153487 iteration: 24275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15402 FastRCNN class loss: 0.07362 FastRCNN total loss: 0.22764 L1 loss: 0.0000e+00 L2 loss: 0.97541 Learning rate: 0.02 Mask loss: 0.13928 RPN box loss: 0.01775 RPN score loss: 0.00344 RPN total loss: 0.0212 Total loss: 1.36353 timestamp: 1654933998.4043725 iteration: 24280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13842 FastRCNN class loss: 0.04646 FastRCNN total loss: 0.18488 L1 loss: 0.0000e+00 L2 loss: 0.97525 Learning rate: 0.02 Mask loss: 0.14449 RPN box loss: 0.02235 RPN score loss: 0.00722 RPN total loss: 0.02958 Total loss: 1.3342 timestamp: 1654934001.5656157 iteration: 24285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12636 FastRCNN class loss: 0.09356 FastRCNN total loss: 0.21992 L1 loss: 0.0000e+00 L2 loss: 0.97509 Learning rate: 0.02 Mask loss: 0.19797 RPN box loss: 0.04091 RPN score loss: 0.00226 RPN total loss: 0.04318 Total loss: 1.43615 timestamp: 1654934004.7499456 iteration: 24290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12763 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.18807 L1 loss: 0.0000e+00 L2 loss: 0.97496 Learning rate: 0.02 Mask loss: 0.17429 RPN box loss: 0.03361 RPN score loss: 0.00661 RPN total loss: 0.04022 Total loss: 1.37753 timestamp: 1654934007.992812 iteration: 24295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14958 FastRCNN class loss: 0.0743 FastRCNN total loss: 0.22388 L1 loss: 0.0000e+00 L2 loss: 0.97479 Learning rate: 0.02 Mask loss: 0.1537 RPN box loss: 0.01774 RPN score loss: 0.00147 RPN total loss: 0.01921 Total loss: 1.37157 timestamp: 1654934011.1844127 iteration: 24300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11478 FastRCNN class loss: 0.07661 FastRCNN total loss: 0.19139 L1 loss: 0.0000e+00 L2 loss: 0.97462 Learning rate: 0.02 Mask loss: 0.14636 RPN box loss: 0.0394 RPN score loss: 0.00809 RPN total loss: 0.04749 Total loss: 1.35986 timestamp: 1654934014.3276596 iteration: 24305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10079 FastRCNN class loss: 0.08089 FastRCNN total loss: 0.18168 L1 loss: 0.0000e+00 L2 loss: 0.97447 Learning rate: 0.02 Mask loss: 0.12358 RPN box loss: 0.01735 RPN score loss: 0.00395 RPN total loss: 0.02131 Total loss: 1.30103 timestamp: 1654934017.4999022 iteration: 24310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11551 FastRCNN class loss: 0.08716 FastRCNN total loss: 0.20268 L1 loss: 0.0000e+00 L2 loss: 0.97429 Learning rate: 0.02 Mask loss: 0.13417 RPN box loss: 0.09611 RPN score loss: 0.00552 RPN total loss: 0.10163 Total loss: 1.41277 timestamp: 1654934020.789139 iteration: 24315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13491 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.22808 L1 loss: 0.0000e+00 L2 loss: 0.97414 Learning rate: 0.02 Mask loss: 0.18011 RPN box loss: 0.08118 RPN score loss: 0.00797 RPN total loss: 0.08915 Total loss: 1.47148 timestamp: 1654934024.0247622 iteration: 24320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14429 FastRCNN class loss: 0.09864 FastRCNN total loss: 0.24293 L1 loss: 0.0000e+00 L2 loss: 0.97402 Learning rate: 0.02 Mask loss: 0.13938 RPN box loss: 0.07884 RPN score loss: 0.01495 RPN total loss: 0.0938 Total loss: 1.45011 timestamp: 1654934027.2320783 iteration: 24325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21835 FastRCNN class loss: 0.09216 FastRCNN total loss: 0.31051 L1 loss: 0.0000e+00 L2 loss: 0.97386 Learning rate: 0.02 Mask loss: 0.15793 RPN box loss: 0.04792 RPN score loss: 0.02576 RPN total loss: 0.07368 Total loss: 1.51597 timestamp: 1654934030.4699497 iteration: 24330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.10731 FastRCNN total loss: 0.23491 L1 loss: 0.0000e+00 L2 loss: 0.97371 Learning rate: 0.02 Mask loss: 0.14927 RPN box loss: 0.02263 RPN score loss: 0.00418 RPN total loss: 0.02681 Total loss: 1.38469 timestamp: 1654934033.5839858 iteration: 24335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15266 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.22957 L1 loss: 0.0000e+00 L2 loss: 0.97355 Learning rate: 0.02 Mask loss: 0.13013 RPN box loss: 0.0452 RPN score loss: 0.00521 RPN total loss: 0.05042 Total loss: 1.38366 timestamp: 1654934036.7201884 iteration: 24340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16114 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.21002 L1 loss: 0.0000e+00 L2 loss: 0.97341 Learning rate: 0.02 Mask loss: 0.09558 RPN box loss: 0.0162 RPN score loss: 0.00224 RPN total loss: 0.01844 Total loss: 1.29746 timestamp: 1654934039.8741431 iteration: 24345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07858 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.1607 L1 loss: 0.0000e+00 L2 loss: 0.97326 Learning rate: 0.02 Mask loss: 0.10349 RPN box loss: 0.01947 RPN score loss: 0.00631 RPN total loss: 0.02578 Total loss: 1.26322 timestamp: 1654934043.0128093 iteration: 24350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19627 FastRCNN class loss: 0.14717 FastRCNN total loss: 0.34344 L1 loss: 0.0000e+00 L2 loss: 0.97311 Learning rate: 0.02 Mask loss: 0.2547 RPN box loss: 0.0269 RPN score loss: 0.01412 RPN total loss: 0.04101 Total loss: 1.61226 timestamp: 1654934046.2295399 iteration: 24355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10074 FastRCNN class loss: 0.07068 FastRCNN total loss: 0.17142 L1 loss: 0.0000e+00 L2 loss: 0.97298 Learning rate: 0.02 Mask loss: 0.16839 RPN box loss: 0.02559 RPN score loss: 0.00626 RPN total loss: 0.03185 Total loss: 1.34464 timestamp: 1654934049.4597173 iteration: 24360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12076 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.18362 L1 loss: 0.0000e+00 L2 loss: 0.97284 Learning rate: 0.02 Mask loss: 0.11187 RPN box loss: 0.02323 RPN score loss: 0.00238 RPN total loss: 0.02561 Total loss: 1.29394 timestamp: 1654934052.6897907 iteration: 24365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11827 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.18886 L1 loss: 0.0000e+00 L2 loss: 0.97269 Learning rate: 0.02 Mask loss: 0.13326 RPN box loss: 0.03766 RPN score loss: 0.00696 RPN total loss: 0.04462 Total loss: 1.33943 timestamp: 1654934055.9041905 iteration: 24370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13001 FastRCNN class loss: 0.12681 FastRCNN total loss: 0.25682 L1 loss: 0.0000e+00 L2 loss: 0.97253 Learning rate: 0.02 Mask loss: 0.20343 RPN box loss: 0.02236 RPN score loss: 0.00322 RPN total loss: 0.02558 Total loss: 1.45836 timestamp: 1654934059.0252979 iteration: 24375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19278 FastRCNN class loss: 0.10435 FastRCNN total loss: 0.29713 L1 loss: 0.0000e+00 L2 loss: 0.97237 Learning rate: 0.02 Mask loss: 0.19012 RPN box loss: 0.0242 RPN score loss: 0.01074 RPN total loss: 0.03493 Total loss: 1.49456 timestamp: 1654934062.2656505 iteration: 24380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1361 FastRCNN class loss: 0.07857 FastRCNN total loss: 0.21467 L1 loss: 0.0000e+00 L2 loss: 0.97222 Learning rate: 0.02 Mask loss: 0.13803 RPN box loss: 0.02727 RPN score loss: 0.01168 RPN total loss: 0.03896 Total loss: 1.36387 timestamp: 1654934065.4510374 iteration: 24385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15103 FastRCNN class loss: 0.07784 FastRCNN total loss: 0.22887 L1 loss: 0.0000e+00 L2 loss: 0.97209 Learning rate: 0.02 Mask loss: 0.14216 RPN box loss: 0.03974 RPN score loss: 0.0085 RPN total loss: 0.04824 Total loss: 1.39136 timestamp: 1654934068.6088953 iteration: 24390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1102 FastRCNN class loss: 0.07744 FastRCNN total loss: 0.18765 L1 loss: 0.0000e+00 L2 loss: 0.97192 Learning rate: 0.02 Mask loss: 0.12575 RPN box loss: 0.0231 RPN score loss: 0.00533 RPN total loss: 0.02843 Total loss: 1.31375 timestamp: 1654934071.735663 iteration: 24395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15529 FastRCNN class loss: 0.12269 FastRCNN total loss: 0.27798 L1 loss: 0.0000e+00 L2 loss: 0.9718 Learning rate: 0.02 Mask loss: 0.18825 RPN box loss: 0.02619 RPN score loss: 0.00779 RPN total loss: 0.03398 Total loss: 1.47201 timestamp: 1654934074.932109 iteration: 24400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14225 FastRCNN class loss: 0.11102 FastRCNN total loss: 0.25327 L1 loss: 0.0000e+00 L2 loss: 0.97161 Learning rate: 0.02 Mask loss: 0.13184 RPN box loss: 0.0259 RPN score loss: 0.00805 RPN total loss: 0.03396 Total loss: 1.39068 timestamp: 1654934078.0740132 iteration: 24405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06793 FastRCNN class loss: 0.06835 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.97147 Learning rate: 0.02 Mask loss: 0.25714 RPN box loss: 0.02464 RPN score loss: 0.00225 RPN total loss: 0.02689 Total loss: 1.39179 timestamp: 1654934081.2969604 iteration: 24410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21694 FastRCNN class loss: 0.13646 FastRCNN total loss: 0.3534 L1 loss: 0.0000e+00 L2 loss: 0.97135 Learning rate: 0.02 Mask loss: 0.16678 RPN box loss: 0.04735 RPN score loss: 0.0056 RPN total loss: 0.05296 Total loss: 1.54449 timestamp: 1654934084.5456197 iteration: 24415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12511 FastRCNN class loss: 0.10066 FastRCNN total loss: 0.22576 L1 loss: 0.0000e+00 L2 loss: 0.9712 Learning rate: 0.02 Mask loss: 0.18986 RPN box loss: 0.06628 RPN score loss: 0.01359 RPN total loss: 0.07987 Total loss: 1.46669 timestamp: 1654934087.731047 iteration: 24420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18839 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.26848 L1 loss: 0.0000e+00 L2 loss: 0.97106 Learning rate: 0.02 Mask loss: 0.12965 RPN box loss: 0.00755 RPN score loss: 0.00264 RPN total loss: 0.01019 Total loss: 1.37938 timestamp: 1654934091.0382447 iteration: 24425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17666 FastRCNN class loss: 0.08377 FastRCNN total loss: 0.26043 L1 loss: 0.0000e+00 L2 loss: 0.9709 Learning rate: 0.02 Mask loss: 0.12877 RPN box loss: 0.02211 RPN score loss: 0.01208 RPN total loss: 0.03418 Total loss: 1.39428 timestamp: 1654934094.2470694 iteration: 24430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21615 FastRCNN class loss: 0.06544 FastRCNN total loss: 0.28159 L1 loss: 0.0000e+00 L2 loss: 0.97075 Learning rate: 0.02 Mask loss: 0.12339 RPN box loss: 0.03533 RPN score loss: 0.00616 RPN total loss: 0.04149 Total loss: 1.41722 timestamp: 1654934097.4371722 iteration: 24435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17203 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.24894 L1 loss: 0.0000e+00 L2 loss: 0.97059 Learning rate: 0.02 Mask loss: 0.18003 RPN box loss: 0.04717 RPN score loss: 0.0138 RPN total loss: 0.06098 Total loss: 1.46053 timestamp: 1654934100.7062292 iteration: 24440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12634 FastRCNN class loss: 0.09875 FastRCNN total loss: 0.2251 L1 loss: 0.0000e+00 L2 loss: 0.97042 Learning rate: 0.02 Mask loss: 0.18006 RPN box loss: 0.0376 RPN score loss: 0.00999 RPN total loss: 0.04759 Total loss: 1.42316 timestamp: 1654934103.8951228 iteration: 24445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16292 FastRCNN class loss: 0.09918 FastRCNN total loss: 0.2621 L1 loss: 0.0000e+00 L2 loss: 0.97029 Learning rate: 0.02 Mask loss: 0.19181 RPN box loss: 0.03142 RPN score loss: 0.00825 RPN total loss: 0.03967 Total loss: 1.46387 timestamp: 1654934107.090778 iteration: 24450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11558 FastRCNN class loss: 0.15702 FastRCNN total loss: 0.2726 L1 loss: 0.0000e+00 L2 loss: 0.97017 Learning rate: 0.02 Mask loss: 0.18871 RPN box loss: 0.04894 RPN score loss: 0.01669 RPN total loss: 0.06564 Total loss: 1.49712 timestamp: 1654934110.3068447 iteration: 24455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12136 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.18211 L1 loss: 0.0000e+00 L2 loss: 0.97003 Learning rate: 0.02 Mask loss: 0.2106 RPN box loss: 0.03492 RPN score loss: 0.01084 RPN total loss: 0.04576 Total loss: 1.4085 timestamp: 1654934113.4817803 iteration: 24460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17397 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.27102 L1 loss: 0.0000e+00 L2 loss: 0.96992 Learning rate: 0.02 Mask loss: 0.17279 RPN box loss: 0.01896 RPN score loss: 0.0075 RPN total loss: 0.02647 Total loss: 1.44019 timestamp: 1654934116.68363 iteration: 24465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14383 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.2166 L1 loss: 0.0000e+00 L2 loss: 0.96974 Learning rate: 0.02 Mask loss: 0.14711 RPN box loss: 0.04992 RPN score loss: 0.00789 RPN total loss: 0.05782 Total loss: 1.39126 timestamp: 1654934119.908209 iteration: 24470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14142 FastRCNN class loss: 0.10705 FastRCNN total loss: 0.24847 L1 loss: 0.0000e+00 L2 loss: 0.96957 Learning rate: 0.02 Mask loss: 0.18408 RPN box loss: 0.0212 RPN score loss: 0.00408 RPN total loss: 0.02528 Total loss: 1.4274 timestamp: 1654934123.1451817 iteration: 24475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13763 FastRCNN class loss: 0.12144 FastRCNN total loss: 0.25907 L1 loss: 0.0000e+00 L2 loss: 0.96944 Learning rate: 0.02 Mask loss: 0.15681 RPN box loss: 0.02172 RPN score loss: 0.00803 RPN total loss: 0.02975 Total loss: 1.41507 timestamp: 1654934126.3325784 iteration: 24480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15975 FastRCNN class loss: 0.12658 FastRCNN total loss: 0.28632 L1 loss: 0.0000e+00 L2 loss: 0.96926 Learning rate: 0.02 Mask loss: 0.23946 RPN box loss: 0.02204 RPN score loss: 0.01006 RPN total loss: 0.0321 Total loss: 1.52714 timestamp: 1654934129.5215628 iteration: 24485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09364 FastRCNN class loss: 0.04617 FastRCNN total loss: 0.1398 L1 loss: 0.0000e+00 L2 loss: 0.96911 Learning rate: 0.02 Mask loss: 0.07933 RPN box loss: 0.01125 RPN score loss: 0.00424 RPN total loss: 0.01549 Total loss: 1.20374 timestamp: 1654934132.6399436 iteration: 24490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06211 FastRCNN class loss: 0.04915 FastRCNN total loss: 0.11126 L1 loss: 0.0000e+00 L2 loss: 0.96898 Learning rate: 0.02 Mask loss: 0.07671 RPN box loss: 0.05463 RPN score loss: 0.00675 RPN total loss: 0.06138 Total loss: 1.21833 timestamp: 1654934135.9293566 iteration: 24495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08694 FastRCNN class loss: 0.04577 FastRCNN total loss: 0.13271 L1 loss: 0.0000e+00 L2 loss: 0.96883 Learning rate: 0.02 Mask loss: 0.11865 RPN box loss: 0.06471 RPN score loss: 0.00522 RPN total loss: 0.06993 Total loss: 1.29012 timestamp: 1654934139.2143934 iteration: 24500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10157 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.16261 L1 loss: 0.0000e+00 L2 loss: 0.96866 Learning rate: 0.02 Mask loss: 0.11574 RPN box loss: 0.02729 RPN score loss: 0.00222 RPN total loss: 0.02951 Total loss: 1.27653 timestamp: 1654934142.340344 iteration: 24505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15675 FastRCNN class loss: 0.12497 FastRCNN total loss: 0.28172 L1 loss: 0.0000e+00 L2 loss: 0.9685 Learning rate: 0.02 Mask loss: 0.18562 RPN box loss: 0.01395 RPN score loss: 0.00784 RPN total loss: 0.02179 Total loss: 1.45762 timestamp: 1654934145.576732 iteration: 24510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14878 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.22112 L1 loss: 0.0000e+00 L2 loss: 0.96837 Learning rate: 0.02 Mask loss: 0.25001 RPN box loss: 0.03103 RPN score loss: 0.00268 RPN total loss: 0.03371 Total loss: 1.47321 timestamp: 1654934148.8160472 iteration: 24515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16664 FastRCNN class loss: 0.10652 FastRCNN total loss: 0.27316 L1 loss: 0.0000e+00 L2 loss: 0.96821 Learning rate: 0.02 Mask loss: 0.22695 RPN box loss: 0.02359 RPN score loss: 0.00866 RPN total loss: 0.03226 Total loss: 1.50058 timestamp: 1654934152.0198078 iteration: 24520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17445 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.25216 L1 loss: 0.0000e+00 L2 loss: 0.96802 Learning rate: 0.02 Mask loss: 0.1784 RPN box loss: 0.0674 RPN score loss: 0.00797 RPN total loss: 0.07537 Total loss: 1.47396 timestamp: 1654934155.22063 iteration: 24525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.147 FastRCNN class loss: 0.09445 FastRCNN total loss: 0.24145 L1 loss: 0.0000e+00 L2 loss: 0.9679 Learning rate: 0.02 Mask loss: 0.16773 RPN box loss: 0.02664 RPN score loss: 0.00563 RPN total loss: 0.03226 Total loss: 1.40934 timestamp: 1654934158.376895 iteration: 24530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.04095 FastRCNN total loss: 0.14095 L1 loss: 0.0000e+00 L2 loss: 0.96776 Learning rate: 0.02 Mask loss: 0.08563 RPN box loss: 0.00949 RPN score loss: 0.00183 RPN total loss: 0.01132 Total loss: 1.20565 timestamp: 1654934161.5667446 iteration: 24535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15573 FastRCNN class loss: 0.07817 FastRCNN total loss: 0.23389 L1 loss: 0.0000e+00 L2 loss: 0.9676 Learning rate: 0.02 Mask loss: 0.14465 RPN box loss: 0.02457 RPN score loss: 0.00336 RPN total loss: 0.02793 Total loss: 1.37407 timestamp: 1654934164.7375944 iteration: 24540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14124 FastRCNN class loss: 0.13285 FastRCNN total loss: 0.2741 L1 loss: 0.0000e+00 L2 loss: 0.96747 Learning rate: 0.02 Mask loss: 0.25491 RPN box loss: 0.0679 RPN score loss: 0.03316 RPN total loss: 0.10106 Total loss: 1.59754 timestamp: 1654934167.942105 iteration: 24545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18971 FastRCNN class loss: 0.08777 FastRCNN total loss: 0.27749 L1 loss: 0.0000e+00 L2 loss: 0.96731 Learning rate: 0.02 Mask loss: 0.11591 RPN box loss: 0.0216 RPN score loss: 0.00474 RPN total loss: 0.02634 Total loss: 1.38704 timestamp: 1654934171.1742148 iteration: 24550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11281 FastRCNN class loss: 0.05288 FastRCNN total loss: 0.16568 L1 loss: 0.0000e+00 L2 loss: 0.96715 Learning rate: 0.02 Mask loss: 0.1202 RPN box loss: 0.01122 RPN score loss: 0.00461 RPN total loss: 0.01583 Total loss: 1.26887 timestamp: 1654934174.408966 iteration: 24555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10088 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.20181 L1 loss: 0.0000e+00 L2 loss: 0.96704 Learning rate: 0.02 Mask loss: 0.13606 RPN box loss: 0.03919 RPN score loss: 0.00363 RPN total loss: 0.04282 Total loss: 1.34773 timestamp: 1654934177.6040492 iteration: 24560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19121 FastRCNN class loss: 0.14715 FastRCNN total loss: 0.33837 L1 loss: 0.0000e+00 L2 loss: 0.9669 Learning rate: 0.02 Mask loss: 0.24677 RPN box loss: 0.06195 RPN score loss: 0.01642 RPN total loss: 0.07837 Total loss: 1.6304 timestamp: 1654934180.7736237 iteration: 24565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10849 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.19008 L1 loss: 0.0000e+00 L2 loss: 0.96676 Learning rate: 0.02 Mask loss: 0.17526 RPN box loss: 0.05196 RPN score loss: 0.00709 RPN total loss: 0.05905 Total loss: 1.39115 timestamp: 1654934183.9495149 iteration: 24570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11817 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.18326 L1 loss: 0.0000e+00 L2 loss: 0.96662 Learning rate: 0.02 Mask loss: 0.09477 RPN box loss: 0.09235 RPN score loss: 0.00552 RPN total loss: 0.09786 Total loss: 1.34252 timestamp: 1654934187.1492546 iteration: 24575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09095 FastRCNN class loss: 0.07309 FastRCNN total loss: 0.16404 L1 loss: 0.0000e+00 L2 loss: 0.96646 Learning rate: 0.02 Mask loss: 0.14573 RPN box loss: 0.02683 RPN score loss: 0.00671 RPN total loss: 0.03354 Total loss: 1.30977 timestamp: 1654934190.2982535 iteration: 24580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10666 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.17768 L1 loss: 0.0000e+00 L2 loss: 0.96632 Learning rate: 0.02 Mask loss: 0.12222 RPN box loss: 0.03092 RPN score loss: 0.00392 RPN total loss: 0.03484 Total loss: 1.30106 timestamp: 1654934193.5208316 iteration: 24585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09734 FastRCNN class loss: 0.04647 FastRCNN total loss: 0.14381 L1 loss: 0.0000e+00 L2 loss: 0.96617 Learning rate: 0.02 Mask loss: 0.10316 RPN box loss: 0.00197 RPN score loss: 0.00205 RPN total loss: 0.00401 Total loss: 1.21716 timestamp: 1654934196.714978 iteration: 24590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06192 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.11489 L1 loss: 0.0000e+00 L2 loss: 0.966 Learning rate: 0.02 Mask loss: 0.0969 RPN box loss: 0.01166 RPN score loss: 0.00376 RPN total loss: 0.01542 Total loss: 1.19321 timestamp: 1654934199.8837323 iteration: 24595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15404 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.23857 L1 loss: 0.0000e+00 L2 loss: 0.96585 Learning rate: 0.02 Mask loss: 0.19256 RPN box loss: 0.01799 RPN score loss: 0.00643 RPN total loss: 0.02441 Total loss: 1.42139 timestamp: 1654934203.1016545 iteration: 24600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.07793 FastRCNN total loss: 0.17937 L1 loss: 0.0000e+00 L2 loss: 0.96568 Learning rate: 0.02 Mask loss: 0.12466 RPN box loss: 0.0254 RPN score loss: 0.00892 RPN total loss: 0.03432 Total loss: 1.30403 timestamp: 1654934206.2240684 iteration: 24605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08332 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.16328 L1 loss: 0.0000e+00 L2 loss: 0.96553 Learning rate: 0.02 Mask loss: 0.14723 RPN box loss: 0.0323 RPN score loss: 0.01414 RPN total loss: 0.04644 Total loss: 1.32249 timestamp: 1654934209.458772 iteration: 24610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16316 FastRCNN class loss: 0.07531 FastRCNN total loss: 0.23847 L1 loss: 0.0000e+00 L2 loss: 0.96541 Learning rate: 0.02 Mask loss: 0.12556 RPN box loss: 0.01295 RPN score loss: 0.00916 RPN total loss: 0.02212 Total loss: 1.35155 timestamp: 1654934212.6303694 iteration: 24615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12222 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.20232 L1 loss: 0.0000e+00 L2 loss: 0.96526 Learning rate: 0.02 Mask loss: 0.17347 RPN box loss: 0.04493 RPN score loss: 0.0085 RPN total loss: 0.05343 Total loss: 1.39448 timestamp: 1654934215.8328965 iteration: 24620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16776 FastRCNN class loss: 0.10235 FastRCNN total loss: 0.2701 L1 loss: 0.0000e+00 L2 loss: 0.96507 Learning rate: 0.02 Mask loss: 0.17218 RPN box loss: 0.02333 RPN score loss: 0.00936 RPN total loss: 0.03269 Total loss: 1.44004 timestamp: 1654934219.0735855 iteration: 24625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18682 FastRCNN class loss: 0.13321 FastRCNN total loss: 0.32003 L1 loss: 0.0000e+00 L2 loss: 0.96495 Learning rate: 0.02 Mask loss: 0.17362 RPN box loss: 0.01962 RPN score loss: 0.00488 RPN total loss: 0.0245 Total loss: 1.48309 timestamp: 1654934222.2923715 iteration: 24630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15085 FastRCNN class loss: 0.09423 FastRCNN total loss: 0.24508 L1 loss: 0.0000e+00 L2 loss: 0.96484 Learning rate: 0.02 Mask loss: 0.20586 RPN box loss: 0.02962 RPN score loss: 0.00656 RPN total loss: 0.03618 Total loss: 1.45196 timestamp: 1654934225.5399976 iteration: 24635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11276 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.17212 L1 loss: 0.0000e+00 L2 loss: 0.96468 Learning rate: 0.02 Mask loss: 0.18255 RPN box loss: 0.02948 RPN score loss: 0.0054 RPN total loss: 0.03488 Total loss: 1.35422 timestamp: 1654934228.8443897 iteration: 24640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12525 FastRCNN class loss: 0.08093 FastRCNN total loss: 0.20617 L1 loss: 0.0000e+00 L2 loss: 0.96454 Learning rate: 0.02 Mask loss: 0.14734 RPN box loss: 0.02394 RPN score loss: 0.00714 RPN total loss: 0.03108 Total loss: 1.34913 timestamp: 1654934231.9978085 iteration: 24645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1196 FastRCNN class loss: 0.10563 FastRCNN total loss: 0.22524 L1 loss: 0.0000e+00 L2 loss: 0.96443 Learning rate: 0.02 Mask loss: 0.12067 RPN box loss: 0.04069 RPN score loss: 0.00462 RPN total loss: 0.04531 Total loss: 1.35565 timestamp: 1654934235.125746 iteration: 24650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12486 FastRCNN class loss: 0.07974 FastRCNN total loss: 0.2046 L1 loss: 0.0000e+00 L2 loss: 0.96428 Learning rate: 0.02 Mask loss: 0.13556 RPN box loss: 0.0545 RPN score loss: 0.0032 RPN total loss: 0.0577 Total loss: 1.36215 timestamp: 1654934238.4104903 iteration: 24655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10991 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.16675 L1 loss: 0.0000e+00 L2 loss: 0.96415 Learning rate: 0.02 Mask loss: 0.16487 RPN box loss: 0.01032 RPN score loss: 0.00305 RPN total loss: 0.01337 Total loss: 1.30913 timestamp: 1654934241.560088 iteration: 24660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16011 FastRCNN class loss: 0.11249 FastRCNN total loss: 0.27261 L1 loss: 0.0000e+00 L2 loss: 0.96401 Learning rate: 0.02 Mask loss: 0.10887 RPN box loss: 0.06113 RPN score loss: 0.00655 RPN total loss: 0.06768 Total loss: 1.41317 timestamp: 1654934244.7454717 iteration: 24665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13947 FastRCNN class loss: 0.14849 FastRCNN total loss: 0.28796 L1 loss: 0.0000e+00 L2 loss: 0.96387 Learning rate: 0.02 Mask loss: 0.17975 RPN box loss: 0.05026 RPN score loss: 0.00837 RPN total loss: 0.05863 Total loss: 1.49022 timestamp: 1654934247.9952426 iteration: 24670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08017 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.12503 L1 loss: 0.0000e+00 L2 loss: 0.96372 Learning rate: 0.02 Mask loss: 0.09177 RPN box loss: 0.01789 RPN score loss: 0.00604 RPN total loss: 0.02393 Total loss: 1.20444 timestamp: 1654934251.1867614 iteration: 24675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12548 FastRCNN class loss: 0.09472 FastRCNN total loss: 0.2202 L1 loss: 0.0000e+00 L2 loss: 0.96356 Learning rate: 0.02 Mask loss: 0.17581 RPN box loss: 0.0619 RPN score loss: 0.00924 RPN total loss: 0.07114 Total loss: 1.4307 timestamp: 1654934254.3520932 iteration: 24680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21688 FastRCNN class loss: 0.09251 FastRCNN total loss: 0.30939 L1 loss: 0.0000e+00 L2 loss: 0.9634 Learning rate: 0.02 Mask loss: 0.18234 RPN box loss: 0.06613 RPN score loss: 0.01004 RPN total loss: 0.07617 Total loss: 1.53131 timestamp: 1654934257.5462854 iteration: 24685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15977 FastRCNN class loss: 0.10019 FastRCNN total loss: 0.25996 L1 loss: 0.0000e+00 L2 loss: 0.96326 Learning rate: 0.02 Mask loss: 0.21141 RPN box loss: 0.03544 RPN score loss: 0.00759 RPN total loss: 0.04303 Total loss: 1.47766 timestamp: 1654934260.7800965 iteration: 24690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0665 FastRCNN class loss: 0.06029 FastRCNN total loss: 0.12679 L1 loss: 0.0000e+00 L2 loss: 0.96313 Learning rate: 0.02 Mask loss: 0.17896 RPN box loss: 0.03779 RPN score loss: 0.00407 RPN total loss: 0.04185 Total loss: 1.31073 timestamp: 1654934264.0763323 iteration: 24695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1169 FastRCNN class loss: 0.11827 FastRCNN total loss: 0.23517 L1 loss: 0.0000e+00 L2 loss: 0.96299 Learning rate: 0.02 Mask loss: 0.14604 RPN box loss: 0.014 RPN score loss: 0.0045 RPN total loss: 0.01849 Total loss: 1.3627 timestamp: 1654934267.3372083 iteration: 24700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22943 FastRCNN class loss: 0.11748 FastRCNN total loss: 0.34691 L1 loss: 0.0000e+00 L2 loss: 0.96286 Learning rate: 0.02 Mask loss: 0.18915 RPN box loss: 0.043 RPN score loss: 0.02181 RPN total loss: 0.0648 Total loss: 1.56373 timestamp: 1654934270.5418198 iteration: 24705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09734 FastRCNN class loss: 0.04311 FastRCNN total loss: 0.14045 L1 loss: 0.0000e+00 L2 loss: 0.9627 Learning rate: 0.02 Mask loss: 0.17808 RPN box loss: 0.02511 RPN score loss: 0.00191 RPN total loss: 0.02702 Total loss: 1.30825 timestamp: 1654934273.6689622 iteration: 24710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14984 FastRCNN class loss: 0.11253 FastRCNN total loss: 0.26237 L1 loss: 0.0000e+00 L2 loss: 0.96253 Learning rate: 0.02 Mask loss: 0.14384 RPN box loss: 0.05198 RPN score loss: 0.01255 RPN total loss: 0.06452 Total loss: 1.43325 timestamp: 1654934276.8793645 iteration: 24715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12299 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.1793 L1 loss: 0.0000e+00 L2 loss: 0.96237 Learning rate: 0.02 Mask loss: 0.14199 RPN box loss: 0.02388 RPN score loss: 0.00359 RPN total loss: 0.02746 Total loss: 1.31112 timestamp: 1654934280.0526435 iteration: 24720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11405 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.17878 L1 loss: 0.0000e+00 L2 loss: 0.96221 Learning rate: 0.02 Mask loss: 0.14132 RPN box loss: 0.02707 RPN score loss: 0.0072 RPN total loss: 0.03427 Total loss: 1.31658 timestamp: 1654934283.2811084 iteration: 24725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22108 FastRCNN class loss: 0.07905 FastRCNN total loss: 0.30013 L1 loss: 0.0000e+00 L2 loss: 0.96206 Learning rate: 0.02 Mask loss: 0.1348 RPN box loss: 0.04077 RPN score loss: 0.00438 RPN total loss: 0.04516 Total loss: 1.44215 timestamp: 1654934286.5708582 iteration: 24730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16148 FastRCNN class loss: 0.15594 FastRCNN total loss: 0.31742 L1 loss: 0.0000e+00 L2 loss: 0.96191 Learning rate: 0.02 Mask loss: 0.19598 RPN box loss: 0.03974 RPN score loss: 0.01389 RPN total loss: 0.05363 Total loss: 1.52895 timestamp: 1654934289.7497065 iteration: 24735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.11816 L1 loss: 0.0000e+00 L2 loss: 0.96175 Learning rate: 0.02 Mask loss: 0.15805 RPN box loss: 0.00965 RPN score loss: 0.00078 RPN total loss: 0.01044 Total loss: 1.2484 timestamp: 1654934292.869556 iteration: 24740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17515 FastRCNN class loss: 0.0851 FastRCNN total loss: 0.26024 L1 loss: 0.0000e+00 L2 loss: 0.96159 Learning rate: 0.02 Mask loss: 0.12753 RPN box loss: 0.03885 RPN score loss: 0.00479 RPN total loss: 0.04364 Total loss: 1.393 timestamp: 1654934296.1035666 iteration: 24745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13952 FastRCNN class loss: 0.08916 FastRCNN total loss: 0.22868 L1 loss: 0.0000e+00 L2 loss: 0.96143 Learning rate: 0.02 Mask loss: 0.16118 RPN box loss: 0.02069 RPN score loss: 0.00427 RPN total loss: 0.02496 Total loss: 1.37624 timestamp: 1654934299.330715 iteration: 24750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12802 FastRCNN class loss: 0.08437 FastRCNN total loss: 0.21239 L1 loss: 0.0000e+00 L2 loss: 0.96126 Learning rate: 0.02 Mask loss: 0.12005 RPN box loss: 0.03031 RPN score loss: 0.00903 RPN total loss: 0.03933 Total loss: 1.33303 timestamp: 1654934302.4437094 iteration: 24755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09765 FastRCNN class loss: 0.0871 FastRCNN total loss: 0.18475 L1 loss: 0.0000e+00 L2 loss: 0.9611 Learning rate: 0.02 Mask loss: 0.17341 RPN box loss: 0.02096 RPN score loss: 0.01996 RPN total loss: 0.04093 Total loss: 1.36018 timestamp: 1654934305.6263525 iteration: 24760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15297 FastRCNN class loss: 0.08203 FastRCNN total loss: 0.235 L1 loss: 0.0000e+00 L2 loss: 0.96097 Learning rate: 0.02 Mask loss: 0.19255 RPN box loss: 0.02864 RPN score loss: 0.00413 RPN total loss: 0.03277 Total loss: 1.42129 timestamp: 1654934308.7759657 iteration: 24765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.16328 L1 loss: 0.0000e+00 L2 loss: 0.96083 Learning rate: 0.02 Mask loss: 0.10185 RPN box loss: 0.04351 RPN score loss: 0.00891 RPN total loss: 0.05241 Total loss: 1.27837 timestamp: 1654934312.0075464 iteration: 24770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17135 FastRCNN class loss: 0.1706 FastRCNN total loss: 0.34195 L1 loss: 0.0000e+00 L2 loss: 0.96069 Learning rate: 0.02 Mask loss: 0.24109 RPN box loss: 0.03153 RPN score loss: 0.01103 RPN total loss: 0.04256 Total loss: 1.58628 timestamp: 1654934315.2133236 iteration: 24775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.149 FastRCNN class loss: 0.06214 FastRCNN total loss: 0.21114 L1 loss: 0.0000e+00 L2 loss: 0.96055 Learning rate: 0.02 Mask loss: 0.33236 RPN box loss: 0.05068 RPN score loss: 0.0096 RPN total loss: 0.06028 Total loss: 1.56432 timestamp: 1654934318.4042704 iteration: 24780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10101 FastRCNN class loss: 0.09137 FastRCNN total loss: 0.19238 L1 loss: 0.0000e+00 L2 loss: 0.96038 Learning rate: 0.02 Mask loss: 0.15114 RPN box loss: 0.01869 RPN score loss: 0.01506 RPN total loss: 0.03375 Total loss: 1.33764 timestamp: 1654934321.7111177 iteration: 24785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16237 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.22175 L1 loss: 0.0000e+00 L2 loss: 0.96023 Learning rate: 0.02 Mask loss: 0.14158 RPN box loss: 0.07933 RPN score loss: 0.01099 RPN total loss: 0.09032 Total loss: 1.41388 timestamp: 1654934324.853181 iteration: 24790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11549 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.17142 L1 loss: 0.0000e+00 L2 loss: 0.96009 Learning rate: 0.02 Mask loss: 0.14905 RPN box loss: 0.01703 RPN score loss: 0.00405 RPN total loss: 0.02108 Total loss: 1.30163 timestamp: 1654934328.0996957 iteration: 24795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12123 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.20242 L1 loss: 0.0000e+00 L2 loss: 0.95993 Learning rate: 0.02 Mask loss: 0.19615 RPN box loss: 0.02391 RPN score loss: 0.00287 RPN total loss: 0.02678 Total loss: 1.38528 timestamp: 1654934331.2792704 iteration: 24800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16511 FastRCNN class loss: 0.08884 FastRCNN total loss: 0.25395 L1 loss: 0.0000e+00 L2 loss: 0.95979 Learning rate: 0.02 Mask loss: 0.17389 RPN box loss: 0.03301 RPN score loss: 0.00804 RPN total loss: 0.04104 Total loss: 1.42867 timestamp: 1654934334.5212011 iteration: 24805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09658 FastRCNN class loss: 0.09608 FastRCNN total loss: 0.19265 L1 loss: 0.0000e+00 L2 loss: 0.95966 Learning rate: 0.02 Mask loss: 0.15595 RPN box loss: 0.03326 RPN score loss: 0.00589 RPN total loss: 0.03914 Total loss: 1.3474 timestamp: 1654934337.748146 iteration: 24810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2325 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.30505 L1 loss: 0.0000e+00 L2 loss: 0.95952 Learning rate: 0.02 Mask loss: 0.13221 RPN box loss: 0.0174 RPN score loss: 0.00429 RPN total loss: 0.0217 Total loss: 1.41847 timestamp: 1654934340.982354 iteration: 24815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06786 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.13869 L1 loss: 0.0000e+00 L2 loss: 0.95937 Learning rate: 0.02 Mask loss: 0.12772 RPN box loss: 0.02035 RPN score loss: 0.00797 RPN total loss: 0.02832 Total loss: 1.2541 timestamp: 1654934344.2065198 iteration: 24820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08907 FastRCNN class loss: 0.04649 FastRCNN total loss: 0.13556 L1 loss: 0.0000e+00 L2 loss: 0.95921 Learning rate: 0.02 Mask loss: 0.10388 RPN box loss: 0.01886 RPN score loss: 0.00308 RPN total loss: 0.02194 Total loss: 1.22058 timestamp: 1654934347.378138 iteration: 24825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21881 FastRCNN class loss: 0.14923 FastRCNN total loss: 0.36804 L1 loss: 0.0000e+00 L2 loss: 0.95906 Learning rate: 0.02 Mask loss: 0.28477 RPN box loss: 0.05291 RPN score loss: 0.01087 RPN total loss: 0.06378 Total loss: 1.67565 timestamp: 1654934350.5759544 iteration: 24830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14297 FastRCNN class loss: 0.05565 FastRCNN total loss: 0.19863 L1 loss: 0.0000e+00 L2 loss: 0.9589 Learning rate: 0.02 Mask loss: 0.12342 RPN box loss: 0.01086 RPN score loss: 0.00175 RPN total loss: 0.01261 Total loss: 1.29355 timestamp: 1654934353.7718694 iteration: 24835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16401 FastRCNN class loss: 0.09446 FastRCNN total loss: 0.25847 L1 loss: 0.0000e+00 L2 loss: 0.95873 Learning rate: 0.02 Mask loss: 0.16103 RPN box loss: 0.03675 RPN score loss: 0.00818 RPN total loss: 0.04493 Total loss: 1.42316 timestamp: 1654934357.0733209 iteration: 24840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07314 FastRCNN class loss: 0.05721 FastRCNN total loss: 0.13035 L1 loss: 0.0000e+00 L2 loss: 0.95859 Learning rate: 0.02 Mask loss: 0.11856 RPN box loss: 0.0358 RPN score loss: 0.00339 RPN total loss: 0.03919 Total loss: 1.24669 timestamp: 1654934360.3066895 iteration: 24845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08854 FastRCNN class loss: 0.04482 FastRCNN total loss: 0.13336 L1 loss: 0.0000e+00 L2 loss: 0.95846 Learning rate: 0.02 Mask loss: 0.09674 RPN box loss: 0.01649 RPN score loss: 0.00349 RPN total loss: 0.01998 Total loss: 1.20855 timestamp: 1654934363.5166934 iteration: 24850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12411 FastRCNN class loss: 0.10209 FastRCNN total loss: 0.22621 L1 loss: 0.0000e+00 L2 loss: 0.9583 Learning rate: 0.02 Mask loss: 0.13173 RPN box loss: 0.02305 RPN score loss: 0.00569 RPN total loss: 0.02874 Total loss: 1.34497 timestamp: 1654934366.6722078 iteration: 24855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12622 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.20382 L1 loss: 0.0000e+00 L2 loss: 0.95816 Learning rate: 0.02 Mask loss: 0.24655 RPN box loss: 0.02176 RPN score loss: 0.00443 RPN total loss: 0.02619 Total loss: 1.43473 timestamp: 1654934369.8410358 iteration: 24860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13213 FastRCNN class loss: 0.11722 FastRCNN total loss: 0.24935 L1 loss: 0.0000e+00 L2 loss: 0.95801 Learning rate: 0.02 Mask loss: 0.15607 RPN box loss: 0.02908 RPN score loss: 0.00609 RPN total loss: 0.03517 Total loss: 1.3986 timestamp: 1654934373.0608423 iteration: 24865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1835 FastRCNN class loss: 0.08176 FastRCNN total loss: 0.26526 L1 loss: 0.0000e+00 L2 loss: 0.95786 Learning rate: 0.02 Mask loss: 0.1686 RPN box loss: 0.02481 RPN score loss: 0.03168 RPN total loss: 0.05649 Total loss: 1.44822 timestamp: 1654934376.2935693 iteration: 24870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12052 FastRCNN class loss: 0.08408 FastRCNN total loss: 0.2046 L1 loss: 0.0000e+00 L2 loss: 0.95774 Learning rate: 0.02 Mask loss: 0.11633 RPN box loss: 0.01236 RPN score loss: 0.00392 RPN total loss: 0.01628 Total loss: 1.29495 timestamp: 1654934379.5474613 iteration: 24875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17792 FastRCNN class loss: 0.11209 FastRCNN total loss: 0.29001 L1 loss: 0.0000e+00 L2 loss: 0.95758 Learning rate: 0.02 Mask loss: 0.16699 RPN box loss: 0.02248 RPN score loss: 0.01103 RPN total loss: 0.0335 Total loss: 1.44809 timestamp: 1654934382.7633321 iteration: 24880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1572 FastRCNN class loss: 0.14192 FastRCNN total loss: 0.29913 L1 loss: 0.0000e+00 L2 loss: 0.95744 Learning rate: 0.02 Mask loss: 0.23406 RPN box loss: 0.01957 RPN score loss: 0.00941 RPN total loss: 0.02898 Total loss: 1.5196 timestamp: 1654934385.907024 iteration: 24885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18193 FastRCNN class loss: 0.09875 FastRCNN total loss: 0.28069 L1 loss: 0.0000e+00 L2 loss: 0.95729 Learning rate: 0.02 Mask loss: 0.1358 RPN box loss: 0.02997 RPN score loss: 0.00739 RPN total loss: 0.03736 Total loss: 1.41114 timestamp: 1654934389.112358 iteration: 24890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14709 FastRCNN class loss: 0.06728 FastRCNN total loss: 0.21436 L1 loss: 0.0000e+00 L2 loss: 0.95713 Learning rate: 0.02 Mask loss: 0.07946 RPN box loss: 0.00892 RPN score loss: 0.00326 RPN total loss: 0.01219 Total loss: 1.26314 timestamp: 1654934392.3509524 iteration: 24895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13339 FastRCNN class loss: 0.07122 FastRCNN total loss: 0.20461 L1 loss: 0.0000e+00 L2 loss: 0.95698 Learning rate: 0.02 Mask loss: 0.15032 RPN box loss: 0.02007 RPN score loss: 0.00538 RPN total loss: 0.02546 Total loss: 1.33736 timestamp: 1654934395.6109846 iteration: 24900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17134 FastRCNN class loss: 0.07143 FastRCNN total loss: 0.24277 L1 loss: 0.0000e+00 L2 loss: 0.95684 Learning rate: 0.02 Mask loss: 0.14961 RPN box loss: 0.00812 RPN score loss: 0.00879 RPN total loss: 0.01691 Total loss: 1.36613 timestamp: 1654934398.8540654 iteration: 24905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.08451 FastRCNN total loss: 0.1873 L1 loss: 0.0000e+00 L2 loss: 0.95668 Learning rate: 0.02 Mask loss: 0.14765 RPN box loss: 0.05486 RPN score loss: 0.0041 RPN total loss: 0.05897 Total loss: 1.3506 timestamp: 1654934402.088044 iteration: 24910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14533 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.19466 L1 loss: 0.0000e+00 L2 loss: 0.95655 Learning rate: 0.02 Mask loss: 0.11563 RPN box loss: 0.02335 RPN score loss: 0.00179 RPN total loss: 0.02514 Total loss: 1.29198 timestamp: 1654934405.2556696 iteration: 24915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14059 FastRCNN class loss: 0.08716 FastRCNN total loss: 0.22775 L1 loss: 0.0000e+00 L2 loss: 0.95639 Learning rate: 0.02 Mask loss: 0.20776 RPN box loss: 0.05717 RPN score loss: 0.00765 RPN total loss: 0.06482 Total loss: 1.45672 timestamp: 1654934408.575985 iteration: 24920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09172 FastRCNN class loss: 0.03774 FastRCNN total loss: 0.12945 L1 loss: 0.0000e+00 L2 loss: 0.95623 Learning rate: 0.02 Mask loss: 0.12519 RPN box loss: 0.01332 RPN score loss: 0.00218 RPN total loss: 0.0155 Total loss: 1.22638 timestamp: 1654934411.7729445 iteration: 24925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17872 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.23509 L1 loss: 0.0000e+00 L2 loss: 0.95608 Learning rate: 0.02 Mask loss: 0.11318 RPN box loss: 0.0131 RPN score loss: 0.00632 RPN total loss: 0.01941 Total loss: 1.32377 timestamp: 1654934415.060942 iteration: 24930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14788 FastRCNN class loss: 0.10875 FastRCNN total loss: 0.25663 L1 loss: 0.0000e+00 L2 loss: 0.95594 Learning rate: 0.02 Mask loss: 0.16445 RPN box loss: 0.04001 RPN score loss: 0.00993 RPN total loss: 0.04994 Total loss: 1.42696 timestamp: 1654934418.3041615 iteration: 24935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11369 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.17634 L1 loss: 0.0000e+00 L2 loss: 0.95577 Learning rate: 0.02 Mask loss: 0.13551 RPN box loss: 0.07108 RPN score loss: 0.00336 RPN total loss: 0.07445 Total loss: 1.34207 timestamp: 1654934421.4328246 iteration: 24940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1425 FastRCNN class loss: 0.05073 FastRCNN total loss: 0.19323 L1 loss: 0.0000e+00 L2 loss: 0.95564 Learning rate: 0.02 Mask loss: 0.14486 RPN box loss: 0.05109 RPN score loss: 0.00452 RPN total loss: 0.05561 Total loss: 1.34933 timestamp: 1654934424.6195397 iteration: 24945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12531 FastRCNN class loss: 0.10189 FastRCNN total loss: 0.22719 L1 loss: 0.0000e+00 L2 loss: 0.95551 Learning rate: 0.02 Mask loss: 0.16042 RPN box loss: 0.06474 RPN score loss: 0.0098 RPN total loss: 0.07454 Total loss: 1.41766 timestamp: 1654934427.8510463 iteration: 24950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15194 FastRCNN class loss: 0.15905 FastRCNN total loss: 0.311 L1 loss: 0.0000e+00 L2 loss: 0.95535 Learning rate: 0.02 Mask loss: 0.24498 RPN box loss: 0.06539 RPN score loss: 0.02315 RPN total loss: 0.08854 Total loss: 1.59987 timestamp: 1654934431.0838804 iteration: 24955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22992 FastRCNN class loss: 0.07241 FastRCNN total loss: 0.30233 L1 loss: 0.0000e+00 L2 loss: 0.95521 Learning rate: 0.02 Mask loss: 0.1883 RPN box loss: 0.02469 RPN score loss: 0.00161 RPN total loss: 0.0263 Total loss: 1.47213 timestamp: 1654934434.2074327 iteration: 24960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08868 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.17302 L1 loss: 0.0000e+00 L2 loss: 0.95504 Learning rate: 0.02 Mask loss: 0.13306 RPN box loss: 0.01732 RPN score loss: 0.0026 RPN total loss: 0.01991 Total loss: 1.28103 timestamp: 1654934437.400935 iteration: 24965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12899 FastRCNN class loss: 0.0521 FastRCNN total loss: 0.18109 L1 loss: 0.0000e+00 L2 loss: 0.95488 Learning rate: 0.02 Mask loss: 0.19351 RPN box loss: 0.01043 RPN score loss: 0.00386 RPN total loss: 0.01429 Total loss: 1.34377 timestamp: 1654934440.505424 iteration: 24970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13894 FastRCNN class loss: 0.13199 FastRCNN total loss: 0.27093 L1 loss: 0.0000e+00 L2 loss: 0.95472 Learning rate: 0.02 Mask loss: 0.14155 RPN box loss: 0.03817 RPN score loss: 0.00898 RPN total loss: 0.04715 Total loss: 1.41435 timestamp: 1654934443.6957405 iteration: 24975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16784 FastRCNN class loss: 0.08773 FastRCNN total loss: 0.25557 L1 loss: 0.0000e+00 L2 loss: 0.95459 Learning rate: 0.02 Mask loss: 0.20369 RPN box loss: 0.03757 RPN score loss: 0.00799 RPN total loss: 0.04556 Total loss: 1.45941 timestamp: 1654934446.9717455 iteration: 24980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12544 FastRCNN class loss: 0.10843 FastRCNN total loss: 0.23387 L1 loss: 0.0000e+00 L2 loss: 0.95446 Learning rate: 0.02 Mask loss: 0.18566 RPN box loss: 0.0447 RPN score loss: 0.00775 RPN total loss: 0.05245 Total loss: 1.42644 timestamp: 1654934450.1797652 iteration: 24985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11576 FastRCNN class loss: 0.08211 FastRCNN total loss: 0.19788 L1 loss: 0.0000e+00 L2 loss: 0.95427 Learning rate: 0.02 Mask loss: 0.13865 RPN box loss: 0.05071 RPN score loss: 0.00605 RPN total loss: 0.05676 Total loss: 1.34755 timestamp: 1654934453.4005718 iteration: 24990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17502 FastRCNN class loss: 0.11881 FastRCNN total loss: 0.29383 L1 loss: 0.0000e+00 L2 loss: 0.95411 Learning rate: 0.02 Mask loss: 0.14233 RPN box loss: 0.05148 RPN score loss: 0.00573 RPN total loss: 0.05721 Total loss: 1.44748 timestamp: 1654934456.6639178 iteration: 24995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09692 FastRCNN class loss: 0.11792 FastRCNN total loss: 0.21484 L1 loss: 0.0000e+00 L2 loss: 0.95398 Learning rate: 0.02 Mask loss: 0.18637 RPN box loss: 0.01278 RPN score loss: 0.00254 RPN total loss: 0.01532 Total loss: 1.37051 timestamp: 1654934459.861253 iteration: 25000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15724 FastRCNN class loss: 0.10498 FastRCNN total loss: 0.26222 L1 loss: 0.0000e+00 L2 loss: 0.95383 Learning rate: 0.02 Mask loss: 0.1781 RPN box loss: 0.01905 RPN score loss: 0.00688 RPN total loss: 0.02593 Total loss: 1.42008 timestamp: 1654934463.0613828 iteration: 25005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20862 FastRCNN class loss: 0.15277 FastRCNN total loss: 0.36139 L1 loss: 0.0000e+00 L2 loss: 0.95368 Learning rate: 0.02 Mask loss: 0.17173 RPN box loss: 0.03778 RPN score loss: 0.04935 RPN total loss: 0.08713 Total loss: 1.57392 timestamp: 1654934466.2323685 iteration: 25010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12464 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 0.95352 Learning rate: 0.02 Mask loss: 0.14878 RPN box loss: 0.04616 RPN score loss: 0.0035 RPN total loss: 0.04966 Total loss: 1.34883 timestamp: 1654934469.4951615 iteration: 25015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08614 FastRCNN class loss: 0.10672 FastRCNN total loss: 0.19286 L1 loss: 0.0000e+00 L2 loss: 0.95339 Learning rate: 0.02 Mask loss: 0.24013 RPN box loss: 0.0772 RPN score loss: 0.01812 RPN total loss: 0.09532 Total loss: 1.4817 timestamp: 1654934472.7060945 iteration: 25020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07981 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.14423 L1 loss: 0.0000e+00 L2 loss: 0.95325 Learning rate: 0.02 Mask loss: 0.08549 RPN box loss: 0.00535 RPN score loss: 0.0016 RPN total loss: 0.00695 Total loss: 1.18992 timestamp: 1654934475.8927758 iteration: 25025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19859 FastRCNN class loss: 0.13548 FastRCNN total loss: 0.33407 L1 loss: 0.0000e+00 L2 loss: 0.95311 Learning rate: 0.02 Mask loss: 0.24806 RPN box loss: 0.02854 RPN score loss: 0.01363 RPN total loss: 0.04217 Total loss: 1.57741 timestamp: 1654934479.06109 iteration: 25030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10336 FastRCNN class loss: 0.06854 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 0.95297 Learning rate: 0.02 Mask loss: 0.12821 RPN box loss: 0.01113 RPN score loss: 0.00225 RPN total loss: 0.01338 Total loss: 1.26645 timestamp: 1654934482.2335644 iteration: 25035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14465 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.22144 L1 loss: 0.0000e+00 L2 loss: 0.95281 Learning rate: 0.02 Mask loss: 0.15723 RPN box loss: 0.04236 RPN score loss: 0.00616 RPN total loss: 0.04852 Total loss: 1.38 timestamp: 1654934485.4105299 iteration: 25040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1905 FastRCNN class loss: 0.15186 FastRCNN total loss: 0.34236 L1 loss: 0.0000e+00 L2 loss: 0.95265 Learning rate: 0.02 Mask loss: 0.22322 RPN box loss: 0.03255 RPN score loss: 0.01655 RPN total loss: 0.04909 Total loss: 1.56732 timestamp: 1654934488.5927608 iteration: 25045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09788 FastRCNN class loss: 0.06662 FastRCNN total loss: 0.16451 L1 loss: 0.0000e+00 L2 loss: 0.95248 Learning rate: 0.02 Mask loss: 0.08461 RPN box loss: 0.01803 RPN score loss: 0.00794 RPN total loss: 0.02597 Total loss: 1.22756 timestamp: 1654934491.8651567 iteration: 25050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.06679 FastRCNN total loss: 0.15691 L1 loss: 0.0000e+00 L2 loss: 0.95231 Learning rate: 0.02 Mask loss: 0.15052 RPN box loss: 0.0308 RPN score loss: 0.00325 RPN total loss: 0.03404 Total loss: 1.29378 timestamp: 1654934495.091916 iteration: 25055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15711 FastRCNN class loss: 0.07607 FastRCNN total loss: 0.23318 L1 loss: 0.0000e+00 L2 loss: 0.95218 Learning rate: 0.02 Mask loss: 0.12049 RPN box loss: 0.0173 RPN score loss: 0.00262 RPN total loss: 0.01993 Total loss: 1.32578 timestamp: 1654934498.2585697 iteration: 25060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14237 FastRCNN class loss: 0.09536 FastRCNN total loss: 0.23773 L1 loss: 0.0000e+00 L2 loss: 0.95205 Learning rate: 0.02 Mask loss: 0.14968 RPN box loss: 0.02606 RPN score loss: 0.00463 RPN total loss: 0.03069 Total loss: 1.37016 timestamp: 1654934501.5007722 iteration: 25065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14562 FastRCNN class loss: 0.09458 FastRCNN total loss: 0.2402 L1 loss: 0.0000e+00 L2 loss: 0.95191 Learning rate: 0.02 Mask loss: 0.13325 RPN box loss: 0.02709 RPN score loss: 0.01487 RPN total loss: 0.04196 Total loss: 1.36732 timestamp: 1654934504.6692345 iteration: 25070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13565 FastRCNN class loss: 0.08697 FastRCNN total loss: 0.22262 L1 loss: 0.0000e+00 L2 loss: 0.95176 Learning rate: 0.02 Mask loss: 0.1491 RPN box loss: 0.04841 RPN score loss: 0.00671 RPN total loss: 0.05512 Total loss: 1.3786 timestamp: 1654934507.863912 iteration: 25075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10852 FastRCNN class loss: 0.08828 FastRCNN total loss: 0.1968 L1 loss: 0.0000e+00 L2 loss: 0.95163 Learning rate: 0.02 Mask loss: 0.17927 RPN box loss: 0.02425 RPN score loss: 0.00381 RPN total loss: 0.02805 Total loss: 1.35575 timestamp: 1654934511.0477881 iteration: 25080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11295 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.18452 L1 loss: 0.0000e+00 L2 loss: 0.95149 Learning rate: 0.02 Mask loss: 0.10893 RPN box loss: 0.02479 RPN score loss: 0.00715 RPN total loss: 0.03194 Total loss: 1.27688 timestamp: 1654934514.2455606 iteration: 25085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09727 FastRCNN class loss: 0.11185 FastRCNN total loss: 0.20912 L1 loss: 0.0000e+00 L2 loss: 0.95134 Learning rate: 0.02 Mask loss: 0.12782 RPN box loss: 0.01813 RPN score loss: 0.00505 RPN total loss: 0.02318 Total loss: 1.31146 timestamp: 1654934517.4497604 iteration: 25090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1259 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.1941 L1 loss: 0.0000e+00 L2 loss: 0.95119 Learning rate: 0.02 Mask loss: 0.19283 RPN box loss: 0.01179 RPN score loss: 0.00247 RPN total loss: 0.01426 Total loss: 1.35238 timestamp: 1654934520.648588 iteration: 25095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12132 FastRCNN class loss: 0.0802 FastRCNN total loss: 0.20151 L1 loss: 0.0000e+00 L2 loss: 0.95104 Learning rate: 0.02 Mask loss: 0.13571 RPN box loss: 0.02606 RPN score loss: 0.01172 RPN total loss: 0.03778 Total loss: 1.32605 timestamp: 1654934523.8212428 iteration: 25100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15835 FastRCNN class loss: 0.06839 FastRCNN total loss: 0.22674 L1 loss: 0.0000e+00 L2 loss: 0.95089 Learning rate: 0.02 Mask loss: 0.09229 RPN box loss: 0.02493 RPN score loss: 0.00827 RPN total loss: 0.03319 Total loss: 1.30311 timestamp: 1654934527.098974 iteration: 25105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15546 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.21075 L1 loss: 0.0000e+00 L2 loss: 0.95075 Learning rate: 0.02 Mask loss: 0.1069 RPN box loss: 0.00909 RPN score loss: 0.00155 RPN total loss: 0.01065 Total loss: 1.27905 timestamp: 1654934530.284205 iteration: 25110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12893 FastRCNN class loss: 0.07611 FastRCNN total loss: 0.20504 L1 loss: 0.0000e+00 L2 loss: 0.95061 Learning rate: 0.02 Mask loss: 0.16648 RPN box loss: 0.0346 RPN score loss: 0.00312 RPN total loss: 0.03772 Total loss: 1.35985 timestamp: 1654934533.5109844 iteration: 25115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16992 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.26338 L1 loss: 0.0000e+00 L2 loss: 0.95046 Learning rate: 0.02 Mask loss: 0.15082 RPN box loss: 0.03271 RPN score loss: 0.00595 RPN total loss: 0.03866 Total loss: 1.40332 timestamp: 1654934536.6728384 iteration: 25120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1714 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.2322 L1 loss: 0.0000e+00 L2 loss: 0.95031 Learning rate: 0.02 Mask loss: 0.17589 RPN box loss: 0.01666 RPN score loss: 0.00633 RPN total loss: 0.02299 Total loss: 1.38139 timestamp: 1654934539.804364 iteration: 25125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06362 FastRCNN class loss: 0.05748 FastRCNN total loss: 0.12111 L1 loss: 0.0000e+00 L2 loss: 0.95018 Learning rate: 0.02 Mask loss: 0.12249 RPN box loss: 0.00402 RPN score loss: 0.00445 RPN total loss: 0.00847 Total loss: 1.20225 timestamp: 1654934543.0467057 iteration: 25130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09977 FastRCNN class loss: 0.08927 FastRCNN total loss: 0.18904 L1 loss: 0.0000e+00 L2 loss: 0.95 Learning rate: 0.02 Mask loss: 0.12555 RPN box loss: 0.01692 RPN score loss: 0.0065 RPN total loss: 0.02342 Total loss: 1.288 timestamp: 1654934546.3121557 iteration: 25135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07948 FastRCNN class loss: 0.0954 FastRCNN total loss: 0.17488 L1 loss: 0.0000e+00 L2 loss: 0.94985 Learning rate: 0.02 Mask loss: 0.16155 RPN box loss: 0.05108 RPN score loss: 0.00348 RPN total loss: 0.05456 Total loss: 1.34085 timestamp: 1654934549.4955819 iteration: 25140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12072 FastRCNN class loss: 0.0631 FastRCNN total loss: 0.18382 L1 loss: 0.0000e+00 L2 loss: 0.94971 Learning rate: 0.02 Mask loss: 0.10431 RPN box loss: 0.00894 RPN score loss: 0.00343 RPN total loss: 0.01237 Total loss: 1.25021 timestamp: 1654934552.6885557 iteration: 25145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1234 FastRCNN class loss: 0.08257 FastRCNN total loss: 0.20597 L1 loss: 0.0000e+00 L2 loss: 0.94957 Learning rate: 0.02 Mask loss: 0.13 RPN box loss: 0.03632 RPN score loss: 0.00494 RPN total loss: 0.04126 Total loss: 1.3268 timestamp: 1654934555.879822 iteration: 25150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16154 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.24315 L1 loss: 0.0000e+00 L2 loss: 0.94942 Learning rate: 0.02 Mask loss: 0.18811 RPN box loss: 0.01566 RPN score loss: 0.00457 RPN total loss: 0.02023 Total loss: 1.40091 timestamp: 1654934559.0457735 iteration: 25155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12982 FastRCNN class loss: 0.07789 FastRCNN total loss: 0.20771 L1 loss: 0.0000e+00 L2 loss: 0.94928 Learning rate: 0.02 Mask loss: 0.09494 RPN box loss: 0.01778 RPN score loss: 0.0068 RPN total loss: 0.02458 Total loss: 1.27651 timestamp: 1654934562.2564394 iteration: 25160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13475 FastRCNN class loss: 0.09191 FastRCNN total loss: 0.22666 L1 loss: 0.0000e+00 L2 loss: 0.94914 Learning rate: 0.02 Mask loss: 0.11017 RPN box loss: 0.04554 RPN score loss: 0.00585 RPN total loss: 0.05138 Total loss: 1.33735 timestamp: 1654934565.4849095 iteration: 25165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08943 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.16496 L1 loss: 0.0000e+00 L2 loss: 0.949 Learning rate: 0.02 Mask loss: 0.13064 RPN box loss: 0.01849 RPN score loss: 0.00509 RPN total loss: 0.02358 Total loss: 1.26817 timestamp: 1654934568.6906354 iteration: 25170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1452 FastRCNN class loss: 0.13672 FastRCNN total loss: 0.28192 L1 loss: 0.0000e+00 L2 loss: 0.94888 Learning rate: 0.02 Mask loss: 0.24464 RPN box loss: 0.0235 RPN score loss: 0.00742 RPN total loss: 0.03092 Total loss: 1.50636 timestamp: 1654934571.9296894 iteration: 25175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16163 FastRCNN class loss: 0.09114 FastRCNN total loss: 0.25276 L1 loss: 0.0000e+00 L2 loss: 0.94872 Learning rate: 0.02 Mask loss: 0.11756 RPN box loss: 0.03731 RPN score loss: 0.00848 RPN total loss: 0.04579 Total loss: 1.36483 timestamp: 1654934575.2157953 iteration: 25180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19154 FastRCNN class loss: 0.1222 FastRCNN total loss: 0.31374 L1 loss: 0.0000e+00 L2 loss: 0.94858 Learning rate: 0.02 Mask loss: 0.19815 RPN box loss: 0.02457 RPN score loss: 0.00924 RPN total loss: 0.03381 Total loss: 1.49427 timestamp: 1654934578.536219 iteration: 25185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11936 FastRCNN class loss: 0.06203 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.94845 Learning rate: 0.02 Mask loss: 0.14772 RPN box loss: 0.01268 RPN score loss: 0.00304 RPN total loss: 0.01572 Total loss: 1.29328 timestamp: 1654934581.737845 iteration: 25190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14142 FastRCNN class loss: 0.08826 FastRCNN total loss: 0.22968 L1 loss: 0.0000e+00 L2 loss: 0.9483 Learning rate: 0.02 Mask loss: 0.23763 RPN box loss: 0.01415 RPN score loss: 0.00315 RPN total loss: 0.0173 Total loss: 1.4329 timestamp: 1654934584.8875442 iteration: 25195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1612 FastRCNN class loss: 0.08936 FastRCNN total loss: 0.25056 L1 loss: 0.0000e+00 L2 loss: 0.94816 Learning rate: 0.02 Mask loss: 0.13757 RPN box loss: 0.08445 RPN score loss: 0.0035 RPN total loss: 0.08795 Total loss: 1.42424 timestamp: 1654934588.1014555 iteration: 25200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20195 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.28009 L1 loss: 0.0000e+00 L2 loss: 0.948 Learning rate: 0.02 Mask loss: 0.18894 RPN box loss: 0.02992 RPN score loss: 0.00796 RPN total loss: 0.03787 Total loss: 1.4549 timestamp: 1654934591.2686057 iteration: 25205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08612 FastRCNN class loss: 0.08643 FastRCNN total loss: 0.17255 L1 loss: 0.0000e+00 L2 loss: 0.94784 Learning rate: 0.02 Mask loss: 0.17431 RPN box loss: 0.00745 RPN score loss: 0.0044 RPN total loss: 0.01184 Total loss: 1.30654 timestamp: 1654934594.564933 iteration: 25210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20353 FastRCNN class loss: 0.09513 FastRCNN total loss: 0.29866 L1 loss: 0.0000e+00 L2 loss: 0.94769 Learning rate: 0.02 Mask loss: 0.15703 RPN box loss: 0.04373 RPN score loss: 0.00623 RPN total loss: 0.04997 Total loss: 1.45335 timestamp: 1654934597.6848438 iteration: 25215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21984 FastRCNN class loss: 0.11547 FastRCNN total loss: 0.33531 L1 loss: 0.0000e+00 L2 loss: 0.94755 Learning rate: 0.02 Mask loss: 0.2006 RPN box loss: 0.04539 RPN score loss: 0.01457 RPN total loss: 0.05996 Total loss: 1.54342 timestamp: 1654934600.9161258 iteration: 25220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18061 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.27289 L1 loss: 0.0000e+00 L2 loss: 0.94742 Learning rate: 0.02 Mask loss: 0.11931 RPN box loss: 0.02644 RPN score loss: 0.01713 RPN total loss: 0.04357 Total loss: 1.38319 timestamp: 1654934604.0386467 iteration: 25225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21748 FastRCNN class loss: 0.11988 FastRCNN total loss: 0.33736 L1 loss: 0.0000e+00 L2 loss: 0.94726 Learning rate: 0.02 Mask loss: 0.21493 RPN box loss: 0.03852 RPN score loss: 0.02184 RPN total loss: 0.06037 Total loss: 1.55992 timestamp: 1654934607.2259877 iteration: 25230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09244 FastRCNN class loss: 0.07754 FastRCNN total loss: 0.16998 L1 loss: 0.0000e+00 L2 loss: 0.94711 Learning rate: 0.02 Mask loss: 0.20093 RPN box loss: 0.02094 RPN score loss: 0.01405 RPN total loss: 0.03499 Total loss: 1.35301 timestamp: 1654934610.487527 iteration: 25235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1253 FastRCNN class loss: 0.09968 FastRCNN total loss: 0.22498 L1 loss: 0.0000e+00 L2 loss: 0.94695 Learning rate: 0.02 Mask loss: 0.12419 RPN box loss: 0.04647 RPN score loss: 0.01196 RPN total loss: 0.05843 Total loss: 1.35455 timestamp: 1654934613.7037966 iteration: 25240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.15501 L1 loss: 0.0000e+00 L2 loss: 0.94677 Learning rate: 0.02 Mask loss: 0.11197 RPN box loss: 0.05079 RPN score loss: 0.01028 RPN total loss: 0.06107 Total loss: 1.27483 timestamp: 1654934616.8685555 iteration: 25245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08484 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.14622 L1 loss: 0.0000e+00 L2 loss: 0.94664 Learning rate: 0.02 Mask loss: 0.12554 RPN box loss: 0.04266 RPN score loss: 0.00474 RPN total loss: 0.04739 Total loss: 1.2658 timestamp: 1654934620.0468535 iteration: 25250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10247 FastRCNN class loss: 0.07369 FastRCNN total loss: 0.17616 L1 loss: 0.0000e+00 L2 loss: 0.94649 Learning rate: 0.02 Mask loss: 0.1768 RPN box loss: 0.04817 RPN score loss: 0.00713 RPN total loss: 0.0553 Total loss: 1.35475 timestamp: 1654934623.1789742 iteration: 25255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21169 FastRCNN class loss: 0.08456 FastRCNN total loss: 0.29625 L1 loss: 0.0000e+00 L2 loss: 0.94633 Learning rate: 0.02 Mask loss: 0.15431 RPN box loss: 0.00793 RPN score loss: 0.00794 RPN total loss: 0.01587 Total loss: 1.41275 timestamp: 1654934626.3856537 iteration: 25260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0997 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.17863 L1 loss: 0.0000e+00 L2 loss: 0.94619 Learning rate: 0.02 Mask loss: 0.16012 RPN box loss: 0.0265 RPN score loss: 0.00316 RPN total loss: 0.02965 Total loss: 1.31459 timestamp: 1654934629.5402288 iteration: 25265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10364 FastRCNN class loss: 0.05518 FastRCNN total loss: 0.15882 L1 loss: 0.0000e+00 L2 loss: 0.94603 Learning rate: 0.02 Mask loss: 0.10118 RPN box loss: 0.01334 RPN score loss: 0.00293 RPN total loss: 0.01627 Total loss: 1.2223 timestamp: 1654934632.7222474 iteration: 25270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07036 FastRCNN class loss: 0.05832 FastRCNN total loss: 0.12868 L1 loss: 0.0000e+00 L2 loss: 0.94587 Learning rate: 0.02 Mask loss: 0.1959 RPN box loss: 0.02982 RPN score loss: 0.00335 RPN total loss: 0.03317 Total loss: 1.30362 timestamp: 1654934635.871049 iteration: 25275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16981 FastRCNN class loss: 0.07753 FastRCNN total loss: 0.24734 L1 loss: 0.0000e+00 L2 loss: 0.94573 Learning rate: 0.02 Mask loss: 0.1548 RPN box loss: 0.06027 RPN score loss: 0.00981 RPN total loss: 0.07008 Total loss: 1.41796 timestamp: 1654934639.0944977 iteration: 25280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14234 FastRCNN class loss: 0.12776 FastRCNN total loss: 0.2701 L1 loss: 0.0000e+00 L2 loss: 0.94561 Learning rate: 0.02 Mask loss: 0.10994 RPN box loss: 0.03596 RPN score loss: 0.0102 RPN total loss: 0.04616 Total loss: 1.3718 timestamp: 1654934642.3052828 iteration: 25285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19666 FastRCNN class loss: 0.05756 FastRCNN total loss: 0.25422 L1 loss: 0.0000e+00 L2 loss: 0.94546 Learning rate: 0.02 Mask loss: 0.125 RPN box loss: 0.03046 RPN score loss: 0.0024 RPN total loss: 0.03286 Total loss: 1.35754 timestamp: 1654934645.517861 iteration: 25290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18206 FastRCNN class loss: 0.06873 FastRCNN total loss: 0.25079 L1 loss: 0.0000e+00 L2 loss: 0.94527 Learning rate: 0.02 Mask loss: 0.09655 RPN box loss: 0.01687 RPN score loss: 0.0055 RPN total loss: 0.02238 Total loss: 1.31499 timestamp: 1654934648.7334604 iteration: 25295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13588 FastRCNN class loss: 0.09218 FastRCNN total loss: 0.22806 L1 loss: 0.0000e+00 L2 loss: 0.94513 Learning rate: 0.02 Mask loss: 0.16004 RPN box loss: 0.06434 RPN score loss: 0.00248 RPN total loss: 0.06682 Total loss: 1.40004 timestamp: 1654934651.8851762 iteration: 25300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09829 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.15118 L1 loss: 0.0000e+00 L2 loss: 0.945 Learning rate: 0.02 Mask loss: 0.17138 RPN box loss: 0.02316 RPN score loss: 0.00561 RPN total loss: 0.02877 Total loss: 1.29633 timestamp: 1654934655.0750766 iteration: 25305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15022 FastRCNN class loss: 0.09344 FastRCNN total loss: 0.24366 L1 loss: 0.0000e+00 L2 loss: 0.94486 Learning rate: 0.02 Mask loss: 0.25439 RPN box loss: 0.04547 RPN score loss: 0.00998 RPN total loss: 0.05545 Total loss: 1.49836 timestamp: 1654934658.2124538 iteration: 25310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06763 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.12215 L1 loss: 0.0000e+00 L2 loss: 0.94473 Learning rate: 0.02 Mask loss: 0.11423 RPN box loss: 0.00394 RPN score loss: 0.00136 RPN total loss: 0.0053 Total loss: 1.18641 timestamp: 1654934661.4893117 iteration: 25315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12155 FastRCNN class loss: 0.07409 FastRCNN total loss: 0.19564 L1 loss: 0.0000e+00 L2 loss: 0.94459 Learning rate: 0.02 Mask loss: 0.23373 RPN box loss: 0.03489 RPN score loss: 0.00217 RPN total loss: 0.03706 Total loss: 1.41102 timestamp: 1654934664.682874 iteration: 25320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13143 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.21354 L1 loss: 0.0000e+00 L2 loss: 0.94446 Learning rate: 0.02 Mask loss: 0.18852 RPN box loss: 0.04304 RPN score loss: 0.00251 RPN total loss: 0.04555 Total loss: 1.39207 timestamp: 1654934667.9024618 iteration: 25325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1304 FastRCNN class loss: 0.07993 FastRCNN total loss: 0.21033 L1 loss: 0.0000e+00 L2 loss: 0.9443 Learning rate: 0.02 Mask loss: 0.14223 RPN box loss: 0.02829 RPN score loss: 0.00829 RPN total loss: 0.03659 Total loss: 1.33345 timestamp: 1654934671.1533196 iteration: 25330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23384 FastRCNN class loss: 0.12188 FastRCNN total loss: 0.35572 L1 loss: 0.0000e+00 L2 loss: 0.94414 Learning rate: 0.02 Mask loss: 0.19715 RPN box loss: 0.02423 RPN score loss: 0.01031 RPN total loss: 0.03454 Total loss: 1.53155 timestamp: 1654934674.3851738 iteration: 25335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.19783 L1 loss: 0.0000e+00 L2 loss: 0.944 Learning rate: 0.02 Mask loss: 0.13941 RPN box loss: 0.02595 RPN score loss: 0.00754 RPN total loss: 0.03349 Total loss: 1.31473 timestamp: 1654934677.642553 iteration: 25340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13457 FastRCNN class loss: 0.08111 FastRCNN total loss: 0.21567 L1 loss: 0.0000e+00 L2 loss: 0.94386 Learning rate: 0.02 Mask loss: 0.11107 RPN box loss: 0.05443 RPN score loss: 0.00575 RPN total loss: 0.06018 Total loss: 1.33078 timestamp: 1654934680.8383458 iteration: 25345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10392 FastRCNN class loss: 0.05347 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.94372 Learning rate: 0.02 Mask loss: 0.15511 RPN box loss: 0.04764 RPN score loss: 0.0061 RPN total loss: 0.05374 Total loss: 1.30997 timestamp: 1654934684.0139759 iteration: 25350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11724 FastRCNN class loss: 0.08059 FastRCNN total loss: 0.19783 L1 loss: 0.0000e+00 L2 loss: 0.94356 Learning rate: 0.02 Mask loss: 0.13675 RPN box loss: 0.02853 RPN score loss: 0.00845 RPN total loss: 0.03697 Total loss: 1.31511 timestamp: 1654934687.234554 iteration: 25355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14549 FastRCNN class loss: 0.10968 FastRCNN total loss: 0.25517 L1 loss: 0.0000e+00 L2 loss: 0.9434 Learning rate: 0.02 Mask loss: 0.16236 RPN box loss: 0.04119 RPN score loss: 0.02126 RPN total loss: 0.06245 Total loss: 1.42338 timestamp: 1654934690.447972 iteration: 25360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14546 FastRCNN class loss: 0.05952 FastRCNN total loss: 0.20498 L1 loss: 0.0000e+00 L2 loss: 0.94327 Learning rate: 0.02 Mask loss: 0.17559 RPN box loss: 0.04991 RPN score loss: 0.00475 RPN total loss: 0.05466 Total loss: 1.3785 timestamp: 1654934693.641583 iteration: 25365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08439 FastRCNN class loss: 0.04056 FastRCNN total loss: 0.12495 L1 loss: 0.0000e+00 L2 loss: 0.94314 Learning rate: 0.02 Mask loss: 0.18987 RPN box loss: 0.00663 RPN score loss: 0.0073 RPN total loss: 0.01393 Total loss: 1.27189 timestamp: 1654934696.8554223 iteration: 25370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13852 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.20614 L1 loss: 0.0000e+00 L2 loss: 0.94299 Learning rate: 0.02 Mask loss: 0.14538 RPN box loss: 0.02516 RPN score loss: 0.00869 RPN total loss: 0.03384 Total loss: 1.32836 timestamp: 1654934700.0139725 iteration: 25375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18173 FastRCNN class loss: 0.09935 FastRCNN total loss: 0.28107 L1 loss: 0.0000e+00 L2 loss: 0.94283 Learning rate: 0.02 Mask loss: 0.22118 RPN box loss: 0.0423 RPN score loss: 0.00881 RPN total loss: 0.05111 Total loss: 1.4962 timestamp: 1654934703.2051709 iteration: 25380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23267 FastRCNN class loss: 0.09516 FastRCNN total loss: 0.32783 L1 loss: 0.0000e+00 L2 loss: 0.94268 Learning rate: 0.02 Mask loss: 0.17547 RPN box loss: 0.02346 RPN score loss: 0.00306 RPN total loss: 0.02652 Total loss: 1.4725 timestamp: 1654934706.4065452 iteration: 25385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1219 FastRCNN class loss: 0.07267 FastRCNN total loss: 0.19458 L1 loss: 0.0000e+00 L2 loss: 0.94256 Learning rate: 0.02 Mask loss: 0.13173 RPN box loss: 0.0267 RPN score loss: 0.00748 RPN total loss: 0.03418 Total loss: 1.30304 timestamp: 1654934709.6270928 iteration: 25390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1192 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 0.94241 Learning rate: 0.02 Mask loss: 0.1487 RPN box loss: 0.05397 RPN score loss: 0.01352 RPN total loss: 0.06749 Total loss: 1.37361 timestamp: 1654934712.929643 iteration: 25395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07245 FastRCNN class loss: 0.05455 FastRCNN total loss: 0.12699 L1 loss: 0.0000e+00 L2 loss: 0.94227 Learning rate: 0.02 Mask loss: 0.11834 RPN box loss: 0.03133 RPN score loss: 0.00436 RPN total loss: 0.03569 Total loss: 1.22329 timestamp: 1654934716.1676347 iteration: 25400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14431 FastRCNN class loss: 0.05965 FastRCNN total loss: 0.20397 L1 loss: 0.0000e+00 L2 loss: 0.94214 Learning rate: 0.02 Mask loss: 0.15025 RPN box loss: 0.01303 RPN score loss: 0.00144 RPN total loss: 0.01447 Total loss: 1.31082 timestamp: 1654934719.3898954 iteration: 25405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1044 FastRCNN class loss: 0.10544 FastRCNN total loss: 0.20984 L1 loss: 0.0000e+00 L2 loss: 0.942 Learning rate: 0.02 Mask loss: 0.10772 RPN box loss: 0.02203 RPN score loss: 0.00293 RPN total loss: 0.02496 Total loss: 1.28452 timestamp: 1654934722.660131 iteration: 25410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10742 FastRCNN class loss: 0.0488 FastRCNN total loss: 0.15622 L1 loss: 0.0000e+00 L2 loss: 0.94187 Learning rate: 0.02 Mask loss: 0.13471 RPN box loss: 0.01097 RPN score loss: 0.0039 RPN total loss: 0.01486 Total loss: 1.24766 timestamp: 1654934725.7909014 iteration: 25415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11981 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.1796 L1 loss: 0.0000e+00 L2 loss: 0.94174 Learning rate: 0.02 Mask loss: 0.18419 RPN box loss: 0.09414 RPN score loss: 0.0047 RPN total loss: 0.09883 Total loss: 1.40436 timestamp: 1654934728.899576 iteration: 25420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10386 FastRCNN class loss: 0.04134 FastRCNN total loss: 0.14521 L1 loss: 0.0000e+00 L2 loss: 0.94158 Learning rate: 0.02 Mask loss: 0.09967 RPN box loss: 0.02409 RPN score loss: 0.00684 RPN total loss: 0.03093 Total loss: 1.21738 timestamp: 1654934732.0630844 iteration: 25425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08592 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.15787 L1 loss: 0.0000e+00 L2 loss: 0.9414 Learning rate: 0.02 Mask loss: 0.17154 RPN box loss: 0.03535 RPN score loss: 0.02489 RPN total loss: 0.06024 Total loss: 1.33106 timestamp: 1654934735.3048756 iteration: 25430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08244 FastRCNN class loss: 0.05036 FastRCNN total loss: 0.1328 L1 loss: 0.0000e+00 L2 loss: 0.94127 Learning rate: 0.02 Mask loss: 0.13103 RPN box loss: 0.01806 RPN score loss: 0.0041 RPN total loss: 0.02216 Total loss: 1.22725 timestamp: 1654934738.5440605 iteration: 25435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10729 FastRCNN class loss: 0.07162 FastRCNN total loss: 0.17891 L1 loss: 0.0000e+00 L2 loss: 0.94111 Learning rate: 0.02 Mask loss: 0.1062 RPN box loss: 0.02693 RPN score loss: 0.00732 RPN total loss: 0.03424 Total loss: 1.26047 timestamp: 1654934741.7570934 iteration: 25440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13266 FastRCNN class loss: 0.1044 FastRCNN total loss: 0.23706 L1 loss: 0.0000e+00 L2 loss: 0.94098 Learning rate: 0.02 Mask loss: 0.20032 RPN box loss: 0.04386 RPN score loss: 0.01666 RPN total loss: 0.06052 Total loss: 1.43888 timestamp: 1654934745.0318878 iteration: 25445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08448 FastRCNN class loss: 0.05486 FastRCNN total loss: 0.13934 L1 loss: 0.0000e+00 L2 loss: 0.94087 Learning rate: 0.02 Mask loss: 0.14334 RPN box loss: 0.02499 RPN score loss: 0.00392 RPN total loss: 0.02891 Total loss: 1.25247 timestamp: 1654934748.180202 iteration: 25450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14843 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.20859 L1 loss: 0.0000e+00 L2 loss: 0.94073 Learning rate: 0.02 Mask loss: 0.14454 RPN box loss: 0.00314 RPN score loss: 0.00515 RPN total loss: 0.00829 Total loss: 1.30215 timestamp: 1654934751.4273403 iteration: 25455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14001 FastRCNN class loss: 0.072 FastRCNN total loss: 0.21201 L1 loss: 0.0000e+00 L2 loss: 0.94058 Learning rate: 0.02 Mask loss: 0.1489 RPN box loss: 0.04443 RPN score loss: 0.0237 RPN total loss: 0.06813 Total loss: 1.36963 timestamp: 1654934754.703884 iteration: 25460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18931 FastRCNN class loss: 0.0837 FastRCNN total loss: 0.27301 L1 loss: 0.0000e+00 L2 loss: 0.94044 Learning rate: 0.02 Mask loss: 0.10411 RPN box loss: 0.03359 RPN score loss: 0.00484 RPN total loss: 0.03844 Total loss: 1.35599 timestamp: 1654934757.8482134 iteration: 25465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14052 FastRCNN class loss: 0.10672 FastRCNN total loss: 0.24724 L1 loss: 0.0000e+00 L2 loss: 0.94029 Learning rate: 0.02 Mask loss: 0.18433 RPN box loss: 0.04033 RPN score loss: 0.00653 RPN total loss: 0.04686 Total loss: 1.41872 timestamp: 1654934761.0205781 iteration: 25470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1642 FastRCNN class loss: 0.07952 FastRCNN total loss: 0.24371 L1 loss: 0.0000e+00 L2 loss: 0.94014 Learning rate: 0.02 Mask loss: 0.15472 RPN box loss: 0.04303 RPN score loss: 0.00864 RPN total loss: 0.05167 Total loss: 1.39025 timestamp: 1654934764.2559192 iteration: 25475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14823 FastRCNN class loss: 0.05799 FastRCNN total loss: 0.20622 L1 loss: 0.0000e+00 L2 loss: 0.93998 Learning rate: 0.02 Mask loss: 0.13269 RPN box loss: 0.02438 RPN score loss: 0.00854 RPN total loss: 0.03293 Total loss: 1.31181 timestamp: 1654934767.4707286 iteration: 25480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.13678 L1 loss: 0.0000e+00 L2 loss: 0.93983 Learning rate: 0.02 Mask loss: 0.12243 RPN box loss: 0.02883 RPN score loss: 0.00141 RPN total loss: 0.03024 Total loss: 1.22927 timestamp: 1654934770.6861413 iteration: 25485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1496 FastRCNN class loss: 0.1085 FastRCNN total loss: 0.2581 L1 loss: 0.0000e+00 L2 loss: 0.93967 Learning rate: 0.02 Mask loss: 0.28282 RPN box loss: 0.01263 RPN score loss: 0.00487 RPN total loss: 0.0175 Total loss: 1.4981 timestamp: 1654934773.8777516 iteration: 25490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20565 FastRCNN class loss: 0.14661 FastRCNN total loss: 0.35226 L1 loss: 0.0000e+00 L2 loss: 0.93954 Learning rate: 0.02 Mask loss: 0.17357 RPN box loss: 0.03599 RPN score loss: 0.00634 RPN total loss: 0.04232 Total loss: 1.50769 timestamp: 1654934777.0574887 iteration: 25495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15028 FastRCNN class loss: 0.12092 FastRCNN total loss: 0.2712 L1 loss: 0.0000e+00 L2 loss: 0.93938 Learning rate: 0.02 Mask loss: 0.1565 RPN box loss: 0.08473 RPN score loss: 0.01178 RPN total loss: 0.09651 Total loss: 1.46359 timestamp: 1654934780.2887118 iteration: 25500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09411 FastRCNN class loss: 0.03411 FastRCNN total loss: 0.12822 L1 loss: 0.0000e+00 L2 loss: 0.93926 Learning rate: 0.02 Mask loss: 0.11392 RPN box loss: 0.00686 RPN score loss: 0.00135 RPN total loss: 0.0082 Total loss: 1.18959 timestamp: 1654934783.4714906 iteration: 25505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12341 FastRCNN class loss: 0.07334 FastRCNN total loss: 0.19675 L1 loss: 0.0000e+00 L2 loss: 0.93909 Learning rate: 0.02 Mask loss: 0.16918 RPN box loss: 0.01105 RPN score loss: 0.00248 RPN total loss: 0.01353 Total loss: 1.31855 timestamp: 1654934786.6383226 iteration: 25510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16824 FastRCNN class loss: 0.12257 FastRCNN total loss: 0.29081 L1 loss: 0.0000e+00 L2 loss: 0.93893 Learning rate: 0.02 Mask loss: 0.21269 RPN box loss: 0.02762 RPN score loss: 0.01023 RPN total loss: 0.03785 Total loss: 1.48027 timestamp: 1654934789.855611 iteration: 25515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1104 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.22203 L1 loss: 0.0000e+00 L2 loss: 0.93878 Learning rate: 0.02 Mask loss: 0.20355 RPN box loss: 0.04135 RPN score loss: 0.01186 RPN total loss: 0.05321 Total loss: 1.41757 timestamp: 1654934793.1385362 iteration: 25520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16928 FastRCNN class loss: 0.08656 FastRCNN total loss: 0.25583 L1 loss: 0.0000e+00 L2 loss: 0.93866 Learning rate: 0.02 Mask loss: 0.17104 RPN box loss: 0.03672 RPN score loss: 0.01984 RPN total loss: 0.05656 Total loss: 1.42209 timestamp: 1654934796.324892 iteration: 25525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1377 FastRCNN class loss: 0.08698 FastRCNN total loss: 0.22469 L1 loss: 0.0000e+00 L2 loss: 0.93852 Learning rate: 0.02 Mask loss: 0.12529 RPN box loss: 0.01584 RPN score loss: 0.00316 RPN total loss: 0.019 Total loss: 1.3075 timestamp: 1654934799.5524528 iteration: 25530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17876 FastRCNN class loss: 0.08184 FastRCNN total loss: 0.2606 L1 loss: 0.0000e+00 L2 loss: 0.93838 Learning rate: 0.02 Mask loss: 0.23147 RPN box loss: 0.02395 RPN score loss: 0.00417 RPN total loss: 0.02812 Total loss: 1.45858 timestamp: 1654934802.7660391 iteration: 25535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12307 FastRCNN class loss: 0.11366 FastRCNN total loss: 0.23673 L1 loss: 0.0000e+00 L2 loss: 0.93825 Learning rate: 0.02 Mask loss: 0.17572 RPN box loss: 0.05647 RPN score loss: 0.01726 RPN total loss: 0.07373 Total loss: 1.42443 timestamp: 1654934806.0009403 iteration: 25540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19744 FastRCNN class loss: 0.12989 FastRCNN total loss: 0.32732 L1 loss: 0.0000e+00 L2 loss: 0.93811 Learning rate: 0.02 Mask loss: 0.16308 RPN box loss: 0.06156 RPN score loss: 0.01176 RPN total loss: 0.07333 Total loss: 1.50184 timestamp: 1654934809.2628062 iteration: 25545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20507 FastRCNN class loss: 0.13593 FastRCNN total loss: 0.341 L1 loss: 0.0000e+00 L2 loss: 0.93797 Learning rate: 0.02 Mask loss: 0.2258 RPN box loss: 0.03941 RPN score loss: 0.00907 RPN total loss: 0.04849 Total loss: 1.55325 timestamp: 1654934812.4665449 iteration: 25550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16746 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.24533 L1 loss: 0.0000e+00 L2 loss: 0.93782 Learning rate: 0.02 Mask loss: 0.09122 RPN box loss: 0.04061 RPN score loss: 0.00183 RPN total loss: 0.04243 Total loss: 1.31681 timestamp: 1654934815.6299865 iteration: 25555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19286 FastRCNN class loss: 0.15088 FastRCNN total loss: 0.34374 L1 loss: 0.0000e+00 L2 loss: 0.93767 Learning rate: 0.02 Mask loss: 0.28762 RPN box loss: 0.07715 RPN score loss: 0.01711 RPN total loss: 0.09427 Total loss: 1.6633 timestamp: 1654934818.8397834 iteration: 25560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10183 FastRCNN class loss: 0.0375 FastRCNN total loss: 0.13933 L1 loss: 0.0000e+00 L2 loss: 0.93754 Learning rate: 0.02 Mask loss: 0.12969 RPN box loss: 0.03215 RPN score loss: 0.00536 RPN total loss: 0.03751 Total loss: 1.24408 timestamp: 1654934822.0324688 iteration: 25565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17021 FastRCNN class loss: 0.10256 FastRCNN total loss: 0.27277 L1 loss: 0.0000e+00 L2 loss: 0.9374 Learning rate: 0.02 Mask loss: 0.17509 RPN box loss: 0.03927 RPN score loss: 0.00593 RPN total loss: 0.0452 Total loss: 1.43047 timestamp: 1654934825.2481973 iteration: 25570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12445 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.19811 L1 loss: 0.0000e+00 L2 loss: 0.93726 Learning rate: 0.02 Mask loss: 0.18709 RPN box loss: 0.03779 RPN score loss: 0.01525 RPN total loss: 0.05304 Total loss: 1.37549 timestamp: 1654934828.425966 iteration: 25575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17663 FastRCNN class loss: 0.12066 FastRCNN total loss: 0.29728 L1 loss: 0.0000e+00 L2 loss: 0.9371 Learning rate: 0.02 Mask loss: 0.1291 RPN box loss: 0.02325 RPN score loss: 0.0091 RPN total loss: 0.03235 Total loss: 1.39584 timestamp: 1654934831.6130216 iteration: 25580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08863 FastRCNN class loss: 0.11593 FastRCNN total loss: 0.20456 L1 loss: 0.0000e+00 L2 loss: 0.93694 Learning rate: 0.02 Mask loss: 0.11596 RPN box loss: 0.06069 RPN score loss: 0.00671 RPN total loss: 0.0674 Total loss: 1.32485 timestamp: 1654934834.7875786 iteration: 25585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1259 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.1885 L1 loss: 0.0000e+00 L2 loss: 0.93679 Learning rate: 0.02 Mask loss: 0.10376 RPN box loss: 0.02098 RPN score loss: 0.00396 RPN total loss: 0.02493 Total loss: 1.25398 timestamp: 1654934837.98942 iteration: 25590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15334 FastRCNN class loss: 0.08735 FastRCNN total loss: 0.24069 L1 loss: 0.0000e+00 L2 loss: 0.93666 Learning rate: 0.02 Mask loss: 0.14489 RPN box loss: 0.05597 RPN score loss: 0.0139 RPN total loss: 0.06987 Total loss: 1.39211 timestamp: 1654934841.2593517 iteration: 25595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.1784 L1 loss: 0.0000e+00 L2 loss: 0.93651 Learning rate: 0.02 Mask loss: 0.14259 RPN box loss: 0.06084 RPN score loss: 0.01178 RPN total loss: 0.07262 Total loss: 1.33012 timestamp: 1654934844.4696946 iteration: 25600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17561 FastRCNN class loss: 0.13792 FastRCNN total loss: 0.31353 L1 loss: 0.0000e+00 L2 loss: 0.93636 Learning rate: 0.02 Mask loss: 0.18741 RPN box loss: 0.0214 RPN score loss: 0.0129 RPN total loss: 0.0343 Total loss: 1.4716 timestamp: 1654934847.7240183 iteration: 25605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08647 FastRCNN class loss: 0.04215 FastRCNN total loss: 0.12862 L1 loss: 0.0000e+00 L2 loss: 0.93624 Learning rate: 0.02 Mask loss: 0.10827 RPN box loss: 0.00552 RPN score loss: 0.00291 RPN total loss: 0.00843 Total loss: 1.18156 timestamp: 1654934850.9157393 iteration: 25610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10992 FastRCNN class loss: 0.08876 FastRCNN total loss: 0.19868 L1 loss: 0.0000e+00 L2 loss: 0.93608 Learning rate: 0.02 Mask loss: 0.16253 RPN box loss: 0.03315 RPN score loss: 0.00572 RPN total loss: 0.03887 Total loss: 1.33616 timestamp: 1654934854.1016607 iteration: 25615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15993 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.2281 L1 loss: 0.0000e+00 L2 loss: 0.93591 Learning rate: 0.02 Mask loss: 0.22751 RPN box loss: 0.02525 RPN score loss: 0.0095 RPN total loss: 0.03475 Total loss: 1.42627 timestamp: 1654934857.2531202 iteration: 25620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15673 FastRCNN class loss: 0.08084 FastRCNN total loss: 0.23757 L1 loss: 0.0000e+00 L2 loss: 0.93579 Learning rate: 0.02 Mask loss: 0.16551 RPN box loss: 0.06509 RPN score loss: 0.00609 RPN total loss: 0.07117 Total loss: 1.41004 timestamp: 1654934860.4359446 iteration: 25625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16045 FastRCNN class loss: 0.09237 FastRCNN total loss: 0.25282 L1 loss: 0.0000e+00 L2 loss: 0.93565 Learning rate: 0.02 Mask loss: 0.15495 RPN box loss: 0.02992 RPN score loss: 0.00319 RPN total loss: 0.03311 Total loss: 1.37653 timestamp: 1654934863.666322 iteration: 25630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14655 FastRCNN class loss: 0.12882 FastRCNN total loss: 0.27537 L1 loss: 0.0000e+00 L2 loss: 0.9355 Learning rate: 0.02 Mask loss: 0.1375 RPN box loss: 0.01689 RPN score loss: 0.00667 RPN total loss: 0.02356 Total loss: 1.37194 timestamp: 1654934866.9179842 iteration: 25635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26678 FastRCNN class loss: 0.08436 FastRCNN total loss: 0.35113 L1 loss: 0.0000e+00 L2 loss: 0.93538 Learning rate: 0.02 Mask loss: 0.20254 RPN box loss: 0.02096 RPN score loss: 0.00472 RPN total loss: 0.02567 Total loss: 1.51472 timestamp: 1654934870.1453953 iteration: 25640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08926 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.16271 L1 loss: 0.0000e+00 L2 loss: 0.93524 Learning rate: 0.02 Mask loss: 0.11355 RPN box loss: 0.00769 RPN score loss: 0.00368 RPN total loss: 0.01138 Total loss: 1.22288 timestamp: 1654934873.317559 iteration: 25645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09339 FastRCNN class loss: 0.04384 FastRCNN total loss: 0.13723 L1 loss: 0.0000e+00 L2 loss: 0.9351 Learning rate: 0.02 Mask loss: 0.12853 RPN box loss: 0.01544 RPN score loss: 0.00189 RPN total loss: 0.01733 Total loss: 1.21819 timestamp: 1654934876.5377345 iteration: 25650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0916 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.15872 L1 loss: 0.0000e+00 L2 loss: 0.93496 Learning rate: 0.02 Mask loss: 0.16902 RPN box loss: 0.04285 RPN score loss: 0.00315 RPN total loss: 0.046 Total loss: 1.3087 timestamp: 1654934879.7529616 iteration: 25655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17255 FastRCNN class loss: 0.11571 FastRCNN total loss: 0.28826 L1 loss: 0.0000e+00 L2 loss: 0.93482 Learning rate: 0.02 Mask loss: 0.20051 RPN box loss: 0.01968 RPN score loss: 0.00464 RPN total loss: 0.02432 Total loss: 1.44791 timestamp: 1654934882.895807 iteration: 25660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13934 FastRCNN class loss: 0.09125 FastRCNN total loss: 0.23059 L1 loss: 0.0000e+00 L2 loss: 0.93469 Learning rate: 0.02 Mask loss: 0.12551 RPN box loss: 0.05939 RPN score loss: 0.00724 RPN total loss: 0.06662 Total loss: 1.35741 timestamp: 1654934886.0958266 iteration: 25665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18397 FastRCNN class loss: 0.09589 FastRCNN total loss: 0.27985 L1 loss: 0.0000e+00 L2 loss: 0.93453 Learning rate: 0.02 Mask loss: 0.1566 RPN box loss: 0.05605 RPN score loss: 0.01765 RPN total loss: 0.0737 Total loss: 1.44467 timestamp: 1654934889.2977479 iteration: 25670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11829 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.17176 L1 loss: 0.0000e+00 L2 loss: 0.93437 Learning rate: 0.02 Mask loss: 0.09845 RPN box loss: 0.04036 RPN score loss: 0.00144 RPN total loss: 0.0418 Total loss: 1.24638 timestamp: 1654934892.4687586 iteration: 25675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.06 FastRCNN total loss: 0.13917 L1 loss: 0.0000e+00 L2 loss: 0.93424 Learning rate: 0.02 Mask loss: 0.14904 RPN box loss: 0.00951 RPN score loss: 0.00569 RPN total loss: 0.0152 Total loss: 1.23765 timestamp: 1654934895.807063 iteration: 25680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16333 FastRCNN class loss: 0.11742 FastRCNN total loss: 0.28075 L1 loss: 0.0000e+00 L2 loss: 0.93408 Learning rate: 0.02 Mask loss: 0.20108 RPN box loss: 0.03436 RPN score loss: 0.01132 RPN total loss: 0.04568 Total loss: 1.46159 timestamp: 1654934898.9770517 iteration: 25685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18599 FastRCNN class loss: 0.10393 FastRCNN total loss: 0.28993 L1 loss: 0.0000e+00 L2 loss: 0.93392 Learning rate: 0.02 Mask loss: 0.16402 RPN box loss: 0.02216 RPN score loss: 0.00566 RPN total loss: 0.02782 Total loss: 1.41568 timestamp: 1654934902.169891 iteration: 25690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14446 FastRCNN class loss: 0.1083 FastRCNN total loss: 0.25277 L1 loss: 0.0000e+00 L2 loss: 0.93381 Learning rate: 0.02 Mask loss: 0.14338 RPN box loss: 0.03619 RPN score loss: 0.00924 RPN total loss: 0.04543 Total loss: 1.37538 timestamp: 1654934905.2966707 iteration: 25695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11801 FastRCNN class loss: 0.06624 FastRCNN total loss: 0.18425 L1 loss: 0.0000e+00 L2 loss: 0.93364 Learning rate: 0.02 Mask loss: 0.11211 RPN box loss: 0.05585 RPN score loss: 0.00944 RPN total loss: 0.06529 Total loss: 1.29529 timestamp: 1654934908.5450597 iteration: 25700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19198 FastRCNN class loss: 0.09666 FastRCNN total loss: 0.28864 L1 loss: 0.0000e+00 L2 loss: 0.93351 Learning rate: 0.02 Mask loss: 0.23552 RPN box loss: 0.01062 RPN score loss: 0.00821 RPN total loss: 0.01883 Total loss: 1.47649 timestamp: 1654934911.767044 iteration: 25705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07063 FastRCNN class loss: 0.0562 FastRCNN total loss: 0.12683 L1 loss: 0.0000e+00 L2 loss: 0.93338 Learning rate: 0.02 Mask loss: 0.20197 RPN box loss: 0.0081 RPN score loss: 0.0036 RPN total loss: 0.0117 Total loss: 1.27389 timestamp: 1654934914.9828305 iteration: 25710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15759 FastRCNN class loss: 0.08384 FastRCNN total loss: 0.24143 L1 loss: 0.0000e+00 L2 loss: 0.93322 Learning rate: 0.02 Mask loss: 0.27364 RPN box loss: 0.03817 RPN score loss: 0.01115 RPN total loss: 0.04931 Total loss: 1.49761 timestamp: 1654934918.1809168 iteration: 25715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10592 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.16537 L1 loss: 0.0000e+00 L2 loss: 0.93308 Learning rate: 0.02 Mask loss: 0.15949 RPN box loss: 0.03509 RPN score loss: 0.00595 RPN total loss: 0.04104 Total loss: 1.29898 timestamp: 1654934921.4083476 iteration: 25720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13484 FastRCNN class loss: 0.04598 FastRCNN total loss: 0.18082 L1 loss: 0.0000e+00 L2 loss: 0.93299 Learning rate: 0.02 Mask loss: 0.12029 RPN box loss: 0.01351 RPN score loss: 0.00247 RPN total loss: 0.01598 Total loss: 1.25008 timestamp: 1654934924.5671449 iteration: 25725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11412 FastRCNN class loss: 0.0502 FastRCNN total loss: 0.16432 L1 loss: 0.0000e+00 L2 loss: 0.93289 Learning rate: 0.02 Mask loss: 0.12442 RPN box loss: 0.03514 RPN score loss: 0.00539 RPN total loss: 0.04054 Total loss: 1.26217 timestamp: 1654934927.8184059 iteration: 25730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14414 FastRCNN class loss: 0.11881 FastRCNN total loss: 0.26294 L1 loss: 0.0000e+00 L2 loss: 0.93276 Learning rate: 0.02 Mask loss: 0.13846 RPN box loss: 0.02746 RPN score loss: 0.00445 RPN total loss: 0.0319 Total loss: 1.36607 timestamp: 1654934930.9594545 iteration: 25735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06248 FastRCNN class loss: 0.03382 FastRCNN total loss: 0.09631 L1 loss: 0.0000e+00 L2 loss: 0.93261 Learning rate: 0.02 Mask loss: 0.13755 RPN box loss: 0.07059 RPN score loss: 0.00313 RPN total loss: 0.07372 Total loss: 1.24019 timestamp: 1654934934.1419888 iteration: 25740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1448 FastRCNN class loss: 0.09675 FastRCNN total loss: 0.24155 L1 loss: 0.0000e+00 L2 loss: 0.93245 Learning rate: 0.02 Mask loss: 0.17599 RPN box loss: 0.06635 RPN score loss: 0.02279 RPN total loss: 0.08914 Total loss: 1.43913 timestamp: 1654934937.4210591 iteration: 25745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15892 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.22161 L1 loss: 0.0000e+00 L2 loss: 0.93229 Learning rate: 0.02 Mask loss: 0.25087 RPN box loss: 0.02187 RPN score loss: 0.0069 RPN total loss: 0.02877 Total loss: 1.43354 timestamp: 1654934940.5641086 iteration: 25750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14185 FastRCNN class loss: 0.09691 FastRCNN total loss: 0.23876 L1 loss: 0.0000e+00 L2 loss: 0.93214 Learning rate: 0.02 Mask loss: 0.15887 RPN box loss: 0.02219 RPN score loss: 0.00492 RPN total loss: 0.0271 Total loss: 1.35688 timestamp: 1654934943.816599 iteration: 25755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09001 FastRCNN class loss: 0.08648 FastRCNN total loss: 0.17649 L1 loss: 0.0000e+00 L2 loss: 0.932 Learning rate: 0.02 Mask loss: 0.1175 RPN box loss: 0.02505 RPN score loss: 0.00554 RPN total loss: 0.0306 Total loss: 1.25658 timestamp: 1654934946.9914746 iteration: 25760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10121 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.17758 L1 loss: 0.0000e+00 L2 loss: 0.93188 Learning rate: 0.02 Mask loss: 0.16216 RPN box loss: 0.03569 RPN score loss: 0.00561 RPN total loss: 0.0413 Total loss: 1.31292 timestamp: 1654934950.1313565 iteration: 25765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12691 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.21411 L1 loss: 0.0000e+00 L2 loss: 0.93172 Learning rate: 0.02 Mask loss: 0.21049 RPN box loss: 0.02881 RPN score loss: 0.00492 RPN total loss: 0.03373 Total loss: 1.39004 timestamp: 1654934953.282117 iteration: 25770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11477 FastRCNN class loss: 0.10311 FastRCNN total loss: 0.21788 L1 loss: 0.0000e+00 L2 loss: 0.93158 Learning rate: 0.02 Mask loss: 0.19828 RPN box loss: 0.06809 RPN score loss: 0.00867 RPN total loss: 0.07676 Total loss: 1.4245 timestamp: 1654934956.521925 iteration: 25775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09427 FastRCNN class loss: 0.06151 FastRCNN total loss: 0.15578 L1 loss: 0.0000e+00 L2 loss: 0.93144 Learning rate: 0.02 Mask loss: 0.15395 RPN box loss: 0.02224 RPN score loss: 0.01096 RPN total loss: 0.0332 Total loss: 1.27437 timestamp: 1654934959.70107 iteration: 25780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08786 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.17239 L1 loss: 0.0000e+00 L2 loss: 0.93128 Learning rate: 0.02 Mask loss: 0.13295 RPN box loss: 0.02968 RPN score loss: 0.00522 RPN total loss: 0.0349 Total loss: 1.27151 timestamp: 1654934962.9023962 iteration: 25785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11345 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.18395 L1 loss: 0.0000e+00 L2 loss: 0.93114 Learning rate: 0.02 Mask loss: 0.15671 RPN box loss: 0.0116 RPN score loss: 0.00551 RPN total loss: 0.01711 Total loss: 1.28892 timestamp: 1654934966.0873218 iteration: 25790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14513 FastRCNN class loss: 0.06449 FastRCNN total loss: 0.20961 L1 loss: 0.0000e+00 L2 loss: 0.93099 Learning rate: 0.02 Mask loss: 0.14237 RPN box loss: 0.0239 RPN score loss: 0.01038 RPN total loss: 0.03428 Total loss: 1.31726 timestamp: 1654934969.272011 iteration: 25795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09108 FastRCNN class loss: 0.04679 FastRCNN total loss: 0.13787 L1 loss: 0.0000e+00 L2 loss: 0.93083 Learning rate: 0.02 Mask loss: 0.15346 RPN box loss: 0.02707 RPN score loss: 0.01177 RPN total loss: 0.03885 Total loss: 1.26101 timestamp: 1654934972.4635847 iteration: 25800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25844 FastRCNN class loss: 0.13645 FastRCNN total loss: 0.39488 L1 loss: 0.0000e+00 L2 loss: 0.93066 Learning rate: 0.02 Mask loss: 0.27566 RPN box loss: 0.02997 RPN score loss: 0.00879 RPN total loss: 0.03875 Total loss: 1.63996 timestamp: 1654934975.713557 iteration: 25805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0974 FastRCNN class loss: 0.09495 FastRCNN total loss: 0.19235 L1 loss: 0.0000e+00 L2 loss: 0.93054 Learning rate: 0.02 Mask loss: 0.14032 RPN box loss: 0.07878 RPN score loss: 0.00653 RPN total loss: 0.08531 Total loss: 1.34852 timestamp: 1654934978.902134 iteration: 25810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1721 FastRCNN class loss: 0.10935 FastRCNN total loss: 0.28145 L1 loss: 0.0000e+00 L2 loss: 0.93042 Learning rate: 0.02 Mask loss: 0.19988 RPN box loss: 0.06348 RPN score loss: 0.01038 RPN total loss: 0.07385 Total loss: 1.4856 timestamp: 1654934982.1255527 iteration: 25815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11426 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.18897 L1 loss: 0.0000e+00 L2 loss: 0.93029 Learning rate: 0.02 Mask loss: 0.2164 RPN box loss: 0.03404 RPN score loss: 0.01502 RPN total loss: 0.04906 Total loss: 1.38471 timestamp: 1654934985.3045652 iteration: 25820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1552 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.24782 L1 loss: 0.0000e+00 L2 loss: 0.93016 Learning rate: 0.02 Mask loss: 0.13852 RPN box loss: 0.0098 RPN score loss: 0.00371 RPN total loss: 0.01351 Total loss: 1.33001 timestamp: 1654934988.4589562 iteration: 25825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07209 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.11841 L1 loss: 0.0000e+00 L2 loss: 0.93002 Learning rate: 0.02 Mask loss: 0.13568 RPN box loss: 0.04293 RPN score loss: 0.00302 RPN total loss: 0.04595 Total loss: 1.23007 timestamp: 1654934991.7615414 iteration: 25830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16833 FastRCNN class loss: 0.08882 FastRCNN total loss: 0.25715 L1 loss: 0.0000e+00 L2 loss: 0.92989 Learning rate: 0.02 Mask loss: 0.18619 RPN box loss: 0.05382 RPN score loss: 0.00717 RPN total loss: 0.06099 Total loss: 1.43422 timestamp: 1654934994.9810936 iteration: 25835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.06704 FastRCNN total loss: 0.18386 L1 loss: 0.0000e+00 L2 loss: 0.92976 Learning rate: 0.02 Mask loss: 0.13382 RPN box loss: 0.02456 RPN score loss: 0.00153 RPN total loss: 0.02608 Total loss: 1.27353 timestamp: 1654934998.165104 iteration: 25840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12757 FastRCNN class loss: 0.06868 FastRCNN total loss: 0.19625 L1 loss: 0.0000e+00 L2 loss: 0.92962 Learning rate: 0.02 Mask loss: 0.2797 RPN box loss: 0.0675 RPN score loss: 0.01309 RPN total loss: 0.08059 Total loss: 1.48616 timestamp: 1654935001.3881335 iteration: 25845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10964 FastRCNN class loss: 0.07066 FastRCNN total loss: 0.1803 L1 loss: 0.0000e+00 L2 loss: 0.92947 Learning rate: 0.02 Mask loss: 0.13342 RPN box loss: 0.03687 RPN score loss: 0.00723 RPN total loss: 0.04411 Total loss: 1.28729 timestamp: 1654935004.642458 iteration: 25850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15663 FastRCNN class loss: 0.15364 FastRCNN total loss: 0.31028 L1 loss: 0.0000e+00 L2 loss: 0.92936 Learning rate: 0.02 Mask loss: 0.22175 RPN box loss: 0.06331 RPN score loss: 0.01331 RPN total loss: 0.07663 Total loss: 1.53801 timestamp: 1654935007.8299506 iteration: 25855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15616 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.24079 L1 loss: 0.0000e+00 L2 loss: 0.9292 Learning rate: 0.02 Mask loss: 0.20545 RPN box loss: 0.03324 RPN score loss: 0.01347 RPN total loss: 0.0467 Total loss: 1.42214 timestamp: 1654935011.0798812 iteration: 25860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11825 FastRCNN class loss: 0.05468 FastRCNN total loss: 0.17293 L1 loss: 0.0000e+00 L2 loss: 0.92904 Learning rate: 0.02 Mask loss: 0.10986 RPN box loss: 0.01129 RPN score loss: 0.00229 RPN total loss: 0.01358 Total loss: 1.2254 timestamp: 1654935014.264465 iteration: 25865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.05716 FastRCNN total loss: 0.15197 L1 loss: 0.0000e+00 L2 loss: 0.92892 Learning rate: 0.02 Mask loss: 0.10946 RPN box loss: 0.01869 RPN score loss: 0.00571 RPN total loss: 0.0244 Total loss: 1.21476 timestamp: 1654935017.3707607 iteration: 25870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11115 FastRCNN class loss: 0.12246 FastRCNN total loss: 0.23361 L1 loss: 0.0000e+00 L2 loss: 0.9288 Learning rate: 0.02 Mask loss: 0.10162 RPN box loss: 0.01154 RPN score loss: 0.00346 RPN total loss: 0.015 Total loss: 1.27904 timestamp: 1654935020.529377 iteration: 25875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06929 FastRCNN class loss: 0.05012 FastRCNN total loss: 0.11941 L1 loss: 0.0000e+00 L2 loss: 0.92864 Learning rate: 0.02 Mask loss: 0.17861 RPN box loss: 0.02043 RPN score loss: 0.01059 RPN total loss: 0.03101 Total loss: 1.25767 timestamp: 1654935023.6819315 iteration: 25880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15191 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.21583 L1 loss: 0.0000e+00 L2 loss: 0.92849 Learning rate: 0.02 Mask loss: 0.11442 RPN box loss: 0.03265 RPN score loss: 0.00439 RPN total loss: 0.03704 Total loss: 1.29578 timestamp: 1654935026.865383 iteration: 25885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.171 FastRCNN class loss: 0.1246 FastRCNN total loss: 0.2956 L1 loss: 0.0000e+00 L2 loss: 0.92834 Learning rate: 0.02 Mask loss: 0.22074 RPN box loss: 0.01232 RPN score loss: 0.01587 RPN total loss: 0.02819 Total loss: 1.47288 timestamp: 1654935030.014282 iteration: 25890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.12651 FastRCNN total loss: 0.25791 L1 loss: 0.0000e+00 L2 loss: 0.92819 Learning rate: 0.02 Mask loss: 0.12571 RPN box loss: 0.03917 RPN score loss: 0.01061 RPN total loss: 0.04978 Total loss: 1.3616 timestamp: 1654935033.2486734 iteration: 25895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18529 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.26799 L1 loss: 0.0000e+00 L2 loss: 0.92807 Learning rate: 0.02 Mask loss: 0.12988 RPN box loss: 0.01933 RPN score loss: 0.00542 RPN total loss: 0.02475 Total loss: 1.3507 timestamp: 1654935036.458769 iteration: 25900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15262 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.22772 L1 loss: 0.0000e+00 L2 loss: 0.92792 Learning rate: 0.02 Mask loss: 0.13554 RPN box loss: 0.01422 RPN score loss: 0.00405 RPN total loss: 0.01827 Total loss: 1.30945 timestamp: 1654935039.7356215 iteration: 25905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13487 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.20308 L1 loss: 0.0000e+00 L2 loss: 0.92778 Learning rate: 0.02 Mask loss: 0.2031 RPN box loss: 0.04645 RPN score loss: 0.00818 RPN total loss: 0.05463 Total loss: 1.38859 timestamp: 1654935042.9514425 iteration: 25910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22553 FastRCNN class loss: 0.1253 FastRCNN total loss: 0.35082 L1 loss: 0.0000e+00 L2 loss: 0.92763 Learning rate: 0.02 Mask loss: 0.12197 RPN box loss: 0.01243 RPN score loss: 0.00976 RPN total loss: 0.0222 Total loss: 1.42262 timestamp: 1654935046.1942484 iteration: 25915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12375 FastRCNN class loss: 0.09128 FastRCNN total loss: 0.21503 L1 loss: 0.0000e+00 L2 loss: 0.92749 Learning rate: 0.02 Mask loss: 0.18183 RPN box loss: 0.02117 RPN score loss: 0.00835 RPN total loss: 0.02952 Total loss: 1.35387 timestamp: 1654935049.4319007 iteration: 25920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13269 FastRCNN class loss: 0.09405 FastRCNN total loss: 0.22674 L1 loss: 0.0000e+00 L2 loss: 0.92736 Learning rate: 0.02 Mask loss: 0.15904 RPN box loss: 0.04408 RPN score loss: 0.00705 RPN total loss: 0.05113 Total loss: 1.36427 timestamp: 1654935052.586671 iteration: 25925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13042 FastRCNN class loss: 0.11121 FastRCNN total loss: 0.24163 L1 loss: 0.0000e+00 L2 loss: 0.92723 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.05327 RPN score loss: 0.01228 RPN total loss: 0.06555 Total loss: 1.36651 timestamp: 1654935055.7582035 iteration: 25930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12807 FastRCNN class loss: 0.06844 FastRCNN total loss: 0.1965 L1 loss: 0.0000e+00 L2 loss: 0.92709 Learning rate: 0.02 Mask loss: 0.19254 RPN box loss: 0.06251 RPN score loss: 0.00623 RPN total loss: 0.06874 Total loss: 1.38487 timestamp: 1654935058.92345 iteration: 25935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17612 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.24731 L1 loss: 0.0000e+00 L2 loss: 0.92694 Learning rate: 0.02 Mask loss: 0.15516 RPN box loss: 0.02337 RPN score loss: 0.00723 RPN total loss: 0.0306 Total loss: 1.36002 timestamp: 1654935062.1195238 iteration: 25940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09213 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.17084 L1 loss: 0.0000e+00 L2 loss: 0.9268 Learning rate: 0.02 Mask loss: 0.17096 RPN box loss: 0.05144 RPN score loss: 0.01493 RPN total loss: 0.06637 Total loss: 1.33497 timestamp: 1654935065.3045723 iteration: 25945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20214 FastRCNN class loss: 0.12292 FastRCNN total loss: 0.32506 L1 loss: 0.0000e+00 L2 loss: 0.92664 Learning rate: 0.02 Mask loss: 0.20709 RPN box loss: 0.04392 RPN score loss: 0.01891 RPN total loss: 0.06283 Total loss: 1.52162 timestamp: 1654935068.5064907 iteration: 25950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12589 FastRCNN class loss: 0.06003 FastRCNN total loss: 0.18592 L1 loss: 0.0000e+00 L2 loss: 0.92651 Learning rate: 0.02 Mask loss: 0.12494 RPN box loss: 0.02319 RPN score loss: 0.00583 RPN total loss: 0.02902 Total loss: 1.2664 timestamp: 1654935071.7469718 iteration: 25955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16968 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.27003 L1 loss: 0.0000e+00 L2 loss: 0.9264 Learning rate: 0.02 Mask loss: 0.14991 RPN box loss: 0.02796 RPN score loss: 0.00376 RPN total loss: 0.03172 Total loss: 1.37806 timestamp: 1654935074.92775 iteration: 25960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18725 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.27591 L1 loss: 0.0000e+00 L2 loss: 0.92626 Learning rate: 0.02 Mask loss: 0.12086 RPN box loss: 0.01277 RPN score loss: 0.00956 RPN total loss: 0.02233 Total loss: 1.34537 timestamp: 1654935078.1377738 iteration: 25965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19202 FastRCNN class loss: 0.1079 FastRCNN total loss: 0.29992 L1 loss: 0.0000e+00 L2 loss: 0.92612 Learning rate: 0.02 Mask loss: 0.18379 RPN box loss: 0.03527 RPN score loss: 0.0155 RPN total loss: 0.05077 Total loss: 1.4606 timestamp: 1654935081.4038408 iteration: 25970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13163 FastRCNN class loss: 0.05142 FastRCNN total loss: 0.18305 L1 loss: 0.0000e+00 L2 loss: 0.92599 Learning rate: 0.02 Mask loss: 0.14557 RPN box loss: 0.01076 RPN score loss: 0.00589 RPN total loss: 0.01665 Total loss: 1.27126 timestamp: 1654935084.624254 iteration: 25975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15012 FastRCNN class loss: 0.11528 FastRCNN total loss: 0.26539 L1 loss: 0.0000e+00 L2 loss: 0.92584 Learning rate: 0.02 Mask loss: 0.23272 RPN box loss: 0.05367 RPN score loss: 0.01245 RPN total loss: 0.06612 Total loss: 1.49008 timestamp: 1654935087.7866347 iteration: 25980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09948 FastRCNN class loss: 0.05864 FastRCNN total loss: 0.15813 L1 loss: 0.0000e+00 L2 loss: 0.9257 Learning rate: 0.02 Mask loss: 0.17367 RPN box loss: 0.04595 RPN score loss: 0.00532 RPN total loss: 0.05127 Total loss: 1.30877 timestamp: 1654935091.0377061 iteration: 25985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13689 FastRCNN class loss: 0.06601 FastRCNN total loss: 0.2029 L1 loss: 0.0000e+00 L2 loss: 0.92557 Learning rate: 0.02 Mask loss: 0.23436 RPN box loss: 0.02833 RPN score loss: 0.00114 RPN total loss: 0.02947 Total loss: 1.3923 timestamp: 1654935094.2373586 iteration: 25990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20164 FastRCNN class loss: 0.10091 FastRCNN total loss: 0.30254 L1 loss: 0.0000e+00 L2 loss: 0.92542 Learning rate: 0.02 Mask loss: 0.14344 RPN box loss: 0.02607 RPN score loss: 0.00609 RPN total loss: 0.03216 Total loss: 1.40357 timestamp: 1654935097.4664764 iteration: 25995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07491 FastRCNN class loss: 0.02706 FastRCNN total loss: 0.10196 L1 loss: 0.0000e+00 L2 loss: 0.92528 Learning rate: 0.02 Mask loss: 0.12239 RPN box loss: 0.00128 RPN score loss: 0.00359 RPN total loss: 0.00487 Total loss: 1.15451 timestamp: 1654935100.6941938 iteration: 26000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.04916 FastRCNN total loss: 0.13318 L1 loss: 0.0000e+00 L2 loss: 0.92514 Learning rate: 0.02 Mask loss: 0.16426 RPN box loss: 0.02463 RPN score loss: 0.00308 RPN total loss: 0.02771 Total loss: 1.25029 timestamp: 1654935103.9366305 iteration: 26005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11827 FastRCNN class loss: 0.06719 FastRCNN total loss: 0.18546 L1 loss: 0.0000e+00 L2 loss: 0.925 Learning rate: 0.02 Mask loss: 0.09471 RPN box loss: 0.02517 RPN score loss: 0.00369 RPN total loss: 0.02886 Total loss: 1.23403 timestamp: 1654935107.0929325 iteration: 26010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14977 FastRCNN class loss: 0.19235 FastRCNN total loss: 0.34212 L1 loss: 0.0000e+00 L2 loss: 0.92486 Learning rate: 0.02 Mask loss: 0.17523 RPN box loss: 0.03253 RPN score loss: 0.00421 RPN total loss: 0.03675 Total loss: 1.47896 timestamp: 1654935110.2595809 iteration: 26015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16167 FastRCNN class loss: 0.11157 FastRCNN total loss: 0.27324 L1 loss: 0.0000e+00 L2 loss: 0.92473 Learning rate: 0.02 Mask loss: 0.15158 RPN box loss: 0.02879 RPN score loss: 0.01071 RPN total loss: 0.0395 Total loss: 1.38905 timestamp: 1654935113.560069 iteration: 26020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14015 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.21125 L1 loss: 0.0000e+00 L2 loss: 0.9246 Learning rate: 0.02 Mask loss: 0.13387 RPN box loss: 0.02274 RPN score loss: 0.00349 RPN total loss: 0.02623 Total loss: 1.29594 timestamp: 1654935116.7717755 iteration: 26025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22344 FastRCNN class loss: 0.05306 FastRCNN total loss: 0.27651 L1 loss: 0.0000e+00 L2 loss: 0.92444 Learning rate: 0.02 Mask loss: 0.12809 RPN box loss: 0.04398 RPN score loss: 0.00222 RPN total loss: 0.0462 Total loss: 1.37524 timestamp: 1654935120.0859044 iteration: 26030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07634 FastRCNN class loss: 0.05759 FastRCNN total loss: 0.13393 L1 loss: 0.0000e+00 L2 loss: 0.92428 Learning rate: 0.02 Mask loss: 0.27558 RPN box loss: 0.04349 RPN score loss: 0.00426 RPN total loss: 0.04776 Total loss: 1.38155 timestamp: 1654935123.2530286 iteration: 26035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09595 FastRCNN class loss: 0.11008 FastRCNN total loss: 0.20603 L1 loss: 0.0000e+00 L2 loss: 0.92413 Learning rate: 0.02 Mask loss: 0.13421 RPN box loss: 0.03231 RPN score loss: 0.01375 RPN total loss: 0.04606 Total loss: 1.31043 timestamp: 1654935126.448467 iteration: 26040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10447 FastRCNN class loss: 0.09523 FastRCNN total loss: 0.1997 L1 loss: 0.0000e+00 L2 loss: 0.92397 Learning rate: 0.02 Mask loss: 0.15628 RPN box loss: 0.0106 RPN score loss: 0.00591 RPN total loss: 0.0165 Total loss: 1.29645 timestamp: 1654935129.6381805 iteration: 26045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14908 FastRCNN class loss: 0.09364 FastRCNN total loss: 0.24272 L1 loss: 0.0000e+00 L2 loss: 0.92382 Learning rate: 0.02 Mask loss: 0.2593 RPN box loss: 0.03123 RPN score loss: 0.00757 RPN total loss: 0.0388 Total loss: 1.46464 timestamp: 1654935132.878356 iteration: 26050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08808 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.14615 L1 loss: 0.0000e+00 L2 loss: 0.92368 Learning rate: 0.02 Mask loss: 0.17012 RPN box loss: 0.05411 RPN score loss: 0.0064 RPN total loss: 0.06051 Total loss: 1.30046 timestamp: 1654935136.0713742 iteration: 26055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.04741 FastRCNN total loss: 0.15377 L1 loss: 0.0000e+00 L2 loss: 0.92355 Learning rate: 0.02 Mask loss: 0.11944 RPN box loss: 0.05418 RPN score loss: 0.00675 RPN total loss: 0.06094 Total loss: 1.2577 timestamp: 1654935139.267438 iteration: 26060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14106 FastRCNN class loss: 0.07746 FastRCNN total loss: 0.21851 L1 loss: 0.0000e+00 L2 loss: 0.92342 Learning rate: 0.02 Mask loss: 0.13966 RPN box loss: 0.05339 RPN score loss: 0.01401 RPN total loss: 0.06739 Total loss: 1.34898 timestamp: 1654935142.4572654 iteration: 26065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0949 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.1517 L1 loss: 0.0000e+00 L2 loss: 0.92328 Learning rate: 0.02 Mask loss: 0.11013 RPN box loss: 0.026 RPN score loss: 0.0034 RPN total loss: 0.0294 Total loss: 1.2145 timestamp: 1654935145.6472502 iteration: 26070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20498 FastRCNN class loss: 0.12343 FastRCNN total loss: 0.32841 L1 loss: 0.0000e+00 L2 loss: 0.92314 Learning rate: 0.02 Mask loss: 0.17914 RPN box loss: 0.04742 RPN score loss: 0.00726 RPN total loss: 0.05468 Total loss: 1.48537 timestamp: 1654935148.8704557 iteration: 26075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15371 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.23515 L1 loss: 0.0000e+00 L2 loss: 0.92299 Learning rate: 0.02 Mask loss: 0.18632 RPN box loss: 0.01776 RPN score loss: 0.0101 RPN total loss: 0.02786 Total loss: 1.37231 timestamp: 1654935152.023934 iteration: 26080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10848 FastRCNN class loss: 0.05472 FastRCNN total loss: 0.1632 L1 loss: 0.0000e+00 L2 loss: 0.92286 Learning rate: 0.02 Mask loss: 0.11062 RPN box loss: 0.01114 RPN score loss: 0.00256 RPN total loss: 0.0137 Total loss: 1.21038 timestamp: 1654935155.229521 iteration: 26085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07071 FastRCNN class loss: 0.04129 FastRCNN total loss: 0.112 L1 loss: 0.0000e+00 L2 loss: 0.9227 Learning rate: 0.02 Mask loss: 0.13661 RPN box loss: 0.0249 RPN score loss: 0.00439 RPN total loss: 0.02929 Total loss: 1.2006 timestamp: 1654935158.4001844 iteration: 26090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15391 FastRCNN class loss: 0.066 FastRCNN total loss: 0.21991 L1 loss: 0.0000e+00 L2 loss: 0.92256 Learning rate: 0.02 Mask loss: 0.14253 RPN box loss: 0.03218 RPN score loss: 0.00281 RPN total loss: 0.03499 Total loss: 1.31999 timestamp: 1654935161.5636928 iteration: 26095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14262 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.22233 L1 loss: 0.0000e+00 L2 loss: 0.92241 Learning rate: 0.02 Mask loss: 0.29078 RPN box loss: 0.01474 RPN score loss: 0.00367 RPN total loss: 0.01841 Total loss: 1.45393 timestamp: 1654935164.7994728 iteration: 26100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1226 FastRCNN class loss: 0.07768 FastRCNN total loss: 0.20028 L1 loss: 0.0000e+00 L2 loss: 0.92227 Learning rate: 0.02 Mask loss: 0.14739 RPN box loss: 0.02293 RPN score loss: 0.01087 RPN total loss: 0.03379 Total loss: 1.30373 timestamp: 1654935168.0265706 iteration: 26105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16981 FastRCNN class loss: 0.08016 FastRCNN total loss: 0.24998 L1 loss: 0.0000e+00 L2 loss: 0.92215 Learning rate: 0.02 Mask loss: 0.17871 RPN box loss: 0.0331 RPN score loss: 0.00459 RPN total loss: 0.0377 Total loss: 1.38854 timestamp: 1654935171.1978393 iteration: 26110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11633 FastRCNN class loss: 0.05381 FastRCNN total loss: 0.17014 L1 loss: 0.0000e+00 L2 loss: 0.92202 Learning rate: 0.02 Mask loss: 0.07178 RPN box loss: 0.00834 RPN score loss: 0.00192 RPN total loss: 0.01027 Total loss: 1.17421 timestamp: 1654935174.4023275 iteration: 26115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08381 FastRCNN class loss: 0.05448 FastRCNN total loss: 0.13829 L1 loss: 0.0000e+00 L2 loss: 0.92187 Learning rate: 0.02 Mask loss: 0.14125 RPN box loss: 0.03334 RPN score loss: 0.0093 RPN total loss: 0.04263 Total loss: 1.24405 timestamp: 1654935177.7167132 iteration: 26120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14831 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.22577 L1 loss: 0.0000e+00 L2 loss: 0.92171 Learning rate: 0.02 Mask loss: 0.13105 RPN box loss: 0.06238 RPN score loss: 0.00628 RPN total loss: 0.06866 Total loss: 1.3472 timestamp: 1654935181.0326517 iteration: 26125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1111 FastRCNN class loss: 0.0822 FastRCNN total loss: 0.1933 L1 loss: 0.0000e+00 L2 loss: 0.92156 Learning rate: 0.02 Mask loss: 0.15298 RPN box loss: 0.01871 RPN score loss: 0.00519 RPN total loss: 0.0239 Total loss: 1.29173 timestamp: 1654935184.2054825 iteration: 26130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22474 FastRCNN class loss: 0.09408 FastRCNN total loss: 0.31882 L1 loss: 0.0000e+00 L2 loss: 0.92142 Learning rate: 0.02 Mask loss: 0.19644 RPN box loss: 0.03758 RPN score loss: 0.00665 RPN total loss: 0.04422 Total loss: 1.48091 timestamp: 1654935187.3924015 iteration: 26135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09951 FastRCNN class loss: 0.08187 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.92127 Learning rate: 0.02 Mask loss: 0.13137 RPN box loss: 0.03433 RPN score loss: 0.00367 RPN total loss: 0.038 Total loss: 1.27203 timestamp: 1654935190.6179059 iteration: 26140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.109 FastRCNN class loss: 0.07912 FastRCNN total loss: 0.18812 L1 loss: 0.0000e+00 L2 loss: 0.92113 Learning rate: 0.02 Mask loss: 0.10011 RPN box loss: 0.01555 RPN score loss: 0.006 RPN total loss: 0.02155 Total loss: 1.23091 timestamp: 1654935193.7515473 iteration: 26145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19564 FastRCNN class loss: 0.12523 FastRCNN total loss: 0.32087 L1 loss: 0.0000e+00 L2 loss: 0.92098 Learning rate: 0.02 Mask loss: 0.1654 RPN box loss: 0.01748 RPN score loss: 0.00272 RPN total loss: 0.0202 Total loss: 1.42744 timestamp: 1654935196.9877172 iteration: 26150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13861 FastRCNN class loss: 0.08771 FastRCNN total loss: 0.22632 L1 loss: 0.0000e+00 L2 loss: 0.92083 Learning rate: 0.02 Mask loss: 0.12186 RPN box loss: 0.0187 RPN score loss: 0.00198 RPN total loss: 0.02068 Total loss: 1.28969 timestamp: 1654935200.152057 iteration: 26155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11943 FastRCNN class loss: 0.08838 FastRCNN total loss: 0.20781 L1 loss: 0.0000e+00 L2 loss: 0.92069 Learning rate: 0.02 Mask loss: 0.15738 RPN box loss: 0.0212 RPN score loss: 0.00496 RPN total loss: 0.02617 Total loss: 1.31204 timestamp: 1654935203.3935432 iteration: 26160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15499 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.23691 L1 loss: 0.0000e+00 L2 loss: 0.92057 Learning rate: 0.02 Mask loss: 0.10792 RPN box loss: 0.00753 RPN score loss: 0.00134 RPN total loss: 0.00887 Total loss: 1.27427 timestamp: 1654935206.6057553 iteration: 26165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07962 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.14025 L1 loss: 0.0000e+00 L2 loss: 0.92044 Learning rate: 0.02 Mask loss: 0.1895 RPN box loss: 0.07332 RPN score loss: 0.00893 RPN total loss: 0.08225 Total loss: 1.33243 timestamp: 1654935209.8235128 iteration: 26170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19171 FastRCNN class loss: 0.15384 FastRCNN total loss: 0.34555 L1 loss: 0.0000e+00 L2 loss: 0.92031 Learning rate: 0.02 Mask loss: 0.14487 RPN box loss: 0.05834 RPN score loss: 0.0117 RPN total loss: 0.07004 Total loss: 1.48077 timestamp: 1654935213.083064 iteration: 26175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21389 FastRCNN class loss: 0.08635 FastRCNN total loss: 0.30025 L1 loss: 0.0000e+00 L2 loss: 0.92019 Learning rate: 0.02 Mask loss: 0.24013 RPN box loss: 0.04069 RPN score loss: 0.00929 RPN total loss: 0.04999 Total loss: 1.51055 timestamp: 1654935216.321589 iteration: 26180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12114 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.18976 L1 loss: 0.0000e+00 L2 loss: 0.92003 Learning rate: 0.02 Mask loss: 0.10633 RPN box loss: 0.01899 RPN score loss: 0.0094 RPN total loss: 0.02839 Total loss: 1.24451 timestamp: 1654935219.5567248 iteration: 26185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18891 FastRCNN class loss: 0.17441 FastRCNN total loss: 0.36332 L1 loss: 0.0000e+00 L2 loss: 0.91986 Learning rate: 0.02 Mask loss: 0.27101 RPN box loss: 0.0445 RPN score loss: 0.00563 RPN total loss: 0.05013 Total loss: 1.60433 timestamp: 1654935222.7605379 iteration: 26190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11207 FastRCNN class loss: 0.07443 FastRCNN total loss: 0.1865 L1 loss: 0.0000e+00 L2 loss: 0.91973 Learning rate: 0.02 Mask loss: 0.20443 RPN box loss: 0.03838 RPN score loss: 0.0105 RPN total loss: 0.04889 Total loss: 1.35955 timestamp: 1654935225.980699 iteration: 26195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14664 FastRCNN class loss: 0.04964 FastRCNN total loss: 0.19628 L1 loss: 0.0000e+00 L2 loss: 0.91961 Learning rate: 0.02 Mask loss: 0.14254 RPN box loss: 0.02055 RPN score loss: 0.00108 RPN total loss: 0.02163 Total loss: 1.28005 timestamp: 1654935229.2213154 iteration: 26200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08015 FastRCNN class loss: 0.04129 FastRCNN total loss: 0.12144 L1 loss: 0.0000e+00 L2 loss: 0.91947 Learning rate: 0.02 Mask loss: 0.09797 RPN box loss: 0.01788 RPN score loss: 0.00432 RPN total loss: 0.02221 Total loss: 1.16109 timestamp: 1654935232.3856282 iteration: 26205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10436 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.17977 L1 loss: 0.0000e+00 L2 loss: 0.91933 Learning rate: 0.02 Mask loss: 0.11921 RPN box loss: 0.03046 RPN score loss: 0.00905 RPN total loss: 0.0395 Total loss: 1.25781 timestamp: 1654935235.6089594 iteration: 26210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11346 FastRCNN class loss: 0.08573 FastRCNN total loss: 0.19919 L1 loss: 0.0000e+00 L2 loss: 0.9192 Learning rate: 0.02 Mask loss: 0.14746 RPN box loss: 0.02341 RPN score loss: 0.00678 RPN total loss: 0.03019 Total loss: 1.29603 timestamp: 1654935238.7902894 iteration: 26215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08325 FastRCNN class loss: 0.05747 FastRCNN total loss: 0.14072 L1 loss: 0.0000e+00 L2 loss: 0.91908 Learning rate: 0.02 Mask loss: 0.13068 RPN box loss: 0.04823 RPN score loss: 0.00509 RPN total loss: 0.05332 Total loss: 1.2438 timestamp: 1654935241.9568799 iteration: 26220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10861 FastRCNN class loss: 0.09689 FastRCNN total loss: 0.2055 L1 loss: 0.0000e+00 L2 loss: 0.91893 Learning rate: 0.02 Mask loss: 0.1905 RPN box loss: 0.02969 RPN score loss: 0.00548 RPN total loss: 0.03517 Total loss: 1.3501 timestamp: 1654935245.1703513 iteration: 26225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13568 FastRCNN class loss: 0.07215 FastRCNN total loss: 0.20783 L1 loss: 0.0000e+00 L2 loss: 0.9188 Learning rate: 0.02 Mask loss: 0.15697 RPN box loss: 0.01971 RPN score loss: 0.00635 RPN total loss: 0.02606 Total loss: 1.30965 timestamp: 1654935248.382124 iteration: 26230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16863 FastRCNN class loss: 0.10186 FastRCNN total loss: 0.27049 L1 loss: 0.0000e+00 L2 loss: 0.91866 Learning rate: 0.02 Mask loss: 0.14991 RPN box loss: 0.05932 RPN score loss: 0.00858 RPN total loss: 0.0679 Total loss: 1.40696 timestamp: 1654935251.5025473 iteration: 26235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12655 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.21411 L1 loss: 0.0000e+00 L2 loss: 0.91852 Learning rate: 0.02 Mask loss: 0.17545 RPN box loss: 0.0321 RPN score loss: 0.00788 RPN total loss: 0.03997 Total loss: 1.34805 timestamp: 1654935254.7103336 iteration: 26240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19269 FastRCNN class loss: 0.10033 FastRCNN total loss: 0.29302 L1 loss: 0.0000e+00 L2 loss: 0.91839 Learning rate: 0.02 Mask loss: 0.15974 RPN box loss: 0.03804 RPN score loss: 0.0134 RPN total loss: 0.05144 Total loss: 1.42258 timestamp: 1654935257.9129727 iteration: 26245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10103 FastRCNN class loss: 0.04766 FastRCNN total loss: 0.1487 L1 loss: 0.0000e+00 L2 loss: 0.91825 Learning rate: 0.02 Mask loss: 0.09935 RPN box loss: 0.0085 RPN score loss: 0.00303 RPN total loss: 0.01153 Total loss: 1.17782 timestamp: 1654935261.1043177 iteration: 26250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11201 FastRCNN class loss: 0.05698 FastRCNN total loss: 0.16899 L1 loss: 0.0000e+00 L2 loss: 0.91811 Learning rate: 0.02 Mask loss: 0.15475 RPN box loss: 0.0149 RPN score loss: 0.00116 RPN total loss: 0.01606 Total loss: 1.25792 timestamp: 1654935264.2640333 iteration: 26255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17572 FastRCNN class loss: 0.06002 FastRCNN total loss: 0.23574 L1 loss: 0.0000e+00 L2 loss: 0.91799 Learning rate: 0.02 Mask loss: 0.12348 RPN box loss: 0.01821 RPN score loss: 0.00783 RPN total loss: 0.02604 Total loss: 1.30325 timestamp: 1654935267.4678018 iteration: 26260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1738 FastRCNN class loss: 0.15673 FastRCNN total loss: 0.33053 L1 loss: 0.0000e+00 L2 loss: 0.91783 Learning rate: 0.02 Mask loss: 0.19754 RPN box loss: 0.0562 RPN score loss: 0.00516 RPN total loss: 0.06136 Total loss: 1.50725 timestamp: 1654935270.623296 iteration: 26265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16485 FastRCNN class loss: 0.08834 FastRCNN total loss: 0.25319 L1 loss: 0.0000e+00 L2 loss: 0.91769 Learning rate: 0.02 Mask loss: 0.15528 RPN box loss: 0.04221 RPN score loss: 0.00487 RPN total loss: 0.04708 Total loss: 1.37323 timestamp: 1654935273.7705793 iteration: 26270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12145 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.18621 L1 loss: 0.0000e+00 L2 loss: 0.91754 Learning rate: 0.02 Mask loss: 0.1413 RPN box loss: 0.04826 RPN score loss: 0.00403 RPN total loss: 0.05229 Total loss: 1.29734 timestamp: 1654935276.95398 iteration: 26275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13188 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.19837 L1 loss: 0.0000e+00 L2 loss: 0.91739 Learning rate: 0.02 Mask loss: 0.11268 RPN box loss: 0.01817 RPN score loss: 0.00164 RPN total loss: 0.0198 Total loss: 1.24824 timestamp: 1654935280.1990323 iteration: 26280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09501 FastRCNN class loss: 0.05401 FastRCNN total loss: 0.14902 L1 loss: 0.0000e+00 L2 loss: 0.91724 Learning rate: 0.02 Mask loss: 0.13244 RPN box loss: 0.00363 RPN score loss: 0.00378 RPN total loss: 0.0074 Total loss: 1.20609 timestamp: 1654935283.4099674 iteration: 26285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11211 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.21305 L1 loss: 0.0000e+00 L2 loss: 0.91713 Learning rate: 0.02 Mask loss: 0.14903 RPN box loss: 0.01677 RPN score loss: 0.01009 RPN total loss: 0.02687 Total loss: 1.30608 timestamp: 1654935286.5860603 iteration: 26290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11192 FastRCNN class loss: 0.04996 FastRCNN total loss: 0.16188 L1 loss: 0.0000e+00 L2 loss: 0.91699 Learning rate: 0.02 Mask loss: 0.22324 RPN box loss: 0.0885 RPN score loss: 0.00833 RPN total loss: 0.09683 Total loss: 1.39894 timestamp: 1654935289.7635372 iteration: 26295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19365 FastRCNN class loss: 0.07568 FastRCNN total loss: 0.26932 L1 loss: 0.0000e+00 L2 loss: 0.91684 Learning rate: 0.02 Mask loss: 0.14346 RPN box loss: 0.04841 RPN score loss: 0.00959 RPN total loss: 0.058 Total loss: 1.38763 timestamp: 1654935292.940497 iteration: 26300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.124 FastRCNN class loss: 0.05884 FastRCNN total loss: 0.18284 L1 loss: 0.0000e+00 L2 loss: 0.9167 Learning rate: 0.02 Mask loss: 0.14215 RPN box loss: 0.0337 RPN score loss: 0.0027 RPN total loss: 0.0364 Total loss: 1.27809 timestamp: 1654935296.1611397 iteration: 26305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14752 FastRCNN class loss: 0.15151 FastRCNN total loss: 0.29902 L1 loss: 0.0000e+00 L2 loss: 0.91656 Learning rate: 0.02 Mask loss: 0.18381 RPN box loss: 0.04893 RPN score loss: 0.00749 RPN total loss: 0.05642 Total loss: 1.45581 timestamp: 1654935299.3811643 iteration: 26310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19691 FastRCNN class loss: 0.12555 FastRCNN total loss: 0.32246 L1 loss: 0.0000e+00 L2 loss: 0.91641 Learning rate: 0.02 Mask loss: 0.31932 RPN box loss: 0.0616 RPN score loss: 0.00581 RPN total loss: 0.06741 Total loss: 1.62559 timestamp: 1654935302.5742404 iteration: 26315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12022 FastRCNN class loss: 0.08561 FastRCNN total loss: 0.20583 L1 loss: 0.0000e+00 L2 loss: 0.91629 Learning rate: 0.02 Mask loss: 0.17589 RPN box loss: 0.01531 RPN score loss: 0.00618 RPN total loss: 0.0215 Total loss: 1.31951 timestamp: 1654935305.8128474 iteration: 26320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14393 FastRCNN class loss: 0.1435 FastRCNN total loss: 0.28743 L1 loss: 0.0000e+00 L2 loss: 0.91614 Learning rate: 0.02 Mask loss: 0.15249 RPN box loss: 0.05298 RPN score loss: 0.00794 RPN total loss: 0.06092 Total loss: 1.41698 timestamp: 1654935309.0283346 iteration: 26325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10993 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.16771 L1 loss: 0.0000e+00 L2 loss: 0.91601 Learning rate: 0.02 Mask loss: 0.16125 RPN box loss: 0.03031 RPN score loss: 0.00935 RPN total loss: 0.03966 Total loss: 1.28463 timestamp: 1654935312.198338 iteration: 26330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16625 FastRCNN class loss: 0.07862 FastRCNN total loss: 0.24487 L1 loss: 0.0000e+00 L2 loss: 0.91588 Learning rate: 0.02 Mask loss: 0.15542 RPN box loss: 0.04292 RPN score loss: 0.00679 RPN total loss: 0.04971 Total loss: 1.36587 timestamp: 1654935315.3815262 iteration: 26335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15185 FastRCNN class loss: 0.10259 FastRCNN total loss: 0.25444 L1 loss: 0.0000e+00 L2 loss: 0.91575 Learning rate: 0.02 Mask loss: 0.16516 RPN box loss: 0.04521 RPN score loss: 0.00991 RPN total loss: 0.05512 Total loss: 1.39047 timestamp: 1654935318.6345153 iteration: 26340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06424 FastRCNN class loss: 0.05387 FastRCNN total loss: 0.11811 L1 loss: 0.0000e+00 L2 loss: 0.9156 Learning rate: 0.02 Mask loss: 0.13316 RPN box loss: 0.00927 RPN score loss: 0.00091 RPN total loss: 0.01019 Total loss: 1.17705 timestamp: 1654935321.8084288 iteration: 26345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13991 FastRCNN class loss: 0.10374 FastRCNN total loss: 0.24365 L1 loss: 0.0000e+00 L2 loss: 0.91547 Learning rate: 0.02 Mask loss: 0.17235 RPN box loss: 0.03511 RPN score loss: 0.00237 RPN total loss: 0.03748 Total loss: 1.36895 timestamp: 1654935324.955251 iteration: 26350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11963 FastRCNN class loss: 0.08656 FastRCNN total loss: 0.20618 L1 loss: 0.0000e+00 L2 loss: 0.91529 Learning rate: 0.02 Mask loss: 0.1268 RPN box loss: 0.07711 RPN score loss: 0.01053 RPN total loss: 0.08764 Total loss: 1.33591 timestamp: 1654935328.116236 iteration: 26355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18241 FastRCNN class loss: 0.14225 FastRCNN total loss: 0.32465 L1 loss: 0.0000e+00 L2 loss: 0.91512 Learning rate: 0.02 Mask loss: 0.16322 RPN box loss: 0.04162 RPN score loss: 0.01012 RPN total loss: 0.05174 Total loss: 1.45473 timestamp: 1654935331.4067824 iteration: 26360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22045 FastRCNN class loss: 0.07478 FastRCNN total loss: 0.29523 L1 loss: 0.0000e+00 L2 loss: 0.91498 Learning rate: 0.02 Mask loss: 0.13691 RPN box loss: 0.02509 RPN score loss: 0.00598 RPN total loss: 0.03107 Total loss: 1.37819 timestamp: 1654935334.5918193 iteration: 26365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15618 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.21406 L1 loss: 0.0000e+00 L2 loss: 0.91487 Learning rate: 0.02 Mask loss: 0.13531 RPN box loss: 0.05713 RPN score loss: 0.01066 RPN total loss: 0.06779 Total loss: 1.33203 timestamp: 1654935337.7950597 iteration: 26370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16161 FastRCNN class loss: 0.12124 FastRCNN total loss: 0.28285 L1 loss: 0.0000e+00 L2 loss: 0.91473 Learning rate: 0.02 Mask loss: 0.16709 RPN box loss: 0.01389 RPN score loss: 0.00329 RPN total loss: 0.01718 Total loss: 1.38186 timestamp: 1654935340.9485073 iteration: 26375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12827 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.18018 L1 loss: 0.0000e+00 L2 loss: 0.9146 Learning rate: 0.02 Mask loss: 0.12603 RPN box loss: 0.01246 RPN score loss: 0.00595 RPN total loss: 0.01841 Total loss: 1.23922 timestamp: 1654935344.128005 iteration: 26380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14718 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.21632 L1 loss: 0.0000e+00 L2 loss: 0.91447 Learning rate: 0.02 Mask loss: 0.12053 RPN box loss: 0.04144 RPN score loss: 0.00499 RPN total loss: 0.04643 Total loss: 1.29775 timestamp: 1654935347.3574889 iteration: 26385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11933 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.17739 L1 loss: 0.0000e+00 L2 loss: 0.91433 Learning rate: 0.02 Mask loss: 0.1909 RPN box loss: 0.01216 RPN score loss: 0.00503 RPN total loss: 0.01718 Total loss: 1.29979 timestamp: 1654935350.5651844 iteration: 26390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05759 FastRCNN class loss: 0.05298 FastRCNN total loss: 0.11057 L1 loss: 0.0000e+00 L2 loss: 0.91418 Learning rate: 0.02 Mask loss: 0.17223 RPN box loss: 0.0295 RPN score loss: 0.0032 RPN total loss: 0.03269 Total loss: 1.22967 timestamp: 1654935353.7437663 iteration: 26395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0933 FastRCNN class loss: 0.09221 FastRCNN total loss: 0.18551 L1 loss: 0.0000e+00 L2 loss: 0.91405 Learning rate: 0.02 Mask loss: 0.14503 RPN box loss: 0.01611 RPN score loss: 0.02736 RPN total loss: 0.04347 Total loss: 1.28805 timestamp: 1654935356.9332778 iteration: 26400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12229 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.19649 L1 loss: 0.0000e+00 L2 loss: 0.91389 Learning rate: 0.02 Mask loss: 0.13987 RPN box loss: 0.02399 RPN score loss: 0.00613 RPN total loss: 0.03013 Total loss: 1.28038 timestamp: 1654935360.108358 iteration: 26405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09837 FastRCNN class loss: 0.10495 FastRCNN total loss: 0.20333 L1 loss: 0.0000e+00 L2 loss: 0.91373 Learning rate: 0.02 Mask loss: 0.18081 RPN box loss: 0.03411 RPN score loss: 0.01348 RPN total loss: 0.04759 Total loss: 1.34545 timestamp: 1654935363.3216596 iteration: 26410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11431 FastRCNN class loss: 0.0667 FastRCNN total loss: 0.18101 L1 loss: 0.0000e+00 L2 loss: 0.91362 Learning rate: 0.02 Mask loss: 0.14672 RPN box loss: 0.05378 RPN score loss: 0.00768 RPN total loss: 0.06146 Total loss: 1.30281 timestamp: 1654935366.5806434 iteration: 26415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13737 FastRCNN class loss: 0.09499 FastRCNN total loss: 0.23236 L1 loss: 0.0000e+00 L2 loss: 0.91347 Learning rate: 0.02 Mask loss: 0.1957 RPN box loss: 0.03841 RPN score loss: 0.00399 RPN total loss: 0.0424 Total loss: 1.38394 timestamp: 1654935369.7680254 iteration: 26420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11319 FastRCNN class loss: 0.06662 FastRCNN total loss: 0.17981 L1 loss: 0.0000e+00 L2 loss: 0.91335 Learning rate: 0.02 Mask loss: 0.11593 RPN box loss: 0.01575 RPN score loss: 0.00789 RPN total loss: 0.02364 Total loss: 1.23272 timestamp: 1654935372.9763434 iteration: 26425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19529 FastRCNN class loss: 0.10364 FastRCNN total loss: 0.29892 L1 loss: 0.0000e+00 L2 loss: 0.9132 Learning rate: 0.02 Mask loss: 0.22818 RPN box loss: 0.01975 RPN score loss: 0.0042 RPN total loss: 0.02395 Total loss: 1.46425 timestamp: 1654935376.2284396 iteration: 26430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1685 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.24095 L1 loss: 0.0000e+00 L2 loss: 0.91308 Learning rate: 0.02 Mask loss: 0.11342 RPN box loss: 0.01393 RPN score loss: 0.00735 RPN total loss: 0.02127 Total loss: 1.28872 timestamp: 1654935379.3976831 iteration: 26435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13882 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.23462 L1 loss: 0.0000e+00 L2 loss: 0.91295 Learning rate: 0.02 Mask loss: 0.1852 RPN box loss: 0.02366 RPN score loss: 0.01005 RPN total loss: 0.03371 Total loss: 1.36648 timestamp: 1654935382.6584299 iteration: 26440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11496 FastRCNN class loss: 0.0972 FastRCNN total loss: 0.21215 L1 loss: 0.0000e+00 L2 loss: 0.91281 Learning rate: 0.02 Mask loss: 0.16595 RPN box loss: 0.02175 RPN score loss: 0.0075 RPN total loss: 0.02925 Total loss: 1.32017 timestamp: 1654935385.8434367 iteration: 26445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19454 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.27048 L1 loss: 0.0000e+00 L2 loss: 0.91268 Learning rate: 0.02 Mask loss: 0.155 RPN box loss: 0.02705 RPN score loss: 0.00492 RPN total loss: 0.03197 Total loss: 1.37013 timestamp: 1654935389.0695722 iteration: 26450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.178 FastRCNN class loss: 0.11868 FastRCNN total loss: 0.29669 L1 loss: 0.0000e+00 L2 loss: 0.91252 Learning rate: 0.02 Mask loss: 0.18511 RPN box loss: 0.03994 RPN score loss: 0.00612 RPN total loss: 0.04606 Total loss: 1.44037 timestamp: 1654935392.3136556 iteration: 26455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09287 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.17126 L1 loss: 0.0000e+00 L2 loss: 0.91237 Learning rate: 0.02 Mask loss: 0.16903 RPN box loss: 0.02638 RPN score loss: 0.00618 RPN total loss: 0.03256 Total loss: 1.28522 timestamp: 1654935395.5423577 iteration: 26460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16543 FastRCNN class loss: 0.09199 FastRCNN total loss: 0.25743 L1 loss: 0.0000e+00 L2 loss: 0.91223 Learning rate: 0.02 Mask loss: 0.134 RPN box loss: 0.02877 RPN score loss: 0.00823 RPN total loss: 0.037 Total loss: 1.34065 timestamp: 1654935398.700008 iteration: 26465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13444 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.20966 L1 loss: 0.0000e+00 L2 loss: 0.91208 Learning rate: 0.02 Mask loss: 0.1787 RPN box loss: 0.03183 RPN score loss: 0.00471 RPN total loss: 0.03653 Total loss: 1.33697 timestamp: 1654935401.84615 iteration: 26470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.077 FastRCNN total loss: 0.21825 L1 loss: 0.0000e+00 L2 loss: 0.91193 Learning rate: 0.02 Mask loss: 0.20297 RPN box loss: 0.01886 RPN score loss: 0.00357 RPN total loss: 0.02242 Total loss: 1.35557 timestamp: 1654935405.0847218 iteration: 26475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08269 FastRCNN class loss: 0.06136 FastRCNN total loss: 0.14406 L1 loss: 0.0000e+00 L2 loss: 0.91179 Learning rate: 0.02 Mask loss: 0.11829 RPN box loss: 0.06053 RPN score loss: 0.00561 RPN total loss: 0.06614 Total loss: 1.24028 timestamp: 1654935408.2455766 iteration: 26480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17941 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.25744 L1 loss: 0.0000e+00 L2 loss: 0.91165 Learning rate: 0.02 Mask loss: 0.11416 RPN box loss: 0.018 RPN score loss: 0.00296 RPN total loss: 0.02097 Total loss: 1.30422 timestamp: 1654935411.4370437 iteration: 26485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10807 FastRCNN class loss: 0.06715 FastRCNN total loss: 0.17523 L1 loss: 0.0000e+00 L2 loss: 0.91153 Learning rate: 0.02 Mask loss: 0.15702 RPN box loss: 0.03605 RPN score loss: 0.00246 RPN total loss: 0.03851 Total loss: 1.28229 timestamp: 1654935414.718015 iteration: 26490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14754 FastRCNN class loss: 0.10151 FastRCNN total loss: 0.24905 L1 loss: 0.0000e+00 L2 loss: 0.9114 Learning rate: 0.02 Mask loss: 0.15824 RPN box loss: 0.0334 RPN score loss: 0.01638 RPN total loss: 0.04978 Total loss: 1.36847 timestamp: 1654935417.8474705 iteration: 26495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19197 FastRCNN class loss: 0.08727 FastRCNN total loss: 0.27924 L1 loss: 0.0000e+00 L2 loss: 0.91127 Learning rate: 0.02 Mask loss: 0.15597 RPN box loss: 0.03038 RPN score loss: 0.00835 RPN total loss: 0.03874 Total loss: 1.38522 timestamp: 1654935421.0023851 iteration: 26500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13735 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.18951 L1 loss: 0.0000e+00 L2 loss: 0.91113 Learning rate: 0.02 Mask loss: 0.14897 RPN box loss: 0.02948 RPN score loss: 0.01048 RPN total loss: 0.03997 Total loss: 1.28958 timestamp: 1654935424.1783402 iteration: 26505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09485 FastRCNN class loss: 0.0763 FastRCNN total loss: 0.17115 L1 loss: 0.0000e+00 L2 loss: 0.91098 Learning rate: 0.02 Mask loss: 0.1797 RPN box loss: 0.04765 RPN score loss: 0.00785 RPN total loss: 0.0555 Total loss: 1.31733 timestamp: 1654935427.4557633 iteration: 26510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17857 FastRCNN class loss: 0.10153 FastRCNN total loss: 0.28011 L1 loss: 0.0000e+00 L2 loss: 0.91084 Learning rate: 0.02 Mask loss: 0.12609 RPN box loss: 0.02519 RPN score loss: 0.00765 RPN total loss: 0.03283 Total loss: 1.34987 timestamp: 1654935430.7229862 iteration: 26515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16772 FastRCNN class loss: 0.08914 FastRCNN total loss: 0.25686 L1 loss: 0.0000e+00 L2 loss: 0.91072 Learning rate: 0.02 Mask loss: 0.15584 RPN box loss: 0.01594 RPN score loss: 0.00156 RPN total loss: 0.01749 Total loss: 1.34092 timestamp: 1654935433.851419 iteration: 26520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15575 FastRCNN class loss: 0.08356 FastRCNN total loss: 0.23931 L1 loss: 0.0000e+00 L2 loss: 0.9106 Learning rate: 0.02 Mask loss: 0.16212 RPN box loss: 0.00803 RPN score loss: 0.00582 RPN total loss: 0.01385 Total loss: 1.32588 timestamp: 1654935437.0738285 iteration: 26525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14632 FastRCNN class loss: 0.08127 FastRCNN total loss: 0.22758 L1 loss: 0.0000e+00 L2 loss: 0.91042 Learning rate: 0.02 Mask loss: 0.18795 RPN box loss: 0.01782 RPN score loss: 0.00357 RPN total loss: 0.02138 Total loss: 1.34734 timestamp: 1654935440.2164466 iteration: 26530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13589 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.22206 L1 loss: 0.0000e+00 L2 loss: 0.91029 Learning rate: 0.02 Mask loss: 0.16411 RPN box loss: 0.02286 RPN score loss: 0.00702 RPN total loss: 0.02988 Total loss: 1.32634 timestamp: 1654935443.4253745 iteration: 26535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16282 FastRCNN class loss: 0.1083 FastRCNN total loss: 0.27113 L1 loss: 0.0000e+00 L2 loss: 0.91016 Learning rate: 0.02 Mask loss: 0.21327 RPN box loss: 0.02669 RPN score loss: 0.01126 RPN total loss: 0.03795 Total loss: 1.4325 timestamp: 1654935446.6005738 iteration: 26540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23645 FastRCNN class loss: 0.09054 FastRCNN total loss: 0.32699 L1 loss: 0.0000e+00 L2 loss: 0.91003 Learning rate: 0.02 Mask loss: 0.22233 RPN box loss: 0.04281 RPN score loss: 0.01274 RPN total loss: 0.05555 Total loss: 1.5149 timestamp: 1654935449.7975686 iteration: 26545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18078 FastRCNN class loss: 0.16327 FastRCNN total loss: 0.34406 L1 loss: 0.0000e+00 L2 loss: 0.90987 Learning rate: 0.02 Mask loss: 0.20583 RPN box loss: 0.05421 RPN score loss: 0.04077 RPN total loss: 0.09498 Total loss: 1.55474 timestamp: 1654935453.0846765 iteration: 26550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.13531 L1 loss: 0.0000e+00 L2 loss: 0.90975 Learning rate: 0.02 Mask loss: 0.12901 RPN box loss: 0.04262 RPN score loss: 0.00533 RPN total loss: 0.04794 Total loss: 1.22201 timestamp: 1654935456.3369105 iteration: 26555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09274 FastRCNN class loss: 0.0579 FastRCNN total loss: 0.15064 L1 loss: 0.0000e+00 L2 loss: 0.90964 Learning rate: 0.02 Mask loss: 0.13681 RPN box loss: 0.0164 RPN score loss: 0.00224 RPN total loss: 0.01863 Total loss: 1.21572 timestamp: 1654935459.5513709 iteration: 26560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10846 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.16878 L1 loss: 0.0000e+00 L2 loss: 0.90952 Learning rate: 0.02 Mask loss: 0.15354 RPN box loss: 0.01831 RPN score loss: 0.00321 RPN total loss: 0.02152 Total loss: 1.25336 timestamp: 1654935462.70842 iteration: 26565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09314 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.15392 L1 loss: 0.0000e+00 L2 loss: 0.90938 Learning rate: 0.02 Mask loss: 0.1324 RPN box loss: 0.04514 RPN score loss: 0.00677 RPN total loss: 0.05191 Total loss: 1.2476 timestamp: 1654935465.9010673 iteration: 26570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0927 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.17276 L1 loss: 0.0000e+00 L2 loss: 0.90922 Learning rate: 0.02 Mask loss: 0.10058 RPN box loss: 0.01199 RPN score loss: 0.00544 RPN total loss: 0.01743 Total loss: 1.2 timestamp: 1654935469.1305985 iteration: 26575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0755 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.13601 L1 loss: 0.0000e+00 L2 loss: 0.90908 Learning rate: 0.02 Mask loss: 0.12697 RPN box loss: 0.02607 RPN score loss: 0.00407 RPN total loss: 0.03014 Total loss: 1.2022 timestamp: 1654935472.2919307 iteration: 26580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04518 FastRCNN class loss: 0.04055 FastRCNN total loss: 0.08572 L1 loss: 0.0000e+00 L2 loss: 0.90893 Learning rate: 0.02 Mask loss: 0.11948 RPN box loss: 0.00437 RPN score loss: 0.00442 RPN total loss: 0.00879 Total loss: 1.12293 timestamp: 1654935475.4038224 iteration: 26585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1217 FastRCNN class loss: 0.11572 FastRCNN total loss: 0.23742 L1 loss: 0.0000e+00 L2 loss: 0.9088 Learning rate: 0.02 Mask loss: 0.13255 RPN box loss: 0.02529 RPN score loss: 0.00954 RPN total loss: 0.03483 Total loss: 1.31361 timestamp: 1654935478.6248572 iteration: 26590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09943 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.17107 L1 loss: 0.0000e+00 L2 loss: 0.90868 Learning rate: 0.02 Mask loss: 0.16667 RPN box loss: 0.03569 RPN score loss: 0.00395 RPN total loss: 0.03964 Total loss: 1.28606 timestamp: 1654935481.8243847 iteration: 26595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14235 FastRCNN class loss: 0.08076 FastRCNN total loss: 0.22311 L1 loss: 0.0000e+00 L2 loss: 0.90856 Learning rate: 0.02 Mask loss: 0.15567 RPN box loss: 0.02561 RPN score loss: 0.00858 RPN total loss: 0.03419 Total loss: 1.32153 timestamp: 1654935485.0411973 iteration: 26600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15487 FastRCNN class loss: 0.11483 FastRCNN total loss: 0.26971 L1 loss: 0.0000e+00 L2 loss: 0.90842 Learning rate: 0.02 Mask loss: 0.14311 RPN box loss: 0.03803 RPN score loss: 0.0172 RPN total loss: 0.05523 Total loss: 1.37647 timestamp: 1654935488.232198 iteration: 26605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10282 FastRCNN class loss: 0.06232 FastRCNN total loss: 0.16515 L1 loss: 0.0000e+00 L2 loss: 0.9083 Learning rate: 0.02 Mask loss: 0.11211 RPN box loss: 0.01075 RPN score loss: 0.00339 RPN total loss: 0.01414 Total loss: 1.19969 timestamp: 1654935491.3820717 iteration: 26610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16309 FastRCNN class loss: 0.11732 FastRCNN total loss: 0.28041 L1 loss: 0.0000e+00 L2 loss: 0.90816 Learning rate: 0.02 Mask loss: 0.13969 RPN box loss: 0.03199 RPN score loss: 0.00778 RPN total loss: 0.03977 Total loss: 1.36803 timestamp: 1654935494.5958204 iteration: 26615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12242 FastRCNN class loss: 0.13659 FastRCNN total loss: 0.25901 L1 loss: 0.0000e+00 L2 loss: 0.90801 Learning rate: 0.02 Mask loss: 0.16059 RPN box loss: 0.04388 RPN score loss: 0.01651 RPN total loss: 0.06039 Total loss: 1.38799 timestamp: 1654935497.8591335 iteration: 26620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14278 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.22188 L1 loss: 0.0000e+00 L2 loss: 0.90787 Learning rate: 0.02 Mask loss: 0.11774 RPN box loss: 0.08355 RPN score loss: 0.0039 RPN total loss: 0.08745 Total loss: 1.33494 timestamp: 1654935501.0667624 iteration: 26625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16068 FastRCNN class loss: 0.09527 FastRCNN total loss: 0.25595 L1 loss: 0.0000e+00 L2 loss: 0.90774 Learning rate: 0.02 Mask loss: 0.21145 RPN box loss: 0.0759 RPN score loss: 0.01276 RPN total loss: 0.08866 Total loss: 1.46379 timestamp: 1654935504.205101 iteration: 26630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11055 FastRCNN class loss: 0.06801 FastRCNN total loss: 0.17856 L1 loss: 0.0000e+00 L2 loss: 0.9076 Learning rate: 0.02 Mask loss: 0.23192 RPN box loss: 0.00781 RPN score loss: 0.00418 RPN total loss: 0.01198 Total loss: 1.33006 timestamp: 1654935507.4078639 iteration: 26635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07506 FastRCNN class loss: 0.03261 FastRCNN total loss: 0.10767 L1 loss: 0.0000e+00 L2 loss: 0.90747 Learning rate: 0.02 Mask loss: 0.08718 RPN box loss: 0.05418 RPN score loss: 0.00799 RPN total loss: 0.06216 Total loss: 1.16449 timestamp: 1654935510.6174147 iteration: 26640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13629 FastRCNN class loss: 0.09554 FastRCNN total loss: 0.23183 L1 loss: 0.0000e+00 L2 loss: 0.90734 Learning rate: 0.02 Mask loss: 0.18093 RPN box loss: 0.04411 RPN score loss: 0.01886 RPN total loss: 0.06297 Total loss: 1.38307 timestamp: 1654935513.8357835 iteration: 26645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17091 FastRCNN class loss: 0.12521 FastRCNN total loss: 0.29611 L1 loss: 0.0000e+00 L2 loss: 0.90718 Learning rate: 0.02 Mask loss: 0.16374 RPN box loss: 0.03319 RPN score loss: 0.01488 RPN total loss: 0.04807 Total loss: 1.41511 timestamp: 1654935517.0310676 iteration: 26650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23589 FastRCNN class loss: 0.08023 FastRCNN total loss: 0.31612 L1 loss: 0.0000e+00 L2 loss: 0.90703 Learning rate: 0.02 Mask loss: 0.11866 RPN box loss: 0.06068 RPN score loss: 0.01597 RPN total loss: 0.07665 Total loss: 1.41846 timestamp: 1654935520.2436497 iteration: 26655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12703 FastRCNN class loss: 0.09994 FastRCNN total loss: 0.22696 L1 loss: 0.0000e+00 L2 loss: 0.90689 Learning rate: 0.02 Mask loss: 0.14745 RPN box loss: 0.01992 RPN score loss: 0.00936 RPN total loss: 0.02928 Total loss: 1.31059 timestamp: 1654935523.4228187 iteration: 26660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15929 FastRCNN class loss: 0.04976 FastRCNN total loss: 0.20905 L1 loss: 0.0000e+00 L2 loss: 0.90677 Learning rate: 0.02 Mask loss: 0.14108 RPN box loss: 0.03811 RPN score loss: 0.0037 RPN total loss: 0.04182 Total loss: 1.29872 timestamp: 1654935526.607146 iteration: 26665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14363 FastRCNN class loss: 0.1078 FastRCNN total loss: 0.25143 L1 loss: 0.0000e+00 L2 loss: 0.90661 Learning rate: 0.02 Mask loss: 0.18405 RPN box loss: 0.00771 RPN score loss: 0.0016 RPN total loss: 0.00932 Total loss: 1.35141 timestamp: 1654935529.813659 iteration: 26670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19639 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.30034 L1 loss: 0.0000e+00 L2 loss: 0.90647 Learning rate: 0.02 Mask loss: 0.23461 RPN box loss: 0.00695 RPN score loss: 0.00373 RPN total loss: 0.01068 Total loss: 1.4521 timestamp: 1654935532.9714572 iteration: 26675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18298 FastRCNN class loss: 0.10793 FastRCNN total loss: 0.2909 L1 loss: 0.0000e+00 L2 loss: 0.90633 Learning rate: 0.02 Mask loss: 0.18167 RPN box loss: 0.02643 RPN score loss: 0.00265 RPN total loss: 0.02908 Total loss: 1.40799 timestamp: 1654935536.1328466 iteration: 26680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.168 L1 loss: 0.0000e+00 L2 loss: 0.9062 Learning rate: 0.02 Mask loss: 0.12492 RPN box loss: 0.04985 RPN score loss: 0.00949 RPN total loss: 0.05934 Total loss: 1.25845 timestamp: 1654935539.335861 iteration: 26685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14732 FastRCNN class loss: 0.09708 FastRCNN total loss: 0.2444 L1 loss: 0.0000e+00 L2 loss: 0.90607 Learning rate: 0.02 Mask loss: 0.19759 RPN box loss: 0.03622 RPN score loss: 0.00846 RPN total loss: 0.04468 Total loss: 1.39273 timestamp: 1654935542.5179377 iteration: 26690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17572 FastRCNN class loss: 0.09436 FastRCNN total loss: 0.27008 L1 loss: 0.0000e+00 L2 loss: 0.90594 Learning rate: 0.02 Mask loss: 0.09867 RPN box loss: 0.035 RPN score loss: 0.01018 RPN total loss: 0.04518 Total loss: 1.31987 timestamp: 1654935545.6648521 iteration: 26695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15058 FastRCNN class loss: 0.08588 FastRCNN total loss: 0.23646 L1 loss: 0.0000e+00 L2 loss: 0.90579 Learning rate: 0.02 Mask loss: 0.29843 RPN box loss: 0.02041 RPN score loss: 0.00424 RPN total loss: 0.02465 Total loss: 1.46532 timestamp: 1654935548.880006 iteration: 26700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07497 FastRCNN class loss: 0.05618 FastRCNN total loss: 0.13115 L1 loss: 0.0000e+00 L2 loss: 0.90563 Learning rate: 0.02 Mask loss: 0.16966 RPN box loss: 0.03084 RPN score loss: 0.00148 RPN total loss: 0.03232 Total loss: 1.23877 timestamp: 1654935552.0575593 iteration: 26705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.124 FastRCNN class loss: 0.07647 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 0.9055 Learning rate: 0.02 Mask loss: 0.10951 RPN box loss: 0.01791 RPN score loss: 0.00276 RPN total loss: 0.02067 Total loss: 1.23615 timestamp: 1654935555.2678454 iteration: 26710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06726 FastRCNN class loss: 0.06739 FastRCNN total loss: 0.13465 L1 loss: 0.0000e+00 L2 loss: 0.90536 Learning rate: 0.02 Mask loss: 0.17371 RPN box loss: 0.13397 RPN score loss: 0.00916 RPN total loss: 0.14313 Total loss: 1.35685 timestamp: 1654935558.5143976 iteration: 26715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1036 FastRCNN class loss: 0.07773 FastRCNN total loss: 0.18133 L1 loss: 0.0000e+00 L2 loss: 0.90524 Learning rate: 0.02 Mask loss: 0.13149 RPN box loss: 0.04368 RPN score loss: 0.00291 RPN total loss: 0.04659 Total loss: 1.26465 timestamp: 1654935561.730217 iteration: 26720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10804 FastRCNN class loss: 0.09642 FastRCNN total loss: 0.20447 L1 loss: 0.0000e+00 L2 loss: 0.9051 Learning rate: 0.02 Mask loss: 0.1342 RPN box loss: 0.09568 RPN score loss: 0.00452 RPN total loss: 0.1002 Total loss: 1.34397 timestamp: 1654935565.0118217 iteration: 26725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1288 FastRCNN class loss: 0.08269 FastRCNN total loss: 0.21149 L1 loss: 0.0000e+00 L2 loss: 0.90493 Learning rate: 0.02 Mask loss: 0.17492 RPN box loss: 0.03203 RPN score loss: 0.0086 RPN total loss: 0.04063 Total loss: 1.33196 timestamp: 1654935568.2217596 iteration: 26730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1958 FastRCNN class loss: 0.16285 FastRCNN total loss: 0.35865 L1 loss: 0.0000e+00 L2 loss: 0.90479 Learning rate: 0.02 Mask loss: 0.25217 RPN box loss: 0.03967 RPN score loss: 0.01061 RPN total loss: 0.05027 Total loss: 1.56589 timestamp: 1654935571.3905134 iteration: 26735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08633 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.15731 L1 loss: 0.0000e+00 L2 loss: 0.90469 Learning rate: 0.02 Mask loss: 0.07614 RPN box loss: 0.03914 RPN score loss: 0.00546 RPN total loss: 0.0446 Total loss: 1.18273 timestamp: 1654935574.5468807 iteration: 26740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11374 FastRCNN class loss: 0.1163 FastRCNN total loss: 0.23003 L1 loss: 0.0000e+00 L2 loss: 0.90456 Learning rate: 0.02 Mask loss: 0.22309 RPN box loss: 0.03982 RPN score loss: 0.00461 RPN total loss: 0.04443 Total loss: 1.40212 timestamp: 1654935577.7511218 iteration: 26745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11594 FastRCNN class loss: 0.04353 FastRCNN total loss: 0.15947 L1 loss: 0.0000e+00 L2 loss: 0.9044 Learning rate: 0.02 Mask loss: 0.09132 RPN box loss: 0.03608 RPN score loss: 0.00432 RPN total loss: 0.0404 Total loss: 1.19559 timestamp: 1654935580.9919193 iteration: 26750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2011 FastRCNN class loss: 0.13265 FastRCNN total loss: 0.33375 L1 loss: 0.0000e+00 L2 loss: 0.90426 Learning rate: 0.02 Mask loss: 0.16147 RPN box loss: 0.01592 RPN score loss: 0.00391 RPN total loss: 0.01984 Total loss: 1.41932 timestamp: 1654935584.213265 iteration: 26755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12285 FastRCNN class loss: 0.07847 FastRCNN total loss: 0.20132 L1 loss: 0.0000e+00 L2 loss: 0.90414 Learning rate: 0.02 Mask loss: 0.12507 RPN box loss: 0.03418 RPN score loss: 0.00632 RPN total loss: 0.0405 Total loss: 1.27102 timestamp: 1654935587.4767292 iteration: 26760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11658 FastRCNN class loss: 0.04677 FastRCNN total loss: 0.16334 L1 loss: 0.0000e+00 L2 loss: 0.90401 Learning rate: 0.02 Mask loss: 0.11185 RPN box loss: 0.04589 RPN score loss: 0.00305 RPN total loss: 0.04893 Total loss: 1.22813 timestamp: 1654935590.6405005 iteration: 26765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1508 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.22461 L1 loss: 0.0000e+00 L2 loss: 0.90387 Learning rate: 0.02 Mask loss: 0.14343 RPN box loss: 0.03429 RPN score loss: 0.00677 RPN total loss: 0.04106 Total loss: 1.31297 timestamp: 1654935593.906452 iteration: 26770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12116 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.20026 L1 loss: 0.0000e+00 L2 loss: 0.90374 Learning rate: 0.02 Mask loss: 0.14567 RPN box loss: 0.03668 RPN score loss: 0.00762 RPN total loss: 0.0443 Total loss: 1.29397 timestamp: 1654935597.1364708 iteration: 26775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09609 FastRCNN class loss: 0.08816 FastRCNN total loss: 0.18425 L1 loss: 0.0000e+00 L2 loss: 0.90362 Learning rate: 0.02 Mask loss: 0.16111 RPN box loss: 0.01315 RPN score loss: 0.00495 RPN total loss: 0.0181 Total loss: 1.26709 timestamp: 1654935600.4007554 iteration: 26780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06189 FastRCNN class loss: 0.04432 FastRCNN total loss: 0.10621 L1 loss: 0.0000e+00 L2 loss: 0.90349 Learning rate: 0.02 Mask loss: 0.24598 RPN box loss: 0.03712 RPN score loss: 0.00435 RPN total loss: 0.04148 Total loss: 1.29717 timestamp: 1654935603.6710448 iteration: 26785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11776 FastRCNN class loss: 0.11675 FastRCNN total loss: 0.23451 L1 loss: 0.0000e+00 L2 loss: 0.90336 Learning rate: 0.02 Mask loss: 0.08818 RPN box loss: 0.01856 RPN score loss: 0.00538 RPN total loss: 0.02394 Total loss: 1.24999 timestamp: 1654935606.8777952 iteration: 26790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1501 FastRCNN class loss: 0.07695 FastRCNN total loss: 0.22705 L1 loss: 0.0000e+00 L2 loss: 0.90325 Learning rate: 0.02 Mask loss: 0.1281 RPN box loss: 0.00974 RPN score loss: 0.00694 RPN total loss: 0.01668 Total loss: 1.27508 timestamp: 1654935610.1521106 iteration: 26795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14225 FastRCNN class loss: 0.10204 FastRCNN total loss: 0.24429 L1 loss: 0.0000e+00 L2 loss: 0.90313 Learning rate: 0.02 Mask loss: 0.15529 RPN box loss: 0.03641 RPN score loss: 0.0075 RPN total loss: 0.04391 Total loss: 1.34661 timestamp: 1654935613.287914 iteration: 26800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09313 FastRCNN class loss: 0.05213 FastRCNN total loss: 0.14526 L1 loss: 0.0000e+00 L2 loss: 0.90297 Learning rate: 0.02 Mask loss: 0.14325 RPN box loss: 0.02021 RPN score loss: 0.00571 RPN total loss: 0.02592 Total loss: 1.2174 timestamp: 1654935616.5021985 iteration: 26805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14591 FastRCNN class loss: 0.06602 FastRCNN total loss: 0.21193 L1 loss: 0.0000e+00 L2 loss: 0.90282 Learning rate: 0.02 Mask loss: 0.14816 RPN box loss: 0.02726 RPN score loss: 0.00187 RPN total loss: 0.02914 Total loss: 1.29205 timestamp: 1654935619.753678 iteration: 26810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07694 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.13199 L1 loss: 0.0000e+00 L2 loss: 0.90268 Learning rate: 0.02 Mask loss: 0.14327 RPN box loss: 0.02646 RPN score loss: 0.00285 RPN total loss: 0.02932 Total loss: 1.20727 timestamp: 1654935622.9483738 iteration: 26815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10794 FastRCNN class loss: 0.09149 FastRCNN total loss: 0.19943 L1 loss: 0.0000e+00 L2 loss: 0.90257 Learning rate: 0.02 Mask loss: 0.18311 RPN box loss: 0.01967 RPN score loss: 0.00672 RPN total loss: 0.02639 Total loss: 1.3115 timestamp: 1654935626.1784933 iteration: 26820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1365 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.20666 L1 loss: 0.0000e+00 L2 loss: 0.90243 Learning rate: 0.02 Mask loss: 0.10768 RPN box loss: 0.00974 RPN score loss: 0.00291 RPN total loss: 0.01265 Total loss: 1.22942 timestamp: 1654935629.3689501 iteration: 26825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14626 FastRCNN class loss: 0.078 FastRCNN total loss: 0.22426 L1 loss: 0.0000e+00 L2 loss: 0.90232 Learning rate: 0.02 Mask loss: 0.15796 RPN box loss: 0.03207 RPN score loss: 0.00517 RPN total loss: 0.03724 Total loss: 1.32178 timestamp: 1654935632.620144 iteration: 26830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12893 FastRCNN class loss: 0.11435 FastRCNN total loss: 0.24328 L1 loss: 0.0000e+00 L2 loss: 0.90218 Learning rate: 0.02 Mask loss: 0.12605 RPN box loss: 0.01995 RPN score loss: 0.00483 RPN total loss: 0.02478 Total loss: 1.29628 timestamp: 1654935635.8302412 iteration: 26835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14886 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.23869 L1 loss: 0.0000e+00 L2 loss: 0.90204 Learning rate: 0.02 Mask loss: 0.14623 RPN box loss: 0.06086 RPN score loss: 0.01071 RPN total loss: 0.07157 Total loss: 1.35854 timestamp: 1654935639.0097122 iteration: 26840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11386 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.19637 L1 loss: 0.0000e+00 L2 loss: 0.9019 Learning rate: 0.02 Mask loss: 0.19034 RPN box loss: 0.03671 RPN score loss: 0.00419 RPN total loss: 0.0409 Total loss: 1.32951 timestamp: 1654935642.2836921 iteration: 26845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12505 FastRCNN class loss: 0.08327 FastRCNN total loss: 0.20832 L1 loss: 0.0000e+00 L2 loss: 0.90175 Learning rate: 0.02 Mask loss: 0.12237 RPN box loss: 0.01445 RPN score loss: 0.00424 RPN total loss: 0.01869 Total loss: 1.25112 timestamp: 1654935645.4548275 iteration: 26850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10633 FastRCNN class loss: 0.0534 FastRCNN total loss: 0.15972 L1 loss: 0.0000e+00 L2 loss: 0.90161 Learning rate: 0.02 Mask loss: 0.1118 RPN box loss: 0.00643 RPN score loss: 0.00322 RPN total loss: 0.00965 Total loss: 1.18279 timestamp: 1654935648.7048824 iteration: 26855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10115 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.14902 L1 loss: 0.0000e+00 L2 loss: 0.90147 Learning rate: 0.02 Mask loss: 0.17804 RPN box loss: 0.03309 RPN score loss: 0.00567 RPN total loss: 0.03876 Total loss: 1.26729 timestamp: 1654935651.878381 iteration: 26860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10435 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.18641 L1 loss: 0.0000e+00 L2 loss: 0.90131 Learning rate: 0.02 Mask loss: 0.13652 RPN box loss: 0.01902 RPN score loss: 0.00234 RPN total loss: 0.02137 Total loss: 1.24561 timestamp: 1654935655.0584044 iteration: 26865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17887 FastRCNN class loss: 0.10293 FastRCNN total loss: 0.2818 L1 loss: 0.0000e+00 L2 loss: 0.90118 Learning rate: 0.02 Mask loss: 0.20102 RPN box loss: 0.0161 RPN score loss: 0.00969 RPN total loss: 0.02579 Total loss: 1.40978 timestamp: 1654935658.2780938 iteration: 26870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12682 FastRCNN class loss: 0.05875 FastRCNN total loss: 0.18557 L1 loss: 0.0000e+00 L2 loss: 0.90108 Learning rate: 0.02 Mask loss: 0.18284 RPN box loss: 0.01433 RPN score loss: 0.00431 RPN total loss: 0.01864 Total loss: 1.28812 timestamp: 1654935661.5145185 iteration: 26875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07846 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.12697 L1 loss: 0.0000e+00 L2 loss: 0.90094 Learning rate: 0.02 Mask loss: 0.13189 RPN box loss: 0.01594 RPN score loss: 0.00157 RPN total loss: 0.01752 Total loss: 1.17731 timestamp: 1654935664.7449114 iteration: 26880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14217 FastRCNN class loss: 0.0864 FastRCNN total loss: 0.22857 L1 loss: 0.0000e+00 L2 loss: 0.90081 Learning rate: 0.02 Mask loss: 0.13407 RPN box loss: 0.02652 RPN score loss: 0.00651 RPN total loss: 0.03303 Total loss: 1.29647 timestamp: 1654935667.8707087 iteration: 26885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1143 FastRCNN class loss: 0.05978 FastRCNN total loss: 0.17408 L1 loss: 0.0000e+00 L2 loss: 0.90068 Learning rate: 0.02 Mask loss: 0.13611 RPN box loss: 0.0216 RPN score loss: 0.00635 RPN total loss: 0.02795 Total loss: 1.23882 timestamp: 1654935671.0458834 iteration: 26890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16277 FastRCNN class loss: 0.08956 FastRCNN total loss: 0.25234 L1 loss: 0.0000e+00 L2 loss: 0.90055 Learning rate: 0.02 Mask loss: 0.1559 RPN box loss: 0.03143 RPN score loss: 0.00979 RPN total loss: 0.04122 Total loss: 1.35001 timestamp: 1654935674.276472 iteration: 26895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11848 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.20078 L1 loss: 0.0000e+00 L2 loss: 0.90042 Learning rate: 0.02 Mask loss: 0.15132 RPN box loss: 0.08085 RPN score loss: 0.00844 RPN total loss: 0.08929 Total loss: 1.34181 timestamp: 1654935677.5095804 iteration: 26900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17808 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.25227 L1 loss: 0.0000e+00 L2 loss: 0.90029 Learning rate: 0.02 Mask loss: 0.1619 RPN box loss: 0.05237 RPN score loss: 0.02069 RPN total loss: 0.07306 Total loss: 1.38752 timestamp: 1654935680.7577515 iteration: 26905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11368 FastRCNN class loss: 0.07287 FastRCNN total loss: 0.18656 L1 loss: 0.0000e+00 L2 loss: 0.90016 Learning rate: 0.02 Mask loss: 0.09845 RPN box loss: 0.02348 RPN score loss: 0.00283 RPN total loss: 0.02631 Total loss: 1.21147 timestamp: 1654935684.014107 iteration: 26910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.08624 FastRCNN total loss: 0.20094 L1 loss: 0.0000e+00 L2 loss: 0.90001 Learning rate: 0.02 Mask loss: 0.12217 RPN box loss: 0.00975 RPN score loss: 0.00554 RPN total loss: 0.0153 Total loss: 1.23841 timestamp: 1654935687.2416272 iteration: 26915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16826 FastRCNN class loss: 0.12158 FastRCNN total loss: 0.28984 L1 loss: 0.0000e+00 L2 loss: 0.89986 Learning rate: 0.02 Mask loss: 0.19399 RPN box loss: 0.03098 RPN score loss: 0.0097 RPN total loss: 0.04068 Total loss: 1.42437 timestamp: 1654935690.452899 iteration: 26920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11598 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.18167 L1 loss: 0.0000e+00 L2 loss: 0.89973 Learning rate: 0.02 Mask loss: 0.1432 RPN box loss: 0.0199 RPN score loss: 0.01023 RPN total loss: 0.03013 Total loss: 1.25473 timestamp: 1654935693.7074387 iteration: 26925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10009 FastRCNN class loss: 0.06216 FastRCNN total loss: 0.16225 L1 loss: 0.0000e+00 L2 loss: 0.8996 Learning rate: 0.02 Mask loss: 0.15079 RPN box loss: 0.01092 RPN score loss: 0.00465 RPN total loss: 0.01557 Total loss: 1.22821 timestamp: 1654935696.9249108 iteration: 26930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15767 FastRCNN class loss: 0.11699 FastRCNN total loss: 0.27466 L1 loss: 0.0000e+00 L2 loss: 0.89945 Learning rate: 0.02 Mask loss: 0.23455 RPN box loss: 0.01697 RPN score loss: 0.00535 RPN total loss: 0.02232 Total loss: 1.43098 timestamp: 1654935700.1086934 iteration: 26935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11771 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.17219 L1 loss: 0.0000e+00 L2 loss: 0.89932 Learning rate: 0.02 Mask loss: 0.095 RPN box loss: 0.02067 RPN score loss: 0.00205 RPN total loss: 0.02272 Total loss: 1.18923 timestamp: 1654935703.2677603 iteration: 26940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14065 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.20791 L1 loss: 0.0000e+00 L2 loss: 0.89923 Learning rate: 0.02 Mask loss: 0.18241 RPN box loss: 0.05413 RPN score loss: 0.01184 RPN total loss: 0.06597 Total loss: 1.35551 timestamp: 1654935706.4090643 iteration: 26945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15098 FastRCNN class loss: 0.07654 FastRCNN total loss: 0.22752 L1 loss: 0.0000e+00 L2 loss: 0.89908 Learning rate: 0.02 Mask loss: 0.18031 RPN box loss: 0.16066 RPN score loss: 0.01569 RPN total loss: 0.17635 Total loss: 1.48327 timestamp: 1654935709.6951232 iteration: 26950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15488 FastRCNN class loss: 0.10102 FastRCNN total loss: 0.25591 L1 loss: 0.0000e+00 L2 loss: 0.89895 Learning rate: 0.02 Mask loss: 0.2052 RPN box loss: 0.01091 RPN score loss: 0.0045 RPN total loss: 0.01541 Total loss: 1.37546 timestamp: 1654935712.9636834 iteration: 26955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07444 FastRCNN class loss: 0.09603 FastRCNN total loss: 0.17047 L1 loss: 0.0000e+00 L2 loss: 0.89881 Learning rate: 0.02 Mask loss: 0.18066 RPN box loss: 0.01525 RPN score loss: 0.00755 RPN total loss: 0.0228 Total loss: 1.27273 timestamp: 1654935716.1490993 iteration: 26960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23496 FastRCNN class loss: 0.08378 FastRCNN total loss: 0.31874 L1 loss: 0.0000e+00 L2 loss: 0.89866 Learning rate: 0.02 Mask loss: 0.13878 RPN box loss: 0.02015 RPN score loss: 0.01384 RPN total loss: 0.03398 Total loss: 1.39017 timestamp: 1654935719.3943517 iteration: 26965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19103 FastRCNN class loss: 0.11382 FastRCNN total loss: 0.30485 L1 loss: 0.0000e+00 L2 loss: 0.89855 Learning rate: 0.02 Mask loss: 0.17618 RPN box loss: 0.04328 RPN score loss: 0.01376 RPN total loss: 0.05704 Total loss: 1.43662 timestamp: 1654935722.5890098 iteration: 26970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14167 FastRCNN class loss: 0.13538 FastRCNN total loss: 0.27705 L1 loss: 0.0000e+00 L2 loss: 0.89841 Learning rate: 0.02 Mask loss: 0.20539 RPN box loss: 0.0165 RPN score loss: 0.00411 RPN total loss: 0.02062 Total loss: 1.40148 timestamp: 1654935725.8721893 iteration: 26975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15131 FastRCNN class loss: 0.08818 FastRCNN total loss: 0.2395 L1 loss: 0.0000e+00 L2 loss: 0.89829 Learning rate: 0.02 Mask loss: 0.21248 RPN box loss: 0.01129 RPN score loss: 0.00757 RPN total loss: 0.01887 Total loss: 1.36913 timestamp: 1654935729.1380606 iteration: 26980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16905 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.24018 L1 loss: 0.0000e+00 L2 loss: 0.89814 Learning rate: 0.02 Mask loss: 0.14552 RPN box loss: 0.04119 RPN score loss: 0.00727 RPN total loss: 0.04846 Total loss: 1.3323 timestamp: 1654935732.3143198 iteration: 26985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1408 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.20883 L1 loss: 0.0000e+00 L2 loss: 0.89801 Learning rate: 0.02 Mask loss: 0.14347 RPN box loss: 0.02624 RPN score loss: 0.00649 RPN total loss: 0.03273 Total loss: 1.28305 timestamp: 1654935735.5251935 iteration: 26990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1024 FastRCNN class loss: 0.05587 FastRCNN total loss: 0.15828 L1 loss: 0.0000e+00 L2 loss: 0.89787 Learning rate: 0.02 Mask loss: 0.13052 RPN box loss: 0.02307 RPN score loss: 0.00229 RPN total loss: 0.02536 Total loss: 1.21203 timestamp: 1654935738.775576 iteration: 26995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19923 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.25573 L1 loss: 0.0000e+00 L2 loss: 0.89776 Learning rate: 0.02 Mask loss: 0.14901 RPN box loss: 0.03229 RPN score loss: 0.00408 RPN total loss: 0.03637 Total loss: 1.33886 timestamp: 1654935741.93867 iteration: 27000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.10285 FastRCNN total loss: 0.2463 L1 loss: 0.0000e+00 L2 loss: 0.89764 Learning rate: 0.02 Mask loss: 0.11969 RPN box loss: 0.01335 RPN score loss: 0.00347 RPN total loss: 0.01682 Total loss: 1.28045 timestamp: 1654935745.1605077 iteration: 27005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07507 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.1367 L1 loss: 0.0000e+00 L2 loss: 0.89749 Learning rate: 0.02 Mask loss: 0.13916 RPN box loss: 0.03201 RPN score loss: 0.00724 RPN total loss: 0.03925 Total loss: 1.21262 timestamp: 1654935748.3781657 iteration: 27010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12068 FastRCNN class loss: 0.07395 FastRCNN total loss: 0.19463 L1 loss: 0.0000e+00 L2 loss: 0.89734 Learning rate: 0.02 Mask loss: 0.15107 RPN box loss: 0.03852 RPN score loss: 0.00385 RPN total loss: 0.04237 Total loss: 1.28541 timestamp: 1654935751.535826 iteration: 27015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17827 FastRCNN class loss: 0.06101 FastRCNN total loss: 0.23928 L1 loss: 0.0000e+00 L2 loss: 0.89718 Learning rate: 0.02 Mask loss: 0.09334 RPN box loss: 0.03211 RPN score loss: 0.00455 RPN total loss: 0.03666 Total loss: 1.26646 timestamp: 1654935754.7737534 iteration: 27020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05603 FastRCNN class loss: 0.04557 FastRCNN total loss: 0.10161 L1 loss: 0.0000e+00 L2 loss: 0.89705 Learning rate: 0.02 Mask loss: 0.12373 RPN box loss: 0.0557 RPN score loss: 0.0033 RPN total loss: 0.059 Total loss: 1.18139 timestamp: 1654935757.9962153 iteration: 27025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13868 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.19664 L1 loss: 0.0000e+00 L2 loss: 0.89693 Learning rate: 0.02 Mask loss: 0.08395 RPN box loss: 0.00765 RPN score loss: 0.00233 RPN total loss: 0.00998 Total loss: 1.18749 timestamp: 1654935761.2451618 iteration: 27030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15589 FastRCNN class loss: 0.08121 FastRCNN total loss: 0.2371 L1 loss: 0.0000e+00 L2 loss: 0.89681 Learning rate: 0.02 Mask loss: 0.12017 RPN box loss: 0.01235 RPN score loss: 0.00291 RPN total loss: 0.01526 Total loss: 1.26934 timestamp: 1654935764.4268603 iteration: 27035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16667 FastRCNN class loss: 0.11638 FastRCNN total loss: 0.28305 L1 loss: 0.0000e+00 L2 loss: 0.89669 Learning rate: 0.02 Mask loss: 0.16809 RPN box loss: 0.04951 RPN score loss: 0.00502 RPN total loss: 0.05453 Total loss: 1.40236 timestamp: 1654935767.6153276 iteration: 27040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20284 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.27624 L1 loss: 0.0000e+00 L2 loss: 0.89653 Learning rate: 0.02 Mask loss: 0.14841 RPN box loss: 0.0188 RPN score loss: 0.00611 RPN total loss: 0.0249 Total loss: 1.34608 timestamp: 1654935770.8792322 iteration: 27045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15013 FastRCNN class loss: 0.12877 FastRCNN total loss: 0.2789 L1 loss: 0.0000e+00 L2 loss: 0.89638 Learning rate: 0.02 Mask loss: 0.26143 RPN box loss: 0.01192 RPN score loss: 0.01075 RPN total loss: 0.02267 Total loss: 1.45938 timestamp: 1654935773.9598813 iteration: 27050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14814 FastRCNN class loss: 0.10518 FastRCNN total loss: 0.25332 L1 loss: 0.0000e+00 L2 loss: 0.89622 Learning rate: 0.02 Mask loss: 0.16378 RPN box loss: 0.02899 RPN score loss: 0.00802 RPN total loss: 0.03701 Total loss: 1.35033 timestamp: 1654935777.1228616 iteration: 27055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.22271 L1 loss: 0.0000e+00 L2 loss: 0.8961 Learning rate: 0.02 Mask loss: 0.14945 RPN box loss: 0.02784 RPN score loss: 0.00406 RPN total loss: 0.0319 Total loss: 1.30016 timestamp: 1654935780.36203 iteration: 27060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11919 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.2025 L1 loss: 0.0000e+00 L2 loss: 0.896 Learning rate: 0.02 Mask loss: 0.1717 RPN box loss: 0.02866 RPN score loss: 0.00865 RPN total loss: 0.0373 Total loss: 1.30751 timestamp: 1654935783.5455356 iteration: 27065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07572 FastRCNN class loss: 0.06836 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.89588 Learning rate: 0.02 Mask loss: 0.1553 RPN box loss: 0.01113 RPN score loss: 0.00488 RPN total loss: 0.01601 Total loss: 1.21127 timestamp: 1654935786.7186897 iteration: 27070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16099 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.23716 L1 loss: 0.0000e+00 L2 loss: 0.89574 Learning rate: 0.02 Mask loss: 0.1974 RPN box loss: 0.01973 RPN score loss: 0.00335 RPN total loss: 0.02307 Total loss: 1.35337 timestamp: 1654935789.806926 iteration: 27075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14788 FastRCNN class loss: 0.05687 FastRCNN total loss: 0.20475 L1 loss: 0.0000e+00 L2 loss: 0.8956 Learning rate: 0.02 Mask loss: 0.19292 RPN box loss: 0.02793 RPN score loss: 0.00262 RPN total loss: 0.03055 Total loss: 1.32382 timestamp: 1654935792.9340982 iteration: 27080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10706 FastRCNN class loss: 0.05372 FastRCNN total loss: 0.16078 L1 loss: 0.0000e+00 L2 loss: 0.89545 Learning rate: 0.02 Mask loss: 0.1635 RPN box loss: 0.01149 RPN score loss: 0.00462 RPN total loss: 0.01611 Total loss: 1.23583 timestamp: 1654935796.1745577 iteration: 27085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20337 FastRCNN class loss: 0.17595 FastRCNN total loss: 0.37931 L1 loss: 0.0000e+00 L2 loss: 0.89532 Learning rate: 0.02 Mask loss: 0.21831 RPN box loss: 0.02374 RPN score loss: 0.00442 RPN total loss: 0.02816 Total loss: 1.5211 timestamp: 1654935799.4522161 iteration: 27090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16129 FastRCNN class loss: 0.08864 FastRCNN total loss: 0.24993 L1 loss: 0.0000e+00 L2 loss: 0.89518 Learning rate: 0.02 Mask loss: 0.13441 RPN box loss: 0.03906 RPN score loss: 0.00442 RPN total loss: 0.04347 Total loss: 1.323 timestamp: 1654935802.5873427 iteration: 27095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09865 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.16949 L1 loss: 0.0000e+00 L2 loss: 0.89505 Learning rate: 0.02 Mask loss: 0.14254 RPN box loss: 0.03766 RPN score loss: 0.00705 RPN total loss: 0.04471 Total loss: 1.25179 timestamp: 1654935805.7632525 iteration: 27100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0922 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.15848 L1 loss: 0.0000e+00 L2 loss: 0.8949 Learning rate: 0.02 Mask loss: 0.18998 RPN box loss: 0.06654 RPN score loss: 0.01527 RPN total loss: 0.08181 Total loss: 1.32517 timestamp: 1654935808.9840243 iteration: 27105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05677 FastRCNN class loss: 0.04727 FastRCNN total loss: 0.10405 L1 loss: 0.0000e+00 L2 loss: 0.89475 Learning rate: 0.02 Mask loss: 0.15194 RPN box loss: 0.0106 RPN score loss: 0.00384 RPN total loss: 0.01444 Total loss: 1.16518 timestamp: 1654935812.1980374 iteration: 27110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06937 FastRCNN class loss: 0.04387 FastRCNN total loss: 0.11323 L1 loss: 0.0000e+00 L2 loss: 0.89459 Learning rate: 0.02 Mask loss: 0.09918 RPN box loss: 0.00336 RPN score loss: 0.00195 RPN total loss: 0.00531 Total loss: 1.11232 timestamp: 1654935815.4 iteration: 27115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17534 FastRCNN class loss: 0.08081 FastRCNN total loss: 0.25615 L1 loss: 0.0000e+00 L2 loss: 0.89448 Learning rate: 0.02 Mask loss: 0.12738 RPN box loss: 0.01556 RPN score loss: 0.00174 RPN total loss: 0.0173 Total loss: 1.29531 timestamp: 1654935818.6185517 iteration: 27120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14367 FastRCNN class loss: 0.10333 FastRCNN total loss: 0.247 L1 loss: 0.0000e+00 L2 loss: 0.89436 Learning rate: 0.02 Mask loss: 0.13824 RPN box loss: 0.03894 RPN score loss: 0.01082 RPN total loss: 0.04976 Total loss: 1.32936 timestamp: 1654935821.8539488 iteration: 27125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12858 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.21221 L1 loss: 0.0000e+00 L2 loss: 0.89423 Learning rate: 0.02 Mask loss: 0.16197 RPN box loss: 0.02401 RPN score loss: 0.00916 RPN total loss: 0.03317 Total loss: 1.30158 timestamp: 1654935825.1321223 iteration: 27130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16988 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.24231 L1 loss: 0.0000e+00 L2 loss: 0.89412 Learning rate: 0.02 Mask loss: 0.14317 RPN box loss: 0.01465 RPN score loss: 0.00337 RPN total loss: 0.01802 Total loss: 1.29762 timestamp: 1654935828.3831346 iteration: 27135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15037 FastRCNN class loss: 0.11679 FastRCNN total loss: 0.26715 L1 loss: 0.0000e+00 L2 loss: 0.89398 Learning rate: 0.02 Mask loss: 0.12402 RPN box loss: 0.08815 RPN score loss: 0.00901 RPN total loss: 0.09716 Total loss: 1.38231 timestamp: 1654935831.5357008 iteration: 27140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14779 FastRCNN class loss: 0.08656 FastRCNN total loss: 0.23435 L1 loss: 0.0000e+00 L2 loss: 0.89383 Learning rate: 0.02 Mask loss: 0.14857 RPN box loss: 0.02721 RPN score loss: 0.00383 RPN total loss: 0.03103 Total loss: 1.30778 timestamp: 1654935834.6952744 iteration: 27145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16599 FastRCNN class loss: 0.11117 FastRCNN total loss: 0.27716 L1 loss: 0.0000e+00 L2 loss: 0.89368 Learning rate: 0.02 Mask loss: 0.19156 RPN box loss: 0.02974 RPN score loss: 0.00586 RPN total loss: 0.0356 Total loss: 1.39801 timestamp: 1654935837.8993084 iteration: 27150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11414 FastRCNN class loss: 0.06275 FastRCNN total loss: 0.17689 L1 loss: 0.0000e+00 L2 loss: 0.89354 Learning rate: 0.02 Mask loss: 0.13009 RPN box loss: 0.04326 RPN score loss: 0.00253 RPN total loss: 0.04579 Total loss: 1.24631 timestamp: 1654935841.0557678 iteration: 27155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.151 FastRCNN class loss: 0.1179 FastRCNN total loss: 0.2689 L1 loss: 0.0000e+00 L2 loss: 0.89339 Learning rate: 0.02 Mask loss: 0.1459 RPN box loss: 0.00768 RPN score loss: 0.00327 RPN total loss: 0.01094 Total loss: 1.31913 timestamp: 1654935844.2689059 iteration: 27160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16877 FastRCNN class loss: 0.1875 FastRCNN total loss: 0.35628 L1 loss: 0.0000e+00 L2 loss: 0.89325 Learning rate: 0.02 Mask loss: 0.20011 RPN box loss: 0.02703 RPN score loss: 0.00701 RPN total loss: 0.03403 Total loss: 1.48367 timestamp: 1654935847.5404022 iteration: 27165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13302 FastRCNN class loss: 0.07781 FastRCNN total loss: 0.21083 L1 loss: 0.0000e+00 L2 loss: 0.89312 Learning rate: 0.02 Mask loss: 0.1646 RPN box loss: 0.02155 RPN score loss: 0.00527 RPN total loss: 0.02682 Total loss: 1.29536 timestamp: 1654935850.7083397 iteration: 27170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13901 FastRCNN class loss: 0.09777 FastRCNN total loss: 0.23678 L1 loss: 0.0000e+00 L2 loss: 0.89297 Learning rate: 0.02 Mask loss: 0.17362 RPN box loss: 0.016 RPN score loss: 0.00541 RPN total loss: 0.0214 Total loss: 1.32477 timestamp: 1654935853.9147542 iteration: 27175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14719 FastRCNN class loss: 0.11891 FastRCNN total loss: 0.2661 L1 loss: 0.0000e+00 L2 loss: 0.89283 Learning rate: 0.02 Mask loss: 0.17842 RPN box loss: 0.03623 RPN score loss: 0.00784 RPN total loss: 0.04408 Total loss: 1.38142 timestamp: 1654935857.0457773 iteration: 27180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12088 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.21352 L1 loss: 0.0000e+00 L2 loss: 0.89271 Learning rate: 0.02 Mask loss: 0.12356 RPN box loss: 0.03794 RPN score loss: 0.00416 RPN total loss: 0.0421 Total loss: 1.27189 timestamp: 1654935860.260931 iteration: 27185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15301 FastRCNN class loss: 0.12813 FastRCNN total loss: 0.28114 L1 loss: 0.0000e+00 L2 loss: 0.89259 Learning rate: 0.02 Mask loss: 0.16279 RPN box loss: 0.01335 RPN score loss: 0.00344 RPN total loss: 0.01679 Total loss: 1.35332 timestamp: 1654935863.4381745 iteration: 27190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13151 FastRCNN class loss: 0.09814 FastRCNN total loss: 0.22965 L1 loss: 0.0000e+00 L2 loss: 0.89246 Learning rate: 0.02 Mask loss: 0.11303 RPN box loss: 0.00969 RPN score loss: 0.00577 RPN total loss: 0.01547 Total loss: 1.25061 timestamp: 1654935866.7095928 iteration: 27195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18908 FastRCNN class loss: 0.08261 FastRCNN total loss: 0.27169 L1 loss: 0.0000e+00 L2 loss: 0.89232 Learning rate: 0.02 Mask loss: 0.19969 RPN box loss: 0.02848 RPN score loss: 0.01274 RPN total loss: 0.04121 Total loss: 1.40491 timestamp: 1654935869.8339798 iteration: 27200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13039 FastRCNN class loss: 0.0979 FastRCNN total loss: 0.22829 L1 loss: 0.0000e+00 L2 loss: 0.89219 Learning rate: 0.02 Mask loss: 0.21161 RPN box loss: 0.01793 RPN score loss: 0.00365 RPN total loss: 0.02158 Total loss: 1.35366 timestamp: 1654935873.056577 iteration: 27205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11602 FastRCNN class loss: 0.14499 FastRCNN total loss: 0.26101 L1 loss: 0.0000e+00 L2 loss: 0.89208 Learning rate: 0.02 Mask loss: 0.10907 RPN box loss: 0.02085 RPN score loss: 0.00363 RPN total loss: 0.02448 Total loss: 1.28664 timestamp: 1654935876.2112463 iteration: 27210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13877 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.22589 L1 loss: 0.0000e+00 L2 loss: 0.89195 Learning rate: 0.02 Mask loss: 0.1465 RPN box loss: 0.04943 RPN score loss: 0.00265 RPN total loss: 0.05208 Total loss: 1.31642 timestamp: 1654935879.400099 iteration: 27215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.163 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.24567 L1 loss: 0.0000e+00 L2 loss: 0.89182 Learning rate: 0.02 Mask loss: 0.17733 RPN box loss: 0.06531 RPN score loss: 0.01366 RPN total loss: 0.07897 Total loss: 1.39377 timestamp: 1654935882.617578 iteration: 27220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11431 FastRCNN class loss: 0.07202 FastRCNN total loss: 0.18633 L1 loss: 0.0000e+00 L2 loss: 0.89165 Learning rate: 0.02 Mask loss: 0.35931 RPN box loss: 0.02094 RPN score loss: 0.00629 RPN total loss: 0.02723 Total loss: 1.46452 timestamp: 1654935885.8473527 iteration: 27225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1567 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.23628 L1 loss: 0.0000e+00 L2 loss: 0.89149 Learning rate: 0.02 Mask loss: 0.13531 RPN box loss: 0.01712 RPN score loss: 0.005 RPN total loss: 0.02212 Total loss: 1.2852 timestamp: 1654935888.9715462 iteration: 27230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24011 FastRCNN class loss: 0.12463 FastRCNN total loss: 0.36474 L1 loss: 0.0000e+00 L2 loss: 0.89137 Learning rate: 0.02 Mask loss: 0.30642 RPN box loss: 0.0379 RPN score loss: 0.00485 RPN total loss: 0.04274 Total loss: 1.60528 timestamp: 1654935892.1650445 iteration: 27235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14521 FastRCNN class loss: 0.07035 FastRCNN total loss: 0.21556 L1 loss: 0.0000e+00 L2 loss: 0.89123 Learning rate: 0.02 Mask loss: 0.1198 RPN box loss: 0.01327 RPN score loss: 0.00448 RPN total loss: 0.01775 Total loss: 1.24434 timestamp: 1654935895.4090688 iteration: 27240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16977 FastRCNN class loss: 0.18727 FastRCNN total loss: 0.35704 L1 loss: 0.0000e+00 L2 loss: 0.89111 Learning rate: 0.02 Mask loss: 0.23852 RPN box loss: 0.03343 RPN score loss: 0.00997 RPN total loss: 0.04339 Total loss: 1.53005 timestamp: 1654935898.6277661 iteration: 27245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1187 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.19094 L1 loss: 0.0000e+00 L2 loss: 0.89099 Learning rate: 0.02 Mask loss: 0.1209 RPN box loss: 0.02837 RPN score loss: 0.00906 RPN total loss: 0.03743 Total loss: 1.24026 timestamp: 1654935901.8616307 iteration: 27250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17923 FastRCNN class loss: 0.08171 FastRCNN total loss: 0.26094 L1 loss: 0.0000e+00 L2 loss: 0.89086 Learning rate: 0.02 Mask loss: 0.19118 RPN box loss: 0.03252 RPN score loss: 0.00217 RPN total loss: 0.03469 Total loss: 1.37767 timestamp: 1654935905.0792522 iteration: 27255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12272 FastRCNN class loss: 0.09698 FastRCNN total loss: 0.2197 L1 loss: 0.0000e+00 L2 loss: 0.89071 Learning rate: 0.02 Mask loss: 0.14763 RPN box loss: 0.01996 RPN score loss: 0.0107 RPN total loss: 0.03065 Total loss: 1.28869 timestamp: 1654935908.3118412 iteration: 27260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17159 FastRCNN class loss: 0.13212 FastRCNN total loss: 0.30371 L1 loss: 0.0000e+00 L2 loss: 0.89056 Learning rate: 0.02 Mask loss: 0.25274 RPN box loss: 0.05687 RPN score loss: 0.00792 RPN total loss: 0.06479 Total loss: 1.51179 timestamp: 1654935911.535222 iteration: 27265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08123 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.13411 L1 loss: 0.0000e+00 L2 loss: 0.89044 Learning rate: 0.02 Mask loss: 0.1035 RPN box loss: 0.01863 RPN score loss: 0.00293 RPN total loss: 0.02157 Total loss: 1.14962 timestamp: 1654935914.7324219 iteration: 27270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12527 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.20507 L1 loss: 0.0000e+00 L2 loss: 0.89031 Learning rate: 0.02 Mask loss: 0.17149 RPN box loss: 0.01925 RPN score loss: 0.00494 RPN total loss: 0.02419 Total loss: 1.29106 timestamp: 1654935918.0494738 iteration: 27275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12177 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.21524 L1 loss: 0.0000e+00 L2 loss: 0.89016 Learning rate: 0.02 Mask loss: 0.15695 RPN box loss: 0.02045 RPN score loss: 0.00418 RPN total loss: 0.02462 Total loss: 1.28697 timestamp: 1654935921.2641547 iteration: 27280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16411 FastRCNN class loss: 0.09747 FastRCNN total loss: 0.26158 L1 loss: 0.0000e+00 L2 loss: 0.89004 Learning rate: 0.02 Mask loss: 0.15181 RPN box loss: 0.05932 RPN score loss: 0.01629 RPN total loss: 0.07562 Total loss: 1.37904 timestamp: 1654935924.4923048 iteration: 27285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13896 FastRCNN class loss: 0.07459 FastRCNN total loss: 0.21355 L1 loss: 0.0000e+00 L2 loss: 0.88991 Learning rate: 0.02 Mask loss: 0.10409 RPN box loss: 0.01238 RPN score loss: 0.00223 RPN total loss: 0.01462 Total loss: 1.22217 timestamp: 1654935927.6733882 iteration: 27290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14356 FastRCNN class loss: 0.06494 FastRCNN total loss: 0.2085 L1 loss: 0.0000e+00 L2 loss: 0.88979 Learning rate: 0.02 Mask loss: 0.12555 RPN box loss: 0.02499 RPN score loss: 0.00367 RPN total loss: 0.02866 Total loss: 1.2525 timestamp: 1654935930.8831446 iteration: 27295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10591 FastRCNN class loss: 0.09663 FastRCNN total loss: 0.20254 L1 loss: 0.0000e+00 L2 loss: 0.88965 Learning rate: 0.02 Mask loss: 0.09217 RPN box loss: 0.0217 RPN score loss: 0.01011 RPN total loss: 0.03182 Total loss: 1.21618 timestamp: 1654935934.109027 iteration: 27300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17598 FastRCNN class loss: 0.09501 FastRCNN total loss: 0.27098 L1 loss: 0.0000e+00 L2 loss: 0.88948 Learning rate: 0.02 Mask loss: 0.17338 RPN box loss: 0.03674 RPN score loss: 0.00787 RPN total loss: 0.04461 Total loss: 1.37847 timestamp: 1654935937.3527136 iteration: 27305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16313 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.23595 L1 loss: 0.0000e+00 L2 loss: 0.88934 Learning rate: 0.02 Mask loss: 0.1228 RPN box loss: 0.0256 RPN score loss: 0.00487 RPN total loss: 0.03047 Total loss: 1.27856 timestamp: 1654935940.5831668 iteration: 27310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18387 FastRCNN class loss: 0.07949 FastRCNN total loss: 0.26336 L1 loss: 0.0000e+00 L2 loss: 0.88922 Learning rate: 0.02 Mask loss: 0.13748 RPN box loss: 0.03539 RPN score loss: 0.0049 RPN total loss: 0.04029 Total loss: 1.33035 timestamp: 1654935943.8403535 iteration: 27315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11925 FastRCNN class loss: 0.07251 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 0.8891 Learning rate: 0.02 Mask loss: 0.14316 RPN box loss: 0.01084 RPN score loss: 0.00275 RPN total loss: 0.01359 Total loss: 1.23762 timestamp: 1654935947.0458086 iteration: 27320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20518 FastRCNN class loss: 0.12039 FastRCNN total loss: 0.32557 L1 loss: 0.0000e+00 L2 loss: 0.88896 Learning rate: 0.02 Mask loss: 0.20688 RPN box loss: 0.03838 RPN score loss: 0.00516 RPN total loss: 0.04354 Total loss: 1.46494 timestamp: 1654935950.1976955 iteration: 27325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10972 FastRCNN class loss: 0.07973 FastRCNN total loss: 0.18946 L1 loss: 0.0000e+00 L2 loss: 0.88881 Learning rate: 0.02 Mask loss: 0.11432 RPN box loss: 0.03498 RPN score loss: 0.01264 RPN total loss: 0.04761 Total loss: 1.24019 timestamp: 1654935953.354445 iteration: 27330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18996 FastRCNN class loss: 0.1302 FastRCNN total loss: 0.32017 L1 loss: 0.0000e+00 L2 loss: 0.88866 Learning rate: 0.02 Mask loss: 0.18333 RPN box loss: 0.04552 RPN score loss: 0.02087 RPN total loss: 0.06639 Total loss: 1.45855 timestamp: 1654935956.5827506 iteration: 27335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07005 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.14249 L1 loss: 0.0000e+00 L2 loss: 0.88853 Learning rate: 0.02 Mask loss: 0.18206 RPN box loss: 0.02155 RPN score loss: 0.00378 RPN total loss: 0.02534 Total loss: 1.23842 timestamp: 1654935959.789564 iteration: 27340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11612 FastRCNN class loss: 0.07711 FastRCNN total loss: 0.19323 L1 loss: 0.0000e+00 L2 loss: 0.88839 Learning rate: 0.02 Mask loss: 0.12117 RPN box loss: 0.06644 RPN score loss: 0.00313 RPN total loss: 0.06958 Total loss: 1.27236 timestamp: 1654935962.9895434 iteration: 27345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11971 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.19317 L1 loss: 0.0000e+00 L2 loss: 0.88826 Learning rate: 0.02 Mask loss: 0.17858 RPN box loss: 0.01089 RPN score loss: 0.00366 RPN total loss: 0.01455 Total loss: 1.27455 timestamp: 1654935966.2475874 iteration: 27350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14017 FastRCNN class loss: 0.09832 FastRCNN total loss: 0.23849 L1 loss: 0.0000e+00 L2 loss: 0.88815 Learning rate: 0.02 Mask loss: 0.17914 RPN box loss: 0.0291 RPN score loss: 0.00661 RPN total loss: 0.03571 Total loss: 1.3415 timestamp: 1654935969.507328 iteration: 27355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15624 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.2299 L1 loss: 0.0000e+00 L2 loss: 0.88802 Learning rate: 0.02 Mask loss: 0.18177 RPN box loss: 0.04418 RPN score loss: 0.00992 RPN total loss: 0.05409 Total loss: 1.35378 timestamp: 1654935972.7346668 iteration: 27360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12901 FastRCNN class loss: 0.10439 FastRCNN total loss: 0.2334 L1 loss: 0.0000e+00 L2 loss: 0.88787 Learning rate: 0.02 Mask loss: 0.17225 RPN box loss: 0.03446 RPN score loss: 0.00531 RPN total loss: 0.03977 Total loss: 1.33328 timestamp: 1654935975.9199967 iteration: 27365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10281 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.15062 L1 loss: 0.0000e+00 L2 loss: 0.88774 Learning rate: 0.02 Mask loss: 0.1613 RPN box loss: 0.02121 RPN score loss: 0.00307 RPN total loss: 0.02428 Total loss: 1.22394 timestamp: 1654935979.1453466 iteration: 27370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17848 FastRCNN class loss: 0.11392 FastRCNN total loss: 0.2924 L1 loss: 0.0000e+00 L2 loss: 0.88762 Learning rate: 0.02 Mask loss: 0.15537 RPN box loss: 0.04744 RPN score loss: 0.00817 RPN total loss: 0.05561 Total loss: 1.391 timestamp: 1654935982.3456395 iteration: 27375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14945 FastRCNN class loss: 0.04188 FastRCNN total loss: 0.19133 L1 loss: 0.0000e+00 L2 loss: 0.88747 Learning rate: 0.02 Mask loss: 0.147 RPN box loss: 0.06049 RPN score loss: 0.02281 RPN total loss: 0.0833 Total loss: 1.30909 timestamp: 1654935985.5696084 iteration: 27380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12084 FastRCNN class loss: 0.12581 FastRCNN total loss: 0.24665 L1 loss: 0.0000e+00 L2 loss: 0.88734 Learning rate: 0.02 Mask loss: 0.20337 RPN box loss: 0.04709 RPN score loss: 0.01418 RPN total loss: 0.06127 Total loss: 1.39863 timestamp: 1654935988.7268925 iteration: 27385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09525 FastRCNN class loss: 0.0661 FastRCNN total loss: 0.16135 L1 loss: 0.0000e+00 L2 loss: 0.88723 Learning rate: 0.02 Mask loss: 0.13873 RPN box loss: 0.05093 RPN score loss: 0.01464 RPN total loss: 0.06556 Total loss: 1.25288 timestamp: 1654935991.9139082 iteration: 27390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08742 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.15182 L1 loss: 0.0000e+00 L2 loss: 0.88712 Learning rate: 0.02 Mask loss: 0.20308 RPN box loss: 0.02374 RPN score loss: 0.00456 RPN total loss: 0.0283 Total loss: 1.27033 timestamp: 1654935995.150718 iteration: 27395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.06768 FastRCNN total loss: 0.16861 L1 loss: 0.0000e+00 L2 loss: 0.887 Learning rate: 0.02 Mask loss: 0.17784 RPN box loss: 0.01079 RPN score loss: 0.00139 RPN total loss: 0.01218 Total loss: 1.24562 timestamp: 1654935998.3881786 iteration: 27400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16416 FastRCNN class loss: 0.07883 FastRCNN total loss: 0.24298 L1 loss: 0.0000e+00 L2 loss: 0.88686 Learning rate: 0.02 Mask loss: 0.16732 RPN box loss: 0.01437 RPN score loss: 0.01145 RPN total loss: 0.02581 Total loss: 1.32298 timestamp: 1654936001.5897968 iteration: 27405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11769 FastRCNN class loss: 0.09268 FastRCNN total loss: 0.21037 L1 loss: 0.0000e+00 L2 loss: 0.8867 Learning rate: 0.02 Mask loss: 0.13691 RPN box loss: 0.06599 RPN score loss: 0.01069 RPN total loss: 0.07668 Total loss: 1.31067 timestamp: 1654936004.7570493 iteration: 27410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12734 FastRCNN class loss: 0.09172 FastRCNN total loss: 0.21905 L1 loss: 0.0000e+00 L2 loss: 0.88656 Learning rate: 0.02 Mask loss: 0.13699 RPN box loss: 0.03021 RPN score loss: 0.02209 RPN total loss: 0.0523 Total loss: 1.29491 timestamp: 1654936007.9203317 iteration: 27415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0679 FastRCNN class loss: 0.03936 FastRCNN total loss: 0.10727 L1 loss: 0.0000e+00 L2 loss: 0.88643 Learning rate: 0.02 Mask loss: 0.10271 RPN box loss: 0.01421 RPN score loss: 0.00129 RPN total loss: 0.0155 Total loss: 1.11191 timestamp: 1654936011.0644107 iteration: 27420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14968 FastRCNN class loss: 0.05192 FastRCNN total loss: 0.2016 L1 loss: 0.0000e+00 L2 loss: 0.88632 Learning rate: 0.02 Mask loss: 0.13214 RPN box loss: 0.03232 RPN score loss: 0.00334 RPN total loss: 0.03566 Total loss: 1.25572 timestamp: 1654936014.3426757 iteration: 27425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.04915 FastRCNN total loss: 0.11895 L1 loss: 0.0000e+00 L2 loss: 0.88619 Learning rate: 0.02 Mask loss: 0.11357 RPN box loss: 0.03065 RPN score loss: 0.01381 RPN total loss: 0.04446 Total loss: 1.16317 timestamp: 1654936017.475809 iteration: 27430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12017 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.18409 L1 loss: 0.0000e+00 L2 loss: 0.88604 Learning rate: 0.02 Mask loss: 0.13004 RPN box loss: 0.02899 RPN score loss: 0.01295 RPN total loss: 0.04194 Total loss: 1.24211 timestamp: 1654936020.735749 iteration: 27435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19404 FastRCNN class loss: 0.13005 FastRCNN total loss: 0.32409 L1 loss: 0.0000e+00 L2 loss: 0.88591 Learning rate: 0.02 Mask loss: 0.17273 RPN box loss: 0.04884 RPN score loss: 0.00883 RPN total loss: 0.05767 Total loss: 1.4404 timestamp: 1654936023.9862556 iteration: 27440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06406 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.13226 L1 loss: 0.0000e+00 L2 loss: 0.88577 Learning rate: 0.02 Mask loss: 0.0947 RPN box loss: 0.03403 RPN score loss: 0.00909 RPN total loss: 0.04312 Total loss: 1.15586 timestamp: 1654936027.1427753 iteration: 27445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15011 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.21909 L1 loss: 0.0000e+00 L2 loss: 0.88562 Learning rate: 0.02 Mask loss: 0.11915 RPN box loss: 0.03493 RPN score loss: 0.00361 RPN total loss: 0.03855 Total loss: 1.2624 timestamp: 1654936030.376093 iteration: 27450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15729 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.23812 L1 loss: 0.0000e+00 L2 loss: 0.88548 Learning rate: 0.02 Mask loss: 0.22189 RPN box loss: 0.04341 RPN score loss: 0.00729 RPN total loss: 0.0507 Total loss: 1.39618 timestamp: 1654936033.5823066 iteration: 27455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10004 FastRCNN class loss: 0.05552 FastRCNN total loss: 0.15556 L1 loss: 0.0000e+00 L2 loss: 0.88535 Learning rate: 0.02 Mask loss: 0.09943 RPN box loss: 0.01592 RPN score loss: 0.00383 RPN total loss: 0.01976 Total loss: 1.16009 timestamp: 1654936036.6887736 iteration: 27460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13061 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.20597 L1 loss: 0.0000e+00 L2 loss: 0.88521 Learning rate: 0.02 Mask loss: 0.1102 RPN box loss: 0.02431 RPN score loss: 0.00144 RPN total loss: 0.02575 Total loss: 1.22714 timestamp: 1654936039.8889523 iteration: 27465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16743 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.24894 L1 loss: 0.0000e+00 L2 loss: 0.88507 Learning rate: 0.02 Mask loss: 0.1479 RPN box loss: 0.01179 RPN score loss: 0.00279 RPN total loss: 0.01458 Total loss: 1.29648 timestamp: 1654936043.104145 iteration: 27470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17867 FastRCNN class loss: 0.15383 FastRCNN total loss: 0.3325 L1 loss: 0.0000e+00 L2 loss: 0.88495 Learning rate: 0.02 Mask loss: 0.20304 RPN box loss: 0.04565 RPN score loss: 0.00902 RPN total loss: 0.05467 Total loss: 1.47516 timestamp: 1654936046.3519416 iteration: 27475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13282 FastRCNN class loss: 0.13289 FastRCNN total loss: 0.26571 L1 loss: 0.0000e+00 L2 loss: 0.88482 Learning rate: 0.02 Mask loss: 0.1456 RPN box loss: 0.03719 RPN score loss: 0.00753 RPN total loss: 0.04472 Total loss: 1.34084 timestamp: 1654936049.454691 iteration: 27480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12072 FastRCNN class loss: 0.08795 FastRCNN total loss: 0.20867 L1 loss: 0.0000e+00 L2 loss: 0.88468 Learning rate: 0.02 Mask loss: 0.16485 RPN box loss: 0.0817 RPN score loss: 0.01358 RPN total loss: 0.09528 Total loss: 1.35349 timestamp: 1654936052.7124348 iteration: 27485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10792 FastRCNN class loss: 0.08234 FastRCNN total loss: 0.19026 L1 loss: 0.0000e+00 L2 loss: 0.88455 Learning rate: 0.02 Mask loss: 0.13572 RPN box loss: 0.01415 RPN score loss: 0.00631 RPN total loss: 0.02046 Total loss: 1.231 timestamp: 1654936055.9306233 iteration: 27490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19316 FastRCNN class loss: 0.09896 FastRCNN total loss: 0.29212 L1 loss: 0.0000e+00 L2 loss: 0.88441 Learning rate: 0.02 Mask loss: 0.18997 RPN box loss: 0.04327 RPN score loss: 0.00425 RPN total loss: 0.04752 Total loss: 1.41402 timestamp: 1654936059.1394958 iteration: 27495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19285 FastRCNN class loss: 0.08604 FastRCNN total loss: 0.27889 L1 loss: 0.0000e+00 L2 loss: 0.8843 Learning rate: 0.02 Mask loss: 0.13183 RPN box loss: 0.02919 RPN score loss: 0.01024 RPN total loss: 0.03943 Total loss: 1.33445 timestamp: 1654936062.3865433 iteration: 27500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12886 FastRCNN class loss: 0.05818 FastRCNN total loss: 0.18704 L1 loss: 0.0000e+00 L2 loss: 0.88415 Learning rate: 0.02 Mask loss: 0.09913 RPN box loss: 0.01971 RPN score loss: 0.00492 RPN total loss: 0.02463 Total loss: 1.19495 timestamp: 1654936065.6469293 iteration: 27505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16738 FastRCNN class loss: 0.08623 FastRCNN total loss: 0.25361 L1 loss: 0.0000e+00 L2 loss: 0.88401 Learning rate: 0.02 Mask loss: 0.16384 RPN box loss: 0.03697 RPN score loss: 0.00604 RPN total loss: 0.04301 Total loss: 1.34446 timestamp: 1654936068.8108296 iteration: 27510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09774 FastRCNN class loss: 0.06369 FastRCNN total loss: 0.16143 L1 loss: 0.0000e+00 L2 loss: 0.88389 Learning rate: 0.02 Mask loss: 0.11451 RPN box loss: 0.04745 RPN score loss: 0.00467 RPN total loss: 0.05212 Total loss: 1.21195 timestamp: 1654936072.044235 iteration: 27515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18225 FastRCNN class loss: 0.11172 FastRCNN total loss: 0.29397 L1 loss: 0.0000e+00 L2 loss: 0.88377 Learning rate: 0.02 Mask loss: 0.15566 RPN box loss: 0.02771 RPN score loss: 0.01321 RPN total loss: 0.04092 Total loss: 1.37432 timestamp: 1654936075.2411473 iteration: 27520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16543 FastRCNN class loss: 0.08167 FastRCNN total loss: 0.24709 L1 loss: 0.0000e+00 L2 loss: 0.88366 Learning rate: 0.02 Mask loss: 0.11786 RPN box loss: 0.02896 RPN score loss: 0.00753 RPN total loss: 0.03649 Total loss: 1.2851 timestamp: 1654936078.4720337 iteration: 27525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12729 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.19311 L1 loss: 0.0000e+00 L2 loss: 0.88353 Learning rate: 0.02 Mask loss: 0.20629 RPN box loss: 0.00954 RPN score loss: 0.01024 RPN total loss: 0.01978 Total loss: 1.30272 timestamp: 1654936081.7030292 iteration: 27530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20808 FastRCNN class loss: 0.14934 FastRCNN total loss: 0.35742 L1 loss: 0.0000e+00 L2 loss: 0.88344 Learning rate: 0.02 Mask loss: 0.21493 RPN box loss: 0.03336 RPN score loss: 0.01007 RPN total loss: 0.04344 Total loss: 1.49923 timestamp: 1654936084.9343154 iteration: 27535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15795 FastRCNN class loss: 0.12287 FastRCNN total loss: 0.28083 L1 loss: 0.0000e+00 L2 loss: 0.88332 Learning rate: 0.02 Mask loss: 0.24222 RPN box loss: 0.03802 RPN score loss: 0.00879 RPN total loss: 0.04682 Total loss: 1.45317 timestamp: 1654936088.185659 iteration: 27540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10536 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.17518 L1 loss: 0.0000e+00 L2 loss: 0.88316 Learning rate: 0.02 Mask loss: 0.12555 RPN box loss: 0.01684 RPN score loss: 0.00347 RPN total loss: 0.02031 Total loss: 1.20421 timestamp: 1654936091.4344904 iteration: 27545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08662 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.15208 L1 loss: 0.0000e+00 L2 loss: 0.88301 Learning rate: 0.02 Mask loss: 0.26743 RPN box loss: 0.08047 RPN score loss: 0.00618 RPN total loss: 0.08666 Total loss: 1.38917 timestamp: 1654936094.6845145 iteration: 27550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13373 FastRCNN class loss: 0.10311 FastRCNN total loss: 0.23684 L1 loss: 0.0000e+00 L2 loss: 0.88288 Learning rate: 0.02 Mask loss: 0.1063 RPN box loss: 0.0384 RPN score loss: 0.0046 RPN total loss: 0.04299 Total loss: 1.26901 timestamp: 1654936097.8964212 iteration: 27555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13689 FastRCNN class loss: 0.08778 FastRCNN total loss: 0.22468 L1 loss: 0.0000e+00 L2 loss: 0.88274 Learning rate: 0.02 Mask loss: 0.19096 RPN box loss: 0.03687 RPN score loss: 0.01193 RPN total loss: 0.0488 Total loss: 1.34717 timestamp: 1654936101.166465 iteration: 27560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15486 FastRCNN class loss: 0.09061 FastRCNN total loss: 0.24547 L1 loss: 0.0000e+00 L2 loss: 0.88261 Learning rate: 0.02 Mask loss: 0.21605 RPN box loss: 0.07473 RPN score loss: 0.0131 RPN total loss: 0.08783 Total loss: 1.43196 timestamp: 1654936104.391251 iteration: 27565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07616 FastRCNN class loss: 0.07158 FastRCNN total loss: 0.14774 L1 loss: 0.0000e+00 L2 loss: 0.88246 Learning rate: 0.02 Mask loss: 0.13079 RPN box loss: 0.0303 RPN score loss: 0.00591 RPN total loss: 0.03621 Total loss: 1.1972 timestamp: 1654936107.6180158 iteration: 27570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10085 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.17224 L1 loss: 0.0000e+00 L2 loss: 0.88231 Learning rate: 0.02 Mask loss: 0.10523 RPN box loss: 0.02517 RPN score loss: 0.00356 RPN total loss: 0.02873 Total loss: 1.18851 timestamp: 1654936110.7385623 iteration: 27575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16072 FastRCNN class loss: 0.10498 FastRCNN total loss: 0.2657 L1 loss: 0.0000e+00 L2 loss: 0.88219 Learning rate: 0.02 Mask loss: 0.15004 RPN box loss: 0.04527 RPN score loss: 0.01173 RPN total loss: 0.05701 Total loss: 1.35494 timestamp: 1654936113.9740129 iteration: 27580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19659 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.2719 L1 loss: 0.0000e+00 L2 loss: 0.88207 Learning rate: 0.02 Mask loss: 0.3007 RPN box loss: 0.04306 RPN score loss: 0.00518 RPN total loss: 0.04824 Total loss: 1.5029 timestamp: 1654936117.216916 iteration: 27585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09964 FastRCNN class loss: 0.10897 FastRCNN total loss: 0.20861 L1 loss: 0.0000e+00 L2 loss: 0.88194 Learning rate: 0.02 Mask loss: 0.16764 RPN box loss: 0.02079 RPN score loss: 0.00953 RPN total loss: 0.03032 Total loss: 1.2885 timestamp: 1654936120.471166 iteration: 27590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09844 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.17029 L1 loss: 0.0000e+00 L2 loss: 0.8818 Learning rate: 0.02 Mask loss: 0.13571 RPN box loss: 0.02345 RPN score loss: 0.01157 RPN total loss: 0.03502 Total loss: 1.22284 timestamp: 1654936123.6826136 iteration: 27595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1872 FastRCNN class loss: 0.11007 FastRCNN total loss: 0.29727 L1 loss: 0.0000e+00 L2 loss: 0.88171 Learning rate: 0.02 Mask loss: 0.1799 RPN box loss: 0.03627 RPN score loss: 0.02611 RPN total loss: 0.06238 Total loss: 1.42125 timestamp: 1654936126.8010058 iteration: 27600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17132 FastRCNN class loss: 0.0667 FastRCNN total loss: 0.23802 L1 loss: 0.0000e+00 L2 loss: 0.88154 Learning rate: 0.02 Mask loss: 0.15484 RPN box loss: 0.01276 RPN score loss: 0.00631 RPN total loss: 0.01908 Total loss: 1.29347 timestamp: 1654936130.0014758 iteration: 27605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08475 FastRCNN class loss: 0.06314 FastRCNN total loss: 0.14789 L1 loss: 0.0000e+00 L2 loss: 0.8814 Learning rate: 0.02 Mask loss: 0.09103 RPN box loss: 0.01669 RPN score loss: 0.00439 RPN total loss: 0.02107 Total loss: 1.1414 timestamp: 1654936133.1666944 iteration: 27610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10774 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.1679 L1 loss: 0.0000e+00 L2 loss: 0.88129 Learning rate: 0.02 Mask loss: 0.08502 RPN box loss: 0.01581 RPN score loss: 0.00242 RPN total loss: 0.01823 Total loss: 1.15244 timestamp: 1654936136.4289715 iteration: 27615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15533 FastRCNN class loss: 0.13203 FastRCNN total loss: 0.28735 L1 loss: 0.0000e+00 L2 loss: 0.88114 Learning rate: 0.02 Mask loss: 0.16257 RPN box loss: 0.0352 RPN score loss: 0.01155 RPN total loss: 0.04674 Total loss: 1.37781 timestamp: 1654936139.6462793 iteration: 27620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0793 FastRCNN class loss: 0.04539 FastRCNN total loss: 0.12469 L1 loss: 0.0000e+00 L2 loss: 0.88102 Learning rate: 0.02 Mask loss: 0.13903 RPN box loss: 0.05122 RPN score loss: 0.00873 RPN total loss: 0.05995 Total loss: 1.20469 timestamp: 1654936142.7893095 iteration: 27625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11382 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.19786 L1 loss: 0.0000e+00 L2 loss: 0.88093 Learning rate: 0.02 Mask loss: 0.19744 RPN box loss: 0.05281 RPN score loss: 0.00748 RPN total loss: 0.06029 Total loss: 1.33651 timestamp: 1654936145.9755065 iteration: 27630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17376 FastRCNN class loss: 0.10475 FastRCNN total loss: 0.27851 L1 loss: 0.0000e+00 L2 loss: 0.88081 Learning rate: 0.02 Mask loss: 0.17211 RPN box loss: 0.01924 RPN score loss: 0.01264 RPN total loss: 0.03188 Total loss: 1.36331 timestamp: 1654936149.1036654 iteration: 27635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17827 FastRCNN class loss: 0.08508 FastRCNN total loss: 0.26335 L1 loss: 0.0000e+00 L2 loss: 0.8807 Learning rate: 0.02 Mask loss: 0.17642 RPN box loss: 0.01889 RPN score loss: 0.00545 RPN total loss: 0.02434 Total loss: 1.34481 timestamp: 1654936152.385594 iteration: 27640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11952 FastRCNN class loss: 0.08656 FastRCNN total loss: 0.20608 L1 loss: 0.0000e+00 L2 loss: 0.88055 Learning rate: 0.02 Mask loss: 0.14673 RPN box loss: 0.02453 RPN score loss: 0.00435 RPN total loss: 0.02888 Total loss: 1.26225 timestamp: 1654936155.559888 iteration: 27645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05321 FastRCNN class loss: 0.03831 FastRCNN total loss: 0.09152 L1 loss: 0.0000e+00 L2 loss: 0.88044 Learning rate: 0.02 Mask loss: 0.1316 RPN box loss: 0.0247 RPN score loss: 0.00695 RPN total loss: 0.03165 Total loss: 1.13521 timestamp: 1654936158.7837384 iteration: 27650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05503 FastRCNN class loss: 0.03241 FastRCNN total loss: 0.08744 L1 loss: 0.0000e+00 L2 loss: 0.88034 Learning rate: 0.02 Mask loss: 0.10621 RPN box loss: 0.00774 RPN score loss: 0.00101 RPN total loss: 0.00875 Total loss: 1.08273 timestamp: 1654936161.9478304 iteration: 27655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14351 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.21205 L1 loss: 0.0000e+00 L2 loss: 0.88017 Learning rate: 0.02 Mask loss: 0.10783 RPN box loss: 0.03069 RPN score loss: 0.00263 RPN total loss: 0.03332 Total loss: 1.23337 timestamp: 1654936165.1151466 iteration: 27660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15303 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.22152 L1 loss: 0.0000e+00 L2 loss: 0.88004 Learning rate: 0.02 Mask loss: 0.21127 RPN box loss: 0.04495 RPN score loss: 0.00329 RPN total loss: 0.04824 Total loss: 1.36107 timestamp: 1654936168.2728426 iteration: 27665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13355 FastRCNN class loss: 0.06171 FastRCNN total loss: 0.19526 L1 loss: 0.0000e+00 L2 loss: 0.87991 Learning rate: 0.02 Mask loss: 0.12103 RPN box loss: 0.04283 RPN score loss: 0.00422 RPN total loss: 0.04705 Total loss: 1.24325 timestamp: 1654936171.4367378 iteration: 27670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0947 FastRCNN class loss: 0.07778 FastRCNN total loss: 0.17248 L1 loss: 0.0000e+00 L2 loss: 0.87977 Learning rate: 0.02 Mask loss: 0.16572 RPN box loss: 0.0506 RPN score loss: 0.01288 RPN total loss: 0.06348 Total loss: 1.28145 timestamp: 1654936174.6845498 iteration: 27675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23663 FastRCNN class loss: 0.09199 FastRCNN total loss: 0.32862 L1 loss: 0.0000e+00 L2 loss: 0.87963 Learning rate: 0.02 Mask loss: 0.21485 RPN box loss: 0.02615 RPN score loss: 0.00347 RPN total loss: 0.02961 Total loss: 1.45272 timestamp: 1654936177.8232393 iteration: 27680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11225 FastRCNN class loss: 0.04368 FastRCNN total loss: 0.15593 L1 loss: 0.0000e+00 L2 loss: 0.87949 Learning rate: 0.02 Mask loss: 0.14795 RPN box loss: 0.04036 RPN score loss: 0.00648 RPN total loss: 0.04684 Total loss: 1.23022 timestamp: 1654936181.0298352 iteration: 27685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10742 FastRCNN class loss: 0.06486 FastRCNN total loss: 0.17228 L1 loss: 0.0000e+00 L2 loss: 0.87935 Learning rate: 0.02 Mask loss: 0.14822 RPN box loss: 0.03706 RPN score loss: 0.01379 RPN total loss: 0.05085 Total loss: 1.2507 timestamp: 1654936184.230877 iteration: 27690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12526 FastRCNN class loss: 0.11608 FastRCNN total loss: 0.24133 L1 loss: 0.0000e+00 L2 loss: 0.87922 Learning rate: 0.02 Mask loss: 0.21652 RPN box loss: 0.02377 RPN score loss: 0.0039 RPN total loss: 0.02767 Total loss: 1.36473 timestamp: 1654936187.482187 iteration: 27695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13341 FastRCNN class loss: 0.10637 FastRCNN total loss: 0.23978 L1 loss: 0.0000e+00 L2 loss: 0.87909 Learning rate: 0.02 Mask loss: 0.16617 RPN box loss: 0.03045 RPN score loss: 0.00497 RPN total loss: 0.03543 Total loss: 1.32046 timestamp: 1654936190.6275666 iteration: 27700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1881 FastRCNN class loss: 0.09655 FastRCNN total loss: 0.28465 L1 loss: 0.0000e+00 L2 loss: 0.87896 Learning rate: 0.02 Mask loss: 0.13595 RPN box loss: 0.0202 RPN score loss: 0.0043 RPN total loss: 0.02451 Total loss: 1.32407 timestamp: 1654936193.8217103 iteration: 27705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1651 FastRCNN class loss: 0.10042 FastRCNN total loss: 0.26552 L1 loss: 0.0000e+00 L2 loss: 0.87886 Learning rate: 0.02 Mask loss: 0.16861 RPN box loss: 0.02458 RPN score loss: 0.00681 RPN total loss: 0.03139 Total loss: 1.34438 timestamp: 1654936196.9840424 iteration: 27710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.07864 FastRCNN total loss: 0.18863 L1 loss: 0.0000e+00 L2 loss: 0.87872 Learning rate: 0.02 Mask loss: 0.22685 RPN box loss: 0.06943 RPN score loss: 0.00783 RPN total loss: 0.07726 Total loss: 1.37146 timestamp: 1654936200.164455 iteration: 27715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15174 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.22759 L1 loss: 0.0000e+00 L2 loss: 0.87859 Learning rate: 0.02 Mask loss: 0.22267 RPN box loss: 0.01795 RPN score loss: 0.00579 RPN total loss: 0.02374 Total loss: 1.3526 timestamp: 1654936203.3379498 iteration: 27720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16552 FastRCNN class loss: 0.09853 FastRCNN total loss: 0.26405 L1 loss: 0.0000e+00 L2 loss: 0.87846 Learning rate: 0.02 Mask loss: 0.15293 RPN box loss: 0.03261 RPN score loss: 0.01167 RPN total loss: 0.04428 Total loss: 1.33973 timestamp: 1654936206.5899858 iteration: 27725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08032 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.13701 L1 loss: 0.0000e+00 L2 loss: 0.87833 Learning rate: 0.02 Mask loss: 0.1007 RPN box loss: 0.02578 RPN score loss: 0.0076 RPN total loss: 0.03338 Total loss: 1.14943 timestamp: 1654936209.755632 iteration: 27730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08201 FastRCNN class loss: 0.07908 FastRCNN total loss: 0.16109 L1 loss: 0.0000e+00 L2 loss: 0.8782 Learning rate: 0.02 Mask loss: 0.19062 RPN box loss: 0.04792 RPN score loss: 0.01802 RPN total loss: 0.06594 Total loss: 1.29585 timestamp: 1654936212.920669 iteration: 27735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18183 FastRCNN class loss: 0.06383 FastRCNN total loss: 0.24565 L1 loss: 0.0000e+00 L2 loss: 0.87804 Learning rate: 0.02 Mask loss: 0.10125 RPN box loss: 0.02771 RPN score loss: 0.00357 RPN total loss: 0.03128 Total loss: 1.25623 timestamp: 1654936216.0909696 iteration: 27740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25218 FastRCNN class loss: 0.09175 FastRCNN total loss: 0.34393 L1 loss: 0.0000e+00 L2 loss: 0.8779 Learning rate: 0.02 Mask loss: 0.09321 RPN box loss: 0.01061 RPN score loss: 0.00898 RPN total loss: 0.01959 Total loss: 1.33463 timestamp: 1654936219.2835016 iteration: 27745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15658 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.22478 L1 loss: 0.0000e+00 L2 loss: 0.87778 Learning rate: 0.02 Mask loss: 0.13528 RPN box loss: 0.02939 RPN score loss: 0.00555 RPN total loss: 0.03494 Total loss: 1.27277 timestamp: 1654936222.4764862 iteration: 27750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12354 FastRCNN class loss: 0.0548 FastRCNN total loss: 0.17834 L1 loss: 0.0000e+00 L2 loss: 0.87767 Learning rate: 0.02 Mask loss: 0.12374 RPN box loss: 0.02539 RPN score loss: 0.00613 RPN total loss: 0.03153 Total loss: 1.21128 timestamp: 1654936225.6947331 iteration: 27755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1846 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.25957 L1 loss: 0.0000e+00 L2 loss: 0.87755 Learning rate: 0.02 Mask loss: 0.16692 RPN box loss: 0.03973 RPN score loss: 0.01039 RPN total loss: 0.05012 Total loss: 1.35416 timestamp: 1654936228.9068286 iteration: 27760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17427 FastRCNN class loss: 0.15501 FastRCNN total loss: 0.32928 L1 loss: 0.0000e+00 L2 loss: 0.87741 Learning rate: 0.02 Mask loss: 0.19724 RPN box loss: 0.05831 RPN score loss: 0.0135 RPN total loss: 0.0718 Total loss: 1.47573 timestamp: 1654936232.0662904 iteration: 27765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11014 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.18036 L1 loss: 0.0000e+00 L2 loss: 0.8773 Learning rate: 0.02 Mask loss: 0.10783 RPN box loss: 0.014 RPN score loss: 0.00193 RPN total loss: 0.01593 Total loss: 1.18142 timestamp: 1654936235.2530057 iteration: 27770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09975 FastRCNN class loss: 0.08303 FastRCNN total loss: 0.18277 L1 loss: 0.0000e+00 L2 loss: 0.87717 Learning rate: 0.02 Mask loss: 0.09307 RPN box loss: 0.02428 RPN score loss: 0.01158 RPN total loss: 0.03586 Total loss: 1.18887 timestamp: 1654936238.5177016 iteration: 27775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12585 FastRCNN class loss: 0.06715 FastRCNN total loss: 0.193 L1 loss: 0.0000e+00 L2 loss: 0.87705 Learning rate: 0.02 Mask loss: 0.15169 RPN box loss: 0.02174 RPN score loss: 0.00656 RPN total loss: 0.0283 Total loss: 1.25004 timestamp: 1654936241.755817 iteration: 27780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14491 FastRCNN class loss: 0.06938 FastRCNN total loss: 0.2143 L1 loss: 0.0000e+00 L2 loss: 0.87692 Learning rate: 0.02 Mask loss: 0.14842 RPN box loss: 0.02822 RPN score loss: 0.0049 RPN total loss: 0.03312 Total loss: 1.27277 timestamp: 1654936245.030322 iteration: 27785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09672 FastRCNN class loss: 0.10018 FastRCNN total loss: 0.1969 L1 loss: 0.0000e+00 L2 loss: 0.87677 Learning rate: 0.02 Mask loss: 0.16421 RPN box loss: 0.04191 RPN score loss: 0.01072 RPN total loss: 0.05263 Total loss: 1.2905 timestamp: 1654936248.2128482 iteration: 27790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1339 FastRCNN class loss: 0.08483 FastRCNN total loss: 0.21873 L1 loss: 0.0000e+00 L2 loss: 0.87664 Learning rate: 0.02 Mask loss: 0.17 RPN box loss: 0.02193 RPN score loss: 0.00689 RPN total loss: 0.02882 Total loss: 1.29419 timestamp: 1654936251.3977435 iteration: 27795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13426 FastRCNN class loss: 0.0713 FastRCNN total loss: 0.20556 L1 loss: 0.0000e+00 L2 loss: 0.87652 Learning rate: 0.02 Mask loss: 0.13965 RPN box loss: 0.02846 RPN score loss: 0.00675 RPN total loss: 0.03521 Total loss: 1.25693 timestamp: 1654936254.6413896 iteration: 27800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10092 FastRCNN class loss: 0.04952 FastRCNN total loss: 0.15044 L1 loss: 0.0000e+00 L2 loss: 0.87638 Learning rate: 0.02 Mask loss: 0.12309 RPN box loss: 0.04545 RPN score loss: 0.00991 RPN total loss: 0.05536 Total loss: 1.20527 timestamp: 1654936257.8059192 iteration: 27805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19357 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.25273 L1 loss: 0.0000e+00 L2 loss: 0.87624 Learning rate: 0.02 Mask loss: 0.13856 RPN box loss: 0.04617 RPN score loss: 0.00266 RPN total loss: 0.04883 Total loss: 1.31637 timestamp: 1654936260.9673243 iteration: 27810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11361 FastRCNN class loss: 0.05414 FastRCNN total loss: 0.16775 L1 loss: 0.0000e+00 L2 loss: 0.87613 Learning rate: 0.02 Mask loss: 0.11179 RPN box loss: 0.03975 RPN score loss: 0.00642 RPN total loss: 0.04617 Total loss: 1.20183 timestamp: 1654936264.1909215 iteration: 27815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13093 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.20298 L1 loss: 0.0000e+00 L2 loss: 0.87602 Learning rate: 0.02 Mask loss: 0.12027 RPN box loss: 0.01348 RPN score loss: 0.00598 RPN total loss: 0.01946 Total loss: 1.21874 timestamp: 1654936267.3758538 iteration: 27820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12117 FastRCNN class loss: 0.05692 FastRCNN total loss: 0.17808 L1 loss: 0.0000e+00 L2 loss: 0.8759 Learning rate: 0.02 Mask loss: 0.13084 RPN box loss: 0.02601 RPN score loss: 0.00375 RPN total loss: 0.02976 Total loss: 1.21459 timestamp: 1654936270.5583913 iteration: 27825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12489 FastRCNN class loss: 0.12495 FastRCNN total loss: 0.24984 L1 loss: 0.0000e+00 L2 loss: 0.87575 Learning rate: 0.02 Mask loss: 0.24314 RPN box loss: 0.0316 RPN score loss: 0.00931 RPN total loss: 0.04091 Total loss: 1.40964 timestamp: 1654936273.7759163 iteration: 27830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14107 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.20594 L1 loss: 0.0000e+00 L2 loss: 0.8756 Learning rate: 0.02 Mask loss: 0.12466 RPN box loss: 0.01213 RPN score loss: 0.00452 RPN total loss: 0.01665 Total loss: 1.22285 timestamp: 1654936277.020855 iteration: 27835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09307 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.17896 L1 loss: 0.0000e+00 L2 loss: 0.87548 Learning rate: 0.02 Mask loss: 0.12886 RPN box loss: 0.03306 RPN score loss: 0.00258 RPN total loss: 0.03565 Total loss: 1.21895 timestamp: 1654936280.2427878 iteration: 27840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13077 FastRCNN class loss: 0.06511 FastRCNN total loss: 0.19588 L1 loss: 0.0000e+00 L2 loss: 0.87536 Learning rate: 0.02 Mask loss: 0.16132 RPN box loss: 0.04765 RPN score loss: 0.01099 RPN total loss: 0.05864 Total loss: 1.29119 timestamp: 1654936283.4248502 iteration: 27845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15843 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.24323 L1 loss: 0.0000e+00 L2 loss: 0.87522 Learning rate: 0.02 Mask loss: 0.1187 RPN box loss: 0.02021 RPN score loss: 0.00337 RPN total loss: 0.02358 Total loss: 1.26073 timestamp: 1654936286.5860698 iteration: 27850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14778 FastRCNN class loss: 0.10618 FastRCNN total loss: 0.25396 L1 loss: 0.0000e+00 L2 loss: 0.87509 Learning rate: 0.02 Mask loss: 0.15251 RPN box loss: 0.0378 RPN score loss: 0.00663 RPN total loss: 0.04443 Total loss: 1.326 timestamp: 1654936289.8454516 iteration: 27855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1386 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.20431 L1 loss: 0.0000e+00 L2 loss: 0.87494 Learning rate: 0.02 Mask loss: 0.11495 RPN box loss: 0.01322 RPN score loss: 0.00196 RPN total loss: 0.01518 Total loss: 1.20937 timestamp: 1654936293.0732884 iteration: 27860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09956 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.1571 L1 loss: 0.0000e+00 L2 loss: 0.87482 Learning rate: 0.02 Mask loss: 0.10149 RPN box loss: 0.01613 RPN score loss: 0.00417 RPN total loss: 0.02031 Total loss: 1.15372 timestamp: 1654936296.282964 iteration: 27865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15986 FastRCNN class loss: 0.11317 FastRCNN total loss: 0.27304 L1 loss: 0.0000e+00 L2 loss: 0.87469 Learning rate: 0.02 Mask loss: 0.15877 RPN box loss: 0.03751 RPN score loss: 0.00889 RPN total loss: 0.0464 Total loss: 1.35289 timestamp: 1654936299.4501615 iteration: 27870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12855 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.20365 L1 loss: 0.0000e+00 L2 loss: 0.87456 Learning rate: 0.02 Mask loss: 0.15898 RPN box loss: 0.02688 RPN score loss: 0.00372 RPN total loss: 0.0306 Total loss: 1.26779 timestamp: 1654936302.638524 iteration: 27875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12662 FastRCNN class loss: 0.05798 FastRCNN total loss: 0.1846 L1 loss: 0.0000e+00 L2 loss: 0.87443 Learning rate: 0.02 Mask loss: 0.1492 RPN box loss: 0.03446 RPN score loss: 0.00427 RPN total loss: 0.03873 Total loss: 1.24696 timestamp: 1654936305.8531375 iteration: 27880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06669 FastRCNN class loss: 0.03957 FastRCNN total loss: 0.10625 L1 loss: 0.0000e+00 L2 loss: 0.87428 Learning rate: 0.02 Mask loss: 0.16125 RPN box loss: 0.02231 RPN score loss: 0.00814 RPN total loss: 0.03045 Total loss: 1.17224 timestamp: 1654936309.147128 iteration: 27885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06666 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.13814 L1 loss: 0.0000e+00 L2 loss: 0.87415 Learning rate: 0.02 Mask loss: 0.26294 RPN box loss: 0.0606 RPN score loss: 0.00401 RPN total loss: 0.06461 Total loss: 1.33984 timestamp: 1654936312.2585552 iteration: 27890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12551 FastRCNN class loss: 0.07901 FastRCNN total loss: 0.20452 L1 loss: 0.0000e+00 L2 loss: 0.87403 Learning rate: 0.02 Mask loss: 0.15335 RPN box loss: 0.02592 RPN score loss: 0.00186 RPN total loss: 0.02778 Total loss: 1.25969 timestamp: 1654936315.4137604 iteration: 27895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.05283 FastRCNN total loss: 0.17532 L1 loss: 0.0000e+00 L2 loss: 0.87391 Learning rate: 0.02 Mask loss: 0.12394 RPN box loss: 0.01656 RPN score loss: 0.00663 RPN total loss: 0.02319 Total loss: 1.19636 timestamp: 1654936318.5975013 iteration: 27900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.08802 FastRCNN total loss: 0.18599 L1 loss: 0.0000e+00 L2 loss: 0.87379 Learning rate: 0.02 Mask loss: 0.1498 RPN box loss: 0.00604 RPN score loss: 0.00307 RPN total loss: 0.00911 Total loss: 1.2187 timestamp: 1654936321.91456 iteration: 27905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14742 FastRCNN class loss: 0.13065 FastRCNN total loss: 0.27807 L1 loss: 0.0000e+00 L2 loss: 0.87366 Learning rate: 0.02 Mask loss: 0.16644 RPN box loss: 0.04452 RPN score loss: 0.01005 RPN total loss: 0.05457 Total loss: 1.37275 timestamp: 1654936325.125795 iteration: 27910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.108 FastRCNN class loss: 0.04417 FastRCNN total loss: 0.15218 L1 loss: 0.0000e+00 L2 loss: 0.87354 Learning rate: 0.02 Mask loss: 0.10602 RPN box loss: 0.01485 RPN score loss: 0.00132 RPN total loss: 0.01617 Total loss: 1.1479 timestamp: 1654936328.2428815 iteration: 27915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17279 FastRCNN class loss: 0.0833 FastRCNN total loss: 0.25609 L1 loss: 0.0000e+00 L2 loss: 0.8734 Learning rate: 0.02 Mask loss: 0.15653 RPN box loss: 0.01758 RPN score loss: 0.00487 RPN total loss: 0.02245 Total loss: 1.30847 timestamp: 1654936331.4180124 iteration: 27920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13351 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.18921 L1 loss: 0.0000e+00 L2 loss: 0.87327 Learning rate: 0.02 Mask loss: 0.11931 RPN box loss: 0.01206 RPN score loss: 0.00287 RPN total loss: 0.01493 Total loss: 1.19671 timestamp: 1654936334.6411273 iteration: 27925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11309 FastRCNN class loss: 0.06053 FastRCNN total loss: 0.17362 L1 loss: 0.0000e+00 L2 loss: 0.87315 Learning rate: 0.02 Mask loss: 0.13184 RPN box loss: 0.00574 RPN score loss: 0.00255 RPN total loss: 0.00829 Total loss: 1.18689 timestamp: 1654936337.8832588 iteration: 27930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13655 FastRCNN class loss: 0.08382 FastRCNN total loss: 0.22037 L1 loss: 0.0000e+00 L2 loss: 0.87302 Learning rate: 0.02 Mask loss: 0.14043 RPN box loss: 0.02813 RPN score loss: 0.0022 RPN total loss: 0.03032 Total loss: 1.26415 timestamp: 1654936341.0154617 iteration: 27935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09735 FastRCNN class loss: 0.07324 FastRCNN total loss: 0.17059 L1 loss: 0.0000e+00 L2 loss: 0.8729 Learning rate: 0.02 Mask loss: 0.11608 RPN box loss: 0.01639 RPN score loss: 0.00285 RPN total loss: 0.01924 Total loss: 1.17882 timestamp: 1654936344.200093 iteration: 27940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11051 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.18507 L1 loss: 0.0000e+00 L2 loss: 0.87279 Learning rate: 0.02 Mask loss: 0.14492 RPN box loss: 0.01229 RPN score loss: 0.00154 RPN total loss: 0.01383 Total loss: 1.21661 timestamp: 1654936347.3824377 iteration: 27945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11932 FastRCNN class loss: 0.05112 FastRCNN total loss: 0.17043 L1 loss: 0.0000e+00 L2 loss: 0.87264 Learning rate: 0.02 Mask loss: 0.10307 RPN box loss: 0.03182 RPN score loss: 0.0038 RPN total loss: 0.03562 Total loss: 1.18176 timestamp: 1654936350.5741994 iteration: 27950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05626 FastRCNN class loss: 0.0411 FastRCNN total loss: 0.09736 L1 loss: 0.0000e+00 L2 loss: 0.8725 Learning rate: 0.02 Mask loss: 0.12016 RPN box loss: 0.02053 RPN score loss: 0.00288 RPN total loss: 0.02341 Total loss: 1.11343 timestamp: 1654936353.7468994 iteration: 27955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12478 FastRCNN class loss: 0.0857 FastRCNN total loss: 0.21049 L1 loss: 0.0000e+00 L2 loss: 0.87237 Learning rate: 0.02 Mask loss: 0.18088 RPN box loss: 0.03509 RPN score loss: 0.00549 RPN total loss: 0.04058 Total loss: 1.30432 timestamp: 1654936356.9743354 iteration: 27960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16705 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.23157 L1 loss: 0.0000e+00 L2 loss: 0.87224 Learning rate: 0.02 Mask loss: 0.13127 RPN box loss: 0.14507 RPN score loss: 0.0075 RPN total loss: 0.15257 Total loss: 1.38765 timestamp: 1654936360.197847 iteration: 27965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11364 FastRCNN class loss: 0.04827 FastRCNN total loss: 0.16191 L1 loss: 0.0000e+00 L2 loss: 0.87211 Learning rate: 0.02 Mask loss: 0.09301 RPN box loss: 0.02314 RPN score loss: 0.00362 RPN total loss: 0.02676 Total loss: 1.15379 timestamp: 1654936363.376625 iteration: 27970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15245 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.2324 L1 loss: 0.0000e+00 L2 loss: 0.87199 Learning rate: 0.02 Mask loss: 0.14115 RPN box loss: 0.03754 RPN score loss: 0.00226 RPN total loss: 0.03979 Total loss: 1.28533 timestamp: 1654936366.5226476 iteration: 27975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18508 FastRCNN class loss: 0.12038 FastRCNN total loss: 0.30545 L1 loss: 0.0000e+00 L2 loss: 0.87185 Learning rate: 0.02 Mask loss: 0.17833 RPN box loss: 0.03607 RPN score loss: 0.00645 RPN total loss: 0.04252 Total loss: 1.39816 timestamp: 1654936369.717058 iteration: 27980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14618 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.22607 L1 loss: 0.0000e+00 L2 loss: 0.87171 Learning rate: 0.02 Mask loss: 0.14576 RPN box loss: 0.02504 RPN score loss: 0.00427 RPN total loss: 0.02931 Total loss: 1.27286 timestamp: 1654936373.0480962 iteration: 27985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16311 FastRCNN class loss: 0.09072 FastRCNN total loss: 0.25383 L1 loss: 0.0000e+00 L2 loss: 0.87159 Learning rate: 0.02 Mask loss: 0.15469 RPN box loss: 0.00962 RPN score loss: 0.00579 RPN total loss: 0.01542 Total loss: 1.29553 timestamp: 1654936376.2391787 iteration: 27990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1431 FastRCNN class loss: 0.10629 FastRCNN total loss: 0.24939 L1 loss: 0.0000e+00 L2 loss: 0.87146 Learning rate: 0.02 Mask loss: 0.13117 RPN box loss: 0.02584 RPN score loss: 0.00594 RPN total loss: 0.03179 Total loss: 1.2838 timestamp: 1654936379.482882 iteration: 27995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14387 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.21988 L1 loss: 0.0000e+00 L2 loss: 0.87134 Learning rate: 0.02 Mask loss: 0.16589 RPN box loss: 0.06458 RPN score loss: 0.0081 RPN total loss: 0.07269 Total loss: 1.3298 timestamp: 1654936382.6362553 iteration: 28000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.14622 L1 loss: 0.0000e+00 L2 loss: 0.87123 Learning rate: 0.02 Mask loss: 0.14713 RPN box loss: 0.01276 RPN score loss: 0.00797 RPN total loss: 0.02074 Total loss: 1.18531 timestamp: 1654936385.8208556 iteration: 28005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14789 FastRCNN class loss: 0.05126 FastRCNN total loss: 0.19915 L1 loss: 0.0000e+00 L2 loss: 0.8711 Learning rate: 0.02 Mask loss: 0.08967 RPN box loss: 0.02737 RPN score loss: 0.00347 RPN total loss: 0.03084 Total loss: 1.19077 timestamp: 1654936389.0274744 iteration: 28010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18491 FastRCNN class loss: 0.08807 FastRCNN total loss: 0.27299 L1 loss: 0.0000e+00 L2 loss: 0.87097 Learning rate: 0.02 Mask loss: 0.18855 RPN box loss: 0.04915 RPN score loss: 0.00342 RPN total loss: 0.05258 Total loss: 1.38509 timestamp: 1654936392.144967 iteration: 28015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14066 FastRCNN class loss: 0.09657 FastRCNN total loss: 0.23723 L1 loss: 0.0000e+00 L2 loss: 0.87082 Learning rate: 0.02 Mask loss: 0.11275 RPN box loss: 0.04501 RPN score loss: 0.00506 RPN total loss: 0.05007 Total loss: 1.27086 timestamp: 1654936395.373895 iteration: 28020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.17159 L1 loss: 0.0000e+00 L2 loss: 0.87067 Learning rate: 0.02 Mask loss: 0.13709 RPN box loss: 0.05157 RPN score loss: 0.00487 RPN total loss: 0.05644 Total loss: 1.23579 timestamp: 1654936398.6399887 iteration: 28025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19454 FastRCNN class loss: 0.10505 FastRCNN total loss: 0.29959 L1 loss: 0.0000e+00 L2 loss: 0.87054 Learning rate: 0.02 Mask loss: 0.16957 RPN box loss: 0.04537 RPN score loss: 0.00804 RPN total loss: 0.05341 Total loss: 1.39311 timestamp: 1654936401.868887 iteration: 28030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20725 FastRCNN class loss: 0.09621 FastRCNN total loss: 0.30346 L1 loss: 0.0000e+00 L2 loss: 0.87042 Learning rate: 0.02 Mask loss: 0.1269 RPN box loss: 0.01284 RPN score loss: 0.0092 RPN total loss: 0.02203 Total loss: 1.32281 timestamp: 1654936405.0548437 iteration: 28035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12431 FastRCNN class loss: 0.13478 FastRCNN total loss: 0.2591 L1 loss: 0.0000e+00 L2 loss: 0.8703 Learning rate: 0.02 Mask loss: 0.19886 RPN box loss: 0.04641 RPN score loss: 0.01282 RPN total loss: 0.05922 Total loss: 1.38748 timestamp: 1654936408.3232012 iteration: 28040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08986 FastRCNN class loss: 0.05706 FastRCNN total loss: 0.14692 L1 loss: 0.0000e+00 L2 loss: 0.87019 Learning rate: 0.02 Mask loss: 0.08444 RPN box loss: 0.00593 RPN score loss: 0.00578 RPN total loss: 0.01171 Total loss: 1.11326 timestamp: 1654936411.5745277 iteration: 28045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20068 FastRCNN class loss: 0.10238 FastRCNN total loss: 0.30305 L1 loss: 0.0000e+00 L2 loss: 0.87006 Learning rate: 0.02 Mask loss: 0.20013 RPN box loss: 0.01455 RPN score loss: 0.01195 RPN total loss: 0.0265 Total loss: 1.39974 timestamp: 1654936414.750385 iteration: 28050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1124 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.17527 L1 loss: 0.0000e+00 L2 loss: 0.86993 Learning rate: 0.02 Mask loss: 0.1543 RPN box loss: 0.00649 RPN score loss: 0.00299 RPN total loss: 0.00948 Total loss: 1.20898 timestamp: 1654936417.9626777 iteration: 28055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12288 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.1819 L1 loss: 0.0000e+00 L2 loss: 0.86977 Learning rate: 0.02 Mask loss: 0.15627 RPN box loss: 0.02196 RPN score loss: 0.00236 RPN total loss: 0.02433 Total loss: 1.23227 timestamp: 1654936421.2232401 iteration: 28060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06768 FastRCNN class loss: 0.07616 FastRCNN total loss: 0.14384 L1 loss: 0.0000e+00 L2 loss: 0.86965 Learning rate: 0.02 Mask loss: 0.08345 RPN box loss: 0.00927 RPN score loss: 0.00465 RPN total loss: 0.01391 Total loss: 1.11085 timestamp: 1654936424.439464 iteration: 28065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13178 FastRCNN class loss: 0.09212 FastRCNN total loss: 0.2239 L1 loss: 0.0000e+00 L2 loss: 0.8695 Learning rate: 0.02 Mask loss: 0.14275 RPN box loss: 0.04149 RPN score loss: 0.00562 RPN total loss: 0.04711 Total loss: 1.28326 timestamp: 1654936427.566692 iteration: 28070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07889 FastRCNN class loss: 0.0987 FastRCNN total loss: 0.17759 L1 loss: 0.0000e+00 L2 loss: 0.86937 Learning rate: 0.02 Mask loss: 0.19966 RPN box loss: 0.02923 RPN score loss: 0.00441 RPN total loss: 0.03364 Total loss: 1.28025 timestamp: 1654936430.8029656 iteration: 28075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16351 FastRCNN class loss: 0.09184 FastRCNN total loss: 0.25535 L1 loss: 0.0000e+00 L2 loss: 0.86921 Learning rate: 0.02 Mask loss: 0.21404 RPN box loss: 0.02011 RPN score loss: 0.00209 RPN total loss: 0.0222 Total loss: 1.3608 timestamp: 1654936434.0283911 iteration: 28080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18043 FastRCNN class loss: 0.09178 FastRCNN total loss: 0.27221 L1 loss: 0.0000e+00 L2 loss: 0.86908 Learning rate: 0.02 Mask loss: 0.18099 RPN box loss: 0.02215 RPN score loss: 0.0047 RPN total loss: 0.02685 Total loss: 1.34913 timestamp: 1654936437.2156582 iteration: 28085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1015 FastRCNN class loss: 0.06271 FastRCNN total loss: 0.16421 L1 loss: 0.0000e+00 L2 loss: 0.86898 Learning rate: 0.02 Mask loss: 0.29989 RPN box loss: 0.00626 RPN score loss: 0.00387 RPN total loss: 0.01014 Total loss: 1.34321 timestamp: 1654936440.361426 iteration: 28090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12827 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.19496 L1 loss: 0.0000e+00 L2 loss: 0.86886 Learning rate: 0.02 Mask loss: 0.11912 RPN box loss: 0.01274 RPN score loss: 0.00508 RPN total loss: 0.01782 Total loss: 1.20076 timestamp: 1654936443.5391338 iteration: 28095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08896 FastRCNN class loss: 0.07733 FastRCNN total loss: 0.16629 L1 loss: 0.0000e+00 L2 loss: 0.86871 Learning rate: 0.02 Mask loss: 0.10517 RPN box loss: 0.04226 RPN score loss: 0.00562 RPN total loss: 0.04788 Total loss: 1.18806 timestamp: 1654936446.7070801 iteration: 28100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13019 FastRCNN class loss: 0.06171 FastRCNN total loss: 0.1919 L1 loss: 0.0000e+00 L2 loss: 0.86859 Learning rate: 0.02 Mask loss: 0.13304 RPN box loss: 0.01691 RPN score loss: 0.00181 RPN total loss: 0.01872 Total loss: 1.21225 timestamp: 1654936449.8789015 iteration: 28105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12043 FastRCNN class loss: 0.08883 FastRCNN total loss: 0.20926 L1 loss: 0.0000e+00 L2 loss: 0.86844 Learning rate: 0.02 Mask loss: 0.21101 RPN box loss: 0.05325 RPN score loss: 0.00908 RPN total loss: 0.06234 Total loss: 1.35105 timestamp: 1654936453.0778632 iteration: 28110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11454 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.18237 L1 loss: 0.0000e+00 L2 loss: 0.86832 Learning rate: 0.02 Mask loss: 0.15517 RPN box loss: 0.02425 RPN score loss: 0.00541 RPN total loss: 0.02966 Total loss: 1.23552 timestamp: 1654936456.3042204 iteration: 28115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12515 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.20285 L1 loss: 0.0000e+00 L2 loss: 0.86821 Learning rate: 0.02 Mask loss: 0.11619 RPN box loss: 0.02929 RPN score loss: 0.00501 RPN total loss: 0.0343 Total loss: 1.22155 timestamp: 1654936459.5070045 iteration: 28120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12263 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.1854 L1 loss: 0.0000e+00 L2 loss: 0.86806 Learning rate: 0.02 Mask loss: 0.15044 RPN box loss: 0.02973 RPN score loss: 0.00315 RPN total loss: 0.03289 Total loss: 1.23679 timestamp: 1654936462.6903071 iteration: 28125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18704 FastRCNN class loss: 0.15645 FastRCNN total loss: 0.3435 L1 loss: 0.0000e+00 L2 loss: 0.86794 Learning rate: 0.02 Mask loss: 0.21492 RPN box loss: 0.04859 RPN score loss: 0.01826 RPN total loss: 0.06685 Total loss: 1.4932 timestamp: 1654936465.91129 iteration: 28130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13054 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.19311 L1 loss: 0.0000e+00 L2 loss: 0.86784 Learning rate: 0.02 Mask loss: 0.09697 RPN box loss: 0.04533 RPN score loss: 0.00413 RPN total loss: 0.04946 Total loss: 1.20738 timestamp: 1654936469.0367749 iteration: 28135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09559 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.14533 L1 loss: 0.0000e+00 L2 loss: 0.86768 Learning rate: 0.02 Mask loss: 0.16144 RPN box loss: 0.03925 RPN score loss: 0.00314 RPN total loss: 0.04239 Total loss: 1.21684 timestamp: 1654936472.1253755 iteration: 28140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0906 FastRCNN class loss: 0.06479 FastRCNN total loss: 0.15538 L1 loss: 0.0000e+00 L2 loss: 0.86754 Learning rate: 0.02 Mask loss: 0.09456 RPN box loss: 0.03302 RPN score loss: 0.01206 RPN total loss: 0.04508 Total loss: 1.16256 timestamp: 1654936475.270542 iteration: 28145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11091 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.18539 L1 loss: 0.0000e+00 L2 loss: 0.86741 Learning rate: 0.02 Mask loss: 0.2979 RPN box loss: 0.04439 RPN score loss: 0.00706 RPN total loss: 0.05145 Total loss: 1.40215 timestamp: 1654936478.5719655 iteration: 28150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16061 FastRCNN class loss: 0.21329 FastRCNN total loss: 0.3739 L1 loss: 0.0000e+00 L2 loss: 0.86728 Learning rate: 0.02 Mask loss: 0.18839 RPN box loss: 0.0313 RPN score loss: 0.00813 RPN total loss: 0.03943 Total loss: 1.469 timestamp: 1654936481.723455 iteration: 28155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.03638 FastRCNN total loss: 0.11219 L1 loss: 0.0000e+00 L2 loss: 0.8672 Learning rate: 0.02 Mask loss: 0.14373 RPN box loss: 0.03745 RPN score loss: 0.0038 RPN total loss: 0.04125 Total loss: 1.16437 timestamp: 1654936484.9238265 iteration: 28160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24785 FastRCNN class loss: 0.09417 FastRCNN total loss: 0.34202 L1 loss: 0.0000e+00 L2 loss: 0.86708 Learning rate: 0.02 Mask loss: 0.14258 RPN box loss: 0.04238 RPN score loss: 0.00716 RPN total loss: 0.04954 Total loss: 1.40122 timestamp: 1654936488.1469646 iteration: 28165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11623 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.18009 L1 loss: 0.0000e+00 L2 loss: 0.86694 Learning rate: 0.02 Mask loss: 0.14544 RPN box loss: 0.02937 RPN score loss: 0.00763 RPN total loss: 0.037 Total loss: 1.22947 timestamp: 1654936491.3292055 iteration: 28170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15029 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.23147 L1 loss: 0.0000e+00 L2 loss: 0.8668 Learning rate: 0.02 Mask loss: 0.17695 RPN box loss: 0.03315 RPN score loss: 0.0213 RPN total loss: 0.05444 Total loss: 1.32966 timestamp: 1654936494.5355732 iteration: 28175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10274 FastRCNN class loss: 0.08302 FastRCNN total loss: 0.18576 L1 loss: 0.0000e+00 L2 loss: 0.86668 Learning rate: 0.02 Mask loss: 0.14167 RPN box loss: 0.01399 RPN score loss: 0.00655 RPN total loss: 0.02055 Total loss: 1.21465 timestamp: 1654936497.7489533 iteration: 28180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16155 FastRCNN class loss: 0.1185 FastRCNN total loss: 0.28005 L1 loss: 0.0000e+00 L2 loss: 0.86656 Learning rate: 0.02 Mask loss: 0.14665 RPN box loss: 0.02237 RPN score loss: 0.01236 RPN total loss: 0.03474 Total loss: 1.32799 timestamp: 1654936500.9154775 iteration: 28185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11327 FastRCNN class loss: 0.06269 FastRCNN total loss: 0.17596 L1 loss: 0.0000e+00 L2 loss: 0.86643 Learning rate: 0.02 Mask loss: 0.13859 RPN box loss: 0.00571 RPN score loss: 0.00257 RPN total loss: 0.00828 Total loss: 1.18926 timestamp: 1654936504.2197876 iteration: 28190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16051 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.2469 L1 loss: 0.0000e+00 L2 loss: 0.86631 Learning rate: 0.02 Mask loss: 0.14112 RPN box loss: 0.0235 RPN score loss: 0.00447 RPN total loss: 0.02797 Total loss: 1.28231 timestamp: 1654936507.4787192 iteration: 28195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10871 FastRCNN class loss: 0.06176 FastRCNN total loss: 0.17047 L1 loss: 0.0000e+00 L2 loss: 0.86618 Learning rate: 0.02 Mask loss: 0.14667 RPN box loss: 0.0129 RPN score loss: 0.00552 RPN total loss: 0.01842 Total loss: 1.20174 timestamp: 1654936510.6000001 iteration: 28200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.17424 L1 loss: 0.0000e+00 L2 loss: 0.86605 Learning rate: 0.02 Mask loss: 0.13505 RPN box loss: 0.04474 RPN score loss: 0.01316 RPN total loss: 0.0579 Total loss: 1.23325 timestamp: 1654936513.8091285 iteration: 28205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12854 FastRCNN class loss: 0.08991 FastRCNN total loss: 0.21845 L1 loss: 0.0000e+00 L2 loss: 0.86594 Learning rate: 0.02 Mask loss: 0.14654 RPN box loss: 0.05448 RPN score loss: 0.01574 RPN total loss: 0.07022 Total loss: 1.30115 timestamp: 1654936517.0670114 iteration: 28210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16727 FastRCNN class loss: 0.07484 FastRCNN total loss: 0.24211 L1 loss: 0.0000e+00 L2 loss: 0.86581 Learning rate: 0.02 Mask loss: 0.15016 RPN box loss: 0.05768 RPN score loss: 0.00598 RPN total loss: 0.06366 Total loss: 1.32173 timestamp: 1654936520.291271 iteration: 28215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11608 FastRCNN class loss: 0.04929 FastRCNN total loss: 0.16537 L1 loss: 0.0000e+00 L2 loss: 0.86566 Learning rate: 0.02 Mask loss: 0.08509 RPN box loss: 0.03306 RPN score loss: 0.00629 RPN total loss: 0.03935 Total loss: 1.15547 timestamp: 1654936523.4219923 iteration: 28220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12949 FastRCNN class loss: 0.08995 FastRCNN total loss: 0.21944 L1 loss: 0.0000e+00 L2 loss: 0.86554 Learning rate: 0.02 Mask loss: 0.16503 RPN box loss: 0.01177 RPN score loss: 0.00325 RPN total loss: 0.01502 Total loss: 1.26502 timestamp: 1654936526.6473355 iteration: 28225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08488 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.15049 L1 loss: 0.0000e+00 L2 loss: 0.86542 Learning rate: 0.02 Mask loss: 0.12329 RPN box loss: 0.02872 RPN score loss: 0.00832 RPN total loss: 0.03704 Total loss: 1.17623 timestamp: 1654936529.8804634 iteration: 28230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15261 FastRCNN class loss: 0.08893 FastRCNN total loss: 0.24155 L1 loss: 0.0000e+00 L2 loss: 0.86529 Learning rate: 0.02 Mask loss: 0.14454 RPN box loss: 0.01601 RPN score loss: 0.00451 RPN total loss: 0.02052 Total loss: 1.2719 timestamp: 1654936533.0824182 iteration: 28235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09351 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.15157 L1 loss: 0.0000e+00 L2 loss: 0.86518 Learning rate: 0.02 Mask loss: 0.12435 RPN box loss: 0.015 RPN score loss: 0.00257 RPN total loss: 0.01756 Total loss: 1.15866 timestamp: 1654936536.3410933 iteration: 28240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18711 FastRCNN class loss: 0.10978 FastRCNN total loss: 0.29688 L1 loss: 0.0000e+00 L2 loss: 0.86506 Learning rate: 0.02 Mask loss: 0.19227 RPN box loss: 0.02693 RPN score loss: 0.0057 RPN total loss: 0.03263 Total loss: 1.38684 timestamp: 1654936539.547298 iteration: 28245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.16064 L1 loss: 0.0000e+00 L2 loss: 0.86494 Learning rate: 0.02 Mask loss: 0.15602 RPN box loss: 0.01168 RPN score loss: 0.0048 RPN total loss: 0.01648 Total loss: 1.19808 timestamp: 1654936542.8570867 iteration: 28250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23631 FastRCNN class loss: 0.13508 FastRCNN total loss: 0.37139 L1 loss: 0.0000e+00 L2 loss: 0.86482 Learning rate: 0.02 Mask loss: 0.22149 RPN box loss: 0.02665 RPN score loss: 0.01148 RPN total loss: 0.03813 Total loss: 1.49583 timestamp: 1654936546.0783315 iteration: 28255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06989 FastRCNN class loss: 0.03977 FastRCNN total loss: 0.10966 L1 loss: 0.0000e+00 L2 loss: 0.86468 Learning rate: 0.02 Mask loss: 0.12578 RPN box loss: 0.02585 RPN score loss: 0.00578 RPN total loss: 0.03163 Total loss: 1.13175 timestamp: 1654936549.3029902 iteration: 28260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17167 FastRCNN class loss: 0.0892 FastRCNN total loss: 0.26087 L1 loss: 0.0000e+00 L2 loss: 0.86454 Learning rate: 0.02 Mask loss: 0.13201 RPN box loss: 0.02983 RPN score loss: 0.00409 RPN total loss: 0.03392 Total loss: 1.29133 timestamp: 1654936552.5229576 iteration: 28265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16508 FastRCNN class loss: 0.07455 FastRCNN total loss: 0.23963 L1 loss: 0.0000e+00 L2 loss: 0.86439 Learning rate: 0.02 Mask loss: 0.16102 RPN box loss: 0.01947 RPN score loss: 0.00378 RPN total loss: 0.02325 Total loss: 1.2883 timestamp: 1654936555.7833703 iteration: 28270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20565 FastRCNN class loss: 0.11099 FastRCNN total loss: 0.31664 L1 loss: 0.0000e+00 L2 loss: 0.86425 Learning rate: 0.02 Mask loss: 0.24588 RPN box loss: 0.0434 RPN score loss: 0.00973 RPN total loss: 0.05313 Total loss: 1.4799 timestamp: 1654936559.0604148 iteration: 28275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15868 FastRCNN class loss: 0.11246 FastRCNN total loss: 0.27113 L1 loss: 0.0000e+00 L2 loss: 0.86411 Learning rate: 0.02 Mask loss: 0.18886 RPN box loss: 0.04402 RPN score loss: 0.00643 RPN total loss: 0.05045 Total loss: 1.37455 timestamp: 1654936562.2825003 iteration: 28280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14518 FastRCNN class loss: 0.1045 FastRCNN total loss: 0.24969 L1 loss: 0.0000e+00 L2 loss: 0.86399 Learning rate: 0.02 Mask loss: 0.24417 RPN box loss: 0.01237 RPN score loss: 0.006 RPN total loss: 0.01837 Total loss: 1.37621 timestamp: 1654936565.4571908 iteration: 28285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17553 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.24222 L1 loss: 0.0000e+00 L2 loss: 0.86386 Learning rate: 0.02 Mask loss: 0.13499 RPN box loss: 0.01566 RPN score loss: 0.00557 RPN total loss: 0.02123 Total loss: 1.2623 timestamp: 1654936568.6960094 iteration: 28290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15923 FastRCNN class loss: 0.0971 FastRCNN total loss: 0.25633 L1 loss: 0.0000e+00 L2 loss: 0.86373 Learning rate: 0.02 Mask loss: 0.23125 RPN box loss: 0.02602 RPN score loss: 0.00537 RPN total loss: 0.03139 Total loss: 1.38271 timestamp: 1654936571.890644 iteration: 28295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17069 FastRCNN class loss: 0.13354 FastRCNN total loss: 0.30423 L1 loss: 0.0000e+00 L2 loss: 0.8636 Learning rate: 0.02 Mask loss: 0.21971 RPN box loss: 0.08174 RPN score loss: 0.00931 RPN total loss: 0.09105 Total loss: 1.47858 timestamp: 1654936575.0710366 iteration: 28300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11115 FastRCNN class loss: 0.15993 FastRCNN total loss: 0.27108 L1 loss: 0.0000e+00 L2 loss: 0.86346 Learning rate: 0.02 Mask loss: 0.20262 RPN box loss: 0.05174 RPN score loss: 0.01426 RPN total loss: 0.066 Total loss: 1.40315 timestamp: 1654936578.255343 iteration: 28305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18856 FastRCNN class loss: 0.07291 FastRCNN total loss: 0.26147 L1 loss: 0.0000e+00 L2 loss: 0.86334 Learning rate: 0.02 Mask loss: 0.12016 RPN box loss: 0.05738 RPN score loss: 0.00415 RPN total loss: 0.06153 Total loss: 1.3065 timestamp: 1654936581.467069 iteration: 28310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17721 FastRCNN class loss: 0.15641 FastRCNN total loss: 0.33363 L1 loss: 0.0000e+00 L2 loss: 0.86323 Learning rate: 0.02 Mask loss: 0.21714 RPN box loss: 0.0469 RPN score loss: 0.01855 RPN total loss: 0.06545 Total loss: 1.47944 timestamp: 1654936584.6559348 iteration: 28315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14799 FastRCNN class loss: 0.15412 FastRCNN total loss: 0.30211 L1 loss: 0.0000e+00 L2 loss: 0.86309 Learning rate: 0.02 Mask loss: 0.15751 RPN box loss: 0.04409 RPN score loss: 0.01582 RPN total loss: 0.0599 Total loss: 1.38262 timestamp: 1654936587.8975582 iteration: 28320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.108 FastRCNN class loss: 0.10499 FastRCNN total loss: 0.21299 L1 loss: 0.0000e+00 L2 loss: 0.86295 Learning rate: 0.02 Mask loss: 0.12473 RPN box loss: 0.01913 RPN score loss: 0.00607 RPN total loss: 0.0252 Total loss: 1.22588 timestamp: 1654936591.0952969 iteration: 28325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.0643 FastRCNN total loss: 0.15409 L1 loss: 0.0000e+00 L2 loss: 0.86283 Learning rate: 0.02 Mask loss: 0.1054 RPN box loss: 0.01181 RPN score loss: 0.0066 RPN total loss: 0.01841 Total loss: 1.14072 timestamp: 1654936594.2097135 iteration: 28330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08912 FastRCNN class loss: 0.08076 FastRCNN total loss: 0.16988 L1 loss: 0.0000e+00 L2 loss: 0.86271 Learning rate: 0.02 Mask loss: 0.14293 RPN box loss: 0.00581 RPN score loss: 0.0035 RPN total loss: 0.00931 Total loss: 1.18482 timestamp: 1654936597.4461882 iteration: 28335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12932 FastRCNN class loss: 0.08403 FastRCNN total loss: 0.21335 L1 loss: 0.0000e+00 L2 loss: 0.8626 Learning rate: 0.02 Mask loss: 0.16064 RPN box loss: 0.03377 RPN score loss: 0.0033 RPN total loss: 0.03707 Total loss: 1.27366 timestamp: 1654936600.6242282 iteration: 28340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09469 FastRCNN class loss: 0.08124 FastRCNN total loss: 0.17593 L1 loss: 0.0000e+00 L2 loss: 0.86246 Learning rate: 0.02 Mask loss: 0.15064 RPN box loss: 0.0216 RPN score loss: 0.00386 RPN total loss: 0.02546 Total loss: 1.21448 timestamp: 1654936603.8697982 iteration: 28345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11427 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.19393 L1 loss: 0.0000e+00 L2 loss: 0.86234 Learning rate: 0.02 Mask loss: 0.1503 RPN box loss: 0.03319 RPN score loss: 0.00657 RPN total loss: 0.03976 Total loss: 1.24632 timestamp: 1654936607.0388358 iteration: 28350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19055 FastRCNN class loss: 0.113 FastRCNN total loss: 0.30355 L1 loss: 0.0000e+00 L2 loss: 0.86221 Learning rate: 0.02 Mask loss: 0.2116 RPN box loss: 0.02303 RPN score loss: 0.00442 RPN total loss: 0.02745 Total loss: 1.40481 timestamp: 1654936610.2894754 iteration: 28355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19676 FastRCNN class loss: 0.0812 FastRCNN total loss: 0.27796 L1 loss: 0.0000e+00 L2 loss: 0.86209 Learning rate: 0.02 Mask loss: 0.15166 RPN box loss: 0.03663 RPN score loss: 0.00553 RPN total loss: 0.04216 Total loss: 1.33387 timestamp: 1654936613.4943 iteration: 28360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13353 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.21915 L1 loss: 0.0000e+00 L2 loss: 0.86194 Learning rate: 0.02 Mask loss: 0.13549 RPN box loss: 0.01223 RPN score loss: 0.00564 RPN total loss: 0.01787 Total loss: 1.23445 timestamp: 1654936616.7593963 iteration: 28365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07567 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.13053 L1 loss: 0.0000e+00 L2 loss: 0.86182 Learning rate: 0.02 Mask loss: 0.17062 RPN box loss: 0.01002 RPN score loss: 0.00255 RPN total loss: 0.01257 Total loss: 1.17554 timestamp: 1654936620.0064414 iteration: 28370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18897 FastRCNN class loss: 0.11468 FastRCNN total loss: 0.30365 L1 loss: 0.0000e+00 L2 loss: 0.8617 Learning rate: 0.02 Mask loss: 0.1487 RPN box loss: 0.01939 RPN score loss: 0.00279 RPN total loss: 0.02218 Total loss: 1.33622 timestamp: 1654936623.231086 iteration: 28375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1356 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.19505 L1 loss: 0.0000e+00 L2 loss: 0.86155 Learning rate: 0.02 Mask loss: 0.13867 RPN box loss: 0.00995 RPN score loss: 0.00297 RPN total loss: 0.01292 Total loss: 1.20819 timestamp: 1654936626.5250268 iteration: 28380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13948 FastRCNN class loss: 0.09488 FastRCNN total loss: 0.23435 L1 loss: 0.0000e+00 L2 loss: 0.86142 Learning rate: 0.02 Mask loss: 0.1553 RPN box loss: 0.02192 RPN score loss: 0.01245 RPN total loss: 0.03436 Total loss: 1.28543 timestamp: 1654936629.8183846 iteration: 28385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22495 FastRCNN class loss: 0.10126 FastRCNN total loss: 0.32622 L1 loss: 0.0000e+00 L2 loss: 0.86129 Learning rate: 0.02 Mask loss: 0.17312 RPN box loss: 0.01381 RPN score loss: 0.00696 RPN total loss: 0.02077 Total loss: 1.3814 timestamp: 1654936633.0280979 iteration: 28390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12083 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.21065 L1 loss: 0.0000e+00 L2 loss: 0.86119 Learning rate: 0.02 Mask loss: 0.15576 RPN box loss: 0.02552 RPN score loss: 0.00672 RPN total loss: 0.03224 Total loss: 1.25985 timestamp: 1654936636.1353204 iteration: 28395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10087 FastRCNN class loss: 0.04954 FastRCNN total loss: 0.15041 L1 loss: 0.0000e+00 L2 loss: 0.86106 Learning rate: 0.02 Mask loss: 0.09395 RPN box loss: 0.03816 RPN score loss: 0.00524 RPN total loss: 0.0434 Total loss: 1.14882 timestamp: 1654936639.3802783 iteration: 28400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13377 FastRCNN class loss: 0.10226 FastRCNN total loss: 0.23603 L1 loss: 0.0000e+00 L2 loss: 0.86094 Learning rate: 0.02 Mask loss: 0.18958 RPN box loss: 0.07584 RPN score loss: 0.01509 RPN total loss: 0.09092 Total loss: 1.37747 timestamp: 1654936642.5909693 iteration: 28405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10768 FastRCNN class loss: 0.075 FastRCNN total loss: 0.18268 L1 loss: 0.0000e+00 L2 loss: 0.86081 Learning rate: 0.02 Mask loss: 0.14849 RPN box loss: 0.00536 RPN score loss: 0.00458 RPN total loss: 0.00994 Total loss: 1.20193 timestamp: 1654936645.7490203 iteration: 28410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21254 FastRCNN class loss: 0.18934 FastRCNN total loss: 0.40188 L1 loss: 0.0000e+00 L2 loss: 0.86069 Learning rate: 0.02 Mask loss: 0.1672 RPN box loss: 0.01999 RPN score loss: 0.01671 RPN total loss: 0.0367 Total loss: 1.46647 timestamp: 1654936648.9841442 iteration: 28415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.211 FastRCNN class loss: 0.13225 FastRCNN total loss: 0.34325 L1 loss: 0.0000e+00 L2 loss: 0.86056 Learning rate: 0.02 Mask loss: 0.20507 RPN box loss: 0.05503 RPN score loss: 0.0096 RPN total loss: 0.06462 Total loss: 1.47351 timestamp: 1654936652.1974928 iteration: 28420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09107 FastRCNN class loss: 0.08789 FastRCNN total loss: 0.17896 L1 loss: 0.0000e+00 L2 loss: 0.86043 Learning rate: 0.02 Mask loss: 0.16551 RPN box loss: 0.05901 RPN score loss: 0.01749 RPN total loss: 0.0765 Total loss: 1.2814 timestamp: 1654936655.3761983 iteration: 28425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06675 FastRCNN class loss: 0.04986 FastRCNN total loss: 0.1166 L1 loss: 0.0000e+00 L2 loss: 0.86029 Learning rate: 0.02 Mask loss: 0.08146 RPN box loss: 0.0536 RPN score loss: 0.00285 RPN total loss: 0.05645 Total loss: 1.1148 timestamp: 1654936658.6322107 iteration: 28430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17361 FastRCNN class loss: 0.09507 FastRCNN total loss: 0.26868 L1 loss: 0.0000e+00 L2 loss: 0.86016 Learning rate: 0.02 Mask loss: 0.19837 RPN box loss: 0.0264 RPN score loss: 0.00553 RPN total loss: 0.03193 Total loss: 1.35915 timestamp: 1654936661.8638802 iteration: 28435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1622 FastRCNN class loss: 0.0929 FastRCNN total loss: 0.2551 L1 loss: 0.0000e+00 L2 loss: 0.86006 Learning rate: 0.02 Mask loss: 0.19095 RPN box loss: 0.03007 RPN score loss: 0.00986 RPN total loss: 0.03992 Total loss: 1.34604 timestamp: 1654936665.1219904 iteration: 28440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09171 FastRCNN class loss: 0.064 FastRCNN total loss: 0.15571 L1 loss: 0.0000e+00 L2 loss: 0.85995 Learning rate: 0.02 Mask loss: 0.12968 RPN box loss: 0.0173 RPN score loss: 0.0015 RPN total loss: 0.0188 Total loss: 1.16414 timestamp: 1654936668.2665033 iteration: 28445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12442 FastRCNN class loss: 0.07047 FastRCNN total loss: 0.19489 L1 loss: 0.0000e+00 L2 loss: 0.85978 Learning rate: 0.02 Mask loss: 0.09369 RPN box loss: 0.02156 RPN score loss: 0.00357 RPN total loss: 0.02513 Total loss: 1.17349 timestamp: 1654936671.433973 iteration: 28450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23975 FastRCNN class loss: 0.08678 FastRCNN total loss: 0.32653 L1 loss: 0.0000e+00 L2 loss: 0.85964 Learning rate: 0.02 Mask loss: 0.21535 RPN box loss: 0.04537 RPN score loss: 0.00437 RPN total loss: 0.04974 Total loss: 1.45126 timestamp: 1654936674.6423113 iteration: 28455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13616 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.22657 L1 loss: 0.0000e+00 L2 loss: 0.85949 Learning rate: 0.02 Mask loss: 0.12536 RPN box loss: 0.04966 RPN score loss: 0.01742 RPN total loss: 0.06709 Total loss: 1.27851 timestamp: 1654936677.8139014 iteration: 28460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13384 FastRCNN class loss: 0.11452 FastRCNN total loss: 0.24836 L1 loss: 0.0000e+00 L2 loss: 0.85938 Learning rate: 0.02 Mask loss: 0.26844 RPN box loss: 0.02761 RPN score loss: 0.00799 RPN total loss: 0.0356 Total loss: 1.41178 timestamp: 1654936680.9552336 iteration: 28465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09027 FastRCNN class loss: 0.05268 FastRCNN total loss: 0.14295 L1 loss: 0.0000e+00 L2 loss: 0.85924 Learning rate: 0.02 Mask loss: 0.10028 RPN box loss: 0.01784 RPN score loss: 0.00387 RPN total loss: 0.02171 Total loss: 1.12417 timestamp: 1654936684.2262077 iteration: 28470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12212 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.18999 L1 loss: 0.0000e+00 L2 loss: 0.85909 Learning rate: 0.02 Mask loss: 0.19776 RPN box loss: 0.01916 RPN score loss: 0.00866 RPN total loss: 0.02782 Total loss: 1.27466 timestamp: 1654936687.4707725 iteration: 28475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09509 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.16848 L1 loss: 0.0000e+00 L2 loss: 0.85895 Learning rate: 0.02 Mask loss: 0.10417 RPN box loss: 0.01642 RPN score loss: 0.00478 RPN total loss: 0.0212 Total loss: 1.15281 timestamp: 1654936690.6610234 iteration: 28480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16367 FastRCNN class loss: 0.08456 FastRCNN total loss: 0.24823 L1 loss: 0.0000e+00 L2 loss: 0.85881 Learning rate: 0.02 Mask loss: 0.17019 RPN box loss: 0.01743 RPN score loss: 0.0159 RPN total loss: 0.03332 Total loss: 1.31055 timestamp: 1654936693.8145847 iteration: 28485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08704 FastRCNN class loss: 0.05744 FastRCNN total loss: 0.14447 L1 loss: 0.0000e+00 L2 loss: 0.85869 Learning rate: 0.02 Mask loss: 0.1271 RPN box loss: 0.06282 RPN score loss: 0.00499 RPN total loss: 0.06781 Total loss: 1.19809 timestamp: 1654936697.028583 iteration: 28490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08235 FastRCNN class loss: 0.07767 FastRCNN total loss: 0.16002 L1 loss: 0.0000e+00 L2 loss: 0.85859 Learning rate: 0.02 Mask loss: 0.10806 RPN box loss: 0.06199 RPN score loss: 0.00455 RPN total loss: 0.06654 Total loss: 1.19321 timestamp: 1654936700.1856518 iteration: 28495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09384 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.15658 L1 loss: 0.0000e+00 L2 loss: 0.85845 Learning rate: 0.02 Mask loss: 0.08679 RPN box loss: 0.01709 RPN score loss: 0.00503 RPN total loss: 0.02211 Total loss: 1.12394 timestamp: 1654936703.317107 iteration: 28500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22576 FastRCNN class loss: 0.11757 FastRCNN total loss: 0.34333 L1 loss: 0.0000e+00 L2 loss: 0.85834 Learning rate: 0.02 Mask loss: 0.23672 RPN box loss: 0.05412 RPN score loss: 0.00613 RPN total loss: 0.06024 Total loss: 1.49863 timestamp: 1654936706.4822702 iteration: 28505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09128 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.15572 L1 loss: 0.0000e+00 L2 loss: 0.85821 Learning rate: 0.02 Mask loss: 0.14574 RPN box loss: 0.0259 RPN score loss: 0.00595 RPN total loss: 0.03185 Total loss: 1.19153 timestamp: 1654936709.6477382 iteration: 28510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15695 FastRCNN class loss: 0.09922 FastRCNN total loss: 0.25618 L1 loss: 0.0000e+00 L2 loss: 0.85809 Learning rate: 0.02 Mask loss: 0.21181 RPN box loss: 0.01385 RPN score loss: 0.0064 RPN total loss: 0.02025 Total loss: 1.34634 timestamp: 1654936712.7996929 iteration: 28515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11527 FastRCNN class loss: 0.05247 FastRCNN total loss: 0.16774 L1 loss: 0.0000e+00 L2 loss: 0.85797 Learning rate: 0.02 Mask loss: 0.09873 RPN box loss: 0.07696 RPN score loss: 0.00429 RPN total loss: 0.08124 Total loss: 1.20568 timestamp: 1654936716.0385954 iteration: 28520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13122 FastRCNN class loss: 0.05507 FastRCNN total loss: 0.1863 L1 loss: 0.0000e+00 L2 loss: 0.85787 Learning rate: 0.02 Mask loss: 0.14807 RPN box loss: 0.00999 RPN score loss: 0.00156 RPN total loss: 0.01155 Total loss: 1.20378 timestamp: 1654936719.2820153 iteration: 28525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09792 FastRCNN class loss: 0.06912 FastRCNN total loss: 0.16705 L1 loss: 0.0000e+00 L2 loss: 0.85774 Learning rate: 0.02 Mask loss: 0.10814 RPN box loss: 0.01986 RPN score loss: 0.00326 RPN total loss: 0.02313 Total loss: 1.15606 timestamp: 1654936722.4253273 iteration: 28530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14529 FastRCNN class loss: 0.07397 FastRCNN total loss: 0.21926 L1 loss: 0.0000e+00 L2 loss: 0.85763 Learning rate: 0.02 Mask loss: 0.12802 RPN box loss: 0.01431 RPN score loss: 0.00726 RPN total loss: 0.02158 Total loss: 1.22649 timestamp: 1654936725.6128924 iteration: 28535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10313 FastRCNN class loss: 0.08573 FastRCNN total loss: 0.18886 L1 loss: 0.0000e+00 L2 loss: 0.8575 Learning rate: 0.02 Mask loss: 0.21193 RPN box loss: 0.02822 RPN score loss: 0.00195 RPN total loss: 0.03017 Total loss: 1.28847 timestamp: 1654936728.7572284 iteration: 28540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20277 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.30352 L1 loss: 0.0000e+00 L2 loss: 0.85737 Learning rate: 0.02 Mask loss: 0.13038 RPN box loss: 0.01312 RPN score loss: 0.00232 RPN total loss: 0.01544 Total loss: 1.30671 timestamp: 1654936731.9447038 iteration: 28545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10333 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.18027 L1 loss: 0.0000e+00 L2 loss: 0.85726 Learning rate: 0.02 Mask loss: 0.15109 RPN box loss: 0.01131 RPN score loss: 0.00674 RPN total loss: 0.01805 Total loss: 1.20667 timestamp: 1654936735.2057118 iteration: 28550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11511 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 0.85713 Learning rate: 0.02 Mask loss: 0.15787 RPN box loss: 0.02715 RPN score loss: 0.01084 RPN total loss: 0.038 Total loss: 1.23765 timestamp: 1654936738.386633 iteration: 28555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1563 FastRCNN class loss: 0.11459 FastRCNN total loss: 0.27089 L1 loss: 0.0000e+00 L2 loss: 0.85701 Learning rate: 0.02 Mask loss: 0.19519 RPN box loss: 0.08712 RPN score loss: 0.01388 RPN total loss: 0.101 Total loss: 1.4241 timestamp: 1654936741.658404 iteration: 28560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16256 FastRCNN class loss: 0.12271 FastRCNN total loss: 0.28527 L1 loss: 0.0000e+00 L2 loss: 0.85689 Learning rate: 0.02 Mask loss: 0.21523 RPN box loss: 0.04689 RPN score loss: 0.01578 RPN total loss: 0.06267 Total loss: 1.42005 timestamp: 1654936744.896551 iteration: 28565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11228 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.17897 L1 loss: 0.0000e+00 L2 loss: 0.85676 Learning rate: 0.02 Mask loss: 0.12607 RPN box loss: 0.00925 RPN score loss: 0.00247 RPN total loss: 0.01172 Total loss: 1.17351 timestamp: 1654936748.1193626 iteration: 28570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1237 FastRCNN class loss: 0.07697 FastRCNN total loss: 0.20067 L1 loss: 0.0000e+00 L2 loss: 0.85664 Learning rate: 0.02 Mask loss: 0.11173 RPN box loss: 0.0633 RPN score loss: 0.00232 RPN total loss: 0.06562 Total loss: 1.23466 timestamp: 1654936751.3464246 iteration: 28575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14672 FastRCNN class loss: 0.10102 FastRCNN total loss: 0.24775 L1 loss: 0.0000e+00 L2 loss: 0.85652 Learning rate: 0.02 Mask loss: 0.13697 RPN box loss: 0.0376 RPN score loss: 0.00858 RPN total loss: 0.04619 Total loss: 1.28742 timestamp: 1654936754.5750475 iteration: 28580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14721 FastRCNN class loss: 0.09267 FastRCNN total loss: 0.23988 L1 loss: 0.0000e+00 L2 loss: 0.85639 Learning rate: 0.02 Mask loss: 0.1657 RPN box loss: 0.01814 RPN score loss: 0.00542 RPN total loss: 0.02356 Total loss: 1.28553 timestamp: 1654936757.7381725 iteration: 28585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12415 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.21276 L1 loss: 0.0000e+00 L2 loss: 0.85628 Learning rate: 0.02 Mask loss: 0.14971 RPN box loss: 0.04124 RPN score loss: 0.01427 RPN total loss: 0.05551 Total loss: 1.27426 timestamp: 1654936760.9608803 iteration: 28590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15062 FastRCNN class loss: 0.09128 FastRCNN total loss: 0.2419 L1 loss: 0.0000e+00 L2 loss: 0.85618 Learning rate: 0.02 Mask loss: 0.24645 RPN box loss: 0.05124 RPN score loss: 0.00273 RPN total loss: 0.05397 Total loss: 1.39849 timestamp: 1654936764.221864 iteration: 28595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14344 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.20872 L1 loss: 0.0000e+00 L2 loss: 0.85605 Learning rate: 0.02 Mask loss: 0.15843 RPN box loss: 0.01425 RPN score loss: 0.00501 RPN total loss: 0.01926 Total loss: 1.24245 timestamp: 1654936767.3967822 iteration: 28600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.183 FastRCNN class loss: 0.14536 FastRCNN total loss: 0.32836 L1 loss: 0.0000e+00 L2 loss: 0.85594 Learning rate: 0.02 Mask loss: 0.22856 RPN box loss: 0.03853 RPN score loss: 0.01399 RPN total loss: 0.05252 Total loss: 1.46538 timestamp: 1654936770.682358 iteration: 28605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0738 FastRCNN class loss: 0.10341 FastRCNN total loss: 0.17721 L1 loss: 0.0000e+00 L2 loss: 0.85579 Learning rate: 0.02 Mask loss: 0.16015 RPN box loss: 0.01813 RPN score loss: 0.01005 RPN total loss: 0.02818 Total loss: 1.22133 timestamp: 1654936773.935064 iteration: 28610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0856 FastRCNN class loss: 0.0552 FastRCNN total loss: 0.1408 L1 loss: 0.0000e+00 L2 loss: 0.85567 Learning rate: 0.02 Mask loss: 0.12235 RPN box loss: 0.06462 RPN score loss: 0.00514 RPN total loss: 0.06976 Total loss: 1.18858 timestamp: 1654936777.0758815 iteration: 28615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13597 FastRCNN class loss: 0.09978 FastRCNN total loss: 0.23575 L1 loss: 0.0000e+00 L2 loss: 0.85557 Learning rate: 0.02 Mask loss: 0.15949 RPN box loss: 0.03123 RPN score loss: 0.00768 RPN total loss: 0.03891 Total loss: 1.28972 timestamp: 1654936780.3116634 iteration: 28620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12555 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.20038 L1 loss: 0.0000e+00 L2 loss: 0.85544 Learning rate: 0.02 Mask loss: 0.10484 RPN box loss: 0.05647 RPN score loss: 0.01102 RPN total loss: 0.06748 Total loss: 1.22813 timestamp: 1654936783.5793486 iteration: 28625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1143 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 0.85531 Learning rate: 0.02 Mask loss: 0.20192 RPN box loss: 0.0237 RPN score loss: 0.00651 RPN total loss: 0.0302 Total loss: 1.26398 timestamp: 1654936786.746131 iteration: 28630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07633 FastRCNN class loss: 0.06272 FastRCNN total loss: 0.13905 L1 loss: 0.0000e+00 L2 loss: 0.85516 Learning rate: 0.02 Mask loss: 0.1262 RPN box loss: 0.01306 RPN score loss: 0.00475 RPN total loss: 0.0178 Total loss: 1.13822 timestamp: 1654936789.9480095 iteration: 28635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19797 FastRCNN class loss: 0.09746 FastRCNN total loss: 0.29543 L1 loss: 0.0000e+00 L2 loss: 0.85504 Learning rate: 0.02 Mask loss: 0.16506 RPN box loss: 0.05755 RPN score loss: 0.02755 RPN total loss: 0.0851 Total loss: 1.40063 timestamp: 1654936793.129986 iteration: 28640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18867 FastRCNN class loss: 0.10919 FastRCNN total loss: 0.29786 L1 loss: 0.0000e+00 L2 loss: 0.85492 Learning rate: 0.02 Mask loss: 0.13443 RPN box loss: 0.01399 RPN score loss: 0.00695 RPN total loss: 0.02094 Total loss: 1.30815 timestamp: 1654936796.3741853 iteration: 28645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10347 FastRCNN class loss: 0.06001 FastRCNN total loss: 0.16348 L1 loss: 0.0000e+00 L2 loss: 0.85481 Learning rate: 0.02 Mask loss: 0.13851 RPN box loss: 0.05686 RPN score loss: 0.0088 RPN total loss: 0.06565 Total loss: 1.22245 timestamp: 1654936799.6262317 iteration: 28650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11218 FastRCNN class loss: 0.10679 FastRCNN total loss: 0.21897 L1 loss: 0.0000e+00 L2 loss: 0.85469 Learning rate: 0.02 Mask loss: 0.15632 RPN box loss: 0.01757 RPN score loss: 0.00405 RPN total loss: 0.02162 Total loss: 1.2516 timestamp: 1654936802.7934716 iteration: 28655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18833 FastRCNN class loss: 0.12222 FastRCNN total loss: 0.31055 L1 loss: 0.0000e+00 L2 loss: 0.85455 Learning rate: 0.02 Mask loss: 0.19328 RPN box loss: 0.03205 RPN score loss: 0.00842 RPN total loss: 0.04047 Total loss: 1.39884 timestamp: 1654936805.9658632 iteration: 28660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17328 FastRCNN class loss: 0.12946 FastRCNN total loss: 0.30274 L1 loss: 0.0000e+00 L2 loss: 0.85441 Learning rate: 0.02 Mask loss: 0.17229 RPN box loss: 0.03178 RPN score loss: 0.00931 RPN total loss: 0.04109 Total loss: 1.37054 timestamp: 1654936809.1159406 iteration: 28665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11842 FastRCNN class loss: 0.0614 FastRCNN total loss: 0.17982 L1 loss: 0.0000e+00 L2 loss: 0.85429 Learning rate: 0.02 Mask loss: 0.13858 RPN box loss: 0.03661 RPN score loss: 0.00647 RPN total loss: 0.04308 Total loss: 1.21577 timestamp: 1654936812.3860395 iteration: 28670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1508 FastRCNN class loss: 0.13405 FastRCNN total loss: 0.28485 L1 loss: 0.0000e+00 L2 loss: 0.85419 Learning rate: 0.02 Mask loss: 0.20945 RPN box loss: 0.0305 RPN score loss: 0.01145 RPN total loss: 0.04195 Total loss: 1.39043 timestamp: 1654936815.5765977 iteration: 28675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12467 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.19858 L1 loss: 0.0000e+00 L2 loss: 0.85403 Learning rate: 0.02 Mask loss: 0.13073 RPN box loss: 0.03445 RPN score loss: 0.00702 RPN total loss: 0.04147 Total loss: 1.22482 timestamp: 1654936818.7521825 iteration: 28680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08381 FastRCNN class loss: 0.03194 FastRCNN total loss: 0.11575 L1 loss: 0.0000e+00 L2 loss: 0.85393 Learning rate: 0.02 Mask loss: 0.0823 RPN box loss: 0.0125 RPN score loss: 0.00375 RPN total loss: 0.01624 Total loss: 1.06823 timestamp: 1654936822.0727267 iteration: 28685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17888 FastRCNN class loss: 0.1417 FastRCNN total loss: 0.32058 L1 loss: 0.0000e+00 L2 loss: 0.85385 Learning rate: 0.02 Mask loss: 0.17001 RPN box loss: 0.02548 RPN score loss: 0.00773 RPN total loss: 0.03321 Total loss: 1.37765 timestamp: 1654936825.2979023 iteration: 28690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.85373 Learning rate: 0.02 Mask loss: 0.13997 RPN box loss: 0.00773 RPN score loss: 0.00191 RPN total loss: 0.00964 Total loss: 1.18526 timestamp: 1654936828.5962193 iteration: 28695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12108 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.18696 L1 loss: 0.0000e+00 L2 loss: 0.85358 Learning rate: 0.02 Mask loss: 0.15761 RPN box loss: 0.01278 RPN score loss: 0.00206 RPN total loss: 0.01484 Total loss: 1.21299 timestamp: 1654936831.825289 iteration: 28700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.21384 L1 loss: 0.0000e+00 L2 loss: 0.85344 Learning rate: 0.02 Mask loss: 0.17433 RPN box loss: 0.01904 RPN score loss: 0.01149 RPN total loss: 0.03052 Total loss: 1.27213 timestamp: 1654936835.0567627 iteration: 28705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1066 FastRCNN class loss: 0.06343 FastRCNN total loss: 0.17002 L1 loss: 0.0000e+00 L2 loss: 0.85331 Learning rate: 0.02 Mask loss: 0.13878 RPN box loss: 0.02026 RPN score loss: 0.00599 RPN total loss: 0.02625 Total loss: 1.18836 timestamp: 1654936838.3072863 iteration: 28710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13316 FastRCNN class loss: 0.04747 FastRCNN total loss: 0.18063 L1 loss: 0.0000e+00 L2 loss: 0.85319 Learning rate: 0.02 Mask loss: 0.12467 RPN box loss: 0.00301 RPN score loss: 0.00127 RPN total loss: 0.00428 Total loss: 1.16277 timestamp: 1654936841.4794035 iteration: 28715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15994 FastRCNN class loss: 0.0981 FastRCNN total loss: 0.25804 L1 loss: 0.0000e+00 L2 loss: 0.85309 Learning rate: 0.02 Mask loss: 0.17123 RPN box loss: 0.04103 RPN score loss: 0.01202 RPN total loss: 0.05305 Total loss: 1.33541 timestamp: 1654936844.6851113 iteration: 28720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22506 FastRCNN class loss: 0.1085 FastRCNN total loss: 0.33356 L1 loss: 0.0000e+00 L2 loss: 0.85297 Learning rate: 0.02 Mask loss: 0.16394 RPN box loss: 0.02451 RPN score loss: 0.00892 RPN total loss: 0.03342 Total loss: 1.3839 timestamp: 1654936847.856151 iteration: 28725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05042 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.10525 L1 loss: 0.0000e+00 L2 loss: 0.85284 Learning rate: 0.02 Mask loss: 0.0896 RPN box loss: 0.00903 RPN score loss: 0.00353 RPN total loss: 0.01256 Total loss: 1.06025 timestamp: 1654936851.0797677 iteration: 28730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26597 FastRCNN class loss: 0.14989 FastRCNN total loss: 0.41587 L1 loss: 0.0000e+00 L2 loss: 0.85271 Learning rate: 0.02 Mask loss: 0.19498 RPN box loss: 0.04579 RPN score loss: 0.00604 RPN total loss: 0.05184 Total loss: 1.5154 timestamp: 1654936854.3219311 iteration: 28735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11479 FastRCNN class loss: 0.10853 FastRCNN total loss: 0.22332 L1 loss: 0.0000e+00 L2 loss: 0.85256 Learning rate: 0.02 Mask loss: 0.17773 RPN box loss: 0.02508 RPN score loss: 0.01526 RPN total loss: 0.04033 Total loss: 1.29394 timestamp: 1654936857.4622128 iteration: 28740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24508 FastRCNN class loss: 0.12188 FastRCNN total loss: 0.36696 L1 loss: 0.0000e+00 L2 loss: 0.85244 Learning rate: 0.02 Mask loss: 0.24954 RPN box loss: 0.04261 RPN score loss: 0.00327 RPN total loss: 0.04588 Total loss: 1.51482 timestamp: 1654936860.6426396 iteration: 28745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08453 FastRCNN class loss: 0.04605 FastRCNN total loss: 0.13058 L1 loss: 0.0000e+00 L2 loss: 0.85232 Learning rate: 0.02 Mask loss: 0.13165 RPN box loss: 0.00628 RPN score loss: 0.01112 RPN total loss: 0.0174 Total loss: 1.13195 timestamp: 1654936863.7980287 iteration: 28750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13039 FastRCNN class loss: 0.10086 FastRCNN total loss: 0.23125 L1 loss: 0.0000e+00 L2 loss: 0.85218 Learning rate: 0.02 Mask loss: 0.19456 RPN box loss: 0.02943 RPN score loss: 0.01003 RPN total loss: 0.03946 Total loss: 1.31745 timestamp: 1654936866.9780655 iteration: 28755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09419 FastRCNN class loss: 0.09573 FastRCNN total loss: 0.18992 L1 loss: 0.0000e+00 L2 loss: 0.85204 Learning rate: 0.02 Mask loss: 0.11057 RPN box loss: 0.01476 RPN score loss: 0.00421 RPN total loss: 0.01897 Total loss: 1.17149 timestamp: 1654936870.2057176 iteration: 28760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10766 FastRCNN class loss: 0.05147 FastRCNN total loss: 0.15913 L1 loss: 0.0000e+00 L2 loss: 0.8519 Learning rate: 0.02 Mask loss: 0.12589 RPN box loss: 0.0127 RPN score loss: 0.00279 RPN total loss: 0.01549 Total loss: 1.1524 timestamp: 1654936873.4537723 iteration: 28765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1854 FastRCNN class loss: 0.15171 FastRCNN total loss: 0.33711 L1 loss: 0.0000e+00 L2 loss: 0.85179 Learning rate: 0.02 Mask loss: 0.16838 RPN box loss: 0.0423 RPN score loss: 0.01379 RPN total loss: 0.05609 Total loss: 1.41337 timestamp: 1654936876.689034 iteration: 28770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12406 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.18017 L1 loss: 0.0000e+00 L2 loss: 0.85166 Learning rate: 0.02 Mask loss: 0.11806 RPN box loss: 0.03707 RPN score loss: 0.00423 RPN total loss: 0.0413 Total loss: 1.19119 timestamp: 1654936879.9543993 iteration: 28775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16882 FastRCNN class loss: 0.09657 FastRCNN total loss: 0.26539 L1 loss: 0.0000e+00 L2 loss: 0.85152 Learning rate: 0.02 Mask loss: 0.16482 RPN box loss: 0.06077 RPN score loss: 0.01365 RPN total loss: 0.07441 Total loss: 1.35615 timestamp: 1654936883.1262007 iteration: 28780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14486 FastRCNN class loss: 0.07132 FastRCNN total loss: 0.21617 L1 loss: 0.0000e+00 L2 loss: 0.85142 Learning rate: 0.02 Mask loss: 0.10333 RPN box loss: 0.01972 RPN score loss: 0.00355 RPN total loss: 0.02328 Total loss: 1.1942 timestamp: 1654936886.2844396 iteration: 28785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10639 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.17537 L1 loss: 0.0000e+00 L2 loss: 0.85131 Learning rate: 0.02 Mask loss: 0.09749 RPN box loss: 0.05087 RPN score loss: 0.00789 RPN total loss: 0.05876 Total loss: 1.18292 timestamp: 1654936889.4763684 iteration: 28790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11942 FastRCNN class loss: 0.10461 FastRCNN total loss: 0.22402 L1 loss: 0.0000e+00 L2 loss: 0.85119 Learning rate: 0.02 Mask loss: 0.17154 RPN box loss: 0.03543 RPN score loss: 0.01125 RPN total loss: 0.04667 Total loss: 1.29343 timestamp: 1654936892.6519783 iteration: 28795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10895 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.18032 L1 loss: 0.0000e+00 L2 loss: 0.85105 Learning rate: 0.02 Mask loss: 0.1675 RPN box loss: 0.10904 RPN score loss: 0.01436 RPN total loss: 0.1234 Total loss: 1.32227 timestamp: 1654936895.8197343 iteration: 28800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17282 FastRCNN class loss: 0.06142 FastRCNN total loss: 0.23425 L1 loss: 0.0000e+00 L2 loss: 0.85095 Learning rate: 0.02 Mask loss: 0.12256 RPN box loss: 0.01329 RPN score loss: 0.00506 RPN total loss: 0.01835 Total loss: 1.2261 timestamp: 1654936899.1159585 iteration: 28805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15851 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.24085 L1 loss: 0.0000e+00 L2 loss: 0.85083 Learning rate: 0.02 Mask loss: 0.1576 RPN box loss: 0.02579 RPN score loss: 0.00233 RPN total loss: 0.02813 Total loss: 1.2774 timestamp: 1654936902.310868 iteration: 28810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07302 FastRCNN class loss: 0.05368 FastRCNN total loss: 0.12669 L1 loss: 0.0000e+00 L2 loss: 0.8507 Learning rate: 0.02 Mask loss: 0.17493 RPN box loss: 0.01232 RPN score loss: 0.00213 RPN total loss: 0.01445 Total loss: 1.16677 timestamp: 1654936905.6212814 iteration: 28815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14037 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.22264 L1 loss: 0.0000e+00 L2 loss: 0.8506 Learning rate: 0.02 Mask loss: 0.20648 RPN box loss: 0.03338 RPN score loss: 0.01664 RPN total loss: 0.05002 Total loss: 1.32974 timestamp: 1654936908.8345287 iteration: 28820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1221 FastRCNN class loss: 0.12933 FastRCNN total loss: 0.25142 L1 loss: 0.0000e+00 L2 loss: 0.85046 Learning rate: 0.02 Mask loss: 0.21747 RPN box loss: 0.02549 RPN score loss: 0.03377 RPN total loss: 0.05926 Total loss: 1.37861 timestamp: 1654936912.1091661 iteration: 28825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11462 FastRCNN class loss: 0.0667 FastRCNN total loss: 0.18132 L1 loss: 0.0000e+00 L2 loss: 0.85032 Learning rate: 0.02 Mask loss: 0.19484 RPN box loss: 0.01537 RPN score loss: 0.00113 RPN total loss: 0.0165 Total loss: 1.24298 timestamp: 1654936915.3904574 iteration: 28830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10705 FastRCNN class loss: 0.05201 FastRCNN total loss: 0.15907 L1 loss: 0.0000e+00 L2 loss: 0.8502 Learning rate: 0.02 Mask loss: 0.15205 RPN box loss: 0.01273 RPN score loss: 0.00192 RPN total loss: 0.01465 Total loss: 1.17597 timestamp: 1654936918.6330044 iteration: 28835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10066 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.17908 L1 loss: 0.0000e+00 L2 loss: 0.85008 Learning rate: 0.02 Mask loss: 0.17789 RPN box loss: 0.04312 RPN score loss: 0.00276 RPN total loss: 0.04588 Total loss: 1.25293 timestamp: 1654936921.8223798 iteration: 28840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20873 FastRCNN class loss: 0.08554 FastRCNN total loss: 0.29427 L1 loss: 0.0000e+00 L2 loss: 0.84994 Learning rate: 0.02 Mask loss: 0.15559 RPN box loss: 0.04736 RPN score loss: 0.0045 RPN total loss: 0.05186 Total loss: 1.35166 timestamp: 1654936924.9899073 iteration: 28845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06826 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.13178 L1 loss: 0.0000e+00 L2 loss: 0.84984 Learning rate: 0.02 Mask loss: 0.14971 RPN box loss: 0.05375 RPN score loss: 0.0092 RPN total loss: 0.06296 Total loss: 1.19429 timestamp: 1654936928.1043234 iteration: 28850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17495 FastRCNN class loss: 0.07024 FastRCNN total loss: 0.24519 L1 loss: 0.0000e+00 L2 loss: 0.8497 Learning rate: 0.02 Mask loss: 0.10581 RPN box loss: 0.07316 RPN score loss: 0.00364 RPN total loss: 0.0768 Total loss: 1.2775 timestamp: 1654936931.2871432 iteration: 28855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21974 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.28963 L1 loss: 0.0000e+00 L2 loss: 0.84957 Learning rate: 0.02 Mask loss: 0.15805 RPN box loss: 0.07427 RPN score loss: 0.00478 RPN total loss: 0.07905 Total loss: 1.3763 timestamp: 1654936934.4389243 iteration: 28860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13496 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.20277 L1 loss: 0.0000e+00 L2 loss: 0.84946 Learning rate: 0.02 Mask loss: 0.15764 RPN box loss: 0.03624 RPN score loss: 0.00643 RPN total loss: 0.04267 Total loss: 1.25253 timestamp: 1654936937.6008205 iteration: 28865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11944 FastRCNN class loss: 0.04122 FastRCNN total loss: 0.16066 L1 loss: 0.0000e+00 L2 loss: 0.84932 Learning rate: 0.02 Mask loss: 0.16719 RPN box loss: 0.03322 RPN score loss: 0.00617 RPN total loss: 0.03939 Total loss: 1.21656 timestamp: 1654936940.7621362 iteration: 28870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20536 FastRCNN class loss: 0.13608 FastRCNN total loss: 0.34144 L1 loss: 0.0000e+00 L2 loss: 0.84919 Learning rate: 0.02 Mask loss: 0.17444 RPN box loss: 0.05191 RPN score loss: 0.02104 RPN total loss: 0.07295 Total loss: 1.43803 timestamp: 1654936943.974783 iteration: 28875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13958 FastRCNN class loss: 0.05573 FastRCNN total loss: 0.19531 L1 loss: 0.0000e+00 L2 loss: 0.84908 Learning rate: 0.02 Mask loss: 0.10836 RPN box loss: 0.01413 RPN score loss: 0.00319 RPN total loss: 0.01732 Total loss: 1.17007 timestamp: 1654936947.2713277 iteration: 28880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12444 FastRCNN class loss: 0.14132 FastRCNN total loss: 0.26577 L1 loss: 0.0000e+00 L2 loss: 0.84894 Learning rate: 0.02 Mask loss: 0.18113 RPN box loss: 0.04379 RPN score loss: 0.01266 RPN total loss: 0.05644 Total loss: 1.35229 timestamp: 1654936950.5082903 iteration: 28885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14965 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.20441 L1 loss: 0.0000e+00 L2 loss: 0.84884 Learning rate: 0.02 Mask loss: 0.109 RPN box loss: 0.0653 RPN score loss: 0.00541 RPN total loss: 0.07071 Total loss: 1.23295 timestamp: 1654936953.704761 iteration: 28890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11762 FastRCNN class loss: 0.06137 FastRCNN total loss: 0.17899 L1 loss: 0.0000e+00 L2 loss: 0.84873 Learning rate: 0.02 Mask loss: 0.15874 RPN box loss: 0.03934 RPN score loss: 0.00675 RPN total loss: 0.04609 Total loss: 1.23255 timestamp: 1654936956.9683053 iteration: 28895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14459 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.21818 L1 loss: 0.0000e+00 L2 loss: 0.84859 Learning rate: 0.02 Mask loss: 0.15142 RPN box loss: 0.06101 RPN score loss: 0.00456 RPN total loss: 0.06557 Total loss: 1.28376 timestamp: 1654936960.143059 iteration: 28900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10139 FastRCNN class loss: 0.08487 FastRCNN total loss: 0.18626 L1 loss: 0.0000e+00 L2 loss: 0.84843 Learning rate: 0.02 Mask loss: 0.1153 RPN box loss: 0.00735 RPN score loss: 0.00264 RPN total loss: 0.00999 Total loss: 1.15999 timestamp: 1654936963.3795686 iteration: 28905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12872 FastRCNN class loss: 0.10174 FastRCNN total loss: 0.23045 L1 loss: 0.0000e+00 L2 loss: 0.84832 Learning rate: 0.02 Mask loss: 0.17491 RPN box loss: 0.03365 RPN score loss: 0.00649 RPN total loss: 0.04014 Total loss: 1.29382 timestamp: 1654936966.5605824 iteration: 28910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13062 FastRCNN class loss: 0.11625 FastRCNN total loss: 0.24688 L1 loss: 0.0000e+00 L2 loss: 0.84818 Learning rate: 0.02 Mask loss: 0.15891 RPN box loss: 0.05164 RPN score loss: 0.0206 RPN total loss: 0.07224 Total loss: 1.32621 timestamp: 1654936969.7301228 iteration: 28915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20267 FastRCNN class loss: 0.07074 FastRCNN total loss: 0.27341 L1 loss: 0.0000e+00 L2 loss: 0.84804 Learning rate: 0.02 Mask loss: 0.15787 RPN box loss: 0.05249 RPN score loss: 0.00665 RPN total loss: 0.05914 Total loss: 1.33845 timestamp: 1654936972.9833343 iteration: 28920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1212 FastRCNN class loss: 0.12342 FastRCNN total loss: 0.24462 L1 loss: 0.0000e+00 L2 loss: 0.84793 Learning rate: 0.02 Mask loss: 0.13633 RPN box loss: 0.02029 RPN score loss: 0.00263 RPN total loss: 0.02292 Total loss: 1.2518 timestamp: 1654936976.1710784 iteration: 28925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09031 FastRCNN class loss: 0.05651 FastRCNN total loss: 0.14682 L1 loss: 0.0000e+00 L2 loss: 0.8478 Learning rate: 0.02 Mask loss: 0.10442 RPN box loss: 0.00966 RPN score loss: 0.00207 RPN total loss: 0.01173 Total loss: 1.11077 timestamp: 1654936979.3348098 iteration: 28930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11324 FastRCNN class loss: 0.08825 FastRCNN total loss: 0.20149 L1 loss: 0.0000e+00 L2 loss: 0.84768 Learning rate: 0.02 Mask loss: 0.10493 RPN box loss: 0.05052 RPN score loss: 0.00327 RPN total loss: 0.0538 Total loss: 1.20789 timestamp: 1654936982.5775514 iteration: 28935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20113 FastRCNN class loss: 0.13233 FastRCNN total loss: 0.33346 L1 loss: 0.0000e+00 L2 loss: 0.84756 Learning rate: 0.02 Mask loss: 0.26903 RPN box loss: 0.04394 RPN score loss: 0.01767 RPN total loss: 0.0616 Total loss: 1.51166 timestamp: 1654936985.6501746 iteration: 28940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11819 FastRCNN class loss: 0.10856 FastRCNN total loss: 0.22675 L1 loss: 0.0000e+00 L2 loss: 0.84745 Learning rate: 0.02 Mask loss: 0.18676 RPN box loss: 0.0322 RPN score loss: 0.00616 RPN total loss: 0.03836 Total loss: 1.29932 timestamp: 1654936988.852844 iteration: 28945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16886 FastRCNN class loss: 0.10072 FastRCNN total loss: 0.26957 L1 loss: 0.0000e+00 L2 loss: 0.8473 Learning rate: 0.02 Mask loss: 0.26981 RPN box loss: 0.01366 RPN score loss: 0.00608 RPN total loss: 0.01973 Total loss: 1.40641 timestamp: 1654936992.1066813 iteration: 28950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08133 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.16044 L1 loss: 0.0000e+00 L2 loss: 0.84719 Learning rate: 0.02 Mask loss: 0.13092 RPN box loss: 0.02461 RPN score loss: 0.00926 RPN total loss: 0.03387 Total loss: 1.17241 timestamp: 1654936995.2374213 iteration: 28955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12571 FastRCNN class loss: 0.08575 FastRCNN total loss: 0.21146 L1 loss: 0.0000e+00 L2 loss: 0.84707 Learning rate: 0.02 Mask loss: 0.15836 RPN box loss: 0.01181 RPN score loss: 0.00656 RPN total loss: 0.01837 Total loss: 1.23525 timestamp: 1654936998.3979461 iteration: 28960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19706 FastRCNN class loss: 0.09569 FastRCNN total loss: 0.29275 L1 loss: 0.0000e+00 L2 loss: 0.84694 Learning rate: 0.02 Mask loss: 0.15976 RPN box loss: 0.02976 RPN score loss: 0.00572 RPN total loss: 0.03548 Total loss: 1.33493 timestamp: 1654937001.630339 iteration: 28965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1848 FastRCNN class loss: 0.06011 FastRCNN total loss: 0.24491 L1 loss: 0.0000e+00 L2 loss: 0.84683 Learning rate: 0.02 Mask loss: 0.16372 RPN box loss: 0.02077 RPN score loss: 0.0049 RPN total loss: 0.02567 Total loss: 1.28113 timestamp: 1654937004.7414067 iteration: 28970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1409 FastRCNN class loss: 0.06001 FastRCNN total loss: 0.20091 L1 loss: 0.0000e+00 L2 loss: 0.8467 Learning rate: 0.02 Mask loss: 0.15464 RPN box loss: 0.02312 RPN score loss: 0.00157 RPN total loss: 0.02468 Total loss: 1.22694 timestamp: 1654937007.9576907 iteration: 28975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17265 FastRCNN class loss: 0.14211 FastRCNN total loss: 0.31476 L1 loss: 0.0000e+00 L2 loss: 0.84657 Learning rate: 0.02 Mask loss: 0.16508 RPN box loss: 0.01621 RPN score loss: 0.0021 RPN total loss: 0.0183 Total loss: 1.34471 timestamp: 1654937011.2126422 iteration: 28980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15165 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.21141 L1 loss: 0.0000e+00 L2 loss: 0.84645 Learning rate: 0.02 Mask loss: 0.10825 RPN box loss: 0.01891 RPN score loss: 0.00378 RPN total loss: 0.02268 Total loss: 1.18879 timestamp: 1654937014.4288452 iteration: 28985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09385 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.14886 L1 loss: 0.0000e+00 L2 loss: 0.84635 Learning rate: 0.02 Mask loss: 0.10151 RPN box loss: 0.02284 RPN score loss: 0.00301 RPN total loss: 0.02585 Total loss: 1.12256 timestamp: 1654937017.5427957 iteration: 28990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13819 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.21606 L1 loss: 0.0000e+00 L2 loss: 0.84623 Learning rate: 0.02 Mask loss: 0.1601 RPN box loss: 0.02181 RPN score loss: 0.00362 RPN total loss: 0.02543 Total loss: 1.24782 timestamp: 1654937020.7825885 iteration: 28995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07485 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.14221 L1 loss: 0.0000e+00 L2 loss: 0.84607 Learning rate: 0.02 Mask loss: 0.10971 RPN box loss: 0.0816 RPN score loss: 0.01369 RPN total loss: 0.09529 Total loss: 1.19327 timestamp: 1654937023.904736 iteration: 29000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13056 FastRCNN class loss: 0.03803 FastRCNN total loss: 0.16859 L1 loss: 0.0000e+00 L2 loss: 0.84594 Learning rate: 0.02 Mask loss: 0.10088 RPN box loss: 0.00454 RPN score loss: 0.00302 RPN total loss: 0.00756 Total loss: 1.12297 timestamp: 1654937027.1378806 iteration: 29005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16826 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.25049 L1 loss: 0.0000e+00 L2 loss: 0.84583 Learning rate: 0.02 Mask loss: 0.18445 RPN box loss: 0.01776 RPN score loss: 0.00504 RPN total loss: 0.0228 Total loss: 1.30357 timestamp: 1654937030.4168255 iteration: 29010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13322 FastRCNN class loss: 0.09364 FastRCNN total loss: 0.22686 L1 loss: 0.0000e+00 L2 loss: 0.84573 Learning rate: 0.02 Mask loss: 0.1195 RPN box loss: 0.0217 RPN score loss: 0.00569 RPN total loss: 0.0274 Total loss: 1.21949 timestamp: 1654937033.6226144 iteration: 29015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08295 FastRCNN class loss: 0.07939 FastRCNN total loss: 0.16233 L1 loss: 0.0000e+00 L2 loss: 0.8456 Learning rate: 0.02 Mask loss: 0.19087 RPN box loss: 0.02174 RPN score loss: 0.00604 RPN total loss: 0.02778 Total loss: 1.22658 timestamp: 1654937036.7945735 iteration: 29020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08798 FastRCNN class loss: 0.05716 FastRCNN total loss: 0.14514 L1 loss: 0.0000e+00 L2 loss: 0.84548 Learning rate: 0.02 Mask loss: 0.15523 RPN box loss: 0.07059 RPN score loss: 0.0038 RPN total loss: 0.07439 Total loss: 1.22023 timestamp: 1654937040.0393512 iteration: 29025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14785 FastRCNN class loss: 0.1165 FastRCNN total loss: 0.26435 L1 loss: 0.0000e+00 L2 loss: 0.84535 Learning rate: 0.02 Mask loss: 0.19633 RPN box loss: 0.01784 RPN score loss: 0.01604 RPN total loss: 0.03388 Total loss: 1.33991 timestamp: 1654937043.2086656 iteration: 29030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05748 FastRCNN class loss: 0.04335 FastRCNN total loss: 0.10083 L1 loss: 0.0000e+00 L2 loss: 0.84522 Learning rate: 0.02 Mask loss: 0.11347 RPN box loss: 0.05936 RPN score loss: 0.00414 RPN total loss: 0.0635 Total loss: 1.12302 timestamp: 1654937046.3917897 iteration: 29035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17432 FastRCNN class loss: 0.1538 FastRCNN total loss: 0.32812 L1 loss: 0.0000e+00 L2 loss: 0.84509 Learning rate: 0.02 Mask loss: 0.25732 RPN box loss: 0.04839 RPN score loss: 0.00666 RPN total loss: 0.05504 Total loss: 1.48557 timestamp: 1654937049.621163 iteration: 29040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17141 FastRCNN class loss: 0.17844 FastRCNN total loss: 0.34986 L1 loss: 0.0000e+00 L2 loss: 0.84495 Learning rate: 0.02 Mask loss: 0.17822 RPN box loss: 0.02526 RPN score loss: 0.00637 RPN total loss: 0.03163 Total loss: 1.40465 timestamp: 1654937052.7343557 iteration: 29045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18805 FastRCNN class loss: 0.09528 FastRCNN total loss: 0.28333 L1 loss: 0.0000e+00 L2 loss: 0.84483 Learning rate: 0.02 Mask loss: 0.18941 RPN box loss: 0.04345 RPN score loss: 0.00963 RPN total loss: 0.05307 Total loss: 1.37064 timestamp: 1654937055.9071748 iteration: 29050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13714 FastRCNN class loss: 0.09498 FastRCNN total loss: 0.23211 L1 loss: 0.0000e+00 L2 loss: 0.84469 Learning rate: 0.02 Mask loss: 0.19952 RPN box loss: 0.04074 RPN score loss: 0.0042 RPN total loss: 0.04494 Total loss: 1.32127 timestamp: 1654937059.1037836 iteration: 29055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11533 FastRCNN class loss: 0.11514 FastRCNN total loss: 0.23047 L1 loss: 0.0000e+00 L2 loss: 0.84456 Learning rate: 0.02 Mask loss: 0.17352 RPN box loss: 0.01406 RPN score loss: 0.00688 RPN total loss: 0.02095 Total loss: 1.2695 timestamp: 1654937062.3063622 iteration: 29060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15525 FastRCNN class loss: 0.11754 FastRCNN total loss: 0.27279 L1 loss: 0.0000e+00 L2 loss: 0.84443 Learning rate: 0.02 Mask loss: 0.13188 RPN box loss: 0.04749 RPN score loss: 0.00788 RPN total loss: 0.05537 Total loss: 1.30447 timestamp: 1654937065.5611947 iteration: 29065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12933 FastRCNN class loss: 0.07575 FastRCNN total loss: 0.20508 L1 loss: 0.0000e+00 L2 loss: 0.84431 Learning rate: 0.02 Mask loss: 0.12961 RPN box loss: 0.04412 RPN score loss: 0.00724 RPN total loss: 0.05136 Total loss: 1.23036 timestamp: 1654937068.7562683 iteration: 29070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11869 FastRCNN class loss: 0.06902 FastRCNN total loss: 0.1877 L1 loss: 0.0000e+00 L2 loss: 0.8442 Learning rate: 0.02 Mask loss: 0.14231 RPN box loss: 0.01746 RPN score loss: 0.00239 RPN total loss: 0.01986 Total loss: 1.19407 timestamp: 1654937071.9842045 iteration: 29075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16998 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.26308 L1 loss: 0.0000e+00 L2 loss: 0.84409 Learning rate: 0.02 Mask loss: 0.14804 RPN box loss: 0.03152 RPN score loss: 0.0074 RPN total loss: 0.03892 Total loss: 1.29412 timestamp: 1654937075.1839197 iteration: 29080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09975 FastRCNN class loss: 0.09147 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.84398 Learning rate: 0.02 Mask loss: 0.13542 RPN box loss: 0.00598 RPN score loss: 0.01963 RPN total loss: 0.02561 Total loss: 1.19622 timestamp: 1654937078.388923 iteration: 29085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14863 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.20592 L1 loss: 0.0000e+00 L2 loss: 0.84388 Learning rate: 0.02 Mask loss: 0.15151 RPN box loss: 0.03613 RPN score loss: 0.00777 RPN total loss: 0.0439 Total loss: 1.24521 timestamp: 1654937081.5825706 iteration: 29090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13328 FastRCNN class loss: 0.04871 FastRCNN total loss: 0.18199 L1 loss: 0.0000e+00 L2 loss: 0.84376 Learning rate: 0.02 Mask loss: 0.16577 RPN box loss: 0.03459 RPN score loss: 0.00303 RPN total loss: 0.03762 Total loss: 1.22914 timestamp: 1654937084.817748 iteration: 29095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14197 FastRCNN class loss: 0.08462 FastRCNN total loss: 0.22659 L1 loss: 0.0000e+00 L2 loss: 0.84363 Learning rate: 0.02 Mask loss: 0.09586 RPN box loss: 0.01436 RPN score loss: 0.00185 RPN total loss: 0.01621 Total loss: 1.18229 timestamp: 1654937087.9622204 iteration: 29100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06955 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.12983 L1 loss: 0.0000e+00 L2 loss: 0.8435 Learning rate: 0.02 Mask loss: 0.10477 RPN box loss: 0.01995 RPN score loss: 0.00334 RPN total loss: 0.02329 Total loss: 1.10139 timestamp: 1654937091.0743024 iteration: 29105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15123 FastRCNN class loss: 0.08478 FastRCNN total loss: 0.23601 L1 loss: 0.0000e+00 L2 loss: 0.84335 Learning rate: 0.02 Mask loss: 0.17488 RPN box loss: 0.10797 RPN score loss: 0.00853 RPN total loss: 0.1165 Total loss: 1.37074 timestamp: 1654937094.332944 iteration: 29110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12265 FastRCNN class loss: 0.12392 FastRCNN total loss: 0.24657 L1 loss: 0.0000e+00 L2 loss: 0.84321 Learning rate: 0.02 Mask loss: 0.15943 RPN box loss: 0.03518 RPN score loss: 0.01182 RPN total loss: 0.047 Total loss: 1.29621 timestamp: 1654937097.5057156 iteration: 29115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17166 FastRCNN class loss: 0.08389 FastRCNN total loss: 0.25555 L1 loss: 0.0000e+00 L2 loss: 0.84309 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.03149 RPN score loss: 0.00342 RPN total loss: 0.0349 Total loss: 1.27186 timestamp: 1654937100.726372 iteration: 29120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11078 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.18 L1 loss: 0.0000e+00 L2 loss: 0.84296 Learning rate: 0.02 Mask loss: 0.13729 RPN box loss: 0.01834 RPN score loss: 0.00464 RPN total loss: 0.02298 Total loss: 1.18323 timestamp: 1654937103.9258277 iteration: 29125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13544 FastRCNN class loss: 0.04956 FastRCNN total loss: 0.185 L1 loss: 0.0000e+00 L2 loss: 0.84283 Learning rate: 0.02 Mask loss: 0.11969 RPN box loss: 0.02261 RPN score loss: 0.0044 RPN total loss: 0.02702 Total loss: 1.17454 timestamp: 1654937107.023233 iteration: 29130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18207 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.26844 L1 loss: 0.0000e+00 L2 loss: 0.84273 Learning rate: 0.02 Mask loss: 0.22032 RPN box loss: 0.02046 RPN score loss: 0.01494 RPN total loss: 0.0354 Total loss: 1.36689 timestamp: 1654937110.2338314 iteration: 29135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10109 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.1787 L1 loss: 0.0000e+00 L2 loss: 0.8426 Learning rate: 0.02 Mask loss: 0.17987 RPN box loss: 0.04977 RPN score loss: 0.0049 RPN total loss: 0.05467 Total loss: 1.25585 timestamp: 1654937113.438021 iteration: 29140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15833 FastRCNN class loss: 0.09892 FastRCNN total loss: 0.25725 L1 loss: 0.0000e+00 L2 loss: 0.84249 Learning rate: 0.02 Mask loss: 0.12486 RPN box loss: 0.02935 RPN score loss: 0.00398 RPN total loss: 0.03332 Total loss: 1.25792 timestamp: 1654937116.6772003 iteration: 29145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11663 FastRCNN class loss: 0.07834 FastRCNN total loss: 0.19496 L1 loss: 0.0000e+00 L2 loss: 0.84237 Learning rate: 0.02 Mask loss: 0.16565 RPN box loss: 0.07554 RPN score loss: 0.00398 RPN total loss: 0.07952 Total loss: 1.28249 timestamp: 1654937119.86767 iteration: 29150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14871 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.23576 L1 loss: 0.0000e+00 L2 loss: 0.84223 Learning rate: 0.02 Mask loss: 0.22288 RPN box loss: 0.01924 RPN score loss: 0.01458 RPN total loss: 0.03383 Total loss: 1.33469 timestamp: 1654937123.0627513 iteration: 29155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20467 FastRCNN class loss: 0.11522 FastRCNN total loss: 0.31989 L1 loss: 0.0000e+00 L2 loss: 0.8421 Learning rate: 0.02 Mask loss: 0.16625 RPN box loss: 0.00557 RPN score loss: 0.00223 RPN total loss: 0.0078 Total loss: 1.33604 timestamp: 1654937126.2137008 iteration: 29160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09496 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.16343 L1 loss: 0.0000e+00 L2 loss: 0.84199 Learning rate: 0.02 Mask loss: 0.14919 RPN box loss: 0.01872 RPN score loss: 0.00319 RPN total loss: 0.02192 Total loss: 1.17653 timestamp: 1654937129.3717406 iteration: 29165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12824 FastRCNN class loss: 0.0826 FastRCNN total loss: 0.21084 L1 loss: 0.0000e+00 L2 loss: 0.84189 Learning rate: 0.02 Mask loss: 0.15291 RPN box loss: 0.04614 RPN score loss: 0.00903 RPN total loss: 0.05517 Total loss: 1.26082 timestamp: 1654937132.5675175 iteration: 29170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11019 FastRCNN class loss: 0.05 FastRCNN total loss: 0.16019 L1 loss: 0.0000e+00 L2 loss: 0.84177 Learning rate: 0.02 Mask loss: 0.08352 RPN box loss: 0.00749 RPN score loss: 0.00443 RPN total loss: 0.01191 Total loss: 1.09739 timestamp: 1654937135.8035243 iteration: 29175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16282 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.22809 L1 loss: 0.0000e+00 L2 loss: 0.84165 Learning rate: 0.02 Mask loss: 0.07936 RPN box loss: 0.02569 RPN score loss: 0.00428 RPN total loss: 0.02997 Total loss: 1.17906 timestamp: 1654937138.9681897 iteration: 29180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.14534 L1 loss: 0.0000e+00 L2 loss: 0.84153 Learning rate: 0.02 Mask loss: 0.10269 RPN box loss: 0.03251 RPN score loss: 0.00293 RPN total loss: 0.03544 Total loss: 1.125 timestamp: 1654937142.1313431 iteration: 29185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10871 FastRCNN class loss: 0.0606 FastRCNN total loss: 0.1693 L1 loss: 0.0000e+00 L2 loss: 0.8414 Learning rate: 0.02 Mask loss: 0.16379 RPN box loss: 0.10843 RPN score loss: 0.01056 RPN total loss: 0.11899 Total loss: 1.29348 timestamp: 1654937145.3637993 iteration: 29190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08687 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.15006 L1 loss: 0.0000e+00 L2 loss: 0.84126 Learning rate: 0.02 Mask loss: 0.15314 RPN box loss: 0.0308 RPN score loss: 0.00638 RPN total loss: 0.03717 Total loss: 1.18164 timestamp: 1654937148.5254629 iteration: 29195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07068 FastRCNN class loss: 0.06091 FastRCNN total loss: 0.1316 L1 loss: 0.0000e+00 L2 loss: 0.84115 Learning rate: 0.02 Mask loss: 0.15113 RPN box loss: 0.02421 RPN score loss: 0.02128 RPN total loss: 0.04549 Total loss: 1.16937 timestamp: 1654937151.7224777 iteration: 29200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1494 FastRCNN class loss: 0.18301 FastRCNN total loss: 0.33241 L1 loss: 0.0000e+00 L2 loss: 0.84103 Learning rate: 0.02 Mask loss: 0.12158 RPN box loss: 0.04549 RPN score loss: 0.00306 RPN total loss: 0.04855 Total loss: 1.34357 timestamp: 1654937154.9139962 iteration: 29205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13213 FastRCNN class loss: 0.06341 FastRCNN total loss: 0.19554 L1 loss: 0.0000e+00 L2 loss: 0.84089 Learning rate: 0.02 Mask loss: 0.13626 RPN box loss: 0.10025 RPN score loss: 0.00656 RPN total loss: 0.10681 Total loss: 1.2795 timestamp: 1654937158.1034992 iteration: 29210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08013 FastRCNN class loss: 0.04564 FastRCNN total loss: 0.12577 L1 loss: 0.0000e+00 L2 loss: 0.84075 Learning rate: 0.02 Mask loss: 0.0859 RPN box loss: 0.02398 RPN score loss: 0.00624 RPN total loss: 0.03022 Total loss: 1.08264 timestamp: 1654937161.2783372 iteration: 29215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09656 FastRCNN class loss: 0.08269 FastRCNN total loss: 0.17925 L1 loss: 0.0000e+00 L2 loss: 0.84062 Learning rate: 0.02 Mask loss: 0.09863 RPN box loss: 0.01758 RPN score loss: 0.00144 RPN total loss: 0.01902 Total loss: 1.13751 timestamp: 1654937164.5754757 iteration: 29220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17216 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.23271 L1 loss: 0.0000e+00 L2 loss: 0.84053 Learning rate: 0.02 Mask loss: 0.17433 RPN box loss: 0.01834 RPN score loss: 0.00205 RPN total loss: 0.02039 Total loss: 1.26795 timestamp: 1654937167.74351 iteration: 29225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10989 FastRCNN class loss: 0.08671 FastRCNN total loss: 0.1966 L1 loss: 0.0000e+00 L2 loss: 0.8404 Learning rate: 0.02 Mask loss: 0.17392 RPN box loss: 0.01353 RPN score loss: 0.00691 RPN total loss: 0.02044 Total loss: 1.23136 timestamp: 1654937170.890509 iteration: 29230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12072 FastRCNN class loss: 0.08096 FastRCNN total loss: 0.20168 L1 loss: 0.0000e+00 L2 loss: 0.84027 Learning rate: 0.02 Mask loss: 0.13015 RPN box loss: 0.07215 RPN score loss: 0.01009 RPN total loss: 0.08223 Total loss: 1.25433 timestamp: 1654937174.0168188 iteration: 29235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12223 FastRCNN class loss: 0.048 FastRCNN total loss: 0.17023 L1 loss: 0.0000e+00 L2 loss: 0.84013 Learning rate: 0.02 Mask loss: 0.14358 RPN box loss: 0.00949 RPN score loss: 0.00153 RPN total loss: 0.01102 Total loss: 1.16496 timestamp: 1654937177.2356546 iteration: 29240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13529 FastRCNN class loss: 0.13849 FastRCNN total loss: 0.27378 L1 loss: 0.0000e+00 L2 loss: 0.84001 Learning rate: 0.02 Mask loss: 0.23464 RPN box loss: 0.03632 RPN score loss: 0.04338 RPN total loss: 0.0797 Total loss: 1.42813 timestamp: 1654937180.4408033 iteration: 29245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.09539 FastRCNN total loss: 0.24667 L1 loss: 0.0000e+00 L2 loss: 0.83989 Learning rate: 0.02 Mask loss: 0.1878 RPN box loss: 0.04117 RPN score loss: 0.01024 RPN total loss: 0.05141 Total loss: 1.32576 timestamp: 1654937183.7121825 iteration: 29250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14067 FastRCNN class loss: 0.11386 FastRCNN total loss: 0.25453 L1 loss: 0.0000e+00 L2 loss: 0.83976 Learning rate: 0.02 Mask loss: 0.14519 RPN box loss: 0.08987 RPN score loss: 0.01037 RPN total loss: 0.10024 Total loss: 1.33972 timestamp: 1654937186.9805381 iteration: 29255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09616 FastRCNN class loss: 0.05188 FastRCNN total loss: 0.14804 L1 loss: 0.0000e+00 L2 loss: 0.83964 Learning rate: 0.02 Mask loss: 0.16207 RPN box loss: 0.0479 RPN score loss: 0.00982 RPN total loss: 0.05771 Total loss: 1.20747 timestamp: 1654937190.2338693 iteration: 29260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10563 FastRCNN class loss: 0.09106 FastRCNN total loss: 0.19669 L1 loss: 0.0000e+00 L2 loss: 0.83951 Learning rate: 0.02 Mask loss: 0.16497 RPN box loss: 0.0212 RPN score loss: 0.00938 RPN total loss: 0.03058 Total loss: 1.23174 timestamp: 1654937193.4223967 iteration: 29265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09573 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.16689 L1 loss: 0.0000e+00 L2 loss: 0.83942 Learning rate: 0.02 Mask loss: 0.15571 RPN box loss: 0.04584 RPN score loss: 0.01168 RPN total loss: 0.05752 Total loss: 1.21954 timestamp: 1654937196.572166 iteration: 29270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11256 FastRCNN class loss: 0.11126 FastRCNN total loss: 0.22382 L1 loss: 0.0000e+00 L2 loss: 0.8393 Learning rate: 0.02 Mask loss: 0.13512 RPN box loss: 0.02713 RPN score loss: 0.00551 RPN total loss: 0.03264 Total loss: 1.23087 timestamp: 1654937199.774267 iteration: 29275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12619 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.20902 L1 loss: 0.0000e+00 L2 loss: 0.83917 Learning rate: 0.02 Mask loss: 0.10779 RPN box loss: 0.00965 RPN score loss: 0.00549 RPN total loss: 0.01515 Total loss: 1.17113 timestamp: 1654937202.9873414 iteration: 29280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10259 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.16407 L1 loss: 0.0000e+00 L2 loss: 0.83904 Learning rate: 0.02 Mask loss: 0.10608 RPN box loss: 0.02232 RPN score loss: 0.00387 RPN total loss: 0.02618 Total loss: 1.13538 timestamp: 1654937206.2093742 iteration: 29285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21596 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.3097 L1 loss: 0.0000e+00 L2 loss: 0.83894 Learning rate: 0.02 Mask loss: 0.15412 RPN box loss: 0.03169 RPN score loss: 0.00734 RPN total loss: 0.03903 Total loss: 1.34179 timestamp: 1654937209.443636 iteration: 29290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15625 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.21952 L1 loss: 0.0000e+00 L2 loss: 0.83884 Learning rate: 0.02 Mask loss: 0.11519 RPN box loss: 0.01259 RPN score loss: 0.00236 RPN total loss: 0.01495 Total loss: 1.18851 timestamp: 1654937212.7545276 iteration: 29295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10924 FastRCNN class loss: 0.06657 FastRCNN total loss: 0.17582 L1 loss: 0.0000e+00 L2 loss: 0.83872 Learning rate: 0.02 Mask loss: 0.12137 RPN box loss: 0.02364 RPN score loss: 0.00539 RPN total loss: 0.02903 Total loss: 1.16494 timestamp: 1654937215.9730506 iteration: 29300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09574 FastRCNN class loss: 0.15491 FastRCNN total loss: 0.25064 L1 loss: 0.0000e+00 L2 loss: 0.83859 Learning rate: 0.02 Mask loss: 0.15223 RPN box loss: 0.04398 RPN score loss: 0.00618 RPN total loss: 0.05016 Total loss: 1.29161 timestamp: 1654937219.1129873 iteration: 29305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12081 FastRCNN class loss: 0.08273 FastRCNN total loss: 0.20354 L1 loss: 0.0000e+00 L2 loss: 0.83848 Learning rate: 0.02 Mask loss: 0.12564 RPN box loss: 0.03536 RPN score loss: 0.00554 RPN total loss: 0.0409 Total loss: 1.20856 timestamp: 1654937222.3229299 iteration: 29310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.05385 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 0.83835 Learning rate: 0.02 Mask loss: 0.12382 RPN box loss: 0.07299 RPN score loss: 0.00498 RPN total loss: 0.07797 Total loss: 1.20399 timestamp: 1654937225.5302145 iteration: 29315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13466 FastRCNN class loss: 0.108 FastRCNN total loss: 0.24266 L1 loss: 0.0000e+00 L2 loss: 0.83822 Learning rate: 0.02 Mask loss: 0.16783 RPN box loss: 0.06244 RPN score loss: 0.01533 RPN total loss: 0.07777 Total loss: 1.32649 timestamp: 1654937228.7890668 iteration: 29320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13233 FastRCNN class loss: 0.05418 FastRCNN total loss: 0.18652 L1 loss: 0.0000e+00 L2 loss: 0.83812 Learning rate: 0.02 Mask loss: 0.13676 RPN box loss: 0.01215 RPN score loss: 0.00567 RPN total loss: 0.01783 Total loss: 1.17922 timestamp: 1654937231.929472 iteration: 29325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1313 FastRCNN class loss: 0.0857 FastRCNN total loss: 0.21701 L1 loss: 0.0000e+00 L2 loss: 0.838 Learning rate: 0.02 Mask loss: 0.23652 RPN box loss: 0.02851 RPN score loss: 0.01104 RPN total loss: 0.03955 Total loss: 1.33108 timestamp: 1654937235.1437826 iteration: 29330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12126 FastRCNN class loss: 0.07279 FastRCNN total loss: 0.19405 L1 loss: 0.0000e+00 L2 loss: 0.83787 Learning rate: 0.02 Mask loss: 0.13547 RPN box loss: 0.01951 RPN score loss: 0.00789 RPN total loss: 0.02739 Total loss: 1.19478 timestamp: 1654937238.3937817 iteration: 29335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15266 FastRCNN class loss: 0.08405 FastRCNN total loss: 0.23671 L1 loss: 0.0000e+00 L2 loss: 0.83776 Learning rate: 0.02 Mask loss: 0.0838 RPN box loss: 0.01622 RPN score loss: 0.00371 RPN total loss: 0.01993 Total loss: 1.1782 timestamp: 1654937241.6129568 iteration: 29340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11839 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.18399 L1 loss: 0.0000e+00 L2 loss: 0.83761 Learning rate: 0.02 Mask loss: 0.16484 RPN box loss: 0.04356 RPN score loss: 0.01372 RPN total loss: 0.05727 Total loss: 1.2437 timestamp: 1654937244.7820857 iteration: 29345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17625 FastRCNN class loss: 0.10005 FastRCNN total loss: 0.27629 L1 loss: 0.0000e+00 L2 loss: 0.83748 Learning rate: 0.02 Mask loss: 0.20593 RPN box loss: 0.02744 RPN score loss: 0.00921 RPN total loss: 0.03665 Total loss: 1.35636 timestamp: 1654937248.0204418 iteration: 29350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19583 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.26732 L1 loss: 0.0000e+00 L2 loss: 0.83736 Learning rate: 0.02 Mask loss: 0.12891 RPN box loss: 0.02009 RPN score loss: 0.0042 RPN total loss: 0.02429 Total loss: 1.25789 timestamp: 1654937251.2451718 iteration: 29355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1352 FastRCNN class loss: 0.11551 FastRCNN total loss: 0.25071 L1 loss: 0.0000e+00 L2 loss: 0.83724 Learning rate: 0.02 Mask loss: 0.20035 RPN box loss: 0.03573 RPN score loss: 0.01078 RPN total loss: 0.04651 Total loss: 1.3348 timestamp: 1654937254.449318 iteration: 29360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15892 FastRCNN class loss: 0.05498 FastRCNN total loss: 0.2139 L1 loss: 0.0000e+00 L2 loss: 0.83712 Learning rate: 0.02 Mask loss: 0.08597 RPN box loss: 0.03752 RPN score loss: 0.00718 RPN total loss: 0.0447 Total loss: 1.1817 timestamp: 1654937257.6592138 iteration: 29365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16254 FastRCNN class loss: 0.0985 FastRCNN total loss: 0.26104 L1 loss: 0.0000e+00 L2 loss: 0.83702 Learning rate: 0.02 Mask loss: 0.17023 RPN box loss: 0.01368 RPN score loss: 0.00329 RPN total loss: 0.01697 Total loss: 1.28525 timestamp: 1654937260.8536737 iteration: 29370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1232 FastRCNN class loss: 0.09917 FastRCNN total loss: 0.22237 L1 loss: 0.0000e+00 L2 loss: 0.83691 Learning rate: 0.02 Mask loss: 0.22694 RPN box loss: 0.05252 RPN score loss: 0.00754 RPN total loss: 0.06005 Total loss: 1.34627 timestamp: 1654937264.0684426 iteration: 29375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12567 FastRCNN class loss: 0.12676 FastRCNN total loss: 0.25243 L1 loss: 0.0000e+00 L2 loss: 0.83677 Learning rate: 0.02 Mask loss: 0.19002 RPN box loss: 0.0513 RPN score loss: 0.01033 RPN total loss: 0.06164 Total loss: 1.34086 timestamp: 1654937267.1763294 iteration: 29380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19267 FastRCNN class loss: 0.10561 FastRCNN total loss: 0.29828 L1 loss: 0.0000e+00 L2 loss: 0.83666 Learning rate: 0.02 Mask loss: 0.17174 RPN box loss: 0.0176 RPN score loss: 0.01235 RPN total loss: 0.02995 Total loss: 1.33663 timestamp: 1654937270.3157187 iteration: 29385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17281 FastRCNN class loss: 0.12554 FastRCNN total loss: 0.29835 L1 loss: 0.0000e+00 L2 loss: 0.83654 Learning rate: 0.02 Mask loss: 0.17925 RPN box loss: 0.01476 RPN score loss: 0.00704 RPN total loss: 0.0218 Total loss: 1.33593 timestamp: 1654937273.517261 iteration: 29390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13766 FastRCNN class loss: 0.08762 FastRCNN total loss: 0.22528 L1 loss: 0.0000e+00 L2 loss: 0.8364 Learning rate: 0.02 Mask loss: 0.17966 RPN box loss: 0.02834 RPN score loss: 0.00377 RPN total loss: 0.03211 Total loss: 1.27344 timestamp: 1654937276.7130806 iteration: 29395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12914 FastRCNN class loss: 0.08981 FastRCNN total loss: 0.21895 L1 loss: 0.0000e+00 L2 loss: 0.83627 Learning rate: 0.02 Mask loss: 0.1585 RPN box loss: 0.03602 RPN score loss: 0.0322 RPN total loss: 0.06822 Total loss: 1.28194 timestamp: 1654937279.929832 iteration: 29400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12463 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.1775 L1 loss: 0.0000e+00 L2 loss: 0.83612 Learning rate: 0.02 Mask loss: 0.20399 RPN box loss: 0.03425 RPN score loss: 0.00861 RPN total loss: 0.04285 Total loss: 1.26046 timestamp: 1654937283.1632018 iteration: 29405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07393 FastRCNN class loss: 0.0738 FastRCNN total loss: 0.14774 L1 loss: 0.0000e+00 L2 loss: 0.836 Learning rate: 0.02 Mask loss: 0.15021 RPN box loss: 0.03639 RPN score loss: 0.00563 RPN total loss: 0.04202 Total loss: 1.17597 timestamp: 1654937286.40427 iteration: 29410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13284 FastRCNN class loss: 0.08172 FastRCNN total loss: 0.21456 L1 loss: 0.0000e+00 L2 loss: 0.83589 Learning rate: 0.02 Mask loss: 0.11486 RPN box loss: 0.02708 RPN score loss: 0.00559 RPN total loss: 0.03266 Total loss: 1.19797 timestamp: 1654937289.567025 iteration: 29415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13487 FastRCNN class loss: 0.06302 FastRCNN total loss: 0.1979 L1 loss: 0.0000e+00 L2 loss: 0.83579 Learning rate: 0.02 Mask loss: 0.16048 RPN box loss: 0.01062 RPN score loss: 0.00476 RPN total loss: 0.01538 Total loss: 1.20955 timestamp: 1654937292.7871099 iteration: 29420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13462 FastRCNN class loss: 0.09618 FastRCNN total loss: 0.2308 L1 loss: 0.0000e+00 L2 loss: 0.83565 Learning rate: 0.02 Mask loss: 0.19852 RPN box loss: 0.03283 RPN score loss: 0.01037 RPN total loss: 0.0432 Total loss: 1.30816 timestamp: 1654937296.0382488 iteration: 29425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10432 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.18329 L1 loss: 0.0000e+00 L2 loss: 0.83552 Learning rate: 0.02 Mask loss: 0.16519 RPN box loss: 0.04394 RPN score loss: 0.0167 RPN total loss: 0.06065 Total loss: 1.24464 timestamp: 1654937299.171934 iteration: 29430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13914 FastRCNN class loss: 0.09532 FastRCNN total loss: 0.23445 L1 loss: 0.0000e+00 L2 loss: 0.83541 Learning rate: 0.02 Mask loss: 0.1675 RPN box loss: 0.08716 RPN score loss: 0.00562 RPN total loss: 0.09278 Total loss: 1.33015 timestamp: 1654937302.4033086 iteration: 29435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15925 FastRCNN class loss: 0.08967 FastRCNN total loss: 0.24892 L1 loss: 0.0000e+00 L2 loss: 0.8353 Learning rate: 0.02 Mask loss: 0.15296 RPN box loss: 0.02832 RPN score loss: 0.00812 RPN total loss: 0.03644 Total loss: 1.27362 timestamp: 1654937305.6397712 iteration: 29440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12785 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.20656 L1 loss: 0.0000e+00 L2 loss: 0.83516 Learning rate: 0.02 Mask loss: 0.16983 RPN box loss: 0.03137 RPN score loss: 0.00454 RPN total loss: 0.03592 Total loss: 1.24747 timestamp: 1654937308.8835182 iteration: 29445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13429 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.20038 L1 loss: 0.0000e+00 L2 loss: 0.83502 Learning rate: 0.02 Mask loss: 0.16078 RPN box loss: 0.05504 RPN score loss: 0.00978 RPN total loss: 0.06483 Total loss: 1.261 timestamp: 1654937312.127304 iteration: 29450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06764 FastRCNN class loss: 0.05738 FastRCNN total loss: 0.12502 L1 loss: 0.0000e+00 L2 loss: 0.8349 Learning rate: 0.02 Mask loss: 0.09274 RPN box loss: 0.00815 RPN score loss: 0.00228 RPN total loss: 0.01043 Total loss: 1.06309 timestamp: 1654937315.3144543 iteration: 29455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14819 FastRCNN class loss: 0.11379 FastRCNN total loss: 0.26198 L1 loss: 0.0000e+00 L2 loss: 0.83478 Learning rate: 0.02 Mask loss: 0.22724 RPN box loss: 0.02425 RPN score loss: 0.01332 RPN total loss: 0.03757 Total loss: 1.36157 timestamp: 1654937318.548369 iteration: 29460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12899 FastRCNN class loss: 0.09106 FastRCNN total loss: 0.22005 L1 loss: 0.0000e+00 L2 loss: 0.83465 Learning rate: 0.02 Mask loss: 0.13333 RPN box loss: 0.04798 RPN score loss: 0.00552 RPN total loss: 0.0535 Total loss: 1.24153 timestamp: 1654937321.7900121 iteration: 29465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.05442 FastRCNN total loss: 0.13308 L1 loss: 0.0000e+00 L2 loss: 0.83452 Learning rate: 0.02 Mask loss: 0.09999 RPN box loss: 0.04599 RPN score loss: 0.02847 RPN total loss: 0.07445 Total loss: 1.14204 timestamp: 1654937324.9240203 iteration: 29470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09128 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.14727 L1 loss: 0.0000e+00 L2 loss: 0.8344 Learning rate: 0.02 Mask loss: 0.08854 RPN box loss: 0.02111 RPN score loss: 0.00534 RPN total loss: 0.02645 Total loss: 1.09667 timestamp: 1654937328.1115947 iteration: 29475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15758 FastRCNN class loss: 0.15915 FastRCNN total loss: 0.31673 L1 loss: 0.0000e+00 L2 loss: 0.83426 Learning rate: 0.02 Mask loss: 0.28135 RPN box loss: 0.04862 RPN score loss: 0.11025 RPN total loss: 0.15887 Total loss: 1.59121 timestamp: 1654937331.2780073 iteration: 29480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10201 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.16095 L1 loss: 0.0000e+00 L2 loss: 0.83414 Learning rate: 0.02 Mask loss: 0.14259 RPN box loss: 0.01661 RPN score loss: 0.00595 RPN total loss: 0.02257 Total loss: 1.16025 timestamp: 1654937334.483331 iteration: 29485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16241 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.23568 L1 loss: 0.0000e+00 L2 loss: 0.83401 Learning rate: 0.02 Mask loss: 0.22676 RPN box loss: 0.03168 RPN score loss: 0.00733 RPN total loss: 0.03901 Total loss: 1.33547 timestamp: 1654937337.635182 iteration: 29490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2131 FastRCNN class loss: 0.06584 FastRCNN total loss: 0.27894 L1 loss: 0.0000e+00 L2 loss: 0.83389 Learning rate: 0.02 Mask loss: 0.18898 RPN box loss: 0.02669 RPN score loss: 0.00358 RPN total loss: 0.03027 Total loss: 1.33208 timestamp: 1654937340.8597887 iteration: 29495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20969 FastRCNN class loss: 0.08935 FastRCNN total loss: 0.29903 L1 loss: 0.0000e+00 L2 loss: 0.83379 Learning rate: 0.02 Mask loss: 0.17979 RPN box loss: 0.02211 RPN score loss: 0.00574 RPN total loss: 0.02785 Total loss: 1.34046 timestamp: 1654937344.0028214 iteration: 29500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2274 FastRCNN class loss: 0.13681 FastRCNN total loss: 0.3642 L1 loss: 0.0000e+00 L2 loss: 0.83368 Learning rate: 0.02 Mask loss: 0.17413 RPN box loss: 0.04402 RPN score loss: 0.0103 RPN total loss: 0.05431 Total loss: 1.42632 timestamp: 1654937347.1833677 iteration: 29505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.18986 L1 loss: 0.0000e+00 L2 loss: 0.83358 Learning rate: 0.02 Mask loss: 0.1168 RPN box loss: 0.03563 RPN score loss: 0.00744 RPN total loss: 0.04307 Total loss: 1.18331 timestamp: 1654937350.335135 iteration: 29510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19546 FastRCNN class loss: 0.06029 FastRCNN total loss: 0.25576 L1 loss: 0.0000e+00 L2 loss: 0.83347 Learning rate: 0.02 Mask loss: 0.14318 RPN box loss: 0.0247 RPN score loss: 0.00292 RPN total loss: 0.02762 Total loss: 1.26002 timestamp: 1654937353.5813017 iteration: 29515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16575 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.26461 L1 loss: 0.0000e+00 L2 loss: 0.83336 Learning rate: 0.02 Mask loss: 0.17788 RPN box loss: 0.02371 RPN score loss: 0.00625 RPN total loss: 0.02997 Total loss: 1.30582 timestamp: 1654937356.8121574 iteration: 29520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1025 FastRCNN class loss: 0.07524 FastRCNN total loss: 0.17774 L1 loss: 0.0000e+00 L2 loss: 0.83324 Learning rate: 0.02 Mask loss: 0.14119 RPN box loss: 0.01958 RPN score loss: 0.0074 RPN total loss: 0.02698 Total loss: 1.17915 timestamp: 1654937360.0152755 iteration: 29525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07519 FastRCNN class loss: 0.06008 FastRCNN total loss: 0.13527 L1 loss: 0.0000e+00 L2 loss: 0.83311 Learning rate: 0.02 Mask loss: 0.12696 RPN box loss: 0.04755 RPN score loss: 0.00308 RPN total loss: 0.05063 Total loss: 1.14597 timestamp: 1654937363.1704035 iteration: 29530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17343 FastRCNN class loss: 0.06374 FastRCNN total loss: 0.23717 L1 loss: 0.0000e+00 L2 loss: 0.83299 Learning rate: 0.02 Mask loss: 0.14639 RPN box loss: 0.07357 RPN score loss: 0.0073 RPN total loss: 0.08087 Total loss: 1.29742 timestamp: 1654937366.3838906 iteration: 29535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13999 FastRCNN class loss: 0.11492 FastRCNN total loss: 0.25491 L1 loss: 0.0000e+00 L2 loss: 0.83288 Learning rate: 0.02 Mask loss: 0.17013 RPN box loss: 0.03008 RPN score loss: 0.00655 RPN total loss: 0.03663 Total loss: 1.29455 timestamp: 1654937369.5277941 iteration: 29540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16021 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.25714 L1 loss: 0.0000e+00 L2 loss: 0.83275 Learning rate: 0.02 Mask loss: 0.16186 RPN box loss: 0.01835 RPN score loss: 0.00529 RPN total loss: 0.02365 Total loss: 1.2754 timestamp: 1654937372.7340674 iteration: 29545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17169 FastRCNN class loss: 0.1176 FastRCNN total loss: 0.28929 L1 loss: 0.0000e+00 L2 loss: 0.8326 Learning rate: 0.02 Mask loss: 0.18859 RPN box loss: 0.0716 RPN score loss: 0.00505 RPN total loss: 0.07665 Total loss: 1.38713 timestamp: 1654937375.9049845 iteration: 29550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13981 FastRCNN class loss: 0.10418 FastRCNN total loss: 0.24399 L1 loss: 0.0000e+00 L2 loss: 0.83248 Learning rate: 0.02 Mask loss: 0.16246 RPN box loss: 0.01947 RPN score loss: 0.01278 RPN total loss: 0.03225 Total loss: 1.27119 timestamp: 1654937379.107834 iteration: 29555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15775 FastRCNN class loss: 0.09029 FastRCNN total loss: 0.24804 L1 loss: 0.0000e+00 L2 loss: 0.83237 Learning rate: 0.02 Mask loss: 0.14444 RPN box loss: 0.0752 RPN score loss: 0.00841 RPN total loss: 0.08361 Total loss: 1.30846 timestamp: 1654937382.2957015 iteration: 29560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13003 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.21419 L1 loss: 0.0000e+00 L2 loss: 0.83227 Learning rate: 0.02 Mask loss: 0.1334 RPN box loss: 0.02818 RPN score loss: 0.00483 RPN total loss: 0.03301 Total loss: 1.21287 timestamp: 1654937385.4807842 iteration: 29565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10928 FastRCNN class loss: 0.04561 FastRCNN total loss: 0.15489 L1 loss: 0.0000e+00 L2 loss: 0.83215 Learning rate: 0.02 Mask loss: 0.09544 RPN box loss: 0.01931 RPN score loss: 0.00159 RPN total loss: 0.0209 Total loss: 1.10338 timestamp: 1654937388.748999 iteration: 29570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1286 FastRCNN class loss: 0.10596 FastRCNN total loss: 0.23456 L1 loss: 0.0000e+00 L2 loss: 0.83202 Learning rate: 0.02 Mask loss: 0.15718 RPN box loss: 0.03558 RPN score loss: 0.00812 RPN total loss: 0.0437 Total loss: 1.26746 timestamp: 1654937391.9779 iteration: 29575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.08563 FastRCNN total loss: 0.19602 L1 loss: 0.0000e+00 L2 loss: 0.83191 Learning rate: 0.02 Mask loss: 0.11347 RPN box loss: 0.04815 RPN score loss: 0.00926 RPN total loss: 0.05741 Total loss: 1.19881 timestamp: 1654937395.1670897 iteration: 29580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13507 FastRCNN class loss: 0.09483 FastRCNN total loss: 0.2299 L1 loss: 0.0000e+00 L2 loss: 0.83176 Learning rate: 0.02 Mask loss: 0.1348 RPN box loss: 0.05831 RPN score loss: 0.00655 RPN total loss: 0.06487 Total loss: 1.26132 timestamp: 1654937398.3803623 iteration: 29585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20784 FastRCNN class loss: 0.08478 FastRCNN total loss: 0.29262 L1 loss: 0.0000e+00 L2 loss: 0.83164 Learning rate: 0.02 Mask loss: 0.15719 RPN box loss: 0.03743 RPN score loss: 0.01139 RPN total loss: 0.04882 Total loss: 1.33027 timestamp: 1654937401.4689128 iteration: 29590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13624 FastRCNN class loss: 0.06211 FastRCNN total loss: 0.19835 L1 loss: 0.0000e+00 L2 loss: 0.83153 Learning rate: 0.02 Mask loss: 0.12686 RPN box loss: 0.01008 RPN score loss: 0.00442 RPN total loss: 0.0145 Total loss: 1.17123 timestamp: 1654937404.6843703 iteration: 29595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21618 FastRCNN class loss: 0.08663 FastRCNN total loss: 0.30281 L1 loss: 0.0000e+00 L2 loss: 0.8314 Learning rate: 0.02 Mask loss: 0.13615 RPN box loss: 0.0133 RPN score loss: 0.00421 RPN total loss: 0.01751 Total loss: 1.28787 timestamp: 1654937407.8416107 iteration: 29600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14776 FastRCNN class loss: 0.09487 FastRCNN total loss: 0.24263 L1 loss: 0.0000e+00 L2 loss: 0.83129 Learning rate: 0.02 Mask loss: 0.19845 RPN box loss: 0.01841 RPN score loss: 0.00471 RPN total loss: 0.02312 Total loss: 1.2955 timestamp: 1654937411.1519554 iteration: 29605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14264 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.21178 L1 loss: 0.0000e+00 L2 loss: 0.83118 Learning rate: 0.02 Mask loss: 0.15658 RPN box loss: 0.04274 RPN score loss: 0.00659 RPN total loss: 0.04933 Total loss: 1.24886 timestamp: 1654937414.430856 iteration: 29610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16346 FastRCNN class loss: 0.1407 FastRCNN total loss: 0.30416 L1 loss: 0.0000e+00 L2 loss: 0.83105 Learning rate: 0.02 Mask loss: 0.16591 RPN box loss: 0.0592 RPN score loss: 0.01581 RPN total loss: 0.07501 Total loss: 1.37612 timestamp: 1654937417.5874527 iteration: 29615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10827 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.16837 L1 loss: 0.0000e+00 L2 loss: 0.83092 Learning rate: 0.02 Mask loss: 0.09766 RPN box loss: 0.02367 RPN score loss: 0.00437 RPN total loss: 0.02804 Total loss: 1.12499 timestamp: 1654937420.7630992 iteration: 29620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05529 FastRCNN class loss: 0.0281 FastRCNN total loss: 0.08339 L1 loss: 0.0000e+00 L2 loss: 0.8308 Learning rate: 0.02 Mask loss: 0.09514 RPN box loss: 0.02465 RPN score loss: 0.00488 RPN total loss: 0.02953 Total loss: 1.03887 timestamp: 1654937424.1008694 iteration: 29625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13568 FastRCNN class loss: 0.07014 FastRCNN total loss: 0.20581 L1 loss: 0.0000e+00 L2 loss: 0.83066 Learning rate: 0.02 Mask loss: 0.118 RPN box loss: 0.01725 RPN score loss: 0.00418 RPN total loss: 0.02143 Total loss: 1.1759 timestamp: 1654937427.3733974 iteration: 29630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2106 FastRCNN class loss: 0.11857 FastRCNN total loss: 0.32917 L1 loss: 0.0000e+00 L2 loss: 0.83054 Learning rate: 0.02 Mask loss: 0.20646 RPN box loss: 0.01592 RPN score loss: 0.0056 RPN total loss: 0.02153 Total loss: 1.3877 timestamp: 1654937430.5822146 iteration: 29635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1089 FastRCNN class loss: 0.09068 FastRCNN total loss: 0.19958 L1 loss: 0.0000e+00 L2 loss: 0.83043 Learning rate: 0.02 Mask loss: 0.17938 RPN box loss: 0.00822 RPN score loss: 0.00432 RPN total loss: 0.01254 Total loss: 1.22193 timestamp: 1654937433.8330634 iteration: 29640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12689 FastRCNN class loss: 0.05294 FastRCNN total loss: 0.17983 L1 loss: 0.0000e+00 L2 loss: 0.83032 Learning rate: 0.02 Mask loss: 0.13064 RPN box loss: 0.0357 RPN score loss: 0.00931 RPN total loss: 0.04501 Total loss: 1.1858 timestamp: 1654937437.0832438 iteration: 29645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14634 FastRCNN class loss: 0.08642 FastRCNN total loss: 0.23276 L1 loss: 0.0000e+00 L2 loss: 0.83018 Learning rate: 0.02 Mask loss: 0.13794 RPN box loss: 0.01677 RPN score loss: 0.00686 RPN total loss: 0.02363 Total loss: 1.22451 timestamp: 1654937440.342442 iteration: 29650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10228 FastRCNN class loss: 0.081 FastRCNN total loss: 0.18328 L1 loss: 0.0000e+00 L2 loss: 0.83004 Learning rate: 0.02 Mask loss: 0.15718 RPN box loss: 0.0224 RPN score loss: 0.00937 RPN total loss: 0.03178 Total loss: 1.20228 timestamp: 1654937443.5113802 iteration: 29655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10919 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.18104 L1 loss: 0.0000e+00 L2 loss: 0.82994 Learning rate: 0.02 Mask loss: 0.15683 RPN box loss: 0.0285 RPN score loss: 0.00457 RPN total loss: 0.03307 Total loss: 1.20088 timestamp: 1654937446.7494397 iteration: 29660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12056 FastRCNN class loss: 0.12872 FastRCNN total loss: 0.24928 L1 loss: 0.0000e+00 L2 loss: 0.82984 Learning rate: 0.02 Mask loss: 0.15237 RPN box loss: 0.01654 RPN score loss: 0.00764 RPN total loss: 0.02418 Total loss: 1.25567 timestamp: 1654937449.9408767 iteration: 29665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15135 FastRCNN class loss: 0.09014 FastRCNN total loss: 0.24149 L1 loss: 0.0000e+00 L2 loss: 0.82972 Learning rate: 0.02 Mask loss: 0.21346 RPN box loss: 0.05372 RPN score loss: 0.00644 RPN total loss: 0.06016 Total loss: 1.34482 timestamp: 1654937453.1075087 iteration: 29670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16005 FastRCNN class loss: 0.06974 FastRCNN total loss: 0.22979 L1 loss: 0.0000e+00 L2 loss: 0.8296 Learning rate: 0.02 Mask loss: 0.10694 RPN box loss: 0.03532 RPN score loss: 0.00514 RPN total loss: 0.04047 Total loss: 1.2068 timestamp: 1654937456.3789003 iteration: 29675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10263 FastRCNN class loss: 0.0646 FastRCNN total loss: 0.16724 L1 loss: 0.0000e+00 L2 loss: 0.82949 Learning rate: 0.02 Mask loss: 0.21319 RPN box loss: 0.01961 RPN score loss: 0.00326 RPN total loss: 0.02287 Total loss: 1.23278 timestamp: 1654937459.6707578 iteration: 29680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19754 FastRCNN class loss: 0.04663 FastRCNN total loss: 0.24417 L1 loss: 0.0000e+00 L2 loss: 0.82935 Learning rate: 0.02 Mask loss: 0.13933 RPN box loss: 0.01272 RPN score loss: 0.00311 RPN total loss: 0.01583 Total loss: 1.22869 timestamp: 1654937462.8131888 iteration: 29685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07056 FastRCNN class loss: 0.04553 FastRCNN total loss: 0.11609 L1 loss: 0.0000e+00 L2 loss: 0.82923 Learning rate: 0.02 Mask loss: 0.11503 RPN box loss: 0.02475 RPN score loss: 0.0019 RPN total loss: 0.02665 Total loss: 1.08701 timestamp: 1654937465.9235332 iteration: 29690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08237 FastRCNN class loss: 0.07352 FastRCNN total loss: 0.15589 L1 loss: 0.0000e+00 L2 loss: 0.82911 Learning rate: 0.02 Mask loss: 0.1766 RPN box loss: 0.01698 RPN score loss: 0.00244 RPN total loss: 0.01942 Total loss: 1.18103 timestamp: 1654937469.0616622 iteration: 29695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14022 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.20223 L1 loss: 0.0000e+00 L2 loss: 0.829 Learning rate: 0.02 Mask loss: 0.12222 RPN box loss: 0.0072 RPN score loss: 0.0022 RPN total loss: 0.0094 Total loss: 1.16285 timestamp: 1654937472.2532482 iteration: 29700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16552 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.24667 L1 loss: 0.0000e+00 L2 loss: 0.82889 Learning rate: 0.02 Mask loss: 0.07486 RPN box loss: 0.02556 RPN score loss: 0.00317 RPN total loss: 0.02873 Total loss: 1.17915 timestamp: 1654937475.4175594 iteration: 29705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06535 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.13953 L1 loss: 0.0000e+00 L2 loss: 0.82875 Learning rate: 0.02 Mask loss: 0.1404 RPN box loss: 0.01493 RPN score loss: 0.00455 RPN total loss: 0.01948 Total loss: 1.12816 timestamp: 1654937478.618341 iteration: 29710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16281 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.23485 L1 loss: 0.0000e+00 L2 loss: 0.82863 Learning rate: 0.02 Mask loss: 0.11586 RPN box loss: 0.04624 RPN score loss: 0.00353 RPN total loss: 0.04977 Total loss: 1.22912 timestamp: 1654937481.7891254 iteration: 29715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1584 FastRCNN class loss: 0.12471 FastRCNN total loss: 0.28312 L1 loss: 0.0000e+00 L2 loss: 0.8285 Learning rate: 0.02 Mask loss: 0.19717 RPN box loss: 0.01527 RPN score loss: 0.01153 RPN total loss: 0.0268 Total loss: 1.33558 timestamp: 1654937485.050197 iteration: 29720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20385 FastRCNN class loss: 0.10638 FastRCNN total loss: 0.31022 L1 loss: 0.0000e+00 L2 loss: 0.82838 Learning rate: 0.02 Mask loss: 0.16172 RPN box loss: 0.04362 RPN score loss: 0.00947 RPN total loss: 0.05309 Total loss: 1.3534 timestamp: 1654937488.226562 iteration: 29725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17136 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.25144 L1 loss: 0.0000e+00 L2 loss: 0.82827 Learning rate: 0.02 Mask loss: 0.21415 RPN box loss: 0.02805 RPN score loss: 0.003 RPN total loss: 0.03106 Total loss: 1.32491 timestamp: 1654937491.3975768 iteration: 29730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07292 FastRCNN class loss: 0.04733 FastRCNN total loss: 0.12025 L1 loss: 0.0000e+00 L2 loss: 0.82816 Learning rate: 0.02 Mask loss: 0.10825 RPN box loss: 0.00451 RPN score loss: 0.00331 RPN total loss: 0.00782 Total loss: 1.06448 timestamp: 1654937494.596202 iteration: 29735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06647 FastRCNN class loss: 0.04756 FastRCNN total loss: 0.11403 L1 loss: 0.0000e+00 L2 loss: 0.82805 Learning rate: 0.02 Mask loss: 0.13848 RPN box loss: 0.03034 RPN score loss: 0.00152 RPN total loss: 0.03186 Total loss: 1.11242 timestamp: 1654937497.8210077 iteration: 29740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09849 FastRCNN class loss: 0.13308 FastRCNN total loss: 0.23157 L1 loss: 0.0000e+00 L2 loss: 0.82795 Learning rate: 0.02 Mask loss: 0.16602 RPN box loss: 0.09063 RPN score loss: 0.02527 RPN total loss: 0.1159 Total loss: 1.34144 timestamp: 1654937501.0967312 iteration: 29745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09254 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.16092 L1 loss: 0.0000e+00 L2 loss: 0.82783 Learning rate: 0.02 Mask loss: 0.20219 RPN box loss: 0.02753 RPN score loss: 0.00693 RPN total loss: 0.03446 Total loss: 1.2254 timestamp: 1654937504.310764 iteration: 29750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07998 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.1596 L1 loss: 0.0000e+00 L2 loss: 0.8277 Learning rate: 0.02 Mask loss: 0.16212 RPN box loss: 0.02457 RPN score loss: 0.01635 RPN total loss: 0.04093 Total loss: 1.19035 timestamp: 1654937507.510242 iteration: 29755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04676 FastRCNN class loss: 0.076 FastRCNN total loss: 0.12276 L1 loss: 0.0000e+00 L2 loss: 0.82758 Learning rate: 0.02 Mask loss: 0.11715 RPN box loss: 0.04033 RPN score loss: 0.00508 RPN total loss: 0.04541 Total loss: 1.1129 timestamp: 1654937510.732426 iteration: 29760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06271 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.15704 L1 loss: 0.0000e+00 L2 loss: 0.82744 Learning rate: 0.02 Mask loss: 0.13068 RPN box loss: 0.03872 RPN score loss: 0.00739 RPN total loss: 0.04611 Total loss: 1.16128 timestamp: 1654937513.9173174 iteration: 29765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12279 FastRCNN class loss: 0.10844 FastRCNN total loss: 0.23123 L1 loss: 0.0000e+00 L2 loss: 0.82733 Learning rate: 0.02 Mask loss: 0.18368 RPN box loss: 0.0289 RPN score loss: 0.012 RPN total loss: 0.04089 Total loss: 1.28313 timestamp: 1654937517.1405509 iteration: 29770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13469 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.2037 L1 loss: 0.0000e+00 L2 loss: 0.82724 Learning rate: 0.02 Mask loss: 0.1245 RPN box loss: 0.02206 RPN score loss: 0.00866 RPN total loss: 0.03072 Total loss: 1.18615 timestamp: 1654937520.3226907 iteration: 29775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19136 FastRCNN class loss: 0.10633 FastRCNN total loss: 0.29769 L1 loss: 0.0000e+00 L2 loss: 0.82713 Learning rate: 0.02 Mask loss: 0.17389 RPN box loss: 0.05582 RPN score loss: 0.00608 RPN total loss: 0.0619 Total loss: 1.36062 timestamp: 1654937523.4944944 iteration: 29780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0923 FastRCNN class loss: 0.11814 FastRCNN total loss: 0.21044 L1 loss: 0.0000e+00 L2 loss: 0.827 Learning rate: 0.02 Mask loss: 0.12909 RPN box loss: 0.05126 RPN score loss: 0.005 RPN total loss: 0.05626 Total loss: 1.22279 timestamp: 1654937526.7086654 iteration: 29785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13955 FastRCNN class loss: 0.09867 FastRCNN total loss: 0.23822 L1 loss: 0.0000e+00 L2 loss: 0.82687 Learning rate: 0.02 Mask loss: 0.24089 RPN box loss: 0.06229 RPN score loss: 0.00537 RPN total loss: 0.06766 Total loss: 1.37364 timestamp: 1654937529.8559337 iteration: 29790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09909 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.16072 L1 loss: 0.0000e+00 L2 loss: 0.82676 Learning rate: 0.02 Mask loss: 0.13812 RPN box loss: 0.0068 RPN score loss: 0.00396 RPN total loss: 0.01076 Total loss: 1.13635 timestamp: 1654937533.100669 iteration: 29795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18889 FastRCNN class loss: 0.19064 FastRCNN total loss: 0.37953 L1 loss: 0.0000e+00 L2 loss: 0.8266 Learning rate: 0.02 Mask loss: 0.21914 RPN box loss: 0.08457 RPN score loss: 0.01437 RPN total loss: 0.09894 Total loss: 1.52421 timestamp: 1654937536.237313 iteration: 29800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09635 FastRCNN class loss: 0.08097 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 0.82649 Learning rate: 0.02 Mask loss: 0.11739 RPN box loss: 0.02028 RPN score loss: 0.00449 RPN total loss: 0.02477 Total loss: 1.14597 timestamp: 1654937539.4114099 iteration: 29805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1295 FastRCNN class loss: 0.05022 FastRCNN total loss: 0.17972 L1 loss: 0.0000e+00 L2 loss: 0.82637 Learning rate: 0.02 Mask loss: 0.10154 RPN box loss: 0.0029 RPN score loss: 0.00522 RPN total loss: 0.00812 Total loss: 1.11574 timestamp: 1654937542.6815662 iteration: 29810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08898 FastRCNN class loss: 0.05428 FastRCNN total loss: 0.14326 L1 loss: 0.0000e+00 L2 loss: 0.82623 Learning rate: 0.02 Mask loss: 0.09408 RPN box loss: 0.03393 RPN score loss: 0.00902 RPN total loss: 0.04295 Total loss: 1.10653 timestamp: 1654937545.9012191 iteration: 29815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10006 FastRCNN class loss: 0.08835 FastRCNN total loss: 0.18841 L1 loss: 0.0000e+00 L2 loss: 0.82612 Learning rate: 0.02 Mask loss: 0.11656 RPN box loss: 0.03752 RPN score loss: 0.01558 RPN total loss: 0.0531 Total loss: 1.1842 timestamp: 1654937549.129052 iteration: 29820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15023 FastRCNN class loss: 0.08696 FastRCNN total loss: 0.23719 L1 loss: 0.0000e+00 L2 loss: 0.82602 Learning rate: 0.02 Mask loss: 0.20297 RPN box loss: 0.02484 RPN score loss: 0.01032 RPN total loss: 0.03517 Total loss: 1.30133 timestamp: 1654937552.3316596 iteration: 29825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19008 FastRCNN class loss: 0.1007 FastRCNN total loss: 0.29078 L1 loss: 0.0000e+00 L2 loss: 0.82589 Learning rate: 0.02 Mask loss: 0.17508 RPN box loss: 0.02068 RPN score loss: 0.0048 RPN total loss: 0.02548 Total loss: 1.31723 timestamp: 1654937555.527752 iteration: 29830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08026 FastRCNN class loss: 0.0446 FastRCNN total loss: 0.12486 L1 loss: 0.0000e+00 L2 loss: 0.82577 Learning rate: 0.02 Mask loss: 0.11683 RPN box loss: 0.01359 RPN score loss: 0.00373 RPN total loss: 0.01732 Total loss: 1.08478 timestamp: 1654937558.7002232 iteration: 29835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25401 FastRCNN class loss: 0.1025 FastRCNN total loss: 0.35651 L1 loss: 0.0000e+00 L2 loss: 0.82566 Learning rate: 0.02 Mask loss: 0.2329 RPN box loss: 0.01533 RPN score loss: 0.00595 RPN total loss: 0.02129 Total loss: 1.43637 timestamp: 1654937561.905608 iteration: 29840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.14901 L1 loss: 0.0000e+00 L2 loss: 0.82556 Learning rate: 0.02 Mask loss: 0.16164 RPN box loss: 0.0164 RPN score loss: 0.00736 RPN total loss: 0.02375 Total loss: 1.15995 timestamp: 1654937565.1549392 iteration: 29845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13085 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.21595 L1 loss: 0.0000e+00 L2 loss: 0.82543 Learning rate: 0.02 Mask loss: 0.10697 RPN box loss: 0.03192 RPN score loss: 0.01709 RPN total loss: 0.049 Total loss: 1.19736 timestamp: 1654937568.355069 iteration: 29850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15639 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 0.8253 Learning rate: 0.02 Mask loss: 0.15767 RPN box loss: 0.12132 RPN score loss: 0.00503 RPN total loss: 0.12635 Total loss: 1.33608 timestamp: 1654937571.585 iteration: 29855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13754 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.22941 L1 loss: 0.0000e+00 L2 loss: 0.82518 Learning rate: 0.02 Mask loss: 0.12218 RPN box loss: 0.02335 RPN score loss: 0.00395 RPN total loss: 0.0273 Total loss: 1.20406 timestamp: 1654937574.825073 iteration: 29860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.14197 L1 loss: 0.0000e+00 L2 loss: 0.82506 Learning rate: 0.02 Mask loss: 0.11543 RPN box loss: 0.03318 RPN score loss: 0.00654 RPN total loss: 0.03972 Total loss: 1.12217 timestamp: 1654937577.9455862 iteration: 29865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18089 FastRCNN class loss: 0.09713 FastRCNN total loss: 0.27802 L1 loss: 0.0000e+00 L2 loss: 0.82495 Learning rate: 0.02 Mask loss: 0.20176 RPN box loss: 0.02988 RPN score loss: 0.00383 RPN total loss: 0.03371 Total loss: 1.33844 timestamp: 1654937581.1068401 iteration: 29870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1298 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.19457 L1 loss: 0.0000e+00 L2 loss: 0.82483 Learning rate: 0.02 Mask loss: 0.13963 RPN box loss: 0.03865 RPN score loss: 0.01205 RPN total loss: 0.0507 Total loss: 1.20973 timestamp: 1654937584.3309336 iteration: 29875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15668 FastRCNN class loss: 0.09847 FastRCNN total loss: 0.25515 L1 loss: 0.0000e+00 L2 loss: 0.82471 Learning rate: 0.02 Mask loss: 0.16075 RPN box loss: 0.04401 RPN score loss: 0.01102 RPN total loss: 0.05503 Total loss: 1.29564 timestamp: 1654937587.6749165 iteration: 29880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11521 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.17596 L1 loss: 0.0000e+00 L2 loss: 0.8246 Learning rate: 0.02 Mask loss: 0.1924 RPN box loss: 0.02351 RPN score loss: 0.0146 RPN total loss: 0.03811 Total loss: 1.23106 timestamp: 1654937590.8143702 iteration: 29885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1133 FastRCNN class loss: 0.073 FastRCNN total loss: 0.1863 L1 loss: 0.0000e+00 L2 loss: 0.82449 Learning rate: 0.02 Mask loss: 0.15086 RPN box loss: 0.08187 RPN score loss: 0.00477 RPN total loss: 0.08664 Total loss: 1.24828 timestamp: 1654937594.0560637 iteration: 29890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16215 FastRCNN class loss: 0.13577 FastRCNN total loss: 0.29792 L1 loss: 0.0000e+00 L2 loss: 0.82438 Learning rate: 0.02 Mask loss: 0.15249 RPN box loss: 0.05669 RPN score loss: 0.01518 RPN total loss: 0.07187 Total loss: 1.34666 timestamp: 1654937597.2834153 iteration: 29895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1638 FastRCNN class loss: 0.04642 FastRCNN total loss: 0.21023 L1 loss: 0.0000e+00 L2 loss: 0.82425 Learning rate: 0.02 Mask loss: 0.13191 RPN box loss: 0.02587 RPN score loss: 0.00437 RPN total loss: 0.03025 Total loss: 1.19663 timestamp: 1654937600.5520155 iteration: 29900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10149 FastRCNN class loss: 0.08746 FastRCNN total loss: 0.18895 L1 loss: 0.0000e+00 L2 loss: 0.82412 Learning rate: 0.02 Mask loss: 0.16082 RPN box loss: 0.01163 RPN score loss: 0.0044 RPN total loss: 0.01603 Total loss: 1.18992 timestamp: 1654937603.8381937 iteration: 29905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25487 FastRCNN class loss: 0.18564 FastRCNN total loss: 0.44051 L1 loss: 0.0000e+00 L2 loss: 0.82398 Learning rate: 0.02 Mask loss: 0.30615 RPN box loss: 0.03528 RPN score loss: 0.0131 RPN total loss: 0.04837 Total loss: 1.61901 timestamp: 1654937607.0763638 iteration: 29910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12628 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.19739 L1 loss: 0.0000e+00 L2 loss: 0.82387 Learning rate: 0.02 Mask loss: 0.17383 RPN box loss: 0.02257 RPN score loss: 0.00696 RPN total loss: 0.02953 Total loss: 1.22462 timestamp: 1654937610.2934353 iteration: 29915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12933 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.19977 L1 loss: 0.0000e+00 L2 loss: 0.82375 Learning rate: 0.02 Mask loss: 0.17533 RPN box loss: 0.06124 RPN score loss: 0.01104 RPN total loss: 0.07228 Total loss: 1.27113 timestamp: 1654937613.54339 iteration: 29920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11265 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.17106 L1 loss: 0.0000e+00 L2 loss: 0.82363 Learning rate: 0.02 Mask loss: 0.09095 RPN box loss: 0.02133 RPN score loss: 0.00883 RPN total loss: 0.03016 Total loss: 1.1158 timestamp: 1654937616.7997398 iteration: 29925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19061 FastRCNN class loss: 0.10986 FastRCNN total loss: 0.30047 L1 loss: 0.0000e+00 L2 loss: 0.82353 Learning rate: 0.02 Mask loss: 0.21595 RPN box loss: 0.04016 RPN score loss: 0.00905 RPN total loss: 0.04921 Total loss: 1.38916 timestamp: 1654937620.0067291 iteration: 29930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18071 FastRCNN class loss: 0.09628 FastRCNN total loss: 0.277 L1 loss: 0.0000e+00 L2 loss: 0.8234 Learning rate: 0.02 Mask loss: 0.16867 RPN box loss: 0.01732 RPN score loss: 0.00871 RPN total loss: 0.02602 Total loss: 1.29509 timestamp: 1654937623.2588665 iteration: 29935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15812 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.22787 L1 loss: 0.0000e+00 L2 loss: 0.8233 Learning rate: 0.02 Mask loss: 0.15786 RPN box loss: 0.05462 RPN score loss: 0.00727 RPN total loss: 0.06188 Total loss: 1.27091 timestamp: 1654937626.5957654 iteration: 29940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16991 FastRCNN class loss: 0.15194 FastRCNN total loss: 0.32185 L1 loss: 0.0000e+00 L2 loss: 0.82319 Learning rate: 0.02 Mask loss: 0.1996 RPN box loss: 0.02104 RPN score loss: 0.00409 RPN total loss: 0.02513 Total loss: 1.36977 timestamp: 1654937629.7777 iteration: 29945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13231 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.19925 L1 loss: 0.0000e+00 L2 loss: 0.82308 Learning rate: 0.02 Mask loss: 0.11877 RPN box loss: 0.02427 RPN score loss: 0.00185 RPN total loss: 0.02612 Total loss: 1.16722 timestamp: 1654937632.9401789 iteration: 29950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18622 FastRCNN class loss: 0.11335 FastRCNN total loss: 0.29957 L1 loss: 0.0000e+00 L2 loss: 0.82295 Learning rate: 0.02 Mask loss: 0.16759 RPN box loss: 0.02386 RPN score loss: 0.00359 RPN total loss: 0.02745 Total loss: 1.31756 timestamp: 1654937636.070931 iteration: 29955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11925 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.18123 L1 loss: 0.0000e+00 L2 loss: 0.82283 Learning rate: 0.02 Mask loss: 0.16768 RPN box loss: 0.01107 RPN score loss: 0.00262 RPN total loss: 0.01369 Total loss: 1.18542 timestamp: 1654937639.2671711 iteration: 29960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16699 FastRCNN class loss: 0.06135 FastRCNN total loss: 0.22834 L1 loss: 0.0000e+00 L2 loss: 0.82272 Learning rate: 0.02 Mask loss: 0.12781 RPN box loss: 0.04664 RPN score loss: 0.00327 RPN total loss: 0.04991 Total loss: 1.22878 timestamp: 1654937642.4720182 iteration: 29965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06951 FastRCNN class loss: 0.04687 FastRCNN total loss: 0.11637 L1 loss: 0.0000e+00 L2 loss: 0.82258 Learning rate: 0.02 Mask loss: 0.10346 RPN box loss: 0.02498 RPN score loss: 0.00442 RPN total loss: 0.0294 Total loss: 1.07181 timestamp: 1654937645.615037 iteration: 29970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13968 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.21589 L1 loss: 0.0000e+00 L2 loss: 0.82245 Learning rate: 0.02 Mask loss: 0.18147 RPN box loss: 0.05181 RPN score loss: 0.00486 RPN total loss: 0.05667 Total loss: 1.27647 timestamp: 1654937648.779607 iteration: 29975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08315 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.15433 L1 loss: 0.0000e+00 L2 loss: 0.82233 Learning rate: 0.02 Mask loss: 0.10113 RPN box loss: 0.01267 RPN score loss: 0.00182 RPN total loss: 0.01449 Total loss: 1.09229 timestamp: 1654937652.0554228 iteration: 29980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18073 FastRCNN class loss: 0.10382 FastRCNN total loss: 0.28456 L1 loss: 0.0000e+00 L2 loss: 0.82221 Learning rate: 0.02 Mask loss: 0.15378 RPN box loss: 0.086 RPN score loss: 0.0063 RPN total loss: 0.0923 Total loss: 1.35285 timestamp: 1654937655.2438529 iteration: 29985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14957 FastRCNN class loss: 0.07836 FastRCNN total loss: 0.22793 L1 loss: 0.0000e+00 L2 loss: 0.82209 Learning rate: 0.02 Mask loss: 0.20316 RPN box loss: 0.03668 RPN score loss: 0.01116 RPN total loss: 0.04784 Total loss: 1.30102 timestamp: 1654937658.384638 iteration: 29990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11658 FastRCNN class loss: 0.09428 FastRCNN total loss: 0.21085 L1 loss: 0.0000e+00 L2 loss: 0.82199 Learning rate: 0.02 Mask loss: 0.09932 RPN box loss: 0.00713 RPN score loss: 0.00381 RPN total loss: 0.01095 Total loss: 1.14311 timestamp: 1654937661.5686545 iteration: 29995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14656 FastRCNN class loss: 0.10443 FastRCNN total loss: 0.25099 L1 loss: 0.0000e+00 L2 loss: 0.82187 Learning rate: 0.02 Mask loss: 0.26249 RPN box loss: 0.05265 RPN score loss: 0.01189 RPN total loss: 0.06454 Total loss: 1.39988 timestamp: 1654937664.7365377 iteration: 30000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12632 FastRCNN class loss: 0.09966 FastRCNN total loss: 0.22598 L1 loss: 0.0000e+00 L2 loss: 0.82174 Learning rate: 0.02 Mask loss: 0.18617 RPN box loss: 0.02376 RPN score loss: 0.00332 RPN total loss: 0.02708 Total loss: 1.26097 Saving checkpoints for 30000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-30000.tlt. ================================= Start evaluation cycle 03 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-30000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.6882s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.3310s - Throughput: 12.1 imgs/s Running inference on batch 003/125... - Step Time: 0.3232s - Throughput: 12.4 imgs/s Running inference on batch 004/125... - Step Time: 0.3293s - Throughput: 12.1 imgs/s Running inference on batch 005/125... - Step Time: 0.3314s - Throughput: 12.1 imgs/s Running inference on batch 006/125... - Step Time: 0.3295s - Throughput: 12.1 imgs/s Running inference on batch 007/125... - Step Time: 0.3274s - Throughput: 12.2 imgs/s Running inference on batch 008/125... - Step Time: 0.3293s - Throughput: 12.1 imgs/s Running inference on batch 009/125... - Step Time: 0.3255s - Throughput: 12.3 imgs/s Running inference on batch 010/125... - Step Time: 0.3177s - Throughput: 12.6 imgs/s Running inference on batch 011/125... - Step Time: 0.3251s - Throughput: 12.3 imgs/s Running inference on batch 012/125... - Step Time: 0.3247s - Throughput: 12.3 imgs/s Running inference on batch 013/125... - Step Time: 0.3142s - Throughput: 12.7 imgs/s Running inference on batch 014/125... - Step Time: 0.3246s - Throughput: 12.3 imgs/s Running inference on batch 015/125... - Step Time: 0.3248s - Throughput: 12.3 imgs/s Running inference on batch 016/125... - Step Time: 0.3232s - Throughput: 12.4 imgs/s Running inference on batch 017/125... - Step Time: 0.3399s - Throughput: 11.8 imgs/s Running inference on batch 018/125... - Step Time: 0.3191s - Throughput: 12.5 imgs/s Running inference on batch 019/125... - Step Time: 0.3278s - Throughput: 12.2 imgs/s Running inference on batch 020/125... - Step Time: 0.3252s - Throughput: 12.3 imgs/s Running inference on batch 021/125... - Step Time: 0.2961s - Throughput: 13.5 imgs/s Running inference on batch 022/125... - Step Time: 0.3269s - Throughput: 12.2 imgs/s Running inference on batch 023/125... - Step Time: 0.3244s - Throughput: 12.3 imgs/s Running inference on batch 024/125... - Step Time: 0.3174s - Throughput: 12.6 imgs/s Running inference on batch 025/125... - Step Time: 0.3249s - Throughput: 12.3 imgs/s Running inference on batch 026/125... - Step Time: 0.3236s - Throughput: 12.4 imgs/s Running inference on batch 027/125... - Step Time: 0.3167s - Throughput: 12.6 imgs/s Running inference on batch 028/125... - Step Time: 0.3107s - Throughput: 12.9 imgs/s Running inference on batch 029/125... - Step Time: 0.3033s - Throughput: 13.2 imgs/s Running inference on batch 030/125... - Step Time: 0.3345s - Throughput: 12.0 imgs/s Running inference on batch 031/125... - Step Time: 0.3301s - Throughput: 12.1 imgs/s Running inference on batch 032/125... - Step Time: 0.3256s - Throughput: 12.3 imgs/s Running inference on batch 033/125... - Step Time: 0.3271s - Throughput: 12.2 imgs/s Running inference on batch 034/125... - Step Time: 0.3283s - Throughput: 12.2 imgs/s Running inference on batch 035/125... - Step Time: 0.3204s - 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Throughput: 12.3 imgs/s Running inference on batch 120/125... - Step Time: 0.3315s - Throughput: 12.1 imgs/s Running inference on batch 121/125... - Step Time: 0.3118s - Throughput: 12.8 imgs/s Running inference on batch 122/125... - Step Time: 0.3162s - Throughput: 12.7 imgs/s Running inference on batch 123/125... - Step Time: 0.3202s - Throughput: 12.5 imgs/s Running inference on batch 124/125... - Step Time: 0.3368s - Throughput: 11.9 imgs/s Running inference on batch 125/125... - Step Time: 0.2676s - Throughput: 14.9 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 12.2 samples/sec Total processed steps: 125 Total processing time: 0.0h 25m 33s ==================== Metrics ==================== AP: 0.192477092 AP50: 0.300041258 AP75: 0.192473844 APl: 0.223955438 APm: 0.053843480 APs: 0.013550637 ARl: 0.432234615 ARm: 0.102896690 ARmax1: 0.265057921 ARmax10: 0.369865656 ARmax100: 0.375854522 ARs: 0.028904991 mask_AP: 0.150549278 mask_AP50: 0.246864662 mask_AP75: 0.153955266 mask_APl: 0.177654296 mask_APm: 0.027089702 mask_APs: 0.004935519 mask_ARl: 0.302947611 mask_ARm: 0.057324946 mask_ARmax1: 0.202643514 mask_ARmax10: 0.254404515 mask_ARmax100: 0.257922977 mask_ARs: 0.011312399 ================================= Start training cycle 04 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654938826.6207197 iteration: 30005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15565 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 0.82164 Learning rate: 0.02 Mask loss: 0.12154 RPN box loss: 0.03334 RPN score loss: 0.00687 RPN total loss: 0.0402 Total loss: 1.19838 timestamp: 1654938829.8319504 iteration: 30010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.15308 L1 loss: 0.0000e+00 L2 loss: 0.82154 Learning rate: 0.02 Mask loss: 0.1208 RPN box loss: 0.02166 RPN score loss: 0.00489 RPN total loss: 0.02656 Total loss: 1.12198 timestamp: 1654938833.018634 iteration: 30015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.19127 L1 loss: 0.0000e+00 L2 loss: 0.82144 Learning rate: 0.02 Mask loss: 0.18849 RPN box loss: 0.00915 RPN score loss: 0.00485 RPN total loss: 0.014 Total loss: 1.2152 timestamp: 1654938836.2291412 iteration: 30020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21042 FastRCNN class loss: 0.09142 FastRCNN total loss: 0.30185 L1 loss: 0.0000e+00 L2 loss: 0.8213 Learning rate: 0.02 Mask loss: 0.19369 RPN box loss: 0.05484 RPN score loss: 0.0039 RPN total loss: 0.05874 Total loss: 1.37558 timestamp: 1654938839.493631 iteration: 30025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1223 FastRCNN class loss: 0.05681 FastRCNN total loss: 0.17911 L1 loss: 0.0000e+00 L2 loss: 0.82118 Learning rate: 0.02 Mask loss: 0.15795 RPN box loss: 0.06135 RPN score loss: 0.00481 RPN total loss: 0.06616 Total loss: 1.2244 timestamp: 1654938842.6511772 iteration: 30030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12219 FastRCNN class loss: 0.07824 FastRCNN total loss: 0.20043 L1 loss: 0.0000e+00 L2 loss: 0.82107 Learning rate: 0.02 Mask loss: 0.09544 RPN box loss: 0.01305 RPN score loss: 0.00319 RPN total loss: 0.01624 Total loss: 1.13319 timestamp: 1654938845.8840494 iteration: 30035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08346 FastRCNN class loss: 0.07767 FastRCNN total loss: 0.16114 L1 loss: 0.0000e+00 L2 loss: 0.82097 Learning rate: 0.02 Mask loss: 0.17648 RPN box loss: 0.00866 RPN score loss: 0.00485 RPN total loss: 0.01351 Total loss: 1.1721 timestamp: 1654938849.0096083 iteration: 30040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12737 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.19227 L1 loss: 0.0000e+00 L2 loss: 0.82085 Learning rate: 0.02 Mask loss: 0.14745 RPN box loss: 0.00802 RPN score loss: 0.00296 RPN total loss: 0.01099 Total loss: 1.17156 timestamp: 1654938852.2078807 iteration: 30045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16721 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.25865 L1 loss: 0.0000e+00 L2 loss: 0.8207 Learning rate: 0.02 Mask loss: 0.09683 RPN box loss: 0.0166 RPN score loss: 0.0026 RPN total loss: 0.0192 Total loss: 1.19538 timestamp: 1654938855.3934653 iteration: 30050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11521 FastRCNN class loss: 0.09305 FastRCNN total loss: 0.20826 L1 loss: 0.0000e+00 L2 loss: 0.82058 Learning rate: 0.02 Mask loss: 0.13687 RPN box loss: 0.01469 RPN score loss: 0.00154 RPN total loss: 0.01623 Total loss: 1.18194 timestamp: 1654938858.6988807 iteration: 30055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.06229 FastRCNN total loss: 0.17912 L1 loss: 0.0000e+00 L2 loss: 0.82049 Learning rate: 0.02 Mask loss: 0.1198 RPN box loss: 0.04232 RPN score loss: 0.01006 RPN total loss: 0.05238 Total loss: 1.17178 timestamp: 1654938861.8892627 iteration: 30060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17595 FastRCNN class loss: 0.14285 FastRCNN total loss: 0.31879 L1 loss: 0.0000e+00 L2 loss: 0.82038 Learning rate: 0.02 Mask loss: 0.22152 RPN box loss: 0.03928 RPN score loss: 0.01121 RPN total loss: 0.05049 Total loss: 1.41118 timestamp: 1654938865.091779 iteration: 30065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10991 FastRCNN class loss: 0.07406 FastRCNN total loss: 0.18397 L1 loss: 0.0000e+00 L2 loss: 0.82026 Learning rate: 0.02 Mask loss: 0.15986 RPN box loss: 0.04182 RPN score loss: 0.00515 RPN total loss: 0.04696 Total loss: 1.21105 timestamp: 1654938868.355606 iteration: 30070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16032 FastRCNN class loss: 0.10063 FastRCNN total loss: 0.26094 L1 loss: 0.0000e+00 L2 loss: 0.82014 Learning rate: 0.02 Mask loss: 0.11674 RPN box loss: 0.03469 RPN score loss: 0.00523 RPN total loss: 0.03992 Total loss: 1.23775 timestamp: 1654938871.5139966 iteration: 30075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20008 FastRCNN class loss: 0.09206 FastRCNN total loss: 0.29215 L1 loss: 0.0000e+00 L2 loss: 0.82001 Learning rate: 0.02 Mask loss: 0.16343 RPN box loss: 0.02562 RPN score loss: 0.00586 RPN total loss: 0.03148 Total loss: 1.30706 timestamp: 1654938874.6523688 iteration: 30080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06389 FastRCNN class loss: 0.02773 FastRCNN total loss: 0.09162 L1 loss: 0.0000e+00 L2 loss: 0.81991 Learning rate: 0.02 Mask loss: 0.1248 RPN box loss: 0.02661 RPN score loss: 0.00369 RPN total loss: 0.0303 Total loss: 1.06664 timestamp: 1654938877.8994868 iteration: 30085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1237 FastRCNN class loss: 0.08671 FastRCNN total loss: 0.2104 L1 loss: 0.0000e+00 L2 loss: 0.8198 Learning rate: 0.02 Mask loss: 0.18747 RPN box loss: 0.03678 RPN score loss: 0.0044 RPN total loss: 0.04118 Total loss: 1.25886 timestamp: 1654938881.1174045 iteration: 30090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18007 FastRCNN class loss: 0.10592 FastRCNN total loss: 0.28599 L1 loss: 0.0000e+00 L2 loss: 0.81968 Learning rate: 0.02 Mask loss: 0.15572 RPN box loss: 0.02958 RPN score loss: 0.00651 RPN total loss: 0.03609 Total loss: 1.29748 timestamp: 1654938884.363296 iteration: 30095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.05662 FastRCNN total loss: 0.15984 L1 loss: 0.0000e+00 L2 loss: 0.81957 Learning rate: 0.02 Mask loss: 0.08857 RPN box loss: 0.02824 RPN score loss: 0.00332 RPN total loss: 0.03156 Total loss: 1.09954 timestamp: 1654938887.5541797 iteration: 30100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11487 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.16294 L1 loss: 0.0000e+00 L2 loss: 0.81944 Learning rate: 0.02 Mask loss: 0.10441 RPN box loss: 0.03097 RPN score loss: 0.00747 RPN total loss: 0.03844 Total loss: 1.12524 timestamp: 1654938890.703006 iteration: 30105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19409 FastRCNN class loss: 0.09599 FastRCNN total loss: 0.29008 L1 loss: 0.0000e+00 L2 loss: 0.81931 Learning rate: 0.02 Mask loss: 0.13957 RPN box loss: 0.05326 RPN score loss: 0.00736 RPN total loss: 0.06063 Total loss: 1.30958 timestamp: 1654938893.948423 iteration: 30110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10089 FastRCNN class loss: 0.07708 FastRCNN total loss: 0.17797 L1 loss: 0.0000e+00 L2 loss: 0.81921 Learning rate: 0.02 Mask loss: 0.12861 RPN box loss: 0.00779 RPN score loss: 0.00447 RPN total loss: 0.01226 Total loss: 1.13805 timestamp: 1654938897.1610255 iteration: 30115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15429 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.22559 L1 loss: 0.0000e+00 L2 loss: 0.81911 Learning rate: 0.02 Mask loss: 0.22589 RPN box loss: 0.02132 RPN score loss: 0.00475 RPN total loss: 0.02607 Total loss: 1.29666 timestamp: 1654938900.2987196 iteration: 30120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.03412 FastRCNN total loss: 0.09989 L1 loss: 0.0000e+00 L2 loss: 0.81897 Learning rate: 0.02 Mask loss: 0.10871 RPN box loss: 0.00228 RPN score loss: 0.00139 RPN total loss: 0.00367 Total loss: 1.03124 timestamp: 1654938903.6765769 iteration: 30125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11918 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.19312 L1 loss: 0.0000e+00 L2 loss: 0.81887 Learning rate: 0.02 Mask loss: 0.12851 RPN box loss: 0.01206 RPN score loss: 0.00281 RPN total loss: 0.01486 Total loss: 1.15536 timestamp: 1654938906.86808 iteration: 30130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11775 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.19966 L1 loss: 0.0000e+00 L2 loss: 0.81875 Learning rate: 0.02 Mask loss: 0.18555 RPN box loss: 0.06702 RPN score loss: 0.00944 RPN total loss: 0.07646 Total loss: 1.28042 timestamp: 1654938910.1099796 iteration: 30135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16095 FastRCNN class loss: 0.08924 FastRCNN total loss: 0.25019 L1 loss: 0.0000e+00 L2 loss: 0.81861 Learning rate: 0.02 Mask loss: 0.13832 RPN box loss: 0.01796 RPN score loss: 0.01482 RPN total loss: 0.03279 Total loss: 1.2399 timestamp: 1654938913.3032799 iteration: 30140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13896 FastRCNN class loss: 0.10396 FastRCNN total loss: 0.24292 L1 loss: 0.0000e+00 L2 loss: 0.81849 Learning rate: 0.02 Mask loss: 0.13722 RPN box loss: 0.03455 RPN score loss: 0.0042 RPN total loss: 0.03875 Total loss: 1.23738 timestamp: 1654938916.460127 iteration: 30145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12524 FastRCNN class loss: 0.0585 FastRCNN total loss: 0.18374 L1 loss: 0.0000e+00 L2 loss: 0.81838 Learning rate: 0.02 Mask loss: 0.09105 RPN box loss: 0.00951 RPN score loss: 0.00196 RPN total loss: 0.01147 Total loss: 1.10464 timestamp: 1654938919.660793 iteration: 30150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.08432 FastRCNN total loss: 0.20329 L1 loss: 0.0000e+00 L2 loss: 0.81824 Learning rate: 0.02 Mask loss: 0.13185 RPN box loss: 0.03412 RPN score loss: 0.00779 RPN total loss: 0.04191 Total loss: 1.1953 timestamp: 1654938922.8968575 iteration: 30155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10319 FastRCNN class loss: 0.04929 FastRCNN total loss: 0.15248 L1 loss: 0.0000e+00 L2 loss: 0.81814 Learning rate: 0.02 Mask loss: 0.08528 RPN box loss: 0.00923 RPN score loss: 0.00311 RPN total loss: 0.01233 Total loss: 1.06824 timestamp: 1654938926.0738263 iteration: 30160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09851 FastRCNN class loss: 0.08673 FastRCNN total loss: 0.18524 L1 loss: 0.0000e+00 L2 loss: 0.81803 Learning rate: 0.02 Mask loss: 0.21606 RPN box loss: 0.01053 RPN score loss: 0.00323 RPN total loss: 0.01376 Total loss: 1.23308 timestamp: 1654938929.2951784 iteration: 30165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10163 FastRCNN class loss: 0.05331 FastRCNN total loss: 0.15493 L1 loss: 0.0000e+00 L2 loss: 0.8179 Learning rate: 0.02 Mask loss: 0.12862 RPN box loss: 0.02482 RPN score loss: 0.00256 RPN total loss: 0.02738 Total loss: 1.12884 timestamp: 1654938932.4860318 iteration: 30170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13972 FastRCNN class loss: 0.09174 FastRCNN total loss: 0.23147 L1 loss: 0.0000e+00 L2 loss: 0.81777 Learning rate: 0.02 Mask loss: 0.25313 RPN box loss: 0.04525 RPN score loss: 0.0126 RPN total loss: 0.05784 Total loss: 1.36021 timestamp: 1654938935.7045112 iteration: 30175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10115 FastRCNN class loss: 0.06837 FastRCNN total loss: 0.16952 L1 loss: 0.0000e+00 L2 loss: 0.81766 Learning rate: 0.02 Mask loss: 0.11605 RPN box loss: 0.00773 RPN score loss: 0.00175 RPN total loss: 0.00948 Total loss: 1.11271 timestamp: 1654938938.8723466 iteration: 30180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12128 FastRCNN class loss: 0.078 FastRCNN total loss: 0.19927 L1 loss: 0.0000e+00 L2 loss: 0.81754 Learning rate: 0.02 Mask loss: 0.16763 RPN box loss: 0.02942 RPN score loss: 0.00684 RPN total loss: 0.03626 Total loss: 1.22071 timestamp: 1654938942.0357366 iteration: 30185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09465 FastRCNN class loss: 0.1276 FastRCNN total loss: 0.22225 L1 loss: 0.0000e+00 L2 loss: 0.8174 Learning rate: 0.02 Mask loss: 0.16888 RPN box loss: 0.03947 RPN score loss: 0.01643 RPN total loss: 0.0559 Total loss: 1.26443 timestamp: 1654938945.1552596 iteration: 30190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11989 FastRCNN class loss: 0.09906 FastRCNN total loss: 0.21894 L1 loss: 0.0000e+00 L2 loss: 0.81726 Learning rate: 0.02 Mask loss: 0.13925 RPN box loss: 0.04441 RPN score loss: 0.00407 RPN total loss: 0.04848 Total loss: 1.22393 timestamp: 1654938948.3635466 iteration: 30195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14249 FastRCNN class loss: 0.10587 FastRCNN total loss: 0.24836 L1 loss: 0.0000e+00 L2 loss: 0.81716 Learning rate: 0.02 Mask loss: 0.1989 RPN box loss: 0.05047 RPN score loss: 0.00683 RPN total loss: 0.0573 Total loss: 1.32172 timestamp: 1654938951.557966 iteration: 30200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18452 FastRCNN class loss: 0.08474 FastRCNN total loss: 0.26926 L1 loss: 0.0000e+00 L2 loss: 0.81707 Learning rate: 0.02 Mask loss: 0.12246 RPN box loss: 0.07611 RPN score loss: 0.0059 RPN total loss: 0.082 Total loss: 1.2908 timestamp: 1654938954.743975 iteration: 30205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13049 FastRCNN class loss: 0.11074 FastRCNN total loss: 0.24124 L1 loss: 0.0000e+00 L2 loss: 0.81696 Learning rate: 0.02 Mask loss: 0.13572 RPN box loss: 0.0383 RPN score loss: 0.00513 RPN total loss: 0.04342 Total loss: 1.23734 timestamp: 1654938957.8506527 iteration: 30210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12684 FastRCNN class loss: 0.09373 FastRCNN total loss: 0.22058 L1 loss: 0.0000e+00 L2 loss: 0.81685 Learning rate: 0.02 Mask loss: 0.20892 RPN box loss: 0.02169 RPN score loss: 0.00342 RPN total loss: 0.0251 Total loss: 1.27145 timestamp: 1654938961.0331566 iteration: 30215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10822 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.18891 L1 loss: 0.0000e+00 L2 loss: 0.81671 Learning rate: 0.02 Mask loss: 0.23109 RPN box loss: 0.02298 RPN score loss: 0.00528 RPN total loss: 0.02826 Total loss: 1.26496 timestamp: 1654938964.2268085 iteration: 30220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0436 FastRCNN class loss: 0.04847 FastRCNN total loss: 0.09207 L1 loss: 0.0000e+00 L2 loss: 0.81658 Learning rate: 0.02 Mask loss: 0.09269 RPN box loss: 0.03519 RPN score loss: 0.00609 RPN total loss: 0.04128 Total loss: 1.04261 timestamp: 1654938967.4337382 iteration: 30225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08086 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.13708 L1 loss: 0.0000e+00 L2 loss: 0.81648 Learning rate: 0.02 Mask loss: 0.11534 RPN box loss: 0.0201 RPN score loss: 0.00777 RPN total loss: 0.02787 Total loss: 1.09677 timestamp: 1654938970.5959334 iteration: 30230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17312 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.27274 L1 loss: 0.0000e+00 L2 loss: 0.81637 Learning rate: 0.02 Mask loss: 0.24571 RPN box loss: 0.01454 RPN score loss: 0.00306 RPN total loss: 0.0176 Total loss: 1.35242 timestamp: 1654938973.8439915 iteration: 30235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12776 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.20393 L1 loss: 0.0000e+00 L2 loss: 0.81627 Learning rate: 0.02 Mask loss: 0.09758 RPN box loss: 0.01019 RPN score loss: 0.00538 RPN total loss: 0.01557 Total loss: 1.13335 timestamp: 1654938977.108335 iteration: 30240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13882 FastRCNN class loss: 0.06471 FastRCNN total loss: 0.20353 L1 loss: 0.0000e+00 L2 loss: 0.81615 Learning rate: 0.02 Mask loss: 0.12108 RPN box loss: 0.0213 RPN score loss: 0.00517 RPN total loss: 0.02647 Total loss: 1.16723 timestamp: 1654938980.310257 iteration: 30245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14358 FastRCNN class loss: 0.09464 FastRCNN total loss: 0.23823 L1 loss: 0.0000e+00 L2 loss: 0.81601 Learning rate: 0.02 Mask loss: 0.15988 RPN box loss: 0.04401 RPN score loss: 0.00643 RPN total loss: 0.05044 Total loss: 1.26457 timestamp: 1654938983.4308438 iteration: 30250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12442 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.17957 L1 loss: 0.0000e+00 L2 loss: 0.81586 Learning rate: 0.02 Mask loss: 0.105 RPN box loss: 0.02841 RPN score loss: 0.00172 RPN total loss: 0.03013 Total loss: 1.13057 timestamp: 1654938986.6158032 iteration: 30255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10725 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.16607 L1 loss: 0.0000e+00 L2 loss: 0.81576 Learning rate: 0.02 Mask loss: 0.09301 RPN box loss: 0.00841 RPN score loss: 0.00423 RPN total loss: 0.01264 Total loss: 1.08748 timestamp: 1654938989.8682258 iteration: 30260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10253 FastRCNN class loss: 0.07293 FastRCNN total loss: 0.17545 L1 loss: 0.0000e+00 L2 loss: 0.81565 Learning rate: 0.02 Mask loss: 0.12904 RPN box loss: 0.01255 RPN score loss: 0.00464 RPN total loss: 0.01719 Total loss: 1.13734 timestamp: 1654938993.0384948 iteration: 30265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14309 FastRCNN class loss: 0.08827 FastRCNN total loss: 0.23136 L1 loss: 0.0000e+00 L2 loss: 0.81553 Learning rate: 0.02 Mask loss: 0.13649 RPN box loss: 0.03774 RPN score loss: 0.00806 RPN total loss: 0.0458 Total loss: 1.22919 timestamp: 1654938996.280191 iteration: 30270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14473 FastRCNN class loss: 0.09143 FastRCNN total loss: 0.23616 L1 loss: 0.0000e+00 L2 loss: 0.81542 Learning rate: 0.02 Mask loss: 0.19448 RPN box loss: 0.01617 RPN score loss: 0.01003 RPN total loss: 0.0262 Total loss: 1.27226 timestamp: 1654938999.4818234 iteration: 30275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14819 FastRCNN class loss: 0.09431 FastRCNN total loss: 0.2425 L1 loss: 0.0000e+00 L2 loss: 0.81529 Learning rate: 0.02 Mask loss: 0.15654 RPN box loss: 0.03521 RPN score loss: 0.0051 RPN total loss: 0.04031 Total loss: 1.25463 timestamp: 1654939002.7636178 iteration: 30280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17131 FastRCNN class loss: 0.08 FastRCNN total loss: 0.25131 L1 loss: 0.0000e+00 L2 loss: 0.81516 Learning rate: 0.02 Mask loss: 0.15894 RPN box loss: 0.00654 RPN score loss: 0.00264 RPN total loss: 0.00918 Total loss: 1.23459 timestamp: 1654939005.9716794 iteration: 30285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11074 FastRCNN class loss: 0.04293 FastRCNN total loss: 0.15367 L1 loss: 0.0000e+00 L2 loss: 0.81503 Learning rate: 0.02 Mask loss: 0.08528 RPN box loss: 0.02268 RPN score loss: 0.00716 RPN total loss: 0.02984 Total loss: 1.08382 timestamp: 1654939009.277893 iteration: 30290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.06434 FastRCNN total loss: 0.16482 L1 loss: 0.0000e+00 L2 loss: 0.81492 Learning rate: 0.02 Mask loss: 0.11324 RPN box loss: 0.02752 RPN score loss: 0.00304 RPN total loss: 0.03056 Total loss: 1.12355 timestamp: 1654939012.4439008 iteration: 30295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1018 FastRCNN class loss: 0.07898 FastRCNN total loss: 0.18077 L1 loss: 0.0000e+00 L2 loss: 0.81481 Learning rate: 0.02 Mask loss: 0.14575 RPN box loss: 0.06377 RPN score loss: 0.01084 RPN total loss: 0.07461 Total loss: 1.21594 timestamp: 1654939015.6192698 iteration: 30300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17407 FastRCNN class loss: 0.11311 FastRCNN total loss: 0.28719 L1 loss: 0.0000e+00 L2 loss: 0.81471 Learning rate: 0.02 Mask loss: 0.15971 RPN box loss: 0.05346 RPN score loss: 0.00719 RPN total loss: 0.06065 Total loss: 1.32225 timestamp: 1654939018.8291867 iteration: 30305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12662 FastRCNN class loss: 0.06553 FastRCNN total loss: 0.19214 L1 loss: 0.0000e+00 L2 loss: 0.8146 Learning rate: 0.02 Mask loss: 0.12521 RPN box loss: 0.03145 RPN score loss: 0.00592 RPN total loss: 0.03738 Total loss: 1.16932 timestamp: 1654939022.0467417 iteration: 30310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13526 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.20375 L1 loss: 0.0000e+00 L2 loss: 0.81448 Learning rate: 0.02 Mask loss: 0.1454 RPN box loss: 0.02475 RPN score loss: 0.00388 RPN total loss: 0.02863 Total loss: 1.19226 timestamp: 1654939025.2407296 iteration: 30315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13775 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.19704 L1 loss: 0.0000e+00 L2 loss: 0.81436 Learning rate: 0.02 Mask loss: 0.17934 RPN box loss: 0.0305 RPN score loss: 0.00981 RPN total loss: 0.04031 Total loss: 1.23106 timestamp: 1654939028.4337904 iteration: 30320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17059 FastRCNN class loss: 0.10137 FastRCNN total loss: 0.27196 L1 loss: 0.0000e+00 L2 loss: 0.81424 Learning rate: 0.02 Mask loss: 0.22324 RPN box loss: 0.0149 RPN score loss: 0.00261 RPN total loss: 0.0175 Total loss: 1.32694 timestamp: 1654939031.6891143 iteration: 30325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0757 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.12376 L1 loss: 0.0000e+00 L2 loss: 0.81413 Learning rate: 0.02 Mask loss: 0.12433 RPN box loss: 0.03734 RPN score loss: 0.0019 RPN total loss: 0.03923 Total loss: 1.10146 timestamp: 1654939034.8432748 iteration: 30330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13894 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.2037 L1 loss: 0.0000e+00 L2 loss: 0.81401 Learning rate: 0.02 Mask loss: 0.14226 RPN box loss: 0.04101 RPN score loss: 0.0044 RPN total loss: 0.04541 Total loss: 1.20538 timestamp: 1654939038.1054971 iteration: 30335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16526 FastRCNN class loss: 0.10019 FastRCNN total loss: 0.26544 L1 loss: 0.0000e+00 L2 loss: 0.81389 Learning rate: 0.02 Mask loss: 0.15094 RPN box loss: 0.0522 RPN score loss: 0.01899 RPN total loss: 0.07119 Total loss: 1.30147 timestamp: 1654939041.342269 iteration: 30340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0977 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.16116 L1 loss: 0.0000e+00 L2 loss: 0.81376 Learning rate: 0.02 Mask loss: 0.21311 RPN box loss: 0.02882 RPN score loss: 0.00782 RPN total loss: 0.03664 Total loss: 1.22467 timestamp: 1654939044.5920699 iteration: 30345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12865 FastRCNN class loss: 0.07364 FastRCNN total loss: 0.20229 L1 loss: 0.0000e+00 L2 loss: 0.81364 Learning rate: 0.02 Mask loss: 0.15169 RPN box loss: 0.01515 RPN score loss: 0.00746 RPN total loss: 0.0226 Total loss: 1.19022 timestamp: 1654939047.7612636 iteration: 30350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19479 FastRCNN class loss: 0.11992 FastRCNN total loss: 0.31471 L1 loss: 0.0000e+00 L2 loss: 0.81352 Learning rate: 0.02 Mask loss: 0.29092 RPN box loss: 0.04562 RPN score loss: 0.02359 RPN total loss: 0.06921 Total loss: 1.48836 timestamp: 1654939050.9626677 iteration: 30355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1423 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.1996 L1 loss: 0.0000e+00 L2 loss: 0.81341 Learning rate: 0.02 Mask loss: 0.10385 RPN box loss: 0.0313 RPN score loss: 0.00396 RPN total loss: 0.03525 Total loss: 1.15211 timestamp: 1654939054.1376617 iteration: 30360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16471 FastRCNN class loss: 0.12269 FastRCNN total loss: 0.28739 L1 loss: 0.0000e+00 L2 loss: 0.81329 Learning rate: 0.02 Mask loss: 0.17161 RPN box loss: 0.04434 RPN score loss: 0.01287 RPN total loss: 0.05721 Total loss: 1.32951 timestamp: 1654939057.317679 iteration: 30365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.07349 FastRCNN total loss: 0.16112 L1 loss: 0.0000e+00 L2 loss: 0.81317 Learning rate: 0.02 Mask loss: 0.10775 RPN box loss: 0.03546 RPN score loss: 0.00625 RPN total loss: 0.04171 Total loss: 1.12376 timestamp: 1654939060.5647094 iteration: 30370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10972 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.17661 L1 loss: 0.0000e+00 L2 loss: 0.81305 Learning rate: 0.02 Mask loss: 0.11251 RPN box loss: 0.02702 RPN score loss: 0.00247 RPN total loss: 0.0295 Total loss: 1.13167 timestamp: 1654939063.741663 iteration: 30375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11432 FastRCNN class loss: 0.08286 FastRCNN total loss: 0.19718 L1 loss: 0.0000e+00 L2 loss: 0.81294 Learning rate: 0.02 Mask loss: 0.24073 RPN box loss: 0.01442 RPN score loss: 0.00486 RPN total loss: 0.01928 Total loss: 1.27012 timestamp: 1654939066.9263194 iteration: 30380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11099 FastRCNN class loss: 0.08085 FastRCNN total loss: 0.19184 L1 loss: 0.0000e+00 L2 loss: 0.81284 Learning rate: 0.02 Mask loss: 0.18403 RPN box loss: 0.02617 RPN score loss: 0.00766 RPN total loss: 0.03383 Total loss: 1.22254 timestamp: 1654939070.1659455 iteration: 30385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31302 FastRCNN class loss: 0.14947 FastRCNN total loss: 0.46249 L1 loss: 0.0000e+00 L2 loss: 0.81272 Learning rate: 0.02 Mask loss: 0.20298 RPN box loss: 0.04168 RPN score loss: 0.03604 RPN total loss: 0.07772 Total loss: 1.55591 timestamp: 1654939073.3525932 iteration: 30390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09009 FastRCNN class loss: 0.04568 FastRCNN total loss: 0.13578 L1 loss: 0.0000e+00 L2 loss: 0.8126 Learning rate: 0.02 Mask loss: 0.2921 RPN box loss: 0.02386 RPN score loss: 0.00414 RPN total loss: 0.02799 Total loss: 1.26847 timestamp: 1654939076.574912 iteration: 30395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09482 FastRCNN class loss: 0.10223 FastRCNN total loss: 0.19705 L1 loss: 0.0000e+00 L2 loss: 0.81249 Learning rate: 0.02 Mask loss: 0.12875 RPN box loss: 0.03093 RPN score loss: 0.00833 RPN total loss: 0.03925 Total loss: 1.17755 timestamp: 1654939079.7870762 iteration: 30400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08786 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.15924 L1 loss: 0.0000e+00 L2 loss: 0.81236 Learning rate: 0.02 Mask loss: 0.14291 RPN box loss: 0.00948 RPN score loss: 0.00494 RPN total loss: 0.01442 Total loss: 1.12894 timestamp: 1654939083.0164785 iteration: 30405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08317 FastRCNN class loss: 0.08319 FastRCNN total loss: 0.16636 L1 loss: 0.0000e+00 L2 loss: 0.81227 Learning rate: 0.02 Mask loss: 0.12967 RPN box loss: 0.00753 RPN score loss: 0.00311 RPN total loss: 0.01064 Total loss: 1.11893 timestamp: 1654939086.1970048 iteration: 30410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15988 FastRCNN class loss: 0.13292 FastRCNN total loss: 0.2928 L1 loss: 0.0000e+00 L2 loss: 0.81216 Learning rate: 0.02 Mask loss: 0.14588 RPN box loss: 0.02927 RPN score loss: 0.00359 RPN total loss: 0.03287 Total loss: 1.2837 timestamp: 1654939089.4446397 iteration: 30415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10281 FastRCNN class loss: 0.07498 FastRCNN total loss: 0.17779 L1 loss: 0.0000e+00 L2 loss: 0.81203 Learning rate: 0.02 Mask loss: 0.12165 RPN box loss: 0.01621 RPN score loss: 0.00565 RPN total loss: 0.02186 Total loss: 1.13333 timestamp: 1654939092.6949372 iteration: 30420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07886 FastRCNN class loss: 0.05861 FastRCNN total loss: 0.13747 L1 loss: 0.0000e+00 L2 loss: 0.81189 Learning rate: 0.02 Mask loss: 0.15447 RPN box loss: 0.04332 RPN score loss: 0.00213 RPN total loss: 0.04545 Total loss: 1.14928 timestamp: 1654939095.88894 iteration: 30425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.18355 L1 loss: 0.0000e+00 L2 loss: 0.81177 Learning rate: 0.02 Mask loss: 0.24078 RPN box loss: 0.0348 RPN score loss: 0.01528 RPN total loss: 0.05008 Total loss: 1.28618 timestamp: 1654939099.1548746 iteration: 30430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18327 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.27702 L1 loss: 0.0000e+00 L2 loss: 0.81167 Learning rate: 0.02 Mask loss: 0.17522 RPN box loss: 0.01912 RPN score loss: 0.00627 RPN total loss: 0.02538 Total loss: 1.2893 timestamp: 1654939102.3800776 iteration: 30435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12437 FastRCNN class loss: 0.08809 FastRCNN total loss: 0.21246 L1 loss: 0.0000e+00 L2 loss: 0.81157 Learning rate: 0.02 Mask loss: 0.2012 RPN box loss: 0.03211 RPN score loss: 0.00854 RPN total loss: 0.04065 Total loss: 1.26587 timestamp: 1654939105.5623431 iteration: 30440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15017 FastRCNN class loss: 0.05097 FastRCNN total loss: 0.20113 L1 loss: 0.0000e+00 L2 loss: 0.81145 Learning rate: 0.02 Mask loss: 0.19719 RPN box loss: 0.01594 RPN score loss: 0.00174 RPN total loss: 0.01768 Total loss: 1.22746 timestamp: 1654939108.783458 iteration: 30445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10245 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.16906 L1 loss: 0.0000e+00 L2 loss: 0.81134 Learning rate: 0.02 Mask loss: 0.13652 RPN box loss: 0.02844 RPN score loss: 0.00635 RPN total loss: 0.03479 Total loss: 1.15172 timestamp: 1654939111.959513 iteration: 30450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12239 FastRCNN class loss: 0.07658 FastRCNN total loss: 0.19897 L1 loss: 0.0000e+00 L2 loss: 0.81122 Learning rate: 0.02 Mask loss: 0.17842 RPN box loss: 0.01626 RPN score loss: 0.0102 RPN total loss: 0.02645 Total loss: 1.21506 timestamp: 1654939115.281294 iteration: 30455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15062 FastRCNN class loss: 0.18053 FastRCNN total loss: 0.33114 L1 loss: 0.0000e+00 L2 loss: 0.81109 Learning rate: 0.02 Mask loss: 0.21603 RPN box loss: 0.04406 RPN score loss: 0.01058 RPN total loss: 0.05464 Total loss: 1.4129 timestamp: 1654939118.4959862 iteration: 30460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1057 FastRCNN class loss: 0.08207 FastRCNN total loss: 0.18777 L1 loss: 0.0000e+00 L2 loss: 0.81097 Learning rate: 0.02 Mask loss: 0.15092 RPN box loss: 0.04653 RPN score loss: 0.01039 RPN total loss: 0.05693 Total loss: 1.20658 timestamp: 1654939121.664669 iteration: 30465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09274 FastRCNN class loss: 0.04147 FastRCNN total loss: 0.1342 L1 loss: 0.0000e+00 L2 loss: 0.81084 Learning rate: 0.02 Mask loss: 0.12403 RPN box loss: 0.00367 RPN score loss: 0.00551 RPN total loss: 0.00918 Total loss: 1.07825 timestamp: 1654939124.83644 iteration: 30470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11136 FastRCNN class loss: 0.11028 FastRCNN total loss: 0.22164 L1 loss: 0.0000e+00 L2 loss: 0.81072 Learning rate: 0.02 Mask loss: 0.17671 RPN box loss: 0.04811 RPN score loss: 0.01489 RPN total loss: 0.063 Total loss: 1.27207 timestamp: 1654939128.0626073 iteration: 30475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14404 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.21843 L1 loss: 0.0000e+00 L2 loss: 0.81061 Learning rate: 0.02 Mask loss: 0.14119 RPN box loss: 0.01444 RPN score loss: 0.00164 RPN total loss: 0.01608 Total loss: 1.18631 timestamp: 1654939131.2440763 iteration: 30480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13981 FastRCNN class loss: 0.11857 FastRCNN total loss: 0.25838 L1 loss: 0.0000e+00 L2 loss: 0.81051 Learning rate: 0.02 Mask loss: 0.15829 RPN box loss: 0.03043 RPN score loss: 0.00399 RPN total loss: 0.03441 Total loss: 1.26159 timestamp: 1654939134.4265044 iteration: 30485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16472 FastRCNN class loss: 0.08047 FastRCNN total loss: 0.24519 L1 loss: 0.0000e+00 L2 loss: 0.81039 Learning rate: 0.02 Mask loss: 0.12997 RPN box loss: 0.02473 RPN score loss: 0.00846 RPN total loss: 0.03319 Total loss: 1.21874 timestamp: 1654939137.66283 iteration: 30490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.084 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.14234 L1 loss: 0.0000e+00 L2 loss: 0.81025 Learning rate: 0.02 Mask loss: 0.12419 RPN box loss: 0.06374 RPN score loss: 0.01176 RPN total loss: 0.0755 Total loss: 1.15228 timestamp: 1654939140.860335 iteration: 30495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12868 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.19982 L1 loss: 0.0000e+00 L2 loss: 0.81015 Learning rate: 0.02 Mask loss: 0.21928 RPN box loss: 0.02312 RPN score loss: 0.00782 RPN total loss: 0.03093 Total loss: 1.26019 timestamp: 1654939144.1387806 iteration: 30500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18555 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.27968 L1 loss: 0.0000e+00 L2 loss: 0.81002 Learning rate: 0.02 Mask loss: 0.14845 RPN box loss: 0.01811 RPN score loss: 0.00424 RPN total loss: 0.02236 Total loss: 1.26052 timestamp: 1654939147.4014857 iteration: 30505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13565 FastRCNN class loss: 0.04969 FastRCNN total loss: 0.18534 L1 loss: 0.0000e+00 L2 loss: 0.80988 Learning rate: 0.02 Mask loss: 0.15601 RPN box loss: 0.00658 RPN score loss: 0.00357 RPN total loss: 0.01015 Total loss: 1.16138 timestamp: 1654939150.5979578 iteration: 30510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12617 FastRCNN class loss: 0.09213 FastRCNN total loss: 0.21829 L1 loss: 0.0000e+00 L2 loss: 0.80977 Learning rate: 0.02 Mask loss: 0.14762 RPN box loss: 0.009 RPN score loss: 0.0046 RPN total loss: 0.0136 Total loss: 1.18928 timestamp: 1654939153.8206134 iteration: 30515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09378 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.17076 L1 loss: 0.0000e+00 L2 loss: 0.80966 Learning rate: 0.02 Mask loss: 0.15599 RPN box loss: 0.03331 RPN score loss: 0.00568 RPN total loss: 0.03899 Total loss: 1.1754 timestamp: 1654939156.9617407 iteration: 30520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.0417 FastRCNN total loss: 0.12458 L1 loss: 0.0000e+00 L2 loss: 0.80955 Learning rate: 0.02 Mask loss: 0.13401 RPN box loss: 0.01797 RPN score loss: 0.00505 RPN total loss: 0.02302 Total loss: 1.09116 timestamp: 1654939160.1417396 iteration: 30525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15287 FastRCNN class loss: 0.08799 FastRCNN total loss: 0.24086 L1 loss: 0.0000e+00 L2 loss: 0.80943 Learning rate: 0.02 Mask loss: 0.11721 RPN box loss: 0.05016 RPN score loss: 0.00603 RPN total loss: 0.05619 Total loss: 1.22369 timestamp: 1654939163.386545 iteration: 30530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13588 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.21006 L1 loss: 0.0000e+00 L2 loss: 0.80933 Learning rate: 0.02 Mask loss: 0.17732 RPN box loss: 0.04808 RPN score loss: 0.00495 RPN total loss: 0.05303 Total loss: 1.24974 timestamp: 1654939166.541524 iteration: 30535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14275 FastRCNN class loss: 0.05478 FastRCNN total loss: 0.19754 L1 loss: 0.0000e+00 L2 loss: 0.80921 Learning rate: 0.02 Mask loss: 0.13768 RPN box loss: 0.02856 RPN score loss: 0.00182 RPN total loss: 0.03037 Total loss: 1.1748 timestamp: 1654939169.734147 iteration: 30540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11232 FastRCNN class loss: 0.04741 FastRCNN total loss: 0.15973 L1 loss: 0.0000e+00 L2 loss: 0.80909 Learning rate: 0.02 Mask loss: 0.07864 RPN box loss: 0.00485 RPN score loss: 0.00189 RPN total loss: 0.00674 Total loss: 1.05421 timestamp: 1654939172.9981523 iteration: 30545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15606 FastRCNN class loss: 0.10148 FastRCNN total loss: 0.25755 L1 loss: 0.0000e+00 L2 loss: 0.80894 Learning rate: 0.02 Mask loss: 0.17676 RPN box loss: 0.06579 RPN score loss: 0.01974 RPN total loss: 0.08553 Total loss: 1.32878 timestamp: 1654939176.1597166 iteration: 30550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10716 FastRCNN class loss: 0.09443 FastRCNN total loss: 0.20159 L1 loss: 0.0000e+00 L2 loss: 0.80882 Learning rate: 0.02 Mask loss: 0.14993 RPN box loss: 0.02493 RPN score loss: 0.0064 RPN total loss: 0.03133 Total loss: 1.19167 timestamp: 1654939179.3798366 iteration: 30555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.06636 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.80871 Learning rate: 0.02 Mask loss: 0.15771 RPN box loss: 0.04045 RPN score loss: 0.01395 RPN total loss: 0.05439 Total loss: 1.18089 timestamp: 1654939182.662771 iteration: 30560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21236 FastRCNN class loss: 0.10188 FastRCNN total loss: 0.31425 L1 loss: 0.0000e+00 L2 loss: 0.8086 Learning rate: 0.02 Mask loss: 0.21288 RPN box loss: 0.01763 RPN score loss: 0.01272 RPN total loss: 0.03035 Total loss: 1.36608 timestamp: 1654939185.880838 iteration: 30565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09986 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.17625 L1 loss: 0.0000e+00 L2 loss: 0.80851 Learning rate: 0.02 Mask loss: 0.15959 RPN box loss: 0.03293 RPN score loss: 0.00742 RPN total loss: 0.04034 Total loss: 1.18469 timestamp: 1654939189.091105 iteration: 30570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15311 FastRCNN class loss: 0.07941 FastRCNN total loss: 0.23252 L1 loss: 0.0000e+00 L2 loss: 0.8084 Learning rate: 0.02 Mask loss: 0.27893 RPN box loss: 0.01227 RPN score loss: 0.00674 RPN total loss: 0.01901 Total loss: 1.33887 timestamp: 1654939192.3001463 iteration: 30575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09408 FastRCNN class loss: 0.04948 FastRCNN total loss: 0.14356 L1 loss: 0.0000e+00 L2 loss: 0.8083 Learning rate: 0.02 Mask loss: 0.15369 RPN box loss: 0.03442 RPN score loss: 0.00733 RPN total loss: 0.04176 Total loss: 1.1473 timestamp: 1654939195.4780633 iteration: 30580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13116 FastRCNN class loss: 0.08512 FastRCNN total loss: 0.21628 L1 loss: 0.0000e+00 L2 loss: 0.80818 Learning rate: 0.02 Mask loss: 0.13188 RPN box loss: 0.01973 RPN score loss: 0.00278 RPN total loss: 0.02251 Total loss: 1.17886 timestamp: 1654939198.7049992 iteration: 30585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20014 FastRCNN class loss: 0.10141 FastRCNN total loss: 0.30154 L1 loss: 0.0000e+00 L2 loss: 0.80805 Learning rate: 0.02 Mask loss: 0.27479 RPN box loss: 0.01241 RPN score loss: 0.01066 RPN total loss: 0.02307 Total loss: 1.40745 timestamp: 1654939201.9359872 iteration: 30590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13239 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.20537 L1 loss: 0.0000e+00 L2 loss: 0.80792 Learning rate: 0.02 Mask loss: 0.16421 RPN box loss: 0.02004 RPN score loss: 0.00251 RPN total loss: 0.02255 Total loss: 1.20005 timestamp: 1654939205.1693516 iteration: 30595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14602 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.22293 L1 loss: 0.0000e+00 L2 loss: 0.80784 Learning rate: 0.02 Mask loss: 0.115 RPN box loss: 0.02821 RPN score loss: 0.00955 RPN total loss: 0.03776 Total loss: 1.18353 timestamp: 1654939208.396711 iteration: 30600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19706 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.27628 L1 loss: 0.0000e+00 L2 loss: 0.80772 Learning rate: 0.02 Mask loss: 0.11261 RPN box loss: 0.04338 RPN score loss: 0.00698 RPN total loss: 0.05036 Total loss: 1.24697 timestamp: 1654939211.606418 iteration: 30605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16508 FastRCNN class loss: 0.08287 FastRCNN total loss: 0.24795 L1 loss: 0.0000e+00 L2 loss: 0.8076 Learning rate: 0.02 Mask loss: 0.11588 RPN box loss: 0.03897 RPN score loss: 0.00913 RPN total loss: 0.0481 Total loss: 1.21952 timestamp: 1654939214.8402026 iteration: 30610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14227 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.21429 L1 loss: 0.0000e+00 L2 loss: 0.80745 Learning rate: 0.02 Mask loss: 0.12067 RPN box loss: 0.06368 RPN score loss: 0.00808 RPN total loss: 0.07176 Total loss: 1.21417 timestamp: 1654939218.0416994 iteration: 30615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14527 FastRCNN class loss: 0.08827 FastRCNN total loss: 0.23354 L1 loss: 0.0000e+00 L2 loss: 0.80735 Learning rate: 0.02 Mask loss: 0.16913 RPN box loss: 0.02842 RPN score loss: 0.00833 RPN total loss: 0.03675 Total loss: 1.24677 timestamp: 1654939221.2942436 iteration: 30620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1538 FastRCNN class loss: 0.10279 FastRCNN total loss: 0.25659 L1 loss: 0.0000e+00 L2 loss: 0.80724 Learning rate: 0.02 Mask loss: 0.18587 RPN box loss: 0.0165 RPN score loss: 0.0045 RPN total loss: 0.02101 Total loss: 1.27072 timestamp: 1654939224.453466 iteration: 30625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13129 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.19884 L1 loss: 0.0000e+00 L2 loss: 0.80714 Learning rate: 0.02 Mask loss: 0.1382 RPN box loss: 0.02511 RPN score loss: 0.00615 RPN total loss: 0.03126 Total loss: 1.17544 timestamp: 1654939227.5770814 iteration: 30630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08912 FastRCNN class loss: 0.04084 FastRCNN total loss: 0.12996 L1 loss: 0.0000e+00 L2 loss: 0.80704 Learning rate: 0.02 Mask loss: 0.09967 RPN box loss: 0.07072 RPN score loss: 0.0113 RPN total loss: 0.08202 Total loss: 1.11869 timestamp: 1654939230.8119211 iteration: 30635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10558 FastRCNN class loss: 0.06373 FastRCNN total loss: 0.1693 L1 loss: 0.0000e+00 L2 loss: 0.80694 Learning rate: 0.02 Mask loss: 0.12691 RPN box loss: 0.01212 RPN score loss: 0.00301 RPN total loss: 0.01513 Total loss: 1.11828 timestamp: 1654939233.962576 iteration: 30640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16291 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.26315 L1 loss: 0.0000e+00 L2 loss: 0.80683 Learning rate: 0.02 Mask loss: 0.17089 RPN box loss: 0.04111 RPN score loss: 0.00349 RPN total loss: 0.0446 Total loss: 1.28547 timestamp: 1654939237.2296596 iteration: 30645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19966 FastRCNN class loss: 0.09498 FastRCNN total loss: 0.29464 L1 loss: 0.0000e+00 L2 loss: 0.80672 Learning rate: 0.02 Mask loss: 0.23154 RPN box loss: 0.0438 RPN score loss: 0.00355 RPN total loss: 0.04735 Total loss: 1.38024 timestamp: 1654939240.351683 iteration: 30650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07701 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.13485 L1 loss: 0.0000e+00 L2 loss: 0.80658 Learning rate: 0.02 Mask loss: 0.15026 RPN box loss: 0.06896 RPN score loss: 0.01148 RPN total loss: 0.08045 Total loss: 1.17213 timestamp: 1654939243.5157826 iteration: 30655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07876 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.13861 L1 loss: 0.0000e+00 L2 loss: 0.80645 Learning rate: 0.02 Mask loss: 0.13875 RPN box loss: 0.01893 RPN score loss: 0.00541 RPN total loss: 0.02434 Total loss: 1.10815 timestamp: 1654939246.7025173 iteration: 30660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15982 FastRCNN class loss: 0.12151 FastRCNN total loss: 0.28133 L1 loss: 0.0000e+00 L2 loss: 0.80633 Learning rate: 0.02 Mask loss: 0.17099 RPN box loss: 0.05041 RPN score loss: 0.00776 RPN total loss: 0.05818 Total loss: 1.31682 timestamp: 1654939249.8775043 iteration: 30665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10661 FastRCNN class loss: 0.06395 FastRCNN total loss: 0.17056 L1 loss: 0.0000e+00 L2 loss: 0.80621 Learning rate: 0.02 Mask loss: 0.15007 RPN box loss: 0.00398 RPN score loss: 0.00156 RPN total loss: 0.00554 Total loss: 1.13238 timestamp: 1654939253.1286318 iteration: 30670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10413 FastRCNN class loss: 0.09289 FastRCNN total loss: 0.19702 L1 loss: 0.0000e+00 L2 loss: 0.8061 Learning rate: 0.02 Mask loss: 0.11704 RPN box loss: 0.02444 RPN score loss: 0.00446 RPN total loss: 0.0289 Total loss: 1.14906 timestamp: 1654939256.335063 iteration: 30675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15136 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.21337 L1 loss: 0.0000e+00 L2 loss: 0.806 Learning rate: 0.02 Mask loss: 0.17375 RPN box loss: 0.00499 RPN score loss: 0.00146 RPN total loss: 0.00645 Total loss: 1.19958 timestamp: 1654939259.542922 iteration: 30680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13579 FastRCNN class loss: 0.07953 FastRCNN total loss: 0.21532 L1 loss: 0.0000e+00 L2 loss: 0.80589 Learning rate: 0.02 Mask loss: 0.10072 RPN box loss: 0.02707 RPN score loss: 0.00461 RPN total loss: 0.03168 Total loss: 1.1536 timestamp: 1654939262.680805 iteration: 30685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15045 FastRCNN class loss: 0.09338 FastRCNN total loss: 0.24383 L1 loss: 0.0000e+00 L2 loss: 0.80577 Learning rate: 0.02 Mask loss: 0.20607 RPN box loss: 0.06643 RPN score loss: 0.00415 RPN total loss: 0.07058 Total loss: 1.32626 timestamp: 1654939265.8530858 iteration: 30690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18578 FastRCNN class loss: 0.11084 FastRCNN total loss: 0.29663 L1 loss: 0.0000e+00 L2 loss: 0.80565 Learning rate: 0.02 Mask loss: 0.22979 RPN box loss: 0.02914 RPN score loss: 0.01483 RPN total loss: 0.04397 Total loss: 1.37605 timestamp: 1654939268.9821274 iteration: 30695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16489 FastRCNN class loss: 0.11417 FastRCNN total loss: 0.27906 L1 loss: 0.0000e+00 L2 loss: 0.80555 Learning rate: 0.02 Mask loss: 0.22372 RPN box loss: 0.0455 RPN score loss: 0.008 RPN total loss: 0.0535 Total loss: 1.36183 timestamp: 1654939272.122992 iteration: 30700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20428 FastRCNN class loss: 0.10558 FastRCNN total loss: 0.30986 L1 loss: 0.0000e+00 L2 loss: 0.80542 Learning rate: 0.02 Mask loss: 0.19256 RPN box loss: 0.04071 RPN score loss: 0.00557 RPN total loss: 0.04628 Total loss: 1.35412 timestamp: 1654939275.2443554 iteration: 30705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08981 FastRCNN class loss: 0.05544 FastRCNN total loss: 0.14525 L1 loss: 0.0000e+00 L2 loss: 0.80533 Learning rate: 0.02 Mask loss: 0.08964 RPN box loss: 0.00572 RPN score loss: 0.00461 RPN total loss: 0.01033 Total loss: 1.05055 timestamp: 1654939278.388672 iteration: 30710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08074 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.14011 L1 loss: 0.0000e+00 L2 loss: 0.80524 Learning rate: 0.02 Mask loss: 0.12838 RPN box loss: 0.00646 RPN score loss: 0.00968 RPN total loss: 0.01614 Total loss: 1.08986 timestamp: 1654939281.6870255 iteration: 30715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10429 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.16326 L1 loss: 0.0000e+00 L2 loss: 0.80512 Learning rate: 0.02 Mask loss: 0.10761 RPN box loss: 0.02663 RPN score loss: 0.00252 RPN total loss: 0.02915 Total loss: 1.10514 timestamp: 1654939284.9150405 iteration: 30720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22002 FastRCNN class loss: 0.07802 FastRCNN total loss: 0.29804 L1 loss: 0.0000e+00 L2 loss: 0.80502 Learning rate: 0.02 Mask loss: 0.12807 RPN box loss: 0.04268 RPN score loss: 0.0167 RPN total loss: 0.05938 Total loss: 1.29051 timestamp: 1654939288.0824127 iteration: 30725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08123 FastRCNN class loss: 0.0377 FastRCNN total loss: 0.11893 L1 loss: 0.0000e+00 L2 loss: 0.80489 Learning rate: 0.02 Mask loss: 0.13181 RPN box loss: 0.01789 RPN score loss: 0.00236 RPN total loss: 0.02025 Total loss: 1.07587 timestamp: 1654939291.2291372 iteration: 30730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11886 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.1833 L1 loss: 0.0000e+00 L2 loss: 0.80477 Learning rate: 0.02 Mask loss: 0.13619 RPN box loss: 0.01777 RPN score loss: 0.00277 RPN total loss: 0.02054 Total loss: 1.1448 timestamp: 1654939294.3816214 iteration: 30735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1203 FastRCNN class loss: 0.09294 FastRCNN total loss: 0.21325 L1 loss: 0.0000e+00 L2 loss: 0.80466 Learning rate: 0.02 Mask loss: 0.11817 RPN box loss: 0.02623 RPN score loss: 0.0043 RPN total loss: 0.03053 Total loss: 1.16661 timestamp: 1654939297.6076763 iteration: 30740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0881 FastRCNN class loss: 0.04307 FastRCNN total loss: 0.13116 L1 loss: 0.0000e+00 L2 loss: 0.80455 Learning rate: 0.02 Mask loss: 0.09739 RPN box loss: 0.01019 RPN score loss: 0.00483 RPN total loss: 0.01502 Total loss: 1.04812 timestamp: 1654939300.7942784 iteration: 30745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11044 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.18647 L1 loss: 0.0000e+00 L2 loss: 0.80443 Learning rate: 0.02 Mask loss: 0.15206 RPN box loss: 0.01408 RPN score loss: 0.0052 RPN total loss: 0.01928 Total loss: 1.16224 timestamp: 1654939303.9392827 iteration: 30750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19443 FastRCNN class loss: 0.14206 FastRCNN total loss: 0.33649 L1 loss: 0.0000e+00 L2 loss: 0.80433 Learning rate: 0.02 Mask loss: 0.15854 RPN box loss: 0.04001 RPN score loss: 0.01382 RPN total loss: 0.05383 Total loss: 1.35319 timestamp: 1654939307.1499314 iteration: 30755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10101 FastRCNN class loss: 0.09955 FastRCNN total loss: 0.20055 L1 loss: 0.0000e+00 L2 loss: 0.8042 Learning rate: 0.02 Mask loss: 0.13825 RPN box loss: 0.02849 RPN score loss: 0.00586 RPN total loss: 0.03435 Total loss: 1.17736 timestamp: 1654939310.400715 iteration: 30760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14339 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.22795 L1 loss: 0.0000e+00 L2 loss: 0.80409 Learning rate: 0.02 Mask loss: 0.15407 RPN box loss: 0.02423 RPN score loss: 0.00431 RPN total loss: 0.02854 Total loss: 1.21465 timestamp: 1654939313.511072 iteration: 30765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20077 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.29071 L1 loss: 0.0000e+00 L2 loss: 0.80397 Learning rate: 0.02 Mask loss: 0.19054 RPN box loss: 0.03335 RPN score loss: 0.00784 RPN total loss: 0.04119 Total loss: 1.32642 timestamp: 1654939316.7203186 iteration: 30770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18217 FastRCNN class loss: 0.09211 FastRCNN total loss: 0.27428 L1 loss: 0.0000e+00 L2 loss: 0.80384 Learning rate: 0.02 Mask loss: 0.15231 RPN box loss: 0.0409 RPN score loss: 0.00459 RPN total loss: 0.04549 Total loss: 1.27593 timestamp: 1654939319.9545934 iteration: 30775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0873 FastRCNN class loss: 0.07767 FastRCNN total loss: 0.16497 L1 loss: 0.0000e+00 L2 loss: 0.80376 Learning rate: 0.02 Mask loss: 0.11807 RPN box loss: 0.03272 RPN score loss: 0.00309 RPN total loss: 0.03582 Total loss: 1.12261 timestamp: 1654939323.169222 iteration: 30780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05172 FastRCNN class loss: 0.03874 FastRCNN total loss: 0.09046 L1 loss: 0.0000e+00 L2 loss: 0.80364 Learning rate: 0.02 Mask loss: 0.21151 RPN box loss: 0.01612 RPN score loss: 0.00457 RPN total loss: 0.02069 Total loss: 1.1263 timestamp: 1654939326.3419995 iteration: 30785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11918 FastRCNN class loss: 0.0708 FastRCNN total loss: 0.18998 L1 loss: 0.0000e+00 L2 loss: 0.80351 Learning rate: 0.02 Mask loss: 0.15423 RPN box loss: 0.03569 RPN score loss: 0.01213 RPN total loss: 0.04783 Total loss: 1.19555 timestamp: 1654939329.5321074 iteration: 30790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12659 FastRCNN class loss: 0.09491 FastRCNN total loss: 0.22151 L1 loss: 0.0000e+00 L2 loss: 0.8034 Learning rate: 0.02 Mask loss: 0.12447 RPN box loss: 0.02421 RPN score loss: 0.00593 RPN total loss: 0.03014 Total loss: 1.17952 timestamp: 1654939332.7032528 iteration: 30795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06945 FastRCNN class loss: 0.08098 FastRCNN total loss: 0.15043 L1 loss: 0.0000e+00 L2 loss: 0.80329 Learning rate: 0.02 Mask loss: 0.16614 RPN box loss: 0.02343 RPN score loss: 0.00495 RPN total loss: 0.02837 Total loss: 1.14823 timestamp: 1654939335.911069 iteration: 30800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19059 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.26002 L1 loss: 0.0000e+00 L2 loss: 0.80315 Learning rate: 0.02 Mask loss: 0.13298 RPN box loss: 0.03373 RPN score loss: 0.00307 RPN total loss: 0.0368 Total loss: 1.23295 timestamp: 1654939339.1557527 iteration: 30805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14728 FastRCNN class loss: 0.08838 FastRCNN total loss: 0.23566 L1 loss: 0.0000e+00 L2 loss: 0.80305 Learning rate: 0.02 Mask loss: 0.14332 RPN box loss: 0.04093 RPN score loss: 0.00438 RPN total loss: 0.04532 Total loss: 1.22735 timestamp: 1654939342.359456 iteration: 30810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07639 FastRCNN class loss: 0.04178 FastRCNN total loss: 0.11816 L1 loss: 0.0000e+00 L2 loss: 0.80292 Learning rate: 0.02 Mask loss: 0.14524 RPN box loss: 0.00417 RPN score loss: 0.00359 RPN total loss: 0.00776 Total loss: 1.07408 timestamp: 1654939345.5824592 iteration: 30815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1379 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.21593 L1 loss: 0.0000e+00 L2 loss: 0.8028 Learning rate: 0.02 Mask loss: 0.18289 RPN box loss: 0.03545 RPN score loss: 0.0081 RPN total loss: 0.04355 Total loss: 1.24518 timestamp: 1654939348.7538266 iteration: 30820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17446 FastRCNN class loss: 0.10355 FastRCNN total loss: 0.27801 L1 loss: 0.0000e+00 L2 loss: 0.80269 Learning rate: 0.02 Mask loss: 0.17583 RPN box loss: 0.01104 RPN score loss: 0.00936 RPN total loss: 0.0204 Total loss: 1.27693 timestamp: 1654939351.8310559 iteration: 30825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19964 FastRCNN class loss: 0.10052 FastRCNN total loss: 0.30016 L1 loss: 0.0000e+00 L2 loss: 0.80258 Learning rate: 0.02 Mask loss: 0.17853 RPN box loss: 0.03921 RPN score loss: 0.00991 RPN total loss: 0.04912 Total loss: 1.33039 timestamp: 1654939355.028032 iteration: 30830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14589 FastRCNN class loss: 0.10739 FastRCNN total loss: 0.25328 L1 loss: 0.0000e+00 L2 loss: 0.80244 Learning rate: 0.02 Mask loss: 0.16368 RPN box loss: 0.01055 RPN score loss: 0.00581 RPN total loss: 0.01636 Total loss: 1.23576 timestamp: 1654939358.1923814 iteration: 30835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06694 FastRCNN class loss: 0.083 FastRCNN total loss: 0.14994 L1 loss: 0.0000e+00 L2 loss: 0.80232 Learning rate: 0.02 Mask loss: 0.10572 RPN box loss: 0.01564 RPN score loss: 0.00924 RPN total loss: 0.02487 Total loss: 1.08286 timestamp: 1654939361.3499165 iteration: 30840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09862 FastRCNN class loss: 0.07429 FastRCNN total loss: 0.17292 L1 loss: 0.0000e+00 L2 loss: 0.8022 Learning rate: 0.02 Mask loss: 0.13048 RPN box loss: 0.02425 RPN score loss: 0.00667 RPN total loss: 0.03092 Total loss: 1.13652 timestamp: 1654939364.4934201 iteration: 30845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.08282 FastRCNN total loss: 0.16813 L1 loss: 0.0000e+00 L2 loss: 0.8021 Learning rate: 0.02 Mask loss: 0.11231 RPN box loss: 0.01692 RPN score loss: 0.00312 RPN total loss: 0.02004 Total loss: 1.10258 timestamp: 1654939367.6628191 iteration: 30850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05916 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.12971 L1 loss: 0.0000e+00 L2 loss: 0.80198 Learning rate: 0.02 Mask loss: 0.1093 RPN box loss: 0.03437 RPN score loss: 0.00358 RPN total loss: 0.03795 Total loss: 1.07894 timestamp: 1654939370.8994439 iteration: 30855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11338 FastRCNN class loss: 0.07868 FastRCNN total loss: 0.19205 L1 loss: 0.0000e+00 L2 loss: 0.80187 Learning rate: 0.02 Mask loss: 0.12714 RPN box loss: 0.02027 RPN score loss: 0.0045 RPN total loss: 0.02477 Total loss: 1.14583 timestamp: 1654939374.0333583 iteration: 30860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09998 FastRCNN class loss: 0.10095 FastRCNN total loss: 0.20093 L1 loss: 0.0000e+00 L2 loss: 0.80176 Learning rate: 0.02 Mask loss: 0.12306 RPN box loss: 0.01579 RPN score loss: 0.00953 RPN total loss: 0.02533 Total loss: 1.15107 timestamp: 1654939377.1721625 iteration: 30865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12616 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.19705 L1 loss: 0.0000e+00 L2 loss: 0.80165 Learning rate: 0.02 Mask loss: 0.15826 RPN box loss: 0.01884 RPN score loss: 0.00356 RPN total loss: 0.0224 Total loss: 1.17937 timestamp: 1654939380.4564295 iteration: 30870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18214 FastRCNN class loss: 0.10273 FastRCNN total loss: 0.28487 L1 loss: 0.0000e+00 L2 loss: 0.80155 Learning rate: 0.02 Mask loss: 0.19702 RPN box loss: 0.0597 RPN score loss: 0.0125 RPN total loss: 0.0722 Total loss: 1.35564 timestamp: 1654939383.6981473 iteration: 30875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16859 FastRCNN class loss: 0.10342 FastRCNN total loss: 0.27202 L1 loss: 0.0000e+00 L2 loss: 0.80145 Learning rate: 0.02 Mask loss: 0.16642 RPN box loss: 0.09222 RPN score loss: 0.01331 RPN total loss: 0.10553 Total loss: 1.34541 timestamp: 1654939386.870284 iteration: 30880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.08995 FastRCNN total loss: 0.25239 L1 loss: 0.0000e+00 L2 loss: 0.8013 Learning rate: 0.02 Mask loss: 0.26127 RPN box loss: 0.04677 RPN score loss: 0.01135 RPN total loss: 0.05812 Total loss: 1.37307 timestamp: 1654939390.0525153 iteration: 30885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15148 FastRCNN class loss: 0.0909 FastRCNN total loss: 0.24239 L1 loss: 0.0000e+00 L2 loss: 0.80117 Learning rate: 0.02 Mask loss: 0.13972 RPN box loss: 0.02046 RPN score loss: 0.00786 RPN total loss: 0.02832 Total loss: 1.2116 timestamp: 1654939393.18424 iteration: 30890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13224 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.19442 L1 loss: 0.0000e+00 L2 loss: 0.80106 Learning rate: 0.02 Mask loss: 0.18502 RPN box loss: 0.03547 RPN score loss: 0.01014 RPN total loss: 0.04561 Total loss: 1.22611 timestamp: 1654939396.3836958 iteration: 30895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08452 FastRCNN class loss: 0.04968 FastRCNN total loss: 0.1342 L1 loss: 0.0000e+00 L2 loss: 0.80097 Learning rate: 0.02 Mask loss: 0.09403 RPN box loss: 0.03035 RPN score loss: 0.00539 RPN total loss: 0.03574 Total loss: 1.06494 timestamp: 1654939399.6023405 iteration: 30900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08876 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.16391 L1 loss: 0.0000e+00 L2 loss: 0.80086 Learning rate: 0.02 Mask loss: 0.19013 RPN box loss: 0.03029 RPN score loss: 0.02599 RPN total loss: 0.05628 Total loss: 1.21118 timestamp: 1654939402.7615156 iteration: 30905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13378 FastRCNN class loss: 0.0463 FastRCNN total loss: 0.18008 L1 loss: 0.0000e+00 L2 loss: 0.80074 Learning rate: 0.02 Mask loss: 0.09313 RPN box loss: 0.00954 RPN score loss: 0.00502 RPN total loss: 0.01456 Total loss: 1.08852 timestamp: 1654939405.9693358 iteration: 30910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.0801 FastRCNN total loss: 0.21286 L1 loss: 0.0000e+00 L2 loss: 0.80063 Learning rate: 0.02 Mask loss: 0.20757 RPN box loss: 0.04033 RPN score loss: 0.0209 RPN total loss: 0.06123 Total loss: 1.28228 timestamp: 1654939409.2125065 iteration: 30915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11408 FastRCNN class loss: 0.07283 FastRCNN total loss: 0.18692 L1 loss: 0.0000e+00 L2 loss: 0.80051 Learning rate: 0.02 Mask loss: 0.10973 RPN box loss: 0.05731 RPN score loss: 0.01165 RPN total loss: 0.06896 Total loss: 1.16611 timestamp: 1654939412.410191 iteration: 30920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0674 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.12981 L1 loss: 0.0000e+00 L2 loss: 0.8004 Learning rate: 0.02 Mask loss: 0.09526 RPN box loss: 0.01579 RPN score loss: 0.00705 RPN total loss: 0.02284 Total loss: 1.04832 timestamp: 1654939415.586413 iteration: 30925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09655 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.14689 L1 loss: 0.0000e+00 L2 loss: 0.8003 Learning rate: 0.02 Mask loss: 0.11938 RPN box loss: 0.01173 RPN score loss: 0.00443 RPN total loss: 0.01615 Total loss: 1.08272 timestamp: 1654939418.8371189 iteration: 30930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12218 FastRCNN class loss: 0.05716 FastRCNN total loss: 0.17934 L1 loss: 0.0000e+00 L2 loss: 0.80019 Learning rate: 0.02 Mask loss: 0.12156 RPN box loss: 0.04124 RPN score loss: 0.00674 RPN total loss: 0.04798 Total loss: 1.14907 timestamp: 1654939422.0191388 iteration: 30935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21006 FastRCNN class loss: 0.102 FastRCNN total loss: 0.31206 L1 loss: 0.0000e+00 L2 loss: 0.80006 Learning rate: 0.02 Mask loss: 0.19398 RPN box loss: 0.02316 RPN score loss: 0.01304 RPN total loss: 0.0362 Total loss: 1.34231 timestamp: 1654939425.2304804 iteration: 30940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14918 FastRCNN class loss: 0.08374 FastRCNN total loss: 0.23291 L1 loss: 0.0000e+00 L2 loss: 0.79993 Learning rate: 0.02 Mask loss: 0.12974 RPN box loss: 0.01374 RPN score loss: 0.00578 RPN total loss: 0.01952 Total loss: 1.1821 timestamp: 1654939428.4746046 iteration: 30945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14863 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.20651 L1 loss: 0.0000e+00 L2 loss: 0.7998 Learning rate: 0.02 Mask loss: 0.15409 RPN box loss: 0.01952 RPN score loss: 0.00418 RPN total loss: 0.0237 Total loss: 1.1841 timestamp: 1654939431.6616235 iteration: 30950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13709 FastRCNN class loss: 0.11592 FastRCNN total loss: 0.25301 L1 loss: 0.0000e+00 L2 loss: 0.79969 Learning rate: 0.02 Mask loss: 0.17514 RPN box loss: 0.0369 RPN score loss: 0.01316 RPN total loss: 0.05006 Total loss: 1.27791 timestamp: 1654939434.8951285 iteration: 30955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13001 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.20528 L1 loss: 0.0000e+00 L2 loss: 0.7996 Learning rate: 0.02 Mask loss: 0.10567 RPN box loss: 0.02623 RPN score loss: 0.0129 RPN total loss: 0.03913 Total loss: 1.14967 timestamp: 1654939438.0946305 iteration: 30960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20054 FastRCNN class loss: 0.11678 FastRCNN total loss: 0.31732 L1 loss: 0.0000e+00 L2 loss: 0.79948 Learning rate: 0.02 Mask loss: 0.15928 RPN box loss: 0.02304 RPN score loss: 0.01044 RPN total loss: 0.03348 Total loss: 1.30956 timestamp: 1654939441.2263322 iteration: 30965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14417 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.2167 L1 loss: 0.0000e+00 L2 loss: 0.79937 Learning rate: 0.02 Mask loss: 0.17856 RPN box loss: 0.05294 RPN score loss: 0.01068 RPN total loss: 0.06362 Total loss: 1.25825 timestamp: 1654939444.434435 iteration: 30970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14956 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.23931 L1 loss: 0.0000e+00 L2 loss: 0.79926 Learning rate: 0.02 Mask loss: 0.15853 RPN box loss: 0.04219 RPN score loss: 0.00806 RPN total loss: 0.05024 Total loss: 1.24735 timestamp: 1654939447.6808681 iteration: 30975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11114 FastRCNN class loss: 0.08241 FastRCNN total loss: 0.19355 L1 loss: 0.0000e+00 L2 loss: 0.79914 Learning rate: 0.02 Mask loss: 0.13425 RPN box loss: 0.02719 RPN score loss: 0.00493 RPN total loss: 0.03212 Total loss: 1.15906 timestamp: 1654939450.883092 iteration: 30980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12635 FastRCNN class loss: 0.08549 FastRCNN total loss: 0.21185 L1 loss: 0.0000e+00 L2 loss: 0.79901 Learning rate: 0.02 Mask loss: 0.12667 RPN box loss: 0.03313 RPN score loss: 0.00419 RPN total loss: 0.03731 Total loss: 1.17484 timestamp: 1654939454.1597362 iteration: 30985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05341 FastRCNN class loss: 0.05173 FastRCNN total loss: 0.10513 L1 loss: 0.0000e+00 L2 loss: 0.79887 Learning rate: 0.02 Mask loss: 0.24082 RPN box loss: 0.00362 RPN score loss: 0.00638 RPN total loss: 0.01 Total loss: 1.15482 timestamp: 1654939457.3131814 iteration: 30990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09747 FastRCNN class loss: 0.08835 FastRCNN total loss: 0.18582 L1 loss: 0.0000e+00 L2 loss: 0.79878 Learning rate: 0.02 Mask loss: 0.14742 RPN box loss: 0.04558 RPN score loss: 0.00333 RPN total loss: 0.04891 Total loss: 1.18093 timestamp: 1654939460.533321 iteration: 30995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15686 FastRCNN class loss: 0.10133 FastRCNN total loss: 0.25819 L1 loss: 0.0000e+00 L2 loss: 0.79865 Learning rate: 0.02 Mask loss: 0.15853 RPN box loss: 0.06084 RPN score loss: 0.01056 RPN total loss: 0.07139 Total loss: 1.28676 timestamp: 1654939463.7632573 iteration: 31000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16368 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.21246 L1 loss: 0.0000e+00 L2 loss: 0.79853 Learning rate: 0.02 Mask loss: 0.10824 RPN box loss: 0.04072 RPN score loss: 0.00613 RPN total loss: 0.04685 Total loss: 1.16607 timestamp: 1654939466.9803188 iteration: 31005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10113 FastRCNN class loss: 0.04782 FastRCNN total loss: 0.14895 L1 loss: 0.0000e+00 L2 loss: 0.79843 Learning rate: 0.02 Mask loss: 0.14038 RPN box loss: 0.06214 RPN score loss: 0.0045 RPN total loss: 0.06663 Total loss: 1.15439 timestamp: 1654939470.1626909 iteration: 31010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16795 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.2336 L1 loss: 0.0000e+00 L2 loss: 0.7983 Learning rate: 0.02 Mask loss: 0.13928 RPN box loss: 0.05537 RPN score loss: 0.00402 RPN total loss: 0.05939 Total loss: 1.23056 timestamp: 1654939473.3716998 iteration: 31015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06717 FastRCNN class loss: 0.0508 FastRCNN total loss: 0.11797 L1 loss: 0.0000e+00 L2 loss: 0.79817 Learning rate: 0.02 Mask loss: 0.13757 RPN box loss: 0.01114 RPN score loss: 0.00471 RPN total loss: 0.01585 Total loss: 1.06956 timestamp: 1654939476.6445901 iteration: 31020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17235 FastRCNN class loss: 0.12807 FastRCNN total loss: 0.30042 L1 loss: 0.0000e+00 L2 loss: 0.79808 Learning rate: 0.02 Mask loss: 0.2576 RPN box loss: 0.03502 RPN score loss: 0.01405 RPN total loss: 0.04908 Total loss: 1.40517 timestamp: 1654939479.9170856 iteration: 31025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12303 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.19809 L1 loss: 0.0000e+00 L2 loss: 0.79799 Learning rate: 0.02 Mask loss: 0.10362 RPN box loss: 0.025 RPN score loss: 0.00473 RPN total loss: 0.02972 Total loss: 1.12942 timestamp: 1654939483.1160142 iteration: 31030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10403 FastRCNN class loss: 0.08623 FastRCNN total loss: 0.19026 L1 loss: 0.0000e+00 L2 loss: 0.79787 Learning rate: 0.02 Mask loss: 0.16877 RPN box loss: 0.07083 RPN score loss: 0.0104 RPN total loss: 0.08123 Total loss: 1.23813 timestamp: 1654939486.324041 iteration: 31035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10467 FastRCNN class loss: 0.10433 FastRCNN total loss: 0.209 L1 loss: 0.0000e+00 L2 loss: 0.79774 Learning rate: 0.02 Mask loss: 0.13815 RPN box loss: 0.04378 RPN score loss: 0.00617 RPN total loss: 0.04995 Total loss: 1.19484 timestamp: 1654939489.4784808 iteration: 31040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22444 FastRCNN class loss: 0.09525 FastRCNN total loss: 0.31968 L1 loss: 0.0000e+00 L2 loss: 0.79765 Learning rate: 0.02 Mask loss: 0.18202 RPN box loss: 0.03649 RPN score loss: 0.00904 RPN total loss: 0.04553 Total loss: 1.34489 timestamp: 1654939492.7434175 iteration: 31045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1337 FastRCNN class loss: 0.06354 FastRCNN total loss: 0.19724 L1 loss: 0.0000e+00 L2 loss: 0.79754 Learning rate: 0.02 Mask loss: 0.11959 RPN box loss: 0.0336 RPN score loss: 0.00418 RPN total loss: 0.03779 Total loss: 1.15215 timestamp: 1654939495.8686192 iteration: 31050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07915 FastRCNN class loss: 0.07454 FastRCNN total loss: 0.15369 L1 loss: 0.0000e+00 L2 loss: 0.79742 Learning rate: 0.02 Mask loss: 0.15829 RPN box loss: 0.0394 RPN score loss: 0.00503 RPN total loss: 0.04443 Total loss: 1.15384 timestamp: 1654939499.057087 iteration: 31055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13964 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.19818 L1 loss: 0.0000e+00 L2 loss: 0.79732 Learning rate: 0.02 Mask loss: 0.10649 RPN box loss: 0.01816 RPN score loss: 0.00431 RPN total loss: 0.02247 Total loss: 1.12447 timestamp: 1654939502.229033 iteration: 31060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14914 FastRCNN class loss: 0.08477 FastRCNN total loss: 0.23391 L1 loss: 0.0000e+00 L2 loss: 0.79719 Learning rate: 0.02 Mask loss: 0.12172 RPN box loss: 0.01498 RPN score loss: 0.00634 RPN total loss: 0.02133 Total loss: 1.17415 timestamp: 1654939505.4083502 iteration: 31065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11666 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.17537 L1 loss: 0.0000e+00 L2 loss: 0.79708 Learning rate: 0.02 Mask loss: 0.12994 RPN box loss: 0.04015 RPN score loss: 0.00325 RPN total loss: 0.0434 Total loss: 1.14579 timestamp: 1654939508.6408756 iteration: 31070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1449 FastRCNN class loss: 0.1099 FastRCNN total loss: 0.2548 L1 loss: 0.0000e+00 L2 loss: 0.79698 Learning rate: 0.02 Mask loss: 0.1665 RPN box loss: 0.02786 RPN score loss: 0.00617 RPN total loss: 0.03403 Total loss: 1.25231 timestamp: 1654939511.8468912 iteration: 31075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12819 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.18701 L1 loss: 0.0000e+00 L2 loss: 0.79686 Learning rate: 0.02 Mask loss: 0.15124 RPN box loss: 0.01874 RPN score loss: 0.00348 RPN total loss: 0.02222 Total loss: 1.15732 timestamp: 1654939515.0782402 iteration: 31080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12385 FastRCNN class loss: 0.04525 FastRCNN total loss: 0.16909 L1 loss: 0.0000e+00 L2 loss: 0.79676 Learning rate: 0.02 Mask loss: 0.13528 RPN box loss: 0.01509 RPN score loss: 0.00696 RPN total loss: 0.02206 Total loss: 1.12319 timestamp: 1654939518.3880548 iteration: 31085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15385 FastRCNN class loss: 0.09612 FastRCNN total loss: 0.24997 L1 loss: 0.0000e+00 L2 loss: 0.79663 Learning rate: 0.02 Mask loss: 0.18294 RPN box loss: 0.00726 RPN score loss: 0.0064 RPN total loss: 0.01366 Total loss: 1.2432 timestamp: 1654939521.5963688 iteration: 31090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.09284 FastRCNN total loss: 0.24454 L1 loss: 0.0000e+00 L2 loss: 0.79651 Learning rate: 0.02 Mask loss: 0.16222 RPN box loss: 0.02442 RPN score loss: 0.00601 RPN total loss: 0.03042 Total loss: 1.2337 timestamp: 1654939524.7709246 iteration: 31095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12934 FastRCNN class loss: 0.08181 FastRCNN total loss: 0.21115 L1 loss: 0.0000e+00 L2 loss: 0.79641 Learning rate: 0.02 Mask loss: 0.18789 RPN box loss: 0.05 RPN score loss: 0.00498 RPN total loss: 0.05498 Total loss: 1.25043 timestamp: 1654939527.96033 iteration: 31100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11432 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.17989 L1 loss: 0.0000e+00 L2 loss: 0.79629 Learning rate: 0.02 Mask loss: 0.22316 RPN box loss: 0.10367 RPN score loss: 0.00995 RPN total loss: 0.11362 Total loss: 1.31296 timestamp: 1654939531.1388912 iteration: 31105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07717 FastRCNN class loss: 0.05161 FastRCNN total loss: 0.12878 L1 loss: 0.0000e+00 L2 loss: 0.79618 Learning rate: 0.02 Mask loss: 0.15996 RPN box loss: 0.03357 RPN score loss: 0.00304 RPN total loss: 0.03661 Total loss: 1.12154 timestamp: 1654939534.2951155 iteration: 31110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20132 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.28709 L1 loss: 0.0000e+00 L2 loss: 0.79607 Learning rate: 0.02 Mask loss: 0.18148 RPN box loss: 0.0292 RPN score loss: 0.00999 RPN total loss: 0.03919 Total loss: 1.30383 timestamp: 1654939537.505808 iteration: 31115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16058 FastRCNN class loss: 0.08971 FastRCNN total loss: 0.25029 L1 loss: 0.0000e+00 L2 loss: 0.79593 Learning rate: 0.02 Mask loss: 0.14682 RPN box loss: 0.04177 RPN score loss: 0.00785 RPN total loss: 0.04962 Total loss: 1.24265 timestamp: 1654939540.747919 iteration: 31120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13249 FastRCNN class loss: 0.08324 FastRCNN total loss: 0.21573 L1 loss: 0.0000e+00 L2 loss: 0.79582 Learning rate: 0.02 Mask loss: 0.106 RPN box loss: 0.04676 RPN score loss: 0.00384 RPN total loss: 0.05061 Total loss: 1.16816 timestamp: 1654939543.9282575 iteration: 31125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10997 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.18059 L1 loss: 0.0000e+00 L2 loss: 0.79574 Learning rate: 0.02 Mask loss: 0.14731 RPN box loss: 0.07252 RPN score loss: 0.01029 RPN total loss: 0.08281 Total loss: 1.20645 timestamp: 1654939547.0813923 iteration: 31130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15388 FastRCNN class loss: 0.03936 FastRCNN total loss: 0.19324 L1 loss: 0.0000e+00 L2 loss: 0.79563 Learning rate: 0.02 Mask loss: 0.09762 RPN box loss: 0.00597 RPN score loss: 0.00245 RPN total loss: 0.00842 Total loss: 1.09489 timestamp: 1654939550.307106 iteration: 31135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13455 FastRCNN class loss: 0.06298 FastRCNN total loss: 0.19753 L1 loss: 0.0000e+00 L2 loss: 0.79552 Learning rate: 0.02 Mask loss: 0.13719 RPN box loss: 0.02093 RPN score loss: 0.00239 RPN total loss: 0.02332 Total loss: 1.15355 timestamp: 1654939553.5041025 iteration: 31140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.0474 FastRCNN total loss: 0.13056 L1 loss: 0.0000e+00 L2 loss: 0.79538 Learning rate: 0.02 Mask loss: 0.11506 RPN box loss: 0.00721 RPN score loss: 0.00226 RPN total loss: 0.00947 Total loss: 1.05046 timestamp: 1654939556.726151 iteration: 31145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1179 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.20154 L1 loss: 0.0000e+00 L2 loss: 0.79528 Learning rate: 0.02 Mask loss: 0.10022 RPN box loss: 0.03363 RPN score loss: 0.00442 RPN total loss: 0.03805 Total loss: 1.13508 timestamp: 1654939559.8799665 iteration: 31150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17811 FastRCNN class loss: 0.12132 FastRCNN total loss: 0.29943 L1 loss: 0.0000e+00 L2 loss: 0.79516 Learning rate: 0.02 Mask loss: 0.19725 RPN box loss: 0.01903 RPN score loss: 0.00411 RPN total loss: 0.02314 Total loss: 1.31498 timestamp: 1654939563.059085 iteration: 31155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16266 FastRCNN class loss: 0.06518 FastRCNN total loss: 0.22784 L1 loss: 0.0000e+00 L2 loss: 0.79505 Learning rate: 0.02 Mask loss: 0.14951 RPN box loss: 0.01636 RPN score loss: 0.00737 RPN total loss: 0.02373 Total loss: 1.19613 timestamp: 1654939566.2867846 iteration: 31160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14281 FastRCNN class loss: 0.05149 FastRCNN total loss: 0.1943 L1 loss: 0.0000e+00 L2 loss: 0.79495 Learning rate: 0.02 Mask loss: 0.10418 RPN box loss: 0.0258 RPN score loss: 0.00269 RPN total loss: 0.02849 Total loss: 1.12191 timestamp: 1654939569.4377608 iteration: 31165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1853 FastRCNN class loss: 0.07238 FastRCNN total loss: 0.25768 L1 loss: 0.0000e+00 L2 loss: 0.79484 Learning rate: 0.02 Mask loss: 0.15364 RPN box loss: 0.01974 RPN score loss: 0.00454 RPN total loss: 0.02428 Total loss: 1.23044 timestamp: 1654939572.5959275 iteration: 31170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13482 FastRCNN class loss: 0.07669 FastRCNN total loss: 0.21151 L1 loss: 0.0000e+00 L2 loss: 0.79475 Learning rate: 0.02 Mask loss: 0.14601 RPN box loss: 0.02158 RPN score loss: 0.00701 RPN total loss: 0.02858 Total loss: 1.18084 timestamp: 1654939575.7556436 iteration: 31175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19073 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.26915 L1 loss: 0.0000e+00 L2 loss: 0.79464 Learning rate: 0.02 Mask loss: 0.12094 RPN box loss: 0.02977 RPN score loss: 0.01574 RPN total loss: 0.04551 Total loss: 1.23024 timestamp: 1654939578.915293 iteration: 31180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12972 FastRCNN class loss: 0.09823 FastRCNN total loss: 0.22795 L1 loss: 0.0000e+00 L2 loss: 0.79451 Learning rate: 0.02 Mask loss: 0.16725 RPN box loss: 0.05653 RPN score loss: 0.01086 RPN total loss: 0.06739 Total loss: 1.2571 timestamp: 1654939582.0232983 iteration: 31185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11311 FastRCNN class loss: 0.10572 FastRCNN total loss: 0.21882 L1 loss: 0.0000e+00 L2 loss: 0.7944 Learning rate: 0.02 Mask loss: 0.16563 RPN box loss: 0.02159 RPN score loss: 0.00485 RPN total loss: 0.02644 Total loss: 1.2053 timestamp: 1654939585.2843566 iteration: 31190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1595 FastRCNN class loss: 0.09202 FastRCNN total loss: 0.25153 L1 loss: 0.0000e+00 L2 loss: 0.79428 Learning rate: 0.02 Mask loss: 0.1189 RPN box loss: 0.02895 RPN score loss: 0.00592 RPN total loss: 0.03487 Total loss: 1.19958 timestamp: 1654939588.474431 iteration: 31195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.154 FastRCNN class loss: 0.08279 FastRCNN total loss: 0.23679 L1 loss: 0.0000e+00 L2 loss: 0.79418 Learning rate: 0.02 Mask loss: 0.1853 RPN box loss: 0.04686 RPN score loss: 0.0069 RPN total loss: 0.05376 Total loss: 1.27003 timestamp: 1654939591.6706126 iteration: 31200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10437 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.17493 L1 loss: 0.0000e+00 L2 loss: 0.79406 Learning rate: 0.02 Mask loss: 0.11357 RPN box loss: 0.01394 RPN score loss: 0.00284 RPN total loss: 0.01678 Total loss: 1.09934 timestamp: 1654939594.8784926 iteration: 31205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.09363 FastRCNN total loss: 0.20514 L1 loss: 0.0000e+00 L2 loss: 0.79394 Learning rate: 0.02 Mask loss: 0.20847 RPN box loss: 0.03964 RPN score loss: 0.01215 RPN total loss: 0.05179 Total loss: 1.25935 timestamp: 1654939598.0545282 iteration: 31210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05987 FastRCNN class loss: 0.04341 FastRCNN total loss: 0.10328 L1 loss: 0.0000e+00 L2 loss: 0.79382 Learning rate: 0.02 Mask loss: 0.11625 RPN box loss: 0.04719 RPN score loss: 0.00602 RPN total loss: 0.05321 Total loss: 1.06655 timestamp: 1654939601.2263763 iteration: 31215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09738 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.17791 L1 loss: 0.0000e+00 L2 loss: 0.79369 Learning rate: 0.02 Mask loss: 0.17338 RPN box loss: 0.0214 RPN score loss: 0.00204 RPN total loss: 0.02344 Total loss: 1.16842 timestamp: 1654939604.373038 iteration: 31220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13545 FastRCNN class loss: 0.08499 FastRCNN total loss: 0.22044 L1 loss: 0.0000e+00 L2 loss: 0.79359 Learning rate: 0.02 Mask loss: 0.15926 RPN box loss: 0.03081 RPN score loss: 0.00639 RPN total loss: 0.03719 Total loss: 1.21048 timestamp: 1654939607.6452618 iteration: 31225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11991 FastRCNN class loss: 0.05976 FastRCNN total loss: 0.17966 L1 loss: 0.0000e+00 L2 loss: 0.79346 Learning rate: 0.02 Mask loss: 0.12599 RPN box loss: 0.00865 RPN score loss: 0.00202 RPN total loss: 0.01068 Total loss: 1.10979 timestamp: 1654939610.8562522 iteration: 31230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15729 FastRCNN class loss: 0.07559 FastRCNN total loss: 0.23288 L1 loss: 0.0000e+00 L2 loss: 0.79339 Learning rate: 0.02 Mask loss: 0.14699 RPN box loss: 0.02017 RPN score loss: 0.00371 RPN total loss: 0.02387 Total loss: 1.19713 timestamp: 1654939614.0891402 iteration: 31235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17207 FastRCNN class loss: 0.1135 FastRCNN total loss: 0.28557 L1 loss: 0.0000e+00 L2 loss: 0.79328 Learning rate: 0.02 Mask loss: 0.20936 RPN box loss: 0.03222 RPN score loss: 0.00635 RPN total loss: 0.03857 Total loss: 1.32678 timestamp: 1654939617.2384586 iteration: 31240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17175 FastRCNN class loss: 0.0975 FastRCNN total loss: 0.26926 L1 loss: 0.0000e+00 L2 loss: 0.79315 Learning rate: 0.02 Mask loss: 0.21403 RPN box loss: 0.02513 RPN score loss: 0.01669 RPN total loss: 0.04182 Total loss: 1.31826 timestamp: 1654939620.3717878 iteration: 31245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15039 FastRCNN class loss: 0.07238 FastRCNN total loss: 0.22277 L1 loss: 0.0000e+00 L2 loss: 0.79303 Learning rate: 0.02 Mask loss: 0.1107 RPN box loss: 0.06607 RPN score loss: 0.00447 RPN total loss: 0.07054 Total loss: 1.19704 timestamp: 1654939623.567425 iteration: 31250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1085 FastRCNN class loss: 0.06191 FastRCNN total loss: 0.17041 L1 loss: 0.0000e+00 L2 loss: 0.79292 Learning rate: 0.02 Mask loss: 0.13602 RPN box loss: 0.01917 RPN score loss: 0.00138 RPN total loss: 0.02055 Total loss: 1.1199 timestamp: 1654939626.7362401 iteration: 31255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.134 FastRCNN class loss: 0.07538 FastRCNN total loss: 0.20938 L1 loss: 0.0000e+00 L2 loss: 0.79279 Learning rate: 0.02 Mask loss: 0.14473 RPN box loss: 0.03744 RPN score loss: 0.01394 RPN total loss: 0.05138 Total loss: 1.19829 timestamp: 1654939629.8434544 iteration: 31260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18524 FastRCNN class loss: 0.08325 FastRCNN total loss: 0.26849 L1 loss: 0.0000e+00 L2 loss: 0.79267 Learning rate: 0.02 Mask loss: 0.17744 RPN box loss: 0.00992 RPN score loss: 0.00393 RPN total loss: 0.01385 Total loss: 1.25245 timestamp: 1654939632.9999676 iteration: 31265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15283 FastRCNN class loss: 0.09503 FastRCNN total loss: 0.24786 L1 loss: 0.0000e+00 L2 loss: 0.79256 Learning rate: 0.02 Mask loss: 0.14983 RPN box loss: 0.04119 RPN score loss: 0.00282 RPN total loss: 0.04401 Total loss: 1.23425 timestamp: 1654939636.2397628 iteration: 31270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0646 FastRCNN class loss: 0.05185 FastRCNN total loss: 0.11645 L1 loss: 0.0000e+00 L2 loss: 0.79248 Learning rate: 0.02 Mask loss: 0.09094 RPN box loss: 0.00802 RPN score loss: 0.00259 RPN total loss: 0.01061 Total loss: 1.01048 timestamp: 1654939639.4156764 iteration: 31275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12164 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.2084 L1 loss: 0.0000e+00 L2 loss: 0.79237 Learning rate: 0.02 Mask loss: 0.10835 RPN box loss: 0.01709 RPN score loss: 0.00481 RPN total loss: 0.0219 Total loss: 1.13102 timestamp: 1654939642.59115 iteration: 31280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14783 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.22127 L1 loss: 0.0000e+00 L2 loss: 0.79226 Learning rate: 0.02 Mask loss: 0.17145 RPN box loss: 0.0547 RPN score loss: 0.00252 RPN total loss: 0.05722 Total loss: 1.2422 timestamp: 1654939645.7872329 iteration: 31285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14546 FastRCNN class loss: 0.06485 FastRCNN total loss: 0.21032 L1 loss: 0.0000e+00 L2 loss: 0.79216 Learning rate: 0.02 Mask loss: 0.17784 RPN box loss: 0.00709 RPN score loss: 0.00194 RPN total loss: 0.00903 Total loss: 1.18935 timestamp: 1654939649.010016 iteration: 31290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10145 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.15802 L1 loss: 0.0000e+00 L2 loss: 0.79203 Learning rate: 0.02 Mask loss: 0.14102 RPN box loss: 0.01505 RPN score loss: 0.00361 RPN total loss: 0.01866 Total loss: 1.10973 timestamp: 1654939652.2375522 iteration: 31295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16415 FastRCNN class loss: 0.08412 FastRCNN total loss: 0.24827 L1 loss: 0.0000e+00 L2 loss: 0.79191 Learning rate: 0.02 Mask loss: 0.11339 RPN box loss: 0.03448 RPN score loss: 0.01128 RPN total loss: 0.04576 Total loss: 1.19932 timestamp: 1654939655.3970609 iteration: 31300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16479 FastRCNN class loss: 0.08327 FastRCNN total loss: 0.24806 L1 loss: 0.0000e+00 L2 loss: 0.79178 Learning rate: 0.02 Mask loss: 0.11234 RPN box loss: 0.01343 RPN score loss: 0.00709 RPN total loss: 0.02052 Total loss: 1.1727 timestamp: 1654939658.5844326 iteration: 31305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10979 FastRCNN class loss: 0.05236 FastRCNN total loss: 0.16215 L1 loss: 0.0000e+00 L2 loss: 0.79168 Learning rate: 0.02 Mask loss: 0.10381 RPN box loss: 0.00931 RPN score loss: 0.00346 RPN total loss: 0.01277 Total loss: 1.07041 timestamp: 1654939661.7687328 iteration: 31310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13051 FastRCNN class loss: 0.08384 FastRCNN total loss: 0.21436 L1 loss: 0.0000e+00 L2 loss: 0.79157 Learning rate: 0.02 Mask loss: 0.1323 RPN box loss: 0.0205 RPN score loss: 0.00714 RPN total loss: 0.02764 Total loss: 1.16586 timestamp: 1654939665.0008183 iteration: 31315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18236 FastRCNN class loss: 0.09754 FastRCNN total loss: 0.2799 L1 loss: 0.0000e+00 L2 loss: 0.79143 Learning rate: 0.02 Mask loss: 0.16302 RPN box loss: 0.09715 RPN score loss: 0.00886 RPN total loss: 0.10602 Total loss: 1.34036 timestamp: 1654939668.2052944 iteration: 31320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06521 FastRCNN class loss: 0.05792 FastRCNN total loss: 0.12313 L1 loss: 0.0000e+00 L2 loss: 0.79132 Learning rate: 0.02 Mask loss: 0.0877 RPN box loss: 0.01542 RPN score loss: 0.00222 RPN total loss: 0.01764 Total loss: 1.01979 timestamp: 1654939671.3309884 iteration: 31325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16823 FastRCNN class loss: 0.10235 FastRCNN total loss: 0.27059 L1 loss: 0.0000e+00 L2 loss: 0.79119 Learning rate: 0.02 Mask loss: 0.23902 RPN box loss: 0.08814 RPN score loss: 0.00698 RPN total loss: 0.09512 Total loss: 1.39591 timestamp: 1654939674.4654706 iteration: 31330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14193 FastRCNN class loss: 0.14425 FastRCNN total loss: 0.28618 L1 loss: 0.0000e+00 L2 loss: 0.79107 Learning rate: 0.02 Mask loss: 0.16727 RPN box loss: 0.02877 RPN score loss: 0.00268 RPN total loss: 0.03145 Total loss: 1.27597 timestamp: 1654939677.644678 iteration: 31335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1067 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.16718 L1 loss: 0.0000e+00 L2 loss: 0.79096 Learning rate: 0.02 Mask loss: 0.11549 RPN box loss: 0.00872 RPN score loss: 0.00689 RPN total loss: 0.01561 Total loss: 1.08924 timestamp: 1654939680.7687235 iteration: 31340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12598 FastRCNN class loss: 0.09788 FastRCNN total loss: 0.22386 L1 loss: 0.0000e+00 L2 loss: 0.79082 Learning rate: 0.02 Mask loss: 0.11869 RPN box loss: 0.02732 RPN score loss: 0.00729 RPN total loss: 0.03462 Total loss: 1.16799 timestamp: 1654939683.9090579 iteration: 31345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14878 FastRCNN class loss: 0.11145 FastRCNN total loss: 0.26023 L1 loss: 0.0000e+00 L2 loss: 0.7907 Learning rate: 0.02 Mask loss: 0.25529 RPN box loss: 0.01971 RPN score loss: 0.00705 RPN total loss: 0.02676 Total loss: 1.33299 timestamp: 1654939687.025951 iteration: 31350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08486 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.13542 L1 loss: 0.0000e+00 L2 loss: 0.7906 Learning rate: 0.02 Mask loss: 0.09598 RPN box loss: 0.05945 RPN score loss: 0.00475 RPN total loss: 0.0642 Total loss: 1.08619 timestamp: 1654939690.2232864 iteration: 31355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13649 FastRCNN class loss: 0.05664 FastRCNN total loss: 0.19313 L1 loss: 0.0000e+00 L2 loss: 0.7905 Learning rate: 0.02 Mask loss: 0.12257 RPN box loss: 0.02374 RPN score loss: 0.00496 RPN total loss: 0.0287 Total loss: 1.1349 timestamp: 1654939693.4663193 iteration: 31360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14012 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.22994 L1 loss: 0.0000e+00 L2 loss: 0.7904 Learning rate: 0.02 Mask loss: 0.11649 RPN box loss: 0.02354 RPN score loss: 0.0019 RPN total loss: 0.02543 Total loss: 1.16227 timestamp: 1654939696.63431 iteration: 31365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10191 FastRCNN class loss: 0.03339 FastRCNN total loss: 0.1353 L1 loss: 0.0000e+00 L2 loss: 0.79029 Learning rate: 0.02 Mask loss: 0.09125 RPN box loss: 0.00561 RPN score loss: 0.00516 RPN total loss: 0.01077 Total loss: 1.0276 timestamp: 1654939699.8696158 iteration: 31370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14761 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.23916 L1 loss: 0.0000e+00 L2 loss: 0.79018 Learning rate: 0.02 Mask loss: 0.14914 RPN box loss: 0.0163 RPN score loss: 0.00275 RPN total loss: 0.01905 Total loss: 1.19754 timestamp: 1654939703.008991 iteration: 31375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12308 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.18872 L1 loss: 0.0000e+00 L2 loss: 0.79006 Learning rate: 0.02 Mask loss: 0.15871 RPN box loss: 0.01729 RPN score loss: 0.00939 RPN total loss: 0.02669 Total loss: 1.16417 timestamp: 1654939706.227547 iteration: 31380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12138 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.18721 L1 loss: 0.0000e+00 L2 loss: 0.78993 Learning rate: 0.02 Mask loss: 0.13312 RPN box loss: 0.04719 RPN score loss: 0.01349 RPN total loss: 0.06068 Total loss: 1.17093 timestamp: 1654939709.4597456 iteration: 31385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13131 FastRCNN class loss: 0.04655 FastRCNN total loss: 0.17786 L1 loss: 0.0000e+00 L2 loss: 0.7898 Learning rate: 0.02 Mask loss: 0.09299 RPN box loss: 0.02176 RPN score loss: 0.00322 RPN total loss: 0.02498 Total loss: 1.08562 timestamp: 1654939712.6446657 iteration: 31390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09944 FastRCNN class loss: 0.063 FastRCNN total loss: 0.16244 L1 loss: 0.0000e+00 L2 loss: 0.78969 Learning rate: 0.02 Mask loss: 0.12426 RPN box loss: 0.02497 RPN score loss: 0.00949 RPN total loss: 0.03446 Total loss: 1.11085 timestamp: 1654939715.8331807 iteration: 31395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08679 FastRCNN class loss: 0.07822 FastRCNN total loss: 0.16501 L1 loss: 0.0000e+00 L2 loss: 0.78957 Learning rate: 0.02 Mask loss: 0.14065 RPN box loss: 0.0129 RPN score loss: 0.00187 RPN total loss: 0.01478 Total loss: 1.11001 timestamp: 1654939719.0479052 iteration: 31400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16182 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.22363 L1 loss: 0.0000e+00 L2 loss: 0.78947 Learning rate: 0.02 Mask loss: 0.11958 RPN box loss: 0.07388 RPN score loss: 0.00468 RPN total loss: 0.07856 Total loss: 1.21124 timestamp: 1654939722.2028682 iteration: 31405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1133 FastRCNN class loss: 0.08843 FastRCNN total loss: 0.20172 L1 loss: 0.0000e+00 L2 loss: 0.78937 Learning rate: 0.02 Mask loss: 0.1803 RPN box loss: 0.06633 RPN score loss: 0.01027 RPN total loss: 0.07661 Total loss: 1.248 timestamp: 1654939725.440337 iteration: 31410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16761 FastRCNN class loss: 0.09866 FastRCNN total loss: 0.26627 L1 loss: 0.0000e+00 L2 loss: 0.78928 Learning rate: 0.02 Mask loss: 0.11522 RPN box loss: 0.00781 RPN score loss: 0.00571 RPN total loss: 0.01351 Total loss: 1.18428 timestamp: 1654939728.7010338 iteration: 31415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15751 FastRCNN class loss: 0.11119 FastRCNN total loss: 0.2687 L1 loss: 0.0000e+00 L2 loss: 0.78917 Learning rate: 0.02 Mask loss: 0.14795 RPN box loss: 0.03141 RPN score loss: 0.01245 RPN total loss: 0.04386 Total loss: 1.24969 timestamp: 1654939731.9222174 iteration: 31420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13337 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.20171 L1 loss: 0.0000e+00 L2 loss: 0.78906 Learning rate: 0.02 Mask loss: 0.13048 RPN box loss: 0.01866 RPN score loss: 0.0025 RPN total loss: 0.02116 Total loss: 1.14241 timestamp: 1654939735.169527 iteration: 31425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15012 FastRCNN class loss: 0.09522 FastRCNN total loss: 0.24533 L1 loss: 0.0000e+00 L2 loss: 0.78892 Learning rate: 0.02 Mask loss: 0.17279 RPN box loss: 0.06956 RPN score loss: 0.01537 RPN total loss: 0.08493 Total loss: 1.29198 timestamp: 1654939738.361245 iteration: 31430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15333 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.25248 L1 loss: 0.0000e+00 L2 loss: 0.78879 Learning rate: 0.02 Mask loss: 0.23078 RPN box loss: 0.01261 RPN score loss: 0.00464 RPN total loss: 0.01725 Total loss: 1.28931 timestamp: 1654939741.5152104 iteration: 31435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12725 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.19341 L1 loss: 0.0000e+00 L2 loss: 0.78869 Learning rate: 0.02 Mask loss: 0.14271 RPN box loss: 0.02889 RPN score loss: 0.00602 RPN total loss: 0.03491 Total loss: 1.15972 timestamp: 1654939744.745106 iteration: 31440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09763 FastRCNN class loss: 0.07589 FastRCNN total loss: 0.17352 L1 loss: 0.0000e+00 L2 loss: 0.7886 Learning rate: 0.02 Mask loss: 0.1297 RPN box loss: 0.01805 RPN score loss: 0.00681 RPN total loss: 0.02486 Total loss: 1.11668 timestamp: 1654939747.927136 iteration: 31445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1463 FastRCNN class loss: 0.08484 FastRCNN total loss: 0.23114 L1 loss: 0.0000e+00 L2 loss: 0.78851 Learning rate: 0.02 Mask loss: 0.19601 RPN box loss: 0.02374 RPN score loss: 0.00493 RPN total loss: 0.02867 Total loss: 1.24433 timestamp: 1654939751.1717837 iteration: 31450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1157 FastRCNN class loss: 0.08575 FastRCNN total loss: 0.20146 L1 loss: 0.0000e+00 L2 loss: 0.78838 Learning rate: 0.02 Mask loss: 0.15751 RPN box loss: 0.02927 RPN score loss: 0.00604 RPN total loss: 0.03531 Total loss: 1.18266 timestamp: 1654939754.3978705 iteration: 31455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16807 FastRCNN class loss: 0.10452 FastRCNN total loss: 0.27259 L1 loss: 0.0000e+00 L2 loss: 0.78826 Learning rate: 0.02 Mask loss: 0.18699 RPN box loss: 0.02111 RPN score loss: 0.01205 RPN total loss: 0.03317 Total loss: 1.281 timestamp: 1654939757.5264184 iteration: 31460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13578 FastRCNN class loss: 0.07412 FastRCNN total loss: 0.2099 L1 loss: 0.0000e+00 L2 loss: 0.78816 Learning rate: 0.02 Mask loss: 0.13192 RPN box loss: 0.02569 RPN score loss: 0.00574 RPN total loss: 0.03144 Total loss: 1.16142 timestamp: 1654939760.7420735 iteration: 31465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11919 FastRCNN class loss: 0.09631 FastRCNN total loss: 0.21551 L1 loss: 0.0000e+00 L2 loss: 0.78807 Learning rate: 0.02 Mask loss: 0.14378 RPN box loss: 0.03077 RPN score loss: 0.00447 RPN total loss: 0.03523 Total loss: 1.18259 timestamp: 1654939763.977777 iteration: 31470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16646 FastRCNN class loss: 0.13414 FastRCNN total loss: 0.3006 L1 loss: 0.0000e+00 L2 loss: 0.78795 Learning rate: 0.02 Mask loss: 0.23648 RPN box loss: 0.04501 RPN score loss: 0.01377 RPN total loss: 0.05878 Total loss: 1.38382 timestamp: 1654939767.0772617 iteration: 31475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17007 FastRCNN class loss: 0.07858 FastRCNN total loss: 0.24865 L1 loss: 0.0000e+00 L2 loss: 0.78784 Learning rate: 0.02 Mask loss: 0.17543 RPN box loss: 0.03532 RPN score loss: 0.00424 RPN total loss: 0.03956 Total loss: 1.25148 timestamp: 1654939770.2739968 iteration: 31480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10326 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.18151 L1 loss: 0.0000e+00 L2 loss: 0.78773 Learning rate: 0.02 Mask loss: 0.12347 RPN box loss: 0.0245 RPN score loss: 0.00934 RPN total loss: 0.03383 Total loss: 1.12654 timestamp: 1654939773.5046544 iteration: 31485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16681 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.2536 L1 loss: 0.0000e+00 L2 loss: 0.78762 Learning rate: 0.02 Mask loss: 0.16786 RPN box loss: 0.04025 RPN score loss: 0.01005 RPN total loss: 0.05031 Total loss: 1.25939 timestamp: 1654939776.651079 iteration: 31490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10201 FastRCNN class loss: 0.0522 FastRCNN total loss: 0.15421 L1 loss: 0.0000e+00 L2 loss: 0.78752 Learning rate: 0.02 Mask loss: 0.09225 RPN box loss: 0.03137 RPN score loss: 0.00292 RPN total loss: 0.03429 Total loss: 1.06827 timestamp: 1654939779.7734263 iteration: 31495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12038 FastRCNN class loss: 0.07711 FastRCNN total loss: 0.19749 L1 loss: 0.0000e+00 L2 loss: 0.7874 Learning rate: 0.02 Mask loss: 0.13684 RPN box loss: 0.02052 RPN score loss: 0.00625 RPN total loss: 0.02678 Total loss: 1.14851 timestamp: 1654939783.0139987 iteration: 31500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16181 FastRCNN class loss: 0.1103 FastRCNN total loss: 0.27211 L1 loss: 0.0000e+00 L2 loss: 0.78731 Learning rate: 0.02 Mask loss: 0.22868 RPN box loss: 0.04936 RPN score loss: 0.01672 RPN total loss: 0.06609 Total loss: 1.35418 timestamp: 1654939786.2600317 iteration: 31505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07434 FastRCNN class loss: 0.04285 FastRCNN total loss: 0.1172 L1 loss: 0.0000e+00 L2 loss: 0.78723 Learning rate: 0.02 Mask loss: 0.15126 RPN box loss: 0.02094 RPN score loss: 0.00332 RPN total loss: 0.02425 Total loss: 1.07993 timestamp: 1654939789.3941092 iteration: 31510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12092 FastRCNN class loss: 0.07859 FastRCNN total loss: 0.19952 L1 loss: 0.0000e+00 L2 loss: 0.78711 Learning rate: 0.02 Mask loss: 0.17977 RPN box loss: 0.04706 RPN score loss: 0.00776 RPN total loss: 0.05482 Total loss: 1.22122 timestamp: 1654939792.5794477 iteration: 31515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16684 FastRCNN class loss: 0.08056 FastRCNN total loss: 0.24739 L1 loss: 0.0000e+00 L2 loss: 0.787 Learning rate: 0.02 Mask loss: 0.11567 RPN box loss: 0.01386 RPN score loss: 0.00584 RPN total loss: 0.0197 Total loss: 1.16976 timestamp: 1654939795.7904036 iteration: 31520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10741 FastRCNN class loss: 0.10093 FastRCNN total loss: 0.20834 L1 loss: 0.0000e+00 L2 loss: 0.78687 Learning rate: 0.02 Mask loss: 0.16556 RPN box loss: 0.03999 RPN score loss: 0.00972 RPN total loss: 0.04971 Total loss: 1.21048 timestamp: 1654939798.959997 iteration: 31525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.06356 FastRCNN total loss: 0.1792 L1 loss: 0.0000e+00 L2 loss: 0.78678 Learning rate: 0.02 Mask loss: 0.19884 RPN box loss: 0.01686 RPN score loss: 0.00966 RPN total loss: 0.02652 Total loss: 1.19134 timestamp: 1654939802.1300573 iteration: 31530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09815 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.18156 L1 loss: 0.0000e+00 L2 loss: 0.78665 Learning rate: 0.02 Mask loss: 0.13611 RPN box loss: 0.10578 RPN score loss: 0.00537 RPN total loss: 0.11115 Total loss: 1.21547 timestamp: 1654939805.3859043 iteration: 31535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.08401 FastRCNN total loss: 0.18468 L1 loss: 0.0000e+00 L2 loss: 0.78652 Learning rate: 0.02 Mask loss: 0.18673 RPN box loss: 0.03834 RPN score loss: 0.00286 RPN total loss: 0.0412 Total loss: 1.19913 timestamp: 1654939808.5179684 iteration: 31540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09416 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.14631 L1 loss: 0.0000e+00 L2 loss: 0.7864 Learning rate: 0.02 Mask loss: 0.21877 RPN box loss: 0.0261 RPN score loss: 0.0023 RPN total loss: 0.0284 Total loss: 1.17988 timestamp: 1654939811.712913 iteration: 31545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09223 FastRCNN class loss: 0.0468 FastRCNN total loss: 0.13903 L1 loss: 0.0000e+00 L2 loss: 0.78629 Learning rate: 0.02 Mask loss: 0.15489 RPN box loss: 0.01534 RPN score loss: 0.00441 RPN total loss: 0.01975 Total loss: 1.09995 timestamp: 1654939814.9373977 iteration: 31550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04938 FastRCNN class loss: 0.03144 FastRCNN total loss: 0.08082 L1 loss: 0.0000e+00 L2 loss: 0.78621 Learning rate: 0.02 Mask loss: 0.10582 RPN box loss: 0.03991 RPN score loss: 0.00251 RPN total loss: 0.04242 Total loss: 1.01526 timestamp: 1654939818.1132517 iteration: 31555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17361 FastRCNN class loss: 0.06626 FastRCNN total loss: 0.23988 L1 loss: 0.0000e+00 L2 loss: 0.78609 Learning rate: 0.02 Mask loss: 0.12051 RPN box loss: 0.01421 RPN score loss: 0.00514 RPN total loss: 0.01935 Total loss: 1.16583 timestamp: 1654939821.3646185 iteration: 31560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11227 FastRCNN class loss: 0.06117 FastRCNN total loss: 0.17344 L1 loss: 0.0000e+00 L2 loss: 0.78599 Learning rate: 0.02 Mask loss: 0.12855 RPN box loss: 0.01428 RPN score loss: 0.00386 RPN total loss: 0.01815 Total loss: 1.10613 timestamp: 1654939824.547321 iteration: 31565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11437 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.19715 L1 loss: 0.0000e+00 L2 loss: 0.78586 Learning rate: 0.02 Mask loss: 0.12816 RPN box loss: 0.03515 RPN score loss: 0.0084 RPN total loss: 0.04356 Total loss: 1.15473 timestamp: 1654939827.7981873 iteration: 31570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1317 FastRCNN class loss: 0.10297 FastRCNN total loss: 0.23467 L1 loss: 0.0000e+00 L2 loss: 0.78574 Learning rate: 0.02 Mask loss: 0.21454 RPN box loss: 0.02968 RPN score loss: 0.00421 RPN total loss: 0.03388 Total loss: 1.26883 timestamp: 1654939831.0186 iteration: 31575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16286 FastRCNN class loss: 0.16408 FastRCNN total loss: 0.32694 L1 loss: 0.0000e+00 L2 loss: 0.78563 Learning rate: 0.02 Mask loss: 0.19291 RPN box loss: 0.03601 RPN score loss: 0.00719 RPN total loss: 0.0432 Total loss: 1.34868 timestamp: 1654939834.1131964 iteration: 31580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10284 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.17665 L1 loss: 0.0000e+00 L2 loss: 0.7855 Learning rate: 0.02 Mask loss: 0.12871 RPN box loss: 0.01549 RPN score loss: 0.00495 RPN total loss: 0.02044 Total loss: 1.11131 timestamp: 1654939837.2024703 iteration: 31585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18785 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.25604 L1 loss: 0.0000e+00 L2 loss: 0.78541 Learning rate: 0.02 Mask loss: 0.14407 RPN box loss: 0.01489 RPN score loss: 0.00859 RPN total loss: 0.02348 Total loss: 1.209 timestamp: 1654939840.4115944 iteration: 31590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12076 FastRCNN class loss: 0.07149 FastRCNN total loss: 0.19225 L1 loss: 0.0000e+00 L2 loss: 0.78531 Learning rate: 0.02 Mask loss: 0.17191 RPN box loss: 0.02383 RPN score loss: 0.01062 RPN total loss: 0.03445 Total loss: 1.18391 timestamp: 1654939843.602888 iteration: 31595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11132 FastRCNN class loss: 0.0795 FastRCNN total loss: 0.19082 L1 loss: 0.0000e+00 L2 loss: 0.78519 Learning rate: 0.02 Mask loss: 0.19379 RPN box loss: 0.02796 RPN score loss: 0.0034 RPN total loss: 0.03135 Total loss: 1.20115 timestamp: 1654939846.762462 iteration: 31600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14431 FastRCNN class loss: 0.1205 FastRCNN total loss: 0.26481 L1 loss: 0.0000e+00 L2 loss: 0.78508 Learning rate: 0.02 Mask loss: 0.17891 RPN box loss: 0.02936 RPN score loss: 0.00483 RPN total loss: 0.03419 Total loss: 1.26298 timestamp: 1654939850.0392191 iteration: 31605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26904 FastRCNN class loss: 0.14886 FastRCNN total loss: 0.41789 L1 loss: 0.0000e+00 L2 loss: 0.78498 Learning rate: 0.02 Mask loss: 0.24736 RPN box loss: 0.05079 RPN score loss: 0.00684 RPN total loss: 0.05763 Total loss: 1.50785 timestamp: 1654939853.2462451 iteration: 31610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16459 FastRCNN class loss: 0.0998 FastRCNN total loss: 0.26439 L1 loss: 0.0000e+00 L2 loss: 0.78487 Learning rate: 0.02 Mask loss: 0.15912 RPN box loss: 0.02809 RPN score loss: 0.00714 RPN total loss: 0.03523 Total loss: 1.24361 timestamp: 1654939856.4705615 iteration: 31615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13178 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.20153 L1 loss: 0.0000e+00 L2 loss: 0.78476 Learning rate: 0.02 Mask loss: 0.17909 RPN box loss: 0.03025 RPN score loss: 0.00252 RPN total loss: 0.03277 Total loss: 1.19815 timestamp: 1654939859.6844208 iteration: 31620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14767 FastRCNN class loss: 0.08288 FastRCNN total loss: 0.23055 L1 loss: 0.0000e+00 L2 loss: 0.78465 Learning rate: 0.02 Mask loss: 0.12469 RPN box loss: 0.02537 RPN score loss: 0.00346 RPN total loss: 0.02883 Total loss: 1.16872 timestamp: 1654939862.8960123 iteration: 31625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14726 FastRCNN class loss: 0.11592 FastRCNN total loss: 0.26318 L1 loss: 0.0000e+00 L2 loss: 0.78454 Learning rate: 0.02 Mask loss: 0.13947 RPN box loss: 0.20653 RPN score loss: 0.00847 RPN total loss: 0.215 Total loss: 1.40219 timestamp: 1654939866.1227443 iteration: 31630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0919 FastRCNN class loss: 0.05254 FastRCNN total loss: 0.14444 L1 loss: 0.0000e+00 L2 loss: 0.78443 Learning rate: 0.02 Mask loss: 0.13587 RPN box loss: 0.03851 RPN score loss: 0.0095 RPN total loss: 0.04801 Total loss: 1.11275 timestamp: 1654939869.294967 iteration: 31635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10642 FastRCNN class loss: 0.15197 FastRCNN total loss: 0.25839 L1 loss: 0.0000e+00 L2 loss: 0.78432 Learning rate: 0.02 Mask loss: 0.24831 RPN box loss: 0.04141 RPN score loss: 0.07652 RPN total loss: 0.11792 Total loss: 1.40894 timestamp: 1654939872.4967585 iteration: 31640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10614 FastRCNN class loss: 0.08921 FastRCNN total loss: 0.19535 L1 loss: 0.0000e+00 L2 loss: 0.78421 Learning rate: 0.02 Mask loss: 0.19073 RPN box loss: 0.02295 RPN score loss: 0.00845 RPN total loss: 0.03141 Total loss: 1.2017 timestamp: 1654939875.7262142 iteration: 31645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13001 FastRCNN class loss: 0.06226 FastRCNN total loss: 0.19227 L1 loss: 0.0000e+00 L2 loss: 0.78414 Learning rate: 0.02 Mask loss: 0.15115 RPN box loss: 0.04446 RPN score loss: 0.00756 RPN total loss: 0.05202 Total loss: 1.17958 timestamp: 1654939878.9898221 iteration: 31650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14642 FastRCNN class loss: 0.06919 FastRCNN total loss: 0.21561 L1 loss: 0.0000e+00 L2 loss: 0.78402 Learning rate: 0.02 Mask loss: 0.14029 RPN box loss: 0.02048 RPN score loss: 0.00844 RPN total loss: 0.02891 Total loss: 1.16883 timestamp: 1654939882.1778183 iteration: 31655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13857 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.19728 L1 loss: 0.0000e+00 L2 loss: 0.78388 Learning rate: 0.02 Mask loss: 0.11883 RPN box loss: 0.01261 RPN score loss: 0.0074 RPN total loss: 0.02001 Total loss: 1.12001 timestamp: 1654939885.436674 iteration: 31660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17913 FastRCNN class loss: 0.10705 FastRCNN total loss: 0.28618 L1 loss: 0.0000e+00 L2 loss: 0.78378 Learning rate: 0.02 Mask loss: 0.16964 RPN box loss: 0.02875 RPN score loss: 0.00933 RPN total loss: 0.03809 Total loss: 1.27769 timestamp: 1654939888.6499195 iteration: 31665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11452 FastRCNN class loss: 0.06171 FastRCNN total loss: 0.17623 L1 loss: 0.0000e+00 L2 loss: 0.78368 Learning rate: 0.02 Mask loss: 0.12789 RPN box loss: 0.01488 RPN score loss: 0.00339 RPN total loss: 0.01827 Total loss: 1.10608 timestamp: 1654939891.812807 iteration: 31670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09754 FastRCNN class loss: 0.0805 FastRCNN total loss: 0.17804 L1 loss: 0.0000e+00 L2 loss: 0.78357 Learning rate: 0.02 Mask loss: 0.10916 RPN box loss: 0.03286 RPN score loss: 0.00691 RPN total loss: 0.03978 Total loss: 1.11055 timestamp: 1654939894.9973 iteration: 31675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18666 FastRCNN class loss: 0.06389 FastRCNN total loss: 0.25055 L1 loss: 0.0000e+00 L2 loss: 0.78347 Learning rate: 0.02 Mask loss: 0.10845 RPN box loss: 0.05306 RPN score loss: 0.00515 RPN total loss: 0.05821 Total loss: 1.20069 timestamp: 1654939898.2018456 iteration: 31680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10176 FastRCNN class loss: 0.06592 FastRCNN total loss: 0.16768 L1 loss: 0.0000e+00 L2 loss: 0.78337 Learning rate: 0.02 Mask loss: 0.10766 RPN box loss: 0.02134 RPN score loss: 0.00704 RPN total loss: 0.02839 Total loss: 1.0871 timestamp: 1654939901.4416025 iteration: 31685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11165 FastRCNN class loss: 0.10824 FastRCNN total loss: 0.21989 L1 loss: 0.0000e+00 L2 loss: 0.78327 Learning rate: 0.02 Mask loss: 0.17185 RPN box loss: 0.03263 RPN score loss: 0.00391 RPN total loss: 0.03655 Total loss: 1.21156 timestamp: 1654939904.6328 iteration: 31690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13785 FastRCNN class loss: 0.09711 FastRCNN total loss: 0.23496 L1 loss: 0.0000e+00 L2 loss: 0.78315 Learning rate: 0.02 Mask loss: 0.16653 RPN box loss: 0.0326 RPN score loss: 0.0059 RPN total loss: 0.0385 Total loss: 1.22314 timestamp: 1654939907.858132 iteration: 31695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11071 FastRCNN class loss: 0.0966 FastRCNN total loss: 0.20732 L1 loss: 0.0000e+00 L2 loss: 0.78303 Learning rate: 0.02 Mask loss: 0.14927 RPN box loss: 0.00988 RPN score loss: 0.00135 RPN total loss: 0.01123 Total loss: 1.15084 timestamp: 1654939911.082141 iteration: 31700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12459 FastRCNN class loss: 0.0861 FastRCNN total loss: 0.21069 L1 loss: 0.0000e+00 L2 loss: 0.78292 Learning rate: 0.02 Mask loss: 0.13688 RPN box loss: 0.01565 RPN score loss: 0.00451 RPN total loss: 0.02016 Total loss: 1.15064 timestamp: 1654939914.2567608 iteration: 31705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21107 FastRCNN class loss: 0.13424 FastRCNN total loss: 0.34531 L1 loss: 0.0000e+00 L2 loss: 0.78283 Learning rate: 0.02 Mask loss: 0.18377 RPN box loss: 0.02398 RPN score loss: 0.0104 RPN total loss: 0.03438 Total loss: 1.34628 timestamp: 1654939917.4042306 iteration: 31710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06397 FastRCNN class loss: 0.08599 FastRCNN total loss: 0.14996 L1 loss: 0.0000e+00 L2 loss: 0.78271 Learning rate: 0.02 Mask loss: 0.11986 RPN box loss: 0.06221 RPN score loss: 0.01435 RPN total loss: 0.07657 Total loss: 1.1291 timestamp: 1654939920.6413178 iteration: 31715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15672 FastRCNN class loss: 0.09613 FastRCNN total loss: 0.25285 L1 loss: 0.0000e+00 L2 loss: 0.78259 Learning rate: 0.02 Mask loss: 0.1738 RPN box loss: 0.02585 RPN score loss: 0.00379 RPN total loss: 0.02964 Total loss: 1.23888 timestamp: 1654939923.7911134 iteration: 31720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1475 FastRCNN class loss: 0.05231 FastRCNN total loss: 0.1998 L1 loss: 0.0000e+00 L2 loss: 0.78249 Learning rate: 0.02 Mask loss: 0.10326 RPN box loss: 0.04903 RPN score loss: 0.00658 RPN total loss: 0.05561 Total loss: 1.14117 timestamp: 1654939927.084654 iteration: 31725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1943 FastRCNN class loss: 0.13955 FastRCNN total loss: 0.33385 L1 loss: 0.0000e+00 L2 loss: 0.78238 Learning rate: 0.02 Mask loss: 0.24027 RPN box loss: 0.06206 RPN score loss: 0.01752 RPN total loss: 0.07958 Total loss: 1.43608 timestamp: 1654939930.2670293 iteration: 31730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1322 FastRCNN class loss: 0.08352 FastRCNN total loss: 0.21571 L1 loss: 0.0000e+00 L2 loss: 0.78229 Learning rate: 0.02 Mask loss: 0.17189 RPN box loss: 0.01371 RPN score loss: 0.00384 RPN total loss: 0.01755 Total loss: 1.18745 timestamp: 1654939933.5638213 iteration: 31735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1522 FastRCNN class loss: 0.10374 FastRCNN total loss: 0.25595 L1 loss: 0.0000e+00 L2 loss: 0.78218 Learning rate: 0.02 Mask loss: 0.13433 RPN box loss: 0.03428 RPN score loss: 0.0054 RPN total loss: 0.03968 Total loss: 1.21213 timestamp: 1654939936.806599 iteration: 31740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12075 FastRCNN class loss: 0.05343 FastRCNN total loss: 0.17418 L1 loss: 0.0000e+00 L2 loss: 0.78207 Learning rate: 0.02 Mask loss: 0.14452 RPN box loss: 0.01558 RPN score loss: 0.00534 RPN total loss: 0.02092 Total loss: 1.1217 timestamp: 1654939940.000145 iteration: 31745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10722 FastRCNN class loss: 0.07303 FastRCNN total loss: 0.18025 L1 loss: 0.0000e+00 L2 loss: 0.78195 Learning rate: 0.02 Mask loss: 0.11207 RPN box loss: 0.00729 RPN score loss: 0.00273 RPN total loss: 0.01003 Total loss: 1.08429 timestamp: 1654939943.1233463 iteration: 31750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09746 FastRCNN class loss: 0.04917 FastRCNN total loss: 0.14663 L1 loss: 0.0000e+00 L2 loss: 0.78182 Learning rate: 0.02 Mask loss: 0.16017 RPN box loss: 0.02945 RPN score loss: 0.00277 RPN total loss: 0.03222 Total loss: 1.12083 timestamp: 1654939946.3150861 iteration: 31755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06748 FastRCNN class loss: 0.04838 FastRCNN total loss: 0.11586 L1 loss: 0.0000e+00 L2 loss: 0.78174 Learning rate: 0.02 Mask loss: 0.10725 RPN box loss: 0.00812 RPN score loss: 0.00272 RPN total loss: 0.01084 Total loss: 1.01569 timestamp: 1654939949.529324 iteration: 31760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16018 FastRCNN class loss: 0.13661 FastRCNN total loss: 0.29679 L1 loss: 0.0000e+00 L2 loss: 0.78166 Learning rate: 0.02 Mask loss: 0.11828 RPN box loss: 0.02555 RPN score loss: 0.01026 RPN total loss: 0.03581 Total loss: 1.23254 timestamp: 1654939952.7396498 iteration: 31765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17089 FastRCNN class loss: 0.09565 FastRCNN total loss: 0.26654 L1 loss: 0.0000e+00 L2 loss: 0.78154 Learning rate: 0.02 Mask loss: 0.19731 RPN box loss: 0.06549 RPN score loss: 0.01265 RPN total loss: 0.07814 Total loss: 1.32354 timestamp: 1654939955.9535658 iteration: 31770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1631 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.24119 L1 loss: 0.0000e+00 L2 loss: 0.78145 Learning rate: 0.02 Mask loss: 0.13413 RPN box loss: 0.02047 RPN score loss: 0.01091 RPN total loss: 0.03138 Total loss: 1.18816 timestamp: 1654939959.2067184 iteration: 31775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18079 FastRCNN class loss: 0.0801 FastRCNN total loss: 0.26089 L1 loss: 0.0000e+00 L2 loss: 0.78132 Learning rate: 0.02 Mask loss: 0.21962 RPN box loss: 0.01878 RPN score loss: 0.00764 RPN total loss: 0.02641 Total loss: 1.28825 timestamp: 1654939962.4915318 iteration: 31780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.07802 FastRCNN total loss: 0.2413 L1 loss: 0.0000e+00 L2 loss: 0.78118 Learning rate: 0.02 Mask loss: 0.1468 RPN box loss: 0.02631 RPN score loss: 0.00656 RPN total loss: 0.03288 Total loss: 1.20215 timestamp: 1654939965.7155225 iteration: 31785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09262 FastRCNN class loss: 0.04381 FastRCNN total loss: 0.13643 L1 loss: 0.0000e+00 L2 loss: 0.78108 Learning rate: 0.02 Mask loss: 0.12293 RPN box loss: 0.0092 RPN score loss: 0.00306 RPN total loss: 0.01226 Total loss: 1.0527 timestamp: 1654939968.899287 iteration: 31790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21094 FastRCNN class loss: 0.07935 FastRCNN total loss: 0.29029 L1 loss: 0.0000e+00 L2 loss: 0.78098 Learning rate: 0.02 Mask loss: 0.17478 RPN box loss: 0.05866 RPN score loss: 0.01347 RPN total loss: 0.07214 Total loss: 1.31818 timestamp: 1654939972.0981216 iteration: 31795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10923 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.16806 L1 loss: 0.0000e+00 L2 loss: 0.78084 Learning rate: 0.02 Mask loss: 0.19217 RPN box loss: 0.02689 RPN score loss: 0.00366 RPN total loss: 0.03055 Total loss: 1.17162 timestamp: 1654939975.3334868 iteration: 31800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20902 FastRCNN class loss: 0.12202 FastRCNN total loss: 0.33104 L1 loss: 0.0000e+00 L2 loss: 0.78073 Learning rate: 0.02 Mask loss: 0.24996 RPN box loss: 0.05365 RPN score loss: 0.00609 RPN total loss: 0.05974 Total loss: 1.42146 timestamp: 1654939978.5752735 iteration: 31805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11931 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.19024 L1 loss: 0.0000e+00 L2 loss: 0.78061 Learning rate: 0.02 Mask loss: 0.13406 RPN box loss: 0.01837 RPN score loss: 0.00348 RPN total loss: 0.02185 Total loss: 1.12675 timestamp: 1654939981.7060397 iteration: 31810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13823 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.19996 L1 loss: 0.0000e+00 L2 loss: 0.7805 Learning rate: 0.02 Mask loss: 0.09701 RPN box loss: 0.00733 RPN score loss: 0.00406 RPN total loss: 0.01138 Total loss: 1.08886 timestamp: 1654939984.9395936 iteration: 31815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22766 FastRCNN class loss: 0.05913 FastRCNN total loss: 0.28679 L1 loss: 0.0000e+00 L2 loss: 0.78039 Learning rate: 0.02 Mask loss: 0.16515 RPN box loss: 0.08233 RPN score loss: 0.00599 RPN total loss: 0.08832 Total loss: 1.32065 timestamp: 1654939988.1393566 iteration: 31820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16037 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.24673 L1 loss: 0.0000e+00 L2 loss: 0.78029 Learning rate: 0.02 Mask loss: 0.13171 RPN box loss: 0.03291 RPN score loss: 0.00467 RPN total loss: 0.03758 Total loss: 1.19632 timestamp: 1654939991.372606 iteration: 31825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15909 FastRCNN class loss: 0.10693 FastRCNN total loss: 0.26602 L1 loss: 0.0000e+00 L2 loss: 0.78019 Learning rate: 0.02 Mask loss: 0.21551 RPN box loss: 0.0267 RPN score loss: 0.00905 RPN total loss: 0.03575 Total loss: 1.29747 timestamp: 1654939994.656347 iteration: 31830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09499 FastRCNN class loss: 0.04207 FastRCNN total loss: 0.13705 L1 loss: 0.0000e+00 L2 loss: 0.78009 Learning rate: 0.02 Mask loss: 0.1121 RPN box loss: 0.01857 RPN score loss: 0.00643 RPN total loss: 0.02499 Total loss: 1.05423 timestamp: 1654939997.8924158 iteration: 31835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20206 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.28409 L1 loss: 0.0000e+00 L2 loss: 0.77999 Learning rate: 0.02 Mask loss: 0.11728 RPN box loss: 0.03307 RPN score loss: 0.00399 RPN total loss: 0.03706 Total loss: 1.21842 timestamp: 1654940001.1298614 iteration: 31840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12538 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.19951 L1 loss: 0.0000e+00 L2 loss: 0.77986 Learning rate: 0.02 Mask loss: 0.09163 RPN box loss: 0.01612 RPN score loss: 0.00545 RPN total loss: 0.02157 Total loss: 1.09257 timestamp: 1654940004.2980363 iteration: 31845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08923 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.17136 L1 loss: 0.0000e+00 L2 loss: 0.77975 Learning rate: 0.02 Mask loss: 0.09859 RPN box loss: 0.01897 RPN score loss: 0.00297 RPN total loss: 0.02194 Total loss: 1.07164 timestamp: 1654940007.415781 iteration: 31850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09257 FastRCNN class loss: 0.06341 FastRCNN total loss: 0.15598 L1 loss: 0.0000e+00 L2 loss: 0.77964 Learning rate: 0.02 Mask loss: 0.12445 RPN box loss: 0.04697 RPN score loss: 0.00755 RPN total loss: 0.05452 Total loss: 1.11458 timestamp: 1654940010.6998992 iteration: 31855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13541 FastRCNN class loss: 0.09103 FastRCNN total loss: 0.22645 L1 loss: 0.0000e+00 L2 loss: 0.77953 Learning rate: 0.02 Mask loss: 0.14964 RPN box loss: 0.00968 RPN score loss: 0.00767 RPN total loss: 0.01734 Total loss: 1.17295 timestamp: 1654940013.9001827 iteration: 31860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16786 FastRCNN class loss: 0.08187 FastRCNN total loss: 0.24973 L1 loss: 0.0000e+00 L2 loss: 0.77942 Learning rate: 0.02 Mask loss: 0.19723 RPN box loss: 0.03253 RPN score loss: 0.00308 RPN total loss: 0.03561 Total loss: 1.262 timestamp: 1654940017.0626767 iteration: 31865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.195 FastRCNN class loss: 0.13396 FastRCNN total loss: 0.32896 L1 loss: 0.0000e+00 L2 loss: 0.77932 Learning rate: 0.02 Mask loss: 0.19031 RPN box loss: 0.04124 RPN score loss: 0.01247 RPN total loss: 0.05371 Total loss: 1.3523 timestamp: 1654940020.2073708 iteration: 31870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18423 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.26066 L1 loss: 0.0000e+00 L2 loss: 0.77923 Learning rate: 0.02 Mask loss: 0.16815 RPN box loss: 0.04194 RPN score loss: 0.01051 RPN total loss: 0.05245 Total loss: 1.26049 timestamp: 1654940023.3481433 iteration: 31875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11886 FastRCNN class loss: 0.05793 FastRCNN total loss: 0.1768 L1 loss: 0.0000e+00 L2 loss: 0.77912 Learning rate: 0.02 Mask loss: 0.15348 RPN box loss: 0.02253 RPN score loss: 0.0027 RPN total loss: 0.02523 Total loss: 1.13463 timestamp: 1654940026.5403051 iteration: 31880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08502 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.14278 L1 loss: 0.0000e+00 L2 loss: 0.779 Learning rate: 0.02 Mask loss: 0.20634 RPN box loss: 0.02718 RPN score loss: 0.00534 RPN total loss: 0.03252 Total loss: 1.16064 timestamp: 1654940029.6710954 iteration: 31885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11606 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.18691 L1 loss: 0.0000e+00 L2 loss: 0.77889 Learning rate: 0.02 Mask loss: 0.20864 RPN box loss: 0.024 RPN score loss: 0.00445 RPN total loss: 0.02845 Total loss: 1.20289 timestamp: 1654940032.8374116 iteration: 31890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07428 FastRCNN class loss: 0.08341 FastRCNN total loss: 0.15769 L1 loss: 0.0000e+00 L2 loss: 0.77877 Learning rate: 0.02 Mask loss: 0.1387 RPN box loss: 0.02064 RPN score loss: 0.00348 RPN total loss: 0.02412 Total loss: 1.09928 timestamp: 1654940036.0857508 iteration: 31895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1575 FastRCNN class loss: 0.07739 FastRCNN total loss: 0.2349 L1 loss: 0.0000e+00 L2 loss: 0.77868 Learning rate: 0.02 Mask loss: 0.18134 RPN box loss: 0.04875 RPN score loss: 0.00801 RPN total loss: 0.05676 Total loss: 1.25168 timestamp: 1654940039.24491 iteration: 31900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10954 FastRCNN class loss: 0.08288 FastRCNN total loss: 0.19242 L1 loss: 0.0000e+00 L2 loss: 0.77856 Learning rate: 0.02 Mask loss: 0.16634 RPN box loss: 0.04697 RPN score loss: 0.01502 RPN total loss: 0.06199 Total loss: 1.19932 timestamp: 1654940042.365069 iteration: 31905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11224 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.18342 L1 loss: 0.0000e+00 L2 loss: 0.77847 Learning rate: 0.02 Mask loss: 0.14814 RPN box loss: 0.04672 RPN score loss: 0.01367 RPN total loss: 0.06039 Total loss: 1.17042 timestamp: 1654940045.5929096 iteration: 31910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16127 FastRCNN class loss: 0.16284 FastRCNN total loss: 0.32411 L1 loss: 0.0000e+00 L2 loss: 0.77836 Learning rate: 0.02 Mask loss: 0.26003 RPN box loss: 0.04164 RPN score loss: 0.00893 RPN total loss: 0.05057 Total loss: 1.41307 timestamp: 1654940048.765815 iteration: 31915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09157 FastRCNN class loss: 0.04394 FastRCNN total loss: 0.13552 L1 loss: 0.0000e+00 L2 loss: 0.77827 Learning rate: 0.02 Mask loss: 0.10775 RPN box loss: 0.07656 RPN score loss: 0.00547 RPN total loss: 0.08203 Total loss: 1.10356 timestamp: 1654940051.975991 iteration: 31920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16905 FastRCNN class loss: 0.06917 FastRCNN total loss: 0.23822 L1 loss: 0.0000e+00 L2 loss: 0.77818 Learning rate: 0.02 Mask loss: 0.14717 RPN box loss: 0.00797 RPN score loss: 0.00488 RPN total loss: 0.01285 Total loss: 1.17642 timestamp: 1654940055.1732364 iteration: 31925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19389 FastRCNN class loss: 0.0713 FastRCNN total loss: 0.26519 L1 loss: 0.0000e+00 L2 loss: 0.77805 Learning rate: 0.02 Mask loss: 0.18332 RPN box loss: 0.02648 RPN score loss: 0.00283 RPN total loss: 0.02931 Total loss: 1.25587 timestamp: 1654940058.424882 iteration: 31930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18287 FastRCNN class loss: 0.10073 FastRCNN total loss: 0.2836 L1 loss: 0.0000e+00 L2 loss: 0.77796 Learning rate: 0.02 Mask loss: 0.15421 RPN box loss: 0.00472 RPN score loss: 0.00286 RPN total loss: 0.00758 Total loss: 1.22335 timestamp: 1654940061.624827 iteration: 31935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1929 FastRCNN class loss: 0.10104 FastRCNN total loss: 0.29394 L1 loss: 0.0000e+00 L2 loss: 0.77786 Learning rate: 0.02 Mask loss: 0.19829 RPN box loss: 0.05724 RPN score loss: 0.01847 RPN total loss: 0.07571 Total loss: 1.34579 timestamp: 1654940064.798297 iteration: 31940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14315 FastRCNN class loss: 0.08632 FastRCNN total loss: 0.22947 L1 loss: 0.0000e+00 L2 loss: 0.77775 Learning rate: 0.02 Mask loss: 0.17961 RPN box loss: 0.01766 RPN score loss: 0.00438 RPN total loss: 0.02205 Total loss: 1.20887 timestamp: 1654940068.015671 iteration: 31945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09224 FastRCNN class loss: 0.06494 FastRCNN total loss: 0.15719 L1 loss: 0.0000e+00 L2 loss: 0.77766 Learning rate: 0.02 Mask loss: 0.10386 RPN box loss: 0.01515 RPN score loss: 0.00336 RPN total loss: 0.01851 Total loss: 1.05722 timestamp: 1654940071.233711 iteration: 31950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11378 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.17263 L1 loss: 0.0000e+00 L2 loss: 0.77756 Learning rate: 0.02 Mask loss: 0.16857 RPN box loss: 0.06094 RPN score loss: 0.00754 RPN total loss: 0.06847 Total loss: 1.18723 timestamp: 1654940074.4439523 iteration: 31955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11947 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.1936 L1 loss: 0.0000e+00 L2 loss: 0.77743 Learning rate: 0.02 Mask loss: 0.1358 RPN box loss: 0.03448 RPN score loss: 0.00434 RPN total loss: 0.03883 Total loss: 1.14566 timestamp: 1654940077.6396432 iteration: 31960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08507 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.14615 L1 loss: 0.0000e+00 L2 loss: 0.77735 Learning rate: 0.02 Mask loss: 0.1316 RPN box loss: 0.0275 RPN score loss: 0.00422 RPN total loss: 0.03172 Total loss: 1.08681 timestamp: 1654940080.8607225 iteration: 31965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10765 FastRCNN class loss: 0.10271 FastRCNN total loss: 0.21036 L1 loss: 0.0000e+00 L2 loss: 0.77724 Learning rate: 0.02 Mask loss: 0.16033 RPN box loss: 0.03955 RPN score loss: 0.00481 RPN total loss: 0.04436 Total loss: 1.19228 timestamp: 1654940084.1067014 iteration: 31970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10866 FastRCNN class loss: 0.07987 FastRCNN total loss: 0.18853 L1 loss: 0.0000e+00 L2 loss: 0.77711 Learning rate: 0.02 Mask loss: 0.14045 RPN box loss: 0.0149 RPN score loss: 0.00601 RPN total loss: 0.02091 Total loss: 1.127 timestamp: 1654940087.2825675 iteration: 31975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15708 FastRCNN class loss: 0.16396 FastRCNN total loss: 0.32105 L1 loss: 0.0000e+00 L2 loss: 0.77704 Learning rate: 0.02 Mask loss: 0.18945 RPN box loss: 0.03227 RPN score loss: 0.01048 RPN total loss: 0.04275 Total loss: 1.33028 timestamp: 1654940090.423251 iteration: 31980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.08878 FastRCNN total loss: 0.17723 L1 loss: 0.0000e+00 L2 loss: 0.77694 Learning rate: 0.02 Mask loss: 0.14908 RPN box loss: 0.01643 RPN score loss: 0.00769 RPN total loss: 0.02412 Total loss: 1.12738 timestamp: 1654940093.5974555 iteration: 31985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19564 FastRCNN class loss: 0.08951 FastRCNN total loss: 0.28515 L1 loss: 0.0000e+00 L2 loss: 0.77681 Learning rate: 0.02 Mask loss: 0.15305 RPN box loss: 0.05613 RPN score loss: 0.01358 RPN total loss: 0.06971 Total loss: 1.28471 timestamp: 1654940096.8129656 iteration: 31990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14696 FastRCNN class loss: 0.08597 FastRCNN total loss: 0.23293 L1 loss: 0.0000e+00 L2 loss: 0.7767 Learning rate: 0.02 Mask loss: 0.22166 RPN box loss: 0.0489 RPN score loss: 0.00532 RPN total loss: 0.05422 Total loss: 1.28551 timestamp: 1654940100.0310488 iteration: 31995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10379 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.16226 L1 loss: 0.0000e+00 L2 loss: 0.77659 Learning rate: 0.02 Mask loss: 0.13957 RPN box loss: 0.03206 RPN score loss: 0.00599 RPN total loss: 0.03806 Total loss: 1.11648 timestamp: 1654940103.1971428 iteration: 32000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11529 FastRCNN class loss: 0.09895 FastRCNN total loss: 0.21424 L1 loss: 0.0000e+00 L2 loss: 0.77647 Learning rate: 0.02 Mask loss: 0.12708 RPN box loss: 0.0335 RPN score loss: 0.00736 RPN total loss: 0.04086 Total loss: 1.15864 timestamp: 1654940106.392341 iteration: 32005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0875 FastRCNN class loss: 0.06232 FastRCNN total loss: 0.14982 L1 loss: 0.0000e+00 L2 loss: 0.77635 Learning rate: 0.02 Mask loss: 0.17769 RPN box loss: 0.00396 RPN score loss: 0.00221 RPN total loss: 0.00617 Total loss: 1.11003 timestamp: 1654940109.607224 iteration: 32010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18964 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.2727 L1 loss: 0.0000e+00 L2 loss: 0.77623 Learning rate: 0.02 Mask loss: 0.26596 RPN box loss: 0.02063 RPN score loss: 0.00362 RPN total loss: 0.02426 Total loss: 1.33915 timestamp: 1654940112.7662141 iteration: 32015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1423 FastRCNN class loss: 0.08955 FastRCNN total loss: 0.23185 L1 loss: 0.0000e+00 L2 loss: 0.77615 Learning rate: 0.02 Mask loss: 0.1654 RPN box loss: 0.045 RPN score loss: 0.00669 RPN total loss: 0.05169 Total loss: 1.22509 timestamp: 1654940115.988047 iteration: 32020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17803 FastRCNN class loss: 0.13284 FastRCNN total loss: 0.31088 L1 loss: 0.0000e+00 L2 loss: 0.77607 Learning rate: 0.02 Mask loss: 0.19109 RPN box loss: 0.05901 RPN score loss: 0.00988 RPN total loss: 0.0689 Total loss: 1.34693 timestamp: 1654940119.1147172 iteration: 32025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11628 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.20669 L1 loss: 0.0000e+00 L2 loss: 0.77597 Learning rate: 0.02 Mask loss: 0.14481 RPN box loss: 0.1264 RPN score loss: 0.0076 RPN total loss: 0.13401 Total loss: 1.26147 timestamp: 1654940122.291945 iteration: 32030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14221 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.23997 L1 loss: 0.0000e+00 L2 loss: 0.77585 Learning rate: 0.02 Mask loss: 0.17081 RPN box loss: 0.02684 RPN score loss: 0.0067 RPN total loss: 0.03354 Total loss: 1.22017 timestamp: 1654940125.517668 iteration: 32035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08358 FastRCNN class loss: 0.05617 FastRCNN total loss: 0.13975 L1 loss: 0.0000e+00 L2 loss: 0.77572 Learning rate: 0.02 Mask loss: 0.11954 RPN box loss: 0.03147 RPN score loss: 0.00856 RPN total loss: 0.04003 Total loss: 1.07505 timestamp: 1654940128.6845593 iteration: 32040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17429 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.25007 L1 loss: 0.0000e+00 L2 loss: 0.77563 Learning rate: 0.02 Mask loss: 0.09534 RPN box loss: 0.03126 RPN score loss: 0.00354 RPN total loss: 0.0348 Total loss: 1.15584 timestamp: 1654940131.7606635 iteration: 32045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13053 FastRCNN class loss: 0.10803 FastRCNN total loss: 0.23856 L1 loss: 0.0000e+00 L2 loss: 0.77554 Learning rate: 0.02 Mask loss: 0.15206 RPN box loss: 0.06016 RPN score loss: 0.00727 RPN total loss: 0.06742 Total loss: 1.23357 timestamp: 1654940134.9446185 iteration: 32050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11724 FastRCNN class loss: 0.03831 FastRCNN total loss: 0.15555 L1 loss: 0.0000e+00 L2 loss: 0.77543 Learning rate: 0.02 Mask loss: 0.15871 RPN box loss: 0.06422 RPN score loss: 0.00579 RPN total loss: 0.07 Total loss: 1.15969 timestamp: 1654940138.128987 iteration: 32055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13684 FastRCNN class loss: 0.08735 FastRCNN total loss: 0.22418 L1 loss: 0.0000e+00 L2 loss: 0.77533 Learning rate: 0.02 Mask loss: 0.20537 RPN box loss: 0.03137 RPN score loss: 0.007 RPN total loss: 0.03837 Total loss: 1.24326 timestamp: 1654940141.3354886 iteration: 32060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14965 FastRCNN class loss: 0.09361 FastRCNN total loss: 0.24326 L1 loss: 0.0000e+00 L2 loss: 0.77522 Learning rate: 0.02 Mask loss: 0.12632 RPN box loss: 0.01955 RPN score loss: 0.00747 RPN total loss: 0.02703 Total loss: 1.17183 timestamp: 1654940144.5211904 iteration: 32065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10053 FastRCNN class loss: 0.09079 FastRCNN total loss: 0.19132 L1 loss: 0.0000e+00 L2 loss: 0.77508 Learning rate: 0.02 Mask loss: 0.14735 RPN box loss: 0.05956 RPN score loss: 0.00753 RPN total loss: 0.0671 Total loss: 1.18085 timestamp: 1654940147.776838 iteration: 32070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16175 FastRCNN class loss: 0.04832 FastRCNN total loss: 0.21007 L1 loss: 0.0000e+00 L2 loss: 0.77496 Learning rate: 0.02 Mask loss: 0.11436 RPN box loss: 0.01138 RPN score loss: 0.00624 RPN total loss: 0.01762 Total loss: 1.117 timestamp: 1654940150.9690926 iteration: 32075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09507 FastRCNN class loss: 0.04365 FastRCNN total loss: 0.13872 L1 loss: 0.0000e+00 L2 loss: 0.77485 Learning rate: 0.02 Mask loss: 0.14611 RPN box loss: 0.02459 RPN score loss: 0.00997 RPN total loss: 0.03456 Total loss: 1.09424 timestamp: 1654940154.1494002 iteration: 32080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06455 FastRCNN class loss: 0.0377 FastRCNN total loss: 0.10225 L1 loss: 0.0000e+00 L2 loss: 0.77474 Learning rate: 0.02 Mask loss: 0.0908 RPN box loss: 0.06716 RPN score loss: 0.00245 RPN total loss: 0.0696 Total loss: 1.03739 timestamp: 1654940157.2695303 iteration: 32085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15209 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.22504 L1 loss: 0.0000e+00 L2 loss: 0.77463 Learning rate: 0.02 Mask loss: 0.1668 RPN box loss: 0.02274 RPN score loss: 0.00263 RPN total loss: 0.02537 Total loss: 1.19184 timestamp: 1654940160.3985834 iteration: 32090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.21481 L1 loss: 0.0000e+00 L2 loss: 0.77452 Learning rate: 0.02 Mask loss: 0.15923 RPN box loss: 0.06454 RPN score loss: 0.01166 RPN total loss: 0.0762 Total loss: 1.22476 timestamp: 1654940163.5343535 iteration: 32095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12588 FastRCNN class loss: 0.07937 FastRCNN total loss: 0.20525 L1 loss: 0.0000e+00 L2 loss: 0.77441 Learning rate: 0.02 Mask loss: 0.18354 RPN box loss: 0.01581 RPN score loss: 0.00112 RPN total loss: 0.01693 Total loss: 1.18013 timestamp: 1654940166.8160417 iteration: 32100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08984 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.1593 L1 loss: 0.0000e+00 L2 loss: 0.77429 Learning rate: 0.02 Mask loss: 0.10891 RPN box loss: 0.0699 RPN score loss: 0.01409 RPN total loss: 0.08399 Total loss: 1.12649 timestamp: 1654940169.9906344 iteration: 32105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.07389 FastRCNN total loss: 0.18178 L1 loss: 0.0000e+00 L2 loss: 0.77417 Learning rate: 0.02 Mask loss: 0.17285 RPN box loss: 0.04599 RPN score loss: 0.00657 RPN total loss: 0.05255 Total loss: 1.18135 timestamp: 1654940173.2225559 iteration: 32110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15862 FastRCNN class loss: 0.09238 FastRCNN total loss: 0.251 L1 loss: 0.0000e+00 L2 loss: 0.77404 Learning rate: 0.02 Mask loss: 0.11897 RPN box loss: 0.04115 RPN score loss: 0.00694 RPN total loss: 0.04809 Total loss: 1.1921 timestamp: 1654940176.3640995 iteration: 32115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18405 FastRCNN class loss: 0.10937 FastRCNN total loss: 0.29342 L1 loss: 0.0000e+00 L2 loss: 0.77394 Learning rate: 0.02 Mask loss: 0.14375 RPN box loss: 0.02882 RPN score loss: 0.00505 RPN total loss: 0.03387 Total loss: 1.24498 timestamp: 1654940179.6038857 iteration: 32120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12777 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.19292 L1 loss: 0.0000e+00 L2 loss: 0.77388 Learning rate: 0.02 Mask loss: 0.15475 RPN box loss: 0.04232 RPN score loss: 0.00823 RPN total loss: 0.05055 Total loss: 1.17209 timestamp: 1654940182.8667433 iteration: 32125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07482 FastRCNN class loss: 0.09225 FastRCNN total loss: 0.16706 L1 loss: 0.0000e+00 L2 loss: 0.77379 Learning rate: 0.02 Mask loss: 0.12774 RPN box loss: 0.04593 RPN score loss: 0.00838 RPN total loss: 0.05431 Total loss: 1.12291 timestamp: 1654940186.0208106 iteration: 32130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.05107 FastRCNN total loss: 0.16578 L1 loss: 0.0000e+00 L2 loss: 0.77369 Learning rate: 0.02 Mask loss: 0.08916 RPN box loss: 0.02323 RPN score loss: 0.00329 RPN total loss: 0.02652 Total loss: 1.05514 timestamp: 1654940189.243812 iteration: 32135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16434 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.24248 L1 loss: 0.0000e+00 L2 loss: 0.77358 Learning rate: 0.02 Mask loss: 0.14172 RPN box loss: 0.01422 RPN score loss: 0.00463 RPN total loss: 0.01885 Total loss: 1.17663 timestamp: 1654940192.3856235 iteration: 32140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12021 FastRCNN class loss: 0.10111 FastRCNN total loss: 0.22132 L1 loss: 0.0000e+00 L2 loss: 0.77346 Learning rate: 0.02 Mask loss: 0.14569 RPN box loss: 0.01955 RPN score loss: 0.00236 RPN total loss: 0.02192 Total loss: 1.16239 timestamp: 1654940195.6487062 iteration: 32145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21368 FastRCNN class loss: 0.13879 FastRCNN total loss: 0.35247 L1 loss: 0.0000e+00 L2 loss: 0.77332 Learning rate: 0.02 Mask loss: 0.24657 RPN box loss: 0.05998 RPN score loss: 0.02002 RPN total loss: 0.08 Total loss: 1.45237 timestamp: 1654940198.8505807 iteration: 32150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14283 FastRCNN class loss: 0.10668 FastRCNN total loss: 0.24951 L1 loss: 0.0000e+00 L2 loss: 0.77322 Learning rate: 0.02 Mask loss: 0.1459 RPN box loss: 0.04864 RPN score loss: 0.01509 RPN total loss: 0.06373 Total loss: 1.23236 timestamp: 1654940201.983574 iteration: 32155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15352 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.22847 L1 loss: 0.0000e+00 L2 loss: 0.7731 Learning rate: 0.02 Mask loss: 0.15722 RPN box loss: 0.05111 RPN score loss: 0.00342 RPN total loss: 0.05453 Total loss: 1.21333 timestamp: 1654940205.1936524 iteration: 32160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12358 FastRCNN class loss: 0.08439 FastRCNN total loss: 0.20797 L1 loss: 0.0000e+00 L2 loss: 0.77301 Learning rate: 0.02 Mask loss: 0.10268 RPN box loss: 0.02668 RPN score loss: 0.00939 RPN total loss: 0.03607 Total loss: 1.11973 timestamp: 1654940208.4078195 iteration: 32165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13719 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.20328 L1 loss: 0.0000e+00 L2 loss: 0.7729 Learning rate: 0.02 Mask loss: 0.15554 RPN box loss: 0.00672 RPN score loss: 0.008 RPN total loss: 0.01473 Total loss: 1.14645 timestamp: 1654940211.5064745 iteration: 32170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18665 FastRCNN class loss: 0.09485 FastRCNN total loss: 0.28149 L1 loss: 0.0000e+00 L2 loss: 0.77279 Learning rate: 0.02 Mask loss: 0.16315 RPN box loss: 0.05661 RPN score loss: 0.00582 RPN total loss: 0.06243 Total loss: 1.27985 timestamp: 1654940214.6714435 iteration: 32175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07835 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.15078 L1 loss: 0.0000e+00 L2 loss: 0.77269 Learning rate: 0.02 Mask loss: 0.15098 RPN box loss: 0.02642 RPN score loss: 0.00607 RPN total loss: 0.03248 Total loss: 1.10693 timestamp: 1654940217.7790492 iteration: 32180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23195 FastRCNN class loss: 0.16566 FastRCNN total loss: 0.39761 L1 loss: 0.0000e+00 L2 loss: 0.77257 Learning rate: 0.02 Mask loss: 0.14289 RPN box loss: 0.02452 RPN score loss: 0.00786 RPN total loss: 0.03238 Total loss: 1.34546 timestamp: 1654940220.9673023 iteration: 32185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0775 FastRCNN class loss: 0.04534 FastRCNN total loss: 0.12284 L1 loss: 0.0000e+00 L2 loss: 0.77249 Learning rate: 0.02 Mask loss: 0.14507 RPN box loss: 0.02069 RPN score loss: 0.00746 RPN total loss: 0.02816 Total loss: 1.06855 timestamp: 1654940224.1457431 iteration: 32190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15441 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.23678 L1 loss: 0.0000e+00 L2 loss: 0.77236 Learning rate: 0.02 Mask loss: 0.16017 RPN box loss: 0.02018 RPN score loss: 0.00719 RPN total loss: 0.02737 Total loss: 1.19668 timestamp: 1654940227.392742 iteration: 32195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16453 FastRCNN class loss: 0.06791 FastRCNN total loss: 0.23244 L1 loss: 0.0000e+00 L2 loss: 0.77224 Learning rate: 0.02 Mask loss: 0.28066 RPN box loss: 0.01147 RPN score loss: 0.00501 RPN total loss: 0.01648 Total loss: 1.30181 timestamp: 1654940230.6473293 iteration: 32200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10208 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 0.77215 Learning rate: 0.02 Mask loss: 0.11332 RPN box loss: 0.0167 RPN score loss: 0.00409 RPN total loss: 0.02079 Total loss: 1.09802 timestamp: 1654940233.7731576 iteration: 32205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07786 FastRCNN class loss: 0.05087 FastRCNN total loss: 0.12873 L1 loss: 0.0000e+00 L2 loss: 0.77204 Learning rate: 0.02 Mask loss: 0.12142 RPN box loss: 0.02177 RPN score loss: 0.00242 RPN total loss: 0.02419 Total loss: 1.04638 timestamp: 1654940236.9736233 iteration: 32210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14698 FastRCNN class loss: 0.10915 FastRCNN total loss: 0.25613 L1 loss: 0.0000e+00 L2 loss: 0.77195 Learning rate: 0.02 Mask loss: 0.2206 RPN box loss: 0.04714 RPN score loss: 0.01961 RPN total loss: 0.06675 Total loss: 1.31543 timestamp: 1654940240.1481404 iteration: 32215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1522 FastRCNN class loss: 0.1092 FastRCNN total loss: 0.2614 L1 loss: 0.0000e+00 L2 loss: 0.77184 Learning rate: 0.02 Mask loss: 0.16586 RPN box loss: 0.02612 RPN score loss: 0.00865 RPN total loss: 0.03477 Total loss: 1.23387 timestamp: 1654940243.390055 iteration: 32220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15899 FastRCNN class loss: 0.09079 FastRCNN total loss: 0.24977 L1 loss: 0.0000e+00 L2 loss: 0.77174 Learning rate: 0.02 Mask loss: 0.12771 RPN box loss: 0.01538 RPN score loss: 0.00365 RPN total loss: 0.01903 Total loss: 1.16824 timestamp: 1654940246.618423 iteration: 32225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.219 FastRCNN class loss: 0.08652 FastRCNN total loss: 0.30552 L1 loss: 0.0000e+00 L2 loss: 0.77163 Learning rate: 0.02 Mask loss: 0.14228 RPN box loss: 0.04091 RPN score loss: 0.00892 RPN total loss: 0.04983 Total loss: 1.26926 timestamp: 1654940249.750595 iteration: 32230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17651 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.23354 L1 loss: 0.0000e+00 L2 loss: 0.77153 Learning rate: 0.02 Mask loss: 0.13586 RPN box loss: 0.03387 RPN score loss: 0.00749 RPN total loss: 0.04136 Total loss: 1.18229 timestamp: 1654940252.9577265 iteration: 32235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.19173 L1 loss: 0.0000e+00 L2 loss: 0.7714 Learning rate: 0.02 Mask loss: 0.10111 RPN box loss: 0.03144 RPN score loss: 0.00782 RPN total loss: 0.03926 Total loss: 1.1035 timestamp: 1654940256.0911725 iteration: 32240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09711 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.18613 L1 loss: 0.0000e+00 L2 loss: 0.7713 Learning rate: 0.02 Mask loss: 0.19079 RPN box loss: 0.0395 RPN score loss: 0.00473 RPN total loss: 0.04423 Total loss: 1.19245 timestamp: 1654940259.2400033 iteration: 32245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09135 FastRCNN class loss: 0.06576 FastRCNN total loss: 0.15711 L1 loss: 0.0000e+00 L2 loss: 0.77121 Learning rate: 0.02 Mask loss: 0.16749 RPN box loss: 0.01965 RPN score loss: 0.00167 RPN total loss: 0.02131 Total loss: 1.11713 timestamp: 1654940262.4696722 iteration: 32250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15471 FastRCNN class loss: 0.09308 FastRCNN total loss: 0.24779 L1 loss: 0.0000e+00 L2 loss: 0.77109 Learning rate: 0.02 Mask loss: 0.11249 RPN box loss: 0.0937 RPN score loss: 0.00844 RPN total loss: 0.10214 Total loss: 1.23351 timestamp: 1654940265.6139183 iteration: 32255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07216 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.11607 L1 loss: 0.0000e+00 L2 loss: 0.77097 Learning rate: 0.02 Mask loss: 0.12302 RPN box loss: 0.03133 RPN score loss: 0.005 RPN total loss: 0.03633 Total loss: 1.04639 timestamp: 1654940268.809901 iteration: 32260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1371 FastRCNN class loss: 0.11158 FastRCNN total loss: 0.24868 L1 loss: 0.0000e+00 L2 loss: 0.77086 Learning rate: 0.02 Mask loss: 0.20443 RPN box loss: 0.03924 RPN score loss: 0.01032 RPN total loss: 0.04957 Total loss: 1.27352 timestamp: 1654940271.9867146 iteration: 32265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13592 FastRCNN class loss: 0.09393 FastRCNN total loss: 0.22985 L1 loss: 0.0000e+00 L2 loss: 0.77074 Learning rate: 0.02 Mask loss: 0.11974 RPN box loss: 0.07857 RPN score loss: 0.00863 RPN total loss: 0.0872 Total loss: 1.20752 timestamp: 1654940275.204662 iteration: 32270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14725 FastRCNN class loss: 0.06008 FastRCNN total loss: 0.20733 L1 loss: 0.0000e+00 L2 loss: 0.77063 Learning rate: 0.02 Mask loss: 0.13816 RPN box loss: 0.0529 RPN score loss: 0.00499 RPN total loss: 0.05789 Total loss: 1.17401 timestamp: 1654940278.4258893 iteration: 32275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05942 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.12201 L1 loss: 0.0000e+00 L2 loss: 0.77051 Learning rate: 0.02 Mask loss: 0.10721 RPN box loss: 0.03312 RPN score loss: 0.0087 RPN total loss: 0.04182 Total loss: 1.04154 timestamp: 1654940281.6400304 iteration: 32280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10116 FastRCNN class loss: 0.06845 FastRCNN total loss: 0.1696 L1 loss: 0.0000e+00 L2 loss: 0.77041 Learning rate: 0.02 Mask loss: 0.1315 RPN box loss: 0.01829 RPN score loss: 0.00337 RPN total loss: 0.02167 Total loss: 1.09318 timestamp: 1654940284.8291063 iteration: 32285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13749 FastRCNN class loss: 0.11794 FastRCNN total loss: 0.25543 L1 loss: 0.0000e+00 L2 loss: 0.77031 Learning rate: 0.02 Mask loss: 0.15857 RPN box loss: 0.02353 RPN score loss: 0.008 RPN total loss: 0.03153 Total loss: 1.21584 timestamp: 1654940288.0397134 iteration: 32290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15108 FastRCNN class loss: 0.06904 FastRCNN total loss: 0.22012 L1 loss: 0.0000e+00 L2 loss: 0.77019 Learning rate: 0.02 Mask loss: 0.11863 RPN box loss: 0.01428 RPN score loss: 0.00326 RPN total loss: 0.01754 Total loss: 1.12648 timestamp: 1654940291.3045757 iteration: 32295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18978 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.26515 L1 loss: 0.0000e+00 L2 loss: 0.77009 Learning rate: 0.02 Mask loss: 0.16888 RPN box loss: 0.01483 RPN score loss: 0.00409 RPN total loss: 0.01892 Total loss: 1.22304 timestamp: 1654940294.4893768 iteration: 32300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1573 FastRCNN class loss: 0.08113 FastRCNN total loss: 0.23842 L1 loss: 0.0000e+00 L2 loss: 0.76996 Learning rate: 0.02 Mask loss: 0.11908 RPN box loss: 0.00742 RPN score loss: 0.00459 RPN total loss: 0.01201 Total loss: 1.13947 timestamp: 1654940297.6581929 iteration: 32305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11079 FastRCNN class loss: 0.08026 FastRCNN total loss: 0.19105 L1 loss: 0.0000e+00 L2 loss: 0.76988 Learning rate: 0.02 Mask loss: 0.17977 RPN box loss: 0.04882 RPN score loss: 0.00663 RPN total loss: 0.05545 Total loss: 1.19615 timestamp: 1654940300.8151805 iteration: 32310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04689 FastRCNN class loss: 0.05252 FastRCNN total loss: 0.09941 L1 loss: 0.0000e+00 L2 loss: 0.7698 Learning rate: 0.02 Mask loss: 0.09709 RPN box loss: 0.02437 RPN score loss: 0.00617 RPN total loss: 0.03054 Total loss: 0.99684 timestamp: 1654940304.101172 iteration: 32315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10793 FastRCNN class loss: 0.08471 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 0.7697 Learning rate: 0.02 Mask loss: 0.10907 RPN box loss: 0.0362 RPN score loss: 0.00554 RPN total loss: 0.04174 Total loss: 1.11316 timestamp: 1654940307.2714741 iteration: 32320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20739 FastRCNN class loss: 0.08924 FastRCNN total loss: 0.29662 L1 loss: 0.0000e+00 L2 loss: 0.76958 Learning rate: 0.02 Mask loss: 0.15815 RPN box loss: 0.03265 RPN score loss: 0.0158 RPN total loss: 0.04844 Total loss: 1.27279 timestamp: 1654940310.5646105 iteration: 32325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.05517 FastRCNN total loss: 0.16867 L1 loss: 0.0000e+00 L2 loss: 0.76947 Learning rate: 0.02 Mask loss: 0.12796 RPN box loss: 0.01963 RPN score loss: 0.00679 RPN total loss: 0.02642 Total loss: 1.09251 timestamp: 1654940313.7381895 iteration: 32330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08814 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.16172 L1 loss: 0.0000e+00 L2 loss: 0.76938 Learning rate: 0.02 Mask loss: 0.1425 RPN box loss: 0.05376 RPN score loss: 0.00869 RPN total loss: 0.06246 Total loss: 1.13606 timestamp: 1654940316.9377825 iteration: 32335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08832 FastRCNN class loss: 0.04411 FastRCNN total loss: 0.13243 L1 loss: 0.0000e+00 L2 loss: 0.76927 Learning rate: 0.02 Mask loss: 0.13237 RPN box loss: 0.03563 RPN score loss: 0.01 RPN total loss: 0.04564 Total loss: 1.07971 timestamp: 1654940320.030874 iteration: 32340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11854 FastRCNN class loss: 0.07648 FastRCNN total loss: 0.19502 L1 loss: 0.0000e+00 L2 loss: 0.76914 Learning rate: 0.02 Mask loss: 0.10434 RPN box loss: 0.013 RPN score loss: 0.00748 RPN total loss: 0.02048 Total loss: 1.08897 timestamp: 1654940323.2595236 iteration: 32345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12779 FastRCNN class loss: 0.06229 FastRCNN total loss: 0.19007 L1 loss: 0.0000e+00 L2 loss: 0.76903 Learning rate: 0.02 Mask loss: 0.17513 RPN box loss: 0.02926 RPN score loss: 0.00849 RPN total loss: 0.03775 Total loss: 1.17198 timestamp: 1654940326.4969041 iteration: 32350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11847 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.19804 L1 loss: 0.0000e+00 L2 loss: 0.76891 Learning rate: 0.02 Mask loss: 0.11679 RPN box loss: 0.01731 RPN score loss: 0.00708 RPN total loss: 0.02439 Total loss: 1.10813 timestamp: 1654940329.6725817 iteration: 32355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25206 FastRCNN class loss: 0.11602 FastRCNN total loss: 0.36808 L1 loss: 0.0000e+00 L2 loss: 0.7688 Learning rate: 0.02 Mask loss: 0.16275 RPN box loss: 0.03224 RPN score loss: 0.01156 RPN total loss: 0.0438 Total loss: 1.34343 timestamp: 1654940332.9442222 iteration: 32360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.0478 FastRCNN total loss: 0.14492 L1 loss: 0.0000e+00 L2 loss: 0.76869 Learning rate: 0.02 Mask loss: 0.27443 RPN box loss: 0.00728 RPN score loss: 0.00289 RPN total loss: 0.01017 Total loss: 1.19821 timestamp: 1654940336.1556864 iteration: 32365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09291 FastRCNN class loss: 0.0712 FastRCNN total loss: 0.16411 L1 loss: 0.0000e+00 L2 loss: 0.76859 Learning rate: 0.02 Mask loss: 0.11094 RPN box loss: 0.03449 RPN score loss: 0.00671 RPN total loss: 0.0412 Total loss: 1.08485 timestamp: 1654940339.3641367 iteration: 32370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06381 FastRCNN class loss: 0.04975 FastRCNN total loss: 0.11356 L1 loss: 0.0000e+00 L2 loss: 0.76849 Learning rate: 0.02 Mask loss: 0.12919 RPN box loss: 0.01366 RPN score loss: 0.00898 RPN total loss: 0.02264 Total loss: 1.03388 timestamp: 1654940342.5962362 iteration: 32375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13493 FastRCNN class loss: 0.07641 FastRCNN total loss: 0.21134 L1 loss: 0.0000e+00 L2 loss: 0.76837 Learning rate: 0.02 Mask loss: 0.16201 RPN box loss: 0.03129 RPN score loss: 0.00421 RPN total loss: 0.0355 Total loss: 1.17721 timestamp: 1654940345.7346203 iteration: 32380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10684 FastRCNN class loss: 0.07387 FastRCNN total loss: 0.18072 L1 loss: 0.0000e+00 L2 loss: 0.76824 Learning rate: 0.02 Mask loss: 0.09748 RPN box loss: 0.01224 RPN score loss: 0.00362 RPN total loss: 0.01586 Total loss: 1.0623 timestamp: 1654940348.8334486 iteration: 32385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1153 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.198 L1 loss: 0.0000e+00 L2 loss: 0.76813 Learning rate: 0.02 Mask loss: 0.13501 RPN box loss: 0.05202 RPN score loss: 0.00709 RPN total loss: 0.05911 Total loss: 1.16025 timestamp: 1654940351.9876382 iteration: 32390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13989 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.21201 L1 loss: 0.0000e+00 L2 loss: 0.76802 Learning rate: 0.02 Mask loss: 0.12982 RPN box loss: 0.032 RPN score loss: 0.00333 RPN total loss: 0.03533 Total loss: 1.14517 timestamp: 1654940355.246378 iteration: 32395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1214 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.18573 L1 loss: 0.0000e+00 L2 loss: 0.76793 Learning rate: 0.02 Mask loss: 0.11069 RPN box loss: 0.04335 RPN score loss: 0.00435 RPN total loss: 0.04769 Total loss: 1.11205 timestamp: 1654940358.4748232 iteration: 32400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16198 FastRCNN class loss: 0.07867 FastRCNN total loss: 0.24064 L1 loss: 0.0000e+00 L2 loss: 0.76782 Learning rate: 0.02 Mask loss: 0.13682 RPN box loss: 0.06814 RPN score loss: 0.01419 RPN total loss: 0.08233 Total loss: 1.22761 timestamp: 1654940361.7332132 iteration: 32405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22922 FastRCNN class loss: 0.09756 FastRCNN total loss: 0.32678 L1 loss: 0.0000e+00 L2 loss: 0.76771 Learning rate: 0.02 Mask loss: 0.17456 RPN box loss: 0.01011 RPN score loss: 0.00886 RPN total loss: 0.01896 Total loss: 1.28801 timestamp: 1654940364.9334288 iteration: 32410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1089 FastRCNN class loss: 0.09768 FastRCNN total loss: 0.20658 L1 loss: 0.0000e+00 L2 loss: 0.76762 Learning rate: 0.02 Mask loss: 0.16765 RPN box loss: 0.03059 RPN score loss: 0.00561 RPN total loss: 0.03621 Total loss: 1.17806 timestamp: 1654940368.191958 iteration: 32415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11947 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.19265 L1 loss: 0.0000e+00 L2 loss: 0.76747 Learning rate: 0.02 Mask loss: 0.1145 RPN box loss: 0.06479 RPN score loss: 0.00267 RPN total loss: 0.06746 Total loss: 1.14208 timestamp: 1654940371.3434794 iteration: 32420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13363 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.21545 L1 loss: 0.0000e+00 L2 loss: 0.76737 Learning rate: 0.02 Mask loss: 0.16486 RPN box loss: 0.02798 RPN score loss: 0.0209 RPN total loss: 0.04888 Total loss: 1.19656 timestamp: 1654940374.5934448 iteration: 32425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12777 FastRCNN class loss: 0.11036 FastRCNN total loss: 0.23813 L1 loss: 0.0000e+00 L2 loss: 0.76728 Learning rate: 0.02 Mask loss: 0.17308 RPN box loss: 0.06919 RPN score loss: 0.01396 RPN total loss: 0.08315 Total loss: 1.26164 timestamp: 1654940377.8306243 iteration: 32430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15822 FastRCNN class loss: 0.09859 FastRCNN total loss: 0.2568 L1 loss: 0.0000e+00 L2 loss: 0.76717 Learning rate: 0.02 Mask loss: 0.14014 RPN box loss: 0.02428 RPN score loss: 0.00466 RPN total loss: 0.02894 Total loss: 1.19306 timestamp: 1654940381.0289624 iteration: 32435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11261 FastRCNN class loss: 0.05027 FastRCNN total loss: 0.16288 L1 loss: 0.0000e+00 L2 loss: 0.76708 Learning rate: 0.02 Mask loss: 0.11957 RPN box loss: 0.01541 RPN score loss: 0.00404 RPN total loss: 0.01945 Total loss: 1.06898 timestamp: 1654940384.17996 iteration: 32440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15844 FastRCNN class loss: 0.07386 FastRCNN total loss: 0.2323 L1 loss: 0.0000e+00 L2 loss: 0.76699 Learning rate: 0.02 Mask loss: 0.22516 RPN box loss: 0.07977 RPN score loss: 0.00785 RPN total loss: 0.08763 Total loss: 1.31208 timestamp: 1654940387.415779 iteration: 32445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15811 FastRCNN class loss: 0.09565 FastRCNN total loss: 0.25376 L1 loss: 0.0000e+00 L2 loss: 0.76688 Learning rate: 0.02 Mask loss: 0.18411 RPN box loss: 0.03642 RPN score loss: 0.00376 RPN total loss: 0.04017 Total loss: 1.24492 timestamp: 1654940390.634383 iteration: 32450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09535 FastRCNN class loss: 0.08976 FastRCNN total loss: 0.1851 L1 loss: 0.0000e+00 L2 loss: 0.76677 Learning rate: 0.02 Mask loss: 0.15649 RPN box loss: 0.03914 RPN score loss: 0.01653 RPN total loss: 0.05566 Total loss: 1.16404 timestamp: 1654940393.819624 iteration: 32455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11843 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.1879 L1 loss: 0.0000e+00 L2 loss: 0.76666 Learning rate: 0.02 Mask loss: 0.16486 RPN box loss: 0.01727 RPN score loss: 0.00498 RPN total loss: 0.02225 Total loss: 1.14167 timestamp: 1654940397.0412097 iteration: 32460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13635 FastRCNN class loss: 0.08758 FastRCNN total loss: 0.22394 L1 loss: 0.0000e+00 L2 loss: 0.76656 Learning rate: 0.02 Mask loss: 0.23646 RPN box loss: 0.02787 RPN score loss: 0.00707 RPN total loss: 0.03494 Total loss: 1.2619 timestamp: 1654940400.1428578 iteration: 32465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11876 FastRCNN class loss: 0.07283 FastRCNN total loss: 0.19158 L1 loss: 0.0000e+00 L2 loss: 0.76646 Learning rate: 0.02 Mask loss: 0.121 RPN box loss: 0.03425 RPN score loss: 0.00688 RPN total loss: 0.04113 Total loss: 1.12018 timestamp: 1654940403.312102 iteration: 32470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11312 FastRCNN class loss: 0.078 FastRCNN total loss: 0.19112 L1 loss: 0.0000e+00 L2 loss: 0.76638 Learning rate: 0.02 Mask loss: 0.13289 RPN box loss: 0.02646 RPN score loss: 0.00363 RPN total loss: 0.0301 Total loss: 1.12049 timestamp: 1654940406.5139284 iteration: 32475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13568 FastRCNN class loss: 0.08373 FastRCNN total loss: 0.21941 L1 loss: 0.0000e+00 L2 loss: 0.76629 Learning rate: 0.02 Mask loss: 0.17329 RPN box loss: 0.02637 RPN score loss: 0.00318 RPN total loss: 0.02955 Total loss: 1.18854 timestamp: 1654940409.682408 iteration: 32480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11925 FastRCNN class loss: 0.11873 FastRCNN total loss: 0.23799 L1 loss: 0.0000e+00 L2 loss: 0.76617 Learning rate: 0.02 Mask loss: 0.1797 RPN box loss: 0.06794 RPN score loss: 0.00675 RPN total loss: 0.07468 Total loss: 1.25854 timestamp: 1654940412.8804607 iteration: 32485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11479 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.18891 L1 loss: 0.0000e+00 L2 loss: 0.76607 Learning rate: 0.02 Mask loss: 0.10766 RPN box loss: 0.02249 RPN score loss: 0.00412 RPN total loss: 0.02661 Total loss: 1.08925 timestamp: 1654940416.0240211 iteration: 32490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09725 FastRCNN class loss: 0.06659 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 0.76596 Learning rate: 0.02 Mask loss: 0.09093 RPN box loss: 0.0111 RPN score loss: 0.00202 RPN total loss: 0.01311 Total loss: 1.03385 timestamp: 1654940419.1938827 iteration: 32495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.06677 FastRCNN total loss: 0.16135 L1 loss: 0.0000e+00 L2 loss: 0.76585 Learning rate: 0.02 Mask loss: 0.08443 RPN box loss: 0.01349 RPN score loss: 0.00459 RPN total loss: 0.01808 Total loss: 1.0297 timestamp: 1654940422.4123025 iteration: 32500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08996 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 0.76574 Learning rate: 0.02 Mask loss: 0.09089 RPN box loss: 0.08405 RPN score loss: 0.00854 RPN total loss: 0.09259 Total loss: 1.12229 timestamp: 1654940425.7609122 iteration: 32505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17359 FastRCNN class loss: 0.06981 FastRCNN total loss: 0.2434 L1 loss: 0.0000e+00 L2 loss: 0.76565 Learning rate: 0.02 Mask loss: 0.15212 RPN box loss: 0.02645 RPN score loss: 0.00569 RPN total loss: 0.03214 Total loss: 1.19331 timestamp: 1654940429.0187461 iteration: 32510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10894 FastRCNN class loss: 0.0904 FastRCNN total loss: 0.19934 L1 loss: 0.0000e+00 L2 loss: 0.76554 Learning rate: 0.02 Mask loss: 0.14394 RPN box loss: 0.03087 RPN score loss: 0.00337 RPN total loss: 0.03424 Total loss: 1.14305 timestamp: 1654940432.266345 iteration: 32515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15792 FastRCNN class loss: 0.1126 FastRCNN total loss: 0.27052 L1 loss: 0.0000e+00 L2 loss: 0.76543 Learning rate: 0.02 Mask loss: 0.20357 RPN box loss: 0.0656 RPN score loss: 0.01349 RPN total loss: 0.07909 Total loss: 1.31862 timestamp: 1654940435.462398 iteration: 32520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15157 FastRCNN class loss: 0.07766 FastRCNN total loss: 0.22923 L1 loss: 0.0000e+00 L2 loss: 0.76532 Learning rate: 0.02 Mask loss: 0.18329 RPN box loss: 0.04156 RPN score loss: 0.00988 RPN total loss: 0.05144 Total loss: 1.22929 timestamp: 1654940438.7039492 iteration: 32525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.08109 FastRCNN total loss: 0.18649 L1 loss: 0.0000e+00 L2 loss: 0.76521 Learning rate: 0.02 Mask loss: 0.16458 RPN box loss: 0.03305 RPN score loss: 0.00976 RPN total loss: 0.0428 Total loss: 1.15909 timestamp: 1654940441.8611515 iteration: 32530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12732 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.19419 L1 loss: 0.0000e+00 L2 loss: 0.76511 Learning rate: 0.02 Mask loss: 0.11952 RPN box loss: 0.01748 RPN score loss: 0.00428 RPN total loss: 0.02177 Total loss: 1.10059 timestamp: 1654940445.1167362 iteration: 32535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12652 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.1862 L1 loss: 0.0000e+00 L2 loss: 0.765 Learning rate: 0.02 Mask loss: 0.13427 RPN box loss: 0.01482 RPN score loss: 0.01046 RPN total loss: 0.02528 Total loss: 1.11075 timestamp: 1654940448.262944 iteration: 32540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16323 FastRCNN class loss: 0.11131 FastRCNN total loss: 0.27454 L1 loss: 0.0000e+00 L2 loss: 0.76489 Learning rate: 0.02 Mask loss: 0.2219 RPN box loss: 0.02444 RPN score loss: 0.00666 RPN total loss: 0.0311 Total loss: 1.29243 timestamp: 1654940451.4866538 iteration: 32545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0925 FastRCNN class loss: 0.05432 FastRCNN total loss: 0.14683 L1 loss: 0.0000e+00 L2 loss: 0.76478 Learning rate: 0.02 Mask loss: 0.1529 RPN box loss: 0.02156 RPN score loss: 0.00418 RPN total loss: 0.02574 Total loss: 1.09025 timestamp: 1654940454.657533 iteration: 32550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11651 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.19272 L1 loss: 0.0000e+00 L2 loss: 0.76469 Learning rate: 0.02 Mask loss: 0.13968 RPN box loss: 0.01403 RPN score loss: 0.0043 RPN total loss: 0.01832 Total loss: 1.1154 timestamp: 1654940457.9920366 iteration: 32555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17534 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.24761 L1 loss: 0.0000e+00 L2 loss: 0.76456 Learning rate: 0.02 Mask loss: 0.23917 RPN box loss: 0.09144 RPN score loss: 0.00858 RPN total loss: 0.10002 Total loss: 1.35136 timestamp: 1654940461.240845 iteration: 32560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12134 FastRCNN class loss: 0.14514 FastRCNN total loss: 0.26648 L1 loss: 0.0000e+00 L2 loss: 0.76444 Learning rate: 0.02 Mask loss: 0.17141 RPN box loss: 0.04803 RPN score loss: 0.00963 RPN total loss: 0.05766 Total loss: 1.26 timestamp: 1654940464.4563982 iteration: 32565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13179 FastRCNN class loss: 0.09017 FastRCNN total loss: 0.22197 L1 loss: 0.0000e+00 L2 loss: 0.76433 Learning rate: 0.02 Mask loss: 0.13185 RPN box loss: 0.05629 RPN score loss: 0.00705 RPN total loss: 0.06334 Total loss: 1.18149 timestamp: 1654940467.6522012 iteration: 32570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12101 FastRCNN class loss: 0.05115 FastRCNN total loss: 0.17216 L1 loss: 0.0000e+00 L2 loss: 0.76423 Learning rate: 0.02 Mask loss: 0.10187 RPN box loss: 0.01362 RPN score loss: 0.00291 RPN total loss: 0.01653 Total loss: 1.05479 timestamp: 1654940470.9363022 iteration: 32575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11326 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.18092 L1 loss: 0.0000e+00 L2 loss: 0.76412 Learning rate: 0.02 Mask loss: 0.13573 RPN box loss: 0.01914 RPN score loss: 0.00926 RPN total loss: 0.02839 Total loss: 1.10917 timestamp: 1654940474.086981 iteration: 32580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12313 FastRCNN class loss: 0.12727 FastRCNN total loss: 0.25041 L1 loss: 0.0000e+00 L2 loss: 0.76403 Learning rate: 0.02 Mask loss: 0.21262 RPN box loss: 0.04586 RPN score loss: 0.01531 RPN total loss: 0.06116 Total loss: 1.28822 timestamp: 1654940477.2377112 iteration: 32585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11584 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.17008 L1 loss: 0.0000e+00 L2 loss: 0.76392 Learning rate: 0.02 Mask loss: 0.17748 RPN box loss: 0.03179 RPN score loss: 0.00271 RPN total loss: 0.03451 Total loss: 1.14599 timestamp: 1654940480.4558096 iteration: 32590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1439 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.21789 L1 loss: 0.0000e+00 L2 loss: 0.76379 Learning rate: 0.02 Mask loss: 0.10488 RPN box loss: 0.01773 RPN score loss: 0.00319 RPN total loss: 0.02092 Total loss: 1.10748 timestamp: 1654940483.7105434 iteration: 32595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19045 FastRCNN class loss: 0.11725 FastRCNN total loss: 0.3077 L1 loss: 0.0000e+00 L2 loss: 0.76369 Learning rate: 0.02 Mask loss: 0.16257 RPN box loss: 0.08056 RPN score loss: 0.01405 RPN total loss: 0.09461 Total loss: 1.32857 timestamp: 1654940486.989924 iteration: 32600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10693 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.17056 L1 loss: 0.0000e+00 L2 loss: 0.7636 Learning rate: 0.02 Mask loss: 0.19623 RPN box loss: 0.02546 RPN score loss: 0.00574 RPN total loss: 0.0312 Total loss: 1.16158 timestamp: 1654940490.2556372 iteration: 32605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13485 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 0.7635 Learning rate: 0.02 Mask loss: 0.17087 RPN box loss: 0.00872 RPN score loss: 0.00357 RPN total loss: 0.01229 Total loss: 1.13929 timestamp: 1654940493.4379914 iteration: 32610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12623 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.20539 L1 loss: 0.0000e+00 L2 loss: 0.7634 Learning rate: 0.02 Mask loss: 0.09374 RPN box loss: 0.01558 RPN score loss: 0.00318 RPN total loss: 0.01876 Total loss: 1.08128 timestamp: 1654940496.6971612 iteration: 32615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14186 FastRCNN class loss: 0.07802 FastRCNN total loss: 0.21988 L1 loss: 0.0000e+00 L2 loss: 0.76327 Learning rate: 0.02 Mask loss: 0.20169 RPN box loss: 0.01775 RPN score loss: 0.01493 RPN total loss: 0.03268 Total loss: 1.21752 timestamp: 1654940499.869657 iteration: 32620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16412 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.22691 L1 loss: 0.0000e+00 L2 loss: 0.76317 Learning rate: 0.02 Mask loss: 0.26075 RPN box loss: 0.02227 RPN score loss: 0.00768 RPN total loss: 0.02995 Total loss: 1.28078 timestamp: 1654940503.0909073 iteration: 32625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11678 FastRCNN class loss: 0.05468 FastRCNN total loss: 0.17146 L1 loss: 0.0000e+00 L2 loss: 0.76306 Learning rate: 0.02 Mask loss: 0.12384 RPN box loss: 0.01308 RPN score loss: 0.00691 RPN total loss: 0.01999 Total loss: 1.07835 timestamp: 1654940506.208294 iteration: 32630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08095 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.16423 L1 loss: 0.0000e+00 L2 loss: 0.76296 Learning rate: 0.02 Mask loss: 0.11682 RPN box loss: 0.02884 RPN score loss: 0.00943 RPN total loss: 0.03827 Total loss: 1.08227 timestamp: 1654940509.4029033 iteration: 32635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08588 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.15171 L1 loss: 0.0000e+00 L2 loss: 0.76284 Learning rate: 0.02 Mask loss: 0.09084 RPN box loss: 0.00857 RPN score loss: 0.00489 RPN total loss: 0.01346 Total loss: 1.01885 timestamp: 1654940512.6332107 iteration: 32640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17127 FastRCNN class loss: 0.09106 FastRCNN total loss: 0.26234 L1 loss: 0.0000e+00 L2 loss: 0.76272 Learning rate: 0.02 Mask loss: 0.14239 RPN box loss: 0.02774 RPN score loss: 0.00875 RPN total loss: 0.03648 Total loss: 1.20393 timestamp: 1654940515.7677052 iteration: 32645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09877 FastRCNN class loss: 0.0542 FastRCNN total loss: 0.15297 L1 loss: 0.0000e+00 L2 loss: 0.76263 Learning rate: 0.02 Mask loss: 0.09267 RPN box loss: 0.03933 RPN score loss: 0.00608 RPN total loss: 0.0454 Total loss: 1.05368 timestamp: 1654940518.9834518 iteration: 32650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12814 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.20037 L1 loss: 0.0000e+00 L2 loss: 0.76252 Learning rate: 0.02 Mask loss: 0.10023 RPN box loss: 0.01986 RPN score loss: 0.00571 RPN total loss: 0.02557 Total loss: 1.08869 timestamp: 1654940522.1485775 iteration: 32655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11135 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.17901 L1 loss: 0.0000e+00 L2 loss: 0.76241 Learning rate: 0.02 Mask loss: 0.14677 RPN box loss: 0.02331 RPN score loss: 0.00559 RPN total loss: 0.0289 Total loss: 1.11709 timestamp: 1654940525.3335707 iteration: 32660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12344 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.19873 L1 loss: 0.0000e+00 L2 loss: 0.7623 Learning rate: 0.02 Mask loss: 0.14168 RPN box loss: 0.0144 RPN score loss: 0.01073 RPN total loss: 0.02513 Total loss: 1.12785 timestamp: 1654940528.510699 iteration: 32665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18264 FastRCNN class loss: 0.08918 FastRCNN total loss: 0.27182 L1 loss: 0.0000e+00 L2 loss: 0.76218 Learning rate: 0.02 Mask loss: 0.14153 RPN box loss: 0.04471 RPN score loss: 0.00764 RPN total loss: 0.05235 Total loss: 1.22788 timestamp: 1654940531.781043 iteration: 32670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14538 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.21877 L1 loss: 0.0000e+00 L2 loss: 0.76209 Learning rate: 0.02 Mask loss: 0.17268 RPN box loss: 0.0421 RPN score loss: 0.00429 RPN total loss: 0.04639 Total loss: 1.19993 timestamp: 1654940534.9449358 iteration: 32675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12867 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.1956 L1 loss: 0.0000e+00 L2 loss: 0.76197 Learning rate: 0.02 Mask loss: 0.13835 RPN box loss: 0.01342 RPN score loss: 0.0027 RPN total loss: 0.01612 Total loss: 1.11205 timestamp: 1654940538.1190279 iteration: 32680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11704 FastRCNN class loss: 0.08222 FastRCNN total loss: 0.19926 L1 loss: 0.0000e+00 L2 loss: 0.76187 Learning rate: 0.02 Mask loss: 0.20118 RPN box loss: 0.0275 RPN score loss: 0.00572 RPN total loss: 0.03323 Total loss: 1.19553 timestamp: 1654940541.3360624 iteration: 32685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08473 FastRCNN class loss: 0.09696 FastRCNN total loss: 0.18169 L1 loss: 0.0000e+00 L2 loss: 0.76177 Learning rate: 0.02 Mask loss: 0.13001 RPN box loss: 0.0514 RPN score loss: 0.00687 RPN total loss: 0.05827 Total loss: 1.13175 timestamp: 1654940544.5801892 iteration: 32690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.1394 FastRCNN total loss: 0.28681 L1 loss: 0.0000e+00 L2 loss: 0.76167 Learning rate: 0.02 Mask loss: 0.16516 RPN box loss: 0.05872 RPN score loss: 0.01305 RPN total loss: 0.07177 Total loss: 1.2854 timestamp: 1654940547.801847 iteration: 32695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0395 FastRCNN class loss: 0.04594 FastRCNN total loss: 0.08544 L1 loss: 0.0000e+00 L2 loss: 0.76154 Learning rate: 0.02 Mask loss: 0.1674 RPN box loss: 0.03672 RPN score loss: 0.00225 RPN total loss: 0.03897 Total loss: 1.05335 timestamp: 1654940551.0341005 iteration: 32700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12804 FastRCNN class loss: 0.06481 FastRCNN total loss: 0.19285 L1 loss: 0.0000e+00 L2 loss: 0.76142 Learning rate: 0.02 Mask loss: 0.16081 RPN box loss: 0.02806 RPN score loss: 0.00555 RPN total loss: 0.03361 Total loss: 1.14868 timestamp: 1654940554.1921456 iteration: 32705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13955 FastRCNN class loss: 0.09304 FastRCNN total loss: 0.23259 L1 loss: 0.0000e+00 L2 loss: 0.7613 Learning rate: 0.02 Mask loss: 0.13834 RPN box loss: 0.05119 RPN score loss: 0.0065 RPN total loss: 0.05769 Total loss: 1.18991 timestamp: 1654940557.4347646 iteration: 32710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0796 FastRCNN class loss: 0.05204 FastRCNN total loss: 0.13164 L1 loss: 0.0000e+00 L2 loss: 0.7612 Learning rate: 0.02 Mask loss: 0.12352 RPN box loss: 0.02233 RPN score loss: 0.00279 RPN total loss: 0.02513 Total loss: 1.04149 timestamp: 1654940560.658079 iteration: 32715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13336 FastRCNN class loss: 0.13952 FastRCNN total loss: 0.27288 L1 loss: 0.0000e+00 L2 loss: 0.7611 Learning rate: 0.02 Mask loss: 0.11611 RPN box loss: 0.01898 RPN score loss: 0.0055 RPN total loss: 0.02448 Total loss: 1.17456 timestamp: 1654940563.7763 iteration: 32720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14307 FastRCNN class loss: 0.08675 FastRCNN total loss: 0.22981 L1 loss: 0.0000e+00 L2 loss: 0.76099 Learning rate: 0.02 Mask loss: 0.14714 RPN box loss: 0.03024 RPN score loss: 0.01143 RPN total loss: 0.04167 Total loss: 1.17961 timestamp: 1654940566.9924908 iteration: 32725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12437 FastRCNN class loss: 0.09753 FastRCNN total loss: 0.22189 L1 loss: 0.0000e+00 L2 loss: 0.76089 Learning rate: 0.02 Mask loss: 0.19076 RPN box loss: 0.02458 RPN score loss: 0.00962 RPN total loss: 0.0342 Total loss: 1.20774 timestamp: 1654940570.2599359 iteration: 32730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.07424 FastRCNN total loss: 0.18653 L1 loss: 0.0000e+00 L2 loss: 0.7608 Learning rate: 0.02 Mask loss: 0.1106 RPN box loss: 0.01709 RPN score loss: 0.00599 RPN total loss: 0.02308 Total loss: 1.08102 timestamp: 1654940573.5088158 iteration: 32735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09226 FastRCNN class loss: 0.06927 FastRCNN total loss: 0.16153 L1 loss: 0.0000e+00 L2 loss: 0.76069 Learning rate: 0.02 Mask loss: 0.14251 RPN box loss: 0.01226 RPN score loss: 0.0031 RPN total loss: 0.01536 Total loss: 1.08009 timestamp: 1654940576.6619637 iteration: 32740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14713 FastRCNN class loss: 0.0903 FastRCNN total loss: 0.23743 L1 loss: 0.0000e+00 L2 loss: 0.76059 Learning rate: 0.02 Mask loss: 0.17655 RPN box loss: 0.08451 RPN score loss: 0.00346 RPN total loss: 0.08797 Total loss: 1.26254 timestamp: 1654940579.8102064 iteration: 32745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16759 FastRCNN class loss: 0.1065 FastRCNN total loss: 0.27409 L1 loss: 0.0000e+00 L2 loss: 0.76052 Learning rate: 0.02 Mask loss: 0.15386 RPN box loss: 0.1189 RPN score loss: 0.00773 RPN total loss: 0.12663 Total loss: 1.3151 timestamp: 1654940583.0230143 iteration: 32750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16082 FastRCNN class loss: 0.07376 FastRCNN total loss: 0.23458 L1 loss: 0.0000e+00 L2 loss: 0.76041 Learning rate: 0.02 Mask loss: 0.16393 RPN box loss: 0.04268 RPN score loss: 0.00388 RPN total loss: 0.04656 Total loss: 1.20548 timestamp: 1654940586.2459905 iteration: 32755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14269 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.2187 L1 loss: 0.0000e+00 L2 loss: 0.76028 Learning rate: 0.02 Mask loss: 0.24303 RPN box loss: 0.02505 RPN score loss: 0.01263 RPN total loss: 0.03768 Total loss: 1.2597 timestamp: 1654940589.473691 iteration: 32760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1422 FastRCNN class loss: 0.10912 FastRCNN total loss: 0.25132 L1 loss: 0.0000e+00 L2 loss: 0.7602 Learning rate: 0.02 Mask loss: 0.15861 RPN box loss: 0.02718 RPN score loss: 0.0094 RPN total loss: 0.03658 Total loss: 1.20671 timestamp: 1654940592.7239413 iteration: 32765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1586 FastRCNN class loss: 0.09331 FastRCNN total loss: 0.25192 L1 loss: 0.0000e+00 L2 loss: 0.7601 Learning rate: 0.02 Mask loss: 0.17666 RPN box loss: 0.01996 RPN score loss: 0.00465 RPN total loss: 0.02461 Total loss: 1.21328 timestamp: 1654940595.8992634 iteration: 32770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0855 FastRCNN class loss: 0.07306 FastRCNN total loss: 0.15856 L1 loss: 0.0000e+00 L2 loss: 0.76 Learning rate: 0.02 Mask loss: 0.13246 RPN box loss: 0.02289 RPN score loss: 0.00604 RPN total loss: 0.02893 Total loss: 1.07995 timestamp: 1654940599.1378658 iteration: 32775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13222 FastRCNN class loss: 0.14455 FastRCNN total loss: 0.27678 L1 loss: 0.0000e+00 L2 loss: 0.7599 Learning rate: 0.02 Mask loss: 0.16111 RPN box loss: 0.02041 RPN score loss: 0.00783 RPN total loss: 0.02825 Total loss: 1.22603 timestamp: 1654940602.2985108 iteration: 32780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.1501 L1 loss: 0.0000e+00 L2 loss: 0.7598 Learning rate: 0.02 Mask loss: 0.11158 RPN box loss: 0.03956 RPN score loss: 0.00175 RPN total loss: 0.04131 Total loss: 1.06278 timestamp: 1654940605.5246873 iteration: 32785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10883 FastRCNN class loss: 0.07898 FastRCNN total loss: 0.18781 L1 loss: 0.0000e+00 L2 loss: 0.7597 Learning rate: 0.02 Mask loss: 0.14468 RPN box loss: 0.04677 RPN score loss: 0.00325 RPN total loss: 0.05002 Total loss: 1.14222 timestamp: 1654940608.6900163 iteration: 32790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07138 FastRCNN class loss: 0.04936 FastRCNN total loss: 0.12074 L1 loss: 0.0000e+00 L2 loss: 0.75962 Learning rate: 0.02 Mask loss: 0.14399 RPN box loss: 0.01518 RPN score loss: 0.00675 RPN total loss: 0.02193 Total loss: 1.04627 timestamp: 1654940611.8950658 iteration: 32795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12001 FastRCNN class loss: 0.05972 FastRCNN total loss: 0.17972 L1 loss: 0.0000e+00 L2 loss: 0.75953 Learning rate: 0.02 Mask loss: 0.15974 RPN box loss: 0.01057 RPN score loss: 0.00294 RPN total loss: 0.01351 Total loss: 1.1125 timestamp: 1654940615.0468745 iteration: 32800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15709 FastRCNN class loss: 0.0929 FastRCNN total loss: 0.24998 L1 loss: 0.0000e+00 L2 loss: 0.75943 Learning rate: 0.02 Mask loss: 0.17922 RPN box loss: 0.03246 RPN score loss: 0.0031 RPN total loss: 0.03556 Total loss: 1.22418 timestamp: 1654940618.2533972 iteration: 32805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09472 FastRCNN class loss: 0.08095 FastRCNN total loss: 0.17567 L1 loss: 0.0000e+00 L2 loss: 0.75929 Learning rate: 0.02 Mask loss: 0.09873 RPN box loss: 0.01731 RPN score loss: 0.00257 RPN total loss: 0.01989 Total loss: 1.05357 timestamp: 1654940621.4856772 iteration: 32810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11298 FastRCNN class loss: 0.08683 FastRCNN total loss: 0.1998 L1 loss: 0.0000e+00 L2 loss: 0.75917 Learning rate: 0.02 Mask loss: 0.16127 RPN box loss: 0.04851 RPN score loss: 0.00791 RPN total loss: 0.05642 Total loss: 1.17667 timestamp: 1654940624.6993892 iteration: 32815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12373 FastRCNN class loss: 0.06094 FastRCNN total loss: 0.18467 L1 loss: 0.0000e+00 L2 loss: 0.75909 Learning rate: 0.02 Mask loss: 0.15257 RPN box loss: 0.01599 RPN score loss: 0.00319 RPN total loss: 0.01918 Total loss: 1.11551 timestamp: 1654940627.9145749 iteration: 32820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14895 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.22801 L1 loss: 0.0000e+00 L2 loss: 0.75899 Learning rate: 0.02 Mask loss: 0.1223 RPN box loss: 0.02539 RPN score loss: 0.00242 RPN total loss: 0.02782 Total loss: 1.13712 timestamp: 1654940631.1677046 iteration: 32825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12501 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.20099 L1 loss: 0.0000e+00 L2 loss: 0.75887 Learning rate: 0.02 Mask loss: 0.18237 RPN box loss: 0.04089 RPN score loss: 0.01013 RPN total loss: 0.05102 Total loss: 1.19325 timestamp: 1654940634.3779774 iteration: 32830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09777 FastRCNN class loss: 0.07658 FastRCNN total loss: 0.17436 L1 loss: 0.0000e+00 L2 loss: 0.75876 Learning rate: 0.02 Mask loss: 0.18795 RPN box loss: 0.04232 RPN score loss: 0.00391 RPN total loss: 0.04623 Total loss: 1.1673 timestamp: 1654940637.5111501 iteration: 32835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11456 FastRCNN class loss: 0.09324 FastRCNN total loss: 0.2078 L1 loss: 0.0000e+00 L2 loss: 0.75866 Learning rate: 0.02 Mask loss: 0.11298 RPN box loss: 0.02402 RPN score loss: 0.00546 RPN total loss: 0.02948 Total loss: 1.10892 timestamp: 1654940640.743093 iteration: 32840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20593 FastRCNN class loss: 0.11967 FastRCNN total loss: 0.32561 L1 loss: 0.0000e+00 L2 loss: 0.75856 Learning rate: 0.02 Mask loss: 0.17095 RPN box loss: 0.0567 RPN score loss: 0.00951 RPN total loss: 0.06621 Total loss: 1.32132 timestamp: 1654940643.9536824 iteration: 32845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06103 FastRCNN class loss: 0.0586 FastRCNN total loss: 0.11962 L1 loss: 0.0000e+00 L2 loss: 0.75846 Learning rate: 0.02 Mask loss: 0.10592 RPN box loss: 0.04825 RPN score loss: 0.00508 RPN total loss: 0.05333 Total loss: 1.03733 timestamp: 1654940647.09365 iteration: 32850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13197 FastRCNN class loss: 0.0707 FastRCNN total loss: 0.20267 L1 loss: 0.0000e+00 L2 loss: 0.75836 Learning rate: 0.02 Mask loss: 0.12723 RPN box loss: 0.01481 RPN score loss: 0.00671 RPN total loss: 0.02152 Total loss: 1.10978 timestamp: 1654940650.2305946 iteration: 32855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13106 FastRCNN class loss: 0.10015 FastRCNN total loss: 0.23121 L1 loss: 0.0000e+00 L2 loss: 0.75826 Learning rate: 0.02 Mask loss: 0.16551 RPN box loss: 0.04121 RPN score loss: 0.01042 RPN total loss: 0.05163 Total loss: 1.20661 timestamp: 1654940653.4260137 iteration: 32860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14536 FastRCNN class loss: 0.08513 FastRCNN total loss: 0.23048 L1 loss: 0.0000e+00 L2 loss: 0.75817 Learning rate: 0.02 Mask loss: 0.1071 RPN box loss: 0.02528 RPN score loss: 0.00192 RPN total loss: 0.0272 Total loss: 1.12296 timestamp: 1654940656.588988 iteration: 32865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.14036 L1 loss: 0.0000e+00 L2 loss: 0.75807 Learning rate: 0.02 Mask loss: 0.125 RPN box loss: 0.02416 RPN score loss: 0.0017 RPN total loss: 0.02586 Total loss: 1.04928 timestamp: 1654940659.734556 iteration: 32870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1071 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.17098 L1 loss: 0.0000e+00 L2 loss: 0.75796 Learning rate: 0.02 Mask loss: 0.15888 RPN box loss: 0.0485 RPN score loss: 0.00939 RPN total loss: 0.05789 Total loss: 1.1457 timestamp: 1654940662.942883 iteration: 32875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15276 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.23648 L1 loss: 0.0000e+00 L2 loss: 0.75787 Learning rate: 0.02 Mask loss: 0.12592 RPN box loss: 0.03872 RPN score loss: 0.00308 RPN total loss: 0.0418 Total loss: 1.16207 timestamp: 1654940666.1388905 iteration: 32880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09549 FastRCNN class loss: 0.05115 FastRCNN total loss: 0.14664 L1 loss: 0.0000e+00 L2 loss: 0.75775 Learning rate: 0.02 Mask loss: 0.10636 RPN box loss: 0.00866 RPN score loss: 0.00362 RPN total loss: 0.01228 Total loss: 1.02303 timestamp: 1654940669.3636436 iteration: 32885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11969 FastRCNN class loss: 0.05564 FastRCNN total loss: 0.17533 L1 loss: 0.0000e+00 L2 loss: 0.75765 Learning rate: 0.02 Mask loss: 0.1669 RPN box loss: 0.02564 RPN score loss: 0.00615 RPN total loss: 0.03179 Total loss: 1.13166 timestamp: 1654940672.5815148 iteration: 32890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18959 FastRCNN class loss: 0.08996 FastRCNN total loss: 0.27955 L1 loss: 0.0000e+00 L2 loss: 0.75754 Learning rate: 0.02 Mask loss: 0.18913 RPN box loss: 0.02653 RPN score loss: 0.00354 RPN total loss: 0.03007 Total loss: 1.25629 timestamp: 1654940675.7526805 iteration: 32895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1148 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.18493 L1 loss: 0.0000e+00 L2 loss: 0.75745 Learning rate: 0.02 Mask loss: 0.11797 RPN box loss: 0.08934 RPN score loss: 0.01229 RPN total loss: 0.10163 Total loss: 1.16198 timestamp: 1654940678.944504 iteration: 32900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12054 FastRCNN class loss: 0.09185 FastRCNN total loss: 0.21239 L1 loss: 0.0000e+00 L2 loss: 0.75736 Learning rate: 0.02 Mask loss: 0.16122 RPN box loss: 0.06185 RPN score loss: 0.00866 RPN total loss: 0.07051 Total loss: 1.20148 timestamp: 1654940682.1511562 iteration: 32905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15904 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.2294 L1 loss: 0.0000e+00 L2 loss: 0.75723 Learning rate: 0.02 Mask loss: 0.14947 RPN box loss: 0.1158 RPN score loss: 0.01049 RPN total loss: 0.12629 Total loss: 1.2624 timestamp: 1654940685.371893 iteration: 32910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15197 FastRCNN class loss: 0.08354 FastRCNN total loss: 0.23552 L1 loss: 0.0000e+00 L2 loss: 0.75714 Learning rate: 0.02 Mask loss: 0.18578 RPN box loss: 0.04531 RPN score loss: 0.00894 RPN total loss: 0.05425 Total loss: 1.23268 timestamp: 1654940688.601867 iteration: 32915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10322 FastRCNN class loss: 0.03312 FastRCNN total loss: 0.13634 L1 loss: 0.0000e+00 L2 loss: 0.75704 Learning rate: 0.02 Mask loss: 0.11134 RPN box loss: 0.00858 RPN score loss: 0.00287 RPN total loss: 0.01145 Total loss: 1.01618 timestamp: 1654940691.8387554 iteration: 32920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16321 FastRCNN class loss: 0.08892 FastRCNN total loss: 0.25213 L1 loss: 0.0000e+00 L2 loss: 0.7569 Learning rate: 0.02 Mask loss: 0.19214 RPN box loss: 0.03499 RPN score loss: 0.01063 RPN total loss: 0.04561 Total loss: 1.24679 timestamp: 1654940694.9682667 iteration: 32925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17421 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.25494 L1 loss: 0.0000e+00 L2 loss: 0.75679 Learning rate: 0.02 Mask loss: 0.18065 RPN box loss: 0.03512 RPN score loss: 0.00704 RPN total loss: 0.04216 Total loss: 1.23455 timestamp: 1654940698.077997 iteration: 32930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10216 FastRCNN class loss: 0.06341 FastRCNN total loss: 0.16556 L1 loss: 0.0000e+00 L2 loss: 0.75671 Learning rate: 0.02 Mask loss: 0.20331 RPN box loss: 0.05628 RPN score loss: 0.0031 RPN total loss: 0.05938 Total loss: 1.18497 timestamp: 1654940701.2154481 iteration: 32935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1162 FastRCNN class loss: 0.08804 FastRCNN total loss: 0.20424 L1 loss: 0.0000e+00 L2 loss: 0.75661 Learning rate: 0.02 Mask loss: 0.13961 RPN box loss: 0.01941 RPN score loss: 0.00803 RPN total loss: 0.02744 Total loss: 1.1279 timestamp: 1654940704.4406242 iteration: 32940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10466 FastRCNN class loss: 0.04142 FastRCNN total loss: 0.14609 L1 loss: 0.0000e+00 L2 loss: 0.7565 Learning rate: 0.02 Mask loss: 0.29774 RPN box loss: 0.03912 RPN score loss: 0.00241 RPN total loss: 0.04153 Total loss: 1.24186 timestamp: 1654940707.6683102 iteration: 32945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1354 FastRCNN class loss: 0.08373 FastRCNN total loss: 0.21913 L1 loss: 0.0000e+00 L2 loss: 0.75638 Learning rate: 0.02 Mask loss: 0.18101 RPN box loss: 0.03169 RPN score loss: 0.02731 RPN total loss: 0.059 Total loss: 1.21551 timestamp: 1654940710.8839726 iteration: 32950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10313 FastRCNN class loss: 0.06657 FastRCNN total loss: 0.1697 L1 loss: 0.0000e+00 L2 loss: 0.75627 Learning rate: 0.02 Mask loss: 0.11144 RPN box loss: 0.02402 RPN score loss: 0.00574 RPN total loss: 0.02976 Total loss: 1.06717 timestamp: 1654940714.040195 iteration: 32955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15235 FastRCNN class loss: 0.08561 FastRCNN total loss: 0.23796 L1 loss: 0.0000e+00 L2 loss: 0.75619 Learning rate: 0.02 Mask loss: 0.14226 RPN box loss: 0.00611 RPN score loss: 0.00581 RPN total loss: 0.01192 Total loss: 1.14833 timestamp: 1654940717.2100167 iteration: 32960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09468 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.15897 L1 loss: 0.0000e+00 L2 loss: 0.75609 Learning rate: 0.02 Mask loss: 0.11861 RPN box loss: 0.01712 RPN score loss: 0.00218 RPN total loss: 0.01929 Total loss: 1.05297 timestamp: 1654940720.4934657 iteration: 32965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11407 FastRCNN class loss: 0.09364 FastRCNN total loss: 0.20771 L1 loss: 0.0000e+00 L2 loss: 0.75597 Learning rate: 0.02 Mask loss: 0.17723 RPN box loss: 0.02613 RPN score loss: 0.00493 RPN total loss: 0.03105 Total loss: 1.17195 timestamp: 1654940723.6481187 iteration: 32970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17895 FastRCNN class loss: 0.0795 FastRCNN total loss: 0.25846 L1 loss: 0.0000e+00 L2 loss: 0.75587 Learning rate: 0.02 Mask loss: 0.15343 RPN box loss: 0.02623 RPN score loss: 0.00847 RPN total loss: 0.03469 Total loss: 1.20245 timestamp: 1654940726.858131 iteration: 32975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09524 FastRCNN class loss: 0.04899 FastRCNN total loss: 0.14423 L1 loss: 0.0000e+00 L2 loss: 0.75579 Learning rate: 0.02 Mask loss: 0.14098 RPN box loss: 0.00473 RPN score loss: 0.00162 RPN total loss: 0.00635 Total loss: 1.04735 timestamp: 1654940730.041277 iteration: 32980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21627 FastRCNN class loss: 0.08406 FastRCNN total loss: 0.30033 L1 loss: 0.0000e+00 L2 loss: 0.75567 Learning rate: 0.02 Mask loss: 0.20837 RPN box loss: 0.0106 RPN score loss: 0.00432 RPN total loss: 0.01492 Total loss: 1.27928 timestamp: 1654940733.30291 iteration: 32985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08913 FastRCNN class loss: 0.06856 FastRCNN total loss: 0.15769 L1 loss: 0.0000e+00 L2 loss: 0.75554 Learning rate: 0.02 Mask loss: 0.18041 RPN box loss: 0.01222 RPN score loss: 0.0012 RPN total loss: 0.01341 Total loss: 1.10705 timestamp: 1654940736.4741826 iteration: 32990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.07675 FastRCNN total loss: 0.22847 L1 loss: 0.0000e+00 L2 loss: 0.75543 Learning rate: 0.02 Mask loss: 0.15254 RPN box loss: 0.03467 RPN score loss: 0.00255 RPN total loss: 0.03723 Total loss: 1.17367 timestamp: 1654940739.6700985 iteration: 32995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08587 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.14615 L1 loss: 0.0000e+00 L2 loss: 0.75534 Learning rate: 0.02 Mask loss: 0.10967 RPN box loss: 0.08418 RPN score loss: 0.0044 RPN total loss: 0.08858 Total loss: 1.09974 timestamp: 1654940742.8470473 iteration: 33000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12267 FastRCNN class loss: 0.11085 FastRCNN total loss: 0.23353 L1 loss: 0.0000e+00 L2 loss: 0.75525 Learning rate: 0.02 Mask loss: 0.1543 RPN box loss: 0.01618 RPN score loss: 0.00766 RPN total loss: 0.02384 Total loss: 1.16692 timestamp: 1654940746.010932 iteration: 33005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11713 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.19679 L1 loss: 0.0000e+00 L2 loss: 0.75514 Learning rate: 0.02 Mask loss: 0.18724 RPN box loss: 0.01141 RPN score loss: 0.00787 RPN total loss: 0.01928 Total loss: 1.15845 timestamp: 1654940749.2229779 iteration: 33010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14261 FastRCNN class loss: 0.15399 FastRCNN total loss: 0.2966 L1 loss: 0.0000e+00 L2 loss: 0.75502 Learning rate: 0.02 Mask loss: 0.31125 RPN box loss: 0.03153 RPN score loss: 0.01186 RPN total loss: 0.04338 Total loss: 1.40626 timestamp: 1654940752.4301023 iteration: 33015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17058 FastRCNN class loss: 0.10349 FastRCNN total loss: 0.27407 L1 loss: 0.0000e+00 L2 loss: 0.75493 Learning rate: 0.02 Mask loss: 0.16195 RPN box loss: 0.03092 RPN score loss: 0.00541 RPN total loss: 0.03633 Total loss: 1.22728 timestamp: 1654940755.597151 iteration: 33020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.05 FastRCNN total loss: 0.13951 L1 loss: 0.0000e+00 L2 loss: 0.75482 Learning rate: 0.02 Mask loss: 0.11636 RPN box loss: 0.01266 RPN score loss: 0.00421 RPN total loss: 0.01687 Total loss: 1.02756 timestamp: 1654940758.7867486 iteration: 33025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20371 FastRCNN class loss: 0.08783 FastRCNN total loss: 0.29154 L1 loss: 0.0000e+00 L2 loss: 0.7547 Learning rate: 0.02 Mask loss: 0.14582 RPN box loss: 0.04085 RPN score loss: 0.00458 RPN total loss: 0.04542 Total loss: 1.23749 timestamp: 1654940761.9705813 iteration: 33030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08806 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.1378 L1 loss: 0.0000e+00 L2 loss: 0.75462 Learning rate: 0.02 Mask loss: 0.14531 RPN box loss: 0.03178 RPN score loss: 0.00781 RPN total loss: 0.0396 Total loss: 1.07733 timestamp: 1654940765.2025545 iteration: 33035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10806 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.16688 L1 loss: 0.0000e+00 L2 loss: 0.75453 Learning rate: 0.02 Mask loss: 0.1256 RPN box loss: 0.00703 RPN score loss: 0.00379 RPN total loss: 0.01082 Total loss: 1.05783 timestamp: 1654940768.3384807 iteration: 33040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16048 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.22307 L1 loss: 0.0000e+00 L2 loss: 0.75442 Learning rate: 0.02 Mask loss: 0.14543 RPN box loss: 0.07453 RPN score loss: 0.00579 RPN total loss: 0.08032 Total loss: 1.20324 timestamp: 1654940771.5897946 iteration: 33045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26767 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.34592 L1 loss: 0.0000e+00 L2 loss: 0.75427 Learning rate: 0.02 Mask loss: 0.14313 RPN box loss: 0.04987 RPN score loss: 0.00393 RPN total loss: 0.05379 Total loss: 1.29712 timestamp: 1654940774.788867 iteration: 33050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14484 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.23304 L1 loss: 0.0000e+00 L2 loss: 0.75417 Learning rate: 0.02 Mask loss: 0.17114 RPN box loss: 0.03886 RPN score loss: 0.01115 RPN total loss: 0.05001 Total loss: 1.20836 timestamp: 1654940778.0156465 iteration: 33055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08276 FastRCNN class loss: 0.05449 FastRCNN total loss: 0.13725 L1 loss: 0.0000e+00 L2 loss: 0.75406 Learning rate: 0.02 Mask loss: 0.12104 RPN box loss: 0.0152 RPN score loss: 0.01664 RPN total loss: 0.03184 Total loss: 1.04418 timestamp: 1654940781.2356603 iteration: 33060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16397 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.24768 L1 loss: 0.0000e+00 L2 loss: 0.75396 Learning rate: 0.02 Mask loss: 0.13591 RPN box loss: 0.02495 RPN score loss: 0.01035 RPN total loss: 0.0353 Total loss: 1.17285 timestamp: 1654940784.4516137 iteration: 33065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14034 FastRCNN class loss: 0.07714 FastRCNN total loss: 0.21748 L1 loss: 0.0000e+00 L2 loss: 0.75389 Learning rate: 0.02 Mask loss: 0.14539 RPN box loss: 0.01379 RPN score loss: 0.00548 RPN total loss: 0.01927 Total loss: 1.13603 timestamp: 1654940787.6216242 iteration: 33070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16154 FastRCNN class loss: 0.09463 FastRCNN total loss: 0.25617 L1 loss: 0.0000e+00 L2 loss: 0.75378 Learning rate: 0.02 Mask loss: 0.21064 RPN box loss: 0.05537 RPN score loss: 0.00897 RPN total loss: 0.06434 Total loss: 1.28493 timestamp: 1654940790.8297276 iteration: 33075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11922 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.20326 L1 loss: 0.0000e+00 L2 loss: 0.75369 Learning rate: 0.02 Mask loss: 0.1264 RPN box loss: 0.0469 RPN score loss: 0.00664 RPN total loss: 0.05354 Total loss: 1.13688 timestamp: 1654940794.0539105 iteration: 33080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13496 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.19327 L1 loss: 0.0000e+00 L2 loss: 0.7536 Learning rate: 0.02 Mask loss: 0.1561 RPN box loss: 0.04455 RPN score loss: 0.00271 RPN total loss: 0.04726 Total loss: 1.15024 timestamp: 1654940797.2477078 iteration: 33085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12778 FastRCNN class loss: 0.07682 FastRCNN total loss: 0.2046 L1 loss: 0.0000e+00 L2 loss: 0.75349 Learning rate: 0.02 Mask loss: 0.14302 RPN box loss: 0.03957 RPN score loss: 0.00708 RPN total loss: 0.04665 Total loss: 1.14776 timestamp: 1654940800.5129204 iteration: 33090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08436 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.14285 L1 loss: 0.0000e+00 L2 loss: 0.75341 Learning rate: 0.02 Mask loss: 0.14318 RPN box loss: 0.0325 RPN score loss: 0.00315 RPN total loss: 0.03564 Total loss: 1.07508 timestamp: 1654940803.7322292 iteration: 33095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13467 FastRCNN class loss: 0.10341 FastRCNN total loss: 0.23808 L1 loss: 0.0000e+00 L2 loss: 0.75331 Learning rate: 0.02 Mask loss: 0.2604 RPN box loss: 0.03526 RPN score loss: 0.00989 RPN total loss: 0.04515 Total loss: 1.29694 timestamp: 1654940806.99043 iteration: 33100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07352 FastRCNN class loss: 0.08731 FastRCNN total loss: 0.16083 L1 loss: 0.0000e+00 L2 loss: 0.75318 Learning rate: 0.02 Mask loss: 0.18014 RPN box loss: 0.03439 RPN score loss: 0.02686 RPN total loss: 0.06125 Total loss: 1.1554 timestamp: 1654940810.1735816 iteration: 33105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13989 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.23595 L1 loss: 0.0000e+00 L2 loss: 0.75307 Learning rate: 0.02 Mask loss: 0.15342 RPN box loss: 0.06799 RPN score loss: 0.01578 RPN total loss: 0.08377 Total loss: 1.2262 timestamp: 1654940813.4691725 iteration: 33110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20094 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.30117 L1 loss: 0.0000e+00 L2 loss: 0.75296 Learning rate: 0.02 Mask loss: 0.15214 RPN box loss: 0.04262 RPN score loss: 0.00576 RPN total loss: 0.04838 Total loss: 1.25465 timestamp: 1654940816.6807601 iteration: 33115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14344 FastRCNN class loss: 0.06776 FastRCNN total loss: 0.2112 L1 loss: 0.0000e+00 L2 loss: 0.75287 Learning rate: 0.02 Mask loss: 0.1426 RPN box loss: 0.06742 RPN score loss: 0.00939 RPN total loss: 0.07682 Total loss: 1.18348 timestamp: 1654940819.9416063 iteration: 33120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13544 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.20654 L1 loss: 0.0000e+00 L2 loss: 0.75276 Learning rate: 0.02 Mask loss: 0.13843 RPN box loss: 0.0432 RPN score loss: 0.01227 RPN total loss: 0.05547 Total loss: 1.1532 timestamp: 1654940823.0880473 iteration: 33125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08918 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.16364 L1 loss: 0.0000e+00 L2 loss: 0.75266 Learning rate: 0.02 Mask loss: 0.09799 RPN box loss: 0.04569 RPN score loss: 0.00229 RPN total loss: 0.04798 Total loss: 1.06227 timestamp: 1654940826.3512385 iteration: 33130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05802 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.10073 L1 loss: 0.0000e+00 L2 loss: 0.75256 Learning rate: 0.02 Mask loss: 0.09403 RPN box loss: 0.02978 RPN score loss: 0.00078 RPN total loss: 0.03056 Total loss: 0.97788 timestamp: 1654940829.5333312 iteration: 33135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12874 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.19021 L1 loss: 0.0000e+00 L2 loss: 0.75246 Learning rate: 0.02 Mask loss: 0.17736 RPN box loss: 0.03132 RPN score loss: 0.01238 RPN total loss: 0.04371 Total loss: 1.16373 timestamp: 1654940832.6726282 iteration: 33140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12554 FastRCNN class loss: 0.09953 FastRCNN total loss: 0.22507 L1 loss: 0.0000e+00 L2 loss: 0.75237 Learning rate: 0.02 Mask loss: 0.17754 RPN box loss: 0.03579 RPN score loss: 0.01515 RPN total loss: 0.05094 Total loss: 1.20592 timestamp: 1654940835.8603547 iteration: 33145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1926 FastRCNN class loss: 0.1294 FastRCNN total loss: 0.322 L1 loss: 0.0000e+00 L2 loss: 0.75226 Learning rate: 0.02 Mask loss: 0.21741 RPN box loss: 0.04824 RPN score loss: 0.00837 RPN total loss: 0.05661 Total loss: 1.34828 timestamp: 1654940839.10657 iteration: 33150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14559 FastRCNN class loss: 0.13019 FastRCNN total loss: 0.27578 L1 loss: 0.0000e+00 L2 loss: 0.75216 Learning rate: 0.02 Mask loss: 0.16005 RPN box loss: 0.05566 RPN score loss: 0.00842 RPN total loss: 0.06408 Total loss: 1.25207 timestamp: 1654940842.2823408 iteration: 33155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1145 FastRCNN class loss: 0.09398 FastRCNN total loss: 0.20848 L1 loss: 0.0000e+00 L2 loss: 0.75209 Learning rate: 0.02 Mask loss: 0.13493 RPN box loss: 0.03443 RPN score loss: 0.00562 RPN total loss: 0.04005 Total loss: 1.13556 timestamp: 1654940845.4521031 iteration: 33160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09439 FastRCNN class loss: 0.11595 FastRCNN total loss: 0.21034 L1 loss: 0.0000e+00 L2 loss: 0.752 Learning rate: 0.02 Mask loss: 0.16216 RPN box loss: 0.04937 RPN score loss: 0.0125 RPN total loss: 0.06187 Total loss: 1.18637 timestamp: 1654940848.6032598 iteration: 33165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17197 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.25109 L1 loss: 0.0000e+00 L2 loss: 0.7519 Learning rate: 0.02 Mask loss: 0.16131 RPN box loss: 0.03779 RPN score loss: 0.00711 RPN total loss: 0.0449 Total loss: 1.2092 timestamp: 1654940851.7881656 iteration: 33170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13725 FastRCNN class loss: 0.11922 FastRCNN total loss: 0.25648 L1 loss: 0.0000e+00 L2 loss: 0.75179 Learning rate: 0.02 Mask loss: 0.13888 RPN box loss: 0.0576 RPN score loss: 0.02074 RPN total loss: 0.07834 Total loss: 1.22548 timestamp: 1654940854.9895563 iteration: 33175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11953 FastRCNN class loss: 0.09352 FastRCNN total loss: 0.21305 L1 loss: 0.0000e+00 L2 loss: 0.7517 Learning rate: 0.02 Mask loss: 0.16563 RPN box loss: 0.03523 RPN score loss: 0.01244 RPN total loss: 0.04766 Total loss: 1.17804 timestamp: 1654940858.141606 iteration: 33180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12759 FastRCNN class loss: 0.11658 FastRCNN total loss: 0.24417 L1 loss: 0.0000e+00 L2 loss: 0.7516 Learning rate: 0.02 Mask loss: 0.20381 RPN box loss: 0.03494 RPN score loss: 0.00787 RPN total loss: 0.04282 Total loss: 1.2424 timestamp: 1654940861.3059747 iteration: 33185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10205 FastRCNN class loss: 0.11312 FastRCNN total loss: 0.21517 L1 loss: 0.0000e+00 L2 loss: 0.75149 Learning rate: 0.02 Mask loss: 0.17048 RPN box loss: 0.03429 RPN score loss: 0.01267 RPN total loss: 0.04696 Total loss: 1.1841 timestamp: 1654940864.4457667 iteration: 33190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17617 FastRCNN class loss: 0.13923 FastRCNN total loss: 0.3154 L1 loss: 0.0000e+00 L2 loss: 0.75138 Learning rate: 0.02 Mask loss: 0.20244 RPN box loss: 0.05316 RPN score loss: 0.02201 RPN total loss: 0.07517 Total loss: 1.34438 timestamp: 1654940867.6746073 iteration: 33195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14091 FastRCNN class loss: 0.09269 FastRCNN total loss: 0.2336 L1 loss: 0.0000e+00 L2 loss: 0.75127 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.00901 RPN score loss: 0.00161 RPN total loss: 0.01062 Total loss: 1.14792 timestamp: 1654940870.8285081 iteration: 33200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15815 FastRCNN class loss: 0.0854 FastRCNN total loss: 0.24355 L1 loss: 0.0000e+00 L2 loss: 0.75118 Learning rate: 0.02 Mask loss: 0.1747 RPN box loss: 0.06065 RPN score loss: 0.00509 RPN total loss: 0.06574 Total loss: 1.23516 timestamp: 1654940873.9813898 iteration: 33205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1366 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.20894 L1 loss: 0.0000e+00 L2 loss: 0.75108 Learning rate: 0.02 Mask loss: 0.18277 RPN box loss: 0.0281 RPN score loss: 0.00571 RPN total loss: 0.0338 Total loss: 1.17659 timestamp: 1654940877.1901183 iteration: 33210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10162 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.16068 L1 loss: 0.0000e+00 L2 loss: 0.75098 Learning rate: 0.02 Mask loss: 0.11351 RPN box loss: 0.00458 RPN score loss: 0.00234 RPN total loss: 0.00692 Total loss: 1.03209 timestamp: 1654940880.32907 iteration: 33215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18675 FastRCNN class loss: 0.10806 FastRCNN total loss: 0.2948 L1 loss: 0.0000e+00 L2 loss: 0.75086 Learning rate: 0.02 Mask loss: 0.15862 RPN box loss: 0.0315 RPN score loss: 0.00308 RPN total loss: 0.03458 Total loss: 1.23887 timestamp: 1654940883.4681554 iteration: 33220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17338 FastRCNN class loss: 0.10542 FastRCNN total loss: 0.2788 L1 loss: 0.0000e+00 L2 loss: 0.75076 Learning rate: 0.02 Mask loss: 0.21687 RPN box loss: 0.04606 RPN score loss: 0.00752 RPN total loss: 0.05358 Total loss: 1.30001 timestamp: 1654940886.7637172 iteration: 33225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08579 FastRCNN class loss: 0.04197 FastRCNN total loss: 0.12777 L1 loss: 0.0000e+00 L2 loss: 0.75064 Learning rate: 0.02 Mask loss: 0.17663 RPN box loss: 0.01783 RPN score loss: 0.00289 RPN total loss: 0.02072 Total loss: 1.07576 timestamp: 1654940889.9694386 iteration: 33230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12101 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.20226 L1 loss: 0.0000e+00 L2 loss: 0.75053 Learning rate: 0.02 Mask loss: 0.09125 RPN box loss: 0.01746 RPN score loss: 0.00329 RPN total loss: 0.02076 Total loss: 1.0648 timestamp: 1654940893.2105145 iteration: 33235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10212 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.19353 L1 loss: 0.0000e+00 L2 loss: 0.75045 Learning rate: 0.02 Mask loss: 0.20119 RPN box loss: 0.03836 RPN score loss: 0.00631 RPN total loss: 0.04467 Total loss: 1.18983 timestamp: 1654940896.433662 iteration: 33240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17055 FastRCNN class loss: 0.10838 FastRCNN total loss: 0.27892 L1 loss: 0.0000e+00 L2 loss: 0.75033 Learning rate: 0.02 Mask loss: 0.23217 RPN box loss: 0.0414 RPN score loss: 0.00859 RPN total loss: 0.04999 Total loss: 1.31142 timestamp: 1654940899.6092548 iteration: 33245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11788 FastRCNN class loss: 0.08743 FastRCNN total loss: 0.20531 L1 loss: 0.0000e+00 L2 loss: 0.75022 Learning rate: 0.02 Mask loss: 0.13509 RPN box loss: 0.02898 RPN score loss: 0.01129 RPN total loss: 0.04027 Total loss: 1.13089 timestamp: 1654940902.8199975 iteration: 33250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14985 FastRCNN class loss: 0.09001 FastRCNN total loss: 0.23986 L1 loss: 0.0000e+00 L2 loss: 0.75014 Learning rate: 0.02 Mask loss: 0.13687 RPN box loss: 0.02657 RPN score loss: 0.00736 RPN total loss: 0.03392 Total loss: 1.16079 timestamp: 1654940905.9661381 iteration: 33255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17791 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.26355 L1 loss: 0.0000e+00 L2 loss: 0.75003 Learning rate: 0.02 Mask loss: 0.1549 RPN box loss: 0.01875 RPN score loss: 0.00788 RPN total loss: 0.02663 Total loss: 1.19512 timestamp: 1654940909.1215339 iteration: 33260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06434 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.13824 L1 loss: 0.0000e+00 L2 loss: 0.74993 Learning rate: 0.02 Mask loss: 0.0967 RPN box loss: 0.03706 RPN score loss: 0.00794 RPN total loss: 0.045 Total loss: 1.02987 timestamp: 1654940912.274361 iteration: 33265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.06365 FastRCNN total loss: 0.14174 L1 loss: 0.0000e+00 L2 loss: 0.74982 Learning rate: 0.02 Mask loss: 0.11666 RPN box loss: 0.01289 RPN score loss: 0.00432 RPN total loss: 0.01721 Total loss: 1.02544 timestamp: 1654940915.4721258 iteration: 33270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12366 FastRCNN class loss: 0.09146 FastRCNN total loss: 0.21512 L1 loss: 0.0000e+00 L2 loss: 0.74973 Learning rate: 0.02 Mask loss: 0.18359 RPN box loss: 0.02316 RPN score loss: 0.01177 RPN total loss: 0.03493 Total loss: 1.18338 timestamp: 1654940918.6334116 iteration: 33275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19072 FastRCNN class loss: 0.09764 FastRCNN total loss: 0.28836 L1 loss: 0.0000e+00 L2 loss: 0.74964 Learning rate: 0.02 Mask loss: 0.189 RPN box loss: 0.03992 RPN score loss: 0.0122 RPN total loss: 0.05212 Total loss: 1.27912 timestamp: 1654940921.8291214 iteration: 33280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11289 FastRCNN class loss: 0.04891 FastRCNN total loss: 0.1618 L1 loss: 0.0000e+00 L2 loss: 0.74954 Learning rate: 0.02 Mask loss: 0.10202 RPN box loss: 0.02422 RPN score loss: 0.00251 RPN total loss: 0.02673 Total loss: 1.04009 timestamp: 1654940925.1016262 iteration: 33285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13885 FastRCNN class loss: 0.09682 FastRCNN total loss: 0.23567 L1 loss: 0.0000e+00 L2 loss: 0.74944 Learning rate: 0.02 Mask loss: 0.17447 RPN box loss: 0.0631 RPN score loss: 0.00748 RPN total loss: 0.07059 Total loss: 1.23016 timestamp: 1654940928.3006217 iteration: 33290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0962 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.16295 L1 loss: 0.0000e+00 L2 loss: 0.74929 Learning rate: 0.02 Mask loss: 0.13896 RPN box loss: 0.03892 RPN score loss: 0.01176 RPN total loss: 0.05068 Total loss: 1.10189 timestamp: 1654940931.52843 iteration: 33295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14638 FastRCNN class loss: 0.11783 FastRCNN total loss: 0.26422 L1 loss: 0.0000e+00 L2 loss: 0.7492 Learning rate: 0.02 Mask loss: 0.14991 RPN box loss: 0.02359 RPN score loss: 0.0023 RPN total loss: 0.02589 Total loss: 1.18922 timestamp: 1654940934.7691846 iteration: 33300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14168 FastRCNN class loss: 0.0964 FastRCNN total loss: 0.23808 L1 loss: 0.0000e+00 L2 loss: 0.74911 Learning rate: 0.02 Mask loss: 0.10729 RPN box loss: 0.03921 RPN score loss: 0.00726 RPN total loss: 0.04646 Total loss: 1.14094 timestamp: 1654940938.0140562 iteration: 33305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12796 FastRCNN class loss: 0.11623 FastRCNN total loss: 0.24419 L1 loss: 0.0000e+00 L2 loss: 0.749 Learning rate: 0.02 Mask loss: 0.14828 RPN box loss: 0.01729 RPN score loss: 0.00499 RPN total loss: 0.02228 Total loss: 1.16374 timestamp: 1654940941.152351 iteration: 33310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16089 FastRCNN class loss: 0.09407 FastRCNN total loss: 0.25495 L1 loss: 0.0000e+00 L2 loss: 0.74889 Learning rate: 0.02 Mask loss: 0.21462 RPN box loss: 0.03559 RPN score loss: 0.00578 RPN total loss: 0.04137 Total loss: 1.25983 timestamp: 1654940944.3746855 iteration: 33315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16522 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.26577 L1 loss: 0.0000e+00 L2 loss: 0.74879 Learning rate: 0.02 Mask loss: 0.19012 RPN box loss: 0.03237 RPN score loss: 0.00426 RPN total loss: 0.03663 Total loss: 1.24131 timestamp: 1654940947.5820234 iteration: 33320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15809 FastRCNN class loss: 0.10977 FastRCNN total loss: 0.26786 L1 loss: 0.0000e+00 L2 loss: 0.74869 Learning rate: 0.02 Mask loss: 0.17751 RPN box loss: 0.005 RPN score loss: 0.00405 RPN total loss: 0.00905 Total loss: 1.20311 timestamp: 1654940950.7159512 iteration: 33325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12067 FastRCNN class loss: 0.08579 FastRCNN total loss: 0.20645 L1 loss: 0.0000e+00 L2 loss: 0.74858 Learning rate: 0.02 Mask loss: 0.1828 RPN box loss: 0.00566 RPN score loss: 0.00225 RPN total loss: 0.00791 Total loss: 1.14575 timestamp: 1654940953.907926 iteration: 33330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2004 FastRCNN class loss: 0.09398 FastRCNN total loss: 0.29438 L1 loss: 0.0000e+00 L2 loss: 0.74849 Learning rate: 0.02 Mask loss: 0.13155 RPN box loss: 0.048 RPN score loss: 0.00493 RPN total loss: 0.05293 Total loss: 1.22734 timestamp: 1654940957.0895743 iteration: 33335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16605 FastRCNN class loss: 0.11609 FastRCNN total loss: 0.28215 L1 loss: 0.0000e+00 L2 loss: 0.74838 Learning rate: 0.02 Mask loss: 0.15932 RPN box loss: 0.02376 RPN score loss: 0.00844 RPN total loss: 0.0322 Total loss: 1.22205 timestamp: 1654940960.2993376 iteration: 33340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08754 FastRCNN class loss: 0.05738 FastRCNN total loss: 0.14492 L1 loss: 0.0000e+00 L2 loss: 0.74828 Learning rate: 0.02 Mask loss: 0.10513 RPN box loss: 0.0106 RPN score loss: 0.00507 RPN total loss: 0.01567 Total loss: 1.01401 timestamp: 1654940963.4881744 iteration: 33345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18175 FastRCNN class loss: 0.08177 FastRCNN total loss: 0.26352 L1 loss: 0.0000e+00 L2 loss: 0.74821 Learning rate: 0.02 Mask loss: 0.16191 RPN box loss: 0.00977 RPN score loss: 0.00375 RPN total loss: 0.01352 Total loss: 1.18716 timestamp: 1654940966.6106217 iteration: 33350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12366 FastRCNN class loss: 0.09045 FastRCNN total loss: 0.21411 L1 loss: 0.0000e+00 L2 loss: 0.74812 Learning rate: 0.02 Mask loss: 0.16161 RPN box loss: 0.02843 RPN score loss: 0.00978 RPN total loss: 0.03821 Total loss: 1.16205 timestamp: 1654940969.813824 iteration: 33355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13088 FastRCNN class loss: 0.07888 FastRCNN total loss: 0.20977 L1 loss: 0.0000e+00 L2 loss: 0.74804 Learning rate: 0.02 Mask loss: 0.2523 RPN box loss: 0.06085 RPN score loss: 0.01259 RPN total loss: 0.07344 Total loss: 1.28355 timestamp: 1654940973.014527 iteration: 33360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10337 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.19236 L1 loss: 0.0000e+00 L2 loss: 0.74795 Learning rate: 0.02 Mask loss: 0.12663 RPN box loss: 0.04991 RPN score loss: 0.00901 RPN total loss: 0.05893 Total loss: 1.12586 timestamp: 1654940976.160951 iteration: 33365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.12231 FastRCNN total loss: 0.25093 L1 loss: 0.0000e+00 L2 loss: 0.74785 Learning rate: 0.02 Mask loss: 0.19571 RPN box loss: 0.03026 RPN score loss: 0.00966 RPN total loss: 0.03992 Total loss: 1.2344 timestamp: 1654940979.3297105 iteration: 33370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15526 FastRCNN class loss: 0.12864 FastRCNN total loss: 0.2839 L1 loss: 0.0000e+00 L2 loss: 0.74774 Learning rate: 0.02 Mask loss: 0.21682 RPN box loss: 0.02993 RPN score loss: 0.0109 RPN total loss: 0.04083 Total loss: 1.28929 timestamp: 1654940982.529358 iteration: 33375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.14852 L1 loss: 0.0000e+00 L2 loss: 0.74763 Learning rate: 0.02 Mask loss: 0.09736 RPN box loss: 0.03469 RPN score loss: 0.00362 RPN total loss: 0.03831 Total loss: 1.03182 timestamp: 1654940985.6639895 iteration: 33380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12891 FastRCNN class loss: 0.05291 FastRCNN total loss: 0.18182 L1 loss: 0.0000e+00 L2 loss: 0.74753 Learning rate: 0.02 Mask loss: 0.14504 RPN box loss: 0.00979 RPN score loss: 0.00131 RPN total loss: 0.0111 Total loss: 1.08549 timestamp: 1654940988.8463736 iteration: 33385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11578 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.18707 L1 loss: 0.0000e+00 L2 loss: 0.74744 Learning rate: 0.02 Mask loss: 0.11812 RPN box loss: 0.02097 RPN score loss: 0.00314 RPN total loss: 0.02411 Total loss: 1.07676 timestamp: 1654940992.018101 iteration: 33390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15528 FastRCNN class loss: 0.09126 FastRCNN total loss: 0.24654 L1 loss: 0.0000e+00 L2 loss: 0.74734 Learning rate: 0.02 Mask loss: 0.14994 RPN box loss: 0.03009 RPN score loss: 0.00955 RPN total loss: 0.03965 Total loss: 1.18347 timestamp: 1654940995.1615803 iteration: 33395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19296 FastRCNN class loss: 0.0986 FastRCNN total loss: 0.29156 L1 loss: 0.0000e+00 L2 loss: 0.74723 Learning rate: 0.02 Mask loss: 0.21246 RPN box loss: 0.02384 RPN score loss: 0.00457 RPN total loss: 0.02841 Total loss: 1.27966 timestamp: 1654940998.3657374 iteration: 33400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12238 FastRCNN class loss: 0.08302 FastRCNN total loss: 0.2054 L1 loss: 0.0000e+00 L2 loss: 0.74712 Learning rate: 0.02 Mask loss: 0.17503 RPN box loss: 0.0122 RPN score loss: 0.00267 RPN total loss: 0.01487 Total loss: 1.14242 timestamp: 1654941001.5623586 iteration: 33405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11126 FastRCNN class loss: 0.064 FastRCNN total loss: 0.17526 L1 loss: 0.0000e+00 L2 loss: 0.74702 Learning rate: 0.02 Mask loss: 0.1132 RPN box loss: 0.09453 RPN score loss: 0.007 RPN total loss: 0.10153 Total loss: 1.13701 timestamp: 1654941004.7601957 iteration: 33410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.05399 FastRCNN total loss: 0.1407 L1 loss: 0.0000e+00 L2 loss: 0.74691 Learning rate: 0.02 Mask loss: 0.15403 RPN box loss: 0.03749 RPN score loss: 0.00193 RPN total loss: 0.03942 Total loss: 1.08106 timestamp: 1654941007.9177063 iteration: 33415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13533 FastRCNN class loss: 0.10115 FastRCNN total loss: 0.23648 L1 loss: 0.0000e+00 L2 loss: 0.74681 Learning rate: 0.02 Mask loss: 0.16495 RPN box loss: 0.02272 RPN score loss: 0.01451 RPN total loss: 0.03723 Total loss: 1.18547 timestamp: 1654941011.1658134 iteration: 33420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.16924 L1 loss: 0.0000e+00 L2 loss: 0.74669 Learning rate: 0.02 Mask loss: 0.22505 RPN box loss: 0.02942 RPN score loss: 0.00555 RPN total loss: 0.03497 Total loss: 1.17595 timestamp: 1654941014.3621135 iteration: 33425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16627 FastRCNN class loss: 0.10326 FastRCNN total loss: 0.26953 L1 loss: 0.0000e+00 L2 loss: 0.74658 Learning rate: 0.02 Mask loss: 0.20076 RPN box loss: 0.02807 RPN score loss: 0.01337 RPN total loss: 0.04144 Total loss: 1.25831 timestamp: 1654941017.565539 iteration: 33430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08031 FastRCNN class loss: 0.03863 FastRCNN total loss: 0.11893 L1 loss: 0.0000e+00 L2 loss: 0.74648 Learning rate: 0.02 Mask loss: 0.10338 RPN box loss: 0.0372 RPN score loss: 0.00749 RPN total loss: 0.04469 Total loss: 1.01348 timestamp: 1654941020.7862437 iteration: 33435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10469 FastRCNN class loss: 0.08727 FastRCNN total loss: 0.19196 L1 loss: 0.0000e+00 L2 loss: 0.74637 Learning rate: 0.02 Mask loss: 0.1169 RPN box loss: 0.04706 RPN score loss: 0.01069 RPN total loss: 0.05775 Total loss: 1.11299 timestamp: 1654941023.9460993 iteration: 33440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10249 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.18418 L1 loss: 0.0000e+00 L2 loss: 0.74626 Learning rate: 0.02 Mask loss: 0.1823 RPN box loss: 0.0253 RPN score loss: 0.00397 RPN total loss: 0.02928 Total loss: 1.14202 timestamp: 1654941027.0975292 iteration: 33445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14597 FastRCNN class loss: 0.09057 FastRCNN total loss: 0.23654 L1 loss: 0.0000e+00 L2 loss: 0.74615 Learning rate: 0.02 Mask loss: 0.19282 RPN box loss: 0.01186 RPN score loss: 0.0053 RPN total loss: 0.01716 Total loss: 1.19267 timestamp: 1654941030.349654 iteration: 33450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1247 FastRCNN class loss: 0.04915 FastRCNN total loss: 0.17386 L1 loss: 0.0000e+00 L2 loss: 0.74606 Learning rate: 0.02 Mask loss: 0.1201 RPN box loss: 0.02991 RPN score loss: 0.00223 RPN total loss: 0.03214 Total loss: 1.07216 timestamp: 1654941033.5840547 iteration: 33455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08746 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.14995 L1 loss: 0.0000e+00 L2 loss: 0.74598 Learning rate: 0.02 Mask loss: 0.08653 RPN box loss: 0.01441 RPN score loss: 0.00077 RPN total loss: 0.01517 Total loss: 0.99763 timestamp: 1654941036.768322 iteration: 33460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13868 FastRCNN class loss: 0.09327 FastRCNN total loss: 0.23195 L1 loss: 0.0000e+00 L2 loss: 0.74588 Learning rate: 0.02 Mask loss: 0.14517 RPN box loss: 0.03514 RPN score loss: 0.00699 RPN total loss: 0.04213 Total loss: 1.16513 timestamp: 1654941040.0198505 iteration: 33465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13779 FastRCNN class loss: 0.09411 FastRCNN total loss: 0.23189 L1 loss: 0.0000e+00 L2 loss: 0.74577 Learning rate: 0.02 Mask loss: 0.18038 RPN box loss: 0.0279 RPN score loss: 0.01153 RPN total loss: 0.03943 Total loss: 1.19747 timestamp: 1654941043.2868679 iteration: 33470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12578 FastRCNN class loss: 0.05875 FastRCNN total loss: 0.18453 L1 loss: 0.0000e+00 L2 loss: 0.74566 Learning rate: 0.02 Mask loss: 0.16469 RPN box loss: 0.02389 RPN score loss: 0.00913 RPN total loss: 0.03302 Total loss: 1.12791 timestamp: 1654941046.5196114 iteration: 33475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13121 FastRCNN class loss: 0.10747 FastRCNN total loss: 0.23868 L1 loss: 0.0000e+00 L2 loss: 0.74556 Learning rate: 0.02 Mask loss: 0.20413 RPN box loss: 0.0622 RPN score loss: 0.01138 RPN total loss: 0.07358 Total loss: 1.26195 timestamp: 1654941049.6605532 iteration: 33480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16891 FastRCNN class loss: 0.10779 FastRCNN total loss: 0.2767 L1 loss: 0.0000e+00 L2 loss: 0.74545 Learning rate: 0.02 Mask loss: 0.1351 RPN box loss: 0.057 RPN score loss: 0.00969 RPN total loss: 0.0667 Total loss: 1.22395 timestamp: 1654941052.8133504 iteration: 33485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12911 FastRCNN class loss: 0.10907 FastRCNN total loss: 0.23818 L1 loss: 0.0000e+00 L2 loss: 0.74532 Learning rate: 0.02 Mask loss: 0.12767 RPN box loss: 0.02106 RPN score loss: 0.00506 RPN total loss: 0.02612 Total loss: 1.13728 timestamp: 1654941056.0729077 iteration: 33490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.21291 L1 loss: 0.0000e+00 L2 loss: 0.74522 Learning rate: 0.02 Mask loss: 0.15068 RPN box loss: 0.01078 RPN score loss: 0.00447 RPN total loss: 0.01525 Total loss: 1.12406 timestamp: 1654941059.3415406 iteration: 33495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09966 FastRCNN class loss: 0.05641 FastRCNN total loss: 0.15607 L1 loss: 0.0000e+00 L2 loss: 0.74512 Learning rate: 0.02 Mask loss: 0.09871 RPN box loss: 0.01395 RPN score loss: 0.00769 RPN total loss: 0.02165 Total loss: 1.02155 timestamp: 1654941062.544711 iteration: 33500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09507 FastRCNN class loss: 0.08674 FastRCNN total loss: 0.18181 L1 loss: 0.0000e+00 L2 loss: 0.74501 Learning rate: 0.02 Mask loss: 0.1546 RPN box loss: 0.02273 RPN score loss: 0.00386 RPN total loss: 0.0266 Total loss: 1.10802 timestamp: 1654941065.7013524 iteration: 33505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07847 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.13254 L1 loss: 0.0000e+00 L2 loss: 0.7449 Learning rate: 0.02 Mask loss: 0.10926 RPN box loss: 0.01026 RPN score loss: 0.00301 RPN total loss: 0.01327 Total loss: 0.99997 timestamp: 1654941068.9400668 iteration: 33510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16286 FastRCNN class loss: 0.14118 FastRCNN total loss: 0.30405 L1 loss: 0.0000e+00 L2 loss: 0.74479 Learning rate: 0.02 Mask loss: 0.16546 RPN box loss: 0.05507 RPN score loss: 0.01298 RPN total loss: 0.06805 Total loss: 1.28235 timestamp: 1654941072.1372495 iteration: 33515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1332 FastRCNN class loss: 0.08526 FastRCNN total loss: 0.21846 L1 loss: 0.0000e+00 L2 loss: 0.74469 Learning rate: 0.02 Mask loss: 0.18411 RPN box loss: 0.01609 RPN score loss: 0.0074 RPN total loss: 0.02349 Total loss: 1.17076 timestamp: 1654941075.2962718 iteration: 33520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.17136 L1 loss: 0.0000e+00 L2 loss: 0.74459 Learning rate: 0.02 Mask loss: 0.18165 RPN box loss: 0.01214 RPN score loss: 0.00546 RPN total loss: 0.0176 Total loss: 1.1152 timestamp: 1654941078.546593 iteration: 33525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11365 FastRCNN class loss: 0.06032 FastRCNN total loss: 0.17397 L1 loss: 0.0000e+00 L2 loss: 0.7445 Learning rate: 0.02 Mask loss: 0.09632 RPN box loss: 0.03322 RPN score loss: 0.00632 RPN total loss: 0.03953 Total loss: 1.05432 timestamp: 1654941081.7780871 iteration: 33530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1531 FastRCNN class loss: 0.0663 FastRCNN total loss: 0.2194 L1 loss: 0.0000e+00 L2 loss: 0.74441 Learning rate: 0.02 Mask loss: 0.15772 RPN box loss: 0.02262 RPN score loss: 0.00149 RPN total loss: 0.02411 Total loss: 1.14564 timestamp: 1654941085.014342 iteration: 33535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10712 FastRCNN class loss: 0.11159 FastRCNN total loss: 0.21871 L1 loss: 0.0000e+00 L2 loss: 0.74431 Learning rate: 0.02 Mask loss: 0.14976 RPN box loss: 0.03145 RPN score loss: 0.01155 RPN total loss: 0.043 Total loss: 1.15578 timestamp: 1654941088.2647657 iteration: 33540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19985 FastRCNN class loss: 0.09288 FastRCNN total loss: 0.29273 L1 loss: 0.0000e+00 L2 loss: 0.7442 Learning rate: 0.02 Mask loss: 0.21278 RPN box loss: 0.01285 RPN score loss: 0.0058 RPN total loss: 0.01866 Total loss: 1.26837 timestamp: 1654941091.43195 iteration: 33545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07118 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.14257 L1 loss: 0.0000e+00 L2 loss: 0.74411 Learning rate: 0.02 Mask loss: 0.11271 RPN box loss: 0.05055 RPN score loss: 0.00643 RPN total loss: 0.05697 Total loss: 1.05636 timestamp: 1654941094.5886786 iteration: 33550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1435 FastRCNN class loss: 0.07886 FastRCNN total loss: 0.22236 L1 loss: 0.0000e+00 L2 loss: 0.74401 Learning rate: 0.02 Mask loss: 0.1157 RPN box loss: 0.02529 RPN score loss: 0.003 RPN total loss: 0.02829 Total loss: 1.11036 timestamp: 1654941097.806248 iteration: 33555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08322 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.13794 L1 loss: 0.0000e+00 L2 loss: 0.74392 Learning rate: 0.02 Mask loss: 0.17008 RPN box loss: 0.02555 RPN score loss: 0.00411 RPN total loss: 0.02966 Total loss: 1.0816 timestamp: 1654941101.0282624 iteration: 33560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13158 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.20142 L1 loss: 0.0000e+00 L2 loss: 0.74383 Learning rate: 0.02 Mask loss: 0.09683 RPN box loss: 0.01394 RPN score loss: 0.00502 RPN total loss: 0.01896 Total loss: 1.06103 timestamp: 1654941104.168851 iteration: 33565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1501 FastRCNN class loss: 0.093 FastRCNN total loss: 0.2431 L1 loss: 0.0000e+00 L2 loss: 0.74372 Learning rate: 0.02 Mask loss: 0.13964 RPN box loss: 0.0288 RPN score loss: 0.00497 RPN total loss: 0.03378 Total loss: 1.16024 timestamp: 1654941107.4137554 iteration: 33570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10933 FastRCNN class loss: 0.0628 FastRCNN total loss: 0.17213 L1 loss: 0.0000e+00 L2 loss: 0.74361 Learning rate: 0.02 Mask loss: 0.13076 RPN box loss: 0.05144 RPN score loss: 0.00413 RPN total loss: 0.05557 Total loss: 1.10207 timestamp: 1654941110.6013212 iteration: 33575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.05884 FastRCNN total loss: 0.14406 L1 loss: 0.0000e+00 L2 loss: 0.74351 Learning rate: 0.02 Mask loss: 0.09049 RPN box loss: 0.02115 RPN score loss: 0.00202 RPN total loss: 0.02317 Total loss: 1.00122 timestamp: 1654941113.771101 iteration: 33580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14376 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.22191 L1 loss: 0.0000e+00 L2 loss: 0.74341 Learning rate: 0.02 Mask loss: 0.11842 RPN box loss: 0.02089 RPN score loss: 0.00494 RPN total loss: 0.02584 Total loss: 1.10958 timestamp: 1654941116.9405572 iteration: 33585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.16951 L1 loss: 0.0000e+00 L2 loss: 0.74332 Learning rate: 0.02 Mask loss: 0.09182 RPN box loss: 0.05392 RPN score loss: 0.00258 RPN total loss: 0.0565 Total loss: 1.06114 timestamp: 1654941120.150541 iteration: 33590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1145 FastRCNN class loss: 0.05458 FastRCNN total loss: 0.16907 L1 loss: 0.0000e+00 L2 loss: 0.74322 Learning rate: 0.02 Mask loss: 0.15089 RPN box loss: 0.01153 RPN score loss: 0.00523 RPN total loss: 0.01676 Total loss: 1.07994 timestamp: 1654941123.3646047 iteration: 33595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14513 FastRCNN class loss: 0.15206 FastRCNN total loss: 0.2972 L1 loss: 0.0000e+00 L2 loss: 0.74311 Learning rate: 0.02 Mask loss: 0.24345 RPN box loss: 0.03298 RPN score loss: 0.01031 RPN total loss: 0.04328 Total loss: 1.32704 timestamp: 1654941126.5923507 iteration: 33600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16657 FastRCNN class loss: 0.08198 FastRCNN total loss: 0.24854 L1 loss: 0.0000e+00 L2 loss: 0.74299 Learning rate: 0.02 Mask loss: 0.20979 RPN box loss: 0.03341 RPN score loss: 0.01552 RPN total loss: 0.04893 Total loss: 1.25026 timestamp: 1654941129.786934 iteration: 33605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0856 FastRCNN class loss: 0.04644 FastRCNN total loss: 0.13204 L1 loss: 0.0000e+00 L2 loss: 0.7429 Learning rate: 0.02 Mask loss: 0.07643 RPN box loss: 0.0076 RPN score loss: 0.00122 RPN total loss: 0.00882 Total loss: 0.96019 timestamp: 1654941132.8899324 iteration: 33610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10553 FastRCNN class loss: 0.04805 FastRCNN total loss: 0.15358 L1 loss: 0.0000e+00 L2 loss: 0.74279 Learning rate: 0.02 Mask loss: 0.14731 RPN box loss: 0.01457 RPN score loss: 0.00321 RPN total loss: 0.01778 Total loss: 1.06146 timestamp: 1654941136.0503886 iteration: 33615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14103 FastRCNN class loss: 0.13222 FastRCNN total loss: 0.27325 L1 loss: 0.0000e+00 L2 loss: 0.74268 Learning rate: 0.02 Mask loss: 0.15767 RPN box loss: 0.03812 RPN score loss: 0.00406 RPN total loss: 0.04218 Total loss: 1.21578 timestamp: 1654941139.2464335 iteration: 33620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1595 FastRCNN class loss: 0.07424 FastRCNN total loss: 0.23375 L1 loss: 0.0000e+00 L2 loss: 0.74258 Learning rate: 0.02 Mask loss: 0.11818 RPN box loss: 0.06024 RPN score loss: 0.00826 RPN total loss: 0.0685 Total loss: 1.163 timestamp: 1654941142.4374707 iteration: 33625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14225 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.22141 L1 loss: 0.0000e+00 L2 loss: 0.74248 Learning rate: 0.02 Mask loss: 0.14088 RPN box loss: 0.03074 RPN score loss: 0.00374 RPN total loss: 0.03448 Total loss: 1.13926 timestamp: 1654941145.635659 iteration: 33630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12843 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.21049 L1 loss: 0.0000e+00 L2 loss: 0.7424 Learning rate: 0.02 Mask loss: 0.13295 RPN box loss: 0.01503 RPN score loss: 0.00621 RPN total loss: 0.02123 Total loss: 1.10708 timestamp: 1654941148.875458 iteration: 33635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18968 FastRCNN class loss: 0.14578 FastRCNN total loss: 0.33546 L1 loss: 0.0000e+00 L2 loss: 0.74229 Learning rate: 0.02 Mask loss: 0.21098 RPN box loss: 0.06708 RPN score loss: 0.01243 RPN total loss: 0.07951 Total loss: 1.36824 timestamp: 1654941152.0322397 iteration: 33640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.05222 FastRCNN total loss: 0.14068 L1 loss: 0.0000e+00 L2 loss: 0.74217 Learning rate: 0.02 Mask loss: 0.11263 RPN box loss: 0.03348 RPN score loss: 0.00322 RPN total loss: 0.03669 Total loss: 1.03217 timestamp: 1654941155.2033823 iteration: 33645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14445 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.24575 L1 loss: 0.0000e+00 L2 loss: 0.74207 Learning rate: 0.02 Mask loss: 0.13842 RPN box loss: 0.05735 RPN score loss: 0.01864 RPN total loss: 0.076 Total loss: 1.20223 timestamp: 1654941158.372944 iteration: 33650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.04724 FastRCNN total loss: 0.14096 L1 loss: 0.0000e+00 L2 loss: 0.74195 Learning rate: 0.02 Mask loss: 0.12847 RPN box loss: 0.01875 RPN score loss: 0.01003 RPN total loss: 0.02877 Total loss: 1.04015 timestamp: 1654941161.580324 iteration: 33655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14461 FastRCNN class loss: 0.14291 FastRCNN total loss: 0.28752 L1 loss: 0.0000e+00 L2 loss: 0.74184 Learning rate: 0.02 Mask loss: 0.21658 RPN box loss: 0.02324 RPN score loss: 0.00806 RPN total loss: 0.03129 Total loss: 1.27723 timestamp: 1654941164.7967741 iteration: 33660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10713 FastRCNN class loss: 0.07919 FastRCNN total loss: 0.18631 L1 loss: 0.0000e+00 L2 loss: 0.74174 Learning rate: 0.02 Mask loss: 0.09334 RPN box loss: 0.0841 RPN score loss: 0.01182 RPN total loss: 0.09593 Total loss: 1.11732 timestamp: 1654941168.020606 iteration: 33665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15169 FastRCNN class loss: 0.12424 FastRCNN total loss: 0.27593 L1 loss: 0.0000e+00 L2 loss: 0.74166 Learning rate: 0.02 Mask loss: 0.13421 RPN box loss: 0.03591 RPN score loss: 0.00851 RPN total loss: 0.04442 Total loss: 1.19621 timestamp: 1654941171.2533057 iteration: 33670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16124 FastRCNN class loss: 0.05274 FastRCNN total loss: 0.21398 L1 loss: 0.0000e+00 L2 loss: 0.74153 Learning rate: 0.02 Mask loss: 0.11771 RPN box loss: 0.01346 RPN score loss: 0.00434 RPN total loss: 0.0178 Total loss: 1.09102 timestamp: 1654941174.4355164 iteration: 33675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15055 FastRCNN class loss: 0.12448 FastRCNN total loss: 0.27503 L1 loss: 0.0000e+00 L2 loss: 0.74144 Learning rate: 0.02 Mask loss: 0.20239 RPN box loss: 0.0348 RPN score loss: 0.00726 RPN total loss: 0.04205 Total loss: 1.2609 timestamp: 1654941177.6099079 iteration: 33680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05362 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.10812 L1 loss: 0.0000e+00 L2 loss: 0.74135 Learning rate: 0.02 Mask loss: 0.15381 RPN box loss: 0.02391 RPN score loss: 0.00306 RPN total loss: 0.02697 Total loss: 1.03025 timestamp: 1654941180.7039623 iteration: 33685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04738 FastRCNN class loss: 0.04823 FastRCNN total loss: 0.09561 L1 loss: 0.0000e+00 L2 loss: 0.74125 Learning rate: 0.02 Mask loss: 0.12397 RPN box loss: 0.03305 RPN score loss: 0.03254 RPN total loss: 0.0656 Total loss: 1.02643 timestamp: 1654941183.8878624 iteration: 33690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17802 FastRCNN class loss: 0.11593 FastRCNN total loss: 0.29396 L1 loss: 0.0000e+00 L2 loss: 0.74116 Learning rate: 0.02 Mask loss: 0.19484 RPN box loss: 0.02001 RPN score loss: 0.0031 RPN total loss: 0.02311 Total loss: 1.25307 timestamp: 1654941187.09896 iteration: 33695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1305 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.18877 L1 loss: 0.0000e+00 L2 loss: 0.74107 Learning rate: 0.02 Mask loss: 0.12723 RPN box loss: 0.01129 RPN score loss: 0.0068 RPN total loss: 0.01809 Total loss: 1.07516 timestamp: 1654941190.3095984 iteration: 33700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12353 FastRCNN class loss: 0.12488 FastRCNN total loss: 0.24841 L1 loss: 0.0000e+00 L2 loss: 0.74098 Learning rate: 0.02 Mask loss: 0.20831 RPN box loss: 0.03891 RPN score loss: 0.02163 RPN total loss: 0.06054 Total loss: 1.25824 timestamp: 1654941193.4424658 iteration: 33705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13621 FastRCNN class loss: 0.06299 FastRCNN total loss: 0.1992 L1 loss: 0.0000e+00 L2 loss: 0.74088 Learning rate: 0.02 Mask loss: 0.09633 RPN box loss: 0.01925 RPN score loss: 0.00461 RPN total loss: 0.02386 Total loss: 1.06027 timestamp: 1654941196.6448596 iteration: 33710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18636 FastRCNN class loss: 0.1039 FastRCNN total loss: 0.29027 L1 loss: 0.0000e+00 L2 loss: 0.74076 Learning rate: 0.02 Mask loss: 0.27946 RPN box loss: 0.02195 RPN score loss: 0.00492 RPN total loss: 0.02688 Total loss: 1.33736 timestamp: 1654941199.8576412 iteration: 33715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09191 FastRCNN class loss: 0.06845 FastRCNN total loss: 0.16036 L1 loss: 0.0000e+00 L2 loss: 0.74069 Learning rate: 0.02 Mask loss: 0.13152 RPN box loss: 0.01535 RPN score loss: 0.00502 RPN total loss: 0.02037 Total loss: 1.05294 timestamp: 1654941203.03781 iteration: 33720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07765 FastRCNN class loss: 0.0597 FastRCNN total loss: 0.13735 L1 loss: 0.0000e+00 L2 loss: 0.7406 Learning rate: 0.02 Mask loss: 0.11521 RPN box loss: 0.05025 RPN score loss: 0.01319 RPN total loss: 0.06344 Total loss: 1.0566 timestamp: 1654941206.2537172 iteration: 33725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12653 FastRCNN class loss: 0.07988 FastRCNN total loss: 0.2064 L1 loss: 0.0000e+00 L2 loss: 0.7405 Learning rate: 0.02 Mask loss: 0.2033 RPN box loss: 0.0313 RPN score loss: 0.02 RPN total loss: 0.0513 Total loss: 1.2015 timestamp: 1654941209.4538262 iteration: 33730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15226 FastRCNN class loss: 0.08358 FastRCNN total loss: 0.23585 L1 loss: 0.0000e+00 L2 loss: 0.74039 Learning rate: 0.02 Mask loss: 0.2191 RPN box loss: 0.02199 RPN score loss: 0.00731 RPN total loss: 0.0293 Total loss: 1.22464 timestamp: 1654941212.6280851 iteration: 33735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09737 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.16832 L1 loss: 0.0000e+00 L2 loss: 0.74029 Learning rate: 0.02 Mask loss: 0.15878 RPN box loss: 0.03847 RPN score loss: 0.00662 RPN total loss: 0.04509 Total loss: 1.11248 timestamp: 1654941215.8451402 iteration: 33740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11727 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.74019 Learning rate: 0.02 Mask loss: 0.12112 RPN box loss: 0.00627 RPN score loss: 0.00198 RPN total loss: 0.00825 Total loss: 1.04923 timestamp: 1654941219.0321157 iteration: 33745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10626 FastRCNN class loss: 0.07236 FastRCNN total loss: 0.17862 L1 loss: 0.0000e+00 L2 loss: 0.7401 Learning rate: 0.02 Mask loss: 0.20131 RPN box loss: 0.01491 RPN score loss: 0.00834 RPN total loss: 0.02325 Total loss: 1.14328 timestamp: 1654941222.2751527 iteration: 33750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21368 FastRCNN class loss: 0.08743 FastRCNN total loss: 0.30111 L1 loss: 0.0000e+00 L2 loss: 0.74 Learning rate: 0.02 Mask loss: 0.16875 RPN box loss: 0.03981 RPN score loss: 0.00797 RPN total loss: 0.04778 Total loss: 1.25764 timestamp: 1654941225.4246712 iteration: 33755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13102 FastRCNN class loss: 0.04709 FastRCNN total loss: 0.17811 L1 loss: 0.0000e+00 L2 loss: 0.73989 Learning rate: 0.02 Mask loss: 0.1595 RPN box loss: 0.01206 RPN score loss: 0.0047 RPN total loss: 0.01675 Total loss: 1.09426 timestamp: 1654941228.5944872 iteration: 33760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14493 FastRCNN class loss: 0.06622 FastRCNN total loss: 0.21115 L1 loss: 0.0000e+00 L2 loss: 0.73981 Learning rate: 0.02 Mask loss: 0.14669 RPN box loss: 0.03347 RPN score loss: 0.00411 RPN total loss: 0.03758 Total loss: 1.13524 timestamp: 1654941231.8248882 iteration: 33765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11533 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.18317 L1 loss: 0.0000e+00 L2 loss: 0.73972 Learning rate: 0.02 Mask loss: 0.14517 RPN box loss: 0.03347 RPN score loss: 0.00596 RPN total loss: 0.03943 Total loss: 1.10749 timestamp: 1654941235.0172114 iteration: 33770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15877 FastRCNN class loss: 0.06351 FastRCNN total loss: 0.22228 L1 loss: 0.0000e+00 L2 loss: 0.73964 Learning rate: 0.02 Mask loss: 0.13903 RPN box loss: 0.04448 RPN score loss: 0.00232 RPN total loss: 0.0468 Total loss: 1.14776 timestamp: 1654941238.2446084 iteration: 33775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13225 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.19991 L1 loss: 0.0000e+00 L2 loss: 0.73954 Learning rate: 0.02 Mask loss: 0.14751 RPN box loss: 0.03272 RPN score loss: 0.0101 RPN total loss: 0.04282 Total loss: 1.12979 timestamp: 1654941241.545273 iteration: 33780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12616 FastRCNN class loss: 0.09071 FastRCNN total loss: 0.21687 L1 loss: 0.0000e+00 L2 loss: 0.73942 Learning rate: 0.02 Mask loss: 0.09054 RPN box loss: 0.01431 RPN score loss: 0.0068 RPN total loss: 0.02111 Total loss: 1.06794 timestamp: 1654941244.7136836 iteration: 33785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15071 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.24305 L1 loss: 0.0000e+00 L2 loss: 0.73931 Learning rate: 0.02 Mask loss: 0.17273 RPN box loss: 0.03108 RPN score loss: 0.00672 RPN total loss: 0.0378 Total loss: 1.19289 timestamp: 1654941247.9361463 iteration: 33790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17999 FastRCNN class loss: 0.11412 FastRCNN total loss: 0.29411 L1 loss: 0.0000e+00 L2 loss: 0.73921 Learning rate: 0.02 Mask loss: 0.20393 RPN box loss: 0.04142 RPN score loss: 0.00982 RPN total loss: 0.05124 Total loss: 1.28849 timestamp: 1654941251.0538752 iteration: 33795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21256 FastRCNN class loss: 0.10276 FastRCNN total loss: 0.31532 L1 loss: 0.0000e+00 L2 loss: 0.73911 Learning rate: 0.02 Mask loss: 0.12504 RPN box loss: 0.02159 RPN score loss: 0.00861 RPN total loss: 0.0302 Total loss: 1.20966 timestamp: 1654941254.2999153 iteration: 33800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19344 FastRCNN class loss: 0.09924 FastRCNN total loss: 0.29268 L1 loss: 0.0000e+00 L2 loss: 0.73901 Learning rate: 0.02 Mask loss: 0.15167 RPN box loss: 0.01401 RPN score loss: 0.008 RPN total loss: 0.02201 Total loss: 1.20538 timestamp: 1654941257.526069 iteration: 33805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15327 FastRCNN class loss: 0.13691 FastRCNN total loss: 0.29018 L1 loss: 0.0000e+00 L2 loss: 0.73892 Learning rate: 0.02 Mask loss: 0.3227 RPN box loss: 0.0646 RPN score loss: 0.0082 RPN total loss: 0.0728 Total loss: 1.4246 timestamp: 1654941260.743123 iteration: 33810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1706 FastRCNN class loss: 0.14637 FastRCNN total loss: 0.31697 L1 loss: 0.0000e+00 L2 loss: 0.73883 Learning rate: 0.02 Mask loss: 0.15859 RPN box loss: 0.02954 RPN score loss: 0.00783 RPN total loss: 0.03736 Total loss: 1.25175 timestamp: 1654941263.8831677 iteration: 33815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1957 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.26387 L1 loss: 0.0000e+00 L2 loss: 0.73876 Learning rate: 0.02 Mask loss: 0.10874 RPN box loss: 0.03563 RPN score loss: 0.00373 RPN total loss: 0.03936 Total loss: 1.15072 timestamp: 1654941267.1654005 iteration: 33820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13389 FastRCNN class loss: 0.08921 FastRCNN total loss: 0.2231 L1 loss: 0.0000e+00 L2 loss: 0.73863 Learning rate: 0.02 Mask loss: 0.16036 RPN box loss: 0.03361 RPN score loss: 0.00898 RPN total loss: 0.04259 Total loss: 1.16468 timestamp: 1654941270.3714073 iteration: 33825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13098 FastRCNN class loss: 0.11106 FastRCNN total loss: 0.24204 L1 loss: 0.0000e+00 L2 loss: 0.73852 Learning rate: 0.02 Mask loss: 0.1557 RPN box loss: 0.10193 RPN score loss: 0.01849 RPN total loss: 0.12041 Total loss: 1.25666 timestamp: 1654941273.544359 iteration: 33830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08544 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.16244 L1 loss: 0.0000e+00 L2 loss: 0.73842 Learning rate: 0.02 Mask loss: 0.09108 RPN box loss: 0.02405 RPN score loss: 0.00747 RPN total loss: 0.03152 Total loss: 1.02347 timestamp: 1654941276.6930583 iteration: 33835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15757 FastRCNN class loss: 0.10707 FastRCNN total loss: 0.26464 L1 loss: 0.0000e+00 L2 loss: 0.73833 Learning rate: 0.02 Mask loss: 0.10978 RPN box loss: 0.01194 RPN score loss: 0.00467 RPN total loss: 0.01661 Total loss: 1.12936 timestamp: 1654941279.842119 iteration: 33840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06421 FastRCNN class loss: 0.03507 FastRCNN total loss: 0.09929 L1 loss: 0.0000e+00 L2 loss: 0.73823 Learning rate: 0.02 Mask loss: 0.0972 RPN box loss: 0.02052 RPN score loss: 0.0083 RPN total loss: 0.02882 Total loss: 0.96354 timestamp: 1654941283.0203269 iteration: 33845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10328 FastRCNN class loss: 0.08566 FastRCNN total loss: 0.18893 L1 loss: 0.0000e+00 L2 loss: 0.73813 Learning rate: 0.02 Mask loss: 0.20878 RPN box loss: 0.01766 RPN score loss: 0.00296 RPN total loss: 0.02062 Total loss: 1.15646 timestamp: 1654941286.2060843 iteration: 33850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16461 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.22824 L1 loss: 0.0000e+00 L2 loss: 0.73804 Learning rate: 0.02 Mask loss: 0.08624 RPN box loss: 0.03298 RPN score loss: 0.00271 RPN total loss: 0.0357 Total loss: 1.08821 timestamp: 1654941289.4299645 iteration: 33855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16909 FastRCNN class loss: 0.085 FastRCNN total loss: 0.25408 L1 loss: 0.0000e+00 L2 loss: 0.73792 Learning rate: 0.02 Mask loss: 0.20316 RPN box loss: 0.00526 RPN score loss: 0.00429 RPN total loss: 0.00955 Total loss: 1.20471 timestamp: 1654941292.6938632 iteration: 33860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10025 FastRCNN class loss: 0.11863 FastRCNN total loss: 0.21888 L1 loss: 0.0000e+00 L2 loss: 0.73782 Learning rate: 0.02 Mask loss: 0.1638 RPN box loss: 0.02268 RPN score loss: 0.00365 RPN total loss: 0.02632 Total loss: 1.14683 timestamp: 1654941295.9394207 iteration: 33865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08111 FastRCNN class loss: 0.05121 FastRCNN total loss: 0.13232 L1 loss: 0.0000e+00 L2 loss: 0.73774 Learning rate: 0.02 Mask loss: 0.12378 RPN box loss: 0.03497 RPN score loss: 0.00293 RPN total loss: 0.0379 Total loss: 1.03174 timestamp: 1654941299.2141635 iteration: 33870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10768 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.1796 L1 loss: 0.0000e+00 L2 loss: 0.73765 Learning rate: 0.02 Mask loss: 0.15763 RPN box loss: 0.01961 RPN score loss: 0.00379 RPN total loss: 0.0234 Total loss: 1.09828 timestamp: 1654941302.3961725 iteration: 33875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16844 FastRCNN class loss: 0.09306 FastRCNN total loss: 0.26149 L1 loss: 0.0000e+00 L2 loss: 0.73754 Learning rate: 0.02 Mask loss: 0.15801 RPN box loss: 0.04517 RPN score loss: 0.01077 RPN total loss: 0.05593 Total loss: 1.21297 timestamp: 1654941305.572625 iteration: 33880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11881 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.18762 L1 loss: 0.0000e+00 L2 loss: 0.73744 Learning rate: 0.02 Mask loss: 0.19969 RPN box loss: 0.03264 RPN score loss: 0.00918 RPN total loss: 0.04182 Total loss: 1.16656 timestamp: 1654941308.771663 iteration: 33885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09593 FastRCNN class loss: 0.05736 FastRCNN total loss: 0.15329 L1 loss: 0.0000e+00 L2 loss: 0.73734 Learning rate: 0.02 Mask loss: 0.16915 RPN box loss: 0.00868 RPN score loss: 0.00372 RPN total loss: 0.0124 Total loss: 1.07217 timestamp: 1654941312.0220578 iteration: 33890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10634 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.17863 L1 loss: 0.0000e+00 L2 loss: 0.73723 Learning rate: 0.02 Mask loss: 0.1949 RPN box loss: 0.02211 RPN score loss: 0.00708 RPN total loss: 0.02919 Total loss: 1.13995 timestamp: 1654941315.2325745 iteration: 33895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11277 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.17942 L1 loss: 0.0000e+00 L2 loss: 0.73711 Learning rate: 0.02 Mask loss: 0.15848 RPN box loss: 0.04258 RPN score loss: 0.00481 RPN total loss: 0.04739 Total loss: 1.12239 timestamp: 1654941318.3263292 iteration: 33900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1273 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.21081 L1 loss: 0.0000e+00 L2 loss: 0.73702 Learning rate: 0.02 Mask loss: 0.12837 RPN box loss: 0.0641 RPN score loss: 0.00803 RPN total loss: 0.07212 Total loss: 1.14833 timestamp: 1654941321.459647 iteration: 33905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15644 FastRCNN class loss: 0.08599 FastRCNN total loss: 0.24243 L1 loss: 0.0000e+00 L2 loss: 0.73691 Learning rate: 0.02 Mask loss: 0.1211 RPN box loss: 0.01298 RPN score loss: 0.00612 RPN total loss: 0.01909 Total loss: 1.11954 timestamp: 1654941324.6567981 iteration: 33910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16619 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.26647 L1 loss: 0.0000e+00 L2 loss: 0.73679 Learning rate: 0.02 Mask loss: 0.17308 RPN box loss: 0.04247 RPN score loss: 0.01016 RPN total loss: 0.05263 Total loss: 1.22897 timestamp: 1654941327.877545 iteration: 33915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18337 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.25759 L1 loss: 0.0000e+00 L2 loss: 0.7367 Learning rate: 0.02 Mask loss: 0.11713 RPN box loss: 0.01829 RPN score loss: 0.00997 RPN total loss: 0.02825 Total loss: 1.13968 timestamp: 1654941331.111942 iteration: 33920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15481 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.21987 L1 loss: 0.0000e+00 L2 loss: 0.73659 Learning rate: 0.02 Mask loss: 0.21148 RPN box loss: 0.02187 RPN score loss: 0.00668 RPN total loss: 0.02855 Total loss: 1.1965 timestamp: 1654941334.3394086 iteration: 33925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11597 FastRCNN class loss: 0.07717 FastRCNN total loss: 0.19314 L1 loss: 0.0000e+00 L2 loss: 0.7365 Learning rate: 0.02 Mask loss: 0.11318 RPN box loss: 0.01056 RPN score loss: 0.00841 RPN total loss: 0.01897 Total loss: 1.06179 timestamp: 1654941337.5479825 iteration: 33930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08822 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.15689 L1 loss: 0.0000e+00 L2 loss: 0.73641 Learning rate: 0.02 Mask loss: 0.09521 RPN box loss: 0.02125 RPN score loss: 0.00454 RPN total loss: 0.02579 Total loss: 1.0143 timestamp: 1654941340.7262943 iteration: 33935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22156 FastRCNN class loss: 0.09179 FastRCNN total loss: 0.31335 L1 loss: 0.0000e+00 L2 loss: 0.73632 Learning rate: 0.02 Mask loss: 0.21646 RPN box loss: 0.00867 RPN score loss: 0.00617 RPN total loss: 0.01484 Total loss: 1.28096 timestamp: 1654941343.9733875 iteration: 33940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09087 FastRCNN class loss: 0.0771 FastRCNN total loss: 0.16798 L1 loss: 0.0000e+00 L2 loss: 0.73621 Learning rate: 0.02 Mask loss: 0.13955 RPN box loss: 0.03643 RPN score loss: 0.01116 RPN total loss: 0.04759 Total loss: 1.09133 timestamp: 1654941347.1429625 iteration: 33945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10354 FastRCNN class loss: 0.08997 FastRCNN total loss: 0.19351 L1 loss: 0.0000e+00 L2 loss: 0.73609 Learning rate: 0.02 Mask loss: 0.16903 RPN box loss: 0.02907 RPN score loss: 0.00311 RPN total loss: 0.03218 Total loss: 1.13081 timestamp: 1654941350.293572 iteration: 33950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1486 FastRCNN class loss: 0.13821 FastRCNN total loss: 0.28681 L1 loss: 0.0000e+00 L2 loss: 0.73601 Learning rate: 0.02 Mask loss: 0.15934 RPN box loss: 0.03265 RPN score loss: 0.01127 RPN total loss: 0.04392 Total loss: 1.22608 timestamp: 1654941353.511796 iteration: 33955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12656 FastRCNN class loss: 0.09158 FastRCNN total loss: 0.21814 L1 loss: 0.0000e+00 L2 loss: 0.73592 Learning rate: 0.02 Mask loss: 0.17208 RPN box loss: 0.01053 RPN score loss: 0.00556 RPN total loss: 0.01608 Total loss: 1.14222 timestamp: 1654941356.7724211 iteration: 33960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11688 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.18731 L1 loss: 0.0000e+00 L2 loss: 0.73582 Learning rate: 0.02 Mask loss: 0.13061 RPN box loss: 0.03353 RPN score loss: 0.00772 RPN total loss: 0.04124 Total loss: 1.09497 timestamp: 1654941359.9171243 iteration: 33965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20205 FastRCNN class loss: 0.09072 FastRCNN total loss: 0.29277 L1 loss: 0.0000e+00 L2 loss: 0.73571 Learning rate: 0.02 Mask loss: 0.25855 RPN box loss: 0.04316 RPN score loss: 0.01329 RPN total loss: 0.05645 Total loss: 1.34347 timestamp: 1654941363.1329587 iteration: 33970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15619 FastRCNN class loss: 0.07561 FastRCNN total loss: 0.2318 L1 loss: 0.0000e+00 L2 loss: 0.73559 Learning rate: 0.02 Mask loss: 0.21885 RPN box loss: 0.01481 RPN score loss: 0.00724 RPN total loss: 0.02205 Total loss: 1.20829 timestamp: 1654941366.2287042 iteration: 33975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15065 FastRCNN class loss: 0.10346 FastRCNN total loss: 0.25411 L1 loss: 0.0000e+00 L2 loss: 0.7355 Learning rate: 0.02 Mask loss: 0.16476 RPN box loss: 0.05138 RPN score loss: 0.01304 RPN total loss: 0.06443 Total loss: 1.21879 timestamp: 1654941369.3967235 iteration: 33980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15508 FastRCNN class loss: 0.08486 FastRCNN total loss: 0.23994 L1 loss: 0.0000e+00 L2 loss: 0.7354 Learning rate: 0.02 Mask loss: 0.17374 RPN box loss: 0.03272 RPN score loss: 0.0091 RPN total loss: 0.04181 Total loss: 1.1909 timestamp: 1654941372.5915542 iteration: 33985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17574 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.23206 L1 loss: 0.0000e+00 L2 loss: 0.73529 Learning rate: 0.02 Mask loss: 0.09531 RPN box loss: 0.00585 RPN score loss: 0.00414 RPN total loss: 0.00998 Total loss: 1.07264 timestamp: 1654941375.7749934 iteration: 33990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18742 FastRCNN class loss: 0.10345 FastRCNN total loss: 0.29087 L1 loss: 0.0000e+00 L2 loss: 0.73515 Learning rate: 0.02 Mask loss: 0.18083 RPN box loss: 0.01108 RPN score loss: 0.00327 RPN total loss: 0.01435 Total loss: 1.22121 timestamp: 1654941378.9373734 iteration: 33995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05466 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.11901 L1 loss: 0.0000e+00 L2 loss: 0.7351 Learning rate: 0.02 Mask loss: 0.10339 RPN box loss: 0.03275 RPN score loss: 0.00764 RPN total loss: 0.04039 Total loss: 0.9979 timestamp: 1654941382.1392424 iteration: 34000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20796 FastRCNN class loss: 0.08805 FastRCNN total loss: 0.29601 L1 loss: 0.0000e+00 L2 loss: 0.735 Learning rate: 0.02 Mask loss: 0.12532 RPN box loss: 0.03668 RPN score loss: 0.00737 RPN total loss: 0.04405 Total loss: 1.20038 timestamp: 1654941385.257977 iteration: 34005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13199 FastRCNN class loss: 0.12754 FastRCNN total loss: 0.25952 L1 loss: 0.0000e+00 L2 loss: 0.73491 Learning rate: 0.02 Mask loss: 0.12717 RPN box loss: 0.01188 RPN score loss: 0.00596 RPN total loss: 0.01783 Total loss: 1.13943 timestamp: 1654941388.4190674 iteration: 34010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15794 FastRCNN class loss: 0.10081 FastRCNN total loss: 0.25875 L1 loss: 0.0000e+00 L2 loss: 0.7348 Learning rate: 0.02 Mask loss: 0.14246 RPN box loss: 0.03628 RPN score loss: 0.01284 RPN total loss: 0.04912 Total loss: 1.18513 timestamp: 1654941391.6291323 iteration: 34015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1277 FastRCNN class loss: 0.06397 FastRCNN total loss: 0.19167 L1 loss: 0.0000e+00 L2 loss: 0.7347 Learning rate: 0.02 Mask loss: 0.10004 RPN box loss: 0.01619 RPN score loss: 0.00909 RPN total loss: 0.02528 Total loss: 1.05169 timestamp: 1654941394.929929 iteration: 34020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16301 FastRCNN class loss: 0.09381 FastRCNN total loss: 0.25682 L1 loss: 0.0000e+00 L2 loss: 0.73459 Learning rate: 0.02 Mask loss: 0.15799 RPN box loss: 0.06518 RPN score loss: 0.0061 RPN total loss: 0.07128 Total loss: 1.22068 timestamp: 1654941398.14162 iteration: 34025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15381 FastRCNN class loss: 0.06761 FastRCNN total loss: 0.22142 L1 loss: 0.0000e+00 L2 loss: 0.73449 Learning rate: 0.02 Mask loss: 0.16857 RPN box loss: 0.01732 RPN score loss: 0.00374 RPN total loss: 0.02106 Total loss: 1.14555 timestamp: 1654941401.3707185 iteration: 34030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16097 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.24448 L1 loss: 0.0000e+00 L2 loss: 0.7344 Learning rate: 0.02 Mask loss: 0.14634 RPN box loss: 0.01276 RPN score loss: 0.00381 RPN total loss: 0.01657 Total loss: 1.14178 timestamp: 1654941404.5493486 iteration: 34035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16595 FastRCNN class loss: 0.07708 FastRCNN total loss: 0.24304 L1 loss: 0.0000e+00 L2 loss: 0.73432 Learning rate: 0.02 Mask loss: 0.12396 RPN box loss: 0.03918 RPN score loss: 0.00795 RPN total loss: 0.04714 Total loss: 1.14845 timestamp: 1654941407.6981986 iteration: 34040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16479 FastRCNN class loss: 0.12455 FastRCNN total loss: 0.28934 L1 loss: 0.0000e+00 L2 loss: 0.73421 Learning rate: 0.02 Mask loss: 0.23508 RPN box loss: 0.04747 RPN score loss: 0.01205 RPN total loss: 0.05952 Total loss: 1.31815 timestamp: 1654941410.8785405 iteration: 34045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08847 FastRCNN class loss: 0.04989 FastRCNN total loss: 0.13836 L1 loss: 0.0000e+00 L2 loss: 0.73409 Learning rate: 0.02 Mask loss: 0.16667 RPN box loss: 0.03648 RPN score loss: 0.00541 RPN total loss: 0.0419 Total loss: 1.08103 timestamp: 1654941414.0277445 iteration: 34050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07356 FastRCNN class loss: 0.03028 FastRCNN total loss: 0.10384 L1 loss: 0.0000e+00 L2 loss: 0.73397 Learning rate: 0.02 Mask loss: 0.0897 RPN box loss: 0.01437 RPN score loss: 0.00333 RPN total loss: 0.0177 Total loss: 0.94521 timestamp: 1654941417.1942253 iteration: 34055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11427 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.17817 L1 loss: 0.0000e+00 L2 loss: 0.73387 Learning rate: 0.02 Mask loss: 0.13697 RPN box loss: 0.05321 RPN score loss: 0.01021 RPN total loss: 0.06342 Total loss: 1.11243 timestamp: 1654941420.4335299 iteration: 34060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21367 FastRCNN class loss: 0.0904 FastRCNN total loss: 0.30407 L1 loss: 0.0000e+00 L2 loss: 0.73378 Learning rate: 0.02 Mask loss: 0.1979 RPN box loss: 0.05528 RPN score loss: 0.00775 RPN total loss: 0.06304 Total loss: 1.29878 timestamp: 1654941423.645261 iteration: 34065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12725 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.18887 L1 loss: 0.0000e+00 L2 loss: 0.73365 Learning rate: 0.02 Mask loss: 0.14443 RPN box loss: 0.0214 RPN score loss: 0.00309 RPN total loss: 0.02449 Total loss: 1.09145 timestamp: 1654941426.777013 iteration: 34070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.0606 FastRCNN total loss: 0.17158 L1 loss: 0.0000e+00 L2 loss: 0.73354 Learning rate: 0.02 Mask loss: 0.1591 RPN box loss: 0.01703 RPN score loss: 0.00325 RPN total loss: 0.02028 Total loss: 1.0845 timestamp: 1654941429.9354112 iteration: 34075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07142 FastRCNN class loss: 0.0846 FastRCNN total loss: 0.15601 L1 loss: 0.0000e+00 L2 loss: 0.73344 Learning rate: 0.02 Mask loss: 0.16058 RPN box loss: 0.0196 RPN score loss: 0.0079 RPN total loss: 0.0275 Total loss: 1.07754 timestamp: 1654941433.1669307 iteration: 34080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16753 FastRCNN class loss: 0.084 FastRCNN total loss: 0.25153 L1 loss: 0.0000e+00 L2 loss: 0.73336 Learning rate: 0.02 Mask loss: 0.18644 RPN box loss: 0.03566 RPN score loss: 0.00655 RPN total loss: 0.04221 Total loss: 1.21354 timestamp: 1654941436.338586 iteration: 34085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16953 FastRCNN class loss: 0.1142 FastRCNN total loss: 0.28373 L1 loss: 0.0000e+00 L2 loss: 0.73326 Learning rate: 0.02 Mask loss: 0.2299 RPN box loss: 0.0341 RPN score loss: 0.01056 RPN total loss: 0.04467 Total loss: 1.29156 timestamp: 1654941439.5401204 iteration: 34090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12593 FastRCNN class loss: 0.09497 FastRCNN total loss: 0.2209 L1 loss: 0.0000e+00 L2 loss: 0.73315 Learning rate: 0.02 Mask loss: 0.15637 RPN box loss: 0.03025 RPN score loss: 0.00939 RPN total loss: 0.03964 Total loss: 1.15006 timestamp: 1654941442.756538 iteration: 34095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11733 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.19278 L1 loss: 0.0000e+00 L2 loss: 0.73306 Learning rate: 0.02 Mask loss: 0.11654 RPN box loss: 0.02096 RPN score loss: 0.00362 RPN total loss: 0.02458 Total loss: 1.06697 timestamp: 1654941445.9743073 iteration: 34100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15276 FastRCNN class loss: 0.07634 FastRCNN total loss: 0.2291 L1 loss: 0.0000e+00 L2 loss: 0.73295 Learning rate: 0.02 Mask loss: 0.1368 RPN box loss: 0.03244 RPN score loss: 0.00745 RPN total loss: 0.03989 Total loss: 1.13874 timestamp: 1654941449.184835 iteration: 34105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13166 FastRCNN class loss: 0.09726 FastRCNN total loss: 0.22892 L1 loss: 0.0000e+00 L2 loss: 0.73289 Learning rate: 0.02 Mask loss: 0.16899 RPN box loss: 0.0188 RPN score loss: 0.00581 RPN total loss: 0.02461 Total loss: 1.15541 timestamp: 1654941452.2650106 iteration: 34110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15651 FastRCNN class loss: 0.09698 FastRCNN total loss: 0.25349 L1 loss: 0.0000e+00 L2 loss: 0.73279 Learning rate: 0.02 Mask loss: 0.1828 RPN box loss: 0.01218 RPN score loss: 0.0086 RPN total loss: 0.02077 Total loss: 1.18986 timestamp: 1654941455.4731154 iteration: 34115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12038 FastRCNN class loss: 0.09626 FastRCNN total loss: 0.21664 L1 loss: 0.0000e+00 L2 loss: 0.73268 Learning rate: 0.02 Mask loss: 0.11761 RPN box loss: 0.02822 RPN score loss: 0.01471 RPN total loss: 0.04293 Total loss: 1.10986 timestamp: 1654941458.7591722 iteration: 34120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1365 FastRCNN class loss: 0.08963 FastRCNN total loss: 0.22614 L1 loss: 0.0000e+00 L2 loss: 0.73259 Learning rate: 0.02 Mask loss: 0.1629 RPN box loss: 0.04052 RPN score loss: 0.00995 RPN total loss: 0.05047 Total loss: 1.1721 timestamp: 1654941461.86066 iteration: 34125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21302 FastRCNN class loss: 0.07589 FastRCNN total loss: 0.28891 L1 loss: 0.0000e+00 L2 loss: 0.73249 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.03236 RPN score loss: 0.01501 RPN total loss: 0.04737 Total loss: 1.2212 timestamp: 1654941465.0153108 iteration: 34130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13546 FastRCNN class loss: 0.18124 FastRCNN total loss: 0.3167 L1 loss: 0.0000e+00 L2 loss: 0.73237 Learning rate: 0.02 Mask loss: 0.24991 RPN box loss: 0.0677 RPN score loss: 0.07772 RPN total loss: 0.14543 Total loss: 1.4444 timestamp: 1654941468.2287068 iteration: 34135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05881 FastRCNN class loss: 0.04821 FastRCNN total loss: 0.10702 L1 loss: 0.0000e+00 L2 loss: 0.73226 Learning rate: 0.02 Mask loss: 0.11802 RPN box loss: 0.04236 RPN score loss: 0.00309 RPN total loss: 0.04545 Total loss: 1.00276 timestamp: 1654941471.3775363 iteration: 34140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18393 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.26647 L1 loss: 0.0000e+00 L2 loss: 0.73216 Learning rate: 0.02 Mask loss: 0.13419 RPN box loss: 0.05175 RPN score loss: 0.00652 RPN total loss: 0.05827 Total loss: 1.1911 timestamp: 1654941474.608113 iteration: 34145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.18406 L1 loss: 0.0000e+00 L2 loss: 0.73206 Learning rate: 0.02 Mask loss: 0.1435 RPN box loss: 0.0696 RPN score loss: 0.00727 RPN total loss: 0.07687 Total loss: 1.13649 timestamp: 1654941477.8594196 iteration: 34150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15531 FastRCNN class loss: 0.06359 FastRCNN total loss: 0.21891 L1 loss: 0.0000e+00 L2 loss: 0.73198 Learning rate: 0.02 Mask loss: 0.15998 RPN box loss: 0.04396 RPN score loss: 0.01092 RPN total loss: 0.05489 Total loss: 1.16575 timestamp: 1654941481.09164 iteration: 34155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12007 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.17631 L1 loss: 0.0000e+00 L2 loss: 0.73189 Learning rate: 0.02 Mask loss: 0.16598 RPN box loss: 0.06514 RPN score loss: 0.0054 RPN total loss: 0.07054 Total loss: 1.14471 timestamp: 1654941484.2530081 iteration: 34160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08001 FastRCNN class loss: 0.04928 FastRCNN total loss: 0.12929 L1 loss: 0.0000e+00 L2 loss: 0.73177 Learning rate: 0.02 Mask loss: 0.08877 RPN box loss: 0.01954 RPN score loss: 0.00112 RPN total loss: 0.02066 Total loss: 0.97049 timestamp: 1654941487.4575837 iteration: 34165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08815 FastRCNN class loss: 0.06031 FastRCNN total loss: 0.14846 L1 loss: 0.0000e+00 L2 loss: 0.73166 Learning rate: 0.02 Mask loss: 0.20406 RPN box loss: 0.04342 RPN score loss: 0.00907 RPN total loss: 0.05249 Total loss: 1.13666 timestamp: 1654941490.653399 iteration: 34170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17924 FastRCNN class loss: 0.09603 FastRCNN total loss: 0.27527 L1 loss: 0.0000e+00 L2 loss: 0.73157 Learning rate: 0.02 Mask loss: 0.19369 RPN box loss: 0.02341 RPN score loss: 0.00701 RPN total loss: 0.03042 Total loss: 1.23096 timestamp: 1654941493.8357258 iteration: 34175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09918 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.15834 L1 loss: 0.0000e+00 L2 loss: 0.73145 Learning rate: 0.02 Mask loss: 0.1129 RPN box loss: 0.01884 RPN score loss: 0.00468 RPN total loss: 0.02352 Total loss: 1.02621 timestamp: 1654941496.9647968 iteration: 34180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17329 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.23972 L1 loss: 0.0000e+00 L2 loss: 0.73134 Learning rate: 0.02 Mask loss: 0.14877 RPN box loss: 0.06732 RPN score loss: 0.00599 RPN total loss: 0.07331 Total loss: 1.19314 timestamp: 1654941500.1459386 iteration: 34185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08921 FastRCNN class loss: 0.03639 FastRCNN total loss: 0.1256 L1 loss: 0.0000e+00 L2 loss: 0.73125 Learning rate: 0.02 Mask loss: 0.15301 RPN box loss: 0.00396 RPN score loss: 0.00128 RPN total loss: 0.00524 Total loss: 1.01509 timestamp: 1654941503.3998902 iteration: 34190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12345 FastRCNN class loss: 0.09851 FastRCNN total loss: 0.22196 L1 loss: 0.0000e+00 L2 loss: 0.73114 Learning rate: 0.02 Mask loss: 0.16601 RPN box loss: 0.02914 RPN score loss: 0.00772 RPN total loss: 0.03685 Total loss: 1.15597 timestamp: 1654941506.5832727 iteration: 34195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15132 FastRCNN class loss: 0.13185 FastRCNN total loss: 0.28317 L1 loss: 0.0000e+00 L2 loss: 0.73107 Learning rate: 0.02 Mask loss: 0.22173 RPN box loss: 0.03113 RPN score loss: 0.01218 RPN total loss: 0.04331 Total loss: 1.27929 timestamp: 1654941509.7327242 iteration: 34200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11884 FastRCNN class loss: 0.08934 FastRCNN total loss: 0.20818 L1 loss: 0.0000e+00 L2 loss: 0.73096 Learning rate: 0.02 Mask loss: 0.12678 RPN box loss: 0.03515 RPN score loss: 0.02436 RPN total loss: 0.05951 Total loss: 1.12543 timestamp: 1654941512.9230993 iteration: 34205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13937 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 0.73083 Learning rate: 0.02 Mask loss: 0.15041 RPN box loss: 0.01571 RPN score loss: 0.00879 RPN total loss: 0.0245 Total loss: 1.12075 timestamp: 1654941516.0813835 iteration: 34210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10363 FastRCNN class loss: 0.04291 FastRCNN total loss: 0.14653 L1 loss: 0.0000e+00 L2 loss: 0.73073 Learning rate: 0.02 Mask loss: 0.11487 RPN box loss: 0.01398 RPN score loss: 0.00686 RPN total loss: 0.02084 Total loss: 1.01297 timestamp: 1654941519.228134 iteration: 34215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07329 FastRCNN class loss: 0.04893 FastRCNN total loss: 0.12222 L1 loss: 0.0000e+00 L2 loss: 0.73065 Learning rate: 0.02 Mask loss: 0.17203 RPN box loss: 0.00409 RPN score loss: 0.00136 RPN total loss: 0.00545 Total loss: 1.03035 timestamp: 1654941522.4513378 iteration: 34220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.05893 FastRCNN total loss: 0.15533 L1 loss: 0.0000e+00 L2 loss: 0.73055 Learning rate: 0.02 Mask loss: 0.13824 RPN box loss: 0.04066 RPN score loss: 0.00522 RPN total loss: 0.04588 Total loss: 1.07001 timestamp: 1654941525.6771638 iteration: 34225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1393 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.20596 L1 loss: 0.0000e+00 L2 loss: 0.73045 Learning rate: 0.02 Mask loss: 0.12934 RPN box loss: 0.05827 RPN score loss: 0.01147 RPN total loss: 0.06974 Total loss: 1.13549 timestamp: 1654941528.8462613 iteration: 34230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16649 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.24185 L1 loss: 0.0000e+00 L2 loss: 0.73037 Learning rate: 0.02 Mask loss: 0.12804 RPN box loss: 0.0101 RPN score loss: 0.00503 RPN total loss: 0.01512 Total loss: 1.11539 timestamp: 1654941531.998309 iteration: 34235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.197 FastRCNN class loss: 0.07161 FastRCNN total loss: 0.26861 L1 loss: 0.0000e+00 L2 loss: 0.73026 Learning rate: 0.02 Mask loss: 0.15518 RPN box loss: 0.04543 RPN score loss: 0.00631 RPN total loss: 0.05174 Total loss: 1.20579 timestamp: 1654941535.285408 iteration: 34240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.19418 L1 loss: 0.0000e+00 L2 loss: 0.73016 Learning rate: 0.02 Mask loss: 0.16647 RPN box loss: 0.01859 RPN score loss: 0.00472 RPN total loss: 0.0233 Total loss: 1.11411 timestamp: 1654941538.4649243 iteration: 34245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10582 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.15514 L1 loss: 0.0000e+00 L2 loss: 0.73005 Learning rate: 0.02 Mask loss: 0.14531 RPN box loss: 0.02956 RPN score loss: 0.00798 RPN total loss: 0.03753 Total loss: 1.06804 timestamp: 1654941541.6843545 iteration: 34250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.102 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.18754 L1 loss: 0.0000e+00 L2 loss: 0.72996 Learning rate: 0.02 Mask loss: 0.14011 RPN box loss: 0.0143 RPN score loss: 0.00496 RPN total loss: 0.01926 Total loss: 1.07686 timestamp: 1654941544.8853939 iteration: 34255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12752 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.19288 L1 loss: 0.0000e+00 L2 loss: 0.72986 Learning rate: 0.02 Mask loss: 0.0913 RPN box loss: 0.0281 RPN score loss: 0.00643 RPN total loss: 0.03453 Total loss: 1.04857 timestamp: 1654941548.0972655 iteration: 34260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10409 FastRCNN class loss: 0.11823 FastRCNN total loss: 0.22232 L1 loss: 0.0000e+00 L2 loss: 0.72976 Learning rate: 0.02 Mask loss: 0.20277 RPN box loss: 0.00839 RPN score loss: 0.00148 RPN total loss: 0.00987 Total loss: 1.16472 timestamp: 1654941551.320042 iteration: 34265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10378 FastRCNN class loss: 0.12022 FastRCNN total loss: 0.224 L1 loss: 0.0000e+00 L2 loss: 0.72966 Learning rate: 0.02 Mask loss: 0.12629 RPN box loss: 0.02348 RPN score loss: 0.01361 RPN total loss: 0.03709 Total loss: 1.11704 timestamp: 1654941554.4262238 iteration: 34270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14291 FastRCNN class loss: 0.09432 FastRCNN total loss: 0.23723 L1 loss: 0.0000e+00 L2 loss: 0.72955 Learning rate: 0.02 Mask loss: 0.13845 RPN box loss: 0.01935 RPN score loss: 0.00969 RPN total loss: 0.02904 Total loss: 1.13427 timestamp: 1654941557.6754146 iteration: 34275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13184 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.20972 L1 loss: 0.0000e+00 L2 loss: 0.72945 Learning rate: 0.02 Mask loss: 0.13307 RPN box loss: 0.01485 RPN score loss: 0.00246 RPN total loss: 0.01731 Total loss: 1.08955 timestamp: 1654941560.8703673 iteration: 34280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12104 FastRCNN class loss: 0.04437 FastRCNN total loss: 0.16541 L1 loss: 0.0000e+00 L2 loss: 0.72934 Learning rate: 0.02 Mask loss: 0.14456 RPN box loss: 0.03094 RPN score loss: 0.00974 RPN total loss: 0.04069 Total loss: 1.08001 timestamp: 1654941564.107957 iteration: 34285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10483 FastRCNN class loss: 0.07431 FastRCNN total loss: 0.17914 L1 loss: 0.0000e+00 L2 loss: 0.72924 Learning rate: 0.02 Mask loss: 0.19378 RPN box loss: 0.03962 RPN score loss: 0.00586 RPN total loss: 0.04548 Total loss: 1.14765 timestamp: 1654941567.3371825 iteration: 34290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16416 FastRCNN class loss: 0.08659 FastRCNN total loss: 0.25075 L1 loss: 0.0000e+00 L2 loss: 0.72916 Learning rate: 0.02 Mask loss: 0.19155 RPN box loss: 0.02831 RPN score loss: 0.00536 RPN total loss: 0.03368 Total loss: 1.20513 timestamp: 1654941570.5016148 iteration: 34295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14564 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.21555 L1 loss: 0.0000e+00 L2 loss: 0.72905 Learning rate: 0.02 Mask loss: 0.1521 RPN box loss: 0.01757 RPN score loss: 0.00273 RPN total loss: 0.02029 Total loss: 1.11699 timestamp: 1654941573.6735485 iteration: 34300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09876 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.1516 L1 loss: 0.0000e+00 L2 loss: 0.72894 Learning rate: 0.02 Mask loss: 0.15157 RPN box loss: 0.01853 RPN score loss: 0.01232 RPN total loss: 0.03085 Total loss: 1.06296 timestamp: 1654941576.8678498 iteration: 34305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11424 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.18573 L1 loss: 0.0000e+00 L2 loss: 0.72887 Learning rate: 0.02 Mask loss: 0.12353 RPN box loss: 0.02201 RPN score loss: 0.00236 RPN total loss: 0.02437 Total loss: 1.06251 timestamp: 1654941580.1054792 iteration: 34310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14355 FastRCNN class loss: 0.09409 FastRCNN total loss: 0.23764 L1 loss: 0.0000e+00 L2 loss: 0.72875 Learning rate: 0.02 Mask loss: 0.14461 RPN box loss: 0.11844 RPN score loss: 0.00266 RPN total loss: 0.12109 Total loss: 1.2321 timestamp: 1654941583.2503252 iteration: 34315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12639 FastRCNN class loss: 0.11287 FastRCNN total loss: 0.23926 L1 loss: 0.0000e+00 L2 loss: 0.72863 Learning rate: 0.02 Mask loss: 0.16985 RPN box loss: 0.07159 RPN score loss: 0.00553 RPN total loss: 0.07712 Total loss: 1.21486 timestamp: 1654941586.4642358 iteration: 34320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10576 FastRCNN class loss: 0.09784 FastRCNN total loss: 0.2036 L1 loss: 0.0000e+00 L2 loss: 0.72856 Learning rate: 0.02 Mask loss: 0.14882 RPN box loss: 0.06054 RPN score loss: 0.01724 RPN total loss: 0.07779 Total loss: 1.15876 timestamp: 1654941589.6694868 iteration: 34325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16214 FastRCNN class loss: 0.07693 FastRCNN total loss: 0.23906 L1 loss: 0.0000e+00 L2 loss: 0.72846 Learning rate: 0.02 Mask loss: 0.14419 RPN box loss: 0.02879 RPN score loss: 0.02572 RPN total loss: 0.05451 Total loss: 1.16622 timestamp: 1654941592.8797557 iteration: 34330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11946 FastRCNN class loss: 0.0952 FastRCNN total loss: 0.21466 L1 loss: 0.0000e+00 L2 loss: 0.72837 Learning rate: 0.02 Mask loss: 0.15187 RPN box loss: 0.0203 RPN score loss: 0.00223 RPN total loss: 0.02253 Total loss: 1.11743 timestamp: 1654941596.1256216 iteration: 34335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16906 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.23263 L1 loss: 0.0000e+00 L2 loss: 0.72826 Learning rate: 0.02 Mask loss: 0.12148 RPN box loss: 0.06461 RPN score loss: 0.0074 RPN total loss: 0.07201 Total loss: 1.15438 timestamp: 1654941599.4190567 iteration: 34340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13914 FastRCNN class loss: 0.04205 FastRCNN total loss: 0.18119 L1 loss: 0.0000e+00 L2 loss: 0.72818 Learning rate: 0.02 Mask loss: 0.10118 RPN box loss: 0.02414 RPN score loss: 0.00585 RPN total loss: 0.02998 Total loss: 1.04054 timestamp: 1654941602.603824 iteration: 34345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08624 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.16194 L1 loss: 0.0000e+00 L2 loss: 0.72807 Learning rate: 0.02 Mask loss: 0.09422 RPN box loss: 0.01692 RPN score loss: 0.00585 RPN total loss: 0.02277 Total loss: 1.007 timestamp: 1654941605.8175647 iteration: 34350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21978 FastRCNN class loss: 0.1634 FastRCNN total loss: 0.38318 L1 loss: 0.0000e+00 L2 loss: 0.72798 Learning rate: 0.02 Mask loss: 0.24045 RPN box loss: 0.0359 RPN score loss: 0.00618 RPN total loss: 0.04209 Total loss: 1.3937 timestamp: 1654941608.9934177 iteration: 34355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11784 FastRCNN class loss: 0.06539 FastRCNN total loss: 0.18323 L1 loss: 0.0000e+00 L2 loss: 0.72789 Learning rate: 0.02 Mask loss: 0.18021 RPN box loss: 0.03477 RPN score loss: 0.0026 RPN total loss: 0.03736 Total loss: 1.1287 timestamp: 1654941612.1340377 iteration: 34360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07119 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.13103 L1 loss: 0.0000e+00 L2 loss: 0.72779 Learning rate: 0.02 Mask loss: 0.11466 RPN box loss: 0.02578 RPN score loss: 0.00584 RPN total loss: 0.03162 Total loss: 1.0051 timestamp: 1654941615.3253613 iteration: 34365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11449 FastRCNN class loss: 0.04696 FastRCNN total loss: 0.16145 L1 loss: 0.0000e+00 L2 loss: 0.72769 Learning rate: 0.02 Mask loss: 0.11402 RPN box loss: 0.02579 RPN score loss: 0.00682 RPN total loss: 0.03261 Total loss: 1.03577 timestamp: 1654941618.444915 iteration: 34370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10233 FastRCNN class loss: 0.10629 FastRCNN total loss: 0.20862 L1 loss: 0.0000e+00 L2 loss: 0.72757 Learning rate: 0.02 Mask loss: 0.17957 RPN box loss: 0.04653 RPN score loss: 0.00502 RPN total loss: 0.05155 Total loss: 1.16731 timestamp: 1654941621.6463776 iteration: 34375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17951 FastRCNN class loss: 0.09647 FastRCNN total loss: 0.27598 L1 loss: 0.0000e+00 L2 loss: 0.72745 Learning rate: 0.02 Mask loss: 0.16644 RPN box loss: 0.04664 RPN score loss: 0.00575 RPN total loss: 0.05239 Total loss: 1.22226 timestamp: 1654941624.8646252 iteration: 34380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10987 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.18399 L1 loss: 0.0000e+00 L2 loss: 0.72736 Learning rate: 0.02 Mask loss: 0.13086 RPN box loss: 0.02736 RPN score loss: 0.0112 RPN total loss: 0.03856 Total loss: 1.08077 timestamp: 1654941628.0486643 iteration: 34385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13567 FastRCNN class loss: 0.0887 FastRCNN total loss: 0.22437 L1 loss: 0.0000e+00 L2 loss: 0.72726 Learning rate: 0.02 Mask loss: 0.15033 RPN box loss: 0.03645 RPN score loss: 0.00611 RPN total loss: 0.04256 Total loss: 1.14452 timestamp: 1654941631.2209926 iteration: 34390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11073 FastRCNN class loss: 0.07099 FastRCNN total loss: 0.18172 L1 loss: 0.0000e+00 L2 loss: 0.72716 Learning rate: 0.02 Mask loss: 0.11076 RPN box loss: 0.04023 RPN score loss: 0.00755 RPN total loss: 0.04778 Total loss: 1.06742 timestamp: 1654941634.4385664 iteration: 34395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17057 FastRCNN class loss: 0.10535 FastRCNN total loss: 0.27592 L1 loss: 0.0000e+00 L2 loss: 0.72709 Learning rate: 0.02 Mask loss: 0.19033 RPN box loss: 0.02934 RPN score loss: 0.01747 RPN total loss: 0.04681 Total loss: 1.24014 timestamp: 1654941637.6865132 iteration: 34400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11753 FastRCNN class loss: 0.09188 FastRCNN total loss: 0.2094 L1 loss: 0.0000e+00 L2 loss: 0.72697 Learning rate: 0.02 Mask loss: 0.11833 RPN box loss: 0.02036 RPN score loss: 0.00665 RPN total loss: 0.02701 Total loss: 1.08171 timestamp: 1654941640.8342216 iteration: 34405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10903 FastRCNN class loss: 0.06373 FastRCNN total loss: 0.17276 L1 loss: 0.0000e+00 L2 loss: 0.72687 Learning rate: 0.02 Mask loss: 0.25657 RPN box loss: 0.03532 RPN score loss: 0.00326 RPN total loss: 0.03858 Total loss: 1.19479 timestamp: 1654941644.0459692 iteration: 34410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18841 FastRCNN class loss: 0.12618 FastRCNN total loss: 0.31459 L1 loss: 0.0000e+00 L2 loss: 0.72678 Learning rate: 0.02 Mask loss: 0.15412 RPN box loss: 0.03882 RPN score loss: 0.00313 RPN total loss: 0.04195 Total loss: 1.23743 timestamp: 1654941647.2128963 iteration: 34415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17243 FastRCNN class loss: 0.1146 FastRCNN total loss: 0.28703 L1 loss: 0.0000e+00 L2 loss: 0.72668 Learning rate: 0.02 Mask loss: 0.20274 RPN box loss: 0.02766 RPN score loss: 0.01472 RPN total loss: 0.04238 Total loss: 1.25883 timestamp: 1654941650.3853984 iteration: 34420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1539 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.21795 L1 loss: 0.0000e+00 L2 loss: 0.7266 Learning rate: 0.02 Mask loss: 0.12542 RPN box loss: 0.00735 RPN score loss: 0.00583 RPN total loss: 0.01317 Total loss: 1.08314 timestamp: 1654941653.6057842 iteration: 34425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13322 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.72651 Learning rate: 0.02 Mask loss: 0.14658 RPN box loss: 0.02293 RPN score loss: 0.01362 RPN total loss: 0.03655 Total loss: 1.10862 timestamp: 1654941656.7297904 iteration: 34430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17498 FastRCNN class loss: 0.05742 FastRCNN total loss: 0.23239 L1 loss: 0.0000e+00 L2 loss: 0.72642 Learning rate: 0.02 Mask loss: 0.11561 RPN box loss: 0.03003 RPN score loss: 0.00485 RPN total loss: 0.03487 Total loss: 1.1093 timestamp: 1654941659.904556 iteration: 34435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1477 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.23136 L1 loss: 0.0000e+00 L2 loss: 0.7263 Learning rate: 0.02 Mask loss: 0.15783 RPN box loss: 0.03833 RPN score loss: 0.00934 RPN total loss: 0.04767 Total loss: 1.16316 timestamp: 1654941663.1510017 iteration: 34440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10475 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.18692 L1 loss: 0.0000e+00 L2 loss: 0.72619 Learning rate: 0.02 Mask loss: 0.14752 RPN box loss: 0.05501 RPN score loss: 0.00995 RPN total loss: 0.06496 Total loss: 1.12559 timestamp: 1654941666.3022716 iteration: 34445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16518 FastRCNN class loss: 0.09907 FastRCNN total loss: 0.26425 L1 loss: 0.0000e+00 L2 loss: 0.7261 Learning rate: 0.02 Mask loss: 0.17797 RPN box loss: 0.04538 RPN score loss: 0.00859 RPN total loss: 0.05397 Total loss: 1.22229 timestamp: 1654941669.3666122 iteration: 34450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.11474 FastRCNN total loss: 0.24532 L1 loss: 0.0000e+00 L2 loss: 0.72601 Learning rate: 0.02 Mask loss: 0.16219 RPN box loss: 0.04672 RPN score loss: 0.01711 RPN total loss: 0.06383 Total loss: 1.19736 timestamp: 1654941672.5548952 iteration: 34455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10625 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.16797 L1 loss: 0.0000e+00 L2 loss: 0.72591 Learning rate: 0.02 Mask loss: 0.18874 RPN box loss: 0.04533 RPN score loss: 0.0085 RPN total loss: 0.05383 Total loss: 1.13645 timestamp: 1654941675.6749814 iteration: 34460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15419 FastRCNN class loss: 0.08336 FastRCNN total loss: 0.23755 L1 loss: 0.0000e+00 L2 loss: 0.72585 Learning rate: 0.02 Mask loss: 0.15816 RPN box loss: 0.02196 RPN score loss: 0.00655 RPN total loss: 0.02851 Total loss: 1.15007 timestamp: 1654941678.8778725 iteration: 34465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10513 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.16707 L1 loss: 0.0000e+00 L2 loss: 0.72572 Learning rate: 0.02 Mask loss: 0.12337 RPN box loss: 0.05985 RPN score loss: 0.00976 RPN total loss: 0.06961 Total loss: 1.08578 timestamp: 1654941682.0655718 iteration: 34470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.10988 FastRCNN total loss: 0.22898 L1 loss: 0.0000e+00 L2 loss: 0.72561 Learning rate: 0.02 Mask loss: 0.17201 RPN box loss: 0.02214 RPN score loss: 0.00383 RPN total loss: 0.02597 Total loss: 1.15257 timestamp: 1654941685.2549329 iteration: 34475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16865 FastRCNN class loss: 0.12989 FastRCNN total loss: 0.29853 L1 loss: 0.0000e+00 L2 loss: 0.72552 Learning rate: 0.02 Mask loss: 0.17366 RPN box loss: 0.0147 RPN score loss: 0.0106 RPN total loss: 0.02529 Total loss: 1.223 timestamp: 1654941688.476414 iteration: 34480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12843 FastRCNN class loss: 0.08024 FastRCNN total loss: 0.20867 L1 loss: 0.0000e+00 L2 loss: 0.72539 Learning rate: 0.02 Mask loss: 0.19135 RPN box loss: 0.03339 RPN score loss: 0.01331 RPN total loss: 0.0467 Total loss: 1.17211 timestamp: 1654941691.6297052 iteration: 34485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11016 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.17077 L1 loss: 0.0000e+00 L2 loss: 0.72532 Learning rate: 0.02 Mask loss: 0.07868 RPN box loss: 0.01068 RPN score loss: 0.00334 RPN total loss: 0.01402 Total loss: 0.98879 timestamp: 1654941694.7702703 iteration: 34490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07704 FastRCNN class loss: 0.04949 FastRCNN total loss: 0.12653 L1 loss: 0.0000e+00 L2 loss: 0.72526 Learning rate: 0.02 Mask loss: 0.07204 RPN box loss: 0.0472 RPN score loss: 0.00625 RPN total loss: 0.05345 Total loss: 0.97728 timestamp: 1654941697.9487755 iteration: 34495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06163 FastRCNN class loss: 0.04906 FastRCNN total loss: 0.11069 L1 loss: 0.0000e+00 L2 loss: 0.72516 Learning rate: 0.02 Mask loss: 0.11216 RPN box loss: 0.04645 RPN score loss: 0.00261 RPN total loss: 0.04906 Total loss: 0.99707 timestamp: 1654941701.12762 iteration: 34500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08843 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.13656 L1 loss: 0.0000e+00 L2 loss: 0.72504 Learning rate: 0.02 Mask loss: 0.12144 RPN box loss: 0.02772 RPN score loss: 0.00801 RPN total loss: 0.03573 Total loss: 1.01877 timestamp: 1654941704.3070397 iteration: 34505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13658 FastRCNN class loss: 0.10377 FastRCNN total loss: 0.24035 L1 loss: 0.0000e+00 L2 loss: 0.72492 Learning rate: 0.02 Mask loss: 0.20797 RPN box loss: 0.0197 RPN score loss: 0.00215 RPN total loss: 0.02185 Total loss: 1.19509 timestamp: 1654941707.474075 iteration: 34510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15405 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.21892 L1 loss: 0.0000e+00 L2 loss: 0.72483 Learning rate: 0.02 Mask loss: 0.24045 RPN box loss: 0.01829 RPN score loss: 0.00726 RPN total loss: 0.02555 Total loss: 1.20975 timestamp: 1654941710.6499577 iteration: 34515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1694 FastRCNN class loss: 0.10366 FastRCNN total loss: 0.27305 L1 loss: 0.0000e+00 L2 loss: 0.72473 Learning rate: 0.02 Mask loss: 0.21305 RPN box loss: 0.04086 RPN score loss: 0.01375 RPN total loss: 0.0546 Total loss: 1.26543 timestamp: 1654941713.8881445 iteration: 34520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12466 FastRCNN class loss: 0.079 FastRCNN total loss: 0.20366 L1 loss: 0.0000e+00 L2 loss: 0.72463 Learning rate: 0.02 Mask loss: 0.16752 RPN box loss: 0.04605 RPN score loss: 0.01179 RPN total loss: 0.05785 Total loss: 1.15365 timestamp: 1654941717.1067388 iteration: 34525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11017 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.1945 L1 loss: 0.0000e+00 L2 loss: 0.72455 Learning rate: 0.02 Mask loss: 0.16146 RPN box loss: 0.02515 RPN score loss: 0.00316 RPN total loss: 0.02831 Total loss: 1.10882 timestamp: 1654941720.2991812 iteration: 34530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0949 FastRCNN class loss: 0.04171 FastRCNN total loss: 0.13661 L1 loss: 0.0000e+00 L2 loss: 0.72447 Learning rate: 0.02 Mask loss: 0.08205 RPN box loss: 0.00703 RPN score loss: 0.00198 RPN total loss: 0.009 Total loss: 0.95214 timestamp: 1654941723.4752347 iteration: 34535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12631 FastRCNN class loss: 0.10059 FastRCNN total loss: 0.2269 L1 loss: 0.0000e+00 L2 loss: 0.72436 Learning rate: 0.02 Mask loss: 0.14298 RPN box loss: 0.01817 RPN score loss: 0.00333 RPN total loss: 0.0215 Total loss: 1.11575 timestamp: 1654941726.7380645 iteration: 34540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15265 FastRCNN class loss: 0.13827 FastRCNN total loss: 0.29092 L1 loss: 0.0000e+00 L2 loss: 0.72427 Learning rate: 0.02 Mask loss: 0.21429 RPN box loss: 0.06798 RPN score loss: 0.02658 RPN total loss: 0.09456 Total loss: 1.32404 timestamp: 1654941729.9857929 iteration: 34545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13163 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.20557 L1 loss: 0.0000e+00 L2 loss: 0.7242 Learning rate: 0.02 Mask loss: 0.11045 RPN box loss: 0.01037 RPN score loss: 0.01158 RPN total loss: 0.02195 Total loss: 1.06217 timestamp: 1654941733.119136 iteration: 34550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11241 FastRCNN class loss: 0.0468 FastRCNN total loss: 0.15922 L1 loss: 0.0000e+00 L2 loss: 0.72412 Learning rate: 0.02 Mask loss: 0.12679 RPN box loss: 0.00371 RPN score loss: 0.00371 RPN total loss: 0.00743 Total loss: 1.01755 timestamp: 1654941736.245524 iteration: 34555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10494 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.19583 L1 loss: 0.0000e+00 L2 loss: 0.72407 Learning rate: 0.02 Mask loss: 0.13975 RPN box loss: 0.02658 RPN score loss: 0.00432 RPN total loss: 0.0309 Total loss: 1.09055 timestamp: 1654941739.4586039 iteration: 34560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2374 FastRCNN class loss: 0.15242 FastRCNN total loss: 0.38982 L1 loss: 0.0000e+00 L2 loss: 0.72398 Learning rate: 0.02 Mask loss: 0.21783 RPN box loss: 0.04226 RPN score loss: 0.01554 RPN total loss: 0.0578 Total loss: 1.38943 timestamp: 1654941742.6893206 iteration: 34565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08354 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.7239 Learning rate: 0.02 Mask loss: 0.15341 RPN box loss: 0.03947 RPN score loss: 0.00996 RPN total loss: 0.04943 Total loss: 1.09318 timestamp: 1654941745.8636034 iteration: 34570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11735 FastRCNN class loss: 0.07389 FastRCNN total loss: 0.19125 L1 loss: 0.0000e+00 L2 loss: 0.7238 Learning rate: 0.02 Mask loss: 0.10977 RPN box loss: 0.07112 RPN score loss: 0.00559 RPN total loss: 0.07671 Total loss: 1.10152 timestamp: 1654941749.0697987 iteration: 34575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09079 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.15337 L1 loss: 0.0000e+00 L2 loss: 0.72372 Learning rate: 0.02 Mask loss: 0.13157 RPN box loss: 0.02215 RPN score loss: 0.00664 RPN total loss: 0.02879 Total loss: 1.03745 timestamp: 1654941752.2743776 iteration: 34580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10068 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.18119 L1 loss: 0.0000e+00 L2 loss: 0.72363 Learning rate: 0.02 Mask loss: 0.11401 RPN box loss: 0.02854 RPN score loss: 0.00451 RPN total loss: 0.03305 Total loss: 1.05187 timestamp: 1654941755.4895642 iteration: 34585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08159 FastRCNN class loss: 0.03904 FastRCNN total loss: 0.12063 L1 loss: 0.0000e+00 L2 loss: 0.72353 Learning rate: 0.02 Mask loss: 0.09907 RPN box loss: 0.00264 RPN score loss: 0.00207 RPN total loss: 0.00471 Total loss: 0.94793 timestamp: 1654941758.6569288 iteration: 34590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0613 FastRCNN class loss: 0.03816 FastRCNN total loss: 0.09945 L1 loss: 0.0000e+00 L2 loss: 0.72341 Learning rate: 0.02 Mask loss: 0.08122 RPN box loss: 0.02102 RPN score loss: 0.00345 RPN total loss: 0.02447 Total loss: 0.92856 timestamp: 1654941761.8468978 iteration: 34595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12103 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.19596 L1 loss: 0.0000e+00 L2 loss: 0.72331 Learning rate: 0.02 Mask loss: 0.13761 RPN box loss: 0.01631 RPN score loss: 0.00359 RPN total loss: 0.0199 Total loss: 1.07678 timestamp: 1654941765.0358105 iteration: 34600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08772 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.15773 L1 loss: 0.0000e+00 L2 loss: 0.72321 Learning rate: 0.02 Mask loss: 0.11913 RPN box loss: 0.01516 RPN score loss: 0.00932 RPN total loss: 0.02448 Total loss: 1.02455 timestamp: 1654941768.2227504 iteration: 34605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07895 FastRCNN class loss: 0.06718 FastRCNN total loss: 0.14614 L1 loss: 0.0000e+00 L2 loss: 0.72312 Learning rate: 0.02 Mask loss: 0.13533 RPN box loss: 0.02339 RPN score loss: 0.01315 RPN total loss: 0.03655 Total loss: 1.04113 timestamp: 1654941771.4355116 iteration: 34610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1547 FastRCNN class loss: 0.09159 FastRCNN total loss: 0.24629 L1 loss: 0.0000e+00 L2 loss: 0.72302 Learning rate: 0.02 Mask loss: 0.11587 RPN box loss: 0.01562 RPN score loss: 0.01148 RPN total loss: 0.02711 Total loss: 1.11228 timestamp: 1654941774.6878042 iteration: 34615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12124 FastRCNN class loss: 0.06158 FastRCNN total loss: 0.18281 L1 loss: 0.0000e+00 L2 loss: 0.72293 Learning rate: 0.02 Mask loss: 0.13741 RPN box loss: 0.04993 RPN score loss: 0.00989 RPN total loss: 0.05982 Total loss: 1.10296 timestamp: 1654941777.7762897 iteration: 34620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16435 FastRCNN class loss: 0.09878 FastRCNN total loss: 0.26312 L1 loss: 0.0000e+00 L2 loss: 0.7228 Learning rate: 0.02 Mask loss: 0.1682 RPN box loss: 0.02372 RPN score loss: 0.00386 RPN total loss: 0.02758 Total loss: 1.18171 timestamp: 1654941781.0097086 iteration: 34625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18398 FastRCNN class loss: 0.14444 FastRCNN total loss: 0.32842 L1 loss: 0.0000e+00 L2 loss: 0.72273 Learning rate: 0.02 Mask loss: 0.15002 RPN box loss: 0.01968 RPN score loss: 0.00369 RPN total loss: 0.02337 Total loss: 1.22453 timestamp: 1654941784.2296684 iteration: 34630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17814 FastRCNN class loss: 0.09353 FastRCNN total loss: 0.27167 L1 loss: 0.0000e+00 L2 loss: 0.72266 Learning rate: 0.02 Mask loss: 0.20604 RPN box loss: 0.02073 RPN score loss: 0.00717 RPN total loss: 0.0279 Total loss: 1.22827 timestamp: 1654941787.4423118 iteration: 34635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14947 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.21387 L1 loss: 0.0000e+00 L2 loss: 0.72254 Learning rate: 0.02 Mask loss: 0.18682 RPN box loss: 0.02896 RPN score loss: 0.01164 RPN total loss: 0.04059 Total loss: 1.16383 timestamp: 1654941790.642419 iteration: 34640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10758 FastRCNN class loss: 0.08032 FastRCNN total loss: 0.1879 L1 loss: 0.0000e+00 L2 loss: 0.72247 Learning rate: 0.02 Mask loss: 0.13927 RPN box loss: 0.02692 RPN score loss: 0.00644 RPN total loss: 0.03336 Total loss: 1.083 timestamp: 1654941793.797413 iteration: 34645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14865 FastRCNN class loss: 0.13647 FastRCNN total loss: 0.28512 L1 loss: 0.0000e+00 L2 loss: 0.7224 Learning rate: 0.02 Mask loss: 0.12654 RPN box loss: 0.03407 RPN score loss: 0.00138 RPN total loss: 0.03544 Total loss: 1.1695 timestamp: 1654941797.0065517 iteration: 34650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15358 FastRCNN class loss: 0.08677 FastRCNN total loss: 0.24035 L1 loss: 0.0000e+00 L2 loss: 0.7223 Learning rate: 0.02 Mask loss: 0.11684 RPN box loss: 0.03581 RPN score loss: 0.00261 RPN total loss: 0.03841 Total loss: 1.1179 timestamp: 1654941800.1212428 iteration: 34655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11359 FastRCNN class loss: 0.06774 FastRCNN total loss: 0.18133 L1 loss: 0.0000e+00 L2 loss: 0.72221 Learning rate: 0.02 Mask loss: 0.1549 RPN box loss: 0.01157 RPN score loss: 0.00213 RPN total loss: 0.01369 Total loss: 1.07214 timestamp: 1654941803.3572247 iteration: 34660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13606 FastRCNN class loss: 0.10965 FastRCNN total loss: 0.2457 L1 loss: 0.0000e+00 L2 loss: 0.72212 Learning rate: 0.02 Mask loss: 0.0997 RPN box loss: 0.05305 RPN score loss: 0.00401 RPN total loss: 0.05706 Total loss: 1.12458 timestamp: 1654941806.5681489 iteration: 34665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13615 FastRCNN class loss: 0.13321 FastRCNN total loss: 0.26936 L1 loss: 0.0000e+00 L2 loss: 0.72204 Learning rate: 0.02 Mask loss: 0.14626 RPN box loss: 0.04067 RPN score loss: 0.00798 RPN total loss: 0.04866 Total loss: 1.18632 timestamp: 1654941809.7686417 iteration: 34670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07837 FastRCNN class loss: 0.04285 FastRCNN total loss: 0.12122 L1 loss: 0.0000e+00 L2 loss: 0.72193 Learning rate: 0.02 Mask loss: 0.09708 RPN box loss: 0.01216 RPN score loss: 0.00283 RPN total loss: 0.01499 Total loss: 0.95522 timestamp: 1654941812.9565609 iteration: 34675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14341 FastRCNN class loss: 0.1074 FastRCNN total loss: 0.25081 L1 loss: 0.0000e+00 L2 loss: 0.72181 Learning rate: 0.02 Mask loss: 0.15433 RPN box loss: 0.04453 RPN score loss: 0.00911 RPN total loss: 0.05364 Total loss: 1.1806 timestamp: 1654941816.1255882 iteration: 34680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24638 FastRCNN class loss: 0.11557 FastRCNN total loss: 0.36195 L1 loss: 0.0000e+00 L2 loss: 0.72171 Learning rate: 0.02 Mask loss: 0.16564 RPN box loss: 0.05314 RPN score loss: 0.00969 RPN total loss: 0.06284 Total loss: 1.31214 timestamp: 1654941819.3429317 iteration: 34685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15255 FastRCNN class loss: 0.1127 FastRCNN total loss: 0.26525 L1 loss: 0.0000e+00 L2 loss: 0.72164 Learning rate: 0.02 Mask loss: 0.17638 RPN box loss: 0.02176 RPN score loss: 0.00669 RPN total loss: 0.02845 Total loss: 1.19172 timestamp: 1654941822.5616782 iteration: 34690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10488 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.1841 L1 loss: 0.0000e+00 L2 loss: 0.72155 Learning rate: 0.02 Mask loss: 0.15557 RPN box loss: 0.03364 RPN score loss: 0.00332 RPN total loss: 0.03696 Total loss: 1.09818 timestamp: 1654941825.8751569 iteration: 34695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11335 FastRCNN class loss: 0.11144 FastRCNN total loss: 0.2248 L1 loss: 0.0000e+00 L2 loss: 0.72147 Learning rate: 0.02 Mask loss: 0.15978 RPN box loss: 0.019 RPN score loss: 0.00739 RPN total loss: 0.0264 Total loss: 1.13244 timestamp: 1654941829.088677 iteration: 34700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25328 FastRCNN class loss: 0.11917 FastRCNN total loss: 0.37244 L1 loss: 0.0000e+00 L2 loss: 0.72139 Learning rate: 0.02 Mask loss: 0.19763 RPN box loss: 0.03994 RPN score loss: 0.02418 RPN total loss: 0.06412 Total loss: 1.35558 timestamp: 1654941832.246842 iteration: 34705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08638 FastRCNN class loss: 0.04414 FastRCNN total loss: 0.13052 L1 loss: 0.0000e+00 L2 loss: 0.72128 Learning rate: 0.02 Mask loss: 0.12735 RPN box loss: 0.01255 RPN score loss: 0.00171 RPN total loss: 0.01426 Total loss: 0.99341 timestamp: 1654941835.4716535 iteration: 34710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12446 FastRCNN class loss: 0.10739 FastRCNN total loss: 0.23185 L1 loss: 0.0000e+00 L2 loss: 0.72117 Learning rate: 0.02 Mask loss: 0.14214 RPN box loss: 0.04326 RPN score loss: 0.01107 RPN total loss: 0.05432 Total loss: 1.14948 timestamp: 1654941838.6831267 iteration: 34715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10102 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.15948 L1 loss: 0.0000e+00 L2 loss: 0.72109 Learning rate: 0.02 Mask loss: 0.12163 RPN box loss: 0.03242 RPN score loss: 0.00453 RPN total loss: 0.03695 Total loss: 1.03915 timestamp: 1654941841.8561826 iteration: 34720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10287 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.1624 L1 loss: 0.0000e+00 L2 loss: 0.72099 Learning rate: 0.02 Mask loss: 0.14809 RPN box loss: 0.03641 RPN score loss: 0.01199 RPN total loss: 0.0484 Total loss: 1.07989 timestamp: 1654941845.0555246 iteration: 34725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18746 FastRCNN class loss: 0.07861 FastRCNN total loss: 0.26607 L1 loss: 0.0000e+00 L2 loss: 0.72088 Learning rate: 0.02 Mask loss: 0.15178 RPN box loss: 0.03573 RPN score loss: 0.0042 RPN total loss: 0.03993 Total loss: 1.17865 timestamp: 1654941848.1786954 iteration: 34730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14171 FastRCNN class loss: 0.14516 FastRCNN total loss: 0.28686 L1 loss: 0.0000e+00 L2 loss: 0.72076 Learning rate: 0.02 Mask loss: 0.17685 RPN box loss: 0.04755 RPN score loss: 0.00775 RPN total loss: 0.0553 Total loss: 1.23977 timestamp: 1654941851.3564556 iteration: 34735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05372 FastRCNN class loss: 0.05046 FastRCNN total loss: 0.10418 L1 loss: 0.0000e+00 L2 loss: 0.72066 Learning rate: 0.02 Mask loss: 0.15851 RPN box loss: 0.01148 RPN score loss: 0.00335 RPN total loss: 0.01482 Total loss: 0.99817 timestamp: 1654941854.5004897 iteration: 34740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15772 FastRCNN class loss: 0.09493 FastRCNN total loss: 0.25265 L1 loss: 0.0000e+00 L2 loss: 0.72057 Learning rate: 0.02 Mask loss: 0.12582 RPN box loss: 0.04308 RPN score loss: 0.0029 RPN total loss: 0.04598 Total loss: 1.14501 timestamp: 1654941857.716321 iteration: 34745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10847 FastRCNN class loss: 0.08386 FastRCNN total loss: 0.19233 L1 loss: 0.0000e+00 L2 loss: 0.72047 Learning rate: 0.02 Mask loss: 0.14874 RPN box loss: 0.01914 RPN score loss: 0.00218 RPN total loss: 0.02131 Total loss: 1.08286 timestamp: 1654941860.9041507 iteration: 34750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13114 FastRCNN class loss: 0.06872 FastRCNN total loss: 0.19986 L1 loss: 0.0000e+00 L2 loss: 0.72038 Learning rate: 0.02 Mask loss: 0.12743 RPN box loss: 0.05557 RPN score loss: 0.00527 RPN total loss: 0.06084 Total loss: 1.10851 timestamp: 1654941864.087039 iteration: 34755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09213 FastRCNN class loss: 0.07998 FastRCNN total loss: 0.17211 L1 loss: 0.0000e+00 L2 loss: 0.72026 Learning rate: 0.02 Mask loss: 0.1641 RPN box loss: 0.0255 RPN score loss: 0.01643 RPN total loss: 0.04194 Total loss: 1.09841 timestamp: 1654941867.2693968 iteration: 34760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13793 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.22083 L1 loss: 0.0000e+00 L2 loss: 0.72018 Learning rate: 0.02 Mask loss: 0.21037 RPN box loss: 0.02671 RPN score loss: 0.00413 RPN total loss: 0.03084 Total loss: 1.18222 timestamp: 1654941870.465569 iteration: 34765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08677 FastRCNN class loss: 0.05391 FastRCNN total loss: 0.14068 L1 loss: 0.0000e+00 L2 loss: 0.72008 Learning rate: 0.02 Mask loss: 0.10891 RPN box loss: 0.03624 RPN score loss: 0.00657 RPN total loss: 0.04281 Total loss: 1.01249 timestamp: 1654941873.6799686 iteration: 34770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14489 FastRCNN class loss: 0.1377 FastRCNN total loss: 0.28259 L1 loss: 0.0000e+00 L2 loss: 0.71997 Learning rate: 0.02 Mask loss: 0.21698 RPN box loss: 0.04666 RPN score loss: 0.00548 RPN total loss: 0.05214 Total loss: 1.27168 timestamp: 1654941876.8462496 iteration: 34775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17066 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.2434 L1 loss: 0.0000e+00 L2 loss: 0.71988 Learning rate: 0.02 Mask loss: 0.26655 RPN box loss: 0.0503 RPN score loss: 0.00696 RPN total loss: 0.05726 Total loss: 1.28708 timestamp: 1654941880.0730252 iteration: 34780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09453 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.17554 L1 loss: 0.0000e+00 L2 loss: 0.71976 Learning rate: 0.02 Mask loss: 0.13954 RPN box loss: 0.01302 RPN score loss: 0.00815 RPN total loss: 0.02117 Total loss: 1.05601 timestamp: 1654941883.2123847 iteration: 34785 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12311 FastRCNN class loss: 0.06356 FastRCNN total loss: 0.18668 L1 loss: 0.0000e+00 L2 loss: 0.71967 Learning rate: 0.02 Mask loss: 0.13868 RPN box loss: 0.0878 RPN score loss: 0.00514 RPN total loss: 0.09294 Total loss: 1.13796 timestamp: 1654941886.4807332 iteration: 34790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09476 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.15023 L1 loss: 0.0000e+00 L2 loss: 0.71957 Learning rate: 0.02 Mask loss: 0.14224 RPN box loss: 0.02119 RPN score loss: 0.00311 RPN total loss: 0.0243 Total loss: 1.03635 timestamp: 1654941889.6751819 iteration: 34795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13372 FastRCNN class loss: 0.09773 FastRCNN total loss: 0.23146 L1 loss: 0.0000e+00 L2 loss: 0.71947 Learning rate: 0.02 Mask loss: 0.22307 RPN box loss: 0.02041 RPN score loss: 0.00621 RPN total loss: 0.02662 Total loss: 1.20061 timestamp: 1654941892.9120831 iteration: 34800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19889 FastRCNN class loss: 0.12053 FastRCNN total loss: 0.31942 L1 loss: 0.0000e+00 L2 loss: 0.71938 Learning rate: 0.02 Mask loss: 0.17842 RPN box loss: 0.0269 RPN score loss: 0.00794 RPN total loss: 0.03484 Total loss: 1.25205 timestamp: 1654941896.1342468 iteration: 34805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.19967 L1 loss: 0.0000e+00 L2 loss: 0.71927 Learning rate: 0.02 Mask loss: 0.17201 RPN box loss: 0.05007 RPN score loss: 0.00479 RPN total loss: 0.05486 Total loss: 1.1458 timestamp: 1654941899.3299305 iteration: 34810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19007 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.26133 L1 loss: 0.0000e+00 L2 loss: 0.71917 Learning rate: 0.02 Mask loss: 0.14503 RPN box loss: 0.02309 RPN score loss: 0.0037 RPN total loss: 0.02679 Total loss: 1.15232 timestamp: 1654941902.5415103 iteration: 34815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.0572 FastRCNN total loss: 0.13667 L1 loss: 0.0000e+00 L2 loss: 0.71908 Learning rate: 0.02 Mask loss: 0.11771 RPN box loss: 0.01084 RPN score loss: 0.01113 RPN total loss: 0.02197 Total loss: 0.99544 timestamp: 1654941905.7117596 iteration: 34820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07531 FastRCNN class loss: 0.0469 FastRCNN total loss: 0.12222 L1 loss: 0.0000e+00 L2 loss: 0.71898 Learning rate: 0.02 Mask loss: 0.10083 RPN box loss: 0.02544 RPN score loss: 0.00279 RPN total loss: 0.02823 Total loss: 0.97026 timestamp: 1654941909.033331 iteration: 34825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21534 FastRCNN class loss: 0.14039 FastRCNN total loss: 0.35573 L1 loss: 0.0000e+00 L2 loss: 0.71889 Learning rate: 0.02 Mask loss: 0.28385 RPN box loss: 0.08306 RPN score loss: 0.0125 RPN total loss: 0.09555 Total loss: 1.45403 timestamp: 1654941912.271594 iteration: 34830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14021 FastRCNN class loss: 0.05927 FastRCNN total loss: 0.19947 L1 loss: 0.0000e+00 L2 loss: 0.71877 Learning rate: 0.02 Mask loss: 0.12972 RPN box loss: 0.02246 RPN score loss: 0.00278 RPN total loss: 0.02523 Total loss: 1.0732 timestamp: 1654941915.5423348 iteration: 34835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13074 FastRCNN class loss: 0.10561 FastRCNN total loss: 0.23634 L1 loss: 0.0000e+00 L2 loss: 0.71866 Learning rate: 0.02 Mask loss: 0.13857 RPN box loss: 0.03085 RPN score loss: 0.0102 RPN total loss: 0.04105 Total loss: 1.13462 timestamp: 1654941918.813277 iteration: 34840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09064 FastRCNN class loss: 0.06249 FastRCNN total loss: 0.15313 L1 loss: 0.0000e+00 L2 loss: 0.71858 Learning rate: 0.02 Mask loss: 0.11815 RPN box loss: 0.0407 RPN score loss: 0.00132 RPN total loss: 0.04201 Total loss: 1.03186 timestamp: 1654941921.966996 iteration: 34845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06887 FastRCNN class loss: 0.03723 FastRCNN total loss: 0.1061 L1 loss: 0.0000e+00 L2 loss: 0.71849 Learning rate: 0.02 Mask loss: 0.12677 RPN box loss: 0.01085 RPN score loss: 0.00179 RPN total loss: 0.01264 Total loss: 0.964 timestamp: 1654941925.1136348 iteration: 34850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09234 FastRCNN class loss: 0.08993 FastRCNN total loss: 0.18227 L1 loss: 0.0000e+00 L2 loss: 0.71839 Learning rate: 0.02 Mask loss: 0.11936 RPN box loss: 0.03449 RPN score loss: 0.0066 RPN total loss: 0.04108 Total loss: 1.06111 timestamp: 1654941928.3783069 iteration: 34855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07691 FastRCNN class loss: 0.05439 FastRCNN total loss: 0.13129 L1 loss: 0.0000e+00 L2 loss: 0.7183 Learning rate: 0.02 Mask loss: 0.25622 RPN box loss: 0.03452 RPN score loss: 0.00797 RPN total loss: 0.04249 Total loss: 1.14831 timestamp: 1654941931.630079 iteration: 34860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11648 FastRCNN class loss: 0.09986 FastRCNN total loss: 0.21634 L1 loss: 0.0000e+00 L2 loss: 0.71818 Learning rate: 0.02 Mask loss: 0.1456 RPN box loss: 0.02461 RPN score loss: 0.00587 RPN total loss: 0.03049 Total loss: 1.1106 timestamp: 1654941934.8245153 iteration: 34865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18245 FastRCNN class loss: 0.09631 FastRCNN total loss: 0.27876 L1 loss: 0.0000e+00 L2 loss: 0.7181 Learning rate: 0.02 Mask loss: 0.19669 RPN box loss: 0.01715 RPN score loss: 0.02211 RPN total loss: 0.03926 Total loss: 1.23281 timestamp: 1654941938.0420818 iteration: 34870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17151 FastRCNN class loss: 0.06596 FastRCNN total loss: 0.23747 L1 loss: 0.0000e+00 L2 loss: 0.71803 Learning rate: 0.02 Mask loss: 0.11932 RPN box loss: 0.02907 RPN score loss: 0.00591 RPN total loss: 0.03498 Total loss: 1.10979 timestamp: 1654941941.198126 iteration: 34875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14325 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.23778 L1 loss: 0.0000e+00 L2 loss: 0.71793 Learning rate: 0.02 Mask loss: 0.16353 RPN box loss: 0.02702 RPN score loss: 0.0047 RPN total loss: 0.03173 Total loss: 1.15097 timestamp: 1654941944.3302352 iteration: 34880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15986 FastRCNN class loss: 0.12171 FastRCNN total loss: 0.28157 L1 loss: 0.0000e+00 L2 loss: 0.71785 Learning rate: 0.02 Mask loss: 0.25518 RPN box loss: 0.02807 RPN score loss: 0.00809 RPN total loss: 0.03616 Total loss: 1.29076 timestamp: 1654941947.5847058 iteration: 34885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16228 FastRCNN class loss: 0.0999 FastRCNN total loss: 0.26218 L1 loss: 0.0000e+00 L2 loss: 0.71776 Learning rate: 0.02 Mask loss: 0.12954 RPN box loss: 0.03377 RPN score loss: 0.00408 RPN total loss: 0.03784 Total loss: 1.14731 timestamp: 1654941950.8610606 iteration: 34890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08839 FastRCNN class loss: 0.05543 FastRCNN total loss: 0.14382 L1 loss: 0.0000e+00 L2 loss: 0.71765 Learning rate: 0.02 Mask loss: 0.08434 RPN box loss: 0.00762 RPN score loss: 0.00366 RPN total loss: 0.01128 Total loss: 0.95709 timestamp: 1654941954.0289667 iteration: 34895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11864 FastRCNN class loss: 0.05887 FastRCNN total loss: 0.1775 L1 loss: 0.0000e+00 L2 loss: 0.71756 Learning rate: 0.02 Mask loss: 0.14657 RPN box loss: 0.02295 RPN score loss: 0.00459 RPN total loss: 0.02754 Total loss: 1.06918 timestamp: 1654941957.185367 iteration: 34900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19544 FastRCNN class loss: 0.09474 FastRCNN total loss: 0.29019 L1 loss: 0.0000e+00 L2 loss: 0.71746 Learning rate: 0.02 Mask loss: 0.1589 RPN box loss: 0.01 RPN score loss: 0.00729 RPN total loss: 0.01729 Total loss: 1.18384 timestamp: 1654941960.4370284 iteration: 34905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12728 FastRCNN class loss: 0.08771 FastRCNN total loss: 0.21498 L1 loss: 0.0000e+00 L2 loss: 0.71736 Learning rate: 0.02 Mask loss: 0.13542 RPN box loss: 0.03558 RPN score loss: 0.00527 RPN total loss: 0.04085 Total loss: 1.10861 timestamp: 1654941963.7111542 iteration: 34910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11099 FastRCNN class loss: 0.04476 FastRCNN total loss: 0.15576 L1 loss: 0.0000e+00 L2 loss: 0.71729 Learning rate: 0.02 Mask loss: 0.10938 RPN box loss: 0.01197 RPN score loss: 0.00225 RPN total loss: 0.01422 Total loss: 0.99664 timestamp: 1654941966.9154646 iteration: 34915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1253 FastRCNN class loss: 0.08521 FastRCNN total loss: 0.21051 L1 loss: 0.0000e+00 L2 loss: 0.71718 Learning rate: 0.02 Mask loss: 0.16958 RPN box loss: 0.04226 RPN score loss: 0.00741 RPN total loss: 0.04967 Total loss: 1.14694 timestamp: 1654941970.0949593 iteration: 34920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07379 FastRCNN class loss: 0.03871 FastRCNN total loss: 0.11251 L1 loss: 0.0000e+00 L2 loss: 0.71708 Learning rate: 0.02 Mask loss: 0.11875 RPN box loss: 0.00764 RPN score loss: 0.00251 RPN total loss: 0.01015 Total loss: 0.95849 timestamp: 1654941973.2975976 iteration: 34925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16913 FastRCNN class loss: 0.05207 FastRCNN total loss: 0.2212 L1 loss: 0.0000e+00 L2 loss: 0.71697 Learning rate: 0.02 Mask loss: 0.11908 RPN box loss: 0.01328 RPN score loss: 0.0056 RPN total loss: 0.01888 Total loss: 1.07613 timestamp: 1654941976.457386 iteration: 34930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.11425 FastRCNN total loss: 0.24287 L1 loss: 0.0000e+00 L2 loss: 0.71687 Learning rate: 0.02 Mask loss: 0.15083 RPN box loss: 0.03432 RPN score loss: 0.01644 RPN total loss: 0.05077 Total loss: 1.16134 timestamp: 1654941979.582401 iteration: 34935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07626 FastRCNN class loss: 0.04865 FastRCNN total loss: 0.12491 L1 loss: 0.0000e+00 L2 loss: 0.71676 Learning rate: 0.02 Mask loss: 0.12805 RPN box loss: 0.03661 RPN score loss: 0.00669 RPN total loss: 0.0433 Total loss: 1.01303 timestamp: 1654941982.813597 iteration: 34940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11578 FastRCNN class loss: 0.04151 FastRCNN total loss: 0.1573 L1 loss: 0.0000e+00 L2 loss: 0.71668 Learning rate: 0.02 Mask loss: 0.16316 RPN box loss: 0.03267 RPN score loss: 0.00298 RPN total loss: 0.03565 Total loss: 1.07278 timestamp: 1654941986.000429 iteration: 34945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13166 FastRCNN class loss: 0.10424 FastRCNN total loss: 0.2359 L1 loss: 0.0000e+00 L2 loss: 0.7166 Learning rate: 0.02 Mask loss: 0.16932 RPN box loss: 0.06534 RPN score loss: 0.00974 RPN total loss: 0.07508 Total loss: 1.1969 timestamp: 1654941989.3661845 iteration: 34950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18648 FastRCNN class loss: 0.18172 FastRCNN total loss: 0.3682 L1 loss: 0.0000e+00 L2 loss: 0.71648 Learning rate: 0.02 Mask loss: 0.25613 RPN box loss: 0.08125 RPN score loss: 0.01595 RPN total loss: 0.0972 Total loss: 1.43801 timestamp: 1654941992.5859609 iteration: 34955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16656 FastRCNN class loss: 0.05483 FastRCNN total loss: 0.22139 L1 loss: 0.0000e+00 L2 loss: 0.7164 Learning rate: 0.02 Mask loss: 0.16797 RPN box loss: 0.02008 RPN score loss: 0.00144 RPN total loss: 0.02152 Total loss: 1.12728 timestamp: 1654941995.7690918 iteration: 34960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08845 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.17557 L1 loss: 0.0000e+00 L2 loss: 0.71629 Learning rate: 0.02 Mask loss: 0.13882 RPN box loss: 0.01978 RPN score loss: 0.00163 RPN total loss: 0.02141 Total loss: 1.05209 timestamp: 1654941998.9428039 iteration: 34965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12683 FastRCNN class loss: 0.04745 FastRCNN total loss: 0.17428 L1 loss: 0.0000e+00 L2 loss: 0.71617 Learning rate: 0.02 Mask loss: 0.20618 RPN box loss: 0.01118 RPN score loss: 0.00241 RPN total loss: 0.01359 Total loss: 1.11022 timestamp: 1654942002.1240482 iteration: 34970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.1117 FastRCNN total loss: 0.22605 L1 loss: 0.0000e+00 L2 loss: 0.71606 Learning rate: 0.02 Mask loss: 0.13316 RPN box loss: 0.02241 RPN score loss: 0.00486 RPN total loss: 0.02727 Total loss: 1.10254 timestamp: 1654942005.3302093 iteration: 34975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13238 FastRCNN class loss: 0.07453 FastRCNN total loss: 0.20691 L1 loss: 0.0000e+00 L2 loss: 0.71599 Learning rate: 0.02 Mask loss: 0.18596 RPN box loss: 0.03602 RPN score loss: 0.00686 RPN total loss: 0.04288 Total loss: 1.15173 timestamp: 1654942008.5387144 iteration: 34980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18289 FastRCNN class loss: 0.12955 FastRCNN total loss: 0.31245 L1 loss: 0.0000e+00 L2 loss: 0.71591 Learning rate: 0.02 Mask loss: 0.14996 RPN box loss: 0.03236 RPN score loss: 0.00553 RPN total loss: 0.03789 Total loss: 1.2162 timestamp: 1654942011.7133389 iteration: 34985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12465 FastRCNN class loss: 0.0944 FastRCNN total loss: 0.21905 L1 loss: 0.0000e+00 L2 loss: 0.71578 Learning rate: 0.02 Mask loss: 0.13429 RPN box loss: 0.03569 RPN score loss: 0.00937 RPN total loss: 0.04506 Total loss: 1.11418 timestamp: 1654942014.9485834 iteration: 34990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17466 FastRCNN class loss: 0.10278 FastRCNN total loss: 0.27744 L1 loss: 0.0000e+00 L2 loss: 0.71571 Learning rate: 0.02 Mask loss: 0.13152 RPN box loss: 0.0297 RPN score loss: 0.00913 RPN total loss: 0.03883 Total loss: 1.1635 timestamp: 1654942018.1679451 iteration: 34995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11347 FastRCNN class loss: 0.09824 FastRCNN total loss: 0.21171 L1 loss: 0.0000e+00 L2 loss: 0.71565 Learning rate: 0.02 Mask loss: 0.20901 RPN box loss: 0.01311 RPN score loss: 0.00398 RPN total loss: 0.01709 Total loss: 1.15347 timestamp: 1654942021.3148515 iteration: 35000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16802 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.26145 L1 loss: 0.0000e+00 L2 loss: 0.71553 Learning rate: 0.02 Mask loss: 0.18057 RPN box loss: 0.02674 RPN score loss: 0.00552 RPN total loss: 0.03227 Total loss: 1.18982 timestamp: 1654942024.5131924 iteration: 35005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17699 FastRCNN class loss: 0.13164 FastRCNN total loss: 0.30863 L1 loss: 0.0000e+00 L2 loss: 0.71544 Learning rate: 0.02 Mask loss: 0.17463 RPN box loss: 0.03864 RPN score loss: 0.03781 RPN total loss: 0.07645 Total loss: 1.27515 timestamp: 1654942027.692576 iteration: 35010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12565 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.19682 L1 loss: 0.0000e+00 L2 loss: 0.71534 Learning rate: 0.02 Mask loss: 0.16098 RPN box loss: 0.04188 RPN score loss: 0.00861 RPN total loss: 0.0505 Total loss: 1.12363 timestamp: 1654942030.933655 iteration: 35015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10841 FastRCNN class loss: 0.08079 FastRCNN total loss: 0.1892 L1 loss: 0.0000e+00 L2 loss: 0.71528 Learning rate: 0.02 Mask loss: 0.22292 RPN box loss: 0.07381 RPN score loss: 0.01241 RPN total loss: 0.08623 Total loss: 1.21363 timestamp: 1654942034.2340813 iteration: 35020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06902 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.12957 L1 loss: 0.0000e+00 L2 loss: 0.71522 Learning rate: 0.02 Mask loss: 0.08353 RPN box loss: 0.00558 RPN score loss: 0.0029 RPN total loss: 0.00848 Total loss: 0.93679 timestamp: 1654942037.4091108 iteration: 35025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17592 FastRCNN class loss: 0.11261 FastRCNN total loss: 0.28852 L1 loss: 0.0000e+00 L2 loss: 0.7151 Learning rate: 0.02 Mask loss: 0.239 RPN box loss: 0.02437 RPN score loss: 0.01809 RPN total loss: 0.04246 Total loss: 1.28509 timestamp: 1654942040.563009 iteration: 35030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13554 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.20502 L1 loss: 0.0000e+00 L2 loss: 0.715 Learning rate: 0.02 Mask loss: 0.14571 RPN box loss: 0.01914 RPN score loss: 0.00217 RPN total loss: 0.02131 Total loss: 1.08703 timestamp: 1654942043.780215 iteration: 35035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10634 FastRCNN class loss: 0.05921 FastRCNN total loss: 0.16555 L1 loss: 0.0000e+00 L2 loss: 0.71489 Learning rate: 0.02 Mask loss: 0.14805 RPN box loss: 0.01393 RPN score loss: 0.00833 RPN total loss: 0.02227 Total loss: 1.05076 timestamp: 1654942046.9800184 iteration: 35040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1994 FastRCNN class loss: 0.11336 FastRCNN total loss: 0.31276 L1 loss: 0.0000e+00 L2 loss: 0.71482 Learning rate: 0.02 Mask loss: 0.20099 RPN box loss: 0.03181 RPN score loss: 0.01266 RPN total loss: 0.04447 Total loss: 1.27304 timestamp: 1654942050.2469041 iteration: 35045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07194 FastRCNN class loss: 0.05127 FastRCNN total loss: 0.12321 L1 loss: 0.0000e+00 L2 loss: 0.71473 Learning rate: 0.02 Mask loss: 0.07329 RPN box loss: 0.014 RPN score loss: 0.00297 RPN total loss: 0.01697 Total loss: 0.92821 timestamp: 1654942053.3986738 iteration: 35050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07156 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.13606 L1 loss: 0.0000e+00 L2 loss: 0.71463 Learning rate: 0.02 Mask loss: 0.14621 RPN box loss: 0.02456 RPN score loss: 0.00135 RPN total loss: 0.02591 Total loss: 1.02282 timestamp: 1654942056.5975142 iteration: 35055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15805 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.23949 L1 loss: 0.0000e+00 L2 loss: 0.71453 Learning rate: 0.02 Mask loss: 0.12256 RPN box loss: 0.01242 RPN score loss: 0.00634 RPN total loss: 0.01876 Total loss: 1.09534 timestamp: 1654942059.832677 iteration: 35060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13346 FastRCNN class loss: 0.08602 FastRCNN total loss: 0.21949 L1 loss: 0.0000e+00 L2 loss: 0.71446 Learning rate: 0.02 Mask loss: 0.1337 RPN box loss: 0.04694 RPN score loss: 0.00961 RPN total loss: 0.05655 Total loss: 1.1242 timestamp: 1654942063.0011513 iteration: 35065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07246 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.15011 L1 loss: 0.0000e+00 L2 loss: 0.71435 Learning rate: 0.02 Mask loss: 0.11248 RPN box loss: 0.02428 RPN score loss: 0.01226 RPN total loss: 0.03654 Total loss: 1.01348 timestamp: 1654942066.207986 iteration: 35070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14524 FastRCNN class loss: 0.10695 FastRCNN total loss: 0.25219 L1 loss: 0.0000e+00 L2 loss: 0.71423 Learning rate: 0.02 Mask loss: 0.13852 RPN box loss: 0.04258 RPN score loss: 0.00672 RPN total loss: 0.0493 Total loss: 1.15425 timestamp: 1654942069.4931443 iteration: 35075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11902 FastRCNN class loss: 0.09526 FastRCNN total loss: 0.21428 L1 loss: 0.0000e+00 L2 loss: 0.71417 Learning rate: 0.02 Mask loss: 0.18167 RPN box loss: 0.015 RPN score loss: 0.00261 RPN total loss: 0.01762 Total loss: 1.12774 timestamp: 1654942072.6476994 iteration: 35080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11742 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.17257 L1 loss: 0.0000e+00 L2 loss: 0.71407 Learning rate: 0.02 Mask loss: 0.09873 RPN box loss: 0.04059 RPN score loss: 0.00547 RPN total loss: 0.04606 Total loss: 1.03144 timestamp: 1654942075.8167531 iteration: 35085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08643 FastRCNN class loss: 0.09307 FastRCNN total loss: 0.1795 L1 loss: 0.0000e+00 L2 loss: 0.71399 Learning rate: 0.02 Mask loss: 0.12151 RPN box loss: 0.02205 RPN score loss: 0.00543 RPN total loss: 0.02748 Total loss: 1.04249 timestamp: 1654942079.0544412 iteration: 35090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11214 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.19095 L1 loss: 0.0000e+00 L2 loss: 0.7139 Learning rate: 0.02 Mask loss: 0.24949 RPN box loss: 0.0086 RPN score loss: 0.0033 RPN total loss: 0.01191 Total loss: 1.16625 timestamp: 1654942082.2259326 iteration: 35095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13463 FastRCNN class loss: 0.08142 FastRCNN total loss: 0.21605 L1 loss: 0.0000e+00 L2 loss: 0.71382 Learning rate: 0.02 Mask loss: 0.13086 RPN box loss: 0.04933 RPN score loss: 0.01193 RPN total loss: 0.06126 Total loss: 1.12199 timestamp: 1654942085.43303 iteration: 35100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.19992 L1 loss: 0.0000e+00 L2 loss: 0.71373 Learning rate: 0.02 Mask loss: 0.08786 RPN box loss: 0.03112 RPN score loss: 0.01287 RPN total loss: 0.044 Total loss: 1.04551 timestamp: 1654942088.6700125 iteration: 35105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11929 FastRCNN class loss: 0.05163 FastRCNN total loss: 0.17093 L1 loss: 0.0000e+00 L2 loss: 0.71364 Learning rate: 0.02 Mask loss: 0.09626 RPN box loss: 0.0115 RPN score loss: 0.00199 RPN total loss: 0.01349 Total loss: 0.99432 timestamp: 1654942091.8499897 iteration: 35110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14026 FastRCNN class loss: 0.08325 FastRCNN total loss: 0.22352 L1 loss: 0.0000e+00 L2 loss: 0.71355 Learning rate: 0.02 Mask loss: 0.17513 RPN box loss: 0.03107 RPN score loss: 0.0047 RPN total loss: 0.03577 Total loss: 1.14797 timestamp: 1654942095.1241412 iteration: 35115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.08503 FastRCNN total loss: 0.21759 L1 loss: 0.0000e+00 L2 loss: 0.71346 Learning rate: 0.02 Mask loss: 0.16931 RPN box loss: 0.03779 RPN score loss: 0.00288 RPN total loss: 0.04067 Total loss: 1.14103 timestamp: 1654942098.2761545 iteration: 35120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13725 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.19822 L1 loss: 0.0000e+00 L2 loss: 0.71338 Learning rate: 0.02 Mask loss: 0.16929 RPN box loss: 0.01695 RPN score loss: 0.00631 RPN total loss: 0.02326 Total loss: 1.10414 timestamp: 1654942101.5149257 iteration: 35125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06493 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.12007 L1 loss: 0.0000e+00 L2 loss: 0.7133 Learning rate: 0.02 Mask loss: 0.13614 RPN box loss: 0.00699 RPN score loss: 0.0024 RPN total loss: 0.00939 Total loss: 0.97891 timestamp: 1654942104.7360475 iteration: 35130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12279 FastRCNN class loss: 0.10321 FastRCNN total loss: 0.226 L1 loss: 0.0000e+00 L2 loss: 0.71316 Learning rate: 0.02 Mask loss: 0.12582 RPN box loss: 0.02699 RPN score loss: 0.00778 RPN total loss: 0.03477 Total loss: 1.09975 timestamp: 1654942107.9617565 iteration: 35135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06948 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.14267 L1 loss: 0.0000e+00 L2 loss: 0.71307 Learning rate: 0.02 Mask loss: 0.16197 RPN box loss: 0.05992 RPN score loss: 0.00616 RPN total loss: 0.06608 Total loss: 1.08379 timestamp: 1654942111.1213524 iteration: 35140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15513 FastRCNN class loss: 0.05609 FastRCNN total loss: 0.21122 L1 loss: 0.0000e+00 L2 loss: 0.71298 Learning rate: 0.02 Mask loss: 0.10695 RPN box loss: 0.00806 RPN score loss: 0.0026 RPN total loss: 0.01066 Total loss: 1.0418 timestamp: 1654942114.2719011 iteration: 35145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13325 FastRCNN class loss: 0.07697 FastRCNN total loss: 0.21023 L1 loss: 0.0000e+00 L2 loss: 0.7129 Learning rate: 0.02 Mask loss: 0.1437 RPN box loss: 0.03343 RPN score loss: 0.00331 RPN total loss: 0.03674 Total loss: 1.10357 timestamp: 1654942117.4622998 iteration: 35150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11391 FastRCNN class loss: 0.06502 FastRCNN total loss: 0.17893 L1 loss: 0.0000e+00 L2 loss: 0.71281 Learning rate: 0.02 Mask loss: 0.16315 RPN box loss: 0.02197 RPN score loss: 0.00508 RPN total loss: 0.02706 Total loss: 1.08194 timestamp: 1654942120.628601 iteration: 35155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10708 FastRCNN class loss: 0.06426 FastRCNN total loss: 0.17133 L1 loss: 0.0000e+00 L2 loss: 0.7127 Learning rate: 0.02 Mask loss: 0.0947 RPN box loss: 0.01732 RPN score loss: 0.00294 RPN total loss: 0.02026 Total loss: 0.99899 timestamp: 1654942123.8037171 iteration: 35160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13723 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.22479 L1 loss: 0.0000e+00 L2 loss: 0.71261 Learning rate: 0.02 Mask loss: 0.11587 RPN box loss: 0.03774 RPN score loss: 0.00315 RPN total loss: 0.04089 Total loss: 1.09416 timestamp: 1654942126.9520912 iteration: 35165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10738 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.17739 L1 loss: 0.0000e+00 L2 loss: 0.71251 Learning rate: 0.02 Mask loss: 0.12229 RPN box loss: 0.01493 RPN score loss: 0.00304 RPN total loss: 0.01797 Total loss: 1.03015 timestamp: 1654942130.0859337 iteration: 35170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1835 FastRCNN class loss: 0.12724 FastRCNN total loss: 0.31074 L1 loss: 0.0000e+00 L2 loss: 0.71244 Learning rate: 0.02 Mask loss: 0.22839 RPN box loss: 0.0249 RPN score loss: 0.01216 RPN total loss: 0.03707 Total loss: 1.28863 timestamp: 1654942133.2866323 iteration: 35175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14749 FastRCNN class loss: 0.09965 FastRCNN total loss: 0.24714 L1 loss: 0.0000e+00 L2 loss: 0.71233 Learning rate: 0.02 Mask loss: 0.11327 RPN box loss: 0.04416 RPN score loss: 0.00664 RPN total loss: 0.05079 Total loss: 1.12354 timestamp: 1654942136.5011625 iteration: 35180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18587 FastRCNN class loss: 0.12174 FastRCNN total loss: 0.30761 L1 loss: 0.0000e+00 L2 loss: 0.71225 Learning rate: 0.02 Mask loss: 0.22118 RPN box loss: 0.02857 RPN score loss: 0.00519 RPN total loss: 0.03376 Total loss: 1.2748 timestamp: 1654942139.7297373 iteration: 35185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12429 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.20056 L1 loss: 0.0000e+00 L2 loss: 0.71217 Learning rate: 0.02 Mask loss: 0.16671 RPN box loss: 0.02306 RPN score loss: 0.00385 RPN total loss: 0.02691 Total loss: 1.10635 timestamp: 1654942142.96228 iteration: 35190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11791 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.1915 L1 loss: 0.0000e+00 L2 loss: 0.71206 Learning rate: 0.02 Mask loss: 0.17662 RPN box loss: 0.03101 RPN score loss: 0.00153 RPN total loss: 0.03254 Total loss: 1.11272 timestamp: 1654942146.0721483 iteration: 35195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18109 FastRCNN class loss: 0.08702 FastRCNN total loss: 0.26811 L1 loss: 0.0000e+00 L2 loss: 0.71197 Learning rate: 0.02 Mask loss: 0.13821 RPN box loss: 0.07355 RPN score loss: 0.00439 RPN total loss: 0.07794 Total loss: 1.19622 timestamp: 1654942149.264607 iteration: 35200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15139 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.21918 L1 loss: 0.0000e+00 L2 loss: 0.71184 Learning rate: 0.02 Mask loss: 0.15311 RPN box loss: 0.02748 RPN score loss: 0.00842 RPN total loss: 0.0359 Total loss: 1.12004 timestamp: 1654942152.45606 iteration: 35205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07936 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.15831 L1 loss: 0.0000e+00 L2 loss: 0.71175 Learning rate: 0.02 Mask loss: 0.15889 RPN box loss: 0.00706 RPN score loss: 0.00346 RPN total loss: 0.01052 Total loss: 1.03947 timestamp: 1654942155.6351664 iteration: 35210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19034 FastRCNN class loss: 0.07733 FastRCNN total loss: 0.26767 L1 loss: 0.0000e+00 L2 loss: 0.71167 Learning rate: 0.02 Mask loss: 0.14351 RPN box loss: 0.02948 RPN score loss: 0.0075 RPN total loss: 0.03698 Total loss: 1.15983 timestamp: 1654942158.8422613 iteration: 35215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18889 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.27866 L1 loss: 0.0000e+00 L2 loss: 0.71156 Learning rate: 0.02 Mask loss: 0.16603 RPN box loss: 0.03836 RPN score loss: 0.0154 RPN total loss: 0.05377 Total loss: 1.21002 timestamp: 1654942162.0568166 iteration: 35220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18277 FastRCNN class loss: 0.10079 FastRCNN total loss: 0.28356 L1 loss: 0.0000e+00 L2 loss: 0.71149 Learning rate: 0.02 Mask loss: 0.11669 RPN box loss: 0.04678 RPN score loss: 0.01057 RPN total loss: 0.05734 Total loss: 1.16908 timestamp: 1654942165.312873 iteration: 35225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15967 FastRCNN class loss: 0.11792 FastRCNN total loss: 0.27759 L1 loss: 0.0000e+00 L2 loss: 0.71139 Learning rate: 0.02 Mask loss: 0.2176 RPN box loss: 0.04365 RPN score loss: 0.02358 RPN total loss: 0.06723 Total loss: 1.27381 timestamp: 1654942168.4867198 iteration: 35230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12318 FastRCNN class loss: 0.07533 FastRCNN total loss: 0.19851 L1 loss: 0.0000e+00 L2 loss: 0.71129 Learning rate: 0.02 Mask loss: 0.21939 RPN box loss: 0.03042 RPN score loss: 0.00994 RPN total loss: 0.04035 Total loss: 1.16954 timestamp: 1654942171.7111194 iteration: 35235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12155 FastRCNN class loss: 0.08022 FastRCNN total loss: 0.20178 L1 loss: 0.0000e+00 L2 loss: 0.7112 Learning rate: 0.02 Mask loss: 0.12562 RPN box loss: 0.02271 RPN score loss: 0.01179 RPN total loss: 0.0345 Total loss: 1.0731 timestamp: 1654942174.9117627 iteration: 35240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0916 FastRCNN class loss: 0.0846 FastRCNN total loss: 0.1762 L1 loss: 0.0000e+00 L2 loss: 0.71109 Learning rate: 0.02 Mask loss: 0.11202 RPN box loss: 0.06145 RPN score loss: 0.01455 RPN total loss: 0.076 Total loss: 1.07531 timestamp: 1654942178.09025 iteration: 35245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.14495 L1 loss: 0.0000e+00 L2 loss: 0.71101 Learning rate: 0.02 Mask loss: 0.12503 RPN box loss: 0.03532 RPN score loss: 0.00202 RPN total loss: 0.03734 Total loss: 1.01832 timestamp: 1654942181.2626107 iteration: 35250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12144 FastRCNN class loss: 0.07759 FastRCNN total loss: 0.19903 L1 loss: 0.0000e+00 L2 loss: 0.71093 Learning rate: 0.02 Mask loss: 0.17074 RPN box loss: 0.02492 RPN score loss: 0.00739 RPN total loss: 0.03232 Total loss: 1.11301 timestamp: 1654942184.4040918 iteration: 35255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15538 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.22398 L1 loss: 0.0000e+00 L2 loss: 0.71081 Learning rate: 0.02 Mask loss: 0.15441 RPN box loss: 0.01803 RPN score loss: 0.00755 RPN total loss: 0.02558 Total loss: 1.11479 timestamp: 1654942187.5628786 iteration: 35260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.06204 FastRCNN total loss: 0.17355 L1 loss: 0.0000e+00 L2 loss: 0.71071 Learning rate: 0.02 Mask loss: 0.17673 RPN box loss: 0.02467 RPN score loss: 0.00535 RPN total loss: 0.03002 Total loss: 1.09101 timestamp: 1654942190.7650142 iteration: 35265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0918 FastRCNN class loss: 0.04903 FastRCNN total loss: 0.14083 L1 loss: 0.0000e+00 L2 loss: 0.7106 Learning rate: 0.02 Mask loss: 0.07604 RPN box loss: 0.00752 RPN score loss: 0.00376 RPN total loss: 0.01128 Total loss: 0.93875 timestamp: 1654942193.971772 iteration: 35270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09159 FastRCNN class loss: 0.06798 FastRCNN total loss: 0.15957 L1 loss: 0.0000e+00 L2 loss: 0.7105 Learning rate: 0.02 Mask loss: 0.17986 RPN box loss: 0.02239 RPN score loss: 0.00333 RPN total loss: 0.02572 Total loss: 1.07566 timestamp: 1654942197.1718109 iteration: 35275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16405 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.22947 L1 loss: 0.0000e+00 L2 loss: 0.7104 Learning rate: 0.02 Mask loss: 0.13979 RPN box loss: 0.06131 RPN score loss: 0.00909 RPN total loss: 0.07039 Total loss: 1.15005 timestamp: 1654942200.3722632 iteration: 35280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14883 FastRCNN class loss: 0.11281 FastRCNN total loss: 0.26163 L1 loss: 0.0000e+00 L2 loss: 0.71031 Learning rate: 0.02 Mask loss: 0.10723 RPN box loss: 0.03776 RPN score loss: 0.01341 RPN total loss: 0.05117 Total loss: 1.13034 timestamp: 1654942203.566711 iteration: 35285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18645 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.24946 L1 loss: 0.0000e+00 L2 loss: 0.71021 Learning rate: 0.02 Mask loss: 0.13001 RPN box loss: 0.02203 RPN score loss: 0.00302 RPN total loss: 0.02504 Total loss: 1.11472 timestamp: 1654942206.7965348 iteration: 35290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18353 FastRCNN class loss: 0.05526 FastRCNN total loss: 0.23879 L1 loss: 0.0000e+00 L2 loss: 0.71009 Learning rate: 0.02 Mask loss: 0.09939 RPN box loss: 0.01844 RPN score loss: 0.00474 RPN total loss: 0.02318 Total loss: 1.07146 timestamp: 1654942210.0126472 iteration: 35295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13992 FastRCNN class loss: 0.09171 FastRCNN total loss: 0.23162 L1 loss: 0.0000e+00 L2 loss: 0.71001 Learning rate: 0.02 Mask loss: 0.1766 RPN box loss: 0.05433 RPN score loss: 0.00512 RPN total loss: 0.05945 Total loss: 1.17768 timestamp: 1654942213.2543678 iteration: 35300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10608 FastRCNN class loss: 0.05241 FastRCNN total loss: 0.15848 L1 loss: 0.0000e+00 L2 loss: 0.70991 Learning rate: 0.02 Mask loss: 0.18186 RPN box loss: 0.01207 RPN score loss: 0.0055 RPN total loss: 0.01756 Total loss: 1.06782 timestamp: 1654942216.4338086 iteration: 35305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13764 FastRCNN class loss: 0.08152 FastRCNN total loss: 0.21916 L1 loss: 0.0000e+00 L2 loss: 0.70983 Learning rate: 0.02 Mask loss: 0.2302 RPN box loss: 0.0342 RPN score loss: 0.00854 RPN total loss: 0.04275 Total loss: 1.20193 timestamp: 1654942219.632628 iteration: 35310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07116 FastRCNN class loss: 0.04537 FastRCNN total loss: 0.11653 L1 loss: 0.0000e+00 L2 loss: 0.70973 Learning rate: 0.02 Mask loss: 0.09634 RPN box loss: 0.00285 RPN score loss: 0.00303 RPN total loss: 0.00587 Total loss: 0.92848 timestamp: 1654942222.8338878 iteration: 35315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10774 FastRCNN class loss: 0.07052 FastRCNN total loss: 0.17826 L1 loss: 0.0000e+00 L2 loss: 0.70964 Learning rate: 0.02 Mask loss: 0.22922 RPN box loss: 0.03683 RPN score loss: 0.00289 RPN total loss: 0.03972 Total loss: 1.15683 timestamp: 1654942226.0512905 iteration: 35320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13951 FastRCNN class loss: 0.07204 FastRCNN total loss: 0.21155 L1 loss: 0.0000e+00 L2 loss: 0.70954 Learning rate: 0.02 Mask loss: 0.16481 RPN box loss: 0.03485 RPN score loss: 0.00405 RPN total loss: 0.0389 Total loss: 1.12479 timestamp: 1654942229.2762341 iteration: 35325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13563 FastRCNN class loss: 0.06756 FastRCNN total loss: 0.20319 L1 loss: 0.0000e+00 L2 loss: 0.70944 Learning rate: 0.02 Mask loss: 0.14287 RPN box loss: 0.05927 RPN score loss: 0.01201 RPN total loss: 0.07128 Total loss: 1.12678 timestamp: 1654942232.4663525 iteration: 35330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21461 FastRCNN class loss: 0.12369 FastRCNN total loss: 0.3383 L1 loss: 0.0000e+00 L2 loss: 0.70934 Learning rate: 0.02 Mask loss: 0.19554 RPN box loss: 0.0238 RPN score loss: 0.00663 RPN total loss: 0.03043 Total loss: 1.2736 timestamp: 1654942235.6477354 iteration: 35335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11746 FastRCNN class loss: 0.07612 FastRCNN total loss: 0.19358 L1 loss: 0.0000e+00 L2 loss: 0.70924 Learning rate: 0.02 Mask loss: 0.13312 RPN box loss: 0.03273 RPN score loss: 0.00399 RPN total loss: 0.03673 Total loss: 1.07267 timestamp: 1654942238.753461 iteration: 35340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12086 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.19523 L1 loss: 0.0000e+00 L2 loss: 0.70915 Learning rate: 0.02 Mask loss: 0.11233 RPN box loss: 0.05286 RPN score loss: 0.00391 RPN total loss: 0.05677 Total loss: 1.07347 timestamp: 1654942241.9457357 iteration: 35345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1144 FastRCNN class loss: 0.05491 FastRCNN total loss: 0.16931 L1 loss: 0.0000e+00 L2 loss: 0.70906 Learning rate: 0.02 Mask loss: 0.15308 RPN box loss: 0.04687 RPN score loss: 0.0105 RPN total loss: 0.05737 Total loss: 1.08883 timestamp: 1654942245.1518648 iteration: 35350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09603 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.16856 L1 loss: 0.0000e+00 L2 loss: 0.70896 Learning rate: 0.02 Mask loss: 0.13679 RPN box loss: 0.03316 RPN score loss: 0.01278 RPN total loss: 0.04594 Total loss: 1.06025 timestamp: 1654942248.3748891 iteration: 35355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20014 FastRCNN class loss: 0.10688 FastRCNN total loss: 0.30702 L1 loss: 0.0000e+00 L2 loss: 0.70884 Learning rate: 0.02 Mask loss: 0.1558 RPN box loss: 0.03636 RPN score loss: 0.02202 RPN total loss: 0.05838 Total loss: 1.23005 timestamp: 1654942251.4606159 iteration: 35360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11382 FastRCNN class loss: 0.04859 FastRCNN total loss: 0.1624 L1 loss: 0.0000e+00 L2 loss: 0.70875 Learning rate: 0.02 Mask loss: 0.15219 RPN box loss: 0.03846 RPN score loss: 0.00479 RPN total loss: 0.04326 Total loss: 1.0666 timestamp: 1654942254.623808 iteration: 35365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05975 FastRCNN class loss: 0.04323 FastRCNN total loss: 0.10298 L1 loss: 0.0000e+00 L2 loss: 0.70867 Learning rate: 0.02 Mask loss: 0.17429 RPN box loss: 0.01353 RPN score loss: 0.00488 RPN total loss: 0.01841 Total loss: 1.00435 timestamp: 1654942257.8699389 iteration: 35370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10649 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.16985 L1 loss: 0.0000e+00 L2 loss: 0.70857 Learning rate: 0.02 Mask loss: 0.13781 RPN box loss: 0.02744 RPN score loss: 0.0055 RPN total loss: 0.03293 Total loss: 1.04917 timestamp: 1654942261.041941 iteration: 35375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13573 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.21005 L1 loss: 0.0000e+00 L2 loss: 0.70848 Learning rate: 0.02 Mask loss: 0.20378 RPN box loss: 0.04109 RPN score loss: 0.01272 RPN total loss: 0.05381 Total loss: 1.17612 timestamp: 1654942264.2767603 iteration: 35380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20958 FastRCNN class loss: 0.07982 FastRCNN total loss: 0.2894 L1 loss: 0.0000e+00 L2 loss: 0.70837 Learning rate: 0.02 Mask loss: 0.15701 RPN box loss: 0.01769 RPN score loss: 0.00335 RPN total loss: 0.02104 Total loss: 1.17583 timestamp: 1654942267.4595973 iteration: 35385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09431 FastRCNN class loss: 0.05139 FastRCNN total loss: 0.1457 L1 loss: 0.0000e+00 L2 loss: 0.70829 Learning rate: 0.02 Mask loss: 0.10542 RPN box loss: 0.0231 RPN score loss: 0.0041 RPN total loss: 0.0272 Total loss: 0.98662 timestamp: 1654942270.638136 iteration: 35390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12088 FastRCNN class loss: 0.1099 FastRCNN total loss: 0.23078 L1 loss: 0.0000e+00 L2 loss: 0.7082 Learning rate: 0.02 Mask loss: 0.12937 RPN box loss: 0.0235 RPN score loss: 0.00796 RPN total loss: 0.03146 Total loss: 1.0998 timestamp: 1654942273.8446145 iteration: 35395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06936 FastRCNN class loss: 0.04127 FastRCNN total loss: 0.11064 L1 loss: 0.0000e+00 L2 loss: 0.70812 Learning rate: 0.02 Mask loss: 0.11519 RPN box loss: 0.03557 RPN score loss: 0.00665 RPN total loss: 0.04222 Total loss: 0.97616 timestamp: 1654942277.0210423 iteration: 35400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13826 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.2119 L1 loss: 0.0000e+00 L2 loss: 0.70804 Learning rate: 0.02 Mask loss: 0.14753 RPN box loss: 0.01993 RPN score loss: 0.00352 RPN total loss: 0.02345 Total loss: 1.09092 timestamp: 1654942280.1962223 iteration: 35405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0747 FastRCNN class loss: 0.08269 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.70796 Learning rate: 0.02 Mask loss: 0.09668 RPN box loss: 0.01897 RPN score loss: 0.00273 RPN total loss: 0.0217 Total loss: 0.98372 timestamp: 1654942283.3939595 iteration: 35410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10896 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.17025 L1 loss: 0.0000e+00 L2 loss: 0.70786 Learning rate: 0.02 Mask loss: 0.12109 RPN box loss: 0.00845 RPN score loss: 0.00303 RPN total loss: 0.01148 Total loss: 1.01067 timestamp: 1654942286.5923913 iteration: 35415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12727 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.19316 L1 loss: 0.0000e+00 L2 loss: 0.70777 Learning rate: 0.02 Mask loss: 0.16478 RPN box loss: 0.03175 RPN score loss: 0.00441 RPN total loss: 0.03616 Total loss: 1.10187 timestamp: 1654942289.7422915 iteration: 35420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07605 FastRCNN class loss: 0.0391 FastRCNN total loss: 0.11515 L1 loss: 0.0000e+00 L2 loss: 0.70769 Learning rate: 0.02 Mask loss: 0.09483 RPN box loss: 0.0151 RPN score loss: 0.00627 RPN total loss: 0.02137 Total loss: 0.93904 timestamp: 1654942292.9276571 iteration: 35425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11148 FastRCNN class loss: 0.07567 FastRCNN total loss: 0.18714 L1 loss: 0.0000e+00 L2 loss: 0.70757 Learning rate: 0.02 Mask loss: 0.16903 RPN box loss: 0.03357 RPN score loss: 0.02393 RPN total loss: 0.0575 Total loss: 1.12123 timestamp: 1654942296.1176503 iteration: 35430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0616 FastRCNN class loss: 0.03742 FastRCNN total loss: 0.09902 L1 loss: 0.0000e+00 L2 loss: 0.70747 Learning rate: 0.02 Mask loss: 0.12011 RPN box loss: 0.01123 RPN score loss: 0.00412 RPN total loss: 0.01534 Total loss: 0.94195 timestamp: 1654942299.3294048 iteration: 35435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07383 FastRCNN class loss: 0.07083 FastRCNN total loss: 0.14466 L1 loss: 0.0000e+00 L2 loss: 0.70739 Learning rate: 0.02 Mask loss: 0.12051 RPN box loss: 0.02812 RPN score loss: 0.00347 RPN total loss: 0.03159 Total loss: 1.00416 timestamp: 1654942302.5305247 iteration: 35440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14049 FastRCNN class loss: 0.09591 FastRCNN total loss: 0.2364 L1 loss: 0.0000e+00 L2 loss: 0.70729 Learning rate: 0.02 Mask loss: 0.20539 RPN box loss: 0.06091 RPN score loss: 0.0099 RPN total loss: 0.07081 Total loss: 1.2199 timestamp: 1654942305.7938776 iteration: 35445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07328 FastRCNN class loss: 0.05898 FastRCNN total loss: 0.13227 L1 loss: 0.0000e+00 L2 loss: 0.70721 Learning rate: 0.02 Mask loss: 0.14375 RPN box loss: 0.01493 RPN score loss: 0.00214 RPN total loss: 0.01707 Total loss: 1.00029 timestamp: 1654942308.9417233 iteration: 35450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14055 FastRCNN class loss: 0.05374 FastRCNN total loss: 0.19429 L1 loss: 0.0000e+00 L2 loss: 0.7071 Learning rate: 0.02 Mask loss: 0.12284 RPN box loss: 0.00976 RPN score loss: 0.00227 RPN total loss: 0.01203 Total loss: 1.03626 timestamp: 1654942312.1580837 iteration: 35455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17402 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.25396 L1 loss: 0.0000e+00 L2 loss: 0.707 Learning rate: 0.02 Mask loss: 0.13848 RPN box loss: 0.03383 RPN score loss: 0.01387 RPN total loss: 0.0477 Total loss: 1.14714 timestamp: 1654942315.41703 iteration: 35460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18845 FastRCNN class loss: 0.07228 FastRCNN total loss: 0.26073 L1 loss: 0.0000e+00 L2 loss: 0.70691 Learning rate: 0.02 Mask loss: 0.09967 RPN box loss: 0.0274 RPN score loss: 0.00242 RPN total loss: 0.02982 Total loss: 1.09713 timestamp: 1654942318.7025373 iteration: 35465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1329 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.22222 L1 loss: 0.0000e+00 L2 loss: 0.7068 Learning rate: 0.02 Mask loss: 0.20483 RPN box loss: 0.04195 RPN score loss: 0.01006 RPN total loss: 0.05201 Total loss: 1.18586 timestamp: 1654942321.933297 iteration: 35470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18198 FastRCNN class loss: 0.08875 FastRCNN total loss: 0.27073 L1 loss: 0.0000e+00 L2 loss: 0.70669 Learning rate: 0.02 Mask loss: 0.16514 RPN box loss: 0.03033 RPN score loss: 0.00791 RPN total loss: 0.03824 Total loss: 1.18081 timestamp: 1654942325.187312 iteration: 35475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10424 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.16492 L1 loss: 0.0000e+00 L2 loss: 0.70659 Learning rate: 0.02 Mask loss: 0.13562 RPN box loss: 0.06197 RPN score loss: 0.00599 RPN total loss: 0.06796 Total loss: 1.07509 timestamp: 1654942328.3896813 iteration: 35480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06141 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.11164 L1 loss: 0.0000e+00 L2 loss: 0.70649 Learning rate: 0.02 Mask loss: 0.14356 RPN box loss: 0.02964 RPN score loss: 0.00163 RPN total loss: 0.03127 Total loss: 0.99297 timestamp: 1654942331.678854 iteration: 35485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12005 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.1892 L1 loss: 0.0000e+00 L2 loss: 0.70639 Learning rate: 0.02 Mask loss: 0.22687 RPN box loss: 0.00829 RPN score loss: 0.00369 RPN total loss: 0.01198 Total loss: 1.13444 timestamp: 1654942334.8971858 iteration: 35490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18116 FastRCNN class loss: 0.12195 FastRCNN total loss: 0.30312 L1 loss: 0.0000e+00 L2 loss: 0.70631 Learning rate: 0.02 Mask loss: 0.15542 RPN box loss: 0.03637 RPN score loss: 0.00853 RPN total loss: 0.0449 Total loss: 1.20975 timestamp: 1654942338.151643 iteration: 35495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15952 FastRCNN class loss: 0.10189 FastRCNN total loss: 0.26141 L1 loss: 0.0000e+00 L2 loss: 0.7062 Learning rate: 0.02 Mask loss: 0.16551 RPN box loss: 0.07389 RPN score loss: 0.00915 RPN total loss: 0.08304 Total loss: 1.21616 timestamp: 1654942341.3942962 iteration: 35500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06038 FastRCNN class loss: 0.03123 FastRCNN total loss: 0.0916 L1 loss: 0.0000e+00 L2 loss: 0.70612 Learning rate: 0.02 Mask loss: 0.10509 RPN box loss: 0.0056 RPN score loss: 0.00671 RPN total loss: 0.01231 Total loss: 0.91512 timestamp: 1654942344.5654602 iteration: 35505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08753 FastRCNN class loss: 0.05356 FastRCNN total loss: 0.14109 L1 loss: 0.0000e+00 L2 loss: 0.70602 Learning rate: 0.02 Mask loss: 0.15441 RPN box loss: 0.01323 RPN score loss: 0.00184 RPN total loss: 0.01508 Total loss: 1.0166 timestamp: 1654942347.841148 iteration: 35510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16324 FastRCNN class loss: 0.13077 FastRCNN total loss: 0.29401 L1 loss: 0.0000e+00 L2 loss: 0.7059 Learning rate: 0.02 Mask loss: 0.21569 RPN box loss: 0.03959 RPN score loss: 0.0088 RPN total loss: 0.04839 Total loss: 1.26399 timestamp: 1654942351.0699356 iteration: 35515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10799 FastRCNN class loss: 0.10429 FastRCNN total loss: 0.21228 L1 loss: 0.0000e+00 L2 loss: 0.70582 Learning rate: 0.02 Mask loss: 0.18468 RPN box loss: 0.04891 RPN score loss: 0.01364 RPN total loss: 0.06255 Total loss: 1.16533 timestamp: 1654942354.317024 iteration: 35520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17963 FastRCNN class loss: 0.09319 FastRCNN total loss: 0.27283 L1 loss: 0.0000e+00 L2 loss: 0.70573 Learning rate: 0.02 Mask loss: 0.19469 RPN box loss: 0.03025 RPN score loss: 0.01389 RPN total loss: 0.04414 Total loss: 1.21739 timestamp: 1654942357.481451 iteration: 35525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15586 FastRCNN class loss: 0.09006 FastRCNN total loss: 0.24591 L1 loss: 0.0000e+00 L2 loss: 0.70563 Learning rate: 0.02 Mask loss: 0.12397 RPN box loss: 0.0182 RPN score loss: 0.00278 RPN total loss: 0.02097 Total loss: 1.09648 timestamp: 1654942360.6819744 iteration: 35530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16831 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.24394 L1 loss: 0.0000e+00 L2 loss: 0.70554 Learning rate: 0.02 Mask loss: 0.21553 RPN box loss: 0.02538 RPN score loss: 0.00895 RPN total loss: 0.03433 Total loss: 1.19935 timestamp: 1654942363.866661 iteration: 35535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09891 FastRCNN class loss: 0.11102 FastRCNN total loss: 0.20993 L1 loss: 0.0000e+00 L2 loss: 0.70545 Learning rate: 0.02 Mask loss: 0.20151 RPN box loss: 0.07016 RPN score loss: 0.01778 RPN total loss: 0.08794 Total loss: 1.20482 timestamp: 1654942367.1110072 iteration: 35540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14786 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.23525 L1 loss: 0.0000e+00 L2 loss: 0.70537 Learning rate: 0.02 Mask loss: 0.15264 RPN box loss: 0.067 RPN score loss: 0.00741 RPN total loss: 0.07441 Total loss: 1.16767 timestamp: 1654942370.316246 iteration: 35545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21589 FastRCNN class loss: 0.12249 FastRCNN total loss: 0.33838 L1 loss: 0.0000e+00 L2 loss: 0.7053 Learning rate: 0.02 Mask loss: 0.22509 RPN box loss: 0.04683 RPN score loss: 0.00822 RPN total loss: 0.05506 Total loss: 1.32383 timestamp: 1654942373.4860647 iteration: 35550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14849 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.21104 L1 loss: 0.0000e+00 L2 loss: 0.70519 Learning rate: 0.02 Mask loss: 0.09465 RPN box loss: 0.04576 RPN score loss: 0.00187 RPN total loss: 0.04764 Total loss: 1.05852 timestamp: 1654942376.7520158 iteration: 35555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12694 FastRCNN class loss: 0.11475 FastRCNN total loss: 0.24169 L1 loss: 0.0000e+00 L2 loss: 0.70509 Learning rate: 0.02 Mask loss: 0.25654 RPN box loss: 0.05507 RPN score loss: 0.0125 RPN total loss: 0.06757 Total loss: 1.27089 timestamp: 1654942379.9298816 iteration: 35560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07899 FastRCNN class loss: 0.0399 FastRCNN total loss: 0.11889 L1 loss: 0.0000e+00 L2 loss: 0.70501 Learning rate: 0.02 Mask loss: 0.12153 RPN box loss: 0.02726 RPN score loss: 0.00848 RPN total loss: 0.03575 Total loss: 0.98118 timestamp: 1654942383.0435328 iteration: 35565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16324 FastRCNN class loss: 0.0796 FastRCNN total loss: 0.24284 L1 loss: 0.0000e+00 L2 loss: 0.70492 Learning rate: 0.02 Mask loss: 0.17201 RPN box loss: 0.02837 RPN score loss: 0.00768 RPN total loss: 0.03605 Total loss: 1.15581 timestamp: 1654942386.1491432 iteration: 35570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.15065 L1 loss: 0.0000e+00 L2 loss: 0.70484 Learning rate: 0.02 Mask loss: 0.15004 RPN box loss: 0.03243 RPN score loss: 0.01256 RPN total loss: 0.04499 Total loss: 1.05052 timestamp: 1654942389.322501 iteration: 35575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14519 FastRCNN class loss: 0.10963 FastRCNN total loss: 0.25482 L1 loss: 0.0000e+00 L2 loss: 0.70476 Learning rate: 0.02 Mask loss: 0.11632 RPN box loss: 0.03168 RPN score loss: 0.00577 RPN total loss: 0.03745 Total loss: 1.11336 timestamp: 1654942392.5162575 iteration: 35580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07114 FastRCNN class loss: 0.12296 FastRCNN total loss: 0.1941 L1 loss: 0.0000e+00 L2 loss: 0.70466 Learning rate: 0.02 Mask loss: 0.11979 RPN box loss: 0.03901 RPN score loss: 0.00588 RPN total loss: 0.04488 Total loss: 1.06344 timestamp: 1654942395.7179523 iteration: 35585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14306 FastRCNN class loss: 0.05028 FastRCNN total loss: 0.19334 L1 loss: 0.0000e+00 L2 loss: 0.70455 Learning rate: 0.02 Mask loss: 0.1033 RPN box loss: 0.01371 RPN score loss: 0.00296 RPN total loss: 0.01668 Total loss: 1.01786 timestamp: 1654942398.9241786 iteration: 35590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12467 FastRCNN class loss: 0.09717 FastRCNN total loss: 0.22184 L1 loss: 0.0000e+00 L2 loss: 0.70446 Learning rate: 0.02 Mask loss: 0.13822 RPN box loss: 0.0318 RPN score loss: 0.01408 RPN total loss: 0.04588 Total loss: 1.1104 timestamp: 1654942402.1168153 iteration: 35595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07378 FastRCNN class loss: 0.06236 FastRCNN total loss: 0.13613 L1 loss: 0.0000e+00 L2 loss: 0.70436 Learning rate: 0.02 Mask loss: 0.13268 RPN box loss: 0.03689 RPN score loss: 0.01215 RPN total loss: 0.04903 Total loss: 1.0222 timestamp: 1654942405.2983577 iteration: 35600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11793 FastRCNN class loss: 0.11813 FastRCNN total loss: 0.23606 L1 loss: 0.0000e+00 L2 loss: 0.70426 Learning rate: 0.02 Mask loss: 0.1417 RPN box loss: 0.05969 RPN score loss: 0.005 RPN total loss: 0.06469 Total loss: 1.14671 timestamp: 1654942408.5615468 iteration: 35605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05609 FastRCNN class loss: 0.03796 FastRCNN total loss: 0.09405 L1 loss: 0.0000e+00 L2 loss: 0.70419 Learning rate: 0.02 Mask loss: 0.10751 RPN box loss: 0.0027 RPN score loss: 0.00188 RPN total loss: 0.00458 Total loss: 0.91033 timestamp: 1654942411.7812588 iteration: 35610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11383 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.19987 L1 loss: 0.0000e+00 L2 loss: 0.70407 Learning rate: 0.02 Mask loss: 0.15575 RPN box loss: 0.03451 RPN score loss: 0.00562 RPN total loss: 0.04013 Total loss: 1.09982 timestamp: 1654942415.038249 iteration: 35615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15111 FastRCNN class loss: 0.07627 FastRCNN total loss: 0.22738 L1 loss: 0.0000e+00 L2 loss: 0.70396 Learning rate: 0.02 Mask loss: 0.24702 RPN box loss: 0.0266 RPN score loss: 0.00567 RPN total loss: 0.03226 Total loss: 1.21062 timestamp: 1654942418.2457445 iteration: 35620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17355 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.2355 L1 loss: 0.0000e+00 L2 loss: 0.70389 Learning rate: 0.02 Mask loss: 0.14087 RPN box loss: 0.07085 RPN score loss: 0.00399 RPN total loss: 0.07485 Total loss: 1.15509 timestamp: 1654942421.484084 iteration: 35625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17517 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.26971 L1 loss: 0.0000e+00 L2 loss: 0.70378 Learning rate: 0.02 Mask loss: 0.13822 RPN box loss: 0.0327 RPN score loss: 0.00551 RPN total loss: 0.03821 Total loss: 1.14991 timestamp: 1654942424.6774871 iteration: 35630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.11071 FastRCNN total loss: 0.20918 L1 loss: 0.0000e+00 L2 loss: 0.70369 Learning rate: 0.02 Mask loss: 0.12695 RPN box loss: 0.02132 RPN score loss: 0.00427 RPN total loss: 0.02559 Total loss: 1.0654 timestamp: 1654942427.9158356 iteration: 35635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18575 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.25003 L1 loss: 0.0000e+00 L2 loss: 0.70361 Learning rate: 0.02 Mask loss: 0.21605 RPN box loss: 0.01991 RPN score loss: 0.00349 RPN total loss: 0.0234 Total loss: 1.19309 timestamp: 1654942431.0887518 iteration: 35640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10263 FastRCNN class loss: 0.06743 FastRCNN total loss: 0.17006 L1 loss: 0.0000e+00 L2 loss: 0.7035 Learning rate: 0.02 Mask loss: 0.1036 RPN box loss: 0.00928 RPN score loss: 0.0022 RPN total loss: 0.01148 Total loss: 0.98864 timestamp: 1654942434.3076346 iteration: 35645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08754 FastRCNN class loss: 0.0407 FastRCNN total loss: 0.12825 L1 loss: 0.0000e+00 L2 loss: 0.70341 Learning rate: 0.02 Mask loss: 0.13325 RPN box loss: 0.01483 RPN score loss: 0.00402 RPN total loss: 0.01885 Total loss: 0.98377 timestamp: 1654942437.4713936 iteration: 35650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06831 FastRCNN class loss: 0.04913 FastRCNN total loss: 0.11744 L1 loss: 0.0000e+00 L2 loss: 0.70333 Learning rate: 0.02 Mask loss: 0.14404 RPN box loss: 0.02708 RPN score loss: 0.00361 RPN total loss: 0.03069 Total loss: 0.9955 timestamp: 1654942440.6823292 iteration: 35655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19889 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.30079 L1 loss: 0.0000e+00 L2 loss: 0.70323 Learning rate: 0.02 Mask loss: 0.20605 RPN box loss: 0.03042 RPN score loss: 0.00677 RPN total loss: 0.03719 Total loss: 1.24726 timestamp: 1654942443.8632855 iteration: 35660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10963 FastRCNN class loss: 0.09107 FastRCNN total loss: 0.2007 L1 loss: 0.0000e+00 L2 loss: 0.70316 Learning rate: 0.02 Mask loss: 0.13021 RPN box loss: 0.03263 RPN score loss: 0.00529 RPN total loss: 0.03792 Total loss: 1.07199 timestamp: 1654942447.0450976 iteration: 35665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10159 FastRCNN class loss: 0.06503 FastRCNN total loss: 0.16661 L1 loss: 0.0000e+00 L2 loss: 0.70305 Learning rate: 0.02 Mask loss: 0.14213 RPN box loss: 0.04779 RPN score loss: 0.02053 RPN total loss: 0.06833 Total loss: 1.08012 timestamp: 1654942450.2593346 iteration: 35670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10251 FastRCNN class loss: 0.04621 FastRCNN total loss: 0.14873 L1 loss: 0.0000e+00 L2 loss: 0.70295 Learning rate: 0.02 Mask loss: 0.1043 RPN box loss: 0.02877 RPN score loss: 0.00229 RPN total loss: 0.03107 Total loss: 0.98704 timestamp: 1654942453.4806197 iteration: 35675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.06522 FastRCNN total loss: 0.14834 L1 loss: 0.0000e+00 L2 loss: 0.70287 Learning rate: 0.02 Mask loss: 0.15161 RPN box loss: 0.00715 RPN score loss: 0.00213 RPN total loss: 0.00928 Total loss: 1.0121 timestamp: 1654942456.789124 iteration: 35680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16271 FastRCNN class loss: 0.12198 FastRCNN total loss: 0.28469 L1 loss: 0.0000e+00 L2 loss: 0.70277 Learning rate: 0.02 Mask loss: 0.20103 RPN box loss: 0.02855 RPN score loss: 0.01202 RPN total loss: 0.04056 Total loss: 1.22905 timestamp: 1654942459.958231 iteration: 35685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1666 FastRCNN class loss: 0.07956 FastRCNN total loss: 0.24616 L1 loss: 0.0000e+00 L2 loss: 0.70266 Learning rate: 0.02 Mask loss: 0.14549 RPN box loss: 0.02991 RPN score loss: 0.00644 RPN total loss: 0.03635 Total loss: 1.13065 timestamp: 1654942463.1272845 iteration: 35690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14552 FastRCNN class loss: 0.1182 FastRCNN total loss: 0.26372 L1 loss: 0.0000e+00 L2 loss: 0.70258 Learning rate: 0.02 Mask loss: 0.1309 RPN box loss: 0.02943 RPN score loss: 0.009 RPN total loss: 0.03843 Total loss: 1.13563 timestamp: 1654942466.3499367 iteration: 35695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1081 FastRCNN class loss: 0.05403 FastRCNN total loss: 0.16213 L1 loss: 0.0000e+00 L2 loss: 0.70246 Learning rate: 0.02 Mask loss: 0.10588 RPN box loss: 0.05302 RPN score loss: 0.00781 RPN total loss: 0.06083 Total loss: 1.03129 timestamp: 1654942469.4765933 iteration: 35700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1936 FastRCNN class loss: 0.09362 FastRCNN total loss: 0.28723 L1 loss: 0.0000e+00 L2 loss: 0.70237 Learning rate: 0.02 Mask loss: 0.20575 RPN box loss: 0.01843 RPN score loss: 0.00984 RPN total loss: 0.02827 Total loss: 1.22363 timestamp: 1654942472.674982 iteration: 35705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.11911 L1 loss: 0.0000e+00 L2 loss: 0.70227 Learning rate: 0.02 Mask loss: 0.16974 RPN box loss: 0.00615 RPN score loss: 0.00482 RPN total loss: 0.01097 Total loss: 1.00209 timestamp: 1654942475.875934 iteration: 35710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14407 FastRCNN class loss: 0.08559 FastRCNN total loss: 0.22966 L1 loss: 0.0000e+00 L2 loss: 0.70216 Learning rate: 0.02 Mask loss: 0.22628 RPN box loss: 0.03379 RPN score loss: 0.01502 RPN total loss: 0.04881 Total loss: 1.20691 timestamp: 1654942479.043909 iteration: 35715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13438 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.20182 L1 loss: 0.0000e+00 L2 loss: 0.70204 Learning rate: 0.02 Mask loss: 0.15404 RPN box loss: 0.0614 RPN score loss: 0.00388 RPN total loss: 0.06528 Total loss: 1.12318 timestamp: 1654942482.3157206 iteration: 35720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09693 FastRCNN class loss: 0.04167 FastRCNN total loss: 0.1386 L1 loss: 0.0000e+00 L2 loss: 0.70199 Learning rate: 0.02 Mask loss: 0.11158 RPN box loss: 0.01407 RPN score loss: 0.00464 RPN total loss: 0.01872 Total loss: 0.97089 timestamp: 1654942485.5105722 iteration: 35725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11122 FastRCNN class loss: 0.04593 FastRCNN total loss: 0.15715 L1 loss: 0.0000e+00 L2 loss: 0.70193 Learning rate: 0.02 Mask loss: 0.11953 RPN box loss: 0.0177 RPN score loss: 0.00204 RPN total loss: 0.01974 Total loss: 0.99835 timestamp: 1654942488.733868 iteration: 35730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13382 FastRCNN class loss: 0.10329 FastRCNN total loss: 0.2371 L1 loss: 0.0000e+00 L2 loss: 0.70185 Learning rate: 0.02 Mask loss: 0.16708 RPN box loss: 0.05543 RPN score loss: 0.00692 RPN total loss: 0.06234 Total loss: 1.16838 timestamp: 1654942491.8845558 iteration: 35735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08533 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.13738 L1 loss: 0.0000e+00 L2 loss: 0.70174 Learning rate: 0.02 Mask loss: 0.12736 RPN box loss: 0.03949 RPN score loss: 0.00201 RPN total loss: 0.04149 Total loss: 1.00797 timestamp: 1654942495.0948431 iteration: 35740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12906 FastRCNN class loss: 0.12139 FastRCNN total loss: 0.25045 L1 loss: 0.0000e+00 L2 loss: 0.70164 Learning rate: 0.02 Mask loss: 0.17164 RPN box loss: 0.04204 RPN score loss: 0.02066 RPN total loss: 0.0627 Total loss: 1.18643 timestamp: 1654942498.331848 iteration: 35745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1469 FastRCNN class loss: 0.05247 FastRCNN total loss: 0.19937 L1 loss: 0.0000e+00 L2 loss: 0.70152 Learning rate: 0.02 Mask loss: 0.21981 RPN box loss: 0.0221 RPN score loss: 0.0072 RPN total loss: 0.0293 Total loss: 1.14999 timestamp: 1654942501.5067966 iteration: 35750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11982 FastRCNN class loss: 0.09809 FastRCNN total loss: 0.21791 L1 loss: 0.0000e+00 L2 loss: 0.70143 Learning rate: 0.02 Mask loss: 0.13582 RPN box loss: 0.02872 RPN score loss: 0.00385 RPN total loss: 0.03258 Total loss: 1.08774 timestamp: 1654942504.7477775 iteration: 35755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09402 FastRCNN class loss: 0.07309 FastRCNN total loss: 0.16712 L1 loss: 0.0000e+00 L2 loss: 0.70135 Learning rate: 0.02 Mask loss: 0.11899 RPN box loss: 0.0246 RPN score loss: 0.0036 RPN total loss: 0.0282 Total loss: 1.01566 timestamp: 1654942507.9638937 iteration: 35760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.15026 L1 loss: 0.0000e+00 L2 loss: 0.70127 Learning rate: 0.02 Mask loss: 0.15598 RPN box loss: 0.03985 RPN score loss: 0.00516 RPN total loss: 0.04501 Total loss: 1.05251 timestamp: 1654942511.178036 iteration: 35765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09978 FastRCNN class loss: 0.08505 FastRCNN total loss: 0.18483 L1 loss: 0.0000e+00 L2 loss: 0.70116 Learning rate: 0.02 Mask loss: 0.19795 RPN box loss: 0.01836 RPN score loss: 0.00401 RPN total loss: 0.02238 Total loss: 1.10631 timestamp: 1654942514.3309374 iteration: 35770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.19309 L1 loss: 0.0000e+00 L2 loss: 0.70107 Learning rate: 0.02 Mask loss: 0.1756 RPN box loss: 0.06142 RPN score loss: 0.00985 RPN total loss: 0.07128 Total loss: 1.14103 timestamp: 1654942517.5301409 iteration: 35775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12901 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.19428 L1 loss: 0.0000e+00 L2 loss: 0.70097 Learning rate: 0.02 Mask loss: 0.1916 RPN box loss: 0.01202 RPN score loss: 0.00944 RPN total loss: 0.02145 Total loss: 1.1083 timestamp: 1654942520.7255743 iteration: 35780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07151 FastRCNN class loss: 0.08026 FastRCNN total loss: 0.15177 L1 loss: 0.0000e+00 L2 loss: 0.70087 Learning rate: 0.02 Mask loss: 0.1258 RPN box loss: 0.01901 RPN score loss: 0.00264 RPN total loss: 0.02166 Total loss: 1.00011 timestamp: 1654942523.8909595 iteration: 35785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09742 FastRCNN class loss: 0.06291 FastRCNN total loss: 0.16033 L1 loss: 0.0000e+00 L2 loss: 0.70078 Learning rate: 0.02 Mask loss: 0.15416 RPN box loss: 0.01009 RPN score loss: 0.00551 RPN total loss: 0.0156 Total loss: 1.03086 timestamp: 1654942527.099267 iteration: 35790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13885 FastRCNN class loss: 0.05273 FastRCNN total loss: 0.19157 L1 loss: 0.0000e+00 L2 loss: 0.70067 Learning rate: 0.02 Mask loss: 0.15069 RPN box loss: 0.02466 RPN score loss: 0.00863 RPN total loss: 0.03329 Total loss: 1.07622 timestamp: 1654942530.327108 iteration: 35795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.05334 FastRCNN total loss: 0.13844 L1 loss: 0.0000e+00 L2 loss: 0.70058 Learning rate: 0.02 Mask loss: 0.1267 RPN box loss: 0.01849 RPN score loss: 0.00128 RPN total loss: 0.01978 Total loss: 0.9855 timestamp: 1654942533.4423652 iteration: 35800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18301 FastRCNN class loss: 0.12032 FastRCNN total loss: 0.30333 L1 loss: 0.0000e+00 L2 loss: 0.70046 Learning rate: 0.02 Mask loss: 0.23508 RPN box loss: 0.03172 RPN score loss: 0.00484 RPN total loss: 0.03656 Total loss: 1.27543 timestamp: 1654942536.6429975 iteration: 35805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14744 FastRCNN class loss: 0.10209 FastRCNN total loss: 0.24954 L1 loss: 0.0000e+00 L2 loss: 0.7004 Learning rate: 0.02 Mask loss: 0.14928 RPN box loss: 0.03273 RPN score loss: 0.00636 RPN total loss: 0.03908 Total loss: 1.13829 timestamp: 1654942539.903707 iteration: 35810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17936 FastRCNN class loss: 0.11493 FastRCNN total loss: 0.29429 L1 loss: 0.0000e+00 L2 loss: 0.70032 Learning rate: 0.02 Mask loss: 0.18115 RPN box loss: 0.04335 RPN score loss: 0.00628 RPN total loss: 0.04964 Total loss: 1.2254 timestamp: 1654942543.055248 iteration: 35815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.18932 L1 loss: 0.0000e+00 L2 loss: 0.70021 Learning rate: 0.02 Mask loss: 0.19656 RPN box loss: 0.03283 RPN score loss: 0.00921 RPN total loss: 0.04204 Total loss: 1.12813 timestamp: 1654942546.2089887 iteration: 35820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16489 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.24703 L1 loss: 0.0000e+00 L2 loss: 0.70013 Learning rate: 0.02 Mask loss: 0.15502 RPN box loss: 0.00993 RPN score loss: 0.00385 RPN total loss: 0.01378 Total loss: 1.11595 timestamp: 1654942549.4255877 iteration: 35825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.06592 FastRCNN total loss: 0.15113 L1 loss: 0.0000e+00 L2 loss: 0.70003 Learning rate: 0.02 Mask loss: 0.15441 RPN box loss: 0.01861 RPN score loss: 0.00351 RPN total loss: 0.02213 Total loss: 1.0277 timestamp: 1654942552.6843383 iteration: 35830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1546 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.233 L1 loss: 0.0000e+00 L2 loss: 0.69994 Learning rate: 0.02 Mask loss: 0.17516 RPN box loss: 0.05778 RPN score loss: 0.00663 RPN total loss: 0.06441 Total loss: 1.1725 timestamp: 1654942555.9254704 iteration: 35835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14306 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.20857 L1 loss: 0.0000e+00 L2 loss: 0.69986 Learning rate: 0.02 Mask loss: 0.1235 RPN box loss: 0.06272 RPN score loss: 0.0008 RPN total loss: 0.06352 Total loss: 1.09544 timestamp: 1654942559.1311772 iteration: 35840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10971 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.17848 L1 loss: 0.0000e+00 L2 loss: 0.69974 Learning rate: 0.02 Mask loss: 0.29681 RPN box loss: 0.04878 RPN score loss: 0.00907 RPN total loss: 0.05785 Total loss: 1.23289 timestamp: 1654942562.3224444 iteration: 35845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.132 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.19746 L1 loss: 0.0000e+00 L2 loss: 0.69965 Learning rate: 0.02 Mask loss: 0.14169 RPN box loss: 0.04405 RPN score loss: 0.00845 RPN total loss: 0.0525 Total loss: 1.0913 timestamp: 1654942565.5580168 iteration: 35850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16096 FastRCNN class loss: 0.15373 FastRCNN total loss: 0.31469 L1 loss: 0.0000e+00 L2 loss: 0.69958 Learning rate: 0.02 Mask loss: 0.22414 RPN box loss: 0.07334 RPN score loss: 0.00951 RPN total loss: 0.08285 Total loss: 1.32126 timestamp: 1654942568.7239861 iteration: 35855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11469 FastRCNN class loss: 0.09099 FastRCNN total loss: 0.20568 L1 loss: 0.0000e+00 L2 loss: 0.69947 Learning rate: 0.02 Mask loss: 0.1976 RPN box loss: 0.03794 RPN score loss: 0.0134 RPN total loss: 0.05134 Total loss: 1.15408 timestamp: 1654942572.0243716 iteration: 35860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11244 FastRCNN class loss: 0.04365 FastRCNN total loss: 0.15609 L1 loss: 0.0000e+00 L2 loss: 0.69937 Learning rate: 0.02 Mask loss: 0.0977 RPN box loss: 0.00775 RPN score loss: 0.00228 RPN total loss: 0.01002 Total loss: 0.96319 timestamp: 1654942575.2399485 iteration: 35865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10177 FastRCNN class loss: 0.05816 FastRCNN total loss: 0.15993 L1 loss: 0.0000e+00 L2 loss: 0.69931 Learning rate: 0.02 Mask loss: 0.10636 RPN box loss: 0.01034 RPN score loss: 0.00476 RPN total loss: 0.01511 Total loss: 0.98071 timestamp: 1654942578.446829 iteration: 35870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09495 FastRCNN class loss: 0.12351 FastRCNN total loss: 0.21845 L1 loss: 0.0000e+00 L2 loss: 0.69922 Learning rate: 0.02 Mask loss: 0.10132 RPN box loss: 0.01939 RPN score loss: 0.00513 RPN total loss: 0.02452 Total loss: 1.04351 timestamp: 1654942581.6345656 iteration: 35875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10167 FastRCNN class loss: 0.04719 FastRCNN total loss: 0.14886 L1 loss: 0.0000e+00 L2 loss: 0.69912 Learning rate: 0.02 Mask loss: 0.17828 RPN box loss: 0.01999 RPN score loss: 0.01371 RPN total loss: 0.03371 Total loss: 1.05996 timestamp: 1654942584.7471037 iteration: 35880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12204 FastRCNN class loss: 0.06552 FastRCNN total loss: 0.18755 L1 loss: 0.0000e+00 L2 loss: 0.69903 Learning rate: 0.02 Mask loss: 0.13296 RPN box loss: 0.04435 RPN score loss: 0.00246 RPN total loss: 0.04682 Total loss: 1.06636 timestamp: 1654942587.9253688 iteration: 35885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13928 FastRCNN class loss: 0.11006 FastRCNN total loss: 0.24935 L1 loss: 0.0000e+00 L2 loss: 0.69893 Learning rate: 0.02 Mask loss: 0.23549 RPN box loss: 0.01118 RPN score loss: 0.01381 RPN total loss: 0.02499 Total loss: 1.20876 timestamp: 1654942591.1378276 iteration: 35890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12101 FastRCNN class loss: 0.09277 FastRCNN total loss: 0.21378 L1 loss: 0.0000e+00 L2 loss: 0.69884 Learning rate: 0.02 Mask loss: 0.12724 RPN box loss: 0.05626 RPN score loss: 0.00802 RPN total loss: 0.06428 Total loss: 1.10413 timestamp: 1654942594.3659458 iteration: 35895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23672 FastRCNN class loss: 0.09291 FastRCNN total loss: 0.32963 L1 loss: 0.0000e+00 L2 loss: 0.69876 Learning rate: 0.02 Mask loss: 0.12476 RPN box loss: 0.01672 RPN score loss: 0.00317 RPN total loss: 0.01988 Total loss: 1.17303 timestamp: 1654942597.557256 iteration: 35900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15953 FastRCNN class loss: 0.08772 FastRCNN total loss: 0.24725 L1 loss: 0.0000e+00 L2 loss: 0.69866 Learning rate: 0.02 Mask loss: 0.12531 RPN box loss: 0.01031 RPN score loss: 0.00507 RPN total loss: 0.01539 Total loss: 1.0866 timestamp: 1654942600.722391 iteration: 35905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.146 FastRCNN class loss: 0.06263 FastRCNN total loss: 0.20863 L1 loss: 0.0000e+00 L2 loss: 0.69856 Learning rate: 0.02 Mask loss: 0.1844 RPN box loss: 0.04059 RPN score loss: 0.00714 RPN total loss: 0.04773 Total loss: 1.13933 timestamp: 1654942603.9567995 iteration: 35910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22662 FastRCNN class loss: 0.09481 FastRCNN total loss: 0.32143 L1 loss: 0.0000e+00 L2 loss: 0.69846 Learning rate: 0.02 Mask loss: 0.12616 RPN box loss: 0.03843 RPN score loss: 0.01105 RPN total loss: 0.04948 Total loss: 1.19553 timestamp: 1654942607.1883993 iteration: 35915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1127 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.17867 L1 loss: 0.0000e+00 L2 loss: 0.69838 Learning rate: 0.02 Mask loss: 0.17549 RPN box loss: 0.02214 RPN score loss: 0.00582 RPN total loss: 0.02796 Total loss: 1.0805 timestamp: 1654942610.388069 iteration: 35920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14512 FastRCNN class loss: 0.12241 FastRCNN total loss: 0.26753 L1 loss: 0.0000e+00 L2 loss: 0.6983 Learning rate: 0.02 Mask loss: 0.15696 RPN box loss: 0.03226 RPN score loss: 0.00475 RPN total loss: 0.03701 Total loss: 1.15979 timestamp: 1654942613.6223805 iteration: 35925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11193 FastRCNN class loss: 0.1054 FastRCNN total loss: 0.21732 L1 loss: 0.0000e+00 L2 loss: 0.69821 Learning rate: 0.02 Mask loss: 0.12412 RPN box loss: 0.03778 RPN score loss: 0.01018 RPN total loss: 0.04796 Total loss: 1.08761 timestamp: 1654942616.8611739 iteration: 35930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16736 FastRCNN class loss: 0.09054 FastRCNN total loss: 0.2579 L1 loss: 0.0000e+00 L2 loss: 0.6981 Learning rate: 0.02 Mask loss: 0.20155 RPN box loss: 0.02973 RPN score loss: 0.00675 RPN total loss: 0.03648 Total loss: 1.19403 timestamp: 1654942620.1279685 iteration: 35935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13509 FastRCNN class loss: 0.06249 FastRCNN total loss: 0.19758 L1 loss: 0.0000e+00 L2 loss: 0.69799 Learning rate: 0.02 Mask loss: 0.13706 RPN box loss: 0.01318 RPN score loss: 0.00471 RPN total loss: 0.01789 Total loss: 1.05052 timestamp: 1654942623.365819 iteration: 35940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06314 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.13752 L1 loss: 0.0000e+00 L2 loss: 0.6979 Learning rate: 0.02 Mask loss: 0.15927 RPN box loss: 0.05581 RPN score loss: 0.01524 RPN total loss: 0.07106 Total loss: 1.06575 timestamp: 1654942626.5640357 iteration: 35945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19397 FastRCNN class loss: 0.10739 FastRCNN total loss: 0.30136 L1 loss: 0.0000e+00 L2 loss: 0.6978 Learning rate: 0.02 Mask loss: 0.17507 RPN box loss: 0.0499 RPN score loss: 0.02037 RPN total loss: 0.07027 Total loss: 1.24449 timestamp: 1654942629.7332823 iteration: 35950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13234 FastRCNN class loss: 0.06856 FastRCNN total loss: 0.2009 L1 loss: 0.0000e+00 L2 loss: 0.69773 Learning rate: 0.02 Mask loss: 0.12251 RPN box loss: 0.029 RPN score loss: 0.00561 RPN total loss: 0.03461 Total loss: 1.05576 timestamp: 1654942632.9679544 iteration: 35955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1683 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.24905 L1 loss: 0.0000e+00 L2 loss: 0.69766 Learning rate: 0.02 Mask loss: 0.13341 RPN box loss: 0.03399 RPN score loss: 0.00388 RPN total loss: 0.03786 Total loss: 1.11798 timestamp: 1654942636.163494 iteration: 35960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15234 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.2221 L1 loss: 0.0000e+00 L2 loss: 0.69757 Learning rate: 0.02 Mask loss: 0.12641 RPN box loss: 0.01203 RPN score loss: 0.00373 RPN total loss: 0.01576 Total loss: 1.06183 timestamp: 1654942639.3568764 iteration: 35965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13526 FastRCNN class loss: 0.09871 FastRCNN total loss: 0.23397 L1 loss: 0.0000e+00 L2 loss: 0.69747 Learning rate: 0.02 Mask loss: 0.17255 RPN box loss: 0.02432 RPN score loss: 0.01628 RPN total loss: 0.0406 Total loss: 1.1446 timestamp: 1654942642.5371637 iteration: 35970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12811 FastRCNN class loss: 0.04294 FastRCNN total loss: 0.17105 L1 loss: 0.0000e+00 L2 loss: 0.69739 Learning rate: 0.02 Mask loss: 0.11872 RPN box loss: 0.01426 RPN score loss: 0.00083 RPN total loss: 0.0151 Total loss: 1.00226 timestamp: 1654942645.7331295 iteration: 35975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.09002 FastRCNN total loss: 0.23346 L1 loss: 0.0000e+00 L2 loss: 0.69728 Learning rate: 0.02 Mask loss: 0.21207 RPN box loss: 0.05805 RPN score loss: 0.00644 RPN total loss: 0.06449 Total loss: 1.2073 timestamp: 1654942648.9169853 iteration: 35980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0761 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.13234 L1 loss: 0.0000e+00 L2 loss: 0.69721 Learning rate: 0.02 Mask loss: 0.17351 RPN box loss: 0.03869 RPN score loss: 0.00523 RPN total loss: 0.04392 Total loss: 1.04698 timestamp: 1654942652.1151528 iteration: 35985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13216 FastRCNN class loss: 0.06395 FastRCNN total loss: 0.1961 L1 loss: 0.0000e+00 L2 loss: 0.69714 Learning rate: 0.02 Mask loss: 0.20312 RPN box loss: 0.06052 RPN score loss: 0.00495 RPN total loss: 0.06547 Total loss: 1.16184 timestamp: 1654942655.2365448 iteration: 35990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15032 FastRCNN class loss: 0.08588 FastRCNN total loss: 0.2362 L1 loss: 0.0000e+00 L2 loss: 0.69703 Learning rate: 0.02 Mask loss: 0.13024 RPN box loss: 0.02372 RPN score loss: 0.00523 RPN total loss: 0.02894 Total loss: 1.09241 timestamp: 1654942658.4113653 iteration: 35995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06407 FastRCNN class loss: 0.02263 FastRCNN total loss: 0.0867 L1 loss: 0.0000e+00 L2 loss: 0.69695 Learning rate: 0.02 Mask loss: 0.10735 RPN box loss: 0.00078 RPN score loss: 0.00145 RPN total loss: 0.00223 Total loss: 0.89323 timestamp: 1654942661.6704676 iteration: 36000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10003 FastRCNN class loss: 0.06095 FastRCNN total loss: 0.16097 L1 loss: 0.0000e+00 L2 loss: 0.69685 Learning rate: 0.02 Mask loss: 0.12423 RPN box loss: 0.0254 RPN score loss: 0.00262 RPN total loss: 0.02801 Total loss: 1.01007 timestamp: 1654942664.891658 iteration: 36005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13234 FastRCNN class loss: 0.06336 FastRCNN total loss: 0.19569 L1 loss: 0.0000e+00 L2 loss: 0.69677 Learning rate: 0.02 Mask loss: 0.09604 RPN box loss: 0.02213 RPN score loss: 0.00399 RPN total loss: 0.02612 Total loss: 1.01463 timestamp: 1654942668.037091 iteration: 36010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12213 FastRCNN class loss: 0.13672 FastRCNN total loss: 0.25885 L1 loss: 0.0000e+00 L2 loss: 0.6967 Learning rate: 0.02 Mask loss: 0.17676 RPN box loss: 0.02411 RPN score loss: 0.00548 RPN total loss: 0.02959 Total loss: 1.1619 timestamp: 1654942671.2552714 iteration: 36015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15303 FastRCNN class loss: 0.10949 FastRCNN total loss: 0.26252 L1 loss: 0.0000e+00 L2 loss: 0.69661 Learning rate: 0.02 Mask loss: 0.17525 RPN box loss: 0.0157 RPN score loss: 0.00715 RPN total loss: 0.02285 Total loss: 1.15724 timestamp: 1654942674.5099905 iteration: 36020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15672 FastRCNN class loss: 0.10442 FastRCNN total loss: 0.26114 L1 loss: 0.0000e+00 L2 loss: 0.69651 Learning rate: 0.02 Mask loss: 0.14537 RPN box loss: 0.02074 RPN score loss: 0.00749 RPN total loss: 0.02823 Total loss: 1.13124 timestamp: 1654942677.748113 iteration: 36025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18007 FastRCNN class loss: 0.0567 FastRCNN total loss: 0.23677 L1 loss: 0.0000e+00 L2 loss: 0.69641 Learning rate: 0.02 Mask loss: 0.11727 RPN box loss: 0.02559 RPN score loss: 0.00254 RPN total loss: 0.02813 Total loss: 1.07859 timestamp: 1654942680.9520168 iteration: 36030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13941 FastRCNN class loss: 0.06959 FastRCNN total loss: 0.20901 L1 loss: 0.0000e+00 L2 loss: 0.69631 Learning rate: 0.02 Mask loss: 0.30612 RPN box loss: 0.03516 RPN score loss: 0.00466 RPN total loss: 0.03982 Total loss: 1.25126 timestamp: 1654942684.1346304 iteration: 36035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07767 FastRCNN class loss: 0.11615 FastRCNN total loss: 0.19383 L1 loss: 0.0000e+00 L2 loss: 0.6962 Learning rate: 0.02 Mask loss: 0.13321 RPN box loss: 0.03461 RPN score loss: 0.01833 RPN total loss: 0.05294 Total loss: 1.07618 timestamp: 1654942687.313684 iteration: 36040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11842 FastRCNN class loss: 0.08881 FastRCNN total loss: 0.20723 L1 loss: 0.0000e+00 L2 loss: 0.6961 Learning rate: 0.02 Mask loss: 0.16335 RPN box loss: 0.01617 RPN score loss: 0.00315 RPN total loss: 0.01932 Total loss: 1.086 timestamp: 1654942690.46189 iteration: 36045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1394 FastRCNN class loss: 0.09692 FastRCNN total loss: 0.23633 L1 loss: 0.0000e+00 L2 loss: 0.69601 Learning rate: 0.02 Mask loss: 0.24834 RPN box loss: 0.06574 RPN score loss: 0.01017 RPN total loss: 0.07592 Total loss: 1.2566 timestamp: 1654942693.682029 iteration: 36050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1128 FastRCNN class loss: 0.06321 FastRCNN total loss: 0.17601 L1 loss: 0.0000e+00 L2 loss: 0.69592 Learning rate: 0.02 Mask loss: 0.17026 RPN box loss: 0.05418 RPN score loss: 0.0031 RPN total loss: 0.05728 Total loss: 1.09947 timestamp: 1654942696.8897028 iteration: 36055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08323 FastRCNN class loss: 0.04733 FastRCNN total loss: 0.13056 L1 loss: 0.0000e+00 L2 loss: 0.69582 Learning rate: 0.02 Mask loss: 0.10602 RPN box loss: 0.06669 RPN score loss: 0.00655 RPN total loss: 0.07324 Total loss: 1.00564 timestamp: 1654942700.0616045 iteration: 36060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12307 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.17874 L1 loss: 0.0000e+00 L2 loss: 0.69574 Learning rate: 0.02 Mask loss: 0.14071 RPN box loss: 0.04546 RPN score loss: 0.01301 RPN total loss: 0.05847 Total loss: 1.07366 timestamp: 1654942703.2414963 iteration: 36065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.113 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.18557 L1 loss: 0.0000e+00 L2 loss: 0.69565 Learning rate: 0.02 Mask loss: 0.11675 RPN box loss: 0.0252 RPN score loss: 0.00403 RPN total loss: 0.02923 Total loss: 1.02719 timestamp: 1654942706.459451 iteration: 36070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15655 FastRCNN class loss: 0.13708 FastRCNN total loss: 0.29362 L1 loss: 0.0000e+00 L2 loss: 0.69557 Learning rate: 0.02 Mask loss: 0.1598 RPN box loss: 0.03365 RPN score loss: 0.00436 RPN total loss: 0.03801 Total loss: 1.187 timestamp: 1654942709.653317 iteration: 36075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1409 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.21605 L1 loss: 0.0000e+00 L2 loss: 0.69545 Learning rate: 0.02 Mask loss: 0.17672 RPN box loss: 0.02287 RPN score loss: 0.00822 RPN total loss: 0.03109 Total loss: 1.11931 timestamp: 1654942712.8155985 iteration: 36080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14045 FastRCNN class loss: 0.06142 FastRCNN total loss: 0.20187 L1 loss: 0.0000e+00 L2 loss: 0.69537 Learning rate: 0.02 Mask loss: 0.108 RPN box loss: 0.01264 RPN score loss: 0.00235 RPN total loss: 0.01499 Total loss: 1.02022 timestamp: 1654942716.0484183 iteration: 36085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08699 FastRCNN class loss: 0.05043 FastRCNN total loss: 0.13742 L1 loss: 0.0000e+00 L2 loss: 0.69527 Learning rate: 0.02 Mask loss: 0.13757 RPN box loss: 0.02053 RPN score loss: 0.00724 RPN total loss: 0.02777 Total loss: 0.99803 timestamp: 1654942719.198226 iteration: 36090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13431 FastRCNN class loss: 0.0641 FastRCNN total loss: 0.19841 L1 loss: 0.0000e+00 L2 loss: 0.69518 Learning rate: 0.02 Mask loss: 0.14699 RPN box loss: 0.03194 RPN score loss: 0.00518 RPN total loss: 0.03712 Total loss: 1.0777 timestamp: 1654942722.379937 iteration: 36095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13758 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.22497 L1 loss: 0.0000e+00 L2 loss: 0.69507 Learning rate: 0.02 Mask loss: 0.27719 RPN box loss: 0.03567 RPN score loss: 0.00529 RPN total loss: 0.04095 Total loss: 1.23818 timestamp: 1654942725.572387 iteration: 36100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11321 FastRCNN class loss: 0.07693 FastRCNN total loss: 0.19014 L1 loss: 0.0000e+00 L2 loss: 0.69497 Learning rate: 0.02 Mask loss: 0.15231 RPN box loss: 0.02298 RPN score loss: 0.01118 RPN total loss: 0.03416 Total loss: 1.07158 timestamp: 1654942728.8142812 iteration: 36105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19941 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.27421 L1 loss: 0.0000e+00 L2 loss: 0.6949 Learning rate: 0.02 Mask loss: 0.17531 RPN box loss: 0.02209 RPN score loss: 0.00693 RPN total loss: 0.02902 Total loss: 1.17344 timestamp: 1654942732.1050375 iteration: 36110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15434 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.20653 L1 loss: 0.0000e+00 L2 loss: 0.69481 Learning rate: 0.02 Mask loss: 0.07573 RPN box loss: 0.00827 RPN score loss: 0.00127 RPN total loss: 0.00955 Total loss: 0.98662 timestamp: 1654942735.2847388 iteration: 36115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0824 FastRCNN class loss: 0.04766 FastRCNN total loss: 0.13006 L1 loss: 0.0000e+00 L2 loss: 0.69471 Learning rate: 0.02 Mask loss: 0.14601 RPN box loss: 0.03397 RPN score loss: 0.01355 RPN total loss: 0.04752 Total loss: 1.0183 timestamp: 1654942738.450215 iteration: 36120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17735 FastRCNN class loss: 0.10218 FastRCNN total loss: 0.27953 L1 loss: 0.0000e+00 L2 loss: 0.6946 Learning rate: 0.02 Mask loss: 0.12797 RPN box loss: 0.03422 RPN score loss: 0.00623 RPN total loss: 0.04045 Total loss: 1.14255 timestamp: 1654942741.6790385 iteration: 36125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12303 FastRCNN class loss: 0.0891 FastRCNN total loss: 0.21214 L1 loss: 0.0000e+00 L2 loss: 0.69449 Learning rate: 0.02 Mask loss: 0.14027 RPN box loss: 0.03103 RPN score loss: 0.00524 RPN total loss: 0.03627 Total loss: 1.08317 timestamp: 1654942744.900993 iteration: 36130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22173 FastRCNN class loss: 0.09811 FastRCNN total loss: 0.31984 L1 loss: 0.0000e+00 L2 loss: 0.6944 Learning rate: 0.02 Mask loss: 0.19405 RPN box loss: 0.04844 RPN score loss: 0.00824 RPN total loss: 0.05669 Total loss: 1.26497 timestamp: 1654942748.0990222 iteration: 36135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09378 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.16111 L1 loss: 0.0000e+00 L2 loss: 0.69429 Learning rate: 0.02 Mask loss: 0.13156 RPN box loss: 0.03526 RPN score loss: 0.00752 RPN total loss: 0.04277 Total loss: 1.02974 timestamp: 1654942751.342826 iteration: 36140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12384 FastRCNN class loss: 0.08367 FastRCNN total loss: 0.20752 L1 loss: 0.0000e+00 L2 loss: 0.69422 Learning rate: 0.02 Mask loss: 0.0959 RPN box loss: 0.0121 RPN score loss: 0.00438 RPN total loss: 0.01648 Total loss: 1.01411 timestamp: 1654942754.5654025 iteration: 36145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19074 FastRCNN class loss: 0.10015 FastRCNN total loss: 0.29089 L1 loss: 0.0000e+00 L2 loss: 0.69412 Learning rate: 0.02 Mask loss: 0.14975 RPN box loss: 0.01428 RPN score loss: 0.00205 RPN total loss: 0.01633 Total loss: 1.1511 timestamp: 1654942757.890999 iteration: 36150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13107 FastRCNN class loss: 0.07749 FastRCNN total loss: 0.20856 L1 loss: 0.0000e+00 L2 loss: 0.694 Learning rate: 0.02 Mask loss: 0.13114 RPN box loss: 0.01809 RPN score loss: 0.00281 RPN total loss: 0.0209 Total loss: 1.0546 timestamp: 1654942761.0992968 iteration: 36155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13065 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.21933 L1 loss: 0.0000e+00 L2 loss: 0.69391 Learning rate: 0.02 Mask loss: 0.1454 RPN box loss: 0.02468 RPN score loss: 0.00428 RPN total loss: 0.02896 Total loss: 1.08759 timestamp: 1654942764.3761163 iteration: 36160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11588 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.18614 L1 loss: 0.0000e+00 L2 loss: 0.69385 Learning rate: 0.02 Mask loss: 0.09725 RPN box loss: 0.00772 RPN score loss: 0.00387 RPN total loss: 0.01159 Total loss: 0.98883 timestamp: 1654942767.5465043 iteration: 36165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1057 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.17814 L1 loss: 0.0000e+00 L2 loss: 0.69379 Learning rate: 0.02 Mask loss: 0.17069 RPN box loss: 0.04323 RPN score loss: 0.00812 RPN total loss: 0.05135 Total loss: 1.09398 timestamp: 1654942770.692492 iteration: 36170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16056 FastRCNN class loss: 0.14515 FastRCNN total loss: 0.30572 L1 loss: 0.0000e+00 L2 loss: 0.69372 Learning rate: 0.02 Mask loss: 0.1531 RPN box loss: 0.03112 RPN score loss: 0.01071 RPN total loss: 0.04182 Total loss: 1.19435 timestamp: 1654942773.9109654 iteration: 36175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18237 FastRCNN class loss: 0.09233 FastRCNN total loss: 0.27471 L1 loss: 0.0000e+00 L2 loss: 0.69365 Learning rate: 0.02 Mask loss: 0.20867 RPN box loss: 0.04126 RPN score loss: 0.0083 RPN total loss: 0.04957 Total loss: 1.22659 timestamp: 1654942777.0687091 iteration: 36180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13427 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.19863 L1 loss: 0.0000e+00 L2 loss: 0.69356 Learning rate: 0.02 Mask loss: 0.11644 RPN box loss: 0.00998 RPN score loss: 0.00595 RPN total loss: 0.01593 Total loss: 1.02456 timestamp: 1654942780.2586732 iteration: 36185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19278 FastRCNN class loss: 0.19518 FastRCNN total loss: 0.38796 L1 loss: 0.0000e+00 L2 loss: 0.69346 Learning rate: 0.02 Mask loss: 0.23201 RPN box loss: 0.04931 RPN score loss: 0.00599 RPN total loss: 0.05531 Total loss: 1.36873 timestamp: 1654942783.4359667 iteration: 36190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08983 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.16206 L1 loss: 0.0000e+00 L2 loss: 0.69337 Learning rate: 0.02 Mask loss: 0.20039 RPN box loss: 0.02602 RPN score loss: 0.00705 RPN total loss: 0.03306 Total loss: 1.08888 timestamp: 1654942786.6234393 iteration: 36195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13266 FastRCNN class loss: 0.05714 FastRCNN total loss: 0.1898 L1 loss: 0.0000e+00 L2 loss: 0.69329 Learning rate: 0.02 Mask loss: 0.16835 RPN box loss: 0.01874 RPN score loss: 0.00089 RPN total loss: 0.01964 Total loss: 1.07108 timestamp: 1654942789.8055048 iteration: 36200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06126 FastRCNN class loss: 0.03685 FastRCNN total loss: 0.09811 L1 loss: 0.0000e+00 L2 loss: 0.69321 Learning rate: 0.02 Mask loss: 0.1107 RPN box loss: 0.00992 RPN score loss: 0.00553 RPN total loss: 0.01545 Total loss: 0.91747 timestamp: 1654942792.9462547 iteration: 36205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08014 FastRCNN class loss: 0.06558 FastRCNN total loss: 0.14572 L1 loss: 0.0000e+00 L2 loss: 0.69312 Learning rate: 0.02 Mask loss: 0.11058 RPN box loss: 0.03978 RPN score loss: 0.00548 RPN total loss: 0.04526 Total loss: 0.99468 timestamp: 1654942796.0963964 iteration: 36210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10293 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.17871 L1 loss: 0.0000e+00 L2 loss: 0.69303 Learning rate: 0.02 Mask loss: 0.14464 RPN box loss: 0.01644 RPN score loss: 0.00601 RPN total loss: 0.02245 Total loss: 1.03883 timestamp: 1654942799.2443075 iteration: 36215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09123 FastRCNN class loss: 0.05309 FastRCNN total loss: 0.14432 L1 loss: 0.0000e+00 L2 loss: 0.69295 Learning rate: 0.02 Mask loss: 0.13183 RPN box loss: 0.0623 RPN score loss: 0.00954 RPN total loss: 0.07184 Total loss: 1.04094 timestamp: 1654942802.4665606 iteration: 36220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09743 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.18013 L1 loss: 0.0000e+00 L2 loss: 0.69284 Learning rate: 0.02 Mask loss: 0.17868 RPN box loss: 0.02686 RPN score loss: 0.00668 RPN total loss: 0.03354 Total loss: 1.0852 timestamp: 1654942805.6341481 iteration: 36225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10012 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.16049 L1 loss: 0.0000e+00 L2 loss: 0.69277 Learning rate: 0.02 Mask loss: 0.13889 RPN box loss: 0.01633 RPN score loss: 0.00694 RPN total loss: 0.02326 Total loss: 1.01542 timestamp: 1654942808.8130152 iteration: 36230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19361 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.29747 L1 loss: 0.0000e+00 L2 loss: 0.69271 Learning rate: 0.02 Mask loss: 0.16984 RPN box loss: 0.04729 RPN score loss: 0.00611 RPN total loss: 0.0534 Total loss: 1.21342 timestamp: 1654942811.9610305 iteration: 36235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14591 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.22871 L1 loss: 0.0000e+00 L2 loss: 0.69261 Learning rate: 0.02 Mask loss: 0.18459 RPN box loss: 0.04269 RPN score loss: 0.00709 RPN total loss: 0.04978 Total loss: 1.15568 timestamp: 1654942815.2073355 iteration: 36240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13596 FastRCNN class loss: 0.10785 FastRCNN total loss: 0.24382 L1 loss: 0.0000e+00 L2 loss: 0.69251 Learning rate: 0.02 Mask loss: 0.15253 RPN box loss: 0.03494 RPN score loss: 0.01414 RPN total loss: 0.04908 Total loss: 1.13794 timestamp: 1654942818.3366857 iteration: 36245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10529 FastRCNN class loss: 0.05394 FastRCNN total loss: 0.15923 L1 loss: 0.0000e+00 L2 loss: 0.69241 Learning rate: 0.02 Mask loss: 0.101 RPN box loss: 0.00439 RPN score loss: 0.00173 RPN total loss: 0.00613 Total loss: 0.95877 timestamp: 1654942821.4321682 iteration: 36250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09586 FastRCNN class loss: 0.06015 FastRCNN total loss: 0.15601 L1 loss: 0.0000e+00 L2 loss: 0.69233 Learning rate: 0.02 Mask loss: 0.13768 RPN box loss: 0.01753 RPN score loss: 0.00677 RPN total loss: 0.0243 Total loss: 1.01031 timestamp: 1654942824.6376286 iteration: 36255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14975 FastRCNN class loss: 0.0583 FastRCNN total loss: 0.20805 L1 loss: 0.0000e+00 L2 loss: 0.69225 Learning rate: 0.02 Mask loss: 0.10559 RPN box loss: 0.02391 RPN score loss: 0.00399 RPN total loss: 0.0279 Total loss: 1.03379 timestamp: 1654942827.828915 iteration: 36260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15927 FastRCNN class loss: 0.14354 FastRCNN total loss: 0.30282 L1 loss: 0.0000e+00 L2 loss: 0.69214 Learning rate: 0.02 Mask loss: 0.20705 RPN box loss: 0.04678 RPN score loss: 0.00367 RPN total loss: 0.05045 Total loss: 1.25245 timestamp: 1654942830.979416 iteration: 36265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14021 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.22383 L1 loss: 0.0000e+00 L2 loss: 0.69201 Learning rate: 0.02 Mask loss: 0.15224 RPN box loss: 0.01574 RPN score loss: 0.00447 RPN total loss: 0.02021 Total loss: 1.08829 timestamp: 1654942834.2095685 iteration: 36270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10292 FastRCNN class loss: 0.05068 FastRCNN total loss: 0.15361 L1 loss: 0.0000e+00 L2 loss: 0.6919 Learning rate: 0.02 Mask loss: 0.13008 RPN box loss: 0.04404 RPN score loss: 0.00645 RPN total loss: 0.05049 Total loss: 1.02607 timestamp: 1654942837.4241474 iteration: 36275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11321 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.1829 L1 loss: 0.0000e+00 L2 loss: 0.69182 Learning rate: 0.02 Mask loss: 0.11359 RPN box loss: 0.01815 RPN score loss: 0.00301 RPN total loss: 0.02116 Total loss: 1.00946 timestamp: 1654942840.6025348 iteration: 36280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09732 FastRCNN class loss: 0.0528 FastRCNN total loss: 0.15012 L1 loss: 0.0000e+00 L2 loss: 0.69171 Learning rate: 0.02 Mask loss: 0.14307 RPN box loss: 0.00567 RPN score loss: 0.00365 RPN total loss: 0.00932 Total loss: 0.99423 timestamp: 1654942843.9196634 iteration: 36285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14388 FastRCNN class loss: 0.11184 FastRCNN total loss: 0.25572 L1 loss: 0.0000e+00 L2 loss: 0.69165 Learning rate: 0.02 Mask loss: 0.12892 RPN box loss: 0.02084 RPN score loss: 0.01398 RPN total loss: 0.03482 Total loss: 1.11111 timestamp: 1654942847.1304722 iteration: 36290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.1527 L1 loss: 0.0000e+00 L2 loss: 0.69155 Learning rate: 0.02 Mask loss: 0.20017 RPN box loss: 0.05263 RPN score loss: 0.00996 RPN total loss: 0.06258 Total loss: 1.10701 timestamp: 1654942850.3221838 iteration: 36295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16025 FastRCNN class loss: 0.07236 FastRCNN total loss: 0.23261 L1 loss: 0.0000e+00 L2 loss: 0.69146 Learning rate: 0.02 Mask loss: 0.13845 RPN box loss: 0.05282 RPN score loss: 0.00834 RPN total loss: 0.06116 Total loss: 1.12368 timestamp: 1654942853.5116098 iteration: 36300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10215 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.17138 L1 loss: 0.0000e+00 L2 loss: 0.69138 Learning rate: 0.02 Mask loss: 0.14821 RPN box loss: 0.02822 RPN score loss: 0.00306 RPN total loss: 0.03128 Total loss: 1.04224 timestamp: 1654942856.763473 iteration: 36305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12198 FastRCNN class loss: 0.11295 FastRCNN total loss: 0.23493 L1 loss: 0.0000e+00 L2 loss: 0.69129 Learning rate: 0.02 Mask loss: 0.18556 RPN box loss: 0.04843 RPN score loss: 0.0102 RPN total loss: 0.05863 Total loss: 1.17041 timestamp: 1654942859.968224 iteration: 36310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12262 FastRCNN class loss: 0.0952 FastRCNN total loss: 0.21782 L1 loss: 0.0000e+00 L2 loss: 0.69119 Learning rate: 0.02 Mask loss: 0.23107 RPN box loss: 0.03533 RPN score loss: 0.00599 RPN total loss: 0.04132 Total loss: 1.1814 timestamp: 1654942863.18733 iteration: 36315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08993 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.1514 L1 loss: 0.0000e+00 L2 loss: 0.69114 Learning rate: 0.02 Mask loss: 0.18413 RPN box loss: 0.01984 RPN score loss: 0.0098 RPN total loss: 0.02964 Total loss: 1.05631 timestamp: 1654942866.5591776 iteration: 36320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15169 FastRCNN class loss: 0.14815 FastRCNN total loss: 0.29984 L1 loss: 0.0000e+00 L2 loss: 0.69105 Learning rate: 0.02 Mask loss: 0.14727 RPN box loss: 0.05953 RPN score loss: 0.00516 RPN total loss: 0.06468 Total loss: 1.20284 timestamp: 1654942869.7471557 iteration: 36325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12715 FastRCNN class loss: 0.06127 FastRCNN total loss: 0.18843 L1 loss: 0.0000e+00 L2 loss: 0.69094 Learning rate: 0.02 Mask loss: 0.14306 RPN box loss: 0.01086 RPN score loss: 0.00596 RPN total loss: 0.01682 Total loss: 1.03925 timestamp: 1654942872.958096 iteration: 36330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19172 FastRCNN class loss: 0.08276 FastRCNN total loss: 0.27448 L1 loss: 0.0000e+00 L2 loss: 0.69085 Learning rate: 0.02 Mask loss: 0.16193 RPN box loss: 0.03382 RPN score loss: 0.00465 RPN total loss: 0.03847 Total loss: 1.16573 timestamp: 1654942876.0987735 iteration: 36335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12276 FastRCNN class loss: 0.07576 FastRCNN total loss: 0.19852 L1 loss: 0.0000e+00 L2 loss: 0.69076 Learning rate: 0.02 Mask loss: 0.15241 RPN box loss: 0.05804 RPN score loss: 0.00913 RPN total loss: 0.06717 Total loss: 1.10886 timestamp: 1654942879.4023032 iteration: 36340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06847 FastRCNN class loss: 0.0445 FastRCNN total loss: 0.11296 L1 loss: 0.0000e+00 L2 loss: 0.69065 Learning rate: 0.02 Mask loss: 0.11342 RPN box loss: 0.00877 RPN score loss: 0.00703 RPN total loss: 0.0158 Total loss: 0.93284 timestamp: 1654942882.5527737 iteration: 36345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16354 FastRCNN class loss: 0.1204 FastRCNN total loss: 0.28394 L1 loss: 0.0000e+00 L2 loss: 0.69059 Learning rate: 0.02 Mask loss: 0.18291 RPN box loss: 0.03554 RPN score loss: 0.0043 RPN total loss: 0.03984 Total loss: 1.19728 timestamp: 1654942885.8164973 iteration: 36350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10542 FastRCNN class loss: 0.08137 FastRCNN total loss: 0.18679 L1 loss: 0.0000e+00 L2 loss: 0.69046 Learning rate: 0.02 Mask loss: 0.12275 RPN box loss: 0.0801 RPN score loss: 0.00991 RPN total loss: 0.09 Total loss: 1.09001 timestamp: 1654942888.9603229 iteration: 36355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18323 FastRCNN class loss: 0.13572 FastRCNN total loss: 0.31895 L1 loss: 0.0000e+00 L2 loss: 0.69032 Learning rate: 0.02 Mask loss: 0.16661 RPN box loss: 0.04049 RPN score loss: 0.01755 RPN total loss: 0.05804 Total loss: 1.23392 timestamp: 1654942892.2466955 iteration: 36360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19421 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.26557 L1 loss: 0.0000e+00 L2 loss: 0.69025 Learning rate: 0.02 Mask loss: 0.12952 RPN box loss: 0.025 RPN score loss: 0.00475 RPN total loss: 0.02975 Total loss: 1.11509 timestamp: 1654942895.4065492 iteration: 36365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13992 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.19661 L1 loss: 0.0000e+00 L2 loss: 0.69021 Learning rate: 0.02 Mask loss: 0.13964 RPN box loss: 0.06522 RPN score loss: 0.0086 RPN total loss: 0.07382 Total loss: 1.10028 timestamp: 1654942898.6555924 iteration: 36370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15925 FastRCNN class loss: 0.09503 FastRCNN total loss: 0.25428 L1 loss: 0.0000e+00 L2 loss: 0.69011 Learning rate: 0.02 Mask loss: 0.18142 RPN box loss: 0.0143 RPN score loss: 0.00218 RPN total loss: 0.01647 Total loss: 1.14228 timestamp: 1654942901.8285391 iteration: 36375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11268 FastRCNN class loss: 0.05493 FastRCNN total loss: 0.16761 L1 loss: 0.0000e+00 L2 loss: 0.69002 Learning rate: 0.02 Mask loss: 0.11521 RPN box loss: 0.00956 RPN score loss: 0.01001 RPN total loss: 0.01957 Total loss: 0.99241 timestamp: 1654942905.057355 iteration: 36380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11978 FastRCNN class loss: 0.05952 FastRCNN total loss: 0.17931 L1 loss: 0.0000e+00 L2 loss: 0.68995 Learning rate: 0.02 Mask loss: 0.10923 RPN box loss: 0.04162 RPN score loss: 0.00695 RPN total loss: 0.04857 Total loss: 1.02705 timestamp: 1654942908.3611789 iteration: 36385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09351 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.15524 L1 loss: 0.0000e+00 L2 loss: 0.68989 Learning rate: 0.02 Mask loss: 0.19195 RPN box loss: 0.00901 RPN score loss: 0.00775 RPN total loss: 0.01675 Total loss: 1.05383 timestamp: 1654942911.5238843 iteration: 36390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09832 FastRCNN class loss: 0.06207 FastRCNN total loss: 0.16039 L1 loss: 0.0000e+00 L2 loss: 0.68979 Learning rate: 0.02 Mask loss: 0.18323 RPN box loss: 0.01523 RPN score loss: 0.00369 RPN total loss: 0.01892 Total loss: 1.05232 timestamp: 1654942914.6597862 iteration: 36395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09381 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.17253 L1 loss: 0.0000e+00 L2 loss: 0.68971 Learning rate: 0.02 Mask loss: 0.15084 RPN box loss: 0.01891 RPN score loss: 0.01902 RPN total loss: 0.03792 Total loss: 1.05099 timestamp: 1654942917.8765726 iteration: 36400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1238 FastRCNN class loss: 0.06684 FastRCNN total loss: 0.19064 L1 loss: 0.0000e+00 L2 loss: 0.68961 Learning rate: 0.02 Mask loss: 0.12259 RPN box loss: 0.02544 RPN score loss: 0.00508 RPN total loss: 0.03052 Total loss: 1.03335 timestamp: 1654942921.1132705 iteration: 36405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10649 FastRCNN class loss: 0.11397 FastRCNN total loss: 0.22046 L1 loss: 0.0000e+00 L2 loss: 0.68951 Learning rate: 0.02 Mask loss: 0.1875 RPN box loss: 0.02455 RPN score loss: 0.01024 RPN total loss: 0.03479 Total loss: 1.13226 timestamp: 1654942924.352502 iteration: 36410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10782 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.17589 L1 loss: 0.0000e+00 L2 loss: 0.68945 Learning rate: 0.02 Mask loss: 0.14297 RPN box loss: 0.0372 RPN score loss: 0.00977 RPN total loss: 0.04697 Total loss: 1.05529 timestamp: 1654942927.4982727 iteration: 36415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14178 FastRCNN class loss: 0.09522 FastRCNN total loss: 0.237 L1 loss: 0.0000e+00 L2 loss: 0.68935 Learning rate: 0.02 Mask loss: 0.18999 RPN box loss: 0.03246 RPN score loss: 0.00456 RPN total loss: 0.03702 Total loss: 1.15337 timestamp: 1654942930.6505854 iteration: 36420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09162 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.15924 L1 loss: 0.0000e+00 L2 loss: 0.68926 Learning rate: 0.02 Mask loss: 0.11026 RPN box loss: 0.0225 RPN score loss: 0.00363 RPN total loss: 0.02613 Total loss: 0.98489 timestamp: 1654942933.8918598 iteration: 36425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18873 FastRCNN class loss: 0.11557 FastRCNN total loss: 0.3043 L1 loss: 0.0000e+00 L2 loss: 0.68915 Learning rate: 0.02 Mask loss: 0.22015 RPN box loss: 0.01267 RPN score loss: 0.00562 RPN total loss: 0.0183 Total loss: 1.2319 timestamp: 1654942937.1095376 iteration: 36430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12074 FastRCNN class loss: 0.06397 FastRCNN total loss: 0.18471 L1 loss: 0.0000e+00 L2 loss: 0.68906 Learning rate: 0.02 Mask loss: 0.11157 RPN box loss: 0.01771 RPN score loss: 0.00261 RPN total loss: 0.02032 Total loss: 1.00567 timestamp: 1654942940.3856435 iteration: 36435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1211 FastRCNN class loss: 0.08585 FastRCNN total loss: 0.20695 L1 loss: 0.0000e+00 L2 loss: 0.68897 Learning rate: 0.02 Mask loss: 0.17427 RPN box loss: 0.02537 RPN score loss: 0.00994 RPN total loss: 0.03531 Total loss: 1.1055 timestamp: 1654942943.5652447 iteration: 36440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09914 FastRCNN class loss: 0.1057 FastRCNN total loss: 0.20484 L1 loss: 0.0000e+00 L2 loss: 0.68888 Learning rate: 0.02 Mask loss: 0.14357 RPN box loss: 0.02017 RPN score loss: 0.00881 RPN total loss: 0.02898 Total loss: 1.06626 timestamp: 1654942946.7290187 iteration: 36445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17926 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.26152 L1 loss: 0.0000e+00 L2 loss: 0.68877 Learning rate: 0.02 Mask loss: 0.15187 RPN box loss: 0.02428 RPN score loss: 0.00239 RPN total loss: 0.02667 Total loss: 1.12882 timestamp: 1654942949.9518986 iteration: 36450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13775 FastRCNN class loss: 0.10742 FastRCNN total loss: 0.24518 L1 loss: 0.0000e+00 L2 loss: 0.68869 Learning rate: 0.02 Mask loss: 0.17195 RPN box loss: 0.02446 RPN score loss: 0.01129 RPN total loss: 0.03575 Total loss: 1.14156 timestamp: 1654942953.2044675 iteration: 36455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12457 FastRCNN class loss: 0.08382 FastRCNN total loss: 0.20839 L1 loss: 0.0000e+00 L2 loss: 0.6886 Learning rate: 0.02 Mask loss: 0.17918 RPN box loss: 0.028 RPN score loss: 0.00621 RPN total loss: 0.03422 Total loss: 1.11039 timestamp: 1654942956.4301279 iteration: 36460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15413 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.22202 L1 loss: 0.0000e+00 L2 loss: 0.68851 Learning rate: 0.02 Mask loss: 0.12715 RPN box loss: 0.03237 RPN score loss: 0.01436 RPN total loss: 0.04674 Total loss: 1.08441 timestamp: 1654942959.555924 iteration: 36465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18677 FastRCNN class loss: 0.09004 FastRCNN total loss: 0.27681 L1 loss: 0.0000e+00 L2 loss: 0.6884 Learning rate: 0.02 Mask loss: 0.1944 RPN box loss: 0.01841 RPN score loss: 0.00354 RPN total loss: 0.02196 Total loss: 1.18157 timestamp: 1654942962.753992 iteration: 36470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13408 FastRCNN class loss: 0.07258 FastRCNN total loss: 0.20667 L1 loss: 0.0000e+00 L2 loss: 0.68829 Learning rate: 0.02 Mask loss: 0.19222 RPN box loss: 0.01428 RPN score loss: 0.0049 RPN total loss: 0.01918 Total loss: 1.10636 timestamp: 1654942965.89782 iteration: 36475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09801 FastRCNN class loss: 0.06578 FastRCNN total loss: 0.16378 L1 loss: 0.0000e+00 L2 loss: 0.6882 Learning rate: 0.02 Mask loss: 0.1147 RPN box loss: 0.0437 RPN score loss: 0.00375 RPN total loss: 0.04745 Total loss: 1.01414 timestamp: 1654942969.1079426 iteration: 36480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12205 FastRCNN class loss: 0.0695 FastRCNN total loss: 0.19155 L1 loss: 0.0000e+00 L2 loss: 0.68813 Learning rate: 0.02 Mask loss: 0.12134 RPN box loss: 0.00985 RPN score loss: 0.00204 RPN total loss: 0.01189 Total loss: 1.0129 timestamp: 1654942972.2706068 iteration: 36485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10142 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.16866 L1 loss: 0.0000e+00 L2 loss: 0.68804 Learning rate: 0.02 Mask loss: 0.15409 RPN box loss: 0.03436 RPN score loss: 0.00318 RPN total loss: 0.03754 Total loss: 1.04833 timestamp: 1654942975.426082 iteration: 36490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16563 FastRCNN class loss: 0.10451 FastRCNN total loss: 0.27014 L1 loss: 0.0000e+00 L2 loss: 0.68795 Learning rate: 0.02 Mask loss: 0.16406 RPN box loss: 0.04407 RPN score loss: 0.01917 RPN total loss: 0.06325 Total loss: 1.1854 timestamp: 1654942978.6265292 iteration: 36495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19399 FastRCNN class loss: 0.07599 FastRCNN total loss: 0.26997 L1 loss: 0.0000e+00 L2 loss: 0.68787 Learning rate: 0.02 Mask loss: 0.14107 RPN box loss: 0.02277 RPN score loss: 0.00603 RPN total loss: 0.0288 Total loss: 1.12771 timestamp: 1654942981.8397753 iteration: 36500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11013 FastRCNN class loss: 0.04414 FastRCNN total loss: 0.15427 L1 loss: 0.0000e+00 L2 loss: 0.68779 Learning rate: 0.02 Mask loss: 0.13819 RPN box loss: 0.02371 RPN score loss: 0.00606 RPN total loss: 0.02976 Total loss: 1.01001 timestamp: 1654942985.1023712 iteration: 36505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.05178 FastRCNN total loss: 0.15874 L1 loss: 0.0000e+00 L2 loss: 0.6877 Learning rate: 0.02 Mask loss: 0.16473 RPN box loss: 0.05596 RPN score loss: 0.00724 RPN total loss: 0.0632 Total loss: 1.07438 timestamp: 1654942988.443042 iteration: 36510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14661 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.22762 L1 loss: 0.0000e+00 L2 loss: 0.6876 Learning rate: 0.02 Mask loss: 0.11624 RPN box loss: 0.03474 RPN score loss: 0.00804 RPN total loss: 0.04278 Total loss: 1.07424 timestamp: 1654942991.6426072 iteration: 36515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17987 FastRCNN class loss: 0.09999 FastRCNN total loss: 0.27987 L1 loss: 0.0000e+00 L2 loss: 0.68753 Learning rate: 0.02 Mask loss: 0.14705 RPN box loss: 0.01155 RPN score loss: 0.00139 RPN total loss: 0.01294 Total loss: 1.12739 timestamp: 1654942994.877276 iteration: 36520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13209 FastRCNN class loss: 0.08376 FastRCNN total loss: 0.21585 L1 loss: 0.0000e+00 L2 loss: 0.68745 Learning rate: 0.02 Mask loss: 0.13746 RPN box loss: 0.00875 RPN score loss: 0.00259 RPN total loss: 0.01134 Total loss: 1.05209 timestamp: 1654942998.0712888 iteration: 36525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13831 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.21047 L1 loss: 0.0000e+00 L2 loss: 0.68733 Learning rate: 0.02 Mask loss: 0.15593 RPN box loss: 0.02304 RPN score loss: 0.00584 RPN total loss: 0.02888 Total loss: 1.08262 timestamp: 1654943001.2680526 iteration: 36530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14878 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.24217 L1 loss: 0.0000e+00 L2 loss: 0.68726 Learning rate: 0.02 Mask loss: 0.15368 RPN box loss: 0.02221 RPN score loss: 0.01197 RPN total loss: 0.03417 Total loss: 1.11728 timestamp: 1654943004.3993382 iteration: 36535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14884 FastRCNN class loss: 0.0991 FastRCNN total loss: 0.24794 L1 loss: 0.0000e+00 L2 loss: 0.68718 Learning rate: 0.02 Mask loss: 0.21787 RPN box loss: 0.02989 RPN score loss: 0.00808 RPN total loss: 0.03797 Total loss: 1.19095 timestamp: 1654943007.5966065 iteration: 36540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24416 FastRCNN class loss: 0.08985 FastRCNN total loss: 0.33401 L1 loss: 0.0000e+00 L2 loss: 0.68709 Learning rate: 0.02 Mask loss: 0.19392 RPN box loss: 0.04743 RPN score loss: 0.01111 RPN total loss: 0.05854 Total loss: 1.27356 timestamp: 1654943010.7742968 iteration: 36545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16479 FastRCNN class loss: 0.14877 FastRCNN total loss: 0.31356 L1 loss: 0.0000e+00 L2 loss: 0.68698 Learning rate: 0.02 Mask loss: 0.20392 RPN box loss: 0.07208 RPN score loss: 0.05034 RPN total loss: 0.12242 Total loss: 1.32688 timestamp: 1654943014.0022986 iteration: 36550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07742 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.12585 L1 loss: 0.0000e+00 L2 loss: 0.68688 Learning rate: 0.02 Mask loss: 0.12571 RPN box loss: 0.04129 RPN score loss: 0.00626 RPN total loss: 0.04754 Total loss: 0.98599 timestamp: 1654943017.228499 iteration: 36555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0801 FastRCNN class loss: 0.04337 FastRCNN total loss: 0.12347 L1 loss: 0.0000e+00 L2 loss: 0.68678 Learning rate: 0.02 Mask loss: 0.12076 RPN box loss: 0.01069 RPN score loss: 0.00422 RPN total loss: 0.01491 Total loss: 0.94592 timestamp: 1654943020.4616537 iteration: 36560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09242 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.16489 L1 loss: 0.0000e+00 L2 loss: 0.68675 Learning rate: 0.02 Mask loss: 0.16115 RPN box loss: 0.03387 RPN score loss: 0.00219 RPN total loss: 0.03606 Total loss: 1.04884 timestamp: 1654943023.6316848 iteration: 36565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07008 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.12223 L1 loss: 0.0000e+00 L2 loss: 0.68666 Learning rate: 0.02 Mask loss: 0.13474 RPN box loss: 0.04875 RPN score loss: 0.00712 RPN total loss: 0.05587 Total loss: 0.99951 timestamp: 1654943026.7877898 iteration: 36570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09087 FastRCNN class loss: 0.05785 FastRCNN total loss: 0.14872 L1 loss: 0.0000e+00 L2 loss: 0.68657 Learning rate: 0.02 Mask loss: 0.11187 RPN box loss: 0.00922 RPN score loss: 0.00537 RPN total loss: 0.01459 Total loss: 0.96175 timestamp: 1654943029.965863 iteration: 36575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06973 FastRCNN class loss: 0.0439 FastRCNN total loss: 0.11363 L1 loss: 0.0000e+00 L2 loss: 0.68648 Learning rate: 0.02 Mask loss: 0.1149 RPN box loss: 0.01825 RPN score loss: 0.00617 RPN total loss: 0.02442 Total loss: 0.93943 timestamp: 1654943033.1125262 iteration: 36580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05732 FastRCNN class loss: 0.0359 FastRCNN total loss: 0.09322 L1 loss: 0.0000e+00 L2 loss: 0.68638 Learning rate: 0.02 Mask loss: 0.11182 RPN box loss: 0.00459 RPN score loss: 0.00137 RPN total loss: 0.00596 Total loss: 0.89739 timestamp: 1654943036.2746572 iteration: 36585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.2221 L1 loss: 0.0000e+00 L2 loss: 0.68631 Learning rate: 0.02 Mask loss: 0.13275 RPN box loss: 0.02979 RPN score loss: 0.01322 RPN total loss: 0.04301 Total loss: 1.08417 timestamp: 1654943039.4283235 iteration: 36590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09946 FastRCNN class loss: 0.06029 FastRCNN total loss: 0.15975 L1 loss: 0.0000e+00 L2 loss: 0.68622 Learning rate: 0.02 Mask loss: 0.16845 RPN box loss: 0.0157 RPN score loss: 0.00237 RPN total loss: 0.01807 Total loss: 1.03249 timestamp: 1654943042.6085858 iteration: 36595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14804 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.21525 L1 loss: 0.0000e+00 L2 loss: 0.68614 Learning rate: 0.02 Mask loss: 0.14771 RPN box loss: 0.02302 RPN score loss: 0.00598 RPN total loss: 0.029 Total loss: 1.0781 timestamp: 1654943045.7979732 iteration: 36600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13542 FastRCNN class loss: 0.11172 FastRCNN total loss: 0.24713 L1 loss: 0.0000e+00 L2 loss: 0.68606 Learning rate: 0.02 Mask loss: 0.13803 RPN box loss: 0.048 RPN score loss: 0.01489 RPN total loss: 0.06289 Total loss: 1.13412 timestamp: 1654943049.0156872 iteration: 36605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09888 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.16782 L1 loss: 0.0000e+00 L2 loss: 0.68596 Learning rate: 0.02 Mask loss: 0.12505 RPN box loss: 0.02289 RPN score loss: 0.00358 RPN total loss: 0.02648 Total loss: 1.00531 timestamp: 1654943052.2200222 iteration: 36610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1855 FastRCNN class loss: 0.09991 FastRCNN total loss: 0.28541 L1 loss: 0.0000e+00 L2 loss: 0.68588 Learning rate: 0.02 Mask loss: 0.13315 RPN box loss: 0.04881 RPN score loss: 0.00798 RPN total loss: 0.05679 Total loss: 1.16123 timestamp: 1654943055.4742885 iteration: 36615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11227 FastRCNN class loss: 0.13163 FastRCNN total loss: 0.24391 L1 loss: 0.0000e+00 L2 loss: 0.68576 Learning rate: 0.02 Mask loss: 0.1734 RPN box loss: 0.03587 RPN score loss: 0.01263 RPN total loss: 0.04851 Total loss: 1.15158 timestamp: 1654943058.6553867 iteration: 36620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15099 FastRCNN class loss: 0.0761 FastRCNN total loss: 0.22709 L1 loss: 0.0000e+00 L2 loss: 0.68566 Learning rate: 0.02 Mask loss: 0.12852 RPN box loss: 0.06514 RPN score loss: 0.00491 RPN total loss: 0.07005 Total loss: 1.11132 timestamp: 1654943061.8441055 iteration: 36625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16189 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.24909 L1 loss: 0.0000e+00 L2 loss: 0.68558 Learning rate: 0.02 Mask loss: 0.21337 RPN box loss: 0.07449 RPN score loss: 0.00756 RPN total loss: 0.08205 Total loss: 1.23009 timestamp: 1654943064.9897628 iteration: 36630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0999 FastRCNN class loss: 0.05663 FastRCNN total loss: 0.15653 L1 loss: 0.0000e+00 L2 loss: 0.68547 Learning rate: 0.02 Mask loss: 0.19365 RPN box loss: 0.0181 RPN score loss: 0.00421 RPN total loss: 0.02232 Total loss: 1.05797 timestamp: 1654943068.178979 iteration: 36635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06048 FastRCNN class loss: 0.04262 FastRCNN total loss: 0.1031 L1 loss: 0.0000e+00 L2 loss: 0.68539 Learning rate: 0.02 Mask loss: 0.07752 RPN box loss: 0.02614 RPN score loss: 0.00688 RPN total loss: 0.03302 Total loss: 0.89903 timestamp: 1654943071.3745432 iteration: 36640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1442 FastRCNN class loss: 0.09785 FastRCNN total loss: 0.24205 L1 loss: 0.0000e+00 L2 loss: 0.68532 Learning rate: 0.02 Mask loss: 0.19194 RPN box loss: 0.03826 RPN score loss: 0.00861 RPN total loss: 0.04687 Total loss: 1.16618 timestamp: 1654943074.6158767 iteration: 36645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16223 FastRCNN class loss: 0.11343 FastRCNN total loss: 0.27565 L1 loss: 0.0000e+00 L2 loss: 0.68521 Learning rate: 0.02 Mask loss: 0.17454 RPN box loss: 0.03183 RPN score loss: 0.00822 RPN total loss: 0.04005 Total loss: 1.17546 timestamp: 1654943077.7939126 iteration: 36650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18787 FastRCNN class loss: 0.06637 FastRCNN total loss: 0.25424 L1 loss: 0.0000e+00 L2 loss: 0.68512 Learning rate: 0.02 Mask loss: 0.11199 RPN box loss: 0.04925 RPN score loss: 0.01343 RPN total loss: 0.06268 Total loss: 1.11403 timestamp: 1654943080.9561772 iteration: 36655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15385 FastRCNN class loss: 0.08653 FastRCNN total loss: 0.24038 L1 loss: 0.0000e+00 L2 loss: 0.68502 Learning rate: 0.02 Mask loss: 0.13667 RPN box loss: 0.02844 RPN score loss: 0.00609 RPN total loss: 0.03453 Total loss: 1.09659 timestamp: 1654943084.135298 iteration: 36660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13319 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.17992 L1 loss: 0.0000e+00 L2 loss: 0.68493 Learning rate: 0.02 Mask loss: 0.12981 RPN box loss: 0.02774 RPN score loss: 0.00196 RPN total loss: 0.0297 Total loss: 1.02435 timestamp: 1654943087.2812207 iteration: 36665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13804 FastRCNN class loss: 0.09009 FastRCNN total loss: 0.22813 L1 loss: 0.0000e+00 L2 loss: 0.68482 Learning rate: 0.02 Mask loss: 0.16457 RPN box loss: 0.00838 RPN score loss: 0.00233 RPN total loss: 0.01072 Total loss: 1.08824 timestamp: 1654943090.4400113 iteration: 36670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16937 FastRCNN class loss: 0.10375 FastRCNN total loss: 0.27312 L1 loss: 0.0000e+00 L2 loss: 0.68476 Learning rate: 0.02 Mask loss: 0.18953 RPN box loss: 0.00821 RPN score loss: 0.00254 RPN total loss: 0.01075 Total loss: 1.15816 timestamp: 1654943093.708441 iteration: 36675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20342 FastRCNN class loss: 0.12416 FastRCNN total loss: 0.32758 L1 loss: 0.0000e+00 L2 loss: 0.68467 Learning rate: 0.02 Mask loss: 0.18823 RPN box loss: 0.01818 RPN score loss: 0.00437 RPN total loss: 0.02254 Total loss: 1.22302 timestamp: 1654943096.8452158 iteration: 36680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15012 FastRCNN class loss: 0.06053 FastRCNN total loss: 0.21065 L1 loss: 0.0000e+00 L2 loss: 0.68457 Learning rate: 0.02 Mask loss: 0.14589 RPN box loss: 0.0349 RPN score loss: 0.00823 RPN total loss: 0.04313 Total loss: 1.08424 timestamp: 1654943100.10756 iteration: 36685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11438 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.19401 L1 loss: 0.0000e+00 L2 loss: 0.6845 Learning rate: 0.02 Mask loss: 0.18432 RPN box loss: 0.03175 RPN score loss: 0.00538 RPN total loss: 0.03712 Total loss: 1.09996 timestamp: 1654943103.2589157 iteration: 36690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22487 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.29845 L1 loss: 0.0000e+00 L2 loss: 0.68443 Learning rate: 0.02 Mask loss: 0.11284 RPN box loss: 0.02005 RPN score loss: 0.00917 RPN total loss: 0.02921 Total loss: 1.12493 timestamp: 1654943106.4966667 iteration: 36695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16551 FastRCNN class loss: 0.09556 FastRCNN total loss: 0.26107 L1 loss: 0.0000e+00 L2 loss: 0.68433 Learning rate: 0.02 Mask loss: 0.21474 RPN box loss: 0.01974 RPN score loss: 0.00444 RPN total loss: 0.02418 Total loss: 1.18432 timestamp: 1654943109.7124944 iteration: 36700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10277 FastRCNN class loss: 0.06952 FastRCNN total loss: 0.17229 L1 loss: 0.0000e+00 L2 loss: 0.68424 Learning rate: 0.02 Mask loss: 0.16122 RPN box loss: 0.02866 RPN score loss: 0.00338 RPN total loss: 0.03204 Total loss: 1.04978 timestamp: 1654943112.88914 iteration: 36705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11253 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.18242 L1 loss: 0.0000e+00 L2 loss: 0.68415 Learning rate: 0.02 Mask loss: 0.10608 RPN box loss: 0.03142 RPN score loss: 0.00269 RPN total loss: 0.03411 Total loss: 1.00676 timestamp: 1654943116.0521789 iteration: 36710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08146 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.16337 L1 loss: 0.0000e+00 L2 loss: 0.68406 Learning rate: 0.02 Mask loss: 0.17498 RPN box loss: 0.10125 RPN score loss: 0.00627 RPN total loss: 0.10752 Total loss: 1.12993 timestamp: 1654943119.1903737 iteration: 36715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07692 FastRCNN class loss: 0.07472 FastRCNN total loss: 0.15164 L1 loss: 0.0000e+00 L2 loss: 0.684 Learning rate: 0.02 Mask loss: 0.14289 RPN box loss: 0.08009 RPN score loss: 0.0061 RPN total loss: 0.08619 Total loss: 1.06472 timestamp: 1654943122.3481627 iteration: 36720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10603 FastRCNN class loss: 0.10042 FastRCNN total loss: 0.20646 L1 loss: 0.0000e+00 L2 loss: 0.6839 Learning rate: 0.02 Mask loss: 0.13702 RPN box loss: 0.05605 RPN score loss: 0.0073 RPN total loss: 0.06335 Total loss: 1.09073 timestamp: 1654943125.5569 iteration: 36725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09849 FastRCNN class loss: 0.09233 FastRCNN total loss: 0.19083 L1 loss: 0.0000e+00 L2 loss: 0.68378 Learning rate: 0.02 Mask loss: 0.15924 RPN box loss: 0.01968 RPN score loss: 0.00462 RPN total loss: 0.02429 Total loss: 1.05814 timestamp: 1654943128.7324388 iteration: 36730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20396 FastRCNN class loss: 0.12721 FastRCNN total loss: 0.33117 L1 loss: 0.0000e+00 L2 loss: 0.6837 Learning rate: 0.02 Mask loss: 0.23522 RPN box loss: 0.03137 RPN score loss: 0.01195 RPN total loss: 0.04331 Total loss: 1.29341 timestamp: 1654943132.0408752 iteration: 36735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1149 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.19621 L1 loss: 0.0000e+00 L2 loss: 0.68363 Learning rate: 0.02 Mask loss: 0.07767 RPN box loss: 0.03199 RPN score loss: 0.00624 RPN total loss: 0.03824 Total loss: 0.99575 timestamp: 1654943135.21592 iteration: 36740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11378 FastRCNN class loss: 0.09498 FastRCNN total loss: 0.20876 L1 loss: 0.0000e+00 L2 loss: 0.68355 Learning rate: 0.02 Mask loss: 0.19183 RPN box loss: 0.02397 RPN score loss: 0.00655 RPN total loss: 0.03052 Total loss: 1.11466 timestamp: 1654943138.4533234 iteration: 36745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12159 FastRCNN class loss: 0.04599 FastRCNN total loss: 0.16758 L1 loss: 0.0000e+00 L2 loss: 0.68346 Learning rate: 0.02 Mask loss: 0.09141 RPN box loss: 0.03514 RPN score loss: 0.00144 RPN total loss: 0.03658 Total loss: 0.97903 timestamp: 1654943141.6208963 iteration: 36750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17495 FastRCNN class loss: 0.14363 FastRCNN total loss: 0.31859 L1 loss: 0.0000e+00 L2 loss: 0.68337 Learning rate: 0.02 Mask loss: 0.15266 RPN box loss: 0.01372 RPN score loss: 0.00435 RPN total loss: 0.01807 Total loss: 1.17269 timestamp: 1654943144.8065917 iteration: 36755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13546 FastRCNN class loss: 0.08391 FastRCNN total loss: 0.21937 L1 loss: 0.0000e+00 L2 loss: 0.68332 Learning rate: 0.02 Mask loss: 0.13053 RPN box loss: 0.03299 RPN score loss: 0.01042 RPN total loss: 0.04341 Total loss: 1.07663 timestamp: 1654943147.9826522 iteration: 36760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10862 FastRCNN class loss: 0.04595 FastRCNN total loss: 0.15458 L1 loss: 0.0000e+00 L2 loss: 0.68323 Learning rate: 0.02 Mask loss: 0.10629 RPN box loss: 0.04224 RPN score loss: 0.001 RPN total loss: 0.04324 Total loss: 0.98735 timestamp: 1654943151.1885684 iteration: 36765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10724 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.17862 L1 loss: 0.0000e+00 L2 loss: 0.68315 Learning rate: 0.02 Mask loss: 0.12669 RPN box loss: 0.03393 RPN score loss: 0.0093 RPN total loss: 0.04323 Total loss: 1.03168 timestamp: 1654943154.4729102 iteration: 36770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11239 FastRCNN class loss: 0.06463 FastRCNN total loss: 0.17703 L1 loss: 0.0000e+00 L2 loss: 0.68307 Learning rate: 0.02 Mask loss: 0.12816 RPN box loss: 0.05749 RPN score loss: 0.0113 RPN total loss: 0.06879 Total loss: 1.05705 timestamp: 1654943157.672843 iteration: 36775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09125 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.17736 L1 loss: 0.0000e+00 L2 loss: 0.68299 Learning rate: 0.02 Mask loss: 0.15152 RPN box loss: 0.02593 RPN score loss: 0.00461 RPN total loss: 0.03053 Total loss: 1.0424 timestamp: 1654943160.9145696 iteration: 36780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06889 FastRCNN class loss: 0.04367 FastRCNN total loss: 0.11257 L1 loss: 0.0000e+00 L2 loss: 0.6829 Learning rate: 0.02 Mask loss: 0.27687 RPN box loss: 0.023 RPN score loss: 0.0041 RPN total loss: 0.0271 Total loss: 1.09944 timestamp: 1654943164.1714833 iteration: 36785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09317 FastRCNN class loss: 0.10458 FastRCNN total loss: 0.19774 L1 loss: 0.0000e+00 L2 loss: 0.68283 Learning rate: 0.02 Mask loss: 0.07688 RPN box loss: 0.01058 RPN score loss: 0.00381 RPN total loss: 0.01439 Total loss: 0.97184 timestamp: 1654943167.307952 iteration: 36790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13705 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.20561 L1 loss: 0.0000e+00 L2 loss: 0.68277 Learning rate: 0.02 Mask loss: 0.13192 RPN box loss: 0.01786 RPN score loss: 0.00504 RPN total loss: 0.02289 Total loss: 1.04318 timestamp: 1654943170.559456 iteration: 36795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13424 FastRCNN class loss: 0.09832 FastRCNN total loss: 0.23256 L1 loss: 0.0000e+00 L2 loss: 0.68268 Learning rate: 0.02 Mask loss: 0.13158 RPN box loss: 0.03996 RPN score loss: 0.00741 RPN total loss: 0.04737 Total loss: 1.09419 timestamp: 1654943173.7739031 iteration: 36800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10684 FastRCNN class loss: 0.05177 FastRCNN total loss: 0.15861 L1 loss: 0.0000e+00 L2 loss: 0.68257 Learning rate: 0.02 Mask loss: 0.15621 RPN box loss: 0.02416 RPN score loss: 0.00708 RPN total loss: 0.03125 Total loss: 1.02864 timestamp: 1654943176.95304 iteration: 36805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11449 FastRCNN class loss: 0.05541 FastRCNN total loss: 0.16991 L1 loss: 0.0000e+00 L2 loss: 0.68244 Learning rate: 0.02 Mask loss: 0.1519 RPN box loss: 0.01813 RPN score loss: 0.0038 RPN total loss: 0.02193 Total loss: 1.02618 timestamp: 1654943180.1402123 iteration: 36810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05741 FastRCNN class loss: 0.04563 FastRCNN total loss: 0.10304 L1 loss: 0.0000e+00 L2 loss: 0.68236 Learning rate: 0.02 Mask loss: 0.11557 RPN box loss: 0.03436 RPN score loss: 0.0018 RPN total loss: 0.03616 Total loss: 0.93714 timestamp: 1654943183.374893 iteration: 36815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09649 FastRCNN class loss: 0.07835 FastRCNN total loss: 0.17484 L1 loss: 0.0000e+00 L2 loss: 0.68229 Learning rate: 0.02 Mask loss: 0.16748 RPN box loss: 0.02593 RPN score loss: 0.01173 RPN total loss: 0.03767 Total loss: 1.06228 timestamp: 1654943186.5705056 iteration: 36820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13265 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.19018 L1 loss: 0.0000e+00 L2 loss: 0.68221 Learning rate: 0.02 Mask loss: 0.10177 RPN box loss: 0.00562 RPN score loss: 0.00433 RPN total loss: 0.00995 Total loss: 0.98411 timestamp: 1654943189.8396654 iteration: 36825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18176 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.2556 L1 loss: 0.0000e+00 L2 loss: 0.68215 Learning rate: 0.02 Mask loss: 0.19913 RPN box loss: 0.03265 RPN score loss: 0.00418 RPN total loss: 0.03683 Total loss: 1.17371 timestamp: 1654943193.0129259 iteration: 36830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1373 FastRCNN class loss: 0.12221 FastRCNN total loss: 0.25952 L1 loss: 0.0000e+00 L2 loss: 0.68205 Learning rate: 0.02 Mask loss: 0.1272 RPN box loss: 0.02036 RPN score loss: 0.00614 RPN total loss: 0.0265 Total loss: 1.09527 timestamp: 1654943196.1769514 iteration: 36835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13999 FastRCNN class loss: 0.09861 FastRCNN total loss: 0.2386 L1 loss: 0.0000e+00 L2 loss: 0.68196 Learning rate: 0.02 Mask loss: 0.14143 RPN box loss: 0.04174 RPN score loss: 0.00834 RPN total loss: 0.05008 Total loss: 1.11207 timestamp: 1654943199.3964338 iteration: 36840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08714 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.15501 L1 loss: 0.0000e+00 L2 loss: 0.68187 Learning rate: 0.02 Mask loss: 0.18296 RPN box loss: 0.02969 RPN score loss: 0.00408 RPN total loss: 0.03377 Total loss: 1.05361 timestamp: 1654943202.6060843 iteration: 36845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11728 FastRCNN class loss: 0.0734 FastRCNN total loss: 0.19068 L1 loss: 0.0000e+00 L2 loss: 0.68175 Learning rate: 0.02 Mask loss: 0.10894 RPN box loss: 0.0092 RPN score loss: 0.00429 RPN total loss: 0.0135 Total loss: 0.99486 timestamp: 1654943205.7615936 iteration: 36850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.0599 FastRCNN total loss: 0.18387 L1 loss: 0.0000e+00 L2 loss: 0.68165 Learning rate: 0.02 Mask loss: 0.11107 RPN box loss: 0.00489 RPN score loss: 0.00878 RPN total loss: 0.01367 Total loss: 0.99027 timestamp: 1654943208.9196825 iteration: 36855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07678 FastRCNN class loss: 0.04287 FastRCNN total loss: 0.11965 L1 loss: 0.0000e+00 L2 loss: 0.68157 Learning rate: 0.02 Mask loss: 0.18125 RPN box loss: 0.05197 RPN score loss: 0.00386 RPN total loss: 0.05583 Total loss: 1.0383 timestamp: 1654943212.1243834 iteration: 36860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.15404 L1 loss: 0.0000e+00 L2 loss: 0.68145 Learning rate: 0.02 Mask loss: 0.12309 RPN box loss: 0.02036 RPN score loss: 0.00153 RPN total loss: 0.02189 Total loss: 0.98047 timestamp: 1654943215.3865879 iteration: 36865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1923 FastRCNN class loss: 0.08906 FastRCNN total loss: 0.28136 L1 loss: 0.0000e+00 L2 loss: 0.68137 Learning rate: 0.02 Mask loss: 0.18122 RPN box loss: 0.01803 RPN score loss: 0.00399 RPN total loss: 0.02202 Total loss: 1.16596 timestamp: 1654943218.5976384 iteration: 36870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14366 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.20515 L1 loss: 0.0000e+00 L2 loss: 0.6813 Learning rate: 0.02 Mask loss: 0.17135 RPN box loss: 0.00662 RPN score loss: 0.00614 RPN total loss: 0.01276 Total loss: 1.07055 timestamp: 1654943221.8138382 iteration: 36875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1064 FastRCNN class loss: 0.06006 FastRCNN total loss: 0.16646 L1 loss: 0.0000e+00 L2 loss: 0.68121 Learning rate: 0.02 Mask loss: 0.13641 RPN box loss: 0.01943 RPN score loss: 0.00295 RPN total loss: 0.02237 Total loss: 1.00646 timestamp: 1654943225.0521069 iteration: 36880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12965 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.21387 L1 loss: 0.0000e+00 L2 loss: 0.68114 Learning rate: 0.02 Mask loss: 0.11968 RPN box loss: 0.02225 RPN score loss: 0.00864 RPN total loss: 0.03089 Total loss: 1.04559 timestamp: 1654943228.1327686 iteration: 36885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12043 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.17241 L1 loss: 0.0000e+00 L2 loss: 0.68107 Learning rate: 0.02 Mask loss: 0.12573 RPN box loss: 0.01707 RPN score loss: 0.00594 RPN total loss: 0.02301 Total loss: 1.00222 timestamp: 1654943231.2960744 iteration: 36890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14838 FastRCNN class loss: 0.08317 FastRCNN total loss: 0.23155 L1 loss: 0.0000e+00 L2 loss: 0.68098 Learning rate: 0.02 Mask loss: 0.1452 RPN box loss: 0.02264 RPN score loss: 0.00687 RPN total loss: 0.02951 Total loss: 1.08724 timestamp: 1654943234.4889932 iteration: 36895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1275 FastRCNN class loss: 0.10161 FastRCNN total loss: 0.22911 L1 loss: 0.0000e+00 L2 loss: 0.6809 Learning rate: 0.02 Mask loss: 0.17036 RPN box loss: 0.04722 RPN score loss: 0.00914 RPN total loss: 0.05636 Total loss: 1.13673 timestamp: 1654943237.7005262 iteration: 36900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16947 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.24788 L1 loss: 0.0000e+00 L2 loss: 0.6808 Learning rate: 0.02 Mask loss: 0.14548 RPN box loss: 0.08398 RPN score loss: 0.01808 RPN total loss: 0.10206 Total loss: 1.17621 timestamp: 1654943240.8994071 iteration: 36905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11224 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.18044 L1 loss: 0.0000e+00 L2 loss: 0.6807 Learning rate: 0.02 Mask loss: 0.09697 RPN box loss: 0.02049 RPN score loss: 0.00254 RPN total loss: 0.02304 Total loss: 0.98114 timestamp: 1654943244.076526 iteration: 36910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14577 FastRCNN class loss: 0.08318 FastRCNN total loss: 0.22895 L1 loss: 0.0000e+00 L2 loss: 0.68058 Learning rate: 0.02 Mask loss: 0.13945 RPN box loss: 0.01455 RPN score loss: 0.00321 RPN total loss: 0.01776 Total loss: 1.06674 timestamp: 1654943247.245449 iteration: 36915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13644 FastRCNN class loss: 0.10223 FastRCNN total loss: 0.23867 L1 loss: 0.0000e+00 L2 loss: 0.68047 Learning rate: 0.02 Mask loss: 0.17426 RPN box loss: 0.04903 RPN score loss: 0.00953 RPN total loss: 0.05856 Total loss: 1.15196 timestamp: 1654943250.5319865 iteration: 36920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08329 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.13858 L1 loss: 0.0000e+00 L2 loss: 0.6804 Learning rate: 0.02 Mask loss: 0.1402 RPN box loss: 0.05332 RPN score loss: 0.00456 RPN total loss: 0.05787 Total loss: 1.01706 timestamp: 1654943253.758756 iteration: 36925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07949 FastRCNN class loss: 0.05913 FastRCNN total loss: 0.13862 L1 loss: 0.0000e+00 L2 loss: 0.68032 Learning rate: 0.02 Mask loss: 0.14802 RPN box loss: 0.02038 RPN score loss: 0.00348 RPN total loss: 0.02386 Total loss: 0.99082 timestamp: 1654943256.863348 iteration: 36930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16487 FastRCNN class loss: 0.10852 FastRCNN total loss: 0.27339 L1 loss: 0.0000e+00 L2 loss: 0.68025 Learning rate: 0.02 Mask loss: 0.2094 RPN box loss: 0.02266 RPN score loss: 0.00407 RPN total loss: 0.02673 Total loss: 1.18978 timestamp: 1654943260.1636207 iteration: 36935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12098 FastRCNN class loss: 0.0492 FastRCNN total loss: 0.17018 L1 loss: 0.0000e+00 L2 loss: 0.68016 Learning rate: 0.02 Mask loss: 0.11477 RPN box loss: 0.01603 RPN score loss: 0.00176 RPN total loss: 0.01778 Total loss: 0.98289 timestamp: 1654943263.322243 iteration: 36940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13334 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.19522 L1 loss: 0.0000e+00 L2 loss: 0.68012 Learning rate: 0.02 Mask loss: 0.21056 RPN box loss: 0.05447 RPN score loss: 0.00847 RPN total loss: 0.06294 Total loss: 1.14884 timestamp: 1654943266.5573983 iteration: 36945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12283 FastRCNN class loss: 0.10775 FastRCNN total loss: 0.23058 L1 loss: 0.0000e+00 L2 loss: 0.68004 Learning rate: 0.02 Mask loss: 0.17838 RPN box loss: 0.03402 RPN score loss: 0.0116 RPN total loss: 0.04562 Total loss: 1.13461 timestamp: 1654943269.7540007 iteration: 36950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15119 FastRCNN class loss: 0.10175 FastRCNN total loss: 0.25294 L1 loss: 0.0000e+00 L2 loss: 0.67996 Learning rate: 0.02 Mask loss: 0.20055 RPN box loss: 0.01652 RPN score loss: 0.00728 RPN total loss: 0.0238 Total loss: 1.15725 timestamp: 1654943272.9903095 iteration: 36955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.08013 FastRCNN total loss: 0.17149 L1 loss: 0.0000e+00 L2 loss: 0.67987 Learning rate: 0.02 Mask loss: 0.16069 RPN box loss: 0.01299 RPN score loss: 0.00877 RPN total loss: 0.02177 Total loss: 1.03381 timestamp: 1654943276.1860816 iteration: 36960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17254 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.24303 L1 loss: 0.0000e+00 L2 loss: 0.67976 Learning rate: 0.02 Mask loss: 0.13813 RPN box loss: 0.02874 RPN score loss: 0.00557 RPN total loss: 0.03431 Total loss: 1.09523 timestamp: 1654943279.4027536 iteration: 36965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1914 FastRCNN class loss: 0.09781 FastRCNN total loss: 0.28921 L1 loss: 0.0000e+00 L2 loss: 0.67968 Learning rate: 0.02 Mask loss: 0.18476 RPN box loss: 0.05814 RPN score loss: 0.01072 RPN total loss: 0.06886 Total loss: 1.22253 timestamp: 1654943282.5088835 iteration: 36970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13096 FastRCNN class loss: 0.11031 FastRCNN total loss: 0.24127 L1 loss: 0.0000e+00 L2 loss: 0.6796 Learning rate: 0.02 Mask loss: 0.18516 RPN box loss: 0.01553 RPN score loss: 0.00616 RPN total loss: 0.0217 Total loss: 1.12773 timestamp: 1654943285.7289805 iteration: 36975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12534 FastRCNN class loss: 0.0706 FastRCNN total loss: 0.19594 L1 loss: 0.0000e+00 L2 loss: 0.67951 Learning rate: 0.02 Mask loss: 0.19329 RPN box loss: 0.02418 RPN score loss: 0.00661 RPN total loss: 0.03079 Total loss: 1.09952 timestamp: 1654943288.9452922 iteration: 36980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1177 FastRCNN class loss: 0.0658 FastRCNN total loss: 0.18349 L1 loss: 0.0000e+00 L2 loss: 0.67941 Learning rate: 0.02 Mask loss: 0.1325 RPN box loss: 0.0214 RPN score loss: 0.00572 RPN total loss: 0.02711 Total loss: 1.02252 timestamp: 1654943292.10704 iteration: 36985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12965 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.19781 L1 loss: 0.0000e+00 L2 loss: 0.67931 Learning rate: 0.02 Mask loss: 0.15694 RPN box loss: 0.01474 RPN score loss: 0.00335 RPN total loss: 0.01809 Total loss: 1.05215 timestamp: 1654943295.3531327 iteration: 36990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09572 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.15456 L1 loss: 0.0000e+00 L2 loss: 0.67923 Learning rate: 0.02 Mask loss: 0.12918 RPN box loss: 0.02276 RPN score loss: 0.00307 RPN total loss: 0.02583 Total loss: 0.98878 timestamp: 1654943298.5607495 iteration: 36995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18943 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.2486 L1 loss: 0.0000e+00 L2 loss: 0.67915 Learning rate: 0.02 Mask loss: 0.13362 RPN box loss: 0.03711 RPN score loss: 0.0033 RPN total loss: 0.04041 Total loss: 1.10179 timestamp: 1654943301.8433585 iteration: 37000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14982 FastRCNN class loss: 0.10784 FastRCNN total loss: 0.25767 L1 loss: 0.0000e+00 L2 loss: 0.67907 Learning rate: 0.02 Mask loss: 0.11756 RPN box loss: 0.02052 RPN score loss: 0.00757 RPN total loss: 0.02809 Total loss: 1.08239 timestamp: 1654943305.0296426 iteration: 37005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06402 FastRCNN class loss: 0.0566 FastRCNN total loss: 0.12063 L1 loss: 0.0000e+00 L2 loss: 0.67899 Learning rate: 0.02 Mask loss: 0.11233 RPN box loss: 0.03782 RPN score loss: 0.00535 RPN total loss: 0.04317 Total loss: 0.95511 timestamp: 1654943308.2289288 iteration: 37010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10401 FastRCNN class loss: 0.07269 FastRCNN total loss: 0.17671 L1 loss: 0.0000e+00 L2 loss: 0.6789 Learning rate: 0.02 Mask loss: 0.1357 RPN box loss: 0.02537 RPN score loss: 0.00322 RPN total loss: 0.02859 Total loss: 1.0199 timestamp: 1654943311.4171882 iteration: 37015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13783 FastRCNN class loss: 0.06466 FastRCNN total loss: 0.20249 L1 loss: 0.0000e+00 L2 loss: 0.67881 Learning rate: 0.02 Mask loss: 0.09041 RPN box loss: 0.02916 RPN score loss: 0.00394 RPN total loss: 0.0331 Total loss: 1.00481 timestamp: 1654943314.553857 iteration: 37020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10815 FastRCNN class loss: 0.04173 FastRCNN total loss: 0.14987 L1 loss: 0.0000e+00 L2 loss: 0.67873 Learning rate: 0.02 Mask loss: 0.13231 RPN box loss: 0.03497 RPN score loss: 0.0022 RPN total loss: 0.03717 Total loss: 0.99809 timestamp: 1654943317.7978032 iteration: 37025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1429 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.20941 L1 loss: 0.0000e+00 L2 loss: 0.67864 Learning rate: 0.02 Mask loss: 0.08449 RPN box loss: 0.01666 RPN score loss: 0.00195 RPN total loss: 0.01861 Total loss: 0.99115 timestamp: 1654943320.9776073 iteration: 37030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12001 FastRCNN class loss: 0.08262 FastRCNN total loss: 0.20263 L1 loss: 0.0000e+00 L2 loss: 0.67855 Learning rate: 0.02 Mask loss: 0.11394 RPN box loss: 0.01573 RPN score loss: 0.00224 RPN total loss: 0.01797 Total loss: 1.01309 timestamp: 1654943324.1712108 iteration: 37035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15337 FastRCNN class loss: 0.12355 FastRCNN total loss: 0.27692 L1 loss: 0.0000e+00 L2 loss: 0.67848 Learning rate: 0.02 Mask loss: 0.16192 RPN box loss: 0.01949 RPN score loss: 0.00346 RPN total loss: 0.02296 Total loss: 1.14027 timestamp: 1654943327.3363788 iteration: 37040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15946 FastRCNN class loss: 0.07382 FastRCNN total loss: 0.23328 L1 loss: 0.0000e+00 L2 loss: 0.67837 Learning rate: 0.02 Mask loss: 0.16908 RPN box loss: 0.02369 RPN score loss: 0.01069 RPN total loss: 0.03438 Total loss: 1.1151 timestamp: 1654943330.563968 iteration: 37045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16496 FastRCNN class loss: 0.13589 FastRCNN total loss: 0.30085 L1 loss: 0.0000e+00 L2 loss: 0.67827 Learning rate: 0.02 Mask loss: 0.2349 RPN box loss: 0.00923 RPN score loss: 0.01425 RPN total loss: 0.02348 Total loss: 1.2375 timestamp: 1654943333.7318337 iteration: 37050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12901 FastRCNN class loss: 0.0903 FastRCNN total loss: 0.2193 L1 loss: 0.0000e+00 L2 loss: 0.67817 Learning rate: 0.02 Mask loss: 0.16317 RPN box loss: 0.01776 RPN score loss: 0.00547 RPN total loss: 0.02323 Total loss: 1.08388 timestamp: 1654943336.9274578 iteration: 37055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12614 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.20976 L1 loss: 0.0000e+00 L2 loss: 0.67808 Learning rate: 0.02 Mask loss: 0.14341 RPN box loss: 0.03238 RPN score loss: 0.00539 RPN total loss: 0.03777 Total loss: 1.06901 timestamp: 1654943340.1432717 iteration: 37060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11236 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.17404 L1 loss: 0.0000e+00 L2 loss: 0.67802 Learning rate: 0.02 Mask loss: 0.16818 RPN box loss: 0.04339 RPN score loss: 0.00889 RPN total loss: 0.05228 Total loss: 1.07252 timestamp: 1654943343.3360066 iteration: 37065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05968 FastRCNN class loss: 0.05344 FastRCNN total loss: 0.11312 L1 loss: 0.0000e+00 L2 loss: 0.67795 Learning rate: 0.02 Mask loss: 0.1528 RPN box loss: 0.01446 RPN score loss: 0.00822 RPN total loss: 0.02268 Total loss: 0.96654 timestamp: 1654943346.496951 iteration: 37070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11387 FastRCNN class loss: 0.0704 FastRCNN total loss: 0.18427 L1 loss: 0.0000e+00 L2 loss: 0.67785 Learning rate: 0.02 Mask loss: 0.18073 RPN box loss: 0.01886 RPN score loss: 0.00241 RPN total loss: 0.02127 Total loss: 1.06412 timestamp: 1654943349.7018235 iteration: 37075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10376 FastRCNN class loss: 0.05932 FastRCNN total loss: 0.16308 L1 loss: 0.0000e+00 L2 loss: 0.67775 Learning rate: 0.02 Mask loss: 0.19001 RPN box loss: 0.01664 RPN score loss: 0.0029 RPN total loss: 0.01955 Total loss: 1.05039 timestamp: 1654943352.9426293 iteration: 37080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13224 FastRCNN class loss: 0.08274 FastRCNN total loss: 0.21498 L1 loss: 0.0000e+00 L2 loss: 0.67768 Learning rate: 0.02 Mask loss: 0.17908 RPN box loss: 0.00763 RPN score loss: 0.00201 RPN total loss: 0.00963 Total loss: 1.08137 timestamp: 1654943356.1171184 iteration: 37085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18709 FastRCNN class loss: 0.14111 FastRCNN total loss: 0.3282 L1 loss: 0.0000e+00 L2 loss: 0.67759 Learning rate: 0.02 Mask loss: 0.20214 RPN box loss: 0.03694 RPN score loss: 0.00336 RPN total loss: 0.0403 Total loss: 1.24823 timestamp: 1654943359.2484097 iteration: 37090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15109 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.2401 L1 loss: 0.0000e+00 L2 loss: 0.6775 Learning rate: 0.02 Mask loss: 0.13365 RPN box loss: 0.03199 RPN score loss: 0.00246 RPN total loss: 0.03444 Total loss: 1.08569 timestamp: 1654943362.384708 iteration: 37095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08148 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.13785 L1 loss: 0.0000e+00 L2 loss: 0.6774 Learning rate: 0.02 Mask loss: 0.12374 RPN box loss: 0.07451 RPN score loss: 0.0094 RPN total loss: 0.08391 Total loss: 1.02291 timestamp: 1654943365.5719407 iteration: 37100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11351 FastRCNN class loss: 0.081 FastRCNN total loss: 0.1945 L1 loss: 0.0000e+00 L2 loss: 0.67731 Learning rate: 0.02 Mask loss: 0.20149 RPN box loss: 0.06851 RPN score loss: 0.01339 RPN total loss: 0.0819 Total loss: 1.15521 timestamp: 1654943368.676645 iteration: 37105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07128 FastRCNN class loss: 0.04847 FastRCNN total loss: 0.11975 L1 loss: 0.0000e+00 L2 loss: 0.67721 Learning rate: 0.02 Mask loss: 0.1348 RPN box loss: 0.01919 RPN score loss: 0.00545 RPN total loss: 0.02464 Total loss: 0.9564 timestamp: 1654943371.8795836 iteration: 37110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08492 FastRCNN class loss: 0.04171 FastRCNN total loss: 0.12663 L1 loss: 0.0000e+00 L2 loss: 0.67709 Learning rate: 0.02 Mask loss: 0.10207 RPN box loss: 0.00314 RPN score loss: 0.00188 RPN total loss: 0.00502 Total loss: 0.9108 timestamp: 1654943375.0831113 iteration: 37115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11043 FastRCNN class loss: 0.08898 FastRCNN total loss: 0.1994 L1 loss: 0.0000e+00 L2 loss: 0.677 Learning rate: 0.02 Mask loss: 0.12749 RPN box loss: 0.03303 RPN score loss: 0.0106 RPN total loss: 0.04364 Total loss: 1.04754 timestamp: 1654943378.2532897 iteration: 37120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11467 FastRCNN class loss: 0.09722 FastRCNN total loss: 0.2119 L1 loss: 0.0000e+00 L2 loss: 0.67694 Learning rate: 0.02 Mask loss: 0.14111 RPN box loss: 0.04022 RPN score loss: 0.01212 RPN total loss: 0.05235 Total loss: 1.08229 timestamp: 1654943381.470823 iteration: 37125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11216 FastRCNN class loss: 0.07063 FastRCNN total loss: 0.18279 L1 loss: 0.0000e+00 L2 loss: 0.67686 Learning rate: 0.02 Mask loss: 0.13376 RPN box loss: 0.01846 RPN score loss: 0.0069 RPN total loss: 0.02536 Total loss: 1.01876 timestamp: 1654943384.644723 iteration: 37130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14456 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.20538 L1 loss: 0.0000e+00 L2 loss: 0.67679 Learning rate: 0.02 Mask loss: 0.13354 RPN box loss: 0.01062 RPN score loss: 0.00537 RPN total loss: 0.01599 Total loss: 1.0317 timestamp: 1654943387.7795184 iteration: 37135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12146 FastRCNN class loss: 0.10979 FastRCNN total loss: 0.23125 L1 loss: 0.0000e+00 L2 loss: 0.67673 Learning rate: 0.02 Mask loss: 0.12573 RPN box loss: 0.07195 RPN score loss: 0.00801 RPN total loss: 0.07996 Total loss: 1.11367 timestamp: 1654943390.9752831 iteration: 37140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13223 FastRCNN class loss: 0.07555 FastRCNN total loss: 0.20778 L1 loss: 0.0000e+00 L2 loss: 0.67664 Learning rate: 0.02 Mask loss: 0.14966 RPN box loss: 0.02363 RPN score loss: 0.00388 RPN total loss: 0.02751 Total loss: 1.06158 timestamp: 1654943394.1881819 iteration: 37145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15081 FastRCNN class loss: 0.09604 FastRCNN total loss: 0.24685 L1 loss: 0.0000e+00 L2 loss: 0.67653 Learning rate: 0.02 Mask loss: 0.16461 RPN box loss: 0.03699 RPN score loss: 0.0073 RPN total loss: 0.04429 Total loss: 1.13228 timestamp: 1654943397.3866603 iteration: 37150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11108 FastRCNN class loss: 0.06958 FastRCNN total loss: 0.18067 L1 loss: 0.0000e+00 L2 loss: 0.67644 Learning rate: 0.02 Mask loss: 0.1456 RPN box loss: 0.01038 RPN score loss: 0.00497 RPN total loss: 0.01536 Total loss: 1.01806 timestamp: 1654943400.5605533 iteration: 37155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08735 FastRCNN class loss: 0.08505 FastRCNN total loss: 0.1724 L1 loss: 0.0000e+00 L2 loss: 0.67634 Learning rate: 0.02 Mask loss: 0.11407 RPN box loss: 0.01435 RPN score loss: 0.00482 RPN total loss: 0.01917 Total loss: 0.98197 timestamp: 1654943403.7206402 iteration: 37160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15672 FastRCNN class loss: 0.17542 FastRCNN total loss: 0.33214 L1 loss: 0.0000e+00 L2 loss: 0.67624 Learning rate: 0.02 Mask loss: 0.17464 RPN box loss: 0.02467 RPN score loss: 0.00799 RPN total loss: 0.03267 Total loss: 1.21569 timestamp: 1654943406.8987582 iteration: 37165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14457 FastRCNN class loss: 0.09634 FastRCNN total loss: 0.2409 L1 loss: 0.0000e+00 L2 loss: 0.67614 Learning rate: 0.02 Mask loss: 0.14769 RPN box loss: 0.02381 RPN score loss: 0.00347 RPN total loss: 0.02728 Total loss: 1.09201 timestamp: 1654943410.0651176 iteration: 37170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13309 FastRCNN class loss: 0.09082 FastRCNN total loss: 0.22392 L1 loss: 0.0000e+00 L2 loss: 0.67607 Learning rate: 0.02 Mask loss: 0.16755 RPN box loss: 0.01867 RPN score loss: 0.00318 RPN total loss: 0.02185 Total loss: 1.08939 timestamp: 1654943413.19394 iteration: 37175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13997 FastRCNN class loss: 0.12015 FastRCNN total loss: 0.26012 L1 loss: 0.0000e+00 L2 loss: 0.67599 Learning rate: 0.02 Mask loss: 0.17192 RPN box loss: 0.03129 RPN score loss: 0.00552 RPN total loss: 0.03681 Total loss: 1.14484 timestamp: 1654943416.273781 iteration: 37180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14138 FastRCNN class loss: 0.11898 FastRCNN total loss: 0.26036 L1 loss: 0.0000e+00 L2 loss: 0.6759 Learning rate: 0.02 Mask loss: 0.13159 RPN box loss: 0.02813 RPN score loss: 0.00297 RPN total loss: 0.03109 Total loss: 1.09894 timestamp: 1654943419.560806 iteration: 37185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17322 FastRCNN class loss: 0.12318 FastRCNN total loss: 0.29639 L1 loss: 0.0000e+00 L2 loss: 0.67582 Learning rate: 0.02 Mask loss: 0.15835 RPN box loss: 0.01713 RPN score loss: 0.00466 RPN total loss: 0.02179 Total loss: 1.15236 timestamp: 1654943422.6997356 iteration: 37190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.09147 FastRCNN total loss: 0.19147 L1 loss: 0.0000e+00 L2 loss: 0.67573 Learning rate: 0.02 Mask loss: 0.1174 RPN box loss: 0.01119 RPN score loss: 0.00191 RPN total loss: 0.0131 Total loss: 0.9977 timestamp: 1654943425.916103 iteration: 37195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13233 FastRCNN class loss: 0.07891 FastRCNN total loss: 0.21124 L1 loss: 0.0000e+00 L2 loss: 0.67566 Learning rate: 0.02 Mask loss: 0.20849 RPN box loss: 0.01025 RPN score loss: 0.01156 RPN total loss: 0.02181 Total loss: 1.11721 timestamp: 1654943429.1570477 iteration: 37200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1193 FastRCNN class loss: 0.11136 FastRCNN total loss: 0.23066 L1 loss: 0.0000e+00 L2 loss: 0.67556 Learning rate: 0.02 Mask loss: 0.24031 RPN box loss: 0.04303 RPN score loss: 0.00396 RPN total loss: 0.04698 Total loss: 1.19352 timestamp: 1654943432.3456228 iteration: 37205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12431 FastRCNN class loss: 0.15591 FastRCNN total loss: 0.28022 L1 loss: 0.0000e+00 L2 loss: 0.67549 Learning rate: 0.02 Mask loss: 0.09899 RPN box loss: 0.00826 RPN score loss: 0.00221 RPN total loss: 0.01046 Total loss: 1.06517 timestamp: 1654943435.4715087 iteration: 37210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11151 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.18256 L1 loss: 0.0000e+00 L2 loss: 0.67542 Learning rate: 0.02 Mask loss: 0.14129 RPN box loss: 0.0177 RPN score loss: 0.00192 RPN total loss: 0.01962 Total loss: 1.01889 timestamp: 1654943438.7252045 iteration: 37215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17577 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.26622 L1 loss: 0.0000e+00 L2 loss: 0.67532 Learning rate: 0.02 Mask loss: 0.18318 RPN box loss: 0.06067 RPN score loss: 0.01671 RPN total loss: 0.07738 Total loss: 1.2021 timestamp: 1654943441.973294 iteration: 37220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10097 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.18999 L1 loss: 0.0000e+00 L2 loss: 0.67521 Learning rate: 0.02 Mask loss: 0.32089 RPN box loss: 0.01834 RPN score loss: 0.0042 RPN total loss: 0.02254 Total loss: 1.20863 timestamp: 1654943445.1154637 iteration: 37225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16084 FastRCNN class loss: 0.08928 FastRCNN total loss: 0.25013 L1 loss: 0.0000e+00 L2 loss: 0.67511 Learning rate: 0.02 Mask loss: 0.1259 RPN box loss: 0.01514 RPN score loss: 0.00421 RPN total loss: 0.01935 Total loss: 1.07049 timestamp: 1654943448.3307867 iteration: 37230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18993 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.27406 L1 loss: 0.0000e+00 L2 loss: 0.67502 Learning rate: 0.02 Mask loss: 0.20312 RPN box loss: 0.04059 RPN score loss: 0.00278 RPN total loss: 0.04338 Total loss: 1.19558 timestamp: 1654943451.5464556 iteration: 37235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15574 FastRCNN class loss: 0.05875 FastRCNN total loss: 0.21449 L1 loss: 0.0000e+00 L2 loss: 0.67495 Learning rate: 0.02 Mask loss: 0.10294 RPN box loss: 0.02596 RPN score loss: 0.0024 RPN total loss: 0.02836 Total loss: 1.02074 timestamp: 1654943454.7673097 iteration: 37240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15798 FastRCNN class loss: 0.16887 FastRCNN total loss: 0.32685 L1 loss: 0.0000e+00 L2 loss: 0.67488 Learning rate: 0.02 Mask loss: 0.28934 RPN box loss: 0.04096 RPN score loss: 0.00999 RPN total loss: 0.05095 Total loss: 1.34203 timestamp: 1654943457.9442892 iteration: 37245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1231 FastRCNN class loss: 0.09242 FastRCNN total loss: 0.21552 L1 loss: 0.0000e+00 L2 loss: 0.67479 Learning rate: 0.02 Mask loss: 0.13005 RPN box loss: 0.02107 RPN score loss: 0.01139 RPN total loss: 0.03246 Total loss: 1.05281 timestamp: 1654943461.1798475 iteration: 37250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18867 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.25145 L1 loss: 0.0000e+00 L2 loss: 0.67469 Learning rate: 0.02 Mask loss: 0.2041 RPN box loss: 0.04599 RPN score loss: 0.00424 RPN total loss: 0.05023 Total loss: 1.18047 timestamp: 1654943464.3689642 iteration: 37255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1045 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.19715 L1 loss: 0.0000e+00 L2 loss: 0.67458 Learning rate: 0.02 Mask loss: 0.12599 RPN box loss: 0.02441 RPN score loss: 0.01251 RPN total loss: 0.03692 Total loss: 1.03465 timestamp: 1654943467.5213528 iteration: 37260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20324 FastRCNN class loss: 0.12707 FastRCNN total loss: 0.33032 L1 loss: 0.0000e+00 L2 loss: 0.67448 Learning rate: 0.02 Mask loss: 0.16829 RPN box loss: 0.05778 RPN score loss: 0.00668 RPN total loss: 0.06447 Total loss: 1.23756 timestamp: 1654943470.7503886 iteration: 37265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1019 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.15838 L1 loss: 0.0000e+00 L2 loss: 0.67441 Learning rate: 0.02 Mask loss: 0.10328 RPN box loss: 0.02312 RPN score loss: 0.00274 RPN total loss: 0.02585 Total loss: 0.96192 timestamp: 1654943473.895123 iteration: 37270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08368 FastRCNN class loss: 0.07404 FastRCNN total loss: 0.15773 L1 loss: 0.0000e+00 L2 loss: 0.67434 Learning rate: 0.02 Mask loss: 0.14244 RPN box loss: 0.00913 RPN score loss: 0.00402 RPN total loss: 0.01315 Total loss: 0.98766 timestamp: 1654943477.1513205 iteration: 37275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11202 FastRCNN class loss: 0.08751 FastRCNN total loss: 0.19952 L1 loss: 0.0000e+00 L2 loss: 0.67424 Learning rate: 0.02 Mask loss: 0.13513 RPN box loss: 0.00872 RPN score loss: 0.0019 RPN total loss: 0.01062 Total loss: 1.01951 timestamp: 1654943480.4945579 iteration: 37280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15208 FastRCNN class loss: 0.10227 FastRCNN total loss: 0.25435 L1 loss: 0.0000e+00 L2 loss: 0.67417 Learning rate: 0.02 Mask loss: 0.13125 RPN box loss: 0.03632 RPN score loss: 0.01396 RPN total loss: 0.05027 Total loss: 1.11004 timestamp: 1654943483.735154 iteration: 37285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11603 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.17613 L1 loss: 0.0000e+00 L2 loss: 0.67408 Learning rate: 0.02 Mask loss: 0.10761 RPN box loss: 0.01825 RPN score loss: 0.00472 RPN total loss: 0.02297 Total loss: 0.98078 timestamp: 1654943486.9208992 iteration: 37290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14864 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.21914 L1 loss: 0.0000e+00 L2 loss: 0.67401 Learning rate: 0.02 Mask loss: 0.14543 RPN box loss: 0.02852 RPN score loss: 0.00242 RPN total loss: 0.03094 Total loss: 1.06951 timestamp: 1654943490.0599968 iteration: 37295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07525 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.15345 L1 loss: 0.0000e+00 L2 loss: 0.67392 Learning rate: 0.02 Mask loss: 0.09133 RPN box loss: 0.02487 RPN score loss: 0.00529 RPN total loss: 0.03016 Total loss: 0.94887 timestamp: 1654943493.1617725 iteration: 37300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18543 FastRCNN class loss: 0.09459 FastRCNN total loss: 0.28002 L1 loss: 0.0000e+00 L2 loss: 0.67379 Learning rate: 0.02 Mask loss: 0.19005 RPN box loss: 0.02956 RPN score loss: 0.00888 RPN total loss: 0.03844 Total loss: 1.18229 timestamp: 1654943496.3085084 iteration: 37305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14414 FastRCNN class loss: 0.06489 FastRCNN total loss: 0.20904 L1 loss: 0.0000e+00 L2 loss: 0.67369 Learning rate: 0.02 Mask loss: 0.12396 RPN box loss: 0.01773 RPN score loss: 0.00556 RPN total loss: 0.02329 Total loss: 1.02998 timestamp: 1654943499.5001595 iteration: 37310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16738 FastRCNN class loss: 0.07473 FastRCNN total loss: 0.2421 L1 loss: 0.0000e+00 L2 loss: 0.67364 Learning rate: 0.02 Mask loss: 0.12808 RPN box loss: 0.02533 RPN score loss: 0.00627 RPN total loss: 0.0316 Total loss: 1.07543 timestamp: 1654943502.6881087 iteration: 37315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09177 FastRCNN class loss: 0.06343 FastRCNN total loss: 0.15519 L1 loss: 0.0000e+00 L2 loss: 0.67357 Learning rate: 0.02 Mask loss: 0.15713 RPN box loss: 0.01026 RPN score loss: 0.00593 RPN total loss: 0.01618 Total loss: 1.00208 timestamp: 1654943505.8977308 iteration: 37320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20174 FastRCNN class loss: 0.09789 FastRCNN total loss: 0.29964 L1 loss: 0.0000e+00 L2 loss: 0.67347 Learning rate: 0.02 Mask loss: 0.20312 RPN box loss: 0.03403 RPN score loss: 0.00824 RPN total loss: 0.04227 Total loss: 1.2185 timestamp: 1654943509.0886114 iteration: 37325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08422 FastRCNN class loss: 0.08275 FastRCNN total loss: 0.16696 L1 loss: 0.0000e+00 L2 loss: 0.67338 Learning rate: 0.02 Mask loss: 0.12836 RPN box loss: 0.03985 RPN score loss: 0.01209 RPN total loss: 0.05194 Total loss: 1.02064 timestamp: 1654943512.2899382 iteration: 37330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17685 FastRCNN class loss: 0.11656 FastRCNN total loss: 0.29341 L1 loss: 0.0000e+00 L2 loss: 0.67327 Learning rate: 0.02 Mask loss: 0.17726 RPN box loss: 0.05897 RPN score loss: 0.03183 RPN total loss: 0.09079 Total loss: 1.23474 timestamp: 1654943515.4471686 iteration: 37335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08467 FastRCNN class loss: 0.05949 FastRCNN total loss: 0.14417 L1 loss: 0.0000e+00 L2 loss: 0.67319 Learning rate: 0.02 Mask loss: 0.1723 RPN box loss: 0.01422 RPN score loss: 0.00952 RPN total loss: 0.02374 Total loss: 1.01339 timestamp: 1654943518.649664 iteration: 37340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10011 FastRCNN class loss: 0.06818 FastRCNN total loss: 0.16829 L1 loss: 0.0000e+00 L2 loss: 0.6731 Learning rate: 0.02 Mask loss: 0.19919 RPN box loss: 0.02467 RPN score loss: 0.00567 RPN total loss: 0.03034 Total loss: 1.07093 timestamp: 1654943521.8831477 iteration: 37345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08933 FastRCNN class loss: 0.05889 FastRCNN total loss: 0.14823 L1 loss: 0.0000e+00 L2 loss: 0.67303 Learning rate: 0.02 Mask loss: 0.18564 RPN box loss: 0.02497 RPN score loss: 0.0035 RPN total loss: 0.02847 Total loss: 1.03536 timestamp: 1654943525.08708 iteration: 37350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.10422 FastRCNN total loss: 0.22438 L1 loss: 0.0000e+00 L2 loss: 0.67298 Learning rate: 0.02 Mask loss: 0.18263 RPN box loss: 0.03 RPN score loss: 0.0069 RPN total loss: 0.0369 Total loss: 1.11689 timestamp: 1654943528.2993035 iteration: 37355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16369 FastRCNN class loss: 0.0946 FastRCNN total loss: 0.25829 L1 loss: 0.0000e+00 L2 loss: 0.67291 Learning rate: 0.02 Mask loss: 0.17295 RPN box loss: 0.02643 RPN score loss: 0.00434 RPN total loss: 0.03077 Total loss: 1.13491 timestamp: 1654943531.4590876 iteration: 37360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.09059 FastRCNN total loss: 0.20611 L1 loss: 0.0000e+00 L2 loss: 0.67281 Learning rate: 0.02 Mask loss: 0.16165 RPN box loss: 0.03782 RPN score loss: 0.00257 RPN total loss: 0.04039 Total loss: 1.08095 timestamp: 1654943534.7200224 iteration: 37365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05778 FastRCNN class loss: 0.04448 FastRCNN total loss: 0.10226 L1 loss: 0.0000e+00 L2 loss: 0.67274 Learning rate: 0.02 Mask loss: 0.16579 RPN box loss: 0.02166 RPN score loss: 0.00502 RPN total loss: 0.02668 Total loss: 0.96747 timestamp: 1654943537.9812438 iteration: 37370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19591 FastRCNN class loss: 0.10718 FastRCNN total loss: 0.3031 L1 loss: 0.0000e+00 L2 loss: 0.67265 Learning rate: 0.02 Mask loss: 0.17911 RPN box loss: 0.04831 RPN score loss: 0.00773 RPN total loss: 0.05604 Total loss: 1.2109 timestamp: 1654943541.113253 iteration: 37375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14894 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.20736 L1 loss: 0.0000e+00 L2 loss: 0.67256 Learning rate: 0.02 Mask loss: 0.16701 RPN box loss: 0.07718 RPN score loss: 0.01188 RPN total loss: 0.08906 Total loss: 1.13598 timestamp: 1654943544.2829306 iteration: 37380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09466 FastRCNN class loss: 0.09438 FastRCNN total loss: 0.18904 L1 loss: 0.0000e+00 L2 loss: 0.67246 Learning rate: 0.02 Mask loss: 0.18086 RPN box loss: 0.05799 RPN score loss: 0.02454 RPN total loss: 0.08253 Total loss: 1.12489 timestamp: 1654943547.5019639 iteration: 37385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08511 FastRCNN class loss: 0.07485 FastRCNN total loss: 0.15995 L1 loss: 0.0000e+00 L2 loss: 0.6724 Learning rate: 0.02 Mask loss: 0.14599 RPN box loss: 0.0399 RPN score loss: 0.00966 RPN total loss: 0.04957 Total loss: 1.02791 timestamp: 1654943550.7182403 iteration: 37390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.078 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.14843 L1 loss: 0.0000e+00 L2 loss: 0.67233 Learning rate: 0.02 Mask loss: 0.19391 RPN box loss: 0.01798 RPN score loss: 0.00701 RPN total loss: 0.02499 Total loss: 1.03966 timestamp: 1654943553.9687378 iteration: 37395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08471 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.14884 L1 loss: 0.0000e+00 L2 loss: 0.67224 Learning rate: 0.02 Mask loss: 0.15089 RPN box loss: 0.00548 RPN score loss: 0.00163 RPN total loss: 0.00711 Total loss: 0.97908 timestamp: 1654943557.1935434 iteration: 37400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.15593 L1 loss: 0.0000e+00 L2 loss: 0.67216 Learning rate: 0.02 Mask loss: 0.14054 RPN box loss: 0.01488 RPN score loss: 0.00836 RPN total loss: 0.02324 Total loss: 0.99187 timestamp: 1654943560.415718 iteration: 37405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09091 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.1781 L1 loss: 0.0000e+00 L2 loss: 0.67206 Learning rate: 0.02 Mask loss: 0.1356 RPN box loss: 0.06381 RPN score loss: 0.01515 RPN total loss: 0.07896 Total loss: 1.06472 timestamp: 1654943563.601478 iteration: 37410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15253 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.24958 L1 loss: 0.0000e+00 L2 loss: 0.67198 Learning rate: 0.02 Mask loss: 0.14506 RPN box loss: 0.02894 RPN score loss: 0.01702 RPN total loss: 0.04596 Total loss: 1.11258 timestamp: 1654943566.7611933 iteration: 37415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06287 FastRCNN class loss: 0.03441 FastRCNN total loss: 0.09727 L1 loss: 0.0000e+00 L2 loss: 0.67189 Learning rate: 0.02 Mask loss: 0.09579 RPN box loss: 0.02221 RPN score loss: 0.00131 RPN total loss: 0.02352 Total loss: 0.88847 timestamp: 1654943569.9666212 iteration: 37420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1176 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.17062 L1 loss: 0.0000e+00 L2 loss: 0.67179 Learning rate: 0.02 Mask loss: 0.13169 RPN box loss: 0.02801 RPN score loss: 0.00569 RPN total loss: 0.0337 Total loss: 1.00781 timestamp: 1654943573.1701899 iteration: 37425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.088 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.13743 L1 loss: 0.0000e+00 L2 loss: 0.67172 Learning rate: 0.02 Mask loss: 0.12059 RPN box loss: 0.03338 RPN score loss: 0.00642 RPN total loss: 0.03979 Total loss: 0.96953 timestamp: 1654943576.3445144 iteration: 37430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10042 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.15091 L1 loss: 0.0000e+00 L2 loss: 0.67163 Learning rate: 0.02 Mask loss: 0.12011 RPN box loss: 0.01971 RPN score loss: 0.00825 RPN total loss: 0.02797 Total loss: 0.97062 timestamp: 1654943579.5100174 iteration: 37435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14763 FastRCNN class loss: 0.10867 FastRCNN total loss: 0.2563 L1 loss: 0.0000e+00 L2 loss: 0.67152 Learning rate: 0.02 Mask loss: 0.16552 RPN box loss: 0.02934 RPN score loss: 0.00883 RPN total loss: 0.03817 Total loss: 1.13152 timestamp: 1654943582.7164366 iteration: 37440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06827 FastRCNN class loss: 0.07474 FastRCNN total loss: 0.143 L1 loss: 0.0000e+00 L2 loss: 0.67143 Learning rate: 0.02 Mask loss: 0.10268 RPN box loss: 0.01503 RPN score loss: 0.00607 RPN total loss: 0.0211 Total loss: 0.9382 timestamp: 1654943585.9518123 iteration: 37445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.17158 L1 loss: 0.0000e+00 L2 loss: 0.67132 Learning rate: 0.02 Mask loss: 0.12196 RPN box loss: 0.01413 RPN score loss: 0.00646 RPN total loss: 0.0206 Total loss: 0.98546 timestamp: 1654943589.1752448 iteration: 37450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14112 FastRCNN class loss: 0.07577 FastRCNN total loss: 0.21689 L1 loss: 0.0000e+00 L2 loss: 0.67122 Learning rate: 0.02 Mask loss: 0.22803 RPN box loss: 0.04322 RPN score loss: 0.00544 RPN total loss: 0.04866 Total loss: 1.1648 timestamp: 1654943592.377209 iteration: 37455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06782 FastRCNN class loss: 0.04641 FastRCNN total loss: 0.11424 L1 loss: 0.0000e+00 L2 loss: 0.67113 Learning rate: 0.02 Mask loss: 0.08999 RPN box loss: 0.01282 RPN score loss: 0.00126 RPN total loss: 0.01408 Total loss: 0.88943 timestamp: 1654943595.662023 iteration: 37460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10941 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.17465 L1 loss: 0.0000e+00 L2 loss: 0.67103 Learning rate: 0.02 Mask loss: 0.1008 RPN box loss: 0.04133 RPN score loss: 0.00125 RPN total loss: 0.04257 Total loss: 0.98905 timestamp: 1654943598.8367088 iteration: 37465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1673 FastRCNN class loss: 0.09259 FastRCNN total loss: 0.2599 L1 loss: 0.0000e+00 L2 loss: 0.67094 Learning rate: 0.02 Mask loss: 0.15321 RPN box loss: 0.01138 RPN score loss: 0.00466 RPN total loss: 0.01604 Total loss: 1.10008 timestamp: 1654943601.986309 iteration: 37470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14965 FastRCNN class loss: 0.13231 FastRCNN total loss: 0.28196 L1 loss: 0.0000e+00 L2 loss: 0.67087 Learning rate: 0.02 Mask loss: 0.17828 RPN box loss: 0.0458 RPN score loss: 0.01 RPN total loss: 0.0558 Total loss: 1.1869 timestamp: 1654943605.1678312 iteration: 37475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12275 FastRCNN class loss: 0.11272 FastRCNN total loss: 0.23547 L1 loss: 0.0000e+00 L2 loss: 0.67078 Learning rate: 0.02 Mask loss: 0.13365 RPN box loss: 0.03732 RPN score loss: 0.00825 RPN total loss: 0.04556 Total loss: 1.08547 timestamp: 1654943608.4105492 iteration: 37480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13665 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.23355 L1 loss: 0.0000e+00 L2 loss: 0.6707 Learning rate: 0.02 Mask loss: 0.17478 RPN box loss: 0.06751 RPN score loss: 0.0056 RPN total loss: 0.07311 Total loss: 1.15213 timestamp: 1654943611.5975657 iteration: 37485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1153 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.19808 L1 loss: 0.0000e+00 L2 loss: 0.67061 Learning rate: 0.02 Mask loss: 0.135 RPN box loss: 0.0122 RPN score loss: 0.00595 RPN total loss: 0.01815 Total loss: 1.02184 timestamp: 1654943614.8454828 iteration: 37490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16885 FastRCNN class loss: 0.09678 FastRCNN total loss: 0.26563 L1 loss: 0.0000e+00 L2 loss: 0.67052 Learning rate: 0.02 Mask loss: 0.18691 RPN box loss: 0.04675 RPN score loss: 0.00338 RPN total loss: 0.05013 Total loss: 1.17319 timestamp: 1654943618.0891058 iteration: 37495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16365 FastRCNN class loss: 0.08382 FastRCNN total loss: 0.24747 L1 loss: 0.0000e+00 L2 loss: 0.67044 Learning rate: 0.02 Mask loss: 0.11221 RPN box loss: 0.02651 RPN score loss: 0.005 RPN total loss: 0.03151 Total loss: 1.06163 timestamp: 1654943621.2581892 iteration: 37500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13455 FastRCNN class loss: 0.07429 FastRCNN total loss: 0.20884 L1 loss: 0.0000e+00 L2 loss: 0.67035 Learning rate: 0.02 Mask loss: 0.11363 RPN box loss: 0.02117 RPN score loss: 0.00247 RPN total loss: 0.02364 Total loss: 1.01646 timestamp: 1654943624.4562411 iteration: 37505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1442 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.23623 L1 loss: 0.0000e+00 L2 loss: 0.67026 Learning rate: 0.02 Mask loss: 0.1554 RPN box loss: 0.03226 RPN score loss: 0.00532 RPN total loss: 0.03758 Total loss: 1.09946 timestamp: 1654943627.7307367 iteration: 37510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10146 FastRCNN class loss: 0.06134 FastRCNN total loss: 0.16279 L1 loss: 0.0000e+00 L2 loss: 0.67017 Learning rate: 0.02 Mask loss: 0.10469 RPN box loss: 0.0268 RPN score loss: 0.00638 RPN total loss: 0.03317 Total loss: 0.97082 timestamp: 1654943630.9788585 iteration: 37515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14982 FastRCNN class loss: 0.1096 FastRCNN total loss: 0.25942 L1 loss: 0.0000e+00 L2 loss: 0.67009 Learning rate: 0.02 Mask loss: 0.14892 RPN box loss: 0.0376 RPN score loss: 0.01254 RPN total loss: 0.05013 Total loss: 1.12856 timestamp: 1654943634.1370692 iteration: 37520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12396 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.19057 L1 loss: 0.0000e+00 L2 loss: 0.67002 Learning rate: 0.02 Mask loss: 0.11491 RPN box loss: 0.01935 RPN score loss: 0.00578 RPN total loss: 0.02513 Total loss: 1.00063 timestamp: 1654943637.268246 iteration: 37525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14959 FastRCNN class loss: 0.07122 FastRCNN total loss: 0.2208 L1 loss: 0.0000e+00 L2 loss: 0.6699 Learning rate: 0.02 Mask loss: 0.20678 RPN box loss: 0.02051 RPN score loss: 0.01042 RPN total loss: 0.03093 Total loss: 1.12841 timestamp: 1654943640.4532044 iteration: 37530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17739 FastRCNN class loss: 0.14058 FastRCNN total loss: 0.31797 L1 loss: 0.0000e+00 L2 loss: 0.66985 Learning rate: 0.02 Mask loss: 0.21706 RPN box loss: 0.04895 RPN score loss: 0.00639 RPN total loss: 0.05534 Total loss: 1.26021 timestamp: 1654943643.690741 iteration: 37535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14778 FastRCNN class loss: 0.12231 FastRCNN total loss: 0.27009 L1 loss: 0.0000e+00 L2 loss: 0.66976 Learning rate: 0.02 Mask loss: 0.23617 RPN box loss: 0.03868 RPN score loss: 0.00575 RPN total loss: 0.04444 Total loss: 1.22046 timestamp: 1654943646.8181536 iteration: 37540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11175 FastRCNN class loss: 0.10092 FastRCNN total loss: 0.21266 L1 loss: 0.0000e+00 L2 loss: 0.66968 Learning rate: 0.02 Mask loss: 0.13649 RPN box loss: 0.01408 RPN score loss: 0.00301 RPN total loss: 0.01709 Total loss: 1.03593 timestamp: 1654943650.0232742 iteration: 37545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09006 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.16235 L1 loss: 0.0000e+00 L2 loss: 0.66959 Learning rate: 0.02 Mask loss: 0.21628 RPN box loss: 0.06315 RPN score loss: 0.00516 RPN total loss: 0.06831 Total loss: 1.11653 timestamp: 1654943653.2041144 iteration: 37550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15384 FastRCNN class loss: 0.076 FastRCNN total loss: 0.22983 L1 loss: 0.0000e+00 L2 loss: 0.66949 Learning rate: 0.02 Mask loss: 0.09229 RPN box loss: 0.04128 RPN score loss: 0.00642 RPN total loss: 0.0477 Total loss: 1.03932 timestamp: 1654943656.3849936 iteration: 37555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11679 FastRCNN class loss: 0.06426 FastRCNN total loss: 0.18105 L1 loss: 0.0000e+00 L2 loss: 0.66938 Learning rate: 0.02 Mask loss: 0.18654 RPN box loss: 0.01555 RPN score loss: 0.01767 RPN total loss: 0.03322 Total loss: 1.07018 timestamp: 1654943659.6662514 iteration: 37560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15686 FastRCNN class loss: 0.09561 FastRCNN total loss: 0.25246 L1 loss: 0.0000e+00 L2 loss: 0.6693 Learning rate: 0.02 Mask loss: 0.21771 RPN box loss: 0.05153 RPN score loss: 0.01325 RPN total loss: 0.06478 Total loss: 1.20425 timestamp: 1654943662.9101179 iteration: 37565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07104 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.13516 L1 loss: 0.0000e+00 L2 loss: 0.66919 Learning rate: 0.02 Mask loss: 0.11749 RPN box loss: 0.03246 RPN score loss: 0.00966 RPN total loss: 0.04212 Total loss: 0.96396 timestamp: 1654943666.1311119 iteration: 37570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11541 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.17486 L1 loss: 0.0000e+00 L2 loss: 0.66909 Learning rate: 0.02 Mask loss: 0.1071 RPN box loss: 0.03035 RPN score loss: 0.00462 RPN total loss: 0.03497 Total loss: 0.98602 timestamp: 1654943669.2476258 iteration: 37575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13635 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.22522 L1 loss: 0.0000e+00 L2 loss: 0.66903 Learning rate: 0.02 Mask loss: 0.14462 RPN box loss: 0.04783 RPN score loss: 0.01043 RPN total loss: 0.05827 Total loss: 1.09713 timestamp: 1654943672.4316041 iteration: 37580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19006 FastRCNN class loss: 0.07407 FastRCNN total loss: 0.26413 L1 loss: 0.0000e+00 L2 loss: 0.66895 Learning rate: 0.02 Mask loss: 0.35445 RPN box loss: 0.0484 RPN score loss: 0.00526 RPN total loss: 0.05366 Total loss: 1.3412 timestamp: 1654943675.5783515 iteration: 37585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09979 FastRCNN class loss: 0.10012 FastRCNN total loss: 0.19991 L1 loss: 0.0000e+00 L2 loss: 0.66885 Learning rate: 0.02 Mask loss: 0.14806 RPN box loss: 0.03123 RPN score loss: 0.0066 RPN total loss: 0.03783 Total loss: 1.05465 timestamp: 1654943678.7939348 iteration: 37590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13929 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.22331 L1 loss: 0.0000e+00 L2 loss: 0.66876 Learning rate: 0.02 Mask loss: 0.13216 RPN box loss: 0.0257 RPN score loss: 0.00993 RPN total loss: 0.03563 Total loss: 1.05985 timestamp: 1654943681.9717364 iteration: 37595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22567 FastRCNN class loss: 0.13066 FastRCNN total loss: 0.35634 L1 loss: 0.0000e+00 L2 loss: 0.66871 Learning rate: 0.02 Mask loss: 0.22193 RPN box loss: 0.02372 RPN score loss: 0.0084 RPN total loss: 0.03212 Total loss: 1.27909 timestamp: 1654943685.1265259 iteration: 37600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10665 FastRCNN class loss: 0.04985 FastRCNN total loss: 0.1565 L1 loss: 0.0000e+00 L2 loss: 0.66863 Learning rate: 0.02 Mask loss: 0.13983 RPN box loss: 0.01213 RPN score loss: 0.00442 RPN total loss: 0.01655 Total loss: 0.98152 timestamp: 1654943688.2377892 iteration: 37605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09696 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.17577 L1 loss: 0.0000e+00 L2 loss: 0.66852 Learning rate: 0.02 Mask loss: 0.08761 RPN box loss: 0.01338 RPN score loss: 0.00136 RPN total loss: 0.01475 Total loss: 0.94665 timestamp: 1654943691.4664063 iteration: 37610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12119 FastRCNN class loss: 0.06165 FastRCNN total loss: 0.18284 L1 loss: 0.0000e+00 L2 loss: 0.66846 Learning rate: 0.02 Mask loss: 0.07416 RPN box loss: 0.01558 RPN score loss: 0.00227 RPN total loss: 0.01785 Total loss: 0.94331 timestamp: 1654943694.7382252 iteration: 37615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16772 FastRCNN class loss: 0.11974 FastRCNN total loss: 0.28745 L1 loss: 0.0000e+00 L2 loss: 0.66838 Learning rate: 0.02 Mask loss: 0.15543 RPN box loss: 0.03664 RPN score loss: 0.01308 RPN total loss: 0.04972 Total loss: 1.16097 timestamp: 1654943697.9706035 iteration: 37620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06236 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.10627 L1 loss: 0.0000e+00 L2 loss: 0.66829 Learning rate: 0.02 Mask loss: 0.12329 RPN box loss: 0.06254 RPN score loss: 0.00705 RPN total loss: 0.0696 Total loss: 0.96745 timestamp: 1654943701.2947161 iteration: 37625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13847 FastRCNN class loss: 0.0976 FastRCNN total loss: 0.23607 L1 loss: 0.0000e+00 L2 loss: 0.6682 Learning rate: 0.02 Mask loss: 0.20329 RPN box loss: 0.05207 RPN score loss: 0.0085 RPN total loss: 0.06056 Total loss: 1.16813 timestamp: 1654943704.4424448 iteration: 37630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15633 FastRCNN class loss: 0.11114 FastRCNN total loss: 0.26747 L1 loss: 0.0000e+00 L2 loss: 0.66812 Learning rate: 0.02 Mask loss: 0.2004 RPN box loss: 0.03286 RPN score loss: 0.00729 RPN total loss: 0.04015 Total loss: 1.17615 timestamp: 1654943707.689603 iteration: 37635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19599 FastRCNN class loss: 0.0919 FastRCNN total loss: 0.28789 L1 loss: 0.0000e+00 L2 loss: 0.66806 Learning rate: 0.02 Mask loss: 0.17724 RPN box loss: 0.02107 RPN score loss: 0.00511 RPN total loss: 0.02617 Total loss: 1.15936 timestamp: 1654943710.8747592 iteration: 37640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18047 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.28177 L1 loss: 0.0000e+00 L2 loss: 0.66796 Learning rate: 0.02 Mask loss: 0.14612 RPN box loss: 0.02231 RPN score loss: 0.00272 RPN total loss: 0.02503 Total loss: 1.12088 timestamp: 1654943714.1389747 iteration: 37645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04355 FastRCNN class loss: 0.04346 FastRCNN total loss: 0.087 L1 loss: 0.0000e+00 L2 loss: 0.6679 Learning rate: 0.02 Mask loss: 0.15292 RPN box loss: 0.02616 RPN score loss: 0.00264 RPN total loss: 0.0288 Total loss: 0.93663 timestamp: 1654943717.4026287 iteration: 37650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0815 FastRCNN class loss: 0.02404 FastRCNN total loss: 0.10554 L1 loss: 0.0000e+00 L2 loss: 0.66784 Learning rate: 0.02 Mask loss: 0.10818 RPN box loss: 0.00502 RPN score loss: 0.00177 RPN total loss: 0.00679 Total loss: 0.88835 timestamp: 1654943720.6330593 iteration: 37655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17108 FastRCNN class loss: 0.07025 FastRCNN total loss: 0.24133 L1 loss: 0.0000e+00 L2 loss: 0.66775 Learning rate: 0.02 Mask loss: 0.10882 RPN box loss: 0.01526 RPN score loss: 0.00173 RPN total loss: 0.01699 Total loss: 1.03489 timestamp: 1654943723.7955987 iteration: 37660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1495 FastRCNN class loss: 0.07896 FastRCNN total loss: 0.22846 L1 loss: 0.0000e+00 L2 loss: 0.66767 Learning rate: 0.02 Mask loss: 0.14739 RPN box loss: 0.03917 RPN score loss: 0.0031 RPN total loss: 0.04227 Total loss: 1.0858 timestamp: 1654943726.9118438 iteration: 37665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13875 FastRCNN class loss: 0.06414 FastRCNN total loss: 0.2029 L1 loss: 0.0000e+00 L2 loss: 0.66759 Learning rate: 0.02 Mask loss: 0.13008 RPN box loss: 0.04103 RPN score loss: 0.00201 RPN total loss: 0.04304 Total loss: 1.04361 timestamp: 1654943730.093853 iteration: 37670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15823 FastRCNN class loss: 0.0902 FastRCNN total loss: 0.24842 L1 loss: 0.0000e+00 L2 loss: 0.66747 Learning rate: 0.02 Mask loss: 0.17686 RPN box loss: 0.02041 RPN score loss: 0.01148 RPN total loss: 0.0319 Total loss: 1.12464 timestamp: 1654943733.308177 iteration: 37675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20352 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.27808 L1 loss: 0.0000e+00 L2 loss: 0.66737 Learning rate: 0.02 Mask loss: 0.19724 RPN box loss: 0.02376 RPN score loss: 0.00418 RPN total loss: 0.02794 Total loss: 1.17062 timestamp: 1654943736.5502982 iteration: 37680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11745 FastRCNN class loss: 0.04502 FastRCNN total loss: 0.16247 L1 loss: 0.0000e+00 L2 loss: 0.66729 Learning rate: 0.02 Mask loss: 0.16062 RPN box loss: 0.02445 RPN score loss: 0.00745 RPN total loss: 0.03191 Total loss: 1.02229 timestamp: 1654943739.7526066 iteration: 37685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.05276 FastRCNN total loss: 0.13588 L1 loss: 0.0000e+00 L2 loss: 0.66718 Learning rate: 0.02 Mask loss: 0.15241 RPN box loss: 0.04196 RPN score loss: 0.01193 RPN total loss: 0.05388 Total loss: 1.00936 timestamp: 1654943743.0177393 iteration: 37690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11748 FastRCNN class loss: 0.10984 FastRCNN total loss: 0.22731 L1 loss: 0.0000e+00 L2 loss: 0.6671 Learning rate: 0.02 Mask loss: 0.22123 RPN box loss: 0.0258 RPN score loss: 0.00183 RPN total loss: 0.02763 Total loss: 1.14328 timestamp: 1654943746.251905 iteration: 37695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13095 FastRCNN class loss: 0.1147 FastRCNN total loss: 0.24564 L1 loss: 0.0000e+00 L2 loss: 0.66703 Learning rate: 0.02 Mask loss: 0.17058 RPN box loss: 0.02019 RPN score loss: 0.00752 RPN total loss: 0.02771 Total loss: 1.11097 timestamp: 1654943749.4447622 iteration: 37700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19168 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.27313 L1 loss: 0.0000e+00 L2 loss: 0.66695 Learning rate: 0.02 Mask loss: 0.11577 RPN box loss: 0.01878 RPN score loss: 0.00428 RPN total loss: 0.02306 Total loss: 1.07891 timestamp: 1654943752.6655726 iteration: 37705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1493 FastRCNN class loss: 0.08194 FastRCNN total loss: 0.23123 L1 loss: 0.0000e+00 L2 loss: 0.66689 Learning rate: 0.02 Mask loss: 0.15259 RPN box loss: 0.03016 RPN score loss: 0.00714 RPN total loss: 0.03729 Total loss: 1.08801 timestamp: 1654943755.874578 iteration: 37710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12567 FastRCNN class loss: 0.07459 FastRCNN total loss: 0.20026 L1 loss: 0.0000e+00 L2 loss: 0.66678 Learning rate: 0.02 Mask loss: 0.23201 RPN box loss: 0.10439 RPN score loss: 0.00787 RPN total loss: 0.11225 Total loss: 1.2113 timestamp: 1654943759.0481155 iteration: 37715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18353 FastRCNN class loss: 0.09273 FastRCNN total loss: 0.27627 L1 loss: 0.0000e+00 L2 loss: 0.66669 Learning rate: 0.02 Mask loss: 0.28431 RPN box loss: 0.01752 RPN score loss: 0.00501 RPN total loss: 0.02253 Total loss: 1.24981 timestamp: 1654943762.1538212 iteration: 37720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16121 FastRCNN class loss: 0.09719 FastRCNN total loss: 0.25841 L1 loss: 0.0000e+00 L2 loss: 0.66664 Learning rate: 0.02 Mask loss: 0.16519 RPN box loss: 0.02879 RPN score loss: 0.0113 RPN total loss: 0.04009 Total loss: 1.13033 timestamp: 1654943765.354809 iteration: 37725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09113 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.15782 L1 loss: 0.0000e+00 L2 loss: 0.66655 Learning rate: 0.02 Mask loss: 0.10613 RPN box loss: 0.02238 RPN score loss: 0.00826 RPN total loss: 0.03064 Total loss: 0.96113 timestamp: 1654943768.4926026 iteration: 37730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13202 FastRCNN class loss: 0.10042 FastRCNN total loss: 0.23244 L1 loss: 0.0000e+00 L2 loss: 0.66645 Learning rate: 0.02 Mask loss: 0.19205 RPN box loss: 0.03938 RPN score loss: 0.02115 RPN total loss: 0.06053 Total loss: 1.15147 timestamp: 1654943771.6997135 iteration: 37735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13172 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.66635 Learning rate: 0.02 Mask loss: 0.09133 RPN box loss: 0.01995 RPN score loss: 0.00432 RPN total loss: 0.02427 Total loss: 0.97552 timestamp: 1654943774.9363039 iteration: 37740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2118 FastRCNN class loss: 0.07908 FastRCNN total loss: 0.29088 L1 loss: 0.0000e+00 L2 loss: 0.66625 Learning rate: 0.02 Mask loss: 0.09007 RPN box loss: 0.01569 RPN score loss: 0.00285 RPN total loss: 0.01854 Total loss: 1.06574 timestamp: 1654943778.0958235 iteration: 37745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13619 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.20472 L1 loss: 0.0000e+00 L2 loss: 0.66618 Learning rate: 0.02 Mask loss: 0.11426 RPN box loss: 0.03175 RPN score loss: 0.0049 RPN total loss: 0.03665 Total loss: 1.0218 timestamp: 1654943781.400887 iteration: 37750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11311 FastRCNN class loss: 0.06623 FastRCNN total loss: 0.17934 L1 loss: 0.0000e+00 L2 loss: 0.6661 Learning rate: 0.02 Mask loss: 0.12149 RPN box loss: 0.02773 RPN score loss: 0.00553 RPN total loss: 0.03327 Total loss: 1.0002 timestamp: 1654943784.5851605 iteration: 37755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16366 FastRCNN class loss: 0.09379 FastRCNN total loss: 0.25745 L1 loss: 0.0000e+00 L2 loss: 0.666 Learning rate: 0.02 Mask loss: 0.14349 RPN box loss: 0.02574 RPN score loss: 0.00538 RPN total loss: 0.03112 Total loss: 1.09806 timestamp: 1654943787.7629335 iteration: 37760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15081 FastRCNN class loss: 0.11686 FastRCNN total loss: 0.26767 L1 loss: 0.0000e+00 L2 loss: 0.66591 Learning rate: 0.02 Mask loss: 0.21484 RPN box loss: 0.07674 RPN score loss: 0.01082 RPN total loss: 0.08757 Total loss: 1.23599 timestamp: 1654943790.951225 iteration: 37765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13634 FastRCNN class loss: 0.067 FastRCNN total loss: 0.20334 L1 loss: 0.0000e+00 L2 loss: 0.66586 Learning rate: 0.02 Mask loss: 0.11717 RPN box loss: 0.01402 RPN score loss: 0.00228 RPN total loss: 0.0163 Total loss: 1.00267 timestamp: 1654943794.0917459 iteration: 37770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09282 FastRCNN class loss: 0.064 FastRCNN total loss: 0.15682 L1 loss: 0.0000e+00 L2 loss: 0.6658 Learning rate: 0.02 Mask loss: 0.08853 RPN box loss: 0.05551 RPN score loss: 0.0079 RPN total loss: 0.06341 Total loss: 0.97457 timestamp: 1654943797.3473976 iteration: 37775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12387 FastRCNN class loss: 0.05574 FastRCNN total loss: 0.1796 L1 loss: 0.0000e+00 L2 loss: 0.66572 Learning rate: 0.02 Mask loss: 0.13612 RPN box loss: 0.01775 RPN score loss: 0.007 RPN total loss: 0.02475 Total loss: 1.0062 timestamp: 1654943800.4810498 iteration: 37780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15197 FastRCNN class loss: 0.06244 FastRCNN total loss: 0.2144 L1 loss: 0.0000e+00 L2 loss: 0.66563 Learning rate: 0.02 Mask loss: 0.16115 RPN box loss: 0.02702 RPN score loss: 0.0065 RPN total loss: 0.03352 Total loss: 1.07471 timestamp: 1654943803.754001 iteration: 37785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09231 FastRCNN class loss: 0.11106 FastRCNN total loss: 0.20337 L1 loss: 0.0000e+00 L2 loss: 0.66552 Learning rate: 0.02 Mask loss: 0.14987 RPN box loss: 0.01694 RPN score loss: 0.00937 RPN total loss: 0.02631 Total loss: 1.04507 timestamp: 1654943807.0528991 iteration: 37790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11977 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.19642 L1 loss: 0.0000e+00 L2 loss: 0.66545 Learning rate: 0.02 Mask loss: 0.15937 RPN box loss: 0.02324 RPN score loss: 0.00365 RPN total loss: 0.02688 Total loss: 1.04812 timestamp: 1654943810.184 iteration: 37795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.09884 FastRCNN total loss: 0.2178 L1 loss: 0.0000e+00 L2 loss: 0.66536 Learning rate: 0.02 Mask loss: 0.17165 RPN box loss: 0.0152 RPN score loss: 0.00275 RPN total loss: 0.01795 Total loss: 1.07276 timestamp: 1654943813.4795134 iteration: 37800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08394 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.14317 L1 loss: 0.0000e+00 L2 loss: 0.66526 Learning rate: 0.02 Mask loss: 0.09713 RPN box loss: 0.00764 RPN score loss: 0.0065 RPN total loss: 0.01414 Total loss: 0.9197 timestamp: 1654943816.6044874 iteration: 37805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19163 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.2495 L1 loss: 0.0000e+00 L2 loss: 0.66519 Learning rate: 0.02 Mask loss: 0.13215 RPN box loss: 0.04779 RPN score loss: 0.00288 RPN total loss: 0.05066 Total loss: 1.09751 timestamp: 1654943819.797893 iteration: 37810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13448 FastRCNN class loss: 0.06032 FastRCNN total loss: 0.1948 L1 loss: 0.0000e+00 L2 loss: 0.66511 Learning rate: 0.02 Mask loss: 0.10803 RPN box loss: 0.01835 RPN score loss: 0.00607 RPN total loss: 0.02442 Total loss: 0.99236 timestamp: 1654943823.0167203 iteration: 37815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14318 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.21723 L1 loss: 0.0000e+00 L2 loss: 0.66504 Learning rate: 0.02 Mask loss: 0.11093 RPN box loss: 0.02192 RPN score loss: 0.00751 RPN total loss: 0.02943 Total loss: 1.02263 timestamp: 1654943826.1728103 iteration: 37820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15522 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.22887 L1 loss: 0.0000e+00 L2 loss: 0.66497 Learning rate: 0.02 Mask loss: 0.14373 RPN box loss: 0.01383 RPN score loss: 0.0044 RPN total loss: 0.01824 Total loss: 1.0558 timestamp: 1654943829.3796158 iteration: 37825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10353 FastRCNN class loss: 0.11289 FastRCNN total loss: 0.21641 L1 loss: 0.0000e+00 L2 loss: 0.66485 Learning rate: 0.02 Mask loss: 0.22959 RPN box loss: 0.02717 RPN score loss: 0.00379 RPN total loss: 0.03096 Total loss: 1.14182 timestamp: 1654943832.6244574 iteration: 37830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14006 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.19957 L1 loss: 0.0000e+00 L2 loss: 0.66477 Learning rate: 0.02 Mask loss: 0.11483 RPN box loss: 0.01754 RPN score loss: 0.00327 RPN total loss: 0.02081 Total loss: 0.99998 timestamp: 1654943835.8700106 iteration: 37835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10121 FastRCNN class loss: 0.09437 FastRCNN total loss: 0.19558 L1 loss: 0.0000e+00 L2 loss: 0.66471 Learning rate: 0.02 Mask loss: 0.12053 RPN box loss: 0.02466 RPN score loss: 0.00282 RPN total loss: 0.02747 Total loss: 1.00829 timestamp: 1654943839.0815144 iteration: 37840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13299 FastRCNN class loss: 0.06083 FastRCNN total loss: 0.19382 L1 loss: 0.0000e+00 L2 loss: 0.66464 Learning rate: 0.02 Mask loss: 0.15763 RPN box loss: 0.0412 RPN score loss: 0.00498 RPN total loss: 0.04618 Total loss: 1.06228 timestamp: 1654943842.2500834 iteration: 37845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16169 FastRCNN class loss: 0.07672 FastRCNN total loss: 0.23841 L1 loss: 0.0000e+00 L2 loss: 0.66457 Learning rate: 0.02 Mask loss: 0.10964 RPN box loss: 0.01464 RPN score loss: 0.00449 RPN total loss: 0.01913 Total loss: 1.03173 timestamp: 1654943845.408778 iteration: 37850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14676 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.2367 L1 loss: 0.0000e+00 L2 loss: 0.66448 Learning rate: 0.02 Mask loss: 0.15879 RPN box loss: 0.04776 RPN score loss: 0.00556 RPN total loss: 0.05333 Total loss: 1.11329 timestamp: 1654943848.6570437 iteration: 37855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13766 FastRCNN class loss: 0.0528 FastRCNN total loss: 0.19046 L1 loss: 0.0000e+00 L2 loss: 0.66438 Learning rate: 0.02 Mask loss: 0.10904 RPN box loss: 0.01369 RPN score loss: 0.0066 RPN total loss: 0.02029 Total loss: 0.98418 timestamp: 1654943851.8514328 iteration: 37860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07891 FastRCNN class loss: 0.05194 FastRCNN total loss: 0.13086 L1 loss: 0.0000e+00 L2 loss: 0.66432 Learning rate: 0.02 Mask loss: 0.11442 RPN box loss: 0.01746 RPN score loss: 0.00257 RPN total loss: 0.02002 Total loss: 0.92963 timestamp: 1654943855.041839 iteration: 37865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14105 FastRCNN class loss: 0.08713 FastRCNN total loss: 0.22817 L1 loss: 0.0000e+00 L2 loss: 0.66425 Learning rate: 0.02 Mask loss: 0.13733 RPN box loss: 0.03531 RPN score loss: 0.00884 RPN total loss: 0.04414 Total loss: 1.0739 timestamp: 1654943858.2961764 iteration: 37870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0838 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.15496 L1 loss: 0.0000e+00 L2 loss: 0.66417 Learning rate: 0.02 Mask loss: 0.18005 RPN box loss: 0.02601 RPN score loss: 0.00179 RPN total loss: 0.0278 Total loss: 1.02698 timestamp: 1654943861.478876 iteration: 37875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13218 FastRCNN class loss: 0.05458 FastRCNN total loss: 0.18676 L1 loss: 0.0000e+00 L2 loss: 0.66408 Learning rate: 0.02 Mask loss: 0.13171 RPN box loss: 0.0395 RPN score loss: 0.00152 RPN total loss: 0.04102 Total loss: 1.02357 timestamp: 1654943864.6705737 iteration: 37880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08033 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.13422 L1 loss: 0.0000e+00 L2 loss: 0.66398 Learning rate: 0.02 Mask loss: 0.17181 RPN box loss: 0.0176 RPN score loss: 0.00435 RPN total loss: 0.02195 Total loss: 0.99195 timestamp: 1654943867.876213 iteration: 37885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08903 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.16718 L1 loss: 0.0000e+00 L2 loss: 0.6639 Learning rate: 0.02 Mask loss: 0.23293 RPN box loss: 0.03128 RPN score loss: 0.00501 RPN total loss: 0.03629 Total loss: 1.1003 timestamp: 1654943871.1125748 iteration: 37890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10221 FastRCNN class loss: 0.06271 FastRCNN total loss: 0.16493 L1 loss: 0.0000e+00 L2 loss: 0.66384 Learning rate: 0.02 Mask loss: 0.15628 RPN box loss: 0.03291 RPN score loss: 0.00365 RPN total loss: 0.03656 Total loss: 1.02161 timestamp: 1654943874.3010652 iteration: 37895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13214 FastRCNN class loss: 0.06608 FastRCNN total loss: 0.19821 L1 loss: 0.0000e+00 L2 loss: 0.66376 Learning rate: 0.02 Mask loss: 0.1187 RPN box loss: 0.03183 RPN score loss: 0.00633 RPN total loss: 0.03816 Total loss: 1.01883 timestamp: 1654943877.5088935 iteration: 37900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0746 FastRCNN class loss: 0.06987 FastRCNN total loss: 0.14446 L1 loss: 0.0000e+00 L2 loss: 0.66367 Learning rate: 0.02 Mask loss: 0.14491 RPN box loss: 0.00574 RPN score loss: 0.00293 RPN total loss: 0.00867 Total loss: 0.96172 timestamp: 1654943880.7120194 iteration: 37905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12752 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.23032 L1 loss: 0.0000e+00 L2 loss: 0.66358 Learning rate: 0.02 Mask loss: 0.16159 RPN box loss: 0.03333 RPN score loss: 0.00974 RPN total loss: 0.04308 Total loss: 1.09856 timestamp: 1654943883.884802 iteration: 37910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08708 FastRCNN class loss: 0.04936 FastRCNN total loss: 0.13645 L1 loss: 0.0000e+00 L2 loss: 0.66349 Learning rate: 0.02 Mask loss: 0.10544 RPN box loss: 0.01263 RPN score loss: 0.00568 RPN total loss: 0.01831 Total loss: 0.92369 timestamp: 1654943887.0611136 iteration: 37915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20309 FastRCNN class loss: 0.08338 FastRCNN total loss: 0.28647 L1 loss: 0.0000e+00 L2 loss: 0.6634 Learning rate: 0.02 Mask loss: 0.16705 RPN box loss: 0.02311 RPN score loss: 0.00631 RPN total loss: 0.02942 Total loss: 1.14634 timestamp: 1654943890.2377443 iteration: 37920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13711 FastRCNN class loss: 0.06615 FastRCNN total loss: 0.20326 L1 loss: 0.0000e+00 L2 loss: 0.66331 Learning rate: 0.02 Mask loss: 0.12543 RPN box loss: 0.01633 RPN score loss: 0.00347 RPN total loss: 0.0198 Total loss: 1.01181 timestamp: 1654943893.4613526 iteration: 37925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10808 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.16969 L1 loss: 0.0000e+00 L2 loss: 0.66324 Learning rate: 0.02 Mask loss: 0.13668 RPN box loss: 0.01504 RPN score loss: 0.00248 RPN total loss: 0.01751 Total loss: 0.98712 timestamp: 1654943896.6524599 iteration: 37930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13303 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.20884 L1 loss: 0.0000e+00 L2 loss: 0.66316 Learning rate: 0.02 Mask loss: 0.12252 RPN box loss: 0.0242 RPN score loss: 0.00212 RPN total loss: 0.02632 Total loss: 1.02084 timestamp: 1654943899.8777292 iteration: 37935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08772 FastRCNN class loss: 0.07872 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.66307 Learning rate: 0.02 Mask loss: 0.10921 RPN box loss: 0.01329 RPN score loss: 0.00303 RPN total loss: 0.01632 Total loss: 0.95504 timestamp: 1654943903.0907593 iteration: 37940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11411 FastRCNN class loss: 0.09186 FastRCNN total loss: 0.20597 L1 loss: 0.0000e+00 L2 loss: 0.663 Learning rate: 0.02 Mask loss: 0.12461 RPN box loss: 0.0048 RPN score loss: 0.00145 RPN total loss: 0.00625 Total loss: 0.99982 timestamp: 1654943906.3088439 iteration: 37945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15067 FastRCNN class loss: 0.05437 FastRCNN total loss: 0.20503 L1 loss: 0.0000e+00 L2 loss: 0.66289 Learning rate: 0.02 Mask loss: 0.10578 RPN box loss: 0.02775 RPN score loss: 0.00484 RPN total loss: 0.03259 Total loss: 1.00629 timestamp: 1654943909.4555705 iteration: 37950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06063 FastRCNN class loss: 0.04667 FastRCNN total loss: 0.1073 L1 loss: 0.0000e+00 L2 loss: 0.6628 Learning rate: 0.02 Mask loss: 0.1123 RPN box loss: 0.01691 RPN score loss: 0.00657 RPN total loss: 0.02349 Total loss: 0.90588 timestamp: 1654943912.6357467 iteration: 37955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12406 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.18797 L1 loss: 0.0000e+00 L2 loss: 0.66273 Learning rate: 0.02 Mask loss: 0.17327 RPN box loss: 0.02886 RPN score loss: 0.00798 RPN total loss: 0.03684 Total loss: 1.06081 timestamp: 1654943915.862139 iteration: 37960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16109 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.23106 L1 loss: 0.0000e+00 L2 loss: 0.66263 Learning rate: 0.02 Mask loss: 0.1379 RPN box loss: 0.13366 RPN score loss: 0.00668 RPN total loss: 0.14035 Total loss: 1.17194 timestamp: 1654943919.0628092 iteration: 37965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.091 FastRCNN class loss: 0.04792 FastRCNN total loss: 0.13892 L1 loss: 0.0000e+00 L2 loss: 0.66255 Learning rate: 0.02 Mask loss: 0.08819 RPN box loss: 0.02394 RPN score loss: 0.00742 RPN total loss: 0.03136 Total loss: 0.92102 timestamp: 1654943922.2143273 iteration: 37970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15809 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.22002 L1 loss: 0.0000e+00 L2 loss: 0.66247 Learning rate: 0.02 Mask loss: 0.13703 RPN box loss: 0.02186 RPN score loss: 0.0047 RPN total loss: 0.02655 Total loss: 1.04607 timestamp: 1654943925.3316362 iteration: 37975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1752 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.27906 L1 loss: 0.0000e+00 L2 loss: 0.66237 Learning rate: 0.02 Mask loss: 0.12805 RPN box loss: 0.0634 RPN score loss: 0.00604 RPN total loss: 0.06945 Total loss: 1.13892 timestamp: 1654943928.5476952 iteration: 37980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11173 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.18088 L1 loss: 0.0000e+00 L2 loss: 0.66227 Learning rate: 0.02 Mask loss: 0.1259 RPN box loss: 0.01909 RPN score loss: 0.00312 RPN total loss: 0.02221 Total loss: 0.99126 timestamp: 1654943931.719031 iteration: 37985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15012 FastRCNN class loss: 0.09954 FastRCNN total loss: 0.24966 L1 loss: 0.0000e+00 L2 loss: 0.66221 Learning rate: 0.02 Mask loss: 0.14401 RPN box loss: 0.01475 RPN score loss: 0.01025 RPN total loss: 0.025 Total loss: 1.08088 timestamp: 1654943934.957504 iteration: 37990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17361 FastRCNN class loss: 0.09663 FastRCNN total loss: 0.27025 L1 loss: 0.0000e+00 L2 loss: 0.66212 Learning rate: 0.02 Mask loss: 0.12067 RPN box loss: 0.02536 RPN score loss: 0.00625 RPN total loss: 0.03162 Total loss: 1.08466 timestamp: 1654943938.179882 iteration: 37995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1456 FastRCNN class loss: 0.07463 FastRCNN total loss: 0.22023 L1 loss: 0.0000e+00 L2 loss: 0.66207 Learning rate: 0.02 Mask loss: 0.15403 RPN box loss: 0.07095 RPN score loss: 0.00845 RPN total loss: 0.07939 Total loss: 1.11572 timestamp: 1654943941.3292842 iteration: 38000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11322 FastRCNN class loss: 0.04274 FastRCNN total loss: 0.15595 L1 loss: 0.0000e+00 L2 loss: 0.662 Learning rate: 0.02 Mask loss: 0.14934 RPN box loss: 0.01591 RPN score loss: 0.01117 RPN total loss: 0.02707 Total loss: 0.99436 timestamp: 1654943944.5100787 iteration: 38005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15968 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.22907 L1 loss: 0.0000e+00 L2 loss: 0.66192 Learning rate: 0.02 Mask loss: 0.08677 RPN box loss: 0.03071 RPN score loss: 0.00594 RPN total loss: 0.03665 Total loss: 1.01441 timestamp: 1654943947.7138813 iteration: 38010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14315 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.21237 L1 loss: 0.0000e+00 L2 loss: 0.66184 Learning rate: 0.02 Mask loss: 0.1611 RPN box loss: 0.05153 RPN score loss: 0.00338 RPN total loss: 0.05491 Total loss: 1.09023 timestamp: 1654943950.8510432 iteration: 38015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12248 FastRCNN class loss: 0.08566 FastRCNN total loss: 0.20814 L1 loss: 0.0000e+00 L2 loss: 0.66174 Learning rate: 0.02 Mask loss: 0.11104 RPN box loss: 0.02518 RPN score loss: 0.01072 RPN total loss: 0.03589 Total loss: 1.0168 timestamp: 1654943954.039106 iteration: 38020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10749 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.18022 L1 loss: 0.0000e+00 L2 loss: 0.66163 Learning rate: 0.02 Mask loss: 0.13047 RPN box loss: 0.05799 RPN score loss: 0.00442 RPN total loss: 0.06241 Total loss: 1.03472 timestamp: 1654943957.2722583 iteration: 38025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16885 FastRCNN class loss: 0.08583 FastRCNN total loss: 0.25468 L1 loss: 0.0000e+00 L2 loss: 0.66155 Learning rate: 0.02 Mask loss: 0.18413 RPN box loss: 0.03431 RPN score loss: 0.00814 RPN total loss: 0.04245 Total loss: 1.14281 timestamp: 1654943960.4629903 iteration: 38030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18238 FastRCNN class loss: 0.0991 FastRCNN total loss: 0.28148 L1 loss: 0.0000e+00 L2 loss: 0.66146 Learning rate: 0.02 Mask loss: 0.11991 RPN box loss: 0.01446 RPN score loss: 0.00965 RPN total loss: 0.0241 Total loss: 1.08695 timestamp: 1654943963.6653178 iteration: 38035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13133 FastRCNN class loss: 0.12398 FastRCNN total loss: 0.25531 L1 loss: 0.0000e+00 L2 loss: 0.66138 Learning rate: 0.02 Mask loss: 0.19779 RPN box loss: 0.04389 RPN score loss: 0.01169 RPN total loss: 0.05558 Total loss: 1.17006 timestamp: 1654943966.9369004 iteration: 38040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06715 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.12005 L1 loss: 0.0000e+00 L2 loss: 0.66133 Learning rate: 0.02 Mask loss: 0.08126 RPN box loss: 0.00617 RPN score loss: 0.00285 RPN total loss: 0.00902 Total loss: 0.87165 timestamp: 1654943970.1751437 iteration: 38045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19791 FastRCNN class loss: 0.11331 FastRCNN total loss: 0.31123 L1 loss: 0.0000e+00 L2 loss: 0.66123 Learning rate: 0.02 Mask loss: 0.18694 RPN box loss: 0.02115 RPN score loss: 0.00553 RPN total loss: 0.02669 Total loss: 1.18608 timestamp: 1654943973.376875 iteration: 38050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10995 FastRCNN class loss: 0.06585 FastRCNN total loss: 0.1758 L1 loss: 0.0000e+00 L2 loss: 0.66114 Learning rate: 0.02 Mask loss: 0.13275 RPN box loss: 0.00726 RPN score loss: 0.00735 RPN total loss: 0.01461 Total loss: 0.98429 timestamp: 1654943976.5834782 iteration: 38055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11952 FastRCNN class loss: 0.06657 FastRCNN total loss: 0.18609 L1 loss: 0.0000e+00 L2 loss: 0.66105 Learning rate: 0.02 Mask loss: 0.15817 RPN box loss: 0.01938 RPN score loss: 0.00086 RPN total loss: 0.02024 Total loss: 1.02555 timestamp: 1654943979.8205526 iteration: 38060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06718 FastRCNN class loss: 0.08139 FastRCNN total loss: 0.14857 L1 loss: 0.0000e+00 L2 loss: 0.66095 Learning rate: 0.02 Mask loss: 0.07667 RPN box loss: 0.00913 RPN score loss: 0.00346 RPN total loss: 0.01259 Total loss: 0.89878 timestamp: 1654943983.0499995 iteration: 38065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19163 FastRCNN class loss: 0.11894 FastRCNN total loss: 0.31057 L1 loss: 0.0000e+00 L2 loss: 0.66085 Learning rate: 0.02 Mask loss: 0.14278 RPN box loss: 0.04924 RPN score loss: 0.00754 RPN total loss: 0.05678 Total loss: 1.17098 timestamp: 1654943986.2918677 iteration: 38070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11697 FastRCNN class loss: 0.09856 FastRCNN total loss: 0.21553 L1 loss: 0.0000e+00 L2 loss: 0.66077 Learning rate: 0.02 Mask loss: 0.19406 RPN box loss: 0.02818 RPN score loss: 0.00216 RPN total loss: 0.03034 Total loss: 1.10069 timestamp: 1654943989.4710445 iteration: 38075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16148 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.2434 L1 loss: 0.0000e+00 L2 loss: 0.66066 Learning rate: 0.02 Mask loss: 0.18043 RPN box loss: 0.02297 RPN score loss: 0.00203 RPN total loss: 0.025 Total loss: 1.10948 timestamp: 1654943992.6626508 iteration: 38080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16506 FastRCNN class loss: 0.09126 FastRCNN total loss: 0.25632 L1 loss: 0.0000e+00 L2 loss: 0.66057 Learning rate: 0.02 Mask loss: 0.16811 RPN box loss: 0.03722 RPN score loss: 0.00564 RPN total loss: 0.04287 Total loss: 1.12788 timestamp: 1654943995.9357178 iteration: 38085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07986 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.12951 L1 loss: 0.0000e+00 L2 loss: 0.66051 Learning rate: 0.02 Mask loss: 0.27167 RPN box loss: 0.01226 RPN score loss: 0.00341 RPN total loss: 0.01567 Total loss: 1.07736 timestamp: 1654943999.1536329 iteration: 38090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11388 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.17128 L1 loss: 0.0000e+00 L2 loss: 0.66044 Learning rate: 0.02 Mask loss: 0.12143 RPN box loss: 0.01235 RPN score loss: 0.00361 RPN total loss: 0.01595 Total loss: 0.9691 timestamp: 1654944002.3241544 iteration: 38095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08367 FastRCNN class loss: 0.08159 FastRCNN total loss: 0.16526 L1 loss: 0.0000e+00 L2 loss: 0.66034 Learning rate: 0.02 Mask loss: 0.11133 RPN box loss: 0.04783 RPN score loss: 0.00558 RPN total loss: 0.05341 Total loss: 0.99035 timestamp: 1654944005.5775535 iteration: 38100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08617 FastRCNN class loss: 0.05461 FastRCNN total loss: 0.14078 L1 loss: 0.0000e+00 L2 loss: 0.66027 Learning rate: 0.02 Mask loss: 0.11907 RPN box loss: 0.02162 RPN score loss: 0.00299 RPN total loss: 0.02461 Total loss: 0.94474 timestamp: 1654944008.814058 iteration: 38105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13136 FastRCNN class loss: 0.10061 FastRCNN total loss: 0.23198 L1 loss: 0.0000e+00 L2 loss: 0.66018 Learning rate: 0.02 Mask loss: 0.19509 RPN box loss: 0.04702 RPN score loss: 0.01347 RPN total loss: 0.06049 Total loss: 1.14773 timestamp: 1654944012.0435998 iteration: 38110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09223 FastRCNN class loss: 0.05368 FastRCNN total loss: 0.14591 L1 loss: 0.0000e+00 L2 loss: 0.66012 Learning rate: 0.02 Mask loss: 0.13806 RPN box loss: 0.03301 RPN score loss: 0.00421 RPN total loss: 0.03722 Total loss: 0.9813 timestamp: 1654944015.189672 iteration: 38115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1383 FastRCNN class loss: 0.07109 FastRCNN total loss: 0.20939 L1 loss: 0.0000e+00 L2 loss: 0.66003 Learning rate: 0.02 Mask loss: 0.1248 RPN box loss: 0.05568 RPN score loss: 0.00298 RPN total loss: 0.05866 Total loss: 1.05287 timestamp: 1654944018.387946 iteration: 38120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10272 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.16982 L1 loss: 0.0000e+00 L2 loss: 0.65992 Learning rate: 0.02 Mask loss: 0.12841 RPN box loss: 0.01975 RPN score loss: 0.00352 RPN total loss: 0.02327 Total loss: 0.98143 timestamp: 1654944021.6428452 iteration: 38125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17582 FastRCNN class loss: 0.16688 FastRCNN total loss: 0.3427 L1 loss: 0.0000e+00 L2 loss: 0.65987 Learning rate: 0.02 Mask loss: 0.20248 RPN box loss: 0.03629 RPN score loss: 0.01544 RPN total loss: 0.05172 Total loss: 1.25677 timestamp: 1654944024.8797293 iteration: 38130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09239 FastRCNN class loss: 0.04411 FastRCNN total loss: 0.1365 L1 loss: 0.0000e+00 L2 loss: 0.65979 Learning rate: 0.02 Mask loss: 0.09366 RPN box loss: 0.02813 RPN score loss: 0.00415 RPN total loss: 0.03228 Total loss: 0.92223 timestamp: 1654944028.093761 iteration: 38135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07426 FastRCNN class loss: 0.04315 FastRCNN total loss: 0.11741 L1 loss: 0.0000e+00 L2 loss: 0.65968 Learning rate: 0.02 Mask loss: 0.15629 RPN box loss: 0.01738 RPN score loss: 0.00632 RPN total loss: 0.02369 Total loss: 0.95708 timestamp: 1654944031.2764213 iteration: 38140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06619 FastRCNN class loss: 0.06874 FastRCNN total loss: 0.13492 L1 loss: 0.0000e+00 L2 loss: 0.65957 Learning rate: 0.02 Mask loss: 0.10016 RPN box loss: 0.03318 RPN score loss: 0.00848 RPN total loss: 0.04166 Total loss: 0.93632 timestamp: 1654944034.392393 iteration: 38145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09691 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.17367 L1 loss: 0.0000e+00 L2 loss: 0.6595 Learning rate: 0.02 Mask loss: 0.26516 RPN box loss: 0.03313 RPN score loss: 0.01121 RPN total loss: 0.04434 Total loss: 1.14267 timestamp: 1654944037.6418376 iteration: 38150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11228 FastRCNN class loss: 0.15952 FastRCNN total loss: 0.2718 L1 loss: 0.0000e+00 L2 loss: 0.65943 Learning rate: 0.02 Mask loss: 0.14407 RPN box loss: 0.0257 RPN score loss: 0.02965 RPN total loss: 0.05535 Total loss: 1.13065 timestamp: 1654944040.7678025 iteration: 38155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06006 FastRCNN class loss: 0.03927 FastRCNN total loss: 0.09933 L1 loss: 0.0000e+00 L2 loss: 0.65938 Learning rate: 0.02 Mask loss: 0.12277 RPN box loss: 0.02892 RPN score loss: 0.0048 RPN total loss: 0.03372 Total loss: 0.91521 timestamp: 1654944043.9706168 iteration: 38160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19022 FastRCNN class loss: 0.10765 FastRCNN total loss: 0.29786 L1 loss: 0.0000e+00 L2 loss: 0.65933 Learning rate: 0.02 Mask loss: 0.13709 RPN box loss: 0.02849 RPN score loss: 0.00788 RPN total loss: 0.03637 Total loss: 1.13065 timestamp: 1654944047.2145677 iteration: 38165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09322 FastRCNN class loss: 0.05658 FastRCNN total loss: 0.1498 L1 loss: 0.0000e+00 L2 loss: 0.65922 Learning rate: 0.02 Mask loss: 0.15655 RPN box loss: 0.02911 RPN score loss: 0.00575 RPN total loss: 0.03486 Total loss: 1.00043 timestamp: 1654944050.3970468 iteration: 38170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.151 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.22438 L1 loss: 0.0000e+00 L2 loss: 0.65913 Learning rate: 0.02 Mask loss: 0.18969 RPN box loss: 0.03152 RPN score loss: 0.02021 RPN total loss: 0.05174 Total loss: 1.12493 timestamp: 1654944053.5348268 iteration: 38175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11625 FastRCNN class loss: 0.08297 FastRCNN total loss: 0.19922 L1 loss: 0.0000e+00 L2 loss: 0.65907 Learning rate: 0.02 Mask loss: 0.13211 RPN box loss: 0.01108 RPN score loss: 0.00346 RPN total loss: 0.01454 Total loss: 1.00494 timestamp: 1654944056.7225637 iteration: 38180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13866 FastRCNN class loss: 0.11286 FastRCNN total loss: 0.25152 L1 loss: 0.0000e+00 L2 loss: 0.65899 Learning rate: 0.02 Mask loss: 0.13167 RPN box loss: 0.01908 RPN score loss: 0.00832 RPN total loss: 0.0274 Total loss: 1.06958 timestamp: 1654944059.9385538 iteration: 38185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.0473 FastRCNN total loss: 0.13261 L1 loss: 0.0000e+00 L2 loss: 0.6589 Learning rate: 0.02 Mask loss: 0.12896 RPN box loss: 0.0046 RPN score loss: 0.00525 RPN total loss: 0.00986 Total loss: 0.93032 timestamp: 1654944063.1337624 iteration: 38190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12883 FastRCNN class loss: 0.09025 FastRCNN total loss: 0.21908 L1 loss: 0.0000e+00 L2 loss: 0.65881 Learning rate: 0.02 Mask loss: 0.14252 RPN box loss: 0.01869 RPN score loss: 0.00402 RPN total loss: 0.02272 Total loss: 1.04312 timestamp: 1654944066.3339484 iteration: 38195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.05466 FastRCNN total loss: 0.16809 L1 loss: 0.0000e+00 L2 loss: 0.65871 Learning rate: 0.02 Mask loss: 0.11776 RPN box loss: 0.01605 RPN score loss: 0.00354 RPN total loss: 0.0196 Total loss: 0.96416 timestamp: 1654944069.4960423 iteration: 38200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12021 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.19162 L1 loss: 0.0000e+00 L2 loss: 0.65862 Learning rate: 0.02 Mask loss: 0.16388 RPN box loss: 0.03765 RPN score loss: 0.0085 RPN total loss: 0.04615 Total loss: 1.06027 timestamp: 1654944072.7488837 iteration: 38205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09881 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.16917 L1 loss: 0.0000e+00 L2 loss: 0.65855 Learning rate: 0.02 Mask loss: 0.13796 RPN box loss: 0.04372 RPN score loss: 0.01501 RPN total loss: 0.05874 Total loss: 1.02441 timestamp: 1654944075.958429 iteration: 38210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1311 FastRCNN class loss: 0.05939 FastRCNN total loss: 0.1905 L1 loss: 0.0000e+00 L2 loss: 0.65848 Learning rate: 0.02 Mask loss: 0.13959 RPN box loss: 0.06094 RPN score loss: 0.00428 RPN total loss: 0.06523 Total loss: 1.05379 timestamp: 1654944079.25438 iteration: 38215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09631 FastRCNN class loss: 0.04044 FastRCNN total loss: 0.13676 L1 loss: 0.0000e+00 L2 loss: 0.65839 Learning rate: 0.02 Mask loss: 0.08024 RPN box loss: 0.03834 RPN score loss: 0.00421 RPN total loss: 0.04256 Total loss: 0.91794 timestamp: 1654944082.4968476 iteration: 38220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11034 FastRCNN class loss: 0.08142 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 0.65832 Learning rate: 0.02 Mask loss: 0.14097 RPN box loss: 0.01428 RPN score loss: 0.0057 RPN total loss: 0.01998 Total loss: 1.01103 timestamp: 1654944085.707981 iteration: 38225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06647 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.13017 L1 loss: 0.0000e+00 L2 loss: 0.65824 Learning rate: 0.02 Mask loss: 0.13047 RPN box loss: 0.02761 RPN score loss: 0.00763 RPN total loss: 0.03523 Total loss: 0.95411 timestamp: 1654944088.9419928 iteration: 38230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10273 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.18593 L1 loss: 0.0000e+00 L2 loss: 0.65817 Learning rate: 0.02 Mask loss: 0.13 RPN box loss: 0.04578 RPN score loss: 0.00172 RPN total loss: 0.04751 Total loss: 1.0216 timestamp: 1654944092.094797 iteration: 38235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10445 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.17 L1 loss: 0.0000e+00 L2 loss: 0.65811 Learning rate: 0.02 Mask loss: 0.12939 RPN box loss: 0.0275 RPN score loss: 0.003 RPN total loss: 0.0305 Total loss: 0.988 timestamp: 1654944095.3080716 iteration: 38240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16191 FastRCNN class loss: 0.10107 FastRCNN total loss: 0.26298 L1 loss: 0.0000e+00 L2 loss: 0.65802 Learning rate: 0.02 Mask loss: 0.17693 RPN box loss: 0.03065 RPN score loss: 0.00682 RPN total loss: 0.03747 Total loss: 1.1354 timestamp: 1654944098.5522444 iteration: 38245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09924 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.17738 L1 loss: 0.0000e+00 L2 loss: 0.65793 Learning rate: 0.02 Mask loss: 0.12332 RPN box loss: 0.0137 RPN score loss: 0.0015 RPN total loss: 0.0152 Total loss: 0.97384 timestamp: 1654944101.7698076 iteration: 38250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19103 FastRCNN class loss: 0.13559 FastRCNN total loss: 0.32662 L1 loss: 0.0000e+00 L2 loss: 0.65785 Learning rate: 0.02 Mask loss: 0.21937 RPN box loss: 0.02441 RPN score loss: 0.01326 RPN total loss: 0.03768 Total loss: 1.24152 timestamp: 1654944104.9738572 iteration: 38255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07811 FastRCNN class loss: 0.04699 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.65776 Learning rate: 0.02 Mask loss: 0.09839 RPN box loss: 0.02317 RPN score loss: 0.00554 RPN total loss: 0.02871 Total loss: 0.90996 timestamp: 1654944108.1676948 iteration: 38260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18928 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.2722 L1 loss: 0.0000e+00 L2 loss: 0.65764 Learning rate: 0.02 Mask loss: 0.14249 RPN box loss: 0.02571 RPN score loss: 0.00683 RPN total loss: 0.03254 Total loss: 1.10488 timestamp: 1654944111.3178186 iteration: 38265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12681 FastRCNN class loss: 0.06311 FastRCNN total loss: 0.18991 L1 loss: 0.0000e+00 L2 loss: 0.65754 Learning rate: 0.02 Mask loss: 0.16166 RPN box loss: 0.01721 RPN score loss: 0.00662 RPN total loss: 0.02383 Total loss: 1.03294 timestamp: 1654944114.4461799 iteration: 38270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2066 FastRCNN class loss: 0.10108 FastRCNN total loss: 0.30767 L1 loss: 0.0000e+00 L2 loss: 0.65745 Learning rate: 0.02 Mask loss: 0.26164 RPN box loss: 0.0297 RPN score loss: 0.01156 RPN total loss: 0.04126 Total loss: 1.26802 timestamp: 1654944117.7012994 iteration: 38275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15511 FastRCNN class loss: 0.09856 FastRCNN total loss: 0.25367 L1 loss: 0.0000e+00 L2 loss: 0.65737 Learning rate: 0.02 Mask loss: 0.18138 RPN box loss: 0.02638 RPN score loss: 0.00596 RPN total loss: 0.03234 Total loss: 1.12476 timestamp: 1654944120.8706813 iteration: 38280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22627 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.32221 L1 loss: 0.0000e+00 L2 loss: 0.65729 Learning rate: 0.02 Mask loss: 0.25718 RPN box loss: 0.0144 RPN score loss: 0.00493 RPN total loss: 0.01934 Total loss: 1.25602 timestamp: 1654944124.0454323 iteration: 38285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14042 FastRCNN class loss: 0.06142 FastRCNN total loss: 0.20184 L1 loss: 0.0000e+00 L2 loss: 0.65721 Learning rate: 0.02 Mask loss: 0.13341 RPN box loss: 0.02436 RPN score loss: 0.00639 RPN total loss: 0.03075 Total loss: 1.02322 timestamp: 1654944127.2809134 iteration: 38290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13166 FastRCNN class loss: 0.09835 FastRCNN total loss: 0.23001 L1 loss: 0.0000e+00 L2 loss: 0.65713 Learning rate: 0.02 Mask loss: 0.21377 RPN box loss: 0.02134 RPN score loss: 0.0045 RPN total loss: 0.02584 Total loss: 1.12675 timestamp: 1654944130.429969 iteration: 38295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12564 FastRCNN class loss: 0.11585 FastRCNN total loss: 0.24149 L1 loss: 0.0000e+00 L2 loss: 0.65704 Learning rate: 0.02 Mask loss: 0.21993 RPN box loss: 0.05321 RPN score loss: 0.01314 RPN total loss: 0.06635 Total loss: 1.18481 timestamp: 1654944133.557068 iteration: 38300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12331 FastRCNN class loss: 0.13463 FastRCNN total loss: 0.25795 L1 loss: 0.0000e+00 L2 loss: 0.65694 Learning rate: 0.02 Mask loss: 0.20007 RPN box loss: 0.05809 RPN score loss: 0.01276 RPN total loss: 0.07085 Total loss: 1.1858 timestamp: 1654944136.8025973 iteration: 38305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14506 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.20645 L1 loss: 0.0000e+00 L2 loss: 0.65686 Learning rate: 0.02 Mask loss: 0.1021 RPN box loss: 0.05104 RPN score loss: 0.00423 RPN total loss: 0.05527 Total loss: 1.02069 timestamp: 1654944139.9417095 iteration: 38310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16815 FastRCNN class loss: 0.16633 FastRCNN total loss: 0.33448 L1 loss: 0.0000e+00 L2 loss: 0.65679 Learning rate: 0.02 Mask loss: 0.21448 RPN box loss: 0.04677 RPN score loss: 0.02455 RPN total loss: 0.07132 Total loss: 1.27707 timestamp: 1654944143.1283147 iteration: 38315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11738 FastRCNN class loss: 0.15497 FastRCNN total loss: 0.27234 L1 loss: 0.0000e+00 L2 loss: 0.65672 Learning rate: 0.02 Mask loss: 0.18927 RPN box loss: 0.06552 RPN score loss: 0.01298 RPN total loss: 0.07849 Total loss: 1.19683 timestamp: 1654944146.322846 iteration: 38320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.1865 L1 loss: 0.0000e+00 L2 loss: 0.65663 Learning rate: 0.02 Mask loss: 0.12364 RPN box loss: 0.01809 RPN score loss: 0.00554 RPN total loss: 0.02364 Total loss: 0.99041 timestamp: 1654944149.5323737 iteration: 38325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11591 FastRCNN class loss: 0.06996 FastRCNN total loss: 0.18587 L1 loss: 0.0000e+00 L2 loss: 0.65655 Learning rate: 0.02 Mask loss: 0.09563 RPN box loss: 0.01647 RPN score loss: 0.00572 RPN total loss: 0.0222 Total loss: 0.96025 timestamp: 1654944152.6871414 iteration: 38330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08473 FastRCNN class loss: 0.07272 FastRCNN total loss: 0.15745 L1 loss: 0.0000e+00 L2 loss: 0.65646 Learning rate: 0.02 Mask loss: 0.12132 RPN box loss: 0.00745 RPN score loss: 0.00349 RPN total loss: 0.01094 Total loss: 0.94617 timestamp: 1654944155.8358908 iteration: 38335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10319 FastRCNN class loss: 0.06973 FastRCNN total loss: 0.17292 L1 loss: 0.0000e+00 L2 loss: 0.65637 Learning rate: 0.02 Mask loss: 0.13983 RPN box loss: 0.04877 RPN score loss: 0.0074 RPN total loss: 0.05617 Total loss: 1.0253 timestamp: 1654944158.953869 iteration: 38340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1246 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.19757 L1 loss: 0.0000e+00 L2 loss: 0.65629 Learning rate: 0.02 Mask loss: 0.1635 RPN box loss: 0.01625 RPN score loss: 0.00486 RPN total loss: 0.02111 Total loss: 1.03848 timestamp: 1654944162.2110932 iteration: 38345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12988 FastRCNN class loss: 0.07276 FastRCNN total loss: 0.20264 L1 loss: 0.0000e+00 L2 loss: 0.65621 Learning rate: 0.02 Mask loss: 0.14919 RPN box loss: 0.03952 RPN score loss: 0.00379 RPN total loss: 0.04332 Total loss: 1.05135 timestamp: 1654944165.3579433 iteration: 38350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1736 FastRCNN class loss: 0.09062 FastRCNN total loss: 0.26422 L1 loss: 0.0000e+00 L2 loss: 0.65613 Learning rate: 0.02 Mask loss: 0.18311 RPN box loss: 0.02317 RPN score loss: 0.00399 RPN total loss: 0.02716 Total loss: 1.13063 timestamp: 1654944168.535355 iteration: 38355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13875 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.22108 L1 loss: 0.0000e+00 L2 loss: 0.65606 Learning rate: 0.02 Mask loss: 0.15749 RPN box loss: 0.03448 RPN score loss: 0.00475 RPN total loss: 0.03923 Total loss: 1.07386 timestamp: 1654944171.6859212 iteration: 38360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12619 FastRCNN class loss: 0.08201 FastRCNN total loss: 0.2082 L1 loss: 0.0000e+00 L2 loss: 0.65595 Learning rate: 0.02 Mask loss: 0.13405 RPN box loss: 0.01518 RPN score loss: 0.00537 RPN total loss: 0.02055 Total loss: 1.01876 timestamp: 1654944174.8065016 iteration: 38365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06608 FastRCNN class loss: 0.04954 FastRCNN total loss: 0.11563 L1 loss: 0.0000e+00 L2 loss: 0.65588 Learning rate: 0.02 Mask loss: 0.14969 RPN box loss: 0.02677 RPN score loss: 0.00501 RPN total loss: 0.03178 Total loss: 0.95298 timestamp: 1654944177.9873884 iteration: 38370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14367 FastRCNN class loss: 0.11226 FastRCNN total loss: 0.25592 L1 loss: 0.0000e+00 L2 loss: 0.6558 Learning rate: 0.02 Mask loss: 0.13235 RPN box loss: 0.01682 RPN score loss: 0.00624 RPN total loss: 0.02306 Total loss: 1.06713 timestamp: 1654944181.2350867 iteration: 38375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16211 FastRCNN class loss: 0.05508 FastRCNN total loss: 0.2172 L1 loss: 0.0000e+00 L2 loss: 0.65572 Learning rate: 0.02 Mask loss: 0.13231 RPN box loss: 0.00648 RPN score loss: 0.0028 RPN total loss: 0.00927 Total loss: 1.0145 timestamp: 1654944184.3755028 iteration: 38380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14389 FastRCNN class loss: 0.09255 FastRCNN total loss: 0.23644 L1 loss: 0.0000e+00 L2 loss: 0.65562 Learning rate: 0.02 Mask loss: 0.15882 RPN box loss: 0.01791 RPN score loss: 0.0144 RPN total loss: 0.03232 Total loss: 1.08321 timestamp: 1654944187.559031 iteration: 38385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25994 FastRCNN class loss: 0.09861 FastRCNN total loss: 0.35854 L1 loss: 0.0000e+00 L2 loss: 0.65553 Learning rate: 0.02 Mask loss: 0.17871 RPN box loss: 0.01462 RPN score loss: 0.00521 RPN total loss: 0.01983 Total loss: 1.21261 timestamp: 1654944190.8043115 iteration: 38390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09825 FastRCNN class loss: 0.0868 FastRCNN total loss: 0.18505 L1 loss: 0.0000e+00 L2 loss: 0.65547 Learning rate: 0.02 Mask loss: 0.15911 RPN box loss: 0.02977 RPN score loss: 0.00489 RPN total loss: 0.03466 Total loss: 1.03429 timestamp: 1654944194.0325015 iteration: 38395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09885 FastRCNN class loss: 0.0379 FastRCNN total loss: 0.13675 L1 loss: 0.0000e+00 L2 loss: 0.65539 Learning rate: 0.02 Mask loss: 0.09304 RPN box loss: 0.0535 RPN score loss: 0.00508 RPN total loss: 0.05858 Total loss: 0.94376 timestamp: 1654944197.2214904 iteration: 38400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15733 FastRCNN class loss: 0.12562 FastRCNN total loss: 0.28295 L1 loss: 0.0000e+00 L2 loss: 0.65532 Learning rate: 0.02 Mask loss: 0.18618 RPN box loss: 0.05178 RPN score loss: 0.0117 RPN total loss: 0.06348 Total loss: 1.18793 timestamp: 1654944200.5014658 iteration: 38405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09198 FastRCNN class loss: 0.06826 FastRCNN total loss: 0.16024 L1 loss: 0.0000e+00 L2 loss: 0.65524 Learning rate: 0.02 Mask loss: 0.12629 RPN box loss: 0.0072 RPN score loss: 0.00806 RPN total loss: 0.01526 Total loss: 0.95703 timestamp: 1654944203.6253448 iteration: 38410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14014 FastRCNN class loss: 0.13418 FastRCNN total loss: 0.27432 L1 loss: 0.0000e+00 L2 loss: 0.65516 Learning rate: 0.02 Mask loss: 0.16077 RPN box loss: 0.02241 RPN score loss: 0.0216 RPN total loss: 0.04401 Total loss: 1.13426 timestamp: 1654944206.8160968 iteration: 38415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15525 FastRCNN class loss: 0.11543 FastRCNN total loss: 0.27068 L1 loss: 0.0000e+00 L2 loss: 0.65506 Learning rate: 0.02 Mask loss: 0.1704 RPN box loss: 0.04679 RPN score loss: 0.00861 RPN total loss: 0.0554 Total loss: 1.15154 timestamp: 1654944210.004882 iteration: 38420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14164 FastRCNN class loss: 0.10444 FastRCNN total loss: 0.24608 L1 loss: 0.0000e+00 L2 loss: 0.65496 Learning rate: 0.02 Mask loss: 0.15632 RPN box loss: 0.06812 RPN score loss: 0.01622 RPN total loss: 0.08434 Total loss: 1.1417 timestamp: 1654944213.2033124 iteration: 38425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08081 FastRCNN class loss: 0.04866 FastRCNN total loss: 0.12947 L1 loss: 0.0000e+00 L2 loss: 0.65487 Learning rate: 0.02 Mask loss: 0.07426 RPN box loss: 0.04994 RPN score loss: 0.00133 RPN total loss: 0.05127 Total loss: 0.90986 timestamp: 1654944216.3549738 iteration: 38430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17229 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.26089 L1 loss: 0.0000e+00 L2 loss: 0.6548 Learning rate: 0.02 Mask loss: 0.19452 RPN box loss: 0.03518 RPN score loss: 0.00541 RPN total loss: 0.04059 Total loss: 1.1508 timestamp: 1654944219.558675 iteration: 38435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14455 FastRCNN class loss: 0.08928 FastRCNN total loss: 0.23383 L1 loss: 0.0000e+00 L2 loss: 0.65474 Learning rate: 0.02 Mask loss: 0.18899 RPN box loss: 0.03168 RPN score loss: 0.00999 RPN total loss: 0.04168 Total loss: 1.11924 timestamp: 1654944222.7069662 iteration: 38440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08209 FastRCNN class loss: 0.0606 FastRCNN total loss: 0.14269 L1 loss: 0.0000e+00 L2 loss: 0.65467 Learning rate: 0.02 Mask loss: 0.13116 RPN box loss: 0.01511 RPN score loss: 0.0061 RPN total loss: 0.02122 Total loss: 0.94974 timestamp: 1654944225.902761 iteration: 38445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12767 FastRCNN class loss: 0.074 FastRCNN total loss: 0.20167 L1 loss: 0.0000e+00 L2 loss: 0.65454 Learning rate: 0.02 Mask loss: 0.08831 RPN box loss: 0.02326 RPN score loss: 0.00539 RPN total loss: 0.02864 Total loss: 0.97316 timestamp: 1654944229.0941272 iteration: 38450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20964 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.28074 L1 loss: 0.0000e+00 L2 loss: 0.65443 Learning rate: 0.02 Mask loss: 0.15569 RPN box loss: 0.03235 RPN score loss: 0.00517 RPN total loss: 0.03752 Total loss: 1.12838 timestamp: 1654944232.3991106 iteration: 38455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12809 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.20944 L1 loss: 0.0000e+00 L2 loss: 0.65433 Learning rate: 0.02 Mask loss: 0.13063 RPN box loss: 0.04835 RPN score loss: 0.01238 RPN total loss: 0.06073 Total loss: 1.05512 timestamp: 1654944235.6229072 iteration: 38460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11168 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.18562 L1 loss: 0.0000e+00 L2 loss: 0.65423 Learning rate: 0.02 Mask loss: 0.20778 RPN box loss: 0.03679 RPN score loss: 0.0072 RPN total loss: 0.04399 Total loss: 1.09162 timestamp: 1654944238.860431 iteration: 38465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07957 FastRCNN class loss: 0.0511 FastRCNN total loss: 0.13067 L1 loss: 0.0000e+00 L2 loss: 0.65415 Learning rate: 0.02 Mask loss: 0.09466 RPN box loss: 0.01768 RPN score loss: 0.00333 RPN total loss: 0.02101 Total loss: 0.90049 timestamp: 1654944242.0375075 iteration: 38470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15224 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.22421 L1 loss: 0.0000e+00 L2 loss: 0.65406 Learning rate: 0.02 Mask loss: 0.18383 RPN box loss: 0.0163 RPN score loss: 0.00611 RPN total loss: 0.02241 Total loss: 1.08451 timestamp: 1654944245.299346 iteration: 38475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08687 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.14743 L1 loss: 0.0000e+00 L2 loss: 0.65396 Learning rate: 0.02 Mask loss: 0.10266 RPN box loss: 0.01972 RPN score loss: 0.00472 RPN total loss: 0.02444 Total loss: 0.9285 timestamp: 1654944248.5267775 iteration: 38480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13189 FastRCNN class loss: 0.07262 FastRCNN total loss: 0.2045 L1 loss: 0.0000e+00 L2 loss: 0.65387 Learning rate: 0.02 Mask loss: 0.15343 RPN box loss: 0.01743 RPN score loss: 0.02099 RPN total loss: 0.03841 Total loss: 1.05021 timestamp: 1654944251.681477 iteration: 38485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10733 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.17446 L1 loss: 0.0000e+00 L2 loss: 0.65378 Learning rate: 0.02 Mask loss: 0.13087 RPN box loss: 0.05221 RPN score loss: 0.00386 RPN total loss: 0.05607 Total loss: 1.01517 timestamp: 1654944254.8746686 iteration: 38490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08199 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.14815 L1 loss: 0.0000e+00 L2 loss: 0.65372 Learning rate: 0.02 Mask loss: 0.1173 RPN box loss: 0.04424 RPN score loss: 0.00506 RPN total loss: 0.04931 Total loss: 0.96848 timestamp: 1654944258.0316362 iteration: 38495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0997 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.17516 L1 loss: 0.0000e+00 L2 loss: 0.65362 Learning rate: 0.02 Mask loss: 0.08401 RPN box loss: 0.01745 RPN score loss: 0.00267 RPN total loss: 0.02012 Total loss: 0.93291 timestamp: 1654944261.2048051 iteration: 38500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18779 FastRCNN class loss: 0.11057 FastRCNN total loss: 0.29836 L1 loss: 0.0000e+00 L2 loss: 0.65351 Learning rate: 0.02 Mask loss: 0.19657 RPN box loss: 0.0478 RPN score loss: 0.00297 RPN total loss: 0.05078 Total loss: 1.19922 timestamp: 1654944264.3374307 iteration: 38505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11898 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.18449 L1 loss: 0.0000e+00 L2 loss: 0.65345 Learning rate: 0.02 Mask loss: 0.14529 RPN box loss: 0.03439 RPN score loss: 0.0103 RPN total loss: 0.04469 Total loss: 1.02792 timestamp: 1654944267.5456536 iteration: 38510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15705 FastRCNN class loss: 0.07726 FastRCNN total loss: 0.2343 L1 loss: 0.0000e+00 L2 loss: 0.65339 Learning rate: 0.02 Mask loss: 0.22973 RPN box loss: 0.00676 RPN score loss: 0.00412 RPN total loss: 0.01089 Total loss: 1.1283 timestamp: 1654944270.7264953 iteration: 38515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10058 FastRCNN class loss: 0.05319 FastRCNN total loss: 0.15377 L1 loss: 0.0000e+00 L2 loss: 0.6533 Learning rate: 0.02 Mask loss: 0.09945 RPN box loss: 0.04234 RPN score loss: 0.00667 RPN total loss: 0.04901 Total loss: 0.95553 timestamp: 1654944273.8917687 iteration: 38520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12303 FastRCNN class loss: 0.0513 FastRCNN total loss: 0.17434 L1 loss: 0.0000e+00 L2 loss: 0.65324 Learning rate: 0.02 Mask loss: 0.15149 RPN box loss: 0.00672 RPN score loss: 0.00192 RPN total loss: 0.00864 Total loss: 0.9877 timestamp: 1654944277.0577576 iteration: 38525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11307 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.16937 L1 loss: 0.0000e+00 L2 loss: 0.65316 Learning rate: 0.02 Mask loss: 0.10103 RPN box loss: 0.01208 RPN score loss: 0.01018 RPN total loss: 0.02226 Total loss: 0.94582 timestamp: 1654944280.3144155 iteration: 38530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17788 FastRCNN class loss: 0.08478 FastRCNN total loss: 0.26266 L1 loss: 0.0000e+00 L2 loss: 0.6531 Learning rate: 0.02 Mask loss: 0.14889 RPN box loss: 0.01072 RPN score loss: 0.00465 RPN total loss: 0.01537 Total loss: 1.08002 timestamp: 1654944283.4655056 iteration: 38535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10121 FastRCNN class loss: 0.09079 FastRCNN total loss: 0.192 L1 loss: 0.0000e+00 L2 loss: 0.65299 Learning rate: 0.02 Mask loss: 0.24227 RPN box loss: 0.02491 RPN score loss: 0.00216 RPN total loss: 0.02706 Total loss: 1.11432 timestamp: 1654944286.6887693 iteration: 38540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22807 FastRCNN class loss: 0.09183 FastRCNN total loss: 0.31989 L1 loss: 0.0000e+00 L2 loss: 0.65291 Learning rate: 0.02 Mask loss: 0.14319 RPN box loss: 0.02426 RPN score loss: 0.0025 RPN total loss: 0.02676 Total loss: 1.14275 timestamp: 1654944289.8890018 iteration: 38545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.06701 FastRCNN total loss: 0.15328 L1 loss: 0.0000e+00 L2 loss: 0.65285 Learning rate: 0.02 Mask loss: 0.1582 RPN box loss: 0.0169 RPN score loss: 0.00604 RPN total loss: 0.02293 Total loss: 0.98726 timestamp: 1654944293.110332 iteration: 38550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12936 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.19525 L1 loss: 0.0000e+00 L2 loss: 0.65275 Learning rate: 0.02 Mask loss: 0.1557 RPN box loss: 0.01643 RPN score loss: 0.00977 RPN total loss: 0.0262 Total loss: 1.02989 timestamp: 1654944296.2991474 iteration: 38555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13654 FastRCNN class loss: 0.10937 FastRCNN total loss: 0.24591 L1 loss: 0.0000e+00 L2 loss: 0.65266 Learning rate: 0.02 Mask loss: 0.1747 RPN box loss: 0.05528 RPN score loss: 0.01366 RPN total loss: 0.06894 Total loss: 1.14221 timestamp: 1654944299.4290147 iteration: 38560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15273 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.25049 L1 loss: 0.0000e+00 L2 loss: 0.65259 Learning rate: 0.02 Mask loss: 0.25354 RPN box loss: 0.04765 RPN score loss: 0.01246 RPN total loss: 0.06011 Total loss: 1.21673 timestamp: 1654944302.5664074 iteration: 38565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09291 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.15307 L1 loss: 0.0000e+00 L2 loss: 0.65251 Learning rate: 0.02 Mask loss: 0.10908 RPN box loss: 0.01596 RPN score loss: 0.00242 RPN total loss: 0.01838 Total loss: 0.93304 timestamp: 1654944305.7308328 iteration: 38570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10474 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.17792 L1 loss: 0.0000e+00 L2 loss: 0.65244 Learning rate: 0.02 Mask loss: 0.12039 RPN box loss: 0.04127 RPN score loss: 0.00347 RPN total loss: 0.04474 Total loss: 0.99548 timestamp: 1654944308.8904872 iteration: 38575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12015 FastRCNN class loss: 0.08789 FastRCNN total loss: 0.20805 L1 loss: 0.0000e+00 L2 loss: 0.65234 Learning rate: 0.02 Mask loss: 0.14004 RPN box loss: 0.02092 RPN score loss: 0.01043 RPN total loss: 0.03135 Total loss: 1.03178 timestamp: 1654944312.0719197 iteration: 38580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12078 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.19866 L1 loss: 0.0000e+00 L2 loss: 0.65225 Learning rate: 0.02 Mask loss: 0.147 RPN box loss: 0.01832 RPN score loss: 0.00368 RPN total loss: 0.022 Total loss: 1.01991 timestamp: 1654944315.2436044 iteration: 38585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12251 FastRCNN class loss: 0.10825 FastRCNN total loss: 0.23076 L1 loss: 0.0000e+00 L2 loss: 0.65218 Learning rate: 0.02 Mask loss: 0.15955 RPN box loss: 0.03903 RPN score loss: 0.01229 RPN total loss: 0.05132 Total loss: 1.09381 timestamp: 1654944318.433171 iteration: 38590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.10798 FastRCNN total loss: 0.22814 L1 loss: 0.0000e+00 L2 loss: 0.65212 Learning rate: 0.02 Mask loss: 0.21273 RPN box loss: 0.03157 RPN score loss: 0.00851 RPN total loss: 0.04008 Total loss: 1.13307 timestamp: 1654944321.6357474 iteration: 38595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11577 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.18988 L1 loss: 0.0000e+00 L2 loss: 0.65205 Learning rate: 0.02 Mask loss: 0.17516 RPN box loss: 0.00626 RPN score loss: 0.00213 RPN total loss: 0.00839 Total loss: 1.02547 timestamp: 1654944324.809812 iteration: 38600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20512 FastRCNN class loss: 0.135 FastRCNN total loss: 0.34012 L1 loss: 0.0000e+00 L2 loss: 0.65197 Learning rate: 0.02 Mask loss: 0.20254 RPN box loss: 0.04555 RPN score loss: 0.01389 RPN total loss: 0.05945 Total loss: 1.25407 timestamp: 1654944327.9724183 iteration: 38605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07417 FastRCNN class loss: 0.09318 FastRCNN total loss: 0.16736 L1 loss: 0.0000e+00 L2 loss: 0.65189 Learning rate: 0.02 Mask loss: 0.13981 RPN box loss: 0.01702 RPN score loss: 0.00911 RPN total loss: 0.02613 Total loss: 0.98519 timestamp: 1654944331.2181005 iteration: 38610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08923 FastRCNN class loss: 0.05814 FastRCNN total loss: 0.14737 L1 loss: 0.0000e+00 L2 loss: 0.65183 Learning rate: 0.02 Mask loss: 0.14238 RPN box loss: 0.05081 RPN score loss: 0.01015 RPN total loss: 0.06096 Total loss: 1.00253 timestamp: 1654944334.5146873 iteration: 38615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11982 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.20547 L1 loss: 0.0000e+00 L2 loss: 0.65174 Learning rate: 0.02 Mask loss: 0.1391 RPN box loss: 0.03081 RPN score loss: 0.00819 RPN total loss: 0.039 Total loss: 1.03532 timestamp: 1654944337.6594503 iteration: 38620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07838 FastRCNN class loss: 0.05387 FastRCNN total loss: 0.13225 L1 loss: 0.0000e+00 L2 loss: 0.65167 Learning rate: 0.02 Mask loss: 0.10909 RPN box loss: 0.06237 RPN score loss: 0.01167 RPN total loss: 0.07405 Total loss: 0.96705 timestamp: 1654944340.9003692 iteration: 38625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11708 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.18732 L1 loss: 0.0000e+00 L2 loss: 0.65159 Learning rate: 0.02 Mask loss: 0.18251 RPN box loss: 0.02254 RPN score loss: 0.00211 RPN total loss: 0.02465 Total loss: 1.04607 timestamp: 1654944344.087155 iteration: 38630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08828 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.14791 L1 loss: 0.0000e+00 L2 loss: 0.65148 Learning rate: 0.02 Mask loss: 0.0996 RPN box loss: 0.01272 RPN score loss: 0.00321 RPN total loss: 0.01593 Total loss: 0.91493 timestamp: 1654944347.2541196 iteration: 38635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20466 FastRCNN class loss: 0.10727 FastRCNN total loss: 0.31193 L1 loss: 0.0000e+00 L2 loss: 0.65141 Learning rate: 0.02 Mask loss: 0.18214 RPN box loss: 0.06941 RPN score loss: 0.01862 RPN total loss: 0.08803 Total loss: 1.2335 timestamp: 1654944350.4631174 iteration: 38640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14231 FastRCNN class loss: 0.08673 FastRCNN total loss: 0.22904 L1 loss: 0.0000e+00 L2 loss: 0.65134 Learning rate: 0.02 Mask loss: 0.14405 RPN box loss: 0.01411 RPN score loss: 0.00465 RPN total loss: 0.01876 Total loss: 1.0432 timestamp: 1654944353.6895573 iteration: 38645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10426 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.16587 L1 loss: 0.0000e+00 L2 loss: 0.65127 Learning rate: 0.02 Mask loss: 0.13211 RPN box loss: 0.06026 RPN score loss: 0.00544 RPN total loss: 0.0657 Total loss: 1.01496 timestamp: 1654944356.8777974 iteration: 38650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13397 FastRCNN class loss: 0.07821 FastRCNN total loss: 0.21218 L1 loss: 0.0000e+00 L2 loss: 0.6512 Learning rate: 0.02 Mask loss: 0.12895 RPN box loss: 0.0165 RPN score loss: 0.00265 RPN total loss: 0.01914 Total loss: 1.01147 timestamp: 1654944360.0516853 iteration: 38655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15 FastRCNN class loss: 0.10985 FastRCNN total loss: 0.25985 L1 loss: 0.0000e+00 L2 loss: 0.65108 Learning rate: 0.02 Mask loss: 0.18623 RPN box loss: 0.02879 RPN score loss: 0.01055 RPN total loss: 0.03933 Total loss: 1.13649 timestamp: 1654944363.2668514 iteration: 38660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19941 FastRCNN class loss: 0.11789 FastRCNN total loss: 0.3173 L1 loss: 0.0000e+00 L2 loss: 0.65099 Learning rate: 0.02 Mask loss: 0.19381 RPN box loss: 0.03055 RPN score loss: 0.00944 RPN total loss: 0.03999 Total loss: 1.2021 timestamp: 1654944366.4924061 iteration: 38665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10006 FastRCNN class loss: 0.05639 FastRCNN total loss: 0.15646 L1 loss: 0.0000e+00 L2 loss: 0.65091 Learning rate: 0.02 Mask loss: 0.12337 RPN box loss: 0.017 RPN score loss: 0.00763 RPN total loss: 0.02463 Total loss: 0.95537 timestamp: 1654944369.685657 iteration: 38670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18893 FastRCNN class loss: 0.12801 FastRCNN total loss: 0.31694 L1 loss: 0.0000e+00 L2 loss: 0.65084 Learning rate: 0.02 Mask loss: 0.1958 RPN box loss: 0.02329 RPN score loss: 0.00856 RPN total loss: 0.03184 Total loss: 1.19542 timestamp: 1654944372.882357 iteration: 38675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15264 FastRCNN class loss: 0.06777 FastRCNN total loss: 0.22041 L1 loss: 0.0000e+00 L2 loss: 0.65074 Learning rate: 0.02 Mask loss: 0.13245 RPN box loss: 0.05467 RPN score loss: 0.00968 RPN total loss: 0.06435 Total loss: 1.06796 timestamp: 1654944376.0183077 iteration: 38680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13552 FastRCNN class loss: 0.04583 FastRCNN total loss: 0.18135 L1 loss: 0.0000e+00 L2 loss: 0.65068 Learning rate: 0.02 Mask loss: 0.07724 RPN box loss: 0.01513 RPN score loss: 0.00461 RPN total loss: 0.01974 Total loss: 0.929 timestamp: 1654944379.2930577 iteration: 38685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19018 FastRCNN class loss: 0.1441 FastRCNN total loss: 0.33428 L1 loss: 0.0000e+00 L2 loss: 0.65064 Learning rate: 0.02 Mask loss: 0.17782 RPN box loss: 0.0255 RPN score loss: 0.00314 RPN total loss: 0.02864 Total loss: 1.19138 timestamp: 1654944382.466043 iteration: 38690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09981 FastRCNN class loss: 0.07706 FastRCNN total loss: 0.17687 L1 loss: 0.0000e+00 L2 loss: 0.65056 Learning rate: 0.02 Mask loss: 0.13598 RPN box loss: 0.00701 RPN score loss: 0.00104 RPN total loss: 0.00805 Total loss: 0.97145 timestamp: 1654944385.6910741 iteration: 38695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12087 FastRCNN class loss: 0.05303 FastRCNN total loss: 0.17389 L1 loss: 0.0000e+00 L2 loss: 0.65046 Learning rate: 0.02 Mask loss: 0.15645 RPN box loss: 0.01378 RPN score loss: 0.00151 RPN total loss: 0.01529 Total loss: 0.99609 timestamp: 1654944388.9794052 iteration: 38700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1474 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.20768 L1 loss: 0.0000e+00 L2 loss: 0.65037 Learning rate: 0.02 Mask loss: 0.16629 RPN box loss: 0.01311 RPN score loss: 0.00498 RPN total loss: 0.01809 Total loss: 1.04243 timestamp: 1654944392.2902365 iteration: 38705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15728 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.22667 L1 loss: 0.0000e+00 L2 loss: 0.65029 Learning rate: 0.02 Mask loss: 0.13202 RPN box loss: 0.01772 RPN score loss: 0.0076 RPN total loss: 0.02532 Total loss: 1.0343 timestamp: 1654944395.5040169 iteration: 38710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11807 FastRCNN class loss: 0.03667 FastRCNN total loss: 0.15474 L1 loss: 0.0000e+00 L2 loss: 0.65021 Learning rate: 0.02 Mask loss: 0.11856 RPN box loss: 0.00296 RPN score loss: 0.00511 RPN total loss: 0.00808 Total loss: 0.93158 timestamp: 1654944398.6883135 iteration: 38715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17215 FastRCNN class loss: 0.09324 FastRCNN total loss: 0.26538 L1 loss: 0.0000e+00 L2 loss: 0.65016 Learning rate: 0.02 Mask loss: 0.1376 RPN box loss: 0.04355 RPN score loss: 0.01386 RPN total loss: 0.05741 Total loss: 1.11055 timestamp: 1654944401.8573158 iteration: 38720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21478 FastRCNN class loss: 0.10995 FastRCNN total loss: 0.32473 L1 loss: 0.0000e+00 L2 loss: 0.65008 Learning rate: 0.02 Mask loss: 0.18012 RPN box loss: 0.04411 RPN score loss: 0.0103 RPN total loss: 0.05441 Total loss: 1.20934 timestamp: 1654944404.9930372 iteration: 38725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05192 FastRCNN class loss: 0.06493 FastRCNN total loss: 0.11685 L1 loss: 0.0000e+00 L2 loss: 0.64999 Learning rate: 0.02 Mask loss: 0.08445 RPN box loss: 0.00965 RPN score loss: 0.00311 RPN total loss: 0.01276 Total loss: 0.86405 timestamp: 1654944408.2449403 iteration: 38730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23858 FastRCNN class loss: 0.14235 FastRCNN total loss: 0.38093 L1 loss: 0.0000e+00 L2 loss: 0.64992 Learning rate: 0.02 Mask loss: 0.16325 RPN box loss: 0.04585 RPN score loss: 0.0076 RPN total loss: 0.05344 Total loss: 1.24754 timestamp: 1654944411.468338 iteration: 38735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1449 FastRCNN class loss: 0.1181 FastRCNN total loss: 0.263 L1 loss: 0.0000e+00 L2 loss: 0.64981 Learning rate: 0.02 Mask loss: 0.20697 RPN box loss: 0.03289 RPN score loss: 0.01326 RPN total loss: 0.04615 Total loss: 1.16593 timestamp: 1654944414.6580105 iteration: 38740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20309 FastRCNN class loss: 0.10525 FastRCNN total loss: 0.30834 L1 loss: 0.0000e+00 L2 loss: 0.64972 Learning rate: 0.02 Mask loss: 0.22455 RPN box loss: 0.05825 RPN score loss: 0.00478 RPN total loss: 0.06303 Total loss: 1.24565 timestamp: 1654944417.855937 iteration: 38745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09106 FastRCNN class loss: 0.03682 FastRCNN total loss: 0.12788 L1 loss: 0.0000e+00 L2 loss: 0.64965 Learning rate: 0.02 Mask loss: 0.13529 RPN box loss: 0.00691 RPN score loss: 0.00299 RPN total loss: 0.0099 Total loss: 0.92272 timestamp: 1654944421.098277 iteration: 38750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07875 FastRCNN class loss: 0.0854 FastRCNN total loss: 0.16415 L1 loss: 0.0000e+00 L2 loss: 0.64957 Learning rate: 0.02 Mask loss: 0.18704 RPN box loss: 0.05962 RPN score loss: 0.00673 RPN total loss: 0.06635 Total loss: 1.06711 timestamp: 1654944424.2853403 iteration: 38755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10507 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.20535 L1 loss: 0.0000e+00 L2 loss: 0.64949 Learning rate: 0.02 Mask loss: 0.12984 RPN box loss: 0.01018 RPN score loss: 0.00117 RPN total loss: 0.01135 Total loss: 0.99603 timestamp: 1654944427.5417175 iteration: 38760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12633 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.18234 L1 loss: 0.0000e+00 L2 loss: 0.64941 Learning rate: 0.02 Mask loss: 0.11811 RPN box loss: 0.00626 RPN score loss: 0.00363 RPN total loss: 0.00989 Total loss: 0.95974 timestamp: 1654944430.7957203 iteration: 38765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16995 FastRCNN class loss: 0.13852 FastRCNN total loss: 0.30848 L1 loss: 0.0000e+00 L2 loss: 0.64934 Learning rate: 0.02 Mask loss: 0.17978 RPN box loss: 0.02371 RPN score loss: 0.00663 RPN total loss: 0.03033 Total loss: 1.16793 timestamp: 1654944433.9648666 iteration: 38770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09651 FastRCNN class loss: 0.05564 FastRCNN total loss: 0.15214 L1 loss: 0.0000e+00 L2 loss: 0.64926 Learning rate: 0.02 Mask loss: 0.11964 RPN box loss: 0.03305 RPN score loss: 0.00573 RPN total loss: 0.03877 Total loss: 0.95982 timestamp: 1654944437.119454 iteration: 38775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18111 FastRCNN class loss: 0.114 FastRCNN total loss: 0.29511 L1 loss: 0.0000e+00 L2 loss: 0.64916 Learning rate: 0.02 Mask loss: 0.21234 RPN box loss: 0.04651 RPN score loss: 0.00911 RPN total loss: 0.05562 Total loss: 1.21223 timestamp: 1654944440.3569381 iteration: 38780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13322 FastRCNN class loss: 0.08093 FastRCNN total loss: 0.21415 L1 loss: 0.0000e+00 L2 loss: 0.64909 Learning rate: 0.02 Mask loss: 0.08958 RPN box loss: 0.02621 RPN score loss: 0.00394 RPN total loss: 0.03015 Total loss: 0.98297 timestamp: 1654944443.631662 iteration: 38785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12281 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.18838 L1 loss: 0.0000e+00 L2 loss: 0.64901 Learning rate: 0.02 Mask loss: 0.08939 RPN box loss: 0.05135 RPN score loss: 0.00541 RPN total loss: 0.05676 Total loss: 0.98354 timestamp: 1654944446.7959967 iteration: 38790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12417 FastRCNN class loss: 0.09124 FastRCNN total loss: 0.2154 L1 loss: 0.0000e+00 L2 loss: 0.64893 Learning rate: 0.02 Mask loss: 0.17609 RPN box loss: 0.03065 RPN score loss: 0.01068 RPN total loss: 0.04133 Total loss: 1.08175 timestamp: 1654944450.0304046 iteration: 38795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14269 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.21612 L1 loss: 0.0000e+00 L2 loss: 0.64886 Learning rate: 0.02 Mask loss: 0.17246 RPN box loss: 0.05608 RPN score loss: 0.0152 RPN total loss: 0.07128 Total loss: 1.10872 timestamp: 1654944453.2448823 iteration: 38800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16403 FastRCNN class loss: 0.04915 FastRCNN total loss: 0.21318 L1 loss: 0.0000e+00 L2 loss: 0.64879 Learning rate: 0.02 Mask loss: 0.10702 RPN box loss: 0.04539 RPN score loss: 0.00583 RPN total loss: 0.05122 Total loss: 1.0202 timestamp: 1654944456.5432127 iteration: 38805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18934 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.26375 L1 loss: 0.0000e+00 L2 loss: 0.64872 Learning rate: 0.02 Mask loss: 0.1782 RPN box loss: 0.03082 RPN score loss: 0.00554 RPN total loss: 0.03637 Total loss: 1.12704 timestamp: 1654944459.7741642 iteration: 38810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08438 FastRCNN class loss: 0.05233 FastRCNN total loss: 0.1367 L1 loss: 0.0000e+00 L2 loss: 0.64863 Learning rate: 0.02 Mask loss: 0.18216 RPN box loss: 0.01294 RPN score loss: 0.00336 RPN total loss: 0.01629 Total loss: 0.98379 timestamp: 1654944462.9913974 iteration: 38815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1057 FastRCNN class loss: 0.08239 FastRCNN total loss: 0.1881 L1 loss: 0.0000e+00 L2 loss: 0.64855 Learning rate: 0.02 Mask loss: 0.21044 RPN box loss: 0.03172 RPN score loss: 0.01309 RPN total loss: 0.04481 Total loss: 1.0919 timestamp: 1654944466.21895 iteration: 38820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15004 FastRCNN class loss: 0.14561 FastRCNN total loss: 0.29565 L1 loss: 0.0000e+00 L2 loss: 0.64846 Learning rate: 0.02 Mask loss: 0.2249 RPN box loss: 0.02113 RPN score loss: 0.0235 RPN total loss: 0.04463 Total loss: 1.21364 timestamp: 1654944469.4766915 iteration: 38825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11637 FastRCNN class loss: 0.07854 FastRCNN total loss: 0.19491 L1 loss: 0.0000e+00 L2 loss: 0.64837 Learning rate: 0.02 Mask loss: 0.20359 RPN box loss: 0.00703 RPN score loss: 0.00187 RPN total loss: 0.00889 Total loss: 1.05577 timestamp: 1654944472.6801996 iteration: 38830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12303 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.17277 L1 loss: 0.0000e+00 L2 loss: 0.6483 Learning rate: 0.02 Mask loss: 0.14206 RPN box loss: 0.00985 RPN score loss: 0.00256 RPN total loss: 0.0124 Total loss: 0.97554 timestamp: 1654944475.8473635 iteration: 38835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10712 FastRCNN class loss: 0.09963 FastRCNN total loss: 0.20675 L1 loss: 0.0000e+00 L2 loss: 0.64823 Learning rate: 0.02 Mask loss: 0.17434 RPN box loss: 0.02902 RPN score loss: 0.00722 RPN total loss: 0.03624 Total loss: 1.06557 timestamp: 1654944479.102457 iteration: 38840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19503 FastRCNN class loss: 0.07106 FastRCNN total loss: 0.26609 L1 loss: 0.0000e+00 L2 loss: 0.64813 Learning rate: 0.02 Mask loss: 0.15061 RPN box loss: 0.02687 RPN score loss: 0.00979 RPN total loss: 0.03666 Total loss: 1.1015 timestamp: 1654944482.2666595 iteration: 38845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06957 FastRCNN class loss: 0.07288 FastRCNN total loss: 0.14245 L1 loss: 0.0000e+00 L2 loss: 0.64807 Learning rate: 0.02 Mask loss: 0.16318 RPN box loss: 0.03126 RPN score loss: 0.01066 RPN total loss: 0.04192 Total loss: 0.99562 timestamp: 1654944485.52561 iteration: 38850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18416 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.2478 L1 loss: 0.0000e+00 L2 loss: 0.64797 Learning rate: 0.02 Mask loss: 0.10347 RPN box loss: 0.03289 RPN score loss: 0.00452 RPN total loss: 0.03741 Total loss: 1.03665 timestamp: 1654944488.7422447 iteration: 38855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22235 FastRCNN class loss: 0.08037 FastRCNN total loss: 0.30273 L1 loss: 0.0000e+00 L2 loss: 0.64788 Learning rate: 0.02 Mask loss: 0.14094 RPN box loss: 0.04808 RPN score loss: 0.00921 RPN total loss: 0.05729 Total loss: 1.14884 timestamp: 1654944491.8897154 iteration: 38860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10672 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.17645 L1 loss: 0.0000e+00 L2 loss: 0.64781 Learning rate: 0.02 Mask loss: 0.13869 RPN box loss: 0.03312 RPN score loss: 0.00728 RPN total loss: 0.04039 Total loss: 1.00334 timestamp: 1654944495.1876218 iteration: 38865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10692 FastRCNN class loss: 0.04612 FastRCNN total loss: 0.15304 L1 loss: 0.0000e+00 L2 loss: 0.64773 Learning rate: 0.02 Mask loss: 0.15444 RPN box loss: 0.02796 RPN score loss: 0.00354 RPN total loss: 0.03151 Total loss: 0.98671 timestamp: 1654944498.4190772 iteration: 38870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13259 FastRCNN class loss: 0.12623 FastRCNN total loss: 0.25882 L1 loss: 0.0000e+00 L2 loss: 0.64766 Learning rate: 0.02 Mask loss: 0.18412 RPN box loss: 0.04578 RPN score loss: 0.0157 RPN total loss: 0.06148 Total loss: 1.15208 timestamp: 1654944501.594525 iteration: 38875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1328 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.1977 L1 loss: 0.0000e+00 L2 loss: 0.64757 Learning rate: 0.02 Mask loss: 0.12685 RPN box loss: 0.03819 RPN score loss: 0.00531 RPN total loss: 0.04349 Total loss: 1.01562 timestamp: 1654944504.7839017 iteration: 38880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10934 FastRCNN class loss: 0.14119 FastRCNN total loss: 0.25052 L1 loss: 0.0000e+00 L2 loss: 0.64749 Learning rate: 0.02 Mask loss: 0.16333 RPN box loss: 0.0375 RPN score loss: 0.01495 RPN total loss: 0.05244 Total loss: 1.11379 timestamp: 1654944508.0633144 iteration: 38885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17121 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.2206 L1 loss: 0.0000e+00 L2 loss: 0.64743 Learning rate: 0.02 Mask loss: 0.1159 RPN box loss: 0.05342 RPN score loss: 0.00382 RPN total loss: 0.05724 Total loss: 1.04117 timestamp: 1654944511.2643545 iteration: 38890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14738 FastRCNN class loss: 0.06904 FastRCNN total loss: 0.21642 L1 loss: 0.0000e+00 L2 loss: 0.64735 Learning rate: 0.02 Mask loss: 0.16596 RPN box loss: 0.04827 RPN score loss: 0.00719 RPN total loss: 0.05546 Total loss: 1.08519 timestamp: 1654944514.466162 iteration: 38895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13863 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.20233 L1 loss: 0.0000e+00 L2 loss: 0.64723 Learning rate: 0.02 Mask loss: 0.12998 RPN box loss: 0.05747 RPN score loss: 0.00464 RPN total loss: 0.06211 Total loss: 1.04165 timestamp: 1654944517.7104034 iteration: 38900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08488 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.17516 L1 loss: 0.0000e+00 L2 loss: 0.64712 Learning rate: 0.02 Mask loss: 0.11835 RPN box loss: 0.00736 RPN score loss: 0.00302 RPN total loss: 0.01038 Total loss: 0.951 timestamp: 1654944520.8943832 iteration: 38905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11884 FastRCNN class loss: 0.13924 FastRCNN total loss: 0.25808 L1 loss: 0.0000e+00 L2 loss: 0.64705 Learning rate: 0.02 Mask loss: 0.15018 RPN box loss: 0.02446 RPN score loss: 0.00958 RPN total loss: 0.03404 Total loss: 1.08935 timestamp: 1654944524.1012423 iteration: 38910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09559 FastRCNN class loss: 0.10645 FastRCNN total loss: 0.20204 L1 loss: 0.0000e+00 L2 loss: 0.64697 Learning rate: 0.02 Mask loss: 0.16358 RPN box loss: 0.05828 RPN score loss: 0.02015 RPN total loss: 0.07843 Total loss: 1.09103 timestamp: 1654944527.3441346 iteration: 38915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26967 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.3446 L1 loss: 0.0000e+00 L2 loss: 0.6469 Learning rate: 0.02 Mask loss: 0.15372 RPN box loss: 0.0433 RPN score loss: 0.00884 RPN total loss: 0.05214 Total loss: 1.19736 timestamp: 1654944530.5366693 iteration: 38920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11886 FastRCNN class loss: 0.09667 FastRCNN total loss: 0.21552 L1 loss: 0.0000e+00 L2 loss: 0.64684 Learning rate: 0.02 Mask loss: 0.13115 RPN box loss: 0.02408 RPN score loss: 0.00554 RPN total loss: 0.02962 Total loss: 1.02313 timestamp: 1654944533.7107086 iteration: 38925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06159 FastRCNN class loss: 0.04148 FastRCNN total loss: 0.10306 L1 loss: 0.0000e+00 L2 loss: 0.64675 Learning rate: 0.02 Mask loss: 0.09236 RPN box loss: 0.00618 RPN score loss: 0.00327 RPN total loss: 0.00945 Total loss: 0.85162 timestamp: 1654944536.9056711 iteration: 38930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12362 FastRCNN class loss: 0.08189 FastRCNN total loss: 0.20551 L1 loss: 0.0000e+00 L2 loss: 0.64666 Learning rate: 0.02 Mask loss: 0.10818 RPN box loss: 0.0528 RPN score loss: 0.00227 RPN total loss: 0.05507 Total loss: 1.01542 timestamp: 1654944540.108109 iteration: 38935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19296 FastRCNN class loss: 0.13141 FastRCNN total loss: 0.32437 L1 loss: 0.0000e+00 L2 loss: 0.64658 Learning rate: 0.02 Mask loss: 0.25685 RPN box loss: 0.04293 RPN score loss: 0.01712 RPN total loss: 0.06006 Total loss: 1.28785 timestamp: 1654944543.2779233 iteration: 38940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11951 FastRCNN class loss: 0.10215 FastRCNN total loss: 0.22166 L1 loss: 0.0000e+00 L2 loss: 0.64648 Learning rate: 0.02 Mask loss: 0.13836 RPN box loss: 0.02719 RPN score loss: 0.00278 RPN total loss: 0.02997 Total loss: 1.03646 timestamp: 1654944546.4238174 iteration: 38945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16913 FastRCNN class loss: 0.10273 FastRCNN total loss: 0.27185 L1 loss: 0.0000e+00 L2 loss: 0.64638 Learning rate: 0.02 Mask loss: 0.28402 RPN box loss: 0.01455 RPN score loss: 0.00404 RPN total loss: 0.01859 Total loss: 1.22085 timestamp: 1654944549.5924218 iteration: 38950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08168 FastRCNN class loss: 0.08347 FastRCNN total loss: 0.16515 L1 loss: 0.0000e+00 L2 loss: 0.64632 Learning rate: 0.02 Mask loss: 0.12362 RPN box loss: 0.02779 RPN score loss: 0.00817 RPN total loss: 0.03596 Total loss: 0.97105 timestamp: 1654944552.788108 iteration: 38955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09913 FastRCNN class loss: 0.07612 FastRCNN total loss: 0.17525 L1 loss: 0.0000e+00 L2 loss: 0.64624 Learning rate: 0.02 Mask loss: 0.14865 RPN box loss: 0.01995 RPN score loss: 0.0065 RPN total loss: 0.02644 Total loss: 0.99658 timestamp: 1654944555.9669049 iteration: 38960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1581 FastRCNN class loss: 0.09807 FastRCNN total loss: 0.25617 L1 loss: 0.0000e+00 L2 loss: 0.64615 Learning rate: 0.02 Mask loss: 0.14961 RPN box loss: 0.04254 RPN score loss: 0.00427 RPN total loss: 0.04681 Total loss: 1.09875 timestamp: 1654944559.1016383 iteration: 38965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.131 FastRCNN class loss: 0.06136 FastRCNN total loss: 0.19236 L1 loss: 0.0000e+00 L2 loss: 0.64609 Learning rate: 0.02 Mask loss: 0.14396 RPN box loss: 0.06509 RPN score loss: 0.00646 RPN total loss: 0.07155 Total loss: 1.05395 timestamp: 1654944562.2857895 iteration: 38970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12359 FastRCNN class loss: 0.06175 FastRCNN total loss: 0.18533 L1 loss: 0.0000e+00 L2 loss: 0.646 Learning rate: 0.02 Mask loss: 0.133 RPN box loss: 0.01837 RPN score loss: 0.00127 RPN total loss: 0.01965 Total loss: 0.98398 timestamp: 1654944565.4788277 iteration: 38975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13454 FastRCNN class loss: 0.1148 FastRCNN total loss: 0.24934 L1 loss: 0.0000e+00 L2 loss: 0.64592 Learning rate: 0.02 Mask loss: 0.14823 RPN box loss: 0.02307 RPN score loss: 0.0028 RPN total loss: 0.02587 Total loss: 1.06936 timestamp: 1654944568.6378815 iteration: 38980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11216 FastRCNN class loss: 0.05103 FastRCNN total loss: 0.16319 L1 loss: 0.0000e+00 L2 loss: 0.64586 Learning rate: 0.02 Mask loss: 0.10325 RPN box loss: 0.01339 RPN score loss: 0.00119 RPN total loss: 0.01457 Total loss: 0.92687 timestamp: 1654944571.766508 iteration: 38985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09516 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.15575 L1 loss: 0.0000e+00 L2 loss: 0.6458 Learning rate: 0.02 Mask loss: 0.09723 RPN box loss: 0.02483 RPN score loss: 0.00318 RPN total loss: 0.02802 Total loss: 0.92679 timestamp: 1654944574.9344103 iteration: 38990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10135 FastRCNN class loss: 0.06383 FastRCNN total loss: 0.16518 L1 loss: 0.0000e+00 L2 loss: 0.64573 Learning rate: 0.02 Mask loss: 0.13422 RPN box loss: 0.02024 RPN score loss: 0.00459 RPN total loss: 0.02483 Total loss: 0.96996 timestamp: 1654944578.1509128 iteration: 38995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07548 FastRCNN class loss: 0.06367 FastRCNN total loss: 0.13915 L1 loss: 0.0000e+00 L2 loss: 0.64564 Learning rate: 0.02 Mask loss: 0.09796 RPN box loss: 0.03466 RPN score loss: 0.01387 RPN total loss: 0.04853 Total loss: 0.93128 timestamp: 1654944581.3043365 iteration: 39000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10747 FastRCNN class loss: 0.02837 FastRCNN total loss: 0.13584 L1 loss: 0.0000e+00 L2 loss: 0.64553 Learning rate: 0.02 Mask loss: 0.11667 RPN box loss: 0.03421 RPN score loss: 0.0013 RPN total loss: 0.03551 Total loss: 0.93355 timestamp: 1654944584.558371 iteration: 39005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14556 FastRCNN class loss: 0.084 FastRCNN total loss: 0.22956 L1 loss: 0.0000e+00 L2 loss: 0.64546 Learning rate: 0.02 Mask loss: 0.15587 RPN box loss: 0.01743 RPN score loss: 0.00393 RPN total loss: 0.02135 Total loss: 1.05224 timestamp: 1654944587.711274 iteration: 39010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14663 FastRCNN class loss: 0.08708 FastRCNN total loss: 0.23371 L1 loss: 0.0000e+00 L2 loss: 0.6454 Learning rate: 0.02 Mask loss: 0.12003 RPN box loss: 0.02235 RPN score loss: 0.00456 RPN total loss: 0.02691 Total loss: 1.02606 timestamp: 1654944590.8718193 iteration: 39015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07489 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.15074 L1 loss: 0.0000e+00 L2 loss: 0.64532 Learning rate: 0.02 Mask loss: 0.17148 RPN box loss: 0.03301 RPN score loss: 0.00551 RPN total loss: 0.03852 Total loss: 1.00606 timestamp: 1654944594.107464 iteration: 39020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09942 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.16679 L1 loss: 0.0000e+00 L2 loss: 0.64525 Learning rate: 0.02 Mask loss: 0.16448 RPN box loss: 0.07085 RPN score loss: 0.00499 RPN total loss: 0.07584 Total loss: 1.05237 timestamp: 1654944597.3517764 iteration: 39025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14275 FastRCNN class loss: 0.13787 FastRCNN total loss: 0.28062 L1 loss: 0.0000e+00 L2 loss: 0.64516 Learning rate: 0.02 Mask loss: 0.18082 RPN box loss: 0.018 RPN score loss: 0.0089 RPN total loss: 0.0269 Total loss: 1.13351 timestamp: 1654944600.4957762 iteration: 39030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1033 FastRCNN class loss: 0.04162 FastRCNN total loss: 0.14492 L1 loss: 0.0000e+00 L2 loss: 0.64509 Learning rate: 0.02 Mask loss: 0.10704 RPN box loss: 0.02259 RPN score loss: 0.00565 RPN total loss: 0.02824 Total loss: 0.92528 timestamp: 1654944603.6759691 iteration: 39035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19826 FastRCNN class loss: 0.17743 FastRCNN total loss: 0.37569 L1 loss: 0.0000e+00 L2 loss: 0.645 Learning rate: 0.02 Mask loss: 0.24659 RPN box loss: 0.0538 RPN score loss: 0.00897 RPN total loss: 0.06277 Total loss: 1.33006 timestamp: 1654944606.8898728 iteration: 39040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18133 FastRCNN class loss: 0.19519 FastRCNN total loss: 0.37653 L1 loss: 0.0000e+00 L2 loss: 0.6449 Learning rate: 0.02 Mask loss: 0.16976 RPN box loss: 0.0233 RPN score loss: 0.00688 RPN total loss: 0.03017 Total loss: 1.22137 timestamp: 1654944609.979806 iteration: 39045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21041 FastRCNN class loss: 0.10058 FastRCNN total loss: 0.31099 L1 loss: 0.0000e+00 L2 loss: 0.64485 Learning rate: 0.02 Mask loss: 0.20069 RPN box loss: 0.03639 RPN score loss: 0.00692 RPN total loss: 0.04331 Total loss: 1.19984 timestamp: 1654944613.161194 iteration: 39050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11139 FastRCNN class loss: 0.10211 FastRCNN total loss: 0.2135 L1 loss: 0.0000e+00 L2 loss: 0.64476 Learning rate: 0.02 Mask loss: 0.1993 RPN box loss: 0.03912 RPN score loss: 0.00328 RPN total loss: 0.04239 Total loss: 1.09995 timestamp: 1654944616.4192035 iteration: 39055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10439 FastRCNN class loss: 0.12136 FastRCNN total loss: 0.22575 L1 loss: 0.0000e+00 L2 loss: 0.64465 Learning rate: 0.02 Mask loss: 0.16745 RPN box loss: 0.0159 RPN score loss: 0.00395 RPN total loss: 0.01985 Total loss: 1.0577 timestamp: 1654944619.5682874 iteration: 39060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18309 FastRCNN class loss: 0.12512 FastRCNN total loss: 0.30821 L1 loss: 0.0000e+00 L2 loss: 0.64457 Learning rate: 0.02 Mask loss: 0.13091 RPN box loss: 0.03915 RPN score loss: 0.01022 RPN total loss: 0.04937 Total loss: 1.13306 timestamp: 1654944622.7920732 iteration: 39065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17331 FastRCNN class loss: 0.08925 FastRCNN total loss: 0.26256 L1 loss: 0.0000e+00 L2 loss: 0.6445 Learning rate: 0.02 Mask loss: 0.13271 RPN box loss: 0.02658 RPN score loss: 0.0065 RPN total loss: 0.03308 Total loss: 1.07284 timestamp: 1654944625.9331136 iteration: 39070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11999 FastRCNN class loss: 0.07836 FastRCNN total loss: 0.19835 L1 loss: 0.0000e+00 L2 loss: 0.64442 Learning rate: 0.02 Mask loss: 0.14744 RPN box loss: 0.01767 RPN score loss: 0.00423 RPN total loss: 0.0219 Total loss: 1.01212 timestamp: 1654944629.133663 iteration: 39075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16083 FastRCNN class loss: 0.08999 FastRCNN total loss: 0.25083 L1 loss: 0.0000e+00 L2 loss: 0.64434 Learning rate: 0.02 Mask loss: 0.13576 RPN box loss: 0.0161 RPN score loss: 0.004 RPN total loss: 0.02009 Total loss: 1.05103 timestamp: 1654944632.3365035 iteration: 39080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09763 FastRCNN class loss: 0.08877 FastRCNN total loss: 0.18641 L1 loss: 0.0000e+00 L2 loss: 0.64428 Learning rate: 0.02 Mask loss: 0.12337 RPN box loss: 0.01509 RPN score loss: 0.01659 RPN total loss: 0.03168 Total loss: 0.98573 timestamp: 1654944635.5266137 iteration: 39085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11688 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.18267 L1 loss: 0.0000e+00 L2 loss: 0.64421 Learning rate: 0.02 Mask loss: 0.15101 RPN box loss: 0.084 RPN score loss: 0.00384 RPN total loss: 0.08784 Total loss: 1.06573 timestamp: 1654944638.748077 iteration: 39090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08284 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.13223 L1 loss: 0.0000e+00 L2 loss: 0.64413 Learning rate: 0.02 Mask loss: 0.14187 RPN box loss: 0.03637 RPN score loss: 0.00124 RPN total loss: 0.03761 Total loss: 0.95584 timestamp: 1654944641.895512 iteration: 39095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12576 FastRCNN class loss: 0.08555 FastRCNN total loss: 0.21132 L1 loss: 0.0000e+00 L2 loss: 0.64405 Learning rate: 0.02 Mask loss: 0.08675 RPN box loss: 0.0106 RPN score loss: 0.00373 RPN total loss: 0.01434 Total loss: 0.95645 timestamp: 1654944645.0823038 iteration: 39100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0758 FastRCNN class loss: 0.06347 FastRCNN total loss: 0.13928 L1 loss: 0.0000e+00 L2 loss: 0.64397 Learning rate: 0.02 Mask loss: 0.09834 RPN box loss: 0.01767 RPN score loss: 0.0009 RPN total loss: 0.01857 Total loss: 0.90016 timestamp: 1654944648.2876325 iteration: 39105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13245 FastRCNN class loss: 0.07945 FastRCNN total loss: 0.2119 L1 loss: 0.0000e+00 L2 loss: 0.64388 Learning rate: 0.02 Mask loss: 0.16173 RPN box loss: 0.08191 RPN score loss: 0.0098 RPN total loss: 0.09171 Total loss: 1.10922 timestamp: 1654944651.4433084 iteration: 39110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12193 FastRCNN class loss: 0.12416 FastRCNN total loss: 0.24609 L1 loss: 0.0000e+00 L2 loss: 0.64379 Learning rate: 0.02 Mask loss: 0.14194 RPN box loss: 0.07203 RPN score loss: 0.01159 RPN total loss: 0.08362 Total loss: 1.11544 timestamp: 1654944654.671196 iteration: 39115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16355 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.23961 L1 loss: 0.0000e+00 L2 loss: 0.64371 Learning rate: 0.02 Mask loss: 0.12811 RPN box loss: 0.02787 RPN score loss: 0.00359 RPN total loss: 0.03146 Total loss: 1.04289 timestamp: 1654944657.8449187 iteration: 39120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09855 FastRCNN class loss: 0.05738 FastRCNN total loss: 0.15594 L1 loss: 0.0000e+00 L2 loss: 0.64363 Learning rate: 0.02 Mask loss: 0.12477 RPN box loss: 0.0114 RPN score loss: 0.00216 RPN total loss: 0.01356 Total loss: 0.93789 timestamp: 1654944661.0607839 iteration: 39125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12474 FastRCNN class loss: 0.04883 FastRCNN total loss: 0.17357 L1 loss: 0.0000e+00 L2 loss: 0.64355 Learning rate: 0.02 Mask loss: 0.11671 RPN box loss: 0.03238 RPN score loss: 0.00383 RPN total loss: 0.03621 Total loss: 0.97003 timestamp: 1654944664.213532 iteration: 39130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13489 FastRCNN class loss: 0.08539 FastRCNN total loss: 0.22028 L1 loss: 0.0000e+00 L2 loss: 0.64348 Learning rate: 0.02 Mask loss: 0.20034 RPN box loss: 0.02174 RPN score loss: 0.00829 RPN total loss: 0.03003 Total loss: 1.09413 timestamp: 1654944667.4259837 iteration: 39135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12679 FastRCNN class loss: 0.10494 FastRCNN total loss: 0.23172 L1 loss: 0.0000e+00 L2 loss: 0.6434 Learning rate: 0.02 Mask loss: 0.19219 RPN box loss: 0.06229 RPN score loss: 0.00676 RPN total loss: 0.06905 Total loss: 1.13637 timestamp: 1654944670.693054 iteration: 39140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15773 FastRCNN class loss: 0.09332 FastRCNN total loss: 0.25105 L1 loss: 0.0000e+00 L2 loss: 0.64332 Learning rate: 0.02 Mask loss: 0.11357 RPN box loss: 0.02976 RPN score loss: 0.00244 RPN total loss: 0.0322 Total loss: 1.04014 timestamp: 1654944673.8812952 iteration: 39145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07774 FastRCNN class loss: 0.08286 FastRCNN total loss: 0.1606 L1 loss: 0.0000e+00 L2 loss: 0.64325 Learning rate: 0.02 Mask loss: 0.16491 RPN box loss: 0.06831 RPN score loss: 0.0061 RPN total loss: 0.07441 Total loss: 1.04317 timestamp: 1654944677.1045299 iteration: 39150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14449 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.22458 L1 loss: 0.0000e+00 L2 loss: 0.64317 Learning rate: 0.02 Mask loss: 0.19377 RPN box loss: 0.03693 RPN score loss: 0.02203 RPN total loss: 0.05896 Total loss: 1.12047 timestamp: 1654944680.3885407 iteration: 39155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18303 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.28433 L1 loss: 0.0000e+00 L2 loss: 0.64308 Learning rate: 0.02 Mask loss: 0.1573 RPN box loss: 0.0074 RPN score loss: 0.00224 RPN total loss: 0.00964 Total loss: 1.09435 timestamp: 1654944683.5829115 iteration: 39160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11858 FastRCNN class loss: 0.06073 FastRCNN total loss: 0.17931 L1 loss: 0.0000e+00 L2 loss: 0.64299 Learning rate: 0.02 Mask loss: 0.15178 RPN box loss: 0.01159 RPN score loss: 0.00254 RPN total loss: 0.01413 Total loss: 0.98821 timestamp: 1654944686.781639 iteration: 39165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15441 FastRCNN class loss: 0.07581 FastRCNN total loss: 0.23021 L1 loss: 0.0000e+00 L2 loss: 0.64293 Learning rate: 0.02 Mask loss: 0.13976 RPN box loss: 0.04947 RPN score loss: 0.01799 RPN total loss: 0.06745 Total loss: 1.08035 timestamp: 1654944690.0093272 iteration: 39170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.05373 FastRCNN total loss: 0.17368 L1 loss: 0.0000e+00 L2 loss: 0.64284 Learning rate: 0.02 Mask loss: 0.07735 RPN box loss: 0.00577 RPN score loss: 0.00177 RPN total loss: 0.00753 Total loss: 0.90139 timestamp: 1654944693.218133 iteration: 39175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11845 FastRCNN class loss: 0.05437 FastRCNN total loss: 0.17283 L1 loss: 0.0000e+00 L2 loss: 0.64274 Learning rate: 0.02 Mask loss: 0.083 RPN box loss: 0.0208 RPN score loss: 0.00661 RPN total loss: 0.02741 Total loss: 0.92598 timestamp: 1654944696.444643 iteration: 39180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09259 FastRCNN class loss: 0.08839 FastRCNN total loss: 0.18099 L1 loss: 0.0000e+00 L2 loss: 0.64268 Learning rate: 0.02 Mask loss: 0.1015 RPN box loss: 0.03293 RPN score loss: 0.00173 RPN total loss: 0.03466 Total loss: 0.95983 timestamp: 1654944699.665675 iteration: 39185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1125 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.1782 L1 loss: 0.0000e+00 L2 loss: 0.64259 Learning rate: 0.02 Mask loss: 0.16615 RPN box loss: 0.06942 RPN score loss: 0.01444 RPN total loss: 0.08385 Total loss: 1.07079 timestamp: 1654944702.8883383 iteration: 39190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08563 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.16082 L1 loss: 0.0000e+00 L2 loss: 0.6425 Learning rate: 0.02 Mask loss: 0.15202 RPN box loss: 0.01976 RPN score loss: 0.0044 RPN total loss: 0.02416 Total loss: 0.9795 timestamp: 1654944706.0768626 iteration: 39195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11991 FastRCNN class loss: 0.07559 FastRCNN total loss: 0.1955 L1 loss: 0.0000e+00 L2 loss: 0.64243 Learning rate: 0.02 Mask loss: 0.15808 RPN box loss: 0.01856 RPN score loss: 0.00676 RPN total loss: 0.02533 Total loss: 1.02133 timestamp: 1654944709.292769 iteration: 39200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13734 FastRCNN class loss: 0.17454 FastRCNN total loss: 0.31189 L1 loss: 0.0000e+00 L2 loss: 0.64234 Learning rate: 0.02 Mask loss: 0.13316 RPN box loss: 0.0353 RPN score loss: 0.01203 RPN total loss: 0.04733 Total loss: 1.13472 timestamp: 1654944712.472643 iteration: 39205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1135 FastRCNN class loss: 0.05356 FastRCNN total loss: 0.16706 L1 loss: 0.0000e+00 L2 loss: 0.64226 Learning rate: 0.02 Mask loss: 0.12118 RPN box loss: 0.02336 RPN score loss: 0.00849 RPN total loss: 0.03185 Total loss: 0.96236 timestamp: 1654944715.672796 iteration: 39210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08062 FastRCNN class loss: 0.03753 FastRCNN total loss: 0.11815 L1 loss: 0.0000e+00 L2 loss: 0.64217 Learning rate: 0.02 Mask loss: 0.08438 RPN box loss: 0.01958 RPN score loss: 0.00668 RPN total loss: 0.02626 Total loss: 0.87095 timestamp: 1654944718.8616421 iteration: 39215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10248 FastRCNN class loss: 0.09249 FastRCNN total loss: 0.19497 L1 loss: 0.0000e+00 L2 loss: 0.64209 Learning rate: 0.02 Mask loss: 0.10009 RPN box loss: 0.00949 RPN score loss: 0.00138 RPN total loss: 0.01088 Total loss: 0.94802 timestamp: 1654944722.0860686 iteration: 39220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16286 FastRCNN class loss: 0.05735 FastRCNN total loss: 0.22022 L1 loss: 0.0000e+00 L2 loss: 0.64201 Learning rate: 0.02 Mask loss: 0.14038 RPN box loss: 0.01685 RPN score loss: 0.00511 RPN total loss: 0.02195 Total loss: 1.02456 timestamp: 1654944725.2672298 iteration: 39225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08019 FastRCNN class loss: 0.07387 FastRCNN total loss: 0.15406 L1 loss: 0.0000e+00 L2 loss: 0.64193 Learning rate: 0.02 Mask loss: 0.16824 RPN box loss: 0.01093 RPN score loss: 0.00427 RPN total loss: 0.01519 Total loss: 0.97943 timestamp: 1654944728.4861193 iteration: 39230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10587 FastRCNN class loss: 0.08109 FastRCNN total loss: 0.18695 L1 loss: 0.0000e+00 L2 loss: 0.64186 Learning rate: 0.02 Mask loss: 0.10741 RPN box loss: 0.04976 RPN score loss: 0.00511 RPN total loss: 0.05487 Total loss: 0.99109 timestamp: 1654944731.622801 iteration: 39235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11489 FastRCNN class loss: 0.05016 FastRCNN total loss: 0.16505 L1 loss: 0.0000e+00 L2 loss: 0.64178 Learning rate: 0.02 Mask loss: 0.13356 RPN box loss: 0.00788 RPN score loss: 0.00749 RPN total loss: 0.01537 Total loss: 0.95576 timestamp: 1654944734.9623706 iteration: 39240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1032 FastRCNN class loss: 0.14804 FastRCNN total loss: 0.25124 L1 loss: 0.0000e+00 L2 loss: 0.64171 Learning rate: 0.02 Mask loss: 0.2439 RPN box loss: 0.02583 RPN score loss: 0.03625 RPN total loss: 0.06208 Total loss: 1.19893 timestamp: 1654944738.147269 iteration: 39245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12987 FastRCNN class loss: 0.08513 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 0.6416 Learning rate: 0.02 Mask loss: 0.17528 RPN box loss: 0.0512 RPN score loss: 0.00704 RPN total loss: 0.05824 Total loss: 1.09012 timestamp: 1654944741.3667939 iteration: 39250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15376 FastRCNN class loss: 0.09354 FastRCNN total loss: 0.2473 L1 loss: 0.0000e+00 L2 loss: 0.64151 Learning rate: 0.02 Mask loss: 0.15448 RPN box loss: 0.05915 RPN score loss: 0.00847 RPN total loss: 0.06762 Total loss: 1.11091 timestamp: 1654944744.531891 iteration: 39255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10526 FastRCNN class loss: 0.05158 FastRCNN total loss: 0.15683 L1 loss: 0.0000e+00 L2 loss: 0.64147 Learning rate: 0.02 Mask loss: 0.1534 RPN box loss: 0.04199 RPN score loss: 0.00594 RPN total loss: 0.04793 Total loss: 0.99963 timestamp: 1654944747.684322 iteration: 39260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11235 FastRCNN class loss: 0.09983 FastRCNN total loss: 0.21218 L1 loss: 0.0000e+00 L2 loss: 0.6414 Learning rate: 0.02 Mask loss: 0.17429 RPN box loss: 0.02553 RPN score loss: 0.00703 RPN total loss: 0.03256 Total loss: 1.06043 timestamp: 1654944750.7933726 iteration: 39265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.20077 L1 loss: 0.0000e+00 L2 loss: 0.64136 Learning rate: 0.02 Mask loss: 0.17095 RPN box loss: 0.04373 RPN score loss: 0.01164 RPN total loss: 0.05537 Total loss: 1.06845 timestamp: 1654944753.9394348 iteration: 39270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07426 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.16546 L1 loss: 0.0000e+00 L2 loss: 0.64126 Learning rate: 0.02 Mask loss: 0.13097 RPN box loss: 0.02144 RPN score loss: 0.00422 RPN total loss: 0.02565 Total loss: 0.96335 timestamp: 1654944757.1069846 iteration: 39275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11222 FastRCNN class loss: 0.08831 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 0.64117 Learning rate: 0.02 Mask loss: 0.10944 RPN box loss: 0.02352 RPN score loss: 0.00258 RPN total loss: 0.0261 Total loss: 0.97725 timestamp: 1654944760.2659347 iteration: 39280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10233 FastRCNN class loss: 0.05793 FastRCNN total loss: 0.16026 L1 loss: 0.0000e+00 L2 loss: 0.64108 Learning rate: 0.02 Mask loss: 0.09586 RPN box loss: 0.01308 RPN score loss: 0.00309 RPN total loss: 0.01617 Total loss: 0.91337 timestamp: 1654944763.419556 iteration: 39285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18681 FastRCNN class loss: 0.08517 FastRCNN total loss: 0.27199 L1 loss: 0.0000e+00 L2 loss: 0.64102 Learning rate: 0.02 Mask loss: 0.14335 RPN box loss: 0.03276 RPN score loss: 0.00479 RPN total loss: 0.03755 Total loss: 1.0939 timestamp: 1654944766.6015286 iteration: 39290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2127 FastRCNN class loss: 0.0693 FastRCNN total loss: 0.282 L1 loss: 0.0000e+00 L2 loss: 0.64096 Learning rate: 0.02 Mask loss: 0.10911 RPN box loss: 0.00587 RPN score loss: 0.00716 RPN total loss: 0.01304 Total loss: 1.04511 timestamp: 1654944769.8905568 iteration: 39295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08409 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.13945 L1 loss: 0.0000e+00 L2 loss: 0.64089 Learning rate: 0.02 Mask loss: 0.10804 RPN box loss: 0.0383 RPN score loss: 0.00711 RPN total loss: 0.04541 Total loss: 0.93378 timestamp: 1654944773.055424 iteration: 39300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0819 FastRCNN class loss: 0.12278 FastRCNN total loss: 0.20467 L1 loss: 0.0000e+00 L2 loss: 0.64081 Learning rate: 0.02 Mask loss: 0.14637 RPN box loss: 0.03972 RPN score loss: 0.00817 RPN total loss: 0.04789 Total loss: 1.03974 timestamp: 1654944776.2288485 iteration: 39305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.20261 L1 loss: 0.0000e+00 L2 loss: 0.64072 Learning rate: 0.02 Mask loss: 0.13386 RPN box loss: 0.04266 RPN score loss: 0.00457 RPN total loss: 0.04723 Total loss: 1.02442 timestamp: 1654944779.4743686 iteration: 39310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08874 FastRCNN class loss: 0.04825 FastRCNN total loss: 0.13699 L1 loss: 0.0000e+00 L2 loss: 0.64063 Learning rate: 0.02 Mask loss: 0.1088 RPN box loss: 0.0787 RPN score loss: 0.00456 RPN total loss: 0.08326 Total loss: 0.96968 timestamp: 1654944782.6295083 iteration: 39315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14704 FastRCNN class loss: 0.1209 FastRCNN total loss: 0.26794 L1 loss: 0.0000e+00 L2 loss: 0.64054 Learning rate: 0.02 Mask loss: 0.15927 RPN box loss: 0.06834 RPN score loss: 0.01551 RPN total loss: 0.08385 Total loss: 1.1516 timestamp: 1654944785.8372264 iteration: 39320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14148 FastRCNN class loss: 0.06567 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 0.64046 Learning rate: 0.02 Mask loss: 0.14101 RPN box loss: 0.0106 RPN score loss: 0.00371 RPN total loss: 0.01431 Total loss: 1.00294 timestamp: 1654944788.9713426 iteration: 39325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07977 FastRCNN class loss: 0.08054 FastRCNN total loss: 0.16031 L1 loss: 0.0000e+00 L2 loss: 0.64039 Learning rate: 0.02 Mask loss: 0.15471 RPN box loss: 0.01401 RPN score loss: 0.00703 RPN total loss: 0.02105 Total loss: 0.97646 timestamp: 1654944792.2477334 iteration: 39330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09787 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.6403 Learning rate: 0.02 Mask loss: 0.13914 RPN box loss: 0.02795 RPN score loss: 0.006 RPN total loss: 0.03396 Total loss: 0.97814 timestamp: 1654944795.3845205 iteration: 39335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.08696 FastRCNN total loss: 0.22548 L1 loss: 0.0000e+00 L2 loss: 0.64025 Learning rate: 0.02 Mask loss: 0.10029 RPN box loss: 0.02413 RPN score loss: 0.00287 RPN total loss: 0.02699 Total loss: 0.99301 timestamp: 1654944798.5562246 iteration: 39340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11454 FastRCNN class loss: 0.05152 FastRCNN total loss: 0.16606 L1 loss: 0.0000e+00 L2 loss: 0.64015 Learning rate: 0.02 Mask loss: 0.16993 RPN box loss: 0.05667 RPN score loss: 0.00875 RPN total loss: 0.06542 Total loss: 1.04156 timestamp: 1654944801.695683 iteration: 39345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15427 FastRCNN class loss: 0.08652 FastRCNN total loss: 0.24079 L1 loss: 0.0000e+00 L2 loss: 0.64006 Learning rate: 0.02 Mask loss: 0.21707 RPN box loss: 0.01723 RPN score loss: 0.00943 RPN total loss: 0.02666 Total loss: 1.12458 timestamp: 1654944804.8471155 iteration: 39350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15862 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.22022 L1 loss: 0.0000e+00 L2 loss: 0.64 Learning rate: 0.02 Mask loss: 0.11968 RPN box loss: 0.02488 RPN score loss: 0.00398 RPN total loss: 0.02886 Total loss: 1.00875 timestamp: 1654944808.1172004 iteration: 39355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12736 FastRCNN class loss: 0.11245 FastRCNN total loss: 0.23982 L1 loss: 0.0000e+00 L2 loss: 0.63991 Learning rate: 0.02 Mask loss: 0.18336 RPN box loss: 0.03055 RPN score loss: 0.00957 RPN total loss: 0.04012 Total loss: 1.1032 timestamp: 1654944811.3019254 iteration: 39360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15458 FastRCNN class loss: 0.05695 FastRCNN total loss: 0.21154 L1 loss: 0.0000e+00 L2 loss: 0.63983 Learning rate: 0.02 Mask loss: 0.08326 RPN box loss: 0.03285 RPN score loss: 0.00498 RPN total loss: 0.03783 Total loss: 0.97246 timestamp: 1654944814.4886825 iteration: 39365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15937 FastRCNN class loss: 0.0921 FastRCNN total loss: 0.25147 L1 loss: 0.0000e+00 L2 loss: 0.63978 Learning rate: 0.02 Mask loss: 0.14124 RPN box loss: 0.01142 RPN score loss: 0.00341 RPN total loss: 0.01483 Total loss: 1.04732 timestamp: 1654944817.6690938 iteration: 39370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12064 FastRCNN class loss: 0.09626 FastRCNN total loss: 0.2169 L1 loss: 0.0000e+00 L2 loss: 0.6397 Learning rate: 0.02 Mask loss: 0.26635 RPN box loss: 0.03418 RPN score loss: 0.01043 RPN total loss: 0.04461 Total loss: 1.16756 timestamp: 1654944820.896217 iteration: 39375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12559 FastRCNN class loss: 0.12024 FastRCNN total loss: 0.24583 L1 loss: 0.0000e+00 L2 loss: 0.63962 Learning rate: 0.02 Mask loss: 0.16728 RPN box loss: 0.02029 RPN score loss: 0.0097 RPN total loss: 0.02999 Total loss: 1.08271 timestamp: 1654944824.1500452 iteration: 39380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18858 FastRCNN class loss: 0.0881 FastRCNN total loss: 0.27668 L1 loss: 0.0000e+00 L2 loss: 0.63955 Learning rate: 0.02 Mask loss: 0.16751 RPN box loss: 0.02169 RPN score loss: 0.01084 RPN total loss: 0.03253 Total loss: 1.11628 timestamp: 1654944827.3229537 iteration: 39385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11032 FastRCNN class loss: 0.11776 FastRCNN total loss: 0.22808 L1 loss: 0.0000e+00 L2 loss: 0.63948 Learning rate: 0.02 Mask loss: 0.15927 RPN box loss: 0.04519 RPN score loss: 0.00437 RPN total loss: 0.04956 Total loss: 1.07639 timestamp: 1654944830.4939759 iteration: 39390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10199 FastRCNN class loss: 0.05899 FastRCNN total loss: 0.16098 L1 loss: 0.0000e+00 L2 loss: 0.63938 Learning rate: 0.02 Mask loss: 0.14037 RPN box loss: 0.02121 RPN score loss: 0.00668 RPN total loss: 0.02789 Total loss: 0.96862 timestamp: 1654944833.678959 iteration: 39395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14539 FastRCNN class loss: 0.1111 FastRCNN total loss: 0.25649 L1 loss: 0.0000e+00 L2 loss: 0.63931 Learning rate: 0.02 Mask loss: 0.16163 RPN box loss: 0.02606 RPN score loss: 0.02572 RPN total loss: 0.05178 Total loss: 1.10921 timestamp: 1654944836.7949483 iteration: 39400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1023 FastRCNN class loss: 0.05558 FastRCNN total loss: 0.15787 L1 loss: 0.0000e+00 L2 loss: 0.63921 Learning rate: 0.02 Mask loss: 0.23587 RPN box loss: 0.02407 RPN score loss: 0.00489 RPN total loss: 0.02897 Total loss: 1.06192 timestamp: 1654944840.0465386 iteration: 39405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.0729 FastRCNN total loss: 0.15576 L1 loss: 0.0000e+00 L2 loss: 0.63914 Learning rate: 0.02 Mask loss: 0.14898 RPN box loss: 0.03924 RPN score loss: 0.00508 RPN total loss: 0.04432 Total loss: 0.9882 timestamp: 1654944843.1846871 iteration: 39410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10925 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 0.63905 Learning rate: 0.02 Mask loss: 0.12239 RPN box loss: 0.02023 RPN score loss: 0.00336 RPN total loss: 0.02359 Total loss: 0.96969 timestamp: 1654944846.407002 iteration: 39415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12746 FastRCNN class loss: 0.05604 FastRCNN total loss: 0.18349 L1 loss: 0.0000e+00 L2 loss: 0.63899 Learning rate: 0.02 Mask loss: 0.15908 RPN box loss: 0.00942 RPN score loss: 0.0018 RPN total loss: 0.01122 Total loss: 0.99278 timestamp: 1654944849.6276786 iteration: 39420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09978 FastRCNN class loss: 0.08431 FastRCNN total loss: 0.18409 L1 loss: 0.0000e+00 L2 loss: 0.63892 Learning rate: 0.02 Mask loss: 0.16955 RPN box loss: 0.03832 RPN score loss: 0.01159 RPN total loss: 0.04991 Total loss: 1.04248 timestamp: 1654944852.8724716 iteration: 39425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13117 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.20573 L1 loss: 0.0000e+00 L2 loss: 0.63883 Learning rate: 0.02 Mask loss: 0.16309 RPN box loss: 0.04752 RPN score loss: 0.01447 RPN total loss: 0.06198 Total loss: 1.06963 timestamp: 1654944856.0938334 iteration: 39430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15092 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.24677 L1 loss: 0.0000e+00 L2 loss: 0.63875 Learning rate: 0.02 Mask loss: 0.1635 RPN box loss: 0.07028 RPN score loss: 0.00349 RPN total loss: 0.07378 Total loss: 1.12279 timestamp: 1654944859.2617757 iteration: 39435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13688 FastRCNN class loss: 0.09591 FastRCNN total loss: 0.23279 L1 loss: 0.0000e+00 L2 loss: 0.63867 Learning rate: 0.02 Mask loss: 0.13991 RPN box loss: 0.02363 RPN score loss: 0.00777 RPN total loss: 0.0314 Total loss: 1.04278 timestamp: 1654944862.4069142 iteration: 39440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10045 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.18387 L1 loss: 0.0000e+00 L2 loss: 0.63858 Learning rate: 0.02 Mask loss: 0.17024 RPN box loss: 0.02565 RPN score loss: 0.00338 RPN total loss: 0.02903 Total loss: 1.02172 timestamp: 1654944865.614159 iteration: 39445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17222 FastRCNN class loss: 0.07957 FastRCNN total loss: 0.25179 L1 loss: 0.0000e+00 L2 loss: 0.63849 Learning rate: 0.02 Mask loss: 0.20677 RPN box loss: 0.04934 RPN score loss: 0.00846 RPN total loss: 0.0578 Total loss: 1.15485 timestamp: 1654944868.8353071 iteration: 39450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10214 FastRCNN class loss: 0.05675 FastRCNN total loss: 0.15889 L1 loss: 0.0000e+00 L2 loss: 0.63841 Learning rate: 0.02 Mask loss: 0.09955 RPN box loss: 0.01091 RPN score loss: 0.00215 RPN total loss: 0.01306 Total loss: 0.90991 timestamp: 1654944872.0459783 iteration: 39455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15945 FastRCNN class loss: 0.11481 FastRCNN total loss: 0.27425 L1 loss: 0.0000e+00 L2 loss: 0.63834 Learning rate: 0.02 Mask loss: 0.2223 RPN box loss: 0.03026 RPN score loss: 0.01506 RPN total loss: 0.04532 Total loss: 1.18021 timestamp: 1654944875.2532065 iteration: 39460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12761 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.19949 L1 loss: 0.0000e+00 L2 loss: 0.63825 Learning rate: 0.02 Mask loss: 0.12483 RPN box loss: 0.03756 RPN score loss: 0.00825 RPN total loss: 0.04581 Total loss: 1.00839 timestamp: 1654944878.434367 iteration: 39465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10208 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.16735 L1 loss: 0.0000e+00 L2 loss: 0.63817 Learning rate: 0.02 Mask loss: 0.1073 RPN box loss: 0.06141 RPN score loss: 0.02298 RPN total loss: 0.0844 Total loss: 0.99722 timestamp: 1654944881.6104438 iteration: 39470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09417 FastRCNN class loss: 0.06029 FastRCNN total loss: 0.15446 L1 loss: 0.0000e+00 L2 loss: 0.63811 Learning rate: 0.02 Mask loss: 0.09192 RPN box loss: 0.02309 RPN score loss: 0.00585 RPN total loss: 0.02894 Total loss: 0.91345 timestamp: 1654944884.7312963 iteration: 39475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1752 FastRCNN class loss: 0.15886 FastRCNN total loss: 0.33405 L1 loss: 0.0000e+00 L2 loss: 0.63801 Learning rate: 0.02 Mask loss: 0.2679 RPN box loss: 0.04088 RPN score loss: 0.074 RPN total loss: 0.11488 Total loss: 1.35484 timestamp: 1654944887.9529188 iteration: 39480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.05457 FastRCNN total loss: 0.12567 L1 loss: 0.0000e+00 L2 loss: 0.63793 Learning rate: 0.02 Mask loss: 0.1291 RPN box loss: 0.02665 RPN score loss: 0.00701 RPN total loss: 0.03366 Total loss: 0.92637 timestamp: 1654944891.1535227 iteration: 39485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10253 FastRCNN class loss: 0.08858 FastRCNN total loss: 0.19112 L1 loss: 0.0000e+00 L2 loss: 0.63785 Learning rate: 0.02 Mask loss: 0.22845 RPN box loss: 0.01999 RPN score loss: 0.00611 RPN total loss: 0.0261 Total loss: 1.08352 timestamp: 1654944894.3640094 iteration: 39490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17604 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.24821 L1 loss: 0.0000e+00 L2 loss: 0.63777 Learning rate: 0.02 Mask loss: 0.22067 RPN box loss: 0.03518 RPN score loss: 0.004 RPN total loss: 0.03918 Total loss: 1.14583 timestamp: 1654944897.5126638 iteration: 39495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18599 FastRCNN class loss: 0.09102 FastRCNN total loss: 0.27701 L1 loss: 0.0000e+00 L2 loss: 0.63769 Learning rate: 0.02 Mask loss: 0.17347 RPN box loss: 0.02313 RPN score loss: 0.00466 RPN total loss: 0.02779 Total loss: 1.11596 timestamp: 1654944900.614583 iteration: 39500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20015 FastRCNN class loss: 0.1053 FastRCNN total loss: 0.30545 L1 loss: 0.0000e+00 L2 loss: 0.63762 Learning rate: 0.02 Mask loss: 0.15015 RPN box loss: 0.0215 RPN score loss: 0.00548 RPN total loss: 0.02698 Total loss: 1.1202 timestamp: 1654944903.891906 iteration: 39505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10268 FastRCNN class loss: 0.05772 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.63757 Learning rate: 0.02 Mask loss: 0.12072 RPN box loss: 0.03938 RPN score loss: 0.00326 RPN total loss: 0.04264 Total loss: 0.96132 timestamp: 1654944907.0746355 iteration: 39510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20274 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.27393 L1 loss: 0.0000e+00 L2 loss: 0.63753 Learning rate: 0.02 Mask loss: 0.13538 RPN box loss: 0.02028 RPN score loss: 0.00292 RPN total loss: 0.0232 Total loss: 1.07004 timestamp: 1654944910.3017256 iteration: 39515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1693 FastRCNN class loss: 0.11455 FastRCNN total loss: 0.28385 L1 loss: 0.0000e+00 L2 loss: 0.63746 Learning rate: 0.02 Mask loss: 0.21112 RPN box loss: 0.02108 RPN score loss: 0.00761 RPN total loss: 0.02868 Total loss: 1.16112 timestamp: 1654944913.464875 iteration: 39520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10106 FastRCNN class loss: 0.07571 FastRCNN total loss: 0.17676 L1 loss: 0.0000e+00 L2 loss: 0.63738 Learning rate: 0.02 Mask loss: 0.13836 RPN box loss: 0.02914 RPN score loss: 0.00732 RPN total loss: 0.03645 Total loss: 0.98895 timestamp: 1654944916.64787 iteration: 39525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.13388 L1 loss: 0.0000e+00 L2 loss: 0.6373 Learning rate: 0.02 Mask loss: 0.12989 RPN box loss: 0.03969 RPN score loss: 0.00473 RPN total loss: 0.04442 Total loss: 0.94549 timestamp: 1654944919.8253906 iteration: 39530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14864 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.21246 L1 loss: 0.0000e+00 L2 loss: 0.63722 Learning rate: 0.02 Mask loss: 0.12757 RPN box loss: 0.05653 RPN score loss: 0.00815 RPN total loss: 0.06469 Total loss: 1.04194 timestamp: 1654944922.990209 iteration: 39535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11991 FastRCNN class loss: 0.11203 FastRCNN total loss: 0.23194 L1 loss: 0.0000e+00 L2 loss: 0.63714 Learning rate: 0.02 Mask loss: 0.1666 RPN box loss: 0.02003 RPN score loss: 0.00457 RPN total loss: 0.0246 Total loss: 1.06028 timestamp: 1654944926.3081343 iteration: 39540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1608 FastRCNN class loss: 0.10616 FastRCNN total loss: 0.26696 L1 loss: 0.0000e+00 L2 loss: 0.63705 Learning rate: 0.02 Mask loss: 0.16112 RPN box loss: 0.01399 RPN score loss: 0.00333 RPN total loss: 0.01733 Total loss: 1.08245 timestamp: 1654944929.549486 iteration: 39545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17291 FastRCNN class loss: 0.09849 FastRCNN total loss: 0.2714 L1 loss: 0.0000e+00 L2 loss: 0.63695 Learning rate: 0.02 Mask loss: 0.19647 RPN box loss: 0.04864 RPN score loss: 0.0062 RPN total loss: 0.05483 Total loss: 1.15965 timestamp: 1654944932.7280922 iteration: 39550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16063 FastRCNN class loss: 0.0909 FastRCNN total loss: 0.25154 L1 loss: 0.0000e+00 L2 loss: 0.63687 Learning rate: 0.02 Mask loss: 0.14574 RPN box loss: 0.01649 RPN score loss: 0.0082 RPN total loss: 0.02469 Total loss: 1.05884 timestamp: 1654944935.8884685 iteration: 39555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15581 FastRCNN class loss: 0.09631 FastRCNN total loss: 0.25212 L1 loss: 0.0000e+00 L2 loss: 0.63681 Learning rate: 0.02 Mask loss: 0.13481 RPN box loss: 0.07253 RPN score loss: 0.00552 RPN total loss: 0.07805 Total loss: 1.10178 timestamp: 1654944939.1733708 iteration: 39560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11264 FastRCNN class loss: 0.073 FastRCNN total loss: 0.18564 L1 loss: 0.0000e+00 L2 loss: 0.63675 Learning rate: 0.02 Mask loss: 0.11953 RPN box loss: 0.019 RPN score loss: 0.00488 RPN total loss: 0.02388 Total loss: 0.9658 timestamp: 1654944942.4263556 iteration: 39565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10755 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.1612 L1 loss: 0.0000e+00 L2 loss: 0.63667 Learning rate: 0.02 Mask loss: 0.09537 RPN box loss: 0.01414 RPN score loss: 0.00402 RPN total loss: 0.01816 Total loss: 0.9114 timestamp: 1654944945.6707237 iteration: 39570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11992 FastRCNN class loss: 0.11108 FastRCNN total loss: 0.231 L1 loss: 0.0000e+00 L2 loss: 0.63658 Learning rate: 0.02 Mask loss: 0.14623 RPN box loss: 0.03886 RPN score loss: 0.00895 RPN total loss: 0.04781 Total loss: 1.06163 timestamp: 1654944948.8735745 iteration: 39575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.104 FastRCNN class loss: 0.1056 FastRCNN total loss: 0.2096 L1 loss: 0.0000e+00 L2 loss: 0.63652 Learning rate: 0.02 Mask loss: 0.13324 RPN box loss: 0.04466 RPN score loss: 0.00424 RPN total loss: 0.0489 Total loss: 1.02827 timestamp: 1654944952.10075 iteration: 39580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.0721 FastRCNN total loss: 0.20809 L1 loss: 0.0000e+00 L2 loss: 0.63641 Learning rate: 0.02 Mask loss: 0.12434 RPN box loss: 0.05926 RPN score loss: 0.00745 RPN total loss: 0.06671 Total loss: 1.03556 timestamp: 1654944955.3280678 iteration: 39585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.08141 FastRCNN total loss: 0.23283 L1 loss: 0.0000e+00 L2 loss: 0.63634 Learning rate: 0.02 Mask loss: 0.16051 RPN box loss: 0.04246 RPN score loss: 0.00732 RPN total loss: 0.04978 Total loss: 1.07946 timestamp: 1654944958.5475824 iteration: 39590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1471 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.2084 L1 loss: 0.0000e+00 L2 loss: 0.63628 Learning rate: 0.02 Mask loss: 0.11132 RPN box loss: 0.02347 RPN score loss: 0.00707 RPN total loss: 0.03054 Total loss: 0.98655 timestamp: 1654944961.7053316 iteration: 39595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20029 FastRCNN class loss: 0.09819 FastRCNN total loss: 0.29848 L1 loss: 0.0000e+00 L2 loss: 0.63621 Learning rate: 0.02 Mask loss: 0.13706 RPN box loss: 0.01319 RPN score loss: 0.00708 RPN total loss: 0.02027 Total loss: 1.09202 timestamp: 1654944964.85847 iteration: 39600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09644 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.15879 L1 loss: 0.0000e+00 L2 loss: 0.63614 Learning rate: 0.02 Mask loss: 0.14916 RPN box loss: 0.02397 RPN score loss: 0.00479 RPN total loss: 0.02876 Total loss: 0.97285 timestamp: 1654944968.03264 iteration: 39605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16864 FastRCNN class loss: 0.07623 FastRCNN total loss: 0.24487 L1 loss: 0.0000e+00 L2 loss: 0.63605 Learning rate: 0.02 Mask loss: 0.15707 RPN box loss: 0.04534 RPN score loss: 0.00589 RPN total loss: 0.05122 Total loss: 1.08922 timestamp: 1654944971.2440848 iteration: 39610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12202 FastRCNN class loss: 0.13627 FastRCNN total loss: 0.25829 L1 loss: 0.0000e+00 L2 loss: 0.63596 Learning rate: 0.02 Mask loss: 0.17549 RPN box loss: 0.05569 RPN score loss: 0.01492 RPN total loss: 0.07061 Total loss: 1.14035 timestamp: 1654944974.4140503 iteration: 39615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15491 FastRCNN class loss: 0.06491 FastRCNN total loss: 0.21982 L1 loss: 0.0000e+00 L2 loss: 0.63589 Learning rate: 0.02 Mask loss: 0.09958 RPN box loss: 0.02517 RPN score loss: 0.00171 RPN total loss: 0.02688 Total loss: 0.98216 timestamp: 1654944977.6425354 iteration: 39620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05846 FastRCNN class loss: 0.02836 FastRCNN total loss: 0.08682 L1 loss: 0.0000e+00 L2 loss: 0.63583 Learning rate: 0.02 Mask loss: 0.09046 RPN box loss: 0.02587 RPN score loss: 0.00185 RPN total loss: 0.02772 Total loss: 0.84083 timestamp: 1654944980.8608396 iteration: 39625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11933 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.16923 L1 loss: 0.0000e+00 L2 loss: 0.63573 Learning rate: 0.02 Mask loss: 0.14354 RPN box loss: 0.01714 RPN score loss: 0.00206 RPN total loss: 0.0192 Total loss: 0.96771 timestamp: 1654944984.0944023 iteration: 39630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19067 FastRCNN class loss: 0.09522 FastRCNN total loss: 0.2859 L1 loss: 0.0000e+00 L2 loss: 0.63565 Learning rate: 0.02 Mask loss: 0.18212 RPN box loss: 0.02333 RPN score loss: 0.00693 RPN total loss: 0.03026 Total loss: 1.13393 timestamp: 1654944987.2811444 iteration: 39635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11121 FastRCNN class loss: 0.09139 FastRCNN total loss: 0.2026 L1 loss: 0.0000e+00 L2 loss: 0.63558 Learning rate: 0.02 Mask loss: 0.13639 RPN box loss: 0.01568 RPN score loss: 0.01019 RPN total loss: 0.02588 Total loss: 1.00046 timestamp: 1654944990.4940755 iteration: 39640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14545 FastRCNN class loss: 0.05625 FastRCNN total loss: 0.2017 L1 loss: 0.0000e+00 L2 loss: 0.6355 Learning rate: 0.02 Mask loss: 0.1434 RPN box loss: 0.0276 RPN score loss: 0.00537 RPN total loss: 0.03296 Total loss: 1.01356 timestamp: 1654944993.7211137 iteration: 39645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14065 FastRCNN class loss: 0.09864 FastRCNN total loss: 0.23929 L1 loss: 0.0000e+00 L2 loss: 0.63541 Learning rate: 0.02 Mask loss: 0.17421 RPN box loss: 0.02864 RPN score loss: 0.00578 RPN total loss: 0.03441 Total loss: 1.08332 timestamp: 1654944996.9545112 iteration: 39650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07848 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.14157 L1 loss: 0.0000e+00 L2 loss: 0.63531 Learning rate: 0.02 Mask loss: 0.14792 RPN box loss: 0.02601 RPN score loss: 0.01539 RPN total loss: 0.04141 Total loss: 0.96621 timestamp: 1654945000.1260893 iteration: 39655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12546 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 0.63525 Learning rate: 0.02 Mask loss: 0.15239 RPN box loss: 0.03216 RPN score loss: 0.00336 RPN total loss: 0.03552 Total loss: 1.02363 timestamp: 1654945003.3387916 iteration: 39660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1268 FastRCNN class loss: 0.16629 FastRCNN total loss: 0.29309 L1 loss: 0.0000e+00 L2 loss: 0.63519 Learning rate: 0.02 Mask loss: 0.16246 RPN box loss: 0.03137 RPN score loss: 0.00571 RPN total loss: 0.03708 Total loss: 1.12782 timestamp: 1654945006.5563498 iteration: 39665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13693 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.21248 L1 loss: 0.0000e+00 L2 loss: 0.63512 Learning rate: 0.02 Mask loss: 0.16975 RPN box loss: 0.06287 RPN score loss: 0.00518 RPN total loss: 0.06805 Total loss: 1.0854 timestamp: 1654945009.7067559 iteration: 39670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12817 FastRCNN class loss: 0.06678 FastRCNN total loss: 0.19495 L1 loss: 0.0000e+00 L2 loss: 0.63505 Learning rate: 0.02 Mask loss: 0.1029 RPN box loss: 0.02167 RPN score loss: 0.00313 RPN total loss: 0.02479 Total loss: 0.95769 timestamp: 1654945012.9199157 iteration: 39675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09901 FastRCNN class loss: 0.0679 FastRCNN total loss: 0.16691 L1 loss: 0.0000e+00 L2 loss: 0.63497 Learning rate: 0.02 Mask loss: 0.16037 RPN box loss: 0.01831 RPN score loss: 0.00288 RPN total loss: 0.02119 Total loss: 0.98343 timestamp: 1654945016.1668873 iteration: 39680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17303 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.2293 L1 loss: 0.0000e+00 L2 loss: 0.63487 Learning rate: 0.02 Mask loss: 0.13224 RPN box loss: 0.01384 RPN score loss: 0.00426 RPN total loss: 0.0181 Total loss: 1.0145 timestamp: 1654945019.327612 iteration: 39685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06816 FastRCNN class loss: 0.04918 FastRCNN total loss: 0.11734 L1 loss: 0.0000e+00 L2 loss: 0.63479 Learning rate: 0.02 Mask loss: 0.12576 RPN box loss: 0.05382 RPN score loss: 0.00144 RPN total loss: 0.05526 Total loss: 0.93314 timestamp: 1654945022.4847786 iteration: 39690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06441 FastRCNN class loss: 0.07531 FastRCNN total loss: 0.13972 L1 loss: 0.0000e+00 L2 loss: 0.63469 Learning rate: 0.02 Mask loss: 0.14854 RPN box loss: 0.01699 RPN score loss: 0.00261 RPN total loss: 0.0196 Total loss: 0.94255 timestamp: 1654945025.6470153 iteration: 39695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11922 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.17387 L1 loss: 0.0000e+00 L2 loss: 0.63462 Learning rate: 0.02 Mask loss: 0.11967 RPN box loss: 0.00568 RPN score loss: 0.00331 RPN total loss: 0.00899 Total loss: 0.93715 timestamp: 1654945028.884257 iteration: 39700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14616 FastRCNN class loss: 0.08686 FastRCNN total loss: 0.23301 L1 loss: 0.0000e+00 L2 loss: 0.63457 Learning rate: 0.02 Mask loss: 0.07912 RPN box loss: 0.01457 RPN score loss: 0.00227 RPN total loss: 0.01684 Total loss: 0.96355 timestamp: 1654945032.1421268 iteration: 39705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09823 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.17146 L1 loss: 0.0000e+00 L2 loss: 0.63448 Learning rate: 0.02 Mask loss: 0.10689 RPN box loss: 0.01253 RPN score loss: 0.00399 RPN total loss: 0.01652 Total loss: 0.92935 timestamp: 1654945035.312665 iteration: 39710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16738 FastRCNN class loss: 0.07143 FastRCNN total loss: 0.23881 L1 loss: 0.0000e+00 L2 loss: 0.63442 Learning rate: 0.02 Mask loss: 0.11275 RPN box loss: 0.03648 RPN score loss: 0.0066 RPN total loss: 0.04307 Total loss: 1.02905 timestamp: 1654945038.5005126 iteration: 39715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1394 FastRCNN class loss: 0.1097 FastRCNN total loss: 0.2491 L1 loss: 0.0000e+00 L2 loss: 0.63434 Learning rate: 0.02 Mask loss: 0.20665 RPN box loss: 0.01878 RPN score loss: 0.01054 RPN total loss: 0.02932 Total loss: 1.1194 timestamp: 1654945041.6935415 iteration: 39720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19286 FastRCNN class loss: 0.08785 FastRCNN total loss: 0.28072 L1 loss: 0.0000e+00 L2 loss: 0.63426 Learning rate: 0.02 Mask loss: 0.16081 RPN box loss: 0.04241 RPN score loss: 0.01132 RPN total loss: 0.05373 Total loss: 1.12951 timestamp: 1654945044.85403 iteration: 39725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1658 FastRCNN class loss: 0.07727 FastRCNN total loss: 0.24307 L1 loss: 0.0000e+00 L2 loss: 0.63421 Learning rate: 0.02 Mask loss: 0.22791 RPN box loss: 0.0341 RPN score loss: 0.00522 RPN total loss: 0.03932 Total loss: 1.14451 timestamp: 1654945048.0350604 iteration: 39730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03809 FastRCNN class loss: 0.04641 FastRCNN total loss: 0.0845 L1 loss: 0.0000e+00 L2 loss: 0.63414 Learning rate: 0.02 Mask loss: 0.10261 RPN box loss: 0.00344 RPN score loss: 0.00132 RPN total loss: 0.00476 Total loss: 0.82602 timestamp: 1654945051.2579145 iteration: 39735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0576 FastRCNN class loss: 0.04881 FastRCNN total loss: 0.1064 L1 loss: 0.0000e+00 L2 loss: 0.63406 Learning rate: 0.02 Mask loss: 0.13383 RPN box loss: 0.01272 RPN score loss: 0.00169 RPN total loss: 0.01442 Total loss: 0.88871 timestamp: 1654945054.4295683 iteration: 39740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0945 FastRCNN class loss: 0.13664 FastRCNN total loss: 0.23115 L1 loss: 0.0000e+00 L2 loss: 0.63402 Learning rate: 0.02 Mask loss: 0.16546 RPN box loss: 0.06464 RPN score loss: 0.02956 RPN total loss: 0.09419 Total loss: 1.12481 timestamp: 1654945057.6238043 iteration: 39745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11058 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.17708 L1 loss: 0.0000e+00 L2 loss: 0.63393 Learning rate: 0.02 Mask loss: 0.22229 RPN box loss: 0.02611 RPN score loss: 0.00483 RPN total loss: 0.03094 Total loss: 1.06423 timestamp: 1654945060.7707787 iteration: 39750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.21434 L1 loss: 0.0000e+00 L2 loss: 0.63383 Learning rate: 0.02 Mask loss: 0.17915 RPN box loss: 0.03754 RPN score loss: 0.01565 RPN total loss: 0.05319 Total loss: 1.08051 timestamp: 1654945063.955645 iteration: 39755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04551 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.10317 L1 loss: 0.0000e+00 L2 loss: 0.63376 Learning rate: 0.02 Mask loss: 0.11702 RPN box loss: 0.02782 RPN score loss: 0.00254 RPN total loss: 0.03036 Total loss: 0.88432 timestamp: 1654945067.1819997 iteration: 39760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07053 FastRCNN class loss: 0.0964 FastRCNN total loss: 0.16693 L1 loss: 0.0000e+00 L2 loss: 0.63366 Learning rate: 0.02 Mask loss: 0.11475 RPN box loss: 0.04011 RPN score loss: 0.0051 RPN total loss: 0.0452 Total loss: 0.96054 timestamp: 1654945070.3983676 iteration: 39765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09542 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.17298 L1 loss: 0.0000e+00 L2 loss: 0.6336 Learning rate: 0.02 Mask loss: 0.16978 RPN box loss: 0.03575 RPN score loss: 0.01455 RPN total loss: 0.05031 Total loss: 1.02666 timestamp: 1654945073.5640926 iteration: 39770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18732 FastRCNN class loss: 0.08456 FastRCNN total loss: 0.27188 L1 loss: 0.0000e+00 L2 loss: 0.63353 Learning rate: 0.02 Mask loss: 0.11914 RPN box loss: 0.01977 RPN score loss: 0.00278 RPN total loss: 0.02255 Total loss: 1.0471 timestamp: 1654945076.7316341 iteration: 39775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17121 FastRCNN class loss: 0.09012 FastRCNN total loss: 0.26133 L1 loss: 0.0000e+00 L2 loss: 0.63345 Learning rate: 0.02 Mask loss: 0.23169 RPN box loss: 0.06899 RPN score loss: 0.00504 RPN total loss: 0.07403 Total loss: 1.2005 timestamp: 1654945079.9065912 iteration: 39780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08544 FastRCNN class loss: 0.09914 FastRCNN total loss: 0.18458 L1 loss: 0.0000e+00 L2 loss: 0.63338 Learning rate: 0.02 Mask loss: 0.12697 RPN box loss: 0.03623 RPN score loss: 0.00343 RPN total loss: 0.03966 Total loss: 0.98458 timestamp: 1654945083.1618886 iteration: 39785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15022 FastRCNN class loss: 0.12019 FastRCNN total loss: 0.27042 L1 loss: 0.0000e+00 L2 loss: 0.63329 Learning rate: 0.02 Mask loss: 0.18912 RPN box loss: 0.04105 RPN score loss: 0.00802 RPN total loss: 0.04908 Total loss: 1.1419 timestamp: 1654945086.3285596 iteration: 39790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1106 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.17741 L1 loss: 0.0000e+00 L2 loss: 0.63321 Learning rate: 0.02 Mask loss: 0.14638 RPN box loss: 0.00701 RPN score loss: 0.00554 RPN total loss: 0.01255 Total loss: 0.96956 timestamp: 1654945089.487581 iteration: 39795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19141 FastRCNN class loss: 0.1913 FastRCNN total loss: 0.3827 L1 loss: 0.0000e+00 L2 loss: 0.63313 Learning rate: 0.02 Mask loss: 0.20559 RPN box loss: 0.07543 RPN score loss: 0.01065 RPN total loss: 0.08608 Total loss: 1.3075 timestamp: 1654945092.691153 iteration: 39800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1022 FastRCNN class loss: 0.07758 FastRCNN total loss: 0.17978 L1 loss: 0.0000e+00 L2 loss: 0.63304 Learning rate: 0.02 Mask loss: 0.11823 RPN box loss: 0.01584 RPN score loss: 0.00612 RPN total loss: 0.02196 Total loss: 0.95301 timestamp: 1654945095.9589233 iteration: 39805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1137 FastRCNN class loss: 0.05152 FastRCNN total loss: 0.16522 L1 loss: 0.0000e+00 L2 loss: 0.63296 Learning rate: 0.02 Mask loss: 0.09348 RPN box loss: 0.00357 RPN score loss: 0.00562 RPN total loss: 0.0092 Total loss: 0.90085 timestamp: 1654945099.1867979 iteration: 39810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05818 FastRCNN class loss: 0.05799 FastRCNN total loss: 0.11617 L1 loss: 0.0000e+00 L2 loss: 0.63287 Learning rate: 0.02 Mask loss: 0.08923 RPN box loss: 0.03131 RPN score loss: 0.00615 RPN total loss: 0.03746 Total loss: 0.87573 timestamp: 1654945102.4491684 iteration: 39815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08356 FastRCNN class loss: 0.07458 FastRCNN total loss: 0.15814 L1 loss: 0.0000e+00 L2 loss: 0.63279 Learning rate: 0.02 Mask loss: 0.10801 RPN box loss: 0.04269 RPN score loss: 0.01636 RPN total loss: 0.05904 Total loss: 0.95798 timestamp: 1654945105.6386375 iteration: 39820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13014 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.20282 L1 loss: 0.0000e+00 L2 loss: 0.63271 Learning rate: 0.02 Mask loss: 0.19701 RPN box loss: 0.02072 RPN score loss: 0.00717 RPN total loss: 0.02789 Total loss: 1.06043 timestamp: 1654945108.8330357 iteration: 39825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18104 FastRCNN class loss: 0.10022 FastRCNN total loss: 0.28126 L1 loss: 0.0000e+00 L2 loss: 0.63263 Learning rate: 0.02 Mask loss: 0.153 RPN box loss: 0.02031 RPN score loss: 0.00575 RPN total loss: 0.02607 Total loss: 1.09296 timestamp: 1654945111.9995954 iteration: 39830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06125 FastRCNN class loss: 0.03453 FastRCNN total loss: 0.09578 L1 loss: 0.0000e+00 L2 loss: 0.63254 Learning rate: 0.02 Mask loss: 0.10728 RPN box loss: 0.01348 RPN score loss: 0.00374 RPN total loss: 0.01722 Total loss: 0.85283 timestamp: 1654945115.200477 iteration: 39835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.219 FastRCNN class loss: 0.09322 FastRCNN total loss: 0.31223 L1 loss: 0.0000e+00 L2 loss: 0.63246 Learning rate: 0.02 Mask loss: 0.22328 RPN box loss: 0.01575 RPN score loss: 0.00196 RPN total loss: 0.01771 Total loss: 1.18568 timestamp: 1654945118.4182754 iteration: 39840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11665 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.18527 L1 loss: 0.0000e+00 L2 loss: 0.63244 Learning rate: 0.02 Mask loss: 0.15624 RPN box loss: 0.01982 RPN score loss: 0.00326 RPN total loss: 0.02309 Total loss: 0.99704 timestamp: 1654945121.5945704 iteration: 39845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10054 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.17555 L1 loss: 0.0000e+00 L2 loss: 0.63235 Learning rate: 0.02 Mask loss: 0.11467 RPN box loss: 0.0255 RPN score loss: 0.01321 RPN total loss: 0.03871 Total loss: 0.96129 timestamp: 1654945124.8259423 iteration: 39850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10118 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.16835 L1 loss: 0.0000e+00 L2 loss: 0.63227 Learning rate: 0.02 Mask loss: 0.17027 RPN box loss: 0.08455 RPN score loss: 0.00503 RPN total loss: 0.08958 Total loss: 1.06047 timestamp: 1654945128.047554 iteration: 39855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14256 FastRCNN class loss: 0.08004 FastRCNN total loss: 0.2226 L1 loss: 0.0000e+00 L2 loss: 0.6322 Learning rate: 0.02 Mask loss: 0.12056 RPN box loss: 0.01144 RPN score loss: 0.00735 RPN total loss: 0.01878 Total loss: 0.99414 timestamp: 1654945131.1978285 iteration: 39860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07843 FastRCNN class loss: 0.05531 FastRCNN total loss: 0.13374 L1 loss: 0.0000e+00 L2 loss: 0.6321 Learning rate: 0.02 Mask loss: 0.12089 RPN box loss: 0.0306 RPN score loss: 0.00478 RPN total loss: 0.03538 Total loss: 0.92211 timestamp: 1654945134.4066358 iteration: 39865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14243 FastRCNN class loss: 0.07262 FastRCNN total loss: 0.21505 L1 loss: 0.0000e+00 L2 loss: 0.63203 Learning rate: 0.02 Mask loss: 0.20252 RPN box loss: 0.02116 RPN score loss: 0.00686 RPN total loss: 0.02802 Total loss: 1.07763 timestamp: 1654945137.4932563 iteration: 39870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11633 FastRCNN class loss: 0.07215 FastRCNN total loss: 0.18848 L1 loss: 0.0000e+00 L2 loss: 0.63197 Learning rate: 0.02 Mask loss: 0.1473 RPN box loss: 0.02856 RPN score loss: 0.0116 RPN total loss: 0.04016 Total loss: 1.00791 timestamp: 1654945140.6900725 iteration: 39875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18486 FastRCNN class loss: 0.08957 FastRCNN total loss: 0.27443 L1 loss: 0.0000e+00 L2 loss: 0.63189 Learning rate: 0.02 Mask loss: 0.18152 RPN box loss: 0.03859 RPN score loss: 0.00837 RPN total loss: 0.04696 Total loss: 1.1348 timestamp: 1654945143.9746172 iteration: 39880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12158 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.19287 L1 loss: 0.0000e+00 L2 loss: 0.63183 Learning rate: 0.02 Mask loss: 0.17938 RPN box loss: 0.0174 RPN score loss: 0.00898 RPN total loss: 0.02638 Total loss: 1.03045 timestamp: 1654945147.1826782 iteration: 39885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10671 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.17327 L1 loss: 0.0000e+00 L2 loss: 0.63175 Learning rate: 0.02 Mask loss: 0.1544 RPN box loss: 0.0331 RPN score loss: 0.00443 RPN total loss: 0.03753 Total loss: 0.99696 timestamp: 1654945150.4007204 iteration: 39890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15043 FastRCNN class loss: 0.10904 FastRCNN total loss: 0.25947 L1 loss: 0.0000e+00 L2 loss: 0.63165 Learning rate: 0.02 Mask loss: 0.15015 RPN box loss: 0.02792 RPN score loss: 0.01243 RPN total loss: 0.04036 Total loss: 1.08162 timestamp: 1654945153.7170932 iteration: 39895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15415 FastRCNN class loss: 0.06182 FastRCNN total loss: 0.21596 L1 loss: 0.0000e+00 L2 loss: 0.63155 Learning rate: 0.02 Mask loss: 0.1443 RPN box loss: 0.01408 RPN score loss: 0.00151 RPN total loss: 0.01559 Total loss: 1.00741 timestamp: 1654945156.8261268 iteration: 39900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12241 FastRCNN class loss: 0.09702 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.63146 Learning rate: 0.02 Mask loss: 0.17448 RPN box loss: 0.01303 RPN score loss: 0.00529 RPN total loss: 0.01831 Total loss: 1.04368 timestamp: 1654945160.0490818 iteration: 39905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20309 FastRCNN class loss: 0.17381 FastRCNN total loss: 0.3769 L1 loss: 0.0000e+00 L2 loss: 0.63138 Learning rate: 0.02 Mask loss: 0.30792 RPN box loss: 0.03083 RPN score loss: 0.00794 RPN total loss: 0.03877 Total loss: 1.35497 timestamp: 1654945163.2666547 iteration: 39910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11224 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.18643 L1 loss: 0.0000e+00 L2 loss: 0.6313 Learning rate: 0.02 Mask loss: 0.17159 RPN box loss: 0.02188 RPN score loss: 0.00844 RPN total loss: 0.03032 Total loss: 1.01963 timestamp: 1654945166.4892895 iteration: 39915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15306 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.21376 L1 loss: 0.0000e+00 L2 loss: 0.63121 Learning rate: 0.02 Mask loss: 0.16535 RPN box loss: 0.06556 RPN score loss: 0.00987 RPN total loss: 0.07543 Total loss: 1.08576 timestamp: 1654945169.7402492 iteration: 39920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08586 FastRCNN class loss: 0.04531 FastRCNN total loss: 0.13117 L1 loss: 0.0000e+00 L2 loss: 0.63114 Learning rate: 0.02 Mask loss: 0.10591 RPN box loss: 0.02978 RPN score loss: 0.00899 RPN total loss: 0.03877 Total loss: 0.90699 timestamp: 1654945172.893122 iteration: 39925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21182 FastRCNN class loss: 0.10435 FastRCNN total loss: 0.31617 L1 loss: 0.0000e+00 L2 loss: 0.63107 Learning rate: 0.02 Mask loss: 0.26486 RPN box loss: 0.04507 RPN score loss: 0.00633 RPN total loss: 0.05139 Total loss: 1.26349 timestamp: 1654945176.018591 iteration: 39930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16929 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.25409 L1 loss: 0.0000e+00 L2 loss: 0.63101 Learning rate: 0.02 Mask loss: 0.1832 RPN box loss: 0.02595 RPN score loss: 0.01413 RPN total loss: 0.04008 Total loss: 1.10838 timestamp: 1654945179.2542334 iteration: 39935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18765 FastRCNN class loss: 0.07269 FastRCNN total loss: 0.26033 L1 loss: 0.0000e+00 L2 loss: 0.63088 Learning rate: 0.02 Mask loss: 0.16765 RPN box loss: 0.0423 RPN score loss: 0.00345 RPN total loss: 0.04575 Total loss: 1.10461 timestamp: 1654945182.5564604 iteration: 39940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13725 FastRCNN class loss: 0.12748 FastRCNN total loss: 0.26473 L1 loss: 0.0000e+00 L2 loss: 0.6308 Learning rate: 0.02 Mask loss: 0.2046 RPN box loss: 0.02509 RPN score loss: 0.00927 RPN total loss: 0.03435 Total loss: 1.13449 timestamp: 1654945185.751722 iteration: 39945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1333 FastRCNN class loss: 0.07689 FastRCNN total loss: 0.21019 L1 loss: 0.0000e+00 L2 loss: 0.63076 Learning rate: 0.02 Mask loss: 0.13684 RPN box loss: 0.02857 RPN score loss: 0.00297 RPN total loss: 0.03155 Total loss: 1.00933 timestamp: 1654945188.8931212 iteration: 39950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17948 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.27361 L1 loss: 0.0000e+00 L2 loss: 0.6307 Learning rate: 0.02 Mask loss: 0.1412 RPN box loss: 0.02822 RPN score loss: 0.00358 RPN total loss: 0.0318 Total loss: 1.07731 timestamp: 1654945192.0624928 iteration: 39955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1214 FastRCNN class loss: 0.06626 FastRCNN total loss: 0.18767 L1 loss: 0.0000e+00 L2 loss: 0.63063 Learning rate: 0.02 Mask loss: 0.14657 RPN box loss: 0.00456 RPN score loss: 0.00422 RPN total loss: 0.00878 Total loss: 0.97366 timestamp: 1654945195.216833 iteration: 39960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16209 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.23062 L1 loss: 0.0000e+00 L2 loss: 0.63055 Learning rate: 0.02 Mask loss: 0.12851 RPN box loss: 0.06782 RPN score loss: 0.0046 RPN total loss: 0.07241 Total loss: 1.06209 timestamp: 1654945198.3750029 iteration: 39965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08481 FastRCNN class loss: 0.04381 FastRCNN total loss: 0.12862 L1 loss: 0.0000e+00 L2 loss: 0.63047 Learning rate: 0.02 Mask loss: 0.09522 RPN box loss: 0.02263 RPN score loss: 0.00144 RPN total loss: 0.02408 Total loss: 0.87839 timestamp: 1654945201.5588164 iteration: 39970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13135 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.20767 L1 loss: 0.0000e+00 L2 loss: 0.63041 Learning rate: 0.02 Mask loss: 0.17193 RPN box loss: 0.06203 RPN score loss: 0.00685 RPN total loss: 0.06888 Total loss: 1.07889 timestamp: 1654945204.8003 iteration: 39975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0605 FastRCNN class loss: 0.04617 FastRCNN total loss: 0.10667 L1 loss: 0.0000e+00 L2 loss: 0.63033 Learning rate: 0.02 Mask loss: 0.10243 RPN box loss: 0.00889 RPN score loss: 0.00294 RPN total loss: 0.01183 Total loss: 0.85126 timestamp: 1654945208.0389187 iteration: 39980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17831 FastRCNN class loss: 0.12448 FastRCNN total loss: 0.30279 L1 loss: 0.0000e+00 L2 loss: 0.63026 Learning rate: 0.02 Mask loss: 0.12681 RPN box loss: 0.04564 RPN score loss: 0.00626 RPN total loss: 0.0519 Total loss: 1.11176 timestamp: 1654945211.2000065 iteration: 39985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13352 FastRCNN class loss: 0.09074 FastRCNN total loss: 0.22426 L1 loss: 0.0000e+00 L2 loss: 0.63018 Learning rate: 0.02 Mask loss: 0.19281 RPN box loss: 0.03398 RPN score loss: 0.01101 RPN total loss: 0.04499 Total loss: 1.09224 timestamp: 1654945214.4105997 iteration: 39990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12154 FastRCNN class loss: 0.0966 FastRCNN total loss: 0.21814 L1 loss: 0.0000e+00 L2 loss: 0.63013 Learning rate: 0.02 Mask loss: 0.10054 RPN box loss: 0.01062 RPN score loss: 0.00156 RPN total loss: 0.01217 Total loss: 0.96098 timestamp: 1654945217.5958564 iteration: 39995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13841 FastRCNN class loss: 0.09583 FastRCNN total loss: 0.23424 L1 loss: 0.0000e+00 L2 loss: 0.63006 Learning rate: 0.02 Mask loss: 0.26446 RPN box loss: 0.06082 RPN score loss: 0.00967 RPN total loss: 0.07049 Total loss: 1.19924 timestamp: 1654945220.833922 iteration: 40000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13734 FastRCNN class loss: 0.10067 FastRCNN total loss: 0.23801 L1 loss: 0.0000e+00 L2 loss: 0.62995 Learning rate: 0.02 Mask loss: 0.19266 RPN box loss: 0.01789 RPN score loss: 0.0035 RPN total loss: 0.02139 Total loss: 1.08201 Saving checkpoints for 40000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-40000.tlt. ================================= Start evaluation cycle 04 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-40000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.9604s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.3373s - Throughput: 11.9 imgs/s Running inference on batch 003/125... - Step Time: 0.3303s - Throughput: 12.1 imgs/s Running inference on batch 004/125... - Step Time: 0.3411s - Throughput: 11.7 imgs/s Running inference on batch 005/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 006/125... - Step Time: 0.3307s - Throughput: 12.1 imgs/s Running inference on batch 007/125... - Step Time: 0.3449s - Throughput: 11.6 imgs/s Running inference on batch 008/125... - Step Time: 0.3363s - Throughput: 11.9 imgs/s Running inference on batch 009/125... - Step Time: 0.3491s - Throughput: 11.5 imgs/s Running inference on batch 010/125... - Step Time: 0.3359s - Throughput: 11.9 imgs/s Running inference on batch 011/125... - Step Time: 0.3434s - Throughput: 11.6 imgs/s Running inference on batch 012/125... - Step Time: 0.3377s - Throughput: 11.8 imgs/s Running inference on batch 013/125... - Step Time: 0.3373s - Throughput: 11.9 imgs/s Running inference on batch 014/125... - Step Time: 0.3268s - Throughput: 12.2 imgs/s Running inference on batch 015/125... - Step Time: 0.3315s - Throughput: 12.1 imgs/s Running inference on batch 016/125... - Step Time: 0.3289s - Throughput: 12.2 imgs/s Running inference on batch 017/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 018/125... - Step Time: 0.2952s - Throughput: 13.6 imgs/s Running inference on batch 019/125... - Step Time: 0.3428s - Throughput: 11.7 imgs/s Running inference on batch 020/125... - Step Time: 0.3242s - Throughput: 12.3 imgs/s Running inference on batch 021/125... - Step Time: 0.3202s - Throughput: 12.5 imgs/s Running inference on batch 022/125... - Step Time: 0.3481s - Throughput: 11.5 imgs/s Running inference on batch 023/125... - Step Time: 0.3395s - Throughput: 11.8 imgs/s Running inference on batch 024/125... - Step Time: 0.3040s - Throughput: 13.2 imgs/s Running inference on batch 025/125... - Step Time: 0.3463s - Throughput: 11.6 imgs/s Running inference on batch 026/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 027/125... - Step Time: 0.3300s - Throughput: 12.1 imgs/s Running inference on batch 028/125... - Step Time: 0.3451s - Throughput: 11.6 imgs/s Running inference on batch 029/125... - Step Time: 0.3313s - Throughput: 12.1 imgs/s Running inference on batch 030/125... - Step Time: 0.3492s - Throughput: 11.5 imgs/s Running inference on batch 031/125... - Step Time: 0.3341s - Throughput: 12.0 imgs/s Running inference on batch 032/125... - Step Time: 0.3382s - Throughput: 11.8 imgs/s Running inference on batch 033/125... - Step Time: 0.3459s - Throughput: 11.6 imgs/s Running inference on batch 034/125... - Step Time: 0.3305s - Throughput: 12.1 imgs/s Running inference on batch 035/125... - Step Time: 0.3263s - Throughput: 12.3 imgs/s Running inference on batch 036/125... - Step Time: 0.3578s - Throughput: 11.2 imgs/s Running inference on batch 037/125... - Step Time: 0.3412s - Throughput: 11.7 imgs/s Running inference on batch 038/125... - Step Time: 0.3366s - Throughput: 11.9 imgs/s Running inference on batch 039/125... - Step Time: 0.3475s - Throughput: 11.5 imgs/s Running inference on batch 040/125... - Step Time: 0.3417s - Throughput: 11.7 imgs/s Running inference on batch 041/125... - Step Time: 0.3344s - Throughput: 12.0 imgs/s Running inference on batch 042/125... - Step Time: 0.3298s - Throughput: 12.1 imgs/s Running inference on batch 043/125... - Step Time: 0.3240s - Throughput: 12.3 imgs/s Running inference on batch 044/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 045/125... - Step Time: 0.3308s - Throughput: 12.1 imgs/s Running inference on batch 046/125... - Step Time: 0.3307s - Throughput: 12.1 imgs/s Running inference on batch 047/125... - Step Time: 0.3419s - Throughput: 11.7 imgs/s Running inference on batch 048/125... - Step Time: 0.3441s - Throughput: 11.6 imgs/s Running inference on batch 049/125... - Step Time: 0.3378s - Throughput: 11.8 imgs/s Running inference on batch 050/125... - Step Time: 0.3386s - Throughput: 11.8 imgs/s Running inference on batch 051/125... - Step Time: 0.3340s - Throughput: 12.0 imgs/s Running inference on batch 052/125... - Step Time: 0.3303s - Throughput: 12.1 imgs/s Running inference on batch 053/125... - Step Time: 0.3444s - Throughput: 11.6 imgs/s Running inference on batch 054/125... - Step Time: 0.3261s - Throughput: 12.3 imgs/s Running inference on batch 055/125... - Step Time: 0.3385s - Throughput: 11.8 imgs/s Running inference on batch 056/125... - Step Time: 0.3349s - Throughput: 11.9 imgs/s Running inference on batch 057/125... - Step Time: 0.3568s - Throughput: 11.2 imgs/s Running inference on batch 058/125... - Step Time: 0.3446s - Throughput: 11.6 imgs/s Running inference on batch 059/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 060/125... - Step Time: 0.3419s - Throughput: 11.7 imgs/s Running inference on batch 061/125... - Step Time: 0.3256s - Throughput: 12.3 imgs/s Running inference on batch 062/125... - Step Time: 0.3345s - Throughput: 12.0 imgs/s Running inference on batch 063/125... - Step Time: 0.3230s - Throughput: 12.4 imgs/s Running inference on batch 064/125... - Step Time: 0.3313s - Throughput: 12.1 imgs/s Running inference on batch 065/125... - Step Time: 0.3256s - Throughput: 12.3 imgs/s Running inference on batch 066/125... - Step Time: 0.3406s - Throughput: 11.7 imgs/s Running inference on batch 067/125... - Step Time: 0.3435s - Throughput: 11.6 imgs/s Running inference on batch 068/125... - Step Time: 0.3407s - Throughput: 11.7 imgs/s Running inference on batch 069/125... - Step Time: 0.3446s - Throughput: 11.6 imgs/s Running inference on batch 070/125... - Step Time: 0.3341s - Throughput: 12.0 imgs/s Running inference on batch 071/125... - Step Time: 0.3357s - Throughput: 11.9 imgs/s Running inference on batch 072/125... - Step Time: 0.3508s - Throughput: 11.4 imgs/s Running inference on batch 073/125... - Step Time: 0.3235s - Throughput: 12.4 imgs/s Running inference on batch 074/125... - Step Time: 0.3416s - Throughput: 11.7 imgs/s Running inference on batch 075/125... - Step Time: 0.3422s - Throughput: 11.7 imgs/s Running inference on batch 076/125... - Step Time: 0.3406s - Throughput: 11.7 imgs/s Running inference on batch 077/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 078/125... - Step Time: 0.3278s - Throughput: 12.2 imgs/s Running inference on batch 079/125... - Step Time: 0.3364s - Throughput: 11.9 imgs/s Running inference on batch 080/125... - Step Time: 0.3366s - Throughput: 11.9 imgs/s Running inference on batch 081/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 082/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 083/125... - Step Time: 0.3517s - Throughput: 11.4 imgs/s Running inference on batch 084/125... - Step Time: 0.3359s - Throughput: 11.9 imgs/s Running inference on batch 085/125... - Step Time: 0.3312s - Throughput: 12.1 imgs/s Running inference on batch 086/125... - Step Time: 0.3223s - Throughput: 12.4 imgs/s Running inference on batch 087/125... - Step Time: 0.3482s - Throughput: 11.5 imgs/s Running inference on batch 088/125... - Step Time: 0.3452s - Throughput: 11.6 imgs/s Running inference on batch 089/125... - Step Time: 0.3316s - Throughput: 12.1 imgs/s Running inference on batch 090/125... - Step Time: 0.3205s - Throughput: 12.5 imgs/s Running inference on batch 091/125... - Step Time: 0.3347s - Throughput: 12.0 imgs/s Running inference on batch 092/125... - Step Time: 0.3372s - Throughput: 11.9 imgs/s Running inference on batch 093/125... - Step Time: 0.3275s - Throughput: 12.2 imgs/s Running inference on batch 094/125... - Step Time: 0.3366s - Throughput: 11.9 imgs/s Running inference on batch 095/125... - Step Time: 0.3252s - Throughput: 12.3 imgs/s Running inference on batch 096/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 097/125... - Step Time: 0.3390s - Throughput: 11.8 imgs/s Running inference on batch 098/125... - Step Time: 0.3332s - Throughput: 12.0 imgs/s Running inference on batch 099/125... - Step Time: 0.3605s - Throughput: 11.1 imgs/s Running inference on batch 100/125... - Step Time: 0.3290s - Throughput: 12.2 imgs/s Running inference on batch 101/125... - Step Time: 0.3409s - Throughput: 11.7 imgs/s Running inference on batch 102/125... - Step Time: 0.3291s - Throughput: 12.2 imgs/s Running inference on batch 103/125... - Step Time: 0.3235s - Throughput: 12.4 imgs/s Running inference on batch 104/125... - Step Time: 0.3332s - Throughput: 12.0 imgs/s Running inference on batch 105/125... - Step Time: 0.3590s - Throughput: 11.1 imgs/s Running inference on batch 106/125... - Step Time: 0.3315s - Throughput: 12.1 imgs/s Running inference on batch 107/125... - Step Time: 0.3315s - Throughput: 12.1 imgs/s Running inference on batch 108/125... - Step Time: 0.3373s - Throughput: 11.9 imgs/s Running inference on batch 109/125... - Step Time: 0.3341s - Throughput: 12.0 imgs/s Running inference on batch 110/125... - Step Time: 0.3449s - Throughput: 11.6 imgs/s Running inference on batch 111/125... - Step Time: 0.3268s - Throughput: 12.2 imgs/s Running inference on batch 112/125... - Step Time: 0.3395s - Throughput: 11.8 imgs/s Running inference on batch 113/125... - Step Time: 0.3355s - Throughput: 11.9 imgs/s Running inference on batch 114/125... - Step Time: 0.3228s - Throughput: 12.4 imgs/s Running inference on batch 115/125... - Step Time: 0.3306s - Throughput: 12.1 imgs/s Running inference on batch 116/125... - Step Time: 0.3210s - Throughput: 12.5 imgs/s Running inference on batch 117/125... - Step Time: 0.3339s - Throughput: 12.0 imgs/s Running inference on batch 118/125... - Step Time: 0.3458s - Throughput: 11.6 imgs/s Running inference on batch 119/125... - Step Time: 0.2935s - Throughput: 13.6 imgs/s Running inference on batch 120/125... - Step Time: 0.3365s - Throughput: 11.9 imgs/s Running inference on batch 121/125... - Step Time: 0.3321s - Throughput: 12.0 imgs/s Running inference on batch 122/125... - Step Time: 0.3291s - Throughput: 12.2 imgs/s Running inference on batch 123/125... - Step Time: 0.3339s - Throughput: 12.0 imgs/s Running inference on batch 124/125... - Step Time: 0.3479s - Throughput: 11.5 imgs/s Running inference on batch 125/125... - Step Time: 0.2744s - Throughput: 14.6 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 12.0 samples/sec Total processed steps: 125 Total processing time: 0.0h 24m 43s ==================== Metrics ==================== AP: 0.199076086 AP50: 0.311007082 AP75: 0.198027328 APl: 0.233047977 APm: 0.044004563 APs: 0.006533645 ARl: 0.415867507 ARm: 0.086824603 ARmax1: 0.264897168 ARmax10: 0.352354437 ARmax100: 0.357122213 ARs: 0.020738440 mask_AP: 0.155023530 mask_AP50: 0.250014573 mask_AP75: 0.163653985 mask_APl: 0.182663575 mask_APm: 0.026956907 mask_APs: 0.011301887 mask_ARl: 0.309407860 mask_ARm: 0.065078303 mask_ARmax1: 0.210464939 mask_ARmax10: 0.259269685 mask_ARmax100: 0.263585597 mask_ARs: 0.019202899 ================================= Start training cycle 05 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654946362.5224693 iteration: 40005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.13839 L1 loss: 0.0000e+00 L2 loss: 0.62991 Learning rate: 0.002 Mask loss: 0.11025 RPN box loss: 0.03557 RPN score loss: 0.0021 RPN total loss: 0.03767 Total loss: 0.91623 timestamp: 1654946365.7560642 iteration: 40010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07846 FastRCNN class loss: 0.06558 FastRCNN total loss: 0.14405 L1 loss: 0.0000e+00 L2 loss: 0.62991 Learning rate: 0.002 Mask loss: 0.12227 RPN box loss: 0.01759 RPN score loss: 0.00508 RPN total loss: 0.02267 Total loss: 0.91889 timestamp: 1654946368.8976443 iteration: 40015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11188 FastRCNN class loss: 0.0541 FastRCNN total loss: 0.16599 L1 loss: 0.0000e+00 L2 loss: 0.62991 Learning rate: 0.002 Mask loss: 0.15251 RPN box loss: 0.0106 RPN score loss: 0.00436 RPN total loss: 0.01496 Total loss: 0.96336 timestamp: 1654946372.0580666 iteration: 40020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16651 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.23738 L1 loss: 0.0000e+00 L2 loss: 0.62991 Learning rate: 0.002 Mask loss: 0.14593 RPN box loss: 0.01731 RPN score loss: 0.00271 RPN total loss: 0.02001 Total loss: 1.03322 timestamp: 1654946375.254605 iteration: 40025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14478 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.20927 L1 loss: 0.0000e+00 L2 loss: 0.6299 Learning rate: 0.002 Mask loss: 0.16161 RPN box loss: 0.051 RPN score loss: 0.00418 RPN total loss: 0.05517 Total loss: 1.05595 timestamp: 1654946378.4738045 iteration: 40030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09487 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.15788 L1 loss: 0.0000e+00 L2 loss: 0.6299 Learning rate: 0.002 Mask loss: 0.09706 RPN box loss: 0.008 RPN score loss: 0.00372 RPN total loss: 0.01172 Total loss: 0.89656 timestamp: 1654946381.6808288 iteration: 40035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07305 FastRCNN class loss: 0.07015 FastRCNN total loss: 0.1432 L1 loss: 0.0000e+00 L2 loss: 0.62989 Learning rate: 0.002 Mask loss: 0.16102 RPN box loss: 0.00666 RPN score loss: 0.00367 RPN total loss: 0.01033 Total loss: 0.94444 timestamp: 1654946384.8851507 iteration: 40040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12646 FastRCNN class loss: 0.06971 FastRCNN total loss: 0.19617 L1 loss: 0.0000e+00 L2 loss: 0.62988 Learning rate: 0.002 Mask loss: 0.15219 RPN box loss: 0.0055 RPN score loss: 0.00191 RPN total loss: 0.00741 Total loss: 0.98564 timestamp: 1654946388.05042 iteration: 40045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16174 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.23313 L1 loss: 0.0000e+00 L2 loss: 0.62987 Learning rate: 0.002 Mask loss: 0.09615 RPN box loss: 0.01613 RPN score loss: 0.00295 RPN total loss: 0.01909 Total loss: 0.97823 timestamp: 1654946391.2126164 iteration: 40050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11163 FastRCNN class loss: 0.07719 FastRCNN total loss: 0.18881 L1 loss: 0.0000e+00 L2 loss: 0.62986 Learning rate: 0.002 Mask loss: 0.14799 RPN box loss: 0.01464 RPN score loss: 0.00251 RPN total loss: 0.01715 Total loss: 0.98382 timestamp: 1654946394.3824065 iteration: 40055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10102 FastRCNN class loss: 0.06064 FastRCNN total loss: 0.16167 L1 loss: 0.0000e+00 L2 loss: 0.62985 Learning rate: 0.002 Mask loss: 0.12077 RPN box loss: 0.03265 RPN score loss: 0.00474 RPN total loss: 0.0374 Total loss: 0.94968 timestamp: 1654946397.6201878 iteration: 40060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14429 FastRCNN class loss: 0.13901 FastRCNN total loss: 0.2833 L1 loss: 0.0000e+00 L2 loss: 0.62984 Learning rate: 0.002 Mask loss: 0.22266 RPN box loss: 0.03609 RPN score loss: 0.01001 RPN total loss: 0.0461 Total loss: 1.18191 timestamp: 1654946400.8152905 iteration: 40065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11148 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.17298 L1 loss: 0.0000e+00 L2 loss: 0.62983 Learning rate: 0.002 Mask loss: 0.16402 RPN box loss: 0.0463 RPN score loss: 0.00207 RPN total loss: 0.04838 Total loss: 1.01521 timestamp: 1654946403.9727554 iteration: 40070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11287 FastRCNN class loss: 0.08585 FastRCNN total loss: 0.19871 L1 loss: 0.0000e+00 L2 loss: 0.62982 Learning rate: 0.002 Mask loss: 0.11618 RPN box loss: 0.04585 RPN score loss: 0.00945 RPN total loss: 0.0553 Total loss: 1.00002 timestamp: 1654946407.312233 iteration: 40075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16318 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.24921 L1 loss: 0.0000e+00 L2 loss: 0.62982 Learning rate: 0.002 Mask loss: 0.15825 RPN box loss: 0.02259 RPN score loss: 0.00474 RPN total loss: 0.02733 Total loss: 1.06461 timestamp: 1654946410.518332 iteration: 40080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05678 FastRCNN class loss: 0.03059 FastRCNN total loss: 0.08738 L1 loss: 0.0000e+00 L2 loss: 0.62981 Learning rate: 0.002 Mask loss: 0.1267 RPN box loss: 0.01138 RPN score loss: 0.00486 RPN total loss: 0.01624 Total loss: 0.86012 timestamp: 1654946413.7267056 iteration: 40085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1306 FastRCNN class loss: 0.08252 FastRCNN total loss: 0.21312 L1 loss: 0.0000e+00 L2 loss: 0.6298 Learning rate: 0.002 Mask loss: 0.18379 RPN box loss: 0.0202 RPN score loss: 0.0046 RPN total loss: 0.0248 Total loss: 1.05151 timestamp: 1654946416.9911406 iteration: 40090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1585 FastRCNN class loss: 0.10982 FastRCNN total loss: 0.26832 L1 loss: 0.0000e+00 L2 loss: 0.62979 Learning rate: 0.002 Mask loss: 0.14418 RPN box loss: 0.02994 RPN score loss: 0.00655 RPN total loss: 0.03649 Total loss: 1.07878 timestamp: 1654946420.1545157 iteration: 40095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06507 FastRCNN class loss: 0.05456 FastRCNN total loss: 0.11963 L1 loss: 0.0000e+00 L2 loss: 0.62978 Learning rate: 0.002 Mask loss: 0.082 RPN box loss: 0.0091 RPN score loss: 0.0025 RPN total loss: 0.0116 Total loss: 0.84301 timestamp: 1654946423.3811917 iteration: 40100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10669 FastRCNN class loss: 0.04928 FastRCNN total loss: 0.15597 L1 loss: 0.0000e+00 L2 loss: 0.62977 Learning rate: 0.002 Mask loss: 0.09607 RPN box loss: 0.0171 RPN score loss: 0.00611 RPN total loss: 0.02322 Total loss: 0.90502 timestamp: 1654946426.592059 iteration: 40105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12938 FastRCNN class loss: 0.09805 FastRCNN total loss: 0.22743 L1 loss: 0.0000e+00 L2 loss: 0.62976 Learning rate: 0.002 Mask loss: 0.13725 RPN box loss: 0.04498 RPN score loss: 0.00706 RPN total loss: 0.05204 Total loss: 1.04648 timestamp: 1654946429.7982497 iteration: 40110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11538 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.17971 L1 loss: 0.0000e+00 L2 loss: 0.62976 Learning rate: 0.002 Mask loss: 0.12093 RPN box loss: 0.00887 RPN score loss: 0.00822 RPN total loss: 0.01708 Total loss: 0.94748 timestamp: 1654946432.9217741 iteration: 40115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.18396 L1 loss: 0.0000e+00 L2 loss: 0.62975 Learning rate: 0.002 Mask loss: 0.16346 RPN box loss: 0.02357 RPN score loss: 0.00383 RPN total loss: 0.02739 Total loss: 1.00457 timestamp: 1654946436.128372 iteration: 40120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04596 FastRCNN class loss: 0.03992 FastRCNN total loss: 0.08588 L1 loss: 0.0000e+00 L2 loss: 0.62974 Learning rate: 0.002 Mask loss: 0.08603 RPN box loss: 0.00392 RPN score loss: 0.00147 RPN total loss: 0.0054 Total loss: 0.80704 timestamp: 1654946439.3443184 iteration: 40125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.07429 FastRCNN total loss: 0.15226 L1 loss: 0.0000e+00 L2 loss: 0.62973 Learning rate: 0.002 Mask loss: 0.12121 RPN box loss: 0.0139 RPN score loss: 0.00328 RPN total loss: 0.01718 Total loss: 0.92037 timestamp: 1654946442.4769692 iteration: 40130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11479 FastRCNN class loss: 0.09703 FastRCNN total loss: 0.21182 L1 loss: 0.0000e+00 L2 loss: 0.62972 Learning rate: 0.002 Mask loss: 0.15284 RPN box loss: 0.04692 RPN score loss: 0.00692 RPN total loss: 0.05384 Total loss: 1.04822 timestamp: 1654946445.6696343 iteration: 40135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11132 FastRCNN class loss: 0.07385 FastRCNN total loss: 0.18517 L1 loss: 0.0000e+00 L2 loss: 0.62971 Learning rate: 0.002 Mask loss: 0.14096 RPN box loss: 0.02565 RPN score loss: 0.00492 RPN total loss: 0.03058 Total loss: 0.98642 timestamp: 1654946448.8679457 iteration: 40140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13363 FastRCNN class loss: 0.08593 FastRCNN total loss: 0.21956 L1 loss: 0.0000e+00 L2 loss: 0.6297 Learning rate: 0.002 Mask loss: 0.13323 RPN box loss: 0.02385 RPN score loss: 0.00262 RPN total loss: 0.02647 Total loss: 1.00897 timestamp: 1654946452.1192417 iteration: 40145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08713 FastRCNN class loss: 0.0579 FastRCNN total loss: 0.14503 L1 loss: 0.0000e+00 L2 loss: 0.6297 Learning rate: 0.002 Mask loss: 0.08588 RPN box loss: 0.00484 RPN score loss: 0.00515 RPN total loss: 0.00999 Total loss: 0.87059 timestamp: 1654946455.3124683 iteration: 40150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13065 FastRCNN class loss: 0.09508 FastRCNN total loss: 0.22573 L1 loss: 0.0000e+00 L2 loss: 0.62969 Learning rate: 0.002 Mask loss: 0.11765 RPN box loss: 0.02201 RPN score loss: 0.00785 RPN total loss: 0.02986 Total loss: 1.00293 timestamp: 1654946458.5002723 iteration: 40155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07481 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.12039 L1 loss: 0.0000e+00 L2 loss: 0.62968 Learning rate: 0.002 Mask loss: 0.08404 RPN box loss: 0.00948 RPN score loss: 0.00173 RPN total loss: 0.01121 Total loss: 0.84531 timestamp: 1654946461.608318 iteration: 40160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10374 FastRCNN class loss: 0.08488 FastRCNN total loss: 0.18862 L1 loss: 0.0000e+00 L2 loss: 0.62967 Learning rate: 0.002 Mask loss: 0.18098 RPN box loss: 0.00614 RPN score loss: 0.00256 RPN total loss: 0.0087 Total loss: 1.00797 timestamp: 1654946464.736502 iteration: 40165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08789 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.1486 L1 loss: 0.0000e+00 L2 loss: 0.62966 Learning rate: 0.002 Mask loss: 0.11913 RPN box loss: 0.02151 RPN score loss: 0.00566 RPN total loss: 0.02717 Total loss: 0.92456 timestamp: 1654946467.8809223 iteration: 40170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10666 FastRCNN class loss: 0.08253 FastRCNN total loss: 0.18919 L1 loss: 0.0000e+00 L2 loss: 0.62965 Learning rate: 0.002 Mask loss: 0.26988 RPN box loss: 0.03739 RPN score loss: 0.01374 RPN total loss: 0.05113 Total loss: 1.13985 timestamp: 1654946471.0778236 iteration: 40175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11264 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.18514 L1 loss: 0.0000e+00 L2 loss: 0.62964 Learning rate: 0.002 Mask loss: 0.11511 RPN box loss: 0.00604 RPN score loss: 0.00752 RPN total loss: 0.01357 Total loss: 0.94345 timestamp: 1654946474.2457213 iteration: 40180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13973 FastRCNN class loss: 0.07741 FastRCNN total loss: 0.21714 L1 loss: 0.0000e+00 L2 loss: 0.62963 Learning rate: 0.002 Mask loss: 0.16012 RPN box loss: 0.02001 RPN score loss: 0.00514 RPN total loss: 0.02515 Total loss: 1.03204 timestamp: 1654946477.428403 iteration: 40185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06982 FastRCNN class loss: 0.12988 FastRCNN total loss: 0.1997 L1 loss: 0.0000e+00 L2 loss: 0.62962 Learning rate: 0.002 Mask loss: 0.14991 RPN box loss: 0.03969 RPN score loss: 0.01237 RPN total loss: 0.05207 Total loss: 1.03129 timestamp: 1654946480.623504 iteration: 40190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0728 FastRCNN class loss: 0.07866 FastRCNN total loss: 0.15146 L1 loss: 0.0000e+00 L2 loss: 0.62961 Learning rate: 0.002 Mask loss: 0.13546 RPN box loss: 0.02612 RPN score loss: 0.00685 RPN total loss: 0.03297 Total loss: 0.94949 timestamp: 1654946483.8264027 iteration: 40195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16391 FastRCNN class loss: 0.11386 FastRCNN total loss: 0.27778 L1 loss: 0.0000e+00 L2 loss: 0.6296 Learning rate: 0.002 Mask loss: 0.17775 RPN box loss: 0.03733 RPN score loss: 0.00686 RPN total loss: 0.0442 Total loss: 1.12931 timestamp: 1654946487.0418537 iteration: 40200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.204 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.30455 L1 loss: 0.0000e+00 L2 loss: 0.62959 Learning rate: 0.002 Mask loss: 0.12561 RPN box loss: 0.0369 RPN score loss: 0.00492 RPN total loss: 0.04182 Total loss: 1.10156 timestamp: 1654946490.280747 iteration: 40205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10338 FastRCNN class loss: 0.0978 FastRCNN total loss: 0.20118 L1 loss: 0.0000e+00 L2 loss: 0.62958 Learning rate: 0.002 Mask loss: 0.12823 RPN box loss: 0.02903 RPN score loss: 0.00185 RPN total loss: 0.03088 Total loss: 0.98987 timestamp: 1654946493.5147877 iteration: 40210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08451 FastRCNN class loss: 0.08098 FastRCNN total loss: 0.16549 L1 loss: 0.0000e+00 L2 loss: 0.62957 Learning rate: 0.002 Mask loss: 0.14498 RPN box loss: 0.01402 RPN score loss: 0.00526 RPN total loss: 0.01928 Total loss: 0.95933 timestamp: 1654946496.6799939 iteration: 40215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12348 FastRCNN class loss: 0.08338 FastRCNN total loss: 0.20685 L1 loss: 0.0000e+00 L2 loss: 0.62956 Learning rate: 0.002 Mask loss: 0.19258 RPN box loss: 0.01838 RPN score loss: 0.00252 RPN total loss: 0.02091 Total loss: 1.04991 timestamp: 1654946499.7710788 iteration: 40220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03907 FastRCNN class loss: 0.04751 FastRCNN total loss: 0.08658 L1 loss: 0.0000e+00 L2 loss: 0.62955 Learning rate: 0.002 Mask loss: 0.0927 RPN box loss: 0.02197 RPN score loss: 0.00472 RPN total loss: 0.0267 Total loss: 0.83552 timestamp: 1654946503.0456219 iteration: 40225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05059 FastRCNN class loss: 0.0482 FastRCNN total loss: 0.09879 L1 loss: 0.0000e+00 L2 loss: 0.62954 Learning rate: 0.002 Mask loss: 0.10042 RPN box loss: 0.01521 RPN score loss: 0.00603 RPN total loss: 0.02125 Total loss: 0.85 timestamp: 1654946506.2169209 iteration: 40230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.07272 FastRCNN total loss: 0.15408 L1 loss: 0.0000e+00 L2 loss: 0.62953 Learning rate: 0.002 Mask loss: 0.20411 RPN box loss: 0.02236 RPN score loss: 0.00719 RPN total loss: 0.02955 Total loss: 1.01727 timestamp: 1654946509.4536097 iteration: 40235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0891 FastRCNN class loss: 0.07416 FastRCNN total loss: 0.16327 L1 loss: 0.0000e+00 L2 loss: 0.62952 Learning rate: 0.002 Mask loss: 0.08794 RPN box loss: 0.00938 RPN score loss: 0.00499 RPN total loss: 0.01437 Total loss: 0.89509 timestamp: 1654946512.651479 iteration: 40240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11822 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.17932 L1 loss: 0.0000e+00 L2 loss: 0.62951 Learning rate: 0.002 Mask loss: 0.10704 RPN box loss: 0.01742 RPN score loss: 0.00541 RPN total loss: 0.02283 Total loss: 0.93869 timestamp: 1654946515.862801 iteration: 40245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09964 FastRCNN class loss: 0.09136 FastRCNN total loss: 0.191 L1 loss: 0.0000e+00 L2 loss: 0.62951 Learning rate: 0.002 Mask loss: 0.14206 RPN box loss: 0.01691 RPN score loss: 0.00475 RPN total loss: 0.02166 Total loss: 0.98423 timestamp: 1654946519.0347083 iteration: 40250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08815 FastRCNN class loss: 0.04037 FastRCNN total loss: 0.12852 L1 loss: 0.0000e+00 L2 loss: 0.6295 Learning rate: 0.002 Mask loss: 0.09193 RPN box loss: 0.01994 RPN score loss: 0.00176 RPN total loss: 0.02169 Total loss: 0.87164 timestamp: 1654946522.1814523 iteration: 40255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0926 FastRCNN class loss: 0.048 FastRCNN total loss: 0.1406 L1 loss: 0.0000e+00 L2 loss: 0.62949 Learning rate: 0.002 Mask loss: 0.08496 RPN box loss: 0.00682 RPN score loss: 0.00281 RPN total loss: 0.00962 Total loss: 0.86467 timestamp: 1654946525.3920405 iteration: 40260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09609 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.16501 L1 loss: 0.0000e+00 L2 loss: 0.62948 Learning rate: 0.002 Mask loss: 0.10837 RPN box loss: 0.00838 RPN score loss: 0.00194 RPN total loss: 0.01032 Total loss: 0.91318 timestamp: 1654946528.620467 iteration: 40265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12425 FastRCNN class loss: 0.08506 FastRCNN total loss: 0.20932 L1 loss: 0.0000e+00 L2 loss: 0.62947 Learning rate: 0.002 Mask loss: 0.12321 RPN box loss: 0.02373 RPN score loss: 0.0073 RPN total loss: 0.03104 Total loss: 0.99304 timestamp: 1654946531.8305929 iteration: 40270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12317 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.19663 L1 loss: 0.0000e+00 L2 loss: 0.62947 Learning rate: 0.002 Mask loss: 0.22963 RPN box loss: 0.01428 RPN score loss: 0.00654 RPN total loss: 0.02082 Total loss: 1.07655 timestamp: 1654946535.0649729 iteration: 40275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.08152 FastRCNN total loss: 0.18657 L1 loss: 0.0000e+00 L2 loss: 0.62946 Learning rate: 0.002 Mask loss: 0.15333 RPN box loss: 0.03064 RPN score loss: 0.00251 RPN total loss: 0.03315 Total loss: 1.00251 timestamp: 1654946538.3317325 iteration: 40280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14232 FastRCNN class loss: 0.05805 FastRCNN total loss: 0.20037 L1 loss: 0.0000e+00 L2 loss: 0.62944 Learning rate: 0.002 Mask loss: 0.15229 RPN box loss: 0.00958 RPN score loss: 0.00197 RPN total loss: 0.01155 Total loss: 0.99365 timestamp: 1654946541.4660797 iteration: 40285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11808 FastRCNN class loss: 0.04653 FastRCNN total loss: 0.16461 L1 loss: 0.0000e+00 L2 loss: 0.62943 Learning rate: 0.002 Mask loss: 0.08138 RPN box loss: 0.02669 RPN score loss: 0.00368 RPN total loss: 0.03036 Total loss: 0.90579 timestamp: 1654946544.653075 iteration: 40290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07776 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.15101 L1 loss: 0.0000e+00 L2 loss: 0.62942 Learning rate: 0.002 Mask loss: 0.10788 RPN box loss: 0.01971 RPN score loss: 0.00573 RPN total loss: 0.02543 Total loss: 0.91375 timestamp: 1654946547.893337 iteration: 40295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10922 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.17988 L1 loss: 0.0000e+00 L2 loss: 0.62941 Learning rate: 0.002 Mask loss: 0.11763 RPN box loss: 0.06474 RPN score loss: 0.0077 RPN total loss: 0.07244 Total loss: 0.99937 timestamp: 1654946551.14307 iteration: 40300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13957 FastRCNN class loss: 0.09867 FastRCNN total loss: 0.23823 L1 loss: 0.0000e+00 L2 loss: 0.62941 Learning rate: 0.002 Mask loss: 0.16697 RPN box loss: 0.03503 RPN score loss: 0.00578 RPN total loss: 0.04081 Total loss: 1.07542 timestamp: 1654946554.425708 iteration: 40305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10382 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 0.6294 Learning rate: 0.002 Mask loss: 0.13809 RPN box loss: 0.01501 RPN score loss: 0.00718 RPN total loss: 0.0222 Total loss: 0.96157 timestamp: 1654946557.5249393 iteration: 40310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13639 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.21673 L1 loss: 0.0000e+00 L2 loss: 0.62939 Learning rate: 0.002 Mask loss: 0.13693 RPN box loss: 0.02427 RPN score loss: 0.0029 RPN total loss: 0.02717 Total loss: 1.01023 timestamp: 1654946560.7679374 iteration: 40315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14961 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.21341 L1 loss: 0.0000e+00 L2 loss: 0.62938 Learning rate: 0.002 Mask loss: 0.17215 RPN box loss: 0.02226 RPN score loss: 0.00514 RPN total loss: 0.0274 Total loss: 1.04233 timestamp: 1654946563.888836 iteration: 40320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13707 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.1959 L1 loss: 0.0000e+00 L2 loss: 0.62937 Learning rate: 0.002 Mask loss: 0.13962 RPN box loss: 0.01203 RPN score loss: 0.00242 RPN total loss: 0.01445 Total loss: 0.97934 timestamp: 1654946567.0624318 iteration: 40325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05779 FastRCNN class loss: 0.04442 FastRCNN total loss: 0.10222 L1 loss: 0.0000e+00 L2 loss: 0.62936 Learning rate: 0.002 Mask loss: 0.11923 RPN box loss: 0.01093 RPN score loss: 0.00214 RPN total loss: 0.01307 Total loss: 0.86388 timestamp: 1654946570.2192736 iteration: 40330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12964 FastRCNN class loss: 0.06996 FastRCNN total loss: 0.19959 L1 loss: 0.0000e+00 L2 loss: 0.62934 Learning rate: 0.002 Mask loss: 0.12158 RPN box loss: 0.02339 RPN score loss: 0.00386 RPN total loss: 0.02725 Total loss: 0.97776 timestamp: 1654946573.377323 iteration: 40335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14892 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.21449 L1 loss: 0.0000e+00 L2 loss: 0.62934 Learning rate: 0.002 Mask loss: 0.12885 RPN box loss: 0.0498 RPN score loss: 0.01511 RPN total loss: 0.06491 Total loss: 1.03759 timestamp: 1654946576.6232336 iteration: 40340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06406 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.12357 L1 loss: 0.0000e+00 L2 loss: 0.62933 Learning rate: 0.002 Mask loss: 0.17268 RPN box loss: 0.01313 RPN score loss: 0.00162 RPN total loss: 0.01475 Total loss: 0.94032 timestamp: 1654946579.7828362 iteration: 40345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07975 FastRCNN class loss: 0.06116 FastRCNN total loss: 0.14091 L1 loss: 0.0000e+00 L2 loss: 0.62931 Learning rate: 0.002 Mask loss: 0.14664 RPN box loss: 0.01607 RPN score loss: 0.00481 RPN total loss: 0.02088 Total loss: 0.93774 timestamp: 1654946582.9171543 iteration: 40350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14167 FastRCNN class loss: 0.11078 FastRCNN total loss: 0.25245 L1 loss: 0.0000e+00 L2 loss: 0.6293 Learning rate: 0.002 Mask loss: 0.23669 RPN box loss: 0.02188 RPN score loss: 0.01703 RPN total loss: 0.0389 Total loss: 1.15735 timestamp: 1654946586.1617258 iteration: 40355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12307 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.17991 L1 loss: 0.0000e+00 L2 loss: 0.6293 Learning rate: 0.002 Mask loss: 0.13303 RPN box loss: 0.02439 RPN score loss: 0.00879 RPN total loss: 0.03318 Total loss: 0.97542 timestamp: 1654946589.3828278 iteration: 40360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11111 FastRCNN class loss: 0.11231 FastRCNN total loss: 0.22342 L1 loss: 0.0000e+00 L2 loss: 0.62929 Learning rate: 0.002 Mask loss: 0.15409 RPN box loss: 0.02468 RPN score loss: 0.00962 RPN total loss: 0.0343 Total loss: 1.0411 timestamp: 1654946592.5535336 iteration: 40365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07956 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.14503 L1 loss: 0.0000e+00 L2 loss: 0.62928 Learning rate: 0.002 Mask loss: 0.10191 RPN box loss: 0.03923 RPN score loss: 0.00336 RPN total loss: 0.04259 Total loss: 0.91881 timestamp: 1654946595.8545938 iteration: 40370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08754 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.14678 L1 loss: 0.0000e+00 L2 loss: 0.62927 Learning rate: 0.002 Mask loss: 0.09186 RPN box loss: 0.02415 RPN score loss: 0.00207 RPN total loss: 0.02623 Total loss: 0.89414 timestamp: 1654946599.0941744 iteration: 40375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09649 FastRCNN class loss: 0.06045 FastRCNN total loss: 0.15694 L1 loss: 0.0000e+00 L2 loss: 0.62926 Learning rate: 0.002 Mask loss: 0.23685 RPN box loss: 0.03895 RPN score loss: 0.00281 RPN total loss: 0.04176 Total loss: 1.06482 timestamp: 1654946602.2510862 iteration: 40380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.16965 L1 loss: 0.0000e+00 L2 loss: 0.62924 Learning rate: 0.002 Mask loss: 0.15868 RPN box loss: 0.01357 RPN score loss: 0.01049 RPN total loss: 0.02406 Total loss: 0.98164 timestamp: 1654946605.4868302 iteration: 40385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22757 FastRCNN class loss: 0.14611 FastRCNN total loss: 0.37369 L1 loss: 0.0000e+00 L2 loss: 0.62923 Learning rate: 0.002 Mask loss: 0.17025 RPN box loss: 0.03994 RPN score loss: 0.03598 RPN total loss: 0.07592 Total loss: 1.2491 timestamp: 1654946608.7091699 iteration: 40390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09335 FastRCNN class loss: 0.05238 FastRCNN total loss: 0.14572 L1 loss: 0.0000e+00 L2 loss: 0.62922 Learning rate: 0.002 Mask loss: 0.26308 RPN box loss: 0.01173 RPN score loss: 0.00381 RPN total loss: 0.01554 Total loss: 1.05357 timestamp: 1654946611.9069793 iteration: 40395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.12113 FastRCNN total loss: 0.20808 L1 loss: 0.0000e+00 L2 loss: 0.62922 Learning rate: 0.002 Mask loss: 0.13318 RPN box loss: 0.04134 RPN score loss: 0.00604 RPN total loss: 0.04738 Total loss: 1.01786 timestamp: 1654946615.0846534 iteration: 40400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05887 FastRCNN class loss: 0.05153 FastRCNN total loss: 0.1104 L1 loss: 0.0000e+00 L2 loss: 0.62921 Learning rate: 0.002 Mask loss: 0.12443 RPN box loss: 0.00323 RPN score loss: 0.00461 RPN total loss: 0.00784 Total loss: 0.87188 timestamp: 1654946618.2747316 iteration: 40405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07996 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.15491 L1 loss: 0.0000e+00 L2 loss: 0.6292 Learning rate: 0.002 Mask loss: 0.11874 RPN box loss: 0.00471 RPN score loss: 0.00202 RPN total loss: 0.00673 Total loss: 0.90958 timestamp: 1654946621.4295282 iteration: 40410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13373 FastRCNN class loss: 0.09829 FastRCNN total loss: 0.23202 L1 loss: 0.0000e+00 L2 loss: 0.62919 Learning rate: 0.002 Mask loss: 0.13599 RPN box loss: 0.02724 RPN score loss: 0.00987 RPN total loss: 0.03711 Total loss: 1.03431 timestamp: 1654946624.5511575 iteration: 40415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08556 FastRCNN class loss: 0.05587 FastRCNN total loss: 0.14143 L1 loss: 0.0000e+00 L2 loss: 0.62918 Learning rate: 0.002 Mask loss: 0.10184 RPN box loss: 0.02257 RPN score loss: 0.00643 RPN total loss: 0.02899 Total loss: 0.90145 timestamp: 1654946627.711725 iteration: 40420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09127 FastRCNN class loss: 0.05342 FastRCNN total loss: 0.14469 L1 loss: 0.0000e+00 L2 loss: 0.62917 Learning rate: 0.002 Mask loss: 0.12449 RPN box loss: 0.0101 RPN score loss: 0.001 RPN total loss: 0.0111 Total loss: 0.90944 timestamp: 1654946630.8694305 iteration: 40425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09616 FastRCNN class loss: 0.07216 FastRCNN total loss: 0.16832 L1 loss: 0.0000e+00 L2 loss: 0.62916 Learning rate: 0.002 Mask loss: 0.16567 RPN box loss: 0.05229 RPN score loss: 0.01224 RPN total loss: 0.06453 Total loss: 1.02768 timestamp: 1654946634.098346 iteration: 40430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1582 FastRCNN class loss: 0.09792 FastRCNN total loss: 0.25611 L1 loss: 0.0000e+00 L2 loss: 0.62915 Learning rate: 0.002 Mask loss: 0.17457 RPN box loss: 0.01107 RPN score loss: 0.0046 RPN total loss: 0.01567 Total loss: 1.07551 timestamp: 1654946637.2369242 iteration: 40435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07729 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.14035 L1 loss: 0.0000e+00 L2 loss: 0.62914 Learning rate: 0.002 Mask loss: 0.17387 RPN box loss: 0.02926 RPN score loss: 0.01201 RPN total loss: 0.04128 Total loss: 0.98463 timestamp: 1654946640.4377701 iteration: 40440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11479 FastRCNN class loss: 0.053 FastRCNN total loss: 0.16779 L1 loss: 0.0000e+00 L2 loss: 0.62913 Learning rate: 0.002 Mask loss: 0.15926 RPN box loss: 0.01201 RPN score loss: 0.00288 RPN total loss: 0.01489 Total loss: 0.97107 timestamp: 1654946643.7122102 iteration: 40445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10012 FastRCNN class loss: 0.0617 FastRCNN total loss: 0.16182 L1 loss: 0.0000e+00 L2 loss: 0.62912 Learning rate: 0.002 Mask loss: 0.15393 RPN box loss: 0.02848 RPN score loss: 0.00698 RPN total loss: 0.03547 Total loss: 0.98035 timestamp: 1654946646.9335032 iteration: 40450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09225 FastRCNN class loss: 0.06996 FastRCNN total loss: 0.16221 L1 loss: 0.0000e+00 L2 loss: 0.62912 Learning rate: 0.002 Mask loss: 0.1637 RPN box loss: 0.00752 RPN score loss: 0.00619 RPN total loss: 0.01372 Total loss: 0.96874 timestamp: 1654946650.1202757 iteration: 40455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15318 FastRCNN class loss: 0.18745 FastRCNN total loss: 0.34063 L1 loss: 0.0000e+00 L2 loss: 0.62911 Learning rate: 0.002 Mask loss: 0.19843 RPN box loss: 0.04801 RPN score loss: 0.01305 RPN total loss: 0.06105 Total loss: 1.22922 timestamp: 1654946653.4188995 iteration: 40460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.17101 L1 loss: 0.0000e+00 L2 loss: 0.6291 Learning rate: 0.002 Mask loss: 0.13341 RPN box loss: 0.02872 RPN score loss: 0.0054 RPN total loss: 0.03412 Total loss: 0.96764 timestamp: 1654946656.5605936 iteration: 40465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11017 FastRCNN class loss: 0.03755 FastRCNN total loss: 0.14773 L1 loss: 0.0000e+00 L2 loss: 0.62909 Learning rate: 0.002 Mask loss: 0.10614 RPN box loss: 0.00344 RPN score loss: 0.00526 RPN total loss: 0.0087 Total loss: 0.89166 timestamp: 1654946659.7087228 iteration: 40470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10498 FastRCNN class loss: 0.10085 FastRCNN total loss: 0.20583 L1 loss: 0.0000e+00 L2 loss: 0.62908 Learning rate: 0.002 Mask loss: 0.143 RPN box loss: 0.0281 RPN score loss: 0.01178 RPN total loss: 0.03988 Total loss: 1.01779 timestamp: 1654946663.0043576 iteration: 40475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13125 FastRCNN class loss: 0.06469 FastRCNN total loss: 0.19593 L1 loss: 0.0000e+00 L2 loss: 0.62907 Learning rate: 0.002 Mask loss: 0.12859 RPN box loss: 0.00997 RPN score loss: 0.00436 RPN total loss: 0.01433 Total loss: 0.96792 timestamp: 1654946666.240316 iteration: 40480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12312 FastRCNN class loss: 0.10372 FastRCNN total loss: 0.22685 L1 loss: 0.0000e+00 L2 loss: 0.62906 Learning rate: 0.002 Mask loss: 0.15867 RPN box loss: 0.03004 RPN score loss: 0.00304 RPN total loss: 0.03308 Total loss: 1.04765 timestamp: 1654946669.4860198 iteration: 40485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10832 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.17309 L1 loss: 0.0000e+00 L2 loss: 0.62905 Learning rate: 0.002 Mask loss: 0.1228 RPN box loss: 0.02231 RPN score loss: 0.00688 RPN total loss: 0.02919 Total loss: 0.95413 timestamp: 1654946672.6497664 iteration: 40490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05579 FastRCNN class loss: 0.04703 FastRCNN total loss: 0.10283 L1 loss: 0.0000e+00 L2 loss: 0.62904 Learning rate: 0.002 Mask loss: 0.11317 RPN box loss: 0.02437 RPN score loss: 0.00658 RPN total loss: 0.03095 Total loss: 0.87599 timestamp: 1654946675.853633 iteration: 40495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12057 FastRCNN class loss: 0.08857 FastRCNN total loss: 0.20914 L1 loss: 0.0000e+00 L2 loss: 0.62903 Learning rate: 0.002 Mask loss: 0.17604 RPN box loss: 0.01999 RPN score loss: 0.00312 RPN total loss: 0.02311 Total loss: 1.03732 timestamp: 1654946679.018214 iteration: 40500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16468 FastRCNN class loss: 0.08215 FastRCNN total loss: 0.24683 L1 loss: 0.0000e+00 L2 loss: 0.62902 Learning rate: 0.002 Mask loss: 0.16222 RPN box loss: 0.01207 RPN score loss: 0.002 RPN total loss: 0.01407 Total loss: 1.05214 timestamp: 1654946682.238667 iteration: 40505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06125 FastRCNN class loss: 0.05066 FastRCNN total loss: 0.11191 L1 loss: 0.0000e+00 L2 loss: 0.62901 Learning rate: 0.002 Mask loss: 0.14871 RPN box loss: 0.00221 RPN score loss: 0.00264 RPN total loss: 0.00485 Total loss: 0.89449 timestamp: 1654946685.4435625 iteration: 40510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13053 FastRCNN class loss: 0.06886 FastRCNN total loss: 0.19939 L1 loss: 0.0000e+00 L2 loss: 0.629 Learning rate: 0.002 Mask loss: 0.12832 RPN box loss: 0.01885 RPN score loss: 0.00355 RPN total loss: 0.0224 Total loss: 0.9791 timestamp: 1654946688.6866977 iteration: 40515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11775 FastRCNN class loss: 0.07278 FastRCNN total loss: 0.19053 L1 loss: 0.0000e+00 L2 loss: 0.62899 Learning rate: 0.002 Mask loss: 0.1238 RPN box loss: 0.03649 RPN score loss: 0.00784 RPN total loss: 0.04432 Total loss: 0.98765 timestamp: 1654946691.8744717 iteration: 40520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06347 FastRCNN class loss: 0.0354 FastRCNN total loss: 0.09887 L1 loss: 0.0000e+00 L2 loss: 0.62898 Learning rate: 0.002 Mask loss: 0.11787 RPN box loss: 0.01643 RPN score loss: 0.00167 RPN total loss: 0.01811 Total loss: 0.86382 timestamp: 1654946694.9809902 iteration: 40525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1452 FastRCNN class loss: 0.0886 FastRCNN total loss: 0.2338 L1 loss: 0.0000e+00 L2 loss: 0.62897 Learning rate: 0.002 Mask loss: 0.12012 RPN box loss: 0.03001 RPN score loss: 0.0046 RPN total loss: 0.03462 Total loss: 1.0175 timestamp: 1654946698.1810446 iteration: 40530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1227 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.20001 L1 loss: 0.0000e+00 L2 loss: 0.62896 Learning rate: 0.002 Mask loss: 0.17383 RPN box loss: 0.04343 RPN score loss: 0.0029 RPN total loss: 0.04634 Total loss: 1.04913 timestamp: 1654946701.4158337 iteration: 40535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.17022 L1 loss: 0.0000e+00 L2 loss: 0.62895 Learning rate: 0.002 Mask loss: 0.13001 RPN box loss: 0.02249 RPN score loss: 0.00463 RPN total loss: 0.02712 Total loss: 0.95629 timestamp: 1654946704.6467688 iteration: 40540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09661 FastRCNN class loss: 0.03884 FastRCNN total loss: 0.13545 L1 loss: 0.0000e+00 L2 loss: 0.62894 Learning rate: 0.002 Mask loss: 0.06154 RPN box loss: 0.00498 RPN score loss: 0.00152 RPN total loss: 0.0065 Total loss: 0.83242 timestamp: 1654946707.8385537 iteration: 40545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14735 FastRCNN class loss: 0.08187 FastRCNN total loss: 0.22922 L1 loss: 0.0000e+00 L2 loss: 0.62893 Learning rate: 0.002 Mask loss: 0.15374 RPN box loss: 0.05887 RPN score loss: 0.02148 RPN total loss: 0.08035 Total loss: 1.09223 timestamp: 1654946711.0587864 iteration: 40550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10136 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.17942 L1 loss: 0.0000e+00 L2 loss: 0.62892 Learning rate: 0.002 Mask loss: 0.12158 RPN box loss: 0.01757 RPN score loss: 0.00373 RPN total loss: 0.0213 Total loss: 0.95121 timestamp: 1654946714.3319688 iteration: 40555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06682 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.13404 L1 loss: 0.0000e+00 L2 loss: 0.62891 Learning rate: 0.002 Mask loss: 0.13657 RPN box loss: 0.02286 RPN score loss: 0.00921 RPN total loss: 0.03208 Total loss: 0.93159 timestamp: 1654946717.5261972 iteration: 40560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15592 FastRCNN class loss: 0.09933 FastRCNN total loss: 0.25524 L1 loss: 0.0000e+00 L2 loss: 0.6289 Learning rate: 0.002 Mask loss: 0.23015 RPN box loss: 0.0147 RPN score loss: 0.01052 RPN total loss: 0.02522 Total loss: 1.13952 timestamp: 1654946720.7393851 iteration: 40565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07436 FastRCNN class loss: 0.06763 FastRCNN total loss: 0.14199 L1 loss: 0.0000e+00 L2 loss: 0.62889 Learning rate: 0.002 Mask loss: 0.15028 RPN box loss: 0.01112 RPN score loss: 0.00257 RPN total loss: 0.01368 Total loss: 0.93484 timestamp: 1654946723.926667 iteration: 40570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0886 FastRCNN class loss: 0.06767 FastRCNN total loss: 0.15627 L1 loss: 0.0000e+00 L2 loss: 0.62888 Learning rate: 0.002 Mask loss: 0.23293 RPN box loss: 0.02028 RPN score loss: 0.00214 RPN total loss: 0.02241 Total loss: 1.0405 timestamp: 1654946727.1481798 iteration: 40575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08298 FastRCNN class loss: 0.04706 FastRCNN total loss: 0.13004 L1 loss: 0.0000e+00 L2 loss: 0.62887 Learning rate: 0.002 Mask loss: 0.14118 RPN box loss: 0.01614 RPN score loss: 0.0027 RPN total loss: 0.01884 Total loss: 0.91893 timestamp: 1654946730.2583475 iteration: 40580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10852 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.18424 L1 loss: 0.0000e+00 L2 loss: 0.62886 Learning rate: 0.002 Mask loss: 0.12949 RPN box loss: 0.02069 RPN score loss: 0.00282 RPN total loss: 0.02351 Total loss: 0.9661 timestamp: 1654946733.4135852 iteration: 40585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14257 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.23014 L1 loss: 0.0000e+00 L2 loss: 0.62885 Learning rate: 0.002 Mask loss: 0.24072 RPN box loss: 0.01009 RPN score loss: 0.00637 RPN total loss: 0.01646 Total loss: 1.11617 timestamp: 1654946736.592159 iteration: 40590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0869 FastRCNN class loss: 0.05257 FastRCNN total loss: 0.13947 L1 loss: 0.0000e+00 L2 loss: 0.62884 Learning rate: 0.002 Mask loss: 0.13306 RPN box loss: 0.01271 RPN score loss: 0.00443 RPN total loss: 0.01714 Total loss: 0.9185 timestamp: 1654946739.7940178 iteration: 40595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13375 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.20307 L1 loss: 0.0000e+00 L2 loss: 0.62883 Learning rate: 0.002 Mask loss: 0.10918 RPN box loss: 0.01127 RPN score loss: 0.00867 RPN total loss: 0.01995 Total loss: 0.96103 timestamp: 1654946742.8975809 iteration: 40600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18075 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.25707 L1 loss: 0.0000e+00 L2 loss: 0.62882 Learning rate: 0.002 Mask loss: 0.12775 RPN box loss: 0.04003 RPN score loss: 0.00935 RPN total loss: 0.04938 Total loss: 1.06301 timestamp: 1654946746.158553 iteration: 40605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14514 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.21701 L1 loss: 0.0000e+00 L2 loss: 0.62881 Learning rate: 0.002 Mask loss: 0.09793 RPN box loss: 0.01527 RPN score loss: 0.00762 RPN total loss: 0.02289 Total loss: 0.96664 timestamp: 1654946749.3576074 iteration: 40610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12734 FastRCNN class loss: 0.06501 FastRCNN total loss: 0.19235 L1 loss: 0.0000e+00 L2 loss: 0.6288 Learning rate: 0.002 Mask loss: 0.10725 RPN box loss: 0.03163 RPN score loss: 0.00647 RPN total loss: 0.0381 Total loss: 0.9665 timestamp: 1654946752.4721017 iteration: 40615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12122 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.21116 L1 loss: 0.0000e+00 L2 loss: 0.62879 Learning rate: 0.002 Mask loss: 0.15004 RPN box loss: 0.04879 RPN score loss: 0.00312 RPN total loss: 0.05191 Total loss: 1.04191 timestamp: 1654946755.6367779 iteration: 40620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1092 FastRCNN class loss: 0.08347 FastRCNN total loss: 0.19268 L1 loss: 0.0000e+00 L2 loss: 0.62878 Learning rate: 0.002 Mask loss: 0.14749 RPN box loss: 0.01466 RPN score loss: 0.00743 RPN total loss: 0.0221 Total loss: 0.99104 timestamp: 1654946758.870331 iteration: 40625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08126 FastRCNN class loss: 0.05998 FastRCNN total loss: 0.14124 L1 loss: 0.0000e+00 L2 loss: 0.62877 Learning rate: 0.002 Mask loss: 0.1211 RPN box loss: 0.03147 RPN score loss: 0.00199 RPN total loss: 0.03346 Total loss: 0.92457 timestamp: 1654946762.0385325 iteration: 40630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06857 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.11309 L1 loss: 0.0000e+00 L2 loss: 0.62876 Learning rate: 0.002 Mask loss: 0.09589 RPN box loss: 0.02285 RPN score loss: 0.00941 RPN total loss: 0.03226 Total loss: 0.87001 timestamp: 1654946765.2290611 iteration: 40635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08814 FastRCNN class loss: 0.04995 FastRCNN total loss: 0.13809 L1 loss: 0.0000e+00 L2 loss: 0.62875 Learning rate: 0.002 Mask loss: 0.11684 RPN box loss: 0.01313 RPN score loss: 0.00156 RPN total loss: 0.01469 Total loss: 0.89837 timestamp: 1654946768.3628354 iteration: 40640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11305 FastRCNN class loss: 0.11818 FastRCNN total loss: 0.23124 L1 loss: 0.0000e+00 L2 loss: 0.62874 Learning rate: 0.002 Mask loss: 0.15228 RPN box loss: 0.0511 RPN score loss: 0.00275 RPN total loss: 0.05385 Total loss: 1.06611 timestamp: 1654946771.526621 iteration: 40645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16087 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.23912 L1 loss: 0.0000e+00 L2 loss: 0.62873 Learning rate: 0.002 Mask loss: 0.13856 RPN box loss: 0.01577 RPN score loss: 0.00352 RPN total loss: 0.01929 Total loss: 1.02571 timestamp: 1654946774.6865628 iteration: 40650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07109 FastRCNN class loss: 0.05455 FastRCNN total loss: 0.12564 L1 loss: 0.0000e+00 L2 loss: 0.62873 Learning rate: 0.002 Mask loss: 0.15227 RPN box loss: 0.02224 RPN score loss: 0.00973 RPN total loss: 0.03197 Total loss: 0.93861 timestamp: 1654946777.846363 iteration: 40655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.066 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.12667 L1 loss: 0.0000e+00 L2 loss: 0.62872 Learning rate: 0.002 Mask loss: 0.12049 RPN box loss: 0.01021 RPN score loss: 0.00082 RPN total loss: 0.01103 Total loss: 0.88691 timestamp: 1654946781.0473273 iteration: 40660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1277 FastRCNN class loss: 0.12297 FastRCNN total loss: 0.25067 L1 loss: 0.0000e+00 L2 loss: 0.62871 Learning rate: 0.002 Mask loss: 0.18337 RPN box loss: 0.04215 RPN score loss: 0.00831 RPN total loss: 0.05046 Total loss: 1.11321 timestamp: 1654946784.1956902 iteration: 40665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10383 FastRCNN class loss: 0.06158 FastRCNN total loss: 0.16541 L1 loss: 0.0000e+00 L2 loss: 0.6287 Learning rate: 0.002 Mask loss: 0.14153 RPN box loss: 0.00978 RPN score loss: 0.00167 RPN total loss: 0.01145 Total loss: 0.94709 timestamp: 1654946787.3928788 iteration: 40670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11227 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.19702 L1 loss: 0.0000e+00 L2 loss: 0.62869 Learning rate: 0.002 Mask loss: 0.11814 RPN box loss: 0.01054 RPN score loss: 0.00736 RPN total loss: 0.0179 Total loss: 0.96175 timestamp: 1654946790.5077846 iteration: 40675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11154 FastRCNN class loss: 0.05433 FastRCNN total loss: 0.16587 L1 loss: 0.0000e+00 L2 loss: 0.62868 Learning rate: 0.002 Mask loss: 0.14125 RPN box loss: 0.00525 RPN score loss: 0.00201 RPN total loss: 0.00725 Total loss: 0.94305 timestamp: 1654946793.7272913 iteration: 40680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15709 FastRCNN class loss: 0.0647 FastRCNN total loss: 0.22179 L1 loss: 0.0000e+00 L2 loss: 0.62867 Learning rate: 0.002 Mask loss: 0.08742 RPN box loss: 0.0239 RPN score loss: 0.006 RPN total loss: 0.0299 Total loss: 0.96778 timestamp: 1654946796.9197478 iteration: 40685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1365 FastRCNN class loss: 0.07542 FastRCNN total loss: 0.21192 L1 loss: 0.0000e+00 L2 loss: 0.62867 Learning rate: 0.002 Mask loss: 0.14399 RPN box loss: 0.05059 RPN score loss: 0.00336 RPN total loss: 0.05395 Total loss: 1.03852 timestamp: 1654946800.1201124 iteration: 40690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16948 FastRCNN class loss: 0.10693 FastRCNN total loss: 0.27641 L1 loss: 0.0000e+00 L2 loss: 0.62866 Learning rate: 0.002 Mask loss: 0.18728 RPN box loss: 0.02666 RPN score loss: 0.00496 RPN total loss: 0.03162 Total loss: 1.12397 timestamp: 1654946803.3720648 iteration: 40695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13506 FastRCNN class loss: 0.09575 FastRCNN total loss: 0.23081 L1 loss: 0.0000e+00 L2 loss: 0.62865 Learning rate: 0.002 Mask loss: 0.22996 RPN box loss: 0.0305 RPN score loss: 0.0074 RPN total loss: 0.0379 Total loss: 1.12732 timestamp: 1654946806.5519931 iteration: 40700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1189 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.19589 L1 loss: 0.0000e+00 L2 loss: 0.62864 Learning rate: 0.002 Mask loss: 0.16133 RPN box loss: 0.01406 RPN score loss: 0.00375 RPN total loss: 0.0178 Total loss: 1.00367 timestamp: 1654946809.8308594 iteration: 40705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04727 FastRCNN class loss: 0.04366 FastRCNN total loss: 0.09092 L1 loss: 0.0000e+00 L2 loss: 0.62863 Learning rate: 0.002 Mask loss: 0.07428 RPN box loss: 0.00404 RPN score loss: 0.00243 RPN total loss: 0.00648 Total loss: 0.80031 timestamp: 1654946813.08947 iteration: 40710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05748 FastRCNN class loss: 0.04312 FastRCNN total loss: 0.1006 L1 loss: 0.0000e+00 L2 loss: 0.62862 Learning rate: 0.002 Mask loss: 0.11375 RPN box loss: 0.00849 RPN score loss: 0.00156 RPN total loss: 0.01005 Total loss: 0.85302 timestamp: 1654946816.3236325 iteration: 40715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05664 FastRCNN class loss: 0.04625 FastRCNN total loss: 0.10289 L1 loss: 0.0000e+00 L2 loss: 0.62861 Learning rate: 0.002 Mask loss: 0.10627 RPN box loss: 0.04256 RPN score loss: 0.00249 RPN total loss: 0.04506 Total loss: 0.88283 timestamp: 1654946819.5907478 iteration: 40720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25018 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.33184 L1 loss: 0.0000e+00 L2 loss: 0.6286 Learning rate: 0.002 Mask loss: 0.11475 RPN box loss: 0.02951 RPN score loss: 0.01153 RPN total loss: 0.04103 Total loss: 1.11623 timestamp: 1654946822.8129659 iteration: 40725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07324 FastRCNN class loss: 0.04036 FastRCNN total loss: 0.1136 L1 loss: 0.0000e+00 L2 loss: 0.62859 Learning rate: 0.002 Mask loss: 0.12518 RPN box loss: 0.01828 RPN score loss: 0.00208 RPN total loss: 0.02036 Total loss: 0.88773 timestamp: 1654946826.0649333 iteration: 40730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08281 FastRCNN class loss: 0.05961 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.62858 Learning rate: 0.002 Mask loss: 0.12865 RPN box loss: 0.01218 RPN score loss: 0.00321 RPN total loss: 0.01539 Total loss: 0.91504 timestamp: 1654946829.2763395 iteration: 40735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10431 FastRCNN class loss: 0.08291 FastRCNN total loss: 0.18721 L1 loss: 0.0000e+00 L2 loss: 0.62857 Learning rate: 0.002 Mask loss: 0.10165 RPN box loss: 0.00938 RPN score loss: 0.00253 RPN total loss: 0.0119 Total loss: 0.92934 timestamp: 1654946832.4075625 iteration: 40740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07654 FastRCNN class loss: 0.03819 FastRCNN total loss: 0.11473 L1 loss: 0.0000e+00 L2 loss: 0.62856 Learning rate: 0.002 Mask loss: 0.08661 RPN box loss: 0.00754 RPN score loss: 0.00591 RPN total loss: 0.01345 Total loss: 0.84335 timestamp: 1654946835.5542827 iteration: 40745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08032 FastRCNN class loss: 0.0681 FastRCNN total loss: 0.14842 L1 loss: 0.0000e+00 L2 loss: 0.62855 Learning rate: 0.002 Mask loss: 0.14339 RPN box loss: 0.01414 RPN score loss: 0.0018 RPN total loss: 0.01595 Total loss: 0.93631 timestamp: 1654946838.765935 iteration: 40750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09779 FastRCNN class loss: 0.09624 FastRCNN total loss: 0.19404 L1 loss: 0.0000e+00 L2 loss: 0.62854 Learning rate: 0.002 Mask loss: 0.13262 RPN box loss: 0.02508 RPN score loss: 0.01126 RPN total loss: 0.03634 Total loss: 0.99154 timestamp: 1654946841.9444766 iteration: 40755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08991 FastRCNN class loss: 0.10814 FastRCNN total loss: 0.19805 L1 loss: 0.0000e+00 L2 loss: 0.62853 Learning rate: 0.002 Mask loss: 0.14656 RPN box loss: 0.02663 RPN score loss: 0.00396 RPN total loss: 0.03059 Total loss: 1.00374 timestamp: 1654946845.1849303 iteration: 40760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0708 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.13969 L1 loss: 0.0000e+00 L2 loss: 0.62852 Learning rate: 0.002 Mask loss: 0.136 RPN box loss: 0.01747 RPN score loss: 0.00256 RPN total loss: 0.02003 Total loss: 0.92424 timestamp: 1654946848.3478973 iteration: 40765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18266 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.26978 L1 loss: 0.0000e+00 L2 loss: 0.62851 Learning rate: 0.002 Mask loss: 0.1806 RPN box loss: 0.01686 RPN score loss: 0.00604 RPN total loss: 0.0229 Total loss: 1.10178 timestamp: 1654946851.595084 iteration: 40770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15468 FastRCNN class loss: 0.08209 FastRCNN total loss: 0.23676 L1 loss: 0.0000e+00 L2 loss: 0.6285 Learning rate: 0.002 Mask loss: 0.13341 RPN box loss: 0.02478 RPN score loss: 0.0029 RPN total loss: 0.02768 Total loss: 1.02635 timestamp: 1654946854.7419128 iteration: 40775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07493 FastRCNN class loss: 0.06626 FastRCNN total loss: 0.14119 L1 loss: 0.0000e+00 L2 loss: 0.6285 Learning rate: 0.002 Mask loss: 0.10322 RPN box loss: 0.0274 RPN score loss: 0.00413 RPN total loss: 0.03153 Total loss: 0.90444 timestamp: 1654946857.9073753 iteration: 40780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04639 FastRCNN class loss: 0.03657 FastRCNN total loss: 0.08296 L1 loss: 0.0000e+00 L2 loss: 0.62849 Learning rate: 0.002 Mask loss: 0.15469 RPN box loss: 0.00598 RPN score loss: 0.00198 RPN total loss: 0.00796 Total loss: 0.8741 timestamp: 1654946861.0933752 iteration: 40785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10651 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.16997 L1 loss: 0.0000e+00 L2 loss: 0.62848 Learning rate: 0.002 Mask loss: 0.15681 RPN box loss: 0.0208 RPN score loss: 0.01271 RPN total loss: 0.0335 Total loss: 0.98876 timestamp: 1654946864.2634897 iteration: 40790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07877 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.1497 L1 loss: 0.0000e+00 L2 loss: 0.62846 Learning rate: 0.002 Mask loss: 0.10585 RPN box loss: 0.01268 RPN score loss: 0.00298 RPN total loss: 0.01566 Total loss: 0.89968 timestamp: 1654946867.431214 iteration: 40795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06862 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.62846 Learning rate: 0.002 Mask loss: 0.13823 RPN box loss: 0.01307 RPN score loss: 0.00613 RPN total loss: 0.0192 Total loss: 0.92216 timestamp: 1654946870.7101452 iteration: 40800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18069 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.24013 L1 loss: 0.0000e+00 L2 loss: 0.62845 Learning rate: 0.002 Mask loss: 0.11438 RPN box loss: 0.01799 RPN score loss: 0.00631 RPN total loss: 0.0243 Total loss: 1.00727 timestamp: 1654946873.918341 iteration: 40805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1034 FastRCNN class loss: 0.08002 FastRCNN total loss: 0.18342 L1 loss: 0.0000e+00 L2 loss: 0.62844 Learning rate: 0.002 Mask loss: 0.14655 RPN box loss: 0.02706 RPN score loss: 0.00182 RPN total loss: 0.02888 Total loss: 0.98729 timestamp: 1654946877.1440446 iteration: 40810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08697 FastRCNN class loss: 0.03842 FastRCNN total loss: 0.12539 L1 loss: 0.0000e+00 L2 loss: 0.62843 Learning rate: 0.002 Mask loss: 0.1298 RPN box loss: 0.00474 RPN score loss: 0.00152 RPN total loss: 0.00626 Total loss: 0.88988 timestamp: 1654946880.3787332 iteration: 40815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09602 FastRCNN class loss: 0.05176 FastRCNN total loss: 0.14778 L1 loss: 0.0000e+00 L2 loss: 0.62842 Learning rate: 0.002 Mask loss: 0.18071 RPN box loss: 0.02863 RPN score loss: 0.00517 RPN total loss: 0.0338 Total loss: 0.9907 timestamp: 1654946883.6229498 iteration: 40820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12652 FastRCNN class loss: 0.10268 FastRCNN total loss: 0.2292 L1 loss: 0.0000e+00 L2 loss: 0.62841 Learning rate: 0.002 Mask loss: 0.17112 RPN box loss: 0.01009 RPN score loss: 0.00509 RPN total loss: 0.01519 Total loss: 1.04392 timestamp: 1654946886.7837355 iteration: 40825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11425 FastRCNN class loss: 0.09276 FastRCNN total loss: 0.20701 L1 loss: 0.0000e+00 L2 loss: 0.6284 Learning rate: 0.002 Mask loss: 0.1703 RPN box loss: 0.02617 RPN score loss: 0.00564 RPN total loss: 0.03181 Total loss: 1.03752 timestamp: 1654946890.0009851 iteration: 40830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09866 FastRCNN class loss: 0.09449 FastRCNN total loss: 0.19315 L1 loss: 0.0000e+00 L2 loss: 0.62839 Learning rate: 0.002 Mask loss: 0.13422 RPN box loss: 0.01342 RPN score loss: 0.00538 RPN total loss: 0.0188 Total loss: 0.97456 timestamp: 1654946893.1311235 iteration: 40835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07934 FastRCNN class loss: 0.08395 FastRCNN total loss: 0.1633 L1 loss: 0.0000e+00 L2 loss: 0.62838 Learning rate: 0.002 Mask loss: 0.10568 RPN box loss: 0.01817 RPN score loss: 0.00641 RPN total loss: 0.02458 Total loss: 0.92193 timestamp: 1654946896.2964225 iteration: 40840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08462 FastRCNN class loss: 0.05623 FastRCNN total loss: 0.14086 L1 loss: 0.0000e+00 L2 loss: 0.62837 Learning rate: 0.002 Mask loss: 0.1119 RPN box loss: 0.01409 RPN score loss: 0.00809 RPN total loss: 0.02218 Total loss: 0.90331 timestamp: 1654946899.414492 iteration: 40845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06845 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.13428 L1 loss: 0.0000e+00 L2 loss: 0.62836 Learning rate: 0.002 Mask loss: 0.09785 RPN box loss: 0.01474 RPN score loss: 0.00346 RPN total loss: 0.01819 Total loss: 0.87869 timestamp: 1654946902.6137087 iteration: 40850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.05222 FastRCNN total loss: 0.12602 L1 loss: 0.0000e+00 L2 loss: 0.62835 Learning rate: 0.002 Mask loss: 0.1006 RPN box loss: 0.02364 RPN score loss: 0.00416 RPN total loss: 0.02781 Total loss: 0.88277 timestamp: 1654946905.7922087 iteration: 40855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09063 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.16905 L1 loss: 0.0000e+00 L2 loss: 0.62834 Learning rate: 0.002 Mask loss: 0.10916 RPN box loss: 0.01501 RPN score loss: 0.00294 RPN total loss: 0.01795 Total loss: 0.92449 timestamp: 1654946908.9473886 iteration: 40860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09735 FastRCNN class loss: 0.1272 FastRCNN total loss: 0.22455 L1 loss: 0.0000e+00 L2 loss: 0.62833 Learning rate: 0.002 Mask loss: 0.14627 RPN box loss: 0.02627 RPN score loss: 0.00646 RPN total loss: 0.03272 Total loss: 1.03188 timestamp: 1654946912.12645 iteration: 40865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11951 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.18921 L1 loss: 0.0000e+00 L2 loss: 0.62832 Learning rate: 0.002 Mask loss: 0.16058 RPN box loss: 0.01575 RPN score loss: 0.00508 RPN total loss: 0.02084 Total loss: 0.99894 timestamp: 1654946915.3834512 iteration: 40870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12436 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.21753 L1 loss: 0.0000e+00 L2 loss: 0.62831 Learning rate: 0.002 Mask loss: 0.1638 RPN box loss: 0.05421 RPN score loss: 0.00893 RPN total loss: 0.06315 Total loss: 1.07278 timestamp: 1654946918.5635383 iteration: 40875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15782 FastRCNN class loss: 0.10017 FastRCNN total loss: 0.25799 L1 loss: 0.0000e+00 L2 loss: 0.6283 Learning rate: 0.002 Mask loss: 0.15526 RPN box loss: 0.02516 RPN score loss: 0.00893 RPN total loss: 0.03409 Total loss: 1.07564 timestamp: 1654946921.77749 iteration: 40880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14656 FastRCNN class loss: 0.12288 FastRCNN total loss: 0.26944 L1 loss: 0.0000e+00 L2 loss: 0.62829 Learning rate: 0.002 Mask loss: 0.23935 RPN box loss: 0.03205 RPN score loss: 0.01045 RPN total loss: 0.0425 Total loss: 1.17957 timestamp: 1654946924.8828132 iteration: 40885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.2148 L1 loss: 0.0000e+00 L2 loss: 0.62828 Learning rate: 0.002 Mask loss: 0.12568 RPN box loss: 0.01451 RPN score loss: 0.01024 RPN total loss: 0.02475 Total loss: 0.99351 timestamp: 1654946928.144563 iteration: 40890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13361 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.2021 L1 loss: 0.0000e+00 L2 loss: 0.62827 Learning rate: 0.002 Mask loss: 0.20326 RPN box loss: 0.03077 RPN score loss: 0.00936 RPN total loss: 0.04012 Total loss: 1.07376 timestamp: 1654946931.3256857 iteration: 40895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06817 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.12102 L1 loss: 0.0000e+00 L2 loss: 0.62826 Learning rate: 0.002 Mask loss: 0.09307 RPN box loss: 0.01968 RPN score loss: 0.00408 RPN total loss: 0.02375 Total loss: 0.86611 timestamp: 1654946934.5751562 iteration: 40900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07829 FastRCNN class loss: 0.07123 FastRCNN total loss: 0.14952 L1 loss: 0.0000e+00 L2 loss: 0.62825 Learning rate: 0.002 Mask loss: 0.18996 RPN box loss: 0.02424 RPN score loss: 0.02013 RPN total loss: 0.04437 Total loss: 1.0121 timestamp: 1654946937.7546961 iteration: 40905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07966 FastRCNN class loss: 0.04489 FastRCNN total loss: 0.12455 L1 loss: 0.0000e+00 L2 loss: 0.62824 Learning rate: 0.002 Mask loss: 0.08603 RPN box loss: 0.02055 RPN score loss: 0.004 RPN total loss: 0.02455 Total loss: 0.86337 timestamp: 1654946940.8965409 iteration: 40910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12776 FastRCNN class loss: 0.07106 FastRCNN total loss: 0.19882 L1 loss: 0.0000e+00 L2 loss: 0.62824 Learning rate: 0.002 Mask loss: 0.16958 RPN box loss: 0.0323 RPN score loss: 0.01261 RPN total loss: 0.04491 Total loss: 1.04155 timestamp: 1654946944.2073994 iteration: 40915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09583 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.17359 L1 loss: 0.0000e+00 L2 loss: 0.62822 Learning rate: 0.002 Mask loss: 0.08611 RPN box loss: 0.02103 RPN score loss: 0.01287 RPN total loss: 0.0339 Total loss: 0.92182 timestamp: 1654946947.417504 iteration: 40920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05215 FastRCNN class loss: 0.04151 FastRCNN total loss: 0.09366 L1 loss: 0.0000e+00 L2 loss: 0.62821 Learning rate: 0.002 Mask loss: 0.08095 RPN box loss: 0.01726 RPN score loss: 0.00715 RPN total loss: 0.02442 Total loss: 0.82724 timestamp: 1654946950.6257102 iteration: 40925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05303 FastRCNN class loss: 0.04735 FastRCNN total loss: 0.10038 L1 loss: 0.0000e+00 L2 loss: 0.6282 Learning rate: 0.002 Mask loss: 0.12328 RPN box loss: 0.00757 RPN score loss: 0.00124 RPN total loss: 0.00881 Total loss: 0.86067 timestamp: 1654946953.801844 iteration: 40930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0679 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.12949 L1 loss: 0.0000e+00 L2 loss: 0.62819 Learning rate: 0.002 Mask loss: 0.11397 RPN box loss: 0.01745 RPN score loss: 0.00221 RPN total loss: 0.01966 Total loss: 0.89132 timestamp: 1654946956.9625144 iteration: 40935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15536 FastRCNN class loss: 0.09994 FastRCNN total loss: 0.2553 L1 loss: 0.0000e+00 L2 loss: 0.62819 Learning rate: 0.002 Mask loss: 0.15596 RPN box loss: 0.02432 RPN score loss: 0.01321 RPN total loss: 0.03753 Total loss: 1.07698 timestamp: 1654946960.1193104 iteration: 40940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09169 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.15477 L1 loss: 0.0000e+00 L2 loss: 0.62818 Learning rate: 0.002 Mask loss: 0.10353 RPN box loss: 0.01311 RPN score loss: 0.00329 RPN total loss: 0.0164 Total loss: 0.90288 timestamp: 1654946963.3798752 iteration: 40945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08699 FastRCNN class loss: 0.0484 FastRCNN total loss: 0.13539 L1 loss: 0.0000e+00 L2 loss: 0.62817 Learning rate: 0.002 Mask loss: 0.12863 RPN box loss: 0.01147 RPN score loss: 0.0085 RPN total loss: 0.01998 Total loss: 0.91217 timestamp: 1654946966.5980718 iteration: 40950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15945 FastRCNN class loss: 0.14418 FastRCNN total loss: 0.30364 L1 loss: 0.0000e+00 L2 loss: 0.62816 Learning rate: 0.002 Mask loss: 0.20651 RPN box loss: 0.02413 RPN score loss: 0.00532 RPN total loss: 0.02946 Total loss: 1.16776 timestamp: 1654946969.8141568 iteration: 40955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10078 FastRCNN class loss: 0.07955 FastRCNN total loss: 0.18032 L1 loss: 0.0000e+00 L2 loss: 0.62815 Learning rate: 0.002 Mask loss: 0.08523 RPN box loss: 0.02685 RPN score loss: 0.0098 RPN total loss: 0.03665 Total loss: 0.93036 timestamp: 1654946973.0499327 iteration: 40960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12993 FastRCNN class loss: 0.09178 FastRCNN total loss: 0.22172 L1 loss: 0.0000e+00 L2 loss: 0.62814 Learning rate: 0.002 Mask loss: 0.14262 RPN box loss: 0.02338 RPN score loss: 0.00945 RPN total loss: 0.03283 Total loss: 1.0253 timestamp: 1654946976.2431347 iteration: 40965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11963 FastRCNN class loss: 0.06289 FastRCNN total loss: 0.18252 L1 loss: 0.0000e+00 L2 loss: 0.62813 Learning rate: 0.002 Mask loss: 0.1601 RPN box loss: 0.02327 RPN score loss: 0.00596 RPN total loss: 0.02923 Total loss: 0.99998 timestamp: 1654946979.4443579 iteration: 40970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10226 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.17401 L1 loss: 0.0000e+00 L2 loss: 0.62812 Learning rate: 0.002 Mask loss: 0.13709 RPN box loss: 0.03831 RPN score loss: 0.00691 RPN total loss: 0.04521 Total loss: 0.98443 timestamp: 1654946982.6386783 iteration: 40975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13118 FastRCNN class loss: 0.07984 FastRCNN total loss: 0.21102 L1 loss: 0.0000e+00 L2 loss: 0.62811 Learning rate: 0.002 Mask loss: 0.11345 RPN box loss: 0.02193 RPN score loss: 0.00319 RPN total loss: 0.02512 Total loss: 0.9777 timestamp: 1654946985.941415 iteration: 40980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08804 FastRCNN class loss: 0.07034 FastRCNN total loss: 0.15838 L1 loss: 0.0000e+00 L2 loss: 0.6281 Learning rate: 0.002 Mask loss: 0.1174 RPN box loss: 0.01369 RPN score loss: 0.00236 RPN total loss: 0.01605 Total loss: 0.91993 timestamp: 1654946989.1629431 iteration: 40985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03181 FastRCNN class loss: 0.04115 FastRCNN total loss: 0.07295 L1 loss: 0.0000e+00 L2 loss: 0.62809 Learning rate: 0.002 Mask loss: 0.17103 RPN box loss: 0.00515 RPN score loss: 0.00448 RPN total loss: 0.00963 Total loss: 0.8817 timestamp: 1654946992.3912702 iteration: 40990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12784 FastRCNN class loss: 0.09422 FastRCNN total loss: 0.22206 L1 loss: 0.0000e+00 L2 loss: 0.62808 Learning rate: 0.002 Mask loss: 0.11972 RPN box loss: 0.01104 RPN score loss: 0.00688 RPN total loss: 0.01792 Total loss: 0.98778 timestamp: 1654946995.5311732 iteration: 40995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11855 FastRCNN class loss: 0.08068 FastRCNN total loss: 0.19923 L1 loss: 0.0000e+00 L2 loss: 0.62807 Learning rate: 0.002 Mask loss: 0.13348 RPN box loss: 0.04923 RPN score loss: 0.00873 RPN total loss: 0.05796 Total loss: 1.01875 timestamp: 1654946998.6345387 iteration: 41000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15485 FastRCNN class loss: 0.07256 FastRCNN total loss: 0.22741 L1 loss: 0.0000e+00 L2 loss: 0.62806 Learning rate: 0.002 Mask loss: 0.10982 RPN box loss: 0.03164 RPN score loss: 0.00308 RPN total loss: 0.03472 Total loss: 1.00001 timestamp: 1654947001.7521958 iteration: 41005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09424 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.14722 L1 loss: 0.0000e+00 L2 loss: 0.62805 Learning rate: 0.002 Mask loss: 0.13512 RPN box loss: 0.03902 RPN score loss: 0.00406 RPN total loss: 0.04307 Total loss: 0.95346 timestamp: 1654947004.9469674 iteration: 41010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12871 FastRCNN class loss: 0.07992 FastRCNN total loss: 0.20863 L1 loss: 0.0000e+00 L2 loss: 0.62805 Learning rate: 0.002 Mask loss: 0.1387 RPN box loss: 0.04993 RPN score loss: 0.00447 RPN total loss: 0.0544 Total loss: 1.02978 timestamp: 1654947008.1249313 iteration: 41015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05162 FastRCNN class loss: 0.03833 FastRCNN total loss: 0.08995 L1 loss: 0.0000e+00 L2 loss: 0.62804 Learning rate: 0.002 Mask loss: 0.11208 RPN box loss: 0.00269 RPN score loss: 0.0018 RPN total loss: 0.00449 Total loss: 0.83456 timestamp: 1654947011.2890737 iteration: 41020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15042 FastRCNN class loss: 0.10762 FastRCNN total loss: 0.25804 L1 loss: 0.0000e+00 L2 loss: 0.62803 Learning rate: 0.002 Mask loss: 0.2114 RPN box loss: 0.0227 RPN score loss: 0.01005 RPN total loss: 0.03276 Total loss: 1.13022 timestamp: 1654947014.5426729 iteration: 41025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10461 FastRCNN class loss: 0.08272 FastRCNN total loss: 0.18733 L1 loss: 0.0000e+00 L2 loss: 0.62801 Learning rate: 0.002 Mask loss: 0.09279 RPN box loss: 0.01001 RPN score loss: 0.00596 RPN total loss: 0.01597 Total loss: 0.92411 timestamp: 1654947017.772696 iteration: 41030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06831 FastRCNN class loss: 0.08184 FastRCNN total loss: 0.15015 L1 loss: 0.0000e+00 L2 loss: 0.628 Learning rate: 0.002 Mask loss: 0.13927 RPN box loss: 0.06426 RPN score loss: 0.01042 RPN total loss: 0.07468 Total loss: 0.9921 timestamp: 1654947020.9679728 iteration: 41035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10212 FastRCNN class loss: 0.09102 FastRCNN total loss: 0.19314 L1 loss: 0.0000e+00 L2 loss: 0.62799 Learning rate: 0.002 Mask loss: 0.14153 RPN box loss: 0.02158 RPN score loss: 0.00651 RPN total loss: 0.02809 Total loss: 0.99075 timestamp: 1654947024.1717045 iteration: 41040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19111 FastRCNN class loss: 0.1108 FastRCNN total loss: 0.30192 L1 loss: 0.0000e+00 L2 loss: 0.62798 Learning rate: 0.002 Mask loss: 0.17445 RPN box loss: 0.02763 RPN score loss: 0.00927 RPN total loss: 0.0369 Total loss: 1.14125 timestamp: 1654947027.4102888 iteration: 41045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11014 FastRCNN class loss: 0.05327 FastRCNN total loss: 0.16341 L1 loss: 0.0000e+00 L2 loss: 0.62797 Learning rate: 0.002 Mask loss: 0.11718 RPN box loss: 0.02382 RPN score loss: 0.00486 RPN total loss: 0.02868 Total loss: 0.93724 timestamp: 1654947030.641054 iteration: 41050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0743 FastRCNN class loss: 0.06729 FastRCNN total loss: 0.14159 L1 loss: 0.0000e+00 L2 loss: 0.62796 Learning rate: 0.002 Mask loss: 0.16561 RPN box loss: 0.02544 RPN score loss: 0.00752 RPN total loss: 0.03295 Total loss: 0.96811 timestamp: 1654947033.7989106 iteration: 41055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07087 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.12827 L1 loss: 0.0000e+00 L2 loss: 0.62795 Learning rate: 0.002 Mask loss: 0.10106 RPN box loss: 0.00435 RPN score loss: 0.00403 RPN total loss: 0.00839 Total loss: 0.86566 timestamp: 1654947036.9854753 iteration: 41060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11348 FastRCNN class loss: 0.08944 FastRCNN total loss: 0.20292 L1 loss: 0.0000e+00 L2 loss: 0.62794 Learning rate: 0.002 Mask loss: 0.12037 RPN box loss: 0.03173 RPN score loss: 0.0035 RPN total loss: 0.03523 Total loss: 0.98646 timestamp: 1654947040.146789 iteration: 41065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13517 FastRCNN class loss: 0.08288 FastRCNN total loss: 0.21805 L1 loss: 0.0000e+00 L2 loss: 0.62793 Learning rate: 0.002 Mask loss: 0.13114 RPN box loss: 0.02212 RPN score loss: 0.00478 RPN total loss: 0.0269 Total loss: 1.00402 timestamp: 1654947043.4179056 iteration: 41070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09301 FastRCNN class loss: 0.09009 FastRCNN total loss: 0.1831 L1 loss: 0.0000e+00 L2 loss: 0.62792 Learning rate: 0.002 Mask loss: 0.1539 RPN box loss: 0.03001 RPN score loss: 0.00753 RPN total loss: 0.03754 Total loss: 1.00247 timestamp: 1654947046.6761072 iteration: 41075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10299 FastRCNN class loss: 0.05113 FastRCNN total loss: 0.15412 L1 loss: 0.0000e+00 L2 loss: 0.62791 Learning rate: 0.002 Mask loss: 0.12819 RPN box loss: 0.01426 RPN score loss: 0.00086 RPN total loss: 0.01512 Total loss: 0.92534 timestamp: 1654947049.891077 iteration: 41080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07384 FastRCNN class loss: 0.04411 FastRCNN total loss: 0.11795 L1 loss: 0.0000e+00 L2 loss: 0.6279 Learning rate: 0.002 Mask loss: 0.11453 RPN box loss: 0.00808 RPN score loss: 0.00404 RPN total loss: 0.01213 Total loss: 0.87251 timestamp: 1654947053.1142306 iteration: 41085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12641 FastRCNN class loss: 0.10417 FastRCNN total loss: 0.23057 L1 loss: 0.0000e+00 L2 loss: 0.6279 Learning rate: 0.002 Mask loss: 0.16851 RPN box loss: 0.00809 RPN score loss: 0.00424 RPN total loss: 0.01233 Total loss: 1.03931 timestamp: 1654947056.320605 iteration: 41090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15391 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.23125 L1 loss: 0.0000e+00 L2 loss: 0.62789 Learning rate: 0.002 Mask loss: 0.19491 RPN box loss: 0.01106 RPN score loss: 0.00293 RPN total loss: 0.01399 Total loss: 1.06804 timestamp: 1654947059.574357 iteration: 41095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10503 FastRCNN class loss: 0.08525 FastRCNN total loss: 0.19029 L1 loss: 0.0000e+00 L2 loss: 0.62788 Learning rate: 0.002 Mask loss: 0.15566 RPN box loss: 0.02827 RPN score loss: 0.00453 RPN total loss: 0.0328 Total loss: 1.00663 timestamp: 1654947062.7765207 iteration: 41100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09646 FastRCNN class loss: 0.05828 FastRCNN total loss: 0.15475 L1 loss: 0.0000e+00 L2 loss: 0.62787 Learning rate: 0.002 Mask loss: 0.16654 RPN box loss: 0.05385 RPN score loss: 0.00737 RPN total loss: 0.06121 Total loss: 1.01038 timestamp: 1654947065.9654295 iteration: 41105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.12776 L1 loss: 0.0000e+00 L2 loss: 0.62786 Learning rate: 0.002 Mask loss: 0.15191 RPN box loss: 0.02739 RPN score loss: 0.00401 RPN total loss: 0.03139 Total loss: 0.93893 timestamp: 1654947069.1600802 iteration: 41110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14848 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.21742 L1 loss: 0.0000e+00 L2 loss: 0.62785 Learning rate: 0.002 Mask loss: 0.16933 RPN box loss: 0.01349 RPN score loss: 0.00856 RPN total loss: 0.02205 Total loss: 1.03665 timestamp: 1654947072.3373325 iteration: 41115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12675 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.21292 L1 loss: 0.0000e+00 L2 loss: 0.62784 Learning rate: 0.002 Mask loss: 0.12603 RPN box loss: 0.01842 RPN score loss: 0.00315 RPN total loss: 0.02157 Total loss: 0.98835 timestamp: 1654947075.4976826 iteration: 41120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10321 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.17754 L1 loss: 0.0000e+00 L2 loss: 0.62783 Learning rate: 0.002 Mask loss: 0.106 RPN box loss: 0.02181 RPN score loss: 0.00366 RPN total loss: 0.02547 Total loss: 0.93683 timestamp: 1654947078.7511716 iteration: 41125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.17843 L1 loss: 0.0000e+00 L2 loss: 0.62782 Learning rate: 0.002 Mask loss: 0.1344 RPN box loss: 0.06299 RPN score loss: 0.00533 RPN total loss: 0.06832 Total loss: 1.00897 timestamp: 1654947081.9635065 iteration: 41130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11135 FastRCNN class loss: 0.0306 FastRCNN total loss: 0.14195 L1 loss: 0.0000e+00 L2 loss: 0.62781 Learning rate: 0.002 Mask loss: 0.08261 RPN box loss: 0.0049 RPN score loss: 0.00184 RPN total loss: 0.00674 Total loss: 0.85911 timestamp: 1654947085.257695 iteration: 41135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0876 FastRCNN class loss: 0.0597 FastRCNN total loss: 0.1473 L1 loss: 0.0000e+00 L2 loss: 0.6278 Learning rate: 0.002 Mask loss: 0.12083 RPN box loss: 0.02343 RPN score loss: 0.00477 RPN total loss: 0.0282 Total loss: 0.92413 timestamp: 1654947088.4570696 iteration: 41140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09112 FastRCNN class loss: 0.04584 FastRCNN total loss: 0.13695 L1 loss: 0.0000e+00 L2 loss: 0.62779 Learning rate: 0.002 Mask loss: 0.09523 RPN box loss: 0.00963 RPN score loss: 0.00276 RPN total loss: 0.01239 Total loss: 0.87236 timestamp: 1654947091.7001963 iteration: 41145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09288 FastRCNN class loss: 0.06534 FastRCNN total loss: 0.15822 L1 loss: 0.0000e+00 L2 loss: 0.62778 Learning rate: 0.002 Mask loss: 0.0985 RPN box loss: 0.01335 RPN score loss: 0.00225 RPN total loss: 0.0156 Total loss: 0.9001 timestamp: 1654947094.9214945 iteration: 41150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11998 FastRCNN class loss: 0.1151 FastRCNN total loss: 0.23508 L1 loss: 0.0000e+00 L2 loss: 0.62777 Learning rate: 0.002 Mask loss: 0.16349 RPN box loss: 0.02721 RPN score loss: 0.00369 RPN total loss: 0.03091 Total loss: 1.05724 timestamp: 1654947098.0869377 iteration: 41155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11604 FastRCNN class loss: 0.05037 FastRCNN total loss: 0.16641 L1 loss: 0.0000e+00 L2 loss: 0.62776 Learning rate: 0.002 Mask loss: 0.13192 RPN box loss: 0.01028 RPN score loss: 0.00288 RPN total loss: 0.01316 Total loss: 0.93925 timestamp: 1654947101.3030105 iteration: 41160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09728 FastRCNN class loss: 0.05347 FastRCNN total loss: 0.15075 L1 loss: 0.0000e+00 L2 loss: 0.62775 Learning rate: 0.002 Mask loss: 0.10226 RPN box loss: 0.01491 RPN score loss: 0.00446 RPN total loss: 0.01937 Total loss: 0.90014 timestamp: 1654947104.5430717 iteration: 41165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12212 FastRCNN class loss: 0.06053 FastRCNN total loss: 0.18265 L1 loss: 0.0000e+00 L2 loss: 0.62774 Learning rate: 0.002 Mask loss: 0.13736 RPN box loss: 0.00967 RPN score loss: 0.00287 RPN total loss: 0.01254 Total loss: 0.96029 timestamp: 1654947107.6913705 iteration: 41170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07385 FastRCNN class loss: 0.06967 FastRCNN total loss: 0.14352 L1 loss: 0.0000e+00 L2 loss: 0.62774 Learning rate: 0.002 Mask loss: 0.11698 RPN box loss: 0.0228 RPN score loss: 0.00474 RPN total loss: 0.02755 Total loss: 0.91579 timestamp: 1654947110.8791792 iteration: 41175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17005 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.23693 L1 loss: 0.0000e+00 L2 loss: 0.62773 Learning rate: 0.002 Mask loss: 0.14655 RPN box loss: 0.02339 RPN score loss: 0.00588 RPN total loss: 0.02927 Total loss: 1.04048 timestamp: 1654947114.0896473 iteration: 41180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10784 FastRCNN class loss: 0.10168 FastRCNN total loss: 0.20952 L1 loss: 0.0000e+00 L2 loss: 0.62772 Learning rate: 0.002 Mask loss: 0.15219 RPN box loss: 0.04158 RPN score loss: 0.00966 RPN total loss: 0.05124 Total loss: 1.04067 timestamp: 1654947117.341962 iteration: 41185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11019 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.19723 L1 loss: 0.0000e+00 L2 loss: 0.62771 Learning rate: 0.002 Mask loss: 0.17276 RPN box loss: 0.01007 RPN score loss: 0.00433 RPN total loss: 0.0144 Total loss: 1.0121 timestamp: 1654947120.4739072 iteration: 41190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10787 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.18289 L1 loss: 0.0000e+00 L2 loss: 0.6277 Learning rate: 0.002 Mask loss: 0.09569 RPN box loss: 0.01568 RPN score loss: 0.00676 RPN total loss: 0.02244 Total loss: 0.92871 timestamp: 1654947123.6477373 iteration: 41195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10889 FastRCNN class loss: 0.05247 FastRCNN total loss: 0.16136 L1 loss: 0.0000e+00 L2 loss: 0.62769 Learning rate: 0.002 Mask loss: 0.12757 RPN box loss: 0.018 RPN score loss: 0.00371 RPN total loss: 0.02171 Total loss: 0.93833 timestamp: 1654947126.8304002 iteration: 41200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08306 FastRCNN class loss: 0.05086 FastRCNN total loss: 0.13392 L1 loss: 0.0000e+00 L2 loss: 0.62768 Learning rate: 0.002 Mask loss: 0.10003 RPN box loss: 0.00981 RPN score loss: 0.00282 RPN total loss: 0.01263 Total loss: 0.87427 timestamp: 1654947129.9939814 iteration: 41205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.08363 FastRCNN total loss: 0.18358 L1 loss: 0.0000e+00 L2 loss: 0.62767 Learning rate: 0.002 Mask loss: 0.18646 RPN box loss: 0.01471 RPN score loss: 0.00982 RPN total loss: 0.02453 Total loss: 1.02224 timestamp: 1654947133.138661 iteration: 41210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06613 FastRCNN class loss: 0.03465 FastRCNN total loss: 0.10078 L1 loss: 0.0000e+00 L2 loss: 0.62766 Learning rate: 0.002 Mask loss: 0.0916 RPN box loss: 0.01313 RPN score loss: 0.00421 RPN total loss: 0.01734 Total loss: 0.83738 timestamp: 1654947136.353952 iteration: 41215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07309 FastRCNN class loss: 0.0652 FastRCNN total loss: 0.13829 L1 loss: 0.0000e+00 L2 loss: 0.62765 Learning rate: 0.002 Mask loss: 0.13492 RPN box loss: 0.03062 RPN score loss: 0.00317 RPN total loss: 0.03379 Total loss: 0.93465 timestamp: 1654947139.5540774 iteration: 41220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.17619 L1 loss: 0.0000e+00 L2 loss: 0.62764 Learning rate: 0.002 Mask loss: 0.18428 RPN box loss: 0.02418 RPN score loss: 0.00689 RPN total loss: 0.03107 Total loss: 1.01917 timestamp: 1654947142.7830803 iteration: 41225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08452 FastRCNN class loss: 0.05795 FastRCNN total loss: 0.14247 L1 loss: 0.0000e+00 L2 loss: 0.62763 Learning rate: 0.002 Mask loss: 0.119 RPN box loss: 0.0185 RPN score loss: 0.00261 RPN total loss: 0.02111 Total loss: 0.9102 timestamp: 1654947145.9527895 iteration: 41230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10838 FastRCNN class loss: 0.05891 FastRCNN total loss: 0.16728 L1 loss: 0.0000e+00 L2 loss: 0.62762 Learning rate: 0.002 Mask loss: 0.13315 RPN box loss: 0.02303 RPN score loss: 0.003 RPN total loss: 0.02602 Total loss: 0.95408 timestamp: 1654947149.1689768 iteration: 41235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11782 FastRCNN class loss: 0.09526 FastRCNN total loss: 0.21308 L1 loss: 0.0000e+00 L2 loss: 0.62761 Learning rate: 0.002 Mask loss: 0.19114 RPN box loss: 0.01781 RPN score loss: 0.00431 RPN total loss: 0.02212 Total loss: 1.05394 timestamp: 1654947152.321884 iteration: 41240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12998 FastRCNN class loss: 0.08749 FastRCNN total loss: 0.21748 L1 loss: 0.0000e+00 L2 loss: 0.6276 Learning rate: 0.002 Mask loss: 0.21212 RPN box loss: 0.02086 RPN score loss: 0.00598 RPN total loss: 0.02683 Total loss: 1.08403 timestamp: 1654947155.4922643 iteration: 41245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12737 FastRCNN class loss: 0.08384 FastRCNN total loss: 0.21121 L1 loss: 0.0000e+00 L2 loss: 0.62759 Learning rate: 0.002 Mask loss: 0.12059 RPN box loss: 0.02093 RPN score loss: 0.00535 RPN total loss: 0.02629 Total loss: 0.98568 timestamp: 1654947158.7748802 iteration: 41250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0825 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.13715 L1 loss: 0.0000e+00 L2 loss: 0.62758 Learning rate: 0.002 Mask loss: 0.10638 RPN box loss: 0.02175 RPN score loss: 0.00363 RPN total loss: 0.02538 Total loss: 0.89649 timestamp: 1654947162.0090065 iteration: 41255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12319 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.19574 L1 loss: 0.0000e+00 L2 loss: 0.62757 Learning rate: 0.002 Mask loss: 0.13669 RPN box loss: 0.03697 RPN score loss: 0.01315 RPN total loss: 0.05012 Total loss: 1.01011 timestamp: 1654947165.2270968 iteration: 41260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14646 FastRCNN class loss: 0.09059 FastRCNN total loss: 0.23705 L1 loss: 0.0000e+00 L2 loss: 0.62756 Learning rate: 0.002 Mask loss: 0.14484 RPN box loss: 0.01022 RPN score loss: 0.00191 RPN total loss: 0.01213 Total loss: 1.02157 timestamp: 1654947168.439334 iteration: 41265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12281 FastRCNN class loss: 0.08555 FastRCNN total loss: 0.20836 L1 loss: 0.0000e+00 L2 loss: 0.62755 Learning rate: 0.002 Mask loss: 0.13362 RPN box loss: 0.02064 RPN score loss: 0.00414 RPN total loss: 0.02478 Total loss: 0.99431 timestamp: 1654947171.6179595 iteration: 41270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0559 FastRCNN class loss: 0.04094 FastRCNN total loss: 0.09684 L1 loss: 0.0000e+00 L2 loss: 0.62753 Learning rate: 0.002 Mask loss: 0.07975 RPN box loss: 0.00469 RPN score loss: 0.00198 RPN total loss: 0.00667 Total loss: 0.81079 timestamp: 1654947174.7397678 iteration: 41275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14074 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.22338 L1 loss: 0.0000e+00 L2 loss: 0.62752 Learning rate: 0.002 Mask loss: 0.10582 RPN box loss: 0.01101 RPN score loss: 0.00373 RPN total loss: 0.01473 Total loss: 0.97146 timestamp: 1654947177.9704025 iteration: 41280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1342 FastRCNN class loss: 0.0763 FastRCNN total loss: 0.21051 L1 loss: 0.0000e+00 L2 loss: 0.62751 Learning rate: 0.002 Mask loss: 0.16411 RPN box loss: 0.03555 RPN score loss: 0.00083 RPN total loss: 0.03638 Total loss: 1.03851 timestamp: 1654947181.2746174 iteration: 41285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08441 FastRCNN class loss: 0.04816 FastRCNN total loss: 0.13257 L1 loss: 0.0000e+00 L2 loss: 0.62751 Learning rate: 0.002 Mask loss: 0.14617 RPN box loss: 0.00932 RPN score loss: 0.00447 RPN total loss: 0.01378 Total loss: 0.92003 timestamp: 1654947184.47968 iteration: 41290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08626 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.14366 L1 loss: 0.0000e+00 L2 loss: 0.6275 Learning rate: 0.002 Mask loss: 0.12664 RPN box loss: 0.0091 RPN score loss: 0.00304 RPN total loss: 0.01214 Total loss: 0.90994 timestamp: 1654947187.6641846 iteration: 41295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.126 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.21688 L1 loss: 0.0000e+00 L2 loss: 0.62749 Learning rate: 0.002 Mask loss: 0.1114 RPN box loss: 0.01585 RPN score loss: 0.00526 RPN total loss: 0.02111 Total loss: 0.97688 timestamp: 1654947190.8750958 iteration: 41300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15466 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.22555 L1 loss: 0.0000e+00 L2 loss: 0.62748 Learning rate: 0.002 Mask loss: 0.09808 RPN box loss: 0.01096 RPN score loss: 0.00431 RPN total loss: 0.01526 Total loss: 0.96637 timestamp: 1654947194.0199642 iteration: 41305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09167 FastRCNN class loss: 0.04463 FastRCNN total loss: 0.1363 L1 loss: 0.0000e+00 L2 loss: 0.62747 Learning rate: 0.002 Mask loss: 0.09571 RPN box loss: 0.01065 RPN score loss: 0.00378 RPN total loss: 0.01442 Total loss: 0.87391 timestamp: 1654947197.2808502 iteration: 41310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10165 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.17168 L1 loss: 0.0000e+00 L2 loss: 0.62746 Learning rate: 0.002 Mask loss: 0.12098 RPN box loss: 0.01727 RPN score loss: 0.00793 RPN total loss: 0.0252 Total loss: 0.94533 timestamp: 1654947200.431939 iteration: 41315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17097 FastRCNN class loss: 0.0818 FastRCNN total loss: 0.25277 L1 loss: 0.0000e+00 L2 loss: 0.62746 Learning rate: 0.002 Mask loss: 0.15988 RPN box loss: 0.06803 RPN score loss: 0.0067 RPN total loss: 0.07473 Total loss: 1.11483 timestamp: 1654947203.6154494 iteration: 41320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06906 FastRCNN class loss: 0.04831 FastRCNN total loss: 0.11737 L1 loss: 0.0000e+00 L2 loss: 0.62745 Learning rate: 0.002 Mask loss: 0.09081 RPN box loss: 0.01388 RPN score loss: 0.00166 RPN total loss: 0.01555 Total loss: 0.85117 timestamp: 1654947206.8307788 iteration: 41325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1273 FastRCNN class loss: 0.12279 FastRCNN total loss: 0.25009 L1 loss: 0.0000e+00 L2 loss: 0.62743 Learning rate: 0.002 Mask loss: 0.19194 RPN box loss: 0.03326 RPN score loss: 0.00659 RPN total loss: 0.03985 Total loss: 1.10931 timestamp: 1654947210.0623918 iteration: 41330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17724 FastRCNN class loss: 0.16355 FastRCNN total loss: 0.34079 L1 loss: 0.0000e+00 L2 loss: 0.62742 Learning rate: 0.002 Mask loss: 0.17791 RPN box loss: 0.01192 RPN score loss: 0.00192 RPN total loss: 0.01384 Total loss: 1.15997 timestamp: 1654947213.2706885 iteration: 41335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06535 FastRCNN class loss: 0.04902 FastRCNN total loss: 0.11436 L1 loss: 0.0000e+00 L2 loss: 0.62742 Learning rate: 0.002 Mask loss: 0.09772 RPN box loss: 0.00749 RPN score loss: 0.00125 RPN total loss: 0.00875 Total loss: 0.84825 timestamp: 1654947216.3845062 iteration: 41340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05909 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.13424 L1 loss: 0.0000e+00 L2 loss: 0.62741 Learning rate: 0.002 Mask loss: 0.0923 RPN box loss: 0.01379 RPN score loss: 0.00749 RPN total loss: 0.02128 Total loss: 0.87523 timestamp: 1654947219.5603845 iteration: 41345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1461 FastRCNN class loss: 0.09439 FastRCNN total loss: 0.24049 L1 loss: 0.0000e+00 L2 loss: 0.6274 Learning rate: 0.002 Mask loss: 0.22592 RPN box loss: 0.02379 RPN score loss: 0.007 RPN total loss: 0.0308 Total loss: 1.1246 timestamp: 1654947222.725113 iteration: 41350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07867 FastRCNN class loss: 0.05132 FastRCNN total loss: 0.13 L1 loss: 0.0000e+00 L2 loss: 0.62739 Learning rate: 0.002 Mask loss: 0.09625 RPN box loss: 0.01544 RPN score loss: 0.00116 RPN total loss: 0.0166 Total loss: 0.87023 timestamp: 1654947225.8967476 iteration: 41355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16876 FastRCNN class loss: 0.06226 FastRCNN total loss: 0.23102 L1 loss: 0.0000e+00 L2 loss: 0.62738 Learning rate: 0.002 Mask loss: 0.11727 RPN box loss: 0.02395 RPN score loss: 0.00667 RPN total loss: 0.03062 Total loss: 1.00628 timestamp: 1654947229.036853 iteration: 41360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.18866 L1 loss: 0.0000e+00 L2 loss: 0.62737 Learning rate: 0.002 Mask loss: 0.10445 RPN box loss: 0.0121 RPN score loss: 0.0014 RPN total loss: 0.0135 Total loss: 0.93399 timestamp: 1654947232.2291434 iteration: 41365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0802 FastRCNN class loss: 0.02598 FastRCNN total loss: 0.10618 L1 loss: 0.0000e+00 L2 loss: 0.62736 Learning rate: 0.002 Mask loss: 0.08572 RPN box loss: 0.01482 RPN score loss: 0.00202 RPN total loss: 0.01683 Total loss: 0.83609 timestamp: 1654947235.392511 iteration: 41370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10387 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.18556 L1 loss: 0.0000e+00 L2 loss: 0.62735 Learning rate: 0.002 Mask loss: 0.13878 RPN box loss: 0.0112 RPN score loss: 0.00224 RPN total loss: 0.01344 Total loss: 0.96514 timestamp: 1654947238.5477738 iteration: 41375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09627 FastRCNN class loss: 0.0714 FastRCNN total loss: 0.16766 L1 loss: 0.0000e+00 L2 loss: 0.62734 Learning rate: 0.002 Mask loss: 0.13178 RPN box loss: 0.03256 RPN score loss: 0.00671 RPN total loss: 0.03926 Total loss: 0.96604 timestamp: 1654947241.6997397 iteration: 41380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.15537 L1 loss: 0.0000e+00 L2 loss: 0.62733 Learning rate: 0.002 Mask loss: 0.1185 RPN box loss: 0.02708 RPN score loss: 0.01261 RPN total loss: 0.03969 Total loss: 0.9409 timestamp: 1654947245.0717435 iteration: 41385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12923 FastRCNN class loss: 0.05288 FastRCNN total loss: 0.18211 L1 loss: 0.0000e+00 L2 loss: 0.62731 Learning rate: 0.002 Mask loss: 0.10184 RPN box loss: 0.00921 RPN score loss: 0.00214 RPN total loss: 0.01134 Total loss: 0.92261 timestamp: 1654947248.2732024 iteration: 41390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06869 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.1278 L1 loss: 0.0000e+00 L2 loss: 0.6273 Learning rate: 0.002 Mask loss: 0.11403 RPN box loss: 0.00991 RPN score loss: 0.00204 RPN total loss: 0.01194 Total loss: 0.88108 timestamp: 1654947251.4671679 iteration: 41395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06426 FastRCNN class loss: 0.06715 FastRCNN total loss: 0.13141 L1 loss: 0.0000e+00 L2 loss: 0.62729 Learning rate: 0.002 Mask loss: 0.11002 RPN box loss: 0.0059 RPN score loss: 0.00721 RPN total loss: 0.01311 Total loss: 0.88182 timestamp: 1654947254.5856044 iteration: 41400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10426 FastRCNN class loss: 0.05606 FastRCNN total loss: 0.16032 L1 loss: 0.0000e+00 L2 loss: 0.62728 Learning rate: 0.002 Mask loss: 0.1301 RPN box loss: 0.02471 RPN score loss: 0.0039 RPN total loss: 0.0286 Total loss: 0.9463 timestamp: 1654947257.735723 iteration: 41405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10825 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.18248 L1 loss: 0.0000e+00 L2 loss: 0.62728 Learning rate: 0.002 Mask loss: 0.17373 RPN box loss: 0.05419 RPN score loss: 0.0095 RPN total loss: 0.06368 Total loss: 1.04716 timestamp: 1654947260.9327202 iteration: 41410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12748 FastRCNN class loss: 0.08594 FastRCNN total loss: 0.21342 L1 loss: 0.0000e+00 L2 loss: 0.62726 Learning rate: 0.002 Mask loss: 0.11204 RPN box loss: 0.00865 RPN score loss: 0.00876 RPN total loss: 0.01741 Total loss: 0.97013 timestamp: 1654947264.094576 iteration: 41415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14011 FastRCNN class loss: 0.1223 FastRCNN total loss: 0.26241 L1 loss: 0.0000e+00 L2 loss: 0.62725 Learning rate: 0.002 Mask loss: 0.14636 RPN box loss: 0.05973 RPN score loss: 0.01045 RPN total loss: 0.07018 Total loss: 1.1062 timestamp: 1654947267.31504 iteration: 41420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08024 FastRCNN class loss: 0.04693 FastRCNN total loss: 0.12717 L1 loss: 0.0000e+00 L2 loss: 0.62725 Learning rate: 0.002 Mask loss: 0.10195 RPN box loss: 0.00954 RPN score loss: 0.00396 RPN total loss: 0.0135 Total loss: 0.86987 timestamp: 1654947270.4409323 iteration: 41425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12953 FastRCNN class loss: 0.10475 FastRCNN total loss: 0.23427 L1 loss: 0.0000e+00 L2 loss: 0.62724 Learning rate: 0.002 Mask loss: 0.15049 RPN box loss: 0.04023 RPN score loss: 0.01499 RPN total loss: 0.05522 Total loss: 1.06722 timestamp: 1654947273.6201074 iteration: 41430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11993 FastRCNN class loss: 0.09771 FastRCNN total loss: 0.21764 L1 loss: 0.0000e+00 L2 loss: 0.62723 Learning rate: 0.002 Mask loss: 0.17014 RPN box loss: 0.01496 RPN score loss: 0.00163 RPN total loss: 0.01659 Total loss: 1.0316 timestamp: 1654947276.8190713 iteration: 41435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11601 FastRCNN class loss: 0.07828 FastRCNN total loss: 0.19429 L1 loss: 0.0000e+00 L2 loss: 0.62722 Learning rate: 0.002 Mask loss: 0.11689 RPN box loss: 0.01332 RPN score loss: 0.00354 RPN total loss: 0.01685 Total loss: 0.95526 timestamp: 1654947280.0245094 iteration: 41440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08886 FastRCNN class loss: 0.05905 FastRCNN total loss: 0.14791 L1 loss: 0.0000e+00 L2 loss: 0.62721 Learning rate: 0.002 Mask loss: 0.11396 RPN box loss: 0.00844 RPN score loss: 0.00281 RPN total loss: 0.01124 Total loss: 0.90033 timestamp: 1654947283.2586432 iteration: 41445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12465 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.19523 L1 loss: 0.0000e+00 L2 loss: 0.6272 Learning rate: 0.002 Mask loss: 0.15695 RPN box loss: 0.02642 RPN score loss: 0.00291 RPN total loss: 0.02933 Total loss: 1.0087 timestamp: 1654947286.4618866 iteration: 41450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0849 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.15329 L1 loss: 0.0000e+00 L2 loss: 0.62719 Learning rate: 0.002 Mask loss: 0.16208 RPN box loss: 0.01336 RPN score loss: 0.00573 RPN total loss: 0.01909 Total loss: 0.96164 timestamp: 1654947289.684269 iteration: 41455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14308 FastRCNN class loss: 0.09405 FastRCNN total loss: 0.23713 L1 loss: 0.0000e+00 L2 loss: 0.62718 Learning rate: 0.002 Mask loss: 0.19212 RPN box loss: 0.02153 RPN score loss: 0.00493 RPN total loss: 0.02647 Total loss: 1.08289 timestamp: 1654947292.9073305 iteration: 41460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1365 FastRCNN class loss: 0.07523 FastRCNN total loss: 0.21173 L1 loss: 0.0000e+00 L2 loss: 0.62717 Learning rate: 0.002 Mask loss: 0.13522 RPN box loss: 0.02013 RPN score loss: 0.00392 RPN total loss: 0.02405 Total loss: 0.99816 timestamp: 1654947296.0295079 iteration: 41465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0744 FastRCNN class loss: 0.08971 FastRCNN total loss: 0.16411 L1 loss: 0.0000e+00 L2 loss: 0.62716 Learning rate: 0.002 Mask loss: 0.13889 RPN box loss: 0.01511 RPN score loss: 0.00496 RPN total loss: 0.02007 Total loss: 0.95023 timestamp: 1654947299.2792957 iteration: 41470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11172 FastRCNN class loss: 0.13237 FastRCNN total loss: 0.24409 L1 loss: 0.0000e+00 L2 loss: 0.62715 Learning rate: 0.002 Mask loss: 0.20744 RPN box loss: 0.03528 RPN score loss: 0.011 RPN total loss: 0.04628 Total loss: 1.12496 timestamp: 1654947302.5385435 iteration: 41475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18155 FastRCNN class loss: 0.08576 FastRCNN total loss: 0.26731 L1 loss: 0.0000e+00 L2 loss: 0.62714 Learning rate: 0.002 Mask loss: 0.15477 RPN box loss: 0.01191 RPN score loss: 0.00296 RPN total loss: 0.01487 Total loss: 1.06408 timestamp: 1654947305.6812384 iteration: 41480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10294 FastRCNN class loss: 0.06602 FastRCNN total loss: 0.16896 L1 loss: 0.0000e+00 L2 loss: 0.62713 Learning rate: 0.002 Mask loss: 0.09697 RPN box loss: 0.02564 RPN score loss: 0.00664 RPN total loss: 0.03228 Total loss: 0.92533 timestamp: 1654947308.9021769 iteration: 41485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11873 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.19476 L1 loss: 0.0000e+00 L2 loss: 0.62711 Learning rate: 0.002 Mask loss: 0.15082 RPN box loss: 0.0302 RPN score loss: 0.01099 RPN total loss: 0.04119 Total loss: 1.01388 timestamp: 1654947312.1071422 iteration: 41490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08022 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.13725 L1 loss: 0.0000e+00 L2 loss: 0.62711 Learning rate: 0.002 Mask loss: 0.094 RPN box loss: 0.01584 RPN score loss: 0.00148 RPN total loss: 0.01732 Total loss: 0.87568 timestamp: 1654947315.3106003 iteration: 41495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08483 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.14534 L1 loss: 0.0000e+00 L2 loss: 0.6271 Learning rate: 0.002 Mask loss: 0.11483 RPN box loss: 0.01732 RPN score loss: 0.00728 RPN total loss: 0.02461 Total loss: 0.91188 timestamp: 1654947318.6125274 iteration: 41500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1374 FastRCNN class loss: 0.11978 FastRCNN total loss: 0.25718 L1 loss: 0.0000e+00 L2 loss: 0.62709 Learning rate: 0.002 Mask loss: 0.22849 RPN box loss: 0.02518 RPN score loss: 0.00946 RPN total loss: 0.03465 Total loss: 1.14741 timestamp: 1654947321.8146431 iteration: 41505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04959 FastRCNN class loss: 0.0439 FastRCNN total loss: 0.09349 L1 loss: 0.0000e+00 L2 loss: 0.62708 Learning rate: 0.002 Mask loss: 0.12162 RPN box loss: 0.0218 RPN score loss: 0.00155 RPN total loss: 0.02335 Total loss: 0.86554 timestamp: 1654947325.0199003 iteration: 41510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06415 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.12842 L1 loss: 0.0000e+00 L2 loss: 0.62707 Learning rate: 0.002 Mask loss: 0.16887 RPN box loss: 0.02564 RPN score loss: 0.00586 RPN total loss: 0.03149 Total loss: 0.95586 timestamp: 1654947328.2527707 iteration: 41515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14383 FastRCNN class loss: 0.07728 FastRCNN total loss: 0.22111 L1 loss: 0.0000e+00 L2 loss: 0.62706 Learning rate: 0.002 Mask loss: 0.10758 RPN box loss: 0.00972 RPN score loss: 0.00393 RPN total loss: 0.01365 Total loss: 0.9694 timestamp: 1654947331.5195465 iteration: 41520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12228 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.20603 L1 loss: 0.0000e+00 L2 loss: 0.62705 Learning rate: 0.002 Mask loss: 0.1569 RPN box loss: 0.02222 RPN score loss: 0.00871 RPN total loss: 0.03093 Total loss: 1.02092 timestamp: 1654947334.8203723 iteration: 41525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07271 FastRCNN class loss: 0.0468 FastRCNN total loss: 0.11951 L1 loss: 0.0000e+00 L2 loss: 0.62704 Learning rate: 0.002 Mask loss: 0.14608 RPN box loss: 0.0079 RPN score loss: 0.00165 RPN total loss: 0.00955 Total loss: 0.90218 timestamp: 1654947337.949877 iteration: 41530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13219 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.19665 L1 loss: 0.0000e+00 L2 loss: 0.62703 Learning rate: 0.002 Mask loss: 0.13465 RPN box loss: 0.02054 RPN score loss: 0.01038 RPN total loss: 0.03092 Total loss: 0.98925 timestamp: 1654947341.0863705 iteration: 41535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.0788 FastRCNN total loss: 0.1722 L1 loss: 0.0000e+00 L2 loss: 0.62702 Learning rate: 0.002 Mask loss: 0.16692 RPN box loss: 0.0202 RPN score loss: 0.00523 RPN total loss: 0.02543 Total loss: 0.99157 timestamp: 1654947344.2869349 iteration: 41540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07573 FastRCNN class loss: 0.05194 FastRCNN total loss: 0.12768 L1 loss: 0.0000e+00 L2 loss: 0.62701 Learning rate: 0.002 Mask loss: 0.15576 RPN box loss: 0.00848 RPN score loss: 0.00514 RPN total loss: 0.01361 Total loss: 0.92406 timestamp: 1654947347.4638941 iteration: 41545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0857 FastRCNN class loss: 0.04671 FastRCNN total loss: 0.13241 L1 loss: 0.0000e+00 L2 loss: 0.627 Learning rate: 0.002 Mask loss: 0.13139 RPN box loss: 0.00654 RPN score loss: 0.00131 RPN total loss: 0.00785 Total loss: 0.89865 timestamp: 1654947350.6241434 iteration: 41550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03382 FastRCNN class loss: 0.02333 FastRCNN total loss: 0.05716 L1 loss: 0.0000e+00 L2 loss: 0.62699 Learning rate: 0.002 Mask loss: 0.09255 RPN box loss: 0.02905 RPN score loss: 0.00095 RPN total loss: 0.03 Total loss: 0.80671 timestamp: 1654947353.8711054 iteration: 41555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12244 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.18173 L1 loss: 0.0000e+00 L2 loss: 0.62698 Learning rate: 0.002 Mask loss: 0.10393 RPN box loss: 0.00785 RPN score loss: 0.00555 RPN total loss: 0.0134 Total loss: 0.92604 timestamp: 1654947357.0308647 iteration: 41560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0923 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.14441 L1 loss: 0.0000e+00 L2 loss: 0.62697 Learning rate: 0.002 Mask loss: 0.12748 RPN box loss: 0.00568 RPN score loss: 0.00196 RPN total loss: 0.00764 Total loss: 0.9065 timestamp: 1654947360.1620793 iteration: 41565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0911 FastRCNN class loss: 0.08424 FastRCNN total loss: 0.17534 L1 loss: 0.0000e+00 L2 loss: 0.62696 Learning rate: 0.002 Mask loss: 0.10876 RPN box loss: 0.01973 RPN score loss: 0.00506 RPN total loss: 0.02479 Total loss: 0.93586 timestamp: 1654947363.3380225 iteration: 41570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11669 FastRCNN class loss: 0.09189 FastRCNN total loss: 0.20858 L1 loss: 0.0000e+00 L2 loss: 0.62695 Learning rate: 0.002 Mask loss: 0.18197 RPN box loss: 0.02294 RPN score loss: 0.00336 RPN total loss: 0.0263 Total loss: 1.04381 timestamp: 1654947366.4875832 iteration: 41575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.14446 FastRCNN total loss: 0.264 L1 loss: 0.0000e+00 L2 loss: 0.62695 Learning rate: 0.002 Mask loss: 0.17541 RPN box loss: 0.02739 RPN score loss: 0.00608 RPN total loss: 0.03347 Total loss: 1.09982 timestamp: 1654947369.6706207 iteration: 41580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09362 FastRCNN class loss: 0.06377 FastRCNN total loss: 0.15738 L1 loss: 0.0000e+00 L2 loss: 0.62694 Learning rate: 0.002 Mask loss: 0.12364 RPN box loss: 0.01654 RPN score loss: 0.00499 RPN total loss: 0.02153 Total loss: 0.92949 timestamp: 1654947372.8057208 iteration: 41585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14064 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.20174 L1 loss: 0.0000e+00 L2 loss: 0.62693 Learning rate: 0.002 Mask loss: 0.12644 RPN box loss: 0.01167 RPN score loss: 0.0126 RPN total loss: 0.02426 Total loss: 0.97937 timestamp: 1654947376.0545373 iteration: 41590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11773 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.17546 L1 loss: 0.0000e+00 L2 loss: 0.62692 Learning rate: 0.002 Mask loss: 0.154 RPN box loss: 0.02215 RPN score loss: 0.00942 RPN total loss: 0.03157 Total loss: 0.98796 timestamp: 1654947379.2572951 iteration: 41595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05274 FastRCNN class loss: 0.05171 FastRCNN total loss: 0.10445 L1 loss: 0.0000e+00 L2 loss: 0.62691 Learning rate: 0.002 Mask loss: 0.16627 RPN box loss: 0.00715 RPN score loss: 0.00428 RPN total loss: 0.01143 Total loss: 0.90905 timestamp: 1654947382.490574 iteration: 41600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11837 FastRCNN class loss: 0.11555 FastRCNN total loss: 0.23392 L1 loss: 0.0000e+00 L2 loss: 0.6269 Learning rate: 0.002 Mask loss: 0.16074 RPN box loss: 0.01814 RPN score loss: 0.00386 RPN total loss: 0.02201 Total loss: 1.04357 timestamp: 1654947385.6045387 iteration: 41605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22125 FastRCNN class loss: 0.13658 FastRCNN total loss: 0.35784 L1 loss: 0.0000e+00 L2 loss: 0.62689 Learning rate: 0.002 Mask loss: 0.17843 RPN box loss: 0.04253 RPN score loss: 0.01093 RPN total loss: 0.05346 Total loss: 1.21663 timestamp: 1654947388.7658653 iteration: 41610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13738 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.22188 L1 loss: 0.0000e+00 L2 loss: 0.62688 Learning rate: 0.002 Mask loss: 0.13715 RPN box loss: 0.02677 RPN score loss: 0.00356 RPN total loss: 0.03033 Total loss: 1.01624 timestamp: 1654947391.9934943 iteration: 41615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08622 FastRCNN class loss: 0.05411 FastRCNN total loss: 0.14033 L1 loss: 0.0000e+00 L2 loss: 0.62687 Learning rate: 0.002 Mask loss: 0.14122 RPN box loss: 0.01787 RPN score loss: 0.00747 RPN total loss: 0.02534 Total loss: 0.93377 timestamp: 1654947395.1436024 iteration: 41620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14084 FastRCNN class loss: 0.0858 FastRCNN total loss: 0.22664 L1 loss: 0.0000e+00 L2 loss: 0.62686 Learning rate: 0.002 Mask loss: 0.107 RPN box loss: 0.02465 RPN score loss: 0.00138 RPN total loss: 0.02604 Total loss: 0.98654 timestamp: 1654947398.3797064 iteration: 41625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11281 FastRCNN class loss: 0.09832 FastRCNN total loss: 0.21113 L1 loss: 0.0000e+00 L2 loss: 0.62685 Learning rate: 0.002 Mask loss: 0.15458 RPN box loss: 0.11567 RPN score loss: 0.00623 RPN total loss: 0.1219 Total loss: 1.11446 timestamp: 1654947401.6184835 iteration: 41630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06945 FastRCNN class loss: 0.05132 FastRCNN total loss: 0.12077 L1 loss: 0.0000e+00 L2 loss: 0.62684 Learning rate: 0.002 Mask loss: 0.10835 RPN box loss: 0.03109 RPN score loss: 0.00672 RPN total loss: 0.03781 Total loss: 0.89377 timestamp: 1654947404.8627937 iteration: 41635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08534 FastRCNN class loss: 0.11578 FastRCNN total loss: 0.20111 L1 loss: 0.0000e+00 L2 loss: 0.62683 Learning rate: 0.002 Mask loss: 0.24608 RPN box loss: 0.03486 RPN score loss: 0.05633 RPN total loss: 0.09119 Total loss: 1.16522 timestamp: 1654947408.0471375 iteration: 41640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08647 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.1725 L1 loss: 0.0000e+00 L2 loss: 0.62682 Learning rate: 0.002 Mask loss: 0.16186 RPN box loss: 0.03126 RPN score loss: 0.0042 RPN total loss: 0.03546 Total loss: 0.99664 timestamp: 1654947411.2416363 iteration: 41645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.05499 FastRCNN total loss: 0.20627 L1 loss: 0.0000e+00 L2 loss: 0.62681 Learning rate: 0.002 Mask loss: 0.15394 RPN box loss: 0.01637 RPN score loss: 0.00532 RPN total loss: 0.02169 Total loss: 1.00872 timestamp: 1654947414.448918 iteration: 41650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11288 FastRCNN class loss: 0.06825 FastRCNN total loss: 0.18113 L1 loss: 0.0000e+00 L2 loss: 0.62681 Learning rate: 0.002 Mask loss: 0.1383 RPN box loss: 0.02642 RPN score loss: 0.01157 RPN total loss: 0.03799 Total loss: 0.98423 timestamp: 1654947417.6040425 iteration: 41655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11174 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.1734 L1 loss: 0.0000e+00 L2 loss: 0.6268 Learning rate: 0.002 Mask loss: 0.11329 RPN box loss: 0.01195 RPN score loss: 0.01253 RPN total loss: 0.02448 Total loss: 0.93796 timestamp: 1654947420.8372502 iteration: 41660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14271 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.22444 L1 loss: 0.0000e+00 L2 loss: 0.62679 Learning rate: 0.002 Mask loss: 0.16535 RPN box loss: 0.02168 RPN score loss: 0.00581 RPN total loss: 0.02749 Total loss: 1.04407 timestamp: 1654947424.07669 iteration: 41665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.14412 L1 loss: 0.0000e+00 L2 loss: 0.62678 Learning rate: 0.002 Mask loss: 0.10637 RPN box loss: 0.01158 RPN score loss: 0.00364 RPN total loss: 0.01522 Total loss: 0.89249 timestamp: 1654947427.285185 iteration: 41670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07568 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.14926 L1 loss: 0.0000e+00 L2 loss: 0.62677 Learning rate: 0.002 Mask loss: 0.10202 RPN box loss: 0.01187 RPN score loss: 0.0038 RPN total loss: 0.01567 Total loss: 0.89372 timestamp: 1654947430.474682 iteration: 41675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14784 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.2123 L1 loss: 0.0000e+00 L2 loss: 0.62676 Learning rate: 0.002 Mask loss: 0.11195 RPN box loss: 0.06166 RPN score loss: 0.00348 RPN total loss: 0.06514 Total loss: 1.01615 timestamp: 1654947433.6965272 iteration: 41680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07645 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.13539 L1 loss: 0.0000e+00 L2 loss: 0.62675 Learning rate: 0.002 Mask loss: 0.10009 RPN box loss: 0.01747 RPN score loss: 0.00106 RPN total loss: 0.01853 Total loss: 0.88077 timestamp: 1654947436.9186041 iteration: 41685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09574 FastRCNN class loss: 0.09483 FastRCNN total loss: 0.19057 L1 loss: 0.0000e+00 L2 loss: 0.62675 Learning rate: 0.002 Mask loss: 0.1612 RPN box loss: 0.00941 RPN score loss: 0.0032 RPN total loss: 0.01261 Total loss: 0.99113 timestamp: 1654947440.0894635 iteration: 41690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1101 FastRCNN class loss: 0.09299 FastRCNN total loss: 0.2031 L1 loss: 0.0000e+00 L2 loss: 0.62674 Learning rate: 0.002 Mask loss: 0.1518 RPN box loss: 0.01884 RPN score loss: 0.00548 RPN total loss: 0.02431 Total loss: 1.00595 timestamp: 1654947443.3455808 iteration: 41695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0904 FastRCNN class loss: 0.08374 FastRCNN total loss: 0.17413 L1 loss: 0.0000e+00 L2 loss: 0.62673 Learning rate: 0.002 Mask loss: 0.12962 RPN box loss: 0.00747 RPN score loss: 0.00223 RPN total loss: 0.0097 Total loss: 0.94017 timestamp: 1654947446.547606 iteration: 41700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12753 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.20077 L1 loss: 0.0000e+00 L2 loss: 0.62671 Learning rate: 0.002 Mask loss: 0.12047 RPN box loss: 0.0186 RPN score loss: 0.00114 RPN total loss: 0.01974 Total loss: 0.9677 timestamp: 1654947449.7777457 iteration: 41705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.11722 FastRCNN total loss: 0.23205 L1 loss: 0.0000e+00 L2 loss: 0.6267 Learning rate: 0.002 Mask loss: 0.17363 RPN box loss: 0.03219 RPN score loss: 0.00779 RPN total loss: 0.03999 Total loss: 1.07237 timestamp: 1654947452.9896905 iteration: 41710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08636 FastRCNN class loss: 0.07363 FastRCNN total loss: 0.15998 L1 loss: 0.0000e+00 L2 loss: 0.62669 Learning rate: 0.002 Mask loss: 0.11216 RPN box loss: 0.05134 RPN score loss: 0.01323 RPN total loss: 0.06457 Total loss: 0.9634 timestamp: 1654947456.224543 iteration: 41715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11324 FastRCNN class loss: 0.08332 FastRCNN total loss: 0.19656 L1 loss: 0.0000e+00 L2 loss: 0.62668 Learning rate: 0.002 Mask loss: 0.14491 RPN box loss: 0.00849 RPN score loss: 0.00442 RPN total loss: 0.01291 Total loss: 0.98106 timestamp: 1654947459.4138188 iteration: 41720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1177 FastRCNN class loss: 0.05273 FastRCNN total loss: 0.17043 L1 loss: 0.0000e+00 L2 loss: 0.62667 Learning rate: 0.002 Mask loss: 0.10419 RPN box loss: 0.01739 RPN score loss: 0.01084 RPN total loss: 0.02823 Total loss: 0.92952 timestamp: 1654947462.5544848 iteration: 41725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13805 FastRCNN class loss: 0.09289 FastRCNN total loss: 0.23095 L1 loss: 0.0000e+00 L2 loss: 0.62666 Learning rate: 0.002 Mask loss: 0.19865 RPN box loss: 0.02048 RPN score loss: 0.0168 RPN total loss: 0.03728 Total loss: 1.09353 timestamp: 1654947465.7604947 iteration: 41730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05899 FastRCNN class loss: 0.04487 FastRCNN total loss: 0.10387 L1 loss: 0.0000e+00 L2 loss: 0.62665 Learning rate: 0.002 Mask loss: 0.14551 RPN box loss: 0.02026 RPN score loss: 0.00726 RPN total loss: 0.02752 Total loss: 0.90355 timestamp: 1654947468.9186814 iteration: 41735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10928 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.19896 L1 loss: 0.0000e+00 L2 loss: 0.62664 Learning rate: 0.002 Mask loss: 0.12291 RPN box loss: 0.02261 RPN score loss: 0.00447 RPN total loss: 0.02709 Total loss: 0.9756 timestamp: 1654947472.1737754 iteration: 41740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14979 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.21241 L1 loss: 0.0000e+00 L2 loss: 0.62664 Learning rate: 0.002 Mask loss: 0.14135 RPN box loss: 0.01179 RPN score loss: 0.00271 RPN total loss: 0.0145 Total loss: 0.99489 timestamp: 1654947475.3688698 iteration: 41745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09017 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.13956 L1 loss: 0.0000e+00 L2 loss: 0.62663 Learning rate: 0.002 Mask loss: 0.11047 RPN box loss: 0.01097 RPN score loss: 0.00226 RPN total loss: 0.01323 Total loss: 0.88988 timestamp: 1654947478.596835 iteration: 41750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08413 FastRCNN class loss: 0.04376 FastRCNN total loss: 0.12789 L1 loss: 0.0000e+00 L2 loss: 0.62662 Learning rate: 0.002 Mask loss: 0.1087 RPN box loss: 0.02133 RPN score loss: 0.00174 RPN total loss: 0.02307 Total loss: 0.88627 timestamp: 1654947481.7975001 iteration: 41755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05202 FastRCNN class loss: 0.03875 FastRCNN total loss: 0.09078 L1 loss: 0.0000e+00 L2 loss: 0.62661 Learning rate: 0.002 Mask loss: 0.09985 RPN box loss: 0.00742 RPN score loss: 0.00199 RPN total loss: 0.00941 Total loss: 0.82664 timestamp: 1654947484.9677293 iteration: 41760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15599 FastRCNN class loss: 0.12338 FastRCNN total loss: 0.27937 L1 loss: 0.0000e+00 L2 loss: 0.6266 Learning rate: 0.002 Mask loss: 0.10791 RPN box loss: 0.01919 RPN score loss: 0.00786 RPN total loss: 0.02705 Total loss: 1.04093 timestamp: 1654947488.12915 iteration: 41765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10057 FastRCNN class loss: 0.07341 FastRCNN total loss: 0.17399 L1 loss: 0.0000e+00 L2 loss: 0.62659 Learning rate: 0.002 Mask loss: 0.17174 RPN box loss: 0.03792 RPN score loss: 0.00452 RPN total loss: 0.04244 Total loss: 1.01475 timestamp: 1654947491.3455188 iteration: 41770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09995 FastRCNN class loss: 0.05575 FastRCNN total loss: 0.15571 L1 loss: 0.0000e+00 L2 loss: 0.62658 Learning rate: 0.002 Mask loss: 0.11726 RPN box loss: 0.02608 RPN score loss: 0.01324 RPN total loss: 0.03933 Total loss: 0.93887 timestamp: 1654947494.50883 iteration: 41775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15504 FastRCNN class loss: 0.05591 FastRCNN total loss: 0.21095 L1 loss: 0.0000e+00 L2 loss: 0.62657 Learning rate: 0.002 Mask loss: 0.17291 RPN box loss: 0.01119 RPN score loss: 0.00538 RPN total loss: 0.01657 Total loss: 1.02701 timestamp: 1654947497.7338023 iteration: 41780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15288 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.21145 L1 loss: 0.0000e+00 L2 loss: 0.62656 Learning rate: 0.002 Mask loss: 0.12461 RPN box loss: 0.02358 RPN score loss: 0.00433 RPN total loss: 0.02791 Total loss: 0.99054 timestamp: 1654947500.915315 iteration: 41785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09363 FastRCNN class loss: 0.04035 FastRCNN total loss: 0.13397 L1 loss: 0.0000e+00 L2 loss: 0.62655 Learning rate: 0.002 Mask loss: 0.1157 RPN box loss: 0.00795 RPN score loss: 0.00325 RPN total loss: 0.0112 Total loss: 0.88742 timestamp: 1654947504.147673 iteration: 41790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16701 FastRCNN class loss: 0.09987 FastRCNN total loss: 0.26688 L1 loss: 0.0000e+00 L2 loss: 0.62654 Learning rate: 0.002 Mask loss: 0.16663 RPN box loss: 0.03628 RPN score loss: 0.00797 RPN total loss: 0.04424 Total loss: 1.10429 timestamp: 1654947507.313763 iteration: 41795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04726 FastRCNN class loss: 0.03955 FastRCNN total loss: 0.08681 L1 loss: 0.0000e+00 L2 loss: 0.62653 Learning rate: 0.002 Mask loss: 0.14377 RPN box loss: 0.01433 RPN score loss: 0.00291 RPN total loss: 0.01724 Total loss: 0.87436 timestamp: 1654947510.4799633 iteration: 41800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13577 FastRCNN class loss: 0.0796 FastRCNN total loss: 0.21537 L1 loss: 0.0000e+00 L2 loss: 0.62652 Learning rate: 0.002 Mask loss: 0.16273 RPN box loss: 0.05796 RPN score loss: 0.00523 RPN total loss: 0.06318 Total loss: 1.0678 timestamp: 1654947513.6415887 iteration: 41805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07903 FastRCNN class loss: 0.05548 FastRCNN total loss: 0.13451 L1 loss: 0.0000e+00 L2 loss: 0.62651 Learning rate: 0.002 Mask loss: 0.12241 RPN box loss: 0.0073 RPN score loss: 0.00114 RPN total loss: 0.00844 Total loss: 0.89188 timestamp: 1654947516.863657 iteration: 41810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11384 FastRCNN class loss: 0.0536 FastRCNN total loss: 0.16744 L1 loss: 0.0000e+00 L2 loss: 0.6265 Learning rate: 0.002 Mask loss: 0.09 RPN box loss: 0.00804 RPN score loss: 0.00453 RPN total loss: 0.01257 Total loss: 0.89651 timestamp: 1654947520.0785909 iteration: 41815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15192 FastRCNN class loss: 0.05444 FastRCNN total loss: 0.20636 L1 loss: 0.0000e+00 L2 loss: 0.62649 Learning rate: 0.002 Mask loss: 0.14012 RPN box loss: 0.01514 RPN score loss: 0.00622 RPN total loss: 0.02137 Total loss: 0.99434 timestamp: 1654947523.2402549 iteration: 41820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12506 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.20513 L1 loss: 0.0000e+00 L2 loss: 0.62648 Learning rate: 0.002 Mask loss: 0.12174 RPN box loss: 0.01226 RPN score loss: 0.00256 RPN total loss: 0.01482 Total loss: 0.96816 timestamp: 1654947526.5090432 iteration: 41825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1507 FastRCNN class loss: 0.09985 FastRCNN total loss: 0.25055 L1 loss: 0.0000e+00 L2 loss: 0.62647 Learning rate: 0.002 Mask loss: 0.19212 RPN box loss: 0.01925 RPN score loss: 0.00932 RPN total loss: 0.02857 Total loss: 1.0977 timestamp: 1654947529.8031166 iteration: 41830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.04062 FastRCNN total loss: 0.13909 L1 loss: 0.0000e+00 L2 loss: 0.62646 Learning rate: 0.002 Mask loss: 0.11148 RPN box loss: 0.0163 RPN score loss: 0.00362 RPN total loss: 0.01992 Total loss: 0.89695 timestamp: 1654947532.9648156 iteration: 41835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16837 FastRCNN class loss: 0.06822 FastRCNN total loss: 0.2366 L1 loss: 0.0000e+00 L2 loss: 0.62645 Learning rate: 0.002 Mask loss: 0.09532 RPN box loss: 0.02693 RPN score loss: 0.00369 RPN total loss: 0.03062 Total loss: 0.98898 timestamp: 1654947536.2287376 iteration: 41840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07727 FastRCNN class loss: 0.0612 FastRCNN total loss: 0.13847 L1 loss: 0.0000e+00 L2 loss: 0.62644 Learning rate: 0.002 Mask loss: 0.08243 RPN box loss: 0.01017 RPN score loss: 0.0019 RPN total loss: 0.01206 Total loss: 0.8594 timestamp: 1654947539.4743848 iteration: 41845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06177 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.1324 L1 loss: 0.0000e+00 L2 loss: 0.62643 Learning rate: 0.002 Mask loss: 0.08422 RPN box loss: 0.01276 RPN score loss: 0.00118 RPN total loss: 0.01394 Total loss: 0.85699 timestamp: 1654947542.6214023 iteration: 41850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11907 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.19503 L1 loss: 0.0000e+00 L2 loss: 0.62642 Learning rate: 0.002 Mask loss: 0.13622 RPN box loss: 0.0729 RPN score loss: 0.00335 RPN total loss: 0.07625 Total loss: 1.03392 timestamp: 1654947545.8663225 iteration: 41855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07792 FastRCNN class loss: 0.08308 FastRCNN total loss: 0.161 L1 loss: 0.0000e+00 L2 loss: 0.62641 Learning rate: 0.002 Mask loss: 0.11078 RPN box loss: 0.00676 RPN score loss: 0.00088 RPN total loss: 0.00764 Total loss: 0.90583 timestamp: 1654947549.081918 iteration: 41860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09856 FastRCNN class loss: 0.06478 FastRCNN total loss: 0.16334 L1 loss: 0.0000e+00 L2 loss: 0.6264 Learning rate: 0.002 Mask loss: 0.13941 RPN box loss: 0.03166 RPN score loss: 0.00414 RPN total loss: 0.0358 Total loss: 0.96495 timestamp: 1654947552.2792578 iteration: 41865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13942 FastRCNN class loss: 0.10378 FastRCNN total loss: 0.2432 L1 loss: 0.0000e+00 L2 loss: 0.62639 Learning rate: 0.002 Mask loss: 0.14921 RPN box loss: 0.03104 RPN score loss: 0.00498 RPN total loss: 0.03602 Total loss: 1.05481 timestamp: 1654947555.457169 iteration: 41870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13089 FastRCNN class loss: 0.06671 FastRCNN total loss: 0.1976 L1 loss: 0.0000e+00 L2 loss: 0.62638 Learning rate: 0.002 Mask loss: 0.16287 RPN box loss: 0.01759 RPN score loss: 0.01029 RPN total loss: 0.02787 Total loss: 1.01472 timestamp: 1654947558.5686529 iteration: 41875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0632 FastRCNN class loss: 0.05128 FastRCNN total loss: 0.11447 L1 loss: 0.0000e+00 L2 loss: 0.62637 Learning rate: 0.002 Mask loss: 0.12732 RPN box loss: 0.01721 RPN score loss: 0.00313 RPN total loss: 0.02034 Total loss: 0.88851 timestamp: 1654947561.7641804 iteration: 41880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04798 FastRCNN class loss: 0.04806 FastRCNN total loss: 0.09604 L1 loss: 0.0000e+00 L2 loss: 0.62636 Learning rate: 0.002 Mask loss: 0.15752 RPN box loss: 0.01659 RPN score loss: 0.00265 RPN total loss: 0.01924 Total loss: 0.89916 timestamp: 1654947564.960996 iteration: 41885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.05581 FastRCNN total loss: 0.13237 L1 loss: 0.0000e+00 L2 loss: 0.62635 Learning rate: 0.002 Mask loss: 0.19631 RPN box loss: 0.00989 RPN score loss: 0.00623 RPN total loss: 0.01612 Total loss: 0.97116 timestamp: 1654947568.1815352 iteration: 41890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05022 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.11081 L1 loss: 0.0000e+00 L2 loss: 0.62634 Learning rate: 0.002 Mask loss: 0.12932 RPN box loss: 0.00579 RPN score loss: 0.00345 RPN total loss: 0.00924 Total loss: 0.8757 timestamp: 1654947571.3894355 iteration: 41895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11755 FastRCNN class loss: 0.07051 FastRCNN total loss: 0.18806 L1 loss: 0.0000e+00 L2 loss: 0.62633 Learning rate: 0.002 Mask loss: 0.15811 RPN box loss: 0.04758 RPN score loss: 0.00575 RPN total loss: 0.05333 Total loss: 1.02583 timestamp: 1654947574.5671122 iteration: 41900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08072 FastRCNN class loss: 0.05498 FastRCNN total loss: 0.1357 L1 loss: 0.0000e+00 L2 loss: 0.62632 Learning rate: 0.002 Mask loss: 0.1247 RPN box loss: 0.024 RPN score loss: 0.01208 RPN total loss: 0.03608 Total loss: 0.92281 timestamp: 1654947577.7425928 iteration: 41905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09963 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.16293 L1 loss: 0.0000e+00 L2 loss: 0.62631 Learning rate: 0.002 Mask loss: 0.12429 RPN box loss: 0.04062 RPN score loss: 0.00564 RPN total loss: 0.04626 Total loss: 0.95979 timestamp: 1654947581.0131364 iteration: 41910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1212 FastRCNN class loss: 0.11159 FastRCNN total loss: 0.23279 L1 loss: 0.0000e+00 L2 loss: 0.6263 Learning rate: 0.002 Mask loss: 0.22343 RPN box loss: 0.03469 RPN score loss: 0.00707 RPN total loss: 0.04176 Total loss: 1.12428 timestamp: 1654947584.1785488 iteration: 41915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09268 FastRCNN class loss: 0.03669 FastRCNN total loss: 0.12937 L1 loss: 0.0000e+00 L2 loss: 0.6263 Learning rate: 0.002 Mask loss: 0.10227 RPN box loss: 0.02451 RPN score loss: 0.00346 RPN total loss: 0.02797 Total loss: 0.88591 timestamp: 1654947587.383147 iteration: 41920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12013 FastRCNN class loss: 0.06062 FastRCNN total loss: 0.18076 L1 loss: 0.0000e+00 L2 loss: 0.62629 Learning rate: 0.002 Mask loss: 0.11027 RPN box loss: 0.00482 RPN score loss: 0.00395 RPN total loss: 0.00877 Total loss: 0.92608 timestamp: 1654947590.5547626 iteration: 41925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12583 FastRCNN class loss: 0.04499 FastRCNN total loss: 0.17082 L1 loss: 0.0000e+00 L2 loss: 0.62628 Learning rate: 0.002 Mask loss: 0.14131 RPN box loss: 0.02999 RPN score loss: 0.0033 RPN total loss: 0.0333 Total loss: 0.97171 timestamp: 1654947593.7953846 iteration: 41930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12211 FastRCNN class loss: 0.10475 FastRCNN total loss: 0.22686 L1 loss: 0.0000e+00 L2 loss: 0.62627 Learning rate: 0.002 Mask loss: 0.1622 RPN box loss: 0.00986 RPN score loss: 0.00307 RPN total loss: 0.01293 Total loss: 1.02827 timestamp: 1654947596.9906561 iteration: 41935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17669 FastRCNN class loss: 0.09677 FastRCNN total loss: 0.27346 L1 loss: 0.0000e+00 L2 loss: 0.62626 Learning rate: 0.002 Mask loss: 0.17936 RPN box loss: 0.02623 RPN score loss: 0.01797 RPN total loss: 0.0442 Total loss: 1.12329 timestamp: 1654947600.2335699 iteration: 41940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07584 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.15411 L1 loss: 0.0000e+00 L2 loss: 0.62625 Learning rate: 0.002 Mask loss: 0.1511 RPN box loss: 0.0102 RPN score loss: 0.00383 RPN total loss: 0.01403 Total loss: 0.94549 timestamp: 1654947603.4220352 iteration: 41945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06593 FastRCNN class loss: 0.05878 FastRCNN total loss: 0.12471 L1 loss: 0.0000e+00 L2 loss: 0.62624 Learning rate: 0.002 Mask loss: 0.08357 RPN box loss: 0.00477 RPN score loss: 0.00487 RPN total loss: 0.00964 Total loss: 0.84415 timestamp: 1654947606.6721852 iteration: 41950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.079 FastRCNN class loss: 0.04719 FastRCNN total loss: 0.12619 L1 loss: 0.0000e+00 L2 loss: 0.62623 Learning rate: 0.002 Mask loss: 0.1402 RPN box loss: 0.042 RPN score loss: 0.00172 RPN total loss: 0.04372 Total loss: 0.93634 timestamp: 1654947609.8411863 iteration: 41955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09795 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.16881 L1 loss: 0.0000e+00 L2 loss: 0.62622 Learning rate: 0.002 Mask loss: 0.12634 RPN box loss: 0.02815 RPN score loss: 0.00595 RPN total loss: 0.03409 Total loss: 0.95546 timestamp: 1654947613.1019337 iteration: 41960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05351 FastRCNN class loss: 0.04149 FastRCNN total loss: 0.095 L1 loss: 0.0000e+00 L2 loss: 0.62621 Learning rate: 0.002 Mask loss: 0.11823 RPN box loss: 0.03059 RPN score loss: 0.00538 RPN total loss: 0.03597 Total loss: 0.87541 timestamp: 1654947616.3541977 iteration: 41965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09925 FastRCNN class loss: 0.0919 FastRCNN total loss: 0.19115 L1 loss: 0.0000e+00 L2 loss: 0.6262 Learning rate: 0.002 Mask loss: 0.1459 RPN box loss: 0.02873 RPN score loss: 0.00511 RPN total loss: 0.03384 Total loss: 0.99709 timestamp: 1654947619.5574834 iteration: 41970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06868 FastRCNN class loss: 0.05983 FastRCNN total loss: 0.12852 L1 loss: 0.0000e+00 L2 loss: 0.62619 Learning rate: 0.002 Mask loss: 0.11079 RPN box loss: 0.01564 RPN score loss: 0.00184 RPN total loss: 0.01748 Total loss: 0.88298 timestamp: 1654947622.7310143 iteration: 41975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11605 FastRCNN class loss: 0.11826 FastRCNN total loss: 0.23431 L1 loss: 0.0000e+00 L2 loss: 0.62618 Learning rate: 0.002 Mask loss: 0.17208 RPN box loss: 0.02113 RPN score loss: 0.01256 RPN total loss: 0.03369 Total loss: 1.06624 timestamp: 1654947625.8694253 iteration: 41980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07086 FastRCNN class loss: 0.07657 FastRCNN total loss: 0.14743 L1 loss: 0.0000e+00 L2 loss: 0.62617 Learning rate: 0.002 Mask loss: 0.1279 RPN box loss: 0.01085 RPN score loss: 0.00595 RPN total loss: 0.0168 Total loss: 0.9183 timestamp: 1654947629.1061194 iteration: 41985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13756 FastRCNN class loss: 0.0795 FastRCNN total loss: 0.21706 L1 loss: 0.0000e+00 L2 loss: 0.62616 Learning rate: 0.002 Mask loss: 0.16001 RPN box loss: 0.022 RPN score loss: 0.01118 RPN total loss: 0.03319 Total loss: 1.03642 timestamp: 1654947632.312526 iteration: 41990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10513 FastRCNN class loss: 0.07647 FastRCNN total loss: 0.18159 L1 loss: 0.0000e+00 L2 loss: 0.62615 Learning rate: 0.002 Mask loss: 0.19673 RPN box loss: 0.03585 RPN score loss: 0.00293 RPN total loss: 0.03878 Total loss: 1.04326 timestamp: 1654947635.6040967 iteration: 41995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08698 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.14175 L1 loss: 0.0000e+00 L2 loss: 0.62614 Learning rate: 0.002 Mask loss: 0.13576 RPN box loss: 0.03354 RPN score loss: 0.00254 RPN total loss: 0.03608 Total loss: 0.93973 timestamp: 1654947638.8111129 iteration: 42000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09425 FastRCNN class loss: 0.07591 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.62613 Learning rate: 0.002 Mask loss: 0.13079 RPN box loss: 0.00735 RPN score loss: 0.00344 RPN total loss: 0.01078 Total loss: 0.93787 timestamp: 1654947641.993418 iteration: 42005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08002 FastRCNN class loss: 0.04802 FastRCNN total loss: 0.12804 L1 loss: 0.0000e+00 L2 loss: 0.62612 Learning rate: 0.002 Mask loss: 0.14827 RPN box loss: 0.00322 RPN score loss: 0.00225 RPN total loss: 0.00548 Total loss: 0.90791 timestamp: 1654947645.1428356 iteration: 42010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14748 FastRCNN class loss: 0.08043 FastRCNN total loss: 0.22791 L1 loss: 0.0000e+00 L2 loss: 0.62611 Learning rate: 0.002 Mask loss: 0.23425 RPN box loss: 0.01803 RPN score loss: 0.00376 RPN total loss: 0.02179 Total loss: 1.11007 timestamp: 1654947648.3491416 iteration: 42015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12564 FastRCNN class loss: 0.07712 FastRCNN total loss: 0.20276 L1 loss: 0.0000e+00 L2 loss: 0.6261 Learning rate: 0.002 Mask loss: 0.14955 RPN box loss: 0.0355 RPN score loss: 0.0087 RPN total loss: 0.0442 Total loss: 1.0226 timestamp: 1654947651.4905963 iteration: 42020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.09421 FastRCNN total loss: 0.20387 L1 loss: 0.0000e+00 L2 loss: 0.6261 Learning rate: 0.002 Mask loss: 0.16169 RPN box loss: 0.02383 RPN score loss: 0.0055 RPN total loss: 0.02933 Total loss: 1.02098 timestamp: 1654947654.672675 iteration: 42025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13448 FastRCNN class loss: 0.10789 FastRCNN total loss: 0.24238 L1 loss: 0.0000e+00 L2 loss: 0.62609 Learning rate: 0.002 Mask loss: 0.13725 RPN box loss: 0.04393 RPN score loss: 0.00935 RPN total loss: 0.05328 Total loss: 1.059 timestamp: 1654947657.821831 iteration: 42030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16052 FastRCNN class loss: 0.07567 FastRCNN total loss: 0.23619 L1 loss: 0.0000e+00 L2 loss: 0.62608 Learning rate: 0.002 Mask loss: 0.1489 RPN box loss: 0.01561 RPN score loss: 0.00272 RPN total loss: 0.01833 Total loss: 1.02951 timestamp: 1654947661.0706542 iteration: 42035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05326 FastRCNN class loss: 0.04431 FastRCNN total loss: 0.09756 L1 loss: 0.0000e+00 L2 loss: 0.62607 Learning rate: 0.002 Mask loss: 0.09043 RPN box loss: 0.04072 RPN score loss: 0.00599 RPN total loss: 0.04671 Total loss: 0.86077 timestamp: 1654947664.2840216 iteration: 42040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12002 FastRCNN class loss: 0.05092 FastRCNN total loss: 0.17094 L1 loss: 0.0000e+00 L2 loss: 0.62606 Learning rate: 0.002 Mask loss: 0.0949 RPN box loss: 0.02675 RPN score loss: 0.00429 RPN total loss: 0.03104 Total loss: 0.92294 timestamp: 1654947667.5030458 iteration: 42045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1218 FastRCNN class loss: 0.08594 FastRCNN total loss: 0.20773 L1 loss: 0.0000e+00 L2 loss: 0.62605 Learning rate: 0.002 Mask loss: 0.13901 RPN box loss: 0.05088 RPN score loss: 0.00885 RPN total loss: 0.05973 Total loss: 1.03252 timestamp: 1654947670.7146854 iteration: 42050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07969 FastRCNN class loss: 0.03891 FastRCNN total loss: 0.11861 L1 loss: 0.0000e+00 L2 loss: 0.62604 Learning rate: 0.002 Mask loss: 0.13779 RPN box loss: 0.0104 RPN score loss: 0.00468 RPN total loss: 0.01508 Total loss: 0.89751 timestamp: 1654947673.8982656 iteration: 42055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10669 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.19627 L1 loss: 0.0000e+00 L2 loss: 0.62603 Learning rate: 0.002 Mask loss: 0.15492 RPN box loss: 0.0219 RPN score loss: 0.0025 RPN total loss: 0.02441 Total loss: 1.00163 timestamp: 1654947677.1261861 iteration: 42060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14211 FastRCNN class loss: 0.07645 FastRCNN total loss: 0.21856 L1 loss: 0.0000e+00 L2 loss: 0.62602 Learning rate: 0.002 Mask loss: 0.11955 RPN box loss: 0.00697 RPN score loss: 0.00776 RPN total loss: 0.01473 Total loss: 0.97887 timestamp: 1654947680.3076792 iteration: 42065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07082 FastRCNN class loss: 0.09095 FastRCNN total loss: 0.16177 L1 loss: 0.0000e+00 L2 loss: 0.62601 Learning rate: 0.002 Mask loss: 0.12191 RPN box loss: 0.03079 RPN score loss: 0.00691 RPN total loss: 0.03771 Total loss: 0.9474 timestamp: 1654947683.5651274 iteration: 42070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11809 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.17113 L1 loss: 0.0000e+00 L2 loss: 0.626 Learning rate: 0.002 Mask loss: 0.10783 RPN box loss: 0.00815 RPN score loss: 0.00515 RPN total loss: 0.0133 Total loss: 0.91826 timestamp: 1654947686.7476947 iteration: 42075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05303 FastRCNN class loss: 0.04403 FastRCNN total loss: 0.09706 L1 loss: 0.0000e+00 L2 loss: 0.62599 Learning rate: 0.002 Mask loss: 0.13777 RPN box loss: 0.01904 RPN score loss: 0.00956 RPN total loss: 0.02859 Total loss: 0.88942 timestamp: 1654947689.8949091 iteration: 42080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05726 FastRCNN class loss: 0.03901 FastRCNN total loss: 0.09627 L1 loss: 0.0000e+00 L2 loss: 0.62598 Learning rate: 0.002 Mask loss: 0.08823 RPN box loss: 0.03868 RPN score loss: 0.00227 RPN total loss: 0.04095 Total loss: 0.85143 timestamp: 1654947693.1383069 iteration: 42085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09445 FastRCNN class loss: 0.05393 FastRCNN total loss: 0.14838 L1 loss: 0.0000e+00 L2 loss: 0.62597 Learning rate: 0.002 Mask loss: 0.14797 RPN box loss: 0.00682 RPN score loss: 0.00384 RPN total loss: 0.01066 Total loss: 0.93298 timestamp: 1654947696.3186479 iteration: 42090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11499 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.1937 L1 loss: 0.0000e+00 L2 loss: 0.62596 Learning rate: 0.002 Mask loss: 0.15405 RPN box loss: 0.04995 RPN score loss: 0.01408 RPN total loss: 0.06403 Total loss: 1.03774 timestamp: 1654947699.4394224 iteration: 42095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08721 FastRCNN class loss: 0.08309 FastRCNN total loss: 0.17029 L1 loss: 0.0000e+00 L2 loss: 0.62595 Learning rate: 0.002 Mask loss: 0.19715 RPN box loss: 0.00929 RPN score loss: 0.00191 RPN total loss: 0.0112 Total loss: 1.0046 timestamp: 1654947702.6592822 iteration: 42100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11676 FastRCNN class loss: 0.09437 FastRCNN total loss: 0.21113 L1 loss: 0.0000e+00 L2 loss: 0.62595 Learning rate: 0.002 Mask loss: 0.12525 RPN box loss: 0.03572 RPN score loss: 0.00796 RPN total loss: 0.04368 Total loss: 1.00601 timestamp: 1654947705.881351 iteration: 42105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12426 FastRCNN class loss: 0.06917 FastRCNN total loss: 0.19343 L1 loss: 0.0000e+00 L2 loss: 0.62594 Learning rate: 0.002 Mask loss: 0.14778 RPN box loss: 0.04825 RPN score loss: 0.00492 RPN total loss: 0.05316 Total loss: 1.02031 timestamp: 1654947709.1393573 iteration: 42110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14994 FastRCNN class loss: 0.0863 FastRCNN total loss: 0.23623 L1 loss: 0.0000e+00 L2 loss: 0.62593 Learning rate: 0.002 Mask loss: 0.11076 RPN box loss: 0.02929 RPN score loss: 0.01048 RPN total loss: 0.03976 Total loss: 1.01268 timestamp: 1654947712.2977734 iteration: 42115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14817 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.23981 L1 loss: 0.0000e+00 L2 loss: 0.62592 Learning rate: 0.002 Mask loss: 0.1247 RPN box loss: 0.02253 RPN score loss: 0.0052 RPN total loss: 0.02773 Total loss: 1.01815 timestamp: 1654947715.5742238 iteration: 42120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11641 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.17631 L1 loss: 0.0000e+00 L2 loss: 0.6259 Learning rate: 0.002 Mask loss: 0.13169 RPN box loss: 0.02481 RPN score loss: 0.00631 RPN total loss: 0.03112 Total loss: 0.96502 timestamp: 1654947718.716696 iteration: 42125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08526 FastRCNN class loss: 0.0929 FastRCNN total loss: 0.17817 L1 loss: 0.0000e+00 L2 loss: 0.62589 Learning rate: 0.002 Mask loss: 0.13435 RPN box loss: 0.0237 RPN score loss: 0.00847 RPN total loss: 0.03216 Total loss: 0.97058 timestamp: 1654947721.9921453 iteration: 42130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.05723 FastRCNN total loss: 0.17286 L1 loss: 0.0000e+00 L2 loss: 0.62589 Learning rate: 0.002 Mask loss: 0.08391 RPN box loss: 0.00918 RPN score loss: 0.00211 RPN total loss: 0.01129 Total loss: 0.89395 timestamp: 1654947725.1743276 iteration: 42135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.15149 L1 loss: 0.0000e+00 L2 loss: 0.62588 Learning rate: 0.002 Mask loss: 0.11204 RPN box loss: 0.01311 RPN score loss: 0.00306 RPN total loss: 0.01617 Total loss: 0.90557 timestamp: 1654947728.4515398 iteration: 42140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.09748 FastRCNN total loss: 0.22146 L1 loss: 0.0000e+00 L2 loss: 0.62587 Learning rate: 0.002 Mask loss: 0.14857 RPN box loss: 0.02079 RPN score loss: 0.00635 RPN total loss: 0.02714 Total loss: 1.02304 timestamp: 1654947731.6295013 iteration: 42145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18931 FastRCNN class loss: 0.09831 FastRCNN total loss: 0.28762 L1 loss: 0.0000e+00 L2 loss: 0.62586 Learning rate: 0.002 Mask loss: 0.19779 RPN box loss: 0.032 RPN score loss: 0.01134 RPN total loss: 0.04334 Total loss: 1.15462 timestamp: 1654947734.8387575 iteration: 42150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12548 FastRCNN class loss: 0.11887 FastRCNN total loss: 0.24436 L1 loss: 0.0000e+00 L2 loss: 0.62585 Learning rate: 0.002 Mask loss: 0.11287 RPN box loss: 0.03524 RPN score loss: 0.0079 RPN total loss: 0.04314 Total loss: 1.02623 timestamp: 1654947738.019904 iteration: 42155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10645 FastRCNN class loss: 0.0693 FastRCNN total loss: 0.17575 L1 loss: 0.0000e+00 L2 loss: 0.62584 Learning rate: 0.002 Mask loss: 0.14198 RPN box loss: 0.02619 RPN score loss: 0.00197 RPN total loss: 0.02815 Total loss: 0.97173 timestamp: 1654947741.2809703 iteration: 42160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04615 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.12133 L1 loss: 0.0000e+00 L2 loss: 0.62583 Learning rate: 0.002 Mask loss: 0.08604 RPN box loss: 0.02661 RPN score loss: 0.00985 RPN total loss: 0.03646 Total loss: 0.86966 timestamp: 1654947744.5198734 iteration: 42165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10905 FastRCNN class loss: 0.05817 FastRCNN total loss: 0.16722 L1 loss: 0.0000e+00 L2 loss: 0.62582 Learning rate: 0.002 Mask loss: 0.15135 RPN box loss: 0.01162 RPN score loss: 0.00724 RPN total loss: 0.01886 Total loss: 0.96325 timestamp: 1654947747.7266517 iteration: 42170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14618 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.21435 L1 loss: 0.0000e+00 L2 loss: 0.62581 Learning rate: 0.002 Mask loss: 0.13876 RPN box loss: 0.0492 RPN score loss: 0.00659 RPN total loss: 0.05579 Total loss: 1.03471 timestamp: 1654947750.9028685 iteration: 42175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06751 FastRCNN class loss: 0.06432 FastRCNN total loss: 0.13183 L1 loss: 0.0000e+00 L2 loss: 0.6258 Learning rate: 0.002 Mask loss: 0.12171 RPN box loss: 0.01406 RPN score loss: 0.00353 RPN total loss: 0.01759 Total loss: 0.89693 timestamp: 1654947754.0543604 iteration: 42180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16488 FastRCNN class loss: 0.17659 FastRCNN total loss: 0.34147 L1 loss: 0.0000e+00 L2 loss: 0.6258 Learning rate: 0.002 Mask loss: 0.11838 RPN box loss: 0.02264 RPN score loss: 0.00381 RPN total loss: 0.02645 Total loss: 1.1121 timestamp: 1654947757.2573607 iteration: 42185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07559 FastRCNN class loss: 0.03977 FastRCNN total loss: 0.11536 L1 loss: 0.0000e+00 L2 loss: 0.62579 Learning rate: 0.002 Mask loss: 0.11705 RPN box loss: 0.00568 RPN score loss: 0.00593 RPN total loss: 0.01162 Total loss: 0.86981 timestamp: 1654947760.4849784 iteration: 42190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12544 FastRCNN class loss: 0.07586 FastRCNN total loss: 0.2013 L1 loss: 0.0000e+00 L2 loss: 0.62578 Learning rate: 0.002 Mask loss: 0.11708 RPN box loss: 0.01123 RPN score loss: 0.00711 RPN total loss: 0.01834 Total loss: 0.96251 timestamp: 1654947763.6468856 iteration: 42195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13785 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.19892 L1 loss: 0.0000e+00 L2 loss: 0.62577 Learning rate: 0.002 Mask loss: 0.23405 RPN box loss: 0.01468 RPN score loss: 0.00524 RPN total loss: 0.01992 Total loss: 1.07866 timestamp: 1654947766.8264577 iteration: 42200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05483 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.12381 L1 loss: 0.0000e+00 L2 loss: 0.62576 Learning rate: 0.002 Mask loss: 0.09316 RPN box loss: 0.00875 RPN score loss: 0.00298 RPN total loss: 0.01173 Total loss: 0.85446 timestamp: 1654947770.0535073 iteration: 42205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06824 FastRCNN class loss: 0.03409 FastRCNN total loss: 0.10233 L1 loss: 0.0000e+00 L2 loss: 0.62575 Learning rate: 0.002 Mask loss: 0.1149 RPN box loss: 0.02889 RPN score loss: 0.0025 RPN total loss: 0.03139 Total loss: 0.87437 timestamp: 1654947773.1886423 iteration: 42210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11638 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.21692 L1 loss: 0.0000e+00 L2 loss: 0.62574 Learning rate: 0.002 Mask loss: 0.20862 RPN box loss: 0.03357 RPN score loss: 0.01878 RPN total loss: 0.05235 Total loss: 1.10362 timestamp: 1654947776.4128616 iteration: 42215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08564 FastRCNN class loss: 0.10418 FastRCNN total loss: 0.18981 L1 loss: 0.0000e+00 L2 loss: 0.62573 Learning rate: 0.002 Mask loss: 0.18176 RPN box loss: 0.01688 RPN score loss: 0.00489 RPN total loss: 0.02177 Total loss: 1.01907 timestamp: 1654947779.621161 iteration: 42220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08739 FastRCNN class loss: 0.06423 FastRCNN total loss: 0.15162 L1 loss: 0.0000e+00 L2 loss: 0.62572 Learning rate: 0.002 Mask loss: 0.10182 RPN box loss: 0.01726 RPN score loss: 0.00573 RPN total loss: 0.02299 Total loss: 0.90215 timestamp: 1654947782.86679 iteration: 42225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14508 FastRCNN class loss: 0.07468 FastRCNN total loss: 0.21975 L1 loss: 0.0000e+00 L2 loss: 0.6257 Learning rate: 0.002 Mask loss: 0.11585 RPN box loss: 0.04818 RPN score loss: 0.01333 RPN total loss: 0.06151 Total loss: 1.02282 timestamp: 1654947786.0462894 iteration: 42230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16979 FastRCNN class loss: 0.05502 FastRCNN total loss: 0.22481 L1 loss: 0.0000e+00 L2 loss: 0.62569 Learning rate: 0.002 Mask loss: 0.13762 RPN box loss: 0.01548 RPN score loss: 0.00328 RPN total loss: 0.01875 Total loss: 1.00687 timestamp: 1654947789.3142467 iteration: 42235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08471 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.1646 L1 loss: 0.0000e+00 L2 loss: 0.62568 Learning rate: 0.002 Mask loss: 0.09695 RPN box loss: 0.02191 RPN score loss: 0.00964 RPN total loss: 0.03155 Total loss: 0.91879 timestamp: 1654947792.4634712 iteration: 42240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11731 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.20133 L1 loss: 0.0000e+00 L2 loss: 0.62568 Learning rate: 0.002 Mask loss: 0.19715 RPN box loss: 0.01288 RPN score loss: 0.00313 RPN total loss: 0.01601 Total loss: 1.04017 timestamp: 1654947795.682912 iteration: 42245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06352 FastRCNN class loss: 0.05001 FastRCNN total loss: 0.11353 L1 loss: 0.0000e+00 L2 loss: 0.62567 Learning rate: 0.002 Mask loss: 0.13452 RPN box loss: 0.01009 RPN score loss: 0.00256 RPN total loss: 0.01265 Total loss: 0.88637 timestamp: 1654947798.8584802 iteration: 42250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15125 FastRCNN class loss: 0.07395 FastRCNN total loss: 0.2252 L1 loss: 0.0000e+00 L2 loss: 0.62566 Learning rate: 0.002 Mask loss: 0.11486 RPN box loss: 0.06126 RPN score loss: 0.00392 RPN total loss: 0.06518 Total loss: 1.0309 timestamp: 1654947801.9744577 iteration: 42255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06572 FastRCNN class loss: 0.0395 FastRCNN total loss: 0.10523 L1 loss: 0.0000e+00 L2 loss: 0.62565 Learning rate: 0.002 Mask loss: 0.11853 RPN box loss: 0.01139 RPN score loss: 0.00607 RPN total loss: 0.01746 Total loss: 0.86687 timestamp: 1654947805.1754923 iteration: 42260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16941 FastRCNN class loss: 0.1331 FastRCNN total loss: 0.30252 L1 loss: 0.0000e+00 L2 loss: 0.62564 Learning rate: 0.002 Mask loss: 0.21466 RPN box loss: 0.02256 RPN score loss: 0.00775 RPN total loss: 0.03031 Total loss: 1.17313 timestamp: 1654947808.3127844 iteration: 42265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12531 FastRCNN class loss: 0.0905 FastRCNN total loss: 0.21581 L1 loss: 0.0000e+00 L2 loss: 0.62563 Learning rate: 0.002 Mask loss: 0.12012 RPN box loss: 0.03989 RPN score loss: 0.00756 RPN total loss: 0.04745 Total loss: 1.00901 timestamp: 1654947811.6115115 iteration: 42270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12733 FastRCNN class loss: 0.04771 FastRCNN total loss: 0.17504 L1 loss: 0.0000e+00 L2 loss: 0.62561 Learning rate: 0.002 Mask loss: 0.12046 RPN box loss: 0.02169 RPN score loss: 0.00386 RPN total loss: 0.02555 Total loss: 0.94667 timestamp: 1654947814.7745564 iteration: 42275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04887 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.11037 L1 loss: 0.0000e+00 L2 loss: 0.6256 Learning rate: 0.002 Mask loss: 0.09679 RPN box loss: 0.00686 RPN score loss: 0.01038 RPN total loss: 0.01724 Total loss: 0.85001 timestamp: 1654947817.9055533 iteration: 42280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06943 FastRCNN class loss: 0.07034 FastRCNN total loss: 0.13977 L1 loss: 0.0000e+00 L2 loss: 0.62559 Learning rate: 0.002 Mask loss: 0.10596 RPN box loss: 0.01457 RPN score loss: 0.0031 RPN total loss: 0.01767 Total loss: 0.88899 timestamp: 1654947821.0813842 iteration: 42285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1129 FastRCNN class loss: 0.08354 FastRCNN total loss: 0.19644 L1 loss: 0.0000e+00 L2 loss: 0.62559 Learning rate: 0.002 Mask loss: 0.12814 RPN box loss: 0.01367 RPN score loss: 0.00409 RPN total loss: 0.01776 Total loss: 0.96793 timestamp: 1654947824.24989 iteration: 42290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15732 FastRCNN class loss: 0.06251 FastRCNN total loss: 0.21983 L1 loss: 0.0000e+00 L2 loss: 0.62558 Learning rate: 0.002 Mask loss: 0.12221 RPN box loss: 0.00775 RPN score loss: 0.00277 RPN total loss: 0.01051 Total loss: 0.97814 timestamp: 1654947827.4078147 iteration: 42295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18342 FastRCNN class loss: 0.06499 FastRCNN total loss: 0.24842 L1 loss: 0.0000e+00 L2 loss: 0.62557 Learning rate: 0.002 Mask loss: 0.15174 RPN box loss: 0.01239 RPN score loss: 0.00273 RPN total loss: 0.01512 Total loss: 1.04085 timestamp: 1654947830.6159198 iteration: 42300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14703 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.22692 L1 loss: 0.0000e+00 L2 loss: 0.62556 Learning rate: 0.002 Mask loss: 0.11265 RPN box loss: 0.00462 RPN score loss: 0.00112 RPN total loss: 0.00574 Total loss: 0.97088 timestamp: 1654947833.8345702 iteration: 42305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08484 FastRCNN class loss: 0.07952 FastRCNN total loss: 0.16436 L1 loss: 0.0000e+00 L2 loss: 0.62555 Learning rate: 0.002 Mask loss: 0.15 RPN box loss: 0.01781 RPN score loss: 0.00835 RPN total loss: 0.02616 Total loss: 0.96607 timestamp: 1654947836.9835713 iteration: 42310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03862 FastRCNN class loss: 0.04862 FastRCNN total loss: 0.08724 L1 loss: 0.0000e+00 L2 loss: 0.62554 Learning rate: 0.002 Mask loss: 0.08755 RPN box loss: 0.0136 RPN score loss: 0.0029 RPN total loss: 0.0165 Total loss: 0.81683 timestamp: 1654947840.2148259 iteration: 42315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10373 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.17972 L1 loss: 0.0000e+00 L2 loss: 0.62553 Learning rate: 0.002 Mask loss: 0.09618 RPN box loss: 0.0262 RPN score loss: 0.00483 RPN total loss: 0.03103 Total loss: 0.93246 timestamp: 1654947843.4422853 iteration: 42320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16011 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.24474 L1 loss: 0.0000e+00 L2 loss: 0.62552 Learning rate: 0.002 Mask loss: 0.14102 RPN box loss: 0.01859 RPN score loss: 0.00882 RPN total loss: 0.02741 Total loss: 1.0387 timestamp: 1654947846.565183 iteration: 42325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10477 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.16096 L1 loss: 0.0000e+00 L2 loss: 0.62551 Learning rate: 0.002 Mask loss: 0.12315 RPN box loss: 0.01504 RPN score loss: 0.0032 RPN total loss: 0.01824 Total loss: 0.92787 timestamp: 1654947849.7939663 iteration: 42330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08769 FastRCNN class loss: 0.06828 FastRCNN total loss: 0.15598 L1 loss: 0.0000e+00 L2 loss: 0.6255 Learning rate: 0.002 Mask loss: 0.14371 RPN box loss: 0.01776 RPN score loss: 0.004 RPN total loss: 0.02176 Total loss: 0.94695 timestamp: 1654947852.9431705 iteration: 42335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11171 FastRCNN class loss: 0.05008 FastRCNN total loss: 0.16179 L1 loss: 0.0000e+00 L2 loss: 0.62549 Learning rate: 0.002 Mask loss: 0.10726 RPN box loss: 0.03587 RPN score loss: 0.00965 RPN total loss: 0.04552 Total loss: 0.94007 timestamp: 1654947856.0604255 iteration: 42340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09283 FastRCNN class loss: 0.08373 FastRCNN total loss: 0.17656 L1 loss: 0.0000e+00 L2 loss: 0.62548 Learning rate: 0.002 Mask loss: 0.10163 RPN box loss: 0.00658 RPN score loss: 0.00585 RPN total loss: 0.01242 Total loss: 0.9161 timestamp: 1654947859.2661986 iteration: 42345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07547 FastRCNN class loss: 0.05141 FastRCNN total loss: 0.12687 L1 loss: 0.0000e+00 L2 loss: 0.62547 Learning rate: 0.002 Mask loss: 0.14858 RPN box loss: 0.00584 RPN score loss: 0.00727 RPN total loss: 0.0131 Total loss: 0.91402 timestamp: 1654947862.3985078 iteration: 42350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11611 FastRCNN class loss: 0.08794 FastRCNN total loss: 0.20405 L1 loss: 0.0000e+00 L2 loss: 0.62546 Learning rate: 0.002 Mask loss: 0.09724 RPN box loss: 0.01518 RPN score loss: 0.00773 RPN total loss: 0.02292 Total loss: 0.94968 timestamp: 1654947865.6149714 iteration: 42355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16864 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.25621 L1 loss: 0.0000e+00 L2 loss: 0.62546 Learning rate: 0.002 Mask loss: 0.13995 RPN box loss: 0.02986 RPN score loss: 0.01277 RPN total loss: 0.04263 Total loss: 1.06425 timestamp: 1654947868.7367115 iteration: 42360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04858 FastRCNN class loss: 0.03417 FastRCNN total loss: 0.08275 L1 loss: 0.0000e+00 L2 loss: 0.62545 Learning rate: 0.002 Mask loss: 0.23495 RPN box loss: 0.03759 RPN score loss: 0.00476 RPN total loss: 0.04235 Total loss: 0.9855 timestamp: 1654947871.9382207 iteration: 42365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05119 FastRCNN class loss: 0.0336 FastRCNN total loss: 0.08479 L1 loss: 0.0000e+00 L2 loss: 0.62544 Learning rate: 0.002 Mask loss: 0.09033 RPN box loss: 0.06384 RPN score loss: 0.00313 RPN total loss: 0.06697 Total loss: 0.86752 timestamp: 1654947875.1711059 iteration: 42370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06899 FastRCNN class loss: 0.05348 FastRCNN total loss: 0.12247 L1 loss: 0.0000e+00 L2 loss: 0.62543 Learning rate: 0.002 Mask loss: 0.1147 RPN box loss: 0.0252 RPN score loss: 0.00443 RPN total loss: 0.02963 Total loss: 0.89223 timestamp: 1654947878.4088874 iteration: 42375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12059 FastRCNN class loss: 0.0709 FastRCNN total loss: 0.19149 L1 loss: 0.0000e+00 L2 loss: 0.62542 Learning rate: 0.002 Mask loss: 0.18119 RPN box loss: 0.02222 RPN score loss: 0.00501 RPN total loss: 0.02723 Total loss: 1.02533 timestamp: 1654947881.5182958 iteration: 42380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07324 FastRCNN class loss: 0.06593 FastRCNN total loss: 0.13917 L1 loss: 0.0000e+00 L2 loss: 0.62541 Learning rate: 0.002 Mask loss: 0.08998 RPN box loss: 0.00988 RPN score loss: 0.00152 RPN total loss: 0.0114 Total loss: 0.86596 timestamp: 1654947884.7531726 iteration: 42385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11931 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.19828 L1 loss: 0.0000e+00 L2 loss: 0.6254 Learning rate: 0.002 Mask loss: 0.12715 RPN box loss: 0.03824 RPN score loss: 0.00679 RPN total loss: 0.04503 Total loss: 0.99586 timestamp: 1654947887.9955533 iteration: 42390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09169 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.15211 L1 loss: 0.0000e+00 L2 loss: 0.62538 Learning rate: 0.002 Mask loss: 0.12464 RPN box loss: 0.02283 RPN score loss: 0.00141 RPN total loss: 0.02424 Total loss: 0.92637 timestamp: 1654947891.180512 iteration: 42395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.04904 FastRCNN total loss: 0.16375 L1 loss: 0.0000e+00 L2 loss: 0.62537 Learning rate: 0.002 Mask loss: 0.10034 RPN box loss: 0.02418 RPN score loss: 0.00898 RPN total loss: 0.03316 Total loss: 0.92262 timestamp: 1654947894.3894978 iteration: 42400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10114 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.17102 L1 loss: 0.0000e+00 L2 loss: 0.62536 Learning rate: 0.002 Mask loss: 0.09941 RPN box loss: 0.05459 RPN score loss: 0.01206 RPN total loss: 0.06665 Total loss: 0.96245 timestamp: 1654947897.6567302 iteration: 42405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13254 FastRCNN class loss: 0.08531 FastRCNN total loss: 0.21785 L1 loss: 0.0000e+00 L2 loss: 0.62535 Learning rate: 0.002 Mask loss: 0.15106 RPN box loss: 0.00898 RPN score loss: 0.00457 RPN total loss: 0.01355 Total loss: 1.00781 timestamp: 1654947900.8927867 iteration: 42410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11274 FastRCNN class loss: 0.10165 FastRCNN total loss: 0.21439 L1 loss: 0.0000e+00 L2 loss: 0.62534 Learning rate: 0.002 Mask loss: 0.16902 RPN box loss: 0.02846 RPN score loss: 0.00416 RPN total loss: 0.03262 Total loss: 1.04137 timestamp: 1654947904.1025016 iteration: 42415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11146 FastRCNN class loss: 0.06485 FastRCNN total loss: 0.17631 L1 loss: 0.0000e+00 L2 loss: 0.62533 Learning rate: 0.002 Mask loss: 0.10505 RPN box loss: 0.02837 RPN score loss: 0.0029 RPN total loss: 0.03128 Total loss: 0.93797 timestamp: 1654947907.3371058 iteration: 42420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07976 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.14846 L1 loss: 0.0000e+00 L2 loss: 0.62532 Learning rate: 0.002 Mask loss: 0.1279 RPN box loss: 0.01685 RPN score loss: 0.01343 RPN total loss: 0.03028 Total loss: 0.93197 timestamp: 1654947910.5384252 iteration: 42425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11631 FastRCNN class loss: 0.09076 FastRCNN total loss: 0.20707 L1 loss: 0.0000e+00 L2 loss: 0.62531 Learning rate: 0.002 Mask loss: 0.15978 RPN box loss: 0.05735 RPN score loss: 0.01574 RPN total loss: 0.07309 Total loss: 1.06526 timestamp: 1654947913.7273476 iteration: 42430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09362 FastRCNN class loss: 0.08245 FastRCNN total loss: 0.17608 L1 loss: 0.0000e+00 L2 loss: 0.6253 Learning rate: 0.002 Mask loss: 0.1162 RPN box loss: 0.01605 RPN score loss: 0.00326 RPN total loss: 0.01931 Total loss: 0.93689 timestamp: 1654947916.9779694 iteration: 42435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10761 FastRCNN class loss: 0.04739 FastRCNN total loss: 0.155 L1 loss: 0.0000e+00 L2 loss: 0.62529 Learning rate: 0.002 Mask loss: 0.09778 RPN box loss: 0.01281 RPN score loss: 0.00068 RPN total loss: 0.0135 Total loss: 0.89158 timestamp: 1654947920.1707516 iteration: 42440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11893 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.1843 L1 loss: 0.0000e+00 L2 loss: 0.62529 Learning rate: 0.002 Mask loss: 0.20426 RPN box loss: 0.01814 RPN score loss: 0.00463 RPN total loss: 0.02277 Total loss: 1.03661 timestamp: 1654947923.3729358 iteration: 42445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.07835 FastRCNN total loss: 0.2183 L1 loss: 0.0000e+00 L2 loss: 0.62528 Learning rate: 0.002 Mask loss: 0.15854 RPN box loss: 0.0178 RPN score loss: 0.00585 RPN total loss: 0.02365 Total loss: 1.02577 timestamp: 1654947926.5978851 iteration: 42450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07667 FastRCNN class loss: 0.09614 FastRCNN total loss: 0.17281 L1 loss: 0.0000e+00 L2 loss: 0.62527 Learning rate: 0.002 Mask loss: 0.13701 RPN box loss: 0.02887 RPN score loss: 0.01484 RPN total loss: 0.0437 Total loss: 0.97879 timestamp: 1654947929.81008 iteration: 42455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07933 FastRCNN class loss: 0.05662 FastRCNN total loss: 0.13595 L1 loss: 0.0000e+00 L2 loss: 0.62526 Learning rate: 0.002 Mask loss: 0.14103 RPN box loss: 0.01674 RPN score loss: 0.00196 RPN total loss: 0.01869 Total loss: 0.92093 timestamp: 1654947933.0257244 iteration: 42460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10885 FastRCNN class loss: 0.065 FastRCNN total loss: 0.17385 L1 loss: 0.0000e+00 L2 loss: 0.62525 Learning rate: 0.002 Mask loss: 0.214 RPN box loss: 0.01178 RPN score loss: 0.00379 RPN total loss: 0.01557 Total loss: 1.02868 timestamp: 1654947936.2783449 iteration: 42465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08741 FastRCNN class loss: 0.06249 FastRCNN total loss: 0.14991 L1 loss: 0.0000e+00 L2 loss: 0.62524 Learning rate: 0.002 Mask loss: 0.09997 RPN box loss: 0.03047 RPN score loss: 0.00499 RPN total loss: 0.03546 Total loss: 0.91058 timestamp: 1654947939.5036526 iteration: 42470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13951 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.21552 L1 loss: 0.0000e+00 L2 loss: 0.62523 Learning rate: 0.002 Mask loss: 0.14162 RPN box loss: 0.01192 RPN score loss: 0.0029 RPN total loss: 0.01482 Total loss: 0.99719 timestamp: 1654947942.7091653 iteration: 42475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16333 FastRCNN class loss: 0.09348 FastRCNN total loss: 0.2568 L1 loss: 0.0000e+00 L2 loss: 0.62522 Learning rate: 0.002 Mask loss: 0.18142 RPN box loss: 0.00945 RPN score loss: 0.00217 RPN total loss: 0.01161 Total loss: 1.07505 timestamp: 1654947945.873878 iteration: 42480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11585 FastRCNN class loss: 0.08578 FastRCNN total loss: 0.20163 L1 loss: 0.0000e+00 L2 loss: 0.62521 Learning rate: 0.002 Mask loss: 0.16094 RPN box loss: 0.04789 RPN score loss: 0.00888 RPN total loss: 0.05676 Total loss: 1.04454 timestamp: 1654947949.0832632 iteration: 42485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07783 FastRCNN class loss: 0.06296 FastRCNN total loss: 0.14078 L1 loss: 0.0000e+00 L2 loss: 0.6252 Learning rate: 0.002 Mask loss: 0.0935 RPN box loss: 0.03954 RPN score loss: 0.00805 RPN total loss: 0.04759 Total loss: 0.90708 timestamp: 1654947952.37038 iteration: 42490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10573 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.16924 L1 loss: 0.0000e+00 L2 loss: 0.6252 Learning rate: 0.002 Mask loss: 0.08293 RPN box loss: 0.01155 RPN score loss: 0.00194 RPN total loss: 0.0135 Total loss: 0.89086 timestamp: 1654947955.580708 iteration: 42495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11143 FastRCNN class loss: 0.05725 FastRCNN total loss: 0.16868 L1 loss: 0.0000e+00 L2 loss: 0.62519 Learning rate: 0.002 Mask loss: 0.08538 RPN box loss: 0.00836 RPN score loss: 0.00367 RPN total loss: 0.01203 Total loss: 0.89128 timestamp: 1654947958.7684824 iteration: 42500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0796 FastRCNN class loss: 0.09441 FastRCNN total loss: 0.17401 L1 loss: 0.0000e+00 L2 loss: 0.62518 Learning rate: 0.002 Mask loss: 0.07715 RPN box loss: 0.02096 RPN score loss: 0.00648 RPN total loss: 0.02745 Total loss: 0.90378 timestamp: 1654947961.9224668 iteration: 42505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08747 FastRCNN class loss: 0.08142 FastRCNN total loss: 0.16889 L1 loss: 0.0000e+00 L2 loss: 0.62517 Learning rate: 0.002 Mask loss: 0.14244 RPN box loss: 0.01322 RPN score loss: 0.00219 RPN total loss: 0.01541 Total loss: 0.95191 timestamp: 1654947965.1402493 iteration: 42510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06646 FastRCNN class loss: 0.07061 FastRCNN total loss: 0.13707 L1 loss: 0.0000e+00 L2 loss: 0.62516 Learning rate: 0.002 Mask loss: 0.11363 RPN box loss: 0.02231 RPN score loss: 0.00455 RPN total loss: 0.02686 Total loss: 0.90272 timestamp: 1654947968.270527 iteration: 42515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14457 FastRCNN class loss: 0.11832 FastRCNN total loss: 0.26289 L1 loss: 0.0000e+00 L2 loss: 0.62515 Learning rate: 0.002 Mask loss: 0.19524 RPN box loss: 0.03912 RPN score loss: 0.00848 RPN total loss: 0.04759 Total loss: 1.13087 timestamp: 1654947971.4829314 iteration: 42520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10324 FastRCNN class loss: 0.05823 FastRCNN total loss: 0.16147 L1 loss: 0.0000e+00 L2 loss: 0.62514 Learning rate: 0.002 Mask loss: 0.15764 RPN box loss: 0.03325 RPN score loss: 0.00669 RPN total loss: 0.03994 Total loss: 0.98418 timestamp: 1654947974.6631548 iteration: 42525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09083 FastRCNN class loss: 0.09447 FastRCNN total loss: 0.1853 L1 loss: 0.0000e+00 L2 loss: 0.62513 Learning rate: 0.002 Mask loss: 0.14374 RPN box loss: 0.03143 RPN score loss: 0.00802 RPN total loss: 0.03945 Total loss: 0.99363 timestamp: 1654947977.8663292 iteration: 42530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.05449 FastRCNN total loss: 0.13765 L1 loss: 0.0000e+00 L2 loss: 0.62512 Learning rate: 0.002 Mask loss: 0.11628 RPN box loss: 0.01066 RPN score loss: 0.00188 RPN total loss: 0.01253 Total loss: 0.89159 timestamp: 1654947981.1013894 iteration: 42535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12654 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.19367 L1 loss: 0.0000e+00 L2 loss: 0.62511 Learning rate: 0.002 Mask loss: 0.13342 RPN box loss: 0.01387 RPN score loss: 0.00745 RPN total loss: 0.02132 Total loss: 0.97352 timestamp: 1654947984.352146 iteration: 42540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1096 FastRCNN class loss: 0.0938 FastRCNN total loss: 0.20341 L1 loss: 0.0000e+00 L2 loss: 0.6251 Learning rate: 0.002 Mask loss: 0.19486 RPN box loss: 0.03214 RPN score loss: 0.0042 RPN total loss: 0.03634 Total loss: 1.05971 timestamp: 1654947987.5124645 iteration: 42545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06474 FastRCNN class loss: 0.0466 FastRCNN total loss: 0.11134 L1 loss: 0.0000e+00 L2 loss: 0.62509 Learning rate: 0.002 Mask loss: 0.14524 RPN box loss: 0.04892 RPN score loss: 0.00678 RPN total loss: 0.0557 Total loss: 0.93738 timestamp: 1654947990.6572244 iteration: 42550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10471 FastRCNN class loss: 0.05868 FastRCNN total loss: 0.16339 L1 loss: 0.0000e+00 L2 loss: 0.62508 Learning rate: 0.002 Mask loss: 0.1247 RPN box loss: 0.00856 RPN score loss: 0.00213 RPN total loss: 0.01068 Total loss: 0.92385 timestamp: 1654947993.766132 iteration: 42555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11639 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.18629 L1 loss: 0.0000e+00 L2 loss: 0.62507 Learning rate: 0.002 Mask loss: 0.19511 RPN box loss: 0.05028 RPN score loss: 0.00798 RPN total loss: 0.05826 Total loss: 1.06473 timestamp: 1654947996.936383 iteration: 42560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08602 FastRCNN class loss: 0.1165 FastRCNN total loss: 0.20252 L1 loss: 0.0000e+00 L2 loss: 0.62506 Learning rate: 0.002 Mask loss: 0.1443 RPN box loss: 0.02421 RPN score loss: 0.00503 RPN total loss: 0.02924 Total loss: 1.00113 timestamp: 1654948000.11478 iteration: 42565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14719 FastRCNN class loss: 0.10402 FastRCNN total loss: 0.25121 L1 loss: 0.0000e+00 L2 loss: 0.62505 Learning rate: 0.002 Mask loss: 0.15548 RPN box loss: 0.02112 RPN score loss: 0.00374 RPN total loss: 0.02486 Total loss: 1.0566 timestamp: 1654948003.3073797 iteration: 42570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09823 FastRCNN class loss: 0.04875 FastRCNN total loss: 0.14698 L1 loss: 0.0000e+00 L2 loss: 0.62504 Learning rate: 0.002 Mask loss: 0.09263 RPN box loss: 0.01133 RPN score loss: 0.00252 RPN total loss: 0.01385 Total loss: 0.8785 timestamp: 1654948006.5378816 iteration: 42575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08299 FastRCNN class loss: 0.06034 FastRCNN total loss: 0.14333 L1 loss: 0.0000e+00 L2 loss: 0.62503 Learning rate: 0.002 Mask loss: 0.11441 RPN box loss: 0.00878 RPN score loss: 0.00562 RPN total loss: 0.0144 Total loss: 0.89717 timestamp: 1654948009.7328205 iteration: 42580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10501 FastRCNN class loss: 0.10279 FastRCNN total loss: 0.20781 L1 loss: 0.0000e+00 L2 loss: 0.62502 Learning rate: 0.002 Mask loss: 0.1677 RPN box loss: 0.04724 RPN score loss: 0.01234 RPN total loss: 0.05958 Total loss: 1.06011 timestamp: 1654948012.8724506 iteration: 42585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14626 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.19522 L1 loss: 0.0000e+00 L2 loss: 0.62501 Learning rate: 0.002 Mask loss: 0.17215 RPN box loss: 0.02047 RPN score loss: 0.00388 RPN total loss: 0.02436 Total loss: 1.01673 timestamp: 1654948016.0501504 iteration: 42590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12459 FastRCNN class loss: 0.06366 FastRCNN total loss: 0.18825 L1 loss: 0.0000e+00 L2 loss: 0.625 Learning rate: 0.002 Mask loss: 0.09195 RPN box loss: 0.01135 RPN score loss: 0.00661 RPN total loss: 0.01796 Total loss: 0.92315 timestamp: 1654948019.186577 iteration: 42595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15024 FastRCNN class loss: 0.12299 FastRCNN total loss: 0.27323 L1 loss: 0.0000e+00 L2 loss: 0.62499 Learning rate: 0.002 Mask loss: 0.14219 RPN box loss: 0.03076 RPN score loss: 0.01062 RPN total loss: 0.04138 Total loss: 1.08179 timestamp: 1654948022.39796 iteration: 42600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10155 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.15433 L1 loss: 0.0000e+00 L2 loss: 0.62498 Learning rate: 0.002 Mask loss: 0.15084 RPN box loss: 0.01968 RPN score loss: 0.00307 RPN total loss: 0.02274 Total loss: 0.9529 timestamp: 1654948025.62229 iteration: 42605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13063 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.18869 L1 loss: 0.0000e+00 L2 loss: 0.62497 Learning rate: 0.002 Mask loss: 0.15682 RPN box loss: 0.00631 RPN score loss: 0.00102 RPN total loss: 0.00733 Total loss: 0.97781 timestamp: 1654948028.7445621 iteration: 42610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07515 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.14996 L1 loss: 0.0000e+00 L2 loss: 0.62496 Learning rate: 0.002 Mask loss: 0.08454 RPN box loss: 0.01356 RPN score loss: 0.00361 RPN total loss: 0.01717 Total loss: 0.87663 timestamp: 1654948031.914558 iteration: 42615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07483 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.14352 L1 loss: 0.0000e+00 L2 loss: 0.62495 Learning rate: 0.002 Mask loss: 0.18364 RPN box loss: 0.00854 RPN score loss: 0.00787 RPN total loss: 0.01641 Total loss: 0.96852 timestamp: 1654948035.1035624 iteration: 42620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.05772 FastRCNN total loss: 0.13637 L1 loss: 0.0000e+00 L2 loss: 0.62494 Learning rate: 0.002 Mask loss: 0.21614 RPN box loss: 0.014 RPN score loss: 0.00214 RPN total loss: 0.01614 Total loss: 0.9936 timestamp: 1654948038.2818248 iteration: 42625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10695 FastRCNN class loss: 0.06431 FastRCNN total loss: 0.17126 L1 loss: 0.0000e+00 L2 loss: 0.62493 Learning rate: 0.002 Mask loss: 0.13348 RPN box loss: 0.01159 RPN score loss: 0.0056 RPN total loss: 0.01719 Total loss: 0.94687 timestamp: 1654948041.476455 iteration: 42630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06949 FastRCNN class loss: 0.07961 FastRCNN total loss: 0.1491 L1 loss: 0.0000e+00 L2 loss: 0.62492 Learning rate: 0.002 Mask loss: 0.12071 RPN box loss: 0.01036 RPN score loss: 0.00332 RPN total loss: 0.01367 Total loss: 0.9084 timestamp: 1654948044.7063692 iteration: 42635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06206 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.12101 L1 loss: 0.0000e+00 L2 loss: 0.62492 Learning rate: 0.002 Mask loss: 0.08483 RPN box loss: 0.00912 RPN score loss: 0.00227 RPN total loss: 0.01139 Total loss: 0.84214 timestamp: 1654948047.927718 iteration: 42640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14411 FastRCNN class loss: 0.0838 FastRCNN total loss: 0.22791 L1 loss: 0.0000e+00 L2 loss: 0.62491 Learning rate: 0.002 Mask loss: 0.12925 RPN box loss: 0.02185 RPN score loss: 0.00445 RPN total loss: 0.0263 Total loss: 1.00836 timestamp: 1654948051.1383007 iteration: 42645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06338 FastRCNN class loss: 0.03885 FastRCNN total loss: 0.10223 L1 loss: 0.0000e+00 L2 loss: 0.6249 Learning rate: 0.002 Mask loss: 0.08513 RPN box loss: 0.01976 RPN score loss: 0.00756 RPN total loss: 0.02732 Total loss: 0.83958 timestamp: 1654948054.302753 iteration: 42650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11201 FastRCNN class loss: 0.05459 FastRCNN total loss: 0.1666 L1 loss: 0.0000e+00 L2 loss: 0.62489 Learning rate: 0.002 Mask loss: 0.10571 RPN box loss: 0.00611 RPN score loss: 0.003 RPN total loss: 0.00911 Total loss: 0.9063 timestamp: 1654948057.501677 iteration: 42655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06837 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.13543 L1 loss: 0.0000e+00 L2 loss: 0.62488 Learning rate: 0.002 Mask loss: 0.13067 RPN box loss: 0.00979 RPN score loss: 0.004 RPN total loss: 0.01379 Total loss: 0.90476 timestamp: 1654948060.7314963 iteration: 42660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1189 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.19886 L1 loss: 0.0000e+00 L2 loss: 0.62487 Learning rate: 0.002 Mask loss: 0.14755 RPN box loss: 0.0161 RPN score loss: 0.00267 RPN total loss: 0.01877 Total loss: 0.99005 timestamp: 1654948063.9322793 iteration: 42665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1308 FastRCNN class loss: 0.09454 FastRCNN total loss: 0.22534 L1 loss: 0.0000e+00 L2 loss: 0.62486 Learning rate: 0.002 Mask loss: 0.1301 RPN box loss: 0.03315 RPN score loss: 0.01027 RPN total loss: 0.04342 Total loss: 1.02372 timestamp: 1654948067.121802 iteration: 42670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08669 FastRCNN class loss: 0.06673 FastRCNN total loss: 0.15342 L1 loss: 0.0000e+00 L2 loss: 0.62485 Learning rate: 0.002 Mask loss: 0.156 RPN box loss: 0.02438 RPN score loss: 0.00876 RPN total loss: 0.03314 Total loss: 0.96741 timestamp: 1654948070.3181112 iteration: 42675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11103 FastRCNN class loss: 0.06422 FastRCNN total loss: 0.17525 L1 loss: 0.0000e+00 L2 loss: 0.62484 Learning rate: 0.002 Mask loss: 0.13332 RPN box loss: 0.00662 RPN score loss: 0.00627 RPN total loss: 0.01289 Total loss: 0.94631 timestamp: 1654948073.5527642 iteration: 42680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14239 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.21461 L1 loss: 0.0000e+00 L2 loss: 0.62483 Learning rate: 0.002 Mask loss: 0.146 RPN box loss: 0.0078 RPN score loss: 0.00634 RPN total loss: 0.01414 Total loss: 0.99957 timestamp: 1654948076.6950612 iteration: 42685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05203 FastRCNN class loss: 0.07746 FastRCNN total loss: 0.12949 L1 loss: 0.0000e+00 L2 loss: 0.62482 Learning rate: 0.002 Mask loss: 0.12958 RPN box loss: 0.03238 RPN score loss: 0.00705 RPN total loss: 0.03943 Total loss: 0.92333 timestamp: 1654948079.8853502 iteration: 42690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1036 FastRCNN class loss: 0.10903 FastRCNN total loss: 0.21263 L1 loss: 0.0000e+00 L2 loss: 0.62481 Learning rate: 0.002 Mask loss: 0.1452 RPN box loss: 0.03778 RPN score loss: 0.01133 RPN total loss: 0.04911 Total loss: 1.03175 timestamp: 1654948083.0935073 iteration: 42695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03638 FastRCNN class loss: 0.03141 FastRCNN total loss: 0.0678 L1 loss: 0.0000e+00 L2 loss: 0.6248 Learning rate: 0.002 Mask loss: 0.13971 RPN box loss: 0.02301 RPN score loss: 0.00355 RPN total loss: 0.02656 Total loss: 0.85886 timestamp: 1654948086.3252978 iteration: 42700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11919 FastRCNN class loss: 0.05131 FastRCNN total loss: 0.1705 L1 loss: 0.0000e+00 L2 loss: 0.62479 Learning rate: 0.002 Mask loss: 0.15491 RPN box loss: 0.01776 RPN score loss: 0.00395 RPN total loss: 0.02171 Total loss: 0.97191 timestamp: 1654948089.536834 iteration: 42705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10592 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.1921 L1 loss: 0.0000e+00 L2 loss: 0.62478 Learning rate: 0.002 Mask loss: 0.13119 RPN box loss: 0.01882 RPN score loss: 0.00578 RPN total loss: 0.0246 Total loss: 0.97268 timestamp: 1654948092.8493128 iteration: 42710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0618 FastRCNN class loss: 0.04126 FastRCNN total loss: 0.10306 L1 loss: 0.0000e+00 L2 loss: 0.62477 Learning rate: 0.002 Mask loss: 0.10706 RPN box loss: 0.01234 RPN score loss: 0.00236 RPN total loss: 0.0147 Total loss: 0.8496 timestamp: 1654948096.0317054 iteration: 42715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13982 FastRCNN class loss: 0.09527 FastRCNN total loss: 0.23509 L1 loss: 0.0000e+00 L2 loss: 0.62476 Learning rate: 0.002 Mask loss: 0.10892 RPN box loss: 0.0165 RPN score loss: 0.00449 RPN total loss: 0.02099 Total loss: 0.98976 timestamp: 1654948099.2466292 iteration: 42720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07257 FastRCNN class loss: 0.0715 FastRCNN total loss: 0.14407 L1 loss: 0.0000e+00 L2 loss: 0.62475 Learning rate: 0.002 Mask loss: 0.13554 RPN box loss: 0.03049 RPN score loss: 0.00955 RPN total loss: 0.04004 Total loss: 0.94441 timestamp: 1654948102.4730444 iteration: 42725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08493 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.16099 L1 loss: 0.0000e+00 L2 loss: 0.62474 Learning rate: 0.002 Mask loss: 0.14497 RPN box loss: 0.03312 RPN score loss: 0.01184 RPN total loss: 0.04497 Total loss: 0.97567 timestamp: 1654948105.6320562 iteration: 42730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1245 FastRCNN class loss: 0.04096 FastRCNN total loss: 0.16546 L1 loss: 0.0000e+00 L2 loss: 0.62473 Learning rate: 0.002 Mask loss: 0.0961 RPN box loss: 0.02442 RPN score loss: 0.00851 RPN total loss: 0.03293 Total loss: 0.91922 timestamp: 1654948108.7474961 iteration: 42735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10154 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.16323 L1 loss: 0.0000e+00 L2 loss: 0.62472 Learning rate: 0.002 Mask loss: 0.13283 RPN box loss: 0.00966 RPN score loss: 0.00538 RPN total loss: 0.01504 Total loss: 0.93581 timestamp: 1654948111.9441001 iteration: 42740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11491 FastRCNN class loss: 0.06652 FastRCNN total loss: 0.18144 L1 loss: 0.0000e+00 L2 loss: 0.62471 Learning rate: 0.002 Mask loss: 0.15193 RPN box loss: 0.05188 RPN score loss: 0.00245 RPN total loss: 0.05433 Total loss: 1.01242 timestamp: 1654948115.0983038 iteration: 42745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11629 FastRCNN class loss: 0.08385 FastRCNN total loss: 0.20014 L1 loss: 0.0000e+00 L2 loss: 0.6247 Learning rate: 0.002 Mask loss: 0.14051 RPN box loss: 0.08755 RPN score loss: 0.0023 RPN total loss: 0.08984 Total loss: 1.0552 timestamp: 1654948118.332033 iteration: 42750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14313 FastRCNN class loss: 0.06889 FastRCNN total loss: 0.21202 L1 loss: 0.0000e+00 L2 loss: 0.62469 Learning rate: 0.002 Mask loss: 0.11884 RPN box loss: 0.03017 RPN score loss: 0.00237 RPN total loss: 0.03254 Total loss: 0.98809 timestamp: 1654948121.5232565 iteration: 42755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15105 FastRCNN class loss: 0.06964 FastRCNN total loss: 0.22069 L1 loss: 0.0000e+00 L2 loss: 0.62468 Learning rate: 0.002 Mask loss: 0.18664 RPN box loss: 0.02009 RPN score loss: 0.01268 RPN total loss: 0.03277 Total loss: 1.06479 timestamp: 1654948124.774079 iteration: 42760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.09425 FastRCNN total loss: 0.2061 L1 loss: 0.0000e+00 L2 loss: 0.62467 Learning rate: 0.002 Mask loss: 0.15492 RPN box loss: 0.01761 RPN score loss: 0.00907 RPN total loss: 0.02669 Total loss: 1.01238 timestamp: 1654948127.9609935 iteration: 42765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1347 FastRCNN class loss: 0.08128 FastRCNN total loss: 0.21598 L1 loss: 0.0000e+00 L2 loss: 0.62466 Learning rate: 0.002 Mask loss: 0.14213 RPN box loss: 0.01406 RPN score loss: 0.00392 RPN total loss: 0.01799 Total loss: 1.00076 timestamp: 1654948131.2166393 iteration: 42770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06292 FastRCNN class loss: 0.06023 FastRCNN total loss: 0.12315 L1 loss: 0.0000e+00 L2 loss: 0.62465 Learning rate: 0.002 Mask loss: 0.10323 RPN box loss: 0.02667 RPN score loss: 0.00125 RPN total loss: 0.02792 Total loss: 0.87895 timestamp: 1654948134.4594984 iteration: 42775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08103 FastRCNN class loss: 0.09335 FastRCNN total loss: 0.17439 L1 loss: 0.0000e+00 L2 loss: 0.62465 Learning rate: 0.002 Mask loss: 0.1485 RPN box loss: 0.01355 RPN score loss: 0.00288 RPN total loss: 0.01642 Total loss: 0.96396 timestamp: 1654948137.6116476 iteration: 42780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07578 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.12683 L1 loss: 0.0000e+00 L2 loss: 0.62464 Learning rate: 0.002 Mask loss: 0.10504 RPN box loss: 0.01959 RPN score loss: 0.00124 RPN total loss: 0.02083 Total loss: 0.87734 timestamp: 1654948140.7479224 iteration: 42785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10962 FastRCNN class loss: 0.07462 FastRCNN total loss: 0.18425 L1 loss: 0.0000e+00 L2 loss: 0.62463 Learning rate: 0.002 Mask loss: 0.11556 RPN box loss: 0.02452 RPN score loss: 0.00216 RPN total loss: 0.02667 Total loss: 0.9511 timestamp: 1654948143.9521594 iteration: 42790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04881 FastRCNN class loss: 0.04667 FastRCNN total loss: 0.09548 L1 loss: 0.0000e+00 L2 loss: 0.62462 Learning rate: 0.002 Mask loss: 0.11703 RPN box loss: 0.01714 RPN score loss: 0.00439 RPN total loss: 0.02153 Total loss: 0.85866 timestamp: 1654948147.070633 iteration: 42795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07647 FastRCNN class loss: 0.03678 FastRCNN total loss: 0.11325 L1 loss: 0.0000e+00 L2 loss: 0.62461 Learning rate: 0.002 Mask loss: 0.11665 RPN box loss: 0.00676 RPN score loss: 0.00132 RPN total loss: 0.00807 Total loss: 0.86258 timestamp: 1654948150.2691092 iteration: 42800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10085 FastRCNN class loss: 0.08645 FastRCNN total loss: 0.1873 L1 loss: 0.0000e+00 L2 loss: 0.6246 Learning rate: 0.002 Mask loss: 0.1643 RPN box loss: 0.02472 RPN score loss: 0.00423 RPN total loss: 0.02894 Total loss: 1.00514 timestamp: 1654948153.5203032 iteration: 42805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08738 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.15245 L1 loss: 0.0000e+00 L2 loss: 0.62459 Learning rate: 0.002 Mask loss: 0.09563 RPN box loss: 0.00655 RPN score loss: 0.00246 RPN total loss: 0.00901 Total loss: 0.88168 timestamp: 1654948156.7350152 iteration: 42810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10239 FastRCNN class loss: 0.06536 FastRCNN total loss: 0.16775 L1 loss: 0.0000e+00 L2 loss: 0.62458 Learning rate: 0.002 Mask loss: 0.14022 RPN box loss: 0.02629 RPN score loss: 0.00614 RPN total loss: 0.03243 Total loss: 0.96497 timestamp: 1654948159.9974627 iteration: 42815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1202 FastRCNN class loss: 0.05563 FastRCNN total loss: 0.17583 L1 loss: 0.0000e+00 L2 loss: 0.62457 Learning rate: 0.002 Mask loss: 0.11972 RPN box loss: 0.01496 RPN score loss: 0.00257 RPN total loss: 0.01753 Total loss: 0.93765 timestamp: 1654948163.1799786 iteration: 42820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13643 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.19239 L1 loss: 0.0000e+00 L2 loss: 0.62456 Learning rate: 0.002 Mask loss: 0.10163 RPN box loss: 0.00731 RPN score loss: 0.00305 RPN total loss: 0.01036 Total loss: 0.92894 timestamp: 1654948166.3378253 iteration: 42825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10915 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.1736 L1 loss: 0.0000e+00 L2 loss: 0.62455 Learning rate: 0.002 Mask loss: 0.15898 RPN box loss: 0.03974 RPN score loss: 0.00439 RPN total loss: 0.04413 Total loss: 1.00126 timestamp: 1654948169.5035765 iteration: 42830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09071 FastRCNN class loss: 0.06332 FastRCNN total loss: 0.15403 L1 loss: 0.0000e+00 L2 loss: 0.62454 Learning rate: 0.002 Mask loss: 0.18157 RPN box loss: 0.03328 RPN score loss: 0.00224 RPN total loss: 0.03552 Total loss: 0.99566 timestamp: 1654948172.6715012 iteration: 42835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11311 FastRCNN class loss: 0.07684 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 0.62453 Learning rate: 0.002 Mask loss: 0.09591 RPN box loss: 0.02008 RPN score loss: 0.00271 RPN total loss: 0.02279 Total loss: 0.93319 timestamp: 1654948175.855724 iteration: 42840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17451 FastRCNN class loss: 0.1184 FastRCNN total loss: 0.29291 L1 loss: 0.0000e+00 L2 loss: 0.62452 Learning rate: 0.002 Mask loss: 0.17252 RPN box loss: 0.03286 RPN score loss: 0.01819 RPN total loss: 0.05105 Total loss: 1.141 timestamp: 1654948179.0524447 iteration: 42845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06573 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.12598 L1 loss: 0.0000e+00 L2 loss: 0.62451 Learning rate: 0.002 Mask loss: 0.10242 RPN box loss: 0.03249 RPN score loss: 0.00631 RPN total loss: 0.03879 Total loss: 0.8917 timestamp: 1654948182.3018432 iteration: 42850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11949 FastRCNN class loss: 0.06523 FastRCNN total loss: 0.18472 L1 loss: 0.0000e+00 L2 loss: 0.6245 Learning rate: 0.002 Mask loss: 0.12869 RPN box loss: 0.02251 RPN score loss: 0.00395 RPN total loss: 0.02647 Total loss: 0.96437 timestamp: 1654948185.460592 iteration: 42855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07909 FastRCNN class loss: 0.08515 FastRCNN total loss: 0.16424 L1 loss: 0.0000e+00 L2 loss: 0.62449 Learning rate: 0.002 Mask loss: 0.15372 RPN box loss: 0.02017 RPN score loss: 0.00619 RPN total loss: 0.02636 Total loss: 0.96881 timestamp: 1654948188.6886292 iteration: 42860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11634 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.19186 L1 loss: 0.0000e+00 L2 loss: 0.62448 Learning rate: 0.002 Mask loss: 0.08629 RPN box loss: 0.02458 RPN score loss: 0.00174 RPN total loss: 0.02631 Total loss: 0.92894 timestamp: 1654948191.896447 iteration: 42865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0666 FastRCNN class loss: 0.06333 FastRCNN total loss: 0.12993 L1 loss: 0.0000e+00 L2 loss: 0.62447 Learning rate: 0.002 Mask loss: 0.10457 RPN box loss: 0.00526 RPN score loss: 0.00099 RPN total loss: 0.00625 Total loss: 0.86522 timestamp: 1654948195.134861 iteration: 42870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.13875 L1 loss: 0.0000e+00 L2 loss: 0.62446 Learning rate: 0.002 Mask loss: 0.1454 RPN box loss: 0.01939 RPN score loss: 0.0096 RPN total loss: 0.02899 Total loss: 0.93759 timestamp: 1654948198.3546405 iteration: 42875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11842 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.18849 L1 loss: 0.0000e+00 L2 loss: 0.62445 Learning rate: 0.002 Mask loss: 0.11229 RPN box loss: 0.02334 RPN score loss: 0.00402 RPN total loss: 0.02736 Total loss: 0.9526 timestamp: 1654948201.571953 iteration: 42880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08638 FastRCNN class loss: 0.0453 FastRCNN total loss: 0.13168 L1 loss: 0.0000e+00 L2 loss: 0.62444 Learning rate: 0.002 Mask loss: 0.1031 RPN box loss: 0.00576 RPN score loss: 0.00153 RPN total loss: 0.00729 Total loss: 0.86651 timestamp: 1654948204.7373328 iteration: 42885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08859 FastRCNN class loss: 0.05363 FastRCNN total loss: 0.14222 L1 loss: 0.0000e+00 L2 loss: 0.62444 Learning rate: 0.002 Mask loss: 0.15715 RPN box loss: 0.0115 RPN score loss: 0.00192 RPN total loss: 0.01343 Total loss: 0.93723 timestamp: 1654948207.9096658 iteration: 42890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14947 FastRCNN class loss: 0.07774 FastRCNN total loss: 0.22721 L1 loss: 0.0000e+00 L2 loss: 0.62443 Learning rate: 0.002 Mask loss: 0.15222 RPN box loss: 0.02612 RPN score loss: 0.00245 RPN total loss: 0.02857 Total loss: 1.03242 timestamp: 1654948211.0635462 iteration: 42895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06729 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.14332 L1 loss: 0.0000e+00 L2 loss: 0.62442 Learning rate: 0.002 Mask loss: 0.11993 RPN box loss: 0.06488 RPN score loss: 0.00993 RPN total loss: 0.07481 Total loss: 0.96247 timestamp: 1654948214.2483385 iteration: 42900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1045 FastRCNN class loss: 0.07743 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.62441 Learning rate: 0.002 Mask loss: 0.15132 RPN box loss: 0.03049 RPN score loss: 0.00927 RPN total loss: 0.03975 Total loss: 0.99741 timestamp: 1654948217.4635978 iteration: 42905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.132 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.21592 L1 loss: 0.0000e+00 L2 loss: 0.6244 Learning rate: 0.002 Mask loss: 0.13532 RPN box loss: 0.01999 RPN score loss: 0.00676 RPN total loss: 0.02675 Total loss: 1.00239 timestamp: 1654948220.738424 iteration: 42910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13717 FastRCNN class loss: 0.09263 FastRCNN total loss: 0.2298 L1 loss: 0.0000e+00 L2 loss: 0.62439 Learning rate: 0.002 Mask loss: 0.17711 RPN box loss: 0.02371 RPN score loss: 0.00806 RPN total loss: 0.03177 Total loss: 1.06307 timestamp: 1654948223.9643223 iteration: 42915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06227 FastRCNN class loss: 0.02754 FastRCNN total loss: 0.0898 L1 loss: 0.0000e+00 L2 loss: 0.62438 Learning rate: 0.002 Mask loss: 0.10062 RPN box loss: 0.00752 RPN score loss: 0.00121 RPN total loss: 0.00873 Total loss: 0.82354 timestamp: 1654948227.2429445 iteration: 42920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11963 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.19331 L1 loss: 0.0000e+00 L2 loss: 0.62437 Learning rate: 0.002 Mask loss: 0.17987 RPN box loss: 0.02676 RPN score loss: 0.00576 RPN total loss: 0.03252 Total loss: 1.03007 timestamp: 1654948230.3831196 iteration: 42925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17338 FastRCNN class loss: 0.08329 FastRCNN total loss: 0.25667 L1 loss: 0.0000e+00 L2 loss: 0.62436 Learning rate: 0.002 Mask loss: 0.17725 RPN box loss: 0.02316 RPN score loss: 0.00316 RPN total loss: 0.02632 Total loss: 1.08461 timestamp: 1654948233.5879982 iteration: 42930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08021 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.13372 L1 loss: 0.0000e+00 L2 loss: 0.62435 Learning rate: 0.002 Mask loss: 0.15744 RPN box loss: 0.04139 RPN score loss: 0.00508 RPN total loss: 0.04647 Total loss: 0.96198 timestamp: 1654948236.7834399 iteration: 42935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08497 FastRCNN class loss: 0.0852 FastRCNN total loss: 0.17017 L1 loss: 0.0000e+00 L2 loss: 0.62434 Learning rate: 0.002 Mask loss: 0.13975 RPN box loss: 0.01428 RPN score loss: 0.00317 RPN total loss: 0.01745 Total loss: 0.95171 timestamp: 1654948239.949739 iteration: 42940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08677 FastRCNN class loss: 0.043 FastRCNN total loss: 0.12977 L1 loss: 0.0000e+00 L2 loss: 0.62433 Learning rate: 0.002 Mask loss: 0.29904 RPN box loss: 0.00629 RPN score loss: 0.00483 RPN total loss: 0.01112 Total loss: 1.06427 timestamp: 1654948243.178396 iteration: 42945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12017 FastRCNN class loss: 0.08195 FastRCNN total loss: 0.20213 L1 loss: 0.0000e+00 L2 loss: 0.62432 Learning rate: 0.002 Mask loss: 0.14153 RPN box loss: 0.02304 RPN score loss: 0.01797 RPN total loss: 0.04101 Total loss: 1.00899 timestamp: 1654948246.4130826 iteration: 42950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06744 FastRCNN class loss: 0.05461 FastRCNN total loss: 0.12205 L1 loss: 0.0000e+00 L2 loss: 0.62431 Learning rate: 0.002 Mask loss: 0.09956 RPN box loss: 0.0246 RPN score loss: 0.00203 RPN total loss: 0.02663 Total loss: 0.87256 timestamp: 1654948249.573223 iteration: 42955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06852 FastRCNN class loss: 0.06622 FastRCNN total loss: 0.13474 L1 loss: 0.0000e+00 L2 loss: 0.6243 Learning rate: 0.002 Mask loss: 0.12348 RPN box loss: 0.00918 RPN score loss: 0.00623 RPN total loss: 0.01541 Total loss: 0.89793 timestamp: 1654948252.8817585 iteration: 42960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06065 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.11565 L1 loss: 0.0000e+00 L2 loss: 0.62429 Learning rate: 0.002 Mask loss: 0.10365 RPN box loss: 0.0069 RPN score loss: 0.00239 RPN total loss: 0.0093 Total loss: 0.8529 timestamp: 1654948256.148967 iteration: 42965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.0802 FastRCNN total loss: 0.18558 L1 loss: 0.0000e+00 L2 loss: 0.62428 Learning rate: 0.002 Mask loss: 0.10901 RPN box loss: 0.02624 RPN score loss: 0.00573 RPN total loss: 0.03196 Total loss: 0.95084 timestamp: 1654948259.3508747 iteration: 42970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11248 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.19055 L1 loss: 0.0000e+00 L2 loss: 0.62427 Learning rate: 0.002 Mask loss: 0.13588 RPN box loss: 0.02142 RPN score loss: 0.00491 RPN total loss: 0.02633 Total loss: 0.97703 timestamp: 1654948262.5355964 iteration: 42975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.05332 FastRCNN total loss: 0.13735 L1 loss: 0.0000e+00 L2 loss: 0.62426 Learning rate: 0.002 Mask loss: 0.11463 RPN box loss: 0.00768 RPN score loss: 0.00208 RPN total loss: 0.00976 Total loss: 0.886 timestamp: 1654948265.8298142 iteration: 42980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16687 FastRCNN class loss: 0.07314 FastRCNN total loss: 0.24001 L1 loss: 0.0000e+00 L2 loss: 0.62425 Learning rate: 0.002 Mask loss: 0.13175 RPN box loss: 0.0086 RPN score loss: 0.00202 RPN total loss: 0.01062 Total loss: 1.00664 timestamp: 1654948269.1062257 iteration: 42985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07519 FastRCNN class loss: 0.06981 FastRCNN total loss: 0.14501 L1 loss: 0.0000e+00 L2 loss: 0.62425 Learning rate: 0.002 Mask loss: 0.16872 RPN box loss: 0.01709 RPN score loss: 0.00291 RPN total loss: 0.02 Total loss: 0.95797 timestamp: 1654948272.2578971 iteration: 42990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09587 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.15821 L1 loss: 0.0000e+00 L2 loss: 0.62424 Learning rate: 0.002 Mask loss: 0.13055 RPN box loss: 0.023 RPN score loss: 0.00343 RPN total loss: 0.02643 Total loss: 0.93943 timestamp: 1654948275.4524963 iteration: 42995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06346 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.11284 L1 loss: 0.0000e+00 L2 loss: 0.62423 Learning rate: 0.002 Mask loss: 0.11347 RPN box loss: 0.0673 RPN score loss: 0.00326 RPN total loss: 0.07057 Total loss: 0.92111 timestamp: 1654948278.6227682 iteration: 43000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13774 FastRCNN class loss: 0.09388 FastRCNN total loss: 0.23162 L1 loss: 0.0000e+00 L2 loss: 0.62422 Learning rate: 0.002 Mask loss: 0.1499 RPN box loss: 0.01524 RPN score loss: 0.00637 RPN total loss: 0.02162 Total loss: 1.02736 timestamp: 1654948281.8230972 iteration: 43005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07719 FastRCNN class loss: 0.05443 FastRCNN total loss: 0.13162 L1 loss: 0.0000e+00 L2 loss: 0.62421 Learning rate: 0.002 Mask loss: 0.16436 RPN box loss: 0.011 RPN score loss: 0.00738 RPN total loss: 0.01838 Total loss: 0.93857 timestamp: 1654948285.008204 iteration: 43010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12605 FastRCNN class loss: 0.13656 FastRCNN total loss: 0.26261 L1 loss: 0.0000e+00 L2 loss: 0.6242 Learning rate: 0.002 Mask loss: 0.2608 RPN box loss: 0.02964 RPN score loss: 0.00969 RPN total loss: 0.03933 Total loss: 1.18694 timestamp: 1654948288.2727246 iteration: 43015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10359 FastRCNN class loss: 0.08086 FastRCNN total loss: 0.18444 L1 loss: 0.0000e+00 L2 loss: 0.62419 Learning rate: 0.002 Mask loss: 0.12118 RPN box loss: 0.02046 RPN score loss: 0.00714 RPN total loss: 0.02761 Total loss: 0.95742 timestamp: 1654948291.4913044 iteration: 43020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05897 FastRCNN class loss: 0.04856 FastRCNN total loss: 0.10753 L1 loss: 0.0000e+00 L2 loss: 0.62419 Learning rate: 0.002 Mask loss: 0.10938 RPN box loss: 0.00578 RPN score loss: 0.00081 RPN total loss: 0.00659 Total loss: 0.84769 timestamp: 1654948294.7302709 iteration: 43025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10908 FastRCNN class loss: 0.08006 FastRCNN total loss: 0.18914 L1 loss: 0.0000e+00 L2 loss: 0.62418 Learning rate: 0.002 Mask loss: 0.12756 RPN box loss: 0.02162 RPN score loss: 0.00183 RPN total loss: 0.02345 Total loss: 0.96434 timestamp: 1654948297.9668388 iteration: 43030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07821 FastRCNN class loss: 0.05872 FastRCNN total loss: 0.13693 L1 loss: 0.0000e+00 L2 loss: 0.62417 Learning rate: 0.002 Mask loss: 0.12243 RPN box loss: 0.021 RPN score loss: 0.00753 RPN total loss: 0.02853 Total loss: 0.91206 timestamp: 1654948301.162231 iteration: 43035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09256 FastRCNN class loss: 0.05376 FastRCNN total loss: 0.14632 L1 loss: 0.0000e+00 L2 loss: 0.62416 Learning rate: 0.002 Mask loss: 0.14137 RPN box loss: 0.00735 RPN score loss: 0.00178 RPN total loss: 0.00913 Total loss: 0.92097 timestamp: 1654948304.2944343 iteration: 43040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15098 FastRCNN class loss: 0.06593 FastRCNN total loss: 0.21691 L1 loss: 0.0000e+00 L2 loss: 0.62415 Learning rate: 0.002 Mask loss: 0.12395 RPN box loss: 0.02477 RPN score loss: 0.00345 RPN total loss: 0.02823 Total loss: 0.99325 timestamp: 1654948307.4558556 iteration: 43045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20672 FastRCNN class loss: 0.06331 FastRCNN total loss: 0.27003 L1 loss: 0.0000e+00 L2 loss: 0.62414 Learning rate: 0.002 Mask loss: 0.13154 RPN box loss: 0.02727 RPN score loss: 0.00359 RPN total loss: 0.03086 Total loss: 1.05657 timestamp: 1654948310.7784576 iteration: 43050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09563 FastRCNN class loss: 0.07535 FastRCNN total loss: 0.17098 L1 loss: 0.0000e+00 L2 loss: 0.62413 Learning rate: 0.002 Mask loss: 0.17895 RPN box loss: 0.0201 RPN score loss: 0.0087 RPN total loss: 0.0288 Total loss: 1.00286 timestamp: 1654948313.9686918 iteration: 43055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07871 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.12948 L1 loss: 0.0000e+00 L2 loss: 0.62412 Learning rate: 0.002 Mask loss: 0.11694 RPN box loss: 0.00954 RPN score loss: 0.02273 RPN total loss: 0.03227 Total loss: 0.90281 timestamp: 1654948317.1992948 iteration: 43060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18713 FastRCNN class loss: 0.07156 FastRCNN total loss: 0.25869 L1 loss: 0.0000e+00 L2 loss: 0.62411 Learning rate: 0.002 Mask loss: 0.1296 RPN box loss: 0.02128 RPN score loss: 0.00331 RPN total loss: 0.02459 Total loss: 1.037 timestamp: 1654948320.387814 iteration: 43065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1356 FastRCNN class loss: 0.05767 FastRCNN total loss: 0.19327 L1 loss: 0.0000e+00 L2 loss: 0.6241 Learning rate: 0.002 Mask loss: 0.12718 RPN box loss: 0.00883 RPN score loss: 0.00128 RPN total loss: 0.01011 Total loss: 0.95465 timestamp: 1654948323.5680983 iteration: 43070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13318 FastRCNN class loss: 0.08784 FastRCNN total loss: 0.22101 L1 loss: 0.0000e+00 L2 loss: 0.62409 Learning rate: 0.002 Mask loss: 0.13606 RPN box loss: 0.02667 RPN score loss: 0.00623 RPN total loss: 0.0329 Total loss: 1.01406 timestamp: 1654948326.8701499 iteration: 43075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11138 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.18158 L1 loss: 0.0000e+00 L2 loss: 0.62408 Learning rate: 0.002 Mask loss: 0.1164 RPN box loss: 0.02922 RPN score loss: 0.0059 RPN total loss: 0.03512 Total loss: 0.95719 timestamp: 1654948330.0973797 iteration: 43080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.04537 FastRCNN total loss: 0.15281 L1 loss: 0.0000e+00 L2 loss: 0.62407 Learning rate: 0.002 Mask loss: 0.12804 RPN box loss: 0.02574 RPN score loss: 0.00243 RPN total loss: 0.02817 Total loss: 0.9331 timestamp: 1654948333.279415 iteration: 43085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14485 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.20998 L1 loss: 0.0000e+00 L2 loss: 0.62406 Learning rate: 0.002 Mask loss: 0.15016 RPN box loss: 0.04245 RPN score loss: 0.00655 RPN total loss: 0.049 Total loss: 1.0332 timestamp: 1654948336.4971352 iteration: 43090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0831 FastRCNN class loss: 0.04885 FastRCNN total loss: 0.13196 L1 loss: 0.0000e+00 L2 loss: 0.62405 Learning rate: 0.002 Mask loss: 0.13744 RPN box loss: 0.02253 RPN score loss: 0.00415 RPN total loss: 0.02667 Total loss: 0.92013 timestamp: 1654948339.6557963 iteration: 43095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.146 FastRCNN class loss: 0.10332 FastRCNN total loss: 0.24932 L1 loss: 0.0000e+00 L2 loss: 0.62404 Learning rate: 0.002 Mask loss: 0.23394 RPN box loss: 0.01007 RPN score loss: 0.00229 RPN total loss: 0.01236 Total loss: 1.11966 timestamp: 1654948342.841688 iteration: 43100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04664 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.12673 L1 loss: 0.0000e+00 L2 loss: 0.62403 Learning rate: 0.002 Mask loss: 0.14825 RPN box loss: 0.01903 RPN score loss: 0.00757 RPN total loss: 0.0266 Total loss: 0.92561 timestamp: 1654948346.0176709 iteration: 43105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11055 FastRCNN class loss: 0.12728 FastRCNN total loss: 0.23783 L1 loss: 0.0000e+00 L2 loss: 0.62402 Learning rate: 0.002 Mask loss: 0.16831 RPN box loss: 0.03377 RPN score loss: 0.0068 RPN total loss: 0.04057 Total loss: 1.07073 timestamp: 1654948349.219631 iteration: 43110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14244 FastRCNN class loss: 0.10335 FastRCNN total loss: 0.2458 L1 loss: 0.0000e+00 L2 loss: 0.62401 Learning rate: 0.002 Mask loss: 0.13571 RPN box loss: 0.02341 RPN score loss: 0.00239 RPN total loss: 0.0258 Total loss: 1.03131 timestamp: 1654948352.4444892 iteration: 43115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13258 FastRCNN class loss: 0.07045 FastRCNN total loss: 0.20302 L1 loss: 0.0000e+00 L2 loss: 0.62399 Learning rate: 0.002 Mask loss: 0.1221 RPN box loss: 0.04708 RPN score loss: 0.00951 RPN total loss: 0.05659 Total loss: 1.0057 timestamp: 1654948355.7091782 iteration: 43120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11329 FastRCNN class loss: 0.0693 FastRCNN total loss: 0.18259 L1 loss: 0.0000e+00 L2 loss: 0.62398 Learning rate: 0.002 Mask loss: 0.11821 RPN box loss: 0.02084 RPN score loss: 0.0082 RPN total loss: 0.02904 Total loss: 0.95383 timestamp: 1654948358.933499 iteration: 43125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06759 FastRCNN class loss: 0.07203 FastRCNN total loss: 0.13962 L1 loss: 0.0000e+00 L2 loss: 0.62398 Learning rate: 0.002 Mask loss: 0.09005 RPN box loss: 0.03539 RPN score loss: 0.00288 RPN total loss: 0.03827 Total loss: 0.89192 timestamp: 1654948362.1385767 iteration: 43130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03409 FastRCNN class loss: 0.03635 FastRCNN total loss: 0.07044 L1 loss: 0.0000e+00 L2 loss: 0.62397 Learning rate: 0.002 Mask loss: 0.0889 RPN box loss: 0.02745 RPN score loss: 0.0018 RPN total loss: 0.02926 Total loss: 0.81257 timestamp: 1654948365.329639 iteration: 43135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0876 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.14744 L1 loss: 0.0000e+00 L2 loss: 0.62396 Learning rate: 0.002 Mask loss: 0.1266 RPN box loss: 0.01885 RPN score loss: 0.00743 RPN total loss: 0.02628 Total loss: 0.92429 timestamp: 1654948368.5106826 iteration: 43140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13891 FastRCNN class loss: 0.10149 FastRCNN total loss: 0.2404 L1 loss: 0.0000e+00 L2 loss: 0.62395 Learning rate: 0.002 Mask loss: 0.1696 RPN box loss: 0.03212 RPN score loss: 0.01248 RPN total loss: 0.04461 Total loss: 1.07856 timestamp: 1654948371.74878 iteration: 43145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.09829 FastRCNN total loss: 0.21506 L1 loss: 0.0000e+00 L2 loss: 0.62394 Learning rate: 0.002 Mask loss: 0.17251 RPN box loss: 0.02812 RPN score loss: 0.00857 RPN total loss: 0.03669 Total loss: 1.0482 timestamp: 1654948374.9448144 iteration: 43150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10309 FastRCNN class loss: 0.11435 FastRCNN total loss: 0.21744 L1 loss: 0.0000e+00 L2 loss: 0.62393 Learning rate: 0.002 Mask loss: 0.1361 RPN box loss: 0.02434 RPN score loss: 0.00469 RPN total loss: 0.02903 Total loss: 1.0065 timestamp: 1654948378.1532168 iteration: 43155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11569 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.18538 L1 loss: 0.0000e+00 L2 loss: 0.62392 Learning rate: 0.002 Mask loss: 0.12925 RPN box loss: 0.016 RPN score loss: 0.00318 RPN total loss: 0.01918 Total loss: 0.95774 timestamp: 1654948381.3321245 iteration: 43160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09387 FastRCNN class loss: 0.11279 FastRCNN total loss: 0.20667 L1 loss: 0.0000e+00 L2 loss: 0.62391 Learning rate: 0.002 Mask loss: 0.15397 RPN box loss: 0.0218 RPN score loss: 0.01468 RPN total loss: 0.03648 Total loss: 1.02103 timestamp: 1654948384.5732863 iteration: 43165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12065 FastRCNN class loss: 0.07532 FastRCNN total loss: 0.19597 L1 loss: 0.0000e+00 L2 loss: 0.6239 Learning rate: 0.002 Mask loss: 0.14573 RPN box loss: 0.02677 RPN score loss: 0.00739 RPN total loss: 0.03416 Total loss: 0.99976 timestamp: 1654948387.7269356 iteration: 43170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09927 FastRCNN class loss: 0.07354 FastRCNN total loss: 0.17281 L1 loss: 0.0000e+00 L2 loss: 0.62389 Learning rate: 0.002 Mask loss: 0.13134 RPN box loss: 0.03462 RPN score loss: 0.00894 RPN total loss: 0.04356 Total loss: 0.9716 timestamp: 1654948390.866563 iteration: 43175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08579 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.17076 L1 loss: 0.0000e+00 L2 loss: 0.62388 Learning rate: 0.002 Mask loss: 0.13738 RPN box loss: 0.01647 RPN score loss: 0.00672 RPN total loss: 0.02319 Total loss: 0.95522 timestamp: 1654948394.0787842 iteration: 43180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09619 FastRCNN class loss: 0.10284 FastRCNN total loss: 0.19902 L1 loss: 0.0000e+00 L2 loss: 0.62387 Learning rate: 0.002 Mask loss: 0.18977 RPN box loss: 0.02176 RPN score loss: 0.00521 RPN total loss: 0.02697 Total loss: 1.03963 timestamp: 1654948397.2869613 iteration: 43185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11206 FastRCNN class loss: 0.11397 FastRCNN total loss: 0.22603 L1 loss: 0.0000e+00 L2 loss: 0.62386 Learning rate: 0.002 Mask loss: 0.17299 RPN box loss: 0.03645 RPN score loss: 0.00836 RPN total loss: 0.0448 Total loss: 1.06769 timestamp: 1654948400.5076654 iteration: 43190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12802 FastRCNN class loss: 0.1051 FastRCNN total loss: 0.23311 L1 loss: 0.0000e+00 L2 loss: 0.62386 Learning rate: 0.002 Mask loss: 0.17629 RPN box loss: 0.02476 RPN score loss: 0.0195 RPN total loss: 0.04426 Total loss: 1.07752 timestamp: 1654948403.6362488 iteration: 43195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11528 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.20505 L1 loss: 0.0000e+00 L2 loss: 0.62385 Learning rate: 0.002 Mask loss: 0.13726 RPN box loss: 0.00954 RPN score loss: 0.00254 RPN total loss: 0.01208 Total loss: 0.97824 timestamp: 1654948406.8551185 iteration: 43200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12693 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.19651 L1 loss: 0.0000e+00 L2 loss: 0.62384 Learning rate: 0.002 Mask loss: 0.17533 RPN box loss: 0.03178 RPN score loss: 0.00409 RPN total loss: 0.03587 Total loss: 1.03155 timestamp: 1654948410.0826833 iteration: 43205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.137 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.20996 L1 loss: 0.0000e+00 L2 loss: 0.62383 Learning rate: 0.002 Mask loss: 0.17888 RPN box loss: 0.02326 RPN score loss: 0.00135 RPN total loss: 0.02461 Total loss: 1.03728 timestamp: 1654948413.2559834 iteration: 43210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05149 FastRCNN class loss: 0.06039 FastRCNN total loss: 0.11188 L1 loss: 0.0000e+00 L2 loss: 0.62382 Learning rate: 0.002 Mask loss: 0.09761 RPN box loss: 0.00321 RPN score loss: 0.0021 RPN total loss: 0.00531 Total loss: 0.83861 timestamp: 1654948416.4988832 iteration: 43215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13137 FastRCNN class loss: 0.0813 FastRCNN total loss: 0.21267 L1 loss: 0.0000e+00 L2 loss: 0.62381 Learning rate: 0.002 Mask loss: 0.14171 RPN box loss: 0.01472 RPN score loss: 0.00505 RPN total loss: 0.01978 Total loss: 0.99797 timestamp: 1654948419.6877625 iteration: 43220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13405 FastRCNN class loss: 0.10248 FastRCNN total loss: 0.23653 L1 loss: 0.0000e+00 L2 loss: 0.6238 Learning rate: 0.002 Mask loss: 0.1988 RPN box loss: 0.02126 RPN score loss: 0.00403 RPN total loss: 0.0253 Total loss: 1.08442 timestamp: 1654948422.904165 iteration: 43225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11583 FastRCNN class loss: 0.05451 FastRCNN total loss: 0.17034 L1 loss: 0.0000e+00 L2 loss: 0.62379 Learning rate: 0.002 Mask loss: 0.14893 RPN box loss: 0.01145 RPN score loss: 0.00239 RPN total loss: 0.01384 Total loss: 0.95691 timestamp: 1654948426.0001056 iteration: 43230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11299 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.18025 L1 loss: 0.0000e+00 L2 loss: 0.62378 Learning rate: 0.002 Mask loss: 0.08222 RPN box loss: 0.00572 RPN score loss: 0.00575 RPN total loss: 0.01147 Total loss: 0.89772 timestamp: 1654948429.240605 iteration: 43235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08596 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.1531 L1 loss: 0.0000e+00 L2 loss: 0.62377 Learning rate: 0.002 Mask loss: 0.13757 RPN box loss: 0.01938 RPN score loss: 0.00681 RPN total loss: 0.02619 Total loss: 0.94063 timestamp: 1654948432.4094229 iteration: 43240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14209 FastRCNN class loss: 0.10013 FastRCNN total loss: 0.24222 L1 loss: 0.0000e+00 L2 loss: 0.62377 Learning rate: 0.002 Mask loss: 0.21715 RPN box loss: 0.03016 RPN score loss: 0.00332 RPN total loss: 0.03348 Total loss: 1.11662 timestamp: 1654948435.5799406 iteration: 43245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09251 FastRCNN class loss: 0.07321 FastRCNN total loss: 0.16572 L1 loss: 0.0000e+00 L2 loss: 0.62375 Learning rate: 0.002 Mask loss: 0.10582 RPN box loss: 0.01565 RPN score loss: 0.00989 RPN total loss: 0.02554 Total loss: 0.92083 timestamp: 1654948438.7572935 iteration: 43250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10347 FastRCNN class loss: 0.08862 FastRCNN total loss: 0.19209 L1 loss: 0.0000e+00 L2 loss: 0.62374 Learning rate: 0.002 Mask loss: 0.12166 RPN box loss: 0.02453 RPN score loss: 0.00469 RPN total loss: 0.02922 Total loss: 0.96671 timestamp: 1654948441.8797283 iteration: 43255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16751 FastRCNN class loss: 0.07019 FastRCNN total loss: 0.2377 L1 loss: 0.0000e+00 L2 loss: 0.62373 Learning rate: 0.002 Mask loss: 0.1504 RPN box loss: 0.00988 RPN score loss: 0.00493 RPN total loss: 0.01481 Total loss: 1.02663 timestamp: 1654948445.034492 iteration: 43260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06795 FastRCNN class loss: 0.04557 FastRCNN total loss: 0.11352 L1 loss: 0.0000e+00 L2 loss: 0.62372 Learning rate: 0.002 Mask loss: 0.08358 RPN box loss: 0.00976 RPN score loss: 0.00517 RPN total loss: 0.01493 Total loss: 0.83574 timestamp: 1654948448.2209527 iteration: 43265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0712 FastRCNN class loss: 0.06338 FastRCNN total loss: 0.13457 L1 loss: 0.0000e+00 L2 loss: 0.62371 Learning rate: 0.002 Mask loss: 0.09605 RPN box loss: 0.01469 RPN score loss: 0.00262 RPN total loss: 0.01731 Total loss: 0.87164 timestamp: 1654948451.4359472 iteration: 43270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10968 FastRCNN class loss: 0.09546 FastRCNN total loss: 0.20514 L1 loss: 0.0000e+00 L2 loss: 0.6237 Learning rate: 0.002 Mask loss: 0.19782 RPN box loss: 0.01966 RPN score loss: 0.00988 RPN total loss: 0.02954 Total loss: 1.0562 timestamp: 1654948454.67149 iteration: 43275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14974 FastRCNN class loss: 0.0957 FastRCNN total loss: 0.24544 L1 loss: 0.0000e+00 L2 loss: 0.62369 Learning rate: 0.002 Mask loss: 0.17893 RPN box loss: 0.02606 RPN score loss: 0.0105 RPN total loss: 0.03656 Total loss: 1.08461 timestamp: 1654948457.832868 iteration: 43280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.04832 FastRCNN total loss: 0.11453 L1 loss: 0.0000e+00 L2 loss: 0.62368 Learning rate: 0.002 Mask loss: 0.08844 RPN box loss: 0.01795 RPN score loss: 0.00439 RPN total loss: 0.02234 Total loss: 0.84899 timestamp: 1654948461.0147665 iteration: 43285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08485 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.16398 L1 loss: 0.0000e+00 L2 loss: 0.62368 Learning rate: 0.002 Mask loss: 0.14898 RPN box loss: 0.03078 RPN score loss: 0.006 RPN total loss: 0.03678 Total loss: 0.97342 timestamp: 1654948464.1940064 iteration: 43290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09671 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.16041 L1 loss: 0.0000e+00 L2 loss: 0.62367 Learning rate: 0.002 Mask loss: 0.14074 RPN box loss: 0.03009 RPN score loss: 0.01323 RPN total loss: 0.04333 Total loss: 0.96815 timestamp: 1654948467.3723333 iteration: 43295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11054 FastRCNN class loss: 0.08484 FastRCNN total loss: 0.19538 L1 loss: 0.0000e+00 L2 loss: 0.62366 Learning rate: 0.002 Mask loss: 0.12909 RPN box loss: 0.01249 RPN score loss: 0.00124 RPN total loss: 0.01373 Total loss: 0.96186 timestamp: 1654948470.5115442 iteration: 43300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11516 FastRCNN class loss: 0.08686 FastRCNN total loss: 0.20203 L1 loss: 0.0000e+00 L2 loss: 0.62365 Learning rate: 0.002 Mask loss: 0.10331 RPN box loss: 0.01703 RPN score loss: 0.00481 RPN total loss: 0.02184 Total loss: 0.95084 timestamp: 1654948473.6749878 iteration: 43305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08959 FastRCNN class loss: 0.10332 FastRCNN total loss: 0.19291 L1 loss: 0.0000e+00 L2 loss: 0.62364 Learning rate: 0.002 Mask loss: 0.12267 RPN box loss: 0.01618 RPN score loss: 0.00713 RPN total loss: 0.02332 Total loss: 0.96253 timestamp: 1654948476.8693774 iteration: 43310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13451 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.20968 L1 loss: 0.0000e+00 L2 loss: 0.62363 Learning rate: 0.002 Mask loss: 0.23546 RPN box loss: 0.02514 RPN score loss: 0.00908 RPN total loss: 0.03422 Total loss: 1.10299 timestamp: 1654948480.0590208 iteration: 43315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10138 FastRCNN class loss: 0.08943 FastRCNN total loss: 0.1908 L1 loss: 0.0000e+00 L2 loss: 0.62362 Learning rate: 0.002 Mask loss: 0.1645 RPN box loss: 0.01495 RPN score loss: 0.00117 RPN total loss: 0.01613 Total loss: 0.99506 timestamp: 1654948483.2243674 iteration: 43320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12736 FastRCNN class loss: 0.10751 FastRCNN total loss: 0.23487 L1 loss: 0.0000e+00 L2 loss: 0.62362 Learning rate: 0.002 Mask loss: 0.14512 RPN box loss: 0.0039 RPN score loss: 0.00663 RPN total loss: 0.01054 Total loss: 1.01414 timestamp: 1654948486.3735402 iteration: 43325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11667 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.18723 L1 loss: 0.0000e+00 L2 loss: 0.62361 Learning rate: 0.002 Mask loss: 0.139 RPN box loss: 0.00688 RPN score loss: 0.00082 RPN total loss: 0.0077 Total loss: 0.95754 timestamp: 1654948489.5622318 iteration: 43330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1295 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.22288 L1 loss: 0.0000e+00 L2 loss: 0.6236 Learning rate: 0.002 Mask loss: 0.12641 RPN box loss: 0.01423 RPN score loss: 0.00782 RPN total loss: 0.02205 Total loss: 0.99494 timestamp: 1654948492.7986426 iteration: 43335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11542 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.1935 L1 loss: 0.0000e+00 L2 loss: 0.62359 Learning rate: 0.002 Mask loss: 0.13643 RPN box loss: 0.01276 RPN score loss: 0.00603 RPN total loss: 0.01879 Total loss: 0.97231 timestamp: 1654948496.0153422 iteration: 43340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07268 FastRCNN class loss: 0.0536 FastRCNN total loss: 0.12628 L1 loss: 0.0000e+00 L2 loss: 0.62358 Learning rate: 0.002 Mask loss: 0.10752 RPN box loss: 0.00597 RPN score loss: 0.00519 RPN total loss: 0.01116 Total loss: 0.86854 timestamp: 1654948499.2451577 iteration: 43345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1304 FastRCNN class loss: 0.06683 FastRCNN total loss: 0.19724 L1 loss: 0.0000e+00 L2 loss: 0.62357 Learning rate: 0.002 Mask loss: 0.13622 RPN box loss: 0.00586 RPN score loss: 0.00308 RPN total loss: 0.00895 Total loss: 0.96597 timestamp: 1654948502.5349042 iteration: 43350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09482 FastRCNN class loss: 0.09095 FastRCNN total loss: 0.18577 L1 loss: 0.0000e+00 L2 loss: 0.62356 Learning rate: 0.002 Mask loss: 0.12719 RPN box loss: 0.0185 RPN score loss: 0.00742 RPN total loss: 0.02592 Total loss: 0.96245 timestamp: 1654948505.6677518 iteration: 43355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11792 FastRCNN class loss: 0.06331 FastRCNN total loss: 0.18123 L1 loss: 0.0000e+00 L2 loss: 0.62356 Learning rate: 0.002 Mask loss: 0.19402 RPN box loss: 0.03366 RPN score loss: 0.01268 RPN total loss: 0.04635 Total loss: 1.04515 timestamp: 1654948508.9272697 iteration: 43360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10625 FastRCNN class loss: 0.07993 FastRCNN total loss: 0.18618 L1 loss: 0.0000e+00 L2 loss: 0.62355 Learning rate: 0.002 Mask loss: 0.1083 RPN box loss: 0.05917 RPN score loss: 0.00929 RPN total loss: 0.06846 Total loss: 0.98648 timestamp: 1654948512.1547596 iteration: 43365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07883 FastRCNN class loss: 0.0957 FastRCNN total loss: 0.17453 L1 loss: 0.0000e+00 L2 loss: 0.62353 Learning rate: 0.002 Mask loss: 0.16596 RPN box loss: 0.00961 RPN score loss: 0.00559 RPN total loss: 0.0152 Total loss: 0.97922 timestamp: 1654948515.3765185 iteration: 43370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09059 FastRCNN class loss: 0.08601 FastRCNN total loss: 0.1766 L1 loss: 0.0000e+00 L2 loss: 0.62352 Learning rate: 0.002 Mask loss: 0.16884 RPN box loss: 0.01276 RPN score loss: 0.00958 RPN total loss: 0.02234 Total loss: 0.9913 timestamp: 1654948518.587132 iteration: 43375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08234 FastRCNN class loss: 0.0542 FastRCNN total loss: 0.13654 L1 loss: 0.0000e+00 L2 loss: 0.62351 Learning rate: 0.002 Mask loss: 0.09391 RPN box loss: 0.02334 RPN score loss: 0.00293 RPN total loss: 0.02627 Total loss: 0.88023 timestamp: 1654948521.8498971 iteration: 43380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07767 FastRCNN class loss: 0.04243 FastRCNN total loss: 0.1201 L1 loss: 0.0000e+00 L2 loss: 0.6235 Learning rate: 0.002 Mask loss: 0.11212 RPN box loss: 0.00663 RPN score loss: 0.00212 RPN total loss: 0.00874 Total loss: 0.86446 timestamp: 1654948525.0659704 iteration: 43385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07266 FastRCNN class loss: 0.04821 FastRCNN total loss: 0.12087 L1 loss: 0.0000e+00 L2 loss: 0.62349 Learning rate: 0.002 Mask loss: 0.11624 RPN box loss: 0.01535 RPN score loss: 0.00419 RPN total loss: 0.01954 Total loss: 0.88013 timestamp: 1654948528.3272407 iteration: 43390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12216 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.20357 L1 loss: 0.0000e+00 L2 loss: 0.62348 Learning rate: 0.002 Mask loss: 0.13372 RPN box loss: 0.01764 RPN score loss: 0.00626 RPN total loss: 0.0239 Total loss: 0.98467 timestamp: 1654948531.5181148 iteration: 43395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17038 FastRCNN class loss: 0.0992 FastRCNN total loss: 0.26958 L1 loss: 0.0000e+00 L2 loss: 0.62347 Learning rate: 0.002 Mask loss: 0.18805 RPN box loss: 0.02561 RPN score loss: 0.00715 RPN total loss: 0.03276 Total loss: 1.11387 timestamp: 1654948534.661067 iteration: 43400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09952 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.16006 L1 loss: 0.0000e+00 L2 loss: 0.62346 Learning rate: 0.002 Mask loss: 0.13272 RPN box loss: 0.01161 RPN score loss: 0.0025 RPN total loss: 0.01411 Total loss: 0.93036 timestamp: 1654948537.8443077 iteration: 43405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07116 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.13085 L1 loss: 0.0000e+00 L2 loss: 0.62346 Learning rate: 0.002 Mask loss: 0.11597 RPN box loss: 0.06058 RPN score loss: 0.0063 RPN total loss: 0.06687 Total loss: 0.93715 timestamp: 1654948541.1389866 iteration: 43410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09062 FastRCNN class loss: 0.06619 FastRCNN total loss: 0.15681 L1 loss: 0.0000e+00 L2 loss: 0.62345 Learning rate: 0.002 Mask loss: 0.11932 RPN box loss: 0.03377 RPN score loss: 0.00451 RPN total loss: 0.03828 Total loss: 0.93786 timestamp: 1654948544.4536986 iteration: 43415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08141 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.14221 L1 loss: 0.0000e+00 L2 loss: 0.62344 Learning rate: 0.002 Mask loss: 0.14237 RPN box loss: 0.01434 RPN score loss: 0.01388 RPN total loss: 0.02823 Total loss: 0.93624 timestamp: 1654948547.635351 iteration: 43420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09772 FastRCNN class loss: 0.0673 FastRCNN total loss: 0.16502 L1 loss: 0.0000e+00 L2 loss: 0.62343 Learning rate: 0.002 Mask loss: 0.21537 RPN box loss: 0.00685 RPN score loss: 0.00065 RPN total loss: 0.0075 Total loss: 1.01131 timestamp: 1654948550.9103491 iteration: 43425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12033 FastRCNN class loss: 0.10206 FastRCNN total loss: 0.22239 L1 loss: 0.0000e+00 L2 loss: 0.62342 Learning rate: 0.002 Mask loss: 0.18738 RPN box loss: 0.01816 RPN score loss: 0.01581 RPN total loss: 0.03397 Total loss: 1.06716 timestamp: 1654948554.0910623 iteration: 43430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08303 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.12694 L1 loss: 0.0000e+00 L2 loss: 0.62341 Learning rate: 0.002 Mask loss: 0.09793 RPN box loss: 0.03312 RPN score loss: 0.00477 RPN total loss: 0.03789 Total loss: 0.88617 timestamp: 1654948557.3280463 iteration: 43435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09123 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.16703 L1 loss: 0.0000e+00 L2 loss: 0.6234 Learning rate: 0.002 Mask loss: 0.10427 RPN box loss: 0.01851 RPN score loss: 0.01322 RPN total loss: 0.03174 Total loss: 0.92643 timestamp: 1654948560.5171695 iteration: 43440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09796 FastRCNN class loss: 0.06933 FastRCNN total loss: 0.16729 L1 loss: 0.0000e+00 L2 loss: 0.62338 Learning rate: 0.002 Mask loss: 0.16899 RPN box loss: 0.01957 RPN score loss: 0.00298 RPN total loss: 0.02255 Total loss: 0.98222 timestamp: 1654948563.773399 iteration: 43445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10504 FastRCNN class loss: 0.06526 FastRCNN total loss: 0.1703 L1 loss: 0.0000e+00 L2 loss: 0.62337 Learning rate: 0.002 Mask loss: 0.17865 RPN box loss: 0.00548 RPN score loss: 0.00708 RPN total loss: 0.01256 Total loss: 0.98488 timestamp: 1654948566.924814 iteration: 43450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.15437 L1 loss: 0.0000e+00 L2 loss: 0.62337 Learning rate: 0.002 Mask loss: 0.1147 RPN box loss: 0.01017 RPN score loss: 0.00212 RPN total loss: 0.01228 Total loss: 0.90472 timestamp: 1654948570.1443892 iteration: 43455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08127 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.14718 L1 loss: 0.0000e+00 L2 loss: 0.62336 Learning rate: 0.002 Mask loss: 0.0861 RPN box loss: 0.00961 RPN score loss: 0.00069 RPN total loss: 0.0103 Total loss: 0.86694 timestamp: 1654948573.355653 iteration: 43460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08778 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.1621 L1 loss: 0.0000e+00 L2 loss: 0.62335 Learning rate: 0.002 Mask loss: 0.14193 RPN box loss: 0.023 RPN score loss: 0.00832 RPN total loss: 0.03132 Total loss: 0.9587 timestamp: 1654948576.5873816 iteration: 43465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16043 FastRCNN class loss: 0.11902 FastRCNN total loss: 0.27945 L1 loss: 0.0000e+00 L2 loss: 0.62335 Learning rate: 0.002 Mask loss: 0.1789 RPN box loss: 0.02258 RPN score loss: 0.00961 RPN total loss: 0.03219 Total loss: 1.11389 timestamp: 1654948579.7694347 iteration: 43470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1201 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.1782 L1 loss: 0.0000e+00 L2 loss: 0.62334 Learning rate: 0.002 Mask loss: 0.17019 RPN box loss: 0.01327 RPN score loss: 0.00364 RPN total loss: 0.01691 Total loss: 0.98864 timestamp: 1654948582.9702702 iteration: 43475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08486 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.17242 L1 loss: 0.0000e+00 L2 loss: 0.62333 Learning rate: 0.002 Mask loss: 0.19078 RPN box loss: 0.02636 RPN score loss: 0.01222 RPN total loss: 0.03858 Total loss: 1.0251 timestamp: 1654948586.1620855 iteration: 43480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11192 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.20281 L1 loss: 0.0000e+00 L2 loss: 0.62332 Learning rate: 0.002 Mask loss: 0.14217 RPN box loss: 0.02945 RPN score loss: 0.00707 RPN total loss: 0.03652 Total loss: 1.00481 timestamp: 1654948589.2343402 iteration: 43485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10272 FastRCNN class loss: 0.09337 FastRCNN total loss: 0.19609 L1 loss: 0.0000e+00 L2 loss: 0.62331 Learning rate: 0.002 Mask loss: 0.1231 RPN box loss: 0.01425 RPN score loss: 0.00377 RPN total loss: 0.01802 Total loss: 0.96052 timestamp: 1654948592.4445977 iteration: 43490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08341 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.15746 L1 loss: 0.0000e+00 L2 loss: 0.6233 Learning rate: 0.002 Mask loss: 0.13616 RPN box loss: 0.00627 RPN score loss: 0.00796 RPN total loss: 0.01423 Total loss: 0.93115 timestamp: 1654948595.637813 iteration: 43495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0647 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.12655 L1 loss: 0.0000e+00 L2 loss: 0.62329 Learning rate: 0.002 Mask loss: 0.08831 RPN box loss: 0.00527 RPN score loss: 0.00418 RPN total loss: 0.00944 Total loss: 0.84759 timestamp: 1654948598.8293617 iteration: 43500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.094 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.16515 L1 loss: 0.0000e+00 L2 loss: 0.62328 Learning rate: 0.002 Mask loss: 0.14439 RPN box loss: 0.01759 RPN score loss: 0.00521 RPN total loss: 0.02281 Total loss: 0.95562 timestamp: 1654948602.0149689 iteration: 43505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10147 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.16285 L1 loss: 0.0000e+00 L2 loss: 0.62327 Learning rate: 0.002 Mask loss: 0.10802 RPN box loss: 0.00497 RPN score loss: 0.0038 RPN total loss: 0.00877 Total loss: 0.90291 timestamp: 1654948605.1523314 iteration: 43510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.10544 FastRCNN total loss: 0.24143 L1 loss: 0.0000e+00 L2 loss: 0.62326 Learning rate: 0.002 Mask loss: 0.14766 RPN box loss: 0.04635 RPN score loss: 0.01348 RPN total loss: 0.05983 Total loss: 1.07217 timestamp: 1654948608.348897 iteration: 43515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0878 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.16225 L1 loss: 0.0000e+00 L2 loss: 0.62325 Learning rate: 0.002 Mask loss: 0.1384 RPN box loss: 0.01078 RPN score loss: 0.00478 RPN total loss: 0.01556 Total loss: 0.93947 timestamp: 1654948611.517031 iteration: 43520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0751 FastRCNN class loss: 0.04709 FastRCNN total loss: 0.1222 L1 loss: 0.0000e+00 L2 loss: 0.62324 Learning rate: 0.002 Mask loss: 0.15207 RPN box loss: 0.00676 RPN score loss: 0.00205 RPN total loss: 0.00881 Total loss: 0.90632 timestamp: 1654948614.737614 iteration: 43525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08851 FastRCNN class loss: 0.0484 FastRCNN total loss: 0.13691 L1 loss: 0.0000e+00 L2 loss: 0.62323 Learning rate: 0.002 Mask loss: 0.09124 RPN box loss: 0.01884 RPN score loss: 0.00105 RPN total loss: 0.01989 Total loss: 0.87127 timestamp: 1654948617.9668677 iteration: 43530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10288 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.16427 L1 loss: 0.0000e+00 L2 loss: 0.62322 Learning rate: 0.002 Mask loss: 0.15052 RPN box loss: 0.01139 RPN score loss: 0.00656 RPN total loss: 0.01795 Total loss: 0.95595 timestamp: 1654948621.2385292 iteration: 43535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10432 FastRCNN class loss: 0.09281 FastRCNN total loss: 0.19713 L1 loss: 0.0000e+00 L2 loss: 0.62321 Learning rate: 0.002 Mask loss: 0.13621 RPN box loss: 0.0148 RPN score loss: 0.0097 RPN total loss: 0.0245 Total loss: 0.98105 timestamp: 1654948624.401386 iteration: 43540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13492 FastRCNN class loss: 0.08837 FastRCNN total loss: 0.22328 L1 loss: 0.0000e+00 L2 loss: 0.6232 Learning rate: 0.002 Mask loss: 0.17689 RPN box loss: 0.0162 RPN score loss: 0.00194 RPN total loss: 0.01814 Total loss: 1.04151 timestamp: 1654948627.5093758 iteration: 43545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06835 FastRCNN class loss: 0.04778 FastRCNN total loss: 0.11613 L1 loss: 0.0000e+00 L2 loss: 0.62319 Learning rate: 0.002 Mask loss: 0.09876 RPN box loss: 0.01229 RPN score loss: 0.00565 RPN total loss: 0.01795 Total loss: 0.85603 timestamp: 1654948630.772503 iteration: 43550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09195 FastRCNN class loss: 0.07648 FastRCNN total loss: 0.16843 L1 loss: 0.0000e+00 L2 loss: 0.62318 Learning rate: 0.002 Mask loss: 0.12806 RPN box loss: 0.01784 RPN score loss: 0.00443 RPN total loss: 0.02227 Total loss: 0.94194 timestamp: 1654948633.9605494 iteration: 43555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05376 FastRCNN class loss: 0.04845 FastRCNN total loss: 0.10221 L1 loss: 0.0000e+00 L2 loss: 0.62318 Learning rate: 0.002 Mask loss: 0.16522 RPN box loss: 0.03333 RPN score loss: 0.00248 RPN total loss: 0.03581 Total loss: 0.92641 timestamp: 1654948637.1294243 iteration: 43560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10593 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.1614 L1 loss: 0.0000e+00 L2 loss: 0.62317 Learning rate: 0.002 Mask loss: 0.09698 RPN box loss: 0.01007 RPN score loss: 0.00556 RPN total loss: 0.01562 Total loss: 0.89717 timestamp: 1654948640.2996264 iteration: 43565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11833 FastRCNN class loss: 0.07863 FastRCNN total loss: 0.19696 L1 loss: 0.0000e+00 L2 loss: 0.62316 Learning rate: 0.002 Mask loss: 0.11671 RPN box loss: 0.02581 RPN score loss: 0.00322 RPN total loss: 0.02903 Total loss: 0.96586 timestamp: 1654948643.4788203 iteration: 43570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09138 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.14553 L1 loss: 0.0000e+00 L2 loss: 0.62315 Learning rate: 0.002 Mask loss: 0.12327 RPN box loss: 0.05112 RPN score loss: 0.00458 RPN total loss: 0.05569 Total loss: 0.94764 timestamp: 1654948646.639833 iteration: 43575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07141 FastRCNN class loss: 0.05177 FastRCNN total loss: 0.12317 L1 loss: 0.0000e+00 L2 loss: 0.62314 Learning rate: 0.002 Mask loss: 0.09219 RPN box loss: 0.01985 RPN score loss: 0.00536 RPN total loss: 0.02521 Total loss: 0.86371 timestamp: 1654948649.8671722 iteration: 43580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10971 FastRCNN class loss: 0.08641 FastRCNN total loss: 0.19612 L1 loss: 0.0000e+00 L2 loss: 0.62313 Learning rate: 0.002 Mask loss: 0.11443 RPN box loss: 0.00896 RPN score loss: 0.0027 RPN total loss: 0.01166 Total loss: 0.94535 timestamp: 1654948653.0849812 iteration: 43585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1013 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.16547 L1 loss: 0.0000e+00 L2 loss: 0.62312 Learning rate: 0.002 Mask loss: 0.09339 RPN box loss: 0.02866 RPN score loss: 0.00254 RPN total loss: 0.0312 Total loss: 0.91317 timestamp: 1654948656.240902 iteration: 43590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10909 FastRCNN class loss: 0.04172 FastRCNN total loss: 0.15081 L1 loss: 0.0000e+00 L2 loss: 0.62311 Learning rate: 0.002 Mask loss: 0.12218 RPN box loss: 0.00708 RPN score loss: 0.00264 RPN total loss: 0.00973 Total loss: 0.90583 timestamp: 1654948659.3881814 iteration: 43595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09599 FastRCNN class loss: 0.12395 FastRCNN total loss: 0.21995 L1 loss: 0.0000e+00 L2 loss: 0.6231 Learning rate: 0.002 Mask loss: 0.21624 RPN box loss: 0.02332 RPN score loss: 0.01338 RPN total loss: 0.0367 Total loss: 1.096 timestamp: 1654948662.6375263 iteration: 43600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08315 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.14223 L1 loss: 0.0000e+00 L2 loss: 0.62309 Learning rate: 0.002 Mask loss: 0.1641 RPN box loss: 0.03201 RPN score loss: 0.01474 RPN total loss: 0.04674 Total loss: 0.97616 timestamp: 1654948665.8292542 iteration: 43605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05327 FastRCNN class loss: 0.04212 FastRCNN total loss: 0.0954 L1 loss: 0.0000e+00 L2 loss: 0.62309 Learning rate: 0.002 Mask loss: 0.07268 RPN box loss: 0.00686 RPN score loss: 0.00105 RPN total loss: 0.00792 Total loss: 0.79908 timestamp: 1654948668.9877224 iteration: 43610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07109 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.1207 L1 loss: 0.0000e+00 L2 loss: 0.62308 Learning rate: 0.002 Mask loss: 0.12456 RPN box loss: 0.00909 RPN score loss: 0.00142 RPN total loss: 0.01051 Total loss: 0.87885 timestamp: 1654948672.200012 iteration: 43615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11031 FastRCNN class loss: 0.11273 FastRCNN total loss: 0.22304 L1 loss: 0.0000e+00 L2 loss: 0.62307 Learning rate: 0.002 Mask loss: 0.15178 RPN box loss: 0.00973 RPN score loss: 0.00416 RPN total loss: 0.01389 Total loss: 1.01178 timestamp: 1654948675.3943586 iteration: 43620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13726 FastRCNN class loss: 0.07858 FastRCNN total loss: 0.21584 L1 loss: 0.0000e+00 L2 loss: 0.62306 Learning rate: 0.002 Mask loss: 0.11878 RPN box loss: 0.02178 RPN score loss: 0.00581 RPN total loss: 0.02759 Total loss: 0.98526 timestamp: 1654948678.5927818 iteration: 43625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09956 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.15944 L1 loss: 0.0000e+00 L2 loss: 0.62305 Learning rate: 0.002 Mask loss: 0.13295 RPN box loss: 0.03606 RPN score loss: 0.00288 RPN total loss: 0.03893 Total loss: 0.95438 timestamp: 1654948681.826314 iteration: 43630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09329 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.1549 L1 loss: 0.0000e+00 L2 loss: 0.62304 Learning rate: 0.002 Mask loss: 0.11594 RPN box loss: 0.00743 RPN score loss: 0.003 RPN total loss: 0.01043 Total loss: 0.90431 timestamp: 1654948685.0604126 iteration: 43635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14639 FastRCNN class loss: 0.14192 FastRCNN total loss: 0.28831 L1 loss: 0.0000e+00 L2 loss: 0.62303 Learning rate: 0.002 Mask loss: 0.18913 RPN box loss: 0.05347 RPN score loss: 0.01036 RPN total loss: 0.06383 Total loss: 1.1643 timestamp: 1654948688.1896229 iteration: 43640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08226 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.13459 L1 loss: 0.0000e+00 L2 loss: 0.62302 Learning rate: 0.002 Mask loss: 0.10435 RPN box loss: 0.02563 RPN score loss: 0.00346 RPN total loss: 0.02908 Total loss: 0.89105 timestamp: 1654948691.383348 iteration: 43645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12984 FastRCNN class loss: 0.09021 FastRCNN total loss: 0.22006 L1 loss: 0.0000e+00 L2 loss: 0.62301 Learning rate: 0.002 Mask loss: 0.12806 RPN box loss: 0.02546 RPN score loss: 0.01211 RPN total loss: 0.03757 Total loss: 1.0087 timestamp: 1654948694.595665 iteration: 43650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08623 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.1452 L1 loss: 0.0000e+00 L2 loss: 0.623 Learning rate: 0.002 Mask loss: 0.11749 RPN box loss: 0.00978 RPN score loss: 0.00619 RPN total loss: 0.01597 Total loss: 0.90166 timestamp: 1654948697.8302567 iteration: 43655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12533 FastRCNN class loss: 0.11385 FastRCNN total loss: 0.23918 L1 loss: 0.0000e+00 L2 loss: 0.623 Learning rate: 0.002 Mask loss: 0.20674 RPN box loss: 0.01561 RPN score loss: 0.00647 RPN total loss: 0.02208 Total loss: 1.09099 timestamp: 1654948701.0939817 iteration: 43660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13644 FastRCNN class loss: 0.07716 FastRCNN total loss: 0.2136 L1 loss: 0.0000e+00 L2 loss: 0.62299 Learning rate: 0.002 Mask loss: 0.09163 RPN box loss: 0.03241 RPN score loss: 0.01366 RPN total loss: 0.04606 Total loss: 0.97427 timestamp: 1654948704.300171 iteration: 43665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14098 FastRCNN class loss: 0.10273 FastRCNN total loss: 0.24371 L1 loss: 0.0000e+00 L2 loss: 0.62298 Learning rate: 0.002 Mask loss: 0.12382 RPN box loss: 0.01303 RPN score loss: 0.00656 RPN total loss: 0.01958 Total loss: 1.01009 timestamp: 1654948707.4292655 iteration: 43670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12689 FastRCNN class loss: 0.04809 FastRCNN total loss: 0.17498 L1 loss: 0.0000e+00 L2 loss: 0.62296 Learning rate: 0.002 Mask loss: 0.10904 RPN box loss: 0.00987 RPN score loss: 0.00185 RPN total loss: 0.01172 Total loss: 0.9187 timestamp: 1654948710.5837784 iteration: 43675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1024 FastRCNN class loss: 0.1291 FastRCNN total loss: 0.2315 L1 loss: 0.0000e+00 L2 loss: 0.62295 Learning rate: 0.002 Mask loss: 0.14955 RPN box loss: 0.02286 RPN score loss: 0.00897 RPN total loss: 0.03183 Total loss: 1.03583 timestamp: 1654948713.8299696 iteration: 43680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07739 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.13787 L1 loss: 0.0000e+00 L2 loss: 0.62294 Learning rate: 0.002 Mask loss: 0.14654 RPN box loss: 0.01848 RPN score loss: 0.00308 RPN total loss: 0.02157 Total loss: 0.92892 timestamp: 1654948717.092491 iteration: 43685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05608 FastRCNN class loss: 0.05394 FastRCNN total loss: 0.11003 L1 loss: 0.0000e+00 L2 loss: 0.62293 Learning rate: 0.002 Mask loss: 0.13043 RPN box loss: 0.01592 RPN score loss: 0.02241 RPN total loss: 0.03833 Total loss: 0.90172 timestamp: 1654948720.3123522 iteration: 43690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14652 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.26655 L1 loss: 0.0000e+00 L2 loss: 0.62292 Learning rate: 0.002 Mask loss: 0.15197 RPN box loss: 0.01878 RPN score loss: 0.00209 RPN total loss: 0.02087 Total loss: 1.06231 timestamp: 1654948723.4556415 iteration: 43695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0871 FastRCNN class loss: 0.051 FastRCNN total loss: 0.1381 L1 loss: 0.0000e+00 L2 loss: 0.62291 Learning rate: 0.002 Mask loss: 0.10847 RPN box loss: 0.01481 RPN score loss: 0.00486 RPN total loss: 0.01968 Total loss: 0.88916 timestamp: 1654948726.6590757 iteration: 43700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12295 FastRCNN class loss: 0.09467 FastRCNN total loss: 0.21762 L1 loss: 0.0000e+00 L2 loss: 0.6229 Learning rate: 0.002 Mask loss: 0.16005 RPN box loss: 0.02716 RPN score loss: 0.01504 RPN total loss: 0.0422 Total loss: 1.04277 timestamp: 1654948729.9027128 iteration: 43705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09765 FastRCNN class loss: 0.04762 FastRCNN total loss: 0.14527 L1 loss: 0.0000e+00 L2 loss: 0.6229 Learning rate: 0.002 Mask loss: 0.08565 RPN box loss: 0.00916 RPN score loss: 0.00374 RPN total loss: 0.0129 Total loss: 0.86672 timestamp: 1654948733.102735 iteration: 43710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07312 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.13513 L1 loss: 0.0000e+00 L2 loss: 0.62289 Learning rate: 0.002 Mask loss: 0.22729 RPN box loss: 0.01744 RPN score loss: 0.00955 RPN total loss: 0.02699 Total loss: 1.01229 timestamp: 1654948736.296941 iteration: 43715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06209 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.12926 L1 loss: 0.0000e+00 L2 loss: 0.62288 Learning rate: 0.002 Mask loss: 0.10889 RPN box loss: 0.00963 RPN score loss: 0.00776 RPN total loss: 0.01739 Total loss: 0.87842 timestamp: 1654948739.4747705 iteration: 43720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08553 FastRCNN class loss: 0.08027 FastRCNN total loss: 0.1658 L1 loss: 0.0000e+00 L2 loss: 0.62287 Learning rate: 0.002 Mask loss: 0.11289 RPN box loss: 0.01781 RPN score loss: 0.00545 RPN total loss: 0.02326 Total loss: 0.92481 timestamp: 1654948742.7073617 iteration: 43725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1031 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.18086 L1 loss: 0.0000e+00 L2 loss: 0.62285 Learning rate: 0.002 Mask loss: 0.19065 RPN box loss: 0.01795 RPN score loss: 0.01332 RPN total loss: 0.03127 Total loss: 1.02563 timestamp: 1654948745.9496531 iteration: 43730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16225 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.25705 L1 loss: 0.0000e+00 L2 loss: 0.62285 Learning rate: 0.002 Mask loss: 0.20427 RPN box loss: 0.0106 RPN score loss: 0.01301 RPN total loss: 0.02361 Total loss: 1.10778 timestamp: 1654948749.1380646 iteration: 43735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04913 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.11945 L1 loss: 0.0000e+00 L2 loss: 0.62284 Learning rate: 0.002 Mask loss: 0.1306 RPN box loss: 0.0214 RPN score loss: 0.00373 RPN total loss: 0.02513 Total loss: 0.89802 timestamp: 1654948752.2808666 iteration: 43740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09784 FastRCNN class loss: 0.06 FastRCNN total loss: 0.15784 L1 loss: 0.0000e+00 L2 loss: 0.62283 Learning rate: 0.002 Mask loss: 0.11001 RPN box loss: 0.00824 RPN score loss: 0.00151 RPN total loss: 0.00975 Total loss: 0.90042 timestamp: 1654948755.4703557 iteration: 43745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10459 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.16798 L1 loss: 0.0000e+00 L2 loss: 0.62282 Learning rate: 0.002 Mask loss: 0.14756 RPN box loss: 0.00956 RPN score loss: 0.00436 RPN total loss: 0.01392 Total loss: 0.95228 timestamp: 1654948758.708762 iteration: 43750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12878 FastRCNN class loss: 0.07612 FastRCNN total loss: 0.2049 L1 loss: 0.0000e+00 L2 loss: 0.62281 Learning rate: 0.002 Mask loss: 0.13568 RPN box loss: 0.02528 RPN score loss: 0.00392 RPN total loss: 0.0292 Total loss: 0.99259 timestamp: 1654948761.9464853 iteration: 43755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09906 FastRCNN class loss: 0.04088 FastRCNN total loss: 0.13994 L1 loss: 0.0000e+00 L2 loss: 0.6228 Learning rate: 0.002 Mask loss: 0.12884 RPN box loss: 0.01075 RPN score loss: 0.00611 RPN total loss: 0.01686 Total loss: 0.90845 timestamp: 1654948765.084235 iteration: 43760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07585 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.13514 L1 loss: 0.0000e+00 L2 loss: 0.62279 Learning rate: 0.002 Mask loss: 0.12991 RPN box loss: 0.00884 RPN score loss: 0.00429 RPN total loss: 0.01313 Total loss: 0.90097 timestamp: 1654948768.239818 iteration: 43765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09094 FastRCNN class loss: 0.05612 FastRCNN total loss: 0.14706 L1 loss: 0.0000e+00 L2 loss: 0.62278 Learning rate: 0.002 Mask loss: 0.14813 RPN box loss: 0.01167 RPN score loss: 0.00475 RPN total loss: 0.01642 Total loss: 0.93439 timestamp: 1654948771.3997533 iteration: 43770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10978 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.16282 L1 loss: 0.0000e+00 L2 loss: 0.62277 Learning rate: 0.002 Mask loss: 0.13804 RPN box loss: 0.01658 RPN score loss: 0.00551 RPN total loss: 0.02209 Total loss: 0.94572 timestamp: 1654948774.5809987 iteration: 43775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08143 FastRCNN class loss: 0.06047 FastRCNN total loss: 0.1419 L1 loss: 0.0000e+00 L2 loss: 0.62276 Learning rate: 0.002 Mask loss: 0.11735 RPN box loss: 0.01948 RPN score loss: 0.00973 RPN total loss: 0.0292 Total loss: 0.91122 timestamp: 1654948777.7530763 iteration: 43780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.17557 L1 loss: 0.0000e+00 L2 loss: 0.62276 Learning rate: 0.002 Mask loss: 0.07633 RPN box loss: 0.03045 RPN score loss: 0.00486 RPN total loss: 0.03532 Total loss: 0.90998 timestamp: 1654948780.9545825 iteration: 43785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.07925 FastRCNN total loss: 0.2205 L1 loss: 0.0000e+00 L2 loss: 0.62275 Learning rate: 0.002 Mask loss: 0.18476 RPN box loss: 0.01313 RPN score loss: 0.00605 RPN total loss: 0.01918 Total loss: 1.04719 timestamp: 1654948784.1469567 iteration: 43790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11858 FastRCNN class loss: 0.09174 FastRCNN total loss: 0.21033 L1 loss: 0.0000e+00 L2 loss: 0.62274 Learning rate: 0.002 Mask loss: 0.21955 RPN box loss: 0.02566 RPN score loss: 0.01149 RPN total loss: 0.03716 Total loss: 1.08978 timestamp: 1654948787.347682 iteration: 43795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14926 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.23876 L1 loss: 0.0000e+00 L2 loss: 0.62273 Learning rate: 0.002 Mask loss: 0.11251 RPN box loss: 0.01852 RPN score loss: 0.00234 RPN total loss: 0.02086 Total loss: 0.99485 timestamp: 1654948790.5624466 iteration: 43800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12385 FastRCNN class loss: 0.07887 FastRCNN total loss: 0.20271 L1 loss: 0.0000e+00 L2 loss: 0.62272 Learning rate: 0.002 Mask loss: 0.12913 RPN box loss: 0.0127 RPN score loss: 0.00328 RPN total loss: 0.01597 Total loss: 0.97054 timestamp: 1654948793.700967 iteration: 43805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11396 FastRCNN class loss: 0.10419 FastRCNN total loss: 0.21815 L1 loss: 0.0000e+00 L2 loss: 0.62271 Learning rate: 0.002 Mask loss: 0.25402 RPN box loss: 0.02893 RPN score loss: 0.01021 RPN total loss: 0.03914 Total loss: 1.13402 timestamp: 1654948796.872724 iteration: 43810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11721 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.21744 L1 loss: 0.0000e+00 L2 loss: 0.6227 Learning rate: 0.002 Mask loss: 0.11978 RPN box loss: 0.01626 RPN score loss: 0.00483 RPN total loss: 0.02109 Total loss: 0.98101 timestamp: 1654948800.084724 iteration: 43815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07972 FastRCNN class loss: 0.06355 FastRCNN total loss: 0.14327 L1 loss: 0.0000e+00 L2 loss: 0.62269 Learning rate: 0.002 Mask loss: 0.0958 RPN box loss: 0.03186 RPN score loss: 0.00304 RPN total loss: 0.0349 Total loss: 0.89667 timestamp: 1654948803.233675 iteration: 43820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09483 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.16024 L1 loss: 0.0000e+00 L2 loss: 0.62269 Learning rate: 0.002 Mask loss: 0.1519 RPN box loss: 0.04461 RPN score loss: 0.00114 RPN total loss: 0.04575 Total loss: 0.98056 timestamp: 1654948806.419179 iteration: 43825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13609 FastRCNN class loss: 0.1192 FastRCNN total loss: 0.25529 L1 loss: 0.0000e+00 L2 loss: 0.62268 Learning rate: 0.002 Mask loss: 0.1613 RPN box loss: 0.04517 RPN score loss: 0.01308 RPN total loss: 0.05825 Total loss: 1.09752 timestamp: 1654948809.677655 iteration: 43830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10226 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.17532 L1 loss: 0.0000e+00 L2 loss: 0.62267 Learning rate: 0.002 Mask loss: 0.07527 RPN box loss: 0.01722 RPN score loss: 0.00442 RPN total loss: 0.02163 Total loss: 0.89489 timestamp: 1654948812.8670523 iteration: 43835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10682 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.18444 L1 loss: 0.0000e+00 L2 loss: 0.62266 Learning rate: 0.002 Mask loss: 0.10552 RPN box loss: 0.00907 RPN score loss: 0.00269 RPN total loss: 0.01176 Total loss: 0.92438 timestamp: 1654948816.0238788 iteration: 43840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05626 FastRCNN class loss: 0.03477 FastRCNN total loss: 0.09103 L1 loss: 0.0000e+00 L2 loss: 0.62265 Learning rate: 0.002 Mask loss: 0.09588 RPN box loss: 0.00489 RPN score loss: 0.00252 RPN total loss: 0.00741 Total loss: 0.81697 timestamp: 1654948819.2493224 iteration: 43845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0905 FastRCNN class loss: 0.07874 FastRCNN total loss: 0.16924 L1 loss: 0.0000e+00 L2 loss: 0.62264 Learning rate: 0.002 Mask loss: 0.16185 RPN box loss: 0.01073 RPN score loss: 0.00152 RPN total loss: 0.01224 Total loss: 0.96597 timestamp: 1654948822.4481614 iteration: 43850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13967 FastRCNN class loss: 0.04507 FastRCNN total loss: 0.18474 L1 loss: 0.0000e+00 L2 loss: 0.62263 Learning rate: 0.002 Mask loss: 0.0887 RPN box loss: 0.01865 RPN score loss: 0.005 RPN total loss: 0.02365 Total loss: 0.91972 timestamp: 1654948825.563303 iteration: 43855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.141 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.19908 L1 loss: 0.0000e+00 L2 loss: 0.62262 Learning rate: 0.002 Mask loss: 0.13803 RPN box loss: 0.00556 RPN score loss: 0.00544 RPN total loss: 0.01101 Total loss: 0.97074 timestamp: 1654948828.718962 iteration: 43860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0879 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.17285 L1 loss: 0.0000e+00 L2 loss: 0.62261 Learning rate: 0.002 Mask loss: 0.16422 RPN box loss: 0.0101 RPN score loss: 0.00167 RPN total loss: 0.01177 Total loss: 0.97146 timestamp: 1654948831.8620267 iteration: 43865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06976 FastRCNN class loss: 0.04985 FastRCNN total loss: 0.1196 L1 loss: 0.0000e+00 L2 loss: 0.6226 Learning rate: 0.002 Mask loss: 0.1196 RPN box loss: 0.00759 RPN score loss: 0.0013 RPN total loss: 0.00889 Total loss: 0.87069 timestamp: 1654948835.0510576 iteration: 43870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07483 FastRCNN class loss: 0.068 FastRCNN total loss: 0.14283 L1 loss: 0.0000e+00 L2 loss: 0.62259 Learning rate: 0.002 Mask loss: 0.1613 RPN box loss: 0.00901 RPN score loss: 0.00409 RPN total loss: 0.0131 Total loss: 0.93983 timestamp: 1654948838.3392184 iteration: 43875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13087 FastRCNN class loss: 0.08136 FastRCNN total loss: 0.21223 L1 loss: 0.0000e+00 L2 loss: 0.62258 Learning rate: 0.002 Mask loss: 0.14778 RPN box loss: 0.01666 RPN score loss: 0.01135 RPN total loss: 0.02802 Total loss: 1.0106 timestamp: 1654948841.4376636 iteration: 43880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15284 FastRCNN class loss: 0.07811 FastRCNN total loss: 0.23095 L1 loss: 0.0000e+00 L2 loss: 0.62257 Learning rate: 0.002 Mask loss: 0.17547 RPN box loss: 0.02276 RPN score loss: 0.01156 RPN total loss: 0.03432 Total loss: 1.06332 timestamp: 1654948844.6761935 iteration: 43885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06544 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.13019 L1 loss: 0.0000e+00 L2 loss: 0.62257 Learning rate: 0.002 Mask loss: 0.15958 RPN box loss: 0.00932 RPN score loss: 0.00476 RPN total loss: 0.01408 Total loss: 0.92642 timestamp: 1654948847.8681598 iteration: 43890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08451 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.14896 L1 loss: 0.0000e+00 L2 loss: 0.62256 Learning rate: 0.002 Mask loss: 0.20771 RPN box loss: 0.01064 RPN score loss: 0.00742 RPN total loss: 0.01807 Total loss: 0.9973 timestamp: 1654948851.020926 iteration: 43895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09461 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.15847 L1 loss: 0.0000e+00 L2 loss: 0.62254 Learning rate: 0.002 Mask loss: 0.13912 RPN box loss: 0.03357 RPN score loss: 0.00255 RPN total loss: 0.03612 Total loss: 0.95626 timestamp: 1654948854.228039 iteration: 43900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08933 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.16125 L1 loss: 0.0000e+00 L2 loss: 0.62253 Learning rate: 0.002 Mask loss: 0.13981 RPN box loss: 0.039 RPN score loss: 0.00638 RPN total loss: 0.04538 Total loss: 0.96896 timestamp: 1654948857.4456806 iteration: 43905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10184 FastRCNN class loss: 0.07642 FastRCNN total loss: 0.17826 L1 loss: 0.0000e+00 L2 loss: 0.62252 Learning rate: 0.002 Mask loss: 0.10202 RPN box loss: 0.00988 RPN score loss: 0.00537 RPN total loss: 0.01525 Total loss: 0.91804 timestamp: 1654948860.6104918 iteration: 43910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09344 FastRCNN class loss: 0.09017 FastRCNN total loss: 0.18361 L1 loss: 0.0000e+00 L2 loss: 0.62251 Learning rate: 0.002 Mask loss: 0.1463 RPN box loss: 0.02958 RPN score loss: 0.0081 RPN total loss: 0.03768 Total loss: 0.99011 timestamp: 1654948863.8085647 iteration: 43915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13528 FastRCNN class loss: 0.08415 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.6225 Learning rate: 0.002 Mask loss: 0.09683 RPN box loss: 0.01084 RPN score loss: 0.0075 RPN total loss: 0.01834 Total loss: 0.95711 timestamp: 1654948867.0274575 iteration: 43920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12285 FastRCNN class loss: 0.05725 FastRCNN total loss: 0.1801 L1 loss: 0.0000e+00 L2 loss: 0.62249 Learning rate: 0.002 Mask loss: 0.16707 RPN box loss: 0.01398 RPN score loss: 0.00407 RPN total loss: 0.01805 Total loss: 0.98771 timestamp: 1654948870.2811906 iteration: 43925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0885 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.15439 L1 loss: 0.0000e+00 L2 loss: 0.62249 Learning rate: 0.002 Mask loss: 0.1171 RPN box loss: 0.00762 RPN score loss: 0.0018 RPN total loss: 0.00943 Total loss: 0.90339 timestamp: 1654948873.5178971 iteration: 43930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.13607 L1 loss: 0.0000e+00 L2 loss: 0.62248 Learning rate: 0.002 Mask loss: 0.08222 RPN box loss: 0.02879 RPN score loss: 0.00191 RPN total loss: 0.0307 Total loss: 0.87147 timestamp: 1654948876.7003896 iteration: 43935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15388 FastRCNN class loss: 0.08299 FastRCNN total loss: 0.23687 L1 loss: 0.0000e+00 L2 loss: 0.62247 Learning rate: 0.002 Mask loss: 0.18564 RPN box loss: 0.01007 RPN score loss: 0.00801 RPN total loss: 0.01808 Total loss: 1.06305 timestamp: 1654948879.9111333 iteration: 43940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07945 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.15137 L1 loss: 0.0000e+00 L2 loss: 0.62246 Learning rate: 0.002 Mask loss: 0.13656 RPN box loss: 0.02113 RPN score loss: 0.00788 RPN total loss: 0.02901 Total loss: 0.9394 timestamp: 1654948883.1333044 iteration: 43945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10271 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.17548 L1 loss: 0.0000e+00 L2 loss: 0.62245 Learning rate: 0.002 Mask loss: 0.16456 RPN box loss: 0.0149 RPN score loss: 0.00272 RPN total loss: 0.01762 Total loss: 0.98011 timestamp: 1654948886.3176928 iteration: 43950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10977 FastRCNN class loss: 0.13472 FastRCNN total loss: 0.24449 L1 loss: 0.0000e+00 L2 loss: 0.62244 Learning rate: 0.002 Mask loss: 0.14173 RPN box loss: 0.0178 RPN score loss: 0.01076 RPN total loss: 0.02856 Total loss: 1.03722 timestamp: 1654948889.5371623 iteration: 43955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.07649 FastRCNN total loss: 0.17713 L1 loss: 0.0000e+00 L2 loss: 0.62243 Learning rate: 0.002 Mask loss: 0.15277 RPN box loss: 0.00735 RPN score loss: 0.00253 RPN total loss: 0.00988 Total loss: 0.96221 timestamp: 1654948892.7215767 iteration: 43960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1162 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.17312 L1 loss: 0.0000e+00 L2 loss: 0.62242 Learning rate: 0.002 Mask loss: 0.13898 RPN box loss: 0.02637 RPN score loss: 0.00519 RPN total loss: 0.03156 Total loss: 0.96608 timestamp: 1654948895.894544 iteration: 43965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1381 FastRCNN class loss: 0.08727 FastRCNN total loss: 0.22537 L1 loss: 0.0000e+00 L2 loss: 0.62241 Learning rate: 0.002 Mask loss: 0.21574 RPN box loss: 0.01837 RPN score loss: 0.00978 RPN total loss: 0.02816 Total loss: 1.09168 timestamp: 1654948899.0824232 iteration: 43970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09844 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.16381 L1 loss: 0.0000e+00 L2 loss: 0.6224 Learning rate: 0.002 Mask loss: 0.16844 RPN box loss: 0.00779 RPN score loss: 0.0124 RPN total loss: 0.02019 Total loss: 0.97484 timestamp: 1654948902.295463 iteration: 43975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1346 FastRCNN class loss: 0.11217 FastRCNN total loss: 0.24677 L1 loss: 0.0000e+00 L2 loss: 0.62239 Learning rate: 0.002 Mask loss: 0.16385 RPN box loss: 0.03245 RPN score loss: 0.01391 RPN total loss: 0.04635 Total loss: 1.07936 timestamp: 1654948905.516903 iteration: 43980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09605 FastRCNN class loss: 0.07332 FastRCNN total loss: 0.16936 L1 loss: 0.0000e+00 L2 loss: 0.62238 Learning rate: 0.002 Mask loss: 0.1817 RPN box loss: 0.02129 RPN score loss: 0.00539 RPN total loss: 0.02668 Total loss: 1.00012 timestamp: 1654948908.7163217 iteration: 43985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14548 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.20332 L1 loss: 0.0000e+00 L2 loss: 0.62237 Learning rate: 0.002 Mask loss: 0.08663 RPN box loss: 0.00652 RPN score loss: 0.00279 RPN total loss: 0.0093 Total loss: 0.92163 timestamp: 1654948911.9245446 iteration: 43990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14453 FastRCNN class loss: 0.09406 FastRCNN total loss: 0.23859 L1 loss: 0.0000e+00 L2 loss: 0.62236 Learning rate: 0.002 Mask loss: 0.15413 RPN box loss: 0.00893 RPN score loss: 0.00253 RPN total loss: 0.01146 Total loss: 1.02655 timestamp: 1654948915.106618 iteration: 43995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06068 FastRCNN class loss: 0.05983 FastRCNN total loss: 0.12051 L1 loss: 0.0000e+00 L2 loss: 0.62235 Learning rate: 0.002 Mask loss: 0.09606 RPN box loss: 0.02971 RPN score loss: 0.00673 RPN total loss: 0.03644 Total loss: 0.87536 timestamp: 1654948918.321286 iteration: 44000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20296 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.27792 L1 loss: 0.0000e+00 L2 loss: 0.62234 Learning rate: 0.002 Mask loss: 0.11571 RPN box loss: 0.02168 RPN score loss: 0.00542 RPN total loss: 0.0271 Total loss: 1.04306 timestamp: 1654948921.5330632 iteration: 44005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07842 FastRCNN class loss: 0.12457 FastRCNN total loss: 0.20299 L1 loss: 0.0000e+00 L2 loss: 0.62233 Learning rate: 0.002 Mask loss: 0.11284 RPN box loss: 0.011 RPN score loss: 0.00345 RPN total loss: 0.01444 Total loss: 0.9526 timestamp: 1654948924.7534943 iteration: 44010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12967 FastRCNN class loss: 0.09939 FastRCNN total loss: 0.22905 L1 loss: 0.0000e+00 L2 loss: 0.62232 Learning rate: 0.002 Mask loss: 0.13555 RPN box loss: 0.02877 RPN score loss: 0.00575 RPN total loss: 0.03452 Total loss: 1.02145 timestamp: 1654948927.9449832 iteration: 44015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11866 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.18234 L1 loss: 0.0000e+00 L2 loss: 0.62231 Learning rate: 0.002 Mask loss: 0.09334 RPN box loss: 0.01783 RPN score loss: 0.00716 RPN total loss: 0.02498 Total loss: 0.92297 timestamp: 1654948931.2556977 iteration: 44020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10372 FastRCNN class loss: 0.07369 FastRCNN total loss: 0.17741 L1 loss: 0.0000e+00 L2 loss: 0.6223 Learning rate: 0.002 Mask loss: 0.14187 RPN box loss: 0.05794 RPN score loss: 0.00584 RPN total loss: 0.06378 Total loss: 1.00536 timestamp: 1654948934.503497 iteration: 44025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11389 FastRCNN class loss: 0.06065 FastRCNN total loss: 0.17454 L1 loss: 0.0000e+00 L2 loss: 0.62229 Learning rate: 0.002 Mask loss: 0.13517 RPN box loss: 0.02464 RPN score loss: 0.00324 RPN total loss: 0.02788 Total loss: 0.95988 timestamp: 1654948937.6354876 iteration: 44030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12409 FastRCNN class loss: 0.07957 FastRCNN total loss: 0.20366 L1 loss: 0.0000e+00 L2 loss: 0.62228 Learning rate: 0.002 Mask loss: 0.15413 RPN box loss: 0.00865 RPN score loss: 0.00078 RPN total loss: 0.00943 Total loss: 0.98951 timestamp: 1654948940.8109405 iteration: 44035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12584 FastRCNN class loss: 0.07816 FastRCNN total loss: 0.204 L1 loss: 0.0000e+00 L2 loss: 0.62227 Learning rate: 0.002 Mask loss: 0.12203 RPN box loss: 0.02043 RPN score loss: 0.0066 RPN total loss: 0.02702 Total loss: 0.97533 timestamp: 1654948943.9682212 iteration: 44040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13166 FastRCNN class loss: 0.13317 FastRCNN total loss: 0.26483 L1 loss: 0.0000e+00 L2 loss: 0.62227 Learning rate: 0.002 Mask loss: 0.20901 RPN box loss: 0.02549 RPN score loss: 0.00918 RPN total loss: 0.03467 Total loss: 1.13077 timestamp: 1654948947.1112113 iteration: 44045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06519 FastRCNN class loss: 0.044 FastRCNN total loss: 0.10919 L1 loss: 0.0000e+00 L2 loss: 0.62226 Learning rate: 0.002 Mask loss: 0.16297 RPN box loss: 0.03166 RPN score loss: 0.00536 RPN total loss: 0.03703 Total loss: 0.93144 timestamp: 1654948950.3259525 iteration: 44050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07837 FastRCNN class loss: 0.04311 FastRCNN total loss: 0.12148 L1 loss: 0.0000e+00 L2 loss: 0.62225 Learning rate: 0.002 Mask loss: 0.10082 RPN box loss: 0.01289 RPN score loss: 0.00372 RPN total loss: 0.01662 Total loss: 0.86116 timestamp: 1654948953.5149288 iteration: 44055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08857 FastRCNN class loss: 0.06015 FastRCNN total loss: 0.14873 L1 loss: 0.0000e+00 L2 loss: 0.62224 Learning rate: 0.002 Mask loss: 0.12889 RPN box loss: 0.03042 RPN score loss: 0.00758 RPN total loss: 0.03799 Total loss: 0.93784 timestamp: 1654948956.7093806 iteration: 44060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1859 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.26028 L1 loss: 0.0000e+00 L2 loss: 0.62222 Learning rate: 0.002 Mask loss: 0.12085 RPN box loss: 0.0372 RPN score loss: 0.00377 RPN total loss: 0.04097 Total loss: 1.04433 timestamp: 1654948959.9039826 iteration: 44065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09209 FastRCNN class loss: 0.05276 FastRCNN total loss: 0.14485 L1 loss: 0.0000e+00 L2 loss: 0.62221 Learning rate: 0.002 Mask loss: 0.13318 RPN box loss: 0.00773 RPN score loss: 0.00226 RPN total loss: 0.00999 Total loss: 0.91024 timestamp: 1654948963.0520148 iteration: 44070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.0493 FastRCNN total loss: 0.14727 L1 loss: 0.0000e+00 L2 loss: 0.6222 Learning rate: 0.002 Mask loss: 0.13638 RPN box loss: 0.00672 RPN score loss: 0.00248 RPN total loss: 0.0092 Total loss: 0.91506 timestamp: 1654948966.240595 iteration: 44075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06433 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.12666 L1 loss: 0.0000e+00 L2 loss: 0.62219 Learning rate: 0.002 Mask loss: 0.14198 RPN box loss: 0.01199 RPN score loss: 0.00726 RPN total loss: 0.01925 Total loss: 0.91009 timestamp: 1654948969.423805 iteration: 44080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09948 FastRCNN class loss: 0.07583 FastRCNN total loss: 0.17532 L1 loss: 0.0000e+00 L2 loss: 0.62218 Learning rate: 0.002 Mask loss: 0.14841 RPN box loss: 0.01527 RPN score loss: 0.00841 RPN total loss: 0.02368 Total loss: 0.96959 timestamp: 1654948972.6813738 iteration: 44085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16593 FastRCNN class loss: 0.12551 FastRCNN total loss: 0.29144 L1 loss: 0.0000e+00 L2 loss: 0.62218 Learning rate: 0.002 Mask loss: 0.2023 RPN box loss: 0.02125 RPN score loss: 0.00682 RPN total loss: 0.02806 Total loss: 1.14397 timestamp: 1654948975.9841733 iteration: 44090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.10779 FastRCNN total loss: 0.21317 L1 loss: 0.0000e+00 L2 loss: 0.62217 Learning rate: 0.002 Mask loss: 0.14735 RPN box loss: 0.03053 RPN score loss: 0.00514 RPN total loss: 0.03566 Total loss: 1.01835 timestamp: 1654948979.1826797 iteration: 44095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0636 FastRCNN class loss: 0.07768 FastRCNN total loss: 0.14128 L1 loss: 0.0000e+00 L2 loss: 0.62216 Learning rate: 0.002 Mask loss: 0.11142 RPN box loss: 0.01027 RPN score loss: 0.00542 RPN total loss: 0.01569 Total loss: 0.89055 timestamp: 1654948982.3444889 iteration: 44100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1581 FastRCNN class loss: 0.08156 FastRCNN total loss: 0.23966 L1 loss: 0.0000e+00 L2 loss: 0.62215 Learning rate: 0.002 Mask loss: 0.13033 RPN box loss: 0.03064 RPN score loss: 0.00692 RPN total loss: 0.03756 Total loss: 1.0297 timestamp: 1654948985.5458105 iteration: 44105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16407 FastRCNN class loss: 0.10276 FastRCNN total loss: 0.26682 L1 loss: 0.0000e+00 L2 loss: 0.62214 Learning rate: 0.002 Mask loss: 0.17065 RPN box loss: 0.011 RPN score loss: 0.00378 RPN total loss: 0.01478 Total loss: 1.07439 timestamp: 1654948988.8096092 iteration: 44110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14742 FastRCNN class loss: 0.09137 FastRCNN total loss: 0.23879 L1 loss: 0.0000e+00 L2 loss: 0.62213 Learning rate: 0.002 Mask loss: 0.1433 RPN box loss: 0.00922 RPN score loss: 0.00495 RPN total loss: 0.01417 Total loss: 1.0184 timestamp: 1654948991.9979124 iteration: 44115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10394 FastRCNN class loss: 0.09869 FastRCNN total loss: 0.20262 L1 loss: 0.0000e+00 L2 loss: 0.62212 Learning rate: 0.002 Mask loss: 0.12285 RPN box loss: 0.01724 RPN score loss: 0.0102 RPN total loss: 0.02745 Total loss: 0.97505 timestamp: 1654948995.2038264 iteration: 44120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15518 FastRCNN class loss: 0.09047 FastRCNN total loss: 0.24565 L1 loss: 0.0000e+00 L2 loss: 0.62211 Learning rate: 0.002 Mask loss: 0.16992 RPN box loss: 0.0311 RPN score loss: 0.00943 RPN total loss: 0.04053 Total loss: 1.07822 timestamp: 1654948998.3890288 iteration: 44125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17481 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.24242 L1 loss: 0.0000e+00 L2 loss: 0.6221 Learning rate: 0.002 Mask loss: 0.13064 RPN box loss: 0.0273 RPN score loss: 0.00599 RPN total loss: 0.03329 Total loss: 1.02845 timestamp: 1654949001.4849162 iteration: 44130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1349 FastRCNN class loss: 0.16814 FastRCNN total loss: 0.30304 L1 loss: 0.0000e+00 L2 loss: 0.6221 Learning rate: 0.002 Mask loss: 0.24732 RPN box loss: 0.03512 RPN score loss: 0.08317 RPN total loss: 0.11829 Total loss: 1.29074 timestamp: 1654949004.6578717 iteration: 44135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04369 FastRCNN class loss: 0.04954 FastRCNN total loss: 0.09323 L1 loss: 0.0000e+00 L2 loss: 0.62209 Learning rate: 0.002 Mask loss: 0.11707 RPN box loss: 0.02189 RPN score loss: 0.00363 RPN total loss: 0.02552 Total loss: 0.85791 timestamp: 1654949007.8319001 iteration: 44140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15646 FastRCNN class loss: 0.0671 FastRCNN total loss: 0.22356 L1 loss: 0.0000e+00 L2 loss: 0.62208 Learning rate: 0.002 Mask loss: 0.1235 RPN box loss: 0.01643 RPN score loss: 0.00304 RPN total loss: 0.01947 Total loss: 0.98861 timestamp: 1654949011.047886 iteration: 44145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1043 FastRCNN class loss: 0.06794 FastRCNN total loss: 0.17224 L1 loss: 0.0000e+00 L2 loss: 0.62206 Learning rate: 0.002 Mask loss: 0.1258 RPN box loss: 0.05377 RPN score loss: 0.00761 RPN total loss: 0.06138 Total loss: 0.98148 timestamp: 1654949014.1967428 iteration: 44150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13435 FastRCNN class loss: 0.06613 FastRCNN total loss: 0.20048 L1 loss: 0.0000e+00 L2 loss: 0.62205 Learning rate: 0.002 Mask loss: 0.15363 RPN box loss: 0.01425 RPN score loss: 0.00803 RPN total loss: 0.02227 Total loss: 0.99844 timestamp: 1654949017.4501045 iteration: 44155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11125 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.18145 L1 loss: 0.0000e+00 L2 loss: 0.62204 Learning rate: 0.002 Mask loss: 0.15667 RPN box loss: 0.03808 RPN score loss: 0.00572 RPN total loss: 0.0438 Total loss: 1.00396 timestamp: 1654949020.6698544 iteration: 44160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04578 FastRCNN class loss: 0.04158 FastRCNN total loss: 0.08735 L1 loss: 0.0000e+00 L2 loss: 0.62203 Learning rate: 0.002 Mask loss: 0.07515 RPN box loss: 0.00875 RPN score loss: 0.00449 RPN total loss: 0.01325 Total loss: 0.79779 timestamp: 1654949023.8694904 iteration: 44165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07901 FastRCNN class loss: 0.04521 FastRCNN total loss: 0.12422 L1 loss: 0.0000e+00 L2 loss: 0.62202 Learning rate: 0.002 Mask loss: 0.15897 RPN box loss: 0.0333 RPN score loss: 0.00913 RPN total loss: 0.04242 Total loss: 0.94764 timestamp: 1654949027.0161273 iteration: 44170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13738 FastRCNN class loss: 0.07375 FastRCNN total loss: 0.21113 L1 loss: 0.0000e+00 L2 loss: 0.62201 Learning rate: 0.002 Mask loss: 0.16318 RPN box loss: 0.01274 RPN score loss: 0.00702 RPN total loss: 0.01976 Total loss: 1.01608 timestamp: 1654949030.2359023 iteration: 44175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06075 FastRCNN class loss: 0.04485 FastRCNN total loss: 0.1056 L1 loss: 0.0000e+00 L2 loss: 0.622 Learning rate: 0.002 Mask loss: 0.10663 RPN box loss: 0.01631 RPN score loss: 0.00406 RPN total loss: 0.02037 Total loss: 0.8546 timestamp: 1654949033.4165404 iteration: 44180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16314 FastRCNN class loss: 0.05493 FastRCNN total loss: 0.21807 L1 loss: 0.0000e+00 L2 loss: 0.62199 Learning rate: 0.002 Mask loss: 0.15065 RPN box loss: 0.0186 RPN score loss: 0.00471 RPN total loss: 0.02331 Total loss: 1.01402 timestamp: 1654949036.6483324 iteration: 44185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05651 FastRCNN class loss: 0.02239 FastRCNN total loss: 0.07889 L1 loss: 0.0000e+00 L2 loss: 0.62198 Learning rate: 0.002 Mask loss: 0.13671 RPN box loss: 0.00228 RPN score loss: 0.00264 RPN total loss: 0.00493 Total loss: 0.84251 timestamp: 1654949039.7814114 iteration: 44190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.09834 FastRCNN total loss: 0.21193 L1 loss: 0.0000e+00 L2 loss: 0.62198 Learning rate: 0.002 Mask loss: 0.16001 RPN box loss: 0.01753 RPN score loss: 0.00771 RPN total loss: 0.02524 Total loss: 1.01916 timestamp: 1654949042.914952 iteration: 44195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16643 FastRCNN class loss: 0.11893 FastRCNN total loss: 0.28536 L1 loss: 0.0000e+00 L2 loss: 0.62197 Learning rate: 0.002 Mask loss: 0.16419 RPN box loss: 0.04569 RPN score loss: 0.00458 RPN total loss: 0.05027 Total loss: 1.12179 timestamp: 1654949046.1564639 iteration: 44200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11372 FastRCNN class loss: 0.07615 FastRCNN total loss: 0.18987 L1 loss: 0.0000e+00 L2 loss: 0.62197 Learning rate: 0.002 Mask loss: 0.12489 RPN box loss: 0.02373 RPN score loss: 0.02399 RPN total loss: 0.04772 Total loss: 0.98444 timestamp: 1654949049.3392007 iteration: 44205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09801 FastRCNN class loss: 0.07535 FastRCNN total loss: 0.17336 L1 loss: 0.0000e+00 L2 loss: 0.62195 Learning rate: 0.002 Mask loss: 0.13612 RPN box loss: 0.00656 RPN score loss: 0.0072 RPN total loss: 0.01376 Total loss: 0.9452 timestamp: 1654949052.5846188 iteration: 44210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10633 FastRCNN class loss: 0.0442 FastRCNN total loss: 0.15053 L1 loss: 0.0000e+00 L2 loss: 0.62194 Learning rate: 0.002 Mask loss: 0.09897 RPN box loss: 0.01527 RPN score loss: 0.00479 RPN total loss: 0.02006 Total loss: 0.8915 timestamp: 1654949055.7886558 iteration: 44215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04668 FastRCNN class loss: 0.04432 FastRCNN total loss: 0.091 L1 loss: 0.0000e+00 L2 loss: 0.62193 Learning rate: 0.002 Mask loss: 0.14526 RPN box loss: 0.00328 RPN score loss: 0.00151 RPN total loss: 0.00479 Total loss: 0.86298 timestamp: 1654949058.990253 iteration: 44220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06866 FastRCNN class loss: 0.0514 FastRCNN total loss: 0.12006 L1 loss: 0.0000e+00 L2 loss: 0.62192 Learning rate: 0.002 Mask loss: 0.11612 RPN box loss: 0.01907 RPN score loss: 0.00073 RPN total loss: 0.0198 Total loss: 0.8779 timestamp: 1654949062.1795526 iteration: 44225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10584 FastRCNN class loss: 0.06091 FastRCNN total loss: 0.16675 L1 loss: 0.0000e+00 L2 loss: 0.62191 Learning rate: 0.002 Mask loss: 0.12327 RPN box loss: 0.03046 RPN score loss: 0.00947 RPN total loss: 0.03993 Total loss: 0.95186 timestamp: 1654949065.3935266 iteration: 44230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12589 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.19351 L1 loss: 0.0000e+00 L2 loss: 0.6219 Learning rate: 0.002 Mask loss: 0.10792 RPN box loss: 0.00568 RPN score loss: 0.00295 RPN total loss: 0.00862 Total loss: 0.93195 timestamp: 1654949068.5894024 iteration: 44235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15484 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.23837 L1 loss: 0.0000e+00 L2 loss: 0.62189 Learning rate: 0.002 Mask loss: 0.15988 RPN box loss: 0.01699 RPN score loss: 0.00251 RPN total loss: 0.0195 Total loss: 1.03964 timestamp: 1654949071.800538 iteration: 44240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11923 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.20598 L1 loss: 0.0000e+00 L2 loss: 0.62189 Learning rate: 0.002 Mask loss: 0.16051 RPN box loss: 0.01034 RPN score loss: 0.00507 RPN total loss: 0.01541 Total loss: 1.00379 timestamp: 1654949075.0638134 iteration: 44245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06721 FastRCNN class loss: 0.039 FastRCNN total loss: 0.10621 L1 loss: 0.0000e+00 L2 loss: 0.62188 Learning rate: 0.002 Mask loss: 0.13092 RPN box loss: 0.02013 RPN score loss: 0.00947 RPN total loss: 0.0296 Total loss: 0.88861 timestamp: 1654949078.2948344 iteration: 44250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05397 FastRCNN class loss: 0.05981 FastRCNN total loss: 0.11378 L1 loss: 0.0000e+00 L2 loss: 0.62187 Learning rate: 0.002 Mask loss: 0.10693 RPN box loss: 0.00635 RPN score loss: 0.00432 RPN total loss: 0.01067 Total loss: 0.85324 timestamp: 1654949081.5183964 iteration: 44255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1261 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.19775 L1 loss: 0.0000e+00 L2 loss: 0.62186 Learning rate: 0.002 Mask loss: 0.08999 RPN box loss: 0.01913 RPN score loss: 0.00545 RPN total loss: 0.02458 Total loss: 0.93418 timestamp: 1654949084.7420375 iteration: 44260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07108 FastRCNN class loss: 0.08307 FastRCNN total loss: 0.15415 L1 loss: 0.0000e+00 L2 loss: 0.62185 Learning rate: 0.002 Mask loss: 0.14667 RPN box loss: 0.01278 RPN score loss: 0.00127 RPN total loss: 0.01405 Total loss: 0.93672 timestamp: 1654949087.8954628 iteration: 44265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06022 FastRCNN class loss: 0.11886 FastRCNN total loss: 0.17909 L1 loss: 0.0000e+00 L2 loss: 0.62184 Learning rate: 0.002 Mask loss: 0.10407 RPN box loss: 0.01369 RPN score loss: 0.01245 RPN total loss: 0.02615 Total loss: 0.93114 timestamp: 1654949091.0525744 iteration: 44270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0982 FastRCNN class loss: 0.07144 FastRCNN total loss: 0.16965 L1 loss: 0.0000e+00 L2 loss: 0.62183 Learning rate: 0.002 Mask loss: 0.13761 RPN box loss: 0.01201 RPN score loss: 0.00355 RPN total loss: 0.01555 Total loss: 0.94464 timestamp: 1654949094.2184658 iteration: 44275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12409 FastRCNN class loss: 0.0719 FastRCNN total loss: 0.19599 L1 loss: 0.0000e+00 L2 loss: 0.62182 Learning rate: 0.002 Mask loss: 0.1193 RPN box loss: 0.01051 RPN score loss: 0.00298 RPN total loss: 0.01349 Total loss: 0.9506 timestamp: 1654949097.4044273 iteration: 44280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07845 FastRCNN class loss: 0.04099 FastRCNN total loss: 0.11944 L1 loss: 0.0000e+00 L2 loss: 0.62181 Learning rate: 0.002 Mask loss: 0.12654 RPN box loss: 0.01236 RPN score loss: 0.01099 RPN total loss: 0.02335 Total loss: 0.89114 timestamp: 1654949100.6358666 iteration: 44285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09411 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.1725 L1 loss: 0.0000e+00 L2 loss: 0.6218 Learning rate: 0.002 Mask loss: 0.17056 RPN box loss: 0.02608 RPN score loss: 0.00376 RPN total loss: 0.02984 Total loss: 0.99471 timestamp: 1654949103.9129367 iteration: 44290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0915 FastRCNN class loss: 0.06005 FastRCNN total loss: 0.15155 L1 loss: 0.0000e+00 L2 loss: 0.62179 Learning rate: 0.002 Mask loss: 0.16466 RPN box loss: 0.02047 RPN score loss: 0.00337 RPN total loss: 0.02385 Total loss: 0.96185 timestamp: 1654949107.185408 iteration: 44295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.04646 FastRCNN total loss: 0.14694 L1 loss: 0.0000e+00 L2 loss: 0.62179 Learning rate: 0.002 Mask loss: 0.12705 RPN box loss: 0.02013 RPN score loss: 0.0065 RPN total loss: 0.02663 Total loss: 0.92241 timestamp: 1654949110.4148521 iteration: 44300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.15962 L1 loss: 0.0000e+00 L2 loss: 0.62178 Learning rate: 0.002 Mask loss: 0.1559 RPN box loss: 0.00826 RPN score loss: 0.0097 RPN total loss: 0.01796 Total loss: 0.95525 timestamp: 1654949113.6633577 iteration: 44305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07632 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.14856 L1 loss: 0.0000e+00 L2 loss: 0.62177 Learning rate: 0.002 Mask loss: 0.11041 RPN box loss: 0.00501 RPN score loss: 0.00613 RPN total loss: 0.01115 Total loss: 0.89189 timestamp: 1654949116.7720532 iteration: 44310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12985 FastRCNN class loss: 0.09706 FastRCNN total loss: 0.22691 L1 loss: 0.0000e+00 L2 loss: 0.62175 Learning rate: 0.002 Mask loss: 0.13348 RPN box loss: 0.03876 RPN score loss: 0.00531 RPN total loss: 0.04407 Total loss: 1.02621 timestamp: 1654949119.9725869 iteration: 44315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10258 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.18027 L1 loss: 0.0000e+00 L2 loss: 0.62174 Learning rate: 0.002 Mask loss: 0.16329 RPN box loss: 0.0486 RPN score loss: 0.00549 RPN total loss: 0.05409 Total loss: 1.01939 timestamp: 1654949123.2947392 iteration: 44320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13814 FastRCNN class loss: 0.08626 FastRCNN total loss: 0.2244 L1 loss: 0.0000e+00 L2 loss: 0.62173 Learning rate: 0.002 Mask loss: 0.14306 RPN box loss: 0.03443 RPN score loss: 0.01186 RPN total loss: 0.04629 Total loss: 1.03548 timestamp: 1654949126.4642074 iteration: 44325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12691 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.20531 L1 loss: 0.0000e+00 L2 loss: 0.62172 Learning rate: 0.002 Mask loss: 0.10663 RPN box loss: 0.02539 RPN score loss: 0.02125 RPN total loss: 0.04664 Total loss: 0.98031 timestamp: 1654949129.6434739 iteration: 44330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09351 FastRCNN class loss: 0.07534 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.62171 Learning rate: 0.002 Mask loss: 0.13967 RPN box loss: 0.02133 RPN score loss: 0.006 RPN total loss: 0.02734 Total loss: 0.95757 timestamp: 1654949132.8763936 iteration: 44335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16019 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.23311 L1 loss: 0.0000e+00 L2 loss: 0.6217 Learning rate: 0.002 Mask loss: 0.126 RPN box loss: 0.0274 RPN score loss: 0.00313 RPN total loss: 0.03052 Total loss: 1.01134 timestamp: 1654949136.0759838 iteration: 44340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08458 FastRCNN class loss: 0.03663 FastRCNN total loss: 0.12121 L1 loss: 0.0000e+00 L2 loss: 0.62169 Learning rate: 0.002 Mask loss: 0.09079 RPN box loss: 0.01565 RPN score loss: 0.00118 RPN total loss: 0.01683 Total loss: 0.85053 timestamp: 1654949139.3178468 iteration: 44345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09035 FastRCNN class loss: 0.06067 FastRCNN total loss: 0.15101 L1 loss: 0.0000e+00 L2 loss: 0.62169 Learning rate: 0.002 Mask loss: 0.08502 RPN box loss: 0.01434 RPN score loss: 0.00528 RPN total loss: 0.01962 Total loss: 0.87734 timestamp: 1654949142.4790242 iteration: 44350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16854 FastRCNN class loss: 0.10398 FastRCNN total loss: 0.27252 L1 loss: 0.0000e+00 L2 loss: 0.62168 Learning rate: 0.002 Mask loss: 0.1952 RPN box loss: 0.02524 RPN score loss: 0.01083 RPN total loss: 0.03607 Total loss: 1.12546 timestamp: 1654949145.718913 iteration: 44355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10544 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.16641 L1 loss: 0.0000e+00 L2 loss: 0.62167 Learning rate: 0.002 Mask loss: 0.168 RPN box loss: 0.01308 RPN score loss: 0.00248 RPN total loss: 0.01557 Total loss: 0.97164 timestamp: 1654949148.9439008 iteration: 44360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08664 FastRCNN class loss: 0.05722 FastRCNN total loss: 0.14386 L1 loss: 0.0000e+00 L2 loss: 0.62166 Learning rate: 0.002 Mask loss: 0.10276 RPN box loss: 0.0132 RPN score loss: 0.00108 RPN total loss: 0.01428 Total loss: 0.88257 timestamp: 1654949152.2317019 iteration: 44365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.05341 FastRCNN total loss: 0.14352 L1 loss: 0.0000e+00 L2 loss: 0.62165 Learning rate: 0.002 Mask loss: 0.11641 RPN box loss: 0.02836 RPN score loss: 0.00374 RPN total loss: 0.03209 Total loss: 0.91367 timestamp: 1654949155.4602745 iteration: 44370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09911 FastRCNN class loss: 0.08657 FastRCNN total loss: 0.18568 L1 loss: 0.0000e+00 L2 loss: 0.62164 Learning rate: 0.002 Mask loss: 0.17008 RPN box loss: 0.01653 RPN score loss: 0.00353 RPN total loss: 0.02006 Total loss: 0.99746 timestamp: 1654949158.6554604 iteration: 44375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16565 FastRCNN class loss: 0.10463 FastRCNN total loss: 0.27027 L1 loss: 0.0000e+00 L2 loss: 0.62163 Learning rate: 0.002 Mask loss: 0.16234 RPN box loss: 0.01921 RPN score loss: 0.00336 RPN total loss: 0.02257 Total loss: 1.07681 timestamp: 1654949161.9329321 iteration: 44380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06383 FastRCNN class loss: 0.05552 FastRCNN total loss: 0.11935 L1 loss: 0.0000e+00 L2 loss: 0.62162 Learning rate: 0.002 Mask loss: 0.1078 RPN box loss: 0.00815 RPN score loss: 0.00954 RPN total loss: 0.01769 Total loss: 0.86647 timestamp: 1654949165.164189 iteration: 44385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09305 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.16338 L1 loss: 0.0000e+00 L2 loss: 0.62161 Learning rate: 0.002 Mask loss: 0.14099 RPN box loss: 0.01851 RPN score loss: 0.00318 RPN total loss: 0.02168 Total loss: 0.94766 timestamp: 1654949168.3811147 iteration: 44390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07053 FastRCNN class loss: 0.05158 FastRCNN total loss: 0.12212 L1 loss: 0.0000e+00 L2 loss: 0.62161 Learning rate: 0.002 Mask loss: 0.10151 RPN box loss: 0.01089 RPN score loss: 0.00201 RPN total loss: 0.01291 Total loss: 0.85814 timestamp: 1654949171.5303602 iteration: 44395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.08719 FastRCNN total loss: 0.18649 L1 loss: 0.0000e+00 L2 loss: 0.6216 Learning rate: 0.002 Mask loss: 0.15722 RPN box loss: 0.0159 RPN score loss: 0.00775 RPN total loss: 0.02365 Total loss: 0.98896 timestamp: 1654949174.736929 iteration: 44400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09679 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.17655 L1 loss: 0.0000e+00 L2 loss: 0.62159 Learning rate: 0.002 Mask loss: 0.11149 RPN box loss: 0.01491 RPN score loss: 0.00237 RPN total loss: 0.01728 Total loss: 0.9269 timestamp: 1654949177.9122632 iteration: 44405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08213 FastRCNN class loss: 0.05962 FastRCNN total loss: 0.14175 L1 loss: 0.0000e+00 L2 loss: 0.62158 Learning rate: 0.002 Mask loss: 0.22172 RPN box loss: 0.02231 RPN score loss: 0.00255 RPN total loss: 0.02486 Total loss: 1.0099 timestamp: 1654949181.1542342 iteration: 44410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1249 FastRCNN class loss: 0.09487 FastRCNN total loss: 0.21977 L1 loss: 0.0000e+00 L2 loss: 0.62157 Learning rate: 0.002 Mask loss: 0.15575 RPN box loss: 0.02094 RPN score loss: 0.00476 RPN total loss: 0.0257 Total loss: 1.02278 timestamp: 1654949184.3302119 iteration: 44415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.17988 L1 loss: 0.0000e+00 L2 loss: 0.62156 Learning rate: 0.002 Mask loss: 0.19484 RPN box loss: 0.04186 RPN score loss: 0.00696 RPN total loss: 0.04882 Total loss: 1.04509 timestamp: 1654949187.523815 iteration: 44420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13245 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.20502 L1 loss: 0.0000e+00 L2 loss: 0.62154 Learning rate: 0.002 Mask loss: 0.11376 RPN box loss: 0.00585 RPN score loss: 0.00178 RPN total loss: 0.00763 Total loss: 0.94796 timestamp: 1654949190.733997 iteration: 44425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06732 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.13099 L1 loss: 0.0000e+00 L2 loss: 0.62153 Learning rate: 0.002 Mask loss: 0.12695 RPN box loss: 0.01106 RPN score loss: 0.00691 RPN total loss: 0.01797 Total loss: 0.89745 timestamp: 1654949193.9046912 iteration: 44430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13455 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.2045 L1 loss: 0.0000e+00 L2 loss: 0.62153 Learning rate: 0.002 Mask loss: 0.11378 RPN box loss: 0.01412 RPN score loss: 0.00274 RPN total loss: 0.01687 Total loss: 0.95668 timestamp: 1654949197.111875 iteration: 44435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12961 FastRCNN class loss: 0.07741 FastRCNN total loss: 0.20702 L1 loss: 0.0000e+00 L2 loss: 0.62152 Learning rate: 0.002 Mask loss: 0.17167 RPN box loss: 0.04137 RPN score loss: 0.00904 RPN total loss: 0.0504 Total loss: 1.0506 timestamp: 1654949200.2310061 iteration: 44440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11176 FastRCNN class loss: 0.08895 FastRCNN total loss: 0.20071 L1 loss: 0.0000e+00 L2 loss: 0.62151 Learning rate: 0.002 Mask loss: 0.13807 RPN box loss: 0.01463 RPN score loss: 0.00637 RPN total loss: 0.021 Total loss: 0.98128 timestamp: 1654949203.3777988 iteration: 44445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12006 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.19672 L1 loss: 0.0000e+00 L2 loss: 0.6215 Learning rate: 0.002 Mask loss: 0.15663 RPN box loss: 0.02441 RPN score loss: 0.01078 RPN total loss: 0.03519 Total loss: 1.01005 timestamp: 1654949206.5588465 iteration: 44450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06457 FastRCNN class loss: 0.08745 FastRCNN total loss: 0.15202 L1 loss: 0.0000e+00 L2 loss: 0.62149 Learning rate: 0.002 Mask loss: 0.13478 RPN box loss: 0.03391 RPN score loss: 0.01421 RPN total loss: 0.04813 Total loss: 0.95642 timestamp: 1654949209.807764 iteration: 44455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08902 FastRCNN class loss: 0.04732 FastRCNN total loss: 0.13634 L1 loss: 0.0000e+00 L2 loss: 0.62148 Learning rate: 0.002 Mask loss: 0.1699 RPN box loss: 0.01893 RPN score loss: 0.01608 RPN total loss: 0.03501 Total loss: 0.96273 timestamp: 1654949213.0665166 iteration: 44460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11741 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.18485 L1 loss: 0.0000e+00 L2 loss: 0.62148 Learning rate: 0.002 Mask loss: 0.14612 RPN box loss: 0.01538 RPN score loss: 0.00274 RPN total loss: 0.01812 Total loss: 0.97056 timestamp: 1654949216.2910495 iteration: 44465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11632 FastRCNN class loss: 0.06869 FastRCNN total loss: 0.185 L1 loss: 0.0000e+00 L2 loss: 0.62147 Learning rate: 0.002 Mask loss: 0.11328 RPN box loss: 0.02534 RPN score loss: 0.00447 RPN total loss: 0.02981 Total loss: 0.94956 timestamp: 1654949219.4661627 iteration: 44470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1135 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.62146 Learning rate: 0.002 Mask loss: 0.1743 RPN box loss: 0.00881 RPN score loss: 0.00355 RPN total loss: 0.01236 Total loss: 0.98952 timestamp: 1654949222.7107153 iteration: 44475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10712 FastRCNN class loss: 0.08518 FastRCNN total loss: 0.19231 L1 loss: 0.0000e+00 L2 loss: 0.62145 Learning rate: 0.002 Mask loss: 0.12972 RPN box loss: 0.01379 RPN score loss: 0.0078 RPN total loss: 0.02158 Total loss: 0.96506 timestamp: 1654949225.9300404 iteration: 44480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09929 FastRCNN class loss: 0.07258 FastRCNN total loss: 0.17188 L1 loss: 0.0000e+00 L2 loss: 0.62144 Learning rate: 0.002 Mask loss: 0.15015 RPN box loss: 0.01914 RPN score loss: 0.00478 RPN total loss: 0.02392 Total loss: 0.96739 timestamp: 1654949229.0762029 iteration: 44485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08914 FastRCNN class loss: 0.04583 FastRCNN total loss: 0.13498 L1 loss: 0.0000e+00 L2 loss: 0.62142 Learning rate: 0.002 Mask loss: 0.07091 RPN box loss: 0.01739 RPN score loss: 0.00253 RPN total loss: 0.01992 Total loss: 0.84723 timestamp: 1654949232.2204227 iteration: 44490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06217 FastRCNN class loss: 0.04234 FastRCNN total loss: 0.10451 L1 loss: 0.0000e+00 L2 loss: 0.62142 Learning rate: 0.002 Mask loss: 0.07071 RPN box loss: 0.02754 RPN score loss: 0.00297 RPN total loss: 0.0305 Total loss: 0.82713 timestamp: 1654949235.3769395 iteration: 44495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05959 FastRCNN class loss: 0.04487 FastRCNN total loss: 0.10447 L1 loss: 0.0000e+00 L2 loss: 0.62141 Learning rate: 0.002 Mask loss: 0.10733 RPN box loss: 0.03505 RPN score loss: 0.0033 RPN total loss: 0.03835 Total loss: 0.87155 timestamp: 1654949238.6493485 iteration: 44500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09295 FastRCNN class loss: 0.05288 FastRCNN total loss: 0.14583 L1 loss: 0.0000e+00 L2 loss: 0.6214 Learning rate: 0.002 Mask loss: 0.11022 RPN box loss: 0.01456 RPN score loss: 0.00334 RPN total loss: 0.0179 Total loss: 0.89535 timestamp: 1654949241.8384352 iteration: 44505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09992 FastRCNN class loss: 0.09482 FastRCNN total loss: 0.19474 L1 loss: 0.0000e+00 L2 loss: 0.62139 Learning rate: 0.002 Mask loss: 0.16909 RPN box loss: 0.03045 RPN score loss: 0.00486 RPN total loss: 0.03531 Total loss: 1.02054 timestamp: 1654949245.062156 iteration: 44510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10718 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.17119 L1 loss: 0.0000e+00 L2 loss: 0.62138 Learning rate: 0.002 Mask loss: 0.19949 RPN box loss: 0.01629 RPN score loss: 0.00313 RPN total loss: 0.01942 Total loss: 1.01149 timestamp: 1654949248.273044 iteration: 44515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13116 FastRCNN class loss: 0.0885 FastRCNN total loss: 0.21967 L1 loss: 0.0000e+00 L2 loss: 0.62137 Learning rate: 0.002 Mask loss: 0.19139 RPN box loss: 0.03301 RPN score loss: 0.00609 RPN total loss: 0.0391 Total loss: 1.07152 timestamp: 1654949251.4558423 iteration: 44520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16401 FastRCNN class loss: 0.06878 FastRCNN total loss: 0.23279 L1 loss: 0.0000e+00 L2 loss: 0.62136 Learning rate: 0.002 Mask loss: 0.14086 RPN box loss: 0.03222 RPN score loss: 0.00963 RPN total loss: 0.04185 Total loss: 1.03686 timestamp: 1654949254.746479 iteration: 44525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10003 FastRCNN class loss: 0.09216 FastRCNN total loss: 0.1922 L1 loss: 0.0000e+00 L2 loss: 0.62135 Learning rate: 0.002 Mask loss: 0.17944 RPN box loss: 0.0143 RPN score loss: 0.00201 RPN total loss: 0.0163 Total loss: 1.0093 timestamp: 1654949257.900425 iteration: 44530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0607 FastRCNN class loss: 0.03657 FastRCNN total loss: 0.09728 L1 loss: 0.0000e+00 L2 loss: 0.62135 Learning rate: 0.002 Mask loss: 0.07639 RPN box loss: 0.0067 RPN score loss: 0.00084 RPN total loss: 0.00754 Total loss: 0.80255 timestamp: 1654949261.085857 iteration: 44535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09603 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.1676 L1 loss: 0.0000e+00 L2 loss: 0.62134 Learning rate: 0.002 Mask loss: 0.11258 RPN box loss: 0.0207 RPN score loss: 0.00227 RPN total loss: 0.02296 Total loss: 0.92448 timestamp: 1654949264.2785995 iteration: 44540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09985 FastRCNN class loss: 0.1041 FastRCNN total loss: 0.20395 L1 loss: 0.0000e+00 L2 loss: 0.62133 Learning rate: 0.002 Mask loss: 0.1728 RPN box loss: 0.02162 RPN score loss: 0.02398 RPN total loss: 0.0456 Total loss: 1.04368 timestamp: 1654949267.4388797 iteration: 44545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07491 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.15055 L1 loss: 0.0000e+00 L2 loss: 0.62132 Learning rate: 0.002 Mask loss: 0.09377 RPN box loss: 0.00903 RPN score loss: 0.00399 RPN total loss: 0.01302 Total loss: 0.87866 timestamp: 1654949270.5715747 iteration: 44550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13393 FastRCNN class loss: 0.05161 FastRCNN total loss: 0.18554 L1 loss: 0.0000e+00 L2 loss: 0.62131 Learning rate: 0.002 Mask loss: 0.10775 RPN box loss: 0.00466 RPN score loss: 0.00447 RPN total loss: 0.00913 Total loss: 0.92373 timestamp: 1654949273.8076649 iteration: 44555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08775 FastRCNN class loss: 0.06813 FastRCNN total loss: 0.15589 L1 loss: 0.0000e+00 L2 loss: 0.62131 Learning rate: 0.002 Mask loss: 0.12023 RPN box loss: 0.0176 RPN score loss: 0.00381 RPN total loss: 0.02142 Total loss: 0.91883 timestamp: 1654949277.0568058 iteration: 44560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20439 FastRCNN class loss: 0.14645 FastRCNN total loss: 0.35083 L1 loss: 0.0000e+00 L2 loss: 0.6213 Learning rate: 0.002 Mask loss: 0.20988 RPN box loss: 0.04223 RPN score loss: 0.01223 RPN total loss: 0.05447 Total loss: 1.23647 timestamp: 1654949280.2778745 iteration: 44565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07077 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.15984 L1 loss: 0.0000e+00 L2 loss: 0.62129 Learning rate: 0.002 Mask loss: 0.15023 RPN box loss: 0.0261 RPN score loss: 0.00509 RPN total loss: 0.0312 Total loss: 0.96255 timestamp: 1654949283.4147904 iteration: 44570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08308 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.13513 L1 loss: 0.0000e+00 L2 loss: 0.62128 Learning rate: 0.002 Mask loss: 0.09567 RPN box loss: 0.05764 RPN score loss: 0.0052 RPN total loss: 0.06284 Total loss: 0.91491 timestamp: 1654949286.619847 iteration: 44575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10405 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.16846 L1 loss: 0.0000e+00 L2 loss: 0.62127 Learning rate: 0.002 Mask loss: 0.12451 RPN box loss: 0.01636 RPN score loss: 0.00513 RPN total loss: 0.02149 Total loss: 0.93574 timestamp: 1654949289.811231 iteration: 44580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08005 FastRCNN class loss: 0.04663 FastRCNN total loss: 0.12667 L1 loss: 0.0000e+00 L2 loss: 0.62126 Learning rate: 0.002 Mask loss: 0.11894 RPN box loss: 0.01651 RPN score loss: 0.00279 RPN total loss: 0.01931 Total loss: 0.88618 timestamp: 1654949293.0238721 iteration: 44585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03559 FastRCNN class loss: 0.04066 FastRCNN total loss: 0.07625 L1 loss: 0.0000e+00 L2 loss: 0.62125 Learning rate: 0.002 Mask loss: 0.0798 RPN box loss: 0.00173 RPN score loss: 0.00369 RPN total loss: 0.00541 Total loss: 0.78272 timestamp: 1654949296.2276123 iteration: 44590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03955 FastRCNN class loss: 0.03769 FastRCNN total loss: 0.07724 L1 loss: 0.0000e+00 L2 loss: 0.62124 Learning rate: 0.002 Mask loss: 0.0783 RPN box loss: 0.00602 RPN score loss: 0.00098 RPN total loss: 0.007 Total loss: 0.78378 timestamp: 1654949299.4164588 iteration: 44595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08014 FastRCNN class loss: 0.06835 FastRCNN total loss: 0.1485 L1 loss: 0.0000e+00 L2 loss: 0.62123 Learning rate: 0.002 Mask loss: 0.13318 RPN box loss: 0.00935 RPN score loss: 0.00326 RPN total loss: 0.01261 Total loss: 0.91552 timestamp: 1654949302.6689239 iteration: 44600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11959 FastRCNN class loss: 0.06695 FastRCNN total loss: 0.18654 L1 loss: 0.0000e+00 L2 loss: 0.62122 Learning rate: 0.002 Mask loss: 0.12095 RPN box loss: 0.01905 RPN score loss: 0.00531 RPN total loss: 0.02436 Total loss: 0.95306 timestamp: 1654949305.902324 iteration: 44605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06503 FastRCNN class loss: 0.07643 FastRCNN total loss: 0.14146 L1 loss: 0.0000e+00 L2 loss: 0.62121 Learning rate: 0.002 Mask loss: 0.1314 RPN box loss: 0.0224 RPN score loss: 0.01318 RPN total loss: 0.03558 Total loss: 0.92965 timestamp: 1654949309.108738 iteration: 44610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14194 FastRCNN class loss: 0.09736 FastRCNN total loss: 0.2393 L1 loss: 0.0000e+00 L2 loss: 0.6212 Learning rate: 0.002 Mask loss: 0.12798 RPN box loss: 0.01097 RPN score loss: 0.00413 RPN total loss: 0.01509 Total loss: 1.00356 timestamp: 1654949312.2964664 iteration: 44615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07395 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.14533 L1 loss: 0.0000e+00 L2 loss: 0.62119 Learning rate: 0.002 Mask loss: 0.14418 RPN box loss: 0.02559 RPN score loss: 0.01022 RPN total loss: 0.0358 Total loss: 0.94651 timestamp: 1654949315.5447237 iteration: 44620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11251 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.1893 L1 loss: 0.0000e+00 L2 loss: 0.62118 Learning rate: 0.002 Mask loss: 0.13182 RPN box loss: 0.01844 RPN score loss: 0.00418 RPN total loss: 0.02262 Total loss: 0.96492 timestamp: 1654949318.7621 iteration: 44625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16742 FastRCNN class loss: 0.13439 FastRCNN total loss: 0.30182 L1 loss: 0.0000e+00 L2 loss: 0.62117 Learning rate: 0.002 Mask loss: 0.13732 RPN box loss: 0.02211 RPN score loss: 0.00463 RPN total loss: 0.02674 Total loss: 1.08704 timestamp: 1654949321.9956274 iteration: 44630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.21341 L1 loss: 0.0000e+00 L2 loss: 0.62116 Learning rate: 0.002 Mask loss: 0.1791 RPN box loss: 0.0186 RPN score loss: 0.00645 RPN total loss: 0.02505 Total loss: 1.03872 timestamp: 1654949325.218841 iteration: 44635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11075 FastRCNN class loss: 0.06678 FastRCNN total loss: 0.17753 L1 loss: 0.0000e+00 L2 loss: 0.62115 Learning rate: 0.002 Mask loss: 0.15525 RPN box loss: 0.02293 RPN score loss: 0.00472 RPN total loss: 0.02766 Total loss: 0.98158 timestamp: 1654949328.5262418 iteration: 44640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07945 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.14179 L1 loss: 0.0000e+00 L2 loss: 0.62114 Learning rate: 0.002 Mask loss: 0.12884 RPN box loss: 0.01221 RPN score loss: 0.00355 RPN total loss: 0.01576 Total loss: 0.90752 timestamp: 1654949331.709423 iteration: 44645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06716 FastRCNN class loss: 0.08897 FastRCNN total loss: 0.15613 L1 loss: 0.0000e+00 L2 loss: 0.62113 Learning rate: 0.002 Mask loss: 0.11375 RPN box loss: 0.02205 RPN score loss: 0.00293 RPN total loss: 0.02498 Total loss: 0.91599 timestamp: 1654949334.9403126 iteration: 44650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10002 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.16592 L1 loss: 0.0000e+00 L2 loss: 0.62112 Learning rate: 0.002 Mask loss: 0.10755 RPN box loss: 0.01644 RPN score loss: 0.00464 RPN total loss: 0.02108 Total loss: 0.91567 timestamp: 1654949338.1988947 iteration: 44655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06205 FastRCNN class loss: 0.04543 FastRCNN total loss: 0.10748 L1 loss: 0.0000e+00 L2 loss: 0.62111 Learning rate: 0.002 Mask loss: 0.12234 RPN box loss: 0.00942 RPN score loss: 0.00189 RPN total loss: 0.01131 Total loss: 0.86224 timestamp: 1654949341.4005625 iteration: 44660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09715 FastRCNN class loss: 0.10795 FastRCNN total loss: 0.2051 L1 loss: 0.0000e+00 L2 loss: 0.6211 Learning rate: 0.002 Mask loss: 0.10174 RPN box loss: 0.03883 RPN score loss: 0.00674 RPN total loss: 0.04558 Total loss: 0.97352 timestamp: 1654949344.6615012 iteration: 44665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09301 FastRCNN class loss: 0.14141 FastRCNN total loss: 0.23442 L1 loss: 0.0000e+00 L2 loss: 0.62109 Learning rate: 0.002 Mask loss: 0.1385 RPN box loss: 0.01627 RPN score loss: 0.00838 RPN total loss: 0.02464 Total loss: 1.01865 timestamp: 1654949347.7514064 iteration: 44670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06704 FastRCNN class loss: 0.029 FastRCNN total loss: 0.09604 L1 loss: 0.0000e+00 L2 loss: 0.62108 Learning rate: 0.002 Mask loss: 0.0788 RPN box loss: 0.00556 RPN score loss: 0.00221 RPN total loss: 0.00776 Total loss: 0.80369 timestamp: 1654949350.9595487 iteration: 44675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13094 FastRCNN class loss: 0.08123 FastRCNN total loss: 0.21217 L1 loss: 0.0000e+00 L2 loss: 0.62107 Learning rate: 0.002 Mask loss: 0.13815 RPN box loss: 0.04373 RPN score loss: 0.00714 RPN total loss: 0.05088 Total loss: 1.02227 timestamp: 1654949354.1574326 iteration: 44680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13485 FastRCNN class loss: 0.10154 FastRCNN total loss: 0.23639 L1 loss: 0.0000e+00 L2 loss: 0.62107 Learning rate: 0.002 Mask loss: 0.15089 RPN box loss: 0.01663 RPN score loss: 0.00855 RPN total loss: 0.02518 Total loss: 1.03352 timestamp: 1654949357.3300018 iteration: 44685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12481 FastRCNN class loss: 0.08802 FastRCNN total loss: 0.21283 L1 loss: 0.0000e+00 L2 loss: 0.62106 Learning rate: 0.002 Mask loss: 0.1691 RPN box loss: 0.01927 RPN score loss: 0.01141 RPN total loss: 0.03068 Total loss: 1.03367 timestamp: 1654949360.534891 iteration: 44690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0411 FastRCNN class loss: 0.06331 FastRCNN total loss: 0.1044 L1 loss: 0.0000e+00 L2 loss: 0.62105 Learning rate: 0.002 Mask loss: 0.12579 RPN box loss: 0.01973 RPN score loss: 0.00341 RPN total loss: 0.02315 Total loss: 0.87439 timestamp: 1654949363.7969 iteration: 44695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10573 FastRCNN class loss: 0.09107 FastRCNN total loss: 0.1968 L1 loss: 0.0000e+00 L2 loss: 0.62104 Learning rate: 0.002 Mask loss: 0.13903 RPN box loss: 0.00907 RPN score loss: 0.00381 RPN total loss: 0.01288 Total loss: 0.96975 timestamp: 1654949366.9992828 iteration: 44700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16159 FastRCNN class loss: 0.10552 FastRCNN total loss: 0.26712 L1 loss: 0.0000e+00 L2 loss: 0.62103 Learning rate: 0.002 Mask loss: 0.18749 RPN box loss: 0.02412 RPN score loss: 0.01001 RPN total loss: 0.03413 Total loss: 1.10977 timestamp: 1654949370.1173797 iteration: 44705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06164 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.11074 L1 loss: 0.0000e+00 L2 loss: 0.62102 Learning rate: 0.002 Mask loss: 0.11428 RPN box loss: 0.01409 RPN score loss: 0.00466 RPN total loss: 0.01875 Total loss: 0.86479 timestamp: 1654949373.2640684 iteration: 44710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11171 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.19984 L1 loss: 0.0000e+00 L2 loss: 0.62101 Learning rate: 0.002 Mask loss: 0.15383 RPN box loss: 0.02778 RPN score loss: 0.01192 RPN total loss: 0.0397 Total loss: 1.01438 timestamp: 1654949376.4756074 iteration: 44715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12196 FastRCNN class loss: 0.05528 FastRCNN total loss: 0.17724 L1 loss: 0.0000e+00 L2 loss: 0.621 Learning rate: 0.002 Mask loss: 0.12108 RPN box loss: 0.0315 RPN score loss: 0.00128 RPN total loss: 0.03278 Total loss: 0.9521 timestamp: 1654949379.6428401 iteration: 44720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07364 FastRCNN class loss: 0.05157 FastRCNN total loss: 0.12521 L1 loss: 0.0000e+00 L2 loss: 0.62099 Learning rate: 0.002 Mask loss: 0.12361 RPN box loss: 0.01736 RPN score loss: 0.01088 RPN total loss: 0.02823 Total loss: 0.89804 timestamp: 1654949382.8487709 iteration: 44725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1179 FastRCNN class loss: 0.07846 FastRCNN total loss: 0.19636 L1 loss: 0.0000e+00 L2 loss: 0.62098 Learning rate: 0.002 Mask loss: 0.12634 RPN box loss: 0.02739 RPN score loss: 0.00394 RPN total loss: 0.03133 Total loss: 0.97501 timestamp: 1654949386.129282 iteration: 44730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.10477 FastRCNN total loss: 0.21112 L1 loss: 0.0000e+00 L2 loss: 0.62097 Learning rate: 0.002 Mask loss: 0.13579 RPN box loss: 0.0188 RPN score loss: 0.00612 RPN total loss: 0.02493 Total loss: 0.99281 timestamp: 1654949389.3078673 iteration: 44735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05468 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.09815 L1 loss: 0.0000e+00 L2 loss: 0.62097 Learning rate: 0.002 Mask loss: 0.13347 RPN box loss: 0.00692 RPN score loss: 0.00178 RPN total loss: 0.0087 Total loss: 0.86129 timestamp: 1654949392.5446002 iteration: 44740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13563 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.20792 L1 loss: 0.0000e+00 L2 loss: 0.62096 Learning rate: 0.002 Mask loss: 0.10531 RPN box loss: 0.01894 RPN score loss: 0.00214 RPN total loss: 0.02108 Total loss: 0.95527 timestamp: 1654949395.7123575 iteration: 44745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.07823 FastRCNN total loss: 0.17304 L1 loss: 0.0000e+00 L2 loss: 0.62095 Learning rate: 0.002 Mask loss: 0.14707 RPN box loss: 0.01368 RPN score loss: 0.00341 RPN total loss: 0.0171 Total loss: 0.95815 timestamp: 1654949398.9016151 iteration: 44750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09585 FastRCNN class loss: 0.09297 FastRCNN total loss: 0.18881 L1 loss: 0.0000e+00 L2 loss: 0.62094 Learning rate: 0.002 Mask loss: 0.12868 RPN box loss: 0.01172 RPN score loss: 0.0058 RPN total loss: 0.01752 Total loss: 0.95595 timestamp: 1654949402.20485 iteration: 44755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.06641 FastRCNN total loss: 0.15316 L1 loss: 0.0000e+00 L2 loss: 0.62093 Learning rate: 0.002 Mask loss: 0.16208 RPN box loss: 0.02131 RPN score loss: 0.01313 RPN total loss: 0.03444 Total loss: 0.97061 timestamp: 1654949405.337279 iteration: 44760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09559 FastRCNN class loss: 0.08613 FastRCNN total loss: 0.18172 L1 loss: 0.0000e+00 L2 loss: 0.62092 Learning rate: 0.002 Mask loss: 0.18714 RPN box loss: 0.02208 RPN score loss: 0.00447 RPN total loss: 0.02656 Total loss: 1.01633 timestamp: 1654949408.575335 iteration: 44765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04967 FastRCNN class loss: 0.03937 FastRCNN total loss: 0.08904 L1 loss: 0.0000e+00 L2 loss: 0.62091 Learning rate: 0.002 Mask loss: 0.09239 RPN box loss: 0.02262 RPN score loss: 0.01121 RPN total loss: 0.03383 Total loss: 0.83616 timestamp: 1654949411.8171475 iteration: 44770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1394 FastRCNN class loss: 0.13984 FastRCNN total loss: 0.27924 L1 loss: 0.0000e+00 L2 loss: 0.6209 Learning rate: 0.002 Mask loss: 0.20763 RPN box loss: 0.02365 RPN score loss: 0.00817 RPN total loss: 0.03182 Total loss: 1.13959 timestamp: 1654949415.0845578 iteration: 44775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13793 FastRCNN class loss: 0.06517 FastRCNN total loss: 0.2031 L1 loss: 0.0000e+00 L2 loss: 0.62089 Learning rate: 0.002 Mask loss: 0.25254 RPN box loss: 0.03039 RPN score loss: 0.00749 RPN total loss: 0.03788 Total loss: 1.11441 timestamp: 1654949418.3133044 iteration: 44780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0822 FastRCNN class loss: 0.06659 FastRCNN total loss: 0.14879 L1 loss: 0.0000e+00 L2 loss: 0.62089 Learning rate: 0.002 Mask loss: 0.13035 RPN box loss: 0.0088 RPN score loss: 0.00385 RPN total loss: 0.01265 Total loss: 0.91268 timestamp: 1654949421.5087423 iteration: 44785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.06242 FastRCNN total loss: 0.16302 L1 loss: 0.0000e+00 L2 loss: 0.62088 Learning rate: 0.002 Mask loss: 0.12383 RPN box loss: 0.07662 RPN score loss: 0.00327 RPN total loss: 0.0799 Total loss: 0.98762 timestamp: 1654949424.7420483 iteration: 44790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.0456 FastRCNN total loss: 0.11476 L1 loss: 0.0000e+00 L2 loss: 0.62087 Learning rate: 0.002 Mask loss: 0.15289 RPN box loss: 0.01245 RPN score loss: 0.00303 RPN total loss: 0.01548 Total loss: 0.90399 timestamp: 1654949427.8824263 iteration: 44795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08029 FastRCNN class loss: 0.06271 FastRCNN total loss: 0.14299 L1 loss: 0.0000e+00 L2 loss: 0.62086 Learning rate: 0.002 Mask loss: 0.18525 RPN box loss: 0.00983 RPN score loss: 0.00429 RPN total loss: 0.01412 Total loss: 0.96322 timestamp: 1654949431.0969968 iteration: 44800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.121 FastRCNN class loss: 0.07703 FastRCNN total loss: 0.19803 L1 loss: 0.0000e+00 L2 loss: 0.62085 Learning rate: 0.002 Mask loss: 0.15222 RPN box loss: 0.01708 RPN score loss: 0.00563 RPN total loss: 0.02271 Total loss: 0.9938 timestamp: 1654949434.2927666 iteration: 44805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08861 FastRCNN class loss: 0.08109 FastRCNN total loss: 0.16971 L1 loss: 0.0000e+00 L2 loss: 0.62084 Learning rate: 0.002 Mask loss: 0.16036 RPN box loss: 0.03883 RPN score loss: 0.00486 RPN total loss: 0.04369 Total loss: 0.9946 timestamp: 1654949437.4868991 iteration: 44810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17419 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.2386 L1 loss: 0.0000e+00 L2 loss: 0.62083 Learning rate: 0.002 Mask loss: 0.12735 RPN box loss: 0.00743 RPN score loss: 0.00362 RPN total loss: 0.01106 Total loss: 0.99784 timestamp: 1654949440.7518332 iteration: 44815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04804 FastRCNN class loss: 0.0405 FastRCNN total loss: 0.08854 L1 loss: 0.0000e+00 L2 loss: 0.62082 Learning rate: 0.002 Mask loss: 0.1216 RPN box loss: 0.00608 RPN score loss: 0.00649 RPN total loss: 0.01257 Total loss: 0.84353 timestamp: 1654949443.9752226 iteration: 44820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04321 FastRCNN class loss: 0.04161 FastRCNN total loss: 0.08483 L1 loss: 0.0000e+00 L2 loss: 0.62081 Learning rate: 0.002 Mask loss: 0.09345 RPN box loss: 0.01504 RPN score loss: 0.00426 RPN total loss: 0.01931 Total loss: 0.8184 timestamp: 1654949447.1274078 iteration: 44825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15771 FastRCNN class loss: 0.12184 FastRCNN total loss: 0.27954 L1 loss: 0.0000e+00 L2 loss: 0.6208 Learning rate: 0.002 Mask loss: 0.24802 RPN box loss: 0.02436 RPN score loss: 0.00623 RPN total loss: 0.03058 Total loss: 1.17896 timestamp: 1654949450.3166022 iteration: 44830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10878 FastRCNN class loss: 0.04462 FastRCNN total loss: 0.1534 L1 loss: 0.0000e+00 L2 loss: 0.62079 Learning rate: 0.002 Mask loss: 0.11146 RPN box loss: 0.00631 RPN score loss: 0.00122 RPN total loss: 0.00753 Total loss: 0.89318 timestamp: 1654949453.553048 iteration: 44835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.124 FastRCNN class loss: 0.08627 FastRCNN total loss: 0.21027 L1 loss: 0.0000e+00 L2 loss: 0.62078 Learning rate: 0.002 Mask loss: 0.13835 RPN box loss: 0.0237 RPN score loss: 0.00787 RPN total loss: 0.03156 Total loss: 1.00097 timestamp: 1654949456.757594 iteration: 44840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08232 FastRCNN class loss: 0.04453 FastRCNN total loss: 0.12685 L1 loss: 0.0000e+00 L2 loss: 0.62077 Learning rate: 0.002 Mask loss: 0.09832 RPN box loss: 0.02477 RPN score loss: 0.00281 RPN total loss: 0.02758 Total loss: 0.87352 timestamp: 1654949459.9270551 iteration: 44845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05036 FastRCNN class loss: 0.03224 FastRCNN total loss: 0.0826 L1 loss: 0.0000e+00 L2 loss: 0.62076 Learning rate: 0.002 Mask loss: 0.09991 RPN box loss: 0.01126 RPN score loss: 0.00265 RPN total loss: 0.0139 Total loss: 0.81718 timestamp: 1654949463.147211 iteration: 44850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10909 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.18332 L1 loss: 0.0000e+00 L2 loss: 0.62076 Learning rate: 0.002 Mask loss: 0.11446 RPN box loss: 0.01403 RPN score loss: 0.00664 RPN total loss: 0.02066 Total loss: 0.9392 timestamp: 1654949466.3516374 iteration: 44855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07656 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.13489 L1 loss: 0.0000e+00 L2 loss: 0.62075 Learning rate: 0.002 Mask loss: 0.14496 RPN box loss: 0.01391 RPN score loss: 0.00325 RPN total loss: 0.01717 Total loss: 0.91776 timestamp: 1654949469.5545151 iteration: 44860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0885 FastRCNN class loss: 0.10007 FastRCNN total loss: 0.18857 L1 loss: 0.0000e+00 L2 loss: 0.62074 Learning rate: 0.002 Mask loss: 0.14462 RPN box loss: 0.01328 RPN score loss: 0.00358 RPN total loss: 0.01685 Total loss: 0.97079 timestamp: 1654949472.7826817 iteration: 44865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.08323 FastRCNN total loss: 0.2051 L1 loss: 0.0000e+00 L2 loss: 0.62072 Learning rate: 0.002 Mask loss: 0.17544 RPN box loss: 0.00683 RPN score loss: 0.01459 RPN total loss: 0.02142 Total loss: 1.02268 timestamp: 1654949476.0358655 iteration: 44870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08131 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.14205 L1 loss: 0.0000e+00 L2 loss: 0.62071 Learning rate: 0.002 Mask loss: 0.09957 RPN box loss: 0.00896 RPN score loss: 0.00419 RPN total loss: 0.01315 Total loss: 0.87549 timestamp: 1654949479.237218 iteration: 44875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09669 FastRCNN class loss: 0.07926 FastRCNN total loss: 0.17595 L1 loss: 0.0000e+00 L2 loss: 0.6207 Learning rate: 0.002 Mask loss: 0.14169 RPN box loss: 0.01514 RPN score loss: 0.00368 RPN total loss: 0.01882 Total loss: 0.95717 timestamp: 1654949482.479112 iteration: 44880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10735 FastRCNN class loss: 0.10451 FastRCNN total loss: 0.21186 L1 loss: 0.0000e+00 L2 loss: 0.6207 Learning rate: 0.002 Mask loss: 0.18474 RPN box loss: 0.01581 RPN score loss: 0.00329 RPN total loss: 0.0191 Total loss: 1.0364 timestamp: 1654949485.624283 iteration: 44885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14444 FastRCNN class loss: 0.09645 FastRCNN total loss: 0.24089 L1 loss: 0.0000e+00 L2 loss: 0.62069 Learning rate: 0.002 Mask loss: 0.11312 RPN box loss: 0.04892 RPN score loss: 0.00447 RPN total loss: 0.05339 Total loss: 1.02808 timestamp: 1654949488.8719962 iteration: 44890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07661 FastRCNN class loss: 0.04123 FastRCNN total loss: 0.11784 L1 loss: 0.0000e+00 L2 loss: 0.62068 Learning rate: 0.002 Mask loss: 0.07062 RPN box loss: 0.00435 RPN score loss: 0.00131 RPN total loss: 0.00566 Total loss: 0.8148 timestamp: 1654949492.097604 iteration: 44895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09108 FastRCNN class loss: 0.06795 FastRCNN total loss: 0.15903 L1 loss: 0.0000e+00 L2 loss: 0.62067 Learning rate: 0.002 Mask loss: 0.13294 RPN box loss: 0.00954 RPN score loss: 0.00351 RPN total loss: 0.01305 Total loss: 0.92569 timestamp: 1654949495.2830703 iteration: 44900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11823 FastRCNN class loss: 0.0746 FastRCNN total loss: 0.19283 L1 loss: 0.0000e+00 L2 loss: 0.62065 Learning rate: 0.002 Mask loss: 0.13513 RPN box loss: 0.00846 RPN score loss: 0.00465 RPN total loss: 0.0131 Total loss: 0.96172 timestamp: 1654949498.4573712 iteration: 44905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11478 FastRCNN class loss: 0.08814 FastRCNN total loss: 0.20292 L1 loss: 0.0000e+00 L2 loss: 0.62064 Learning rate: 0.002 Mask loss: 0.12472 RPN box loss: 0.01337 RPN score loss: 0.00654 RPN total loss: 0.01991 Total loss: 0.96819 timestamp: 1654949501.823822 iteration: 44910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.0418 FastRCNN total loss: 0.1382 L1 loss: 0.0000e+00 L2 loss: 0.62064 Learning rate: 0.002 Mask loss: 0.09743 RPN box loss: 0.01063 RPN score loss: 0.00331 RPN total loss: 0.01394 Total loss: 0.87021 timestamp: 1654949505.102079 iteration: 44915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10156 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.17606 L1 loss: 0.0000e+00 L2 loss: 0.62063 Learning rate: 0.002 Mask loss: 0.14853 RPN box loss: 0.01551 RPN score loss: 0.00369 RPN total loss: 0.0192 Total loss: 0.96442 timestamp: 1654949508.3582745 iteration: 44920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0693 FastRCNN class loss: 0.03407 FastRCNN total loss: 0.10337 L1 loss: 0.0000e+00 L2 loss: 0.62062 Learning rate: 0.002 Mask loss: 0.11213 RPN box loss: 0.00622 RPN score loss: 0.00221 RPN total loss: 0.00843 Total loss: 0.84455 timestamp: 1654949511.6110063 iteration: 44925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11845 FastRCNN class loss: 0.04825 FastRCNN total loss: 0.16669 L1 loss: 0.0000e+00 L2 loss: 0.62061 Learning rate: 0.002 Mask loss: 0.11255 RPN box loss: 0.01038 RPN score loss: 0.00218 RPN total loss: 0.01255 Total loss: 0.91241 timestamp: 1654949514.8160894 iteration: 44930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08102 FastRCNN class loss: 0.08414 FastRCNN total loss: 0.16516 L1 loss: 0.0000e+00 L2 loss: 0.6206 Learning rate: 0.002 Mask loss: 0.14368 RPN box loss: 0.02029 RPN score loss: 0.00638 RPN total loss: 0.02667 Total loss: 0.95611 timestamp: 1654949517.984921 iteration: 44935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0724 FastRCNN class loss: 0.06613 FastRCNN total loss: 0.13852 L1 loss: 0.0000e+00 L2 loss: 0.62059 Learning rate: 0.002 Mask loss: 0.12734 RPN box loss: 0.02163 RPN score loss: 0.00426 RPN total loss: 0.02589 Total loss: 0.91235 timestamp: 1654949521.1909041 iteration: 44940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14554 FastRCNN class loss: 0.04821 FastRCNN total loss: 0.19376 L1 loss: 0.0000e+00 L2 loss: 0.62058 Learning rate: 0.002 Mask loss: 0.14916 RPN box loss: 0.00983 RPN score loss: 0.00211 RPN total loss: 0.01195 Total loss: 0.97545 timestamp: 1654949524.478203 iteration: 44945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09379 FastRCNN class loss: 0.10412 FastRCNN total loss: 0.19791 L1 loss: 0.0000e+00 L2 loss: 0.62057 Learning rate: 0.002 Mask loss: 0.14242 RPN box loss: 0.03273 RPN score loss: 0.00871 RPN total loss: 0.04144 Total loss: 1.00233 timestamp: 1654949527.6845884 iteration: 44950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13945 FastRCNN class loss: 0.17689 FastRCNN total loss: 0.31635 L1 loss: 0.0000e+00 L2 loss: 0.62057 Learning rate: 0.002 Mask loss: 0.24131 RPN box loss: 0.04993 RPN score loss: 0.01304 RPN total loss: 0.06297 Total loss: 1.24119 timestamp: 1654949530.9134576 iteration: 44955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17395 FastRCNN class loss: 0.07015 FastRCNN total loss: 0.2441 L1 loss: 0.0000e+00 L2 loss: 0.62056 Learning rate: 0.002 Mask loss: 0.13813 RPN box loss: 0.00428 RPN score loss: 0.0025 RPN total loss: 0.00679 Total loss: 1.00957 timestamp: 1654949534.1520648 iteration: 44960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06931 FastRCNN class loss: 0.07554 FastRCNN total loss: 0.14485 L1 loss: 0.0000e+00 L2 loss: 0.62054 Learning rate: 0.002 Mask loss: 0.12202 RPN box loss: 0.00913 RPN score loss: 0.00197 RPN total loss: 0.0111 Total loss: 0.89852 timestamp: 1654949537.3611593 iteration: 44965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09245 FastRCNN class loss: 0.04699 FastRCNN total loss: 0.13945 L1 loss: 0.0000e+00 L2 loss: 0.62053 Learning rate: 0.002 Mask loss: 0.17916 RPN box loss: 0.00444 RPN score loss: 0.0008 RPN total loss: 0.00524 Total loss: 0.94438 timestamp: 1654949540.51069 iteration: 44970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09606 FastRCNN class loss: 0.0964 FastRCNN total loss: 0.19246 L1 loss: 0.0000e+00 L2 loss: 0.62052 Learning rate: 0.002 Mask loss: 0.12627 RPN box loss: 0.01692 RPN score loss: 0.00326 RPN total loss: 0.02019 Total loss: 0.95944 timestamp: 1654949543.788557 iteration: 44975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1118 FastRCNN class loss: 0.08668 FastRCNN total loss: 0.19847 L1 loss: 0.0000e+00 L2 loss: 0.62051 Learning rate: 0.002 Mask loss: 0.16706 RPN box loss: 0.02303 RPN score loss: 0.0065 RPN total loss: 0.02953 Total loss: 1.01558 timestamp: 1654949547.0880418 iteration: 44980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08456 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.16591 L1 loss: 0.0000e+00 L2 loss: 0.6205 Learning rate: 0.002 Mask loss: 0.14946 RPN box loss: 0.01699 RPN score loss: 0.00288 RPN total loss: 0.01986 Total loss: 0.95574 timestamp: 1654949550.2933245 iteration: 44985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08734 FastRCNN class loss: 0.0804 FastRCNN total loss: 0.16774 L1 loss: 0.0000e+00 L2 loss: 0.62049 Learning rate: 0.002 Mask loss: 0.14088 RPN box loss: 0.02541 RPN score loss: 0.00865 RPN total loss: 0.03406 Total loss: 0.96317 timestamp: 1654949553.4650342 iteration: 44990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14846 FastRCNN class loss: 0.09156 FastRCNN total loss: 0.24002 L1 loss: 0.0000e+00 L2 loss: 0.62048 Learning rate: 0.002 Mask loss: 0.1294 RPN box loss: 0.01444 RPN score loss: 0.0031 RPN total loss: 0.01754 Total loss: 1.00744 timestamp: 1654949556.707874 iteration: 44995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0922 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.1749 L1 loss: 0.0000e+00 L2 loss: 0.62047 Learning rate: 0.002 Mask loss: 0.18027 RPN box loss: 0.00734 RPN score loss: 0.00572 RPN total loss: 0.01307 Total loss: 0.98871 timestamp: 1654949559.9791238 iteration: 45000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12131 FastRCNN class loss: 0.07898 FastRCNN total loss: 0.20029 L1 loss: 0.0000e+00 L2 loss: 0.62047 Learning rate: 0.002 Mask loss: 0.16276 RPN box loss: 0.02472 RPN score loss: 0.0033 RPN total loss: 0.02802 Total loss: 1.01154 timestamp: 1654949563.198031 iteration: 45005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1441 FastRCNN class loss: 0.12693 FastRCNN total loss: 0.27103 L1 loss: 0.0000e+00 L2 loss: 0.62046 Learning rate: 0.002 Mask loss: 0.15096 RPN box loss: 0.01763 RPN score loss: 0.03874 RPN total loss: 0.05637 Total loss: 1.09882 timestamp: 1654949566.3809433 iteration: 45010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06958 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.12434 L1 loss: 0.0000e+00 L2 loss: 0.62045 Learning rate: 0.002 Mask loss: 0.15154 RPN box loss: 0.01656 RPN score loss: 0.00185 RPN total loss: 0.01841 Total loss: 0.91474 timestamp: 1654949569.659519 iteration: 45015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08438 FastRCNN class loss: 0.09018 FastRCNN total loss: 0.17456 L1 loss: 0.0000e+00 L2 loss: 0.62044 Learning rate: 0.002 Mask loss: 0.17389 RPN box loss: 0.08199 RPN score loss: 0.01187 RPN total loss: 0.09386 Total loss: 1.06275 timestamp: 1654949572.9021158 iteration: 45020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05308 FastRCNN class loss: 0.04754 FastRCNN total loss: 0.10062 L1 loss: 0.0000e+00 L2 loss: 0.62043 Learning rate: 0.002 Mask loss: 0.07878 RPN box loss: 0.00587 RPN score loss: 0.00282 RPN total loss: 0.00869 Total loss: 0.80852 timestamp: 1654949576.0123024 iteration: 45025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16417 FastRCNN class loss: 0.08694 FastRCNN total loss: 0.25111 L1 loss: 0.0000e+00 L2 loss: 0.62042 Learning rate: 0.002 Mask loss: 0.20662 RPN box loss: 0.0186 RPN score loss: 0.01336 RPN total loss: 0.03196 Total loss: 1.1101 timestamp: 1654949579.2361395 iteration: 45030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10372 FastRCNN class loss: 0.0421 FastRCNN total loss: 0.14582 L1 loss: 0.0000e+00 L2 loss: 0.62041 Learning rate: 0.002 Mask loss: 0.10675 RPN box loss: 0.00539 RPN score loss: 0.00374 RPN total loss: 0.00913 Total loss: 0.88211 timestamp: 1654949582.4550097 iteration: 45035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10058 FastRCNN class loss: 0.04778 FastRCNN total loss: 0.14836 L1 loss: 0.0000e+00 L2 loss: 0.6204 Learning rate: 0.002 Mask loss: 0.11974 RPN box loss: 0.00809 RPN score loss: 0.00643 RPN total loss: 0.01451 Total loss: 0.90302 timestamp: 1654949585.6684926 iteration: 45040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15697 FastRCNN class loss: 0.10376 FastRCNN total loss: 0.26073 L1 loss: 0.0000e+00 L2 loss: 0.62039 Learning rate: 0.002 Mask loss: 0.19858 RPN box loss: 0.02661 RPN score loss: 0.00743 RPN total loss: 0.03404 Total loss: 1.11374 timestamp: 1654949588.8942533 iteration: 45045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07236 FastRCNN class loss: 0.05612 FastRCNN total loss: 0.12848 L1 loss: 0.0000e+00 L2 loss: 0.62039 Learning rate: 0.002 Mask loss: 0.06282 RPN box loss: 0.01217 RPN score loss: 0.00186 RPN total loss: 0.01404 Total loss: 0.82572 timestamp: 1654949592.0945282 iteration: 45050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05657 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.11693 L1 loss: 0.0000e+00 L2 loss: 0.62038 Learning rate: 0.002 Mask loss: 0.11538 RPN box loss: 0.00722 RPN score loss: 0.00205 RPN total loss: 0.00926 Total loss: 0.86196 timestamp: 1654949595.2881556 iteration: 45055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.06359 FastRCNN total loss: 0.17708 L1 loss: 0.0000e+00 L2 loss: 0.62037 Learning rate: 0.002 Mask loss: 0.12311 RPN box loss: 0.01016 RPN score loss: 0.00249 RPN total loss: 0.01265 Total loss: 0.9332 timestamp: 1654949598.5327647 iteration: 45060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10162 FastRCNN class loss: 0.06562 FastRCNN total loss: 0.16724 L1 loss: 0.0000e+00 L2 loss: 0.62036 Learning rate: 0.002 Mask loss: 0.12768 RPN box loss: 0.01219 RPN score loss: 0.00979 RPN total loss: 0.02198 Total loss: 0.93725 timestamp: 1654949601.756911 iteration: 45065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11545 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.18484 L1 loss: 0.0000e+00 L2 loss: 0.62035 Learning rate: 0.002 Mask loss: 0.12772 RPN box loss: 0.01837 RPN score loss: 0.00948 RPN total loss: 0.02785 Total loss: 0.96075 timestamp: 1654949604.9913712 iteration: 45070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12635 FastRCNN class loss: 0.07415 FastRCNN total loss: 0.2005 L1 loss: 0.0000e+00 L2 loss: 0.62034 Learning rate: 0.002 Mask loss: 0.1355 RPN box loss: 0.03174 RPN score loss: 0.00529 RPN total loss: 0.03702 Total loss: 0.99336 timestamp: 1654949608.1907253 iteration: 45075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06524 FastRCNN class loss: 0.0823 FastRCNN total loss: 0.14754 L1 loss: 0.0000e+00 L2 loss: 0.62033 Learning rate: 0.002 Mask loss: 0.12567 RPN box loss: 0.00857 RPN score loss: 0.00158 RPN total loss: 0.01015 Total loss: 0.90369 timestamp: 1654949611.366647 iteration: 45080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09677 FastRCNN class loss: 0.05597 FastRCNN total loss: 0.15274 L1 loss: 0.0000e+00 L2 loss: 0.62032 Learning rate: 0.002 Mask loss: 0.0982 RPN box loss: 0.0186 RPN score loss: 0.00333 RPN total loss: 0.02193 Total loss: 0.89319 timestamp: 1654949614.543281 iteration: 45085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06619 FastRCNN class loss: 0.08625 FastRCNN total loss: 0.15244 L1 loss: 0.0000e+00 L2 loss: 0.62031 Learning rate: 0.002 Mask loss: 0.11214 RPN box loss: 0.01553 RPN score loss: 0.00353 RPN total loss: 0.01906 Total loss: 0.90395 timestamp: 1654949617.7483814 iteration: 45090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08609 FastRCNN class loss: 0.05725 FastRCNN total loss: 0.14334 L1 loss: 0.0000e+00 L2 loss: 0.6203 Learning rate: 0.002 Mask loss: 0.19105 RPN box loss: 0.00857 RPN score loss: 0.0041 RPN total loss: 0.01267 Total loss: 0.96736 timestamp: 1654949620.9526343 iteration: 45095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1176 FastRCNN class loss: 0.08261 FastRCNN total loss: 0.20021 L1 loss: 0.0000e+00 L2 loss: 0.62029 Learning rate: 0.002 Mask loss: 0.13926 RPN box loss: 0.01675 RPN score loss: 0.00913 RPN total loss: 0.02588 Total loss: 0.98564 timestamp: 1654949624.1700537 iteration: 45100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09831 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.15759 L1 loss: 0.0000e+00 L2 loss: 0.62028 Learning rate: 0.002 Mask loss: 0.07966 RPN box loss: 0.01277 RPN score loss: 0.00781 RPN total loss: 0.02057 Total loss: 0.8781 timestamp: 1654949627.3638797 iteration: 45105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10669 FastRCNN class loss: 0.04235 FastRCNN total loss: 0.14905 L1 loss: 0.0000e+00 L2 loss: 0.62027 Learning rate: 0.002 Mask loss: 0.09049 RPN box loss: 0.00615 RPN score loss: 0.00121 RPN total loss: 0.00736 Total loss: 0.86717 timestamp: 1654949630.5377958 iteration: 45110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08839 FastRCNN class loss: 0.06878 FastRCNN total loss: 0.15717 L1 loss: 0.0000e+00 L2 loss: 0.62026 Learning rate: 0.002 Mask loss: 0.15234 RPN box loss: 0.01921 RPN score loss: 0.00207 RPN total loss: 0.02128 Total loss: 0.95105 timestamp: 1654949633.726625 iteration: 45115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14748 FastRCNN class loss: 0.07692 FastRCNN total loss: 0.2244 L1 loss: 0.0000e+00 L2 loss: 0.62025 Learning rate: 0.002 Mask loss: 0.13663 RPN box loss: 0.02338 RPN score loss: 0.00219 RPN total loss: 0.02557 Total loss: 1.00685 timestamp: 1654949636.9813194 iteration: 45120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16042 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.22299 L1 loss: 0.0000e+00 L2 loss: 0.62025 Learning rate: 0.002 Mask loss: 0.15213 RPN box loss: 0.01402 RPN score loss: 0.0074 RPN total loss: 0.02142 Total loss: 1.01679 timestamp: 1654949640.1377158 iteration: 45125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05949 FastRCNN class loss: 0.04902 FastRCNN total loss: 0.10851 L1 loss: 0.0000e+00 L2 loss: 0.62024 Learning rate: 0.002 Mask loss: 0.12076 RPN box loss: 0.00504 RPN score loss: 0.0063 RPN total loss: 0.01134 Total loss: 0.86085 timestamp: 1654949643.2736328 iteration: 45130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06924 FastRCNN class loss: 0.07953 FastRCNN total loss: 0.14877 L1 loss: 0.0000e+00 L2 loss: 0.62023 Learning rate: 0.002 Mask loss: 0.11599 RPN box loss: 0.01001 RPN score loss: 0.00271 RPN total loss: 0.01273 Total loss: 0.89773 timestamp: 1654949646.4417782 iteration: 45135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05402 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.13533 L1 loss: 0.0000e+00 L2 loss: 0.62022 Learning rate: 0.002 Mask loss: 0.12014 RPN box loss: 0.01325 RPN score loss: 0.00354 RPN total loss: 0.0168 Total loss: 0.89249 timestamp: 1654949649.6913493 iteration: 45140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10044 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.1592 L1 loss: 0.0000e+00 L2 loss: 0.62021 Learning rate: 0.002 Mask loss: 0.1044 RPN box loss: 0.00777 RPN score loss: 0.0022 RPN total loss: 0.00997 Total loss: 0.89377 timestamp: 1654949652.823584 iteration: 45145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07974 FastRCNN class loss: 0.06542 FastRCNN total loss: 0.14516 L1 loss: 0.0000e+00 L2 loss: 0.6202 Learning rate: 0.002 Mask loss: 0.1364 RPN box loss: 0.02873 RPN score loss: 0.00335 RPN total loss: 0.03208 Total loss: 0.93384 timestamp: 1654949655.9184554 iteration: 45150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09936 FastRCNN class loss: 0.07066 FastRCNN total loss: 0.17001 L1 loss: 0.0000e+00 L2 loss: 0.62019 Learning rate: 0.002 Mask loss: 0.16669 RPN box loss: 0.01613 RPN score loss: 0.0039 RPN total loss: 0.02003 Total loss: 0.97693 timestamp: 1654949659.0621724 iteration: 45155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.078 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.13327 L1 loss: 0.0000e+00 L2 loss: 0.62018 Learning rate: 0.002 Mask loss: 0.09706 RPN box loss: 0.01036 RPN score loss: 0.00181 RPN total loss: 0.01217 Total loss: 0.86268 timestamp: 1654949662.2360854 iteration: 45160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08431 FastRCNN class loss: 0.07061 FastRCNN total loss: 0.15492 L1 loss: 0.0000e+00 L2 loss: 0.62017 Learning rate: 0.002 Mask loss: 0.097 RPN box loss: 0.02711 RPN score loss: 0.00369 RPN total loss: 0.0308 Total loss: 0.90289 timestamp: 1654949665.441511 iteration: 45165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04958 FastRCNN class loss: 0.04188 FastRCNN total loss: 0.09145 L1 loss: 0.0000e+00 L2 loss: 0.62016 Learning rate: 0.002 Mask loss: 0.11639 RPN box loss: 0.01147 RPN score loss: 0.00273 RPN total loss: 0.0142 Total loss: 0.84221 timestamp: 1654949668.744842 iteration: 45170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11052 FastRCNN class loss: 0.1129 FastRCNN total loss: 0.22342 L1 loss: 0.0000e+00 L2 loss: 0.62015 Learning rate: 0.002 Mask loss: 0.20226 RPN box loss: 0.01378 RPN score loss: 0.00919 RPN total loss: 0.02296 Total loss: 1.0688 timestamp: 1654949672.0000026 iteration: 45175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10544 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.1756 L1 loss: 0.0000e+00 L2 loss: 0.62014 Learning rate: 0.002 Mask loss: 0.10455 RPN box loss: 0.03456 RPN score loss: 0.00546 RPN total loss: 0.04002 Total loss: 0.94031 timestamp: 1654949675.2044296 iteration: 45180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16262 FastRCNN class loss: 0.12367 FastRCNN total loss: 0.28628 L1 loss: 0.0000e+00 L2 loss: 0.62013 Learning rate: 0.002 Mask loss: 0.16433 RPN box loss: 0.01695 RPN score loss: 0.0041 RPN total loss: 0.02106 Total loss: 1.0918 timestamp: 1654949678.4490547 iteration: 45185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11274 FastRCNN class loss: 0.06767 FastRCNN total loss: 0.18041 L1 loss: 0.0000e+00 L2 loss: 0.62013 Learning rate: 0.002 Mask loss: 0.16195 RPN box loss: 0.01214 RPN score loss: 0.00521 RPN total loss: 0.01735 Total loss: 0.97984 timestamp: 1654949681.6509693 iteration: 45190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09781 FastRCNN class loss: 0.06626 FastRCNN total loss: 0.16407 L1 loss: 0.0000e+00 L2 loss: 0.62012 Learning rate: 0.002 Mask loss: 0.15175 RPN box loss: 0.01515 RPN score loss: 0.00244 RPN total loss: 0.0176 Total loss: 0.95353 timestamp: 1654949684.8242295 iteration: 45195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16516 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.24304 L1 loss: 0.0000e+00 L2 loss: 0.62011 Learning rate: 0.002 Mask loss: 0.12335 RPN box loss: 0.0434 RPN score loss: 0.00604 RPN total loss: 0.04945 Total loss: 1.03594 timestamp: 1654949688.0406058 iteration: 45200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15233 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.23019 L1 loss: 0.0000e+00 L2 loss: 0.6201 Learning rate: 0.002 Mask loss: 0.14812 RPN box loss: 0.01413 RPN score loss: 0.00388 RPN total loss: 0.018 Total loss: 1.01642 timestamp: 1654949691.2036781 iteration: 45205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07602 FastRCNN class loss: 0.06325 FastRCNN total loss: 0.13927 L1 loss: 0.0000e+00 L2 loss: 0.62009 Learning rate: 0.002 Mask loss: 0.15527 RPN box loss: 0.00782 RPN score loss: 0.00357 RPN total loss: 0.0114 Total loss: 0.92603 timestamp: 1654949694.4659395 iteration: 45210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15183 FastRCNN class loss: 0.06649 FastRCNN total loss: 0.21831 L1 loss: 0.0000e+00 L2 loss: 0.62008 Learning rate: 0.002 Mask loss: 0.15238 RPN box loss: 0.01907 RPN score loss: 0.0075 RPN total loss: 0.02657 Total loss: 1.01734 timestamp: 1654949697.605349 iteration: 45215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18249 FastRCNN class loss: 0.08114 FastRCNN total loss: 0.26363 L1 loss: 0.0000e+00 L2 loss: 0.62007 Learning rate: 0.002 Mask loss: 0.16272 RPN box loss: 0.04648 RPN score loss: 0.01548 RPN total loss: 0.06196 Total loss: 1.10839 timestamp: 1654949700.8471146 iteration: 45220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13849 FastRCNN class loss: 0.08121 FastRCNN total loss: 0.2197 L1 loss: 0.0000e+00 L2 loss: 0.62006 Learning rate: 0.002 Mask loss: 0.09833 RPN box loss: 0.02658 RPN score loss: 0.01102 RPN total loss: 0.0376 Total loss: 0.97569 timestamp: 1654949704.1416166 iteration: 45225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15564 FastRCNN class loss: 0.11306 FastRCNN total loss: 0.2687 L1 loss: 0.0000e+00 L2 loss: 0.62006 Learning rate: 0.002 Mask loss: 0.17728 RPN box loss: 0.03727 RPN score loss: 0.01501 RPN total loss: 0.05228 Total loss: 1.11832 timestamp: 1654949707.269998 iteration: 45230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06744 FastRCNN class loss: 0.06623 FastRCNN total loss: 0.13366 L1 loss: 0.0000e+00 L2 loss: 0.62005 Learning rate: 0.002 Mask loss: 0.18681 RPN box loss: 0.01486 RPN score loss: 0.01132 RPN total loss: 0.02618 Total loss: 0.96669 timestamp: 1654949710.5201917 iteration: 45235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08317 FastRCNN class loss: 0.07683 FastRCNN total loss: 0.15999 L1 loss: 0.0000e+00 L2 loss: 0.62004 Learning rate: 0.002 Mask loss: 0.11488 RPN box loss: 0.00666 RPN score loss: 0.00173 RPN total loss: 0.00839 Total loss: 0.90329 timestamp: 1654949713.6905558 iteration: 45240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06382 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.13987 L1 loss: 0.0000e+00 L2 loss: 0.62002 Learning rate: 0.002 Mask loss: 0.10064 RPN box loss: 0.02151 RPN score loss: 0.00616 RPN total loss: 0.02768 Total loss: 0.88821 timestamp: 1654949716.927169 iteration: 45245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07784 FastRCNN class loss: 0.0609 FastRCNN total loss: 0.13874 L1 loss: 0.0000e+00 L2 loss: 0.62001 Learning rate: 0.002 Mask loss: 0.12044 RPN box loss: 0.04412 RPN score loss: 0.00387 RPN total loss: 0.04799 Total loss: 0.92718 timestamp: 1654949720.091721 iteration: 45250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08571 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.62 Learning rate: 0.002 Mask loss: 0.14953 RPN box loss: 0.01327 RPN score loss: 0.0058 RPN total loss: 0.01907 Total loss: 0.94868 timestamp: 1654949723.3249319 iteration: 45255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14699 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.20488 L1 loss: 0.0000e+00 L2 loss: 0.61999 Learning rate: 0.002 Mask loss: 0.11751 RPN box loss: 0.00589 RPN score loss: 0.00525 RPN total loss: 0.01114 Total loss: 0.95351 timestamp: 1654949726.5932732 iteration: 45260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07208 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.13988 L1 loss: 0.0000e+00 L2 loss: 0.61998 Learning rate: 0.002 Mask loss: 0.13655 RPN box loss: 0.01413 RPN score loss: 0.00377 RPN total loss: 0.0179 Total loss: 0.91432 timestamp: 1654949729.7946434 iteration: 45265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07151 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.11603 L1 loss: 0.0000e+00 L2 loss: 0.61997 Learning rate: 0.002 Mask loss: 0.05793 RPN box loss: 0.00257 RPN score loss: 0.00167 RPN total loss: 0.00424 Total loss: 0.79817 timestamp: 1654949733.0169625 iteration: 45270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06731 FastRCNN class loss: 0.06486 FastRCNN total loss: 0.13217 L1 loss: 0.0000e+00 L2 loss: 0.61996 Learning rate: 0.002 Mask loss: 0.14946 RPN box loss: 0.0171 RPN score loss: 0.00314 RPN total loss: 0.02024 Total loss: 0.92184 timestamp: 1654949736.1572876 iteration: 45275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.14463 L1 loss: 0.0000e+00 L2 loss: 0.61995 Learning rate: 0.002 Mask loss: 0.12466 RPN box loss: 0.0243 RPN score loss: 0.00411 RPN total loss: 0.02841 Total loss: 0.91765 timestamp: 1654949739.370376 iteration: 45280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10665 FastRCNN class loss: 0.08698 FastRCNN total loss: 0.19363 L1 loss: 0.0000e+00 L2 loss: 0.61994 Learning rate: 0.002 Mask loss: 0.10318 RPN box loss: 0.02572 RPN score loss: 0.01456 RPN total loss: 0.04028 Total loss: 0.95703 timestamp: 1654949742.5850472 iteration: 45285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14587 FastRCNN class loss: 0.05768 FastRCNN total loss: 0.20354 L1 loss: 0.0000e+00 L2 loss: 0.61994 Learning rate: 0.002 Mask loss: 0.10239 RPN box loss: 0.02913 RPN score loss: 0.00083 RPN total loss: 0.02995 Total loss: 0.95582 timestamp: 1654949745.8057375 iteration: 45290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1382 FastRCNN class loss: 0.0526 FastRCNN total loss: 0.1908 L1 loss: 0.0000e+00 L2 loss: 0.61993 Learning rate: 0.002 Mask loss: 0.08926 RPN box loss: 0.01155 RPN score loss: 0.00148 RPN total loss: 0.01303 Total loss: 0.91302 timestamp: 1654949748.9013045 iteration: 45295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09833 FastRCNN class loss: 0.08185 FastRCNN total loss: 0.18018 L1 loss: 0.0000e+00 L2 loss: 0.61992 Learning rate: 0.002 Mask loss: 0.15274 RPN box loss: 0.01633 RPN score loss: 0.00164 RPN total loss: 0.01797 Total loss: 0.9708 timestamp: 1654949752.1123307 iteration: 45300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06289 FastRCNN class loss: 0.05333 FastRCNN total loss: 0.11623 L1 loss: 0.0000e+00 L2 loss: 0.61991 Learning rate: 0.002 Mask loss: 0.16855 RPN box loss: 0.01042 RPN score loss: 0.00336 RPN total loss: 0.01378 Total loss: 0.91846 timestamp: 1654949755.3327782 iteration: 45305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10459 FastRCNN class loss: 0.07726 FastRCNN total loss: 0.18184 L1 loss: 0.0000e+00 L2 loss: 0.6199 Learning rate: 0.002 Mask loss: 0.18294 RPN box loss: 0.01708 RPN score loss: 0.00771 RPN total loss: 0.02479 Total loss: 1.00948 timestamp: 1654949758.4601502 iteration: 45310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04767 FastRCNN class loss: 0.03811 FastRCNN total loss: 0.08578 L1 loss: 0.0000e+00 L2 loss: 0.61989 Learning rate: 0.002 Mask loss: 0.092 RPN box loss: 0.00221 RPN score loss: 0.00087 RPN total loss: 0.00309 Total loss: 0.80075 timestamp: 1654949761.6726947 iteration: 45315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09535 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.15163 L1 loss: 0.0000e+00 L2 loss: 0.61988 Learning rate: 0.002 Mask loss: 0.15294 RPN box loss: 0.02231 RPN score loss: 0.0018 RPN total loss: 0.02411 Total loss: 0.94855 timestamp: 1654949764.7825944 iteration: 45320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09023 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.15592 L1 loss: 0.0000e+00 L2 loss: 0.61987 Learning rate: 0.002 Mask loss: 0.15269 RPN box loss: 0.03265 RPN score loss: 0.00341 RPN total loss: 0.03606 Total loss: 0.96453 timestamp: 1654949768.037508 iteration: 45325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08794 FastRCNN class loss: 0.06927 FastRCNN total loss: 0.15721 L1 loss: 0.0000e+00 L2 loss: 0.61986 Learning rate: 0.002 Mask loss: 0.13151 RPN box loss: 0.01727 RPN score loss: 0.00608 RPN total loss: 0.02335 Total loss: 0.93194 timestamp: 1654949771.2577655 iteration: 45330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13218 FastRCNN class loss: 0.09285 FastRCNN total loss: 0.22504 L1 loss: 0.0000e+00 L2 loss: 0.61985 Learning rate: 0.002 Mask loss: 0.14357 RPN box loss: 0.01561 RPN score loss: 0.0046 RPN total loss: 0.02021 Total loss: 1.00867 timestamp: 1654949774.4176984 iteration: 45335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08221 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.1511 L1 loss: 0.0000e+00 L2 loss: 0.61984 Learning rate: 0.002 Mask loss: 0.11589 RPN box loss: 0.01036 RPN score loss: 0.00286 RPN total loss: 0.01322 Total loss: 0.90006 timestamp: 1654949777.5815604 iteration: 45340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08367 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.13843 L1 loss: 0.0000e+00 L2 loss: 0.61984 Learning rate: 0.002 Mask loss: 0.1039 RPN box loss: 0.05316 RPN score loss: 0.01006 RPN total loss: 0.06322 Total loss: 0.92539 timestamp: 1654949780.7725239 iteration: 45345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.14045 L1 loss: 0.0000e+00 L2 loss: 0.61983 Learning rate: 0.002 Mask loss: 0.11359 RPN box loss: 0.03329 RPN score loss: 0.00316 RPN total loss: 0.03644 Total loss: 0.91032 timestamp: 1654949783.9595327 iteration: 45350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0545 FastRCNN class loss: 0.05649 FastRCNN total loss: 0.11099 L1 loss: 0.0000e+00 L2 loss: 0.61982 Learning rate: 0.002 Mask loss: 0.12461 RPN box loss: 0.01757 RPN score loss: 0.00931 RPN total loss: 0.02687 Total loss: 0.8823 timestamp: 1654949787.1721265 iteration: 45355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14088 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.21625 L1 loss: 0.0000e+00 L2 loss: 0.61981 Learning rate: 0.002 Mask loss: 0.16755 RPN box loss: 0.03232 RPN score loss: 0.01692 RPN total loss: 0.04924 Total loss: 1.05285 timestamp: 1654949790.3503344 iteration: 45360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.16285 L1 loss: 0.0000e+00 L2 loss: 0.6198 Learning rate: 0.002 Mask loss: 0.11485 RPN box loss: 0.03132 RPN score loss: 0.00229 RPN total loss: 0.0336 Total loss: 0.9311 timestamp: 1654949793.5062785 iteration: 45365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.03393 FastRCNN total loss: 0.12873 L1 loss: 0.0000e+00 L2 loss: 0.61979 Learning rate: 0.002 Mask loss: 0.13384 RPN box loss: 0.00632 RPN score loss: 0.00358 RPN total loss: 0.0099 Total loss: 0.89226 timestamp: 1654949796.7865534 iteration: 45370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.15241 L1 loss: 0.0000e+00 L2 loss: 0.61978 Learning rate: 0.002 Mask loss: 0.13085 RPN box loss: 0.00706 RPN score loss: 0.00824 RPN total loss: 0.0153 Total loss: 0.91833 timestamp: 1654949800.0236318 iteration: 45375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12198 FastRCNN class loss: 0.07479 FastRCNN total loss: 0.19677 L1 loss: 0.0000e+00 L2 loss: 0.61977 Learning rate: 0.002 Mask loss: 0.17542 RPN box loss: 0.02417 RPN score loss: 0.01059 RPN total loss: 0.03476 Total loss: 1.02671 timestamp: 1654949803.2688053 iteration: 45380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15413 FastRCNN class loss: 0.08315 FastRCNN total loss: 0.23729 L1 loss: 0.0000e+00 L2 loss: 0.61975 Learning rate: 0.002 Mask loss: 0.14032 RPN box loss: 0.01266 RPN score loss: 0.00785 RPN total loss: 0.0205 Total loss: 1.01787 timestamp: 1654949806.4414253 iteration: 45385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.04717 FastRCNN total loss: 0.13918 L1 loss: 0.0000e+00 L2 loss: 0.61974 Learning rate: 0.002 Mask loss: 0.10429 RPN box loss: 0.025 RPN score loss: 0.005 RPN total loss: 0.03 Total loss: 0.89322 timestamp: 1654949809.6819258 iteration: 45390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10128 FastRCNN class loss: 0.08573 FastRCNN total loss: 0.18701 L1 loss: 0.0000e+00 L2 loss: 0.61973 Learning rate: 0.002 Mask loss: 0.14405 RPN box loss: 0.03972 RPN score loss: 0.00622 RPN total loss: 0.04595 Total loss: 0.99673 timestamp: 1654949812.9269018 iteration: 45395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05467 FastRCNN class loss: 0.03513 FastRCNN total loss: 0.0898 L1 loss: 0.0000e+00 L2 loss: 0.61972 Learning rate: 0.002 Mask loss: 0.11074 RPN box loss: 0.02679 RPN score loss: 0.00534 RPN total loss: 0.03213 Total loss: 0.8524 timestamp: 1654949816.199918 iteration: 45400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09792 FastRCNN class loss: 0.04989 FastRCNN total loss: 0.14781 L1 loss: 0.0000e+00 L2 loss: 0.61971 Learning rate: 0.002 Mask loss: 0.12516 RPN box loss: 0.00782 RPN score loss: 0.00174 RPN total loss: 0.00956 Total loss: 0.90225 timestamp: 1654949819.3786178 iteration: 45405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05357 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.11932 L1 loss: 0.0000e+00 L2 loss: 0.61971 Learning rate: 0.002 Mask loss: 0.08607 RPN box loss: 0.01782 RPN score loss: 0.00262 RPN total loss: 0.02044 Total loss: 0.84554 timestamp: 1654949822.5536053 iteration: 45410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09124 FastRCNN class loss: 0.04155 FastRCNN total loss: 0.13278 L1 loss: 0.0000e+00 L2 loss: 0.6197 Learning rate: 0.002 Mask loss: 0.11493 RPN box loss: 0.00749 RPN score loss: 0.00446 RPN total loss: 0.01196 Total loss: 0.87937 timestamp: 1654949825.836678 iteration: 45415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1156 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.18325 L1 loss: 0.0000e+00 L2 loss: 0.61969 Learning rate: 0.002 Mask loss: 0.1484 RPN box loss: 0.02352 RPN score loss: 0.00504 RPN total loss: 0.02857 Total loss: 0.97991 timestamp: 1654949828.9418333 iteration: 45420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06041 FastRCNN class loss: 0.03639 FastRCNN total loss: 0.0968 L1 loss: 0.0000e+00 L2 loss: 0.61968 Learning rate: 0.002 Mask loss: 0.09079 RPN box loss: 0.00463 RPN score loss: 0.01223 RPN total loss: 0.01686 Total loss: 0.82413 timestamp: 1654949832.2056813 iteration: 45425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07311 FastRCNN class loss: 0.07659 FastRCNN total loss: 0.14969 L1 loss: 0.0000e+00 L2 loss: 0.61967 Learning rate: 0.002 Mask loss: 0.16036 RPN box loss: 0.02008 RPN score loss: 0.01174 RPN total loss: 0.03182 Total loss: 0.96155 timestamp: 1654949835.4821422 iteration: 45430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09316 FastRCNN class loss: 0.0385 FastRCNN total loss: 0.13166 L1 loss: 0.0000e+00 L2 loss: 0.61966 Learning rate: 0.002 Mask loss: 0.12027 RPN box loss: 0.01635 RPN score loss: 0.00214 RPN total loss: 0.01849 Total loss: 0.89008 timestamp: 1654949838.6585882 iteration: 45435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09814 FastRCNN class loss: 0.06472 FastRCNN total loss: 0.16287 L1 loss: 0.0000e+00 L2 loss: 0.61966 Learning rate: 0.002 Mask loss: 0.10367 RPN box loss: 0.01512 RPN score loss: 0.00155 RPN total loss: 0.01667 Total loss: 0.90286 timestamp: 1654949841.775166 iteration: 45440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13719 FastRCNN class loss: 0.08949 FastRCNN total loss: 0.22668 L1 loss: 0.0000e+00 L2 loss: 0.61965 Learning rate: 0.002 Mask loss: 0.1872 RPN box loss: 0.03575 RPN score loss: 0.0072 RPN total loss: 0.04295 Total loss: 1.07647 timestamp: 1654949844.98073 iteration: 45445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05949 FastRCNN class loss: 0.0534 FastRCNN total loss: 0.11289 L1 loss: 0.0000e+00 L2 loss: 0.61964 Learning rate: 0.002 Mask loss: 0.12183 RPN box loss: 0.01074 RPN score loss: 0.00562 RPN total loss: 0.01636 Total loss: 0.87071 timestamp: 1654949848.2166603 iteration: 45450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09283 FastRCNN class loss: 0.05288 FastRCNN total loss: 0.14571 L1 loss: 0.0000e+00 L2 loss: 0.61963 Learning rate: 0.002 Mask loss: 0.10354 RPN box loss: 0.00598 RPN score loss: 0.00153 RPN total loss: 0.00751 Total loss: 0.87639 timestamp: 1654949851.4406214 iteration: 45455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12029 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.20884 L1 loss: 0.0000e+00 L2 loss: 0.61962 Learning rate: 0.002 Mask loss: 0.143 RPN box loss: 0.01955 RPN score loss: 0.00852 RPN total loss: 0.02807 Total loss: 0.99953 timestamp: 1654949854.6505163 iteration: 45460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16307 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.23829 L1 loss: 0.0000e+00 L2 loss: 0.61961 Learning rate: 0.002 Mask loss: 0.09571 RPN box loss: 0.01492 RPN score loss: 0.00314 RPN total loss: 0.01806 Total loss: 0.97168 timestamp: 1654949857.8485563 iteration: 45465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09391 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.15262 L1 loss: 0.0000e+00 L2 loss: 0.6196 Learning rate: 0.002 Mask loss: 0.17795 RPN box loss: 0.02956 RPN score loss: 0.00593 RPN total loss: 0.03549 Total loss: 0.98567 timestamp: 1654949860.989836 iteration: 45470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12375 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.20339 L1 loss: 0.0000e+00 L2 loss: 0.61959 Learning rate: 0.002 Mask loss: 0.16496 RPN box loss: 0.03111 RPN score loss: 0.00482 RPN total loss: 0.03593 Total loss: 1.02387 timestamp: 1654949864.1409955 iteration: 45475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1107 FastRCNN class loss: 0.05503 FastRCNN total loss: 0.16573 L1 loss: 0.0000e+00 L2 loss: 0.61958 Learning rate: 0.002 Mask loss: 0.13301 RPN box loss: 0.01571 RPN score loss: 0.00372 RPN total loss: 0.01943 Total loss: 0.93775 timestamp: 1654949867.2825549 iteration: 45480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05078 FastRCNN class loss: 0.043 FastRCNN total loss: 0.09378 L1 loss: 0.0000e+00 L2 loss: 0.61957 Learning rate: 0.002 Mask loss: 0.10017 RPN box loss: 0.00744 RPN score loss: 0.00346 RPN total loss: 0.0109 Total loss: 0.82443 timestamp: 1654949870.4965847 iteration: 45485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10304 FastRCNN class loss: 0.07151 FastRCNN total loss: 0.17456 L1 loss: 0.0000e+00 L2 loss: 0.61956 Learning rate: 0.002 Mask loss: 0.18928 RPN box loss: 0.00551 RPN score loss: 0.00304 RPN total loss: 0.00854 Total loss: 0.99194 timestamp: 1654949873.7123992 iteration: 45490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16027 FastRCNN class loss: 0.12379 FastRCNN total loss: 0.28407 L1 loss: 0.0000e+00 L2 loss: 0.61955 Learning rate: 0.002 Mask loss: 0.14869 RPN box loss: 0.01562 RPN score loss: 0.00418 RPN total loss: 0.01981 Total loss: 1.07211 timestamp: 1654949876.8815012 iteration: 45495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11971 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.20333 L1 loss: 0.0000e+00 L2 loss: 0.61954 Learning rate: 0.002 Mask loss: 0.13075 RPN box loss: 0.04644 RPN score loss: 0.00754 RPN total loss: 0.05398 Total loss: 1.0076 timestamp: 1654949880.0687776 iteration: 45500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06364 FastRCNN class loss: 0.03309 FastRCNN total loss: 0.09673 L1 loss: 0.0000e+00 L2 loss: 0.61953 Learning rate: 0.002 Mask loss: 0.09443 RPN box loss: 0.00342 RPN score loss: 0.00361 RPN total loss: 0.00702 Total loss: 0.81772 timestamp: 1654949883.3376133 iteration: 45505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04837 FastRCNN class loss: 0.05206 FastRCNN total loss: 0.10044 L1 loss: 0.0000e+00 L2 loss: 0.61952 Learning rate: 0.002 Mask loss: 0.13693 RPN box loss: 0.00824 RPN score loss: 0.00059 RPN total loss: 0.00883 Total loss: 0.86571 timestamp: 1654949886.6226926 iteration: 45510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13035 FastRCNN class loss: 0.12151 FastRCNN total loss: 0.25186 L1 loss: 0.0000e+00 L2 loss: 0.61952 Learning rate: 0.002 Mask loss: 0.15949 RPN box loss: 0.02345 RPN score loss: 0.0078 RPN total loss: 0.03126 Total loss: 1.06212 timestamp: 1654949889.821568 iteration: 45515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10486 FastRCNN class loss: 0.08403 FastRCNN total loss: 0.18889 L1 loss: 0.0000e+00 L2 loss: 0.61951 Learning rate: 0.002 Mask loss: 0.18229 RPN box loss: 0.01133 RPN score loss: 0.01008 RPN total loss: 0.02141 Total loss: 1.0121 timestamp: 1654949893.0402899 iteration: 45520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09393 FastRCNN class loss: 0.07777 FastRCNN total loss: 0.1717 L1 loss: 0.0000e+00 L2 loss: 0.6195 Learning rate: 0.002 Mask loss: 0.16607 RPN box loss: 0.0169 RPN score loss: 0.01052 RPN total loss: 0.02743 Total loss: 0.98469 timestamp: 1654949896.3284106 iteration: 45525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11466 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.18536 L1 loss: 0.0000e+00 L2 loss: 0.61949 Learning rate: 0.002 Mask loss: 0.09601 RPN box loss: 0.00903 RPN score loss: 0.00123 RPN total loss: 0.01026 Total loss: 0.91112 timestamp: 1654949899.5201213 iteration: 45530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13012 FastRCNN class loss: 0.07154 FastRCNN total loss: 0.20166 L1 loss: 0.0000e+00 L2 loss: 0.61948 Learning rate: 0.002 Mask loss: 0.18175 RPN box loss: 0.01657 RPN score loss: 0.00907 RPN total loss: 0.02564 Total loss: 1.02852 timestamp: 1654949902.6881437 iteration: 45535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09989 FastRCNN class loss: 0.12057 FastRCNN total loss: 0.22046 L1 loss: 0.0000e+00 L2 loss: 0.61947 Learning rate: 0.002 Mask loss: 0.17396 RPN box loss: 0.03037 RPN score loss: 0.01495 RPN total loss: 0.04532 Total loss: 1.0592 timestamp: 1654949905.8333793 iteration: 45540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08767 FastRCNN class loss: 0.07648 FastRCNN total loss: 0.16415 L1 loss: 0.0000e+00 L2 loss: 0.61946 Learning rate: 0.002 Mask loss: 0.13666 RPN box loss: 0.02582 RPN score loss: 0.00718 RPN total loss: 0.03301 Total loss: 0.95327 timestamp: 1654949909.1354685 iteration: 45545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16691 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.27076 L1 loss: 0.0000e+00 L2 loss: 0.61945 Learning rate: 0.002 Mask loss: 0.15773 RPN box loss: 0.02472 RPN score loss: 0.00438 RPN total loss: 0.0291 Total loss: 1.07705 timestamp: 1654949912.2209518 iteration: 45550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06983 FastRCNN class loss: 0.05962 FastRCNN total loss: 0.12946 L1 loss: 0.0000e+00 L2 loss: 0.61944 Learning rate: 0.002 Mask loss: 0.08174 RPN box loss: 0.01109 RPN score loss: 0.0041 RPN total loss: 0.01519 Total loss: 0.84584 timestamp: 1654949915.4753742 iteration: 45555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15095 FastRCNN class loss: 0.14124 FastRCNN total loss: 0.2922 L1 loss: 0.0000e+00 L2 loss: 0.61944 Learning rate: 0.002 Mask loss: 0.24971 RPN box loss: 0.02519 RPN score loss: 0.01369 RPN total loss: 0.03887 Total loss: 1.20021 timestamp: 1654949918.6932075 iteration: 45560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05704 FastRCNN class loss: 0.04156 FastRCNN total loss: 0.09861 L1 loss: 0.0000e+00 L2 loss: 0.61943 Learning rate: 0.002 Mask loss: 0.09296 RPN box loss: 0.0217 RPN score loss: 0.01072 RPN total loss: 0.03242 Total loss: 0.84341 timestamp: 1654949921.8962903 iteration: 45565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14568 FastRCNN class loss: 0.06302 FastRCNN total loss: 0.20869 L1 loss: 0.0000e+00 L2 loss: 0.61942 Learning rate: 0.002 Mask loss: 0.14591 RPN box loss: 0.01648 RPN score loss: 0.00256 RPN total loss: 0.01904 Total loss: 0.99306 timestamp: 1654949925.1146023 iteration: 45570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04204 FastRCNN class loss: 0.05399 FastRCNN total loss: 0.09602 L1 loss: 0.0000e+00 L2 loss: 0.61941 Learning rate: 0.002 Mask loss: 0.13006 RPN box loss: 0.01339 RPN score loss: 0.01085 RPN total loss: 0.02424 Total loss: 0.86974 timestamp: 1654949928.3562832 iteration: 45575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13168 FastRCNN class loss: 0.10088 FastRCNN total loss: 0.23256 L1 loss: 0.0000e+00 L2 loss: 0.6194 Learning rate: 0.002 Mask loss: 0.09967 RPN box loss: 0.0211 RPN score loss: 0.00474 RPN total loss: 0.02584 Total loss: 0.97747 timestamp: 1654949931.6038578 iteration: 45580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0609 FastRCNN class loss: 0.10379 FastRCNN total loss: 0.16469 L1 loss: 0.0000e+00 L2 loss: 0.61939 Learning rate: 0.002 Mask loss: 0.11901 RPN box loss: 0.02943 RPN score loss: 0.00837 RPN total loss: 0.03779 Total loss: 0.94088 timestamp: 1654949934.8575432 iteration: 45585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11685 FastRCNN class loss: 0.05256 FastRCNN total loss: 0.1694 L1 loss: 0.0000e+00 L2 loss: 0.61938 Learning rate: 0.002 Mask loss: 0.09631 RPN box loss: 0.00632 RPN score loss: 0.00195 RPN total loss: 0.00828 Total loss: 0.89338 timestamp: 1654949938.062249 iteration: 45590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09037 FastRCNN class loss: 0.08574 FastRCNN total loss: 0.17612 L1 loss: 0.0000e+00 L2 loss: 0.61937 Learning rate: 0.002 Mask loss: 0.12411 RPN box loss: 0.03474 RPN score loss: 0.01236 RPN total loss: 0.04711 Total loss: 0.9667 timestamp: 1654949941.311527 iteration: 45595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0649 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.61936 Learning rate: 0.002 Mask loss: 0.13522 RPN box loss: 0.02239 RPN score loss: 0.00659 RPN total loss: 0.02898 Total loss: 0.9219 timestamp: 1654949944.582436 iteration: 45600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12219 FastRCNN class loss: 0.12832 FastRCNN total loss: 0.25051 L1 loss: 0.0000e+00 L2 loss: 0.61935 Learning rate: 0.002 Mask loss: 0.17141 RPN box loss: 0.02322 RPN score loss: 0.00558 RPN total loss: 0.0288 Total loss: 1.07007 timestamp: 1654949947.7878976 iteration: 45605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07389 FastRCNN class loss: 0.03941 FastRCNN total loss: 0.1133 L1 loss: 0.0000e+00 L2 loss: 0.61935 Learning rate: 0.002 Mask loss: 0.10344 RPN box loss: 0.00404 RPN score loss: 0.00079 RPN total loss: 0.00483 Total loss: 0.84092 timestamp: 1654949951.0055711 iteration: 45610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07881 FastRCNN class loss: 0.07872 FastRCNN total loss: 0.15753 L1 loss: 0.0000e+00 L2 loss: 0.61934 Learning rate: 0.002 Mask loss: 0.14749 RPN box loss: 0.01851 RPN score loss: 0.00177 RPN total loss: 0.02028 Total loss: 0.94464 timestamp: 1654949954.2348619 iteration: 45615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12316 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.19511 L1 loss: 0.0000e+00 L2 loss: 0.61933 Learning rate: 0.002 Mask loss: 0.18914 RPN box loss: 0.01775 RPN score loss: 0.00227 RPN total loss: 0.02003 Total loss: 1.0236 timestamp: 1654949957.4364705 iteration: 45620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13653 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.20883 L1 loss: 0.0000e+00 L2 loss: 0.61932 Learning rate: 0.002 Mask loss: 0.14248 RPN box loss: 0.02033 RPN score loss: 0.0061 RPN total loss: 0.02643 Total loss: 0.99706 timestamp: 1654949960.6079235 iteration: 45625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12415 FastRCNN class loss: 0.0779 FastRCNN total loss: 0.20206 L1 loss: 0.0000e+00 L2 loss: 0.61931 Learning rate: 0.002 Mask loss: 0.13732 RPN box loss: 0.05309 RPN score loss: 0.00146 RPN total loss: 0.05456 Total loss: 1.01325 timestamp: 1654949963.8752394 iteration: 45630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10039 FastRCNN class loss: 0.10997 FastRCNN total loss: 0.21036 L1 loss: 0.0000e+00 L2 loss: 0.6193 Learning rate: 0.002 Mask loss: 0.12608 RPN box loss: 0.01341 RPN score loss: 0.00405 RPN total loss: 0.01746 Total loss: 0.97319 timestamp: 1654949967.0572724 iteration: 45635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14947 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.21895 L1 loss: 0.0000e+00 L2 loss: 0.61929 Learning rate: 0.002 Mask loss: 0.18273 RPN box loss: 0.00757 RPN score loss: 0.00325 RPN total loss: 0.01083 Total loss: 1.0318 timestamp: 1654949970.2712128 iteration: 45640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05655 FastRCNN class loss: 0.05947 FastRCNN total loss: 0.11602 L1 loss: 0.0000e+00 L2 loss: 0.61928 Learning rate: 0.002 Mask loss: 0.10237 RPN box loss: 0.00354 RPN score loss: 0.00123 RPN total loss: 0.00477 Total loss: 0.84245 timestamp: 1654949973.4229658 iteration: 45645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08458 FastRCNN class loss: 0.03912 FastRCNN total loss: 0.1237 L1 loss: 0.0000e+00 L2 loss: 0.61927 Learning rate: 0.002 Mask loss: 0.12194 RPN box loss: 0.0126 RPN score loss: 0.00327 RPN total loss: 0.01587 Total loss: 0.88077 timestamp: 1654949976.6312397 iteration: 45650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05488 FastRCNN class loss: 0.05299 FastRCNN total loss: 0.10787 L1 loss: 0.0000e+00 L2 loss: 0.61926 Learning rate: 0.002 Mask loss: 0.13994 RPN box loss: 0.01091 RPN score loss: 0.00152 RPN total loss: 0.01243 Total loss: 0.8795 timestamp: 1654949979.803808 iteration: 45655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14191 FastRCNN class loss: 0.08748 FastRCNN total loss: 0.22939 L1 loss: 0.0000e+00 L2 loss: 0.61925 Learning rate: 0.002 Mask loss: 0.18091 RPN box loss: 0.02408 RPN score loss: 0.00561 RPN total loss: 0.0297 Total loss: 1.05924 timestamp: 1654949983.0389073 iteration: 45660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09467 FastRCNN class loss: 0.082 FastRCNN total loss: 0.17666 L1 loss: 0.0000e+00 L2 loss: 0.61924 Learning rate: 0.002 Mask loss: 0.13028 RPN box loss: 0.03291 RPN score loss: 0.00343 RPN total loss: 0.03634 Total loss: 0.96252 timestamp: 1654949986.2157552 iteration: 45665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14082 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.22313 L1 loss: 0.0000e+00 L2 loss: 0.61924 Learning rate: 0.002 Mask loss: 0.14063 RPN box loss: 0.02942 RPN score loss: 0.01533 RPN total loss: 0.04475 Total loss: 1.02774 timestamp: 1654949989.5037804 iteration: 45670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07885 FastRCNN class loss: 0.03861 FastRCNN total loss: 0.11746 L1 loss: 0.0000e+00 L2 loss: 0.61923 Learning rate: 0.002 Mask loss: 0.09265 RPN box loss: 0.01781 RPN score loss: 0.0031 RPN total loss: 0.0209 Total loss: 0.85024 timestamp: 1654949992.7355585 iteration: 45675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05504 FastRCNN class loss: 0.054 FastRCNN total loss: 0.10904 L1 loss: 0.0000e+00 L2 loss: 0.61922 Learning rate: 0.002 Mask loss: 0.15318 RPN box loss: 0.00338 RPN score loss: 0.00038 RPN total loss: 0.00376 Total loss: 0.88521 timestamp: 1654949995.9726915 iteration: 45680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12408 FastRCNN class loss: 0.09759 FastRCNN total loss: 0.22168 L1 loss: 0.0000e+00 L2 loss: 0.61921 Learning rate: 0.002 Mask loss: 0.17132 RPN box loss: 0.02736 RPN score loss: 0.00534 RPN total loss: 0.03271 Total loss: 1.04491 timestamp: 1654949999.1287775 iteration: 45685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12425 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.20154 L1 loss: 0.0000e+00 L2 loss: 0.6192 Learning rate: 0.002 Mask loss: 0.15822 RPN box loss: 0.0273 RPN score loss: 0.0034 RPN total loss: 0.0307 Total loss: 1.00966 timestamp: 1654950002.282601 iteration: 45690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07514 FastRCNN class loss: 0.10238 FastRCNN total loss: 0.17752 L1 loss: 0.0000e+00 L2 loss: 0.61918 Learning rate: 0.002 Mask loss: 0.11583 RPN box loss: 0.01125 RPN score loss: 0.00394 RPN total loss: 0.01519 Total loss: 0.92771 timestamp: 1654950005.5378265 iteration: 45695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08502 FastRCNN class loss: 0.06079 FastRCNN total loss: 0.14581 L1 loss: 0.0000e+00 L2 loss: 0.61917 Learning rate: 0.002 Mask loss: 0.10649 RPN box loss: 0.02112 RPN score loss: 0.01167 RPN total loss: 0.03279 Total loss: 0.90426 timestamp: 1654950008.7710798 iteration: 45700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14451 FastRCNN class loss: 0.08533 FastRCNN total loss: 0.22984 L1 loss: 0.0000e+00 L2 loss: 0.61916 Learning rate: 0.002 Mask loss: 0.14246 RPN box loss: 0.00713 RPN score loss: 0.01146 RPN total loss: 0.01859 Total loss: 1.01005 timestamp: 1654950011.9716074 iteration: 45705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05152 FastRCNN class loss: 0.04853 FastRCNN total loss: 0.10006 L1 loss: 0.0000e+00 L2 loss: 0.61915 Learning rate: 0.002 Mask loss: 0.15055 RPN box loss: 0.00498 RPN score loss: 0.00398 RPN total loss: 0.00895 Total loss: 0.87871 timestamp: 1654950015.2230213 iteration: 45710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12547 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.19034 L1 loss: 0.0000e+00 L2 loss: 0.61915 Learning rate: 0.002 Mask loss: 0.19567 RPN box loss: 0.01942 RPN score loss: 0.01421 RPN total loss: 0.03364 Total loss: 1.03879 timestamp: 1654950018.42686 iteration: 45715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09425 FastRCNN class loss: 0.05822 FastRCNN total loss: 0.15247 L1 loss: 0.0000e+00 L2 loss: 0.61913 Learning rate: 0.002 Mask loss: 0.13905 RPN box loss: 0.02485 RPN score loss: 0.00289 RPN total loss: 0.02775 Total loss: 0.93841 timestamp: 1654950021.6374445 iteration: 45720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09362 FastRCNN class loss: 0.04003 FastRCNN total loss: 0.13365 L1 loss: 0.0000e+00 L2 loss: 0.61912 Learning rate: 0.002 Mask loss: 0.09668 RPN box loss: 0.02245 RPN score loss: 0.00102 RPN total loss: 0.02347 Total loss: 0.87292 timestamp: 1654950024.9056814 iteration: 45725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07109 FastRCNN class loss: 0.04508 FastRCNN total loss: 0.11618 L1 loss: 0.0000e+00 L2 loss: 0.61912 Learning rate: 0.002 Mask loss: 0.11918 RPN box loss: 0.01256 RPN score loss: 0.00449 RPN total loss: 0.01705 Total loss: 0.87153 timestamp: 1654950028.08106 iteration: 45730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11259 FastRCNN class loss: 0.08431 FastRCNN total loss: 0.19691 L1 loss: 0.0000e+00 L2 loss: 0.61911 Learning rate: 0.002 Mask loss: 0.11133 RPN box loss: 0.03631 RPN score loss: 0.00088 RPN total loss: 0.03718 Total loss: 0.96453 timestamp: 1654950031.2435277 iteration: 45735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.03916 FastRCNN total loss: 0.11494 L1 loss: 0.0000e+00 L2 loss: 0.6191 Learning rate: 0.002 Mask loss: 0.12374 RPN box loss: 0.05216 RPN score loss: 0.00136 RPN total loss: 0.05352 Total loss: 0.91131 timestamp: 1654950034.4079022 iteration: 45740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09512 FastRCNN class loss: 0.06302 FastRCNN total loss: 0.15814 L1 loss: 0.0000e+00 L2 loss: 0.61909 Learning rate: 0.002 Mask loss: 0.12722 RPN box loss: 0.03386 RPN score loss: 0.01573 RPN total loss: 0.04958 Total loss: 0.95404 timestamp: 1654950037.6755524 iteration: 45745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09831 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.14887 L1 loss: 0.0000e+00 L2 loss: 0.61908 Learning rate: 0.002 Mask loss: 0.15192 RPN box loss: 0.01106 RPN score loss: 0.00496 RPN total loss: 0.01602 Total loss: 0.9359 timestamp: 1654950040.928355 iteration: 45750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08513 FastRCNN class loss: 0.09344 FastRCNN total loss: 0.17857 L1 loss: 0.0000e+00 L2 loss: 0.61908 Learning rate: 0.002 Mask loss: 0.15493 RPN box loss: 0.04704 RPN score loss: 0.00634 RPN total loss: 0.05338 Total loss: 1.00595 timestamp: 1654950044.1653025 iteration: 45755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05453 FastRCNN class loss: 0.08879 FastRCNN total loss: 0.14332 L1 loss: 0.0000e+00 L2 loss: 0.61906 Learning rate: 0.002 Mask loss: 0.12051 RPN box loss: 0.00955 RPN score loss: 0.00441 RPN total loss: 0.01397 Total loss: 0.89686 timestamp: 1654950047.411231 iteration: 45760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06012 FastRCNN class loss: 0.05389 FastRCNN total loss: 0.11401 L1 loss: 0.0000e+00 L2 loss: 0.61905 Learning rate: 0.002 Mask loss: 0.14285 RPN box loss: 0.02889 RPN score loss: 0.00754 RPN total loss: 0.03643 Total loss: 0.91233 timestamp: 1654950050.6724231 iteration: 45765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08207 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.15325 L1 loss: 0.0000e+00 L2 loss: 0.61905 Learning rate: 0.002 Mask loss: 0.15108 RPN box loss: 0.00365 RPN score loss: 0.00332 RPN total loss: 0.00697 Total loss: 0.93034 timestamp: 1654950053.9003947 iteration: 45770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09347 FastRCNN class loss: 0.08279 FastRCNN total loss: 0.17626 L1 loss: 0.0000e+00 L2 loss: 0.61904 Learning rate: 0.002 Mask loss: 0.15966 RPN box loss: 0.04609 RPN score loss: 0.00482 RPN total loss: 0.05091 Total loss: 1.00586 timestamp: 1654950057.1043446 iteration: 45775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07007 FastRCNN class loss: 0.05869 FastRCNN total loss: 0.12875 L1 loss: 0.0000e+00 L2 loss: 0.61903 Learning rate: 0.002 Mask loss: 0.13994 RPN box loss: 0.00984 RPN score loss: 0.00669 RPN total loss: 0.01653 Total loss: 0.90425 timestamp: 1654950060.3021321 iteration: 45780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06158 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.12586 L1 loss: 0.0000e+00 L2 loss: 0.61902 Learning rate: 0.002 Mask loss: 0.10543 RPN box loss: 0.01074 RPN score loss: 0.00303 RPN total loss: 0.01377 Total loss: 0.86408 timestamp: 1654950063.5284846 iteration: 45785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06997 FastRCNN class loss: 0.05184 FastRCNN total loss: 0.12181 L1 loss: 0.0000e+00 L2 loss: 0.61901 Learning rate: 0.002 Mask loss: 0.12828 RPN box loss: 0.00567 RPN score loss: 0.00158 RPN total loss: 0.00725 Total loss: 0.87634 timestamp: 1654950066.736641 iteration: 45790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09576 FastRCNN class loss: 0.05921 FastRCNN total loss: 0.15497 L1 loss: 0.0000e+00 L2 loss: 0.61899 Learning rate: 0.002 Mask loss: 0.12744 RPN box loss: 0.01649 RPN score loss: 0.01067 RPN total loss: 0.02717 Total loss: 0.92857 timestamp: 1654950069.9559758 iteration: 45795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05478 FastRCNN class loss: 0.03848 FastRCNN total loss: 0.09326 L1 loss: 0.0000e+00 L2 loss: 0.61898 Learning rate: 0.002 Mask loss: 0.11802 RPN box loss: 0.01566 RPN score loss: 0.00169 RPN total loss: 0.01735 Total loss: 0.84761 timestamp: 1654950073.1074395 iteration: 45800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1833 FastRCNN class loss: 0.12851 FastRCNN total loss: 0.31181 L1 loss: 0.0000e+00 L2 loss: 0.61897 Learning rate: 0.002 Mask loss: 0.19049 RPN box loss: 0.01901 RPN score loss: 0.00677 RPN total loss: 0.02578 Total loss: 1.14705 timestamp: 1654950076.3616104 iteration: 45805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10056 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.18307 L1 loss: 0.0000e+00 L2 loss: 0.61896 Learning rate: 0.002 Mask loss: 0.12373 RPN box loss: 0.07625 RPN score loss: 0.00229 RPN total loss: 0.07854 Total loss: 1.0043 timestamp: 1654950079.5806139 iteration: 45810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12345 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.2208 L1 loss: 0.0000e+00 L2 loss: 0.61895 Learning rate: 0.002 Mask loss: 0.17634 RPN box loss: 0.02221 RPN score loss: 0.00737 RPN total loss: 0.02958 Total loss: 1.04566 timestamp: 1654950082.848599 iteration: 45815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10516 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.18141 L1 loss: 0.0000e+00 L2 loss: 0.61894 Learning rate: 0.002 Mask loss: 0.18453 RPN box loss: 0.02447 RPN score loss: 0.00992 RPN total loss: 0.03439 Total loss: 1.01927 timestamp: 1654950086.0716686 iteration: 45820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14503 FastRCNN class loss: 0.08085 FastRCNN total loss: 0.22588 L1 loss: 0.0000e+00 L2 loss: 0.61893 Learning rate: 0.002 Mask loss: 0.13789 RPN box loss: 0.00461 RPN score loss: 0.00367 RPN total loss: 0.00828 Total loss: 0.99099 timestamp: 1654950089.2990723 iteration: 45825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06439 FastRCNN class loss: 0.0438 FastRCNN total loss: 0.1082 L1 loss: 0.0000e+00 L2 loss: 0.61893 Learning rate: 0.002 Mask loss: 0.13203 RPN box loss: 0.01261 RPN score loss: 0.00142 RPN total loss: 0.01403 Total loss: 0.87319 timestamp: 1654950092.5107062 iteration: 45830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11223 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.195 L1 loss: 0.0000e+00 L2 loss: 0.61892 Learning rate: 0.002 Mask loss: 0.14919 RPN box loss: 0.03746 RPN score loss: 0.00581 RPN total loss: 0.04327 Total loss: 1.00638 timestamp: 1654950095.650646 iteration: 45835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13882 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.20092 L1 loss: 0.0000e+00 L2 loss: 0.61891 Learning rate: 0.002 Mask loss: 0.12287 RPN box loss: 0.03584 RPN score loss: 0.00661 RPN total loss: 0.04246 Total loss: 0.98516 timestamp: 1654950098.890581 iteration: 45840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.15558 L1 loss: 0.0000e+00 L2 loss: 0.6189 Learning rate: 0.002 Mask loss: 0.28936 RPN box loss: 0.03375 RPN score loss: 0.01529 RPN total loss: 0.04904 Total loss: 1.11288 timestamp: 1654950102.0359614 iteration: 45845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09764 FastRCNN class loss: 0.06305 FastRCNN total loss: 0.1607 L1 loss: 0.0000e+00 L2 loss: 0.61889 Learning rate: 0.002 Mask loss: 0.14002 RPN box loss: 0.02174 RPN score loss: 0.00181 RPN total loss: 0.02354 Total loss: 0.94315 timestamp: 1654950105.2416062 iteration: 45850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11663 FastRCNN class loss: 0.10392 FastRCNN total loss: 0.22055 L1 loss: 0.0000e+00 L2 loss: 0.61888 Learning rate: 0.002 Mask loss: 0.17655 RPN box loss: 0.03347 RPN score loss: 0.01282 RPN total loss: 0.0463 Total loss: 1.06229 timestamp: 1654950108.4908316 iteration: 45855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10321 FastRCNN class loss: 0.08002 FastRCNN total loss: 0.18323 L1 loss: 0.0000e+00 L2 loss: 0.61887 Learning rate: 0.002 Mask loss: 0.17345 RPN box loss: 0.01478 RPN score loss: 0.01659 RPN total loss: 0.03137 Total loss: 1.00693 timestamp: 1654950111.7188725 iteration: 45860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08453 FastRCNN class loss: 0.04823 FastRCNN total loss: 0.13275 L1 loss: 0.0000e+00 L2 loss: 0.61886 Learning rate: 0.002 Mask loss: 0.07922 RPN box loss: 0.009 RPN score loss: 0.00146 RPN total loss: 0.01046 Total loss: 0.8413 timestamp: 1654950114.9444964 iteration: 45865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06008 FastRCNN class loss: 0.04785 FastRCNN total loss: 0.10793 L1 loss: 0.0000e+00 L2 loss: 0.61885 Learning rate: 0.002 Mask loss: 0.09688 RPN box loss: 0.01044 RPN score loss: 0.0021 RPN total loss: 0.01255 Total loss: 0.83622 timestamp: 1654950118.121727 iteration: 45870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07785 FastRCNN class loss: 0.10043 FastRCNN total loss: 0.17828 L1 loss: 0.0000e+00 L2 loss: 0.61885 Learning rate: 0.002 Mask loss: 0.08906 RPN box loss: 0.00514 RPN score loss: 0.00405 RPN total loss: 0.00919 Total loss: 0.89537 timestamp: 1654950121.3946233 iteration: 45875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05225 FastRCNN class loss: 0.03936 FastRCNN total loss: 0.09161 L1 loss: 0.0000e+00 L2 loss: 0.61884 Learning rate: 0.002 Mask loss: 0.12888 RPN box loss: 0.01646 RPN score loss: 0.00948 RPN total loss: 0.02594 Total loss: 0.86527 timestamp: 1654950124.661406 iteration: 45880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1065 FastRCNN class loss: 0.05655 FastRCNN total loss: 0.16305 L1 loss: 0.0000e+00 L2 loss: 0.61883 Learning rate: 0.002 Mask loss: 0.11243 RPN box loss: 0.0251 RPN score loss: 0.00331 RPN total loss: 0.0284 Total loss: 0.92271 timestamp: 1654950127.8648403 iteration: 45885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12237 FastRCNN class loss: 0.11089 FastRCNN total loss: 0.23327 L1 loss: 0.0000e+00 L2 loss: 0.61882 Learning rate: 0.002 Mask loss: 0.20049 RPN box loss: 0.00754 RPN score loss: 0.00489 RPN total loss: 0.01243 Total loss: 1.06501 timestamp: 1654950131.029196 iteration: 45890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11334 FastRCNN class loss: 0.10667 FastRCNN total loss: 0.22002 L1 loss: 0.0000e+00 L2 loss: 0.61881 Learning rate: 0.002 Mask loss: 0.11762 RPN box loss: 0.0212 RPN score loss: 0.005 RPN total loss: 0.0262 Total loss: 0.98265 timestamp: 1654950134.1946971 iteration: 45895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14582 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.21399 L1 loss: 0.0000e+00 L2 loss: 0.6188 Learning rate: 0.002 Mask loss: 0.11231 RPN box loss: 0.01228 RPN score loss: 0.00798 RPN total loss: 0.02026 Total loss: 0.96536 timestamp: 1654950137.3871539 iteration: 45900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11165 FastRCNN class loss: 0.06151 FastRCNN total loss: 0.17316 L1 loss: 0.0000e+00 L2 loss: 0.61879 Learning rate: 0.002 Mask loss: 0.1241 RPN box loss: 0.01214 RPN score loss: 0.00402 RPN total loss: 0.01615 Total loss: 0.9322 timestamp: 1654950140.525414 iteration: 45905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10552 FastRCNN class loss: 0.06342 FastRCNN total loss: 0.16894 L1 loss: 0.0000e+00 L2 loss: 0.61878 Learning rate: 0.002 Mask loss: 0.16631 RPN box loss: 0.02534 RPN score loss: 0.00816 RPN total loss: 0.0335 Total loss: 0.98753 timestamp: 1654950143.75016 iteration: 45910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18209 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.26369 L1 loss: 0.0000e+00 L2 loss: 0.61877 Learning rate: 0.002 Mask loss: 0.11749 RPN box loss: 0.01112 RPN score loss: 0.00723 RPN total loss: 0.01835 Total loss: 1.0183 timestamp: 1654950146.9635184 iteration: 45915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13814 FastRCNN class loss: 0.08307 FastRCNN total loss: 0.22122 L1 loss: 0.0000e+00 L2 loss: 0.61876 Learning rate: 0.002 Mask loss: 0.13277 RPN box loss: 0.01135 RPN score loss: 0.00463 RPN total loss: 0.01598 Total loss: 0.98873 timestamp: 1654950150.2506728 iteration: 45920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09733 FastRCNN class loss: 0.07371 FastRCNN total loss: 0.17105 L1 loss: 0.0000e+00 L2 loss: 0.61875 Learning rate: 0.002 Mask loss: 0.15157 RPN box loss: 0.02922 RPN score loss: 0.00465 RPN total loss: 0.03386 Total loss: 0.97523 timestamp: 1654950153.4610186 iteration: 45925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09472 FastRCNN class loss: 0.09642 FastRCNN total loss: 0.19114 L1 loss: 0.0000e+00 L2 loss: 0.61874 Learning rate: 0.002 Mask loss: 0.11835 RPN box loss: 0.02352 RPN score loss: 0.00783 RPN total loss: 0.03135 Total loss: 0.95959 timestamp: 1654950156.6144273 iteration: 45930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12978 FastRCNN class loss: 0.09817 FastRCNN total loss: 0.22795 L1 loss: 0.0000e+00 L2 loss: 0.61874 Learning rate: 0.002 Mask loss: 0.14995 RPN box loss: 0.02012 RPN score loss: 0.00549 RPN total loss: 0.02561 Total loss: 1.02226 timestamp: 1654950159.8051848 iteration: 45935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13354 FastRCNN class loss: 0.05378 FastRCNN total loss: 0.18733 L1 loss: 0.0000e+00 L2 loss: 0.61873 Learning rate: 0.002 Mask loss: 0.10787 RPN box loss: 0.01335 RPN score loss: 0.00875 RPN total loss: 0.0221 Total loss: 0.93603 timestamp: 1654950163.0178492 iteration: 45940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0804 FastRCNN class loss: 0.06667 FastRCNN total loss: 0.14708 L1 loss: 0.0000e+00 L2 loss: 0.61872 Learning rate: 0.002 Mask loss: 0.14925 RPN box loss: 0.00651 RPN score loss: 0.00964 RPN total loss: 0.01616 Total loss: 0.9312 timestamp: 1654950166.1912327 iteration: 45945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14217 FastRCNN class loss: 0.1032 FastRCNN total loss: 0.24537 L1 loss: 0.0000e+00 L2 loss: 0.61871 Learning rate: 0.002 Mask loss: 0.16296 RPN box loss: 0.05375 RPN score loss: 0.01029 RPN total loss: 0.06404 Total loss: 1.09108 timestamp: 1654950169.432299 iteration: 45950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.05544 FastRCNN total loss: 0.1756 L1 loss: 0.0000e+00 L2 loss: 0.6187 Learning rate: 0.002 Mask loss: 0.13433 RPN box loss: 0.01121 RPN score loss: 0.00412 RPN total loss: 0.01533 Total loss: 0.94396 timestamp: 1654950172.6006525 iteration: 45955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1335 FastRCNN class loss: 0.08055 FastRCNN total loss: 0.21405 L1 loss: 0.0000e+00 L2 loss: 0.61869 Learning rate: 0.002 Mask loss: 0.13542 RPN box loss: 0.0192 RPN score loss: 0.00553 RPN total loss: 0.02474 Total loss: 0.9929 timestamp: 1654950175.8567874 iteration: 45960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13115 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.19776 L1 loss: 0.0000e+00 L2 loss: 0.61868 Learning rate: 0.002 Mask loss: 0.14092 RPN box loss: 0.00724 RPN score loss: 0.0026 RPN total loss: 0.00984 Total loss: 0.9672 timestamp: 1654950179.0490773 iteration: 45965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12105 FastRCNN class loss: 0.0894 FastRCNN total loss: 0.21046 L1 loss: 0.0000e+00 L2 loss: 0.61867 Learning rate: 0.002 Mask loss: 0.16673 RPN box loss: 0.01333 RPN score loss: 0.01076 RPN total loss: 0.02409 Total loss: 1.01994 timestamp: 1654950182.2207878 iteration: 45970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0969 FastRCNN class loss: 0.03969 FastRCNN total loss: 0.13659 L1 loss: 0.0000e+00 L2 loss: 0.61866 Learning rate: 0.002 Mask loss: 0.12498 RPN box loss: 0.007 RPN score loss: 0.00146 RPN total loss: 0.00846 Total loss: 0.88869 timestamp: 1654950185.3548841 iteration: 45975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12916 FastRCNN class loss: 0.09208 FastRCNN total loss: 0.22124 L1 loss: 0.0000e+00 L2 loss: 0.61865 Learning rate: 0.002 Mask loss: 0.18193 RPN box loss: 0.01615 RPN score loss: 0.00169 RPN total loss: 0.01784 Total loss: 1.03967 timestamp: 1654950188.5864513 iteration: 45980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09726 FastRCNN class loss: 0.05033 FastRCNN total loss: 0.14759 L1 loss: 0.0000e+00 L2 loss: 0.61865 Learning rate: 0.002 Mask loss: 0.15414 RPN box loss: 0.04268 RPN score loss: 0.00347 RPN total loss: 0.04615 Total loss: 0.96653 timestamp: 1654950191.8277478 iteration: 45985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.102 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.16646 L1 loss: 0.0000e+00 L2 loss: 0.61864 Learning rate: 0.002 Mask loss: 0.18281 RPN box loss: 0.02909 RPN score loss: 0.00278 RPN total loss: 0.03186 Total loss: 0.99977 timestamp: 1654950195.0145073 iteration: 45990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10717 FastRCNN class loss: 0.0853 FastRCNN total loss: 0.19247 L1 loss: 0.0000e+00 L2 loss: 0.61863 Learning rate: 0.002 Mask loss: 0.10976 RPN box loss: 0.04205 RPN score loss: 0.00298 RPN total loss: 0.04503 Total loss: 0.96589 timestamp: 1654950198.145507 iteration: 45995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05442 FastRCNN class loss: 0.02542 FastRCNN total loss: 0.07984 L1 loss: 0.0000e+00 L2 loss: 0.61862 Learning rate: 0.002 Mask loss: 0.09632 RPN box loss: 0.00171 RPN score loss: 0.00191 RPN total loss: 0.00362 Total loss: 0.79841 timestamp: 1654950201.3757713 iteration: 46000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07815 FastRCNN class loss: 0.05317 FastRCNN total loss: 0.13132 L1 loss: 0.0000e+00 L2 loss: 0.61861 Learning rate: 0.002 Mask loss: 0.1511 RPN box loss: 0.01037 RPN score loss: 0.00226 RPN total loss: 0.01264 Total loss: 0.91367 timestamp: 1654950204.5329204 iteration: 46005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08428 FastRCNN class loss: 0.04854 FastRCNN total loss: 0.13281 L1 loss: 0.0000e+00 L2 loss: 0.6186 Learning rate: 0.002 Mask loss: 0.08819 RPN box loss: 0.01189 RPN score loss: 0.0091 RPN total loss: 0.02099 Total loss: 0.86059 timestamp: 1654950207.817659 iteration: 46010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09993 FastRCNN class loss: 0.12266 FastRCNN total loss: 0.22259 L1 loss: 0.0000e+00 L2 loss: 0.61859 Learning rate: 0.002 Mask loss: 0.16412 RPN box loss: 0.01603 RPN score loss: 0.00405 RPN total loss: 0.02008 Total loss: 1.02538 timestamp: 1654950211.0181217 iteration: 46015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11991 FastRCNN class loss: 0.08929 FastRCNN total loss: 0.20919 L1 loss: 0.0000e+00 L2 loss: 0.61858 Learning rate: 0.002 Mask loss: 0.13956 RPN box loss: 0.0074 RPN score loss: 0.0061 RPN total loss: 0.01351 Total loss: 0.98084 timestamp: 1654950214.2242496 iteration: 46020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14477 FastRCNN class loss: 0.07133 FastRCNN total loss: 0.2161 L1 loss: 0.0000e+00 L2 loss: 0.61858 Learning rate: 0.002 Mask loss: 0.16312 RPN box loss: 0.01962 RPN score loss: 0.00455 RPN total loss: 0.02417 Total loss: 1.02197 timestamp: 1654950217.3869512 iteration: 46025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20885 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.284 L1 loss: 0.0000e+00 L2 loss: 0.61857 Learning rate: 0.002 Mask loss: 0.10071 RPN box loss: 0.01582 RPN score loss: 0.00169 RPN total loss: 0.01752 Total loss: 1.0208 timestamp: 1654950220.5303288 iteration: 46030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06347 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.12775 L1 loss: 0.0000e+00 L2 loss: 0.61856 Learning rate: 0.002 Mask loss: 0.21756 RPN box loss: 0.01352 RPN score loss: 0.00365 RPN total loss: 0.01716 Total loss: 0.98104 timestamp: 1654950223.7004466 iteration: 46035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.074 FastRCNN class loss: 0.11186 FastRCNN total loss: 0.18586 L1 loss: 0.0000e+00 L2 loss: 0.61855 Learning rate: 0.002 Mask loss: 0.15245 RPN box loss: 0.01858 RPN score loss: 0.00737 RPN total loss: 0.02596 Total loss: 0.98282 timestamp: 1654950226.837514 iteration: 46040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12722 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.21461 L1 loss: 0.0000e+00 L2 loss: 0.61854 Learning rate: 0.002 Mask loss: 0.17084 RPN box loss: 0.00866 RPN score loss: 0.00421 RPN total loss: 0.01287 Total loss: 1.01687 timestamp: 1654950229.9708025 iteration: 46045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.08089 FastRCNN total loss: 0.19088 L1 loss: 0.0000e+00 L2 loss: 0.61853 Learning rate: 0.002 Mask loss: 0.22722 RPN box loss: 0.019 RPN score loss: 0.00894 RPN total loss: 0.02794 Total loss: 1.06457 timestamp: 1654950233.2165928 iteration: 46050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09391 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.14746 L1 loss: 0.0000e+00 L2 loss: 0.61852 Learning rate: 0.002 Mask loss: 0.17103 RPN box loss: 0.03798 RPN score loss: 0.00548 RPN total loss: 0.04346 Total loss: 0.98047 timestamp: 1654950236.3561614 iteration: 46055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07953 FastRCNN class loss: 0.05247 FastRCNN total loss: 0.132 L1 loss: 0.0000e+00 L2 loss: 0.61851 Learning rate: 0.002 Mask loss: 0.08725 RPN box loss: 0.03561 RPN score loss: 0.0031 RPN total loss: 0.03871 Total loss: 0.87647 timestamp: 1654950239.446589 iteration: 46060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09752 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.17207 L1 loss: 0.0000e+00 L2 loss: 0.6185 Learning rate: 0.002 Mask loss: 0.15084 RPN box loss: 0.02853 RPN score loss: 0.00843 RPN total loss: 0.03696 Total loss: 0.97837 timestamp: 1654950242.6017854 iteration: 46065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09602 FastRCNN class loss: 0.07097 FastRCNN total loss: 0.16699 L1 loss: 0.0000e+00 L2 loss: 0.61849 Learning rate: 0.002 Mask loss: 0.10726 RPN box loss: 0.01487 RPN score loss: 0.00421 RPN total loss: 0.01907 Total loss: 0.91182 timestamp: 1654950245.8058581 iteration: 46070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14508 FastRCNN class loss: 0.11838 FastRCNN total loss: 0.26346 L1 loss: 0.0000e+00 L2 loss: 0.61848 Learning rate: 0.002 Mask loss: 0.14648 RPN box loss: 0.018 RPN score loss: 0.00439 RPN total loss: 0.02239 Total loss: 1.05081 timestamp: 1654950248.9381917 iteration: 46075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12866 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.20542 L1 loss: 0.0000e+00 L2 loss: 0.61847 Learning rate: 0.002 Mask loss: 0.13748 RPN box loss: 0.01319 RPN score loss: 0.00286 RPN total loss: 0.01605 Total loss: 0.97742 timestamp: 1654950252.1038208 iteration: 46080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09368 FastRCNN class loss: 0.04583 FastRCNN total loss: 0.13951 L1 loss: 0.0000e+00 L2 loss: 0.61847 Learning rate: 0.002 Mask loss: 0.10766 RPN box loss: 0.00687 RPN score loss: 0.00226 RPN total loss: 0.00913 Total loss: 0.87477 timestamp: 1654950255.254057 iteration: 46085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07776 FastRCNN class loss: 0.04897 FastRCNN total loss: 0.12672 L1 loss: 0.0000e+00 L2 loss: 0.61846 Learning rate: 0.002 Mask loss: 0.11497 RPN box loss: 0.00978 RPN score loss: 0.00573 RPN total loss: 0.01551 Total loss: 0.87566 timestamp: 1654950258.4156432 iteration: 46090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10177 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.1588 L1 loss: 0.0000e+00 L2 loss: 0.61845 Learning rate: 0.002 Mask loss: 0.13096 RPN box loss: 0.01109 RPN score loss: 0.00187 RPN total loss: 0.01296 Total loss: 0.92117 timestamp: 1654950261.6337166 iteration: 46095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11247 FastRCNN class loss: 0.06889 FastRCNN total loss: 0.18136 L1 loss: 0.0000e+00 L2 loss: 0.61844 Learning rate: 0.002 Mask loss: 0.17738 RPN box loss: 0.01144 RPN score loss: 0.00164 RPN total loss: 0.01308 Total loss: 0.99026 timestamp: 1654950264.8616047 iteration: 46100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07676 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.15198 L1 loss: 0.0000e+00 L2 loss: 0.61843 Learning rate: 0.002 Mask loss: 0.13708 RPN box loss: 0.02033 RPN score loss: 0.00826 RPN total loss: 0.02859 Total loss: 0.93608 timestamp: 1654950267.9917758 iteration: 46105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08224 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.15065 L1 loss: 0.0000e+00 L2 loss: 0.61842 Learning rate: 0.002 Mask loss: 0.15983 RPN box loss: 0.01355 RPN score loss: 0.00147 RPN total loss: 0.01502 Total loss: 0.94392 timestamp: 1654950271.2176695 iteration: 46110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09446 FastRCNN class loss: 0.0387 FastRCNN total loss: 0.13316 L1 loss: 0.0000e+00 L2 loss: 0.61841 Learning rate: 0.002 Mask loss: 0.06582 RPN box loss: 0.0072 RPN score loss: 0.00396 RPN total loss: 0.01116 Total loss: 0.82854 timestamp: 1654950274.428403 iteration: 46115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09303 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.17142 L1 loss: 0.0000e+00 L2 loss: 0.6184 Learning rate: 0.002 Mask loss: 0.13242 RPN box loss: 0.02051 RPN score loss: 0.00496 RPN total loss: 0.02546 Total loss: 0.94771 timestamp: 1654950277.605038 iteration: 46120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14237 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.22826 L1 loss: 0.0000e+00 L2 loss: 0.6184 Learning rate: 0.002 Mask loss: 0.12655 RPN box loss: 0.01487 RPN score loss: 0.00591 RPN total loss: 0.02077 Total loss: 0.99397 timestamp: 1654950280.847684 iteration: 46125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08844 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.16028 L1 loss: 0.0000e+00 L2 loss: 0.61839 Learning rate: 0.002 Mask loss: 0.11916 RPN box loss: 0.00793 RPN score loss: 0.00397 RPN total loss: 0.01189 Total loss: 0.90972 timestamp: 1654950284.005345 iteration: 46130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13825 FastRCNN class loss: 0.0691 FastRCNN total loss: 0.20735 L1 loss: 0.0000e+00 L2 loss: 0.61838 Learning rate: 0.002 Mask loss: 0.14469 RPN box loss: 0.03282 RPN score loss: 0.00419 RPN total loss: 0.03702 Total loss: 1.00743 timestamp: 1654950287.192693 iteration: 46135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06471 FastRCNN class loss: 0.05228 FastRCNN total loss: 0.117 L1 loss: 0.0000e+00 L2 loss: 0.61837 Learning rate: 0.002 Mask loss: 0.1148 RPN box loss: 0.01555 RPN score loss: 0.00302 RPN total loss: 0.01857 Total loss: 0.86873 timestamp: 1654950290.3067496 iteration: 46140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09917 FastRCNN class loss: 0.05451 FastRCNN total loss: 0.15368 L1 loss: 0.0000e+00 L2 loss: 0.61836 Learning rate: 0.002 Mask loss: 0.08932 RPN box loss: 0.01094 RPN score loss: 0.00108 RPN total loss: 0.01202 Total loss: 0.87337 timestamp: 1654950293.5912478 iteration: 46145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15872 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.24038 L1 loss: 0.0000e+00 L2 loss: 0.61834 Learning rate: 0.002 Mask loss: 0.13006 RPN box loss: 0.01078 RPN score loss: 0.00233 RPN total loss: 0.01311 Total loss: 1.0019 timestamp: 1654950296.7902482 iteration: 46150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08788 FastRCNN class loss: 0.05347 FastRCNN total loss: 0.14134 L1 loss: 0.0000e+00 L2 loss: 0.61833 Learning rate: 0.002 Mask loss: 0.10292 RPN box loss: 0.01622 RPN score loss: 0.00234 RPN total loss: 0.01856 Total loss: 0.88115 timestamp: 1654950299.9561265 iteration: 46155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09217 FastRCNN class loss: 0.0934 FastRCNN total loss: 0.18557 L1 loss: 0.0000e+00 L2 loss: 0.61832 Learning rate: 0.002 Mask loss: 0.11232 RPN box loss: 0.0133 RPN score loss: 0.00411 RPN total loss: 0.01741 Total loss: 0.93362 timestamp: 1654950303.1679604 iteration: 46160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11424 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.17055 L1 loss: 0.0000e+00 L2 loss: 0.61831 Learning rate: 0.002 Mask loss: 0.09961 RPN box loss: 0.00403 RPN score loss: 0.00232 RPN total loss: 0.00635 Total loss: 0.89482 timestamp: 1654950306.2780614 iteration: 46165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11521 FastRCNN class loss: 0.06725 FastRCNN total loss: 0.18245 L1 loss: 0.0000e+00 L2 loss: 0.61831 Learning rate: 0.002 Mask loss: 0.15833 RPN box loss: 0.03733 RPN score loss: 0.00891 RPN total loss: 0.04623 Total loss: 1.00532 timestamp: 1654950309.479615 iteration: 46170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15937 FastRCNN class loss: 0.13225 FastRCNN total loss: 0.29162 L1 loss: 0.0000e+00 L2 loss: 0.6183 Learning rate: 0.002 Mask loss: 0.12706 RPN box loss: 0.01326 RPN score loss: 0.00744 RPN total loss: 0.02071 Total loss: 1.05769 timestamp: 1654950312.7091198 iteration: 46175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11397 FastRCNN class loss: 0.08091 FastRCNN total loss: 0.19488 L1 loss: 0.0000e+00 L2 loss: 0.61829 Learning rate: 0.002 Mask loss: 0.1826 RPN box loss: 0.02408 RPN score loss: 0.00796 RPN total loss: 0.03204 Total loss: 1.02781 timestamp: 1654950315.9819229 iteration: 46180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07138 FastRCNN class loss: 0.06026 FastRCNN total loss: 0.13164 L1 loss: 0.0000e+00 L2 loss: 0.61828 Learning rate: 0.002 Mask loss: 0.08645 RPN box loss: 0.00927 RPN score loss: 0.00489 RPN total loss: 0.01416 Total loss: 0.85054 timestamp: 1654950319.200741 iteration: 46185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11802 FastRCNN class loss: 0.11739 FastRCNN total loss: 0.23541 L1 loss: 0.0000e+00 L2 loss: 0.61828 Learning rate: 0.002 Mask loss: 0.18644 RPN box loss: 0.03921 RPN score loss: 0.00586 RPN total loss: 0.04507 Total loss: 1.0852 timestamp: 1654950322.4656265 iteration: 46190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08613 FastRCNN class loss: 0.05804 FastRCNN total loss: 0.14417 L1 loss: 0.0000e+00 L2 loss: 0.61826 Learning rate: 0.002 Mask loss: 0.18096 RPN box loss: 0.02262 RPN score loss: 0.00251 RPN total loss: 0.02513 Total loss: 0.96853 timestamp: 1654950325.6437778 iteration: 46195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08404 FastRCNN class loss: 0.03918 FastRCNN total loss: 0.12322 L1 loss: 0.0000e+00 L2 loss: 0.61825 Learning rate: 0.002 Mask loss: 0.1168 RPN box loss: 0.00906 RPN score loss: 0.00193 RPN total loss: 0.01099 Total loss: 0.86926 timestamp: 1654950328.824336 iteration: 46200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06203 FastRCNN class loss: 0.04291 FastRCNN total loss: 0.10494 L1 loss: 0.0000e+00 L2 loss: 0.61824 Learning rate: 0.002 Mask loss: 0.09745 RPN box loss: 0.009 RPN score loss: 0.00112 RPN total loss: 0.01011 Total loss: 0.83075 timestamp: 1654950332.0139625 iteration: 46205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06193 FastRCNN class loss: 0.04362 FastRCNN total loss: 0.10555 L1 loss: 0.0000e+00 L2 loss: 0.61824 Learning rate: 0.002 Mask loss: 0.10407 RPN box loss: 0.01841 RPN score loss: 0.00582 RPN total loss: 0.02424 Total loss: 0.85209 timestamp: 1654950335.259344 iteration: 46210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07047 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.13219 L1 loss: 0.0000e+00 L2 loss: 0.61823 Learning rate: 0.002 Mask loss: 0.12079 RPN box loss: 0.01425 RPN score loss: 0.00393 RPN total loss: 0.01818 Total loss: 0.8894 timestamp: 1654950338.439341 iteration: 46215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.15935 L1 loss: 0.0000e+00 L2 loss: 0.61822 Learning rate: 0.002 Mask loss: 0.13248 RPN box loss: 0.03276 RPN score loss: 0.00431 RPN total loss: 0.03706 Total loss: 0.94711 timestamp: 1654950341.69769 iteration: 46220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08232 FastRCNN class loss: 0.08021 FastRCNN total loss: 0.16253 L1 loss: 0.0000e+00 L2 loss: 0.61821 Learning rate: 0.002 Mask loss: 0.16941 RPN box loss: 0.01041 RPN score loss: 0.00277 RPN total loss: 0.01317 Total loss: 0.96332 timestamp: 1654950344.8283446 iteration: 46225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08723 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.14452 L1 loss: 0.0000e+00 L2 loss: 0.6182 Learning rate: 0.002 Mask loss: 0.12766 RPN box loss: 0.01065 RPN score loss: 0.00523 RPN total loss: 0.01588 Total loss: 0.90626 timestamp: 1654950348.0668702 iteration: 46230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13026 FastRCNN class loss: 0.0867 FastRCNN total loss: 0.21696 L1 loss: 0.0000e+00 L2 loss: 0.6182 Learning rate: 0.002 Mask loss: 0.13047 RPN box loss: 0.03585 RPN score loss: 0.01066 RPN total loss: 0.04651 Total loss: 1.01214 timestamp: 1654950351.2412024 iteration: 46235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.17539 L1 loss: 0.0000e+00 L2 loss: 0.61819 Learning rate: 0.002 Mask loss: 0.15108 RPN box loss: 0.01436 RPN score loss: 0.00685 RPN total loss: 0.0212 Total loss: 0.96586 timestamp: 1654950354.4187555 iteration: 46240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12125 FastRCNN class loss: 0.09444 FastRCNN total loss: 0.21569 L1 loss: 0.0000e+00 L2 loss: 0.61818 Learning rate: 0.002 Mask loss: 0.1411 RPN box loss: 0.01715 RPN score loss: 0.00919 RPN total loss: 0.02634 Total loss: 1.00131 timestamp: 1654950357.579255 iteration: 46245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14175 FastRCNN class loss: 0.04393 FastRCNN total loss: 0.18569 L1 loss: 0.0000e+00 L2 loss: 0.61817 Learning rate: 0.002 Mask loss: 0.09605 RPN box loss: 0.00597 RPN score loss: 0.00164 RPN total loss: 0.00761 Total loss: 0.90752 timestamp: 1654950360.7685022 iteration: 46250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10225 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.15205 L1 loss: 0.0000e+00 L2 loss: 0.61816 Learning rate: 0.002 Mask loss: 0.13727 RPN box loss: 0.0087 RPN score loss: 0.00352 RPN total loss: 0.01222 Total loss: 0.91971 timestamp: 1654950363.9689977 iteration: 46255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11725 FastRCNN class loss: 0.05457 FastRCNN total loss: 0.17182 L1 loss: 0.0000e+00 L2 loss: 0.61815 Learning rate: 0.002 Mask loss: 0.09905 RPN box loss: 0.00725 RPN score loss: 0.00223 RPN total loss: 0.00948 Total loss: 0.8985 timestamp: 1654950367.1002889 iteration: 46260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11115 FastRCNN class loss: 0.12515 FastRCNN total loss: 0.2363 L1 loss: 0.0000e+00 L2 loss: 0.61814 Learning rate: 0.002 Mask loss: 0.15907 RPN box loss: 0.03172 RPN score loss: 0.00238 RPN total loss: 0.03409 Total loss: 1.04761 timestamp: 1654950370.2455752 iteration: 46265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12619 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.20014 L1 loss: 0.0000e+00 L2 loss: 0.61813 Learning rate: 0.002 Mask loss: 0.13472 RPN box loss: 0.00895 RPN score loss: 0.00729 RPN total loss: 0.01624 Total loss: 0.96922 timestamp: 1654950373.4482048 iteration: 46270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08843 FastRCNN class loss: 0.05217 FastRCNN total loss: 0.14059 L1 loss: 0.0000e+00 L2 loss: 0.61812 Learning rate: 0.002 Mask loss: 0.14151 RPN box loss: 0.03054 RPN score loss: 0.01094 RPN total loss: 0.04148 Total loss: 0.94171 timestamp: 1654950376.6135495 iteration: 46275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10996 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.18171 L1 loss: 0.0000e+00 L2 loss: 0.61811 Learning rate: 0.002 Mask loss: 0.09853 RPN box loss: 0.02351 RPN score loss: 0.00526 RPN total loss: 0.02877 Total loss: 0.92712 timestamp: 1654950379.8189113 iteration: 46280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07974 FastRCNN class loss: 0.04603 FastRCNN total loss: 0.12578 L1 loss: 0.0000e+00 L2 loss: 0.6181 Learning rate: 0.002 Mask loss: 0.1203 RPN box loss: 0.00338 RPN score loss: 0.00174 RPN total loss: 0.00511 Total loss: 0.86929 timestamp: 1654950383.0399861 iteration: 46285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0933 FastRCNN class loss: 0.08128 FastRCNN total loss: 0.17459 L1 loss: 0.0000e+00 L2 loss: 0.61809 Learning rate: 0.002 Mask loss: 0.11551 RPN box loss: 0.01593 RPN score loss: 0.00938 RPN total loss: 0.02532 Total loss: 0.9335 timestamp: 1654950386.2813582 iteration: 46290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06934 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.12473 L1 loss: 0.0000e+00 L2 loss: 0.61809 Learning rate: 0.002 Mask loss: 0.14519 RPN box loss: 0.02983 RPN score loss: 0.00751 RPN total loss: 0.03734 Total loss: 0.92535 timestamp: 1654950389.4732628 iteration: 46295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14758 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.21971 L1 loss: 0.0000e+00 L2 loss: 0.61808 Learning rate: 0.002 Mask loss: 0.1268 RPN box loss: 0.01284 RPN score loss: 0.00525 RPN total loss: 0.01809 Total loss: 0.98268 timestamp: 1654950392.697705 iteration: 46300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10542 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.17132 L1 loss: 0.0000e+00 L2 loss: 0.61807 Learning rate: 0.002 Mask loss: 0.14496 RPN box loss: 0.01662 RPN score loss: 0.00294 RPN total loss: 0.01956 Total loss: 0.9539 timestamp: 1654950395.899572 iteration: 46305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12974 FastRCNN class loss: 0.12285 FastRCNN total loss: 0.25259 L1 loss: 0.0000e+00 L2 loss: 0.61806 Learning rate: 0.002 Mask loss: 0.17167 RPN box loss: 0.02716 RPN score loss: 0.00426 RPN total loss: 0.03142 Total loss: 1.07374 timestamp: 1654950399.104596 iteration: 46310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09809 FastRCNN class loss: 0.08523 FastRCNN total loss: 0.18333 L1 loss: 0.0000e+00 L2 loss: 0.61804 Learning rate: 0.002 Mask loss: 0.20799 RPN box loss: 0.02496 RPN score loss: 0.00601 RPN total loss: 0.03097 Total loss: 1.04033 timestamp: 1654950402.2761798 iteration: 46315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08493 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.14536 L1 loss: 0.0000e+00 L2 loss: 0.61804 Learning rate: 0.002 Mask loss: 0.11562 RPN box loss: 0.00879 RPN score loss: 0.00444 RPN total loss: 0.01323 Total loss: 0.89225 timestamp: 1654950405.575745 iteration: 46320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08762 FastRCNN class loss: 0.10696 FastRCNN total loss: 0.19458 L1 loss: 0.0000e+00 L2 loss: 0.61803 Learning rate: 0.002 Mask loss: 0.12595 RPN box loss: 0.02647 RPN score loss: 0.00584 RPN total loss: 0.03231 Total loss: 0.97087 timestamp: 1654950408.7833838 iteration: 46325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07285 FastRCNN class loss: 0.05224 FastRCNN total loss: 0.12509 L1 loss: 0.0000e+00 L2 loss: 0.61802 Learning rate: 0.002 Mask loss: 0.10902 RPN box loss: 0.00968 RPN score loss: 0.00412 RPN total loss: 0.0138 Total loss: 0.86594 timestamp: 1654950412.0335581 iteration: 46330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16872 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.23792 L1 loss: 0.0000e+00 L2 loss: 0.61801 Learning rate: 0.002 Mask loss: 0.13949 RPN box loss: 0.0412 RPN score loss: 0.00538 RPN total loss: 0.04658 Total loss: 1.042 timestamp: 1654950415.2765167 iteration: 46335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08186 FastRCNN class loss: 0.06622 FastRCNN total loss: 0.14808 L1 loss: 0.0000e+00 L2 loss: 0.618 Learning rate: 0.002 Mask loss: 0.14681 RPN box loss: 0.049 RPN score loss: 0.00782 RPN total loss: 0.05682 Total loss: 0.96971 timestamp: 1654950418.5448794 iteration: 46340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04412 FastRCNN class loss: 0.04752 FastRCNN total loss: 0.09164 L1 loss: 0.0000e+00 L2 loss: 0.61799 Learning rate: 0.002 Mask loss: 0.10499 RPN box loss: 0.00583 RPN score loss: 0.00278 RPN total loss: 0.00861 Total loss: 0.82323 timestamp: 1654950421.7622716 iteration: 46345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09986 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.17986 L1 loss: 0.0000e+00 L2 loss: 0.61799 Learning rate: 0.002 Mask loss: 0.15716 RPN box loss: 0.0226 RPN score loss: 0.00274 RPN total loss: 0.02534 Total loss: 0.98034 timestamp: 1654950424.995407 iteration: 46350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1064 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.192 L1 loss: 0.0000e+00 L2 loss: 0.61798 Learning rate: 0.002 Mask loss: 0.10561 RPN box loss: 0.03968 RPN score loss: 0.00556 RPN total loss: 0.04525 Total loss: 0.96083 timestamp: 1654950428.2964897 iteration: 46355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12444 FastRCNN class loss: 0.11928 FastRCNN total loss: 0.24372 L1 loss: 0.0000e+00 L2 loss: 0.61796 Learning rate: 0.002 Mask loss: 0.13824 RPN box loss: 0.03429 RPN score loss: 0.0136 RPN total loss: 0.04789 Total loss: 1.04782 timestamp: 1654950431.4901156 iteration: 46360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20586 FastRCNN class loss: 0.06592 FastRCNN total loss: 0.27178 L1 loss: 0.0000e+00 L2 loss: 0.61795 Learning rate: 0.002 Mask loss: 0.12134 RPN box loss: 0.00726 RPN score loss: 0.00238 RPN total loss: 0.00964 Total loss: 1.02071 timestamp: 1654950434.7856028 iteration: 46365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0936 FastRCNN class loss: 0.05904 FastRCNN total loss: 0.15265 L1 loss: 0.0000e+00 L2 loss: 0.61794 Learning rate: 0.002 Mask loss: 0.13406 RPN box loss: 0.02429 RPN score loss: 0.0062 RPN total loss: 0.03049 Total loss: 0.93513 timestamp: 1654950437.950804 iteration: 46370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07858 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.14915 L1 loss: 0.0000e+00 L2 loss: 0.61794 Learning rate: 0.002 Mask loss: 0.13087 RPN box loss: 0.00586 RPN score loss: 0.00304 RPN total loss: 0.0089 Total loss: 0.90685 timestamp: 1654950441.0805993 iteration: 46375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.05786 FastRCNN total loss: 0.13366 L1 loss: 0.0000e+00 L2 loss: 0.61793 Learning rate: 0.002 Mask loss: 0.09237 RPN box loss: 0.00529 RPN score loss: 0.00163 RPN total loss: 0.00692 Total loss: 0.85089 timestamp: 1654950444.3280764 iteration: 46380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1201 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.18081 L1 loss: 0.0000e+00 L2 loss: 0.61792 Learning rate: 0.002 Mask loss: 0.10901 RPN box loss: 0.02109 RPN score loss: 0.00218 RPN total loss: 0.02326 Total loss: 0.93101 timestamp: 1654950447.5993538 iteration: 46385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08813 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.14752 L1 loss: 0.0000e+00 L2 loss: 0.61791 Learning rate: 0.002 Mask loss: 0.15842 RPN box loss: 0.00825 RPN score loss: 0.00461 RPN total loss: 0.01286 Total loss: 0.93671 timestamp: 1654950450.7847617 iteration: 46390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0673 FastRCNN class loss: 0.04834 FastRCNN total loss: 0.11564 L1 loss: 0.0000e+00 L2 loss: 0.6179 Learning rate: 0.002 Mask loss: 0.15088 RPN box loss: 0.00764 RPN score loss: 0.00144 RPN total loss: 0.00909 Total loss: 0.89351 timestamp: 1654950454.0141103 iteration: 46395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.09177 FastRCNN total loss: 0.19329 L1 loss: 0.0000e+00 L2 loss: 0.61789 Learning rate: 0.002 Mask loss: 0.14407 RPN box loss: 0.00863 RPN score loss: 0.01489 RPN total loss: 0.02352 Total loss: 0.97878 timestamp: 1654950457.1903458 iteration: 46400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09234 FastRCNN class loss: 0.05942 FastRCNN total loss: 0.15176 L1 loss: 0.0000e+00 L2 loss: 0.61788 Learning rate: 0.002 Mask loss: 0.13163 RPN box loss: 0.0107 RPN score loss: 0.00237 RPN total loss: 0.01307 Total loss: 0.91433 timestamp: 1654950460.4470744 iteration: 46405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.16929 L1 loss: 0.0000e+00 L2 loss: 0.61787 Learning rate: 0.002 Mask loss: 0.1493 RPN box loss: 0.01894 RPN score loss: 0.01126 RPN total loss: 0.03021 Total loss: 0.96667 timestamp: 1654950463.6451046 iteration: 46410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0765 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.14363 L1 loss: 0.0000e+00 L2 loss: 0.61787 Learning rate: 0.002 Mask loss: 0.11953 RPN box loss: 0.02119 RPN score loss: 0.00581 RPN total loss: 0.027 Total loss: 0.90803 timestamp: 1654950466.8596013 iteration: 46415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10751 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.1943 L1 loss: 0.0000e+00 L2 loss: 0.61786 Learning rate: 0.002 Mask loss: 0.17971 RPN box loss: 0.01921 RPN score loss: 0.00744 RPN total loss: 0.02666 Total loss: 1.01852 timestamp: 1654950470.0278387 iteration: 46420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09603 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.61785 Learning rate: 0.002 Mask loss: 0.13516 RPN box loss: 0.01991 RPN score loss: 0.00464 RPN total loss: 0.02455 Total loss: 0.93833 timestamp: 1654950473.2284184 iteration: 46425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13883 FastRCNN class loss: 0.09185 FastRCNN total loss: 0.23068 L1 loss: 0.0000e+00 L2 loss: 0.61784 Learning rate: 0.002 Mask loss: 0.18827 RPN box loss: 0.01374 RPN score loss: 0.00321 RPN total loss: 0.01695 Total loss: 1.05374 timestamp: 1654950476.3888817 iteration: 46430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12222 FastRCNN class loss: 0.08606 FastRCNN total loss: 0.20828 L1 loss: 0.0000e+00 L2 loss: 0.61783 Learning rate: 0.002 Mask loss: 0.12529 RPN box loss: 0.00898 RPN score loss: 0.0073 RPN total loss: 0.01628 Total loss: 0.96769 timestamp: 1654950479.6008766 iteration: 46435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08047 FastRCNN class loss: 0.07304 FastRCNN total loss: 0.1535 L1 loss: 0.0000e+00 L2 loss: 0.61782 Learning rate: 0.002 Mask loss: 0.15991 RPN box loss: 0.00946 RPN score loss: 0.00754 RPN total loss: 0.01699 Total loss: 0.94823 timestamp: 1654950482.8621545 iteration: 46440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06764 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.1401 L1 loss: 0.0000e+00 L2 loss: 0.61781 Learning rate: 0.002 Mask loss: 0.12577 RPN box loss: 0.01004 RPN score loss: 0.00399 RPN total loss: 0.01403 Total loss: 0.89772 timestamp: 1654950486.0464416 iteration: 46445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10958 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.17527 L1 loss: 0.0000e+00 L2 loss: 0.6178 Learning rate: 0.002 Mask loss: 0.13416 RPN box loss: 0.0138 RPN score loss: 0.00165 RPN total loss: 0.01545 Total loss: 0.94267 timestamp: 1654950489.1876855 iteration: 46450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.09381 FastRCNN total loss: 0.19312 L1 loss: 0.0000e+00 L2 loss: 0.6178 Learning rate: 0.002 Mask loss: 0.15654 RPN box loss: 0.01216 RPN score loss: 0.00566 RPN total loss: 0.01782 Total loss: 0.98527 timestamp: 1654950492.4108112 iteration: 46455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09661 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.16869 L1 loss: 0.0000e+00 L2 loss: 0.61779 Learning rate: 0.002 Mask loss: 0.14249 RPN box loss: 0.00816 RPN score loss: 0.00769 RPN total loss: 0.01585 Total loss: 0.94481 timestamp: 1654950495.6024473 iteration: 46460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14975 FastRCNN class loss: 0.08181 FastRCNN total loss: 0.23156 L1 loss: 0.0000e+00 L2 loss: 0.61777 Learning rate: 0.002 Mask loss: 0.12596 RPN box loss: 0.01893 RPN score loss: 0.00153 RPN total loss: 0.02047 Total loss: 0.99576 timestamp: 1654950498.8007972 iteration: 46465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13847 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.21075 L1 loss: 0.0000e+00 L2 loss: 0.61776 Learning rate: 0.002 Mask loss: 0.14718 RPN box loss: 0.01726 RPN score loss: 0.00197 RPN total loss: 0.01922 Total loss: 0.99491 timestamp: 1654950501.9611301 iteration: 46470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11286 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.18813 L1 loss: 0.0000e+00 L2 loss: 0.61775 Learning rate: 0.002 Mask loss: 0.16751 RPN box loss: 0.00737 RPN score loss: 0.00375 RPN total loss: 0.01112 Total loss: 0.98451 timestamp: 1654950505.1935284 iteration: 46475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05173 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.10222 L1 loss: 0.0000e+00 L2 loss: 0.61774 Learning rate: 0.002 Mask loss: 0.10641 RPN box loss: 0.02363 RPN score loss: 0.00432 RPN total loss: 0.02795 Total loss: 0.85432 timestamp: 1654950508.331545 iteration: 46480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11228 FastRCNN class loss: 0.06913 FastRCNN total loss: 0.18141 L1 loss: 0.0000e+00 L2 loss: 0.61773 Learning rate: 0.002 Mask loss: 0.09154 RPN box loss: 0.00536 RPN score loss: 0.00126 RPN total loss: 0.00662 Total loss: 0.89729 timestamp: 1654950511.5330472 iteration: 46485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09149 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.1465 L1 loss: 0.0000e+00 L2 loss: 0.61772 Learning rate: 0.002 Mask loss: 0.12906 RPN box loss: 0.01367 RPN score loss: 0.00397 RPN total loss: 0.01764 Total loss: 0.91092 timestamp: 1654950514.74018 iteration: 46490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12947 FastRCNN class loss: 0.08178 FastRCNN total loss: 0.21125 L1 loss: 0.0000e+00 L2 loss: 0.61771 Learning rate: 0.002 Mask loss: 0.16143 RPN box loss: 0.03538 RPN score loss: 0.01316 RPN total loss: 0.04854 Total loss: 1.03894 timestamp: 1654950517.9387505 iteration: 46495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13536 FastRCNN class loss: 0.06567 FastRCNN total loss: 0.20103 L1 loss: 0.0000e+00 L2 loss: 0.6177 Learning rate: 0.002 Mask loss: 0.14058 RPN box loss: 0.0117 RPN score loss: 0.0037 RPN total loss: 0.0154 Total loss: 0.97472 timestamp: 1654950521.1441386 iteration: 46500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09492 FastRCNN class loss: 0.05255 FastRCNN total loss: 0.14747 L1 loss: 0.0000e+00 L2 loss: 0.61769 Learning rate: 0.002 Mask loss: 0.1305 RPN box loss: 0.0084 RPN score loss: 0.00906 RPN total loss: 0.01746 Total loss: 0.91312 timestamp: 1654950524.3407075 iteration: 46505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07346 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.12776 L1 loss: 0.0000e+00 L2 loss: 0.61768 Learning rate: 0.002 Mask loss: 0.15976 RPN box loss: 0.03171 RPN score loss: 0.00479 RPN total loss: 0.0365 Total loss: 0.94169 timestamp: 1654950527.5546155 iteration: 46510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12981 FastRCNN class loss: 0.07781 FastRCNN total loss: 0.20763 L1 loss: 0.0000e+00 L2 loss: 0.61767 Learning rate: 0.002 Mask loss: 0.11381 RPN box loss: 0.01671 RPN score loss: 0.00985 RPN total loss: 0.02656 Total loss: 0.96567 timestamp: 1654950530.7739904 iteration: 46515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13843 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.2085 L1 loss: 0.0000e+00 L2 loss: 0.61766 Learning rate: 0.002 Mask loss: 0.14607 RPN box loss: 0.00476 RPN score loss: 0.00419 RPN total loss: 0.00895 Total loss: 0.98118 timestamp: 1654950533.962539 iteration: 46520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08289 FastRCNN class loss: 0.05307 FastRCNN total loss: 0.13596 L1 loss: 0.0000e+00 L2 loss: 0.61765 Learning rate: 0.002 Mask loss: 0.12339 RPN box loss: 0.00622 RPN score loss: 0.00152 RPN total loss: 0.00774 Total loss: 0.88475 timestamp: 1654950537.184858 iteration: 46525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.15991 L1 loss: 0.0000e+00 L2 loss: 0.61765 Learning rate: 0.002 Mask loss: 0.1492 RPN box loss: 0.01719 RPN score loss: 0.00159 RPN total loss: 0.01878 Total loss: 0.94553 timestamp: 1654950540.4193037 iteration: 46530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1004 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.17431 L1 loss: 0.0000e+00 L2 loss: 0.61764 Learning rate: 0.002 Mask loss: 0.10496 RPN box loss: 0.01325 RPN score loss: 0.00656 RPN total loss: 0.01981 Total loss: 0.91672 timestamp: 1654950543.5944471 iteration: 46535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07886 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.17275 L1 loss: 0.0000e+00 L2 loss: 0.61763 Learning rate: 0.002 Mask loss: 0.1945 RPN box loss: 0.01124 RPN score loss: 0.00738 RPN total loss: 0.01862 Total loss: 1.00349 timestamp: 1654950546.8005672 iteration: 46540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13811 FastRCNN class loss: 0.08234 FastRCNN total loss: 0.22045 L1 loss: 0.0000e+00 L2 loss: 0.61762 Learning rate: 0.002 Mask loss: 0.15947 RPN box loss: 0.01477 RPN score loss: 0.00768 RPN total loss: 0.02245 Total loss: 1.02 timestamp: 1654950549.977701 iteration: 46545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13576 FastRCNN class loss: 0.13428 FastRCNN total loss: 0.27004 L1 loss: 0.0000e+00 L2 loss: 0.61761 Learning rate: 0.002 Mask loss: 0.20143 RPN box loss: 0.0304 RPN score loss: 0.02715 RPN total loss: 0.05756 Total loss: 1.14664 timestamp: 1654950553.2167754 iteration: 46550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05605 FastRCNN class loss: 0.0361 FastRCNN total loss: 0.09216 L1 loss: 0.0000e+00 L2 loss: 0.6176 Learning rate: 0.002 Mask loss: 0.10424 RPN box loss: 0.01605 RPN score loss: 0.00566 RPN total loss: 0.0217 Total loss: 0.8357 timestamp: 1654950556.3794992 iteration: 46555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06931 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.11743 L1 loss: 0.0000e+00 L2 loss: 0.61759 Learning rate: 0.002 Mask loss: 0.12403 RPN box loss: 0.00353 RPN score loss: 0.0026 RPN total loss: 0.00613 Total loss: 0.86519 timestamp: 1654950559.5790353 iteration: 46560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08266 FastRCNN class loss: 0.05313 FastRCNN total loss: 0.13579 L1 loss: 0.0000e+00 L2 loss: 0.61758 Learning rate: 0.002 Mask loss: 0.14102 RPN box loss: 0.00651 RPN score loss: 0.00383 RPN total loss: 0.01034 Total loss: 0.90473 timestamp: 1654950562.6993368 iteration: 46565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04614 FastRCNN class loss: 0.04458 FastRCNN total loss: 0.09072 L1 loss: 0.0000e+00 L2 loss: 0.61757 Learning rate: 0.002 Mask loss: 0.12329 RPN box loss: 0.01431 RPN score loss: 0.00226 RPN total loss: 0.01657 Total loss: 0.84815 timestamp: 1654950565.853136 iteration: 46570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0589 FastRCNN class loss: 0.04659 FastRCNN total loss: 0.10549 L1 loss: 0.0000e+00 L2 loss: 0.61756 Learning rate: 0.002 Mask loss: 0.08998 RPN box loss: 0.00832 RPN score loss: 0.00126 RPN total loss: 0.00959 Total loss: 0.82263 timestamp: 1654950569.0717554 iteration: 46575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0585 FastRCNN class loss: 0.03659 FastRCNN total loss: 0.09508 L1 loss: 0.0000e+00 L2 loss: 0.61755 Learning rate: 0.002 Mask loss: 0.11087 RPN box loss: 0.00863 RPN score loss: 0.00304 RPN total loss: 0.01168 Total loss: 0.83518 timestamp: 1654950572.267036 iteration: 46580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08602 FastRCNN class loss: 0.04367 FastRCNN total loss: 0.1297 L1 loss: 0.0000e+00 L2 loss: 0.61755 Learning rate: 0.002 Mask loss: 0.10504 RPN box loss: 0.00495 RPN score loss: 0.00274 RPN total loss: 0.00769 Total loss: 0.85997 timestamp: 1654950575.4112618 iteration: 46585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08659 FastRCNN class loss: 0.09484 FastRCNN total loss: 0.18143 L1 loss: 0.0000e+00 L2 loss: 0.61754 Learning rate: 0.002 Mask loss: 0.12659 RPN box loss: 0.01361 RPN score loss: 0.0097 RPN total loss: 0.02331 Total loss: 0.94886 timestamp: 1654950578.5879557 iteration: 46590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08405 FastRCNN class loss: 0.05266 FastRCNN total loss: 0.13671 L1 loss: 0.0000e+00 L2 loss: 0.61753 Learning rate: 0.002 Mask loss: 0.14736 RPN box loss: 0.01685 RPN score loss: 0.0014 RPN total loss: 0.01824 Total loss: 0.91985 timestamp: 1654950581.832712 iteration: 46595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12272 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.2002 L1 loss: 0.0000e+00 L2 loss: 0.61752 Learning rate: 0.002 Mask loss: 0.13614 RPN box loss: 0.02001 RPN score loss: 0.00611 RPN total loss: 0.02612 Total loss: 0.97998 timestamp: 1654950585.025746 iteration: 46600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11637 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.21371 L1 loss: 0.0000e+00 L2 loss: 0.61751 Learning rate: 0.002 Mask loss: 0.14172 RPN box loss: 0.03068 RPN score loss: 0.01075 RPN total loss: 0.04143 Total loss: 1.01437 timestamp: 1654950588.205203 iteration: 46605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0528 FastRCNN class loss: 0.05199 FastRCNN total loss: 0.10478 L1 loss: 0.0000e+00 L2 loss: 0.61751 Learning rate: 0.002 Mask loss: 0.09333 RPN box loss: 0.0067 RPN score loss: 0.0018 RPN total loss: 0.0085 Total loss: 0.82411 timestamp: 1654950591.3810277 iteration: 46610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15876 FastRCNN class loss: 0.08379 FastRCNN total loss: 0.24255 L1 loss: 0.0000e+00 L2 loss: 0.6175 Learning rate: 0.002 Mask loss: 0.11875 RPN box loss: 0.04015 RPN score loss: 0.00517 RPN total loss: 0.04532 Total loss: 1.02412 timestamp: 1654950594.6296635 iteration: 46615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.10963 FastRCNN total loss: 0.19634 L1 loss: 0.0000e+00 L2 loss: 0.61749 Learning rate: 0.002 Mask loss: 0.17386 RPN box loss: 0.01971 RPN score loss: 0.00909 RPN total loss: 0.0288 Total loss: 1.01648 timestamp: 1654950597.8658495 iteration: 46620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10353 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.17078 L1 loss: 0.0000e+00 L2 loss: 0.61748 Learning rate: 0.002 Mask loss: 0.09754 RPN box loss: 0.06528 RPN score loss: 0.00438 RPN total loss: 0.06965 Total loss: 0.95545 timestamp: 1654950601.0706651 iteration: 46625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0908 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.16561 L1 loss: 0.0000e+00 L2 loss: 0.61747 Learning rate: 0.002 Mask loss: 0.16955 RPN box loss: 0.03579 RPN score loss: 0.00731 RPN total loss: 0.0431 Total loss: 0.99573 timestamp: 1654950604.3048463 iteration: 46630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.04595 FastRCNN total loss: 0.11618 L1 loss: 0.0000e+00 L2 loss: 0.61746 Learning rate: 0.002 Mask loss: 0.16858 RPN box loss: 0.00925 RPN score loss: 0.00176 RPN total loss: 0.01101 Total loss: 0.91323 timestamp: 1654950607.5194051 iteration: 46635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09092 FastRCNN class loss: 0.05483 FastRCNN total loss: 0.14576 L1 loss: 0.0000e+00 L2 loss: 0.61745 Learning rate: 0.002 Mask loss: 0.093 RPN box loss: 0.02371 RPN score loss: 0.00919 RPN total loss: 0.0329 Total loss: 0.88911 timestamp: 1654950610.770372 iteration: 46640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11843 FastRCNN class loss: 0.09441 FastRCNN total loss: 0.21284 L1 loss: 0.0000e+00 L2 loss: 0.61744 Learning rate: 0.002 Mask loss: 0.17045 RPN box loss: 0.02448 RPN score loss: 0.01297 RPN total loss: 0.03745 Total loss: 1.03819 timestamp: 1654950613.9807599 iteration: 46645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10997 FastRCNN class loss: 0.09132 FastRCNN total loss: 0.2013 L1 loss: 0.0000e+00 L2 loss: 0.61743 Learning rate: 0.002 Mask loss: 0.14469 RPN box loss: 0.01713 RPN score loss: 0.01143 RPN total loss: 0.02856 Total loss: 0.99198 timestamp: 1654950617.1487641 iteration: 46650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17534 FastRCNN class loss: 0.0834 FastRCNN total loss: 0.25874 L1 loss: 0.0000e+00 L2 loss: 0.61742 Learning rate: 0.002 Mask loss: 0.12339 RPN box loss: 0.02671 RPN score loss: 0.01247 RPN total loss: 0.03918 Total loss: 1.03872 timestamp: 1654950620.4014428 iteration: 46655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11973 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.19256 L1 loss: 0.0000e+00 L2 loss: 0.61741 Learning rate: 0.002 Mask loss: 0.0992 RPN box loss: 0.01133 RPN score loss: 0.00754 RPN total loss: 0.01888 Total loss: 0.92805 timestamp: 1654950623.5757635 iteration: 46660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07513 FastRCNN class loss: 0.04903 FastRCNN total loss: 0.12415 L1 loss: 0.0000e+00 L2 loss: 0.6174 Learning rate: 0.002 Mask loss: 0.10879 RPN box loss: 0.03733 RPN score loss: 0.00233 RPN total loss: 0.03967 Total loss: 0.89001 timestamp: 1654950626.8130558 iteration: 46665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08282 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.15211 L1 loss: 0.0000e+00 L2 loss: 0.61739 Learning rate: 0.002 Mask loss: 0.13487 RPN box loss: 0.00549 RPN score loss: 0.00096 RPN total loss: 0.00645 Total loss: 0.91082 timestamp: 1654950630.0443082 iteration: 46670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12523 FastRCNN class loss: 0.08829 FastRCNN total loss: 0.21353 L1 loss: 0.0000e+00 L2 loss: 0.61738 Learning rate: 0.002 Mask loss: 0.13512 RPN box loss: 0.0173 RPN score loss: 0.00171 RPN total loss: 0.01901 Total loss: 0.98504 timestamp: 1654950633.212094 iteration: 46675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13872 FastRCNN class loss: 0.09428 FastRCNN total loss: 0.233 L1 loss: 0.0000e+00 L2 loss: 0.61737 Learning rate: 0.002 Mask loss: 0.14596 RPN box loss: 0.00697 RPN score loss: 0.00089 RPN total loss: 0.00786 Total loss: 1.0042 timestamp: 1654950636.3419628 iteration: 46680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08577 FastRCNN class loss: 0.04239 FastRCNN total loss: 0.12817 L1 loss: 0.0000e+00 L2 loss: 0.61736 Learning rate: 0.002 Mask loss: 0.12818 RPN box loss: 0.01256 RPN score loss: 0.00449 RPN total loss: 0.01705 Total loss: 0.89076 timestamp: 1654950639.5290537 iteration: 46685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08333 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.15088 L1 loss: 0.0000e+00 L2 loss: 0.61736 Learning rate: 0.002 Mask loss: 0.15914 RPN box loss: 0.0215 RPN score loss: 0.0096 RPN total loss: 0.0311 Total loss: 0.95847 timestamp: 1654950642.650503 iteration: 46690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15796 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.23897 L1 loss: 0.0000e+00 L2 loss: 0.61735 Learning rate: 0.002 Mask loss: 0.1025 RPN box loss: 0.01634 RPN score loss: 0.00707 RPN total loss: 0.02341 Total loss: 0.98223 timestamp: 1654950645.8372748 iteration: 46695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1284 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.21456 L1 loss: 0.0000e+00 L2 loss: 0.61734 Learning rate: 0.002 Mask loss: 0.2284 RPN box loss: 0.02031 RPN score loss: 0.00809 RPN total loss: 0.0284 Total loss: 1.0887 timestamp: 1654950649.0776951 iteration: 46700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05687 FastRCNN class loss: 0.06699 FastRCNN total loss: 0.12386 L1 loss: 0.0000e+00 L2 loss: 0.61733 Learning rate: 0.002 Mask loss: 0.16603 RPN box loss: 0.01516 RPN score loss: 0.00434 RPN total loss: 0.0195 Total loss: 0.92672 timestamp: 1654950652.2982035 iteration: 46705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10875 FastRCNN class loss: 0.08265 FastRCNN total loss: 0.1914 L1 loss: 0.0000e+00 L2 loss: 0.61732 Learning rate: 0.002 Mask loss: 0.10066 RPN box loss: 0.00779 RPN score loss: 0.0045 RPN total loss: 0.01229 Total loss: 0.92167 timestamp: 1654950655.541439 iteration: 46710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1128 FastRCNN class loss: 0.08382 FastRCNN total loss: 0.19662 L1 loss: 0.0000e+00 L2 loss: 0.61731 Learning rate: 0.002 Mask loss: 0.16982 RPN box loss: 0.03867 RPN score loss: 0.00578 RPN total loss: 0.04445 Total loss: 1.0282 timestamp: 1654950658.7573884 iteration: 46715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05422 FastRCNN class loss: 0.0738 FastRCNN total loss: 0.12802 L1 loss: 0.0000e+00 L2 loss: 0.61731 Learning rate: 0.002 Mask loss: 0.15962 RPN box loss: 0.0132 RPN score loss: 0.00617 RPN total loss: 0.01937 Total loss: 0.92432 timestamp: 1654950661.9502566 iteration: 46720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06953 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.14161 L1 loss: 0.0000e+00 L2 loss: 0.6173 Learning rate: 0.002 Mask loss: 0.11818 RPN box loss: 0.05507 RPN score loss: 0.00265 RPN total loss: 0.05773 Total loss: 0.93481 timestamp: 1654950665.1468663 iteration: 46725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10478 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.19351 L1 loss: 0.0000e+00 L2 loss: 0.61729 Learning rate: 0.002 Mask loss: 0.13253 RPN box loss: 0.01139 RPN score loss: 0.00683 RPN total loss: 0.01822 Total loss: 0.96154 timestamp: 1654950668.3447328 iteration: 46730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14439 FastRCNN class loss: 0.09472 FastRCNN total loss: 0.23911 L1 loss: 0.0000e+00 L2 loss: 0.61728 Learning rate: 0.002 Mask loss: 0.21502 RPN box loss: 0.02039 RPN score loss: 0.01205 RPN total loss: 0.03244 Total loss: 1.10384 timestamp: 1654950671.5256302 iteration: 46735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06135 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.12939 L1 loss: 0.0000e+00 L2 loss: 0.61726 Learning rate: 0.002 Mask loss: 0.07483 RPN box loss: 0.02165 RPN score loss: 0.00463 RPN total loss: 0.02628 Total loss: 0.84777 timestamp: 1654950674.769522 iteration: 46740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08455 FastRCNN class loss: 0.08638 FastRCNN total loss: 0.17093 L1 loss: 0.0000e+00 L2 loss: 0.61726 Learning rate: 0.002 Mask loss: 0.19508 RPN box loss: 0.02621 RPN score loss: 0.00473 RPN total loss: 0.03095 Total loss: 1.01421 timestamp: 1654950678.0133467 iteration: 46745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08411 FastRCNN class loss: 0.04022 FastRCNN total loss: 0.12433 L1 loss: 0.0000e+00 L2 loss: 0.61725 Learning rate: 0.002 Mask loss: 0.08245 RPN box loss: 0.02644 RPN score loss: 0.00453 RPN total loss: 0.03097 Total loss: 0.85499 timestamp: 1654950681.2205582 iteration: 46750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13466 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.23051 L1 loss: 0.0000e+00 L2 loss: 0.61724 Learning rate: 0.002 Mask loss: 0.1298 RPN box loss: 0.00686 RPN score loss: 0.00316 RPN total loss: 0.01002 Total loss: 0.98757 timestamp: 1654950684.3495417 iteration: 46755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10417 FastRCNN class loss: 0.09227 FastRCNN total loss: 0.19644 L1 loss: 0.0000e+00 L2 loss: 0.61723 Learning rate: 0.002 Mask loss: 0.13242 RPN box loss: 0.00583 RPN score loss: 0.00474 RPN total loss: 0.01057 Total loss: 0.95665 timestamp: 1654950687.5426795 iteration: 46760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.03358 FastRCNN total loss: 0.12772 L1 loss: 0.0000e+00 L2 loss: 0.61722 Learning rate: 0.002 Mask loss: 0.09367 RPN box loss: 0.03371 RPN score loss: 0.00076 RPN total loss: 0.03447 Total loss: 0.87309 timestamp: 1654950690.7098696 iteration: 46765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0939 FastRCNN class loss: 0.06371 FastRCNN total loss: 0.15761 L1 loss: 0.0000e+00 L2 loss: 0.61721 Learning rate: 0.002 Mask loss: 0.13044 RPN box loss: 0.02252 RPN score loss: 0.007 RPN total loss: 0.02952 Total loss: 0.93479 timestamp: 1654950693.919004 iteration: 46770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09974 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.17725 L1 loss: 0.0000e+00 L2 loss: 0.6172 Learning rate: 0.002 Mask loss: 0.14255 RPN box loss: 0.02536 RPN score loss: 0.01071 RPN total loss: 0.03606 Total loss: 0.97307 timestamp: 1654950697.1242747 iteration: 46775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0618 FastRCNN class loss: 0.09013 FastRCNN total loss: 0.15193 L1 loss: 0.0000e+00 L2 loss: 0.61719 Learning rate: 0.002 Mask loss: 0.15382 RPN box loss: 0.02242 RPN score loss: 0.00338 RPN total loss: 0.02581 Total loss: 0.94875 timestamp: 1654950700.3554523 iteration: 46780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0317 FastRCNN class loss: 0.03205 FastRCNN total loss: 0.06375 L1 loss: 0.0000e+00 L2 loss: 0.61718 Learning rate: 0.002 Mask loss: 0.23869 RPN box loss: 0.00652 RPN score loss: 0.0033 RPN total loss: 0.00981 Total loss: 0.92943 timestamp: 1654950703.5927563 iteration: 46785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05062 FastRCNN class loss: 0.08017 FastRCNN total loss: 0.13079 L1 loss: 0.0000e+00 L2 loss: 0.61718 Learning rate: 0.002 Mask loss: 0.08592 RPN box loss: 0.01304 RPN score loss: 0.00461 RPN total loss: 0.01765 Total loss: 0.85153 timestamp: 1654950706.7675607 iteration: 46790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10337 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.15916 L1 loss: 0.0000e+00 L2 loss: 0.61717 Learning rate: 0.002 Mask loss: 0.10828 RPN box loss: 0.00959 RPN score loss: 0.00517 RPN total loss: 0.01475 Total loss: 0.89936 timestamp: 1654950710.008647 iteration: 46795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13405 FastRCNN class loss: 0.1122 FastRCNN total loss: 0.24626 L1 loss: 0.0000e+00 L2 loss: 0.61716 Learning rate: 0.002 Mask loss: 0.11998 RPN box loss: 0.02742 RPN score loss: 0.00166 RPN total loss: 0.02908 Total loss: 1.01248 timestamp: 1654950713.2399666 iteration: 46800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0524 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.10673 L1 loss: 0.0000e+00 L2 loss: 0.61715 Learning rate: 0.002 Mask loss: 0.1441 RPN box loss: 0.01099 RPN score loss: 0.00126 RPN total loss: 0.01225 Total loss: 0.88023 timestamp: 1654950716.4906073 iteration: 46805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08334 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.13631 L1 loss: 0.0000e+00 L2 loss: 0.61714 Learning rate: 0.002 Mask loss: 0.12087 RPN box loss: 0.0062 RPN score loss: 0.00128 RPN total loss: 0.00749 Total loss: 0.88181 timestamp: 1654950719.648417 iteration: 46810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05348 FastRCNN class loss: 0.04375 FastRCNN total loss: 0.09724 L1 loss: 0.0000e+00 L2 loss: 0.61713 Learning rate: 0.002 Mask loss: 0.1377 RPN box loss: 0.02967 RPN score loss: 0.00142 RPN total loss: 0.03109 Total loss: 0.88315 timestamp: 1654950722.8826451 iteration: 46815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07116 FastRCNN class loss: 0.08459 FastRCNN total loss: 0.15575 L1 loss: 0.0000e+00 L2 loss: 0.61712 Learning rate: 0.002 Mask loss: 0.15969 RPN box loss: 0.01205 RPN score loss: 0.00356 RPN total loss: 0.0156 Total loss: 0.94817 timestamp: 1654950726.1506963 iteration: 46820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1115 FastRCNN class loss: 0.05702 FastRCNN total loss: 0.16852 L1 loss: 0.0000e+00 L2 loss: 0.61711 Learning rate: 0.002 Mask loss: 0.09599 RPN box loss: 0.00651 RPN score loss: 0.0047 RPN total loss: 0.01121 Total loss: 0.89285 timestamp: 1654950729.3282633 iteration: 46825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14544 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.21983 L1 loss: 0.0000e+00 L2 loss: 0.61711 Learning rate: 0.002 Mask loss: 0.14508 RPN box loss: 0.0307 RPN score loss: 0.00219 RPN total loss: 0.03289 Total loss: 1.01491 timestamp: 1654950732.5398424 iteration: 46830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09227 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.18414 L1 loss: 0.0000e+00 L2 loss: 0.6171 Learning rate: 0.002 Mask loss: 0.10987 RPN box loss: 0.01327 RPN score loss: 0.00222 RPN total loss: 0.01548 Total loss: 0.92659 timestamp: 1654950735.7441623 iteration: 46835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12529 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.20537 L1 loss: 0.0000e+00 L2 loss: 0.61709 Learning rate: 0.002 Mask loss: 0.13695 RPN box loss: 0.02796 RPN score loss: 0.0058 RPN total loss: 0.03376 Total loss: 0.99317 timestamp: 1654950738.893714 iteration: 46840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05494 FastRCNN class loss: 0.05626 FastRCNN total loss: 0.11119 L1 loss: 0.0000e+00 L2 loss: 0.61708 Learning rate: 0.002 Mask loss: 0.15859 RPN box loss: 0.01172 RPN score loss: 0.0055 RPN total loss: 0.01723 Total loss: 0.90409 timestamp: 1654950742.0844774 iteration: 46845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10951 FastRCNN class loss: 0.07147 FastRCNN total loss: 0.18097 L1 loss: 0.0000e+00 L2 loss: 0.61707 Learning rate: 0.002 Mask loss: 0.11177 RPN box loss: 0.00865 RPN score loss: 0.00261 RPN total loss: 0.01126 Total loss: 0.92107 timestamp: 1654950745.2134237 iteration: 46850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10131 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.15147 L1 loss: 0.0000e+00 L2 loss: 0.61706 Learning rate: 0.002 Mask loss: 0.09864 RPN box loss: 0.00927 RPN score loss: 0.00262 RPN total loss: 0.01189 Total loss: 0.87904 timestamp: 1654950748.3866642 iteration: 46855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05866 FastRCNN class loss: 0.03817 FastRCNN total loss: 0.09684 L1 loss: 0.0000e+00 L2 loss: 0.61705 Learning rate: 0.002 Mask loss: 0.13661 RPN box loss: 0.00911 RPN score loss: 0.00286 RPN total loss: 0.01197 Total loss: 0.86246 timestamp: 1654950751.532379 iteration: 46860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06749 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.13446 L1 loss: 0.0000e+00 L2 loss: 0.61704 Learning rate: 0.002 Mask loss: 0.12492 RPN box loss: 0.01753 RPN score loss: 0.00225 RPN total loss: 0.01978 Total loss: 0.8962 timestamp: 1654950754.6788323 iteration: 46865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14569 FastRCNN class loss: 0.09295 FastRCNN total loss: 0.23864 L1 loss: 0.0000e+00 L2 loss: 0.61703 Learning rate: 0.002 Mask loss: 0.1657 RPN box loss: 0.01065 RPN score loss: 0.00789 RPN total loss: 0.01853 Total loss: 1.0399 timestamp: 1654950757.89083 iteration: 46870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.14689 L1 loss: 0.0000e+00 L2 loss: 0.61702 Learning rate: 0.002 Mask loss: 0.14567 RPN box loss: 0.00747 RPN score loss: 0.0041 RPN total loss: 0.01157 Total loss: 0.92115 timestamp: 1654950761.0986273 iteration: 46875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.04604 FastRCNN total loss: 0.12891 L1 loss: 0.0000e+00 L2 loss: 0.61701 Learning rate: 0.002 Mask loss: 0.10935 RPN box loss: 0.01574 RPN score loss: 0.00146 RPN total loss: 0.0172 Total loss: 0.87247 timestamp: 1654950764.3356543 iteration: 46880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12919 FastRCNN class loss: 0.0731 FastRCNN total loss: 0.20229 L1 loss: 0.0000e+00 L2 loss: 0.617 Learning rate: 0.002 Mask loss: 0.09825 RPN box loss: 0.02776 RPN score loss: 0.00732 RPN total loss: 0.03508 Total loss: 0.95262 timestamp: 1654950767.440275 iteration: 46885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05989 FastRCNN class loss: 0.03377 FastRCNN total loss: 0.09367 L1 loss: 0.0000e+00 L2 loss: 0.61699 Learning rate: 0.002 Mask loss: 0.09819 RPN box loss: 0.0151 RPN score loss: 0.00489 RPN total loss: 0.01999 Total loss: 0.82884 timestamp: 1654950770.6581717 iteration: 46890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07408 FastRCNN class loss: 0.06341 FastRCNN total loss: 0.13749 L1 loss: 0.0000e+00 L2 loss: 0.61698 Learning rate: 0.002 Mask loss: 0.09604 RPN box loss: 0.02087 RPN score loss: 0.00722 RPN total loss: 0.02809 Total loss: 0.87861 timestamp: 1654950773.9341884 iteration: 46895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0954 FastRCNN class loss: 0.0763 FastRCNN total loss: 0.1717 L1 loss: 0.0000e+00 L2 loss: 0.61698 Learning rate: 0.002 Mask loss: 0.1506 RPN box loss: 0.04168 RPN score loss: 0.00433 RPN total loss: 0.04602 Total loss: 0.98529 timestamp: 1654950777.1905618 iteration: 46900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14182 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.21025 L1 loss: 0.0000e+00 L2 loss: 0.61697 Learning rate: 0.002 Mask loss: 0.15562 RPN box loss: 0.04978 RPN score loss: 0.01538 RPN total loss: 0.06516 Total loss: 1.048 timestamp: 1654950780.4453049 iteration: 46905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07844 FastRCNN class loss: 0.05087 FastRCNN total loss: 0.12931 L1 loss: 0.0000e+00 L2 loss: 0.61696 Learning rate: 0.002 Mask loss: 0.09294 RPN box loss: 0.01473 RPN score loss: 0.00135 RPN total loss: 0.01608 Total loss: 0.85528 timestamp: 1654950783.664083 iteration: 46910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06242 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.13534 L1 loss: 0.0000e+00 L2 loss: 0.61695 Learning rate: 0.002 Mask loss: 0.10775 RPN box loss: 0.00626 RPN score loss: 0.0035 RPN total loss: 0.00976 Total loss: 0.8698 timestamp: 1654950786.793013 iteration: 46915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14047 FastRCNN class loss: 0.10631 FastRCNN total loss: 0.24678 L1 loss: 0.0000e+00 L2 loss: 0.61694 Learning rate: 0.002 Mask loss: 0.16024 RPN box loss: 0.02107 RPN score loss: 0.00901 RPN total loss: 0.03008 Total loss: 1.05404 timestamp: 1654950789.9246151 iteration: 46920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08268 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.13764 L1 loss: 0.0000e+00 L2 loss: 0.61693 Learning rate: 0.002 Mask loss: 0.12212 RPN box loss: 0.01222 RPN score loss: 0.00525 RPN total loss: 0.01747 Total loss: 0.89415 timestamp: 1654950793.100468 iteration: 46925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0764 FastRCNN class loss: 0.04741 FastRCNN total loss: 0.12381 L1 loss: 0.0000e+00 L2 loss: 0.61692 Learning rate: 0.002 Mask loss: 0.13433 RPN box loss: 0.00906 RPN score loss: 0.00217 RPN total loss: 0.01122 Total loss: 0.88629 timestamp: 1654950796.3784492 iteration: 46930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14234 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.23141 L1 loss: 0.0000e+00 L2 loss: 0.61691 Learning rate: 0.002 Mask loss: 0.20183 RPN box loss: 0.01864 RPN score loss: 0.0026 RPN total loss: 0.02124 Total loss: 1.07139 timestamp: 1654950799.6520545 iteration: 46935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08394 FastRCNN class loss: 0.04731 FastRCNN total loss: 0.13125 L1 loss: 0.0000e+00 L2 loss: 0.6169 Learning rate: 0.002 Mask loss: 0.10594 RPN box loss: 0.01145 RPN score loss: 0.00558 RPN total loss: 0.01703 Total loss: 0.87113 timestamp: 1654950802.8550277 iteration: 46940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13669 FastRCNN class loss: 0.05441 FastRCNN total loss: 0.1911 L1 loss: 0.0000e+00 L2 loss: 0.6169 Learning rate: 0.002 Mask loss: 0.17197 RPN box loss: 0.02346 RPN score loss: 0.00771 RPN total loss: 0.03116 Total loss: 1.01113 timestamp: 1654950806.160165 iteration: 46945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10206 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.18499 L1 loss: 0.0000e+00 L2 loss: 0.61689 Learning rate: 0.002 Mask loss: 0.17494 RPN box loss: 0.02136 RPN score loss: 0.00956 RPN total loss: 0.03092 Total loss: 1.00773 timestamp: 1654950809.387533 iteration: 46950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12354 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 0.61688 Learning rate: 0.002 Mask loss: 0.19418 RPN box loss: 0.01376 RPN score loss: 0.00352 RPN total loss: 0.01728 Total loss: 1.02888 timestamp: 1654950812.560248 iteration: 46955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04485 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.10835 L1 loss: 0.0000e+00 L2 loss: 0.61687 Learning rate: 0.002 Mask loss: 0.12814 RPN box loss: 0.00663 RPN score loss: 0.00585 RPN total loss: 0.01248 Total loss: 0.86583 timestamp: 1654950815.8181386 iteration: 46960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17079 FastRCNN class loss: 0.0684 FastRCNN total loss: 0.23919 L1 loss: 0.0000e+00 L2 loss: 0.61686 Learning rate: 0.002 Mask loss: 0.11902 RPN box loss: 0.00805 RPN score loss: 0.00402 RPN total loss: 0.01206 Total loss: 0.98713 timestamp: 1654950819.040893 iteration: 46965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12178 FastRCNN class loss: 0.10302 FastRCNN total loss: 0.2248 L1 loss: 0.0000e+00 L2 loss: 0.61685 Learning rate: 0.002 Mask loss: 0.17149 RPN box loss: 0.01892 RPN score loss: 0.01136 RPN total loss: 0.03029 Total loss: 1.04343 timestamp: 1654950822.1945095 iteration: 46970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.09772 FastRCNN total loss: 0.17884 L1 loss: 0.0000e+00 L2 loss: 0.61684 Learning rate: 0.002 Mask loss: 0.16682 RPN box loss: 0.00929 RPN score loss: 0.003 RPN total loss: 0.01229 Total loss: 0.97478 timestamp: 1654950825.4510102 iteration: 46975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09892 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.16897 L1 loss: 0.0000e+00 L2 loss: 0.61683 Learning rate: 0.002 Mask loss: 0.15143 RPN box loss: 0.02634 RPN score loss: 0.00586 RPN total loss: 0.03219 Total loss: 0.96942 timestamp: 1654950828.6298919 iteration: 46980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0921 FastRCNN class loss: 0.0586 FastRCNN total loss: 0.1507 L1 loss: 0.0000e+00 L2 loss: 0.61683 Learning rate: 0.002 Mask loss: 0.1179 RPN box loss: 0.01204 RPN score loss: 0.0053 RPN total loss: 0.01734 Total loss: 0.90276 timestamp: 1654950831.7644405 iteration: 46985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09085 FastRCNN class loss: 0.04881 FastRCNN total loss: 0.13966 L1 loss: 0.0000e+00 L2 loss: 0.61681 Learning rate: 0.002 Mask loss: 0.12359 RPN box loss: 0.01799 RPN score loss: 0.00185 RPN total loss: 0.01984 Total loss: 0.8999 timestamp: 1654950834.8703203 iteration: 46990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08621 FastRCNN class loss: 0.05817 FastRCNN total loss: 0.14437 L1 loss: 0.0000e+00 L2 loss: 0.6168 Learning rate: 0.002 Mask loss: 0.11421 RPN box loss: 0.01214 RPN score loss: 0.00389 RPN total loss: 0.01603 Total loss: 0.89142 timestamp: 1654950838.0718374 iteration: 46995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1624 FastRCNN class loss: 0.05166 FastRCNN total loss: 0.21405 L1 loss: 0.0000e+00 L2 loss: 0.61679 Learning rate: 0.002 Mask loss: 0.12726 RPN box loss: 0.01649 RPN score loss: 0.00327 RPN total loss: 0.01976 Total loss: 0.97787 timestamp: 1654950841.3436573 iteration: 47000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14662 FastRCNN class loss: 0.08435 FastRCNN total loss: 0.23096 L1 loss: 0.0000e+00 L2 loss: 0.61678 Learning rate: 0.002 Mask loss: 0.11701 RPN box loss: 0.01627 RPN score loss: 0.00526 RPN total loss: 0.02153 Total loss: 0.98628 timestamp: 1654950844.5547054 iteration: 47005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05028 FastRCNN class loss: 0.04701 FastRCNN total loss: 0.09729 L1 loss: 0.0000e+00 L2 loss: 0.61677 Learning rate: 0.002 Mask loss: 0.09871 RPN box loss: 0.03211 RPN score loss: 0.00114 RPN total loss: 0.03325 Total loss: 0.84602 timestamp: 1654950847.8172464 iteration: 47010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05625 FastRCNN class loss: 0.06134 FastRCNN total loss: 0.11759 L1 loss: 0.0000e+00 L2 loss: 0.61676 Learning rate: 0.002 Mask loss: 0.11958 RPN box loss: 0.0241 RPN score loss: 0.00179 RPN total loss: 0.02589 Total loss: 0.87982 timestamp: 1654950850.9785697 iteration: 47015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10508 FastRCNN class loss: 0.04913 FastRCNN total loss: 0.15421 L1 loss: 0.0000e+00 L2 loss: 0.61675 Learning rate: 0.002 Mask loss: 0.08963 RPN box loss: 0.03128 RPN score loss: 0.00419 RPN total loss: 0.03548 Total loss: 0.89607 timestamp: 1654950854.2260156 iteration: 47020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10334 FastRCNN class loss: 0.04292 FastRCNN total loss: 0.14626 L1 loss: 0.0000e+00 L2 loss: 0.61674 Learning rate: 0.002 Mask loss: 0.12876 RPN box loss: 0.02511 RPN score loss: 0.00351 RPN total loss: 0.02862 Total loss: 0.92038 timestamp: 1654950857.4462152 iteration: 47025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13796 FastRCNN class loss: 0.04977 FastRCNN total loss: 0.18773 L1 loss: 0.0000e+00 L2 loss: 0.61673 Learning rate: 0.002 Mask loss: 0.07213 RPN box loss: 0.00876 RPN score loss: 0.00224 RPN total loss: 0.01099 Total loss: 0.88759 timestamp: 1654950860.6987574 iteration: 47030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13582 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.20695 L1 loss: 0.0000e+00 L2 loss: 0.61673 Learning rate: 0.002 Mask loss: 0.11439 RPN box loss: 0.00688 RPN score loss: 0.00064 RPN total loss: 0.00752 Total loss: 0.94559 timestamp: 1654950863.8557289 iteration: 47035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11947 FastRCNN class loss: 0.10638 FastRCNN total loss: 0.22585 L1 loss: 0.0000e+00 L2 loss: 0.61672 Learning rate: 0.002 Mask loss: 0.14001 RPN box loss: 0.01382 RPN score loss: 0.00533 RPN total loss: 0.01914 Total loss: 1.00173 timestamp: 1654950867.0740278 iteration: 47040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10166 FastRCNN class loss: 0.05455 FastRCNN total loss: 0.15621 L1 loss: 0.0000e+00 L2 loss: 0.61671 Learning rate: 0.002 Mask loss: 0.12467 RPN box loss: 0.01912 RPN score loss: 0.00801 RPN total loss: 0.02713 Total loss: 0.92471 timestamp: 1654950870.2412772 iteration: 47045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12421 FastRCNN class loss: 0.11225 FastRCNN total loss: 0.23646 L1 loss: 0.0000e+00 L2 loss: 0.6167 Learning rate: 0.002 Mask loss: 0.2112 RPN box loss: 0.00757 RPN score loss: 0.00862 RPN total loss: 0.01619 Total loss: 1.08054 timestamp: 1654950873.4231534 iteration: 47050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10284 FastRCNN class loss: 0.08181 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 0.61669 Learning rate: 0.002 Mask loss: 0.12731 RPN box loss: 0.03667 RPN score loss: 0.00822 RPN total loss: 0.04489 Total loss: 0.97355 timestamp: 1654950876.6417832 iteration: 47055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07566 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.14196 L1 loss: 0.0000e+00 L2 loss: 0.61668 Learning rate: 0.002 Mask loss: 0.12386 RPN box loss: 0.01793 RPN score loss: 0.00582 RPN total loss: 0.02375 Total loss: 0.90624 timestamp: 1654950879.8579276 iteration: 47060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07431 FastRCNN class loss: 0.05162 FastRCNN total loss: 0.12592 L1 loss: 0.0000e+00 L2 loss: 0.61667 Learning rate: 0.002 Mask loss: 0.14218 RPN box loss: 0.00957 RPN score loss: 0.00233 RPN total loss: 0.0119 Total loss: 0.89667 timestamp: 1654950883.0786867 iteration: 47065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04347 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.10271 L1 loss: 0.0000e+00 L2 loss: 0.61667 Learning rate: 0.002 Mask loss: 0.14455 RPN box loss: 0.00732 RPN score loss: 0.0072 RPN total loss: 0.01452 Total loss: 0.87844 timestamp: 1654950886.2712672 iteration: 47070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09592 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.15789 L1 loss: 0.0000e+00 L2 loss: 0.61666 Learning rate: 0.002 Mask loss: 0.19099 RPN box loss: 0.01954 RPN score loss: 0.00279 RPN total loss: 0.02233 Total loss: 0.98788 timestamp: 1654950889.4761133 iteration: 47075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06667 FastRCNN class loss: 0.04395 FastRCNN total loss: 0.11062 L1 loss: 0.0000e+00 L2 loss: 0.61665 Learning rate: 0.002 Mask loss: 0.14779 RPN box loss: 0.0231 RPN score loss: 0.00116 RPN total loss: 0.02426 Total loss: 0.89932 timestamp: 1654950892.7145238 iteration: 47080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07716 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.14223 L1 loss: 0.0000e+00 L2 loss: 0.61664 Learning rate: 0.002 Mask loss: 0.1614 RPN box loss: 0.0061 RPN score loss: 0.00416 RPN total loss: 0.01026 Total loss: 0.93052 timestamp: 1654950895.9163496 iteration: 47085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1473 FastRCNN class loss: 0.1376 FastRCNN total loss: 0.28489 L1 loss: 0.0000e+00 L2 loss: 0.61663 Learning rate: 0.002 Mask loss: 0.17053 RPN box loss: 0.01822 RPN score loss: 0.00249 RPN total loss: 0.02071 Total loss: 1.09276 timestamp: 1654950899.1490142 iteration: 47090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.20993 L1 loss: 0.0000e+00 L2 loss: 0.61662 Learning rate: 0.002 Mask loss: 0.11686 RPN box loss: 0.02366 RPN score loss: 0.00138 RPN total loss: 0.02505 Total loss: 0.96846 timestamp: 1654950902.3010547 iteration: 47095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06849 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.13012 L1 loss: 0.0000e+00 L2 loss: 0.61661 Learning rate: 0.002 Mask loss: 0.11589 RPN box loss: 0.01544 RPN score loss: 0.0095 RPN total loss: 0.02494 Total loss: 0.88756 timestamp: 1654950905.462375 iteration: 47100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07162 FastRCNN class loss: 0.07341 FastRCNN total loss: 0.14503 L1 loss: 0.0000e+00 L2 loss: 0.61661 Learning rate: 0.002 Mask loss: 0.19241 RPN box loss: 0.01562 RPN score loss: 0.00747 RPN total loss: 0.02309 Total loss: 0.97714 timestamp: 1654950908.6554015 iteration: 47105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08507 FastRCNN class loss: 0.04983 FastRCNN total loss: 0.1349 L1 loss: 0.0000e+00 L2 loss: 0.6166 Learning rate: 0.002 Mask loss: 0.12901 RPN box loss: 0.0021 RPN score loss: 0.00461 RPN total loss: 0.00671 Total loss: 0.88721 timestamp: 1654950911.7591376 iteration: 47110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04104 FastRCNN class loss: 0.0391 FastRCNN total loss: 0.08014 L1 loss: 0.0000e+00 L2 loss: 0.61659 Learning rate: 0.002 Mask loss: 0.08137 RPN box loss: 0.00257 RPN score loss: 0.00259 RPN total loss: 0.00517 Total loss: 0.78326 timestamp: 1654950915.0401704 iteration: 47115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10178 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.16824 L1 loss: 0.0000e+00 L2 loss: 0.61657 Learning rate: 0.002 Mask loss: 0.12572 RPN box loss: 0.00961 RPN score loss: 0.00377 RPN total loss: 0.01339 Total loss: 0.92392 timestamp: 1654950918.2740383 iteration: 47120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12327 FastRCNN class loss: 0.09054 FastRCNN total loss: 0.2138 L1 loss: 0.0000e+00 L2 loss: 0.61656 Learning rate: 0.002 Mask loss: 0.13108 RPN box loss: 0.01676 RPN score loss: 0.01437 RPN total loss: 0.03114 Total loss: 0.99258 timestamp: 1654950921.4987483 iteration: 47125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08055 FastRCNN class loss: 0.06737 FastRCNN total loss: 0.14792 L1 loss: 0.0000e+00 L2 loss: 0.61656 Learning rate: 0.002 Mask loss: 0.14745 RPN box loss: 0.01213 RPN score loss: 0.00542 RPN total loss: 0.01756 Total loss: 0.92949 timestamp: 1654950924.747445 iteration: 47130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10935 FastRCNN class loss: 0.05717 FastRCNN total loss: 0.16652 L1 loss: 0.0000e+00 L2 loss: 0.61655 Learning rate: 0.002 Mask loss: 0.131 RPN box loss: 0.01439 RPN score loss: 0.00312 RPN total loss: 0.01751 Total loss: 0.93158 timestamp: 1654950927.9118216 iteration: 47135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12648 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.22232 L1 loss: 0.0000e+00 L2 loss: 0.61654 Learning rate: 0.002 Mask loss: 0.11136 RPN box loss: 0.04588 RPN score loss: 0.00549 RPN total loss: 0.05138 Total loss: 1.00161 timestamp: 1654950931.1446195 iteration: 47140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08941 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.16184 L1 loss: 0.0000e+00 L2 loss: 0.61653 Learning rate: 0.002 Mask loss: 0.13388 RPN box loss: 0.01464 RPN score loss: 0.00238 RPN total loss: 0.01702 Total loss: 0.92927 timestamp: 1654950934.3416939 iteration: 47145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09184 FastRCNN class loss: 0.07849 FastRCNN total loss: 0.17033 L1 loss: 0.0000e+00 L2 loss: 0.61652 Learning rate: 0.002 Mask loss: 0.14957 RPN box loss: 0.01156 RPN score loss: 0.0043 RPN total loss: 0.01586 Total loss: 0.95229 timestamp: 1654950937.5760481 iteration: 47150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07263 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.13495 L1 loss: 0.0000e+00 L2 loss: 0.61651 Learning rate: 0.002 Mask loss: 0.12772 RPN box loss: 0.02361 RPN score loss: 0.00722 RPN total loss: 0.03084 Total loss: 0.91002 timestamp: 1654950940.7964883 iteration: 47155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07107 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.13989 L1 loss: 0.0000e+00 L2 loss: 0.6165 Learning rate: 0.002 Mask loss: 0.10439 RPN box loss: 0.00665 RPN score loss: 0.0028 RPN total loss: 0.00945 Total loss: 0.87023 timestamp: 1654950943.9540682 iteration: 47160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11948 FastRCNN class loss: 0.16076 FastRCNN total loss: 0.28024 L1 loss: 0.0000e+00 L2 loss: 0.61649 Learning rate: 0.002 Mask loss: 0.1756 RPN box loss: 0.01527 RPN score loss: 0.00687 RPN total loss: 0.02214 Total loss: 1.09447 timestamp: 1654950947.206859 iteration: 47165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09622 FastRCNN class loss: 0.06594 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 0.61649 Learning rate: 0.002 Mask loss: 0.13453 RPN box loss: 0.02049 RPN score loss: 0.00484 RPN total loss: 0.02533 Total loss: 0.9385 timestamp: 1654950950.3788614 iteration: 47170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12606 FastRCNN class loss: 0.0823 FastRCNN total loss: 0.20837 L1 loss: 0.0000e+00 L2 loss: 0.61648 Learning rate: 0.002 Mask loss: 0.16205 RPN box loss: 0.00615 RPN score loss: 0.00292 RPN total loss: 0.00907 Total loss: 0.99597 timestamp: 1654950953.551126 iteration: 47175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1205 FastRCNN class loss: 0.11917 FastRCNN total loss: 0.23966 L1 loss: 0.0000e+00 L2 loss: 0.61647 Learning rate: 0.002 Mask loss: 0.1706 RPN box loss: 0.01863 RPN score loss: 0.00689 RPN total loss: 0.02552 Total loss: 1.05226 timestamp: 1654950956.7286496 iteration: 47180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13361 FastRCNN class loss: 0.1218 FastRCNN total loss: 0.25541 L1 loss: 0.0000e+00 L2 loss: 0.61646 Learning rate: 0.002 Mask loss: 0.1368 RPN box loss: 0.02158 RPN score loss: 0.00394 RPN total loss: 0.02553 Total loss: 1.0342 timestamp: 1654950960.0149093 iteration: 47185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11256 FastRCNN class loss: 0.09224 FastRCNN total loss: 0.2048 L1 loss: 0.0000e+00 L2 loss: 0.61645 Learning rate: 0.002 Mask loss: 0.13663 RPN box loss: 0.01711 RPN score loss: 0.00351 RPN total loss: 0.02062 Total loss: 0.9785 timestamp: 1654950963.2345963 iteration: 47190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10455 FastRCNN class loss: 0.06884 FastRCNN total loss: 0.1734 L1 loss: 0.0000e+00 L2 loss: 0.61644 Learning rate: 0.002 Mask loss: 0.10589 RPN box loss: 0.00467 RPN score loss: 0.00304 RPN total loss: 0.00771 Total loss: 0.90343 timestamp: 1654950966.4512382 iteration: 47195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08408 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.15807 L1 loss: 0.0000e+00 L2 loss: 0.61644 Learning rate: 0.002 Mask loss: 0.19309 RPN box loss: 0.00668 RPN score loss: 0.00415 RPN total loss: 0.01083 Total loss: 0.97843 timestamp: 1654950969.60061 iteration: 47200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.09256 FastRCNN total loss: 0.19323 L1 loss: 0.0000e+00 L2 loss: 0.61643 Learning rate: 0.002 Mask loss: 0.18 RPN box loss: 0.01125 RPN score loss: 0.00318 RPN total loss: 0.01443 Total loss: 1.00407 timestamp: 1654950972.7688684 iteration: 47205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10174 FastRCNN class loss: 0.15222 FastRCNN total loss: 0.25396 L1 loss: 0.0000e+00 L2 loss: 0.61642 Learning rate: 0.002 Mask loss: 0.08747 RPN box loss: 0.01941 RPN score loss: 0.00181 RPN total loss: 0.02122 Total loss: 0.97907 timestamp: 1654950975.9410112 iteration: 47210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10224 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.17929 L1 loss: 0.0000e+00 L2 loss: 0.61641 Learning rate: 0.002 Mask loss: 0.12521 RPN box loss: 0.04931 RPN score loss: 0.00102 RPN total loss: 0.05033 Total loss: 0.97124 timestamp: 1654950979.1004686 iteration: 47215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14047 FastRCNN class loss: 0.09972 FastRCNN total loss: 0.24019 L1 loss: 0.0000e+00 L2 loss: 0.6164 Learning rate: 0.002 Mask loss: 0.16798 RPN box loss: 0.02972 RPN score loss: 0.01127 RPN total loss: 0.04099 Total loss: 1.06557 timestamp: 1654950982.258821 iteration: 47220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06483 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.12884 L1 loss: 0.0000e+00 L2 loss: 0.61639 Learning rate: 0.002 Mask loss: 0.30385 RPN box loss: 0.01681 RPN score loss: 0.0021 RPN total loss: 0.01891 Total loss: 1.068 timestamp: 1654950985.4902802 iteration: 47225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09802 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.15775 L1 loss: 0.0000e+00 L2 loss: 0.61638 Learning rate: 0.002 Mask loss: 0.1094 RPN box loss: 0.01607 RPN score loss: 0.00247 RPN total loss: 0.01854 Total loss: 0.90208 timestamp: 1654950988.727455 iteration: 47230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16682 FastRCNN class loss: 0.08738 FastRCNN total loss: 0.2542 L1 loss: 0.0000e+00 L2 loss: 0.61637 Learning rate: 0.002 Mask loss: 0.19936 RPN box loss: 0.01681 RPN score loss: 0.00409 RPN total loss: 0.0209 Total loss: 1.09083 timestamp: 1654950991.9290488 iteration: 47235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13564 FastRCNN class loss: 0.05656 FastRCNN total loss: 0.1922 L1 loss: 0.0000e+00 L2 loss: 0.61636 Learning rate: 0.002 Mask loss: 0.09222 RPN box loss: 0.00655 RPN score loss: 0.00302 RPN total loss: 0.00957 Total loss: 0.91036 timestamp: 1654950995.1220329 iteration: 47240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11948 FastRCNN class loss: 0.16198 FastRCNN total loss: 0.28146 L1 loss: 0.0000e+00 L2 loss: 0.61635 Learning rate: 0.002 Mask loss: 0.20558 RPN box loss: 0.01824 RPN score loss: 0.00609 RPN total loss: 0.02433 Total loss: 1.12772 timestamp: 1654950998.2736988 iteration: 47245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10645 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.18143 L1 loss: 0.0000e+00 L2 loss: 0.61634 Learning rate: 0.002 Mask loss: 0.1195 RPN box loss: 0.01209 RPN score loss: 0.0093 RPN total loss: 0.02139 Total loss: 0.93866 timestamp: 1654951001.423543 iteration: 47250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13988 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.20967 L1 loss: 0.0000e+00 L2 loss: 0.61633 Learning rate: 0.002 Mask loss: 0.1767 RPN box loss: 0.04239 RPN score loss: 0.00343 RPN total loss: 0.04582 Total loss: 1.04852 timestamp: 1654951004.5707312 iteration: 47255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10433 FastRCNN class loss: 0.08941 FastRCNN total loss: 0.19374 L1 loss: 0.0000e+00 L2 loss: 0.61632 Learning rate: 0.002 Mask loss: 0.13131 RPN box loss: 0.01098 RPN score loss: 0.00816 RPN total loss: 0.01914 Total loss: 0.96052 timestamp: 1654951007.8169591 iteration: 47260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09753 FastRCNN class loss: 0.10409 FastRCNN total loss: 0.20162 L1 loss: 0.0000e+00 L2 loss: 0.61631 Learning rate: 0.002 Mask loss: 0.1439 RPN box loss: 0.04572 RPN score loss: 0.00967 RPN total loss: 0.05538 Total loss: 1.01722 timestamp: 1654951011.0888693 iteration: 47265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09431 FastRCNN class loss: 0.04913 FastRCNN total loss: 0.14344 L1 loss: 0.0000e+00 L2 loss: 0.6163 Learning rate: 0.002 Mask loss: 0.08685 RPN box loss: 0.01601 RPN score loss: 0.00299 RPN total loss: 0.019 Total loss: 0.8656 timestamp: 1654951014.2951753 iteration: 47270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08456 FastRCNN class loss: 0.05217 FastRCNN total loss: 0.13673 L1 loss: 0.0000e+00 L2 loss: 0.6163 Learning rate: 0.002 Mask loss: 0.15215 RPN box loss: 0.00983 RPN score loss: 0.00479 RPN total loss: 0.01461 Total loss: 0.91979 timestamp: 1654951017.4628255 iteration: 47275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06206 FastRCNN class loss: 0.07467 FastRCNN total loss: 0.13673 L1 loss: 0.0000e+00 L2 loss: 0.61628 Learning rate: 0.002 Mask loss: 0.12158 RPN box loss: 0.00945 RPN score loss: 0.00268 RPN total loss: 0.01212 Total loss: 0.88672 timestamp: 1654951020.6566067 iteration: 47280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14328 FastRCNN class loss: 0.08988 FastRCNN total loss: 0.23316 L1 loss: 0.0000e+00 L2 loss: 0.61628 Learning rate: 0.002 Mask loss: 0.11831 RPN box loss: 0.02465 RPN score loss: 0.01344 RPN total loss: 0.03809 Total loss: 1.00584 timestamp: 1654951023.8398583 iteration: 47285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08406 FastRCNN class loss: 0.05166 FastRCNN total loss: 0.13573 L1 loss: 0.0000e+00 L2 loss: 0.61627 Learning rate: 0.002 Mask loss: 0.09206 RPN box loss: 0.01184 RPN score loss: 0.0018 RPN total loss: 0.01364 Total loss: 0.85769 timestamp: 1654951027.1139219 iteration: 47290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12415 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.19071 L1 loss: 0.0000e+00 L2 loss: 0.61626 Learning rate: 0.002 Mask loss: 0.11695 RPN box loss: 0.00889 RPN score loss: 0.00194 RPN total loss: 0.01083 Total loss: 0.93476 timestamp: 1654951030.2544672 iteration: 47295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06183 FastRCNN class loss: 0.08104 FastRCNN total loss: 0.14287 L1 loss: 0.0000e+00 L2 loss: 0.61625 Learning rate: 0.002 Mask loss: 0.09061 RPN box loss: 0.01209 RPN score loss: 0.00934 RPN total loss: 0.02143 Total loss: 0.87116 timestamp: 1654951033.5206485 iteration: 47300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10439 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.18447 L1 loss: 0.0000e+00 L2 loss: 0.61624 Learning rate: 0.002 Mask loss: 0.12547 RPN box loss: 0.01054 RPN score loss: 0.00452 RPN total loss: 0.01506 Total loss: 0.94124 timestamp: 1654951036.698809 iteration: 47305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10649 FastRCNN class loss: 0.06247 FastRCNN total loss: 0.16896 L1 loss: 0.0000e+00 L2 loss: 0.61623 Learning rate: 0.002 Mask loss: 0.11224 RPN box loss: 0.01513 RPN score loss: 0.00423 RPN total loss: 0.01936 Total loss: 0.91678 timestamp: 1654951039.8890717 iteration: 47310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13543 FastRCNN class loss: 0.07053 FastRCNN total loss: 0.20596 L1 loss: 0.0000e+00 L2 loss: 0.61622 Learning rate: 0.002 Mask loss: 0.12546 RPN box loss: 0.01289 RPN score loss: 0.00636 RPN total loss: 0.01925 Total loss: 0.96689 timestamp: 1654951043.077 iteration: 47315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07347 FastRCNN class loss: 0.04902 FastRCNN total loss: 0.12249 L1 loss: 0.0000e+00 L2 loss: 0.61621 Learning rate: 0.002 Mask loss: 0.13736 RPN box loss: 0.0088 RPN score loss: 0.00254 RPN total loss: 0.01135 Total loss: 0.88741 timestamp: 1654951046.302741 iteration: 47320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15099 FastRCNN class loss: 0.07503 FastRCNN total loss: 0.22602 L1 loss: 0.0000e+00 L2 loss: 0.6162 Learning rate: 0.002 Mask loss: 0.1643 RPN box loss: 0.01921 RPN score loss: 0.00308 RPN total loss: 0.02229 Total loss: 1.02882 timestamp: 1654951049.492138 iteration: 47325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08859 FastRCNN class loss: 0.07278 FastRCNN total loss: 0.16137 L1 loss: 0.0000e+00 L2 loss: 0.6162 Learning rate: 0.002 Mask loss: 0.1227 RPN box loss: 0.0187 RPN score loss: 0.01071 RPN total loss: 0.0294 Total loss: 0.92967 timestamp: 1654951052.6942065 iteration: 47330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12804 FastRCNN class loss: 0.11643 FastRCNN total loss: 0.24446 L1 loss: 0.0000e+00 L2 loss: 0.61619 Learning rate: 0.002 Mask loss: 0.16184 RPN box loss: 0.02557 RPN score loss: 0.01415 RPN total loss: 0.03972 Total loss: 1.06221 timestamp: 1654951055.9426591 iteration: 47335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08596 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.1418 L1 loss: 0.0000e+00 L2 loss: 0.61618 Learning rate: 0.002 Mask loss: 0.18373 RPN box loss: 0.00786 RPN score loss: 0.00219 RPN total loss: 0.01005 Total loss: 0.95176 timestamp: 1654951059.1809342 iteration: 47340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07565 FastRCNN class loss: 0.06024 FastRCNN total loss: 0.13589 L1 loss: 0.0000e+00 L2 loss: 0.61616 Learning rate: 0.002 Mask loss: 0.11174 RPN box loss: 0.0184 RPN score loss: 0.00361 RPN total loss: 0.02201 Total loss: 0.88581 timestamp: 1654951062.3565202 iteration: 47345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10295 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.16634 L1 loss: 0.0000e+00 L2 loss: 0.61615 Learning rate: 0.002 Mask loss: 0.15061 RPN box loss: 0.00965 RPN score loss: 0.0015 RPN total loss: 0.01115 Total loss: 0.94426 timestamp: 1654951065.6030958 iteration: 47350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06945 FastRCNN class loss: 0.06798 FastRCNN total loss: 0.13743 L1 loss: 0.0000e+00 L2 loss: 0.61614 Learning rate: 0.002 Mask loss: 0.15591 RPN box loss: 0.01329 RPN score loss: 0.00512 RPN total loss: 0.0184 Total loss: 0.92789 timestamp: 1654951068.7988236 iteration: 47355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15604 FastRCNN class loss: 0.0756 FastRCNN total loss: 0.23164 L1 loss: 0.0000e+00 L2 loss: 0.61614 Learning rate: 0.002 Mask loss: 0.14595 RPN box loss: 0.02754 RPN score loss: 0.00382 RPN total loss: 0.03136 Total loss: 1.02508 timestamp: 1654951072.0323522 iteration: 47360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08991 FastRCNN class loss: 0.08735 FastRCNN total loss: 0.17726 L1 loss: 0.0000e+00 L2 loss: 0.61613 Learning rate: 0.002 Mask loss: 0.16679 RPN box loss: 0.01874 RPN score loss: 0.00158 RPN total loss: 0.02032 Total loss: 0.9805 timestamp: 1654951075.2438447 iteration: 47365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08606 FastRCNN class loss: 0.04562 FastRCNN total loss: 0.13168 L1 loss: 0.0000e+00 L2 loss: 0.61612 Learning rate: 0.002 Mask loss: 0.15319 RPN box loss: 0.00549 RPN score loss: 0.00186 RPN total loss: 0.00735 Total loss: 0.90834 timestamp: 1654951078.4705522 iteration: 47370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15059 FastRCNN class loss: 0.09568 FastRCNN total loss: 0.24626 L1 loss: 0.0000e+00 L2 loss: 0.61611 Learning rate: 0.002 Mask loss: 0.11467 RPN box loss: 0.03494 RPN score loss: 0.00827 RPN total loss: 0.04321 Total loss: 1.02026 timestamp: 1654951081.709498 iteration: 47375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06604 FastRCNN class loss: 0.03851 FastRCNN total loss: 0.10455 L1 loss: 0.0000e+00 L2 loss: 0.61611 Learning rate: 0.002 Mask loss: 0.12954 RPN box loss: 0.02724 RPN score loss: 0.00402 RPN total loss: 0.03126 Total loss: 0.88145 timestamp: 1654951084.9018493 iteration: 47380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08888 FastRCNN class loss: 0.09177 FastRCNN total loss: 0.18065 L1 loss: 0.0000e+00 L2 loss: 0.6161 Learning rate: 0.002 Mask loss: 0.16576 RPN box loss: 0.04082 RPN score loss: 0.0152 RPN total loss: 0.05602 Total loss: 1.01853 timestamp: 1654951088.0120664 iteration: 47385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13241 FastRCNN class loss: 0.08321 FastRCNN total loss: 0.21562 L1 loss: 0.0000e+00 L2 loss: 0.61609 Learning rate: 0.002 Mask loss: 0.16578 RPN box loss: 0.0344 RPN score loss: 0.01403 RPN total loss: 0.04843 Total loss: 1.04592 timestamp: 1654951091.2187104 iteration: 47390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09162 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.16255 L1 loss: 0.0000e+00 L2 loss: 0.61608 Learning rate: 0.002 Mask loss: 0.17354 RPN box loss: 0.00969 RPN score loss: 0.00348 RPN total loss: 0.01317 Total loss: 0.96534 timestamp: 1654951094.394425 iteration: 47395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04338 FastRCNN class loss: 0.05643 FastRCNN total loss: 0.09981 L1 loss: 0.0000e+00 L2 loss: 0.61607 Learning rate: 0.002 Mask loss: 0.12425 RPN box loss: 0.00653 RPN score loss: 0.00174 RPN total loss: 0.00827 Total loss: 0.8484 timestamp: 1654951097.723657 iteration: 47400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.19292 L1 loss: 0.0000e+00 L2 loss: 0.61606 Learning rate: 0.002 Mask loss: 0.14065 RPN box loss: 0.0046 RPN score loss: 0.00751 RPN total loss: 0.01211 Total loss: 0.96174 timestamp: 1654951101.0360768 iteration: 47405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09379 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.16598 L1 loss: 0.0000e+00 L2 loss: 0.61605 Learning rate: 0.002 Mask loss: 0.1235 RPN box loss: 0.03315 RPN score loss: 0.00772 RPN total loss: 0.04087 Total loss: 0.9464 timestamp: 1654951104.2130222 iteration: 47410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.17633 L1 loss: 0.0000e+00 L2 loss: 0.61604 Learning rate: 0.002 Mask loss: 0.12203 RPN box loss: 0.01615 RPN score loss: 0.01679 RPN total loss: 0.03295 Total loss: 0.94735 timestamp: 1654951107.4753187 iteration: 47415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04536 FastRCNN class loss: 0.03033 FastRCNN total loss: 0.07569 L1 loss: 0.0000e+00 L2 loss: 0.61603 Learning rate: 0.002 Mask loss: 0.08508 RPN box loss: 0.01578 RPN score loss: 0.00118 RPN total loss: 0.01697 Total loss: 0.79377 timestamp: 1654951110.7340515 iteration: 47420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.14345 L1 loss: 0.0000e+00 L2 loss: 0.61602 Learning rate: 0.002 Mask loss: 0.11555 RPN box loss: 0.01614 RPN score loss: 0.00529 RPN total loss: 0.02143 Total loss: 0.89646 timestamp: 1654951113.8955493 iteration: 47425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09092 FastRCNN class loss: 0.04756 FastRCNN total loss: 0.13848 L1 loss: 0.0000e+00 L2 loss: 0.61601 Learning rate: 0.002 Mask loss: 0.11669 RPN box loss: 0.02974 RPN score loss: 0.01295 RPN total loss: 0.04269 Total loss: 0.91387 timestamp: 1654951117.0698714 iteration: 47430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08605 FastRCNN class loss: 0.05737 FastRCNN total loss: 0.14342 L1 loss: 0.0000e+00 L2 loss: 0.61601 Learning rate: 0.002 Mask loss: 0.13561 RPN box loss: 0.00692 RPN score loss: 0.00468 RPN total loss: 0.0116 Total loss: 0.90664 timestamp: 1654951120.2519116 iteration: 47435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17667 FastRCNN class loss: 0.1315 FastRCNN total loss: 0.30817 L1 loss: 0.0000e+00 L2 loss: 0.616 Learning rate: 0.002 Mask loss: 0.16587 RPN box loss: 0.01643 RPN score loss: 0.0049 RPN total loss: 0.02133 Total loss: 1.11137 timestamp: 1654951123.4679606 iteration: 47440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06616 FastRCNN class loss: 0.05829 FastRCNN total loss: 0.12445 L1 loss: 0.0000e+00 L2 loss: 0.61599 Learning rate: 0.002 Mask loss: 0.10028 RPN box loss: 0.01693 RPN score loss: 0.0056 RPN total loss: 0.02253 Total loss: 0.86324 timestamp: 1654951126.6013012 iteration: 47445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11402 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.18322 L1 loss: 0.0000e+00 L2 loss: 0.61598 Learning rate: 0.002 Mask loss: 0.11092 RPN box loss: 0.01142 RPN score loss: 0.00405 RPN total loss: 0.01547 Total loss: 0.92559 timestamp: 1654951129.7430215 iteration: 47450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12419 FastRCNN class loss: 0.06678 FastRCNN total loss: 0.19097 L1 loss: 0.0000e+00 L2 loss: 0.61597 Learning rate: 0.002 Mask loss: 0.21082 RPN box loss: 0.02891 RPN score loss: 0.0035 RPN total loss: 0.03241 Total loss: 1.05016 timestamp: 1654951132.982683 iteration: 47455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04673 FastRCNN class loss: 0.04676 FastRCNN total loss: 0.09349 L1 loss: 0.0000e+00 L2 loss: 0.61595 Learning rate: 0.002 Mask loss: 0.07573 RPN box loss: 0.00651 RPN score loss: 0.00072 RPN total loss: 0.00722 Total loss: 0.7924 timestamp: 1654951136.191758 iteration: 47460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10303 FastRCNN class loss: 0.0548 FastRCNN total loss: 0.15783 L1 loss: 0.0000e+00 L2 loss: 0.61594 Learning rate: 0.002 Mask loss: 0.10993 RPN box loss: 0.00894 RPN score loss: 0.00238 RPN total loss: 0.01132 Total loss: 0.89502 timestamp: 1654951139.4059508 iteration: 47465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15355 FastRCNN class loss: 0.06791 FastRCNN total loss: 0.22146 L1 loss: 0.0000e+00 L2 loss: 0.61593 Learning rate: 0.002 Mask loss: 0.13766 RPN box loss: 0.00929 RPN score loss: 0.00375 RPN total loss: 0.01304 Total loss: 0.9881 timestamp: 1654951142.560849 iteration: 47470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12556 FastRCNN class loss: 0.11596 FastRCNN total loss: 0.24152 L1 loss: 0.0000e+00 L2 loss: 0.61593 Learning rate: 0.002 Mask loss: 0.17262 RPN box loss: 0.02622 RPN score loss: 0.00654 RPN total loss: 0.03276 Total loss: 1.06282 timestamp: 1654951145.7176824 iteration: 47475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11519 FastRCNN class loss: 0.12466 FastRCNN total loss: 0.23985 L1 loss: 0.0000e+00 L2 loss: 0.61592 Learning rate: 0.002 Mask loss: 0.12716 RPN box loss: 0.01157 RPN score loss: 0.00539 RPN total loss: 0.01696 Total loss: 0.99989 timestamp: 1654951148.9087052 iteration: 47480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1148 FastRCNN class loss: 0.09331 FastRCNN total loss: 0.20811 L1 loss: 0.0000e+00 L2 loss: 0.61591 Learning rate: 0.002 Mask loss: 0.17861 RPN box loss: 0.04434 RPN score loss: 0.00959 RPN total loss: 0.05394 Total loss: 1.05656 timestamp: 1654951152.1355243 iteration: 47485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10613 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.18453 L1 loss: 0.0000e+00 L2 loss: 0.6159 Learning rate: 0.002 Mask loss: 0.12596 RPN box loss: 0.00792 RPN score loss: 0.00568 RPN total loss: 0.0136 Total loss: 0.94 timestamp: 1654951155.3156998 iteration: 47490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17222 FastRCNN class loss: 0.10377 FastRCNN total loss: 0.27599 L1 loss: 0.0000e+00 L2 loss: 0.61589 Learning rate: 0.002 Mask loss: 0.20524 RPN box loss: 0.02676 RPN score loss: 0.0037 RPN total loss: 0.03046 Total loss: 1.12759 timestamp: 1654951158.5573113 iteration: 47495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14512 FastRCNN class loss: 0.0741 FastRCNN total loss: 0.21922 L1 loss: 0.0000e+00 L2 loss: 0.61588 Learning rate: 0.002 Mask loss: 0.12072 RPN box loss: 0.02157 RPN score loss: 0.00618 RPN total loss: 0.02775 Total loss: 0.98358 timestamp: 1654951161.6839066 iteration: 47500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12407 FastRCNN class loss: 0.06511 FastRCNN total loss: 0.18918 L1 loss: 0.0000e+00 L2 loss: 0.61587 Learning rate: 0.002 Mask loss: 0.10937 RPN box loss: 0.00934 RPN score loss: 0.00331 RPN total loss: 0.01265 Total loss: 0.92706 timestamp: 1654951164.9682674 iteration: 47505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11056 FastRCNN class loss: 0.08569 FastRCNN total loss: 0.19625 L1 loss: 0.0000e+00 L2 loss: 0.61586 Learning rate: 0.002 Mask loss: 0.14483 RPN box loss: 0.02407 RPN score loss: 0.00218 RPN total loss: 0.02625 Total loss: 0.98319 timestamp: 1654951168.208143 iteration: 47510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.12345 L1 loss: 0.0000e+00 L2 loss: 0.61584 Learning rate: 0.002 Mask loss: 0.10129 RPN box loss: 0.01491 RPN score loss: 0.00259 RPN total loss: 0.0175 Total loss: 0.85809 timestamp: 1654951171.3490837 iteration: 47515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16253 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.2544 L1 loss: 0.0000e+00 L2 loss: 0.61584 Learning rate: 0.002 Mask loss: 0.15384 RPN box loss: 0.02219 RPN score loss: 0.01261 RPN total loss: 0.03481 Total loss: 1.05889 timestamp: 1654951174.5241184 iteration: 47520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.05138 FastRCNN total loss: 0.13033 L1 loss: 0.0000e+00 L2 loss: 0.61583 Learning rate: 0.002 Mask loss: 0.12034 RPN box loss: 0.0141 RPN score loss: 0.00598 RPN total loss: 0.02008 Total loss: 0.88658 timestamp: 1654951177.6789963 iteration: 47525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09244 FastRCNN class loss: 0.06102 FastRCNN total loss: 0.15346 L1 loss: 0.0000e+00 L2 loss: 0.61582 Learning rate: 0.002 Mask loss: 0.12534 RPN box loss: 0.01891 RPN score loss: 0.0032 RPN total loss: 0.02211 Total loss: 0.91673 timestamp: 1654951180.9031737 iteration: 47530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16863 FastRCNN class loss: 0.14425 FastRCNN total loss: 0.31287 L1 loss: 0.0000e+00 L2 loss: 0.61582 Learning rate: 0.002 Mask loss: 0.17378 RPN box loss: 0.02254 RPN score loss: 0.00824 RPN total loss: 0.03078 Total loss: 1.13324 timestamp: 1654951184.1535635 iteration: 47535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15092 FastRCNN class loss: 0.11252 FastRCNN total loss: 0.26344 L1 loss: 0.0000e+00 L2 loss: 0.61581 Learning rate: 0.002 Mask loss: 0.24327 RPN box loss: 0.03206 RPN score loss: 0.00482 RPN total loss: 0.03688 Total loss: 1.1594 timestamp: 1654951187.3356395 iteration: 47540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08284 FastRCNN class loss: 0.07421 FastRCNN total loss: 0.15705 L1 loss: 0.0000e+00 L2 loss: 0.6158 Learning rate: 0.002 Mask loss: 0.11346 RPN box loss: 0.01035 RPN score loss: 0.00202 RPN total loss: 0.01237 Total loss: 0.89868 timestamp: 1654951190.5308669 iteration: 47545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05476 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.11043 L1 loss: 0.0000e+00 L2 loss: 0.61579 Learning rate: 0.002 Mask loss: 0.19741 RPN box loss: 0.03881 RPN score loss: 0.00482 RPN total loss: 0.04364 Total loss: 0.96727 timestamp: 1654951193.7953231 iteration: 47550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08106 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.15542 L1 loss: 0.0000e+00 L2 loss: 0.61578 Learning rate: 0.002 Mask loss: 0.08326 RPN box loss: 0.02441 RPN score loss: 0.00525 RPN total loss: 0.02966 Total loss: 0.88412 timestamp: 1654951197.0575504 iteration: 47555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07616 FastRCNN class loss: 0.06102 FastRCNN total loss: 0.13718 L1 loss: 0.0000e+00 L2 loss: 0.61578 Learning rate: 0.002 Mask loss: 0.16346 RPN box loss: 0.01833 RPN score loss: 0.00812 RPN total loss: 0.02645 Total loss: 0.94286 timestamp: 1654951200.2635207 iteration: 47560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14998 FastRCNN class loss: 0.10731 FastRCNN total loss: 0.25729 L1 loss: 0.0000e+00 L2 loss: 0.61577 Learning rate: 0.002 Mask loss: 0.25835 RPN box loss: 0.02251 RPN score loss: 0.00759 RPN total loss: 0.0301 Total loss: 1.1615 timestamp: 1654951203.4573655 iteration: 47565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05624 FastRCNN class loss: 0.04193 FastRCNN total loss: 0.09817 L1 loss: 0.0000e+00 L2 loss: 0.61576 Learning rate: 0.002 Mask loss: 0.11377 RPN box loss: 0.02747 RPN score loss: 0.00385 RPN total loss: 0.03131 Total loss: 0.85901 timestamp: 1654951206.6725018 iteration: 47570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0866 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.16169 L1 loss: 0.0000e+00 L2 loss: 0.61574 Learning rate: 0.002 Mask loss: 0.09202 RPN box loss: 0.02361 RPN score loss: 0.00238 RPN total loss: 0.02599 Total loss: 0.89544 timestamp: 1654951209.8287983 iteration: 47575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12672 FastRCNN class loss: 0.07865 FastRCNN total loss: 0.20538 L1 loss: 0.0000e+00 L2 loss: 0.61573 Learning rate: 0.002 Mask loss: 0.13947 RPN box loss: 0.01499 RPN score loss: 0.0071 RPN total loss: 0.02209 Total loss: 0.98267 timestamp: 1654951213.0576475 iteration: 47580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13913 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.21232 L1 loss: 0.0000e+00 L2 loss: 0.61573 Learning rate: 0.002 Mask loss: 0.33604 RPN box loss: 0.04792 RPN score loss: 0.00393 RPN total loss: 0.05185 Total loss: 1.21593 timestamp: 1654951216.3027139 iteration: 47585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08313 FastRCNN class loss: 0.06899 FastRCNN total loss: 0.15212 L1 loss: 0.0000e+00 L2 loss: 0.61572 Learning rate: 0.002 Mask loss: 0.14666 RPN box loss: 0.01617 RPN score loss: 0.01069 RPN total loss: 0.02686 Total loss: 0.94136 timestamp: 1654951219.573023 iteration: 47590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08001 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.14429 L1 loss: 0.0000e+00 L2 loss: 0.61571 Learning rate: 0.002 Mask loss: 0.12869 RPN box loss: 0.01259 RPN score loss: 0.01182 RPN total loss: 0.0244 Total loss: 0.91309 timestamp: 1654951222.7659862 iteration: 47595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11948 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.19376 L1 loss: 0.0000e+00 L2 loss: 0.6157 Learning rate: 0.002 Mask loss: 0.1676 RPN box loss: 0.02052 RPN score loss: 0.0069 RPN total loss: 0.02742 Total loss: 1.00448 timestamp: 1654951225.928667 iteration: 47600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12573 FastRCNN class loss: 0.06155 FastRCNN total loss: 0.18729 L1 loss: 0.0000e+00 L2 loss: 0.61569 Learning rate: 0.002 Mask loss: 0.12073 RPN box loss: 0.01022 RPN score loss: 0.00378 RPN total loss: 0.01401 Total loss: 0.93771 timestamp: 1654951229.2019732 iteration: 47605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05652 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.11192 L1 loss: 0.0000e+00 L2 loss: 0.61568 Learning rate: 0.002 Mask loss: 0.07043 RPN box loss: 0.00623 RPN score loss: 0.00095 RPN total loss: 0.00719 Total loss: 0.80522 timestamp: 1654951232.4150333 iteration: 47610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08537 FastRCNN class loss: 0.05167 FastRCNN total loss: 0.13704 L1 loss: 0.0000e+00 L2 loss: 0.61567 Learning rate: 0.002 Mask loss: 0.06714 RPN box loss: 0.01126 RPN score loss: 0.00167 RPN total loss: 0.01292 Total loss: 0.83277 timestamp: 1654951235.618298 iteration: 47615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10711 FastRCNN class loss: 0.09949 FastRCNN total loss: 0.2066 L1 loss: 0.0000e+00 L2 loss: 0.61567 Learning rate: 0.002 Mask loss: 0.14462 RPN box loss: 0.02156 RPN score loss: 0.01342 RPN total loss: 0.03499 Total loss: 1.00187 timestamp: 1654951238.8430371 iteration: 47620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05725 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.11595 L1 loss: 0.0000e+00 L2 loss: 0.61566 Learning rate: 0.002 Mask loss: 0.11635 RPN box loss: 0.02653 RPN score loss: 0.00624 RPN total loss: 0.03277 Total loss: 0.88073 timestamp: 1654951242.0852888 iteration: 47625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09814 FastRCNN class loss: 0.05878 FastRCNN total loss: 0.15692 L1 loss: 0.0000e+00 L2 loss: 0.61565 Learning rate: 0.002 Mask loss: 0.16332 RPN box loss: 0.01577 RPN score loss: 0.0062 RPN total loss: 0.02197 Total loss: 0.95785 timestamp: 1654951245.3356426 iteration: 47630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11357 FastRCNN class loss: 0.09121 FastRCNN total loss: 0.20477 L1 loss: 0.0000e+00 L2 loss: 0.61564 Learning rate: 0.002 Mask loss: 0.16617 RPN box loss: 0.02298 RPN score loss: 0.00686 RPN total loss: 0.02984 Total loss: 1.01642 timestamp: 1654951248.5081139 iteration: 47635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14752 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.21938 L1 loss: 0.0000e+00 L2 loss: 0.61562 Learning rate: 0.002 Mask loss: 0.1564 RPN box loss: 0.02055 RPN score loss: 0.00147 RPN total loss: 0.02202 Total loss: 1.01343 timestamp: 1654951251.75781 iteration: 47640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0985 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.1688 L1 loss: 0.0000e+00 L2 loss: 0.61561 Learning rate: 0.002 Mask loss: 0.11889 RPN box loss: 0.0141 RPN score loss: 0.00258 RPN total loss: 0.01667 Total loss: 0.91997 timestamp: 1654951254.9708548 iteration: 47645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05212 FastRCNN class loss: 0.03569 FastRCNN total loss: 0.08781 L1 loss: 0.0000e+00 L2 loss: 0.61561 Learning rate: 0.002 Mask loss: 0.1124 RPN box loss: 0.00519 RPN score loss: 0.00866 RPN total loss: 0.01385 Total loss: 0.82966 timestamp: 1654951258.167092 iteration: 47650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0586 FastRCNN class loss: 0.03138 FastRCNN total loss: 0.08998 L1 loss: 0.0000e+00 L2 loss: 0.6156 Learning rate: 0.002 Mask loss: 0.11033 RPN box loss: 0.00265 RPN score loss: 0.00123 RPN total loss: 0.00387 Total loss: 0.81978 timestamp: 1654951261.4063585 iteration: 47655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10238 FastRCNN class loss: 0.05663 FastRCNN total loss: 0.15901 L1 loss: 0.0000e+00 L2 loss: 0.61559 Learning rate: 0.002 Mask loss: 0.09678 RPN box loss: 0.00781 RPN score loss: 0.00206 RPN total loss: 0.00987 Total loss: 0.88125 timestamp: 1654951264.6334155 iteration: 47660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10863 FastRCNN class loss: 0.05955 FastRCNN total loss: 0.16818 L1 loss: 0.0000e+00 L2 loss: 0.61559 Learning rate: 0.002 Mask loss: 0.16085 RPN box loss: 0.01549 RPN score loss: 0.00166 RPN total loss: 0.01716 Total loss: 0.96177 timestamp: 1654951267.8597534 iteration: 47665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08348 FastRCNN class loss: 0.04372 FastRCNN total loss: 0.1272 L1 loss: 0.0000e+00 L2 loss: 0.61558 Learning rate: 0.002 Mask loss: 0.12411 RPN box loss: 0.00971 RPN score loss: 0.00216 RPN total loss: 0.01188 Total loss: 0.87877 timestamp: 1654951270.9751787 iteration: 47670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06803 FastRCNN class loss: 0.08595 FastRCNN total loss: 0.15398 L1 loss: 0.0000e+00 L2 loss: 0.61557 Learning rate: 0.002 Mask loss: 0.16347 RPN box loss: 0.00872 RPN score loss: 0.00628 RPN total loss: 0.015 Total loss: 0.94802 timestamp: 1654951274.1784103 iteration: 47675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1812 FastRCNN class loss: 0.12498 FastRCNN total loss: 0.30617 L1 loss: 0.0000e+00 L2 loss: 0.61556 Learning rate: 0.002 Mask loss: 0.13466 RPN box loss: 0.01105 RPN score loss: 0.00137 RPN total loss: 0.01242 Total loss: 1.06881 timestamp: 1654951277.3765352 iteration: 47680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09779 FastRCNN class loss: 0.0478 FastRCNN total loss: 0.14559 L1 loss: 0.0000e+00 L2 loss: 0.61555 Learning rate: 0.002 Mask loss: 0.14213 RPN box loss: 0.02905 RPN score loss: 0.00694 RPN total loss: 0.03598 Total loss: 0.93925 timestamp: 1654951280.5655966 iteration: 47685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06774 FastRCNN class loss: 0.05403 FastRCNN total loss: 0.12177 L1 loss: 0.0000e+00 L2 loss: 0.61554 Learning rate: 0.002 Mask loss: 0.13302 RPN box loss: 0.01993 RPN score loss: 0.00335 RPN total loss: 0.02328 Total loss: 0.8936 timestamp: 1654951283.827832 iteration: 47690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1093 FastRCNN class loss: 0.10587 FastRCNN total loss: 0.21517 L1 loss: 0.0000e+00 L2 loss: 0.61553 Learning rate: 0.002 Mask loss: 0.16566 RPN box loss: 0.01797 RPN score loss: 0.00122 RPN total loss: 0.01918 Total loss: 1.01555 timestamp: 1654951287.10121 iteration: 47695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13493 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.22521 L1 loss: 0.0000e+00 L2 loss: 0.61552 Learning rate: 0.002 Mask loss: 0.14881 RPN box loss: 0.01877 RPN score loss: 0.00323 RPN total loss: 0.022 Total loss: 1.01153 timestamp: 1654951290.3587518 iteration: 47700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10617 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.17743 L1 loss: 0.0000e+00 L2 loss: 0.61551 Learning rate: 0.002 Mask loss: 0.10006 RPN box loss: 0.0114 RPN score loss: 0.00168 RPN total loss: 0.01308 Total loss: 0.90607 timestamp: 1654951293.5318441 iteration: 47705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10503 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.17845 L1 loss: 0.0000e+00 L2 loss: 0.6155 Learning rate: 0.002 Mask loss: 0.14181 RPN box loss: 0.01586 RPN score loss: 0.00404 RPN total loss: 0.0199 Total loss: 0.95567 timestamp: 1654951296.7087953 iteration: 47710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07993 FastRCNN class loss: 0.08476 FastRCNN total loss: 0.16469 L1 loss: 0.0000e+00 L2 loss: 0.61549 Learning rate: 0.002 Mask loss: 0.21062 RPN box loss: 0.02177 RPN score loss: 0.01463 RPN total loss: 0.0364 Total loss: 1.02721 timestamp: 1654951299.8709376 iteration: 47715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12591 FastRCNN class loss: 0.06267 FastRCNN total loss: 0.18858 L1 loss: 0.0000e+00 L2 loss: 0.61548 Learning rate: 0.002 Mask loss: 0.16557 RPN box loss: 0.00724 RPN score loss: 0.00482 RPN total loss: 0.01206 Total loss: 0.98169 timestamp: 1654951303.0348938 iteration: 47720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0906 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.17121 L1 loss: 0.0000e+00 L2 loss: 0.61547 Learning rate: 0.002 Mask loss: 0.1383 RPN box loss: 0.01221 RPN score loss: 0.01051 RPN total loss: 0.02272 Total loss: 0.9477 timestamp: 1654951306.2063456 iteration: 47725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05813 FastRCNN class loss: 0.04953 FastRCNN total loss: 0.10765 L1 loss: 0.0000e+00 L2 loss: 0.61546 Learning rate: 0.002 Mask loss: 0.09965 RPN box loss: 0.01007 RPN score loss: 0.00657 RPN total loss: 0.01665 Total loss: 0.83942 timestamp: 1654951309.3897707 iteration: 47730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08556 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.15755 L1 loss: 0.0000e+00 L2 loss: 0.61545 Learning rate: 0.002 Mask loss: 0.17484 RPN box loss: 0.01694 RPN score loss: 0.01077 RPN total loss: 0.02771 Total loss: 0.97555 timestamp: 1654951312.6138644 iteration: 47735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08859 FastRCNN class loss: 0.03524 FastRCNN total loss: 0.12383 L1 loss: 0.0000e+00 L2 loss: 0.61544 Learning rate: 0.002 Mask loss: 0.0857 RPN box loss: 0.02163 RPN score loss: 0.00264 RPN total loss: 0.02427 Total loss: 0.84924 timestamp: 1654951315.8044317 iteration: 47740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13455 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.21096 L1 loss: 0.0000e+00 L2 loss: 0.61543 Learning rate: 0.002 Mask loss: 0.08505 RPN box loss: 0.00361 RPN score loss: 0.00242 RPN total loss: 0.00603 Total loss: 0.91748 timestamp: 1654951319.018004 iteration: 47745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.17566 L1 loss: 0.0000e+00 L2 loss: 0.61542 Learning rate: 0.002 Mask loss: 0.11148 RPN box loss: 0.02107 RPN score loss: 0.00259 RPN total loss: 0.02366 Total loss: 0.92623 timestamp: 1654951322.209658 iteration: 47750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.085 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.14484 L1 loss: 0.0000e+00 L2 loss: 0.61541 Learning rate: 0.002 Mask loss: 0.12586 RPN box loss: 0.01604 RPN score loss: 0.0031 RPN total loss: 0.01914 Total loss: 0.90525 timestamp: 1654951325.43674 iteration: 47755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06661 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.13087 L1 loss: 0.0000e+00 L2 loss: 0.6154 Learning rate: 0.002 Mask loss: 0.12241 RPN box loss: 0.02503 RPN score loss: 0.01146 RPN total loss: 0.03649 Total loss: 0.90517 timestamp: 1654951328.6301517 iteration: 47760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11814 FastRCNN class loss: 0.12297 FastRCNN total loss: 0.24112 L1 loss: 0.0000e+00 L2 loss: 0.61539 Learning rate: 0.002 Mask loss: 0.17229 RPN box loss: 0.02441 RPN score loss: 0.008 RPN total loss: 0.0324 Total loss: 1.0612 timestamp: 1654951331.8181694 iteration: 47765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05695 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.1225 L1 loss: 0.0000e+00 L2 loss: 0.61538 Learning rate: 0.002 Mask loss: 0.08945 RPN box loss: 0.00909 RPN score loss: 0.00279 RPN total loss: 0.01189 Total loss: 0.83922 timestamp: 1654951334.9842064 iteration: 47770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05122 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.11726 L1 loss: 0.0000e+00 L2 loss: 0.61538 Learning rate: 0.002 Mask loss: 0.09814 RPN box loss: 0.00952 RPN score loss: 0.00487 RPN total loss: 0.01439 Total loss: 0.84516 timestamp: 1654951338.1956022 iteration: 47775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09985 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.1519 L1 loss: 0.0000e+00 L2 loss: 0.61537 Learning rate: 0.002 Mask loss: 0.12916 RPN box loss: 0.01638 RPN score loss: 0.00546 RPN total loss: 0.02183 Total loss: 0.91826 timestamp: 1654951341.3559363 iteration: 47780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12612 FastRCNN class loss: 0.05443 FastRCNN total loss: 0.18055 L1 loss: 0.0000e+00 L2 loss: 0.61536 Learning rate: 0.002 Mask loss: 0.11765 RPN box loss: 0.01025 RPN score loss: 0.00229 RPN total loss: 0.01255 Total loss: 0.92611 timestamp: 1654951344.5778956 iteration: 47785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09255 FastRCNN class loss: 0.10645 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.61535 Learning rate: 0.002 Mask loss: 0.14629 RPN box loss: 0.0084 RPN score loss: 0.00817 RPN total loss: 0.01657 Total loss: 0.97721 timestamp: 1654951347.819094 iteration: 47790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07968 FastRCNN class loss: 0.06396 FastRCNN total loss: 0.14364 L1 loss: 0.0000e+00 L2 loss: 0.61534 Learning rate: 0.002 Mask loss: 0.16138 RPN box loss: 0.00922 RPN score loss: 0.002 RPN total loss: 0.01123 Total loss: 0.93159 timestamp: 1654951350.9994855 iteration: 47795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09408 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.16347 L1 loss: 0.0000e+00 L2 loss: 0.61534 Learning rate: 0.002 Mask loss: 0.1017 RPN box loss: 0.01516 RPN score loss: 0.00142 RPN total loss: 0.01658 Total loss: 0.89708 timestamp: 1654951354.1869795 iteration: 47800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06444 FastRCNN class loss: 0.04751 FastRCNN total loss: 0.11195 L1 loss: 0.0000e+00 L2 loss: 0.61533 Learning rate: 0.002 Mask loss: 0.09513 RPN box loss: 0.00357 RPN score loss: 0.00913 RPN total loss: 0.0127 Total loss: 0.83511 timestamp: 1654951357.4440546 iteration: 47805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12143 FastRCNN class loss: 0.05823 FastRCNN total loss: 0.17966 L1 loss: 0.0000e+00 L2 loss: 0.61532 Learning rate: 0.002 Mask loss: 0.10994 RPN box loss: 0.04084 RPN score loss: 0.0024 RPN total loss: 0.04324 Total loss: 0.94816 timestamp: 1654951360.6146688 iteration: 47810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.04415 FastRCNN total loss: 0.11879 L1 loss: 0.0000e+00 L2 loss: 0.61531 Learning rate: 0.002 Mask loss: 0.10403 RPN box loss: 0.04561 RPN score loss: 0.00795 RPN total loss: 0.05357 Total loss: 0.89169 timestamp: 1654951363.8605247 iteration: 47815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10804 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.16932 L1 loss: 0.0000e+00 L2 loss: 0.6153 Learning rate: 0.002 Mask loss: 0.10912 RPN box loss: 0.0117 RPN score loss: 0.00518 RPN total loss: 0.01688 Total loss: 0.91062 timestamp: 1654951367.0263064 iteration: 47820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.05853 FastRCNN total loss: 0.13718 L1 loss: 0.0000e+00 L2 loss: 0.61529 Learning rate: 0.002 Mask loss: 0.13228 RPN box loss: 0.01523 RPN score loss: 0.00197 RPN total loss: 0.0172 Total loss: 0.90195 timestamp: 1654951370.2708275 iteration: 47825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06426 FastRCNN class loss: 0.074 FastRCNN total loss: 0.13825 L1 loss: 0.0000e+00 L2 loss: 0.61528 Learning rate: 0.002 Mask loss: 0.17902 RPN box loss: 0.01361 RPN score loss: 0.00584 RPN total loss: 0.01945 Total loss: 0.952 timestamp: 1654951373.4622436 iteration: 47830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07981 FastRCNN class loss: 0.05884 FastRCNN total loss: 0.13865 L1 loss: 0.0000e+00 L2 loss: 0.61527 Learning rate: 0.002 Mask loss: 0.11227 RPN box loss: 0.01169 RPN score loss: 0.00218 RPN total loss: 0.01387 Total loss: 0.88007 timestamp: 1654951376.6764324 iteration: 47835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.17624 L1 loss: 0.0000e+00 L2 loss: 0.61526 Learning rate: 0.002 Mask loss: 0.1078 RPN box loss: 0.01218 RPN score loss: 0.00221 RPN total loss: 0.0144 Total loss: 0.9137 timestamp: 1654951379.8205302 iteration: 47840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.16154 L1 loss: 0.0000e+00 L2 loss: 0.61525 Learning rate: 0.002 Mask loss: 0.15211 RPN box loss: 0.01497 RPN score loss: 0.0039 RPN total loss: 0.01887 Total loss: 0.94778 timestamp: 1654951383.069662 iteration: 47845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15534 FastRCNN class loss: 0.07349 FastRCNN total loss: 0.22882 L1 loss: 0.0000e+00 L2 loss: 0.61525 Learning rate: 0.002 Mask loss: 0.11204 RPN box loss: 0.01189 RPN score loss: 0.00192 RPN total loss: 0.01381 Total loss: 0.96992 timestamp: 1654951386.2291439 iteration: 47850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10443 FastRCNN class loss: 0.07027 FastRCNN total loss: 0.17471 L1 loss: 0.0000e+00 L2 loss: 0.61524 Learning rate: 0.002 Mask loss: 0.13535 RPN box loss: 0.03941 RPN score loss: 0.01122 RPN total loss: 0.05064 Total loss: 0.97593 timestamp: 1654951389.3941822 iteration: 47855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10811 FastRCNN class loss: 0.04393 FastRCNN total loss: 0.15204 L1 loss: 0.0000e+00 L2 loss: 0.61523 Learning rate: 0.002 Mask loss: 0.10421 RPN box loss: 0.01241 RPN score loss: 0.0057 RPN total loss: 0.01811 Total loss: 0.88958 timestamp: 1654951392.569487 iteration: 47860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05015 FastRCNN class loss: 0.03802 FastRCNN total loss: 0.08817 L1 loss: 0.0000e+00 L2 loss: 0.61522 Learning rate: 0.002 Mask loss: 0.09592 RPN box loss: 0.00962 RPN score loss: 0.00426 RPN total loss: 0.01388 Total loss: 0.81318 timestamp: 1654951395.828745 iteration: 47865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13631 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.22371 L1 loss: 0.0000e+00 L2 loss: 0.61521 Learning rate: 0.002 Mask loss: 0.13781 RPN box loss: 0.02463 RPN score loss: 0.00498 RPN total loss: 0.02961 Total loss: 1.00633 timestamp: 1654951399.050224 iteration: 47870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06928 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.12785 L1 loss: 0.0000e+00 L2 loss: 0.6152 Learning rate: 0.002 Mask loss: 0.13793 RPN box loss: 0.01088 RPN score loss: 0.00354 RPN total loss: 0.01442 Total loss: 0.8954 timestamp: 1654951402.20167 iteration: 47875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06739 FastRCNN class loss: 0.04524 FastRCNN total loss: 0.11263 L1 loss: 0.0000e+00 L2 loss: 0.61519 Learning rate: 0.002 Mask loss: 0.11884 RPN box loss: 0.01915 RPN score loss: 0.00099 RPN total loss: 0.02014 Total loss: 0.8668 timestamp: 1654951405.4086258 iteration: 47880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06052 FastRCNN class loss: 0.04291 FastRCNN total loss: 0.10343 L1 loss: 0.0000e+00 L2 loss: 0.61519 Learning rate: 0.002 Mask loss: 0.14497 RPN box loss: 0.01222 RPN score loss: 0.00745 RPN total loss: 0.01967 Total loss: 0.88325 timestamp: 1654951408.5949745 iteration: 47885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08131 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.14705 L1 loss: 0.0000e+00 L2 loss: 0.61518 Learning rate: 0.002 Mask loss: 0.20765 RPN box loss: 0.01429 RPN score loss: 0.00445 RPN total loss: 0.01874 Total loss: 0.98862 timestamp: 1654951411.8206067 iteration: 47890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10192 FastRCNN class loss: 0.06812 FastRCNN total loss: 0.17004 L1 loss: 0.0000e+00 L2 loss: 0.61517 Learning rate: 0.002 Mask loss: 0.13608 RPN box loss: 0.02473 RPN score loss: 0.00257 RPN total loss: 0.0273 Total loss: 0.94859 timestamp: 1654951415.06539 iteration: 47895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0974 FastRCNN class loss: 0.0526 FastRCNN total loss: 0.15 L1 loss: 0.0000e+00 L2 loss: 0.61516 Learning rate: 0.002 Mask loss: 0.1119 RPN box loss: 0.02712 RPN score loss: 0.00525 RPN total loss: 0.03237 Total loss: 0.90943 timestamp: 1654951418.2373095 iteration: 47900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07222 FastRCNN class loss: 0.09493 FastRCNN total loss: 0.16715 L1 loss: 0.0000e+00 L2 loss: 0.61515 Learning rate: 0.002 Mask loss: 0.11992 RPN box loss: 0.00525 RPN score loss: 0.00104 RPN total loss: 0.00629 Total loss: 0.90851 timestamp: 1654951421.4658222 iteration: 47905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11043 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.20017 L1 loss: 0.0000e+00 L2 loss: 0.61514 Learning rate: 0.002 Mask loss: 0.12732 RPN box loss: 0.02238 RPN score loss: 0.00877 RPN total loss: 0.03116 Total loss: 0.97379 timestamp: 1654951424.7098362 iteration: 47910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08426 FastRCNN class loss: 0.04681 FastRCNN total loss: 0.13108 L1 loss: 0.0000e+00 L2 loss: 0.61513 Learning rate: 0.002 Mask loss: 0.10315 RPN box loss: 0.00547 RPN score loss: 0.00129 RPN total loss: 0.00676 Total loss: 0.85611 timestamp: 1654951427.9484406 iteration: 47915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10952 FastRCNN class loss: 0.05275 FastRCNN total loss: 0.16227 L1 loss: 0.0000e+00 L2 loss: 0.61512 Learning rate: 0.002 Mask loss: 0.14821 RPN box loss: 0.00813 RPN score loss: 0.00527 RPN total loss: 0.0134 Total loss: 0.93899 timestamp: 1654951431.1736076 iteration: 47920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11504 FastRCNN class loss: 0.05257 FastRCNN total loss: 0.1676 L1 loss: 0.0000e+00 L2 loss: 0.61511 Learning rate: 0.002 Mask loss: 0.10729 RPN box loss: 0.0119 RPN score loss: 0.00201 RPN total loss: 0.01391 Total loss: 0.90392 timestamp: 1654951434.3942552 iteration: 47925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0802 FastRCNN class loss: 0.05592 FastRCNN total loss: 0.13612 L1 loss: 0.0000e+00 L2 loss: 0.61511 Learning rate: 0.002 Mask loss: 0.11857 RPN box loss: 0.00701 RPN score loss: 0.00531 RPN total loss: 0.01232 Total loss: 0.88212 timestamp: 1654951437.5286372 iteration: 47930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.13777 L1 loss: 0.0000e+00 L2 loss: 0.6151 Learning rate: 0.002 Mask loss: 0.10794 RPN box loss: 0.02144 RPN score loss: 0.00191 RPN total loss: 0.02335 Total loss: 0.88416 timestamp: 1654951440.6916113 iteration: 47935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.14265 L1 loss: 0.0000e+00 L2 loss: 0.61509 Learning rate: 0.002 Mask loss: 0.10372 RPN box loss: 0.00821 RPN score loss: 0.00327 RPN total loss: 0.01148 Total loss: 0.87295 timestamp: 1654951443.9422681 iteration: 47940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05767 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.12423 L1 loss: 0.0000e+00 L2 loss: 0.61508 Learning rate: 0.002 Mask loss: 0.1097 RPN box loss: 0.0059 RPN score loss: 0.00195 RPN total loss: 0.00784 Total loss: 0.85685 timestamp: 1654951447.1268215 iteration: 47945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12142 FastRCNN class loss: 0.05642 FastRCNN total loss: 0.17784 L1 loss: 0.0000e+00 L2 loss: 0.61507 Learning rate: 0.002 Mask loss: 0.10462 RPN box loss: 0.02249 RPN score loss: 0.00192 RPN total loss: 0.02441 Total loss: 0.92195 timestamp: 1654951450.3140564 iteration: 47950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04706 FastRCNN class loss: 0.04509 FastRCNN total loss: 0.09215 L1 loss: 0.0000e+00 L2 loss: 0.61506 Learning rate: 0.002 Mask loss: 0.10865 RPN box loss: 0.00656 RPN score loss: 0.00334 RPN total loss: 0.0099 Total loss: 0.82576 timestamp: 1654951453.5186155 iteration: 47955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08058 FastRCNN class loss: 0.06231 FastRCNN total loss: 0.1429 L1 loss: 0.0000e+00 L2 loss: 0.61505 Learning rate: 0.002 Mask loss: 0.12993 RPN box loss: 0.0267 RPN score loss: 0.00854 RPN total loss: 0.03524 Total loss: 0.92312 timestamp: 1654951456.6794262 iteration: 47960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12082 FastRCNN class loss: 0.06143 FastRCNN total loss: 0.18225 L1 loss: 0.0000e+00 L2 loss: 0.61505 Learning rate: 0.002 Mask loss: 0.1314 RPN box loss: 0.06099 RPN score loss: 0.00722 RPN total loss: 0.06821 Total loss: 0.99691 timestamp: 1654951459.843494 iteration: 47965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06622 FastRCNN class loss: 0.04562 FastRCNN total loss: 0.11184 L1 loss: 0.0000e+00 L2 loss: 0.61504 Learning rate: 0.002 Mask loss: 0.08729 RPN box loss: 0.01594 RPN score loss: 0.00142 RPN total loss: 0.01736 Total loss: 0.83152 timestamp: 1654951463.0239933 iteration: 47970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10083 FastRCNN class loss: 0.04338 FastRCNN total loss: 0.14421 L1 loss: 0.0000e+00 L2 loss: 0.61503 Learning rate: 0.002 Mask loss: 0.11567 RPN box loss: 0.01625 RPN score loss: 0.00089 RPN total loss: 0.01714 Total loss: 0.89205 timestamp: 1654951466.2290766 iteration: 47975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10456 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.16714 L1 loss: 0.0000e+00 L2 loss: 0.61502 Learning rate: 0.002 Mask loss: 0.11513 RPN box loss: 0.01638 RPN score loss: 0.00615 RPN total loss: 0.02252 Total loss: 0.91981 timestamp: 1654951469.4250152 iteration: 47980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07234 FastRCNN class loss: 0.06402 FastRCNN total loss: 0.13636 L1 loss: 0.0000e+00 L2 loss: 0.61501 Learning rate: 0.002 Mask loss: 0.12053 RPN box loss: 0.0162 RPN score loss: 0.00482 RPN total loss: 0.02102 Total loss: 0.89293 timestamp: 1654951472.5899425 iteration: 47985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12477 FastRCNN class loss: 0.0825 FastRCNN total loss: 0.20727 L1 loss: 0.0000e+00 L2 loss: 0.615 Learning rate: 0.002 Mask loss: 0.13813 RPN box loss: 0.00605 RPN score loss: 0.00682 RPN total loss: 0.01286 Total loss: 0.97326 timestamp: 1654951475.8466456 iteration: 47990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.132 FastRCNN class loss: 0.09814 FastRCNN total loss: 0.23014 L1 loss: 0.0000e+00 L2 loss: 0.61499 Learning rate: 0.002 Mask loss: 0.10967 RPN box loss: 0.01044 RPN score loss: 0.00787 RPN total loss: 0.01831 Total loss: 0.97311 timestamp: 1654951479.0633726 iteration: 47995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08831 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.14939 L1 loss: 0.0000e+00 L2 loss: 0.61498 Learning rate: 0.002 Mask loss: 0.12611 RPN box loss: 0.02551 RPN score loss: 0.00594 RPN total loss: 0.03145 Total loss: 0.92192 timestamp: 1654951482.236768 iteration: 48000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0708 FastRCNN class loss: 0.04291 FastRCNN total loss: 0.11372 L1 loss: 0.0000e+00 L2 loss: 0.61497 Learning rate: 0.002 Mask loss: 0.13355 RPN box loss: 0.00896 RPN score loss: 0.00455 RPN total loss: 0.0135 Total loss: 0.87574 timestamp: 1654951485.425412 iteration: 48005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09657 FastRCNN class loss: 0.07011 FastRCNN total loss: 0.16668 L1 loss: 0.0000e+00 L2 loss: 0.61497 Learning rate: 0.002 Mask loss: 0.09 RPN box loss: 0.01417 RPN score loss: 0.00291 RPN total loss: 0.01708 Total loss: 0.88872 timestamp: 1654951488.6162293 iteration: 48010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.07315 FastRCNN total loss: 0.19713 L1 loss: 0.0000e+00 L2 loss: 0.61496 Learning rate: 0.002 Mask loss: 0.17761 RPN box loss: 0.02406 RPN score loss: 0.00147 RPN total loss: 0.02554 Total loss: 1.01523 timestamp: 1654951491.7855914 iteration: 48015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10775 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.19232 L1 loss: 0.0000e+00 L2 loss: 0.61495 Learning rate: 0.002 Mask loss: 0.08814 RPN box loss: 0.01488 RPN score loss: 0.00694 RPN total loss: 0.02182 Total loss: 0.91724 timestamp: 1654951494.9726727 iteration: 48020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07594 FastRCNN class loss: 0.06864 FastRCNN total loss: 0.14459 L1 loss: 0.0000e+00 L2 loss: 0.61494 Learning rate: 0.002 Mask loss: 0.14043 RPN box loss: 0.01329 RPN score loss: 0.00443 RPN total loss: 0.01772 Total loss: 0.91768 timestamp: 1654951498.1593864 iteration: 48025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14867 FastRCNN class loss: 0.07216 FastRCNN total loss: 0.22082 L1 loss: 0.0000e+00 L2 loss: 0.61493 Learning rate: 0.002 Mask loss: 0.11076 RPN box loss: 0.01826 RPN score loss: 0.00588 RPN total loss: 0.02415 Total loss: 0.97066 timestamp: 1654951501.36676 iteration: 48030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1312 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.2103 L1 loss: 0.0000e+00 L2 loss: 0.61492 Learning rate: 0.002 Mask loss: 0.11373 RPN box loss: 0.01 RPN score loss: 0.00848 RPN total loss: 0.01848 Total loss: 0.95743 timestamp: 1654951504.5947068 iteration: 48035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.103 FastRCNN class loss: 0.1158 FastRCNN total loss: 0.2188 L1 loss: 0.0000e+00 L2 loss: 0.61491 Learning rate: 0.002 Mask loss: 0.1701 RPN box loss: 0.0228 RPN score loss: 0.01858 RPN total loss: 0.04137 Total loss: 1.04519 timestamp: 1654951507.809376 iteration: 48040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07967 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.6149 Learning rate: 0.002 Mask loss: 0.07208 RPN box loss: 0.00391 RPN score loss: 0.00134 RPN total loss: 0.00525 Total loss: 0.83632 timestamp: 1654951511.1010396 iteration: 48045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13234 FastRCNN class loss: 0.07164 FastRCNN total loss: 0.20398 L1 loss: 0.0000e+00 L2 loss: 0.61489 Learning rate: 0.002 Mask loss: 0.14377 RPN box loss: 0.0101 RPN score loss: 0.00436 RPN total loss: 0.01446 Total loss: 0.9771 timestamp: 1654951514.2451117 iteration: 48050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07444 FastRCNN class loss: 0.05361 FastRCNN total loss: 0.12805 L1 loss: 0.0000e+00 L2 loss: 0.61488 Learning rate: 0.002 Mask loss: 0.10072 RPN box loss: 0.00501 RPN score loss: 0.0042 RPN total loss: 0.0092 Total loss: 0.85286 timestamp: 1654951517.3600934 iteration: 48055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07173 FastRCNN class loss: 0.04605 FastRCNN total loss: 0.11778 L1 loss: 0.0000e+00 L2 loss: 0.61487 Learning rate: 0.002 Mask loss: 0.13049 RPN box loss: 0.01512 RPN score loss: 0.00151 RPN total loss: 0.01663 Total loss: 0.87978 timestamp: 1654951520.5243347 iteration: 48060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06464 FastRCNN class loss: 0.07363 FastRCNN total loss: 0.13828 L1 loss: 0.0000e+00 L2 loss: 0.61487 Learning rate: 0.002 Mask loss: 0.07629 RPN box loss: 0.00935 RPN score loss: 0.00145 RPN total loss: 0.0108 Total loss: 0.84023 timestamp: 1654951523.6903465 iteration: 48065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16438 FastRCNN class loss: 0.10796 FastRCNN total loss: 0.27234 L1 loss: 0.0000e+00 L2 loss: 0.61486 Learning rate: 0.002 Mask loss: 0.1415 RPN box loss: 0.01828 RPN score loss: 0.00674 RPN total loss: 0.02502 Total loss: 1.05372 timestamp: 1654951526.9046645 iteration: 48070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.14921 L1 loss: 0.0000e+00 L2 loss: 0.61485 Learning rate: 0.002 Mask loss: 0.17132 RPN box loss: 0.01636 RPN score loss: 0.0033 RPN total loss: 0.01966 Total loss: 0.95503 timestamp: 1654951530.1502335 iteration: 48075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.14895 L1 loss: 0.0000e+00 L2 loss: 0.61484 Learning rate: 0.002 Mask loss: 0.1609 RPN box loss: 0.01572 RPN score loss: 0.00255 RPN total loss: 0.01828 Total loss: 0.94296 timestamp: 1654951533.3258994 iteration: 48080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13307 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.21884 L1 loss: 0.0000e+00 L2 loss: 0.61483 Learning rate: 0.002 Mask loss: 0.15376 RPN box loss: 0.01022 RPN score loss: 0.0048 RPN total loss: 0.01502 Total loss: 1.00246 timestamp: 1654951536.5188308 iteration: 48085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07223 FastRCNN class loss: 0.04877 FastRCNN total loss: 0.121 L1 loss: 0.0000e+00 L2 loss: 0.61482 Learning rate: 0.002 Mask loss: 0.26327 RPN box loss: 0.00533 RPN score loss: 0.00238 RPN total loss: 0.00771 Total loss: 1.0068 timestamp: 1654951539.7192533 iteration: 48090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05857 FastRCNN class loss: 0.04668 FastRCNN total loss: 0.10525 L1 loss: 0.0000e+00 L2 loss: 0.61481 Learning rate: 0.002 Mask loss: 0.10394 RPN box loss: 0.02019 RPN score loss: 0.00291 RPN total loss: 0.0231 Total loss: 0.8471 timestamp: 1654951542.9516025 iteration: 48095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05336 FastRCNN class loss: 0.06518 FastRCNN total loss: 0.11854 L1 loss: 0.0000e+00 L2 loss: 0.6148 Learning rate: 0.002 Mask loss: 0.09916 RPN box loss: 0.02459 RPN score loss: 0.00308 RPN total loss: 0.02766 Total loss: 0.86017 timestamp: 1654951546.1590793 iteration: 48100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06224 FastRCNN class loss: 0.04445 FastRCNN total loss: 0.10668 L1 loss: 0.0000e+00 L2 loss: 0.61479 Learning rate: 0.002 Mask loss: 0.12463 RPN box loss: 0.00852 RPN score loss: 0.0013 RPN total loss: 0.00982 Total loss: 0.85593 timestamp: 1654951549.332372 iteration: 48105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08781 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.16956 L1 loss: 0.0000e+00 L2 loss: 0.61478 Learning rate: 0.002 Mask loss: 0.18862 RPN box loss: 0.02726 RPN score loss: 0.00771 RPN total loss: 0.03498 Total loss: 1.00794 timestamp: 1654951552.5349994 iteration: 48110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07726 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.13383 L1 loss: 0.0000e+00 L2 loss: 0.61477 Learning rate: 0.002 Mask loss: 0.13575 RPN box loss: 0.01434 RPN score loss: 0.00288 RPN total loss: 0.01723 Total loss: 0.90158 timestamp: 1654951555.7564507 iteration: 48115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12052 FastRCNN class loss: 0.07811 FastRCNN total loss: 0.19863 L1 loss: 0.0000e+00 L2 loss: 0.61476 Learning rate: 0.002 Mask loss: 0.11772 RPN box loss: 0.02949 RPN score loss: 0.00157 RPN total loss: 0.03107 Total loss: 0.96218 timestamp: 1654951558.904902 iteration: 48120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09586 FastRCNN class loss: 0.05582 FastRCNN total loss: 0.15168 L1 loss: 0.0000e+00 L2 loss: 0.61476 Learning rate: 0.002 Mask loss: 0.12736 RPN box loss: 0.01518 RPN score loss: 0.00108 RPN total loss: 0.01626 Total loss: 0.91006 timestamp: 1654951562.1784236 iteration: 48125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13088 FastRCNN class loss: 0.1394 FastRCNN total loss: 0.27028 L1 loss: 0.0000e+00 L2 loss: 0.61475 Learning rate: 0.002 Mask loss: 0.16525 RPN box loss: 0.03773 RPN score loss: 0.01024 RPN total loss: 0.04797 Total loss: 1.09825 timestamp: 1654951565.3537948 iteration: 48130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11874 FastRCNN class loss: 0.06176 FastRCNN total loss: 0.18049 L1 loss: 0.0000e+00 L2 loss: 0.61474 Learning rate: 0.002 Mask loss: 0.08459 RPN box loss: 0.01515 RPN score loss: 0.00481 RPN total loss: 0.01997 Total loss: 0.89979 timestamp: 1654951568.5621905 iteration: 48135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1114 FastRCNN class loss: 0.04806 FastRCNN total loss: 0.15946 L1 loss: 0.0000e+00 L2 loss: 0.61473 Learning rate: 0.002 Mask loss: 0.12316 RPN box loss: 0.00807 RPN score loss: 0.00188 RPN total loss: 0.00994 Total loss: 0.90729 timestamp: 1654951571.8712986 iteration: 48140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08821 FastRCNN class loss: 0.05425 FastRCNN total loss: 0.14246 L1 loss: 0.0000e+00 L2 loss: 0.61472 Learning rate: 0.002 Mask loss: 0.11877 RPN box loss: 0.02684 RPN score loss: 0.00458 RPN total loss: 0.03142 Total loss: 0.90737 timestamp: 1654951575.0876436 iteration: 48145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.17178 L1 loss: 0.0000e+00 L2 loss: 0.61471 Learning rate: 0.002 Mask loss: 0.24028 RPN box loss: 0.02926 RPN score loss: 0.00328 RPN total loss: 0.03253 Total loss: 1.0593 timestamp: 1654951578.274347 iteration: 48150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11549 FastRCNN class loss: 0.15526 FastRCNN total loss: 0.27074 L1 loss: 0.0000e+00 L2 loss: 0.6147 Learning rate: 0.002 Mask loss: 0.14736 RPN box loss: 0.01189 RPN score loss: 0.00952 RPN total loss: 0.02141 Total loss: 1.05421 timestamp: 1654951581.472498 iteration: 48155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07712 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.12164 L1 loss: 0.0000e+00 L2 loss: 0.61469 Learning rate: 0.002 Mask loss: 0.12772 RPN box loss: 0.0084 RPN score loss: 0.0045 RPN total loss: 0.0129 Total loss: 0.87695 timestamp: 1654951584.6319218 iteration: 48160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14424 FastRCNN class loss: 0.08814 FastRCNN total loss: 0.23238 L1 loss: 0.0000e+00 L2 loss: 0.61468 Learning rate: 0.002 Mask loss: 0.12622 RPN box loss: 0.02188 RPN score loss: 0.00689 RPN total loss: 0.02878 Total loss: 1.00206 timestamp: 1654951587.802996 iteration: 48165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.081 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.12978 L1 loss: 0.0000e+00 L2 loss: 0.61467 Learning rate: 0.002 Mask loss: 0.13192 RPN box loss: 0.01413 RPN score loss: 0.00325 RPN total loss: 0.01737 Total loss: 0.89375 timestamp: 1654951591.0447783 iteration: 48170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10508 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.17124 L1 loss: 0.0000e+00 L2 loss: 0.61466 Learning rate: 0.002 Mask loss: 0.18494 RPN box loss: 0.0159 RPN score loss: 0.01953 RPN total loss: 0.03543 Total loss: 1.00627 timestamp: 1654951594.242535 iteration: 48175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.06532 FastRCNN total loss: 0.13448 L1 loss: 0.0000e+00 L2 loss: 0.61465 Learning rate: 0.002 Mask loss: 0.11305 RPN box loss: 0.01168 RPN score loss: 0.00174 RPN total loss: 0.01342 Total loss: 0.87559 timestamp: 1654951597.4235067 iteration: 48180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10996 FastRCNN class loss: 0.10436 FastRCNN total loss: 0.21432 L1 loss: 0.0000e+00 L2 loss: 0.61464 Learning rate: 0.002 Mask loss: 0.11776 RPN box loss: 0.01139 RPN score loss: 0.00745 RPN total loss: 0.01885 Total loss: 0.96557 timestamp: 1654951600.6396408 iteration: 48185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08388 FastRCNN class loss: 0.04856 FastRCNN total loss: 0.13244 L1 loss: 0.0000e+00 L2 loss: 0.61463 Learning rate: 0.002 Mask loss: 0.12281 RPN box loss: 0.00786 RPN score loss: 0.00255 RPN total loss: 0.01041 Total loss: 0.88029 timestamp: 1654951603.8438954 iteration: 48190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10624 FastRCNN class loss: 0.07587 FastRCNN total loss: 0.18211 L1 loss: 0.0000e+00 L2 loss: 0.61462 Learning rate: 0.002 Mask loss: 0.11855 RPN box loss: 0.00884 RPN score loss: 0.00308 RPN total loss: 0.01191 Total loss: 0.9272 timestamp: 1654951607.0007505 iteration: 48195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07401 FastRCNN class loss: 0.03679 FastRCNN total loss: 0.1108 L1 loss: 0.0000e+00 L2 loss: 0.61461 Learning rate: 0.002 Mask loss: 0.11679 RPN box loss: 0.0074 RPN score loss: 0.00347 RPN total loss: 0.01087 Total loss: 0.85308 timestamp: 1654951610.1698916 iteration: 48200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08021 FastRCNN class loss: 0.07076 FastRCNN total loss: 0.15096 L1 loss: 0.0000e+00 L2 loss: 0.6146 Learning rate: 0.002 Mask loss: 0.12983 RPN box loss: 0.02736 RPN score loss: 0.00834 RPN total loss: 0.0357 Total loss: 0.93109 timestamp: 1654951613.332151 iteration: 48205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09756 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.16488 L1 loss: 0.0000e+00 L2 loss: 0.61459 Learning rate: 0.002 Mask loss: 0.12966 RPN box loss: 0.02974 RPN score loss: 0.01367 RPN total loss: 0.04341 Total loss: 0.95255 timestamp: 1654951616.5213048 iteration: 48210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09699 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.16044 L1 loss: 0.0000e+00 L2 loss: 0.61458 Learning rate: 0.002 Mask loss: 0.12669 RPN box loss: 0.02635 RPN score loss: 0.00479 RPN total loss: 0.03114 Total loss: 0.93286 timestamp: 1654951619.6924686 iteration: 48215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0988 FastRCNN class loss: 0.03612 FastRCNN total loss: 0.13492 L1 loss: 0.0000e+00 L2 loss: 0.61458 Learning rate: 0.002 Mask loss: 0.07595 RPN box loss: 0.02217 RPN score loss: 0.00213 RPN total loss: 0.0243 Total loss: 0.84975 timestamp: 1654951622.8571913 iteration: 48220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09599 FastRCNN class loss: 0.06014 FastRCNN total loss: 0.15613 L1 loss: 0.0000e+00 L2 loss: 0.61457 Learning rate: 0.002 Mask loss: 0.13008 RPN box loss: 0.00979 RPN score loss: 0.00222 RPN total loss: 0.01201 Total loss: 0.91279 timestamp: 1654951626.061889 iteration: 48225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08701 FastRCNN class loss: 0.0562 FastRCNN total loss: 0.14321 L1 loss: 0.0000e+00 L2 loss: 0.61456 Learning rate: 0.002 Mask loss: 0.13465 RPN box loss: 0.00723 RPN score loss: 0.00416 RPN total loss: 0.0114 Total loss: 0.90381 timestamp: 1654951629.2272239 iteration: 48230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08161 FastRCNN class loss: 0.07427 FastRCNN total loss: 0.15588 L1 loss: 0.0000e+00 L2 loss: 0.61455 Learning rate: 0.002 Mask loss: 0.1243 RPN box loss: 0.01058 RPN score loss: 0.00235 RPN total loss: 0.01293 Total loss: 0.90767 timestamp: 1654951632.4490685 iteration: 48235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04971 FastRCNN class loss: 0.04764 FastRCNN total loss: 0.09735 L1 loss: 0.0000e+00 L2 loss: 0.61454 Learning rate: 0.002 Mask loss: 0.11281 RPN box loss: 0.01326 RPN score loss: 0.00183 RPN total loss: 0.01509 Total loss: 0.83979 timestamp: 1654951635.552479 iteration: 48240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09514 FastRCNN class loss: 0.09116 FastRCNN total loss: 0.1863 L1 loss: 0.0000e+00 L2 loss: 0.61453 Learning rate: 0.002 Mask loss: 0.17066 RPN box loss: 0.01019 RPN score loss: 0.00543 RPN total loss: 0.01561 Total loss: 0.98711 timestamp: 1654951638.7432523 iteration: 48245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.05759 FastRCNN total loss: 0.14455 L1 loss: 0.0000e+00 L2 loss: 0.61453 Learning rate: 0.002 Mask loss: 0.11067 RPN box loss: 0.01192 RPN score loss: 0.00149 RPN total loss: 0.01341 Total loss: 0.88316 timestamp: 1654951641.9233851 iteration: 48250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21152 FastRCNN class loss: 0.13637 FastRCNN total loss: 0.34788 L1 loss: 0.0000e+00 L2 loss: 0.61452 Learning rate: 0.002 Mask loss: 0.21158 RPN box loss: 0.01062 RPN score loss: 0.01151 RPN total loss: 0.02213 Total loss: 1.19611 timestamp: 1654951645.1590586 iteration: 48255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05702 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.10049 L1 loss: 0.0000e+00 L2 loss: 0.61451 Learning rate: 0.002 Mask loss: 0.08919 RPN box loss: 0.01269 RPN score loss: 0.00446 RPN total loss: 0.01715 Total loss: 0.82135 timestamp: 1654951648.3756483 iteration: 48260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11368 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.17819 L1 loss: 0.0000e+00 L2 loss: 0.6145 Learning rate: 0.002 Mask loss: 0.11984 RPN box loss: 0.01084 RPN score loss: 0.00368 RPN total loss: 0.01452 Total loss: 0.92705 timestamp: 1654951651.5263443 iteration: 48265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17464 FastRCNN class loss: 0.06708 FastRCNN total loss: 0.24172 L1 loss: 0.0000e+00 L2 loss: 0.61449 Learning rate: 0.002 Mask loss: 0.16527 RPN box loss: 0.01012 RPN score loss: 0.00424 RPN total loss: 0.01436 Total loss: 1.03585 timestamp: 1654951654.6577935 iteration: 48270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14858 FastRCNN class loss: 0.09372 FastRCNN total loss: 0.2423 L1 loss: 0.0000e+00 L2 loss: 0.61448 Learning rate: 0.002 Mask loss: 0.23887 RPN box loss: 0.01836 RPN score loss: 0.00529 RPN total loss: 0.02366 Total loss: 1.11931 timestamp: 1654951657.8586588 iteration: 48275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09948 FastRCNN class loss: 0.08946 FastRCNN total loss: 0.18894 L1 loss: 0.0000e+00 L2 loss: 0.61447 Learning rate: 0.002 Mask loss: 0.13389 RPN box loss: 0.00964 RPN score loss: 0.00449 RPN total loss: 0.01412 Total loss: 0.95142 timestamp: 1654951661.046333 iteration: 48280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12605 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.19259 L1 loss: 0.0000e+00 L2 loss: 0.61446 Learning rate: 0.002 Mask loss: 0.14907 RPN box loss: 0.01286 RPN score loss: 0.00282 RPN total loss: 0.01567 Total loss: 0.97178 timestamp: 1654951664.2626464 iteration: 48285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12291 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.18141 L1 loss: 0.0000e+00 L2 loss: 0.61445 Learning rate: 0.002 Mask loss: 0.11025 RPN box loss: 0.01213 RPN score loss: 0.00262 RPN total loss: 0.01475 Total loss: 0.92086 timestamp: 1654951667.4974737 iteration: 48290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15349 FastRCNN class loss: 0.10089 FastRCNN total loss: 0.25438 L1 loss: 0.0000e+00 L2 loss: 0.61444 Learning rate: 0.002 Mask loss: 0.20788 RPN box loss: 0.01585 RPN score loss: 0.00507 RPN total loss: 0.02092 Total loss: 1.09762 timestamp: 1654951670.6559024 iteration: 48295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14761 FastRCNN class loss: 0.1173 FastRCNN total loss: 0.26492 L1 loss: 0.0000e+00 L2 loss: 0.61443 Learning rate: 0.002 Mask loss: 0.20841 RPN box loss: 0.03651 RPN score loss: 0.00831 RPN total loss: 0.04482 Total loss: 1.13259 timestamp: 1654951673.8876865 iteration: 48300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07799 FastRCNN class loss: 0.10728 FastRCNN total loss: 0.18527 L1 loss: 0.0000e+00 L2 loss: 0.61442 Learning rate: 0.002 Mask loss: 0.1603 RPN box loss: 0.03869 RPN score loss: 0.01068 RPN total loss: 0.04937 Total loss: 1.00936 timestamp: 1654951677.0622628 iteration: 48305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15852 FastRCNN class loss: 0.07568 FastRCNN total loss: 0.2342 L1 loss: 0.0000e+00 L2 loss: 0.61441 Learning rate: 0.002 Mask loss: 0.10893 RPN box loss: 0.03845 RPN score loss: 0.00182 RPN total loss: 0.04026 Total loss: 0.9978 timestamp: 1654951680.2092552 iteration: 48310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15168 FastRCNN class loss: 0.12309 FastRCNN total loss: 0.27477 L1 loss: 0.0000e+00 L2 loss: 0.6144 Learning rate: 0.002 Mask loss: 0.19706 RPN box loss: 0.03011 RPN score loss: 0.01755 RPN total loss: 0.04766 Total loss: 1.13389 timestamp: 1654951683.394089 iteration: 48315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11393 FastRCNN class loss: 0.11627 FastRCNN total loss: 0.2302 L1 loss: 0.0000e+00 L2 loss: 0.6144 Learning rate: 0.002 Mask loss: 0.12291 RPN box loss: 0.03288 RPN score loss: 0.00986 RPN total loss: 0.04274 Total loss: 1.01025 timestamp: 1654951686.5898438 iteration: 48320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09409 FastRCNN class loss: 0.06176 FastRCNN total loss: 0.15585 L1 loss: 0.0000e+00 L2 loss: 0.61439 Learning rate: 0.002 Mask loss: 0.11389 RPN box loss: 0.01015 RPN score loss: 0.0072 RPN total loss: 0.01735 Total loss: 0.90147 timestamp: 1654951689.8271708 iteration: 48325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06631 FastRCNN class loss: 0.06311 FastRCNN total loss: 0.12942 L1 loss: 0.0000e+00 L2 loss: 0.61438 Learning rate: 0.002 Mask loss: 0.0931 RPN box loss: 0.00731 RPN score loss: 0.00238 RPN total loss: 0.00969 Total loss: 0.84659 timestamp: 1654951693.0595229 iteration: 48330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0674 FastRCNN class loss: 0.06046 FastRCNN total loss: 0.12786 L1 loss: 0.0000e+00 L2 loss: 0.61437 Learning rate: 0.002 Mask loss: 0.12043 RPN box loss: 0.00608 RPN score loss: 0.00065 RPN total loss: 0.00673 Total loss: 0.86939 timestamp: 1654951696.2705784 iteration: 48335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06688 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.13335 L1 loss: 0.0000e+00 L2 loss: 0.61436 Learning rate: 0.002 Mask loss: 0.14184 RPN box loss: 0.03259 RPN score loss: 0.0076 RPN total loss: 0.04019 Total loss: 0.92975 timestamp: 1654951699.3944886 iteration: 48340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09211 FastRCNN class loss: 0.06518 FastRCNN total loss: 0.15728 L1 loss: 0.0000e+00 L2 loss: 0.61435 Learning rate: 0.002 Mask loss: 0.14879 RPN box loss: 0.00581 RPN score loss: 0.00327 RPN total loss: 0.00909 Total loss: 0.92952 timestamp: 1654951702.600987 iteration: 48345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10106 FastRCNN class loss: 0.06681 FastRCNN total loss: 0.16787 L1 loss: 0.0000e+00 L2 loss: 0.61434 Learning rate: 0.002 Mask loss: 0.15474 RPN box loss: 0.00893 RPN score loss: 0.00247 RPN total loss: 0.01141 Total loss: 0.94836 timestamp: 1654951705.822143 iteration: 48350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12786 FastRCNN class loss: 0.06777 FastRCNN total loss: 0.19563 L1 loss: 0.0000e+00 L2 loss: 0.61433 Learning rate: 0.002 Mask loss: 0.16135 RPN box loss: 0.02281 RPN score loss: 0.00196 RPN total loss: 0.02478 Total loss: 0.99609 timestamp: 1654951709.008636 iteration: 48355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13489 FastRCNN class loss: 0.07193 FastRCNN total loss: 0.20682 L1 loss: 0.0000e+00 L2 loss: 0.61432 Learning rate: 0.002 Mask loss: 0.14648 RPN box loss: 0.0177 RPN score loss: 0.01112 RPN total loss: 0.02882 Total loss: 0.99644 timestamp: 1654951712.2089455 iteration: 48360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10314 FastRCNN class loss: 0.08014 FastRCNN total loss: 0.18327 L1 loss: 0.0000e+00 L2 loss: 0.61431 Learning rate: 0.002 Mask loss: 0.12487 RPN box loss: 0.01844 RPN score loss: 0.00083 RPN total loss: 0.01928 Total loss: 0.94173 timestamp: 1654951715.3159509 iteration: 48365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05146 FastRCNN class loss: 0.0434 FastRCNN total loss: 0.09486 L1 loss: 0.0000e+00 L2 loss: 0.6143 Learning rate: 0.002 Mask loss: 0.12257 RPN box loss: 0.01581 RPN score loss: 0.00193 RPN total loss: 0.01774 Total loss: 0.84946 timestamp: 1654951718.5093777 iteration: 48370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07768 FastRCNN class loss: 0.08584 FastRCNN total loss: 0.16351 L1 loss: 0.0000e+00 L2 loss: 0.61429 Learning rate: 0.002 Mask loss: 0.1169 RPN box loss: 0.0145 RPN score loss: 0.00284 RPN total loss: 0.01735 Total loss: 0.91205 timestamp: 1654951721.72174 iteration: 48375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.05163 FastRCNN total loss: 0.14619 L1 loss: 0.0000e+00 L2 loss: 0.61428 Learning rate: 0.002 Mask loss: 0.12057 RPN box loss: 0.00877 RPN score loss: 0.0028 RPN total loss: 0.01157 Total loss: 0.89262 timestamp: 1654951724.9361506 iteration: 48380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09719 FastRCNN class loss: 0.07624 FastRCNN total loss: 0.17344 L1 loss: 0.0000e+00 L2 loss: 0.61427 Learning rate: 0.002 Mask loss: 0.14618 RPN box loss: 0.00958 RPN score loss: 0.01377 RPN total loss: 0.02335 Total loss: 0.95724 timestamp: 1654951728.132483 iteration: 48385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16445 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.25162 L1 loss: 0.0000e+00 L2 loss: 0.61426 Learning rate: 0.002 Mask loss: 0.15839 RPN box loss: 0.00728 RPN score loss: 0.00361 RPN total loss: 0.01089 Total loss: 1.03516 timestamp: 1654951731.3323328 iteration: 48390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0724 FastRCNN class loss: 0.07162 FastRCNN total loss: 0.14403 L1 loss: 0.0000e+00 L2 loss: 0.61425 Learning rate: 0.002 Mask loss: 0.14985 RPN box loss: 0.01274 RPN score loss: 0.00753 RPN total loss: 0.02027 Total loss: 0.9284 timestamp: 1654951734.5586421 iteration: 48395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08641 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.1349 L1 loss: 0.0000e+00 L2 loss: 0.61424 Learning rate: 0.002 Mask loss: 0.08343 RPN box loss: 0.02172 RPN score loss: 0.00292 RPN total loss: 0.02465 Total loss: 0.85722 timestamp: 1654951737.7692704 iteration: 48400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14689 FastRCNN class loss: 0.09949 FastRCNN total loss: 0.24638 L1 loss: 0.0000e+00 L2 loss: 0.61423 Learning rate: 0.002 Mask loss: 0.16729 RPN box loss: 0.04097 RPN score loss: 0.01601 RPN total loss: 0.05699 Total loss: 1.0849 timestamp: 1654951741.012086 iteration: 48405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05986 FastRCNN class loss: 0.06165 FastRCNN total loss: 0.12151 L1 loss: 0.0000e+00 L2 loss: 0.61422 Learning rate: 0.002 Mask loss: 0.10143 RPN box loss: 0.00328 RPN score loss: 0.00328 RPN total loss: 0.00656 Total loss: 0.84373 timestamp: 1654951744.1708498 iteration: 48410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12179 FastRCNN class loss: 0.11766 FastRCNN total loss: 0.23945 L1 loss: 0.0000e+00 L2 loss: 0.61422 Learning rate: 0.002 Mask loss: 0.14782 RPN box loss: 0.01959 RPN score loss: 0.00827 RPN total loss: 0.02786 Total loss: 1.02935 timestamp: 1654951747.347483 iteration: 48415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14049 FastRCNN class loss: 0.11111 FastRCNN total loss: 0.2516 L1 loss: 0.0000e+00 L2 loss: 0.61421 Learning rate: 0.002 Mask loss: 0.14673 RPN box loss: 0.03959 RPN score loss: 0.00655 RPN total loss: 0.04615 Total loss: 1.05868 timestamp: 1654951750.546647 iteration: 48420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07731 FastRCNN class loss: 0.07939 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.6142 Learning rate: 0.002 Mask loss: 0.14804 RPN box loss: 0.03219 RPN score loss: 0.01138 RPN total loss: 0.04357 Total loss: 0.96251 timestamp: 1654951753.7211118 iteration: 48425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07364 FastRCNN class loss: 0.04175 FastRCNN total loss: 0.11539 L1 loss: 0.0000e+00 L2 loss: 0.61419 Learning rate: 0.002 Mask loss: 0.0708 RPN box loss: 0.01752 RPN score loss: 0.00118 RPN total loss: 0.0187 Total loss: 0.81907 timestamp: 1654951756.939797 iteration: 48430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18157 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.26007 L1 loss: 0.0000e+00 L2 loss: 0.61418 Learning rate: 0.002 Mask loss: 0.1712 RPN box loss: 0.01637 RPN score loss: 0.00421 RPN total loss: 0.02059 Total loss: 1.06603 timestamp: 1654951760.229231 iteration: 48435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11485 FastRCNN class loss: 0.07675 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 0.61417 Learning rate: 0.002 Mask loss: 0.15161 RPN box loss: 0.01789 RPN score loss: 0.01333 RPN total loss: 0.03122 Total loss: 0.9886 timestamp: 1654951763.4679065 iteration: 48440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05561 FastRCNN class loss: 0.0513 FastRCNN total loss: 0.10692 L1 loss: 0.0000e+00 L2 loss: 0.61417 Learning rate: 0.002 Mask loss: 0.11573 RPN box loss: 0.00666 RPN score loss: 0.00319 RPN total loss: 0.00985 Total loss: 0.84667 timestamp: 1654951766.711268 iteration: 48445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.05823 FastRCNN total loss: 0.17166 L1 loss: 0.0000e+00 L2 loss: 0.61416 Learning rate: 0.002 Mask loss: 0.08669 RPN box loss: 0.01822 RPN score loss: 0.00465 RPN total loss: 0.02287 Total loss: 0.89538 timestamp: 1654951769.958036 iteration: 48450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20275 FastRCNN class loss: 0.08028 FastRCNN total loss: 0.28303 L1 loss: 0.0000e+00 L2 loss: 0.61415 Learning rate: 0.002 Mask loss: 0.20345 RPN box loss: 0.03125 RPN score loss: 0.00088 RPN total loss: 0.03213 Total loss: 1.13277 timestamp: 1654951773.1714838 iteration: 48455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10902 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.1952 L1 loss: 0.0000e+00 L2 loss: 0.61414 Learning rate: 0.002 Mask loss: 0.11628 RPN box loss: 0.03471 RPN score loss: 0.01324 RPN total loss: 0.04795 Total loss: 0.97357 timestamp: 1654951776.4029179 iteration: 48460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0985 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.17356 L1 loss: 0.0000e+00 L2 loss: 0.61413 Learning rate: 0.002 Mask loss: 0.20027 RPN box loss: 0.02723 RPN score loss: 0.00609 RPN total loss: 0.03332 Total loss: 1.02129 timestamp: 1654951779.602314 iteration: 48465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05819 FastRCNN class loss: 0.04022 FastRCNN total loss: 0.0984 L1 loss: 0.0000e+00 L2 loss: 0.61412 Learning rate: 0.002 Mask loss: 0.09416 RPN box loss: 0.01109 RPN score loss: 0.00439 RPN total loss: 0.01548 Total loss: 0.82218 timestamp: 1654951782.7685454 iteration: 48470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08082 FastRCNN class loss: 0.06293 FastRCNN total loss: 0.14375 L1 loss: 0.0000e+00 L2 loss: 0.61411 Learning rate: 0.002 Mask loss: 0.16008 RPN box loss: 0.01063 RPN score loss: 0.00717 RPN total loss: 0.0178 Total loss: 0.93574 timestamp: 1654951785.9413157 iteration: 48475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07089 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.13286 L1 loss: 0.0000e+00 L2 loss: 0.61411 Learning rate: 0.002 Mask loss: 0.10416 RPN box loss: 0.01416 RPN score loss: 0.00083 RPN total loss: 0.01499 Total loss: 0.86613 timestamp: 1654951789.1009166 iteration: 48480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10867 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.17315 L1 loss: 0.0000e+00 L2 loss: 0.6141 Learning rate: 0.002 Mask loss: 0.14303 RPN box loss: 0.01426 RPN score loss: 0.01877 RPN total loss: 0.03302 Total loss: 0.96331 timestamp: 1654951792.3080122 iteration: 48485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07382 FastRCNN class loss: 0.04181 FastRCNN total loss: 0.11563 L1 loss: 0.0000e+00 L2 loss: 0.61409 Learning rate: 0.002 Mask loss: 0.11275 RPN box loss: 0.03853 RPN score loss: 0.00237 RPN total loss: 0.0409 Total loss: 0.88336 timestamp: 1654951795.6090868 iteration: 48490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06408 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.13337 L1 loss: 0.0000e+00 L2 loss: 0.61408 Learning rate: 0.002 Mask loss: 0.10102 RPN box loss: 0.0129 RPN score loss: 0.00248 RPN total loss: 0.01538 Total loss: 0.86385 timestamp: 1654951798.8171453 iteration: 48495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07223 FastRCNN class loss: 0.0543 FastRCNN total loss: 0.12653 L1 loss: 0.0000e+00 L2 loss: 0.61407 Learning rate: 0.002 Mask loss: 0.07955 RPN box loss: 0.01049 RPN score loss: 0.00177 RPN total loss: 0.01226 Total loss: 0.8324 timestamp: 1654951802.0984547 iteration: 48500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13103 FastRCNN class loss: 0.08803 FastRCNN total loss: 0.21905 L1 loss: 0.0000e+00 L2 loss: 0.61406 Learning rate: 0.002 Mask loss: 0.18483 RPN box loss: 0.03598 RPN score loss: 0.00254 RPN total loss: 0.03852 Total loss: 1.05647 timestamp: 1654951805.2391336 iteration: 48505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08475 FastRCNN class loss: 0.0598 FastRCNN total loss: 0.14455 L1 loss: 0.0000e+00 L2 loss: 0.61405 Learning rate: 0.002 Mask loss: 0.13843 RPN box loss: 0.01739 RPN score loss: 0.00617 RPN total loss: 0.02356 Total loss: 0.9206 timestamp: 1654951808.4557455 iteration: 48510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12057 FastRCNN class loss: 0.08579 FastRCNN total loss: 0.20636 L1 loss: 0.0000e+00 L2 loss: 0.61404 Learning rate: 0.002 Mask loss: 0.22551 RPN box loss: 0.01006 RPN score loss: 0.00266 RPN total loss: 0.01272 Total loss: 1.05864 timestamp: 1654951811.6541646 iteration: 48515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11215 FastRCNN class loss: 0.04203 FastRCNN total loss: 0.15418 L1 loss: 0.0000e+00 L2 loss: 0.61403 Learning rate: 0.002 Mask loss: 0.09947 RPN box loss: 0.06243 RPN score loss: 0.00134 RPN total loss: 0.06377 Total loss: 0.93145 timestamp: 1654951814.8248665 iteration: 48520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10068 FastRCNN class loss: 0.05319 FastRCNN total loss: 0.15386 L1 loss: 0.0000e+00 L2 loss: 0.61402 Learning rate: 0.002 Mask loss: 0.10987 RPN box loss: 0.00592 RPN score loss: 0.00064 RPN total loss: 0.00656 Total loss: 0.88431 timestamp: 1654951818.0760825 iteration: 48525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08813 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.13774 L1 loss: 0.0000e+00 L2 loss: 0.61402 Learning rate: 0.002 Mask loss: 0.09442 RPN box loss: 0.00964 RPN score loss: 0.00171 RPN total loss: 0.01134 Total loss: 0.85752 timestamp: 1654951821.3001406 iteration: 48530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1554 FastRCNN class loss: 0.07706 FastRCNN total loss: 0.23246 L1 loss: 0.0000e+00 L2 loss: 0.61401 Learning rate: 0.002 Mask loss: 0.12814 RPN box loss: 0.01186 RPN score loss: 0.00408 RPN total loss: 0.01594 Total loss: 0.99054 timestamp: 1654951824.5088668 iteration: 48535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07831 FastRCNN class loss: 0.1033 FastRCNN total loss: 0.18161 L1 loss: 0.0000e+00 L2 loss: 0.614 Learning rate: 0.002 Mask loss: 0.21645 RPN box loss: 0.01649 RPN score loss: 0.00706 RPN total loss: 0.02355 Total loss: 1.03562 timestamp: 1654951827.6449466 iteration: 48540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17198 FastRCNN class loss: 0.10021 FastRCNN total loss: 0.2722 L1 loss: 0.0000e+00 L2 loss: 0.61399 Learning rate: 0.002 Mask loss: 0.11026 RPN box loss: 0.0106 RPN score loss: 0.00293 RPN total loss: 0.01352 Total loss: 1.00998 timestamp: 1654951830.8070843 iteration: 48545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08777 FastRCNN class loss: 0.06175 FastRCNN total loss: 0.14953 L1 loss: 0.0000e+00 L2 loss: 0.61399 Learning rate: 0.002 Mask loss: 0.14434 RPN box loss: 0.00612 RPN score loss: 0.00453 RPN total loss: 0.01065 Total loss: 0.9185 timestamp: 1654951833.9969888 iteration: 48550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06417 FastRCNN class loss: 0.05336 FastRCNN total loss: 0.11753 L1 loss: 0.0000e+00 L2 loss: 0.61398 Learning rate: 0.002 Mask loss: 0.15591 RPN box loss: 0.01287 RPN score loss: 0.00797 RPN total loss: 0.02084 Total loss: 0.90826 timestamp: 1654951837.2658012 iteration: 48555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10977 FastRCNN class loss: 0.10091 FastRCNN total loss: 0.21068 L1 loss: 0.0000e+00 L2 loss: 0.61397 Learning rate: 0.002 Mask loss: 0.1799 RPN box loss: 0.03826 RPN score loss: 0.00915 RPN total loss: 0.0474 Total loss: 1.05196 timestamp: 1654951840.4867253 iteration: 48560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12255 FastRCNN class loss: 0.10147 FastRCNN total loss: 0.22401 L1 loss: 0.0000e+00 L2 loss: 0.61396 Learning rate: 0.002 Mask loss: 0.19673 RPN box loss: 0.02901 RPN score loss: 0.01594 RPN total loss: 0.04495 Total loss: 1.07966 timestamp: 1654951843.6779256 iteration: 48565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12777 FastRCNN class loss: 0.077 FastRCNN total loss: 0.20477 L1 loss: 0.0000e+00 L2 loss: 0.61395 Learning rate: 0.002 Mask loss: 0.12422 RPN box loss: 0.01551 RPN score loss: 0.00123 RPN total loss: 0.01674 Total loss: 0.95967 timestamp: 1654951846.8811471 iteration: 48570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07122 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.13364 L1 loss: 0.0000e+00 L2 loss: 0.61394 Learning rate: 0.002 Mask loss: 0.10233 RPN box loss: 0.02324 RPN score loss: 0.00752 RPN total loss: 0.03076 Total loss: 0.88068 timestamp: 1654951850.1259224 iteration: 48575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11522 FastRCNN class loss: 0.08259 FastRCNN total loss: 0.19781 L1 loss: 0.0000e+00 L2 loss: 0.61393 Learning rate: 0.002 Mask loss: 0.11795 RPN box loss: 0.01112 RPN score loss: 0.00618 RPN total loss: 0.0173 Total loss: 0.947 timestamp: 1654951853.2915323 iteration: 48580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10954 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.18964 L1 loss: 0.0000e+00 L2 loss: 0.61392 Learning rate: 0.002 Mask loss: 0.12962 RPN box loss: 0.00926 RPN score loss: 0.00537 RPN total loss: 0.01463 Total loss: 0.94781 timestamp: 1654951856.5705373 iteration: 48585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08765 FastRCNN class loss: 0.07836 FastRCNN total loss: 0.16601 L1 loss: 0.0000e+00 L2 loss: 0.61391 Learning rate: 0.002 Mask loss: 0.13354 RPN box loss: 0.02934 RPN score loss: 0.00896 RPN total loss: 0.03829 Total loss: 0.95176 timestamp: 1654951859.8264496 iteration: 48590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1085 FastRCNN class loss: 0.09404 FastRCNN total loss: 0.20254 L1 loss: 0.0000e+00 L2 loss: 0.6139 Learning rate: 0.002 Mask loss: 0.2022 RPN box loss: 0.02032 RPN score loss: 0.00627 RPN total loss: 0.02659 Total loss: 1.04523 timestamp: 1654951862.9781709 iteration: 48595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09277 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.1688 L1 loss: 0.0000e+00 L2 loss: 0.61389 Learning rate: 0.002 Mask loss: 0.15785 RPN box loss: 0.01309 RPN score loss: 0.00264 RPN total loss: 0.01572 Total loss: 0.95627 timestamp: 1654951866.196499 iteration: 48600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13597 FastRCNN class loss: 0.12837 FastRCNN total loss: 0.26434 L1 loss: 0.0000e+00 L2 loss: 0.61389 Learning rate: 0.002 Mask loss: 0.17572 RPN box loss: 0.02601 RPN score loss: 0.00818 RPN total loss: 0.03419 Total loss: 1.08812 timestamp: 1654951869.3651803 iteration: 48605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05553 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.12662 L1 loss: 0.0000e+00 L2 loss: 0.61388 Learning rate: 0.002 Mask loss: 0.13153 RPN box loss: 0.01313 RPN score loss: 0.00721 RPN total loss: 0.02034 Total loss: 0.89237 timestamp: 1654951872.5915892 iteration: 48610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08367 FastRCNN class loss: 0.051 FastRCNN total loss: 0.13467 L1 loss: 0.0000e+00 L2 loss: 0.61387 Learning rate: 0.002 Mask loss: 0.11132 RPN box loss: 0.0232 RPN score loss: 0.00554 RPN total loss: 0.02874 Total loss: 0.8886 timestamp: 1654951875.7521265 iteration: 48615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06866 FastRCNN class loss: 0.072 FastRCNN total loss: 0.14066 L1 loss: 0.0000e+00 L2 loss: 0.61386 Learning rate: 0.002 Mask loss: 0.13994 RPN box loss: 0.02624 RPN score loss: 0.00386 RPN total loss: 0.0301 Total loss: 0.92456 timestamp: 1654951878.96835 iteration: 48620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05442 FastRCNN class loss: 0.06202 FastRCNN total loss: 0.11645 L1 loss: 0.0000e+00 L2 loss: 0.61385 Learning rate: 0.002 Mask loss: 0.10165 RPN box loss: 0.02609 RPN score loss: 0.012 RPN total loss: 0.03809 Total loss: 0.87004 timestamp: 1654951882.1860726 iteration: 48625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11654 FastRCNN class loss: 0.06459 FastRCNN total loss: 0.18113 L1 loss: 0.0000e+00 L2 loss: 0.61384 Learning rate: 0.002 Mask loss: 0.15788 RPN box loss: 0.01442 RPN score loss: 0.00314 RPN total loss: 0.01755 Total loss: 0.97041 timestamp: 1654951885.3434737 iteration: 48630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07512 FastRCNN class loss: 0.04736 FastRCNN total loss: 0.12249 L1 loss: 0.0000e+00 L2 loss: 0.61383 Learning rate: 0.002 Mask loss: 0.09495 RPN box loss: 0.00556 RPN score loss: 0.0042 RPN total loss: 0.00976 Total loss: 0.84103 timestamp: 1654951888.521796 iteration: 48635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13518 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.22273 L1 loss: 0.0000e+00 L2 loss: 0.61382 Learning rate: 0.002 Mask loss: 0.16059 RPN box loss: 0.03846 RPN score loss: 0.01313 RPN total loss: 0.05159 Total loss: 1.04874 timestamp: 1654951891.7108064 iteration: 48640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13225 FastRCNN class loss: 0.07316 FastRCNN total loss: 0.2054 L1 loss: 0.0000e+00 L2 loss: 0.61382 Learning rate: 0.002 Mask loss: 0.14783 RPN box loss: 0.00899 RPN score loss: 0.00851 RPN total loss: 0.0175 Total loss: 0.98456 timestamp: 1654951894.914289 iteration: 48645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05385 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.10332 L1 loss: 0.0000e+00 L2 loss: 0.61381 Learning rate: 0.002 Mask loss: 0.118 RPN box loss: 0.01305 RPN score loss: 0.00747 RPN total loss: 0.02052 Total loss: 0.85565 timestamp: 1654951898.164069 iteration: 48650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08666 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.1472 L1 loss: 0.0000e+00 L2 loss: 0.6138 Learning rate: 0.002 Mask loss: 0.12174 RPN box loss: 0.016 RPN score loss: 0.00345 RPN total loss: 0.01945 Total loss: 0.9022 timestamp: 1654951901.372824 iteration: 48655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12313 FastRCNN class loss: 0.09248 FastRCNN total loss: 0.21561 L1 loss: 0.0000e+00 L2 loss: 0.61379 Learning rate: 0.002 Mask loss: 0.15339 RPN box loss: 0.0152 RPN score loss: 0.00375 RPN total loss: 0.01895 Total loss: 1.00174 timestamp: 1654951904.6305852 iteration: 48660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17383 FastRCNN class loss: 0.13165 FastRCNN total loss: 0.30549 L1 loss: 0.0000e+00 L2 loss: 0.61378 Learning rate: 0.002 Mask loss: 0.16745 RPN box loss: 0.01845 RPN score loss: 0.00713 RPN total loss: 0.02558 Total loss: 1.1123 timestamp: 1654951907.773368 iteration: 48665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06016 FastRCNN class loss: 0.04493 FastRCNN total loss: 0.10509 L1 loss: 0.0000e+00 L2 loss: 0.61377 Learning rate: 0.002 Mask loss: 0.10531 RPN box loss: 0.00597 RPN score loss: 0.00718 RPN total loss: 0.01315 Total loss: 0.83731 timestamp: 1654951911.0105586 iteration: 48670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1277 FastRCNN class loss: 0.08506 FastRCNN total loss: 0.21276 L1 loss: 0.0000e+00 L2 loss: 0.61376 Learning rate: 0.002 Mask loss: 0.18085 RPN box loss: 0.01736 RPN score loss: 0.00378 RPN total loss: 0.02114 Total loss: 1.02851 timestamp: 1654951914.2283587 iteration: 48675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10153 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.16111 L1 loss: 0.0000e+00 L2 loss: 0.61375 Learning rate: 0.002 Mask loss: 0.11079 RPN box loss: 0.02185 RPN score loss: 0.00735 RPN total loss: 0.0292 Total loss: 0.91484 timestamp: 1654951917.3737066 iteration: 48680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.03677 FastRCNN total loss: 0.11254 L1 loss: 0.0000e+00 L2 loss: 0.61374 Learning rate: 0.002 Mask loss: 0.07714 RPN box loss: 0.00835 RPN score loss: 0.00137 RPN total loss: 0.00972 Total loss: 0.81314 timestamp: 1654951920.6529577 iteration: 48685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15104 FastRCNN class loss: 0.10057 FastRCNN total loss: 0.25161 L1 loss: 0.0000e+00 L2 loss: 0.61373 Learning rate: 0.002 Mask loss: 0.14829 RPN box loss: 0.01474 RPN score loss: 0.00514 RPN total loss: 0.01988 Total loss: 1.03352 timestamp: 1654951923.7991433 iteration: 48690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05939 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.12044 L1 loss: 0.0000e+00 L2 loss: 0.61373 Learning rate: 0.002 Mask loss: 0.1334 RPN box loss: 0.00713 RPN score loss: 0.00244 RPN total loss: 0.00957 Total loss: 0.87714 timestamp: 1654951926.966405 iteration: 48695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08818 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.14037 L1 loss: 0.0000e+00 L2 loss: 0.61372 Learning rate: 0.002 Mask loss: 0.14644 RPN box loss: 0.0113 RPN score loss: 0.00177 RPN total loss: 0.01307 Total loss: 0.91361 timestamp: 1654951930.113819 iteration: 48700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10014 FastRCNN class loss: 0.0646 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.61371 Learning rate: 0.002 Mask loss: 0.15439 RPN box loss: 0.00883 RPN score loss: 0.00468 RPN total loss: 0.01351 Total loss: 0.94636 timestamp: 1654951933.2942488 iteration: 48705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11052 FastRCNN class loss: 0.06671 FastRCNN total loss: 0.17723 L1 loss: 0.0000e+00 L2 loss: 0.6137 Learning rate: 0.002 Mask loss: 0.11741 RPN box loss: 0.01217 RPN score loss: 0.00184 RPN total loss: 0.01401 Total loss: 0.92235 timestamp: 1654951936.5137086 iteration: 48710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08233 FastRCNN class loss: 0.03592 FastRCNN total loss: 0.11826 L1 loss: 0.0000e+00 L2 loss: 0.61369 Learning rate: 0.002 Mask loss: 0.1185 RPN box loss: 0.00263 RPN score loss: 0.00375 RPN total loss: 0.00638 Total loss: 0.85683 timestamp: 1654951939.6631703 iteration: 48715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08834 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.16454 L1 loss: 0.0000e+00 L2 loss: 0.61368 Learning rate: 0.002 Mask loss: 0.1323 RPN box loss: 0.01342 RPN score loss: 0.00874 RPN total loss: 0.02216 Total loss: 0.93269 timestamp: 1654951942.8343203 iteration: 48720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17716 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.26571 L1 loss: 0.0000e+00 L2 loss: 0.61367 Learning rate: 0.002 Mask loss: 0.15879 RPN box loss: 0.01273 RPN score loss: 0.00805 RPN total loss: 0.02079 Total loss: 1.05897 timestamp: 1654951946.0154626 iteration: 48725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04489 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.10706 L1 loss: 0.0000e+00 L2 loss: 0.61367 Learning rate: 0.002 Mask loss: 0.09375 RPN box loss: 0.00547 RPN score loss: 0.00234 RPN total loss: 0.00781 Total loss: 0.82229 timestamp: 1654951949.2183886 iteration: 48730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15542 FastRCNN class loss: 0.10068 FastRCNN total loss: 0.25609 L1 loss: 0.0000e+00 L2 loss: 0.61366 Learning rate: 0.002 Mask loss: 0.14902 RPN box loss: 0.04136 RPN score loss: 0.00547 RPN total loss: 0.04684 Total loss: 1.06561 timestamp: 1654951952.4047682 iteration: 48735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09463 FastRCNN class loss: 0.08826 FastRCNN total loss: 0.18289 L1 loss: 0.0000e+00 L2 loss: 0.61365 Learning rate: 0.002 Mask loss: 0.1875 RPN box loss: 0.01361 RPN score loss: 0.0121 RPN total loss: 0.02572 Total loss: 1.00976 timestamp: 1654951955.6368878 iteration: 48740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16009 FastRCNN class loss: 0.09145 FastRCNN total loss: 0.25154 L1 loss: 0.0000e+00 L2 loss: 0.61364 Learning rate: 0.002 Mask loss: 0.18817 RPN box loss: 0.0261 RPN score loss: 0.00491 RPN total loss: 0.03101 Total loss: 1.08436 timestamp: 1654951958.8167274 iteration: 48745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07267 FastRCNN class loss: 0.03856 FastRCNN total loss: 0.11123 L1 loss: 0.0000e+00 L2 loss: 0.61363 Learning rate: 0.002 Mask loss: 0.11923 RPN box loss: 0.00591 RPN score loss: 0.00305 RPN total loss: 0.00896 Total loss: 0.85305 timestamp: 1654951961.9512937 iteration: 48750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06678 FastRCNN class loss: 0.07661 FastRCNN total loss: 0.1434 L1 loss: 0.0000e+00 L2 loss: 0.61362 Learning rate: 0.002 Mask loss: 0.18758 RPN box loss: 0.02132 RPN score loss: 0.01226 RPN total loss: 0.03358 Total loss: 0.97818 timestamp: 1654951965.195653 iteration: 48755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07548 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.14915 L1 loss: 0.0000e+00 L2 loss: 0.61361 Learning rate: 0.002 Mask loss: 0.11494 RPN box loss: 0.00721 RPN score loss: 0.00156 RPN total loss: 0.00877 Total loss: 0.88647 timestamp: 1654951968.4416761 iteration: 48760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08294 FastRCNN class loss: 0.03753 FastRCNN total loss: 0.12047 L1 loss: 0.0000e+00 L2 loss: 0.6136 Learning rate: 0.002 Mask loss: 0.11481 RPN box loss: 0.00601 RPN score loss: 0.00093 RPN total loss: 0.00694 Total loss: 0.85583 timestamp: 1654951971.6522784 iteration: 48765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11575 FastRCNN class loss: 0.12099 FastRCNN total loss: 0.23674 L1 loss: 0.0000e+00 L2 loss: 0.61359 Learning rate: 0.002 Mask loss: 0.15443 RPN box loss: 0.02208 RPN score loss: 0.00441 RPN total loss: 0.02649 Total loss: 1.03126 timestamp: 1654951974.7878327 iteration: 48770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07 FastRCNN class loss: 0.04917 FastRCNN total loss: 0.11916 L1 loss: 0.0000e+00 L2 loss: 0.61358 Learning rate: 0.002 Mask loss: 0.09695 RPN box loss: 0.01786 RPN score loss: 0.00578 RPN total loss: 0.02363 Total loss: 0.85333 timestamp: 1654951977.9949453 iteration: 48775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14732 FastRCNN class loss: 0.11142 FastRCNN total loss: 0.25874 L1 loss: 0.0000e+00 L2 loss: 0.61357 Learning rate: 0.002 Mask loss: 0.17106 RPN box loss: 0.03263 RPN score loss: 0.00995 RPN total loss: 0.04258 Total loss: 1.08594 timestamp: 1654951981.2239594 iteration: 48780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06674 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.12523 L1 loss: 0.0000e+00 L2 loss: 0.61356 Learning rate: 0.002 Mask loss: 0.08749 RPN box loss: 0.00519 RPN score loss: 0.00205 RPN total loss: 0.00724 Total loss: 0.83352 timestamp: 1654951984.4433322 iteration: 48785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.05692 FastRCNN total loss: 0.1179 L1 loss: 0.0000e+00 L2 loss: 0.61355 Learning rate: 0.002 Mask loss: 0.08153 RPN box loss: 0.03441 RPN score loss: 0.00496 RPN total loss: 0.03937 Total loss: 0.85235 timestamp: 1654951987.6016357 iteration: 48790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10332 FastRCNN class loss: 0.07467 FastRCNN total loss: 0.17799 L1 loss: 0.0000e+00 L2 loss: 0.61354 Learning rate: 0.002 Mask loss: 0.15886 RPN box loss: 0.01653 RPN score loss: 0.00714 RPN total loss: 0.02368 Total loss: 0.97406 timestamp: 1654951990.7587562 iteration: 48795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07237 FastRCNN class loss: 0.06041 FastRCNN total loss: 0.13279 L1 loss: 0.0000e+00 L2 loss: 0.61353 Learning rate: 0.002 Mask loss: 0.14267 RPN box loss: 0.04409 RPN score loss: 0.0097 RPN total loss: 0.05379 Total loss: 0.94278 timestamp: 1654951993.9423614 iteration: 48800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13826 FastRCNN class loss: 0.06858 FastRCNN total loss: 0.20683 L1 loss: 0.0000e+00 L2 loss: 0.61352 Learning rate: 0.002 Mask loss: 0.10123 RPN box loss: 0.0122 RPN score loss: 0.00519 RPN total loss: 0.01739 Total loss: 0.93897 timestamp: 1654951997.1549594 iteration: 48805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12055 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.19352 L1 loss: 0.0000e+00 L2 loss: 0.61351 Learning rate: 0.002 Mask loss: 0.13431 RPN box loss: 0.01112 RPN score loss: 0.00423 RPN total loss: 0.01535 Total loss: 0.9567 timestamp: 1654952000.2332852 iteration: 48810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07817 FastRCNN class loss: 0.05256 FastRCNN total loss: 0.13073 L1 loss: 0.0000e+00 L2 loss: 0.61351 Learning rate: 0.002 Mask loss: 0.15182 RPN box loss: 0.00608 RPN score loss: 0.00307 RPN total loss: 0.00916 Total loss: 0.90521 timestamp: 1654952003.385581 iteration: 48815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09538 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.17065 L1 loss: 0.0000e+00 L2 loss: 0.6135 Learning rate: 0.002 Mask loss: 0.17233 RPN box loss: 0.02144 RPN score loss: 0.01196 RPN total loss: 0.0334 Total loss: 0.98989 timestamp: 1654952006.636348 iteration: 48820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08446 FastRCNN class loss: 0.12886 FastRCNN total loss: 0.21332 L1 loss: 0.0000e+00 L2 loss: 0.61349 Learning rate: 0.002 Mask loss: 0.17928 RPN box loss: 0.0207 RPN score loss: 0.02605 RPN total loss: 0.04675 Total loss: 1.05285 timestamp: 1654952009.8972528 iteration: 48825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.08087 FastRCNN total loss: 0.17066 L1 loss: 0.0000e+00 L2 loss: 0.61348 Learning rate: 0.002 Mask loss: 0.13581 RPN box loss: 0.00312 RPN score loss: 0.0043 RPN total loss: 0.00741 Total loss: 0.92737 timestamp: 1654952013.148565 iteration: 48830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07426 FastRCNN class loss: 0.05011 FastRCNN total loss: 0.12437 L1 loss: 0.0000e+00 L2 loss: 0.61347 Learning rate: 0.002 Mask loss: 0.13874 RPN box loss: 0.01101 RPN score loss: 0.00041 RPN total loss: 0.01143 Total loss: 0.888 timestamp: 1654952016.3219256 iteration: 48835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06881 FastRCNN class loss: 0.068 FastRCNN total loss: 0.13682 L1 loss: 0.0000e+00 L2 loss: 0.61346 Learning rate: 0.002 Mask loss: 0.15879 RPN box loss: 0.01102 RPN score loss: 0.00262 RPN total loss: 0.01364 Total loss: 0.9227 timestamp: 1654952019.4939735 iteration: 48840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11129 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.16785 L1 loss: 0.0000e+00 L2 loss: 0.61345 Learning rate: 0.002 Mask loss: 0.13166 RPN box loss: 0.01485 RPN score loss: 0.00716 RPN total loss: 0.02201 Total loss: 0.93497 timestamp: 1654952022.6376216 iteration: 48845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07284 FastRCNN class loss: 0.08125 FastRCNN total loss: 0.15409 L1 loss: 0.0000e+00 L2 loss: 0.61344 Learning rate: 0.002 Mask loss: 0.15742 RPN box loss: 0.02334 RPN score loss: 0.00478 RPN total loss: 0.02812 Total loss: 0.95307 timestamp: 1654952025.8674943 iteration: 48850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12987 FastRCNN class loss: 0.06267 FastRCNN total loss: 0.19254 L1 loss: 0.0000e+00 L2 loss: 0.61343 Learning rate: 0.002 Mask loss: 0.08858 RPN box loss: 0.03839 RPN score loss: 0.00368 RPN total loss: 0.04207 Total loss: 0.93662 timestamp: 1654952029.049888 iteration: 48855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15458 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.21945 L1 loss: 0.0000e+00 L2 loss: 0.61342 Learning rate: 0.002 Mask loss: 0.1318 RPN box loss: 0.02022 RPN score loss: 0.01279 RPN total loss: 0.03301 Total loss: 0.99768 timestamp: 1654952032.280165 iteration: 48860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07978 FastRCNN class loss: 0.06064 FastRCNN total loss: 0.14042 L1 loss: 0.0000e+00 L2 loss: 0.61341 Learning rate: 0.002 Mask loss: 0.15382 RPN box loss: 0.01276 RPN score loss: 0.00357 RPN total loss: 0.01633 Total loss: 0.92398 timestamp: 1654952035.4793818 iteration: 48865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10471 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.1476 L1 loss: 0.0000e+00 L2 loss: 0.61341 Learning rate: 0.002 Mask loss: 0.16563 RPN box loss: 0.01431 RPN score loss: 0.00191 RPN total loss: 0.01622 Total loss: 0.94285 timestamp: 1654952038.6497743 iteration: 48870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13174 FastRCNN class loss: 0.12736 FastRCNN total loss: 0.2591 L1 loss: 0.0000e+00 L2 loss: 0.6134 Learning rate: 0.002 Mask loss: 0.15037 RPN box loss: 0.03635 RPN score loss: 0.00752 RPN total loss: 0.04387 Total loss: 1.06674 timestamp: 1654952041.9027445 iteration: 48875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0676 FastRCNN class loss: 0.04171 FastRCNN total loss: 0.10931 L1 loss: 0.0000e+00 L2 loss: 0.61339 Learning rate: 0.002 Mask loss: 0.10021 RPN box loss: 0.01235 RPN score loss: 0.00126 RPN total loss: 0.01361 Total loss: 0.83652 timestamp: 1654952045.0711024 iteration: 48880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09856 FastRCNN class loss: 0.13706 FastRCNN total loss: 0.23562 L1 loss: 0.0000e+00 L2 loss: 0.61338 Learning rate: 0.002 Mask loss: 0.16599 RPN box loss: 0.02595 RPN score loss: 0.00937 RPN total loss: 0.03532 Total loss: 1.05031 timestamp: 1654952048.2618492 iteration: 48885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1101 FastRCNN class loss: 0.04482 FastRCNN total loss: 0.15491 L1 loss: 0.0000e+00 L2 loss: 0.61337 Learning rate: 0.002 Mask loss: 0.12749 RPN box loss: 0.00781 RPN score loss: 0.00523 RPN total loss: 0.01304 Total loss: 0.90882 timestamp: 1654952051.4645228 iteration: 48890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08039 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.14305 L1 loss: 0.0000e+00 L2 loss: 0.61337 Learning rate: 0.002 Mask loss: 0.13622 RPN box loss: 0.0126 RPN score loss: 0.00175 RPN total loss: 0.01435 Total loss: 0.90697 timestamp: 1654952054.7007234 iteration: 48895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10888 FastRCNN class loss: 0.06719 FastRCNN total loss: 0.17607 L1 loss: 0.0000e+00 L2 loss: 0.61336 Learning rate: 0.002 Mask loss: 0.13228 RPN box loss: 0.02443 RPN score loss: 0.0072 RPN total loss: 0.03162 Total loss: 0.95333 timestamp: 1654952057.850779 iteration: 48900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08237 FastRCNN class loss: 0.07977 FastRCNN total loss: 0.16215 L1 loss: 0.0000e+00 L2 loss: 0.61335 Learning rate: 0.002 Mask loss: 0.10734 RPN box loss: 0.00623 RPN score loss: 0.00528 RPN total loss: 0.01151 Total loss: 0.89435 timestamp: 1654952061.0845966 iteration: 48905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09581 FastRCNN class loss: 0.08953 FastRCNN total loss: 0.18534 L1 loss: 0.0000e+00 L2 loss: 0.61334 Learning rate: 0.002 Mask loss: 0.12353 RPN box loss: 0.01291 RPN score loss: 0.00728 RPN total loss: 0.02018 Total loss: 0.9424 timestamp: 1654952064.2444856 iteration: 48910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10092 FastRCNN class loss: 0.10269 FastRCNN total loss: 0.20361 L1 loss: 0.0000e+00 L2 loss: 0.61333 Learning rate: 0.002 Mask loss: 0.15434 RPN box loss: 0.03492 RPN score loss: 0.02242 RPN total loss: 0.05734 Total loss: 1.02861 timestamp: 1654952067.4120746 iteration: 48915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16349 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 0.61332 Learning rate: 0.002 Mask loss: 0.13622 RPN box loss: 0.01244 RPN score loss: 0.00741 RPN total loss: 0.01985 Total loss: 0.99615 timestamp: 1654952070.718531 iteration: 48920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10589 FastRCNN class loss: 0.09006 FastRCNN total loss: 0.19595 L1 loss: 0.0000e+00 L2 loss: 0.61331 Learning rate: 0.002 Mask loss: 0.11471 RPN box loss: 0.02064 RPN score loss: 0.00272 RPN total loss: 0.02336 Total loss: 0.94733 timestamp: 1654952073.9507322 iteration: 48925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05405 FastRCNN class loss: 0.04512 FastRCNN total loss: 0.09917 L1 loss: 0.0000e+00 L2 loss: 0.6133 Learning rate: 0.002 Mask loss: 0.10259 RPN box loss: 0.00397 RPN score loss: 0.00182 RPN total loss: 0.00579 Total loss: 0.82085 timestamp: 1654952077.068285 iteration: 48930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05882 FastRCNN class loss: 0.06374 FastRCNN total loss: 0.12256 L1 loss: 0.0000e+00 L2 loss: 0.61329 Learning rate: 0.002 Mask loss: 0.08684 RPN box loss: 0.01395 RPN score loss: 0.0044 RPN total loss: 0.01835 Total loss: 0.84104 timestamp: 1654952080.2403827 iteration: 48935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14372 FastRCNN class loss: 0.09809 FastRCNN total loss: 0.24181 L1 loss: 0.0000e+00 L2 loss: 0.61328 Learning rate: 0.002 Mask loss: 0.20078 RPN box loss: 0.02874 RPN score loss: 0.01023 RPN total loss: 0.03897 Total loss: 1.09485 timestamp: 1654952083.3075638 iteration: 48940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06769 FastRCNN class loss: 0.08869 FastRCNN total loss: 0.15639 L1 loss: 0.0000e+00 L2 loss: 0.61327 Learning rate: 0.002 Mask loss: 0.12234 RPN box loss: 0.03152 RPN score loss: 0.0015 RPN total loss: 0.03302 Total loss: 0.92502 timestamp: 1654952086.5587811 iteration: 48945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10844 FastRCNN class loss: 0.08066 FastRCNN total loss: 0.1891 L1 loss: 0.0000e+00 L2 loss: 0.61326 Learning rate: 0.002 Mask loss: 0.22844 RPN box loss: 0.0111 RPN score loss: 0.0029 RPN total loss: 0.014 Total loss: 1.0448 timestamp: 1654952089.8477986 iteration: 48950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06186 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.13175 L1 loss: 0.0000e+00 L2 loss: 0.61325 Learning rate: 0.002 Mask loss: 0.12795 RPN box loss: 0.01196 RPN score loss: 0.00918 RPN total loss: 0.02114 Total loss: 0.89409 timestamp: 1654952093.0576246 iteration: 48955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07003 FastRCNN class loss: 0.07869 FastRCNN total loss: 0.14871 L1 loss: 0.0000e+00 L2 loss: 0.61324 Learning rate: 0.002 Mask loss: 0.12393 RPN box loss: 0.00584 RPN score loss: 0.00374 RPN total loss: 0.00958 Total loss: 0.89547 timestamp: 1654952096.2375212 iteration: 48960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12719 FastRCNN class loss: 0.1087 FastRCNN total loss: 0.23589 L1 loss: 0.0000e+00 L2 loss: 0.61324 Learning rate: 0.002 Mask loss: 0.12778 RPN box loss: 0.0262 RPN score loss: 0.00451 RPN total loss: 0.03071 Total loss: 1.00761 timestamp: 1654952099.4406908 iteration: 48965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11211 FastRCNN class loss: 0.06334 FastRCNN total loss: 0.17546 L1 loss: 0.0000e+00 L2 loss: 0.61323 Learning rate: 0.002 Mask loss: 0.12784 RPN box loss: 0.02667 RPN score loss: 0.00372 RPN total loss: 0.0304 Total loss: 0.94693 timestamp: 1654952102.6330836 iteration: 48970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10321 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.1599 L1 loss: 0.0000e+00 L2 loss: 0.61322 Learning rate: 0.002 Mask loss: 0.13493 RPN box loss: 0.01649 RPN score loss: 0.00165 RPN total loss: 0.01814 Total loss: 0.92618 timestamp: 1654952105.844127 iteration: 48975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10877 FastRCNN class loss: 0.10421 FastRCNN total loss: 0.21298 L1 loss: 0.0000e+00 L2 loss: 0.61321 Learning rate: 0.002 Mask loss: 0.13502 RPN box loss: 0.01182 RPN score loss: 0.00221 RPN total loss: 0.01403 Total loss: 0.97524 timestamp: 1654952108.9781284 iteration: 48980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08648 FastRCNN class loss: 0.04902 FastRCNN total loss: 0.1355 L1 loss: 0.0000e+00 L2 loss: 0.6132 Learning rate: 0.002 Mask loss: 0.08985 RPN box loss: 0.00934 RPN score loss: 0.00298 RPN total loss: 0.01232 Total loss: 0.85087 timestamp: 1654952112.2451026 iteration: 48985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10037 FastRCNN class loss: 0.0506 FastRCNN total loss: 0.15097 L1 loss: 0.0000e+00 L2 loss: 0.6132 Learning rate: 0.002 Mask loss: 0.08754 RPN box loss: 0.01556 RPN score loss: 0.00222 RPN total loss: 0.01778 Total loss: 0.86948 timestamp: 1654952115.5245676 iteration: 48990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08791 FastRCNN class loss: 0.06314 FastRCNN total loss: 0.15105 L1 loss: 0.0000e+00 L2 loss: 0.61319 Learning rate: 0.002 Mask loss: 0.1537 RPN box loss: 0.00734 RPN score loss: 0.00379 RPN total loss: 0.01113 Total loss: 0.92908 timestamp: 1654952118.7553015 iteration: 48995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08155 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.15412 L1 loss: 0.0000e+00 L2 loss: 0.61318 Learning rate: 0.002 Mask loss: 0.11285 RPN box loss: 0.01279 RPN score loss: 0.01222 RPN total loss: 0.025 Total loss: 0.90515 timestamp: 1654952122.0041013 iteration: 49000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08195 FastRCNN class loss: 0.03219 FastRCNN total loss: 0.11414 L1 loss: 0.0000e+00 L2 loss: 0.61317 Learning rate: 0.002 Mask loss: 0.09753 RPN box loss: 0.01274 RPN score loss: 0.00227 RPN total loss: 0.01501 Total loss: 0.83985 timestamp: 1654952125.1723998 iteration: 49005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14371 FastRCNN class loss: 0.08989 FastRCNN total loss: 0.23361 L1 loss: 0.0000e+00 L2 loss: 0.61316 Learning rate: 0.002 Mask loss: 0.16138 RPN box loss: 0.00975 RPN score loss: 0.00603 RPN total loss: 0.01578 Total loss: 1.02391 timestamp: 1654952128.356201 iteration: 49010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20095 FastRCNN class loss: 0.11956 FastRCNN total loss: 0.32051 L1 loss: 0.0000e+00 L2 loss: 0.61315 Learning rate: 0.002 Mask loss: 0.11671 RPN box loss: 0.01133 RPN score loss: 0.00927 RPN total loss: 0.0206 Total loss: 1.07097 timestamp: 1654952131.5064409 iteration: 49015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09266 FastRCNN class loss: 0.07944 FastRCNN total loss: 0.17209 L1 loss: 0.0000e+00 L2 loss: 0.61314 Learning rate: 0.002 Mask loss: 0.16055 RPN box loss: 0.01455 RPN score loss: 0.00457 RPN total loss: 0.01912 Total loss: 0.9649 timestamp: 1654952134.720573 iteration: 49020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06509 FastRCNN class loss: 0.04655 FastRCNN total loss: 0.11163 L1 loss: 0.0000e+00 L2 loss: 0.61313 Learning rate: 0.002 Mask loss: 0.14464 RPN box loss: 0.02857 RPN score loss: 0.00206 RPN total loss: 0.03064 Total loss: 0.90004 timestamp: 1654952137.9184542 iteration: 49025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11889 FastRCNN class loss: 0.09353 FastRCNN total loss: 0.21242 L1 loss: 0.0000e+00 L2 loss: 0.61313 Learning rate: 0.002 Mask loss: 0.13549 RPN box loss: 0.0138 RPN score loss: 0.00229 RPN total loss: 0.01609 Total loss: 0.97712 timestamp: 1654952141.1529486 iteration: 49030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07066 FastRCNN class loss: 0.04383 FastRCNN total loss: 0.11449 L1 loss: 0.0000e+00 L2 loss: 0.61312 Learning rate: 0.002 Mask loss: 0.10755 RPN box loss: 0.01106 RPN score loss: 0.00148 RPN total loss: 0.01254 Total loss: 0.8477 timestamp: 1654952144.3919017 iteration: 49035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19402 FastRCNN class loss: 0.17164 FastRCNN total loss: 0.36566 L1 loss: 0.0000e+00 L2 loss: 0.61311 Learning rate: 0.002 Mask loss: 0.22223 RPN box loss: 0.02937 RPN score loss: 0.00426 RPN total loss: 0.03364 Total loss: 1.23463 timestamp: 1654952147.6817625 iteration: 49040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14349 FastRCNN class loss: 0.14571 FastRCNN total loss: 0.2892 L1 loss: 0.0000e+00 L2 loss: 0.61309 Learning rate: 0.002 Mask loss: 0.16231 RPN box loss: 0.0136 RPN score loss: 0.00494 RPN total loss: 0.01853 Total loss: 1.08314 timestamp: 1654952150.8713355 iteration: 49045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15808 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.23007 L1 loss: 0.0000e+00 L2 loss: 0.61309 Learning rate: 0.002 Mask loss: 0.16452 RPN box loss: 0.0238 RPN score loss: 0.00572 RPN total loss: 0.02953 Total loss: 1.0372 timestamp: 1654952154.0836816 iteration: 49050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10134 FastRCNN class loss: 0.10301 FastRCNN total loss: 0.20435 L1 loss: 0.0000e+00 L2 loss: 0.61308 Learning rate: 0.002 Mask loss: 0.17811 RPN box loss: 0.02028 RPN score loss: 0.00421 RPN total loss: 0.02449 Total loss: 1.02003 timestamp: 1654952157.2965062 iteration: 49055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07292 FastRCNN class loss: 0.09953 FastRCNN total loss: 0.17245 L1 loss: 0.0000e+00 L2 loss: 0.61307 Learning rate: 0.002 Mask loss: 0.11796 RPN box loss: 0.00948 RPN score loss: 0.00117 RPN total loss: 0.01066 Total loss: 0.91414 timestamp: 1654952160.5060503 iteration: 49060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10059 FastRCNN class loss: 0.10027 FastRCNN total loss: 0.20086 L1 loss: 0.0000e+00 L2 loss: 0.61306 Learning rate: 0.002 Mask loss: 0.12101 RPN box loss: 0.01872 RPN score loss: 0.00924 RPN total loss: 0.02796 Total loss: 0.96289 timestamp: 1654952163.7002501 iteration: 49065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12669 FastRCNN class loss: 0.08494 FastRCNN total loss: 0.21163 L1 loss: 0.0000e+00 L2 loss: 0.61305 Learning rate: 0.002 Mask loss: 0.11252 RPN box loss: 0.02405 RPN score loss: 0.00232 RPN total loss: 0.02636 Total loss: 0.96356 timestamp: 1654952166.9396079 iteration: 49070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.16443 L1 loss: 0.0000e+00 L2 loss: 0.61304 Learning rate: 0.002 Mask loss: 0.11829 RPN box loss: 0.01331 RPN score loss: 0.00164 RPN total loss: 0.01495 Total loss: 0.91072 timestamp: 1654952170.1805127 iteration: 49075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.0736 FastRCNN total loss: 0.19609 L1 loss: 0.0000e+00 L2 loss: 0.61303 Learning rate: 0.002 Mask loss: 0.13001 RPN box loss: 0.02826 RPN score loss: 0.00378 RPN total loss: 0.03204 Total loss: 0.97117 timestamp: 1654952173.4879026 iteration: 49080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07446 FastRCNN class loss: 0.05714 FastRCNN total loss: 0.1316 L1 loss: 0.0000e+00 L2 loss: 0.61302 Learning rate: 0.002 Mask loss: 0.11694 RPN box loss: 0.00561 RPN score loss: 0.00778 RPN total loss: 0.0134 Total loss: 0.87496 timestamp: 1654952176.7327213 iteration: 49085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14418 FastRCNN class loss: 0.04812 FastRCNN total loss: 0.19231 L1 loss: 0.0000e+00 L2 loss: 0.61302 Learning rate: 0.002 Mask loss: 0.12775 RPN box loss: 0.04162 RPN score loss: 0.00495 RPN total loss: 0.04657 Total loss: 0.97964 timestamp: 1654952179.941785 iteration: 49090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07052 FastRCNN class loss: 0.04816 FastRCNN total loss: 0.11868 L1 loss: 0.0000e+00 L2 loss: 0.61301 Learning rate: 0.002 Mask loss: 0.12584 RPN box loss: 0.02277 RPN score loss: 0.00148 RPN total loss: 0.02425 Total loss: 0.88179 timestamp: 1654952183.1706216 iteration: 49095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12225 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.19006 L1 loss: 0.0000e+00 L2 loss: 0.61301 Learning rate: 0.002 Mask loss: 0.08068 RPN box loss: 0.00902 RPN score loss: 0.00101 RPN total loss: 0.01003 Total loss: 0.89377 timestamp: 1654952186.4586833 iteration: 49100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07198 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.13133 L1 loss: 0.0000e+00 L2 loss: 0.613 Learning rate: 0.002 Mask loss: 0.09158 RPN box loss: 0.00481 RPN score loss: 0.00349 RPN total loss: 0.0083 Total loss: 0.8442 timestamp: 1654952189.6651433 iteration: 49105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11593 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.19017 L1 loss: 0.0000e+00 L2 loss: 0.61299 Learning rate: 0.002 Mask loss: 0.17114 RPN box loss: 0.0587 RPN score loss: 0.00532 RPN total loss: 0.06402 Total loss: 1.03832 timestamp: 1654952192.8412173 iteration: 49110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09227 FastRCNN class loss: 0.11288 FastRCNN total loss: 0.20515 L1 loss: 0.0000e+00 L2 loss: 0.61298 Learning rate: 0.002 Mask loss: 0.13805 RPN box loss: 0.03969 RPN score loss: 0.00969 RPN total loss: 0.04938 Total loss: 1.00556 timestamp: 1654952196.158175 iteration: 49115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08836 FastRCNN class loss: 0.08049 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.61297 Learning rate: 0.002 Mask loss: 0.11075 RPN box loss: 0.02219 RPN score loss: 0.00102 RPN total loss: 0.0232 Total loss: 0.91577 timestamp: 1654952199.388941 iteration: 49120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07741 FastRCNN class loss: 0.05126 FastRCNN total loss: 0.12868 L1 loss: 0.0000e+00 L2 loss: 0.61296 Learning rate: 0.002 Mask loss: 0.11965 RPN box loss: 0.0112 RPN score loss: 0.00211 RPN total loss: 0.01331 Total loss: 0.87459 timestamp: 1654952202.604438 iteration: 49125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08899 FastRCNN class loss: 0.03914 FastRCNN total loss: 0.12813 L1 loss: 0.0000e+00 L2 loss: 0.61295 Learning rate: 0.002 Mask loss: 0.11405 RPN box loss: 0.00817 RPN score loss: 0.00213 RPN total loss: 0.0103 Total loss: 0.86543 timestamp: 1654952205.7993164 iteration: 49130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.0802 FastRCNN total loss: 0.16788 L1 loss: 0.0000e+00 L2 loss: 0.61294 Learning rate: 0.002 Mask loss: 0.18245 RPN box loss: 0.01266 RPN score loss: 0.01083 RPN total loss: 0.02348 Total loss: 0.98675 timestamp: 1654952208.93725 iteration: 49135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09159 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.16404 L1 loss: 0.0000e+00 L2 loss: 0.61293 Learning rate: 0.002 Mask loss: 0.14655 RPN box loss: 0.01817 RPN score loss: 0.00353 RPN total loss: 0.0217 Total loss: 0.94522 timestamp: 1654952212.1575828 iteration: 49140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09584 FastRCNN class loss: 0.0706 FastRCNN total loss: 0.16645 L1 loss: 0.0000e+00 L2 loss: 0.61292 Learning rate: 0.002 Mask loss: 0.11642 RPN box loss: 0.01377 RPN score loss: 0.00226 RPN total loss: 0.01603 Total loss: 0.91182 timestamp: 1654952215.3583105 iteration: 49145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1083 FastRCNN class loss: 0.07402 FastRCNN total loss: 0.18233 L1 loss: 0.0000e+00 L2 loss: 0.61292 Learning rate: 0.002 Mask loss: 0.18249 RPN box loss: 0.01741 RPN score loss: 0.00337 RPN total loss: 0.02078 Total loss: 0.99852 timestamp: 1654952218.5295818 iteration: 49150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09637 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.16246 L1 loss: 0.0000e+00 L2 loss: 0.61291 Learning rate: 0.002 Mask loss: 0.19396 RPN box loss: 0.00781 RPN score loss: 0.00561 RPN total loss: 0.01342 Total loss: 0.98275 timestamp: 1654952221.7198925 iteration: 49155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10489 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.17356 L1 loss: 0.0000e+00 L2 loss: 0.6129 Learning rate: 0.002 Mask loss: 0.13075 RPN box loss: 0.0086 RPN score loss: 0.00084 RPN total loss: 0.00943 Total loss: 0.92664 timestamp: 1654952224.920225 iteration: 49160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0799 FastRCNN class loss: 0.05443 FastRCNN total loss: 0.13434 L1 loss: 0.0000e+00 L2 loss: 0.61289 Learning rate: 0.002 Mask loss: 0.1497 RPN box loss: 0.00719 RPN score loss: 0.00209 RPN total loss: 0.00927 Total loss: 0.90621 timestamp: 1654952228.1242964 iteration: 49165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10989 FastRCNN class loss: 0.05947 FastRCNN total loss: 0.16936 L1 loss: 0.0000e+00 L2 loss: 0.61288 Learning rate: 0.002 Mask loss: 0.12285 RPN box loss: 0.02429 RPN score loss: 0.01321 RPN total loss: 0.03749 Total loss: 0.94259 timestamp: 1654952231.29624 iteration: 49170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09386 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.14058 L1 loss: 0.0000e+00 L2 loss: 0.61287 Learning rate: 0.002 Mask loss: 0.06313 RPN box loss: 0.00482 RPN score loss: 0.00106 RPN total loss: 0.00588 Total loss: 0.82245 timestamp: 1654952234.4706159 iteration: 49175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05484 FastRCNN class loss: 0.05468 FastRCNN total loss: 0.10953 L1 loss: 0.0000e+00 L2 loss: 0.61286 Learning rate: 0.002 Mask loss: 0.07282 RPN box loss: 0.01419 RPN score loss: 0.01176 RPN total loss: 0.02595 Total loss: 0.82116 timestamp: 1654952237.7496233 iteration: 49180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07751 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.14728 L1 loss: 0.0000e+00 L2 loss: 0.61285 Learning rate: 0.002 Mask loss: 0.0921 RPN box loss: 0.00741 RPN score loss: 0.00198 RPN total loss: 0.00938 Total loss: 0.86162 timestamp: 1654952241.019536 iteration: 49185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11247 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.19102 L1 loss: 0.0000e+00 L2 loss: 0.61285 Learning rate: 0.002 Mask loss: 0.16366 RPN box loss: 0.04486 RPN score loss: 0.00625 RPN total loss: 0.05111 Total loss: 1.01864 timestamp: 1654952244.3459642 iteration: 49190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08653 FastRCNN class loss: 0.059 FastRCNN total loss: 0.14553 L1 loss: 0.0000e+00 L2 loss: 0.61284 Learning rate: 0.002 Mask loss: 0.12874 RPN box loss: 0.01661 RPN score loss: 0.00224 RPN total loss: 0.01885 Total loss: 0.90596 timestamp: 1654952247.5200005 iteration: 49195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08567 FastRCNN class loss: 0.0679 FastRCNN total loss: 0.15357 L1 loss: 0.0000e+00 L2 loss: 0.61283 Learning rate: 0.002 Mask loss: 0.13008 RPN box loss: 0.01614 RPN score loss: 0.00419 RPN total loss: 0.02033 Total loss: 0.91681 timestamp: 1654952250.755989 iteration: 49200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.131 FastRCNN class loss: 0.16511 FastRCNN total loss: 0.29611 L1 loss: 0.0000e+00 L2 loss: 0.61282 Learning rate: 0.002 Mask loss: 0.11602 RPN box loss: 0.03875 RPN score loss: 0.00336 RPN total loss: 0.04211 Total loss: 1.06706 timestamp: 1654952253.9572408 iteration: 49205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10544 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.16387 L1 loss: 0.0000e+00 L2 loss: 0.61281 Learning rate: 0.002 Mask loss: 0.12839 RPN box loss: 0.01929 RPN score loss: 0.00354 RPN total loss: 0.02283 Total loss: 0.9279 timestamp: 1654952257.176204 iteration: 49210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08306 FastRCNN class loss: 0.03604 FastRCNN total loss: 0.11911 L1 loss: 0.0000e+00 L2 loss: 0.6128 Learning rate: 0.002 Mask loss: 0.07846 RPN box loss: 0.00951 RPN score loss: 0.0039 RPN total loss: 0.01341 Total loss: 0.82378 timestamp: 1654952260.4174182 iteration: 49215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10116 FastRCNN class loss: 0.07263 FastRCNN total loss: 0.17379 L1 loss: 0.0000e+00 L2 loss: 0.61279 Learning rate: 0.002 Mask loss: 0.10224 RPN box loss: 0.00581 RPN score loss: 0.00163 RPN total loss: 0.00744 Total loss: 0.89626 timestamp: 1654952263.7111034 iteration: 49220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11705 FastRCNN class loss: 0.04964 FastRCNN total loss: 0.16668 L1 loss: 0.0000e+00 L2 loss: 0.61278 Learning rate: 0.002 Mask loss: 0.12688 RPN box loss: 0.01219 RPN score loss: 0.00143 RPN total loss: 0.01362 Total loss: 0.91996 timestamp: 1654952266.906924 iteration: 49225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0875 FastRCNN class loss: 0.06887 FastRCNN total loss: 0.15638 L1 loss: 0.0000e+00 L2 loss: 0.61277 Learning rate: 0.002 Mask loss: 0.14187 RPN box loss: 0.00707 RPN score loss: 0.00331 RPN total loss: 0.01038 Total loss: 0.92139 timestamp: 1654952270.1189282 iteration: 49230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08381 FastRCNN class loss: 0.06211 FastRCNN total loss: 0.14592 L1 loss: 0.0000e+00 L2 loss: 0.61276 Learning rate: 0.002 Mask loss: 0.09781 RPN box loss: 0.01398 RPN score loss: 0.00367 RPN total loss: 0.01764 Total loss: 0.87414 timestamp: 1654952273.2573614 iteration: 49235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10219 FastRCNN class loss: 0.04544 FastRCNN total loss: 0.14763 L1 loss: 0.0000e+00 L2 loss: 0.61275 Learning rate: 0.002 Mask loss: 0.11481 RPN box loss: 0.00638 RPN score loss: 0.00731 RPN total loss: 0.01369 Total loss: 0.88888 timestamp: 1654952276.5054448 iteration: 49240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09941 FastRCNN class loss: 0.11052 FastRCNN total loss: 0.20994 L1 loss: 0.0000e+00 L2 loss: 0.61274 Learning rate: 0.002 Mask loss: 0.19522 RPN box loss: 0.02823 RPN score loss: 0.02655 RPN total loss: 0.05477 Total loss: 1.07266 timestamp: 1654952279.7124403 iteration: 49245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12285 FastRCNN class loss: 0.08346 FastRCNN total loss: 0.20631 L1 loss: 0.0000e+00 L2 loss: 0.61273 Learning rate: 0.002 Mask loss: 0.16489 RPN box loss: 0.02628 RPN score loss: 0.00825 RPN total loss: 0.03453 Total loss: 1.01846 timestamp: 1654952282.997629 iteration: 49250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10856 FastRCNN class loss: 0.10232 FastRCNN total loss: 0.21088 L1 loss: 0.0000e+00 L2 loss: 0.61272 Learning rate: 0.002 Mask loss: 0.15073 RPN box loss: 0.01984 RPN score loss: 0.00695 RPN total loss: 0.02679 Total loss: 1.00112 timestamp: 1654952286.1932926 iteration: 49255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0955 FastRCNN class loss: 0.04459 FastRCNN total loss: 0.14009 L1 loss: 0.0000e+00 L2 loss: 0.61271 Learning rate: 0.002 Mask loss: 0.15849 RPN box loss: 0.01232 RPN score loss: 0.00751 RPN total loss: 0.01983 Total loss: 0.93112 timestamp: 1654952289.408147 iteration: 49260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.10834 FastRCNN total loss: 0.17944 L1 loss: 0.0000e+00 L2 loss: 0.6127 Learning rate: 0.002 Mask loss: 0.16285 RPN box loss: 0.00618 RPN score loss: 0.00583 RPN total loss: 0.01201 Total loss: 0.967 timestamp: 1654952292.5627909 iteration: 49265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.05708 FastRCNN total loss: 0.14011 L1 loss: 0.0000e+00 L2 loss: 0.61269 Learning rate: 0.002 Mask loss: 0.16351 RPN box loss: 0.02028 RPN score loss: 0.01224 RPN total loss: 0.03252 Total loss: 0.94883 timestamp: 1654952295.7093005 iteration: 49270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07061 FastRCNN class loss: 0.09163 FastRCNN total loss: 0.16224 L1 loss: 0.0000e+00 L2 loss: 0.61268 Learning rate: 0.002 Mask loss: 0.11694 RPN box loss: 0.0148 RPN score loss: 0.00105 RPN total loss: 0.01585 Total loss: 0.90771 timestamp: 1654952298.9045198 iteration: 49275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07505 FastRCNN class loss: 0.05563 FastRCNN total loss: 0.13067 L1 loss: 0.0000e+00 L2 loss: 0.61267 Learning rate: 0.002 Mask loss: 0.09057 RPN box loss: 0.00834 RPN score loss: 0.00257 RPN total loss: 0.01091 Total loss: 0.84483 timestamp: 1654952302.0930495 iteration: 49280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09079 FastRCNN class loss: 0.05489 FastRCNN total loss: 0.14569 L1 loss: 0.0000e+00 L2 loss: 0.61267 Learning rate: 0.002 Mask loss: 0.11547 RPN box loss: 0.01216 RPN score loss: 0.00906 RPN total loss: 0.02122 Total loss: 0.89504 timestamp: 1654952305.3317325 iteration: 49285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15133 FastRCNN class loss: 0.08693 FastRCNN total loss: 0.23826 L1 loss: 0.0000e+00 L2 loss: 0.61266 Learning rate: 0.002 Mask loss: 0.1272 RPN box loss: 0.01909 RPN score loss: 0.00515 RPN total loss: 0.02424 Total loss: 1.00236 timestamp: 1654952308.460873 iteration: 49290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09971 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.16176 L1 loss: 0.0000e+00 L2 loss: 0.61265 Learning rate: 0.002 Mask loss: 0.10113 RPN box loss: 0.00449 RPN score loss: 0.00314 RPN total loss: 0.00762 Total loss: 0.88316 timestamp: 1654952311.6809752 iteration: 49295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07102 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.13507 L1 loss: 0.0000e+00 L2 loss: 0.61264 Learning rate: 0.002 Mask loss: 0.10508 RPN box loss: 0.01036 RPN score loss: 0.0053 RPN total loss: 0.01566 Total loss: 0.86845 timestamp: 1654952314.892296 iteration: 49300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06772 FastRCNN class loss: 0.12112 FastRCNN total loss: 0.18884 L1 loss: 0.0000e+00 L2 loss: 0.61264 Learning rate: 0.002 Mask loss: 0.12805 RPN box loss: 0.02054 RPN score loss: 0.00308 RPN total loss: 0.02362 Total loss: 0.95314 timestamp: 1654952318.11716 iteration: 49305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10676 FastRCNN class loss: 0.07611 FastRCNN total loss: 0.18287 L1 loss: 0.0000e+00 L2 loss: 0.61263 Learning rate: 0.002 Mask loss: 0.10937 RPN box loss: 0.03381 RPN score loss: 0.00169 RPN total loss: 0.0355 Total loss: 0.94038 timestamp: 1654952321.3426845 iteration: 49310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06043 FastRCNN class loss: 0.0428 FastRCNN total loss: 0.10323 L1 loss: 0.0000e+00 L2 loss: 0.61262 Learning rate: 0.002 Mask loss: 0.09837 RPN box loss: 0.06901 RPN score loss: 0.0026 RPN total loss: 0.07162 Total loss: 0.88584 timestamp: 1654952324.60436 iteration: 49315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11657 FastRCNN class loss: 0.09666 FastRCNN total loss: 0.21323 L1 loss: 0.0000e+00 L2 loss: 0.61262 Learning rate: 0.002 Mask loss: 0.15072 RPN box loss: 0.03282 RPN score loss: 0.01018 RPN total loss: 0.04301 Total loss: 1.01957 timestamp: 1654952327.822673 iteration: 49320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.14386 L1 loss: 0.0000e+00 L2 loss: 0.61261 Learning rate: 0.002 Mask loss: 0.12363 RPN box loss: 0.00855 RPN score loss: 0.0069 RPN total loss: 0.01546 Total loss: 0.89555 timestamp: 1654952330.921188 iteration: 49325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09872 FastRCNN class loss: 0.0772 FastRCNN total loss: 0.17592 L1 loss: 0.0000e+00 L2 loss: 0.6126 Learning rate: 0.002 Mask loss: 0.24347 RPN box loss: 0.01513 RPN score loss: 0.00587 RPN total loss: 0.021 Total loss: 1.05299 timestamp: 1654952334.1179254 iteration: 49330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08468 FastRCNN class loss: 0.05357 FastRCNN total loss: 0.13825 L1 loss: 0.0000e+00 L2 loss: 0.61259 Learning rate: 0.002 Mask loss: 0.12131 RPN box loss: 0.01033 RPN score loss: 0.00643 RPN total loss: 0.01676 Total loss: 0.88892 timestamp: 1654952337.328861 iteration: 49335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12317 FastRCNN class loss: 0.09111 FastRCNN total loss: 0.21428 L1 loss: 0.0000e+00 L2 loss: 0.61259 Learning rate: 0.002 Mask loss: 0.08054 RPN box loss: 0.00854 RPN score loss: 0.00202 RPN total loss: 0.01056 Total loss: 0.91797 timestamp: 1654952340.5450253 iteration: 49340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06551 FastRCNN class loss: 0.04234 FastRCNN total loss: 0.10785 L1 loss: 0.0000e+00 L2 loss: 0.61258 Learning rate: 0.002 Mask loss: 0.13967 RPN box loss: 0.03417 RPN score loss: 0.01104 RPN total loss: 0.04521 Total loss: 0.90531 timestamp: 1654952343.7196953 iteration: 49345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08415 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.15386 L1 loss: 0.0000e+00 L2 loss: 0.61256 Learning rate: 0.002 Mask loss: 0.15753 RPN box loss: 0.01362 RPN score loss: 0.0053 RPN total loss: 0.01892 Total loss: 0.94287 timestamp: 1654952346.9803154 iteration: 49350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15248 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.21033 L1 loss: 0.0000e+00 L2 loss: 0.61255 Learning rate: 0.002 Mask loss: 0.11945 RPN box loss: 0.02834 RPN score loss: 0.00096 RPN total loss: 0.0293 Total loss: 0.97163 timestamp: 1654952350.1960957 iteration: 49355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11557 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.61254 Learning rate: 0.002 Mask loss: 0.15033 RPN box loss: 0.0217 RPN score loss: 0.00814 RPN total loss: 0.02984 Total loss: 1.01215 timestamp: 1654952353.3950682 iteration: 49360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09683 FastRCNN class loss: 0.05506 FastRCNN total loss: 0.15189 L1 loss: 0.0000e+00 L2 loss: 0.61253 Learning rate: 0.002 Mask loss: 0.08143 RPN box loss: 0.00616 RPN score loss: 0.00509 RPN total loss: 0.01126 Total loss: 0.85711 timestamp: 1654952356.5926433 iteration: 49365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09976 FastRCNN class loss: 0.08525 FastRCNN total loss: 0.18501 L1 loss: 0.0000e+00 L2 loss: 0.61253 Learning rate: 0.002 Mask loss: 0.13838 RPN box loss: 0.00482 RPN score loss: 0.00368 RPN total loss: 0.00851 Total loss: 0.94442 timestamp: 1654952359.8567457 iteration: 49370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.05508 FastRCNN total loss: 0.1403 L1 loss: 0.0000e+00 L2 loss: 0.61252 Learning rate: 0.002 Mask loss: 0.16852 RPN box loss: 0.0198 RPN score loss: 0.00825 RPN total loss: 0.02805 Total loss: 0.94939 timestamp: 1654952363.005714 iteration: 49375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11481 FastRCNN class loss: 0.09327 FastRCNN total loss: 0.20808 L1 loss: 0.0000e+00 L2 loss: 0.61251 Learning rate: 0.002 Mask loss: 0.14715 RPN box loss: 0.04877 RPN score loss: 0.00759 RPN total loss: 0.05636 Total loss: 1.0241 timestamp: 1654952366.2153635 iteration: 49380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1362 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.22211 L1 loss: 0.0000e+00 L2 loss: 0.6125 Learning rate: 0.002 Mask loss: 0.13429 RPN box loss: 0.01494 RPN score loss: 0.0074 RPN total loss: 0.02234 Total loss: 0.99124 timestamp: 1654952369.3707962 iteration: 49385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07227 FastRCNN class loss: 0.09157 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 0.61249 Learning rate: 0.002 Mask loss: 0.12375 RPN box loss: 0.00912 RPN score loss: 0.00168 RPN total loss: 0.0108 Total loss: 0.91088 timestamp: 1654952372.6163843 iteration: 49390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0832 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.15292 L1 loss: 0.0000e+00 L2 loss: 0.61248 Learning rate: 0.002 Mask loss: 0.1216 RPN box loss: 0.00972 RPN score loss: 0.00108 RPN total loss: 0.0108 Total loss: 0.8978 timestamp: 1654952375.8576806 iteration: 49395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11648 FastRCNN class loss: 0.09451 FastRCNN total loss: 0.21099 L1 loss: 0.0000e+00 L2 loss: 0.61247 Learning rate: 0.002 Mask loss: 0.14671 RPN box loss: 0.02105 RPN score loss: 0.02261 RPN total loss: 0.04366 Total loss: 1.01384 timestamp: 1654952379.02028 iteration: 49400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07185 FastRCNN class loss: 0.05152 FastRCNN total loss: 0.12337 L1 loss: 0.0000e+00 L2 loss: 0.61246 Learning rate: 0.002 Mask loss: 0.19453 RPN box loss: 0.03182 RPN score loss: 0.00907 RPN total loss: 0.04089 Total loss: 0.97126 timestamp: 1654952382.1020992 iteration: 49405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07396 FastRCNN class loss: 0.06284 FastRCNN total loss: 0.1368 L1 loss: 0.0000e+00 L2 loss: 0.61246 Learning rate: 0.002 Mask loss: 0.12078 RPN box loss: 0.03284 RPN score loss: 0.00458 RPN total loss: 0.03742 Total loss: 0.90745 timestamp: 1654952385.2701447 iteration: 49410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08861 FastRCNN class loss: 0.07254 FastRCNN total loss: 0.16116 L1 loss: 0.0000e+00 L2 loss: 0.61245 Learning rate: 0.002 Mask loss: 0.10471 RPN box loss: 0.01149 RPN score loss: 0.00122 RPN total loss: 0.01271 Total loss: 0.89102 timestamp: 1654952388.4144742 iteration: 49415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06665 FastRCNN class loss: 0.0451 FastRCNN total loss: 0.11174 L1 loss: 0.0000e+00 L2 loss: 0.61244 Learning rate: 0.002 Mask loss: 0.15506 RPN box loss: 0.0081 RPN score loss: 0.00214 RPN total loss: 0.01024 Total loss: 0.88948 timestamp: 1654952391.6959078 iteration: 49420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08164 FastRCNN class loss: 0.06111 FastRCNN total loss: 0.14276 L1 loss: 0.0000e+00 L2 loss: 0.61243 Learning rate: 0.002 Mask loss: 0.14552 RPN box loss: 0.01357 RPN score loss: 0.00564 RPN total loss: 0.01921 Total loss: 0.91992 timestamp: 1654952394.9773695 iteration: 49425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06591 FastRCNN class loss: 0.05812 FastRCNN total loss: 0.12403 L1 loss: 0.0000e+00 L2 loss: 0.61242 Learning rate: 0.002 Mask loss: 0.14023 RPN box loss: 0.02806 RPN score loss: 0.01471 RPN total loss: 0.04277 Total loss: 0.91945 timestamp: 1654952398.1857533 iteration: 49430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14758 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.23434 L1 loss: 0.0000e+00 L2 loss: 0.61241 Learning rate: 0.002 Mask loss: 0.1557 RPN box loss: 0.03548 RPN score loss: 0.00762 RPN total loss: 0.0431 Total loss: 1.04556 timestamp: 1654952401.5580003 iteration: 49435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12986 FastRCNN class loss: 0.09198 FastRCNN total loss: 0.22184 L1 loss: 0.0000e+00 L2 loss: 0.6124 Learning rate: 0.002 Mask loss: 0.15781 RPN box loss: 0.01743 RPN score loss: 0.00355 RPN total loss: 0.02098 Total loss: 1.01304 timestamp: 1654952404.8970647 iteration: 49440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08907 FastRCNN class loss: 0.06652 FastRCNN total loss: 0.15559 L1 loss: 0.0000e+00 L2 loss: 0.61239 Learning rate: 0.002 Mask loss: 0.12483 RPN box loss: 0.01428 RPN score loss: 0.00395 RPN total loss: 0.01822 Total loss: 0.91104 timestamp: 1654952408.172744 iteration: 49445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12442 FastRCNN class loss: 0.05088 FastRCNN total loss: 0.1753 L1 loss: 0.0000e+00 L2 loss: 0.61238 Learning rate: 0.002 Mask loss: 0.16646 RPN box loss: 0.03488 RPN score loss: 0.00878 RPN total loss: 0.04366 Total loss: 0.9978 timestamp: 1654952411.5279412 iteration: 49450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07864 FastRCNN class loss: 0.04814 FastRCNN total loss: 0.12678 L1 loss: 0.0000e+00 L2 loss: 0.61237 Learning rate: 0.002 Mask loss: 0.09057 RPN box loss: 0.0071 RPN score loss: 0.00271 RPN total loss: 0.00981 Total loss: 0.83954 timestamp: 1654952414.6880164 iteration: 49455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10187 FastRCNN class loss: 0.09053 FastRCNN total loss: 0.19241 L1 loss: 0.0000e+00 L2 loss: 0.61237 Learning rate: 0.002 Mask loss: 0.18092 RPN box loss: 0.01586 RPN score loss: 0.01329 RPN total loss: 0.02915 Total loss: 1.01484 timestamp: 1654952417.9385672 iteration: 49460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08638 FastRCNN class loss: 0.07993 FastRCNN total loss: 0.16631 L1 loss: 0.0000e+00 L2 loss: 0.61236 Learning rate: 0.002 Mask loss: 0.11495 RPN box loss: 0.01649 RPN score loss: 0.00437 RPN total loss: 0.02085 Total loss: 0.91446 timestamp: 1654952421.1720307 iteration: 49465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06656 FastRCNN class loss: 0.05382 FastRCNN total loss: 0.12038 L1 loss: 0.0000e+00 L2 loss: 0.61235 Learning rate: 0.002 Mask loss: 0.10316 RPN box loss: 0.01664 RPN score loss: 0.0172 RPN total loss: 0.03384 Total loss: 0.86972 timestamp: 1654952424.5386317 iteration: 49470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08471 FastRCNN class loss: 0.06681 FastRCNN total loss: 0.15152 L1 loss: 0.0000e+00 L2 loss: 0.61234 Learning rate: 0.002 Mask loss: 0.09101 RPN box loss: 0.01067 RPN score loss: 0.00211 RPN total loss: 0.01279 Total loss: 0.86766 timestamp: 1654952427.819071 iteration: 49475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1487 FastRCNN class loss: 0.12884 FastRCNN total loss: 0.27754 L1 loss: 0.0000e+00 L2 loss: 0.61233 Learning rate: 0.002 Mask loss: 0.25126 RPN box loss: 0.0347 RPN score loss: 0.07441 RPN total loss: 0.10911 Total loss: 1.25023 timestamp: 1654952431.0464563 iteration: 49480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04651 FastRCNN class loss: 0.04739 FastRCNN total loss: 0.0939 L1 loss: 0.0000e+00 L2 loss: 0.61232 Learning rate: 0.002 Mask loss: 0.14711 RPN box loss: 0.00487 RPN score loss: 0.00249 RPN total loss: 0.00736 Total loss: 0.86069 timestamp: 1654952434.4328854 iteration: 49485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10599 FastRCNN class loss: 0.06553 FastRCNN total loss: 0.17151 L1 loss: 0.0000e+00 L2 loss: 0.61231 Learning rate: 0.002 Mask loss: 0.16935 RPN box loss: 0.01664 RPN score loss: 0.00277 RPN total loss: 0.01941 Total loss: 0.97258 timestamp: 1654952437.592278 iteration: 49490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10764 FastRCNN class loss: 0.063 FastRCNN total loss: 0.17064 L1 loss: 0.0000e+00 L2 loss: 0.6123 Learning rate: 0.002 Mask loss: 0.1534 RPN box loss: 0.00799 RPN score loss: 0.00211 RPN total loss: 0.0101 Total loss: 0.94645 timestamp: 1654952440.85468 iteration: 49495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.08396 FastRCNN total loss: 0.23138 L1 loss: 0.0000e+00 L2 loss: 0.61229 Learning rate: 0.002 Mask loss: 0.14942 RPN box loss: 0.0383 RPN score loss: 0.00839 RPN total loss: 0.04668 Total loss: 1.03977 timestamp: 1654952444.033398 iteration: 49500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15005 FastRCNN class loss: 0.10272 FastRCNN total loss: 0.25277 L1 loss: 0.0000e+00 L2 loss: 0.61228 Learning rate: 0.002 Mask loss: 0.16354 RPN box loss: 0.0139 RPN score loss: 0.00625 RPN total loss: 0.02016 Total loss: 1.04875 timestamp: 1654952447.327461 iteration: 49505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0968 FastRCNN class loss: 0.0487 FastRCNN total loss: 0.1455 L1 loss: 0.0000e+00 L2 loss: 0.61227 Learning rate: 0.002 Mask loss: 0.10299 RPN box loss: 0.01164 RPN score loss: 0.00257 RPN total loss: 0.01421 Total loss: 0.87498 timestamp: 1654952450.5437093 iteration: 49510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14305 FastRCNN class loss: 0.05432 FastRCNN total loss: 0.19737 L1 loss: 0.0000e+00 L2 loss: 0.61226 Learning rate: 0.002 Mask loss: 0.11727 RPN box loss: 0.02484 RPN score loss: 0.00163 RPN total loss: 0.02647 Total loss: 0.95338 timestamp: 1654952453.8173196 iteration: 49515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12325 FastRCNN class loss: 0.08913 FastRCNN total loss: 0.21238 L1 loss: 0.0000e+00 L2 loss: 0.61226 Learning rate: 0.002 Mask loss: 0.15055 RPN box loss: 0.01917 RPN score loss: 0.00114 RPN total loss: 0.02032 Total loss: 0.9955 timestamp: 1654952457.083897 iteration: 49520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06849 FastRCNN class loss: 0.06899 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.61225 Learning rate: 0.002 Mask loss: 0.12105 RPN box loss: 0.00801 RPN score loss: 0.00206 RPN total loss: 0.01007 Total loss: 0.88085 timestamp: 1654952460.2852004 iteration: 49525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06656 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.1219 L1 loss: 0.0000e+00 L2 loss: 0.61224 Learning rate: 0.002 Mask loss: 0.12833 RPN box loss: 0.02335 RPN score loss: 0.00406 RPN total loss: 0.02741 Total loss: 0.88988 timestamp: 1654952463.5561872 iteration: 49530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09838 FastRCNN class loss: 0.06958 FastRCNN total loss: 0.16796 L1 loss: 0.0000e+00 L2 loss: 0.61223 Learning rate: 0.002 Mask loss: 0.12343 RPN box loss: 0.0233 RPN score loss: 0.00404 RPN total loss: 0.02734 Total loss: 0.93096 timestamp: 1654952466.8488579 iteration: 49535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08552 FastRCNN class loss: 0.09714 FastRCNN total loss: 0.18266 L1 loss: 0.0000e+00 L2 loss: 0.61223 Learning rate: 0.002 Mask loss: 0.1529 RPN box loss: 0.01435 RPN score loss: 0.00648 RPN total loss: 0.02083 Total loss: 0.96861 timestamp: 1654952470.0956912 iteration: 49540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09927 FastRCNN class loss: 0.09788 FastRCNN total loss: 0.19715 L1 loss: 0.0000e+00 L2 loss: 0.61222 Learning rate: 0.002 Mask loss: 0.14099 RPN box loss: 0.01208 RPN score loss: 0.00605 RPN total loss: 0.01813 Total loss: 0.96849 timestamp: 1654952473.3412888 iteration: 49545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11144 FastRCNN class loss: 0.07817 FastRCNN total loss: 0.18961 L1 loss: 0.0000e+00 L2 loss: 0.61221 Learning rate: 0.002 Mask loss: 0.14538 RPN box loss: 0.04835 RPN score loss: 0.00512 RPN total loss: 0.05347 Total loss: 1.00067 timestamp: 1654952476.6283338 iteration: 49550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11773 FastRCNN class loss: 0.08472 FastRCNN total loss: 0.20246 L1 loss: 0.0000e+00 L2 loss: 0.6122 Learning rate: 0.002 Mask loss: 0.14043 RPN box loss: 0.0076 RPN score loss: 0.00804 RPN total loss: 0.01564 Total loss: 0.97072 timestamp: 1654952479.845561 iteration: 49555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11142 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.1752 L1 loss: 0.0000e+00 L2 loss: 0.61218 Learning rate: 0.002 Mask loss: 0.11871 RPN box loss: 0.02976 RPN score loss: 0.00572 RPN total loss: 0.03548 Total loss: 0.94157 timestamp: 1654952483.1593163 iteration: 49560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08523 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.14717 L1 loss: 0.0000e+00 L2 loss: 0.61218 Learning rate: 0.002 Mask loss: 0.11796 RPN box loss: 0.01094 RPN score loss: 0.00308 RPN total loss: 0.01402 Total loss: 0.89133 timestamp: 1654952486.3428864 iteration: 49565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06229 FastRCNN class loss: 0.04202 FastRCNN total loss: 0.10431 L1 loss: 0.0000e+00 L2 loss: 0.61217 Learning rate: 0.002 Mask loss: 0.10206 RPN box loss: 0.01156 RPN score loss: 0.00092 RPN total loss: 0.01248 Total loss: 0.83102 timestamp: 1654952489.5856082 iteration: 49570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09672 FastRCNN class loss: 0.07801 FastRCNN total loss: 0.17473 L1 loss: 0.0000e+00 L2 loss: 0.61216 Learning rate: 0.002 Mask loss: 0.14374 RPN box loss: 0.02291 RPN score loss: 0.00314 RPN total loss: 0.02605 Total loss: 0.95667 timestamp: 1654952492.8363523 iteration: 49575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09006 FastRCNN class loss: 0.10164 FastRCNN total loss: 0.1917 L1 loss: 0.0000e+00 L2 loss: 0.61215 Learning rate: 0.002 Mask loss: 0.12779 RPN box loss: 0.03464 RPN score loss: 0.00435 RPN total loss: 0.03899 Total loss: 0.97063 timestamp: 1654952496.0885222 iteration: 49580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12006 FastRCNN class loss: 0.0695 FastRCNN total loss: 0.18956 L1 loss: 0.0000e+00 L2 loss: 0.61215 Learning rate: 0.002 Mask loss: 0.11683 RPN box loss: 0.01668 RPN score loss: 0.00648 RPN total loss: 0.02316 Total loss: 0.9417 timestamp: 1654952499.3056324 iteration: 49585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13268 FastRCNN class loss: 0.06432 FastRCNN total loss: 0.19699 L1 loss: 0.0000e+00 L2 loss: 0.61214 Learning rate: 0.002 Mask loss: 0.1401 RPN box loss: 0.01265 RPN score loss: 0.00493 RPN total loss: 0.01757 Total loss: 0.9668 timestamp: 1654952502.6195204 iteration: 49590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09281 FastRCNN class loss: 0.04959 FastRCNN total loss: 0.14239 L1 loss: 0.0000e+00 L2 loss: 0.61213 Learning rate: 0.002 Mask loss: 0.10927 RPN box loss: 0.00671 RPN score loss: 0.00828 RPN total loss: 0.01499 Total loss: 0.87878 timestamp: 1654952506.0130453 iteration: 49595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16097 FastRCNN class loss: 0.07955 FastRCNN total loss: 0.24052 L1 loss: 0.0000e+00 L2 loss: 0.61212 Learning rate: 0.002 Mask loss: 0.11903 RPN box loss: 0.00946 RPN score loss: 0.00306 RPN total loss: 0.01251 Total loss: 0.98418 timestamp: 1654952509.1918902 iteration: 49600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06167 FastRCNN class loss: 0.07003 FastRCNN total loss: 0.1317 L1 loss: 0.0000e+00 L2 loss: 0.61211 Learning rate: 0.002 Mask loss: 0.14789 RPN box loss: 0.00402 RPN score loss: 0.00254 RPN total loss: 0.00656 Total loss: 0.89826 timestamp: 1654952512.4265075 iteration: 49605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10355 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.16251 L1 loss: 0.0000e+00 L2 loss: 0.6121 Learning rate: 0.002 Mask loss: 0.14199 RPN box loss: 0.01249 RPN score loss: 0.0048 RPN total loss: 0.0173 Total loss: 0.93389 timestamp: 1654952515.555411 iteration: 49610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12695 FastRCNN class loss: 0.12036 FastRCNN total loss: 0.24731 L1 loss: 0.0000e+00 L2 loss: 0.61209 Learning rate: 0.002 Mask loss: 0.15989 RPN box loss: 0.04029 RPN score loss: 0.01091 RPN total loss: 0.0512 Total loss: 1.07049 timestamp: 1654952518.9105217 iteration: 49615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09993 FastRCNN class loss: 0.05363 FastRCNN total loss: 0.15356 L1 loss: 0.0000e+00 L2 loss: 0.61208 Learning rate: 0.002 Mask loss: 0.10164 RPN box loss: 0.02031 RPN score loss: 0.00161 RPN total loss: 0.02192 Total loss: 0.88919 timestamp: 1654952522.0923483 iteration: 49620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05835 FastRCNN class loss: 0.02405 FastRCNN total loss: 0.0824 L1 loss: 0.0000e+00 L2 loss: 0.61207 Learning rate: 0.002 Mask loss: 0.08561 RPN box loss: 0.01887 RPN score loss: 0.00117 RPN total loss: 0.02004 Total loss: 0.80013 timestamp: 1654952525.349719 iteration: 49625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08595 FastRCNN class loss: 0.04836 FastRCNN total loss: 0.1343 L1 loss: 0.0000e+00 L2 loss: 0.61206 Learning rate: 0.002 Mask loss: 0.1219 RPN box loss: 0.00639 RPN score loss: 0.00186 RPN total loss: 0.00825 Total loss: 0.87652 timestamp: 1654952528.5842252 iteration: 49630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15309 FastRCNN class loss: 0.08714 FastRCNN total loss: 0.24023 L1 loss: 0.0000e+00 L2 loss: 0.61205 Learning rate: 0.002 Mask loss: 0.16457 RPN box loss: 0.01509 RPN score loss: 0.00375 RPN total loss: 0.01884 Total loss: 1.03569 timestamp: 1654952531.9656093 iteration: 49635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10187 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.15509 L1 loss: 0.0000e+00 L2 loss: 0.61205 Learning rate: 0.002 Mask loss: 0.13863 RPN box loss: 0.00508 RPN score loss: 0.00633 RPN total loss: 0.01141 Total loss: 0.91718 timestamp: 1654952535.144284 iteration: 49640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11149 FastRCNN class loss: 0.04538 FastRCNN total loss: 0.15687 L1 loss: 0.0000e+00 L2 loss: 0.61204 Learning rate: 0.002 Mask loss: 0.12646 RPN box loss: 0.02037 RPN score loss: 0.00643 RPN total loss: 0.0268 Total loss: 0.92217 timestamp: 1654952538.3691719 iteration: 49645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14497 FastRCNN class loss: 0.07661 FastRCNN total loss: 0.22158 L1 loss: 0.0000e+00 L2 loss: 0.61203 Learning rate: 0.002 Mask loss: 0.11761 RPN box loss: 0.01866 RPN score loss: 0.00356 RPN total loss: 0.02222 Total loss: 0.97343 timestamp: 1654952541.8046498 iteration: 49650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08096 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.1482 L1 loss: 0.0000e+00 L2 loss: 0.61201 Learning rate: 0.002 Mask loss: 0.13125 RPN box loss: 0.02097 RPN score loss: 0.00846 RPN total loss: 0.02943 Total loss: 0.92089 timestamp: 1654952544.9350898 iteration: 49655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08049 FastRCNN class loss: 0.05575 FastRCNN total loss: 0.13624 L1 loss: 0.0000e+00 L2 loss: 0.612 Learning rate: 0.002 Mask loss: 0.13034 RPN box loss: 0.00807 RPN score loss: 0.00201 RPN total loss: 0.01008 Total loss: 0.88866 timestamp: 1654952548.1864126 iteration: 49660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08395 FastRCNN class loss: 0.11506 FastRCNN total loss: 0.19901 L1 loss: 0.0000e+00 L2 loss: 0.61199 Learning rate: 0.002 Mask loss: 0.13658 RPN box loss: 0.0232 RPN score loss: 0.0042 RPN total loss: 0.0274 Total loss: 0.97498 timestamp: 1654952551.4406168 iteration: 49665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11119 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.19572 L1 loss: 0.0000e+00 L2 loss: 0.61198 Learning rate: 0.002 Mask loss: 0.17535 RPN box loss: 0.01623 RPN score loss: 0.00484 RPN total loss: 0.02107 Total loss: 1.00412 timestamp: 1654952554.6994998 iteration: 49670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10834 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.16767 L1 loss: 0.0000e+00 L2 loss: 0.61198 Learning rate: 0.002 Mask loss: 0.09832 RPN box loss: 0.01404 RPN score loss: 0.00377 RPN total loss: 0.01781 Total loss: 0.89578 timestamp: 1654952557.8427036 iteration: 49675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08142 FastRCNN class loss: 0.05104 FastRCNN total loss: 0.13246 L1 loss: 0.0000e+00 L2 loss: 0.61197 Learning rate: 0.002 Mask loss: 0.19489 RPN box loss: 0.01062 RPN score loss: 0.00182 RPN total loss: 0.01243 Total loss: 0.95175 timestamp: 1654952561.1581924 iteration: 49680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12899 FastRCNN class loss: 0.03654 FastRCNN total loss: 0.16552 L1 loss: 0.0000e+00 L2 loss: 0.61196 Learning rate: 0.002 Mask loss: 0.11944 RPN box loss: 0.00422 RPN score loss: 0.00167 RPN total loss: 0.00589 Total loss: 0.90281 timestamp: 1654952564.3359888 iteration: 49685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06464 FastRCNN class loss: 0.04359 FastRCNN total loss: 0.10823 L1 loss: 0.0000e+00 L2 loss: 0.61195 Learning rate: 0.002 Mask loss: 0.14436 RPN box loss: 0.02055 RPN score loss: 0.00071 RPN total loss: 0.02126 Total loss: 0.8858 timestamp: 1654952567.5187712 iteration: 49690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05928 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.1141 L1 loss: 0.0000e+00 L2 loss: 0.61194 Learning rate: 0.002 Mask loss: 0.13298 RPN box loss: 0.00768 RPN score loss: 0.00207 RPN total loss: 0.00975 Total loss: 0.86876 timestamp: 1654952570.74742 iteration: 49695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10457 FastRCNN class loss: 0.04568 FastRCNN total loss: 0.15025 L1 loss: 0.0000e+00 L2 loss: 0.61193 Learning rate: 0.002 Mask loss: 0.09334 RPN box loss: 0.00524 RPN score loss: 0.00096 RPN total loss: 0.0062 Total loss: 0.86172 timestamp: 1654952574.019566 iteration: 49700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14625 FastRCNN class loss: 0.09341 FastRCNN total loss: 0.23967 L1 loss: 0.0000e+00 L2 loss: 0.61192 Learning rate: 0.002 Mask loss: 0.06698 RPN box loss: 0.00633 RPN score loss: 0.00373 RPN total loss: 0.01005 Total loss: 0.92862 timestamp: 1654952577.2902393 iteration: 49705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07338 FastRCNN class loss: 0.0822 FastRCNN total loss: 0.15558 L1 loss: 0.0000e+00 L2 loss: 0.61191 Learning rate: 0.002 Mask loss: 0.11853 RPN box loss: 0.00459 RPN score loss: 0.00119 RPN total loss: 0.00578 Total loss: 0.89181 timestamp: 1654952580.5801418 iteration: 49710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12307 FastRCNN class loss: 0.06515 FastRCNN total loss: 0.18821 L1 loss: 0.0000e+00 L2 loss: 0.61191 Learning rate: 0.002 Mask loss: 0.0935 RPN box loss: 0.01564 RPN score loss: 0.0036 RPN total loss: 0.01925 Total loss: 0.91287 timestamp: 1654952583.8507118 iteration: 49715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06999 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.15283 L1 loss: 0.0000e+00 L2 loss: 0.6119 Learning rate: 0.002 Mask loss: 0.14952 RPN box loss: 0.01822 RPN score loss: 0.00602 RPN total loss: 0.02424 Total loss: 0.9385 timestamp: 1654952587.0472665 iteration: 49720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14703 FastRCNN class loss: 0.10719 FastRCNN total loss: 0.25422 L1 loss: 0.0000e+00 L2 loss: 0.61189 Learning rate: 0.002 Mask loss: 0.17048 RPN box loss: 0.01968 RPN score loss: 0.00932 RPN total loss: 0.029 Total loss: 1.06559 timestamp: 1654952590.4100525 iteration: 49725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12938 FastRCNN class loss: 0.05544 FastRCNN total loss: 0.18482 L1 loss: 0.0000e+00 L2 loss: 0.61188 Learning rate: 0.002 Mask loss: 0.13586 RPN box loss: 0.01992 RPN score loss: 0.00621 RPN total loss: 0.02612 Total loss: 0.95868 timestamp: 1654952593.5622194 iteration: 49730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04408 FastRCNN class loss: 0.03023 FastRCNN total loss: 0.07432 L1 loss: 0.0000e+00 L2 loss: 0.61187 Learning rate: 0.002 Mask loss: 0.09477 RPN box loss: 0.00289 RPN score loss: 0.00381 RPN total loss: 0.0067 Total loss: 0.78765 timestamp: 1654952596.857621 iteration: 49735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03866 FastRCNN class loss: 0.03644 FastRCNN total loss: 0.07509 L1 loss: 0.0000e+00 L2 loss: 0.61186 Learning rate: 0.002 Mask loss: 0.11462 RPN box loss: 0.00609 RPN score loss: 0.00066 RPN total loss: 0.00675 Total loss: 0.80832 timestamp: 1654952600.0315301 iteration: 49740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06666 FastRCNN class loss: 0.10032 FastRCNN total loss: 0.16698 L1 loss: 0.0000e+00 L2 loss: 0.61185 Learning rate: 0.002 Mask loss: 0.14877 RPN box loss: 0.05412 RPN score loss: 0.01911 RPN total loss: 0.07323 Total loss: 1.00083 timestamp: 1654952603.304879 iteration: 49745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07326 FastRCNN class loss: 0.04708 FastRCNN total loss: 0.12034 L1 loss: 0.0000e+00 L2 loss: 0.61185 Learning rate: 0.002 Mask loss: 0.17459 RPN box loss: 0.02215 RPN score loss: 0.00478 RPN total loss: 0.02693 Total loss: 0.9337 timestamp: 1654952606.4646792 iteration: 49750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08013 FastRCNN class loss: 0.09039 FastRCNN total loss: 0.17053 L1 loss: 0.0000e+00 L2 loss: 0.61184 Learning rate: 0.002 Mask loss: 0.16748 RPN box loss: 0.02082 RPN score loss: 0.01021 RPN total loss: 0.03103 Total loss: 0.98087 timestamp: 1654952609.7793007 iteration: 49755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04162 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.10507 L1 loss: 0.0000e+00 L2 loss: 0.61182 Learning rate: 0.002 Mask loss: 0.10419 RPN box loss: 0.00662 RPN score loss: 0.0019 RPN total loss: 0.00853 Total loss: 0.82961 timestamp: 1654952613.101554 iteration: 49760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06249 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.13087 L1 loss: 0.0000e+00 L2 loss: 0.61181 Learning rate: 0.002 Mask loss: 0.10472 RPN box loss: 0.0174 RPN score loss: 0.00952 RPN total loss: 0.02692 Total loss: 0.87432 timestamp: 1654952616.278876 iteration: 49765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10535 FastRCNN class loss: 0.0871 FastRCNN total loss: 0.19245 L1 loss: 0.0000e+00 L2 loss: 0.61181 Learning rate: 0.002 Mask loss: 0.15873 RPN box loss: 0.01537 RPN score loss: 0.00609 RPN total loss: 0.02145 Total loss: 0.98444 timestamp: 1654952619.6090899 iteration: 49770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13496 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.20532 L1 loss: 0.0000e+00 L2 loss: 0.6118 Learning rate: 0.002 Mask loss: 0.12551 RPN box loss: 0.01791 RPN score loss: 0.00381 RPN total loss: 0.02172 Total loss: 0.96435 timestamp: 1654952622.7951238 iteration: 49775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11646 FastRCNN class loss: 0.06899 FastRCNN total loss: 0.18545 L1 loss: 0.0000e+00 L2 loss: 0.61179 Learning rate: 0.002 Mask loss: 0.14593 RPN box loss: 0.03605 RPN score loss: 0.00219 RPN total loss: 0.03824 Total loss: 0.98141 timestamp: 1654952626.0709164 iteration: 49780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07213 FastRCNN class loss: 0.11963 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 0.61179 Learning rate: 0.002 Mask loss: 0.12842 RPN box loss: 0.03156 RPN score loss: 0.00578 RPN total loss: 0.03733 Total loss: 0.96931 timestamp: 1654952629.240692 iteration: 49785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.10523 FastRCNN total loss: 0.23663 L1 loss: 0.0000e+00 L2 loss: 0.61177 Learning rate: 0.002 Mask loss: 0.1601 RPN box loss: 0.03265 RPN score loss: 0.00493 RPN total loss: 0.03759 Total loss: 1.04609 timestamp: 1654952632.4411905 iteration: 49790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08877 FastRCNN class loss: 0.05854 FastRCNN total loss: 0.14731 L1 loss: 0.0000e+00 L2 loss: 0.61176 Learning rate: 0.002 Mask loss: 0.13447 RPN box loss: 0.00491 RPN score loss: 0.00235 RPN total loss: 0.00727 Total loss: 0.90082 timestamp: 1654952635.5654535 iteration: 49795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15093 FastRCNN class loss: 0.14748 FastRCNN total loss: 0.29841 L1 loss: 0.0000e+00 L2 loss: 0.61175 Learning rate: 0.002 Mask loss: 0.20526 RPN box loss: 0.05773 RPN score loss: 0.01623 RPN total loss: 0.07396 Total loss: 1.18938 timestamp: 1654952638.840101 iteration: 49800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07473 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.15037 L1 loss: 0.0000e+00 L2 loss: 0.61174 Learning rate: 0.002 Mask loss: 0.09271 RPN box loss: 0.01237 RPN score loss: 0.00581 RPN total loss: 0.01818 Total loss: 0.87302 timestamp: 1654952642.0697503 iteration: 49805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09192 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.14365 L1 loss: 0.0000e+00 L2 loss: 0.61174 Learning rate: 0.002 Mask loss: 0.09765 RPN box loss: 0.00219 RPN score loss: 0.00168 RPN total loss: 0.00387 Total loss: 0.85691 timestamp: 1654952645.375701 iteration: 49810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06202 FastRCNN class loss: 0.03936 FastRCNN total loss: 0.10138 L1 loss: 0.0000e+00 L2 loss: 0.61173 Learning rate: 0.002 Mask loss: 0.09949 RPN box loss: 0.00947 RPN score loss: 0.00561 RPN total loss: 0.01509 Total loss: 0.82769 timestamp: 1654952648.6010978 iteration: 49815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09321 FastRCNN class loss: 0.11308 FastRCNN total loss: 0.20628 L1 loss: 0.0000e+00 L2 loss: 0.61172 Learning rate: 0.002 Mask loss: 0.1254 RPN box loss: 0.01578 RPN score loss: 0.01043 RPN total loss: 0.02621 Total loss: 0.96961 timestamp: 1654952651.997563 iteration: 49820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1129 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.18795 L1 loss: 0.0000e+00 L2 loss: 0.61171 Learning rate: 0.002 Mask loss: 0.15223 RPN box loss: 0.01905 RPN score loss: 0.00711 RPN total loss: 0.02616 Total loss: 0.97805 timestamp: 1654952655.2818918 iteration: 49825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12826 FastRCNN class loss: 0.08091 FastRCNN total loss: 0.20916 L1 loss: 0.0000e+00 L2 loss: 0.6117 Learning rate: 0.002 Mask loss: 0.14459 RPN box loss: 0.00674 RPN score loss: 0.00555 RPN total loss: 0.0123 Total loss: 0.97775 timestamp: 1654952658.5301945 iteration: 49830 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0542 FastRCNN class loss: 0.03684 FastRCNN total loss: 0.09104 L1 loss: 0.0000e+00 L2 loss: 0.61169 Learning rate: 0.002 Mask loss: 0.12308 RPN box loss: 0.0052 RPN score loss: 0.00231 RPN total loss: 0.00751 Total loss: 0.83332 timestamp: 1654952661.928677 iteration: 49835 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16863 FastRCNN class loss: 0.09644 FastRCNN total loss: 0.26507 L1 loss: 0.0000e+00 L2 loss: 0.61168 Learning rate: 0.002 Mask loss: 0.18877 RPN box loss: 0.01634 RPN score loss: 0.00115 RPN total loss: 0.0175 Total loss: 1.08301 timestamp: 1654952665.1577237 iteration: 49840 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06769 FastRCNN class loss: 0.06332 FastRCNN total loss: 0.13101 L1 loss: 0.0000e+00 L2 loss: 0.61168 Learning rate: 0.002 Mask loss: 0.14842 RPN box loss: 0.00621 RPN score loss: 0.00427 RPN total loss: 0.01048 Total loss: 0.90158 timestamp: 1654952668.4245803 iteration: 49845 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08265 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.15044 L1 loss: 0.0000e+00 L2 loss: 0.61167 Learning rate: 0.002 Mask loss: 0.11085 RPN box loss: 0.0167 RPN score loss: 0.01122 RPN total loss: 0.02792 Total loss: 0.90088 timestamp: 1654952671.63712 iteration: 49850 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09522 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.16524 L1 loss: 0.0000e+00 L2 loss: 0.61166 Learning rate: 0.002 Mask loss: 0.14294 RPN box loss: 0.027 RPN score loss: 0.00497 RPN total loss: 0.03198 Total loss: 0.95183 timestamp: 1654952674.943386 iteration: 49855 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10729 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.17986 L1 loss: 0.0000e+00 L2 loss: 0.61166 Learning rate: 0.002 Mask loss: 0.12034 RPN box loss: 0.00946 RPN score loss: 0.00494 RPN total loss: 0.0144 Total loss: 0.92625 timestamp: 1654952678.1369567 iteration: 49860 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0625 FastRCNN class loss: 0.0482 FastRCNN total loss: 0.1107 L1 loss: 0.0000e+00 L2 loss: 0.61165 Learning rate: 0.002 Mask loss: 0.1193 RPN box loss: 0.00693 RPN score loss: 0.00451 RPN total loss: 0.01145 Total loss: 0.85309 timestamp: 1654952681.4737957 iteration: 49865 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08363 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.14459 L1 loss: 0.0000e+00 L2 loss: 0.61164 Learning rate: 0.002 Mask loss: 0.15127 RPN box loss: 0.00723 RPN score loss: 0.00696 RPN total loss: 0.0142 Total loss: 0.92169 timestamp: 1654952684.7506776 iteration: 49870 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08821 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.1525 L1 loss: 0.0000e+00 L2 loss: 0.61163 Learning rate: 0.002 Mask loss: 0.12324 RPN box loss: 0.01247 RPN score loss: 0.00532 RPN total loss: 0.0178 Total loss: 0.90516 timestamp: 1654952687.9572642 iteration: 49875 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10752 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.18513 L1 loss: 0.0000e+00 L2 loss: 0.61162 Learning rate: 0.002 Mask loss: 0.14212 RPN box loss: 0.01706 RPN score loss: 0.00604 RPN total loss: 0.0231 Total loss: 0.96197 timestamp: 1654952691.3089068 iteration: 49880 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10722 FastRCNN class loss: 0.0634 FastRCNN total loss: 0.17063 L1 loss: 0.0000e+00 L2 loss: 0.61161 Learning rate: 0.002 Mask loss: 0.15474 RPN box loss: 0.00681 RPN score loss: 0.00946 RPN total loss: 0.01627 Total loss: 0.95324 timestamp: 1654952694.5513785 iteration: 49885 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07717 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.14912 L1 loss: 0.0000e+00 L2 loss: 0.6116 Learning rate: 0.002 Mask loss: 0.1417 RPN box loss: 0.01913 RPN score loss: 0.00401 RPN total loss: 0.02314 Total loss: 0.92556 timestamp: 1654952697.8830466 iteration: 49890 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10315 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.18892 L1 loss: 0.0000e+00 L2 loss: 0.61159 Learning rate: 0.002 Mask loss: 0.13317 RPN box loss: 0.01717 RPN score loss: 0.00857 RPN total loss: 0.02574 Total loss: 0.95942 timestamp: 1654952701.0905318 iteration: 49895 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10951 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.16303 L1 loss: 0.0000e+00 L2 loss: 0.61158 Learning rate: 0.002 Mask loss: 0.13581 RPN box loss: 0.00578 RPN score loss: 0.00278 RPN total loss: 0.00855 Total loss: 0.91897 timestamp: 1654952704.3632894 iteration: 49900 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07386 FastRCNN class loss: 0.07653 FastRCNN total loss: 0.15039 L1 loss: 0.0000e+00 L2 loss: 0.61157 Learning rate: 0.002 Mask loss: 0.11676 RPN box loss: 0.00877 RPN score loss: 0.00546 RPN total loss: 0.01423 Total loss: 0.89295 timestamp: 1654952707.6473534 iteration: 49905 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14019 FastRCNN class loss: 0.12215 FastRCNN total loss: 0.26234 L1 loss: 0.0000e+00 L2 loss: 0.61156 Learning rate: 0.002 Mask loss: 0.26444 RPN box loss: 0.02085 RPN score loss: 0.01282 RPN total loss: 0.03367 Total loss: 1.172 timestamp: 1654952711.0519497 iteration: 49910 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14112 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.2234 L1 loss: 0.0000e+00 L2 loss: 0.61155 Learning rate: 0.002 Mask loss: 0.16334 RPN box loss: 0.02325 RPN score loss: 0.00233 RPN total loss: 0.02558 Total loss: 1.02386 timestamp: 1654952714.300933 iteration: 49915 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10807 FastRCNN class loss: 0.06081 FastRCNN total loss: 0.16887 L1 loss: 0.0000e+00 L2 loss: 0.61154 Learning rate: 0.002 Mask loss: 0.15874 RPN box loss: 0.0331 RPN score loss: 0.00942 RPN total loss: 0.04252 Total loss: 0.98166 timestamp: 1654952717.5213633 iteration: 49920 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04859 FastRCNN class loss: 0.0416 FastRCNN total loss: 0.09019 L1 loss: 0.0000e+00 L2 loss: 0.61153 Learning rate: 0.002 Mask loss: 0.0854 RPN box loss: 0.02109 RPN score loss: 0.00789 RPN total loss: 0.02899 Total loss: 0.8161 timestamp: 1654952720.886078 iteration: 49925 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17625 FastRCNN class loss: 0.09821 FastRCNN total loss: 0.27446 L1 loss: 0.0000e+00 L2 loss: 0.61152 Learning rate: 0.002 Mask loss: 0.22807 RPN box loss: 0.02045 RPN score loss: 0.00916 RPN total loss: 0.02961 Total loss: 1.14366 timestamp: 1654952724.120505 iteration: 49930 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.129 FastRCNN class loss: 0.09012 FastRCNN total loss: 0.21912 L1 loss: 0.0000e+00 L2 loss: 0.61151 Learning rate: 0.002 Mask loss: 0.17112 RPN box loss: 0.01192 RPN score loss: 0.00385 RPN total loss: 0.01577 Total loss: 1.01752 timestamp: 1654952727.3910158 iteration: 49935 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13714 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.21042 L1 loss: 0.0000e+00 L2 loss: 0.6115 Learning rate: 0.002 Mask loss: 0.13553 RPN box loss: 0.0209 RPN score loss: 0.00217 RPN total loss: 0.02307 Total loss: 0.98053 timestamp: 1654952730.6257944 iteration: 49940 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08566 FastRCNN class loss: 0.0939 FastRCNN total loss: 0.17955 L1 loss: 0.0000e+00 L2 loss: 0.61149 Learning rate: 0.002 Mask loss: 0.17254 RPN box loss: 0.01496 RPN score loss: 0.00478 RPN total loss: 0.01974 Total loss: 0.98332 timestamp: 1654952733.9077823 iteration: 49945 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08573 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.15678 L1 loss: 0.0000e+00 L2 loss: 0.61149 Learning rate: 0.002 Mask loss: 0.11766 RPN box loss: 0.01166 RPN score loss: 0.00274 RPN total loss: 0.0144 Total loss: 0.90033 timestamp: 1654952737.0746694 iteration: 49950 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12983 FastRCNN class loss: 0.08734 FastRCNN total loss: 0.21717 L1 loss: 0.0000e+00 L2 loss: 0.61148 Learning rate: 0.002 Mask loss: 0.1328 RPN box loss: 0.01728 RPN score loss: 0.00211 RPN total loss: 0.01939 Total loss: 0.98084 timestamp: 1654952740.2891269 iteration: 49955 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07664 FastRCNN class loss: 0.05087 FastRCNN total loss: 0.12751 L1 loss: 0.0000e+00 L2 loss: 0.61147 Learning rate: 0.002 Mask loss: 0.14821 RPN box loss: 0.0047 RPN score loss: 0.00146 RPN total loss: 0.00616 Total loss: 0.89335 timestamp: 1654952743.46228 iteration: 49960 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12224 FastRCNN class loss: 0.05405 FastRCNN total loss: 0.17629 L1 loss: 0.0000e+00 L2 loss: 0.61146 Learning rate: 0.002 Mask loss: 0.11641 RPN box loss: 0.03078 RPN score loss: 0.00354 RPN total loss: 0.03431 Total loss: 0.93847 timestamp: 1654952746.742506 iteration: 49965 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05991 FastRCNN class loss: 0.04106 FastRCNN total loss: 0.10097 L1 loss: 0.0000e+00 L2 loss: 0.61146 Learning rate: 0.002 Mask loss: 0.09534 RPN box loss: 0.00629 RPN score loss: 0.00044 RPN total loss: 0.00672 Total loss: 0.81449 timestamp: 1654952749.968749 iteration: 49970 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11222 FastRCNN class loss: 0.06718 FastRCNN total loss: 0.17939 L1 loss: 0.0000e+00 L2 loss: 0.61145 Learning rate: 0.002 Mask loss: 0.15982 RPN box loss: 0.01535 RPN score loss: 0.0042 RPN total loss: 0.01955 Total loss: 0.97022 timestamp: 1654952753.19895 iteration: 49975 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05066 FastRCNN class loss: 0.04262 FastRCNN total loss: 0.09328 L1 loss: 0.0000e+00 L2 loss: 0.61144 Learning rate: 0.002 Mask loss: 0.10013 RPN box loss: 0.00574 RPN score loss: 0.00195 RPN total loss: 0.00769 Total loss: 0.81254 timestamp: 1654952756.442642 iteration: 49980 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16132 FastRCNN class loss: 0.11156 FastRCNN total loss: 0.27287 L1 loss: 0.0000e+00 L2 loss: 0.61143 Learning rate: 0.002 Mask loss: 0.11399 RPN box loss: 0.04366 RPN score loss: 0.00561 RPN total loss: 0.04927 Total loss: 1.04756 timestamp: 1654952759.5345829 iteration: 49985 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11869 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.19363 L1 loss: 0.0000e+00 L2 loss: 0.61142 Learning rate: 0.002 Mask loss: 0.18403 RPN box loss: 0.02501 RPN score loss: 0.00757 RPN total loss: 0.03259 Total loss: 1.02166 timestamp: 1654952762.8223536 iteration: 49990 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11769 FastRCNN class loss: 0.08996 FastRCNN total loss: 0.20764 L1 loss: 0.0000e+00 L2 loss: 0.61141 Learning rate: 0.002 Mask loss: 0.08812 RPN box loss: 0.00447 RPN score loss: 0.00095 RPN total loss: 0.00542 Total loss: 0.9126 timestamp: 1654952766.0660253 iteration: 49995 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12856 FastRCNN class loss: 0.0775 FastRCNN total loss: 0.20606 L1 loss: 0.0000e+00 L2 loss: 0.6114 Learning rate: 0.002 Mask loss: 0.20624 RPN box loss: 0.02355 RPN score loss: 0.0079 RPN total loss: 0.03145 Total loss: 1.05516 timestamp: 1654952769.4702256 iteration: 50000 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07975 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.15359 L1 loss: 0.0000e+00 L2 loss: 0.61139 Learning rate: 0.002 Mask loss: 0.16304 RPN box loss: 0.01926 RPN score loss: 0.00311 RPN total loss: 0.02237 Total loss: 0.9504 Saving checkpoints for 50000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-50000.tlt. ================================= Start evaluation cycle 05 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-50000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.0965s - Throughput: 0.8 imgs/s Running inference on batch 002/125... - Step Time: 0.3448s - Throughput: 11.6 imgs/s Running inference on batch 003/125... - Step Time: 0.3298s - Throughput: 12.1 imgs/s Running inference on batch 004/125... - Step Time: 0.3450s - Throughput: 11.6 imgs/s Running inference on batch 005/125... - Step Time: 0.3861s - Throughput: 10.4 imgs/s Running inference on batch 006/125... - Step Time: 0.3444s - Throughput: 11.6 imgs/s Running inference on batch 007/125... - Step Time: 0.3320s - Throughput: 12.0 imgs/s Running inference on batch 008/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 009/125... - Step Time: 0.3040s - Throughput: 13.2 imgs/s Running inference on batch 010/125... - Step Time: 0.3356s - Throughput: 11.9 imgs/s Running inference on batch 011/125... - Step Time: 0.3079s - Throughput: 13.0 imgs/s Running inference on batch 012/125... - Step Time: 0.3332s - Throughput: 12.0 imgs/s Running inference on batch 013/125... - Step Time: 0.3305s - Throughput: 12.1 imgs/s Running inference on batch 014/125... - Step Time: 0.3466s - Throughput: 11.5 imgs/s Running inference on batch 015/125... - Step Time: 0.3430s - Throughput: 11.7 imgs/s Running inference on batch 016/125... - Step Time: 0.3399s - Throughput: 11.8 imgs/s Running inference on batch 017/125... - Step Time: 0.3423s - Throughput: 11.7 imgs/s Running inference on batch 018/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 019/125... - Step Time: 0.3028s - Throughput: 13.2 imgs/s Running inference on batch 020/125... - Step Time: 0.3312s - Throughput: 12.1 imgs/s Running inference on batch 021/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 022/125... - Step Time: 0.3483s - Throughput: 11.5 imgs/s Running inference on batch 023/125... - Step Time: 0.3396s - Throughput: 11.8 imgs/s Running inference on batch 024/125... - Step Time: 0.3254s - Throughput: 12.3 imgs/s Running inference on batch 025/125... - Step Time: 0.3329s - Throughput: 12.0 imgs/s Running inference on batch 026/125... - Step Time: 0.3347s - Throughput: 12.0 imgs/s Running inference on batch 027/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 028/125... - Step Time: 0.3372s - Throughput: 11.9 imgs/s Running inference on batch 029/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 030/125... - Step Time: 0.3379s - Throughput: 11.8 imgs/s Running inference on batch 031/125... - Step Time: 0.3456s - Throughput: 11.6 imgs/s Running inference on batch 032/125... - Step Time: 0.3409s - Throughput: 11.7 imgs/s Running inference on batch 033/125... - Step Time: 0.3544s - Throughput: 11.3 imgs/s Running inference on batch 034/125... - Step Time: 0.3398s - Throughput: 11.8 imgs/s Running inference on batch 035/125... - Step Time: 0.3208s - Throughput: 12.5 imgs/s Running inference on batch 036/125... - Step Time: 0.3416s - Throughput: 11.7 imgs/s Running inference on batch 037/125... - Step Time: 0.3412s - Throughput: 11.7 imgs/s Running inference on batch 038/125... - Step Time: 0.3347s - Throughput: 12.0 imgs/s Running inference on batch 039/125... - Step Time: 0.3402s - Throughput: 11.8 imgs/s Running inference on batch 040/125... - Step Time: 0.3479s - Throughput: 11.5 imgs/s Running inference on batch 041/125... - Step Time: 0.3065s - Throughput: 13.1 imgs/s Running inference on batch 042/125... - Step Time: 0.3289s - Throughput: 12.2 imgs/s Running inference on batch 043/125... - Step Time: 0.3260s - Throughput: 12.3 imgs/s Running inference on batch 044/125... - Step Time: 0.3272s - Throughput: 12.2 imgs/s Running inference on batch 045/125... - Step Time: 0.3355s - Throughput: 11.9 imgs/s Running inference on batch 046/125... - Step Time: 0.3404s - Throughput: 11.8 imgs/s Running inference on batch 047/125... - Step Time: 0.3406s - Throughput: 11.7 imgs/s Running inference on batch 048/125... - Step Time: 0.3518s - Throughput: 11.4 imgs/s Running inference on batch 049/125... - Step Time: 0.3321s - Throughput: 12.0 imgs/s Running inference on batch 050/125... - Step Time: 0.3382s - Throughput: 11.8 imgs/s Running inference on batch 051/125... - Step Time: 0.3361s - Throughput: 11.9 imgs/s Running inference on batch 052/125... - Step Time: 0.2961s - Throughput: 13.5 imgs/s Running inference on batch 053/125... - Step Time: 0.2912s - Throughput: 13.7 imgs/s Running inference on batch 054/125... - Step Time: 0.3272s - Throughput: 12.2 imgs/s Running inference on batch 055/125... - Step Time: 0.3272s - Throughput: 12.2 imgs/s Running inference on batch 056/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 057/125... - Step Time: 0.3400s - Throughput: 11.8 imgs/s Running inference on batch 058/125... - Step Time: 0.3387s - Throughput: 11.8 imgs/s Running inference on batch 059/125... - Step Time: 0.3345s - 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Throughput: 11.8 imgs/s Running inference on batch 120/125... - Step Time: 0.3414s - Throughput: 11.7 imgs/s Running inference on batch 121/125... - Step Time: 0.3300s - Throughput: 12.1 imgs/s Running inference on batch 122/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 123/125... - Step Time: 0.3322s - Throughput: 12.0 imgs/s Running inference on batch 124/125... - Step Time: 0.3557s - Throughput: 11.2 imgs/s Running inference on batch 125/125... - Step Time: 0.3382s - Throughput: 11.8 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 11.8 samples/sec Total processed steps: 125 Total processing time: 0.0h 24m 34s ==================== Metrics ==================== AP: 0.214040890 AP50: 0.331665814 AP75: 0.218266159 APl: 0.250781059 APm: 0.056060340 APs: 0.009431091 ARl: 0.452491164 ARm: 0.111719489 ARmax1: 0.296205401 ARmax10: 0.385236800 ARmax100: 0.389807731 ARs: 0.020177709 mask_AP: 0.168079302 mask_AP50: 0.283871949 mask_AP75: 0.173493460 mask_APl: 0.199278891 mask_APm: 0.030322967 mask_APs: 0.000604134 mask_ARl: 0.323905051 mask_ARm: 0.060097944 mask_ARmax1: 0.227029905 mask_ARmax10: 0.272278666 mask_ARmax100: 0.274468541 mask_ARs: 0.008997585 ================================= Start training cycle 06 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654953922.746327 iteration: 50005 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10107 FastRCNN class loss: 0.04795 FastRCNN total loss: 0.14903 L1 loss: 0.0000e+00 L2 loss: 0.61138 Learning rate: 0.002 Mask loss: 0.10606 RPN box loss: 0.01367 RPN score loss: 0.00141 RPN total loss: 0.01508 Total loss: 0.88155 timestamp: 1654953925.9282675 iteration: 50010 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05868 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.1204 L1 loss: 0.0000e+00 L2 loss: 0.61138 Learning rate: 0.002 Mask loss: 0.10811 RPN box loss: 0.01195 RPN score loss: 0.00165 RPN total loss: 0.0136 Total loss: 0.85349 timestamp: 1654953929.2678432 iteration: 50015 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07857 FastRCNN class loss: 0.05407 FastRCNN total loss: 0.13263 L1 loss: 0.0000e+00 L2 loss: 0.61137 Learning rate: 0.002 Mask loss: 0.14325 RPN box loss: 0.00536 RPN score loss: 0.00416 RPN total loss: 0.00951 Total loss: 0.89677 timestamp: 1654953932.42208 iteration: 50020 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13749 FastRCNN class loss: 0.06423 FastRCNN total loss: 0.20172 L1 loss: 0.0000e+00 L2 loss: 0.61136 Learning rate: 0.002 Mask loss: 0.14107 RPN box loss: 0.0093 RPN score loss: 0.00158 RPN total loss: 0.01088 Total loss: 0.96503 timestamp: 1654953935.8356085 iteration: 50025 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10297 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.15975 L1 loss: 0.0000e+00 L2 loss: 0.61135 Learning rate: 0.002 Mask loss: 0.13128 RPN box loss: 0.02933 RPN score loss: 0.00242 RPN total loss: 0.03175 Total loss: 0.93414 timestamp: 1654953939.025877 iteration: 50030 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0829 FastRCNN class loss: 0.06764 FastRCNN total loss: 0.15054 L1 loss: 0.0000e+00 L2 loss: 0.61135 Learning rate: 0.002 Mask loss: 0.0807 RPN box loss: 0.00703 RPN score loss: 0.00387 RPN total loss: 0.0109 Total loss: 0.85349 timestamp: 1654953942.3612027 iteration: 50035 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06565 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.12628 L1 loss: 0.0000e+00 L2 loss: 0.61134 Learning rate: 0.002 Mask loss: 0.15076 RPN box loss: 0.00764 RPN score loss: 0.00507 RPN total loss: 0.01271 Total loss: 0.90108 timestamp: 1654953945.9161108 iteration: 50040 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07693 FastRCNN class loss: 0.0655 FastRCNN total loss: 0.14243 L1 loss: 0.0000e+00 L2 loss: 0.61133 Learning rate: 0.002 Mask loss: 0.1481 RPN box loss: 0.0053 RPN score loss: 0.00096 RPN total loss: 0.00626 Total loss: 0.90812 timestamp: 1654953949.1086464 iteration: 50045 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14045 FastRCNN class loss: 0.07675 FastRCNN total loss: 0.21719 L1 loss: 0.0000e+00 L2 loss: 0.61132 Learning rate: 0.002 Mask loss: 0.09358 RPN box loss: 0.01268 RPN score loss: 0.00583 RPN total loss: 0.0185 Total loss: 0.9406 timestamp: 1654953952.3557386 iteration: 50050 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08923 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 0.61131 Learning rate: 0.002 Mask loss: 0.14037 RPN box loss: 0.00946 RPN score loss: 0.0014 RPN total loss: 0.01085 Total loss: 0.92618 timestamp: 1654953955.618973 iteration: 50055 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07291 FastRCNN class loss: 0.05491 FastRCNN total loss: 0.12783 L1 loss: 0.0000e+00 L2 loss: 0.6113 Learning rate: 0.002 Mask loss: 0.10664 RPN box loss: 0.00934 RPN score loss: 0.00302 RPN total loss: 0.01236 Total loss: 0.85813 timestamp: 1654953958.915908 iteration: 50060 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12202 FastRCNN class loss: 0.13007 FastRCNN total loss: 0.25209 L1 loss: 0.0000e+00 L2 loss: 0.61129 Learning rate: 0.002 Mask loss: 0.19187 RPN box loss: 0.02747 RPN score loss: 0.01145 RPN total loss: 0.03892 Total loss: 1.09417 timestamp: 1654953962.0975473 iteration: 50065 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09453 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.15232 L1 loss: 0.0000e+00 L2 loss: 0.61128 Learning rate: 0.002 Mask loss: 0.14871 RPN box loss: 0.01722 RPN score loss: 0.00135 RPN total loss: 0.01857 Total loss: 0.93088 timestamp: 1654953965.331848 iteration: 50070 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11457 FastRCNN class loss: 0.09426 FastRCNN total loss: 0.20883 L1 loss: 0.0000e+00 L2 loss: 0.61127 Learning rate: 0.002 Mask loss: 0.10946 RPN box loss: 0.01414 RPN score loss: 0.00448 RPN total loss: 0.01862 Total loss: 0.94818 timestamp: 1654953968.5665014 iteration: 50075 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10826 FastRCNN class loss: 0.07631 FastRCNN total loss: 0.18457 L1 loss: 0.0000e+00 L2 loss: 0.61126 Learning rate: 0.002 Mask loss: 0.14175 RPN box loss: 0.01311 RPN score loss: 0.00517 RPN total loss: 0.01829 Total loss: 0.95586 timestamp: 1654953972.020685 iteration: 50080 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06219 FastRCNN class loss: 0.03089 FastRCNN total loss: 0.09308 L1 loss: 0.0000e+00 L2 loss: 0.61126 Learning rate: 0.002 Mask loss: 0.12625 RPN box loss: 0.00512 RPN score loss: 0.00445 RPN total loss: 0.00957 Total loss: 0.84016 timestamp: 1654953975.243691 iteration: 50085 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11971 FastRCNN class loss: 0.07949 FastRCNN total loss: 0.1992 L1 loss: 0.0000e+00 L2 loss: 0.61125 Learning rate: 0.002 Mask loss: 0.17835 RPN box loss: 0.01457 RPN score loss: 0.002 RPN total loss: 0.01657 Total loss: 1.00538 timestamp: 1654953978.5633833 iteration: 50090 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13206 FastRCNN class loss: 0.08865 FastRCNN total loss: 0.22072 L1 loss: 0.0000e+00 L2 loss: 0.61124 Learning rate: 0.002 Mask loss: 0.1269 RPN box loss: 0.01349 RPN score loss: 0.00504 RPN total loss: 0.01852 Total loss: 0.97738 timestamp: 1654953981.7957773 iteration: 50095 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06294 FastRCNN class loss: 0.04175 FastRCNN total loss: 0.10468 L1 loss: 0.0000e+00 L2 loss: 0.61123 Learning rate: 0.002 Mask loss: 0.07961 RPN box loss: 0.01186 RPN score loss: 0.00531 RPN total loss: 0.01717 Total loss: 0.8127 timestamp: 1654953985.000954 iteration: 50100 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09013 FastRCNN class loss: 0.04953 FastRCNN total loss: 0.13966 L1 loss: 0.0000e+00 L2 loss: 0.61122 Learning rate: 0.002 Mask loss: 0.09576 RPN box loss: 0.02357 RPN score loss: 0.00767 RPN total loss: 0.03124 Total loss: 0.87788 timestamp: 1654953988.2661197 iteration: 50105 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07202 FastRCNN class loss: 0.07511 FastRCNN total loss: 0.14714 L1 loss: 0.0000e+00 L2 loss: 0.61121 Learning rate: 0.002 Mask loss: 0.11432 RPN box loss: 0.04106 RPN score loss: 0.0044 RPN total loss: 0.04545 Total loss: 0.91812 timestamp: 1654953991.4795945 iteration: 50110 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0863 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.15195 L1 loss: 0.0000e+00 L2 loss: 0.6112 Learning rate: 0.002 Mask loss: 0.11439 RPN box loss: 0.0047 RPN score loss: 0.00594 RPN total loss: 0.01064 Total loss: 0.88818 timestamp: 1654953994.7500324 iteration: 50115 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13887 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.21634 L1 loss: 0.0000e+00 L2 loss: 0.61119 Learning rate: 0.002 Mask loss: 0.16002 RPN box loss: 0.00873 RPN score loss: 0.00511 RPN total loss: 0.01385 Total loss: 1.0014 timestamp: 1654953997.9627907 iteration: 50120 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02822 FastRCNN class loss: 0.03218 FastRCNN total loss: 0.0604 L1 loss: 0.0000e+00 L2 loss: 0.61118 Learning rate: 0.002 Mask loss: 0.08605 RPN box loss: 0.00391 RPN score loss: 0.00253 RPN total loss: 0.00644 Total loss: 0.76408 timestamp: 1654954001.2994611 iteration: 50125 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.06743 FastRCNN total loss: 0.14159 L1 loss: 0.0000e+00 L2 loss: 0.61117 Learning rate: 0.002 Mask loss: 0.10738 RPN box loss: 0.0062 RPN score loss: 0.00437 RPN total loss: 0.01057 Total loss: 0.87071 timestamp: 1654954004.5197136 iteration: 50130 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08971 FastRCNN class loss: 0.07723 FastRCNN total loss: 0.16694 L1 loss: 0.0000e+00 L2 loss: 0.61117 Learning rate: 0.002 Mask loss: 0.15822 RPN box loss: 0.02584 RPN score loss: 0.008 RPN total loss: 0.03385 Total loss: 0.97018 timestamp: 1654954007.8485985 iteration: 50135 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09806 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.17019 L1 loss: 0.0000e+00 L2 loss: 0.61116 Learning rate: 0.002 Mask loss: 0.14588 RPN box loss: 0.01608 RPN score loss: 0.00522 RPN total loss: 0.0213 Total loss: 0.94852 timestamp: 1654954011.146841 iteration: 50140 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10621 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.1876 L1 loss: 0.0000e+00 L2 loss: 0.61115 Learning rate: 0.002 Mask loss: 0.1359 RPN box loss: 0.01904 RPN score loss: 0.0023 RPN total loss: 0.02134 Total loss: 0.95599 timestamp: 1654954014.3688343 iteration: 50145 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10942 FastRCNN class loss: 0.05991 FastRCNN total loss: 0.16933 L1 loss: 0.0000e+00 L2 loss: 0.61114 Learning rate: 0.002 Mask loss: 0.08924 RPN box loss: 0.0046 RPN score loss: 0.00117 RPN total loss: 0.00576 Total loss: 0.87547 timestamp: 1654954017.6244721 iteration: 50150 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09917 FastRCNN class loss: 0.08666 FastRCNN total loss: 0.18582 L1 loss: 0.0000e+00 L2 loss: 0.61113 Learning rate: 0.002 Mask loss: 0.11588 RPN box loss: 0.02463 RPN score loss: 0.00321 RPN total loss: 0.02783 Total loss: 0.94067 timestamp: 1654954020.7887688 iteration: 50155 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07242 FastRCNN class loss: 0.04111 FastRCNN total loss: 0.11352 L1 loss: 0.0000e+00 L2 loss: 0.61112 Learning rate: 0.002 Mask loss: 0.08494 RPN box loss: 0.00605 RPN score loss: 0.00163 RPN total loss: 0.00768 Total loss: 0.81726 timestamp: 1654954024.0441408 iteration: 50160 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09848 FastRCNN class loss: 0.07912 FastRCNN total loss: 0.1776 L1 loss: 0.0000e+00 L2 loss: 0.61111 Learning rate: 0.002 Mask loss: 0.15802 RPN box loss: 0.00531 RPN score loss: 0.00114 RPN total loss: 0.00645 Total loss: 0.95319 timestamp: 1654954027.2727888 iteration: 50165 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07362 FastRCNN class loss: 0.04837 FastRCNN total loss: 0.12199 L1 loss: 0.0000e+00 L2 loss: 0.6111 Learning rate: 0.002 Mask loss: 0.11153 RPN box loss: 0.0038 RPN score loss: 0.00235 RPN total loss: 0.00615 Total loss: 0.85076 timestamp: 1654954030.5968885 iteration: 50170 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10102 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.17398 L1 loss: 0.0000e+00 L2 loss: 0.61109 Learning rate: 0.002 Mask loss: 0.25841 RPN box loss: 0.02506 RPN score loss: 0.00561 RPN total loss: 0.03067 Total loss: 1.07415 timestamp: 1654954033.9044645 iteration: 50175 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08742 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.15576 L1 loss: 0.0000e+00 L2 loss: 0.61108 Learning rate: 0.002 Mask loss: 0.12086 RPN box loss: 0.00628 RPN score loss: 0.00272 RPN total loss: 0.009 Total loss: 0.8967 timestamp: 1654954037.2470508 iteration: 50180 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10909 FastRCNN class loss: 0.07156 FastRCNN total loss: 0.18064 L1 loss: 0.0000e+00 L2 loss: 0.61107 Learning rate: 0.002 Mask loss: 0.15556 RPN box loss: 0.0117 RPN score loss: 0.00274 RPN total loss: 0.01444 Total loss: 0.96172 timestamp: 1654954040.472246 iteration: 50185 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05588 FastRCNN class loss: 0.11733 FastRCNN total loss: 0.17322 L1 loss: 0.0000e+00 L2 loss: 0.61106 Learning rate: 0.002 Mask loss: 0.13524 RPN box loss: 0.01556 RPN score loss: 0.01359 RPN total loss: 0.02916 Total loss: 0.94867 timestamp: 1654954043.726284 iteration: 50190 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05488 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.12128 L1 loss: 0.0000e+00 L2 loss: 0.61105 Learning rate: 0.002 Mask loss: 0.13185 RPN box loss: 0.01802 RPN score loss: 0.00559 RPN total loss: 0.02361 Total loss: 0.88779 timestamp: 1654954046.9414504 iteration: 50195 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13221 FastRCNN class loss: 0.09827 FastRCNN total loss: 0.23049 L1 loss: 0.0000e+00 L2 loss: 0.61104 Learning rate: 0.002 Mask loss: 0.16814 RPN box loss: 0.01902 RPN score loss: 0.00763 RPN total loss: 0.02666 Total loss: 1.03632 timestamp: 1654954050.1417964 iteration: 50200 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15538 FastRCNN class loss: 0.09071 FastRCNN total loss: 0.24609 L1 loss: 0.0000e+00 L2 loss: 0.61103 Learning rate: 0.002 Mask loss: 0.11578 RPN box loss: 0.02352 RPN score loss: 0.00365 RPN total loss: 0.02717 Total loss: 1.00008 timestamp: 1654954053.3640928 iteration: 50205 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07082 FastRCNN class loss: 0.09256 FastRCNN total loss: 0.16339 L1 loss: 0.0000e+00 L2 loss: 0.61103 Learning rate: 0.002 Mask loss: 0.11346 RPN box loss: 0.01371 RPN score loss: 0.00197 RPN total loss: 0.01568 Total loss: 0.90355 timestamp: 1654954056.6042485 iteration: 50210 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.17517 L1 loss: 0.0000e+00 L2 loss: 0.61102 Learning rate: 0.002 Mask loss: 0.15102 RPN box loss: 0.0113 RPN score loss: 0.00496 RPN total loss: 0.01625 Total loss: 0.95346 timestamp: 1654954059.8688893 iteration: 50215 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10461 FastRCNN class loss: 0.07239 FastRCNN total loss: 0.177 L1 loss: 0.0000e+00 L2 loss: 0.61101 Learning rate: 0.002 Mask loss: 0.21795 RPN box loss: 0.00819 RPN score loss: 0.00373 RPN total loss: 0.01192 Total loss: 1.01788 timestamp: 1654954063.1021855 iteration: 50220 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04521 FastRCNN class loss: 0.04438 FastRCNN total loss: 0.08959 L1 loss: 0.0000e+00 L2 loss: 0.611 Learning rate: 0.002 Mask loss: 0.08581 RPN box loss: 0.00838 RPN score loss: 0.00402 RPN total loss: 0.0124 Total loss: 0.79881 timestamp: 1654954066.3315635 iteration: 50225 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05314 FastRCNN class loss: 0.04579 FastRCNN total loss: 0.09893 L1 loss: 0.0000e+00 L2 loss: 0.61099 Learning rate: 0.002 Mask loss: 0.09688 RPN box loss: 0.01086 RPN score loss: 0.00616 RPN total loss: 0.01702 Total loss: 0.82382 timestamp: 1654954069.501208 iteration: 50230 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08673 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.15417 L1 loss: 0.0000e+00 L2 loss: 0.61098 Learning rate: 0.002 Mask loss: 0.16711 RPN box loss: 0.01204 RPN score loss: 0.00471 RPN total loss: 0.01675 Total loss: 0.94901 timestamp: 1654954072.7341197 iteration: 50235 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10957 FastRCNN class loss: 0.07616 FastRCNN total loss: 0.18573 L1 loss: 0.0000e+00 L2 loss: 0.61097 Learning rate: 0.002 Mask loss: 0.07868 RPN box loss: 0.00755 RPN score loss: 0.00143 RPN total loss: 0.00898 Total loss: 0.88436 timestamp: 1654954075.902733 iteration: 50240 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11392 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.16689 L1 loss: 0.0000e+00 L2 loss: 0.61096 Learning rate: 0.002 Mask loss: 0.10209 RPN box loss: 0.0068 RPN score loss: 0.00507 RPN total loss: 0.01187 Total loss: 0.89181 timestamp: 1654954079.246011 iteration: 50245 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06811 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.14252 L1 loss: 0.0000e+00 L2 loss: 0.61096 Learning rate: 0.002 Mask loss: 0.13881 RPN box loss: 0.01081 RPN score loss: 0.00279 RPN total loss: 0.0136 Total loss: 0.90589 timestamp: 1654954082.4474547 iteration: 50250 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08346 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.13371 L1 loss: 0.0000e+00 L2 loss: 0.61095 Learning rate: 0.002 Mask loss: 0.09599 RPN box loss: 0.00999 RPN score loss: 0.00213 RPN total loss: 0.01212 Total loss: 0.85277 timestamp: 1654954085.6318161 iteration: 50255 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08537 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.14419 L1 loss: 0.0000e+00 L2 loss: 0.61094 Learning rate: 0.002 Mask loss: 0.08093 RPN box loss: 0.00474 RPN score loss: 0.0021 RPN total loss: 0.00683 Total loss: 0.8429 timestamp: 1654954088.9271028 iteration: 50260 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06371 FastRCNN class loss: 0.05554 FastRCNN total loss: 0.11925 L1 loss: 0.0000e+00 L2 loss: 0.61093 Learning rate: 0.002 Mask loss: 0.10035 RPN box loss: 0.00539 RPN score loss: 0.00153 RPN total loss: 0.00692 Total loss: 0.83745 timestamp: 1654954092.0396533 iteration: 50265 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11719 FastRCNN class loss: 0.09226 FastRCNN total loss: 0.20945 L1 loss: 0.0000e+00 L2 loss: 0.61093 Learning rate: 0.002 Mask loss: 0.12798 RPN box loss: 0.01152 RPN score loss: 0.00435 RPN total loss: 0.01587 Total loss: 0.96422 timestamp: 1654954095.3382967 iteration: 50270 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10329 FastRCNN class loss: 0.06192 FastRCNN total loss: 0.16521 L1 loss: 0.0000e+00 L2 loss: 0.61092 Learning rate: 0.002 Mask loss: 0.20035 RPN box loss: 0.00847 RPN score loss: 0.00486 RPN total loss: 0.01333 Total loss: 0.98981 timestamp: 1654954098.5272543 iteration: 50275 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09613 FastRCNN class loss: 0.07371 FastRCNN total loss: 0.16984 L1 loss: 0.0000e+00 L2 loss: 0.61091 Learning rate: 0.002 Mask loss: 0.14255 RPN box loss: 0.02133 RPN score loss: 0.00211 RPN total loss: 0.02345 Total loss: 0.94674 timestamp: 1654954101.8988523 iteration: 50280 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13028 FastRCNN class loss: 0.05366 FastRCNN total loss: 0.18394 L1 loss: 0.0000e+00 L2 loss: 0.6109 Learning rate: 0.002 Mask loss: 0.14489 RPN box loss: 0.00422 RPN score loss: 0.00161 RPN total loss: 0.00583 Total loss: 0.94555 timestamp: 1654954105.0580451 iteration: 50285 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13056 FastRCNN class loss: 0.05286 FastRCNN total loss: 0.18342 L1 loss: 0.0000e+00 L2 loss: 0.61089 Learning rate: 0.002 Mask loss: 0.07957 RPN box loss: 0.02485 RPN score loss: 0.00488 RPN total loss: 0.02973 Total loss: 0.90361 timestamp: 1654954108.4220815 iteration: 50290 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07203 FastRCNN class loss: 0.06753 FastRCNN total loss: 0.13956 L1 loss: 0.0000e+00 L2 loss: 0.61088 Learning rate: 0.002 Mask loss: 0.10075 RPN box loss: 0.01207 RPN score loss: 0.00634 RPN total loss: 0.01841 Total loss: 0.8696 timestamp: 1654954111.6542573 iteration: 50295 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.06592 FastRCNN total loss: 0.16614 L1 loss: 0.0000e+00 L2 loss: 0.61087 Learning rate: 0.002 Mask loss: 0.12333 RPN box loss: 0.02547 RPN score loss: 0.0083 RPN total loss: 0.03377 Total loss: 0.93412 timestamp: 1654954115.0178583 iteration: 50300 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15567 FastRCNN class loss: 0.09976 FastRCNN total loss: 0.25543 L1 loss: 0.0000e+00 L2 loss: 0.61086 Learning rate: 0.002 Mask loss: 0.1628 RPN box loss: 0.02258 RPN score loss: 0.00384 RPN total loss: 0.02642 Total loss: 1.05551 timestamp: 1654954118.1567013 iteration: 50305 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06764 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.12366 L1 loss: 0.0000e+00 L2 loss: 0.61085 Learning rate: 0.002 Mask loss: 0.11777 RPN box loss: 0.0073 RPN score loss: 0.00642 RPN total loss: 0.01372 Total loss: 0.86601 timestamp: 1654954121.4119065 iteration: 50310 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11275 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.18173 L1 loss: 0.0000e+00 L2 loss: 0.61084 Learning rate: 0.002 Mask loss: 0.12777 RPN box loss: 0.01123 RPN score loss: 0.00187 RPN total loss: 0.0131 Total loss: 0.93344 timestamp: 1654954124.6076941 iteration: 50315 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12025 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.18185 L1 loss: 0.0000e+00 L2 loss: 0.61083 Learning rate: 0.002 Mask loss: 0.14847 RPN box loss: 0.02148 RPN score loss: 0.00314 RPN total loss: 0.02462 Total loss: 0.96577 timestamp: 1654954127.9416325 iteration: 50320 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11845 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.17901 L1 loss: 0.0000e+00 L2 loss: 0.61082 Learning rate: 0.002 Mask loss: 0.13055 RPN box loss: 0.01121 RPN score loss: 0.00425 RPN total loss: 0.01546 Total loss: 0.93585 timestamp: 1654954131.1463377 iteration: 50325 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06077 FastRCNN class loss: 0.03691 FastRCNN total loss: 0.09768 L1 loss: 0.0000e+00 L2 loss: 0.61081 Learning rate: 0.002 Mask loss: 0.12571 RPN box loss: 0.0057 RPN score loss: 0.00136 RPN total loss: 0.00706 Total loss: 0.84126 timestamp: 1654954134.3627954 iteration: 50330 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09258 FastRCNN class loss: 0.06423 FastRCNN total loss: 0.15681 L1 loss: 0.0000e+00 L2 loss: 0.61081 Learning rate: 0.002 Mask loss: 0.11299 RPN box loss: 0.01186 RPN score loss: 0.00434 RPN total loss: 0.0162 Total loss: 0.89681 timestamp: 1654954137.6399186 iteration: 50335 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10118 FastRCNN class loss: 0.07218 FastRCNN total loss: 0.17336 L1 loss: 0.0000e+00 L2 loss: 0.6108 Learning rate: 0.002 Mask loss: 0.12047 RPN box loss: 0.03517 RPN score loss: 0.01218 RPN total loss: 0.04735 Total loss: 0.95199 timestamp: 1654954140.8588412 iteration: 50340 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04999 FastRCNN class loss: 0.05442 FastRCNN total loss: 0.10441 L1 loss: 0.0000e+00 L2 loss: 0.61079 Learning rate: 0.002 Mask loss: 0.17428 RPN box loss: 0.01174 RPN score loss: 0.00237 RPN total loss: 0.01411 Total loss: 0.90358 timestamp: 1654954144.113975 iteration: 50345 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07891 FastRCNN class loss: 0.04604 FastRCNN total loss: 0.12495 L1 loss: 0.0000e+00 L2 loss: 0.61078 Learning rate: 0.002 Mask loss: 0.1428 RPN box loss: 0.00771 RPN score loss: 0.00645 RPN total loss: 0.01416 Total loss: 0.89268 timestamp: 1654954147.2829983 iteration: 50350 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12583 FastRCNN class loss: 0.0967 FastRCNN total loss: 0.22253 L1 loss: 0.0000e+00 L2 loss: 0.61077 Learning rate: 0.002 Mask loss: 0.24278 RPN box loss: 0.01593 RPN score loss: 0.00833 RPN total loss: 0.02426 Total loss: 1.10034 timestamp: 1654954150.5447145 iteration: 50355 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09805 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.15717 L1 loss: 0.0000e+00 L2 loss: 0.61076 Learning rate: 0.002 Mask loss: 0.08724 RPN box loss: 0.01034 RPN score loss: 0.00238 RPN total loss: 0.01272 Total loss: 0.86789 timestamp: 1654954153.788835 iteration: 50360 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1161 FastRCNN class loss: 0.10201 FastRCNN total loss: 0.21812 L1 loss: 0.0000e+00 L2 loss: 0.61075 Learning rate: 0.002 Mask loss: 0.1472 RPN box loss: 0.01999 RPN score loss: 0.00817 RPN total loss: 0.02815 Total loss: 1.00422 timestamp: 1654954157.0380962 iteration: 50365 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09378 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.61074 Learning rate: 0.002 Mask loss: 0.10428 RPN box loss: 0.02399 RPN score loss: 0.00207 RPN total loss: 0.02606 Total loss: 0.89614 timestamp: 1654954160.3302321 iteration: 50370 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07487 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.13648 L1 loss: 0.0000e+00 L2 loss: 0.61073 Learning rate: 0.002 Mask loss: 0.09516 RPN box loss: 0.02104 RPN score loss: 0.00494 RPN total loss: 0.02598 Total loss: 0.86835 timestamp: 1654954163.6312647 iteration: 50375 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07667 FastRCNN class loss: 0.06165 FastRCNN total loss: 0.13832 L1 loss: 0.0000e+00 L2 loss: 0.61072 Learning rate: 0.002 Mask loss: 0.21114 RPN box loss: 0.01814 RPN score loss: 0.00291 RPN total loss: 0.02105 Total loss: 0.98122 timestamp: 1654954166.9299467 iteration: 50380 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09131 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.17807 L1 loss: 0.0000e+00 L2 loss: 0.61071 Learning rate: 0.002 Mask loss: 0.15203 RPN box loss: 0.01844 RPN score loss: 0.00613 RPN total loss: 0.02458 Total loss: 0.96538 timestamp: 1654954170.107967 iteration: 50385 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19236 FastRCNN class loss: 0.12045 FastRCNN total loss: 0.31281 L1 loss: 0.0000e+00 L2 loss: 0.6107 Learning rate: 0.002 Mask loss: 0.15761 RPN box loss: 0.02548 RPN score loss: 0.02741 RPN total loss: 0.05288 Total loss: 1.13399 timestamp: 1654954173.3800855 iteration: 50390 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08618 FastRCNN class loss: 0.0507 FastRCNN total loss: 0.13689 L1 loss: 0.0000e+00 L2 loss: 0.61069 Learning rate: 0.002 Mask loss: 0.20991 RPN box loss: 0.00401 RPN score loss: 0.00309 RPN total loss: 0.0071 Total loss: 0.96458 timestamp: 1654954176.625039 iteration: 50395 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08474 FastRCNN class loss: 0.11207 FastRCNN total loss: 0.19681 L1 loss: 0.0000e+00 L2 loss: 0.61068 Learning rate: 0.002 Mask loss: 0.12406 RPN box loss: 0.01255 RPN score loss: 0.00315 RPN total loss: 0.0157 Total loss: 0.94725 timestamp: 1654954179.9088178 iteration: 50400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06912 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.12017 L1 loss: 0.0000e+00 L2 loss: 0.61067 Learning rate: 0.002 Mask loss: 0.12332 RPN box loss: 0.00253 RPN score loss: 0.00243 RPN total loss: 0.00495 Total loss: 0.85912 timestamp: 1654954183.1194046 iteration: 50405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04841 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.10862 L1 loss: 0.0000e+00 L2 loss: 0.61066 Learning rate: 0.002 Mask loss: 0.11796 RPN box loss: 0.00662 RPN score loss: 0.00125 RPN total loss: 0.00786 Total loss: 0.84511 timestamp: 1654954186.4187975 iteration: 50410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.10413 FastRCNN total loss: 0.2046 L1 loss: 0.0000e+00 L2 loss: 0.61065 Learning rate: 0.002 Mask loss: 0.1257 RPN box loss: 0.02592 RPN score loss: 0.00215 RPN total loss: 0.02807 Total loss: 0.96903 timestamp: 1654954189.6596603 iteration: 50415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10227 FastRCNN class loss: 0.07078 FastRCNN total loss: 0.17305 L1 loss: 0.0000e+00 L2 loss: 0.61065 Learning rate: 0.002 Mask loss: 0.10235 RPN box loss: 0.0078 RPN score loss: 0.00509 RPN total loss: 0.01289 Total loss: 0.89893 timestamp: 1654954193.0720134 iteration: 50420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05948 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.11471 L1 loss: 0.0000e+00 L2 loss: 0.61064 Learning rate: 0.002 Mask loss: 0.11524 RPN box loss: 0.0195 RPN score loss: 0.00477 RPN total loss: 0.02426 Total loss: 0.86485 timestamp: 1654954196.4078054 iteration: 50425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09336 FastRCNN class loss: 0.07739 FastRCNN total loss: 0.17075 L1 loss: 0.0000e+00 L2 loss: 0.61063 Learning rate: 0.002 Mask loss: 0.16459 RPN box loss: 0.0335 RPN score loss: 0.01317 RPN total loss: 0.04667 Total loss: 0.99264 timestamp: 1654954199.648375 iteration: 50430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18011 FastRCNN class loss: 0.08549 FastRCNN total loss: 0.2656 L1 loss: 0.0000e+00 L2 loss: 0.61062 Learning rate: 0.002 Mask loss: 0.16146 RPN box loss: 0.01445 RPN score loss: 0.00209 RPN total loss: 0.01654 Total loss: 1.05422 timestamp: 1654954202.8834357 iteration: 50435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08487 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.15855 L1 loss: 0.0000e+00 L2 loss: 0.61061 Learning rate: 0.002 Mask loss: 0.16861 RPN box loss: 0.01891 RPN score loss: 0.00708 RPN total loss: 0.02598 Total loss: 0.96376 timestamp: 1654954206.0767214 iteration: 50440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1252 FastRCNN class loss: 0.06 FastRCNN total loss: 0.1852 L1 loss: 0.0000e+00 L2 loss: 0.6106 Learning rate: 0.002 Mask loss: 0.14834 RPN box loss: 0.00727 RPN score loss: 0.00122 RPN total loss: 0.00849 Total loss: 0.95263 timestamp: 1654954209.4042692 iteration: 50445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10702 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.1707 L1 loss: 0.0000e+00 L2 loss: 0.6106 Learning rate: 0.002 Mask loss: 0.14178 RPN box loss: 0.01887 RPN score loss: 0.00876 RPN total loss: 0.02763 Total loss: 0.95071 timestamp: 1654954212.599169 iteration: 50450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07911 FastRCNN class loss: 0.054 FastRCNN total loss: 0.13311 L1 loss: 0.0000e+00 L2 loss: 0.61059 Learning rate: 0.002 Mask loss: 0.14742 RPN box loss: 0.00642 RPN score loss: 0.00697 RPN total loss: 0.01339 Total loss: 0.90451 timestamp: 1654954215.8445446 iteration: 50455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14884 FastRCNN class loss: 0.1611 FastRCNN total loss: 0.30995 L1 loss: 0.0000e+00 L2 loss: 0.61058 Learning rate: 0.002 Mask loss: 0.18032 RPN box loss: 0.0331 RPN score loss: 0.00749 RPN total loss: 0.04059 Total loss: 1.14144 timestamp: 1654954219.0720966 iteration: 50460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08481 FastRCNN class loss: 0.07475 FastRCNN total loss: 0.15957 L1 loss: 0.0000e+00 L2 loss: 0.61057 Learning rate: 0.002 Mask loss: 0.13853 RPN box loss: 0.0119 RPN score loss: 0.00602 RPN total loss: 0.01792 Total loss: 0.92659 timestamp: 1654954222.3113906 iteration: 50465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08265 FastRCNN class loss: 0.03822 FastRCNN total loss: 0.12087 L1 loss: 0.0000e+00 L2 loss: 0.61056 Learning rate: 0.002 Mask loss: 0.09296 RPN box loss: 0.00301 RPN score loss: 0.0046 RPN total loss: 0.00761 Total loss: 0.832 timestamp: 1654954225.5056503 iteration: 50470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10319 FastRCNN class loss: 0.09303 FastRCNN total loss: 0.19623 L1 loss: 0.0000e+00 L2 loss: 0.61055 Learning rate: 0.002 Mask loss: 0.13788 RPN box loss: 0.0339 RPN score loss: 0.01036 RPN total loss: 0.04425 Total loss: 0.98891 timestamp: 1654954228.7554123 iteration: 50475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1455 FastRCNN class loss: 0.07288 FastRCNN total loss: 0.21837 L1 loss: 0.0000e+00 L2 loss: 0.61054 Learning rate: 0.002 Mask loss: 0.12461 RPN box loss: 0.00934 RPN score loss: 0.00249 RPN total loss: 0.01183 Total loss: 0.96535 timestamp: 1654954232.0612907 iteration: 50480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14338 FastRCNN class loss: 0.10716 FastRCNN total loss: 0.25054 L1 loss: 0.0000e+00 L2 loss: 0.61053 Learning rate: 0.002 Mask loss: 0.15874 RPN box loss: 0.02193 RPN score loss: 0.00327 RPN total loss: 0.0252 Total loss: 1.04501 timestamp: 1654954235.305623 iteration: 50485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10325 FastRCNN class loss: 0.07653 FastRCNN total loss: 0.17978 L1 loss: 0.0000e+00 L2 loss: 0.61053 Learning rate: 0.002 Mask loss: 0.13386 RPN box loss: 0.01393 RPN score loss: 0.00477 RPN total loss: 0.0187 Total loss: 0.94287 timestamp: 1654954238.5751138 iteration: 50490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06725 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.11014 L1 loss: 0.0000e+00 L2 loss: 0.61052 Learning rate: 0.002 Mask loss: 0.116 RPN box loss: 0.00881 RPN score loss: 0.0073 RPN total loss: 0.01611 Total loss: 0.85277 timestamp: 1654954241.7901776 iteration: 50495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09347 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.16779 L1 loss: 0.0000e+00 L2 loss: 0.61051 Learning rate: 0.002 Mask loss: 0.16299 RPN box loss: 0.01238 RPN score loss: 0.00235 RPN total loss: 0.01474 Total loss: 0.95603 timestamp: 1654954245.1310616 iteration: 50500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13355 FastRCNN class loss: 0.06471 FastRCNN total loss: 0.19826 L1 loss: 0.0000e+00 L2 loss: 0.6105 Learning rate: 0.002 Mask loss: 0.14975 RPN box loss: 0.01364 RPN score loss: 0.00091 RPN total loss: 0.01455 Total loss: 0.97306 timestamp: 1654954248.369291 iteration: 50505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06472 FastRCNN class loss: 0.05367 FastRCNN total loss: 0.11838 L1 loss: 0.0000e+00 L2 loss: 0.61049 Learning rate: 0.002 Mask loss: 0.12783 RPN box loss: 0.00223 RPN score loss: 0.00385 RPN total loss: 0.00607 Total loss: 0.86278 timestamp: 1654954251.6721897 iteration: 50510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10822 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.17353 L1 loss: 0.0000e+00 L2 loss: 0.61048 Learning rate: 0.002 Mask loss: 0.13211 RPN box loss: 0.01216 RPN score loss: 0.00371 RPN total loss: 0.01586 Total loss: 0.93199 timestamp: 1654954254.8665454 iteration: 50515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11912 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.19752 L1 loss: 0.0000e+00 L2 loss: 0.61047 Learning rate: 0.002 Mask loss: 0.1434 RPN box loss: 0.02132 RPN score loss: 0.00233 RPN total loss: 0.02364 Total loss: 0.97504 timestamp: 1654954258.205091 iteration: 50520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04888 FastRCNN class loss: 0.03203 FastRCNN total loss: 0.08091 L1 loss: 0.0000e+00 L2 loss: 0.61046 Learning rate: 0.002 Mask loss: 0.12226 RPN box loss: 0.01341 RPN score loss: 0.00276 RPN total loss: 0.01617 Total loss: 0.8298 timestamp: 1654954261.4468877 iteration: 50525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15616 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.23842 L1 loss: 0.0000e+00 L2 loss: 0.61045 Learning rate: 0.002 Mask loss: 0.11748 RPN box loss: 0.01632 RPN score loss: 0.0042 RPN total loss: 0.02052 Total loss: 0.98687 timestamp: 1654954264.7497137 iteration: 50530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10479 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.17286 L1 loss: 0.0000e+00 L2 loss: 0.61044 Learning rate: 0.002 Mask loss: 0.15261 RPN box loss: 0.024 RPN score loss: 0.00246 RPN total loss: 0.02646 Total loss: 0.96238 timestamp: 1654954268.085817 iteration: 50535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10405 FastRCNN class loss: 0.06135 FastRCNN total loss: 0.1654 L1 loss: 0.0000e+00 L2 loss: 0.61044 Learning rate: 0.002 Mask loss: 0.13008 RPN box loss: 0.01849 RPN score loss: 0.00365 RPN total loss: 0.02214 Total loss: 0.92805 timestamp: 1654954271.2948627 iteration: 50540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05661 FastRCNN class loss: 0.03457 FastRCNN total loss: 0.09118 L1 loss: 0.0000e+00 L2 loss: 0.61043 Learning rate: 0.002 Mask loss: 0.0644 RPN box loss: 0.00354 RPN score loss: 0.00141 RPN total loss: 0.00495 Total loss: 0.77095 timestamp: 1654954274.690958 iteration: 50545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1242 FastRCNN class loss: 0.06642 FastRCNN total loss: 0.19062 L1 loss: 0.0000e+00 L2 loss: 0.61042 Learning rate: 0.002 Mask loss: 0.15256 RPN box loss: 0.03754 RPN score loss: 0.01181 RPN total loss: 0.04935 Total loss: 1.00295 timestamp: 1654954277.8503404 iteration: 50550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09882 FastRCNN class loss: 0.07221 FastRCNN total loss: 0.17103 L1 loss: 0.0000e+00 L2 loss: 0.61041 Learning rate: 0.002 Mask loss: 0.11628 RPN box loss: 0.01255 RPN score loss: 0.00336 RPN total loss: 0.01591 Total loss: 0.91363 timestamp: 1654954281.106587 iteration: 50555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07868 FastRCNN class loss: 0.05133 FastRCNN total loss: 0.13001 L1 loss: 0.0000e+00 L2 loss: 0.6104 Learning rate: 0.002 Mask loss: 0.12946 RPN box loss: 0.0181 RPN score loss: 0.00573 RPN total loss: 0.02383 Total loss: 0.8937 timestamp: 1654954284.2955945 iteration: 50560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1484 FastRCNN class loss: 0.10735 FastRCNN total loss: 0.25575 L1 loss: 0.0000e+00 L2 loss: 0.61039 Learning rate: 0.002 Mask loss: 0.19542 RPN box loss: 0.01389 RPN score loss: 0.01084 RPN total loss: 0.02473 Total loss: 1.08628 timestamp: 1654954287.506488 iteration: 50565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05562 FastRCNN class loss: 0.05655 FastRCNN total loss: 0.11217 L1 loss: 0.0000e+00 L2 loss: 0.61039 Learning rate: 0.002 Mask loss: 0.14432 RPN box loss: 0.00644 RPN score loss: 0.00211 RPN total loss: 0.00855 Total loss: 0.87543 timestamp: 1654954290.6873655 iteration: 50570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1072 FastRCNN class loss: 0.06938 FastRCNN total loss: 0.17659 L1 loss: 0.0000e+00 L2 loss: 0.61037 Learning rate: 0.002 Mask loss: 0.24221 RPN box loss: 0.0103 RPN score loss: 0.00186 RPN total loss: 0.01216 Total loss: 1.04134 timestamp: 1654954293.923999 iteration: 50575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08739 FastRCNN class loss: 0.052 FastRCNN total loss: 0.13938 L1 loss: 0.0000e+00 L2 loss: 0.61036 Learning rate: 0.002 Mask loss: 0.13851 RPN box loss: 0.02233 RPN score loss: 0.00238 RPN total loss: 0.02472 Total loss: 0.91297 timestamp: 1654954297.079262 iteration: 50580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09903 FastRCNN class loss: 0.0802 FastRCNN total loss: 0.17923 L1 loss: 0.0000e+00 L2 loss: 0.61035 Learning rate: 0.002 Mask loss: 0.1405 RPN box loss: 0.01388 RPN score loss: 0.00677 RPN total loss: 0.02065 Total loss: 0.95074 timestamp: 1654954300.3392324 iteration: 50585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13454 FastRCNN class loss: 0.07469 FastRCNN total loss: 0.20923 L1 loss: 0.0000e+00 L2 loss: 0.61034 Learning rate: 0.002 Mask loss: 0.22882 RPN box loss: 0.0108 RPN score loss: 0.00537 RPN total loss: 0.01617 Total loss: 1.06455 timestamp: 1654954303.5998836 iteration: 50590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08156 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.14691 L1 loss: 0.0000e+00 L2 loss: 0.61033 Learning rate: 0.002 Mask loss: 0.13604 RPN box loss: 0.01346 RPN score loss: 0.00372 RPN total loss: 0.01717 Total loss: 0.91045 timestamp: 1654954306.7377932 iteration: 50595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11077 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.18093 L1 loss: 0.0000e+00 L2 loss: 0.61033 Learning rate: 0.002 Mask loss: 0.11343 RPN box loss: 0.0128 RPN score loss: 0.0066 RPN total loss: 0.0194 Total loss: 0.92409 timestamp: 1654954309.9940677 iteration: 50600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15648 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.23435 L1 loss: 0.0000e+00 L2 loss: 0.61032 Learning rate: 0.002 Mask loss: 0.1127 RPN box loss: 0.02342 RPN score loss: 0.00845 RPN total loss: 0.03187 Total loss: 0.98924 timestamp: 1654954313.1845746 iteration: 50605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11781 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.19852 L1 loss: 0.0000e+00 L2 loss: 0.61031 Learning rate: 0.002 Mask loss: 0.09636 RPN box loss: 0.01632 RPN score loss: 0.00909 RPN total loss: 0.02541 Total loss: 0.9306 timestamp: 1654954316.5460477 iteration: 50610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12181 FastRCNN class loss: 0.05578 FastRCNN total loss: 0.17759 L1 loss: 0.0000e+00 L2 loss: 0.6103 Learning rate: 0.002 Mask loss: 0.10681 RPN box loss: 0.01799 RPN score loss: 0.00734 RPN total loss: 0.02533 Total loss: 0.92004 timestamp: 1654954319.7557778 iteration: 50615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08192 FastRCNN class loss: 0.06529 FastRCNN total loss: 0.14721 L1 loss: 0.0000e+00 L2 loss: 0.61029 Learning rate: 0.002 Mask loss: 0.15237 RPN box loss: 0.01822 RPN score loss: 0.00263 RPN total loss: 0.02085 Total loss: 0.93072 timestamp: 1654954322.9718113 iteration: 50620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.06571 FastRCNN total loss: 0.1584 L1 loss: 0.0000e+00 L2 loss: 0.61029 Learning rate: 0.002 Mask loss: 0.13082 RPN box loss: 0.0065 RPN score loss: 0.0084 RPN total loss: 0.0149 Total loss: 0.9144 timestamp: 1654954326.2200851 iteration: 50625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07499 FastRCNN class loss: 0.0501 FastRCNN total loss: 0.12509 L1 loss: 0.0000e+00 L2 loss: 0.61028 Learning rate: 0.002 Mask loss: 0.11572 RPN box loss: 0.01092 RPN score loss: 0.00424 RPN total loss: 0.01516 Total loss: 0.86624 timestamp: 1654954329.4272919 iteration: 50630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09657 FastRCNN class loss: 0.04816 FastRCNN total loss: 0.14473 L1 loss: 0.0000e+00 L2 loss: 0.61027 Learning rate: 0.002 Mask loss: 0.10173 RPN box loss: 0.01504 RPN score loss: 0.00464 RPN total loss: 0.01968 Total loss: 0.87641 timestamp: 1654954332.5884624 iteration: 50635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06051 FastRCNN class loss: 0.051 FastRCNN total loss: 0.11151 L1 loss: 0.0000e+00 L2 loss: 0.61026 Learning rate: 0.002 Mask loss: 0.11169 RPN box loss: 0.00883 RPN score loss: 0.00123 RPN total loss: 0.01006 Total loss: 0.84352 timestamp: 1654954335.8743808 iteration: 50640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11104 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.22267 L1 loss: 0.0000e+00 L2 loss: 0.61026 Learning rate: 0.002 Mask loss: 0.1661 RPN box loss: 0.0289 RPN score loss: 0.00348 RPN total loss: 0.03238 Total loss: 1.0314 timestamp: 1654954339.1623447 iteration: 50645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13735 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.2187 L1 loss: 0.0000e+00 L2 loss: 0.61025 Learning rate: 0.002 Mask loss: 0.14254 RPN box loss: 0.01121 RPN score loss: 0.00374 RPN total loss: 0.01495 Total loss: 0.98645 timestamp: 1654954342.4820895 iteration: 50650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08042 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.14727 L1 loss: 0.0000e+00 L2 loss: 0.61024 Learning rate: 0.002 Mask loss: 0.15124 RPN box loss: 0.01363 RPN score loss: 0.00498 RPN total loss: 0.01861 Total loss: 0.92736 timestamp: 1654954345.7861626 iteration: 50655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08061 FastRCNN class loss: 0.06254 FastRCNN total loss: 0.14315 L1 loss: 0.0000e+00 L2 loss: 0.61023 Learning rate: 0.002 Mask loss: 0.10547 RPN box loss: 0.00826 RPN score loss: 0.00294 RPN total loss: 0.0112 Total loss: 0.87005 timestamp: 1654954349.0100305 iteration: 50660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0819 FastRCNN class loss: 0.09554 FastRCNN total loss: 0.17744 L1 loss: 0.0000e+00 L2 loss: 0.61022 Learning rate: 0.002 Mask loss: 0.14204 RPN box loss: 0.03288 RPN score loss: 0.00446 RPN total loss: 0.03734 Total loss: 0.96704 timestamp: 1654954352.307176 iteration: 50665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06927 FastRCNN class loss: 0.04381 FastRCNN total loss: 0.11308 L1 loss: 0.0000e+00 L2 loss: 0.61022 Learning rate: 0.002 Mask loss: 0.12479 RPN box loss: 0.00605 RPN score loss: 0.00124 RPN total loss: 0.0073 Total loss: 0.85539 timestamp: 1654954355.4895432 iteration: 50670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07789 FastRCNN class loss: 0.06199 FastRCNN total loss: 0.13988 L1 loss: 0.0000e+00 L2 loss: 0.61021 Learning rate: 0.002 Mask loss: 0.0954 RPN box loss: 0.01533 RPN score loss: 0.004 RPN total loss: 0.01933 Total loss: 0.86481 timestamp: 1654954358.8395753 iteration: 50675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09804 FastRCNN class loss: 0.04696 FastRCNN total loss: 0.145 L1 loss: 0.0000e+00 L2 loss: 0.6102 Learning rate: 0.002 Mask loss: 0.13112 RPN box loss: 0.00344 RPN score loss: 0.00118 RPN total loss: 0.00462 Total loss: 0.89094 timestamp: 1654954362.0364952 iteration: 50680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1443 FastRCNN class loss: 0.07144 FastRCNN total loss: 0.21574 L1 loss: 0.0000e+00 L2 loss: 0.61019 Learning rate: 0.002 Mask loss: 0.09146 RPN box loss: 0.01822 RPN score loss: 0.00505 RPN total loss: 0.02326 Total loss: 0.94065 timestamp: 1654954365.4138799 iteration: 50685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15216 FastRCNN class loss: 0.08318 FastRCNN total loss: 0.23535 L1 loss: 0.0000e+00 L2 loss: 0.61018 Learning rate: 0.002 Mask loss: 0.14054 RPN box loss: 0.03537 RPN score loss: 0.00497 RPN total loss: 0.04033 Total loss: 1.02641 timestamp: 1654954368.6438055 iteration: 50690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14736 FastRCNN class loss: 0.12004 FastRCNN total loss: 0.2674 L1 loss: 0.0000e+00 L2 loss: 0.61018 Learning rate: 0.002 Mask loss: 0.19015 RPN box loss: 0.01873 RPN score loss: 0.00391 RPN total loss: 0.02263 Total loss: 1.09036 timestamp: 1654954371.9585216 iteration: 50695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1223 FastRCNN class loss: 0.07633 FastRCNN total loss: 0.19863 L1 loss: 0.0000e+00 L2 loss: 0.61017 Learning rate: 0.002 Mask loss: 0.1844 RPN box loss: 0.03057 RPN score loss: 0.00581 RPN total loss: 0.03638 Total loss: 1.02959 timestamp: 1654954375.271528 iteration: 50700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08779 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.14775 L1 loss: 0.0000e+00 L2 loss: 0.61016 Learning rate: 0.002 Mask loss: 0.14849 RPN box loss: 0.0089 RPN score loss: 0.00341 RPN total loss: 0.01231 Total loss: 0.9187 timestamp: 1654954378.5329695 iteration: 50705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04431 FastRCNN class loss: 0.04568 FastRCNN total loss: 0.08999 L1 loss: 0.0000e+00 L2 loss: 0.61015 Learning rate: 0.002 Mask loss: 0.0725 RPN box loss: 0.0039 RPN score loss: 0.00173 RPN total loss: 0.00563 Total loss: 0.77827 timestamp: 1654954381.883356 iteration: 50710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06073 FastRCNN class loss: 0.04148 FastRCNN total loss: 0.10221 L1 loss: 0.0000e+00 L2 loss: 0.61014 Learning rate: 0.002 Mask loss: 0.10738 RPN box loss: 0.00656 RPN score loss: 0.00295 RPN total loss: 0.00951 Total loss: 0.82924 timestamp: 1654954385.096002 iteration: 50715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06334 FastRCNN class loss: 0.04363 FastRCNN total loss: 0.10697 L1 loss: 0.0000e+00 L2 loss: 0.61013 Learning rate: 0.002 Mask loss: 0.10768 RPN box loss: 0.01116 RPN score loss: 0.00282 RPN total loss: 0.01399 Total loss: 0.83877 timestamp: 1654954388.337275 iteration: 50720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25281 FastRCNN class loss: 0.06079 FastRCNN total loss: 0.3136 L1 loss: 0.0000e+00 L2 loss: 0.61012 Learning rate: 0.002 Mask loss: 0.10892 RPN box loss: 0.02434 RPN score loss: 0.00929 RPN total loss: 0.03363 Total loss: 1.06627 timestamp: 1654954391.6131077 iteration: 50725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06685 FastRCNN class loss: 0.03877 FastRCNN total loss: 0.10562 L1 loss: 0.0000e+00 L2 loss: 0.61011 Learning rate: 0.002 Mask loss: 0.12251 RPN box loss: 0.01735 RPN score loss: 0.00121 RPN total loss: 0.01856 Total loss: 0.8568 timestamp: 1654954394.93937 iteration: 50730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06575 FastRCNN class loss: 0.054 FastRCNN total loss: 0.11975 L1 loss: 0.0000e+00 L2 loss: 0.6101 Learning rate: 0.002 Mask loss: 0.12063 RPN box loss: 0.01795 RPN score loss: 0.00293 RPN total loss: 0.02088 Total loss: 0.87137 timestamp: 1654954398.168294 iteration: 50735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09887 FastRCNN class loss: 0.08296 FastRCNN total loss: 0.18183 L1 loss: 0.0000e+00 L2 loss: 0.61009 Learning rate: 0.002 Mask loss: 0.10066 RPN box loss: 0.00776 RPN score loss: 0.00239 RPN total loss: 0.01015 Total loss: 0.90273 timestamp: 1654954401.496781 iteration: 50740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05989 FastRCNN class loss: 0.03567 FastRCNN total loss: 0.09556 L1 loss: 0.0000e+00 L2 loss: 0.61008 Learning rate: 0.002 Mask loss: 0.08682 RPN box loss: 0.00644 RPN score loss: 0.00728 RPN total loss: 0.01372 Total loss: 0.80618 timestamp: 1654954404.6615312 iteration: 50745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05684 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.11619 L1 loss: 0.0000e+00 L2 loss: 0.61007 Learning rate: 0.002 Mask loss: 0.12317 RPN box loss: 0.01113 RPN score loss: 0.00409 RPN total loss: 0.01521 Total loss: 0.86465 timestamp: 1654954407.8821063 iteration: 50750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09416 FastRCNN class loss: 0.09723 FastRCNN total loss: 0.19139 L1 loss: 0.0000e+00 L2 loss: 0.61006 Learning rate: 0.002 Mask loss: 0.12613 RPN box loss: 0.02192 RPN score loss: 0.01349 RPN total loss: 0.03541 Total loss: 0.96299 timestamp: 1654954411.0519001 iteration: 50755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07077 FastRCNN class loss: 0.08932 FastRCNN total loss: 0.16009 L1 loss: 0.0000e+00 L2 loss: 0.61005 Learning rate: 0.002 Mask loss: 0.14319 RPN box loss: 0.01533 RPN score loss: 0.00461 RPN total loss: 0.01993 Total loss: 0.93327 timestamp: 1654954414.279073 iteration: 50760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08937 FastRCNN class loss: 0.06515 FastRCNN total loss: 0.15452 L1 loss: 0.0000e+00 L2 loss: 0.61004 Learning rate: 0.002 Mask loss: 0.13426 RPN box loss: 0.0134 RPN score loss: 0.00493 RPN total loss: 0.01833 Total loss: 0.91715 timestamp: 1654954417.5502095 iteration: 50765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16055 FastRCNN class loss: 0.08554 FastRCNN total loss: 0.24609 L1 loss: 0.0000e+00 L2 loss: 0.61003 Learning rate: 0.002 Mask loss: 0.18125 RPN box loss: 0.01157 RPN score loss: 0.00442 RPN total loss: 0.01599 Total loss: 1.05337 timestamp: 1654954420.725672 iteration: 50770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14648 FastRCNN class loss: 0.08787 FastRCNN total loss: 0.23435 L1 loss: 0.0000e+00 L2 loss: 0.61003 Learning rate: 0.002 Mask loss: 0.14006 RPN box loss: 0.01586 RPN score loss: 0.00277 RPN total loss: 0.01863 Total loss: 1.00306 timestamp: 1654954423.9517837 iteration: 50775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08612 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.14813 L1 loss: 0.0000e+00 L2 loss: 0.61002 Learning rate: 0.002 Mask loss: 0.11074 RPN box loss: 0.021 RPN score loss: 0.00398 RPN total loss: 0.02499 Total loss: 0.89387 timestamp: 1654954427.214033 iteration: 50780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05323 FastRCNN class loss: 0.04282 FastRCNN total loss: 0.09605 L1 loss: 0.0000e+00 L2 loss: 0.61001 Learning rate: 0.002 Mask loss: 0.13904 RPN box loss: 0.00564 RPN score loss: 0.00311 RPN total loss: 0.00875 Total loss: 0.85385 timestamp: 1654954430.5423372 iteration: 50785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11073 FastRCNN class loss: 0.0688 FastRCNN total loss: 0.17953 L1 loss: 0.0000e+00 L2 loss: 0.61 Learning rate: 0.002 Mask loss: 0.161 RPN box loss: 0.01654 RPN score loss: 0.01047 RPN total loss: 0.02702 Total loss: 0.97754 timestamp: 1654954433.702542 iteration: 50790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08756 FastRCNN class loss: 0.09654 FastRCNN total loss: 0.1841 L1 loss: 0.0000e+00 L2 loss: 0.60999 Learning rate: 0.002 Mask loss: 0.11147 RPN box loss: 0.01376 RPN score loss: 0.00285 RPN total loss: 0.01661 Total loss: 0.92216 timestamp: 1654954436.982565 iteration: 50795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06477 FastRCNN class loss: 0.06142 FastRCNN total loss: 0.12619 L1 loss: 0.0000e+00 L2 loss: 0.60998 Learning rate: 0.002 Mask loss: 0.14158 RPN box loss: 0.02136 RPN score loss: 0.00604 RPN total loss: 0.0274 Total loss: 0.90515 timestamp: 1654954440.156286 iteration: 50800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.185 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.24069 L1 loss: 0.0000e+00 L2 loss: 0.60997 Learning rate: 0.002 Mask loss: 0.11221 RPN box loss: 0.00929 RPN score loss: 0.00292 RPN total loss: 0.01221 Total loss: 0.97508 timestamp: 1654954443.4896748 iteration: 50805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11849 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.20015 L1 loss: 0.0000e+00 L2 loss: 0.60996 Learning rate: 0.002 Mask loss: 0.1256 RPN box loss: 0.02414 RPN score loss: 0.00293 RPN total loss: 0.02707 Total loss: 0.96278 timestamp: 1654954446.6666958 iteration: 50810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07493 FastRCNN class loss: 0.03082 FastRCNN total loss: 0.10575 L1 loss: 0.0000e+00 L2 loss: 0.60996 Learning rate: 0.002 Mask loss: 0.12989 RPN box loss: 0.00311 RPN score loss: 0.00088 RPN total loss: 0.00399 Total loss: 0.84959 timestamp: 1654954449.848633 iteration: 50815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0897 FastRCNN class loss: 0.06553 FastRCNN total loss: 0.15523 L1 loss: 0.0000e+00 L2 loss: 0.60995 Learning rate: 0.002 Mask loss: 0.17912 RPN box loss: 0.01585 RPN score loss: 0.00467 RPN total loss: 0.02053 Total loss: 0.96482 timestamp: 1654954453.146048 iteration: 50820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11661 FastRCNN class loss: 0.0876 FastRCNN total loss: 0.20421 L1 loss: 0.0000e+00 L2 loss: 0.60994 Learning rate: 0.002 Mask loss: 0.16748 RPN box loss: 0.0098 RPN score loss: 0.00256 RPN total loss: 0.01236 Total loss: 0.994 timestamp: 1654954456.2744644 iteration: 50825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12794 FastRCNN class loss: 0.08377 FastRCNN total loss: 0.21171 L1 loss: 0.0000e+00 L2 loss: 0.60993 Learning rate: 0.002 Mask loss: 0.13969 RPN box loss: 0.01816 RPN score loss: 0.0025 RPN total loss: 0.02066 Total loss: 0.98199 timestamp: 1654954459.54556 iteration: 50830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08525 FastRCNN class loss: 0.1049 FastRCNN total loss: 0.19014 L1 loss: 0.0000e+00 L2 loss: 0.60992 Learning rate: 0.002 Mask loss: 0.14768 RPN box loss: 0.00606 RPN score loss: 0.00719 RPN total loss: 0.01325 Total loss: 0.961 timestamp: 1654954462.7212265 iteration: 50835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04938 FastRCNN class loss: 0.07911 FastRCNN total loss: 0.12849 L1 loss: 0.0000e+00 L2 loss: 0.60991 Learning rate: 0.002 Mask loss: 0.10107 RPN box loss: 0.00656 RPN score loss: 0.007 RPN total loss: 0.01356 Total loss: 0.85303 timestamp: 1654954466.0957808 iteration: 50840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09662 FastRCNN class loss: 0.06005 FastRCNN total loss: 0.15668 L1 loss: 0.0000e+00 L2 loss: 0.6099 Learning rate: 0.002 Mask loss: 0.12019 RPN box loss: 0.01005 RPN score loss: 0.00781 RPN total loss: 0.01786 Total loss: 0.90463 timestamp: 1654954469.2296386 iteration: 50845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.11359 L1 loss: 0.0000e+00 L2 loss: 0.60989 Learning rate: 0.002 Mask loss: 0.08807 RPN box loss: 0.01358 RPN score loss: 0.0039 RPN total loss: 0.01749 Total loss: 0.82903 timestamp: 1654954472.5787663 iteration: 50850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07499 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.13532 L1 loss: 0.0000e+00 L2 loss: 0.60988 Learning rate: 0.002 Mask loss: 0.09452 RPN box loss: 0.01823 RPN score loss: 0.00234 RPN total loss: 0.02057 Total loss: 0.86029 timestamp: 1654954475.7874103 iteration: 50855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07225 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.15309 L1 loss: 0.0000e+00 L2 loss: 0.60987 Learning rate: 0.002 Mask loss: 0.1032 RPN box loss: 0.01052 RPN score loss: 0.00234 RPN total loss: 0.01286 Total loss: 0.87902 timestamp: 1654954479.0573926 iteration: 50860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.074 FastRCNN total loss: 0.15797 L1 loss: 0.0000e+00 L2 loss: 0.60987 Learning rate: 0.002 Mask loss: 0.11316 RPN box loss: 0.01334 RPN score loss: 0.00689 RPN total loss: 0.02023 Total loss: 0.90122 timestamp: 1654954482.2302842 iteration: 50865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10284 FastRCNN class loss: 0.06046 FastRCNN total loss: 0.1633 L1 loss: 0.0000e+00 L2 loss: 0.60985 Learning rate: 0.002 Mask loss: 0.14443 RPN box loss: 0.01889 RPN score loss: 0.00431 RPN total loss: 0.0232 Total loss: 0.94079 timestamp: 1654954485.5426059 iteration: 50870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.08291 FastRCNN total loss: 0.23428 L1 loss: 0.0000e+00 L2 loss: 0.60985 Learning rate: 0.002 Mask loss: 0.17871 RPN box loss: 0.03551 RPN score loss: 0.01049 RPN total loss: 0.046 Total loss: 1.06884 timestamp: 1654954488.792027 iteration: 50875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13756 FastRCNN class loss: 0.09196 FastRCNN total loss: 0.22953 L1 loss: 0.0000e+00 L2 loss: 0.60984 Learning rate: 0.002 Mask loss: 0.1385 RPN box loss: 0.0103 RPN score loss: 0.00694 RPN total loss: 0.01723 Total loss: 0.99509 timestamp: 1654954492.0262465 iteration: 50880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1432 FastRCNN class loss: 0.12158 FastRCNN total loss: 0.26478 L1 loss: 0.0000e+00 L2 loss: 0.60983 Learning rate: 0.002 Mask loss: 0.23608 RPN box loss: 0.02951 RPN score loss: 0.01098 RPN total loss: 0.04049 Total loss: 1.15117 timestamp: 1654954495.3077621 iteration: 50885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10084 FastRCNN class loss: 0.10423 FastRCNN total loss: 0.20507 L1 loss: 0.0000e+00 L2 loss: 0.60982 Learning rate: 0.002 Mask loss: 0.12778 RPN box loss: 0.0104 RPN score loss: 0.01084 RPN total loss: 0.02124 Total loss: 0.96391 timestamp: 1654954498.4551723 iteration: 50890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10056 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.16653 L1 loss: 0.0000e+00 L2 loss: 0.60981 Learning rate: 0.002 Mask loss: 0.16985 RPN box loss: 0.01058 RPN score loss: 0.00766 RPN total loss: 0.01824 Total loss: 0.96443 timestamp: 1654954501.6989324 iteration: 50895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10103 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.15408 L1 loss: 0.0000e+00 L2 loss: 0.6098 Learning rate: 0.002 Mask loss: 0.09701 RPN box loss: 0.0152 RPN score loss: 0.00456 RPN total loss: 0.01976 Total loss: 0.88065 timestamp: 1654954504.9499989 iteration: 50900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07862 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.15243 L1 loss: 0.0000e+00 L2 loss: 0.60979 Learning rate: 0.002 Mask loss: 0.17186 RPN box loss: 0.02417 RPN score loss: 0.01699 RPN total loss: 0.04117 Total loss: 0.97525 timestamp: 1654954508.2300951 iteration: 50905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08468 FastRCNN class loss: 0.03854 FastRCNN total loss: 0.12322 L1 loss: 0.0000e+00 L2 loss: 0.60978 Learning rate: 0.002 Mask loss: 0.08561 RPN box loss: 0.0075 RPN score loss: 0.00855 RPN total loss: 0.01604 Total loss: 0.83466 timestamp: 1654954511.4190435 iteration: 50910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11274 FastRCNN class loss: 0.05792 FastRCNN total loss: 0.17066 L1 loss: 0.0000e+00 L2 loss: 0.60977 Learning rate: 0.002 Mask loss: 0.17498 RPN box loss: 0.02648 RPN score loss: 0.01557 RPN total loss: 0.04205 Total loss: 0.99747 timestamp: 1654954514.704516 iteration: 50915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.08675 FastRCNN total loss: 0.17559 L1 loss: 0.0000e+00 L2 loss: 0.60976 Learning rate: 0.002 Mask loss: 0.08791 RPN box loss: 0.01706 RPN score loss: 0.01049 RPN total loss: 0.02755 Total loss: 0.90082 timestamp: 1654954517.88007 iteration: 50920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0362 FastRCNN class loss: 0.03383 FastRCNN total loss: 0.07003 L1 loss: 0.0000e+00 L2 loss: 0.60975 Learning rate: 0.002 Mask loss: 0.07873 RPN box loss: 0.00833 RPN score loss: 0.01113 RPN total loss: 0.01946 Total loss: 0.77797 timestamp: 1654954521.1334922 iteration: 50925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0513 FastRCNN class loss: 0.04267 FastRCNN total loss: 0.09397 L1 loss: 0.0000e+00 L2 loss: 0.60975 Learning rate: 0.002 Mask loss: 0.12693 RPN box loss: 0.00518 RPN score loss: 0.00069 RPN total loss: 0.00587 Total loss: 0.83651 timestamp: 1654954524.327866 iteration: 50930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10307 FastRCNN class loss: 0.05661 FastRCNN total loss: 0.15967 L1 loss: 0.0000e+00 L2 loss: 0.60974 Learning rate: 0.002 Mask loss: 0.1035 RPN box loss: 0.01457 RPN score loss: 0.00327 RPN total loss: 0.01783 Total loss: 0.89075 timestamp: 1654954527.572529 iteration: 50935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.08805 FastRCNN total loss: 0.23947 L1 loss: 0.0000e+00 L2 loss: 0.60973 Learning rate: 0.002 Mask loss: 0.16484 RPN box loss: 0.02162 RPN score loss: 0.01974 RPN total loss: 0.04136 Total loss: 1.0554 timestamp: 1654954530.8761683 iteration: 50940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11618 FastRCNN class loss: 0.07272 FastRCNN total loss: 0.18891 L1 loss: 0.0000e+00 L2 loss: 0.60972 Learning rate: 0.002 Mask loss: 0.11078 RPN box loss: 0.00847 RPN score loss: 0.00363 RPN total loss: 0.0121 Total loss: 0.92151 timestamp: 1654954534.1254456 iteration: 50945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06776 FastRCNN class loss: 0.03927 FastRCNN total loss: 0.10703 L1 loss: 0.0000e+00 L2 loss: 0.60971 Learning rate: 0.002 Mask loss: 0.12556 RPN box loss: 0.00497 RPN score loss: 0.00459 RPN total loss: 0.00955 Total loss: 0.85186 timestamp: 1654954537.4583344 iteration: 50950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.147 FastRCNN class loss: 0.13249 FastRCNN total loss: 0.27949 L1 loss: 0.0000e+00 L2 loss: 0.60971 Learning rate: 0.002 Mask loss: 0.19693 RPN box loss: 0.02166 RPN score loss: 0.00739 RPN total loss: 0.02905 Total loss: 1.11518 timestamp: 1654954540.6613295 iteration: 50955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1065 FastRCNN class loss: 0.07534 FastRCNN total loss: 0.18184 L1 loss: 0.0000e+00 L2 loss: 0.6097 Learning rate: 0.002 Mask loss: 0.08547 RPN box loss: 0.01373 RPN score loss: 0.01151 RPN total loss: 0.02525 Total loss: 0.90225 timestamp: 1654954543.8957202 iteration: 50960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11169 FastRCNN class loss: 0.08979 FastRCNN total loss: 0.20149 L1 loss: 0.0000e+00 L2 loss: 0.60969 Learning rate: 0.002 Mask loss: 0.13591 RPN box loss: 0.01492 RPN score loss: 0.0047 RPN total loss: 0.01962 Total loss: 0.96671 timestamp: 1654954547.06362 iteration: 50965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11049 FastRCNN class loss: 0.07061 FastRCNN total loss: 0.18111 L1 loss: 0.0000e+00 L2 loss: 0.60968 Learning rate: 0.002 Mask loss: 0.14039 RPN box loss: 0.01412 RPN score loss: 0.00484 RPN total loss: 0.01896 Total loss: 0.95013 timestamp: 1654954550.4518182 iteration: 50970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11363 FastRCNN class loss: 0.07935 FastRCNN total loss: 0.19298 L1 loss: 0.0000e+00 L2 loss: 0.60967 Learning rate: 0.002 Mask loss: 0.12515 RPN box loss: 0.01964 RPN score loss: 0.00543 RPN total loss: 0.02507 Total loss: 0.95287 timestamp: 1654954553.5977166 iteration: 50975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0798 FastRCNN class loss: 0.0734 FastRCNN total loss: 0.1532 L1 loss: 0.0000e+00 L2 loss: 0.60966 Learning rate: 0.002 Mask loss: 0.11905 RPN box loss: 0.01496 RPN score loss: 0.00302 RPN total loss: 0.01799 Total loss: 0.8999 timestamp: 1654954556.8725104 iteration: 50980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10816 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.18229 L1 loss: 0.0000e+00 L2 loss: 0.60966 Learning rate: 0.002 Mask loss: 0.10667 RPN box loss: 0.01586 RPN score loss: 0.00217 RPN total loss: 0.01803 Total loss: 0.91664 timestamp: 1654954560.0684743 iteration: 50985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04651 FastRCNN class loss: 0.03905 FastRCNN total loss: 0.08556 L1 loss: 0.0000e+00 L2 loss: 0.60965 Learning rate: 0.002 Mask loss: 0.16993 RPN box loss: 0.00356 RPN score loss: 0.0043 RPN total loss: 0.00786 Total loss: 0.873 timestamp: 1654954563.356849 iteration: 50990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12048 FastRCNN class loss: 0.09277 FastRCNN total loss: 0.21325 L1 loss: 0.0000e+00 L2 loss: 0.60964 Learning rate: 0.002 Mask loss: 0.11876 RPN box loss: 0.00977 RPN score loss: 0.0045 RPN total loss: 0.01426 Total loss: 0.95592 timestamp: 1654954566.6550205 iteration: 50995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1177 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.18553 L1 loss: 0.0000e+00 L2 loss: 0.60963 Learning rate: 0.002 Mask loss: 0.12814 RPN box loss: 0.04355 RPN score loss: 0.00862 RPN total loss: 0.05218 Total loss: 0.97548 timestamp: 1654954569.9315133 iteration: 51000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15451 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.20279 L1 loss: 0.0000e+00 L2 loss: 0.60962 Learning rate: 0.002 Mask loss: 0.11425 RPN box loss: 0.01685 RPN score loss: 0.00586 RPN total loss: 0.02271 Total loss: 0.94937 timestamp: 1654954573.1785228 iteration: 51005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08523 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.13988 L1 loss: 0.0000e+00 L2 loss: 0.60961 Learning rate: 0.002 Mask loss: 0.12978 RPN box loss: 0.00992 RPN score loss: 0.00261 RPN total loss: 0.01254 Total loss: 0.89181 timestamp: 1654954576.4283893 iteration: 51010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1018 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.17845 L1 loss: 0.0000e+00 L2 loss: 0.6096 Learning rate: 0.002 Mask loss: 0.12513 RPN box loss: 0.02775 RPN score loss: 0.00427 RPN total loss: 0.03202 Total loss: 0.9452 timestamp: 1654954579.7043712 iteration: 51015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04722 FastRCNN class loss: 0.04069 FastRCNN total loss: 0.0879 L1 loss: 0.0000e+00 L2 loss: 0.60959 Learning rate: 0.002 Mask loss: 0.11852 RPN box loss: 0.00298 RPN score loss: 0.00246 RPN total loss: 0.00544 Total loss: 0.82145 timestamp: 1654954582.8750741 iteration: 51020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12469 FastRCNN class loss: 0.10884 FastRCNN total loss: 0.23353 L1 loss: 0.0000e+00 L2 loss: 0.60958 Learning rate: 0.002 Mask loss: 0.21963 RPN box loss: 0.01951 RPN score loss: 0.00777 RPN total loss: 0.02728 Total loss: 1.09002 timestamp: 1654954586.199373 iteration: 51025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08448 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.15677 L1 loss: 0.0000e+00 L2 loss: 0.60957 Learning rate: 0.002 Mask loss: 0.08966 RPN box loss: 0.0078 RPN score loss: 0.00371 RPN total loss: 0.01151 Total loss: 0.86751 timestamp: 1654954589.484062 iteration: 51030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05155 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.1207 L1 loss: 0.0000e+00 L2 loss: 0.60957 Learning rate: 0.002 Mask loss: 0.14066 RPN box loss: 0.0436 RPN score loss: 0.00616 RPN total loss: 0.04976 Total loss: 0.92069 timestamp: 1654954592.7718751 iteration: 51035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.0893 FastRCNN total loss: 0.18571 L1 loss: 0.0000e+00 L2 loss: 0.60955 Learning rate: 0.002 Mask loss: 0.15543 RPN box loss: 0.02469 RPN score loss: 0.005 RPN total loss: 0.02969 Total loss: 0.98038 timestamp: 1654954596.0486305 iteration: 51040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16981 FastRCNN class loss: 0.08642 FastRCNN total loss: 0.25623 L1 loss: 0.0000e+00 L2 loss: 0.60955 Learning rate: 0.002 Mask loss: 0.16956 RPN box loss: 0.01238 RPN score loss: 0.00978 RPN total loss: 0.02216 Total loss: 1.0575 timestamp: 1654954599.3200245 iteration: 51045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12758 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.18351 L1 loss: 0.0000e+00 L2 loss: 0.60954 Learning rate: 0.002 Mask loss: 0.1174 RPN box loss: 0.01764 RPN score loss: 0.00214 RPN total loss: 0.01977 Total loss: 0.93022 timestamp: 1654954602.6383626 iteration: 51050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07818 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.1481 L1 loss: 0.0000e+00 L2 loss: 0.60953 Learning rate: 0.002 Mask loss: 0.17163 RPN box loss: 0.04834 RPN score loss: 0.00381 RPN total loss: 0.05215 Total loss: 0.98141 timestamp: 1654954605.7981699 iteration: 51055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07761 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.12708 L1 loss: 0.0000e+00 L2 loss: 0.60952 Learning rate: 0.002 Mask loss: 0.10153 RPN box loss: 0.0057 RPN score loss: 0.00223 RPN total loss: 0.00793 Total loss: 0.84606 timestamp: 1654954609.0336869 iteration: 51060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12056 FastRCNN class loss: 0.09035 FastRCNN total loss: 0.2109 L1 loss: 0.0000e+00 L2 loss: 0.60951 Learning rate: 0.002 Mask loss: 0.12438 RPN box loss: 0.00941 RPN score loss: 0.00829 RPN total loss: 0.0177 Total loss: 0.96249 timestamp: 1654954612.2376702 iteration: 51065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08215 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.14691 L1 loss: 0.0000e+00 L2 loss: 0.6095 Learning rate: 0.002 Mask loss: 0.12331 RPN box loss: 0.015 RPN score loss: 0.00506 RPN total loss: 0.02006 Total loss: 0.89979 timestamp: 1654954615.555905 iteration: 51070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10002 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.18497 L1 loss: 0.0000e+00 L2 loss: 0.6095 Learning rate: 0.002 Mask loss: 0.1471 RPN box loss: 0.02177 RPN score loss: 0.00496 RPN total loss: 0.02673 Total loss: 0.96829 timestamp: 1654954618.7079604 iteration: 51075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08966 FastRCNN class loss: 0.04865 FastRCNN total loss: 0.13831 L1 loss: 0.0000e+00 L2 loss: 0.60949 Learning rate: 0.002 Mask loss: 0.11607 RPN box loss: 0.01379 RPN score loss: 0.00326 RPN total loss: 0.01705 Total loss: 0.88091 timestamp: 1654954621.9415686 iteration: 51080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06217 FastRCNN class loss: 0.04006 FastRCNN total loss: 0.10223 L1 loss: 0.0000e+00 L2 loss: 0.60948 Learning rate: 0.002 Mask loss: 0.11603 RPN box loss: 0.00559 RPN score loss: 0.00401 RPN total loss: 0.0096 Total loss: 0.83734 timestamp: 1654954625.2368684 iteration: 51085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14021 FastRCNN class loss: 0.10227 FastRCNN total loss: 0.24248 L1 loss: 0.0000e+00 L2 loss: 0.60947 Learning rate: 0.002 Mask loss: 0.15848 RPN box loss: 0.00486 RPN score loss: 0.00261 RPN total loss: 0.00747 Total loss: 1.0179 timestamp: 1654954628.5115867 iteration: 51090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12768 FastRCNN class loss: 0.07288 FastRCNN total loss: 0.20056 L1 loss: 0.0000e+00 L2 loss: 0.60946 Learning rate: 0.002 Mask loss: 0.15253 RPN box loss: 0.00977 RPN score loss: 0.00172 RPN total loss: 0.01149 Total loss: 0.97403 timestamp: 1654954631.806364 iteration: 51095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1231 FastRCNN class loss: 0.08685 FastRCNN total loss: 0.20994 L1 loss: 0.0000e+00 L2 loss: 0.60946 Learning rate: 0.002 Mask loss: 0.1725 RPN box loss: 0.0159 RPN score loss: 0.00256 RPN total loss: 0.01846 Total loss: 1.01037 timestamp: 1654954635.071885 iteration: 51100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11246 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.16541 L1 loss: 0.0000e+00 L2 loss: 0.60945 Learning rate: 0.002 Mask loss: 0.17088 RPN box loss: 0.01569 RPN score loss: 0.00611 RPN total loss: 0.0218 Total loss: 0.96754 timestamp: 1654954638.3677819 iteration: 51105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07488 FastRCNN class loss: 0.04666 FastRCNN total loss: 0.12154 L1 loss: 0.0000e+00 L2 loss: 0.60944 Learning rate: 0.002 Mask loss: 0.14631 RPN box loss: 0.01985 RPN score loss: 0.00276 RPN total loss: 0.02261 Total loss: 0.8999 timestamp: 1654954641.5325446 iteration: 51110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14736 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.21397 L1 loss: 0.0000e+00 L2 loss: 0.60943 Learning rate: 0.002 Mask loss: 0.16303 RPN box loss: 0.02065 RPN score loss: 0.00648 RPN total loss: 0.02714 Total loss: 1.01356 timestamp: 1654954644.8781002 iteration: 51115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13749 FastRCNN class loss: 0.08422 FastRCNN total loss: 0.22172 L1 loss: 0.0000e+00 L2 loss: 0.60941 Learning rate: 0.002 Mask loss: 0.12998 RPN box loss: 0.01286 RPN score loss: 0.0024 RPN total loss: 0.01526 Total loss: 0.97637 timestamp: 1654954648.0640676 iteration: 51120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09236 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.16717 L1 loss: 0.0000e+00 L2 loss: 0.60941 Learning rate: 0.002 Mask loss: 0.10248 RPN box loss: 0.03203 RPN score loss: 0.00229 RPN total loss: 0.03433 Total loss: 0.91339 timestamp: 1654954651.3952785 iteration: 51125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12288 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.18839 L1 loss: 0.0000e+00 L2 loss: 0.6094 Learning rate: 0.002 Mask loss: 0.13422 RPN box loss: 0.02646 RPN score loss: 0.00635 RPN total loss: 0.03281 Total loss: 0.96482 timestamp: 1654954654.6018975 iteration: 51130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09145 FastRCNN class loss: 0.03157 FastRCNN total loss: 0.12302 L1 loss: 0.0000e+00 L2 loss: 0.60939 Learning rate: 0.002 Mask loss: 0.07658 RPN box loss: 0.00521 RPN score loss: 0.00131 RPN total loss: 0.00653 Total loss: 0.81552 timestamp: 1654954657.925132 iteration: 51135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08142 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.13297 L1 loss: 0.0000e+00 L2 loss: 0.60939 Learning rate: 0.002 Mask loss: 0.11444 RPN box loss: 0.02216 RPN score loss: 0.00443 RPN total loss: 0.0266 Total loss: 0.88339 timestamp: 1654954661.1255262 iteration: 51140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08478 FastRCNN class loss: 0.03922 FastRCNN total loss: 0.124 L1 loss: 0.0000e+00 L2 loss: 0.60938 Learning rate: 0.002 Mask loss: 0.09848 RPN box loss: 0.00805 RPN score loss: 0.00067 RPN total loss: 0.00872 Total loss: 0.84058 timestamp: 1654954664.52544 iteration: 51145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11451 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.17486 L1 loss: 0.0000e+00 L2 loss: 0.60937 Learning rate: 0.002 Mask loss: 0.09341 RPN box loss: 0.00864 RPN score loss: 0.00507 RPN total loss: 0.01372 Total loss: 0.89135 timestamp: 1654954667.7321851 iteration: 51150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12603 FastRCNN class loss: 0.116 FastRCNN total loss: 0.24203 L1 loss: 0.0000e+00 L2 loss: 0.60936 Learning rate: 0.002 Mask loss: 0.16902 RPN box loss: 0.02785 RPN score loss: 0.00349 RPN total loss: 0.03134 Total loss: 1.05175 timestamp: 1654954670.9040449 iteration: 51155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11113 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.16318 L1 loss: 0.0000e+00 L2 loss: 0.60935 Learning rate: 0.002 Mask loss: 0.12646 RPN box loss: 0.00765 RPN score loss: 0.00597 RPN total loss: 0.01362 Total loss: 0.9126 timestamp: 1654954674.094276 iteration: 51160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09205 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.14179 L1 loss: 0.0000e+00 L2 loss: 0.60934 Learning rate: 0.002 Mask loss: 0.10314 RPN box loss: 0.01247 RPN score loss: 0.00185 RPN total loss: 0.01433 Total loss: 0.8686 timestamp: 1654954677.2342508 iteration: 51165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08463 FastRCNN class loss: 0.05878 FastRCNN total loss: 0.14341 L1 loss: 0.0000e+00 L2 loss: 0.60934 Learning rate: 0.002 Mask loss: 0.13613 RPN box loss: 0.00828 RPN score loss: 0.00325 RPN total loss: 0.01153 Total loss: 0.90041 timestamp: 1654954680.5057495 iteration: 51170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10005 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.17753 L1 loss: 0.0000e+00 L2 loss: 0.60933 Learning rate: 0.002 Mask loss: 0.11736 RPN box loss: 0.01645 RPN score loss: 0.0032 RPN total loss: 0.01965 Total loss: 0.92388 timestamp: 1654954683.7347095 iteration: 51175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16921 FastRCNN class loss: 0.06878 FastRCNN total loss: 0.23799 L1 loss: 0.0000e+00 L2 loss: 0.60932 Learning rate: 0.002 Mask loss: 0.15 RPN box loss: 0.01619 RPN score loss: 0.0031 RPN total loss: 0.01929 Total loss: 1.0166 timestamp: 1654954687.0984852 iteration: 51180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10013 FastRCNN class loss: 0.10561 FastRCNN total loss: 0.20573 L1 loss: 0.0000e+00 L2 loss: 0.60931 Learning rate: 0.002 Mask loss: 0.15035 RPN box loss: 0.03416 RPN score loss: 0.00697 RPN total loss: 0.04113 Total loss: 1.00652 timestamp: 1654954690.383108 iteration: 51185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09497 FastRCNN class loss: 0.09013 FastRCNN total loss: 0.18509 L1 loss: 0.0000e+00 L2 loss: 0.6093 Learning rate: 0.002 Mask loss: 0.18669 RPN box loss: 0.01391 RPN score loss: 0.0023 RPN total loss: 0.0162 Total loss: 0.99728 timestamp: 1654954693.5428882 iteration: 51190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09656 FastRCNN class loss: 0.07258 FastRCNN total loss: 0.16915 L1 loss: 0.0000e+00 L2 loss: 0.60929 Learning rate: 0.002 Mask loss: 0.09965 RPN box loss: 0.01595 RPN score loss: 0.00926 RPN total loss: 0.02521 Total loss: 0.90329 timestamp: 1654954696.7914953 iteration: 51195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09575 FastRCNN class loss: 0.05531 FastRCNN total loss: 0.15106 L1 loss: 0.0000e+00 L2 loss: 0.60928 Learning rate: 0.002 Mask loss: 0.12615 RPN box loss: 0.0107 RPN score loss: 0.00618 RPN total loss: 0.01688 Total loss: 0.90338 timestamp: 1654954700.1450825 iteration: 51200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.074 FastRCNN class loss: 0.05135 FastRCNN total loss: 0.12534 L1 loss: 0.0000e+00 L2 loss: 0.60927 Learning rate: 0.002 Mask loss: 0.10365 RPN box loss: 0.0079 RPN score loss: 0.00182 RPN total loss: 0.00973 Total loss: 0.84799 timestamp: 1654954703.372571 iteration: 51205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09659 FastRCNN class loss: 0.07648 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 0.60927 Learning rate: 0.002 Mask loss: 0.20408 RPN box loss: 0.01285 RPN score loss: 0.00998 RPN total loss: 0.02284 Total loss: 1.00925 timestamp: 1654954706.5631957 iteration: 51210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0688 FastRCNN class loss: 0.03239 FastRCNN total loss: 0.10119 L1 loss: 0.0000e+00 L2 loss: 0.60926 Learning rate: 0.002 Mask loss: 0.08827 RPN box loss: 0.01891 RPN score loss: 0.00265 RPN total loss: 0.02156 Total loss: 0.82028 timestamp: 1654954709.8842053 iteration: 51215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06717 FastRCNN class loss: 0.0582 FastRCNN total loss: 0.12537 L1 loss: 0.0000e+00 L2 loss: 0.60925 Learning rate: 0.002 Mask loss: 0.12897 RPN box loss: 0.01196 RPN score loss: 0.00144 RPN total loss: 0.0134 Total loss: 0.877 timestamp: 1654954713.108184 iteration: 51220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12359 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.19853 L1 loss: 0.0000e+00 L2 loss: 0.60924 Learning rate: 0.002 Mask loss: 0.15902 RPN box loss: 0.0243 RPN score loss: 0.00428 RPN total loss: 0.02858 Total loss: 0.99537 timestamp: 1654954716.4508014 iteration: 51225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09005 FastRCNN class loss: 0.05126 FastRCNN total loss: 0.14132 L1 loss: 0.0000e+00 L2 loss: 0.60923 Learning rate: 0.002 Mask loss: 0.12011 RPN box loss: 0.01365 RPN score loss: 0.00253 RPN total loss: 0.01618 Total loss: 0.88684 timestamp: 1654954719.714119 iteration: 51230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08553 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.14808 L1 loss: 0.0000e+00 L2 loss: 0.60922 Learning rate: 0.002 Mask loss: 0.12657 RPN box loss: 0.0179 RPN score loss: 0.00232 RPN total loss: 0.02022 Total loss: 0.90409 timestamp: 1654954722.9367013 iteration: 51235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.0863 FastRCNN total loss: 0.19781 L1 loss: 0.0000e+00 L2 loss: 0.60921 Learning rate: 0.002 Mask loss: 0.19454 RPN box loss: 0.01163 RPN score loss: 0.00671 RPN total loss: 0.01833 Total loss: 1.01989 timestamp: 1654954726.1773584 iteration: 51240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.08443 FastRCNN total loss: 0.19739 L1 loss: 0.0000e+00 L2 loss: 0.6092 Learning rate: 0.002 Mask loss: 0.18174 RPN box loss: 0.01598 RPN score loss: 0.00436 RPN total loss: 0.02034 Total loss: 1.00867 timestamp: 1654954729.5004017 iteration: 51245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09391 FastRCNN class loss: 0.06985 FastRCNN total loss: 0.16376 L1 loss: 0.0000e+00 L2 loss: 0.6092 Learning rate: 0.002 Mask loss: 0.12456 RPN box loss: 0.01563 RPN score loss: 0.00448 RPN total loss: 0.02011 Total loss: 0.91763 timestamp: 1654954732.6674604 iteration: 51250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05913 FastRCNN class loss: 0.04885 FastRCNN total loss: 0.10798 L1 loss: 0.0000e+00 L2 loss: 0.60919 Learning rate: 0.002 Mask loss: 0.10371 RPN box loss: 0.01161 RPN score loss: 0.00143 RPN total loss: 0.01304 Total loss: 0.83391 timestamp: 1654954735.910912 iteration: 51255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08729 FastRCNN class loss: 0.05878 FastRCNN total loss: 0.14607 L1 loss: 0.0000e+00 L2 loss: 0.60917 Learning rate: 0.002 Mask loss: 0.11405 RPN box loss: 0.01197 RPN score loss: 0.01271 RPN total loss: 0.02468 Total loss: 0.89398 timestamp: 1654954739.162489 iteration: 51260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12074 FastRCNN class loss: 0.08067 FastRCNN total loss: 0.20142 L1 loss: 0.0000e+00 L2 loss: 0.60916 Learning rate: 0.002 Mask loss: 0.14891 RPN box loss: 0.0046 RPN score loss: 0.00811 RPN total loss: 0.01271 Total loss: 0.9722 timestamp: 1654954742.483785 iteration: 51265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09696 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.16465 L1 loss: 0.0000e+00 L2 loss: 0.60915 Learning rate: 0.002 Mask loss: 0.13267 RPN box loss: 0.01905 RPN score loss: 0.00283 RPN total loss: 0.02189 Total loss: 0.92836 timestamp: 1654954745.826526 iteration: 51270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07131 FastRCNN class loss: 0.03781 FastRCNN total loss: 0.10912 L1 loss: 0.0000e+00 L2 loss: 0.60914 Learning rate: 0.002 Mask loss: 0.08006 RPN box loss: 0.00489 RPN score loss: 0.00346 RPN total loss: 0.00836 Total loss: 0.80668 timestamp: 1654954749.0288172 iteration: 51275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09294 FastRCNN class loss: 0.08045 FastRCNN total loss: 0.17339 L1 loss: 0.0000e+00 L2 loss: 0.60913 Learning rate: 0.002 Mask loss: 0.09576 RPN box loss: 0.00748 RPN score loss: 0.00219 RPN total loss: 0.00967 Total loss: 0.88795 timestamp: 1654954752.4697878 iteration: 51280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11424 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.17955 L1 loss: 0.0000e+00 L2 loss: 0.60912 Learning rate: 0.002 Mask loss: 0.16194 RPN box loss: 0.02809 RPN score loss: 0.00276 RPN total loss: 0.03085 Total loss: 0.98146 timestamp: 1654954755.6822464 iteration: 51285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07223 FastRCNN class loss: 0.04727 FastRCNN total loss: 0.1195 L1 loss: 0.0000e+00 L2 loss: 0.60912 Learning rate: 0.002 Mask loss: 0.14008 RPN box loss: 0.01168 RPN score loss: 0.00152 RPN total loss: 0.0132 Total loss: 0.8819 timestamp: 1654954759.0026197 iteration: 51290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08177 FastRCNN class loss: 0.05919 FastRCNN total loss: 0.14096 L1 loss: 0.0000e+00 L2 loss: 0.60911 Learning rate: 0.002 Mask loss: 0.13224 RPN box loss: 0.01565 RPN score loss: 0.0061 RPN total loss: 0.02175 Total loss: 0.90406 timestamp: 1654954762.2188299 iteration: 51295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11932 FastRCNN class loss: 0.08518 FastRCNN total loss: 0.2045 L1 loss: 0.0000e+00 L2 loss: 0.6091 Learning rate: 0.002 Mask loss: 0.10288 RPN box loss: 0.01003 RPN score loss: 0.00714 RPN total loss: 0.01717 Total loss: 0.93365 timestamp: 1654954765.4437397 iteration: 51300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15317 FastRCNN class loss: 0.07067 FastRCNN total loss: 0.22384 L1 loss: 0.0000e+00 L2 loss: 0.60909 Learning rate: 0.002 Mask loss: 0.10424 RPN box loss: 0.00709 RPN score loss: 0.00403 RPN total loss: 0.01112 Total loss: 0.9483 timestamp: 1654954768.6390564 iteration: 51305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.04882 FastRCNN total loss: 0.13556 L1 loss: 0.0000e+00 L2 loss: 0.60909 Learning rate: 0.002 Mask loss: 0.09747 RPN box loss: 0.01401 RPN score loss: 0.00509 RPN total loss: 0.01911 Total loss: 0.86122 timestamp: 1654954771.8802927 iteration: 51310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10299 FastRCNN class loss: 0.06039 FastRCNN total loss: 0.16338 L1 loss: 0.0000e+00 L2 loss: 0.60908 Learning rate: 0.002 Mask loss: 0.11694 RPN box loss: 0.00886 RPN score loss: 0.00693 RPN total loss: 0.01579 Total loss: 0.90519 timestamp: 1654954775.1734264 iteration: 51315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1659 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.25269 L1 loss: 0.0000e+00 L2 loss: 0.60907 Learning rate: 0.002 Mask loss: 0.16114 RPN box loss: 0.0375 RPN score loss: 0.00855 RPN total loss: 0.04606 Total loss: 1.06896 timestamp: 1654954778.3299656 iteration: 51320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07187 FastRCNN class loss: 0.05554 FastRCNN total loss: 0.12741 L1 loss: 0.0000e+00 L2 loss: 0.60906 Learning rate: 0.002 Mask loss: 0.09289 RPN box loss: 0.01068 RPN score loss: 0.00883 RPN total loss: 0.01952 Total loss: 0.84887 timestamp: 1654954781.737263 iteration: 51325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11996 FastRCNN class loss: 0.11821 FastRCNN total loss: 0.23818 L1 loss: 0.0000e+00 L2 loss: 0.60905 Learning rate: 0.002 Mask loss: 0.19388 RPN box loss: 0.03388 RPN score loss: 0.00596 RPN total loss: 0.03984 Total loss: 1.08095 timestamp: 1654954784.9323723 iteration: 51330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.12507 FastRCNN total loss: 0.23673 L1 loss: 0.0000e+00 L2 loss: 0.60904 Learning rate: 0.002 Mask loss: 0.16379 RPN box loss: 0.01904 RPN score loss: 0.00273 RPN total loss: 0.02177 Total loss: 1.03133 timestamp: 1654954788.1391056 iteration: 51335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05276 FastRCNN class loss: 0.03699 FastRCNN total loss: 0.08974 L1 loss: 0.0000e+00 L2 loss: 0.60903 Learning rate: 0.002 Mask loss: 0.09713 RPN box loss: 0.01027 RPN score loss: 0.00211 RPN total loss: 0.01238 Total loss: 0.80829 timestamp: 1654954791.4035766 iteration: 51340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06388 FastRCNN class loss: 0.06603 FastRCNN total loss: 0.12991 L1 loss: 0.0000e+00 L2 loss: 0.60902 Learning rate: 0.002 Mask loss: 0.09691 RPN box loss: 0.0192 RPN score loss: 0.00359 RPN total loss: 0.02279 Total loss: 0.85863 timestamp: 1654954794.679769 iteration: 51345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13237 FastRCNN class loss: 0.09947 FastRCNN total loss: 0.23184 L1 loss: 0.0000e+00 L2 loss: 0.60901 Learning rate: 0.002 Mask loss: 0.18704 RPN box loss: 0.01452 RPN score loss: 0.00496 RPN total loss: 0.01948 Total loss: 1.04737 timestamp: 1654954797.8871014 iteration: 51350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08013 FastRCNN class loss: 0.0492 FastRCNN total loss: 0.12932 L1 loss: 0.0000e+00 L2 loss: 0.609 Learning rate: 0.002 Mask loss: 0.09213 RPN box loss: 0.0113 RPN score loss: 0.00109 RPN total loss: 0.01239 Total loss: 0.84286 timestamp: 1654954801.2693682 iteration: 51355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13869 FastRCNN class loss: 0.06376 FastRCNN total loss: 0.20245 L1 loss: 0.0000e+00 L2 loss: 0.60899 Learning rate: 0.002 Mask loss: 0.10956 RPN box loss: 0.02004 RPN score loss: 0.00562 RPN total loss: 0.02566 Total loss: 0.94666 timestamp: 1654954804.4261847 iteration: 51360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09153 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.16724 L1 loss: 0.0000e+00 L2 loss: 0.60898 Learning rate: 0.002 Mask loss: 0.10633 RPN box loss: 0.00924 RPN score loss: 0.00297 RPN total loss: 0.0122 Total loss: 0.89475 timestamp: 1654954807.7527483 iteration: 51365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05797 FastRCNN class loss: 0.02078 FastRCNN total loss: 0.07875 L1 loss: 0.0000e+00 L2 loss: 0.60898 Learning rate: 0.002 Mask loss: 0.08877 RPN box loss: 0.01022 RPN score loss: 0.0009 RPN total loss: 0.01112 Total loss: 0.78763 timestamp: 1654954811.0445452 iteration: 51370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.06998 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.60897 Learning rate: 0.002 Mask loss: 0.13539 RPN box loss: 0.01051 RPN score loss: 0.00315 RPN total loss: 0.01366 Total loss: 0.91473 timestamp: 1654954814.2347722 iteration: 51375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0954 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.15476 L1 loss: 0.0000e+00 L2 loss: 0.60896 Learning rate: 0.002 Mask loss: 0.13638 RPN box loss: 0.01474 RPN score loss: 0.00598 RPN total loss: 0.02072 Total loss: 0.92082 timestamp: 1654954817.4909923 iteration: 51380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11475 FastRCNN class loss: 0.06085 FastRCNN total loss: 0.1756 L1 loss: 0.0000e+00 L2 loss: 0.60895 Learning rate: 0.002 Mask loss: 0.11841 RPN box loss: 0.01312 RPN score loss: 0.01245 RPN total loss: 0.02558 Total loss: 0.92854 timestamp: 1654954820.679167 iteration: 51385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12642 FastRCNN class loss: 0.04954 FastRCNN total loss: 0.17596 L1 loss: 0.0000e+00 L2 loss: 0.60894 Learning rate: 0.002 Mask loss: 0.09111 RPN box loss: 0.00801 RPN score loss: 0.00164 RPN total loss: 0.00965 Total loss: 0.88566 timestamp: 1654954823.9952369 iteration: 51390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06459 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.11203 L1 loss: 0.0000e+00 L2 loss: 0.60893 Learning rate: 0.002 Mask loss: 0.11075 RPN box loss: 0.02289 RPN score loss: 0.0021 RPN total loss: 0.025 Total loss: 0.8567 timestamp: 1654954827.1931307 iteration: 51395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06621 FastRCNN class loss: 0.07404 FastRCNN total loss: 0.14026 L1 loss: 0.0000e+00 L2 loss: 0.60892 Learning rate: 0.002 Mask loss: 0.1187 RPN box loss: 0.01107 RPN score loss: 0.00297 RPN total loss: 0.01404 Total loss: 0.88192 timestamp: 1654954830.4796455 iteration: 51400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08953 FastRCNN class loss: 0.04958 FastRCNN total loss: 0.13912 L1 loss: 0.0000e+00 L2 loss: 0.60891 Learning rate: 0.002 Mask loss: 0.12171 RPN box loss: 0.02111 RPN score loss: 0.00417 RPN total loss: 0.02528 Total loss: 0.89502 timestamp: 1654954833.7231457 iteration: 51405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0801 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.14885 L1 loss: 0.0000e+00 L2 loss: 0.60891 Learning rate: 0.002 Mask loss: 0.15449 RPN box loss: 0.04232 RPN score loss: 0.00759 RPN total loss: 0.04991 Total loss: 0.96216 timestamp: 1654954836.991806 iteration: 51410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12684 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.20756 L1 loss: 0.0000e+00 L2 loss: 0.6089 Learning rate: 0.002 Mask loss: 0.10815 RPN box loss: 0.00634 RPN score loss: 0.0049 RPN total loss: 0.01124 Total loss: 0.93585 timestamp: 1654954840.2200215 iteration: 51415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13532 FastRCNN class loss: 0.12037 FastRCNN total loss: 0.25569 L1 loss: 0.0000e+00 L2 loss: 0.60889 Learning rate: 0.002 Mask loss: 0.1401 RPN box loss: 0.04395 RPN score loss: 0.00632 RPN total loss: 0.05027 Total loss: 1.05496 timestamp: 1654954843.4831045 iteration: 51420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07755 FastRCNN class loss: 0.05419 FastRCNN total loss: 0.13175 L1 loss: 0.0000e+00 L2 loss: 0.60888 Learning rate: 0.002 Mask loss: 0.09995 RPN box loss: 0.0091 RPN score loss: 0.00181 RPN total loss: 0.01091 Total loss: 0.85148 timestamp: 1654954846.8898156 iteration: 51425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09437 FastRCNN class loss: 0.08427 FastRCNN total loss: 0.17864 L1 loss: 0.0000e+00 L2 loss: 0.60887 Learning rate: 0.002 Mask loss: 0.14712 RPN box loss: 0.03065 RPN score loss: 0.01168 RPN total loss: 0.04233 Total loss: 0.97696 timestamp: 1654954850.0103831 iteration: 51430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09388 FastRCNN class loss: 0.08998 FastRCNN total loss: 0.18386 L1 loss: 0.0000e+00 L2 loss: 0.60887 Learning rate: 0.002 Mask loss: 0.17685 RPN box loss: 0.01031 RPN score loss: 0.00666 RPN total loss: 0.01697 Total loss: 0.98654 timestamp: 1654954853.3175294 iteration: 51435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11365 FastRCNN class loss: 0.08054 FastRCNN total loss: 0.19419 L1 loss: 0.0000e+00 L2 loss: 0.60886 Learning rate: 0.002 Mask loss: 0.12133 RPN box loss: 0.01977 RPN score loss: 0.00268 RPN total loss: 0.02245 Total loss: 0.94682 timestamp: 1654954856.528209 iteration: 51440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08121 FastRCNN class loss: 0.05804 FastRCNN total loss: 0.13925 L1 loss: 0.0000e+00 L2 loss: 0.60885 Learning rate: 0.002 Mask loss: 0.1068 RPN box loss: 0.00997 RPN score loss: 0.00291 RPN total loss: 0.01288 Total loss: 0.86777 timestamp: 1654954859.922186 iteration: 51445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11446 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.18155 L1 loss: 0.0000e+00 L2 loss: 0.60884 Learning rate: 0.002 Mask loss: 0.16863 RPN box loss: 0.02507 RPN score loss: 0.00762 RPN total loss: 0.03269 Total loss: 0.99171 timestamp: 1654954863.1445642 iteration: 51450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07781 FastRCNN class loss: 0.06335 FastRCNN total loss: 0.14116 L1 loss: 0.0000e+00 L2 loss: 0.60883 Learning rate: 0.002 Mask loss: 0.15753 RPN box loss: 0.00987 RPN score loss: 0.00561 RPN total loss: 0.01548 Total loss: 0.92299 timestamp: 1654954866.3847322 iteration: 51455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11459 FastRCNN class loss: 0.08755 FastRCNN total loss: 0.20214 L1 loss: 0.0000e+00 L2 loss: 0.60882 Learning rate: 0.002 Mask loss: 0.18823 RPN box loss: 0.01407 RPN score loss: 0.00728 RPN total loss: 0.02135 Total loss: 1.02054 timestamp: 1654954869.5801609 iteration: 51460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.07299 FastRCNN total loss: 0.16421 L1 loss: 0.0000e+00 L2 loss: 0.60881 Learning rate: 0.002 Mask loss: 0.13033 RPN box loss: 0.00822 RPN score loss: 0.004 RPN total loss: 0.01223 Total loss: 0.91557 timestamp: 1654954872.78386 iteration: 51465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06069 FastRCNN class loss: 0.08884 FastRCNN total loss: 0.14953 L1 loss: 0.0000e+00 L2 loss: 0.6088 Learning rate: 0.002 Mask loss: 0.14004 RPN box loss: 0.01221 RPN score loss: 0.00421 RPN total loss: 0.01642 Total loss: 0.91479 timestamp: 1654954875.9353845 iteration: 51470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09713 FastRCNN class loss: 0.12586 FastRCNN total loss: 0.22299 L1 loss: 0.0000e+00 L2 loss: 0.60879 Learning rate: 0.002 Mask loss: 0.2064 RPN box loss: 0.0209 RPN score loss: 0.00904 RPN total loss: 0.02993 Total loss: 1.06811 timestamp: 1654954879.2912323 iteration: 51475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11511 FastRCNN class loss: 0.05723 FastRCNN total loss: 0.17234 L1 loss: 0.0000e+00 L2 loss: 0.60878 Learning rate: 0.002 Mask loss: 0.14165 RPN box loss: 0.01133 RPN score loss: 0.00331 RPN total loss: 0.01464 Total loss: 0.93741 timestamp: 1654954882.4857352 iteration: 51480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1055 FastRCNN class loss: 0.08492 FastRCNN total loss: 0.19043 L1 loss: 0.0000e+00 L2 loss: 0.60877 Learning rate: 0.002 Mask loss: 0.10471 RPN box loss: 0.01653 RPN score loss: 0.00672 RPN total loss: 0.02324 Total loss: 0.92715 timestamp: 1654954885.725708 iteration: 51485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08895 FastRCNN class loss: 0.09295 FastRCNN total loss: 0.18191 L1 loss: 0.0000e+00 L2 loss: 0.60876 Learning rate: 0.002 Mask loss: 0.16218 RPN box loss: 0.01663 RPN score loss: 0.01131 RPN total loss: 0.02794 Total loss: 0.98079 timestamp: 1654954888.9899 iteration: 51490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06995 FastRCNN class loss: 0.05764 FastRCNN total loss: 0.1276 L1 loss: 0.0000e+00 L2 loss: 0.60876 Learning rate: 0.002 Mask loss: 0.09009 RPN box loss: 0.01716 RPN score loss: 0.00181 RPN total loss: 0.01897 Total loss: 0.84541 timestamp: 1654954892.156506 iteration: 51495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07402 FastRCNN class loss: 0.06231 FastRCNN total loss: 0.13633 L1 loss: 0.0000e+00 L2 loss: 0.60875 Learning rate: 0.002 Mask loss: 0.12379 RPN box loss: 0.00665 RPN score loss: 0.00568 RPN total loss: 0.01233 Total loss: 0.88121 timestamp: 1654954895.3766763 iteration: 51500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.09849 FastRCNN total loss: 0.21332 L1 loss: 0.0000e+00 L2 loss: 0.60874 Learning rate: 0.002 Mask loss: 0.23071 RPN box loss: 0.02438 RPN score loss: 0.00834 RPN total loss: 0.03272 Total loss: 1.0855 timestamp: 1654954898.561035 iteration: 51505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04384 FastRCNN class loss: 0.03483 FastRCNN total loss: 0.07867 L1 loss: 0.0000e+00 L2 loss: 0.60873 Learning rate: 0.002 Mask loss: 0.10747 RPN box loss: 0.01783 RPN score loss: 0.00092 RPN total loss: 0.01875 Total loss: 0.81362 timestamp: 1654954901.84344 iteration: 51510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0615 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.12175 L1 loss: 0.0000e+00 L2 loss: 0.60873 Learning rate: 0.002 Mask loss: 0.17139 RPN box loss: 0.01224 RPN score loss: 0.00839 RPN total loss: 0.02062 Total loss: 0.92248 timestamp: 1654954905.0516372 iteration: 51515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12831 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.20733 L1 loss: 0.0000e+00 L2 loss: 0.60872 Learning rate: 0.002 Mask loss: 0.10709 RPN box loss: 0.00568 RPN score loss: 0.00238 RPN total loss: 0.00806 Total loss: 0.9312 timestamp: 1654954908.3636727 iteration: 51520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.07485 FastRCNN total loss: 0.16891 L1 loss: 0.0000e+00 L2 loss: 0.60871 Learning rate: 0.002 Mask loss: 0.16099 RPN box loss: 0.01084 RPN score loss: 0.00648 RPN total loss: 0.01731 Total loss: 0.95592 timestamp: 1654954911.5737143 iteration: 51525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05534 FastRCNN class loss: 0.05353 FastRCNN total loss: 0.10887 L1 loss: 0.0000e+00 L2 loss: 0.6087 Learning rate: 0.002 Mask loss: 0.14338 RPN box loss: 0.01065 RPN score loss: 0.00527 RPN total loss: 0.01592 Total loss: 0.87687 timestamp: 1654954914.8207302 iteration: 51530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.112 FastRCNN class loss: 0.0578 FastRCNN total loss: 0.16981 L1 loss: 0.0000e+00 L2 loss: 0.60869 Learning rate: 0.002 Mask loss: 0.14283 RPN box loss: 0.02282 RPN score loss: 0.00457 RPN total loss: 0.02739 Total loss: 0.94871 timestamp: 1654954918.1884234 iteration: 51535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09044 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.17765 L1 loss: 0.0000e+00 L2 loss: 0.60868 Learning rate: 0.002 Mask loss: 0.16477 RPN box loss: 0.0139 RPN score loss: 0.00213 RPN total loss: 0.01603 Total loss: 0.96713 timestamp: 1654954921.440405 iteration: 51540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07211 FastRCNN class loss: 0.0453 FastRCNN total loss: 0.1174 L1 loss: 0.0000e+00 L2 loss: 0.60867 Learning rate: 0.002 Mask loss: 0.15244 RPN box loss: 0.01252 RPN score loss: 0.00398 RPN total loss: 0.0165 Total loss: 0.89502 timestamp: 1654954924.7521033 iteration: 51545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07223 FastRCNN class loss: 0.04492 FastRCNN total loss: 0.11715 L1 loss: 0.0000e+00 L2 loss: 0.60866 Learning rate: 0.002 Mask loss: 0.09841 RPN box loss: 0.00941 RPN score loss: 0.00119 RPN total loss: 0.0106 Total loss: 0.83482 timestamp: 1654954927.9539485 iteration: 51550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03119 FastRCNN class loss: 0.02867 FastRCNN total loss: 0.05986 L1 loss: 0.0000e+00 L2 loss: 0.60865 Learning rate: 0.002 Mask loss: 0.09484 RPN box loss: 0.01449 RPN score loss: 0.0009 RPN total loss: 0.01539 Total loss: 0.77873 timestamp: 1654954931.4041212 iteration: 51555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10654 FastRCNN class loss: 0.05422 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.60864 Learning rate: 0.002 Mask loss: 0.10859 RPN box loss: 0.0072 RPN score loss: 0.00351 RPN total loss: 0.01071 Total loss: 0.88871 timestamp: 1654954934.6502807 iteration: 51560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08898 FastRCNN class loss: 0.06292 FastRCNN total loss: 0.1519 L1 loss: 0.0000e+00 L2 loss: 0.60863 Learning rate: 0.002 Mask loss: 0.1253 RPN box loss: 0.00472 RPN score loss: 0.00189 RPN total loss: 0.00661 Total loss: 0.89244 timestamp: 1654954937.928704 iteration: 51565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06989 FastRCNN class loss: 0.07286 FastRCNN total loss: 0.14275 L1 loss: 0.0000e+00 L2 loss: 0.60862 Learning rate: 0.002 Mask loss: 0.1087 RPN box loss: 0.01597 RPN score loss: 0.00802 RPN total loss: 0.02399 Total loss: 0.88407 timestamp: 1654954941.140808 iteration: 51570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08985 FastRCNN class loss: 0.08111 FastRCNN total loss: 0.17097 L1 loss: 0.0000e+00 L2 loss: 0.60861 Learning rate: 0.002 Mask loss: 0.1614 RPN box loss: 0.02089 RPN score loss: 0.00433 RPN total loss: 0.02522 Total loss: 0.9662 timestamp: 1654954944.483615 iteration: 51575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11842 FastRCNN class loss: 0.12573 FastRCNN total loss: 0.24415 L1 loss: 0.0000e+00 L2 loss: 0.60861 Learning rate: 0.002 Mask loss: 0.16846 RPN box loss: 0.02518 RPN score loss: 0.00649 RPN total loss: 0.03167 Total loss: 1.05289 timestamp: 1654954947.7581236 iteration: 51580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09007 FastRCNN class loss: 0.06439 FastRCNN total loss: 0.15445 L1 loss: 0.0000e+00 L2 loss: 0.6086 Learning rate: 0.002 Mask loss: 0.11108 RPN box loss: 0.01017 RPN score loss: 0.0049 RPN total loss: 0.01507 Total loss: 0.8892 timestamp: 1654954951.0259216 iteration: 51585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13096 FastRCNN class loss: 0.06403 FastRCNN total loss: 0.19499 L1 loss: 0.0000e+00 L2 loss: 0.60859 Learning rate: 0.002 Mask loss: 0.11833 RPN box loss: 0.00727 RPN score loss: 0.00556 RPN total loss: 0.01283 Total loss: 0.93473 timestamp: 1654954954.3530622 iteration: 51590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11871 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.17704 L1 loss: 0.0000e+00 L2 loss: 0.60858 Learning rate: 0.002 Mask loss: 0.16555 RPN box loss: 0.01985 RPN score loss: 0.00853 RPN total loss: 0.02838 Total loss: 0.97954 timestamp: 1654954957.5413716 iteration: 51595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04751 FastRCNN class loss: 0.05266 FastRCNN total loss: 0.10018 L1 loss: 0.0000e+00 L2 loss: 0.60858 Learning rate: 0.002 Mask loss: 0.14404 RPN box loss: 0.00831 RPN score loss: 0.00076 RPN total loss: 0.00907 Total loss: 0.86186 timestamp: 1654954960.7556436 iteration: 51600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10593 FastRCNN class loss: 0.1093 FastRCNN total loss: 0.21524 L1 loss: 0.0000e+00 L2 loss: 0.60857 Learning rate: 0.002 Mask loss: 0.1647 RPN box loss: 0.01084 RPN score loss: 0.00243 RPN total loss: 0.01328 Total loss: 1.00178 timestamp: 1654954963.959981 iteration: 51605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16525 FastRCNN class loss: 0.12741 FastRCNN total loss: 0.29266 L1 loss: 0.0000e+00 L2 loss: 0.60856 Learning rate: 0.002 Mask loss: 0.16421 RPN box loss: 0.02944 RPN score loss: 0.00968 RPN total loss: 0.03911 Total loss: 1.10455 timestamp: 1654954967.2886138 iteration: 51610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11671 FastRCNN class loss: 0.08391 FastRCNN total loss: 0.20062 L1 loss: 0.0000e+00 L2 loss: 0.60855 Learning rate: 0.002 Mask loss: 0.14149 RPN box loss: 0.01618 RPN score loss: 0.0071 RPN total loss: 0.02328 Total loss: 0.97394 timestamp: 1654954970.5543227 iteration: 51615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06307 FastRCNN class loss: 0.05371 FastRCNN total loss: 0.11678 L1 loss: 0.0000e+00 L2 loss: 0.60854 Learning rate: 0.002 Mask loss: 0.13417 RPN box loss: 0.02092 RPN score loss: 0.00512 RPN total loss: 0.02604 Total loss: 0.88553 timestamp: 1654954973.8948212 iteration: 51620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09702 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.16817 L1 loss: 0.0000e+00 L2 loss: 0.60853 Learning rate: 0.002 Mask loss: 0.10136 RPN box loss: 0.01447 RPN score loss: 0.002 RPN total loss: 0.01647 Total loss: 0.89453 timestamp: 1654954977.070782 iteration: 51625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14169 FastRCNN class loss: 0.08579 FastRCNN total loss: 0.22748 L1 loss: 0.0000e+00 L2 loss: 0.60852 Learning rate: 0.002 Mask loss: 0.13995 RPN box loss: 0.08219 RPN score loss: 0.00482 RPN total loss: 0.087 Total loss: 1.06295 timestamp: 1654954980.4613824 iteration: 51630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04935 FastRCNN class loss: 0.04049 FastRCNN total loss: 0.08984 L1 loss: 0.0000e+00 L2 loss: 0.60851 Learning rate: 0.002 Mask loss: 0.10458 RPN box loss: 0.02312 RPN score loss: 0.00868 RPN total loss: 0.03181 Total loss: 0.83473 timestamp: 1654954983.6555595 iteration: 51635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07782 FastRCNN class loss: 0.10613 FastRCNN total loss: 0.18395 L1 loss: 0.0000e+00 L2 loss: 0.60851 Learning rate: 0.002 Mask loss: 0.24369 RPN box loss: 0.03477 RPN score loss: 0.05062 RPN total loss: 0.0854 Total loss: 1.12154 timestamp: 1654954986.9654558 iteration: 51640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.0823 FastRCNN total loss: 0.16752 L1 loss: 0.0000e+00 L2 loss: 0.6085 Learning rate: 0.002 Mask loss: 0.14886 RPN box loss: 0.01263 RPN score loss: 0.00665 RPN total loss: 0.01928 Total loss: 0.94416 timestamp: 1654954990.2642658 iteration: 51645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1375 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.20075 L1 loss: 0.0000e+00 L2 loss: 0.60849 Learning rate: 0.002 Mask loss: 0.14998 RPN box loss: 0.01381 RPN score loss: 0.00571 RPN total loss: 0.01952 Total loss: 0.97874 timestamp: 1654954993.5015378 iteration: 51650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10118 FastRCNN class loss: 0.06179 FastRCNN total loss: 0.16297 L1 loss: 0.0000e+00 L2 loss: 0.60848 Learning rate: 0.002 Mask loss: 0.13341 RPN box loss: 0.01241 RPN score loss: 0.00659 RPN total loss: 0.01901 Total loss: 0.92386 timestamp: 1654954996.8187072 iteration: 51655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.06753 FastRCNN total loss: 0.16209 L1 loss: 0.0000e+00 L2 loss: 0.60847 Learning rate: 0.002 Mask loss: 0.10662 RPN box loss: 0.01164 RPN score loss: 0.00284 RPN total loss: 0.01448 Total loss: 0.89166 timestamp: 1654955000.044867 iteration: 51660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14136 FastRCNN class loss: 0.07382 FastRCNN total loss: 0.21518 L1 loss: 0.0000e+00 L2 loss: 0.60847 Learning rate: 0.002 Mask loss: 0.1439 RPN box loss: 0.01593 RPN score loss: 0.00342 RPN total loss: 0.01935 Total loss: 0.98691 timestamp: 1654955003.3225074 iteration: 51665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08223 FastRCNN class loss: 0.04317 FastRCNN total loss: 0.1254 L1 loss: 0.0000e+00 L2 loss: 0.60846 Learning rate: 0.002 Mask loss: 0.0933 RPN box loss: 0.00955 RPN score loss: 0.00175 RPN total loss: 0.01131 Total loss: 0.83846 timestamp: 1654955006.5053194 iteration: 51670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06791 FastRCNN class loss: 0.06873 FastRCNN total loss: 0.13664 L1 loss: 0.0000e+00 L2 loss: 0.60845 Learning rate: 0.002 Mask loss: 0.09931 RPN box loss: 0.01398 RPN score loss: 0.00254 RPN total loss: 0.01651 Total loss: 0.86091 timestamp: 1654955009.8090389 iteration: 51675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13288 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.2038 L1 loss: 0.0000e+00 L2 loss: 0.60844 Learning rate: 0.002 Mask loss: 0.10486 RPN box loss: 0.03234 RPN score loss: 0.00451 RPN total loss: 0.03685 Total loss: 0.95395 timestamp: 1654955012.986858 iteration: 51680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07207 FastRCNN class loss: 0.057 FastRCNN total loss: 0.12908 L1 loss: 0.0000e+00 L2 loss: 0.60844 Learning rate: 0.002 Mask loss: 0.0882 RPN box loss: 0.01784 RPN score loss: 0.00183 RPN total loss: 0.01967 Total loss: 0.84538 timestamp: 1654955016.2899284 iteration: 51685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08492 FastRCNN class loss: 0.09423 FastRCNN total loss: 0.17916 L1 loss: 0.0000e+00 L2 loss: 0.60843 Learning rate: 0.002 Mask loss: 0.16113 RPN box loss: 0.00803 RPN score loss: 0.00156 RPN total loss: 0.00959 Total loss: 0.95831 timestamp: 1654955019.45863 iteration: 51690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09878 FastRCNN class loss: 0.07735 FastRCNN total loss: 0.17613 L1 loss: 0.0000e+00 L2 loss: 0.60842 Learning rate: 0.002 Mask loss: 0.14583 RPN box loss: 0.01508 RPN score loss: 0.00642 RPN total loss: 0.0215 Total loss: 0.95188 timestamp: 1654955022.7423365 iteration: 51695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09333 FastRCNN class loss: 0.09431 FastRCNN total loss: 0.18764 L1 loss: 0.0000e+00 L2 loss: 0.60841 Learning rate: 0.002 Mask loss: 0.12321 RPN box loss: 0.00773 RPN score loss: 0.00093 RPN total loss: 0.00866 Total loss: 0.92792 timestamp: 1654955025.9956794 iteration: 51700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10464 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.16851 L1 loss: 0.0000e+00 L2 loss: 0.6084 Learning rate: 0.002 Mask loss: 0.11322 RPN box loss: 0.0139 RPN score loss: 0.00343 RPN total loss: 0.01734 Total loss: 0.90746 timestamp: 1654955029.227613 iteration: 51705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14378 FastRCNN class loss: 0.10769 FastRCNN total loss: 0.25146 L1 loss: 0.0000e+00 L2 loss: 0.60839 Learning rate: 0.002 Mask loss: 0.18608 RPN box loss: 0.01239 RPN score loss: 0.01022 RPN total loss: 0.02261 Total loss: 1.06853 timestamp: 1654955032.530381 iteration: 51710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07228 FastRCNN class loss: 0.07816 FastRCNN total loss: 0.15043 L1 loss: 0.0000e+00 L2 loss: 0.60838 Learning rate: 0.002 Mask loss: 0.11148 RPN box loss: 0.04121 RPN score loss: 0.01564 RPN total loss: 0.05686 Total loss: 0.92715 timestamp: 1654955035.7155368 iteration: 51715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10335 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.17938 L1 loss: 0.0000e+00 L2 loss: 0.60837 Learning rate: 0.002 Mask loss: 0.14634 RPN box loss: 0.00601 RPN score loss: 0.00417 RPN total loss: 0.01018 Total loss: 0.94427 timestamp: 1654955039.0689676 iteration: 51720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10729 FastRCNN class loss: 0.04912 FastRCNN total loss: 0.15641 L1 loss: 0.0000e+00 L2 loss: 0.60836 Learning rate: 0.002 Mask loss: 0.0985 RPN box loss: 0.01136 RPN score loss: 0.00527 RPN total loss: 0.01663 Total loss: 0.87989 timestamp: 1654955042.2693655 iteration: 51725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14891 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.24239 L1 loss: 0.0000e+00 L2 loss: 0.60835 Learning rate: 0.002 Mask loss: 0.20095 RPN box loss: 0.0221 RPN score loss: 0.01463 RPN total loss: 0.03673 Total loss: 1.08843 timestamp: 1654955045.5884569 iteration: 51730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06147 FastRCNN class loss: 0.04193 FastRCNN total loss: 0.10341 L1 loss: 0.0000e+00 L2 loss: 0.60834 Learning rate: 0.002 Mask loss: 0.15203 RPN box loss: 0.02055 RPN score loss: 0.00348 RPN total loss: 0.02403 Total loss: 0.88781 timestamp: 1654955048.8206954 iteration: 51735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10821 FastRCNN class loss: 0.08917 FastRCNN total loss: 0.19738 L1 loss: 0.0000e+00 L2 loss: 0.60834 Learning rate: 0.002 Mask loss: 0.1273 RPN box loss: 0.0174 RPN score loss: 0.00416 RPN total loss: 0.02156 Total loss: 0.95458 timestamp: 1654955052.1212351 iteration: 51740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14782 FastRCNN class loss: 0.06297 FastRCNN total loss: 0.21079 L1 loss: 0.0000e+00 L2 loss: 0.60833 Learning rate: 0.002 Mask loss: 0.14466 RPN box loss: 0.01313 RPN score loss: 0.00242 RPN total loss: 0.01555 Total loss: 0.97933 timestamp: 1654955055.3304982 iteration: 51745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09155 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.1566 L1 loss: 0.0000e+00 L2 loss: 0.60832 Learning rate: 0.002 Mask loss: 0.10563 RPN box loss: 0.00593 RPN score loss: 0.00601 RPN total loss: 0.01194 Total loss: 0.88249 timestamp: 1654955058.6542366 iteration: 51750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09214 FastRCNN class loss: 0.05084 FastRCNN total loss: 0.14297 L1 loss: 0.0000e+00 L2 loss: 0.60831 Learning rate: 0.002 Mask loss: 0.11409 RPN box loss: 0.01461 RPN score loss: 0.00228 RPN total loss: 0.01689 Total loss: 0.88226 timestamp: 1654955061.9259121 iteration: 51755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0754 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.12026 L1 loss: 0.0000e+00 L2 loss: 0.6083 Learning rate: 0.002 Mask loss: 0.09783 RPN box loss: 0.01141 RPN score loss: 0.00112 RPN total loss: 0.01253 Total loss: 0.83892 timestamp: 1654955065.1454506 iteration: 51760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12071 FastRCNN class loss: 0.10845 FastRCNN total loss: 0.22915 L1 loss: 0.0000e+00 L2 loss: 0.60829 Learning rate: 0.002 Mask loss: 0.10358 RPN box loss: 0.01757 RPN score loss: 0.00473 RPN total loss: 0.02231 Total loss: 0.96333 timestamp: 1654955068.396839 iteration: 51765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10179 FastRCNN class loss: 0.08426 FastRCNN total loss: 0.18606 L1 loss: 0.0000e+00 L2 loss: 0.60828 Learning rate: 0.002 Mask loss: 0.16867 RPN box loss: 0.0194 RPN score loss: 0.01695 RPN total loss: 0.03634 Total loss: 0.99936 timestamp: 1654955071.6179755 iteration: 51770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10061 FastRCNN class loss: 0.05309 FastRCNN total loss: 0.15369 L1 loss: 0.0000e+00 L2 loss: 0.60828 Learning rate: 0.002 Mask loss: 0.11989 RPN box loss: 0.00751 RPN score loss: 0.01038 RPN total loss: 0.01789 Total loss: 0.89975 timestamp: 1654955074.9170804 iteration: 51775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1282 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.19055 L1 loss: 0.0000e+00 L2 loss: 0.60827 Learning rate: 0.002 Mask loss: 0.16095 RPN box loss: 0.02265 RPN score loss: 0.00454 RPN total loss: 0.02719 Total loss: 0.98696 timestamp: 1654955078.1411874 iteration: 51780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11936 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.17204 L1 loss: 0.0000e+00 L2 loss: 0.60826 Learning rate: 0.002 Mask loss: 0.12203 RPN box loss: 0.01995 RPN score loss: 0.00379 RPN total loss: 0.02374 Total loss: 0.92608 timestamp: 1654955081.5846684 iteration: 51785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07117 FastRCNN class loss: 0.03832 FastRCNN total loss: 0.10949 L1 loss: 0.0000e+00 L2 loss: 0.60825 Learning rate: 0.002 Mask loss: 0.12014 RPN box loss: 0.00612 RPN score loss: 0.00137 RPN total loss: 0.00748 Total loss: 0.84536 timestamp: 1654955084.7724843 iteration: 51790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15303 FastRCNN class loss: 0.09688 FastRCNN total loss: 0.24991 L1 loss: 0.0000e+00 L2 loss: 0.60824 Learning rate: 0.002 Mask loss: 0.14977 RPN box loss: 0.02981 RPN score loss: 0.00289 RPN total loss: 0.03269 Total loss: 1.0406 timestamp: 1654955088.0680442 iteration: 51795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05311 FastRCNN class loss: 0.03563 FastRCNN total loss: 0.08873 L1 loss: 0.0000e+00 L2 loss: 0.60823 Learning rate: 0.002 Mask loss: 0.13308 RPN box loss: 0.01742 RPN score loss: 0.00415 RPN total loss: 0.02157 Total loss: 0.8516 timestamp: 1654955091.2729259 iteration: 51800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14436 FastRCNN class loss: 0.0825 FastRCNN total loss: 0.22686 L1 loss: 0.0000e+00 L2 loss: 0.60822 Learning rate: 0.002 Mask loss: 0.1645 RPN box loss: 0.04006 RPN score loss: 0.0019 RPN total loss: 0.04196 Total loss: 1.04153 timestamp: 1654955094.4979517 iteration: 51805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0766 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.13443 L1 loss: 0.0000e+00 L2 loss: 0.60821 Learning rate: 0.002 Mask loss: 0.11087 RPN box loss: 0.0068 RPN score loss: 0.00122 RPN total loss: 0.00801 Total loss: 0.86152 timestamp: 1654955097.7788298 iteration: 51810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09309 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.14307 L1 loss: 0.0000e+00 L2 loss: 0.6082 Learning rate: 0.002 Mask loss: 0.08954 RPN box loss: 0.00429 RPN score loss: 0.00108 RPN total loss: 0.00537 Total loss: 0.84619 timestamp: 1654955100.9286997 iteration: 51815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15656 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.2193 L1 loss: 0.0000e+00 L2 loss: 0.60819 Learning rate: 0.002 Mask loss: 0.1416 RPN box loss: 0.01613 RPN score loss: 0.00484 RPN total loss: 0.02098 Total loss: 0.99007 timestamp: 1654955104.249092 iteration: 51820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10881 FastRCNN class loss: 0.07892 FastRCNN total loss: 0.18773 L1 loss: 0.0000e+00 L2 loss: 0.60818 Learning rate: 0.002 Mask loss: 0.12432 RPN box loss: 0.00688 RPN score loss: 0.00419 RPN total loss: 0.01107 Total loss: 0.9313 timestamp: 1654955107.4993331 iteration: 51825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12089 FastRCNN class loss: 0.08443 FastRCNN total loss: 0.20532 L1 loss: 0.0000e+00 L2 loss: 0.60817 Learning rate: 0.002 Mask loss: 0.19392 RPN box loss: 0.01726 RPN score loss: 0.00558 RPN total loss: 0.02284 Total loss: 1.03025 timestamp: 1654955110.8851063 iteration: 51830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09764 FastRCNN class loss: 0.04589 FastRCNN total loss: 0.14353 L1 loss: 0.0000e+00 L2 loss: 0.60817 Learning rate: 0.002 Mask loss: 0.10843 RPN box loss: 0.03626 RPN score loss: 0.00407 RPN total loss: 0.04033 Total loss: 0.90045 timestamp: 1654955114.1719747 iteration: 51835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15735 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.22933 L1 loss: 0.0000e+00 L2 loss: 0.60816 Learning rate: 0.002 Mask loss: 0.10427 RPN box loss: 0.0116 RPN score loss: 0.00353 RPN total loss: 0.01513 Total loss: 0.95688 timestamp: 1654955117.5504553 iteration: 51840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.15107 L1 loss: 0.0000e+00 L2 loss: 0.60815 Learning rate: 0.002 Mask loss: 0.08284 RPN box loss: 0.008 RPN score loss: 0.00231 RPN total loss: 0.01032 Total loss: 0.85237 timestamp: 1654955120.7385938 iteration: 51845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05679 FastRCNN class loss: 0.06632 FastRCNN total loss: 0.12311 L1 loss: 0.0000e+00 L2 loss: 0.60814 Learning rate: 0.002 Mask loss: 0.08848 RPN box loss: 0.00903 RPN score loss: 0.00235 RPN total loss: 0.01138 Total loss: 0.83111 timestamp: 1654955124.0085406 iteration: 51850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.16446 L1 loss: 0.0000e+00 L2 loss: 0.60813 Learning rate: 0.002 Mask loss: 0.13396 RPN box loss: 0.05565 RPN score loss: 0.00335 RPN total loss: 0.059 Total loss: 0.96555 timestamp: 1654955127.2803543 iteration: 51855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09302 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.17062 L1 loss: 0.0000e+00 L2 loss: 0.60812 Learning rate: 0.002 Mask loss: 0.11942 RPN box loss: 0.00576 RPN score loss: 0.00155 RPN total loss: 0.00732 Total loss: 0.90548 timestamp: 1654955130.5338156 iteration: 51860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11243 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.17883 L1 loss: 0.0000e+00 L2 loss: 0.60811 Learning rate: 0.002 Mask loss: 0.13269 RPN box loss: 0.02651 RPN score loss: 0.00219 RPN total loss: 0.0287 Total loss: 0.94833 timestamp: 1654955133.8992965 iteration: 51865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10584 FastRCNN class loss: 0.08202 FastRCNN total loss: 0.18785 L1 loss: 0.0000e+00 L2 loss: 0.6081 Learning rate: 0.002 Mask loss: 0.14631 RPN box loss: 0.01278 RPN score loss: 0.00321 RPN total loss: 0.01599 Total loss: 0.95825 timestamp: 1654955136.9945123 iteration: 51870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11121 FastRCNN class loss: 0.0767 FastRCNN total loss: 0.18791 L1 loss: 0.0000e+00 L2 loss: 0.60809 Learning rate: 0.002 Mask loss: 0.15674 RPN box loss: 0.01314 RPN score loss: 0.00643 RPN total loss: 0.01957 Total loss: 0.97231 timestamp: 1654955140.1735833 iteration: 51875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05878 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.1055 L1 loss: 0.0000e+00 L2 loss: 0.60808 Learning rate: 0.002 Mask loss: 0.13821 RPN box loss: 0.00903 RPN score loss: 0.00209 RPN total loss: 0.01112 Total loss: 0.86291 timestamp: 1654955143.4075773 iteration: 51880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05211 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.09709 L1 loss: 0.0000e+00 L2 loss: 0.60807 Learning rate: 0.002 Mask loss: 0.15194 RPN box loss: 0.01674 RPN score loss: 0.00321 RPN total loss: 0.01995 Total loss: 0.87705 timestamp: 1654955146.6657288 iteration: 51885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08709 FastRCNN class loss: 0.05403 FastRCNN total loss: 0.14112 L1 loss: 0.0000e+00 L2 loss: 0.60807 Learning rate: 0.002 Mask loss: 0.17876 RPN box loss: 0.01071 RPN score loss: 0.00537 RPN total loss: 0.01608 Total loss: 0.94403 timestamp: 1654955149.8031442 iteration: 51890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04836 FastRCNN class loss: 0.05997 FastRCNN total loss: 0.10833 L1 loss: 0.0000e+00 L2 loss: 0.60805 Learning rate: 0.002 Mask loss: 0.12036 RPN box loss: 0.00811 RPN score loss: 0.00223 RPN total loss: 0.01035 Total loss: 0.84709 timestamp: 1654955153.1214006 iteration: 51895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09224 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.15899 L1 loss: 0.0000e+00 L2 loss: 0.60804 Learning rate: 0.002 Mask loss: 0.15419 RPN box loss: 0.02306 RPN score loss: 0.0046 RPN total loss: 0.02767 Total loss: 0.94889 timestamp: 1654955156.3562694 iteration: 51900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09887 FastRCNN class loss: 0.06328 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 0.60803 Learning rate: 0.002 Mask loss: 0.13345 RPN box loss: 0.00466 RPN score loss: 0.0148 RPN total loss: 0.01946 Total loss: 0.92309 timestamp: 1654955159.5846946 iteration: 51905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09363 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.15536 L1 loss: 0.0000e+00 L2 loss: 0.60803 Learning rate: 0.002 Mask loss: 0.1194 RPN box loss: 0.02428 RPN score loss: 0.0049 RPN total loss: 0.02918 Total loss: 0.91197 timestamp: 1654955162.8307226 iteration: 51910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12273 FastRCNN class loss: 0.12662 FastRCNN total loss: 0.24936 L1 loss: 0.0000e+00 L2 loss: 0.60802 Learning rate: 0.002 Mask loss: 0.21442 RPN box loss: 0.01997 RPN score loss: 0.00817 RPN total loss: 0.02814 Total loss: 1.09995 timestamp: 1654955166.2344615 iteration: 51915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07686 FastRCNN class loss: 0.04259 FastRCNN total loss: 0.11945 L1 loss: 0.0000e+00 L2 loss: 0.60802 Learning rate: 0.002 Mask loss: 0.10116 RPN box loss: 0.01842 RPN score loss: 0.00202 RPN total loss: 0.02044 Total loss: 0.84906 timestamp: 1654955169.5791554 iteration: 51920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11408 FastRCNN class loss: 0.05414 FastRCNN total loss: 0.16822 L1 loss: 0.0000e+00 L2 loss: 0.60801 Learning rate: 0.002 Mask loss: 0.10698 RPN box loss: 0.00443 RPN score loss: 0.00255 RPN total loss: 0.00698 Total loss: 0.89019 timestamp: 1654955172.789041 iteration: 51925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10786 FastRCNN class loss: 0.0543 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 0.608 Learning rate: 0.002 Mask loss: 0.14526 RPN box loss: 0.01586 RPN score loss: 0.00441 RPN total loss: 0.02027 Total loss: 0.9357 timestamp: 1654955176.0850682 iteration: 51930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11233 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.1973 L1 loss: 0.0000e+00 L2 loss: 0.60799 Learning rate: 0.002 Mask loss: 0.13084 RPN box loss: 0.0096 RPN score loss: 0.00197 RPN total loss: 0.01157 Total loss: 0.94771 timestamp: 1654955179.2583878 iteration: 51935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14515 FastRCNN class loss: 0.089 FastRCNN total loss: 0.23415 L1 loss: 0.0000e+00 L2 loss: 0.60798 Learning rate: 0.002 Mask loss: 0.16902 RPN box loss: 0.03083 RPN score loss: 0.01565 RPN total loss: 0.04649 Total loss: 1.05764 timestamp: 1654955182.530191 iteration: 51940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07546 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.15033 L1 loss: 0.0000e+00 L2 loss: 0.60797 Learning rate: 0.002 Mask loss: 0.15974 RPN box loss: 0.00996 RPN score loss: 0.00329 RPN total loss: 0.01325 Total loss: 0.9313 timestamp: 1654955185.7937398 iteration: 51945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05994 FastRCNN class loss: 0.06135 FastRCNN total loss: 0.12129 L1 loss: 0.0000e+00 L2 loss: 0.60796 Learning rate: 0.002 Mask loss: 0.07869 RPN box loss: 0.01265 RPN score loss: 0.00202 RPN total loss: 0.01468 Total loss: 0.82262 timestamp: 1654955189.0684407 iteration: 51950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08476 FastRCNN class loss: 0.0532 FastRCNN total loss: 0.13796 L1 loss: 0.0000e+00 L2 loss: 0.60795 Learning rate: 0.002 Mask loss: 0.14015 RPN box loss: 0.03754 RPN score loss: 0.00161 RPN total loss: 0.03915 Total loss: 0.92521 timestamp: 1654955192.3013628 iteration: 51955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09886 FastRCNN class loss: 0.07801 FastRCNN total loss: 0.17686 L1 loss: 0.0000e+00 L2 loss: 0.60794 Learning rate: 0.002 Mask loss: 0.10733 RPN box loss: 0.01669 RPN score loss: 0.00612 RPN total loss: 0.02281 Total loss: 0.91495 timestamp: 1654955195.6719215 iteration: 51960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04942 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.10511 L1 loss: 0.0000e+00 L2 loss: 0.60793 Learning rate: 0.002 Mask loss: 0.10787 RPN box loss: 0.01281 RPN score loss: 0.00704 RPN total loss: 0.01985 Total loss: 0.84077 timestamp: 1654955198.9968245 iteration: 51965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08859 FastRCNN class loss: 0.08079 FastRCNN total loss: 0.16938 L1 loss: 0.0000e+00 L2 loss: 0.60793 Learning rate: 0.002 Mask loss: 0.14594 RPN box loss: 0.02276 RPN score loss: 0.00403 RPN total loss: 0.02679 Total loss: 0.95003 timestamp: 1654955202.2269287 iteration: 51970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.082 FastRCNN class loss: 0.05403 FastRCNN total loss: 0.13603 L1 loss: 0.0000e+00 L2 loss: 0.60792 Learning rate: 0.002 Mask loss: 0.12126 RPN box loss: 0.01153 RPN score loss: 0.00383 RPN total loss: 0.01536 Total loss: 0.88057 timestamp: 1654955205.5933528 iteration: 51975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09716 FastRCNN class loss: 0.09975 FastRCNN total loss: 0.19692 L1 loss: 0.0000e+00 L2 loss: 0.60791 Learning rate: 0.002 Mask loss: 0.17103 RPN box loss: 0.01164 RPN score loss: 0.01309 RPN total loss: 0.02473 Total loss: 1.00058 timestamp: 1654955208.8275976 iteration: 51980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07889 FastRCNN class loss: 0.07894 FastRCNN total loss: 0.15783 L1 loss: 0.0000e+00 L2 loss: 0.6079 Learning rate: 0.002 Mask loss: 0.12543 RPN box loss: 0.00809 RPN score loss: 0.00691 RPN total loss: 0.01499 Total loss: 0.90615 timestamp: 1654955212.1044514 iteration: 51985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.125 FastRCNN class loss: 0.0752 FastRCNN total loss: 0.20019 L1 loss: 0.0000e+00 L2 loss: 0.60789 Learning rate: 0.002 Mask loss: 0.14325 RPN box loss: 0.01825 RPN score loss: 0.00801 RPN total loss: 0.02627 Total loss: 0.9776 timestamp: 1654955215.3295195 iteration: 51990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1034 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.171 L1 loss: 0.0000e+00 L2 loss: 0.60788 Learning rate: 0.002 Mask loss: 0.18884 RPN box loss: 0.0353 RPN score loss: 0.00319 RPN total loss: 0.0385 Total loss: 1.00622 timestamp: 1654955218.681221 iteration: 51995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08436 FastRCNN class loss: 0.05117 FastRCNN total loss: 0.13553 L1 loss: 0.0000e+00 L2 loss: 0.60788 Learning rate: 0.002 Mask loss: 0.13193 RPN box loss: 0.0336 RPN score loss: 0.00214 RPN total loss: 0.03574 Total loss: 0.91107 timestamp: 1654955221.8724957 iteration: 52000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.1718 L1 loss: 0.0000e+00 L2 loss: 0.60787 Learning rate: 0.002 Mask loss: 0.13556 RPN box loss: 0.00784 RPN score loss: 0.0026 RPN total loss: 0.01043 Total loss: 0.92566 timestamp: 1654955225.1719582 iteration: 52005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08036 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.12969 L1 loss: 0.0000e+00 L2 loss: 0.60786 Learning rate: 0.002 Mask loss: 0.15276 RPN box loss: 0.00294 RPN score loss: 0.0021 RPN total loss: 0.00504 Total loss: 0.89535 timestamp: 1654955228.350794 iteration: 52010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.06216 FastRCNN total loss: 0.15534 L1 loss: 0.0000e+00 L2 loss: 0.60785 Learning rate: 0.002 Mask loss: 0.19612 RPN box loss: 0.01519 RPN score loss: 0.00354 RPN total loss: 0.01873 Total loss: 0.97803 timestamp: 1654955231.599173 iteration: 52015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11073 FastRCNN class loss: 0.0726 FastRCNN total loss: 0.18333 L1 loss: 0.0000e+00 L2 loss: 0.60784 Learning rate: 0.002 Mask loss: 0.14121 RPN box loss: 0.02216 RPN score loss: 0.00604 RPN total loss: 0.0282 Total loss: 0.96058 timestamp: 1654955234.9540925 iteration: 52020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.17416 L1 loss: 0.0000e+00 L2 loss: 0.60783 Learning rate: 0.002 Mask loss: 0.15428 RPN box loss: 0.01755 RPN score loss: 0.00874 RPN total loss: 0.02628 Total loss: 0.96255 timestamp: 1654955238.159352 iteration: 52025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10157 FastRCNN class loss: 0.10192 FastRCNN total loss: 0.20349 L1 loss: 0.0000e+00 L2 loss: 0.60783 Learning rate: 0.002 Mask loss: 0.14108 RPN box loss: 0.05585 RPN score loss: 0.006 RPN total loss: 0.06185 Total loss: 1.01425 timestamp: 1654955241.418126 iteration: 52030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07121 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.13045 L1 loss: 0.0000e+00 L2 loss: 0.60782 Learning rate: 0.002 Mask loss: 0.12965 RPN box loss: 0.01661 RPN score loss: 0.00465 RPN total loss: 0.02125 Total loss: 0.88918 timestamp: 1654955244.6203158 iteration: 52035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05018 FastRCNN class loss: 0.04008 FastRCNN total loss: 0.09026 L1 loss: 0.0000e+00 L2 loss: 0.60781 Learning rate: 0.002 Mask loss: 0.08702 RPN box loss: 0.02025 RPN score loss: 0.0031 RPN total loss: 0.02334 Total loss: 0.80843 timestamp: 1654955247.8963008 iteration: 52040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1125 FastRCNN class loss: 0.05698 FastRCNN total loss: 0.16947 L1 loss: 0.0000e+00 L2 loss: 0.6078 Learning rate: 0.002 Mask loss: 0.09323 RPN box loss: 0.01807 RPN score loss: 0.00354 RPN total loss: 0.02161 Total loss: 0.89211 timestamp: 1654955251.082753 iteration: 52045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14044 FastRCNN class loss: 0.07973 FastRCNN total loss: 0.22017 L1 loss: 0.0000e+00 L2 loss: 0.60779 Learning rate: 0.002 Mask loss: 0.13952 RPN box loss: 0.02646 RPN score loss: 0.0086 RPN total loss: 0.03506 Total loss: 1.00253 timestamp: 1654955254.3399951 iteration: 52050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08927 FastRCNN class loss: 0.03289 FastRCNN total loss: 0.12216 L1 loss: 0.0000e+00 L2 loss: 0.60778 Learning rate: 0.002 Mask loss: 0.12417 RPN box loss: 0.00799 RPN score loss: 0.00702 RPN total loss: 0.01501 Total loss: 0.86912 timestamp: 1654955257.5186188 iteration: 52055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09365 FastRCNN class loss: 0.08426 FastRCNN total loss: 0.17791 L1 loss: 0.0000e+00 L2 loss: 0.60777 Learning rate: 0.002 Mask loss: 0.15114 RPN box loss: 0.01994 RPN score loss: 0.0054 RPN total loss: 0.02533 Total loss: 0.96215 timestamp: 1654955260.7519636 iteration: 52060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12935 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.21008 L1 loss: 0.0000e+00 L2 loss: 0.60777 Learning rate: 0.002 Mask loss: 0.12217 RPN box loss: 0.00616 RPN score loss: 0.00552 RPN total loss: 0.01168 Total loss: 0.95169 timestamp: 1654955263.9172025 iteration: 52065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07934 FastRCNN class loss: 0.08431 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 0.60776 Learning rate: 0.002 Mask loss: 0.11933 RPN box loss: 0.00755 RPN score loss: 0.00867 RPN total loss: 0.01622 Total loss: 0.90696 timestamp: 1654955267.216867 iteration: 52070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13391 FastRCNN class loss: 0.0529 FastRCNN total loss: 0.18681 L1 loss: 0.0000e+00 L2 loss: 0.60775 Learning rate: 0.002 Mask loss: 0.10421 RPN box loss: 0.00428 RPN score loss: 0.00235 RPN total loss: 0.00662 Total loss: 0.90539 timestamp: 1654955270.5894454 iteration: 52075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0782 FastRCNN class loss: 0.04774 FastRCNN total loss: 0.12595 L1 loss: 0.0000e+00 L2 loss: 0.60774 Learning rate: 0.002 Mask loss: 0.14442 RPN box loss: 0.01443 RPN score loss: 0.00784 RPN total loss: 0.02227 Total loss: 0.90037 timestamp: 1654955273.766357 iteration: 52080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04647 FastRCNN class loss: 0.03674 FastRCNN total loss: 0.08321 L1 loss: 0.0000e+00 L2 loss: 0.60773 Learning rate: 0.002 Mask loss: 0.08731 RPN box loss: 0.0187 RPN score loss: 0.00149 RPN total loss: 0.0202 Total loss: 0.79844 timestamp: 1654955277.0740843 iteration: 52085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09402 FastRCNN class loss: 0.0612 FastRCNN total loss: 0.15522 L1 loss: 0.0000e+00 L2 loss: 0.60772 Learning rate: 0.002 Mask loss: 0.13592 RPN box loss: 0.00608 RPN score loss: 0.00107 RPN total loss: 0.00715 Total loss: 0.90601 timestamp: 1654955280.2990148 iteration: 52090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10199 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.18733 L1 loss: 0.0000e+00 L2 loss: 0.60771 Learning rate: 0.002 Mask loss: 0.1551 RPN box loss: 0.03471 RPN score loss: 0.01082 RPN total loss: 0.04552 Total loss: 0.99567 timestamp: 1654955283.5823019 iteration: 52095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07339 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.14075 L1 loss: 0.0000e+00 L2 loss: 0.6077 Learning rate: 0.002 Mask loss: 0.17935 RPN box loss: 0.00777 RPN score loss: 0.00325 RPN total loss: 0.01102 Total loss: 0.93882 timestamp: 1654955286.7340186 iteration: 52100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10321 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.18713 L1 loss: 0.0000e+00 L2 loss: 0.6077 Learning rate: 0.002 Mask loss: 0.12633 RPN box loss: 0.02009 RPN score loss: 0.005 RPN total loss: 0.02509 Total loss: 0.94624 timestamp: 1654955290.0276704 iteration: 52105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11211 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.17827 L1 loss: 0.0000e+00 L2 loss: 0.60769 Learning rate: 0.002 Mask loss: 0.14885 RPN box loss: 0.01758 RPN score loss: 0.00452 RPN total loss: 0.0221 Total loss: 0.95691 timestamp: 1654955293.2398615 iteration: 52110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.06811 FastRCNN total loss: 0.1857 L1 loss: 0.0000e+00 L2 loss: 0.60768 Learning rate: 0.002 Mask loss: 0.1055 RPN box loss: 0.03312 RPN score loss: 0.00358 RPN total loss: 0.0367 Total loss: 0.93558 timestamp: 1654955296.502658 iteration: 52115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12962 FastRCNN class loss: 0.09673 FastRCNN total loss: 0.22635 L1 loss: 0.0000e+00 L2 loss: 0.60767 Learning rate: 0.002 Mask loss: 0.12749 RPN box loss: 0.01909 RPN score loss: 0.0029 RPN total loss: 0.02199 Total loss: 0.9835 timestamp: 1654955299.6873448 iteration: 52120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11328 FastRCNN class loss: 0.05338 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.60766 Learning rate: 0.002 Mask loss: 0.13026 RPN box loss: 0.0178 RPN score loss: 0.00728 RPN total loss: 0.02508 Total loss: 0.92966 timestamp: 1654955303.0008686 iteration: 52125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0645 FastRCNN class loss: 0.08737 FastRCNN total loss: 0.15187 L1 loss: 0.0000e+00 L2 loss: 0.60765 Learning rate: 0.002 Mask loss: 0.13602 RPN box loss: 0.01936 RPN score loss: 0.00209 RPN total loss: 0.02145 Total loss: 0.91699 timestamp: 1654955306.2706685 iteration: 52130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12686 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.17688 L1 loss: 0.0000e+00 L2 loss: 0.60764 Learning rate: 0.002 Mask loss: 0.0828 RPN box loss: 0.01119 RPN score loss: 0.00168 RPN total loss: 0.01287 Total loss: 0.8802 timestamp: 1654955309.4850383 iteration: 52135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06505 FastRCNN class loss: 0.05108 FastRCNN total loss: 0.11613 L1 loss: 0.0000e+00 L2 loss: 0.60764 Learning rate: 0.002 Mask loss: 0.11231 RPN box loss: 0.00946 RPN score loss: 0.00269 RPN total loss: 0.01215 Total loss: 0.84823 timestamp: 1654955312.6910584 iteration: 52140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0859 FastRCNN class loss: 0.08784 FastRCNN total loss: 0.17374 L1 loss: 0.0000e+00 L2 loss: 0.60763 Learning rate: 0.002 Mask loss: 0.14736 RPN box loss: 0.01927 RPN score loss: 0.0059 RPN total loss: 0.02517 Total loss: 0.9539 timestamp: 1654955315.8648689 iteration: 52145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18904 FastRCNN class loss: 0.10113 FastRCNN total loss: 0.29018 L1 loss: 0.0000e+00 L2 loss: 0.60762 Learning rate: 0.002 Mask loss: 0.18944 RPN box loss: 0.02696 RPN score loss: 0.01487 RPN total loss: 0.04183 Total loss: 1.12906 timestamp: 1654955319.1992085 iteration: 52150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11693 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.21767 L1 loss: 0.0000e+00 L2 loss: 0.60761 Learning rate: 0.002 Mask loss: 0.10849 RPN box loss: 0.03038 RPN score loss: 0.00976 RPN total loss: 0.04014 Total loss: 0.97392 timestamp: 1654955322.361992 iteration: 52155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10343 FastRCNN class loss: 0.06006 FastRCNN total loss: 0.16349 L1 loss: 0.0000e+00 L2 loss: 0.6076 Learning rate: 0.002 Mask loss: 0.14852 RPN box loss: 0.01997 RPN score loss: 0.00655 RPN total loss: 0.02652 Total loss: 0.94612 timestamp: 1654955325.619673 iteration: 52160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05881 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.14182 L1 loss: 0.0000e+00 L2 loss: 0.60759 Learning rate: 0.002 Mask loss: 0.0902 RPN box loss: 0.01692 RPN score loss: 0.01337 RPN total loss: 0.03029 Total loss: 0.8699 timestamp: 1654955328.914082 iteration: 52165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10094 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.16218 L1 loss: 0.0000e+00 L2 loss: 0.60758 Learning rate: 0.002 Mask loss: 0.14214 RPN box loss: 0.00468 RPN score loss: 0.00338 RPN total loss: 0.00806 Total loss: 0.91995 timestamp: 1654955332.2068582 iteration: 52170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11126 FastRCNN class loss: 0.05794 FastRCNN total loss: 0.1692 L1 loss: 0.0000e+00 L2 loss: 0.60757 Learning rate: 0.002 Mask loss: 0.1503 RPN box loss: 0.03789 RPN score loss: 0.00309 RPN total loss: 0.04098 Total loss: 0.96806 timestamp: 1654955335.374629 iteration: 52175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.056 FastRCNN class loss: 0.05395 FastRCNN total loss: 0.10995 L1 loss: 0.0000e+00 L2 loss: 0.60757 Learning rate: 0.002 Mask loss: 0.1244 RPN box loss: 0.0163 RPN score loss: 0.00288 RPN total loss: 0.01918 Total loss: 0.86109 timestamp: 1654955338.634151 iteration: 52180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17477 FastRCNN class loss: 0.1759 FastRCNN total loss: 0.35067 L1 loss: 0.0000e+00 L2 loss: 0.60756 Learning rate: 0.002 Mask loss: 0.12474 RPN box loss: 0.01545 RPN score loss: 0.00948 RPN total loss: 0.02493 Total loss: 1.10789 timestamp: 1654955341.8357465 iteration: 52185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08448 FastRCNN class loss: 0.03592 FastRCNN total loss: 0.1204 L1 loss: 0.0000e+00 L2 loss: 0.60755 Learning rate: 0.002 Mask loss: 0.12085 RPN box loss: 0.00725 RPN score loss: 0.00457 RPN total loss: 0.01182 Total loss: 0.86062 timestamp: 1654955345.1035466 iteration: 52190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.14148 L1 loss: 0.0000e+00 L2 loss: 0.60754 Learning rate: 0.002 Mask loss: 0.11144 RPN box loss: 0.02623 RPN score loss: 0.00699 RPN total loss: 0.03322 Total loss: 0.89368 timestamp: 1654955348.5028265 iteration: 52195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13958 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.20217 L1 loss: 0.0000e+00 L2 loss: 0.60753 Learning rate: 0.002 Mask loss: 0.24427 RPN box loss: 0.00988 RPN score loss: 0.00986 RPN total loss: 0.01974 Total loss: 1.07371 timestamp: 1654955351.7066681 iteration: 52200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04581 FastRCNN class loss: 0.06393 FastRCNN total loss: 0.10974 L1 loss: 0.0000e+00 L2 loss: 0.60752 Learning rate: 0.002 Mask loss: 0.09483 RPN box loss: 0.00526 RPN score loss: 0.00416 RPN total loss: 0.00942 Total loss: 0.82152 timestamp: 1654955354.9281101 iteration: 52205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06097 FastRCNN class loss: 0.03778 FastRCNN total loss: 0.09875 L1 loss: 0.0000e+00 L2 loss: 0.60751 Learning rate: 0.002 Mask loss: 0.10786 RPN box loss: 0.02543 RPN score loss: 0.00126 RPN total loss: 0.02668 Total loss: 0.84081 timestamp: 1654955358.1153328 iteration: 52210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09953 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.18574 L1 loss: 0.0000e+00 L2 loss: 0.6075 Learning rate: 0.002 Mask loss: 0.20965 RPN box loss: 0.02493 RPN score loss: 0.01052 RPN total loss: 0.03545 Total loss: 1.03834 timestamp: 1654955361.371299 iteration: 52215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08955 FastRCNN class loss: 0.1012 FastRCNN total loss: 0.19075 L1 loss: 0.0000e+00 L2 loss: 0.60749 Learning rate: 0.002 Mask loss: 0.1576 RPN box loss: 0.0174 RPN score loss: 0.00663 RPN total loss: 0.02403 Total loss: 0.97987 timestamp: 1654955364.5205142 iteration: 52220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11339 FastRCNN class loss: 0.07341 FastRCNN total loss: 0.1868 L1 loss: 0.0000e+00 L2 loss: 0.60749 Learning rate: 0.002 Mask loss: 0.09649 RPN box loss: 0.0107 RPN score loss: 0.00407 RPN total loss: 0.01476 Total loss: 0.90554 timestamp: 1654955367.8277366 iteration: 52225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11075 FastRCNN class loss: 0.06208 FastRCNN total loss: 0.17282 L1 loss: 0.0000e+00 L2 loss: 0.60748 Learning rate: 0.002 Mask loss: 0.10493 RPN box loss: 0.02413 RPN score loss: 0.01028 RPN total loss: 0.03441 Total loss: 0.91965 timestamp: 1654955371.051605 iteration: 52230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14987 FastRCNN class loss: 0.05253 FastRCNN total loss: 0.2024 L1 loss: 0.0000e+00 L2 loss: 0.60747 Learning rate: 0.002 Mask loss: 0.1382 RPN box loss: 0.01916 RPN score loss: 0.00549 RPN total loss: 0.02465 Total loss: 0.97272 timestamp: 1654955374.3339865 iteration: 52235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06252 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.12856 L1 loss: 0.0000e+00 L2 loss: 0.60746 Learning rate: 0.002 Mask loss: 0.09179 RPN box loss: 0.01431 RPN score loss: 0.00888 RPN total loss: 0.02319 Total loss: 0.85099 timestamp: 1654955377.5337434 iteration: 52240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08164 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.1512 L1 loss: 0.0000e+00 L2 loss: 0.60745 Learning rate: 0.002 Mask loss: 0.17674 RPN box loss: 0.01049 RPN score loss: 0.00475 RPN total loss: 0.01523 Total loss: 0.95063 timestamp: 1654955380.9071681 iteration: 52245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.04793 FastRCNN total loss: 0.10891 L1 loss: 0.0000e+00 L2 loss: 0.60744 Learning rate: 0.002 Mask loss: 0.13308 RPN box loss: 0.01083 RPN score loss: 0.00158 RPN total loss: 0.0124 Total loss: 0.86184 timestamp: 1654955384.2383685 iteration: 52250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13453 FastRCNN class loss: 0.07086 FastRCNN total loss: 0.20539 L1 loss: 0.0000e+00 L2 loss: 0.60743 Learning rate: 0.002 Mask loss: 0.1195 RPN box loss: 0.03341 RPN score loss: 0.00482 RPN total loss: 0.03823 Total loss: 0.97056 timestamp: 1654955387.3987975 iteration: 52255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05346 FastRCNN class loss: 0.03809 FastRCNN total loss: 0.09155 L1 loss: 0.0000e+00 L2 loss: 0.60743 Learning rate: 0.002 Mask loss: 0.12226 RPN box loss: 0.0073 RPN score loss: 0.00669 RPN total loss: 0.01399 Total loss: 0.83522 timestamp: 1654955390.6008124 iteration: 52260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.139 FastRCNN class loss: 0.12358 FastRCNN total loss: 0.26258 L1 loss: 0.0000e+00 L2 loss: 0.60741 Learning rate: 0.002 Mask loss: 0.21017 RPN box loss: 0.01596 RPN score loss: 0.0067 RPN total loss: 0.02266 Total loss: 1.10282 timestamp: 1654955393.7702992 iteration: 52265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.20375 L1 loss: 0.0000e+00 L2 loss: 0.6074 Learning rate: 0.002 Mask loss: 0.11281 RPN box loss: 0.02745 RPN score loss: 0.00843 RPN total loss: 0.03588 Total loss: 0.95984 timestamp: 1654955397.0850942 iteration: 52270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12117 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.17613 L1 loss: 0.0000e+00 L2 loss: 0.60739 Learning rate: 0.002 Mask loss: 0.12448 RPN box loss: 0.0198 RPN score loss: 0.00243 RPN total loss: 0.02223 Total loss: 0.93022 timestamp: 1654955400.263097 iteration: 52275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04041 FastRCNN class loss: 0.04776 FastRCNN total loss: 0.08818 L1 loss: 0.0000e+00 L2 loss: 0.60738 Learning rate: 0.002 Mask loss: 0.09225 RPN box loss: 0.01854 RPN score loss: 0.00764 RPN total loss: 0.02618 Total loss: 0.81398 timestamp: 1654955403.6203117 iteration: 52280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05229 FastRCNN class loss: 0.06322 FastRCNN total loss: 0.11551 L1 loss: 0.0000e+00 L2 loss: 0.60737 Learning rate: 0.002 Mask loss: 0.1052 RPN box loss: 0.0086 RPN score loss: 0.00192 RPN total loss: 0.01053 Total loss: 0.8386 timestamp: 1654955406.8970008 iteration: 52285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11785 FastRCNN class loss: 0.08727 FastRCNN total loss: 0.20512 L1 loss: 0.0000e+00 L2 loss: 0.60736 Learning rate: 0.002 Mask loss: 0.12156 RPN box loss: 0.01048 RPN score loss: 0.00657 RPN total loss: 0.01705 Total loss: 0.95109 timestamp: 1654955410.1855056 iteration: 52290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17377 FastRCNN class loss: 0.0634 FastRCNN total loss: 0.23717 L1 loss: 0.0000e+00 L2 loss: 0.60736 Learning rate: 0.002 Mask loss: 0.12038 RPN box loss: 0.00593 RPN score loss: 0.00248 RPN total loss: 0.00841 Total loss: 0.97332 timestamp: 1654955413.3705125 iteration: 52295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18122 FastRCNN class loss: 0.06896 FastRCNN total loss: 0.25018 L1 loss: 0.0000e+00 L2 loss: 0.60735 Learning rate: 0.002 Mask loss: 0.16635 RPN box loss: 0.01777 RPN score loss: 0.00409 RPN total loss: 0.02186 Total loss: 1.04573 timestamp: 1654955416.6984005 iteration: 52300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10533 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.17081 L1 loss: 0.0000e+00 L2 loss: 0.60734 Learning rate: 0.002 Mask loss: 0.10508 RPN box loss: 0.00487 RPN score loss: 0.00314 RPN total loss: 0.00801 Total loss: 0.89124 timestamp: 1654955419.964885 iteration: 52305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10247 FastRCNN class loss: 0.07369 FastRCNN total loss: 0.17616 L1 loss: 0.0000e+00 L2 loss: 0.60733 Learning rate: 0.002 Mask loss: 0.14819 RPN box loss: 0.01671 RPN score loss: 0.00509 RPN total loss: 0.02181 Total loss: 0.95348 timestamp: 1654955423.1745014 iteration: 52310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03364 FastRCNN class loss: 0.0539 FastRCNN total loss: 0.08754 L1 loss: 0.0000e+00 L2 loss: 0.60732 Learning rate: 0.002 Mask loss: 0.09479 RPN box loss: 0.00726 RPN score loss: 0.00299 RPN total loss: 0.01025 Total loss: 0.7999 timestamp: 1654955426.4882236 iteration: 52315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0761 FastRCNN class loss: 0.07152 FastRCNN total loss: 0.14762 L1 loss: 0.0000e+00 L2 loss: 0.60731 Learning rate: 0.002 Mask loss: 0.09368 RPN box loss: 0.02351 RPN score loss: 0.00492 RPN total loss: 0.02842 Total loss: 0.87704 timestamp: 1654955429.7037218 iteration: 52320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14459 FastRCNN class loss: 0.08935 FastRCNN total loss: 0.23394 L1 loss: 0.0000e+00 L2 loss: 0.6073 Learning rate: 0.002 Mask loss: 0.14531 RPN box loss: 0.01378 RPN score loss: 0.00995 RPN total loss: 0.02373 Total loss: 1.01028 timestamp: 1654955432.9672716 iteration: 52325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07831 FastRCNN class loss: 0.05242 FastRCNN total loss: 0.13073 L1 loss: 0.0000e+00 L2 loss: 0.60729 Learning rate: 0.002 Mask loss: 0.11466 RPN box loss: 0.0131 RPN score loss: 0.00359 RPN total loss: 0.01669 Total loss: 0.86938 timestamp: 1654955436.1465187 iteration: 52330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0582 FastRCNN class loss: 0.05787 FastRCNN total loss: 0.11608 L1 loss: 0.0000e+00 L2 loss: 0.60728 Learning rate: 0.002 Mask loss: 0.13948 RPN box loss: 0.02384 RPN score loss: 0.0031 RPN total loss: 0.02694 Total loss: 0.88978 timestamp: 1654955439.371414 iteration: 52335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0664 FastRCNN class loss: 0.04428 FastRCNN total loss: 0.11068 L1 loss: 0.0000e+00 L2 loss: 0.60727 Learning rate: 0.002 Mask loss: 0.10892 RPN box loss: 0.00997 RPN score loss: 0.00745 RPN total loss: 0.01742 Total loss: 0.8443 timestamp: 1654955442.5544527 iteration: 52340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10136 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.17438 L1 loss: 0.0000e+00 L2 loss: 0.60726 Learning rate: 0.002 Mask loss: 0.09343 RPN box loss: 0.00832 RPN score loss: 0.00256 RPN total loss: 0.01088 Total loss: 0.88595 timestamp: 1654955445.8217914 iteration: 52345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06119 FastRCNN class loss: 0.0418 FastRCNN total loss: 0.10299 L1 loss: 0.0000e+00 L2 loss: 0.60726 Learning rate: 0.002 Mask loss: 0.15038 RPN box loss: 0.01042 RPN score loss: 0.00615 RPN total loss: 0.01658 Total loss: 0.87721 timestamp: 1654955449.028874 iteration: 52350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09361 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.16358 L1 loss: 0.0000e+00 L2 loss: 0.60725 Learning rate: 0.002 Mask loss: 0.10225 RPN box loss: 0.01065 RPN score loss: 0.00616 RPN total loss: 0.01681 Total loss: 0.8899 timestamp: 1654955452.2969358 iteration: 52355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15138 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.22901 L1 loss: 0.0000e+00 L2 loss: 0.60724 Learning rate: 0.002 Mask loss: 0.12039 RPN box loss: 0.01758 RPN score loss: 0.00841 RPN total loss: 0.026 Total loss: 0.98264 timestamp: 1654955455.3910038 iteration: 52360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06398 FastRCNN class loss: 0.03621 FastRCNN total loss: 0.10018 L1 loss: 0.0000e+00 L2 loss: 0.60723 Learning rate: 0.002 Mask loss: 0.20091 RPN box loss: 0.03473 RPN score loss: 0.00185 RPN total loss: 0.03658 Total loss: 0.94491 timestamp: 1654955458.679917 iteration: 52365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05614 FastRCNN class loss: 0.04631 FastRCNN total loss: 0.10245 L1 loss: 0.0000e+00 L2 loss: 0.60722 Learning rate: 0.002 Mask loss: 0.09336 RPN box loss: 0.01273 RPN score loss: 0.00169 RPN total loss: 0.01443 Total loss: 0.81746 timestamp: 1654955461.956782 iteration: 52370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0513 FastRCNN class loss: 0.04554 FastRCNN total loss: 0.09684 L1 loss: 0.0000e+00 L2 loss: 0.60722 Learning rate: 0.002 Mask loss: 0.11128 RPN box loss: 0.01024 RPN score loss: 0.00492 RPN total loss: 0.01516 Total loss: 0.83049 timestamp: 1654955465.1421494 iteration: 52375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10806 FastRCNN class loss: 0.06993 FastRCNN total loss: 0.17799 L1 loss: 0.0000e+00 L2 loss: 0.60721 Learning rate: 0.002 Mask loss: 0.17265 RPN box loss: 0.00957 RPN score loss: 0.00675 RPN total loss: 0.01632 Total loss: 0.97416 timestamp: 1654955468.4192643 iteration: 52380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07791 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.1376 L1 loss: 0.0000e+00 L2 loss: 0.6072 Learning rate: 0.002 Mask loss: 0.08689 RPN box loss: 0.01078 RPN score loss: 0.0017 RPN total loss: 0.01248 Total loss: 0.84417 timestamp: 1654955471.609998 iteration: 52385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11251 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.18849 L1 loss: 0.0000e+00 L2 loss: 0.60719 Learning rate: 0.002 Mask loss: 0.12217 RPN box loss: 0.03386 RPN score loss: 0.00469 RPN total loss: 0.03854 Total loss: 0.95639 timestamp: 1654955474.983831 iteration: 52390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09354 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.15265 L1 loss: 0.0000e+00 L2 loss: 0.60718 Learning rate: 0.002 Mask loss: 0.12952 RPN box loss: 0.01026 RPN score loss: 0.00241 RPN total loss: 0.01267 Total loss: 0.90201 timestamp: 1654955478.2076356 iteration: 52395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08963 FastRCNN class loss: 0.04859 FastRCNN total loss: 0.13822 L1 loss: 0.0000e+00 L2 loss: 0.60717 Learning rate: 0.002 Mask loss: 0.09891 RPN box loss: 0.01026 RPN score loss: 0.00725 RPN total loss: 0.01751 Total loss: 0.8618 timestamp: 1654955481.4703598 iteration: 52400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10201 FastRCNN class loss: 0.07191 FastRCNN total loss: 0.17392 L1 loss: 0.0000e+00 L2 loss: 0.60716 Learning rate: 0.002 Mask loss: 0.09392 RPN box loss: 0.05257 RPN score loss: 0.00995 RPN total loss: 0.06252 Total loss: 0.93752 timestamp: 1654955484.6966712 iteration: 52405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13122 FastRCNN class loss: 0.08201 FastRCNN total loss: 0.21323 L1 loss: 0.0000e+00 L2 loss: 0.60715 Learning rate: 0.002 Mask loss: 0.15506 RPN box loss: 0.00988 RPN score loss: 0.011 RPN total loss: 0.02088 Total loss: 0.99632 timestamp: 1654955488.0724995 iteration: 52410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.08956 FastRCNN total loss: 0.17897 L1 loss: 0.0000e+00 L2 loss: 0.60714 Learning rate: 0.002 Mask loss: 0.16004 RPN box loss: 0.02031 RPN score loss: 0.00457 RPN total loss: 0.02488 Total loss: 0.97104 timestamp: 1654955491.3933675 iteration: 52415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13213 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.19789 L1 loss: 0.0000e+00 L2 loss: 0.60714 Learning rate: 0.002 Mask loss: 0.10906 RPN box loss: 0.02711 RPN score loss: 0.00335 RPN total loss: 0.03046 Total loss: 0.94454 timestamp: 1654955494.6555126 iteration: 52420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08132 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.14176 L1 loss: 0.0000e+00 L2 loss: 0.60713 Learning rate: 0.002 Mask loss: 0.14175 RPN box loss: 0.01303 RPN score loss: 0.01674 RPN total loss: 0.02978 Total loss: 0.92041 timestamp: 1654955497.9628336 iteration: 52425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09684 FastRCNN class loss: 0.0938 FastRCNN total loss: 0.19063 L1 loss: 0.0000e+00 L2 loss: 0.60712 Learning rate: 0.002 Mask loss: 0.15838 RPN box loss: 0.04692 RPN score loss: 0.01594 RPN total loss: 0.06287 Total loss: 1.019 timestamp: 1654955501.1935644 iteration: 52430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11478 FastRCNN class loss: 0.09079 FastRCNN total loss: 0.20557 L1 loss: 0.0000e+00 L2 loss: 0.60711 Learning rate: 0.002 Mask loss: 0.11875 RPN box loss: 0.01222 RPN score loss: 0.00374 RPN total loss: 0.01597 Total loss: 0.9474 timestamp: 1654955504.465126 iteration: 52435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12336 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.6071 Learning rate: 0.002 Mask loss: 0.09609 RPN box loss: 0.00934 RPN score loss: 0.00123 RPN total loss: 0.01057 Total loss: 0.89342 timestamp: 1654955507.6585648 iteration: 52440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14544 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.20971 L1 loss: 0.0000e+00 L2 loss: 0.60709 Learning rate: 0.002 Mask loss: 0.2115 RPN box loss: 0.01007 RPN score loss: 0.00788 RPN total loss: 0.01795 Total loss: 1.04625 timestamp: 1654955510.9592342 iteration: 52445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1178 FastRCNN class loss: 0.08412 FastRCNN total loss: 0.20192 L1 loss: 0.0000e+00 L2 loss: 0.60709 Learning rate: 0.002 Mask loss: 0.16516 RPN box loss: 0.02654 RPN score loss: 0.00411 RPN total loss: 0.03065 Total loss: 1.00482 timestamp: 1654955514.163968 iteration: 52450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07701 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.15909 L1 loss: 0.0000e+00 L2 loss: 0.60708 Learning rate: 0.002 Mask loss: 0.13217 RPN box loss: 0.02373 RPN score loss: 0.0131 RPN total loss: 0.03683 Total loss: 0.93517 timestamp: 1654955517.3720942 iteration: 52455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07573 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.12896 L1 loss: 0.0000e+00 L2 loss: 0.60707 Learning rate: 0.002 Mask loss: 0.13356 RPN box loss: 0.00636 RPN score loss: 0.00314 RPN total loss: 0.00949 Total loss: 0.87908 timestamp: 1654955520.6083086 iteration: 52460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08197 FastRCNN class loss: 0.06802 FastRCNN total loss: 0.14999 L1 loss: 0.0000e+00 L2 loss: 0.60706 Learning rate: 0.002 Mask loss: 0.1829 RPN box loss: 0.01362 RPN score loss: 0.00259 RPN total loss: 0.01621 Total loss: 0.95615 timestamp: 1654955523.9092915 iteration: 52465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.05344 FastRCNN total loss: 0.14015 L1 loss: 0.0000e+00 L2 loss: 0.60705 Learning rate: 0.002 Mask loss: 0.10475 RPN box loss: 0.0104 RPN score loss: 0.00299 RPN total loss: 0.01339 Total loss: 0.86533 timestamp: 1654955527.1800363 iteration: 52470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08233 FastRCNN class loss: 0.08632 FastRCNN total loss: 0.16865 L1 loss: 0.0000e+00 L2 loss: 0.60704 Learning rate: 0.002 Mask loss: 0.13721 RPN box loss: 0.0087 RPN score loss: 0.00449 RPN total loss: 0.01319 Total loss: 0.92609 timestamp: 1654955530.387866 iteration: 52475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10259 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.15713 L1 loss: 0.0000e+00 L2 loss: 0.60703 Learning rate: 0.002 Mask loss: 0.13031 RPN box loss: 0.01175 RPN score loss: 0.00424 RPN total loss: 0.016 Total loss: 0.91047 timestamp: 1654955533.7193549 iteration: 52480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10159 FastRCNN class loss: 0.08455 FastRCNN total loss: 0.18614 L1 loss: 0.0000e+00 L2 loss: 0.60702 Learning rate: 0.002 Mask loss: 0.1455 RPN box loss: 0.02998 RPN score loss: 0.00877 RPN total loss: 0.03875 Total loss: 0.97741 timestamp: 1654955536.949018 iteration: 52485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08198 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.14185 L1 loss: 0.0000e+00 L2 loss: 0.60702 Learning rate: 0.002 Mask loss: 0.09156 RPN box loss: 0.01999 RPN score loss: 0.00445 RPN total loss: 0.02445 Total loss: 0.86487 timestamp: 1654955540.1971748 iteration: 52490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09793 FastRCNN class loss: 0.06403 FastRCNN total loss: 0.16196 L1 loss: 0.0000e+00 L2 loss: 0.60701 Learning rate: 0.002 Mask loss: 0.08524 RPN box loss: 0.00854 RPN score loss: 0.00194 RPN total loss: 0.01048 Total loss: 0.86469 timestamp: 1654955543.3846073 iteration: 52495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13104 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.19486 L1 loss: 0.0000e+00 L2 loss: 0.607 Learning rate: 0.002 Mask loss: 0.0812 RPN box loss: 0.01024 RPN score loss: 0.00248 RPN total loss: 0.01272 Total loss: 0.89578 timestamp: 1654955546.6075976 iteration: 52500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08225 FastRCNN class loss: 0.08594 FastRCNN total loss: 0.1682 L1 loss: 0.0000e+00 L2 loss: 0.60699 Learning rate: 0.002 Mask loss: 0.07719 RPN box loss: 0.01723 RPN score loss: 0.00467 RPN total loss: 0.0219 Total loss: 0.87427 timestamp: 1654955549.9012606 iteration: 52505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11513 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.17442 L1 loss: 0.0000e+00 L2 loss: 0.60698 Learning rate: 0.002 Mask loss: 0.13289 RPN box loss: 0.02803 RPN score loss: 0.00338 RPN total loss: 0.03141 Total loss: 0.9457 timestamp: 1654955553.1481588 iteration: 52510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07022 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.14219 L1 loss: 0.0000e+00 L2 loss: 0.60698 Learning rate: 0.002 Mask loss: 0.11392 RPN box loss: 0.01145 RPN score loss: 0.00228 RPN total loss: 0.01373 Total loss: 0.87681 timestamp: 1654955556.3104563 iteration: 52515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14228 FastRCNN class loss: 0.09769 FastRCNN total loss: 0.23997 L1 loss: 0.0000e+00 L2 loss: 0.60697 Learning rate: 0.002 Mask loss: 0.18601 RPN box loss: 0.03247 RPN score loss: 0.00897 RPN total loss: 0.04144 Total loss: 1.0744 timestamp: 1654955559.545128 iteration: 52520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08816 FastRCNN class loss: 0.06987 FastRCNN total loss: 0.15802 L1 loss: 0.0000e+00 L2 loss: 0.60696 Learning rate: 0.002 Mask loss: 0.15827 RPN box loss: 0.02567 RPN score loss: 0.0098 RPN total loss: 0.03548 Total loss: 0.95873 timestamp: 1654955562.8623333 iteration: 52525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06812 FastRCNN class loss: 0.05808 FastRCNN total loss: 0.1262 L1 loss: 0.0000e+00 L2 loss: 0.60695 Learning rate: 0.002 Mask loss: 0.15058 RPN box loss: 0.01937 RPN score loss: 0.00305 RPN total loss: 0.02242 Total loss: 0.90615 timestamp: 1654955566.1612964 iteration: 52530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11851 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.18461 L1 loss: 0.0000e+00 L2 loss: 0.60694 Learning rate: 0.002 Mask loss: 0.11228 RPN box loss: 0.00982 RPN score loss: 0.00319 RPN total loss: 0.01302 Total loss: 0.91686 timestamp: 1654955569.5432634 iteration: 52535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12873 FastRCNN class loss: 0.05778 FastRCNN total loss: 0.18651 L1 loss: 0.0000e+00 L2 loss: 0.60693 Learning rate: 0.002 Mask loss: 0.13262 RPN box loss: 0.00647 RPN score loss: 0.00671 RPN total loss: 0.01317 Total loss: 0.93924 timestamp: 1654955572.7778928 iteration: 52540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09264 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.17168 L1 loss: 0.0000e+00 L2 loss: 0.60692 Learning rate: 0.002 Mask loss: 0.17639 RPN box loss: 0.01361 RPN score loss: 0.00397 RPN total loss: 0.01758 Total loss: 0.97257 timestamp: 1654955576.083354 iteration: 52545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07901 FastRCNN class loss: 0.05317 FastRCNN total loss: 0.13218 L1 loss: 0.0000e+00 L2 loss: 0.60692 Learning rate: 0.002 Mask loss: 0.13609 RPN box loss: 0.04288 RPN score loss: 0.00699 RPN total loss: 0.04987 Total loss: 0.92505 timestamp: 1654955579.2365043 iteration: 52550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09562 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.14786 L1 loss: 0.0000e+00 L2 loss: 0.60691 Learning rate: 0.002 Mask loss: 0.13392 RPN box loss: 0.00972 RPN score loss: 0.00243 RPN total loss: 0.01215 Total loss: 0.90084 timestamp: 1654955582.4634612 iteration: 52555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13525 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.20346 L1 loss: 0.0000e+00 L2 loss: 0.6069 Learning rate: 0.002 Mask loss: 0.22877 RPN box loss: 0.02819 RPN score loss: 0.0104 RPN total loss: 0.0386 Total loss: 1.07773 timestamp: 1654955585.6540823 iteration: 52560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08434 FastRCNN class loss: 0.11587 FastRCNN total loss: 0.20021 L1 loss: 0.0000e+00 L2 loss: 0.60689 Learning rate: 0.002 Mask loss: 0.13938 RPN box loss: 0.02209 RPN score loss: 0.00311 RPN total loss: 0.0252 Total loss: 0.97169 timestamp: 1654955588.9410791 iteration: 52565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.135 FastRCNN class loss: 0.1075 FastRCNN total loss: 0.2425 L1 loss: 0.0000e+00 L2 loss: 0.60688 Learning rate: 0.002 Mask loss: 0.14764 RPN box loss: 0.01774 RPN score loss: 0.00639 RPN total loss: 0.02413 Total loss: 1.02115 timestamp: 1654955592.1760821 iteration: 52570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09472 FastRCNN class loss: 0.0447 FastRCNN total loss: 0.13942 L1 loss: 0.0000e+00 L2 loss: 0.60687 Learning rate: 0.002 Mask loss: 0.0898 RPN box loss: 0.00724 RPN score loss: 0.00225 RPN total loss: 0.00949 Total loss: 0.84558 timestamp: 1654955595.496263 iteration: 52575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07495 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.13306 L1 loss: 0.0000e+00 L2 loss: 0.60686 Learning rate: 0.002 Mask loss: 0.11209 RPN box loss: 0.00714 RPN score loss: 0.0064 RPN total loss: 0.01355 Total loss: 0.86555 timestamp: 1654955599.16907 iteration: 52580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10994 FastRCNN class loss: 0.11092 FastRCNN total loss: 0.22086 L1 loss: 0.0000e+00 L2 loss: 0.60685 Learning rate: 0.002 Mask loss: 0.18058 RPN box loss: 0.03339 RPN score loss: 0.01301 RPN total loss: 0.0464 Total loss: 1.0547 timestamp: 1654955602.2892628 iteration: 52585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12204 FastRCNN class loss: 0.04652 FastRCNN total loss: 0.16855 L1 loss: 0.0000e+00 L2 loss: 0.60684 Learning rate: 0.002 Mask loss: 0.18045 RPN box loss: 0.01702 RPN score loss: 0.00199 RPN total loss: 0.01901 Total loss: 0.97485 timestamp: 1654955605.6775506 iteration: 52590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.16179 L1 loss: 0.0000e+00 L2 loss: 0.60683 Learning rate: 0.002 Mask loss: 0.0905 RPN box loss: 0.0108 RPN score loss: 0.00241 RPN total loss: 0.01321 Total loss: 0.87233 timestamp: 1654955608.8988166 iteration: 52595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16634 FastRCNN class loss: 0.12859 FastRCNN total loss: 0.29493 L1 loss: 0.0000e+00 L2 loss: 0.60682 Learning rate: 0.002 Mask loss: 0.14627 RPN box loss: 0.01414 RPN score loss: 0.00802 RPN total loss: 0.02216 Total loss: 1.07018 timestamp: 1654955612.2472272 iteration: 52600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1064 FastRCNN class loss: 0.0641 FastRCNN total loss: 0.1705 L1 loss: 0.0000e+00 L2 loss: 0.60681 Learning rate: 0.002 Mask loss: 0.19133 RPN box loss: 0.01377 RPN score loss: 0.00152 RPN total loss: 0.01529 Total loss: 0.98394 timestamp: 1654955615.4490423 iteration: 52605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11795 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.18434 L1 loss: 0.0000e+00 L2 loss: 0.60681 Learning rate: 0.002 Mask loss: 0.15534 RPN box loss: 0.00562 RPN score loss: 0.00135 RPN total loss: 0.00698 Total loss: 0.95347 timestamp: 1654955618.6712537 iteration: 52610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08733 FastRCNN class loss: 0.07673 FastRCNN total loss: 0.16406 L1 loss: 0.0000e+00 L2 loss: 0.6068 Learning rate: 0.002 Mask loss: 0.08476 RPN box loss: 0.00495 RPN score loss: 0.00197 RPN total loss: 0.00692 Total loss: 0.86255 timestamp: 1654955621.9642994 iteration: 52615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.13702 L1 loss: 0.0000e+00 L2 loss: 0.60679 Learning rate: 0.002 Mask loss: 0.1625 RPN box loss: 0.00574 RPN score loss: 0.01216 RPN total loss: 0.0179 Total loss: 0.92421 timestamp: 1654955625.2503963 iteration: 52620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10293 FastRCNN class loss: 0.05947 FastRCNN total loss: 0.16239 L1 loss: 0.0000e+00 L2 loss: 0.60678 Learning rate: 0.002 Mask loss: 0.192 RPN box loss: 0.01081 RPN score loss: 0.00543 RPN total loss: 0.01625 Total loss: 0.97742 timestamp: 1654955628.4950612 iteration: 52625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11073 FastRCNN class loss: 0.05803 FastRCNN total loss: 0.16876 L1 loss: 0.0000e+00 L2 loss: 0.60677 Learning rate: 0.002 Mask loss: 0.13669 RPN box loss: 0.01298 RPN score loss: 0.00242 RPN total loss: 0.0154 Total loss: 0.92762 timestamp: 1654955631.5866163 iteration: 52630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05533 FastRCNN class loss: 0.08373 FastRCNN total loss: 0.13906 L1 loss: 0.0000e+00 L2 loss: 0.60676 Learning rate: 0.002 Mask loss: 0.10772 RPN box loss: 0.01976 RPN score loss: 0.0033 RPN total loss: 0.02305 Total loss: 0.87659 timestamp: 1654955634.859529 iteration: 52635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06815 FastRCNN class loss: 0.05628 FastRCNN total loss: 0.12443 L1 loss: 0.0000e+00 L2 loss: 0.60675 Learning rate: 0.002 Mask loss: 0.08383 RPN box loss: 0.00893 RPN score loss: 0.00416 RPN total loss: 0.01308 Total loss: 0.82809 timestamp: 1654955638.091163 iteration: 52640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.16231 L1 loss: 0.0000e+00 L2 loss: 0.60674 Learning rate: 0.002 Mask loss: 0.12678 RPN box loss: 0.02964 RPN score loss: 0.00611 RPN total loss: 0.03575 Total loss: 0.93158 timestamp: 1654955641.3571892 iteration: 52645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07547 FastRCNN class loss: 0.04046 FastRCNN total loss: 0.11592 L1 loss: 0.0000e+00 L2 loss: 0.60674 Learning rate: 0.002 Mask loss: 0.08854 RPN box loss: 0.00336 RPN score loss: 0.00942 RPN total loss: 0.01278 Total loss: 0.82398 timestamp: 1654955644.5247838 iteration: 52650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10677 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.16671 L1 loss: 0.0000e+00 L2 loss: 0.60673 Learning rate: 0.002 Mask loss: 0.09193 RPN box loss: 0.00826 RPN score loss: 0.00998 RPN total loss: 0.01824 Total loss: 0.88362 timestamp: 1654955647.8466089 iteration: 52655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06261 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.12411 L1 loss: 0.0000e+00 L2 loss: 0.60672 Learning rate: 0.002 Mask loss: 0.13716 RPN box loss: 0.00763 RPN score loss: 0.00301 RPN total loss: 0.01063 Total loss: 0.87863 timestamp: 1654955651.0188987 iteration: 52660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12093 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.18487 L1 loss: 0.0000e+00 L2 loss: 0.60672 Learning rate: 0.002 Mask loss: 0.13906 RPN box loss: 0.01324 RPN score loss: 0.00409 RPN total loss: 0.01733 Total loss: 0.94798 timestamp: 1654955654.2720716 iteration: 52665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13004 FastRCNN class loss: 0.08793 FastRCNN total loss: 0.21797 L1 loss: 0.0000e+00 L2 loss: 0.60671 Learning rate: 0.002 Mask loss: 0.134 RPN box loss: 0.02235 RPN score loss: 0.01048 RPN total loss: 0.03282 Total loss: 0.9915 timestamp: 1654955657.5381098 iteration: 52670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10431 FastRCNN class loss: 0.05347 FastRCNN total loss: 0.15778 L1 loss: 0.0000e+00 L2 loss: 0.6067 Learning rate: 0.002 Mask loss: 0.14752 RPN box loss: 0.01601 RPN score loss: 0.01264 RPN total loss: 0.02865 Total loss: 0.94065 timestamp: 1654955660.8396547 iteration: 52675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1094 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.17319 L1 loss: 0.0000e+00 L2 loss: 0.60669 Learning rate: 0.002 Mask loss: 0.13369 RPN box loss: 0.00662 RPN score loss: 0.00251 RPN total loss: 0.00913 Total loss: 0.9227 timestamp: 1654955664.046052 iteration: 52680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11732 FastRCNN class loss: 0.06236 FastRCNN total loss: 0.17968 L1 loss: 0.0000e+00 L2 loss: 0.60668 Learning rate: 0.002 Mask loss: 0.14476 RPN box loss: 0.00942 RPN score loss: 0.00735 RPN total loss: 0.01677 Total loss: 0.94789 timestamp: 1654955667.2793581 iteration: 52685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05407 FastRCNN class loss: 0.07477 FastRCNN total loss: 0.12884 L1 loss: 0.0000e+00 L2 loss: 0.60667 Learning rate: 0.002 Mask loss: 0.13514 RPN box loss: 0.02569 RPN score loss: 0.00591 RPN total loss: 0.0316 Total loss: 0.90224 timestamp: 1654955670.611787 iteration: 52690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.11701 FastRCNN total loss: 0.19793 L1 loss: 0.0000e+00 L2 loss: 0.60666 Learning rate: 0.002 Mask loss: 0.12692 RPN box loss: 0.02181 RPN score loss: 0.0111 RPN total loss: 0.03291 Total loss: 0.96441 timestamp: 1654955673.7716465 iteration: 52695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03859 FastRCNN class loss: 0.0424 FastRCNN total loss: 0.08099 L1 loss: 0.0000e+00 L2 loss: 0.60665 Learning rate: 0.002 Mask loss: 0.16726 RPN box loss: 0.01167 RPN score loss: 0.00384 RPN total loss: 0.01551 Total loss: 0.87042 timestamp: 1654955677.0252404 iteration: 52700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07382 FastRCNN class loss: 0.04877 FastRCNN total loss: 0.12259 L1 loss: 0.0000e+00 L2 loss: 0.60664 Learning rate: 0.002 Mask loss: 0.13586 RPN box loss: 0.01388 RPN score loss: 0.00537 RPN total loss: 0.01926 Total loss: 0.88435 timestamp: 1654955680.2390683 iteration: 52705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09229 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.17601 L1 loss: 0.0000e+00 L2 loss: 0.60663 Learning rate: 0.002 Mask loss: 0.12518 RPN box loss: 0.01632 RPN score loss: 0.00553 RPN total loss: 0.02185 Total loss: 0.92968 timestamp: 1654955683.601563 iteration: 52710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05354 FastRCNN class loss: 0.04747 FastRCNN total loss: 0.10101 L1 loss: 0.0000e+00 L2 loss: 0.60663 Learning rate: 0.002 Mask loss: 0.11816 RPN box loss: 0.01533 RPN score loss: 0.00291 RPN total loss: 0.01824 Total loss: 0.84404 timestamp: 1654955686.8434875 iteration: 52715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15145 FastRCNN class loss: 0.0824 FastRCNN total loss: 0.23386 L1 loss: 0.0000e+00 L2 loss: 0.60662 Learning rate: 0.002 Mask loss: 0.10591 RPN box loss: 0.01135 RPN score loss: 0.00448 RPN total loss: 0.01583 Total loss: 0.96222 timestamp: 1654955690.248376 iteration: 52720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07493 FastRCNN class loss: 0.08491 FastRCNN total loss: 0.15984 L1 loss: 0.0000e+00 L2 loss: 0.60661 Learning rate: 0.002 Mask loss: 0.13238 RPN box loss: 0.02027 RPN score loss: 0.00936 RPN total loss: 0.02964 Total loss: 0.92847 timestamp: 1654955693.4350808 iteration: 52725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07034 FastRCNN class loss: 0.0788 FastRCNN total loss: 0.14914 L1 loss: 0.0000e+00 L2 loss: 0.6066 Learning rate: 0.002 Mask loss: 0.14532 RPN box loss: 0.0122 RPN score loss: 0.0115 RPN total loss: 0.0237 Total loss: 0.92476 timestamp: 1654955696.7101538 iteration: 52730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11554 FastRCNN class loss: 0.05817 FastRCNN total loss: 0.17371 L1 loss: 0.0000e+00 L2 loss: 0.60659 Learning rate: 0.002 Mask loss: 0.09646 RPN box loss: 0.0154 RPN score loss: 0.00664 RPN total loss: 0.02204 Total loss: 0.89881 timestamp: 1654955699.9003065 iteration: 52735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0673 FastRCNN class loss: 0.05634 FastRCNN total loss: 0.12365 L1 loss: 0.0000e+00 L2 loss: 0.60658 Learning rate: 0.002 Mask loss: 0.11969 RPN box loss: 0.01055 RPN score loss: 0.00135 RPN total loss: 0.01191 Total loss: 0.86182 timestamp: 1654955703.3025432 iteration: 52740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14302 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.2095 L1 loss: 0.0000e+00 L2 loss: 0.60657 Learning rate: 0.002 Mask loss: 0.14288 RPN box loss: 0.02799 RPN score loss: 0.00215 RPN total loss: 0.03013 Total loss: 0.98909 timestamp: 1654955706.5605896 iteration: 52745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09788 FastRCNN class loss: 0.0707 FastRCNN total loss: 0.16858 L1 loss: 0.0000e+00 L2 loss: 0.60656 Learning rate: 0.002 Mask loss: 0.14147 RPN box loss: 0.07748 RPN score loss: 0.00565 RPN total loss: 0.08313 Total loss: 0.99975 timestamp: 1654955709.7307203 iteration: 52750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.104 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.16161 L1 loss: 0.0000e+00 L2 loss: 0.60656 Learning rate: 0.002 Mask loss: 0.11253 RPN box loss: 0.02129 RPN score loss: 0.00166 RPN total loss: 0.02295 Total loss: 0.90365 timestamp: 1654955712.9597828 iteration: 52755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12179 FastRCNN class loss: 0.07177 FastRCNN total loss: 0.19356 L1 loss: 0.0000e+00 L2 loss: 0.60655 Learning rate: 0.002 Mask loss: 0.17802 RPN box loss: 0.0199 RPN score loss: 0.01653 RPN total loss: 0.03643 Total loss: 1.01456 timestamp: 1654955716.199678 iteration: 52760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11237 FastRCNN class loss: 0.09981 FastRCNN total loss: 0.21218 L1 loss: 0.0000e+00 L2 loss: 0.60654 Learning rate: 0.002 Mask loss: 0.15667 RPN box loss: 0.0125 RPN score loss: 0.0095 RPN total loss: 0.022 Total loss: 0.99739 timestamp: 1654955719.451948 iteration: 52765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14533 FastRCNN class loss: 0.08932 FastRCNN total loss: 0.23465 L1 loss: 0.0000e+00 L2 loss: 0.60653 Learning rate: 0.002 Mask loss: 0.13292 RPN box loss: 0.01323 RPN score loss: 0.00322 RPN total loss: 0.01645 Total loss: 0.99055 timestamp: 1654955722.6381102 iteration: 52770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0447 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.10654 L1 loss: 0.0000e+00 L2 loss: 0.60652 Learning rate: 0.002 Mask loss: 0.1101 RPN box loss: 0.02061 RPN score loss: 0.00215 RPN total loss: 0.02276 Total loss: 0.84592 timestamp: 1654955725.9906301 iteration: 52775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08509 FastRCNN class loss: 0.09578 FastRCNN total loss: 0.18087 L1 loss: 0.0000e+00 L2 loss: 0.60651 Learning rate: 0.002 Mask loss: 0.14943 RPN box loss: 0.01149 RPN score loss: 0.00539 RPN total loss: 0.01688 Total loss: 0.95369 timestamp: 1654955729.2521777 iteration: 52780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08408 FastRCNN class loss: 0.04455 FastRCNN total loss: 0.12863 L1 loss: 0.0000e+00 L2 loss: 0.6065 Learning rate: 0.002 Mask loss: 0.09651 RPN box loss: 0.01189 RPN score loss: 0.00021 RPN total loss: 0.0121 Total loss: 0.84375 timestamp: 1654955732.5255458 iteration: 52785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0704 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.13457 L1 loss: 0.0000e+00 L2 loss: 0.60649 Learning rate: 0.002 Mask loss: 0.11305 RPN box loss: 0.02211 RPN score loss: 0.00203 RPN total loss: 0.02414 Total loss: 0.87826 timestamp: 1654955735.87451 iteration: 52790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04351 FastRCNN class loss: 0.04027 FastRCNN total loss: 0.08378 L1 loss: 0.0000e+00 L2 loss: 0.60649 Learning rate: 0.002 Mask loss: 0.11873 RPN box loss: 0.01611 RPN score loss: 0.00314 RPN total loss: 0.01926 Total loss: 0.82825 timestamp: 1654955739.1488512 iteration: 52795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09104 FastRCNN class loss: 0.04176 FastRCNN total loss: 0.1328 L1 loss: 0.0000e+00 L2 loss: 0.60648 Learning rate: 0.002 Mask loss: 0.11209 RPN box loss: 0.00665 RPN score loss: 0.00164 RPN total loss: 0.00829 Total loss: 0.85966 timestamp: 1654955742.444699 iteration: 52800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08647 FastRCNN class loss: 0.09007 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 0.60647 Learning rate: 0.002 Mask loss: 0.16209 RPN box loss: 0.02075 RPN score loss: 0.00379 RPN total loss: 0.02454 Total loss: 0.96965 timestamp: 1654955745.6906457 iteration: 52805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07342 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.13488 L1 loss: 0.0000e+00 L2 loss: 0.60646 Learning rate: 0.002 Mask loss: 0.09306 RPN box loss: 0.00548 RPN score loss: 0.00268 RPN total loss: 0.00816 Total loss: 0.84256 timestamp: 1654955749.0884998 iteration: 52810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.17675 L1 loss: 0.0000e+00 L2 loss: 0.60645 Learning rate: 0.002 Mask loss: 0.14192 RPN box loss: 0.02099 RPN score loss: 0.00671 RPN total loss: 0.0277 Total loss: 0.95282 timestamp: 1654955752.2621815 iteration: 52815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08314 FastRCNN class loss: 0.05446 FastRCNN total loss: 0.1376 L1 loss: 0.0000e+00 L2 loss: 0.60644 Learning rate: 0.002 Mask loss: 0.12052 RPN box loss: 0.01257 RPN score loss: 0.00228 RPN total loss: 0.01486 Total loss: 0.87942 timestamp: 1654955755.5561624 iteration: 52820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15702 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.23928 L1 loss: 0.0000e+00 L2 loss: 0.60644 Learning rate: 0.002 Mask loss: 0.09847 RPN box loss: 0.00922 RPN score loss: 0.00338 RPN total loss: 0.01259 Total loss: 0.95679 timestamp: 1654955758.7803676 iteration: 52825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.06619 FastRCNN total loss: 0.16016 L1 loss: 0.0000e+00 L2 loss: 0.60643 Learning rate: 0.002 Mask loss: 0.1508 RPN box loss: 0.01654 RPN score loss: 0.0055 RPN total loss: 0.02204 Total loss: 0.93943 timestamp: 1654955762.093758 iteration: 52830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06605 FastRCNN class loss: 0.0634 FastRCNN total loss: 0.12945 L1 loss: 0.0000e+00 L2 loss: 0.60642 Learning rate: 0.002 Mask loss: 0.17894 RPN box loss: 0.02209 RPN score loss: 0.00163 RPN total loss: 0.02372 Total loss: 0.93854 timestamp: 1654955765.2196486 iteration: 52835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1218 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.19378 L1 loss: 0.0000e+00 L2 loss: 0.60641 Learning rate: 0.002 Mask loss: 0.08955 RPN box loss: 0.0063 RPN score loss: 0.00289 RPN total loss: 0.00919 Total loss: 0.89893 timestamp: 1654955768.4597342 iteration: 52840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15489 FastRCNN class loss: 0.11238 FastRCNN total loss: 0.26727 L1 loss: 0.0000e+00 L2 loss: 0.6064 Learning rate: 0.002 Mask loss: 0.17091 RPN box loss: 0.02219 RPN score loss: 0.00798 RPN total loss: 0.03017 Total loss: 1.07475 timestamp: 1654955771.7136106 iteration: 52845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06137 FastRCNN class loss: 0.05597 FastRCNN total loss: 0.11734 L1 loss: 0.0000e+00 L2 loss: 0.60639 Learning rate: 0.002 Mask loss: 0.10337 RPN box loss: 0.01699 RPN score loss: 0.00581 RPN total loss: 0.0228 Total loss: 0.84991 timestamp: 1654955774.888852 iteration: 52850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1212 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.19438 L1 loss: 0.0000e+00 L2 loss: 0.60638 Learning rate: 0.002 Mask loss: 0.12923 RPN box loss: 0.01456 RPN score loss: 0.00378 RPN total loss: 0.01834 Total loss: 0.94833 timestamp: 1654955778.1934557 iteration: 52855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07628 FastRCNN class loss: 0.09315 FastRCNN total loss: 0.16942 L1 loss: 0.0000e+00 L2 loss: 0.60637 Learning rate: 0.002 Mask loss: 0.15031 RPN box loss: 0.00993 RPN score loss: 0.00561 RPN total loss: 0.01555 Total loss: 0.94166 timestamp: 1654955781.4053092 iteration: 52860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.092 FastRCNN class loss: 0.06206 FastRCNN total loss: 0.15406 L1 loss: 0.0000e+00 L2 loss: 0.60636 Learning rate: 0.002 Mask loss: 0.08448 RPN box loss: 0.01781 RPN score loss: 0.0033 RPN total loss: 0.02111 Total loss: 0.86601 timestamp: 1654955784.6764498 iteration: 52865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07773 FastRCNN class loss: 0.058 FastRCNN total loss: 0.13573 L1 loss: 0.0000e+00 L2 loss: 0.60635 Learning rate: 0.002 Mask loss: 0.10133 RPN box loss: 0.0047 RPN score loss: 0.00088 RPN total loss: 0.00558 Total loss: 0.84899 timestamp: 1654955787.9227371 iteration: 52870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07379 FastRCNN class loss: 0.04437 FastRCNN total loss: 0.11816 L1 loss: 0.0000e+00 L2 loss: 0.60635 Learning rate: 0.002 Mask loss: 0.1514 RPN box loss: 0.01425 RPN score loss: 0.00875 RPN total loss: 0.023 Total loss: 0.89891 timestamp: 1654955791.1825864 iteration: 52875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08535 FastRCNN class loss: 0.07472 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.60634 Learning rate: 0.002 Mask loss: 0.10678 RPN box loss: 0.02045 RPN score loss: 0.00237 RPN total loss: 0.02282 Total loss: 0.89601 timestamp: 1654955794.3634489 iteration: 52880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08438 FastRCNN class loss: 0.04196 FastRCNN total loss: 0.12634 L1 loss: 0.0000e+00 L2 loss: 0.60633 Learning rate: 0.002 Mask loss: 0.09838 RPN box loss: 0.00466 RPN score loss: 0.00373 RPN total loss: 0.00839 Total loss: 0.83943 timestamp: 1654955797.5759227 iteration: 52885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0992 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.14964 L1 loss: 0.0000e+00 L2 loss: 0.60632 Learning rate: 0.002 Mask loss: 0.1603 RPN box loss: 0.01602 RPN score loss: 0.0034 RPN total loss: 0.01942 Total loss: 0.93568 timestamp: 1654955800.7668982 iteration: 52890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13652 FastRCNN class loss: 0.07278 FastRCNN total loss: 0.2093 L1 loss: 0.0000e+00 L2 loss: 0.60632 Learning rate: 0.002 Mask loss: 0.14851 RPN box loss: 0.01769 RPN score loss: 0.00193 RPN total loss: 0.01962 Total loss: 0.98375 timestamp: 1654955804.1035626 iteration: 52895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09408 FastRCNN class loss: 0.07264 FastRCNN total loss: 0.16672 L1 loss: 0.0000e+00 L2 loss: 0.60631 Learning rate: 0.002 Mask loss: 0.11435 RPN box loss: 0.0652 RPN score loss: 0.00765 RPN total loss: 0.07284 Total loss: 0.96022 timestamp: 1654955807.45856 iteration: 52900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0979 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.16578 L1 loss: 0.0000e+00 L2 loss: 0.6063 Learning rate: 0.002 Mask loss: 0.16325 RPN box loss: 0.02797 RPN score loss: 0.00886 RPN total loss: 0.03683 Total loss: 0.97216 timestamp: 1654955810.5845559 iteration: 52905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12058 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.19173 L1 loss: 0.0000e+00 L2 loss: 0.60629 Learning rate: 0.002 Mask loss: 0.13908 RPN box loss: 0.08886 RPN score loss: 0.00495 RPN total loss: 0.09381 Total loss: 1.03091 timestamp: 1654955814.0272424 iteration: 52910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11953 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.20893 L1 loss: 0.0000e+00 L2 loss: 0.60628 Learning rate: 0.002 Mask loss: 0.16134 RPN box loss: 0.01925 RPN score loss: 0.00846 RPN total loss: 0.0277 Total loss: 1.00425 timestamp: 1654955817.1820939 iteration: 52915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05734 FastRCNN class loss: 0.0268 FastRCNN total loss: 0.08413 L1 loss: 0.0000e+00 L2 loss: 0.60627 Learning rate: 0.002 Mask loss: 0.09181 RPN box loss: 0.00823 RPN score loss: 0.00313 RPN total loss: 0.01136 Total loss: 0.79358 timestamp: 1654955820.462947 iteration: 52920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15326 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.22997 L1 loss: 0.0000e+00 L2 loss: 0.60626 Learning rate: 0.002 Mask loss: 0.17819 RPN box loss: 0.02494 RPN score loss: 0.00748 RPN total loss: 0.03242 Total loss: 1.04684 timestamp: 1654955823.6574328 iteration: 52925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18502 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.26822 L1 loss: 0.0000e+00 L2 loss: 0.60625 Learning rate: 0.002 Mask loss: 0.19392 RPN box loss: 0.03015 RPN score loss: 0.00267 RPN total loss: 0.03282 Total loss: 1.10121 timestamp: 1654955827.027437 iteration: 52930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07425 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.12335 L1 loss: 0.0000e+00 L2 loss: 0.60624 Learning rate: 0.002 Mask loss: 0.14701 RPN box loss: 0.03654 RPN score loss: 0.00483 RPN total loss: 0.04137 Total loss: 0.91798 timestamp: 1654955830.2421167 iteration: 52935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08303 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.15671 L1 loss: 0.0000e+00 L2 loss: 0.60624 Learning rate: 0.002 Mask loss: 0.13976 RPN box loss: 0.0111 RPN score loss: 0.00224 RPN total loss: 0.01334 Total loss: 0.91605 timestamp: 1654955833.4601512 iteration: 52940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06593 FastRCNN class loss: 0.03992 FastRCNN total loss: 0.10585 L1 loss: 0.0000e+00 L2 loss: 0.60623 Learning rate: 0.002 Mask loss: 0.29687 RPN box loss: 0.00583 RPN score loss: 0.0054 RPN total loss: 0.01123 Total loss: 1.02018 timestamp: 1654955836.6208704 iteration: 52945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09713 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.16669 L1 loss: 0.0000e+00 L2 loss: 0.60622 Learning rate: 0.002 Mask loss: 0.1426 RPN box loss: 0.015 RPN score loss: 0.0148 RPN total loss: 0.0298 Total loss: 0.94531 timestamp: 1654955839.9040315 iteration: 52950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07481 FastRCNN class loss: 0.05528 FastRCNN total loss: 0.13009 L1 loss: 0.0000e+00 L2 loss: 0.60621 Learning rate: 0.002 Mask loss: 0.09812 RPN box loss: 0.01468 RPN score loss: 0.00215 RPN total loss: 0.01683 Total loss: 0.85125 timestamp: 1654955843.1986988 iteration: 52955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08261 FastRCNN class loss: 0.06641 FastRCNN total loss: 0.14901 L1 loss: 0.0000e+00 L2 loss: 0.6062 Learning rate: 0.002 Mask loss: 0.11894 RPN box loss: 0.00813 RPN score loss: 0.00643 RPN total loss: 0.01456 Total loss: 0.88871 timestamp: 1654955846.3867838 iteration: 52960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0551 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.10708 L1 loss: 0.0000e+00 L2 loss: 0.60619 Learning rate: 0.002 Mask loss: 0.10101 RPN box loss: 0.00662 RPN score loss: 0.00201 RPN total loss: 0.00863 Total loss: 0.8229 timestamp: 1654955849.6415045 iteration: 52965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11325 FastRCNN class loss: 0.08444 FastRCNN total loss: 0.19768 L1 loss: 0.0000e+00 L2 loss: 0.60618 Learning rate: 0.002 Mask loss: 0.10059 RPN box loss: 0.02376 RPN score loss: 0.00356 RPN total loss: 0.02732 Total loss: 0.93177 timestamp: 1654955852.7967405 iteration: 52970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11737 FastRCNN class loss: 0.06367 FastRCNN total loss: 0.18104 L1 loss: 0.0000e+00 L2 loss: 0.60617 Learning rate: 0.002 Mask loss: 0.13291 RPN box loss: 0.01559 RPN score loss: 0.00456 RPN total loss: 0.02015 Total loss: 0.94027 timestamp: 1654955856.1213152 iteration: 52975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07715 FastRCNN class loss: 0.04599 FastRCNN total loss: 0.12315 L1 loss: 0.0000e+00 L2 loss: 0.60616 Learning rate: 0.002 Mask loss: 0.11149 RPN box loss: 0.00733 RPN score loss: 0.0012 RPN total loss: 0.00853 Total loss: 0.84933 timestamp: 1654955859.346595 iteration: 52980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1329 FastRCNN class loss: 0.06633 FastRCNN total loss: 0.19922 L1 loss: 0.0000e+00 L2 loss: 0.60616 Learning rate: 0.002 Mask loss: 0.12204 RPN box loss: 0.00626 RPN score loss: 0.00451 RPN total loss: 0.01077 Total loss: 0.93819 timestamp: 1654955862.6178586 iteration: 52985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0691 FastRCNN class loss: 0.06653 FastRCNN total loss: 0.13562 L1 loss: 0.0000e+00 L2 loss: 0.60615 Learning rate: 0.002 Mask loss: 0.16235 RPN box loss: 0.00981 RPN score loss: 0.00806 RPN total loss: 0.01786 Total loss: 0.92198 timestamp: 1654955865.756621 iteration: 52990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09126 FastRCNN class loss: 0.05011 FastRCNN total loss: 0.14137 L1 loss: 0.0000e+00 L2 loss: 0.60614 Learning rate: 0.002 Mask loss: 0.13542 RPN box loss: 0.01106 RPN score loss: 0.00148 RPN total loss: 0.01254 Total loss: 0.89548 timestamp: 1654955869.1227353 iteration: 52995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06795 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.12692 L1 loss: 0.0000e+00 L2 loss: 0.60613 Learning rate: 0.002 Mask loss: 0.11651 RPN box loss: 0.0623 RPN score loss: 0.00431 RPN total loss: 0.06661 Total loss: 0.91618 timestamp: 1654955872.247478 iteration: 53000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10432 FastRCNN class loss: 0.08797 FastRCNN total loss: 0.19229 L1 loss: 0.0000e+00 L2 loss: 0.60612 Learning rate: 0.002 Mask loss: 0.14282 RPN box loss: 0.01473 RPN score loss: 0.00579 RPN total loss: 0.02052 Total loss: 0.96176 timestamp: 1654955875.5652971 iteration: 53005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05625 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.11265 L1 loss: 0.0000e+00 L2 loss: 0.60612 Learning rate: 0.002 Mask loss: 0.1567 RPN box loss: 0.00957 RPN score loss: 0.00456 RPN total loss: 0.01413 Total loss: 0.8896 timestamp: 1654955878.8933082 iteration: 53010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10445 FastRCNN class loss: 0.12259 FastRCNN total loss: 0.22705 L1 loss: 0.0000e+00 L2 loss: 0.60611 Learning rate: 0.002 Mask loss: 0.24885 RPN box loss: 0.02868 RPN score loss: 0.00805 RPN total loss: 0.03673 Total loss: 1.11874 timestamp: 1654955882.073302 iteration: 53015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08998 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.17225 L1 loss: 0.0000e+00 L2 loss: 0.6061 Learning rate: 0.002 Mask loss: 0.11194 RPN box loss: 0.01146 RPN score loss: 0.00657 RPN total loss: 0.01804 Total loss: 0.90833 timestamp: 1654955885.442564 iteration: 53020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06096 FastRCNN class loss: 0.04867 FastRCNN total loss: 0.10963 L1 loss: 0.0000e+00 L2 loss: 0.60609 Learning rate: 0.002 Mask loss: 0.10255 RPN box loss: 0.00473 RPN score loss: 0.0016 RPN total loss: 0.00633 Total loss: 0.82461 timestamp: 1654955888.671259 iteration: 53025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12296 FastRCNN class loss: 0.07927 FastRCNN total loss: 0.20223 L1 loss: 0.0000e+00 L2 loss: 0.60609 Learning rate: 0.002 Mask loss: 0.13618 RPN box loss: 0.018 RPN score loss: 0.00134 RPN total loss: 0.01934 Total loss: 0.96383 timestamp: 1654955891.9370458 iteration: 53030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07266 FastRCNN class loss: 0.05574 FastRCNN total loss: 0.1284 L1 loss: 0.0000e+00 L2 loss: 0.60608 Learning rate: 0.002 Mask loss: 0.13936 RPN box loss: 0.01639 RPN score loss: 0.01113 RPN total loss: 0.02752 Total loss: 0.90136 timestamp: 1654955895.1326814 iteration: 53035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08047 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.13476 L1 loss: 0.0000e+00 L2 loss: 0.60607 Learning rate: 0.002 Mask loss: 0.11256 RPN box loss: 0.00792 RPN score loss: 0.00221 RPN total loss: 0.01014 Total loss: 0.86352 timestamp: 1654955898.3778949 iteration: 53040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15909 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.21529 L1 loss: 0.0000e+00 L2 loss: 0.60606 Learning rate: 0.002 Mask loss: 0.11816 RPN box loss: 0.01746 RPN score loss: 0.00492 RPN total loss: 0.02238 Total loss: 0.9619 timestamp: 1654955901.6053126 iteration: 53045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14383 FastRCNN class loss: 0.06862 FastRCNN total loss: 0.21245 L1 loss: 0.0000e+00 L2 loss: 0.60605 Learning rate: 0.002 Mask loss: 0.12572 RPN box loss: 0.0083 RPN score loss: 0.00497 RPN total loss: 0.01327 Total loss: 0.95749 timestamp: 1654955904.9325538 iteration: 53050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09613 FastRCNN class loss: 0.07279 FastRCNN total loss: 0.16892 L1 loss: 0.0000e+00 L2 loss: 0.60605 Learning rate: 0.002 Mask loss: 0.15382 RPN box loss: 0.01389 RPN score loss: 0.00794 RPN total loss: 0.02183 Total loss: 0.95061 timestamp: 1654955908.1493752 iteration: 53055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09732 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.15742 L1 loss: 0.0000e+00 L2 loss: 0.60604 Learning rate: 0.002 Mask loss: 0.11536 RPN box loss: 0.01078 RPN score loss: 0.01232 RPN total loss: 0.0231 Total loss: 0.90191 timestamp: 1654955911.4467287 iteration: 53060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16478 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.2334 L1 loss: 0.0000e+00 L2 loss: 0.60603 Learning rate: 0.002 Mask loss: 0.12458 RPN box loss: 0.01059 RPN score loss: 0.00604 RPN total loss: 0.01664 Total loss: 0.98064 timestamp: 1654955914.7497017 iteration: 53065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07842 FastRCNN class loss: 0.05414 FastRCNN total loss: 0.13255 L1 loss: 0.0000e+00 L2 loss: 0.60602 Learning rate: 0.002 Mask loss: 0.11179 RPN box loss: 0.00513 RPN score loss: 0.00154 RPN total loss: 0.00667 Total loss: 0.85703 timestamp: 1654955917.968904 iteration: 53070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11395 FastRCNN class loss: 0.09292 FastRCNN total loss: 0.20687 L1 loss: 0.0000e+00 L2 loss: 0.60601 Learning rate: 0.002 Mask loss: 0.13539 RPN box loss: 0.01426 RPN score loss: 0.00529 RPN total loss: 0.01955 Total loss: 0.96782 timestamp: 1654955921.2348204 iteration: 53075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10847 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.18688 L1 loss: 0.0000e+00 L2 loss: 0.606 Learning rate: 0.002 Mask loss: 0.11649 RPN box loss: 0.01812 RPN score loss: 0.00453 RPN total loss: 0.02265 Total loss: 0.93201 timestamp: 1654955924.4615834 iteration: 53080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11362 FastRCNN class loss: 0.04163 FastRCNN total loss: 0.15525 L1 loss: 0.0000e+00 L2 loss: 0.60599 Learning rate: 0.002 Mask loss: 0.13926 RPN box loss: 0.01615 RPN score loss: 0.00445 RPN total loss: 0.0206 Total loss: 0.92111 timestamp: 1654955927.7799883 iteration: 53085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08982 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.15633 L1 loss: 0.0000e+00 L2 loss: 0.60598 Learning rate: 0.002 Mask loss: 0.12245 RPN box loss: 0.02681 RPN score loss: 0.00494 RPN total loss: 0.03175 Total loss: 0.91651 timestamp: 1654955930.9553938 iteration: 53090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05929 FastRCNN class loss: 0.03935 FastRCNN total loss: 0.09864 L1 loss: 0.0000e+00 L2 loss: 0.60597 Learning rate: 0.002 Mask loss: 0.12171 RPN box loss: 0.0151 RPN score loss: 0.00184 RPN total loss: 0.01694 Total loss: 0.84327 timestamp: 1654955934.2212775 iteration: 53095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10021 FastRCNN class loss: 0.0883 FastRCNN total loss: 0.18851 L1 loss: 0.0000e+00 L2 loss: 0.60596 Learning rate: 0.002 Mask loss: 0.20649 RPN box loss: 0.00803 RPN score loss: 0.00169 RPN total loss: 0.00972 Total loss: 1.01068 timestamp: 1654955937.4806464 iteration: 53100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06356 FastRCNN class loss: 0.08407 FastRCNN total loss: 0.14763 L1 loss: 0.0000e+00 L2 loss: 0.60596 Learning rate: 0.002 Mask loss: 0.17002 RPN box loss: 0.00669 RPN score loss: 0.01408 RPN total loss: 0.02077 Total loss: 0.94437 timestamp: 1654955940.7449033 iteration: 53105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12996 FastRCNN class loss: 0.10985 FastRCNN total loss: 0.23981 L1 loss: 0.0000e+00 L2 loss: 0.60595 Learning rate: 0.002 Mask loss: 0.16881 RPN box loss: 0.03127 RPN score loss: 0.0044 RPN total loss: 0.03567 Total loss: 1.05024 timestamp: 1654955943.9527128 iteration: 53110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15177 FastRCNN class loss: 0.08772 FastRCNN total loss: 0.23949 L1 loss: 0.0000e+00 L2 loss: 0.60593 Learning rate: 0.002 Mask loss: 0.13092 RPN box loss: 0.02462 RPN score loss: 0.00296 RPN total loss: 0.02758 Total loss: 1.00392 timestamp: 1654955947.185037 iteration: 53115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12609 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.19049 L1 loss: 0.0000e+00 L2 loss: 0.60592 Learning rate: 0.002 Mask loss: 0.12012 RPN box loss: 0.02957 RPN score loss: 0.00949 RPN total loss: 0.03906 Total loss: 0.95559 timestamp: 1654955950.4370627 iteration: 53120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.16716 L1 loss: 0.0000e+00 L2 loss: 0.60591 Learning rate: 0.002 Mask loss: 0.11395 RPN box loss: 0.01816 RPN score loss: 0.00848 RPN total loss: 0.02664 Total loss: 0.91367 timestamp: 1654955953.6321278 iteration: 53125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06239 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.12713 L1 loss: 0.0000e+00 L2 loss: 0.60591 Learning rate: 0.002 Mask loss: 0.0875 RPN box loss: 0.01199 RPN score loss: 0.00171 RPN total loss: 0.0137 Total loss: 0.83423 timestamp: 1654955956.8950415 iteration: 53130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03691 FastRCNN class loss: 0.03093 FastRCNN total loss: 0.06784 L1 loss: 0.0000e+00 L2 loss: 0.6059 Learning rate: 0.002 Mask loss: 0.07381 RPN box loss: 0.02688 RPN score loss: 0.00675 RPN total loss: 0.03363 Total loss: 0.78117 timestamp: 1654955960.1319394 iteration: 53135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10336 FastRCNN class loss: 0.05785 FastRCNN total loss: 0.16121 L1 loss: 0.0000e+00 L2 loss: 0.60589 Learning rate: 0.002 Mask loss: 0.12903 RPN box loss: 0.0112 RPN score loss: 0.00474 RPN total loss: 0.01594 Total loss: 0.91207 timestamp: 1654955963.4947543 iteration: 53140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08031 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.16024 L1 loss: 0.0000e+00 L2 loss: 0.60588 Learning rate: 0.002 Mask loss: 0.16466 RPN box loss: 0.028 RPN score loss: 0.01096 RPN total loss: 0.03896 Total loss: 0.96974 timestamp: 1654955966.6599936 iteration: 53145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10978 FastRCNN class loss: 0.0871 FastRCNN total loss: 0.19689 L1 loss: 0.0000e+00 L2 loss: 0.60587 Learning rate: 0.002 Mask loss: 0.14379 RPN box loss: 0.01692 RPN score loss: 0.0102 RPN total loss: 0.02712 Total loss: 0.97366 timestamp: 1654955969.8888435 iteration: 53150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10503 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.20687 L1 loss: 0.0000e+00 L2 loss: 0.60586 Learning rate: 0.002 Mask loss: 0.13322 RPN box loss: 0.03108 RPN score loss: 0.00699 RPN total loss: 0.03807 Total loss: 0.98402 timestamp: 1654955973.1081831 iteration: 53155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09897 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.16387 L1 loss: 0.0000e+00 L2 loss: 0.60585 Learning rate: 0.002 Mask loss: 0.12723 RPN box loss: 0.01414 RPN score loss: 0.00198 RPN total loss: 0.01612 Total loss: 0.91306 timestamp: 1654955976.3962076 iteration: 53160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07756 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.15809 L1 loss: 0.0000e+00 L2 loss: 0.60584 Learning rate: 0.002 Mask loss: 0.15177 RPN box loss: 0.02022 RPN score loss: 0.01398 RPN total loss: 0.03421 Total loss: 0.94991 timestamp: 1654955979.5698402 iteration: 53165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1049 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.17647 L1 loss: 0.0000e+00 L2 loss: 0.60583 Learning rate: 0.002 Mask loss: 0.14929 RPN box loss: 0.00813 RPN score loss: 0.00779 RPN total loss: 0.01592 Total loss: 0.94751 timestamp: 1654955982.950111 iteration: 53170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0902 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.1735 L1 loss: 0.0000e+00 L2 loss: 0.60582 Learning rate: 0.002 Mask loss: 0.13506 RPN box loss: 0.03102 RPN score loss: 0.00559 RPN total loss: 0.03661 Total loss: 0.95099 timestamp: 1654955986.1968546 iteration: 53175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06941 FastRCNN class loss: 0.07875 FastRCNN total loss: 0.14816 L1 loss: 0.0000e+00 L2 loss: 0.60582 Learning rate: 0.002 Mask loss: 0.1429 RPN box loss: 0.02403 RPN score loss: 0.00494 RPN total loss: 0.02897 Total loss: 0.92584 timestamp: 1654955989.3591132 iteration: 53180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09917 FastRCNN class loss: 0.09653 FastRCNN total loss: 0.19569 L1 loss: 0.0000e+00 L2 loss: 0.60581 Learning rate: 0.002 Mask loss: 0.19462 RPN box loss: 0.01706 RPN score loss: 0.00472 RPN total loss: 0.02178 Total loss: 1.0179 timestamp: 1654955992.6784987 iteration: 53185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11942 FastRCNN class loss: 0.11328 FastRCNN total loss: 0.23269 L1 loss: 0.0000e+00 L2 loss: 0.6058 Learning rate: 0.002 Mask loss: 0.15412 RPN box loss: 0.03047 RPN score loss: 0.01137 RPN total loss: 0.04185 Total loss: 1.03446 timestamp: 1654955995.8637 iteration: 53190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1099 FastRCNN class loss: 0.09968 FastRCNN total loss: 0.20958 L1 loss: 0.0000e+00 L2 loss: 0.6058 Learning rate: 0.002 Mask loss: 0.17452 RPN box loss: 0.02072 RPN score loss: 0.01537 RPN total loss: 0.03609 Total loss: 1.02599 timestamp: 1654955999.099035 iteration: 53195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13174 FastRCNN class loss: 0.08839 FastRCNN total loss: 0.22013 L1 loss: 0.0000e+00 L2 loss: 0.60579 Learning rate: 0.002 Mask loss: 0.13511 RPN box loss: 0.00915 RPN score loss: 0.0018 RPN total loss: 0.01095 Total loss: 0.97197 timestamp: 1654956002.2797732 iteration: 53200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14004 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.22294 L1 loss: 0.0000e+00 L2 loss: 0.60578 Learning rate: 0.002 Mask loss: 0.15791 RPN box loss: 0.0273 RPN score loss: 0.00945 RPN total loss: 0.03676 Total loss: 1.02338 timestamp: 1654956005.589793 iteration: 53205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09325 FastRCNN class loss: 0.05918 FastRCNN total loss: 0.15243 L1 loss: 0.0000e+00 L2 loss: 0.60577 Learning rate: 0.002 Mask loss: 0.16173 RPN box loss: 0.00765 RPN score loss: 0.00241 RPN total loss: 0.01006 Total loss: 0.92999 timestamp: 1654956008.8041697 iteration: 53210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04399 FastRCNN class loss: 0.05298 FastRCNN total loss: 0.09696 L1 loss: 0.0000e+00 L2 loss: 0.60576 Learning rate: 0.002 Mask loss: 0.09176 RPN box loss: 0.00247 RPN score loss: 0.00059 RPN total loss: 0.00305 Total loss: 0.79754 timestamp: 1654956012.0460114 iteration: 53215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13407 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.2238 L1 loss: 0.0000e+00 L2 loss: 0.60575 Learning rate: 0.002 Mask loss: 0.14628 RPN box loss: 0.01233 RPN score loss: 0.00681 RPN total loss: 0.01914 Total loss: 0.99497 timestamp: 1654956015.2306979 iteration: 53220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12848 FastRCNN class loss: 0.0995 FastRCNN total loss: 0.22798 L1 loss: 0.0000e+00 L2 loss: 0.60574 Learning rate: 0.002 Mask loss: 0.18979 RPN box loss: 0.01539 RPN score loss: 0.00486 RPN total loss: 0.02024 Total loss: 1.04377 timestamp: 1654956018.5168326 iteration: 53225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10572 FastRCNN class loss: 0.04723 FastRCNN total loss: 0.15295 L1 loss: 0.0000e+00 L2 loss: 0.60573 Learning rate: 0.002 Mask loss: 0.14749 RPN box loss: 0.01336 RPN score loss: 0.0025 RPN total loss: 0.01586 Total loss: 0.92204 timestamp: 1654956021.822883 iteration: 53230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09762 FastRCNN class loss: 0.06552 FastRCNN total loss: 0.16314 L1 loss: 0.0000e+00 L2 loss: 0.60573 Learning rate: 0.002 Mask loss: 0.07755 RPN box loss: 0.00511 RPN score loss: 0.00274 RPN total loss: 0.00785 Total loss: 0.85427 timestamp: 1654956025.0595965 iteration: 53235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10788 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.17962 L1 loss: 0.0000e+00 L2 loss: 0.60572 Learning rate: 0.002 Mask loss: 0.13465 RPN box loss: 0.01685 RPN score loss: 0.00685 RPN total loss: 0.02369 Total loss: 0.94368 timestamp: 1654956028.359416 iteration: 53240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12954 FastRCNN class loss: 0.09436 FastRCNN total loss: 0.2239 L1 loss: 0.0000e+00 L2 loss: 0.60571 Learning rate: 0.002 Mask loss: 0.21868 RPN box loss: 0.01267 RPN score loss: 0.00383 RPN total loss: 0.0165 Total loss: 1.06479 timestamp: 1654956031.5424666 iteration: 53245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.16356 L1 loss: 0.0000e+00 L2 loss: 0.60569 Learning rate: 0.002 Mask loss: 0.10102 RPN box loss: 0.01437 RPN score loss: 0.00919 RPN total loss: 0.02356 Total loss: 0.89384 timestamp: 1654956034.8402705 iteration: 53250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10572 FastRCNN class loss: 0.09131 FastRCNN total loss: 0.19703 L1 loss: 0.0000e+00 L2 loss: 0.60568 Learning rate: 0.002 Mask loss: 0.13154 RPN box loss: 0.02078 RPN score loss: 0.00415 RPN total loss: 0.02493 Total loss: 0.95918 timestamp: 1654956038.0906794 iteration: 53255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13809 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.21599 L1 loss: 0.0000e+00 L2 loss: 0.60568 Learning rate: 0.002 Mask loss: 0.13606 RPN box loss: 0.01651 RPN score loss: 0.00567 RPN total loss: 0.02218 Total loss: 0.97992 timestamp: 1654956041.414186 iteration: 53260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06124 FastRCNN class loss: 0.04637 FastRCNN total loss: 0.10761 L1 loss: 0.0000e+00 L2 loss: 0.60567 Learning rate: 0.002 Mask loss: 0.08208 RPN box loss: 0.03338 RPN score loss: 0.00729 RPN total loss: 0.04067 Total loss: 0.83603 timestamp: 1654956044.5674007 iteration: 53265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07218 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.13287 L1 loss: 0.0000e+00 L2 loss: 0.60566 Learning rate: 0.002 Mask loss: 0.1049 RPN box loss: 0.01794 RPN score loss: 0.00587 RPN total loss: 0.02381 Total loss: 0.86723 timestamp: 1654956047.7970526 iteration: 53270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11364 FastRCNN class loss: 0.08408 FastRCNN total loss: 0.19772 L1 loss: 0.0000e+00 L2 loss: 0.60565 Learning rate: 0.002 Mask loss: 0.17518 RPN box loss: 0.0182 RPN score loss: 0.01054 RPN total loss: 0.02874 Total loss: 1.00729 timestamp: 1654956050.9824908 iteration: 53275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1137 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.19522 L1 loss: 0.0000e+00 L2 loss: 0.60564 Learning rate: 0.002 Mask loss: 0.14635 RPN box loss: 0.03105 RPN score loss: 0.00798 RPN total loss: 0.03903 Total loss: 0.98625 timestamp: 1654956054.3635073 iteration: 53280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06995 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.12779 L1 loss: 0.0000e+00 L2 loss: 0.60563 Learning rate: 0.002 Mask loss: 0.08951 RPN box loss: 0.01396 RPN score loss: 0.00274 RPN total loss: 0.0167 Total loss: 0.83963 timestamp: 1654956057.6479032 iteration: 53285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06004 FastRCNN class loss: 0.07512 FastRCNN total loss: 0.13516 L1 loss: 0.0000e+00 L2 loss: 0.60563 Learning rate: 0.002 Mask loss: 0.14652 RPN box loss: 0.01685 RPN score loss: 0.01046 RPN total loss: 0.02731 Total loss: 0.91462 timestamp: 1654956060.7953064 iteration: 53290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09513 FastRCNN class loss: 0.06776 FastRCNN total loss: 0.1629 L1 loss: 0.0000e+00 L2 loss: 0.60562 Learning rate: 0.002 Mask loss: 0.13341 RPN box loss: 0.02519 RPN score loss: 0.01127 RPN total loss: 0.03646 Total loss: 0.93839 timestamp: 1654956064.1067855 iteration: 53295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10569 FastRCNN class loss: 0.08341 FastRCNN total loss: 0.1891 L1 loss: 0.0000e+00 L2 loss: 0.60561 Learning rate: 0.002 Mask loss: 0.12596 RPN box loss: 0.00892 RPN score loss: 0.00146 RPN total loss: 0.01039 Total loss: 0.93106 timestamp: 1654956067.3319745 iteration: 53300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11416 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.19938 L1 loss: 0.0000e+00 L2 loss: 0.6056 Learning rate: 0.002 Mask loss: 0.10808 RPN box loss: 0.01438 RPN score loss: 0.00849 RPN total loss: 0.02287 Total loss: 0.93592 timestamp: 1654956070.6718183 iteration: 53305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11068 FastRCNN class loss: 0.1091 FastRCNN total loss: 0.21979 L1 loss: 0.0000e+00 L2 loss: 0.60559 Learning rate: 0.002 Mask loss: 0.13511 RPN box loss: 0.01302 RPN score loss: 0.00223 RPN total loss: 0.01524 Total loss: 0.97574 timestamp: 1654956073.8722198 iteration: 53310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12109 FastRCNN class loss: 0.08406 FastRCNN total loss: 0.20515 L1 loss: 0.0000e+00 L2 loss: 0.60558 Learning rate: 0.002 Mask loss: 0.20953 RPN box loss: 0.03799 RPN score loss: 0.00377 RPN total loss: 0.04176 Total loss: 1.06203 timestamp: 1654956077.169636 iteration: 53315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09148 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.17184 L1 loss: 0.0000e+00 L2 loss: 0.60558 Learning rate: 0.002 Mask loss: 0.16673 RPN box loss: 0.01017 RPN score loss: 0.00276 RPN total loss: 0.01293 Total loss: 0.95707 timestamp: 1654956080.3840926 iteration: 53320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13579 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.21094 L1 loss: 0.0000e+00 L2 loss: 0.60557 Learning rate: 0.002 Mask loss: 0.15774 RPN box loss: 0.00562 RPN score loss: 0.00413 RPN total loss: 0.00975 Total loss: 0.98399 timestamp: 1654956083.577224 iteration: 53325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08742 FastRCNN class loss: 0.06145 FastRCNN total loss: 0.14887 L1 loss: 0.0000e+00 L2 loss: 0.60556 Learning rate: 0.002 Mask loss: 0.13998 RPN box loss: 0.00604 RPN score loss: 0.00141 RPN total loss: 0.00746 Total loss: 0.90186 timestamp: 1654956086.7565942 iteration: 53330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13645 FastRCNN class loss: 0.09053 FastRCNN total loss: 0.22698 L1 loss: 0.0000e+00 L2 loss: 0.60555 Learning rate: 0.002 Mask loss: 0.12315 RPN box loss: 0.01374 RPN score loss: 0.00434 RPN total loss: 0.01808 Total loss: 0.97376 timestamp: 1654956090.0333722 iteration: 53335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13146 FastRCNN class loss: 0.09136 FastRCNN total loss: 0.22282 L1 loss: 0.0000e+00 L2 loss: 0.60554 Learning rate: 0.002 Mask loss: 0.13418 RPN box loss: 0.01088 RPN score loss: 0.00588 RPN total loss: 0.01676 Total loss: 0.97931 timestamp: 1654956093.1861136 iteration: 53340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04639 FastRCNN class loss: 0.05389 FastRCNN total loss: 0.10029 L1 loss: 0.0000e+00 L2 loss: 0.60553 Learning rate: 0.002 Mask loss: 0.1095 RPN box loss: 0.00457 RPN score loss: 0.00306 RPN total loss: 0.00763 Total loss: 0.82295 timestamp: 1654956096.4774532 iteration: 53345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12425 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.18338 L1 loss: 0.0000e+00 L2 loss: 0.60552 Learning rate: 0.002 Mask loss: 0.13451 RPN box loss: 0.00371 RPN score loss: 0.00227 RPN total loss: 0.00598 Total loss: 0.92938 timestamp: 1654956099.758674 iteration: 53350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09087 FastRCNN class loss: 0.09655 FastRCNN total loss: 0.18743 L1 loss: 0.0000e+00 L2 loss: 0.60552 Learning rate: 0.002 Mask loss: 0.1334 RPN box loss: 0.01847 RPN score loss: 0.00735 RPN total loss: 0.02582 Total loss: 0.95216 timestamp: 1654956102.949422 iteration: 53355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10491 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.16938 L1 loss: 0.0000e+00 L2 loss: 0.60551 Learning rate: 0.002 Mask loss: 0.1922 RPN box loss: 0.03087 RPN score loss: 0.0109 RPN total loss: 0.04177 Total loss: 1.00886 timestamp: 1654956106.2747397 iteration: 53360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09374 FastRCNN class loss: 0.06933 FastRCNN total loss: 0.16307 L1 loss: 0.0000e+00 L2 loss: 0.6055 Learning rate: 0.002 Mask loss: 0.10851 RPN box loss: 0.04181 RPN score loss: 0.00821 RPN total loss: 0.05002 Total loss: 0.9271 timestamp: 1654956109.5181093 iteration: 53365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.09034 FastRCNN total loss: 0.16144 L1 loss: 0.0000e+00 L2 loss: 0.60549 Learning rate: 0.002 Mask loss: 0.16102 RPN box loss: 0.00938 RPN score loss: 0.00644 RPN total loss: 0.01582 Total loss: 0.94377 timestamp: 1654956112.7454188 iteration: 53370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09983 FastRCNN class loss: 0.09721 FastRCNN total loss: 0.19704 L1 loss: 0.0000e+00 L2 loss: 0.60548 Learning rate: 0.002 Mask loss: 0.16245 RPN box loss: 0.01322 RPN score loss: 0.01096 RPN total loss: 0.02419 Total loss: 0.98916 timestamp: 1654956115.9549265 iteration: 53375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07045 FastRCNN class loss: 0.04632 FastRCNN total loss: 0.11677 L1 loss: 0.0000e+00 L2 loss: 0.60547 Learning rate: 0.002 Mask loss: 0.0914 RPN box loss: 0.02261 RPN score loss: 0.00287 RPN total loss: 0.02548 Total loss: 0.83912 timestamp: 1654956119.2829025 iteration: 53380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09794 FastRCNN class loss: 0.0473 FastRCNN total loss: 0.14524 L1 loss: 0.0000e+00 L2 loss: 0.60546 Learning rate: 0.002 Mask loss: 0.1188 RPN box loss: 0.006 RPN score loss: 0.00199 RPN total loss: 0.00799 Total loss: 0.87749 timestamp: 1654956122.4238203 iteration: 53385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05621 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.10254 L1 loss: 0.0000e+00 L2 loss: 0.60545 Learning rate: 0.002 Mask loss: 0.1121 RPN box loss: 0.00875 RPN score loss: 0.00133 RPN total loss: 0.01008 Total loss: 0.83017 timestamp: 1654956125.7851405 iteration: 53390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12851 FastRCNN class loss: 0.08147 FastRCNN total loss: 0.20998 L1 loss: 0.0000e+00 L2 loss: 0.60545 Learning rate: 0.002 Mask loss: 0.13788 RPN box loss: 0.01572 RPN score loss: 0.00726 RPN total loss: 0.02298 Total loss: 0.97629 timestamp: 1654956129.1205525 iteration: 53395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15329 FastRCNN class loss: 0.09739 FastRCNN total loss: 0.25068 L1 loss: 0.0000e+00 L2 loss: 0.60544 Learning rate: 0.002 Mask loss: 0.19175 RPN box loss: 0.02824 RPN score loss: 0.00553 RPN total loss: 0.03378 Total loss: 1.08164 timestamp: 1654956132.3544867 iteration: 53400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1018 FastRCNN class loss: 0.06246 FastRCNN total loss: 0.16426 L1 loss: 0.0000e+00 L2 loss: 0.60544 Learning rate: 0.002 Mask loss: 0.13742 RPN box loss: 0.01104 RPN score loss: 0.00184 RPN total loss: 0.01288 Total loss: 0.91999 timestamp: 1654956135.632328 iteration: 53405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05677 FastRCNN class loss: 0.05474 FastRCNN total loss: 0.11151 L1 loss: 0.0000e+00 L2 loss: 0.60543 Learning rate: 0.002 Mask loss: 0.11379 RPN box loss: 0.04143 RPN score loss: 0.00953 RPN total loss: 0.05096 Total loss: 0.88169 timestamp: 1654956138.8355608 iteration: 53410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06067 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.125 L1 loss: 0.0000e+00 L2 loss: 0.60542 Learning rate: 0.002 Mask loss: 0.11856 RPN box loss: 0.02063 RPN score loss: 0.00569 RPN total loss: 0.02632 Total loss: 0.8753 timestamp: 1654956142.1211894 iteration: 53415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06921 FastRCNN class loss: 0.05905 FastRCNN total loss: 0.12827 L1 loss: 0.0000e+00 L2 loss: 0.60541 Learning rate: 0.002 Mask loss: 0.13979 RPN box loss: 0.0124 RPN score loss: 0.0153 RPN total loss: 0.02771 Total loss: 0.90117 timestamp: 1654956145.305475 iteration: 53420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07978 FastRCNN class loss: 0.06322 FastRCNN total loss: 0.14301 L1 loss: 0.0000e+00 L2 loss: 0.6054 Learning rate: 0.002 Mask loss: 0.21287 RPN box loss: 0.00613 RPN score loss: 0.00336 RPN total loss: 0.00949 Total loss: 0.97077 timestamp: 1654956148.5691674 iteration: 53425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11795 FastRCNN class loss: 0.093 FastRCNN total loss: 0.21096 L1 loss: 0.0000e+00 L2 loss: 0.60539 Learning rate: 0.002 Mask loss: 0.17294 RPN box loss: 0.01532 RPN score loss: 0.01786 RPN total loss: 0.03318 Total loss: 1.02248 timestamp: 1654956151.6798375 iteration: 53430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07749 FastRCNN class loss: 0.0383 FastRCNN total loss: 0.11579 L1 loss: 0.0000e+00 L2 loss: 0.60538 Learning rate: 0.002 Mask loss: 0.09128 RPN box loss: 0.01917 RPN score loss: 0.00461 RPN total loss: 0.02379 Total loss: 0.83623 timestamp: 1654956154.993438 iteration: 53435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08359 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.15647 L1 loss: 0.0000e+00 L2 loss: 0.60537 Learning rate: 0.002 Mask loss: 0.10021 RPN box loss: 0.00961 RPN score loss: 0.00889 RPN total loss: 0.01851 Total loss: 0.88056 timestamp: 1654956158.2169745 iteration: 53440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08188 FastRCNN class loss: 0.07164 FastRCNN total loss: 0.15352 L1 loss: 0.0000e+00 L2 loss: 0.60536 Learning rate: 0.002 Mask loss: 0.17513 RPN box loss: 0.01246 RPN score loss: 0.00136 RPN total loss: 0.01382 Total loss: 0.94783 timestamp: 1654956161.4503782 iteration: 53445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08518 FastRCNN class loss: 0.06084 FastRCNN total loss: 0.14602 L1 loss: 0.0000e+00 L2 loss: 0.60535 Learning rate: 0.002 Mask loss: 0.16985 RPN box loss: 0.00388 RPN score loss: 0.00384 RPN total loss: 0.00773 Total loss: 0.92894 timestamp: 1654956164.6384764 iteration: 53450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09436 FastRCNN class loss: 0.04773 FastRCNN total loss: 0.14209 L1 loss: 0.0000e+00 L2 loss: 0.60534 Learning rate: 0.002 Mask loss: 0.11602 RPN box loss: 0.00356 RPN score loss: 0.00144 RPN total loss: 0.005 Total loss: 0.86846 timestamp: 1654956167.991417 iteration: 53455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07314 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.1341 L1 loss: 0.0000e+00 L2 loss: 0.60534 Learning rate: 0.002 Mask loss: 0.0935 RPN box loss: 0.01203 RPN score loss: 0.00232 RPN total loss: 0.01435 Total loss: 0.84729 timestamp: 1654956171.3161905 iteration: 53460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07367 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.1624 L1 loss: 0.0000e+00 L2 loss: 0.60533 Learning rate: 0.002 Mask loss: 0.14311 RPN box loss: 0.01916 RPN score loss: 0.01055 RPN total loss: 0.0297 Total loss: 0.94055 timestamp: 1654956174.434845 iteration: 53465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12364 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.203 L1 loss: 0.0000e+00 L2 loss: 0.60532 Learning rate: 0.002 Mask loss: 0.16236 RPN box loss: 0.0188 RPN score loss: 0.00863 RPN total loss: 0.02743 Total loss: 0.99812 timestamp: 1654956177.7433732 iteration: 53470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13284 FastRCNN class loss: 0.04733 FastRCNN total loss: 0.18017 L1 loss: 0.0000e+00 L2 loss: 0.60531 Learning rate: 0.002 Mask loss: 0.15809 RPN box loss: 0.01104 RPN score loss: 0.00148 RPN total loss: 0.01252 Total loss: 0.95609 timestamp: 1654956180.9997828 iteration: 53475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08657 FastRCNN class loss: 0.09644 FastRCNN total loss: 0.18301 L1 loss: 0.0000e+00 L2 loss: 0.6053 Learning rate: 0.002 Mask loss: 0.16896 RPN box loss: 0.01942 RPN score loss: 0.01472 RPN total loss: 0.03414 Total loss: 0.99142 timestamp: 1654956184.2152512 iteration: 53480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11888 FastRCNN class loss: 0.10261 FastRCNN total loss: 0.22148 L1 loss: 0.0000e+00 L2 loss: 0.6053 Learning rate: 0.002 Mask loss: 0.14888 RPN box loss: 0.01819 RPN score loss: 0.00464 RPN total loss: 0.02283 Total loss: 0.99849 timestamp: 1654956187.353928 iteration: 53485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08724 FastRCNN class loss: 0.0932 FastRCNN total loss: 0.18044 L1 loss: 0.0000e+00 L2 loss: 0.60529 Learning rate: 0.002 Mask loss: 0.12169 RPN box loss: 0.01442 RPN score loss: 0.00244 RPN total loss: 0.01685 Total loss: 0.92427 timestamp: 1654956190.6119103 iteration: 53490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07922 FastRCNN class loss: 0.07845 FastRCNN total loss: 0.15767 L1 loss: 0.0000e+00 L2 loss: 0.60528 Learning rate: 0.002 Mask loss: 0.12161 RPN box loss: 0.00551 RPN score loss: 0.00576 RPN total loss: 0.01127 Total loss: 0.89583 timestamp: 1654956193.8520658 iteration: 53495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07722 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.13462 L1 loss: 0.0000e+00 L2 loss: 0.60527 Learning rate: 0.002 Mask loss: 0.09359 RPN box loss: 0.00452 RPN score loss: 0.00444 RPN total loss: 0.00896 Total loss: 0.84244 timestamp: 1654956197.2109742 iteration: 53500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0804 FastRCNN class loss: 0.06359 FastRCNN total loss: 0.144 L1 loss: 0.0000e+00 L2 loss: 0.60526 Learning rate: 0.002 Mask loss: 0.13928 RPN box loss: 0.01578 RPN score loss: 0.00589 RPN total loss: 0.02167 Total loss: 0.91021 timestamp: 1654956200.4961967 iteration: 53505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07555 FastRCNN class loss: 0.04663 FastRCNN total loss: 0.12217 L1 loss: 0.0000e+00 L2 loss: 0.60525 Learning rate: 0.002 Mask loss: 0.10018 RPN box loss: 0.01235 RPN score loss: 0.00414 RPN total loss: 0.01649 Total loss: 0.84409 timestamp: 1654956203.6733265 iteration: 53510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14388 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.23346 L1 loss: 0.0000e+00 L2 loss: 0.60524 Learning rate: 0.002 Mask loss: 0.14208 RPN box loss: 0.04108 RPN score loss: 0.0107 RPN total loss: 0.05178 Total loss: 1.03255 timestamp: 1654956207.054569 iteration: 53515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.05742 FastRCNN total loss: 0.14505 L1 loss: 0.0000e+00 L2 loss: 0.60523 Learning rate: 0.002 Mask loss: 0.1321 RPN box loss: 0.01112 RPN score loss: 0.00091 RPN total loss: 0.01203 Total loss: 0.89442 timestamp: 1654956210.2627835 iteration: 53520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07119 FastRCNN class loss: 0.04803 FastRCNN total loss: 0.11922 L1 loss: 0.0000e+00 L2 loss: 0.60523 Learning rate: 0.002 Mask loss: 0.15601 RPN box loss: 0.00509 RPN score loss: 0.00113 RPN total loss: 0.00622 Total loss: 0.88667 timestamp: 1654956213.4755907 iteration: 53525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09962 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.16039 L1 loss: 0.0000e+00 L2 loss: 0.60522 Learning rate: 0.002 Mask loss: 0.09526 RPN box loss: 0.00588 RPN score loss: 0.00414 RPN total loss: 0.01002 Total loss: 0.87088 timestamp: 1654956216.7216988 iteration: 53530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0946 FastRCNN class loss: 0.06395 FastRCNN total loss: 0.15855 L1 loss: 0.0000e+00 L2 loss: 0.60521 Learning rate: 0.002 Mask loss: 0.13905 RPN box loss: 0.00991 RPN score loss: 0.00205 RPN total loss: 0.01197 Total loss: 0.91477 timestamp: 1654956220.0235276 iteration: 53535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07714 FastRCNN class loss: 0.09537 FastRCNN total loss: 0.17251 L1 loss: 0.0000e+00 L2 loss: 0.6052 Learning rate: 0.002 Mask loss: 0.13024 RPN box loss: 0.01637 RPN score loss: 0.0066 RPN total loss: 0.02297 Total loss: 0.93092 timestamp: 1654956223.1866152 iteration: 53540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.0859 FastRCNN total loss: 0.19629 L1 loss: 0.0000e+00 L2 loss: 0.60519 Learning rate: 0.002 Mask loss: 0.17565 RPN box loss: 0.01404 RPN score loss: 0.00409 RPN total loss: 0.01814 Total loss: 0.99526 timestamp: 1654956226.3686197 iteration: 53545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07117 FastRCNN class loss: 0.04941 FastRCNN total loss: 0.12058 L1 loss: 0.0000e+00 L2 loss: 0.60518 Learning rate: 0.002 Mask loss: 0.09701 RPN box loss: 0.02371 RPN score loss: 0.00262 RPN total loss: 0.02634 Total loss: 0.8491 timestamp: 1654956229.5522132 iteration: 53550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0889 FastRCNN class loss: 0.0669 FastRCNN total loss: 0.1558 L1 loss: 0.0000e+00 L2 loss: 0.60518 Learning rate: 0.002 Mask loss: 0.12786 RPN box loss: 0.01228 RPN score loss: 0.00138 RPN total loss: 0.01366 Total loss: 0.90249 timestamp: 1654956232.9488697 iteration: 53555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03707 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.08756 L1 loss: 0.0000e+00 L2 loss: 0.60517 Learning rate: 0.002 Mask loss: 0.16033 RPN box loss: 0.02608 RPN score loss: 0.00559 RPN total loss: 0.03167 Total loss: 0.88474 timestamp: 1654956236.1667287 iteration: 53560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08874 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.14658 L1 loss: 0.0000e+00 L2 loss: 0.60516 Learning rate: 0.002 Mask loss: 0.0958 RPN box loss: 0.00425 RPN score loss: 0.00776 RPN total loss: 0.01201 Total loss: 0.85955 timestamp: 1654956239.427739 iteration: 53565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.08954 FastRCNN total loss: 0.2025 L1 loss: 0.0000e+00 L2 loss: 0.60515 Learning rate: 0.002 Mask loss: 0.11766 RPN box loss: 0.02564 RPN score loss: 0.00493 RPN total loss: 0.03057 Total loss: 0.95588 timestamp: 1654956242.6930525 iteration: 53570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07844 FastRCNN class loss: 0.05364 FastRCNN total loss: 0.13208 L1 loss: 0.0000e+00 L2 loss: 0.60515 Learning rate: 0.002 Mask loss: 0.12677 RPN box loss: 0.046 RPN score loss: 0.00229 RPN total loss: 0.04829 Total loss: 0.91229 timestamp: 1654956245.9013133 iteration: 53575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07012 FastRCNN class loss: 0.04378 FastRCNN total loss: 0.1139 L1 loss: 0.0000e+00 L2 loss: 0.60514 Learning rate: 0.002 Mask loss: 0.09307 RPN box loss: 0.01339 RPN score loss: 0.00258 RPN total loss: 0.01598 Total loss: 0.82808 timestamp: 1654956249.2326345 iteration: 53580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11939 FastRCNN class loss: 0.06836 FastRCNN total loss: 0.18776 L1 loss: 0.0000e+00 L2 loss: 0.60513 Learning rate: 0.002 Mask loss: 0.11792 RPN box loss: 0.00832 RPN score loss: 0.00353 RPN total loss: 0.01186 Total loss: 0.92267 timestamp: 1654956252.3208961 iteration: 53585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10361 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.16437 L1 loss: 0.0000e+00 L2 loss: 0.60512 Learning rate: 0.002 Mask loss: 0.10089 RPN box loss: 0.01614 RPN score loss: 0.00368 RPN total loss: 0.01981 Total loss: 0.89019 timestamp: 1654956255.5634623 iteration: 53590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07721 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.12219 L1 loss: 0.0000e+00 L2 loss: 0.60511 Learning rate: 0.002 Mask loss: 0.10597 RPN box loss: 0.0046 RPN score loss: 0.00404 RPN total loss: 0.00863 Total loss: 0.84191 timestamp: 1654956258.7828205 iteration: 53595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08358 FastRCNN class loss: 0.11472 FastRCNN total loss: 0.1983 L1 loss: 0.0000e+00 L2 loss: 0.6051 Learning rate: 0.002 Mask loss: 0.2031 RPN box loss: 0.01679 RPN score loss: 0.01345 RPN total loss: 0.03024 Total loss: 1.03674 timestamp: 1654956262.0545075 iteration: 53600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09824 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.1757 L1 loss: 0.0000e+00 L2 loss: 0.6051 Learning rate: 0.002 Mask loss: 0.19191 RPN box loss: 0.01755 RPN score loss: 0.00896 RPN total loss: 0.02651 Total loss: 0.99922 timestamp: 1654956265.2326167 iteration: 53605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0502 FastRCNN class loss: 0.03935 FastRCNN total loss: 0.08955 L1 loss: 0.0000e+00 L2 loss: 0.60509 Learning rate: 0.002 Mask loss: 0.06537 RPN box loss: 0.00566 RPN score loss: 0.00222 RPN total loss: 0.00789 Total loss: 0.7679 timestamp: 1654956268.408169 iteration: 53610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08342 FastRCNN class loss: 0.04479 FastRCNN total loss: 0.12821 L1 loss: 0.0000e+00 L2 loss: 0.60508 Learning rate: 0.002 Mask loss: 0.12192 RPN box loss: 0.00753 RPN score loss: 0.00128 RPN total loss: 0.00882 Total loss: 0.86403 timestamp: 1654956271.578863 iteration: 53615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10119 FastRCNN class loss: 0.09924 FastRCNN total loss: 0.20043 L1 loss: 0.0000e+00 L2 loss: 0.60507 Learning rate: 0.002 Mask loss: 0.13332 RPN box loss: 0.00721 RPN score loss: 0.0039 RPN total loss: 0.01111 Total loss: 0.94993 timestamp: 1654956274.9050062 iteration: 53620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.113 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.18524 L1 loss: 0.0000e+00 L2 loss: 0.60506 Learning rate: 0.002 Mask loss: 0.11271 RPN box loss: 0.01564 RPN score loss: 0.00757 RPN total loss: 0.02321 Total loss: 0.92622 timestamp: 1654956278.2560732 iteration: 53625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10387 FastRCNN class loss: 0.05739 FastRCNN total loss: 0.16127 L1 loss: 0.0000e+00 L2 loss: 0.60506 Learning rate: 0.002 Mask loss: 0.12637 RPN box loss: 0.01808 RPN score loss: 0.00211 RPN total loss: 0.02019 Total loss: 0.91289 timestamp: 1654956281.4512773 iteration: 53630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10016 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.16079 L1 loss: 0.0000e+00 L2 loss: 0.60505 Learning rate: 0.002 Mask loss: 0.11328 RPN box loss: 0.01169 RPN score loss: 0.0032 RPN total loss: 0.01489 Total loss: 0.89401 timestamp: 1654956284.7263172 iteration: 53635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13116 FastRCNN class loss: 0.12906 FastRCNN total loss: 0.26022 L1 loss: 0.0000e+00 L2 loss: 0.60504 Learning rate: 0.002 Mask loss: 0.20047 RPN box loss: 0.03264 RPN score loss: 0.0121 RPN total loss: 0.04474 Total loss: 1.11048 timestamp: 1654956287.9421368 iteration: 53640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08805 FastRCNN class loss: 0.05335 FastRCNN total loss: 0.14141 L1 loss: 0.0000e+00 L2 loss: 0.60503 Learning rate: 0.002 Mask loss: 0.10915 RPN box loss: 0.01964 RPN score loss: 0.00386 RPN total loss: 0.0235 Total loss: 0.87909 timestamp: 1654956291.3508954 iteration: 53645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12982 FastRCNN class loss: 0.08205 FastRCNN total loss: 0.21187 L1 loss: 0.0000e+00 L2 loss: 0.60502 Learning rate: 0.002 Mask loss: 0.1336 RPN box loss: 0.01971 RPN score loss: 0.01304 RPN total loss: 0.03275 Total loss: 0.98324 timestamp: 1654956294.5297463 iteration: 53650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07179 FastRCNN class loss: 0.06813 FastRCNN total loss: 0.13992 L1 loss: 0.0000e+00 L2 loss: 0.60502 Learning rate: 0.002 Mask loss: 0.11882 RPN box loss: 0.00841 RPN score loss: 0.006 RPN total loss: 0.01441 Total loss: 0.87817 timestamp: 1654956297.8571522 iteration: 53655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09801 FastRCNN class loss: 0.11209 FastRCNN total loss: 0.21011 L1 loss: 0.0000e+00 L2 loss: 0.60501 Learning rate: 0.002 Mask loss: 0.19299 RPN box loss: 0.01198 RPN score loss: 0.00421 RPN total loss: 0.01619 Total loss: 1.0243 timestamp: 1654956301.01276 iteration: 53660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10708 FastRCNN class loss: 0.08296 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 0.605 Learning rate: 0.002 Mask loss: 0.08955 RPN box loss: 0.0206 RPN score loss: 0.01266 RPN total loss: 0.03325 Total loss: 0.91785 timestamp: 1654956304.3196416 iteration: 53665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12493 FastRCNN class loss: 0.09654 FastRCNN total loss: 0.22147 L1 loss: 0.0000e+00 L2 loss: 0.60499 Learning rate: 0.002 Mask loss: 0.12438 RPN box loss: 0.00916 RPN score loss: 0.00584 RPN total loss: 0.01501 Total loss: 0.96585 timestamp: 1654956307.523575 iteration: 53670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13087 FastRCNN class loss: 0.05023 FastRCNN total loss: 0.1811 L1 loss: 0.0000e+00 L2 loss: 0.60498 Learning rate: 0.002 Mask loss: 0.1028 RPN box loss: 0.00743 RPN score loss: 0.00187 RPN total loss: 0.0093 Total loss: 0.89819 timestamp: 1654956310.8515108 iteration: 53675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08651 FastRCNN class loss: 0.10203 FastRCNN total loss: 0.18853 L1 loss: 0.0000e+00 L2 loss: 0.60497 Learning rate: 0.002 Mask loss: 0.14565 RPN box loss: 0.01997 RPN score loss: 0.00491 RPN total loss: 0.02489 Total loss: 0.96403 timestamp: 1654956314.0915573 iteration: 53680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07554 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.12822 L1 loss: 0.0000e+00 L2 loss: 0.60496 Learning rate: 0.002 Mask loss: 0.13646 RPN box loss: 0.00723 RPN score loss: 0.00187 RPN total loss: 0.0091 Total loss: 0.87874 timestamp: 1654956317.3562167 iteration: 53685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06798 FastRCNN class loss: 0.06087 FastRCNN total loss: 0.12885 L1 loss: 0.0000e+00 L2 loss: 0.60495 Learning rate: 0.002 Mask loss: 0.13081 RPN box loss: 0.01066 RPN score loss: 0.01844 RPN total loss: 0.0291 Total loss: 0.8937 timestamp: 1654956320.644971 iteration: 53690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15508 FastRCNN class loss: 0.1226 FastRCNN total loss: 0.27768 L1 loss: 0.0000e+00 L2 loss: 0.60494 Learning rate: 0.002 Mask loss: 0.14344 RPN box loss: 0.01682 RPN score loss: 0.0023 RPN total loss: 0.01912 Total loss: 1.04517 timestamp: 1654956323.8426526 iteration: 53695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10377 FastRCNN class loss: 0.05122 FastRCNN total loss: 0.15499 L1 loss: 0.0000e+00 L2 loss: 0.60493 Learning rate: 0.002 Mask loss: 0.11606 RPN box loss: 0.00946 RPN score loss: 0.0015 RPN total loss: 0.01095 Total loss: 0.88694 timestamp: 1654956327.1448848 iteration: 53700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13039 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.2115 L1 loss: 0.0000e+00 L2 loss: 0.60492 Learning rate: 0.002 Mask loss: 0.15928 RPN box loss: 0.02468 RPN score loss: 0.01714 RPN total loss: 0.04182 Total loss: 1.01753 timestamp: 1654956330.3649025 iteration: 53705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07615 FastRCNN class loss: 0.04658 FastRCNN total loss: 0.12272 L1 loss: 0.0000e+00 L2 loss: 0.60492 Learning rate: 0.002 Mask loss: 0.083 RPN box loss: 0.00815 RPN score loss: 0.00203 RPN total loss: 0.01018 Total loss: 0.82082 timestamp: 1654956333.6204824 iteration: 53710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10932 FastRCNN class loss: 0.08381 FastRCNN total loss: 0.19313 L1 loss: 0.0000e+00 L2 loss: 0.60491 Learning rate: 0.002 Mask loss: 0.22575 RPN box loss: 0.01642 RPN score loss: 0.00279 RPN total loss: 0.0192 Total loss: 1.04299 timestamp: 1654956336.7996337 iteration: 53715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07335 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.14011 L1 loss: 0.0000e+00 L2 loss: 0.6049 Learning rate: 0.002 Mask loss: 0.11061 RPN box loss: 0.00691 RPN score loss: 0.00322 RPN total loss: 0.01013 Total loss: 0.86574 timestamp: 1654956339.992487 iteration: 53720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10359 FastRCNN class loss: 0.07583 FastRCNN total loss: 0.17942 L1 loss: 0.0000e+00 L2 loss: 0.60489 Learning rate: 0.002 Mask loss: 0.12652 RPN box loss: 0.02698 RPN score loss: 0.00966 RPN total loss: 0.03664 Total loss: 0.94746 timestamp: 1654956343.2407117 iteration: 53725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10333 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.18246 L1 loss: 0.0000e+00 L2 loss: 0.60488 Learning rate: 0.002 Mask loss: 0.19005 RPN box loss: 0.01664 RPN score loss: 0.01303 RPN total loss: 0.02966 Total loss: 1.00705 timestamp: 1654956346.499705 iteration: 53730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09038 FastRCNN class loss: 0.07848 FastRCNN total loss: 0.16886 L1 loss: 0.0000e+00 L2 loss: 0.60487 Learning rate: 0.002 Mask loss: 0.19785 RPN box loss: 0.01159 RPN score loss: 0.00373 RPN total loss: 0.01532 Total loss: 0.9869 timestamp: 1654956349.7847393 iteration: 53735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05421 FastRCNN class loss: 0.06706 FastRCNN total loss: 0.12127 L1 loss: 0.0000e+00 L2 loss: 0.60486 Learning rate: 0.002 Mask loss: 0.12731 RPN box loss: 0.01541 RPN score loss: 0.00503 RPN total loss: 0.02045 Total loss: 0.87388 timestamp: 1654956352.9341624 iteration: 53740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0828 FastRCNN class loss: 0.06322 FastRCNN total loss: 0.14603 L1 loss: 0.0000e+00 L2 loss: 0.60486 Learning rate: 0.002 Mask loss: 0.10576 RPN box loss: 0.0036 RPN score loss: 0.00069 RPN total loss: 0.00429 Total loss: 0.86093 timestamp: 1654956356.2660737 iteration: 53745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09984 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.16532 L1 loss: 0.0000e+00 L2 loss: 0.60485 Learning rate: 0.002 Mask loss: 0.15275 RPN box loss: 0.00718 RPN score loss: 0.00366 RPN total loss: 0.01083 Total loss: 0.93375 timestamp: 1654956359.5017788 iteration: 53750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16087 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.23145 L1 loss: 0.0000e+00 L2 loss: 0.60484 Learning rate: 0.002 Mask loss: 0.13293 RPN box loss: 0.02112 RPN score loss: 0.00394 RPN total loss: 0.02506 Total loss: 0.99427 timestamp: 1654956362.7829745 iteration: 53755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07788 FastRCNN class loss: 0.04261 FastRCNN total loss: 0.12048 L1 loss: 0.0000e+00 L2 loss: 0.60483 Learning rate: 0.002 Mask loss: 0.13386 RPN box loss: 0.0096 RPN score loss: 0.00104 RPN total loss: 0.01064 Total loss: 0.86981 timestamp: 1654956365.9714336 iteration: 53760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07982 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.13621 L1 loss: 0.0000e+00 L2 loss: 0.60482 Learning rate: 0.002 Mask loss: 0.13537 RPN box loss: 0.0138 RPN score loss: 0.00492 RPN total loss: 0.01872 Total loss: 0.89512 timestamp: 1654956369.2154357 iteration: 53765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08176 FastRCNN class loss: 0.05041 FastRCNN total loss: 0.13217 L1 loss: 0.0000e+00 L2 loss: 0.60481 Learning rate: 0.002 Mask loss: 0.13932 RPN box loss: 0.00824 RPN score loss: 0.00536 RPN total loss: 0.0136 Total loss: 0.8899 timestamp: 1654956372.4978068 iteration: 53770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09735 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.15722 L1 loss: 0.0000e+00 L2 loss: 0.6048 Learning rate: 0.002 Mask loss: 0.12628 RPN box loss: 0.01721 RPN score loss: 0.00383 RPN total loss: 0.02103 Total loss: 0.90934 timestamp: 1654956375.8748722 iteration: 53775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08644 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.1456 L1 loss: 0.0000e+00 L2 loss: 0.60479 Learning rate: 0.002 Mask loss: 0.12331 RPN box loss: 0.01607 RPN score loss: 0.00988 RPN total loss: 0.02594 Total loss: 0.89965 timestamp: 1654956379.178712 iteration: 53780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10397 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.17722 L1 loss: 0.0000e+00 L2 loss: 0.60479 Learning rate: 0.002 Mask loss: 0.07594 RPN box loss: 0.0115 RPN score loss: 0.00318 RPN total loss: 0.01467 Total loss: 0.87262 timestamp: 1654956382.539763 iteration: 53785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12481 FastRCNN class loss: 0.0706 FastRCNN total loss: 0.19541 L1 loss: 0.0000e+00 L2 loss: 0.60478 Learning rate: 0.002 Mask loss: 0.17498 RPN box loss: 0.01044 RPN score loss: 0.00572 RPN total loss: 0.01615 Total loss: 0.99131 timestamp: 1654956385.9384482 iteration: 53790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1359 FastRCNN class loss: 0.09032 FastRCNN total loss: 0.22622 L1 loss: 0.0000e+00 L2 loss: 0.60477 Learning rate: 0.002 Mask loss: 0.21491 RPN box loss: 0.01878 RPN score loss: 0.00605 RPN total loss: 0.02483 Total loss: 1.07073 timestamp: 1654956389.136498 iteration: 53795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16967 FastRCNN class loss: 0.0834 FastRCNN total loss: 0.25307 L1 loss: 0.0000e+00 L2 loss: 0.60476 Learning rate: 0.002 Mask loss: 0.10238 RPN box loss: 0.0181 RPN score loss: 0.00319 RPN total loss: 0.02129 Total loss: 0.98151 timestamp: 1654956392.4722037 iteration: 53800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12791 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.20241 L1 loss: 0.0000e+00 L2 loss: 0.60475 Learning rate: 0.002 Mask loss: 0.1235 RPN box loss: 0.01156 RPN score loss: 0.00285 RPN total loss: 0.01441 Total loss: 0.94507 timestamp: 1654956395.649018 iteration: 53805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11006 FastRCNN class loss: 0.10995 FastRCNN total loss: 0.22001 L1 loss: 0.0000e+00 L2 loss: 0.60474 Learning rate: 0.002 Mask loss: 0.2334 RPN box loss: 0.01773 RPN score loss: 0.0071 RPN total loss: 0.02483 Total loss: 1.08299 timestamp: 1654956398.9310162 iteration: 53810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11824 FastRCNN class loss: 0.10984 FastRCNN total loss: 0.22809 L1 loss: 0.0000e+00 L2 loss: 0.60473 Learning rate: 0.002 Mask loss: 0.11889 RPN box loss: 0.02155 RPN score loss: 0.00488 RPN total loss: 0.02643 Total loss: 0.97814 timestamp: 1654956402.103709 iteration: 53815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10023 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.16329 L1 loss: 0.0000e+00 L2 loss: 0.60473 Learning rate: 0.002 Mask loss: 0.09994 RPN box loss: 0.03085 RPN score loss: 0.00252 RPN total loss: 0.03337 Total loss: 0.90134 timestamp: 1654956405.3599503 iteration: 53820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10653 FastRCNN class loss: 0.06979 FastRCNN total loss: 0.17632 L1 loss: 0.0000e+00 L2 loss: 0.60472 Learning rate: 0.002 Mask loss: 0.15523 RPN box loss: 0.01221 RPN score loss: 0.00117 RPN total loss: 0.01338 Total loss: 0.94965 timestamp: 1654956408.5188222 iteration: 53825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1216 FastRCNN class loss: 0.10561 FastRCNN total loss: 0.2272 L1 loss: 0.0000e+00 L2 loss: 0.60471 Learning rate: 0.002 Mask loss: 0.15551 RPN box loss: 0.03078 RPN score loss: 0.01051 RPN total loss: 0.0413 Total loss: 1.02872 timestamp: 1654956411.7247856 iteration: 53830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08102 FastRCNN class loss: 0.07274 FastRCNN total loss: 0.15376 L1 loss: 0.0000e+00 L2 loss: 0.60471 Learning rate: 0.002 Mask loss: 0.07949 RPN box loss: 0.00634 RPN score loss: 0.00456 RPN total loss: 0.0109 Total loss: 0.84886 timestamp: 1654956414.9556496 iteration: 53835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13474 FastRCNN class loss: 0.07843 FastRCNN total loss: 0.21317 L1 loss: 0.0000e+00 L2 loss: 0.6047 Learning rate: 0.002 Mask loss: 0.10596 RPN box loss: 0.0071 RPN score loss: 0.00304 RPN total loss: 0.01014 Total loss: 0.93397 timestamp: 1654956418.2408092 iteration: 53840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04529 FastRCNN class loss: 0.03108 FastRCNN total loss: 0.07637 L1 loss: 0.0000e+00 L2 loss: 0.60469 Learning rate: 0.002 Mask loss: 0.08446 RPN box loss: 0.0048 RPN score loss: 0.00143 RPN total loss: 0.00624 Total loss: 0.77175 timestamp: 1654956421.4437149 iteration: 53845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10737 FastRCNN class loss: 0.09422 FastRCNN total loss: 0.20159 L1 loss: 0.0000e+00 L2 loss: 0.60468 Learning rate: 0.002 Mask loss: 0.15408 RPN box loss: 0.01115 RPN score loss: 0.00227 RPN total loss: 0.01342 Total loss: 0.97377 timestamp: 1654956424.6855526 iteration: 53850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12912 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.17183 L1 loss: 0.0000e+00 L2 loss: 0.60467 Learning rate: 0.002 Mask loss: 0.08612 RPN box loss: 0.0091 RPN score loss: 0.00282 RPN total loss: 0.01192 Total loss: 0.87454 timestamp: 1654956428.1000612 iteration: 53855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14457 FastRCNN class loss: 0.06272 FastRCNN total loss: 0.2073 L1 loss: 0.0000e+00 L2 loss: 0.60467 Learning rate: 0.002 Mask loss: 0.13736 RPN box loss: 0.00541 RPN score loss: 0.00107 RPN total loss: 0.00648 Total loss: 0.9558 timestamp: 1654956431.2795627 iteration: 53860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08382 FastRCNN class loss: 0.09852 FastRCNN total loss: 0.18233 L1 loss: 0.0000e+00 L2 loss: 0.60466 Learning rate: 0.002 Mask loss: 0.15646 RPN box loss: 0.0084 RPN score loss: 0.00281 RPN total loss: 0.01121 Total loss: 0.95466 timestamp: 1654956434.6179607 iteration: 53865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05108 FastRCNN class loss: 0.04611 FastRCNN total loss: 0.09718 L1 loss: 0.0000e+00 L2 loss: 0.60465 Learning rate: 0.002 Mask loss: 0.11564 RPN box loss: 0.0088 RPN score loss: 0.00219 RPN total loss: 0.01099 Total loss: 0.82846 timestamp: 1654956437.8361628 iteration: 53870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07698 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.14647 L1 loss: 0.0000e+00 L2 loss: 0.60464 Learning rate: 0.002 Mask loss: 0.1535 RPN box loss: 0.0052 RPN score loss: 0.0009 RPN total loss: 0.0061 Total loss: 0.91069 timestamp: 1654956441.0943098 iteration: 53875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.08626 FastRCNN total loss: 0.18949 L1 loss: 0.0000e+00 L2 loss: 0.60463 Learning rate: 0.002 Mask loss: 0.14153 RPN box loss: 0.01629 RPN score loss: 0.01167 RPN total loss: 0.02795 Total loss: 0.9636 timestamp: 1654956444.256865 iteration: 53880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08463 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.15213 L1 loss: 0.0000e+00 L2 loss: 0.60462 Learning rate: 0.002 Mask loss: 0.17968 RPN box loss: 0.01777 RPN score loss: 0.00743 RPN total loss: 0.0252 Total loss: 0.96162 timestamp: 1654956447.6213012 iteration: 53885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05981 FastRCNN class loss: 0.0511 FastRCNN total loss: 0.11091 L1 loss: 0.0000e+00 L2 loss: 0.60461 Learning rate: 0.002 Mask loss: 0.15487 RPN box loss: 0.0037 RPN score loss: 0.00498 RPN total loss: 0.00868 Total loss: 0.87907 timestamp: 1654956450.827939 iteration: 53890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08623 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.1454 L1 loss: 0.0000e+00 L2 loss: 0.6046 Learning rate: 0.002 Mask loss: 0.19347 RPN box loss: 0.00972 RPN score loss: 0.00673 RPN total loss: 0.01645 Total loss: 0.95992 timestamp: 1654956454.1574311 iteration: 53895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.13982 L1 loss: 0.0000e+00 L2 loss: 0.60459 Learning rate: 0.002 Mask loss: 0.14354 RPN box loss: 0.03229 RPN score loss: 0.00383 RPN total loss: 0.03612 Total loss: 0.92407 timestamp: 1654956457.471461 iteration: 53900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09141 FastRCNN class loss: 0.06341 FastRCNN total loss: 0.15482 L1 loss: 0.0000e+00 L2 loss: 0.60458 Learning rate: 0.002 Mask loss: 0.1283 RPN box loss: 0.02868 RPN score loss: 0.00481 RPN total loss: 0.0335 Total loss: 0.92119 timestamp: 1654956460.6536415 iteration: 53905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10296 FastRCNN class loss: 0.06913 FastRCNN total loss: 0.17208 L1 loss: 0.0000e+00 L2 loss: 0.60457 Learning rate: 0.002 Mask loss: 0.10012 RPN box loss: 0.02001 RPN score loss: 0.00488 RPN total loss: 0.02489 Total loss: 0.90167 timestamp: 1654956463.9192905 iteration: 53910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10904 FastRCNN class loss: 0.09863 FastRCNN total loss: 0.20768 L1 loss: 0.0000e+00 L2 loss: 0.60456 Learning rate: 0.002 Mask loss: 0.1485 RPN box loss: 0.02011 RPN score loss: 0.00743 RPN total loss: 0.02754 Total loss: 0.98829 timestamp: 1654956467.2017617 iteration: 53915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1331 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.2173 L1 loss: 0.0000e+00 L2 loss: 0.60456 Learning rate: 0.002 Mask loss: 0.0937 RPN box loss: 0.00847 RPN score loss: 0.00464 RPN total loss: 0.01311 Total loss: 0.92867 timestamp: 1654956470.5351317 iteration: 53920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11226 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.16773 L1 loss: 0.0000e+00 L2 loss: 0.60455 Learning rate: 0.002 Mask loss: 0.16285 RPN box loss: 0.01127 RPN score loss: 0.00461 RPN total loss: 0.01587 Total loss: 0.95099 timestamp: 1654956473.6970694 iteration: 53925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08528 FastRCNN class loss: 0.06439 FastRCNN total loss: 0.14967 L1 loss: 0.0000e+00 L2 loss: 0.60454 Learning rate: 0.002 Mask loss: 0.11747 RPN box loss: 0.00778 RPN score loss: 0.0016 RPN total loss: 0.00937 Total loss: 0.88105 timestamp: 1654956477.036602 iteration: 53930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09593 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.15404 L1 loss: 0.0000e+00 L2 loss: 0.60453 Learning rate: 0.002 Mask loss: 0.08446 RPN box loss: 0.02732 RPN score loss: 0.00419 RPN total loss: 0.0315 Total loss: 0.87454 timestamp: 1654956480.1869829 iteration: 53935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.06508 FastRCNN total loss: 0.17754 L1 loss: 0.0000e+00 L2 loss: 0.60452 Learning rate: 0.002 Mask loss: 0.16975 RPN box loss: 0.0062 RPN score loss: 0.00478 RPN total loss: 0.01098 Total loss: 0.96279 timestamp: 1654956483.4294515 iteration: 53940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07787 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.14276 L1 loss: 0.0000e+00 L2 loss: 0.60451 Learning rate: 0.002 Mask loss: 0.12054 RPN box loss: 0.00877 RPN score loss: 0.00804 RPN total loss: 0.01681 Total loss: 0.88462 timestamp: 1654956486.5473676 iteration: 53945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10232 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.16993 L1 loss: 0.0000e+00 L2 loss: 0.6045 Learning rate: 0.002 Mask loss: 0.17254 RPN box loss: 0.01816 RPN score loss: 0.00162 RPN total loss: 0.01978 Total loss: 0.96675 timestamp: 1654956489.775991 iteration: 53950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10484 FastRCNN class loss: 0.11333 FastRCNN total loss: 0.21817 L1 loss: 0.0000e+00 L2 loss: 0.6045 Learning rate: 0.002 Mask loss: 0.12947 RPN box loss: 0.00898 RPN score loss: 0.00719 RPN total loss: 0.01617 Total loss: 0.9683 timestamp: 1654956493.0485802 iteration: 53955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09617 FastRCNN class loss: 0.0663 FastRCNN total loss: 0.16247 L1 loss: 0.0000e+00 L2 loss: 0.60449 Learning rate: 0.002 Mask loss: 0.15323 RPN box loss: 0.0122 RPN score loss: 0.00171 RPN total loss: 0.0139 Total loss: 0.93409 timestamp: 1654956496.2172327 iteration: 53960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.098 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.15329 L1 loss: 0.0000e+00 L2 loss: 0.60448 Learning rate: 0.002 Mask loss: 0.11646 RPN box loss: 0.01788 RPN score loss: 0.00687 RPN total loss: 0.02475 Total loss: 0.89897 timestamp: 1654956499.5345433 iteration: 53965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12068 FastRCNN class loss: 0.06812 FastRCNN total loss: 0.1888 L1 loss: 0.0000e+00 L2 loss: 0.60447 Learning rate: 0.002 Mask loss: 0.2249 RPN box loss: 0.01804 RPN score loss: 0.01184 RPN total loss: 0.02988 Total loss: 1.04804 timestamp: 1654956502.7708473 iteration: 53970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09225 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.15639 L1 loss: 0.0000e+00 L2 loss: 0.60446 Learning rate: 0.002 Mask loss: 0.16195 RPN box loss: 0.00768 RPN score loss: 0.00431 RPN total loss: 0.01198 Total loss: 0.93478 timestamp: 1654956506.117617 iteration: 53975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11172 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.18953 L1 loss: 0.0000e+00 L2 loss: 0.60445 Learning rate: 0.002 Mask loss: 0.13285 RPN box loss: 0.02018 RPN score loss: 0.01032 RPN total loss: 0.0305 Total loss: 0.95733 timestamp: 1654956509.3026752 iteration: 53980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08429 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.16094 L1 loss: 0.0000e+00 L2 loss: 0.60444 Learning rate: 0.002 Mask loss: 0.15441 RPN box loss: 0.02545 RPN score loss: 0.0087 RPN total loss: 0.03414 Total loss: 0.95394 timestamp: 1654956512.5610847 iteration: 53985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12695 FastRCNN class loss: 0.05021 FastRCNN total loss: 0.17716 L1 loss: 0.0000e+00 L2 loss: 0.60444 Learning rate: 0.002 Mask loss: 0.08535 RPN box loss: 0.00786 RPN score loss: 0.00331 RPN total loss: 0.01117 Total loss: 0.87812 timestamp: 1654956515.7977488 iteration: 53990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13279 FastRCNN class loss: 0.09159 FastRCNN total loss: 0.22438 L1 loss: 0.0000e+00 L2 loss: 0.60443 Learning rate: 0.002 Mask loss: 0.14887 RPN box loss: 0.00817 RPN score loss: 0.00472 RPN total loss: 0.01289 Total loss: 0.99057 timestamp: 1654956518.9939327 iteration: 53995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04969 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.1103 L1 loss: 0.0000e+00 L2 loss: 0.60442 Learning rate: 0.002 Mask loss: 0.1006 RPN box loss: 0.01405 RPN score loss: 0.00703 RPN total loss: 0.02108 Total loss: 0.83639 timestamp: 1654956522.2859583 iteration: 54000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14971 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.22134 L1 loss: 0.0000e+00 L2 loss: 0.60441 Learning rate: 0.002 Mask loss: 0.10686 RPN box loss: 0.01198 RPN score loss: 0.00257 RPN total loss: 0.01456 Total loss: 0.94717 timestamp: 1654956525.5508142 iteration: 54005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09124 FastRCNN class loss: 0.12786 FastRCNN total loss: 0.2191 L1 loss: 0.0000e+00 L2 loss: 0.6044 Learning rate: 0.002 Mask loss: 0.1181 RPN box loss: 0.00696 RPN score loss: 0.00566 RPN total loss: 0.01262 Total loss: 0.95422 timestamp: 1654956528.8452702 iteration: 54010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08805 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.16613 L1 loss: 0.0000e+00 L2 loss: 0.60439 Learning rate: 0.002 Mask loss: 0.1416 RPN box loss: 0.01941 RPN score loss: 0.0067 RPN total loss: 0.02611 Total loss: 0.93822 timestamp: 1654956532.0403874 iteration: 54015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10159 FastRCNN class loss: 0.04733 FastRCNN total loss: 0.14892 L1 loss: 0.0000e+00 L2 loss: 0.60438 Learning rate: 0.002 Mask loss: 0.09152 RPN box loss: 0.0098 RPN score loss: 0.00867 RPN total loss: 0.01848 Total loss: 0.86329 timestamp: 1654956535.2597055 iteration: 54020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08451 FastRCNN class loss: 0.0651 FastRCNN total loss: 0.14962 L1 loss: 0.0000e+00 L2 loss: 0.60436 Learning rate: 0.002 Mask loss: 0.134 RPN box loss: 0.04923 RPN score loss: 0.00678 RPN total loss: 0.05601 Total loss: 0.94399 timestamp: 1654956538.4739 iteration: 54025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10845 FastRCNN class loss: 0.05 FastRCNN total loss: 0.15845 L1 loss: 0.0000e+00 L2 loss: 0.60436 Learning rate: 0.002 Mask loss: 0.12729 RPN box loss: 0.01331 RPN score loss: 0.00565 RPN total loss: 0.01896 Total loss: 0.90905 timestamp: 1654956541.848791 iteration: 54030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10444 FastRCNN class loss: 0.08221 FastRCNN total loss: 0.18665 L1 loss: 0.0000e+00 L2 loss: 0.60435 Learning rate: 0.002 Mask loss: 0.15539 RPN box loss: 0.00892 RPN score loss: 0.00334 RPN total loss: 0.01227 Total loss: 0.95865 timestamp: 1654956545.0352952 iteration: 54035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10728 FastRCNN class loss: 0.07793 FastRCNN total loss: 0.18521 L1 loss: 0.0000e+00 L2 loss: 0.60434 Learning rate: 0.002 Mask loss: 0.12625 RPN box loss: 0.0223 RPN score loss: 0.00274 RPN total loss: 0.02504 Total loss: 0.94084 timestamp: 1654956548.3210683 iteration: 54040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14023 FastRCNN class loss: 0.1099 FastRCNN total loss: 0.25013 L1 loss: 0.0000e+00 L2 loss: 0.60434 Learning rate: 0.002 Mask loss: 0.20499 RPN box loss: 0.01939 RPN score loss: 0.01372 RPN total loss: 0.0331 Total loss: 1.09256 timestamp: 1654956551.4884307 iteration: 54045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0727 FastRCNN class loss: 0.04771 FastRCNN total loss: 0.12042 L1 loss: 0.0000e+00 L2 loss: 0.60433 Learning rate: 0.002 Mask loss: 0.18721 RPN box loss: 0.01252 RPN score loss: 0.00531 RPN total loss: 0.01782 Total loss: 0.92978 timestamp: 1654956554.7282085 iteration: 54050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05317 FastRCNN class loss: 0.04168 FastRCNN total loss: 0.09485 L1 loss: 0.0000e+00 L2 loss: 0.60432 Learning rate: 0.002 Mask loss: 0.09567 RPN box loss: 0.00604 RPN score loss: 0.00218 RPN total loss: 0.00822 Total loss: 0.80306 timestamp: 1654956557.8737462 iteration: 54055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.04896 FastRCNN total loss: 0.12981 L1 loss: 0.0000e+00 L2 loss: 0.60431 Learning rate: 0.002 Mask loss: 0.12471 RPN box loss: 0.03027 RPN score loss: 0.006 RPN total loss: 0.03627 Total loss: 0.8951 timestamp: 1654956561.113218 iteration: 54060 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17081 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.25159 L1 loss: 0.0000e+00 L2 loss: 0.6043 Learning rate: 0.002 Mask loss: 0.13014 RPN box loss: 0.02308 RPN score loss: 0.00399 RPN total loss: 0.02707 Total loss: 1.01309 timestamp: 1654956564.437814 iteration: 54065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09659 FastRCNN class loss: 0.05315 FastRCNN total loss: 0.14974 L1 loss: 0.0000e+00 L2 loss: 0.60429 Learning rate: 0.002 Mask loss: 0.12634 RPN box loss: 0.01287 RPN score loss: 0.00214 RPN total loss: 0.01501 Total loss: 0.89538 timestamp: 1654956567.661335 iteration: 54070 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08184 FastRCNN class loss: 0.04703 FastRCNN total loss: 0.12887 L1 loss: 0.0000e+00 L2 loss: 0.60428 Learning rate: 0.002 Mask loss: 0.13708 RPN box loss: 0.00533 RPN score loss: 0.00408 RPN total loss: 0.00941 Total loss: 0.87964 timestamp: 1654956570.9921346 iteration: 54075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05924 FastRCNN class loss: 0.05486 FastRCNN total loss: 0.1141 L1 loss: 0.0000e+00 L2 loss: 0.60427 Learning rate: 0.002 Mask loss: 0.14065 RPN box loss: 0.01061 RPN score loss: 0.005 RPN total loss: 0.0156 Total loss: 0.87462 timestamp: 1654956574.2005136 iteration: 54080 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.15207 L1 loss: 0.0000e+00 L2 loss: 0.60426 Learning rate: 0.002 Mask loss: 0.15125 RPN box loss: 0.01351 RPN score loss: 0.0038 RPN total loss: 0.01731 Total loss: 0.92489 timestamp: 1654956577.6148074 iteration: 54085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14605 FastRCNN class loss: 0.10717 FastRCNN total loss: 0.25322 L1 loss: 0.0000e+00 L2 loss: 0.60425 Learning rate: 0.002 Mask loss: 0.19618 RPN box loss: 0.0265 RPN score loss: 0.00625 RPN total loss: 0.03275 Total loss: 1.0864 timestamp: 1654956580.8063462 iteration: 54090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.08048 FastRCNN total loss: 0.1699 L1 loss: 0.0000e+00 L2 loss: 0.60425 Learning rate: 0.002 Mask loss: 0.13326 RPN box loss: 0.00906 RPN score loss: 0.00465 RPN total loss: 0.01371 Total loss: 0.92111 timestamp: 1654956584.223595 iteration: 54095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07516 FastRCNN class loss: 0.08468 FastRCNN total loss: 0.15983 L1 loss: 0.0000e+00 L2 loss: 0.60424 Learning rate: 0.002 Mask loss: 0.10347 RPN box loss: 0.00704 RPN score loss: 0.00155 RPN total loss: 0.00858 Total loss: 0.87612 timestamp: 1654956587.4076574 iteration: 54100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.16364 L1 loss: 0.0000e+00 L2 loss: 0.60423 Learning rate: 0.002 Mask loss: 0.11747 RPN box loss: 0.02372 RPN score loss: 0.00685 RPN total loss: 0.03056 Total loss: 0.9159 timestamp: 1654956590.712993 iteration: 54105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08509 FastRCNN class loss: 0.0585 FastRCNN total loss: 0.14359 L1 loss: 0.0000e+00 L2 loss: 0.60422 Learning rate: 0.002 Mask loss: 0.15247 RPN box loss: 0.01064 RPN score loss: 0.00408 RPN total loss: 0.01473 Total loss: 0.91501 timestamp: 1654956594.0088718 iteration: 54110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11971 FastRCNN class loss: 0.07202 FastRCNN total loss: 0.19174 L1 loss: 0.0000e+00 L2 loss: 0.60422 Learning rate: 0.002 Mask loss: 0.13775 RPN box loss: 0.00839 RPN score loss: 0.00571 RPN total loss: 0.01411 Total loss: 0.94781 timestamp: 1654956597.1901555 iteration: 54115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10445 FastRCNN class loss: 0.09465 FastRCNN total loss: 0.1991 L1 loss: 0.0000e+00 L2 loss: 0.60421 Learning rate: 0.002 Mask loss: 0.12656 RPN box loss: 0.01505 RPN score loss: 0.00738 RPN total loss: 0.02243 Total loss: 0.95229 timestamp: 1654956600.5035887 iteration: 54120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.06827 FastRCNN total loss: 0.20083 L1 loss: 0.0000e+00 L2 loss: 0.6042 Learning rate: 0.002 Mask loss: 0.15446 RPN box loss: 0.01409 RPN score loss: 0.00937 RPN total loss: 0.02346 Total loss: 0.98295 timestamp: 1654956603.6485178 iteration: 54125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16037 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.22726 L1 loss: 0.0000e+00 L2 loss: 0.60419 Learning rate: 0.002 Mask loss: 0.11411 RPN box loss: 0.02602 RPN score loss: 0.00628 RPN total loss: 0.0323 Total loss: 0.97786 timestamp: 1654956606.8750672 iteration: 54130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12364 FastRCNN class loss: 0.16131 FastRCNN total loss: 0.28495 L1 loss: 0.0000e+00 L2 loss: 0.60418 Learning rate: 0.002 Mask loss: 0.24717 RPN box loss: 0.03196 RPN score loss: 0.07319 RPN total loss: 0.10516 Total loss: 1.24145 timestamp: 1654956610.0272455 iteration: 54135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03611 FastRCNN class loss: 0.04649 FastRCNN total loss: 0.0826 L1 loss: 0.0000e+00 L2 loss: 0.60417 Learning rate: 0.002 Mask loss: 0.11317 RPN box loss: 0.03079 RPN score loss: 0.00204 RPN total loss: 0.03282 Total loss: 0.83276 timestamp: 1654956613.3862484 iteration: 54140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13954 FastRCNN class loss: 0.05525 FastRCNN total loss: 0.1948 L1 loss: 0.0000e+00 L2 loss: 0.60416 Learning rate: 0.002 Mask loss: 0.11403 RPN box loss: 0.00923 RPN score loss: 0.00302 RPN total loss: 0.01225 Total loss: 0.92523 timestamp: 1654956616.5142612 iteration: 54145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1033 FastRCNN class loss: 0.06376 FastRCNN total loss: 0.16706 L1 loss: 0.0000e+00 L2 loss: 0.60415 Learning rate: 0.002 Mask loss: 0.12703 RPN box loss: 0.04286 RPN score loss: 0.01143 RPN total loss: 0.05428 Total loss: 0.95253 timestamp: 1654956620.0097866 iteration: 54150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13658 FastRCNN class loss: 0.06924 FastRCNN total loss: 0.20581 L1 loss: 0.0000e+00 L2 loss: 0.60414 Learning rate: 0.002 Mask loss: 0.15072 RPN box loss: 0.02122 RPN score loss: 0.00667 RPN total loss: 0.02789 Total loss: 0.98857 timestamp: 1654956623.192089 iteration: 54155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.06937 FastRCNN total loss: 0.15854 L1 loss: 0.0000e+00 L2 loss: 0.60414 Learning rate: 0.002 Mask loss: 0.14645 RPN box loss: 0.02447 RPN score loss: 0.00108 RPN total loss: 0.02555 Total loss: 0.93468 timestamp: 1654956626.490932 iteration: 54160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05742 FastRCNN class loss: 0.05042 FastRCNN total loss: 0.10784 L1 loss: 0.0000e+00 L2 loss: 0.60413 Learning rate: 0.002 Mask loss: 0.07746 RPN box loss: 0.00877 RPN score loss: 0.00327 RPN total loss: 0.01205 Total loss: 0.80147 timestamp: 1654956629.7586646 iteration: 54165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09019 FastRCNN class loss: 0.04385 FastRCNN total loss: 0.13404 L1 loss: 0.0000e+00 L2 loss: 0.60412 Learning rate: 0.002 Mask loss: 0.1598 RPN box loss: 0.01635 RPN score loss: 0.00857 RPN total loss: 0.02492 Total loss: 0.92288 timestamp: 1654956632.9770885 iteration: 54170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13608 FastRCNN class loss: 0.07655 FastRCNN total loss: 0.21263 L1 loss: 0.0000e+00 L2 loss: 0.60411 Learning rate: 0.002 Mask loss: 0.16238 RPN box loss: 0.01114 RPN score loss: 0.0095 RPN total loss: 0.02064 Total loss: 0.99975 timestamp: 1654956636.273422 iteration: 54175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05927 FastRCNN class loss: 0.05258 FastRCNN total loss: 0.11185 L1 loss: 0.0000e+00 L2 loss: 0.6041 Learning rate: 0.002 Mask loss: 0.11262 RPN box loss: 0.00927 RPN score loss: 0.0051 RPN total loss: 0.01437 Total loss: 0.84294 timestamp: 1654956639.4465356 iteration: 54180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14087 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.19274 L1 loss: 0.0000e+00 L2 loss: 0.60409 Learning rate: 0.002 Mask loss: 0.15259 RPN box loss: 0.00746 RPN score loss: 0.00516 RPN total loss: 0.01262 Total loss: 0.96204 timestamp: 1654956642.736615 iteration: 54185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08595 FastRCNN class loss: 0.03139 FastRCNN total loss: 0.11734 L1 loss: 0.0000e+00 L2 loss: 0.60408 Learning rate: 0.002 Mask loss: 0.13135 RPN box loss: 0.00278 RPN score loss: 0.00099 RPN total loss: 0.00377 Total loss: 0.85654 timestamp: 1654956645.9599557 iteration: 54190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10219 FastRCNN class loss: 0.09126 FastRCNN total loss: 0.19345 L1 loss: 0.0000e+00 L2 loss: 0.60407 Learning rate: 0.002 Mask loss: 0.14847 RPN box loss: 0.01491 RPN score loss: 0.01002 RPN total loss: 0.02493 Total loss: 0.97092 timestamp: 1654956649.3898027 iteration: 54195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14768 FastRCNN class loss: 0.12295 FastRCNN total loss: 0.27064 L1 loss: 0.0000e+00 L2 loss: 0.60407 Learning rate: 0.002 Mask loss: 0.16619 RPN box loss: 0.03527 RPN score loss: 0.00525 RPN total loss: 0.04052 Total loss: 1.08141 timestamp: 1654956652.6138158 iteration: 54200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08819 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.16299 L1 loss: 0.0000e+00 L2 loss: 0.60406 Learning rate: 0.002 Mask loss: 0.11773 RPN box loss: 0.01717 RPN score loss: 0.02331 RPN total loss: 0.04048 Total loss: 0.92526 timestamp: 1654956655.925758 iteration: 54205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09266 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.16256 L1 loss: 0.0000e+00 L2 loss: 0.60405 Learning rate: 0.002 Mask loss: 0.12993 RPN box loss: 0.0089 RPN score loss: 0.00515 RPN total loss: 0.01405 Total loss: 0.91059 timestamp: 1654956659.1012855 iteration: 54210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11239 FastRCNN class loss: 0.04866 FastRCNN total loss: 0.16105 L1 loss: 0.0000e+00 L2 loss: 0.60404 Learning rate: 0.002 Mask loss: 0.09258 RPN box loss: 0.01292 RPN score loss: 0.00701 RPN total loss: 0.01993 Total loss: 0.8776 timestamp: 1654956662.3620064 iteration: 54215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05779 FastRCNN class loss: 0.04552 FastRCNN total loss: 0.10331 L1 loss: 0.0000e+00 L2 loss: 0.60403 Learning rate: 0.002 Mask loss: 0.151 RPN box loss: 0.00308 RPN score loss: 0.00271 RPN total loss: 0.00579 Total loss: 0.86414 timestamp: 1654956665.6309006 iteration: 54220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07698 FastRCNN class loss: 0.04403 FastRCNN total loss: 0.12101 L1 loss: 0.0000e+00 L2 loss: 0.60402 Learning rate: 0.002 Mask loss: 0.11306 RPN box loss: 0.01095 RPN score loss: 0.00063 RPN total loss: 0.01159 Total loss: 0.84968 timestamp: 1654956668.7960818 iteration: 54225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10567 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.16187 L1 loss: 0.0000e+00 L2 loss: 0.60401 Learning rate: 0.002 Mask loss: 0.10635 RPN box loss: 0.02051 RPN score loss: 0.00699 RPN total loss: 0.0275 Total loss: 0.89974 timestamp: 1654956672.2053232 iteration: 54230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12183 FastRCNN class loss: 0.07146 FastRCNN total loss: 0.19328 L1 loss: 0.0000e+00 L2 loss: 0.604 Learning rate: 0.002 Mask loss: 0.10572 RPN box loss: 0.00551 RPN score loss: 0.00348 RPN total loss: 0.00899 Total loss: 0.912 timestamp: 1654956675.3365953 iteration: 54235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17123 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.23299 L1 loss: 0.0000e+00 L2 loss: 0.60399 Learning rate: 0.002 Mask loss: 0.15352 RPN box loss: 0.01331 RPN score loss: 0.00299 RPN total loss: 0.0163 Total loss: 1.00681 timestamp: 1654956678.548887 iteration: 54240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0852 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.16477 L1 loss: 0.0000e+00 L2 loss: 0.60399 Learning rate: 0.002 Mask loss: 0.16263 RPN box loss: 0.01724 RPN score loss: 0.00174 RPN total loss: 0.01898 Total loss: 0.95037 timestamp: 1654956681.7720194 iteration: 54245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05849 FastRCNN class loss: 0.03608 FastRCNN total loss: 0.09457 L1 loss: 0.0000e+00 L2 loss: 0.60398 Learning rate: 0.002 Mask loss: 0.11817 RPN box loss: 0.01511 RPN score loss: 0.00728 RPN total loss: 0.0224 Total loss: 0.83912 timestamp: 1654956685.0406864 iteration: 54250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07312 FastRCNN class loss: 0.06628 FastRCNN total loss: 0.13941 L1 loss: 0.0000e+00 L2 loss: 0.60397 Learning rate: 0.002 Mask loss: 0.11139 RPN box loss: 0.00578 RPN score loss: 0.00494 RPN total loss: 0.01072 Total loss: 0.86548 timestamp: 1654956688.1632643 iteration: 54255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11866 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.17808 L1 loss: 0.0000e+00 L2 loss: 0.60396 Learning rate: 0.002 Mask loss: 0.09145 RPN box loss: 0.00934 RPN score loss: 0.00673 RPN total loss: 0.01607 Total loss: 0.88956 timestamp: 1654956691.440462 iteration: 54260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06654 FastRCNN class loss: 0.08055 FastRCNN total loss: 0.14709 L1 loss: 0.0000e+00 L2 loss: 0.60395 Learning rate: 0.002 Mask loss: 0.14878 RPN box loss: 0.00948 RPN score loss: 0.00127 RPN total loss: 0.01075 Total loss: 0.91058 timestamp: 1654956694.6623564 iteration: 54265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07578 FastRCNN class loss: 0.09537 FastRCNN total loss: 0.17115 L1 loss: 0.0000e+00 L2 loss: 0.60395 Learning rate: 0.002 Mask loss: 0.1048 RPN box loss: 0.01435 RPN score loss: 0.00946 RPN total loss: 0.0238 Total loss: 0.9037 timestamp: 1654956697.9958303 iteration: 54270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09633 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.16576 L1 loss: 0.0000e+00 L2 loss: 0.60394 Learning rate: 0.002 Mask loss: 0.13897 RPN box loss: 0.01331 RPN score loss: 0.00526 RPN total loss: 0.01857 Total loss: 0.92723 timestamp: 1654956701.379012 iteration: 54275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13898 FastRCNN class loss: 0.06232 FastRCNN total loss: 0.2013 L1 loss: 0.0000e+00 L2 loss: 0.60393 Learning rate: 0.002 Mask loss: 0.12027 RPN box loss: 0.00896 RPN score loss: 0.00136 RPN total loss: 0.01032 Total loss: 0.93582 timestamp: 1654956704.601373 iteration: 54280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07414 FastRCNN class loss: 0.04031 FastRCNN total loss: 0.11445 L1 loss: 0.0000e+00 L2 loss: 0.60392 Learning rate: 0.002 Mask loss: 0.12947 RPN box loss: 0.01109 RPN score loss: 0.00236 RPN total loss: 0.01346 Total loss: 0.8613 timestamp: 1654956707.8613746 iteration: 54285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.092 FastRCNN class loss: 0.08767 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.60391 Learning rate: 0.002 Mask loss: 0.18083 RPN box loss: 0.02319 RPN score loss: 0.00137 RPN total loss: 0.02456 Total loss: 0.98896 timestamp: 1654956711.2017457 iteration: 54290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07751 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.12756 L1 loss: 0.0000e+00 L2 loss: 0.6039 Learning rate: 0.002 Mask loss: 0.1513 RPN box loss: 0.01373 RPN score loss: 0.00189 RPN total loss: 0.01561 Total loss: 0.89838 timestamp: 1654956714.5928228 iteration: 54295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09027 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.15104 L1 loss: 0.0000e+00 L2 loss: 0.6039 Learning rate: 0.002 Mask loss: 0.12474 RPN box loss: 0.01691 RPN score loss: 0.00286 RPN total loss: 0.01977 Total loss: 0.89944 timestamp: 1654956717.8822129 iteration: 54300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08964 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.15674 L1 loss: 0.0000e+00 L2 loss: 0.60389 Learning rate: 0.002 Mask loss: 0.15861 RPN box loss: 0.01408 RPN score loss: 0.0056 RPN total loss: 0.01967 Total loss: 0.93892 timestamp: 1654956721.1496894 iteration: 54305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05668 FastRCNN class loss: 0.06678 FastRCNN total loss: 0.12346 L1 loss: 0.0000e+00 L2 loss: 0.60388 Learning rate: 0.002 Mask loss: 0.10082 RPN box loss: 0.00543 RPN score loss: 0.0021 RPN total loss: 0.00754 Total loss: 0.8357 timestamp: 1654956724.3293233 iteration: 54310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10263 FastRCNN class loss: 0.10154 FastRCNN total loss: 0.20417 L1 loss: 0.0000e+00 L2 loss: 0.60387 Learning rate: 0.002 Mask loss: 0.12848 RPN box loss: 0.01914 RPN score loss: 0.00243 RPN total loss: 0.02157 Total loss: 0.95809 timestamp: 1654956727.652243 iteration: 54315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08876 FastRCNN class loss: 0.07324 FastRCNN total loss: 0.16201 L1 loss: 0.0000e+00 L2 loss: 0.60386 Learning rate: 0.002 Mask loss: 0.15335 RPN box loss: 0.03701 RPN score loss: 0.00494 RPN total loss: 0.04195 Total loss: 0.96116 timestamp: 1654956730.9060254 iteration: 54320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12927 FastRCNN class loss: 0.08474 FastRCNN total loss: 0.21402 L1 loss: 0.0000e+00 L2 loss: 0.60385 Learning rate: 0.002 Mask loss: 0.1397 RPN box loss: 0.02927 RPN score loss: 0.01385 RPN total loss: 0.04313 Total loss: 1.00069 timestamp: 1654956734.1784117 iteration: 54325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13213 FastRCNN class loss: 0.0987 FastRCNN total loss: 0.23083 L1 loss: 0.0000e+00 L2 loss: 0.60384 Learning rate: 0.002 Mask loss: 0.11332 RPN box loss: 0.01724 RPN score loss: 0.01904 RPN total loss: 0.03628 Total loss: 0.98427 timestamp: 1654956737.3770432 iteration: 54330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.16741 L1 loss: 0.0000e+00 L2 loss: 0.60383 Learning rate: 0.002 Mask loss: 0.13757 RPN box loss: 0.0233 RPN score loss: 0.00428 RPN total loss: 0.02757 Total loss: 0.93639 timestamp: 1654956740.5239446 iteration: 54335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1348 FastRCNN class loss: 0.0787 FastRCNN total loss: 0.2135 L1 loss: 0.0000e+00 L2 loss: 0.60382 Learning rate: 0.002 Mask loss: 0.12728 RPN box loss: 0.02541 RPN score loss: 0.00219 RPN total loss: 0.0276 Total loss: 0.9722 timestamp: 1654956743.8270671 iteration: 54340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09607 FastRCNN class loss: 0.03287 FastRCNN total loss: 0.12894 L1 loss: 0.0000e+00 L2 loss: 0.60381 Learning rate: 0.002 Mask loss: 0.09047 RPN box loss: 0.01197 RPN score loss: 0.00176 RPN total loss: 0.01374 Total loss: 0.83696 timestamp: 1654956747.0218618 iteration: 54345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07236 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.13182 L1 loss: 0.0000e+00 L2 loss: 0.6038 Learning rate: 0.002 Mask loss: 0.08743 RPN box loss: 0.01376 RPN score loss: 0.00375 RPN total loss: 0.01751 Total loss: 0.84056 timestamp: 1654956750.4349189 iteration: 54350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13053 FastRCNN class loss: 0.10777 FastRCNN total loss: 0.2383 L1 loss: 0.0000e+00 L2 loss: 0.60379 Learning rate: 0.002 Mask loss: 0.18582 RPN box loss: 0.02306 RPN score loss: 0.00491 RPN total loss: 0.02797 Total loss: 1.05588 timestamp: 1654956753.6870987 iteration: 54355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09048 FastRCNN class loss: 0.05314 FastRCNN total loss: 0.14362 L1 loss: 0.0000e+00 L2 loss: 0.60378 Learning rate: 0.002 Mask loss: 0.16141 RPN box loss: 0.01009 RPN score loss: 0.00423 RPN total loss: 0.01432 Total loss: 0.92312 timestamp: 1654956757.0363114 iteration: 54360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07034 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.11991 L1 loss: 0.0000e+00 L2 loss: 0.60378 Learning rate: 0.002 Mask loss: 0.1049 RPN box loss: 0.01278 RPN score loss: 0.00177 RPN total loss: 0.01455 Total loss: 0.84313 timestamp: 1654956760.2663832 iteration: 54365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10714 FastRCNN class loss: 0.04315 FastRCNN total loss: 0.15029 L1 loss: 0.0000e+00 L2 loss: 0.60377 Learning rate: 0.002 Mask loss: 0.1116 RPN box loss: 0.0185 RPN score loss: 0.00603 RPN total loss: 0.02453 Total loss: 0.89018 timestamp: 1654956763.5267422 iteration: 54370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09637 FastRCNN class loss: 0.0891 FastRCNN total loss: 0.18547 L1 loss: 0.0000e+00 L2 loss: 0.60376 Learning rate: 0.002 Mask loss: 0.14754 RPN box loss: 0.01363 RPN score loss: 0.00372 RPN total loss: 0.01736 Total loss: 0.95412 timestamp: 1654956766.5840504 iteration: 54375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1432 FastRCNN class loss: 0.08806 FastRCNN total loss: 0.23125 L1 loss: 0.0000e+00 L2 loss: 0.60375 Learning rate: 0.002 Mask loss: 0.1692 RPN box loss: 0.01404 RPN score loss: 0.00675 RPN total loss: 0.02079 Total loss: 1.02499 timestamp: 1654956769.83579 iteration: 54380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05609 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.11525 L1 loss: 0.0000e+00 L2 loss: 0.60374 Learning rate: 0.002 Mask loss: 0.10687 RPN box loss: 0.00544 RPN score loss: 0.00761 RPN total loss: 0.01306 Total loss: 0.83892 timestamp: 1654956773.2023108 iteration: 54385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09359 FastRCNN class loss: 0.06857 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 0.60374 Learning rate: 0.002 Mask loss: 0.14444 RPN box loss: 0.01132 RPN score loss: 0.00258 RPN total loss: 0.0139 Total loss: 0.92424 timestamp: 1654956776.3725462 iteration: 54390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07548 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.13678 L1 loss: 0.0000e+00 L2 loss: 0.60373 Learning rate: 0.002 Mask loss: 0.10828 RPN box loss: 0.01143 RPN score loss: 0.00263 RPN total loss: 0.01406 Total loss: 0.86286 timestamp: 1654956779.6368737 iteration: 54395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11824 FastRCNN class loss: 0.09438 FastRCNN total loss: 0.21261 L1 loss: 0.0000e+00 L2 loss: 0.60373 Learning rate: 0.002 Mask loss: 0.15525 RPN box loss: 0.021 RPN score loss: 0.01449 RPN total loss: 0.03548 Total loss: 1.00707 timestamp: 1654956782.817024 iteration: 54400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08492 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.15629 L1 loss: 0.0000e+00 L2 loss: 0.60372 Learning rate: 0.002 Mask loss: 0.10806 RPN box loss: 0.01542 RPN score loss: 0.00191 RPN total loss: 0.01733 Total loss: 0.88541 timestamp: 1654956786.137661 iteration: 54405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09393 FastRCNN class loss: 0.05293 FastRCNN total loss: 0.14687 L1 loss: 0.0000e+00 L2 loss: 0.60371 Learning rate: 0.002 Mask loss: 0.21121 RPN box loss: 0.01766 RPN score loss: 0.00214 RPN total loss: 0.0198 Total loss: 0.98158 timestamp: 1654956789.3012109 iteration: 54410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10896 FastRCNN class loss: 0.07795 FastRCNN total loss: 0.1869 L1 loss: 0.0000e+00 L2 loss: 0.6037 Learning rate: 0.002 Mask loss: 0.17015 RPN box loss: 0.01414 RPN score loss: 0.00416 RPN total loss: 0.0183 Total loss: 0.97905 timestamp: 1654956792.5650117 iteration: 54415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08844 FastRCNN class loss: 0.07232 FastRCNN total loss: 0.16076 L1 loss: 0.0000e+00 L2 loss: 0.60369 Learning rate: 0.002 Mask loss: 0.18322 RPN box loss: 0.03139 RPN score loss: 0.00917 RPN total loss: 0.04056 Total loss: 0.98823 timestamp: 1654956795.7782779 iteration: 54420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08071 FastRCNN class loss: 0.05036 FastRCNN total loss: 0.13107 L1 loss: 0.0000e+00 L2 loss: 0.60368 Learning rate: 0.002 Mask loss: 0.1042 RPN box loss: 0.00462 RPN score loss: 0.00116 RPN total loss: 0.00577 Total loss: 0.84473 timestamp: 1654956799.1459832 iteration: 54425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06106 FastRCNN class loss: 0.05461 FastRCNN total loss: 0.11567 L1 loss: 0.0000e+00 L2 loss: 0.60367 Learning rate: 0.002 Mask loss: 0.1179 RPN box loss: 0.0123 RPN score loss: 0.00516 RPN total loss: 0.01747 Total loss: 0.8547 timestamp: 1654956802.3451834 iteration: 54430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13676 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.20034 L1 loss: 0.0000e+00 L2 loss: 0.60366 Learning rate: 0.002 Mask loss: 0.11395 RPN box loss: 0.01133 RPN score loss: 0.00536 RPN total loss: 0.0167 Total loss: 0.93465 timestamp: 1654956805.6216521 iteration: 54435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09983 FastRCNN class loss: 0.06041 FastRCNN total loss: 0.16024 L1 loss: 0.0000e+00 L2 loss: 0.60365 Learning rate: 0.002 Mask loss: 0.15688 RPN box loss: 0.02659 RPN score loss: 0.0081 RPN total loss: 0.03469 Total loss: 0.95546 timestamp: 1654956808.8323267 iteration: 54440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09107 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.16928 L1 loss: 0.0000e+00 L2 loss: 0.60364 Learning rate: 0.002 Mask loss: 0.13467 RPN box loss: 0.01221 RPN score loss: 0.00721 RPN total loss: 0.01942 Total loss: 0.92701 timestamp: 1654956812.0759358 iteration: 54445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10661 FastRCNN class loss: 0.08501 FastRCNN total loss: 0.19163 L1 loss: 0.0000e+00 L2 loss: 0.60363 Learning rate: 0.002 Mask loss: 0.15263 RPN box loss: 0.02429 RPN score loss: 0.00821 RPN total loss: 0.0325 Total loss: 0.98039 timestamp: 1654956815.3575478 iteration: 54450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05471 FastRCNN class loss: 0.07714 FastRCNN total loss: 0.13185 L1 loss: 0.0000e+00 L2 loss: 0.60362 Learning rate: 0.002 Mask loss: 0.11973 RPN box loss: 0.03108 RPN score loss: 0.0145 RPN total loss: 0.04558 Total loss: 0.90079 timestamp: 1654956818.569739 iteration: 54455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08096 FastRCNN class loss: 0.05511 FastRCNN total loss: 0.13607 L1 loss: 0.0000e+00 L2 loss: 0.60362 Learning rate: 0.002 Mask loss: 0.15999 RPN box loss: 0.01167 RPN score loss: 0.01467 RPN total loss: 0.02633 Total loss: 0.92601 timestamp: 1654956821.9013352 iteration: 54460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12671 FastRCNN class loss: 0.07336 FastRCNN total loss: 0.20007 L1 loss: 0.0000e+00 L2 loss: 0.60361 Learning rate: 0.002 Mask loss: 0.1593 RPN box loss: 0.00664 RPN score loss: 0.00436 RPN total loss: 0.011 Total loss: 0.97399 timestamp: 1654956825.0961368 iteration: 54465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10995 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.18165 L1 loss: 0.0000e+00 L2 loss: 0.60361 Learning rate: 0.002 Mask loss: 0.11429 RPN box loss: 0.02179 RPN score loss: 0.00383 RPN total loss: 0.02563 Total loss: 0.92518 timestamp: 1654956828.4130468 iteration: 54470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11203 FastRCNN class loss: 0.08355 FastRCNN total loss: 0.19558 L1 loss: 0.0000e+00 L2 loss: 0.6036 Learning rate: 0.002 Mask loss: 0.17306 RPN box loss: 0.01305 RPN score loss: 0.0053 RPN total loss: 0.01834 Total loss: 0.99058 timestamp: 1654956831.6398568 iteration: 54475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10527 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.1934 L1 loss: 0.0000e+00 L2 loss: 0.60358 Learning rate: 0.002 Mask loss: 0.13513 RPN box loss: 0.01235 RPN score loss: 0.00535 RPN total loss: 0.0177 Total loss: 0.94982 timestamp: 1654956834.831632 iteration: 54480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09241 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.15774 L1 loss: 0.0000e+00 L2 loss: 0.60357 Learning rate: 0.002 Mask loss: 0.15418 RPN box loss: 0.01485 RPN score loss: 0.00755 RPN total loss: 0.0224 Total loss: 0.93789 timestamp: 1654956838.0371227 iteration: 54485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07969 FastRCNN class loss: 0.04909 FastRCNN total loss: 0.12878 L1 loss: 0.0000e+00 L2 loss: 0.60356 Learning rate: 0.002 Mask loss: 0.07063 RPN box loss: 0.00969 RPN score loss: 0.00639 RPN total loss: 0.01608 Total loss: 0.81906 timestamp: 1654956841.3364174 iteration: 54490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05789 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.10788 L1 loss: 0.0000e+00 L2 loss: 0.60355 Learning rate: 0.002 Mask loss: 0.07565 RPN box loss: 0.00692 RPN score loss: 0.00213 RPN total loss: 0.00905 Total loss: 0.79613 timestamp: 1654956844.524147 iteration: 54495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06616 FastRCNN class loss: 0.04607 FastRCNN total loss: 0.11223 L1 loss: 0.0000e+00 L2 loss: 0.60355 Learning rate: 0.002 Mask loss: 0.10217 RPN box loss: 0.01873 RPN score loss: 0.00478 RPN total loss: 0.02351 Total loss: 0.84145 timestamp: 1654956847.836217 iteration: 54500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.05013 FastRCNN total loss: 0.13415 L1 loss: 0.0000e+00 L2 loss: 0.60354 Learning rate: 0.002 Mask loss: 0.10666 RPN box loss: 0.01046 RPN score loss: 0.00212 RPN total loss: 0.01259 Total loss: 0.85694 timestamp: 1654956851.1479266 iteration: 54505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08401 FastRCNN class loss: 0.08648 FastRCNN total loss: 0.1705 L1 loss: 0.0000e+00 L2 loss: 0.60354 Learning rate: 0.002 Mask loss: 0.16466 RPN box loss: 0.02062 RPN score loss: 0.00374 RPN total loss: 0.02436 Total loss: 0.96305 timestamp: 1654956854.3394823 iteration: 54510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10182 FastRCNN class loss: 0.06174 FastRCNN total loss: 0.16356 L1 loss: 0.0000e+00 L2 loss: 0.60353 Learning rate: 0.002 Mask loss: 0.17809 RPN box loss: 0.01405 RPN score loss: 0.00268 RPN total loss: 0.01673 Total loss: 0.96191 timestamp: 1654956857.6195943 iteration: 54515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13165 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.21087 L1 loss: 0.0000e+00 L2 loss: 0.60352 Learning rate: 0.002 Mask loss: 0.18978 RPN box loss: 0.01903 RPN score loss: 0.00787 RPN total loss: 0.0269 Total loss: 1.03107 timestamp: 1654956860.8293335 iteration: 54520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12669 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.18818 L1 loss: 0.0000e+00 L2 loss: 0.60351 Learning rate: 0.002 Mask loss: 0.13225 RPN box loss: 0.04629 RPN score loss: 0.00506 RPN total loss: 0.05134 Total loss: 0.97528 timestamp: 1654956864.1196823 iteration: 54525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.16316 L1 loss: 0.0000e+00 L2 loss: 0.6035 Learning rate: 0.002 Mask loss: 0.1665 RPN box loss: 0.01418 RPN score loss: 0.0013 RPN total loss: 0.01548 Total loss: 0.94864 timestamp: 1654956867.3046224 iteration: 54530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06353 FastRCNN class loss: 0.03484 FastRCNN total loss: 0.09836 L1 loss: 0.0000e+00 L2 loss: 0.60349 Learning rate: 0.002 Mask loss: 0.0781 RPN box loss: 0.00661 RPN score loss: 0.0008 RPN total loss: 0.00741 Total loss: 0.78737 timestamp: 1654956870.6266797 iteration: 54535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06841 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.1335 L1 loss: 0.0000e+00 L2 loss: 0.60348 Learning rate: 0.002 Mask loss: 0.10997 RPN box loss: 0.01925 RPN score loss: 0.00166 RPN total loss: 0.0209 Total loss: 0.86786 timestamp: 1654956873.8088858 iteration: 54540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08572 FastRCNN class loss: 0.11625 FastRCNN total loss: 0.20197 L1 loss: 0.0000e+00 L2 loss: 0.60348 Learning rate: 0.002 Mask loss: 0.17757 RPN box loss: 0.01625 RPN score loss: 0.01859 RPN total loss: 0.03484 Total loss: 1.01786 timestamp: 1654956877.0121717 iteration: 54545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07945 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.1525 L1 loss: 0.0000e+00 L2 loss: 0.60347 Learning rate: 0.002 Mask loss: 0.09225 RPN box loss: 0.00834 RPN score loss: 0.00475 RPN total loss: 0.0131 Total loss: 0.86131 timestamp: 1654956880.2456567 iteration: 54550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13096 FastRCNN class loss: 0.05221 FastRCNN total loss: 0.18317 L1 loss: 0.0000e+00 L2 loss: 0.60346 Learning rate: 0.002 Mask loss: 0.10512 RPN box loss: 0.0037 RPN score loss: 0.00246 RPN total loss: 0.00616 Total loss: 0.8979 timestamp: 1654956883.5203266 iteration: 54555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08333 FastRCNN class loss: 0.06944 FastRCNN total loss: 0.15277 L1 loss: 0.0000e+00 L2 loss: 0.60345 Learning rate: 0.002 Mask loss: 0.11928 RPN box loss: 0.01645 RPN score loss: 0.00245 RPN total loss: 0.0189 Total loss: 0.89439 timestamp: 1654956886.8564832 iteration: 54560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18054 FastRCNN class loss: 0.11745 FastRCNN total loss: 0.29799 L1 loss: 0.0000e+00 L2 loss: 0.60344 Learning rate: 0.002 Mask loss: 0.1953 RPN box loss: 0.01795 RPN score loss: 0.01044 RPN total loss: 0.02838 Total loss: 1.12512 timestamp: 1654956890.078103 iteration: 54565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06491 FastRCNN class loss: 0.08253 FastRCNN total loss: 0.14744 L1 loss: 0.0000e+00 L2 loss: 0.60344 Learning rate: 0.002 Mask loss: 0.14723 RPN box loss: 0.02095 RPN score loss: 0.009 RPN total loss: 0.02995 Total loss: 0.92806 timestamp: 1654956893.4408817 iteration: 54570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0743 FastRCNN class loss: 0.05661 FastRCNN total loss: 0.13091 L1 loss: 0.0000e+00 L2 loss: 0.60343 Learning rate: 0.002 Mask loss: 0.09226 RPN box loss: 0.05495 RPN score loss: 0.007 RPN total loss: 0.06196 Total loss: 0.88856 timestamp: 1654956896.6565623 iteration: 54575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09153 FastRCNN class loss: 0.06101 FastRCNN total loss: 0.15254 L1 loss: 0.0000e+00 L2 loss: 0.60342 Learning rate: 0.002 Mask loss: 0.13236 RPN box loss: 0.00863 RPN score loss: 0.00746 RPN total loss: 0.01609 Total loss: 0.90442 timestamp: 1654956899.992297 iteration: 54580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09475 FastRCNN class loss: 0.06085 FastRCNN total loss: 0.1556 L1 loss: 0.0000e+00 L2 loss: 0.60341 Learning rate: 0.002 Mask loss: 0.13977 RPN box loss: 0.01579 RPN score loss: 0.00482 RPN total loss: 0.02061 Total loss: 0.9194 timestamp: 1654956903.2081347 iteration: 54585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03795 FastRCNN class loss: 0.04286 FastRCNN total loss: 0.08081 L1 loss: 0.0000e+00 L2 loss: 0.6034 Learning rate: 0.002 Mask loss: 0.08592 RPN box loss: 0.0016 RPN score loss: 0.00313 RPN total loss: 0.00474 Total loss: 0.77486 timestamp: 1654956906.5518658 iteration: 54590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0487 FastRCNN class loss: 0.04607 FastRCNN total loss: 0.09477 L1 loss: 0.0000e+00 L2 loss: 0.60339 Learning rate: 0.002 Mask loss: 0.07622 RPN box loss: 0.00327 RPN score loss: 0.00185 RPN total loss: 0.00511 Total loss: 0.7795 timestamp: 1654956909.6968186 iteration: 54595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09044 FastRCNN class loss: 0.06928 FastRCNN total loss: 0.15972 L1 loss: 0.0000e+00 L2 loss: 0.60338 Learning rate: 0.002 Mask loss: 0.12452 RPN box loss: 0.00755 RPN score loss: 0.00489 RPN total loss: 0.01245 Total loss: 0.90008 timestamp: 1654956912.9444306 iteration: 54600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11505 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.18056 L1 loss: 0.0000e+00 L2 loss: 0.60338 Learning rate: 0.002 Mask loss: 0.11938 RPN box loss: 0.0092 RPN score loss: 0.0048 RPN total loss: 0.01399 Total loss: 0.91731 timestamp: 1654956916.1300614 iteration: 54605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07619 FastRCNN class loss: 0.07314 FastRCNN total loss: 0.14933 L1 loss: 0.0000e+00 L2 loss: 0.60337 Learning rate: 0.002 Mask loss: 0.13688 RPN box loss: 0.01764 RPN score loss: 0.00793 RPN total loss: 0.02557 Total loss: 0.91514 timestamp: 1654956919.4043398 iteration: 54610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14398 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.23084 L1 loss: 0.0000e+00 L2 loss: 0.60336 Learning rate: 0.002 Mask loss: 0.12387 RPN box loss: 0.00986 RPN score loss: 0.00397 RPN total loss: 0.01383 Total loss: 0.9719 timestamp: 1654956922.7227752 iteration: 54615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05227 FastRCNN class loss: 0.06931 FastRCNN total loss: 0.12158 L1 loss: 0.0000e+00 L2 loss: 0.60335 Learning rate: 0.002 Mask loss: 0.13721 RPN box loss: 0.02146 RPN score loss: 0.00579 RPN total loss: 0.02725 Total loss: 0.8894 timestamp: 1654956925.8788602 iteration: 54620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12532 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.19046 L1 loss: 0.0000e+00 L2 loss: 0.60334 Learning rate: 0.002 Mask loss: 0.12562 RPN box loss: 0.0157 RPN score loss: 0.00277 RPN total loss: 0.01847 Total loss: 0.93789 timestamp: 1654956929.188602 iteration: 54625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14304 FastRCNN class loss: 0.12723 FastRCNN total loss: 0.27026 L1 loss: 0.0000e+00 L2 loss: 0.60333 Learning rate: 0.002 Mask loss: 0.13541 RPN box loss: 0.01978 RPN score loss: 0.00253 RPN total loss: 0.02231 Total loss: 1.03131 timestamp: 1654956932.395653 iteration: 54630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13314 FastRCNN class loss: 0.08269 FastRCNN total loss: 0.21583 L1 loss: 0.0000e+00 L2 loss: 0.60332 Learning rate: 0.002 Mask loss: 0.1729 RPN box loss: 0.01444 RPN score loss: 0.00511 RPN total loss: 0.01955 Total loss: 1.0116 timestamp: 1654956935.6358202 iteration: 54635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10771 FastRCNN class loss: 0.05959 FastRCNN total loss: 0.16731 L1 loss: 0.0000e+00 L2 loss: 0.60331 Learning rate: 0.002 Mask loss: 0.15026 RPN box loss: 0.0194 RPN score loss: 0.00312 RPN total loss: 0.02252 Total loss: 0.9434 timestamp: 1654956938.894714 iteration: 54640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07335 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.13387 L1 loss: 0.0000e+00 L2 loss: 0.6033 Learning rate: 0.002 Mask loss: 0.12509 RPN box loss: 0.01189 RPN score loss: 0.00337 RPN total loss: 0.01527 Total loss: 0.87753 timestamp: 1654956942.1204169 iteration: 54645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06376 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.1474 L1 loss: 0.0000e+00 L2 loss: 0.60329 Learning rate: 0.002 Mask loss: 0.11282 RPN box loss: 0.017 RPN score loss: 0.00322 RPN total loss: 0.02022 Total loss: 0.88374 timestamp: 1654956945.2772117 iteration: 54650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10568 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 0.60329 Learning rate: 0.002 Mask loss: 0.10896 RPN box loss: 0.01042 RPN score loss: 0.002 RPN total loss: 0.01242 Total loss: 0.8898 timestamp: 1654956948.5841331 iteration: 54655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08894 FastRCNN class loss: 0.05339 FastRCNN total loss: 0.14233 L1 loss: 0.0000e+00 L2 loss: 0.60328 Learning rate: 0.002 Mask loss: 0.12304 RPN box loss: 0.00991 RPN score loss: 0.00108 RPN total loss: 0.01098 Total loss: 0.87964 timestamp: 1654956951.68967 iteration: 54660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08901 FastRCNN class loss: 0.08734 FastRCNN total loss: 0.17635 L1 loss: 0.0000e+00 L2 loss: 0.60328 Learning rate: 0.002 Mask loss: 0.10028 RPN box loss: 0.03098 RPN score loss: 0.00383 RPN total loss: 0.03482 Total loss: 0.91473 timestamp: 1654956954.9363542 iteration: 54665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09883 FastRCNN class loss: 0.13856 FastRCNN total loss: 0.23739 L1 loss: 0.0000e+00 L2 loss: 0.60327 Learning rate: 0.002 Mask loss: 0.13205 RPN box loss: 0.01647 RPN score loss: 0.00868 RPN total loss: 0.02515 Total loss: 0.99787 timestamp: 1654956958.2207067 iteration: 54670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07011 FastRCNN class loss: 0.03586 FastRCNN total loss: 0.10597 L1 loss: 0.0000e+00 L2 loss: 0.60326 Learning rate: 0.002 Mask loss: 0.0802 RPN box loss: 0.00227 RPN score loss: 0.00032 RPN total loss: 0.00258 Total loss: 0.79201 timestamp: 1654956961.4881315 iteration: 54675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10605 FastRCNN class loss: 0.08223 FastRCNN total loss: 0.18828 L1 loss: 0.0000e+00 L2 loss: 0.60325 Learning rate: 0.002 Mask loss: 0.12559 RPN box loss: 0.01003 RPN score loss: 0.00751 RPN total loss: 0.01754 Total loss: 0.93466 timestamp: 1654956964.737522 iteration: 54680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14625 FastRCNN class loss: 0.09178 FastRCNN total loss: 0.23804 L1 loss: 0.0000e+00 L2 loss: 0.60324 Learning rate: 0.002 Mask loss: 0.15777 RPN box loss: 0.02847 RPN score loss: 0.00685 RPN total loss: 0.03532 Total loss: 1.03436 timestamp: 1654956967.9340405 iteration: 54685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11439 FastRCNN class loss: 0.07702 FastRCNN total loss: 0.19141 L1 loss: 0.0000e+00 L2 loss: 0.60323 Learning rate: 0.002 Mask loss: 0.16275 RPN box loss: 0.01175 RPN score loss: 0.00952 RPN total loss: 0.02127 Total loss: 0.97866 timestamp: 1654956971.1940627 iteration: 54690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05147 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.12007 L1 loss: 0.0000e+00 L2 loss: 0.60322 Learning rate: 0.002 Mask loss: 0.1254 RPN box loss: 0.01684 RPN score loss: 0.00255 RPN total loss: 0.01939 Total loss: 0.86809 timestamp: 1654956974.3671033 iteration: 54695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07911 FastRCNN class loss: 0.09801 FastRCNN total loss: 0.17712 L1 loss: 0.0000e+00 L2 loss: 0.60322 Learning rate: 0.002 Mask loss: 0.12846 RPN box loss: 0.00905 RPN score loss: 0.00382 RPN total loss: 0.01288 Total loss: 0.92167 timestamp: 1654956977.6851676 iteration: 54700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1772 FastRCNN class loss: 0.09774 FastRCNN total loss: 0.27494 L1 loss: 0.0000e+00 L2 loss: 0.60321 Learning rate: 0.002 Mask loss: 0.1831 RPN box loss: 0.01974 RPN score loss: 0.01051 RPN total loss: 0.03025 Total loss: 1.0915 timestamp: 1654956980.8950365 iteration: 54705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07317 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.12322 L1 loss: 0.0000e+00 L2 loss: 0.6032 Learning rate: 0.002 Mask loss: 0.11426 RPN box loss: 0.00738 RPN score loss: 0.00481 RPN total loss: 0.01219 Total loss: 0.85288 timestamp: 1654956984.1291857 iteration: 54710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10191 FastRCNN class loss: 0.07956 FastRCNN total loss: 0.18147 L1 loss: 0.0000e+00 L2 loss: 0.60319 Learning rate: 0.002 Mask loss: 0.13849 RPN box loss: 0.02907 RPN score loss: 0.00884 RPN total loss: 0.03791 Total loss: 0.96108 timestamp: 1654956987.3181431 iteration: 54715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08906 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.14191 L1 loss: 0.0000e+00 L2 loss: 0.60319 Learning rate: 0.002 Mask loss: 0.11278 RPN box loss: 0.00411 RPN score loss: 0.00268 RPN total loss: 0.00679 Total loss: 0.86466 timestamp: 1654956990.581346 iteration: 54720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08089 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.13604 L1 loss: 0.0000e+00 L2 loss: 0.60318 Learning rate: 0.002 Mask loss: 0.12144 RPN box loss: 0.00704 RPN score loss: 0.00442 RPN total loss: 0.01146 Total loss: 0.87212 timestamp: 1654956993.7629433 iteration: 54725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.161 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.22691 L1 loss: 0.0000e+00 L2 loss: 0.60317 Learning rate: 0.002 Mask loss: 0.13102 RPN box loss: 0.02103 RPN score loss: 0.00265 RPN total loss: 0.02368 Total loss: 0.98478 timestamp: 1654956997.0531268 iteration: 54730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12103 FastRCNN class loss: 0.10263 FastRCNN total loss: 0.22366 L1 loss: 0.0000e+00 L2 loss: 0.60316 Learning rate: 0.002 Mask loss: 0.14016 RPN box loss: 0.01501 RPN score loss: 0.00671 RPN total loss: 0.02173 Total loss: 0.98871 timestamp: 1654957000.321023 iteration: 54735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04404 FastRCNN class loss: 0.04 FastRCNN total loss: 0.08405 L1 loss: 0.0000e+00 L2 loss: 0.60315 Learning rate: 0.002 Mask loss: 0.12709 RPN box loss: 0.00726 RPN score loss: 0.00461 RPN total loss: 0.01187 Total loss: 0.82615 timestamp: 1654957003.4741397 iteration: 54740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11038 FastRCNN class loss: 0.08397 FastRCNN total loss: 0.19435 L1 loss: 0.0000e+00 L2 loss: 0.60314 Learning rate: 0.002 Mask loss: 0.11345 RPN box loss: 0.02157 RPN score loss: 0.00229 RPN total loss: 0.02386 Total loss: 0.93479 timestamp: 1654957006.7175128 iteration: 54745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08967 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.17447 L1 loss: 0.0000e+00 L2 loss: 0.60313 Learning rate: 0.002 Mask loss: 0.14075 RPN box loss: 0.01046 RPN score loss: 0.00228 RPN total loss: 0.01274 Total loss: 0.93109 timestamp: 1654957009.94895 iteration: 54750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.10126 FastRCNN total loss: 0.19467 L1 loss: 0.0000e+00 L2 loss: 0.60312 Learning rate: 0.002 Mask loss: 0.11504 RPN box loss: 0.00922 RPN score loss: 0.00464 RPN total loss: 0.01385 Total loss: 0.92668 timestamp: 1654957013.2576008 iteration: 54755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05241 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.11846 L1 loss: 0.0000e+00 L2 loss: 0.60311 Learning rate: 0.002 Mask loss: 0.14658 RPN box loss: 0.01468 RPN score loss: 0.01019 RPN total loss: 0.02487 Total loss: 0.89302 timestamp: 1654957016.4063194 iteration: 54760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08352 FastRCNN class loss: 0.07682 FastRCNN total loss: 0.16034 L1 loss: 0.0000e+00 L2 loss: 0.6031 Learning rate: 0.002 Mask loss: 0.17253 RPN box loss: 0.01804 RPN score loss: 0.00926 RPN total loss: 0.0273 Total loss: 0.96327 timestamp: 1654957019.6558495 iteration: 54765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04916 FastRCNN class loss: 0.03846 FastRCNN total loss: 0.08762 L1 loss: 0.0000e+00 L2 loss: 0.60309 Learning rate: 0.002 Mask loss: 0.09267 RPN box loss: 0.01065 RPN score loss: 0.00365 RPN total loss: 0.0143 Total loss: 0.79769 timestamp: 1654957022.9063237 iteration: 54770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12751 FastRCNN class loss: 0.1158 FastRCNN total loss: 0.2433 L1 loss: 0.0000e+00 L2 loss: 0.60308 Learning rate: 0.002 Mask loss: 0.1954 RPN box loss: 0.02499 RPN score loss: 0.00698 RPN total loss: 0.03197 Total loss: 1.07376 timestamp: 1654957026.2562976 iteration: 54775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10732 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.17156 L1 loss: 0.0000e+00 L2 loss: 0.60308 Learning rate: 0.002 Mask loss: 0.23408 RPN box loss: 0.02605 RPN score loss: 0.00393 RPN total loss: 0.02998 Total loss: 1.0387 timestamp: 1654957029.4322338 iteration: 54780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06521 FastRCNN class loss: 0.06058 FastRCNN total loss: 0.1258 L1 loss: 0.0000e+00 L2 loss: 0.60307 Learning rate: 0.002 Mask loss: 0.12369 RPN box loss: 0.0086 RPN score loss: 0.00375 RPN total loss: 0.01235 Total loss: 0.86491 timestamp: 1654957032.765422 iteration: 54785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07556 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.12503 L1 loss: 0.0000e+00 L2 loss: 0.60306 Learning rate: 0.002 Mask loss: 0.11861 RPN box loss: 0.07035 RPN score loss: 0.00536 RPN total loss: 0.07571 Total loss: 0.92241 timestamp: 1654957036.1086266 iteration: 54790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09039 FastRCNN class loss: 0.05199 FastRCNN total loss: 0.14237 L1 loss: 0.0000e+00 L2 loss: 0.60305 Learning rate: 0.002 Mask loss: 0.14886 RPN box loss: 0.01384 RPN score loss: 0.00126 RPN total loss: 0.0151 Total loss: 0.90939 timestamp: 1654957039.2699022 iteration: 54795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08187 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.14488 L1 loss: 0.0000e+00 L2 loss: 0.60305 Learning rate: 0.002 Mask loss: 0.17989 RPN box loss: 0.00916 RPN score loss: 0.00297 RPN total loss: 0.01213 Total loss: 0.93995 timestamp: 1654957042.4703395 iteration: 54800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10936 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.17878 L1 loss: 0.0000e+00 L2 loss: 0.60304 Learning rate: 0.002 Mask loss: 0.15263 RPN box loss: 0.01246 RPN score loss: 0.00405 RPN total loss: 0.01651 Total loss: 0.95096 timestamp: 1654957045.6537077 iteration: 54805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11183 FastRCNN class loss: 0.08087 FastRCNN total loss: 0.1927 L1 loss: 0.0000e+00 L2 loss: 0.60303 Learning rate: 0.002 Mask loss: 0.15368 RPN box loss: 0.02345 RPN score loss: 0.00485 RPN total loss: 0.02831 Total loss: 0.97772 timestamp: 1654957049.0361228 iteration: 54810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15813 FastRCNN class loss: 0.06158 FastRCNN total loss: 0.21971 L1 loss: 0.0000e+00 L2 loss: 0.60302 Learning rate: 0.002 Mask loss: 0.12633 RPN box loss: 0.00555 RPN score loss: 0.00552 RPN total loss: 0.01107 Total loss: 0.96013 timestamp: 1654957052.2477229 iteration: 54815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04468 FastRCNN class loss: 0.03945 FastRCNN total loss: 0.08414 L1 loss: 0.0000e+00 L2 loss: 0.60302 Learning rate: 0.002 Mask loss: 0.11728 RPN box loss: 0.00589 RPN score loss: 0.00386 RPN total loss: 0.00975 Total loss: 0.81418 timestamp: 1654957055.6738987 iteration: 54820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05172 FastRCNN class loss: 0.04513 FastRCNN total loss: 0.09685 L1 loss: 0.0000e+00 L2 loss: 0.60301 Learning rate: 0.002 Mask loss: 0.09179 RPN box loss: 0.00947 RPN score loss: 0.00234 RPN total loss: 0.01181 Total loss: 0.80346 timestamp: 1654957058.799637 iteration: 54825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13467 FastRCNN class loss: 0.10948 FastRCNN total loss: 0.24416 L1 loss: 0.0000e+00 L2 loss: 0.603 Learning rate: 0.002 Mask loss: 0.22947 RPN box loss: 0.02097 RPN score loss: 0.00379 RPN total loss: 0.02477 Total loss: 1.10139 timestamp: 1654957062.0463812 iteration: 54830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.05163 FastRCNN total loss: 0.16393 L1 loss: 0.0000e+00 L2 loss: 0.60298 Learning rate: 0.002 Mask loss: 0.10957 RPN box loss: 0.01008 RPN score loss: 0.00226 RPN total loss: 0.01233 Total loss: 0.88882 timestamp: 1654957065.2602122 iteration: 54835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10061 FastRCNN class loss: 0.0834 FastRCNN total loss: 0.18401 L1 loss: 0.0000e+00 L2 loss: 0.60297 Learning rate: 0.002 Mask loss: 0.15002 RPN box loss: 0.0154 RPN score loss: 0.00769 RPN total loss: 0.0231 Total loss: 0.9601 timestamp: 1654957068.5992584 iteration: 54840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06462 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.11269 L1 loss: 0.0000e+00 L2 loss: 0.60297 Learning rate: 0.002 Mask loss: 0.09653 RPN box loss: 0.02202 RPN score loss: 0.00295 RPN total loss: 0.02497 Total loss: 0.83715 timestamp: 1654957071.8342955 iteration: 54845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08982 FastRCNN class loss: 0.03567 FastRCNN total loss: 0.12549 L1 loss: 0.0000e+00 L2 loss: 0.60296 Learning rate: 0.002 Mask loss: 0.10518 RPN box loss: 0.01223 RPN score loss: 0.00165 RPN total loss: 0.01388 Total loss: 0.84751 timestamp: 1654957075.0128288 iteration: 54850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07867 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.60295 Learning rate: 0.002 Mask loss: 0.10327 RPN box loss: 0.01152 RPN score loss: 0.00547 RPN total loss: 0.017 Total loss: 0.87157 timestamp: 1654957078.343448 iteration: 54855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06066 FastRCNN class loss: 0.04906 FastRCNN total loss: 0.10972 L1 loss: 0.0000e+00 L2 loss: 0.60294 Learning rate: 0.002 Mask loss: 0.13703 RPN box loss: 0.00942 RPN score loss: 0.00326 RPN total loss: 0.01268 Total loss: 0.86237 timestamp: 1654957081.5770907 iteration: 54860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10527 FastRCNN class loss: 0.09193 FastRCNN total loss: 0.19719 L1 loss: 0.0000e+00 L2 loss: 0.60293 Learning rate: 0.002 Mask loss: 0.16041 RPN box loss: 0.0104 RPN score loss: 0.00385 RPN total loss: 0.01426 Total loss: 0.97479 timestamp: 1654957084.824695 iteration: 54865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12278 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.18892 L1 loss: 0.0000e+00 L2 loss: 0.60292 Learning rate: 0.002 Mask loss: 0.16828 RPN box loss: 0.00896 RPN score loss: 0.01031 RPN total loss: 0.01927 Total loss: 0.97938 timestamp: 1654957088.0047398 iteration: 54870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07393 FastRCNN class loss: 0.0571 FastRCNN total loss: 0.13104 L1 loss: 0.0000e+00 L2 loss: 0.60291 Learning rate: 0.002 Mask loss: 0.09478 RPN box loss: 0.00719 RPN score loss: 0.00355 RPN total loss: 0.01074 Total loss: 0.83947 timestamp: 1654957091.2361188 iteration: 54875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.08329 FastRCNN total loss: 0.18422 L1 loss: 0.0000e+00 L2 loss: 0.6029 Learning rate: 0.002 Mask loss: 0.13961 RPN box loss: 0.01639 RPN score loss: 0.0043 RPN total loss: 0.02069 Total loss: 0.94742 timestamp: 1654957094.41584 iteration: 54880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10343 FastRCNN class loss: 0.09546 FastRCNN total loss: 0.19888 L1 loss: 0.0000e+00 L2 loss: 0.6029 Learning rate: 0.002 Mask loss: 0.18074 RPN box loss: 0.01601 RPN score loss: 0.00248 RPN total loss: 0.01849 Total loss: 1.00102 timestamp: 1654957097.6233754 iteration: 54885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.137 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.22153 L1 loss: 0.0000e+00 L2 loss: 0.60289 Learning rate: 0.002 Mask loss: 0.11412 RPN box loss: 0.04117 RPN score loss: 0.00448 RPN total loss: 0.04565 Total loss: 0.98419 timestamp: 1654957100.7793891 iteration: 54890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1045 FastRCNN class loss: 0.04215 FastRCNN total loss: 0.14665 L1 loss: 0.0000e+00 L2 loss: 0.60288 Learning rate: 0.002 Mask loss: 0.07212 RPN box loss: 0.00564 RPN score loss: 0.00465 RPN total loss: 0.01028 Total loss: 0.83193 timestamp: 1654957104.1008909 iteration: 54895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08568 FastRCNN class loss: 0.0684 FastRCNN total loss: 0.15408 L1 loss: 0.0000e+00 L2 loss: 0.60287 Learning rate: 0.002 Mask loss: 0.13447 RPN box loss: 0.00858 RPN score loss: 0.00201 RPN total loss: 0.01059 Total loss: 0.90201 timestamp: 1654957107.4932811 iteration: 54900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09401 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.16614 L1 loss: 0.0000e+00 L2 loss: 0.60286 Learning rate: 0.002 Mask loss: 0.12356 RPN box loss: 0.00813 RPN score loss: 0.00197 RPN total loss: 0.01011 Total loss: 0.90266 timestamp: 1654957110.7367713 iteration: 54905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08684 FastRCNN class loss: 0.08468 FastRCNN total loss: 0.17153 L1 loss: 0.0000e+00 L2 loss: 0.60285 Learning rate: 0.002 Mask loss: 0.11883 RPN box loss: 0.00632 RPN score loss: 0.00156 RPN total loss: 0.00789 Total loss: 0.90109 timestamp: 1654957114.0099473 iteration: 54910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09193 FastRCNN class loss: 0.04255 FastRCNN total loss: 0.13448 L1 loss: 0.0000e+00 L2 loss: 0.60284 Learning rate: 0.002 Mask loss: 0.09688 RPN box loss: 0.00771 RPN score loss: 0.00338 RPN total loss: 0.01109 Total loss: 0.8453 timestamp: 1654957117.1531456 iteration: 54915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08853 FastRCNN class loss: 0.06938 FastRCNN total loss: 0.15791 L1 loss: 0.0000e+00 L2 loss: 0.60284 Learning rate: 0.002 Mask loss: 0.14856 RPN box loss: 0.01395 RPN score loss: 0.00292 RPN total loss: 0.01687 Total loss: 0.92618 timestamp: 1654957120.4718049 iteration: 54920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09705 FastRCNN class loss: 0.03134 FastRCNN total loss: 0.12839 L1 loss: 0.0000e+00 L2 loss: 0.60283 Learning rate: 0.002 Mask loss: 0.11628 RPN box loss: 0.00554 RPN score loss: 0.00114 RPN total loss: 0.00669 Total loss: 0.85419 timestamp: 1654957123.6926293 iteration: 54925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11104 FastRCNN class loss: 0.0464 FastRCNN total loss: 0.15744 L1 loss: 0.0000e+00 L2 loss: 0.60282 Learning rate: 0.002 Mask loss: 0.11213 RPN box loss: 0.01647 RPN score loss: 0.00317 RPN total loss: 0.01964 Total loss: 0.89203 timestamp: 1654957126.870286 iteration: 54930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08847 FastRCNN class loss: 0.08703 FastRCNN total loss: 0.17551 L1 loss: 0.0000e+00 L2 loss: 0.60281 Learning rate: 0.002 Mask loss: 0.14136 RPN box loss: 0.03127 RPN score loss: 0.00783 RPN total loss: 0.03911 Total loss: 0.95878 timestamp: 1654957130.0857084 iteration: 54935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07492 FastRCNN class loss: 0.05181 FastRCNN total loss: 0.12673 L1 loss: 0.0000e+00 L2 loss: 0.6028 Learning rate: 0.002 Mask loss: 0.11949 RPN box loss: 0.00552 RPN score loss: 0.00412 RPN total loss: 0.00965 Total loss: 0.85866 timestamp: 1654957133.2876656 iteration: 54940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14301 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.18973 L1 loss: 0.0000e+00 L2 loss: 0.60279 Learning rate: 0.002 Mask loss: 0.14354 RPN box loss: 0.01148 RPN score loss: 0.00236 RPN total loss: 0.01384 Total loss: 0.94991 timestamp: 1654957136.535153 iteration: 54945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08021 FastRCNN class loss: 0.09692 FastRCNN total loss: 0.17713 L1 loss: 0.0000e+00 L2 loss: 0.60279 Learning rate: 0.002 Mask loss: 0.13266 RPN box loss: 0.02457 RPN score loss: 0.00501 RPN total loss: 0.02958 Total loss: 0.94216 timestamp: 1654957139.9554787 iteration: 54950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.16166 FastRCNN total loss: 0.27397 L1 loss: 0.0000e+00 L2 loss: 0.60278 Learning rate: 0.002 Mask loss: 0.21817 RPN box loss: 0.02926 RPN score loss: 0.01237 RPN total loss: 0.04163 Total loss: 1.13654 timestamp: 1654957143.1462998 iteration: 54955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15066 FastRCNN class loss: 0.05393 FastRCNN total loss: 0.20458 L1 loss: 0.0000e+00 L2 loss: 0.60277 Learning rate: 0.002 Mask loss: 0.13859 RPN box loss: 0.01516 RPN score loss: 0.00347 RPN total loss: 0.01864 Total loss: 0.96457 timestamp: 1654957146.430929 iteration: 54960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06597 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.60276 Learning rate: 0.002 Mask loss: 0.12089 RPN box loss: 0.00945 RPN score loss: 0.00078 RPN total loss: 0.01023 Total loss: 0.87015 timestamp: 1654957149.7059073 iteration: 54965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.13029 L1 loss: 0.0000e+00 L2 loss: 0.60275 Learning rate: 0.002 Mask loss: 0.16023 RPN box loss: 0.00417 RPN score loss: 0.00127 RPN total loss: 0.00544 Total loss: 0.89871 timestamp: 1654957152.879344 iteration: 54970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09812 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.19044 L1 loss: 0.0000e+00 L2 loss: 0.60274 Learning rate: 0.002 Mask loss: 0.12386 RPN box loss: 0.01272 RPN score loss: 0.00539 RPN total loss: 0.01811 Total loss: 0.93514 timestamp: 1654957156.0761876 iteration: 54975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10909 FastRCNN class loss: 0.08671 FastRCNN total loss: 0.19581 L1 loss: 0.0000e+00 L2 loss: 0.60273 Learning rate: 0.002 Mask loss: 0.15507 RPN box loss: 0.01287 RPN score loss: 0.00513 RPN total loss: 0.018 Total loss: 0.9716 timestamp: 1654957159.2581706 iteration: 54980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09022 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.17154 L1 loss: 0.0000e+00 L2 loss: 0.60272 Learning rate: 0.002 Mask loss: 0.1512 RPN box loss: 0.0126 RPN score loss: 0.00293 RPN total loss: 0.01553 Total loss: 0.94098 timestamp: 1654957162.5063326 iteration: 54985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06794 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.60271 Learning rate: 0.002 Mask loss: 0.13239 RPN box loss: 0.01493 RPN score loss: 0.00901 RPN total loss: 0.02394 Total loss: 0.89652 timestamp: 1654957165.692255 iteration: 54990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13344 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.23078 L1 loss: 0.0000e+00 L2 loss: 0.6027 Learning rate: 0.002 Mask loss: 0.11541 RPN box loss: 0.02321 RPN score loss: 0.0033 RPN total loss: 0.02651 Total loss: 0.97539 timestamp: 1654957168.9964993 iteration: 54995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10596 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.18567 L1 loss: 0.0000e+00 L2 loss: 0.60269 Learning rate: 0.002 Mask loss: 0.16059 RPN box loss: 0.01433 RPN score loss: 0.00301 RPN total loss: 0.01734 Total loss: 0.96629 timestamp: 1654957172.1924973 iteration: 55000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09892 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.16744 L1 loss: 0.0000e+00 L2 loss: 0.60269 Learning rate: 0.002 Mask loss: 0.15849 RPN box loss: 0.01801 RPN score loss: 0.00543 RPN total loss: 0.02344 Total loss: 0.95205 timestamp: 1654957175.437051 iteration: 55005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12612 FastRCNN class loss: 0.10737 FastRCNN total loss: 0.23348 L1 loss: 0.0000e+00 L2 loss: 0.60268 Learning rate: 0.002 Mask loss: 0.14677 RPN box loss: 0.02014 RPN score loss: 0.02426 RPN total loss: 0.0444 Total loss: 1.02733 timestamp: 1654957178.5949128 iteration: 55010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07355 FastRCNN class loss: 0.05747 FastRCNN total loss: 0.13102 L1 loss: 0.0000e+00 L2 loss: 0.60267 Learning rate: 0.002 Mask loss: 0.16063 RPN box loss: 0.01316 RPN score loss: 0.00669 RPN total loss: 0.01985 Total loss: 0.91417 timestamp: 1654957181.780814 iteration: 55015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.06363 FastRCNN total loss: 0.1428 L1 loss: 0.0000e+00 L2 loss: 0.60266 Learning rate: 0.002 Mask loss: 0.17389 RPN box loss: 0.0497 RPN score loss: 0.0115 RPN total loss: 0.0612 Total loss: 0.98055 timestamp: 1654957185.0189013 iteration: 55020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06762 FastRCNN class loss: 0.05538 FastRCNN total loss: 0.123 L1 loss: 0.0000e+00 L2 loss: 0.60265 Learning rate: 0.002 Mask loss: 0.07989 RPN box loss: 0.0071 RPN score loss: 0.00154 RPN total loss: 0.00864 Total loss: 0.81418 timestamp: 1654957188.236755 iteration: 55025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15056 FastRCNN class loss: 0.09108 FastRCNN total loss: 0.24164 L1 loss: 0.0000e+00 L2 loss: 0.60265 Learning rate: 0.002 Mask loss: 0.19398 RPN box loss: 0.01404 RPN score loss: 0.01624 RPN total loss: 0.03029 Total loss: 1.06855 timestamp: 1654957191.503031 iteration: 55030 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09718 FastRCNN class loss: 0.04044 FastRCNN total loss: 0.13762 L1 loss: 0.0000e+00 L2 loss: 0.60264 Learning rate: 0.002 Mask loss: 0.10696 RPN box loss: 0.00491 RPN score loss: 0.00146 RPN total loss: 0.00636 Total loss: 0.85358 timestamp: 1654957194.6654232 iteration: 55035 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09673 FastRCNN class loss: 0.0477 FastRCNN total loss: 0.14443 L1 loss: 0.0000e+00 L2 loss: 0.60263 Learning rate: 0.002 Mask loss: 0.12249 RPN box loss: 0.00525 RPN score loss: 0.00479 RPN total loss: 0.01004 Total loss: 0.87959 timestamp: 1654957197.9213398 iteration: 55040 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11493 FastRCNN class loss: 0.09672 FastRCNN total loss: 0.21165 L1 loss: 0.0000e+00 L2 loss: 0.60262 Learning rate: 0.002 Mask loss: 0.19511 RPN box loss: 0.01497 RPN score loss: 0.00609 RPN total loss: 0.02106 Total loss: 1.03044 timestamp: 1654957201.0697732 iteration: 55045 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07119 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.12358 L1 loss: 0.0000e+00 L2 loss: 0.60261 Learning rate: 0.002 Mask loss: 0.06355 RPN box loss: 0.0077 RPN score loss: 0.00092 RPN total loss: 0.00862 Total loss: 0.79836 timestamp: 1654957204.3508472 iteration: 55050 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06114 FastRCNN class loss: 0.05227 FastRCNN total loss: 0.11341 L1 loss: 0.0000e+00 L2 loss: 0.6026 Learning rate: 0.002 Mask loss: 0.11695 RPN box loss: 0.0074 RPN score loss: 0.00192 RPN total loss: 0.00932 Total loss: 0.84228 timestamp: 1654957207.6049895 iteration: 55055 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10922 FastRCNN class loss: 0.05667 FastRCNN total loss: 0.16588 L1 loss: 0.0000e+00 L2 loss: 0.60259 Learning rate: 0.002 Mask loss: 0.1175 RPN box loss: 0.01023 RPN score loss: 0.00221 RPN total loss: 0.01244 Total loss: 0.89841 timestamp: 1654957210.945553 iteration: 55060 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11522 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.18609 L1 loss: 0.0000e+00 L2 loss: 0.60258 Learning rate: 0.002 Mask loss: 0.11238 RPN box loss: 0.0099 RPN score loss: 0.00614 RPN total loss: 0.01603 Total loss: 0.91709 timestamp: 1654957214.1850743 iteration: 55065 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09187 FastRCNN class loss: 0.08059 FastRCNN total loss: 0.17246 L1 loss: 0.0000e+00 L2 loss: 0.60258 Learning rate: 0.002 Mask loss: 0.11475 RPN box loss: 0.02583 RPN score loss: 0.00811 RPN total loss: 0.03394 Total loss: 0.92373 timestamp: 1654957217.497718 iteration: 55070 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11278 FastRCNN class loss: 0.0775 FastRCNN total loss: 0.19028 L1 loss: 0.0000e+00 L2 loss: 0.60257 Learning rate: 0.002 Mask loss: 0.1378 RPN box loss: 0.02107 RPN score loss: 0.00839 RPN total loss: 0.02946 Total loss: 0.96012 timestamp: 1654957220.7944663 iteration: 55075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08141 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.15765 L1 loss: 0.0000e+00 L2 loss: 0.60256 Learning rate: 0.002 Mask loss: 0.11314 RPN box loss: 0.00678 RPN score loss: 0.00235 RPN total loss: 0.00913 Total loss: 0.88248 timestamp: 1654957224.0816665 iteration: 55080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08134 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.13635 L1 loss: 0.0000e+00 L2 loss: 0.60255 Learning rate: 0.002 Mask loss: 0.10262 RPN box loss: 0.00983 RPN score loss: 0.00461 RPN total loss: 0.01444 Total loss: 0.85596 timestamp: 1654957227.3803113 iteration: 55085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09103 FastRCNN class loss: 0.09463 FastRCNN total loss: 0.18566 L1 loss: 0.0000e+00 L2 loss: 0.60254 Learning rate: 0.002 Mask loss: 0.11687 RPN box loss: 0.00926 RPN score loss: 0.00298 RPN total loss: 0.01224 Total loss: 0.91731 timestamp: 1654957230.5986826 iteration: 55090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09466 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.15595 L1 loss: 0.0000e+00 L2 loss: 0.60254 Learning rate: 0.002 Mask loss: 0.19457 RPN box loss: 0.00692 RPN score loss: 0.00143 RPN total loss: 0.00835 Total loss: 0.96141 timestamp: 1654957233.7208176 iteration: 55095 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12715 FastRCNN class loss: 0.08537 FastRCNN total loss: 0.21252 L1 loss: 0.0000e+00 L2 loss: 0.60253 Learning rate: 0.002 Mask loss: 0.14872 RPN box loss: 0.01468 RPN score loss: 0.00913 RPN total loss: 0.02381 Total loss: 0.98758 timestamp: 1654957236.8403614 iteration: 55100 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07549 FastRCNN class loss: 0.05797 FastRCNN total loss: 0.13346 L1 loss: 0.0000e+00 L2 loss: 0.60252 Learning rate: 0.002 Mask loss: 0.07663 RPN box loss: 0.00992 RPN score loss: 0.01079 RPN total loss: 0.02071 Total loss: 0.83333 timestamp: 1654957240.1296942 iteration: 55105 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06361 FastRCNN class loss: 0.04205 FastRCNN total loss: 0.10566 L1 loss: 0.0000e+00 L2 loss: 0.60251 Learning rate: 0.002 Mask loss: 0.089 RPN box loss: 0.00714 RPN score loss: 0.00268 RPN total loss: 0.00982 Total loss: 0.80699 timestamp: 1654957243.423731 iteration: 55110 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10773 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.17832 L1 loss: 0.0000e+00 L2 loss: 0.6025 Learning rate: 0.002 Mask loss: 0.14075 RPN box loss: 0.02332 RPN score loss: 0.00389 RPN total loss: 0.02722 Total loss: 0.94879 timestamp: 1654957246.6549292 iteration: 55115 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12599 FastRCNN class loss: 0.07952 FastRCNN total loss: 0.20551 L1 loss: 0.0000e+00 L2 loss: 0.60249 Learning rate: 0.002 Mask loss: 0.13239 RPN box loss: 0.01848 RPN score loss: 0.0018 RPN total loss: 0.02028 Total loss: 0.96068 timestamp: 1654957249.8534124 iteration: 55120 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10243 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.16196 L1 loss: 0.0000e+00 L2 loss: 0.60249 Learning rate: 0.002 Mask loss: 0.16529 RPN box loss: 0.00499 RPN score loss: 0.00399 RPN total loss: 0.00899 Total loss: 0.93872 timestamp: 1654957253.1330562 iteration: 55125 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03699 FastRCNN class loss: 0.04502 FastRCNN total loss: 0.08201 L1 loss: 0.0000e+00 L2 loss: 0.60248 Learning rate: 0.002 Mask loss: 0.10751 RPN box loss: 0.00507 RPN score loss: 0.00129 RPN total loss: 0.00636 Total loss: 0.79836 timestamp: 1654957256.3349838 iteration: 55130 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08108 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.14062 L1 loss: 0.0000e+00 L2 loss: 0.60247 Learning rate: 0.002 Mask loss: 0.1052 RPN box loss: 0.0125 RPN score loss: 0.00568 RPN total loss: 0.01819 Total loss: 0.86648 timestamp: 1654957259.659574 iteration: 55135 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04452 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.1064 L1 loss: 0.0000e+00 L2 loss: 0.60246 Learning rate: 0.002 Mask loss: 0.11282 RPN box loss: 0.01134 RPN score loss: 0.00512 RPN total loss: 0.01646 Total loss: 0.83814 timestamp: 1654957262.9183083 iteration: 55140 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08835 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.13663 L1 loss: 0.0000e+00 L2 loss: 0.60245 Learning rate: 0.002 Mask loss: 0.09537 RPN box loss: 0.00772 RPN score loss: 0.00114 RPN total loss: 0.00886 Total loss: 0.84331 timestamp: 1654957266.088168 iteration: 55145 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07378 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.14803 L1 loss: 0.0000e+00 L2 loss: 0.60244 Learning rate: 0.002 Mask loss: 0.12917 RPN box loss: 0.03127 RPN score loss: 0.00501 RPN total loss: 0.03628 Total loss: 0.91592 timestamp: 1654957269.3980837 iteration: 55150 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0759 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.13919 L1 loss: 0.0000e+00 L2 loss: 0.60243 Learning rate: 0.002 Mask loss: 0.15399 RPN box loss: 0.01474 RPN score loss: 0.00198 RPN total loss: 0.01672 Total loss: 0.91234 timestamp: 1654957272.6363666 iteration: 55155 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07554 FastRCNN class loss: 0.04535 FastRCNN total loss: 0.12089 L1 loss: 0.0000e+00 L2 loss: 0.60243 Learning rate: 0.002 Mask loss: 0.09074 RPN box loss: 0.00868 RPN score loss: 0.00217 RPN total loss: 0.01085 Total loss: 0.8249 timestamp: 1654957275.937316 iteration: 55160 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09346 FastRCNN class loss: 0.07021 FastRCNN total loss: 0.16366 L1 loss: 0.0000e+00 L2 loss: 0.60242 Learning rate: 0.002 Mask loss: 0.09135 RPN box loss: 0.0163 RPN score loss: 0.00333 RPN total loss: 0.01963 Total loss: 0.87707 timestamp: 1654957279.1082902 iteration: 55165 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07791 FastRCNN class loss: 0.04248 FastRCNN total loss: 0.12039 L1 loss: 0.0000e+00 L2 loss: 0.60241 Learning rate: 0.002 Mask loss: 0.12407 RPN box loss: 0.00949 RPN score loss: 0.00594 RPN total loss: 0.01543 Total loss: 0.8623 timestamp: 1654957282.3543491 iteration: 55170 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11886 FastRCNN class loss: 0.11046 FastRCNN total loss: 0.22932 L1 loss: 0.0000e+00 L2 loss: 0.6024 Learning rate: 0.002 Mask loss: 0.20408 RPN box loss: 0.01446 RPN score loss: 0.00264 RPN total loss: 0.0171 Total loss: 1.0529 timestamp: 1654957285.485735 iteration: 55175 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12296 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.1986 L1 loss: 0.0000e+00 L2 loss: 0.60239 Learning rate: 0.002 Mask loss: 0.11322 RPN box loss: 0.02568 RPN score loss: 0.00662 RPN total loss: 0.0323 Total loss: 0.94652 timestamp: 1654957288.7819114 iteration: 55180 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12631 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.22516 L1 loss: 0.0000e+00 L2 loss: 0.60238 Learning rate: 0.002 Mask loss: 0.1527 RPN box loss: 0.00991 RPN score loss: 0.00356 RPN total loss: 0.01347 Total loss: 0.99371 timestamp: 1654957292.0253522 iteration: 55185 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08711 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.14733 L1 loss: 0.0000e+00 L2 loss: 0.60238 Learning rate: 0.002 Mask loss: 0.13113 RPN box loss: 0.00425 RPN score loss: 0.00292 RPN total loss: 0.00717 Total loss: 0.888 timestamp: 1654957295.33075 iteration: 55190 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08119 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.14596 L1 loss: 0.0000e+00 L2 loss: 0.60237 Learning rate: 0.002 Mask loss: 0.1427 RPN box loss: 0.01184 RPN score loss: 0.00318 RPN total loss: 0.01502 Total loss: 0.90605 timestamp: 1654957298.609956 iteration: 55195 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1119 FastRCNN class loss: 0.06799 FastRCNN total loss: 0.17989 L1 loss: 0.0000e+00 L2 loss: 0.60236 Learning rate: 0.002 Mask loss: 0.11725 RPN box loss: 0.01646 RPN score loss: 0.00216 RPN total loss: 0.01862 Total loss: 0.91813 timestamp: 1654957301.7987494 iteration: 55200 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11541 FastRCNN class loss: 0.06833 FastRCNN total loss: 0.18374 L1 loss: 0.0000e+00 L2 loss: 0.60235 Learning rate: 0.002 Mask loss: 0.13834 RPN box loss: 0.01754 RPN score loss: 0.00283 RPN total loss: 0.02037 Total loss: 0.9448 timestamp: 1654957305.1420262 iteration: 55205 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07365 FastRCNN class loss: 0.0643 FastRCNN total loss: 0.13794 L1 loss: 0.0000e+00 L2 loss: 0.60234 Learning rate: 0.002 Mask loss: 0.15206 RPN box loss: 0.00635 RPN score loss: 0.00262 RPN total loss: 0.00898 Total loss: 0.90133 timestamp: 1654957308.3904207 iteration: 55210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11068 FastRCNN class loss: 0.06058 FastRCNN total loss: 0.17126 L1 loss: 0.0000e+00 L2 loss: 0.60234 Learning rate: 0.002 Mask loss: 0.14367 RPN box loss: 0.01523 RPN score loss: 0.00155 RPN total loss: 0.01678 Total loss: 0.93405 timestamp: 1654957311.6885746 iteration: 55215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12988 FastRCNN class loss: 0.0612 FastRCNN total loss: 0.19108 L1 loss: 0.0000e+00 L2 loss: 0.60233 Learning rate: 0.002 Mask loss: 0.14057 RPN box loss: 0.024 RPN score loss: 0.00866 RPN total loss: 0.03265 Total loss: 0.96662 timestamp: 1654957314.8921616 iteration: 55220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12462 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.20223 L1 loss: 0.0000e+00 L2 loss: 0.60232 Learning rate: 0.002 Mask loss: 0.09201 RPN box loss: 0.0177 RPN score loss: 0.00879 RPN total loss: 0.02649 Total loss: 0.92305 timestamp: 1654957318.1582792 iteration: 55225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.09809 FastRCNN total loss: 0.21526 L1 loss: 0.0000e+00 L2 loss: 0.60231 Learning rate: 0.002 Mask loss: 0.17018 RPN box loss: 0.02592 RPN score loss: 0.01944 RPN total loss: 0.04536 Total loss: 1.03311 timestamp: 1654957321.3316805 iteration: 55230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06031 FastRCNN class loss: 0.07514 FastRCNN total loss: 0.13545 L1 loss: 0.0000e+00 L2 loss: 0.6023 Learning rate: 0.002 Mask loss: 0.18234 RPN box loss: 0.013 RPN score loss: 0.01545 RPN total loss: 0.02845 Total loss: 0.94854 timestamp: 1654957324.554338 iteration: 55235 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10629 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.17666 L1 loss: 0.0000e+00 L2 loss: 0.60229 Learning rate: 0.002 Mask loss: 0.11003 RPN box loss: 0.01285 RPN score loss: 0.0123 RPN total loss: 0.02516 Total loss: 0.91414 timestamp: 1654957327.8274288 iteration: 55240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07318 FastRCNN class loss: 0.06682 FastRCNN total loss: 0.14 L1 loss: 0.0000e+00 L2 loss: 0.60228 Learning rate: 0.002 Mask loss: 0.10378 RPN box loss: 0.0201 RPN score loss: 0.01344 RPN total loss: 0.03354 Total loss: 0.8796 timestamp: 1654957331.071587 iteration: 55245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0591 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.11298 L1 loss: 0.0000e+00 L2 loss: 0.60227 Learning rate: 0.002 Mask loss: 0.11761 RPN box loss: 0.03689 RPN score loss: 0.00416 RPN total loss: 0.04106 Total loss: 0.87392 timestamp: 1654957334.3774915 iteration: 55250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10666 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.17918 L1 loss: 0.0000e+00 L2 loss: 0.60226 Learning rate: 0.002 Mask loss: 0.14414 RPN box loss: 0.01026 RPN score loss: 0.00273 RPN total loss: 0.01299 Total loss: 0.93858 timestamp: 1654957337.6224263 iteration: 55255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15847 FastRCNN class loss: 0.0628 FastRCNN total loss: 0.22128 L1 loss: 0.0000e+00 L2 loss: 0.60225 Learning rate: 0.002 Mask loss: 0.11257 RPN box loss: 0.00588 RPN score loss: 0.0036 RPN total loss: 0.00948 Total loss: 0.94558 timestamp: 1654957340.9688816 iteration: 55260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0817 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.14404 L1 loss: 0.0000e+00 L2 loss: 0.60225 Learning rate: 0.002 Mask loss: 0.14636 RPN box loss: 0.00876 RPN score loss: 0.0018 RPN total loss: 0.01056 Total loss: 0.90321 timestamp: 1654957344.118243 iteration: 55265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07347 FastRCNN class loss: 0.04128 FastRCNN total loss: 0.11475 L1 loss: 0.0000e+00 L2 loss: 0.60224 Learning rate: 0.002 Mask loss: 0.05616 RPN box loss: 0.00297 RPN score loss: 0.0009 RPN total loss: 0.00387 Total loss: 0.77702 timestamp: 1654957347.401262 iteration: 55270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07203 FastRCNN class loss: 0.05498 FastRCNN total loss: 0.12701 L1 loss: 0.0000e+00 L2 loss: 0.60223 Learning rate: 0.002 Mask loss: 0.15076 RPN box loss: 0.0116 RPN score loss: 0.0068 RPN total loss: 0.01841 Total loss: 0.89841 timestamp: 1654957350.5737813 iteration: 55275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.17168 L1 loss: 0.0000e+00 L2 loss: 0.60222 Learning rate: 0.002 Mask loss: 0.14056 RPN box loss: 0.01878 RPN score loss: 0.00416 RPN total loss: 0.02293 Total loss: 0.93739 timestamp: 1654957353.7188606 iteration: 55280 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10206 FastRCNN class loss: 0.09301 FastRCNN total loss: 0.19506 L1 loss: 0.0000e+00 L2 loss: 0.60221 Learning rate: 0.002 Mask loss: 0.09988 RPN box loss: 0.02186 RPN score loss: 0.01344 RPN total loss: 0.0353 Total loss: 0.93245 timestamp: 1654957357.0330005 iteration: 55285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14207 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.19746 L1 loss: 0.0000e+00 L2 loss: 0.6022 Learning rate: 0.002 Mask loss: 0.10913 RPN box loss: 0.02263 RPN score loss: 0.00206 RPN total loss: 0.02469 Total loss: 0.93349 timestamp: 1654957360.22709 iteration: 55290 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13478 FastRCNN class loss: 0.046 FastRCNN total loss: 0.18078 L1 loss: 0.0000e+00 L2 loss: 0.6022 Learning rate: 0.002 Mask loss: 0.08873 RPN box loss: 0.01022 RPN score loss: 0.00214 RPN total loss: 0.01236 Total loss: 0.88407 timestamp: 1654957363.4684014 iteration: 55295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09115 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.60219 Learning rate: 0.002 Mask loss: 0.1455 RPN box loss: 0.02923 RPN score loss: 0.00301 RPN total loss: 0.03223 Total loss: 0.94636 timestamp: 1654957366.6471703 iteration: 55300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07131 FastRCNN class loss: 0.04794 FastRCNN total loss: 0.11925 L1 loss: 0.0000e+00 L2 loss: 0.60218 Learning rate: 0.002 Mask loss: 0.16035 RPN box loss: 0.00785 RPN score loss: 0.00177 RPN total loss: 0.00961 Total loss: 0.89138 timestamp: 1654957369.8034694 iteration: 55305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10185 FastRCNN class loss: 0.06316 FastRCNN total loss: 0.16501 L1 loss: 0.0000e+00 L2 loss: 0.60216 Learning rate: 0.002 Mask loss: 0.17995 RPN box loss: 0.01508 RPN score loss: 0.0101 RPN total loss: 0.02518 Total loss: 0.9723 timestamp: 1654957373.0653086 iteration: 55310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05442 FastRCNN class loss: 0.04358 FastRCNN total loss: 0.09801 L1 loss: 0.0000e+00 L2 loss: 0.60215 Learning rate: 0.002 Mask loss: 0.08822 RPN box loss: 0.00232 RPN score loss: 0.00137 RPN total loss: 0.00369 Total loss: 0.79208 timestamp: 1654957376.412166 iteration: 55315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.0553 FastRCNN total loss: 0.13185 L1 loss: 0.0000e+00 L2 loss: 0.60215 Learning rate: 0.002 Mask loss: 0.13556 RPN box loss: 0.01487 RPN score loss: 0.002 RPN total loss: 0.01687 Total loss: 0.88642 timestamp: 1654957379.7083163 iteration: 55320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08655 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.1541 L1 loss: 0.0000e+00 L2 loss: 0.60214 Learning rate: 0.002 Mask loss: 0.14756 RPN box loss: 0.01836 RPN score loss: 0.00311 RPN total loss: 0.02147 Total loss: 0.92526 timestamp: 1654957383.0157754 iteration: 55325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1105 FastRCNN class loss: 0.06757 FastRCNN total loss: 0.17807 L1 loss: 0.0000e+00 L2 loss: 0.60213 Learning rate: 0.002 Mask loss: 0.12768 RPN box loss: 0.01393 RPN score loss: 0.01135 RPN total loss: 0.02528 Total loss: 0.93316 timestamp: 1654957386.2141805 iteration: 55330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11243 FastRCNN class loss: 0.0844 FastRCNN total loss: 0.19683 L1 loss: 0.0000e+00 L2 loss: 0.60212 Learning rate: 0.002 Mask loss: 0.14876 RPN box loss: 0.00768 RPN score loss: 0.00236 RPN total loss: 0.01004 Total loss: 0.95775 timestamp: 1654957389.5137782 iteration: 55335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06271 FastRCNN class loss: 0.05904 FastRCNN total loss: 0.12174 L1 loss: 0.0000e+00 L2 loss: 0.60211 Learning rate: 0.002 Mask loss: 0.11521 RPN box loss: 0.01072 RPN score loss: 0.00204 RPN total loss: 0.01276 Total loss: 0.85183 timestamp: 1654957392.7372198 iteration: 55340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0691 FastRCNN class loss: 0.05485 FastRCNN total loss: 0.12395 L1 loss: 0.0000e+00 L2 loss: 0.60211 Learning rate: 0.002 Mask loss: 0.10652 RPN box loss: 0.02824 RPN score loss: 0.00627 RPN total loss: 0.03451 Total loss: 0.86708 timestamp: 1654957396.03751 iteration: 55345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06619 FastRCNN class loss: 0.05794 FastRCNN total loss: 0.12413 L1 loss: 0.0000e+00 L2 loss: 0.6021 Learning rate: 0.002 Mask loss: 0.11031 RPN box loss: 0.01589 RPN score loss: 0.00252 RPN total loss: 0.01841 Total loss: 0.85495 timestamp: 1654957399.1245427 iteration: 55350 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06126 FastRCNN class loss: 0.0556 FastRCNN total loss: 0.11686 L1 loss: 0.0000e+00 L2 loss: 0.60209 Learning rate: 0.002 Mask loss: 0.12202 RPN box loss: 0.01386 RPN score loss: 0.00804 RPN total loss: 0.02191 Total loss: 0.86287 timestamp: 1654957402.3534622 iteration: 55355 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12651 FastRCNN class loss: 0.08164 FastRCNN total loss: 0.20815 L1 loss: 0.0000e+00 L2 loss: 0.60208 Learning rate: 0.002 Mask loss: 0.15853 RPN box loss: 0.02339 RPN score loss: 0.01842 RPN total loss: 0.04181 Total loss: 1.01057 timestamp: 1654957405.544456 iteration: 55360 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10059 FastRCNN class loss: 0.04628 FastRCNN total loss: 0.14687 L1 loss: 0.0000e+00 L2 loss: 0.60207 Learning rate: 0.002 Mask loss: 0.11054 RPN box loss: 0.03096 RPN score loss: 0.00621 RPN total loss: 0.03717 Total loss: 0.89665 timestamp: 1654957408.8606782 iteration: 55365 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05609 FastRCNN class loss: 0.03924 FastRCNN total loss: 0.09533 L1 loss: 0.0000e+00 L2 loss: 0.60206 Learning rate: 0.002 Mask loss: 0.15536 RPN box loss: 0.00274 RPN score loss: 0.00219 RPN total loss: 0.00493 Total loss: 0.85768 timestamp: 1654957412.1593342 iteration: 55370 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07982 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.14056 L1 loss: 0.0000e+00 L2 loss: 0.60205 Learning rate: 0.002 Mask loss: 0.1172 RPN box loss: 0.00814 RPN score loss: 0.00372 RPN total loss: 0.01185 Total loss: 0.87166 timestamp: 1654957415.3549557 iteration: 55375 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10153 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.17329 L1 loss: 0.0000e+00 L2 loss: 0.60204 Learning rate: 0.002 Mask loss: 0.16997 RPN box loss: 0.01935 RPN score loss: 0.00624 RPN total loss: 0.02558 Total loss: 0.97088 timestamp: 1654957418.6094267 iteration: 55380 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12209 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.60203 Learning rate: 0.002 Mask loss: 0.13106 RPN box loss: 0.01065 RPN score loss: 0.00424 RPN total loss: 0.0149 Total loss: 0.94155 timestamp: 1654957421.7845814 iteration: 55385 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07154 FastRCNN class loss: 0.04075 FastRCNN total loss: 0.11229 L1 loss: 0.0000e+00 L2 loss: 0.60202 Learning rate: 0.002 Mask loss: 0.0957 RPN box loss: 0.02067 RPN score loss: 0.00342 RPN total loss: 0.02408 Total loss: 0.83408 timestamp: 1654957424.9795592 iteration: 55390 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10601 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.20335 L1 loss: 0.0000e+00 L2 loss: 0.60201 Learning rate: 0.002 Mask loss: 0.13418 RPN box loss: 0.03168 RPN score loss: 0.00639 RPN total loss: 0.03807 Total loss: 0.9776 timestamp: 1654957428.2613842 iteration: 55395 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06416 FastRCNN class loss: 0.03826 FastRCNN total loss: 0.10242 L1 loss: 0.0000e+00 L2 loss: 0.602 Learning rate: 0.002 Mask loss: 0.10181 RPN box loss: 0.01246 RPN score loss: 0.00434 RPN total loss: 0.0168 Total loss: 0.82303 timestamp: 1654957431.454379 iteration: 55400 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10776 FastRCNN class loss: 0.05488 FastRCNN total loss: 0.16264 L1 loss: 0.0000e+00 L2 loss: 0.60199 Learning rate: 0.002 Mask loss: 0.12255 RPN box loss: 0.00785 RPN score loss: 0.00116 RPN total loss: 0.00901 Total loss: 0.89619 timestamp: 1654957434.6385396 iteration: 55405 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05396 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.12506 L1 loss: 0.0000e+00 L2 loss: 0.60199 Learning rate: 0.002 Mask loss: 0.08511 RPN box loss: 0.01436 RPN score loss: 0.00497 RPN total loss: 0.01933 Total loss: 0.83148 timestamp: 1654957437.870202 iteration: 55410 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06849 FastRCNN class loss: 0.03665 FastRCNN total loss: 0.10513 L1 loss: 0.0000e+00 L2 loss: 0.60198 Learning rate: 0.002 Mask loss: 0.11143 RPN box loss: 0.00342 RPN score loss: 0.00132 RPN total loss: 0.00475 Total loss: 0.82329 timestamp: 1654957440.996971 iteration: 55415 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13066 FastRCNN class loss: 0.0653 FastRCNN total loss: 0.19596 L1 loss: 0.0000e+00 L2 loss: 0.60197 Learning rate: 0.002 Mask loss: 0.15822 RPN box loss: 0.00827 RPN score loss: 0.0011 RPN total loss: 0.00937 Total loss: 0.96553 timestamp: 1654957444.2393615 iteration: 55420 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05505 FastRCNN class loss: 0.04215 FastRCNN total loss: 0.0972 L1 loss: 0.0000e+00 L2 loss: 0.60196 Learning rate: 0.002 Mask loss: 0.08908 RPN box loss: 0.00673 RPN score loss: 0.00603 RPN total loss: 0.01276 Total loss: 0.80099 timestamp: 1654957447.4929032 iteration: 55425 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.088 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.15965 L1 loss: 0.0000e+00 L2 loss: 0.60195 Learning rate: 0.002 Mask loss: 0.1519 RPN box loss: 0.01399 RPN score loss: 0.01228 RPN total loss: 0.02627 Total loss: 0.93977 timestamp: 1654957450.718336 iteration: 55430 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08005 FastRCNN class loss: 0.04055 FastRCNN total loss: 0.1206 L1 loss: 0.0000e+00 L2 loss: 0.60195 Learning rate: 0.002 Mask loss: 0.12949 RPN box loss: 0.01353 RPN score loss: 0.00066 RPN total loss: 0.0142 Total loss: 0.86624 timestamp: 1654957454.0721774 iteration: 55435 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.15302 L1 loss: 0.0000e+00 L2 loss: 0.60194 Learning rate: 0.002 Mask loss: 0.11099 RPN box loss: 0.01135 RPN score loss: 0.00262 RPN total loss: 0.01396 Total loss: 0.87991 timestamp: 1654957457.222226 iteration: 55440 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12939 FastRCNN class loss: 0.0777 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 0.60193 Learning rate: 0.002 Mask loss: 0.19739 RPN box loss: 0.02062 RPN score loss: 0.00561 RPN total loss: 0.02623 Total loss: 1.03264 timestamp: 1654957460.4576147 iteration: 55445 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05098 FastRCNN class loss: 0.04124 FastRCNN total loss: 0.09222 L1 loss: 0.0000e+00 L2 loss: 0.60193 Learning rate: 0.002 Mask loss: 0.11725 RPN box loss: 0.00753 RPN score loss: 0.0043 RPN total loss: 0.01184 Total loss: 0.82324 timestamp: 1654957463.5960968 iteration: 55450 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08301 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.14269 L1 loss: 0.0000e+00 L2 loss: 0.60192 Learning rate: 0.002 Mask loss: 0.10225 RPN box loss: 0.00246 RPN score loss: 0.0013 RPN total loss: 0.00376 Total loss: 0.85061 timestamp: 1654957466.961448 iteration: 55455 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.08006 FastRCNN total loss: 0.20868 L1 loss: 0.0000e+00 L2 loss: 0.60191 Learning rate: 0.002 Mask loss: 0.13556 RPN box loss: 0.01547 RPN score loss: 0.0134 RPN total loss: 0.02887 Total loss: 0.97502 timestamp: 1654957470.1442466 iteration: 55460 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13361 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.20806 L1 loss: 0.0000e+00 L2 loss: 0.6019 Learning rate: 0.002 Mask loss: 0.09923 RPN box loss: 0.01818 RPN score loss: 0.00127 RPN total loss: 0.01945 Total loss: 0.92864 timestamp: 1654957473.3704402 iteration: 55465 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07371 FastRCNN class loss: 0.04883 FastRCNN total loss: 0.12254 L1 loss: 0.0000e+00 L2 loss: 0.60189 Learning rate: 0.002 Mask loss: 0.15473 RPN box loss: 0.01599 RPN score loss: 0.003 RPN total loss: 0.01899 Total loss: 0.89816 timestamp: 1654957476.5736122 iteration: 55470 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10082 FastRCNN class loss: 0.06828 FastRCNN total loss: 0.1691 L1 loss: 0.0000e+00 L2 loss: 0.60188 Learning rate: 0.002 Mask loss: 0.15615 RPN box loss: 0.01847 RPN score loss: 0.00421 RPN total loss: 0.02268 Total loss: 0.94982 timestamp: 1654957479.8023963 iteration: 55475 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09316 FastRCNN class loss: 0.04009 FastRCNN total loss: 0.13325 L1 loss: 0.0000e+00 L2 loss: 0.60187 Learning rate: 0.002 Mask loss: 0.1195 RPN box loss: 0.01188 RPN score loss: 0.00262 RPN total loss: 0.0145 Total loss: 0.86913 timestamp: 1654957483.0479608 iteration: 55480 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06809 FastRCNN class loss: 0.04591 FastRCNN total loss: 0.11401 L1 loss: 0.0000e+00 L2 loss: 0.60187 Learning rate: 0.002 Mask loss: 0.09575 RPN box loss: 0.01127 RPN score loss: 0.00273 RPN total loss: 0.01401 Total loss: 0.82563 timestamp: 1654957486.3902483 iteration: 55485 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10818 FastRCNN class loss: 0.07927 FastRCNN total loss: 0.18745 L1 loss: 0.0000e+00 L2 loss: 0.60185 Learning rate: 0.002 Mask loss: 0.21159 RPN box loss: 0.00481 RPN score loss: 0.00094 RPN total loss: 0.00575 Total loss: 1.00664 timestamp: 1654957489.5967495 iteration: 55490 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13288 FastRCNN class loss: 0.10592 FastRCNN total loss: 0.23881 L1 loss: 0.0000e+00 L2 loss: 0.60185 Learning rate: 0.002 Mask loss: 0.14826 RPN box loss: 0.01422 RPN score loss: 0.00308 RPN total loss: 0.01729 Total loss: 1.0062 timestamp: 1654957492.829265 iteration: 55495 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13402 FastRCNN class loss: 0.09245 FastRCNN total loss: 0.22647 L1 loss: 0.0000e+00 L2 loss: 0.60184 Learning rate: 0.002 Mask loss: 0.12633 RPN box loss: 0.04056 RPN score loss: 0.00716 RPN total loss: 0.04773 Total loss: 1.00236 timestamp: 1654957496.1317656 iteration: 55500 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05741 FastRCNN class loss: 0.03486 FastRCNN total loss: 0.09226 L1 loss: 0.0000e+00 L2 loss: 0.60183 Learning rate: 0.002 Mask loss: 0.09772 RPN box loss: 0.00326 RPN score loss: 0.00261 RPN total loss: 0.00587 Total loss: 0.79768 timestamp: 1654957499.2965918 iteration: 55505 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04298 FastRCNN class loss: 0.05667 FastRCNN total loss: 0.09965 L1 loss: 0.0000e+00 L2 loss: 0.60182 Learning rate: 0.002 Mask loss: 0.12846 RPN box loss: 0.00662 RPN score loss: 0.00065 RPN total loss: 0.00727 Total loss: 0.8372 timestamp: 1654957502.5550685 iteration: 55510 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12314 FastRCNN class loss: 0.10657 FastRCNN total loss: 0.22972 L1 loss: 0.0000e+00 L2 loss: 0.60182 Learning rate: 0.002 Mask loss: 0.14764 RPN box loss: 0.02076 RPN score loss: 0.00786 RPN total loss: 0.02862 Total loss: 1.00779 timestamp: 1654957505.7138705 iteration: 55515 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09502 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.16731 L1 loss: 0.0000e+00 L2 loss: 0.60181 Learning rate: 0.002 Mask loss: 0.15762 RPN box loss: 0.01362 RPN score loss: 0.00914 RPN total loss: 0.02277 Total loss: 0.94951 timestamp: 1654957508.99767 iteration: 55520 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10861 FastRCNN class loss: 0.08753 FastRCNN total loss: 0.19614 L1 loss: 0.0000e+00 L2 loss: 0.6018 Learning rate: 0.002 Mask loss: 0.1921 RPN box loss: 0.01071 RPN score loss: 0.01072 RPN total loss: 0.02143 Total loss: 1.01147 timestamp: 1654957512.2259011 iteration: 55525 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09643 FastRCNN class loss: 0.07015 FastRCNN total loss: 0.16658 L1 loss: 0.0000e+00 L2 loss: 0.60179 Learning rate: 0.002 Mask loss: 0.09302 RPN box loss: 0.00708 RPN score loss: 0.00799 RPN total loss: 0.01506 Total loss: 0.87646 timestamp: 1654957515.555613 iteration: 55530 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12242 FastRCNN class loss: 0.06953 FastRCNN total loss: 0.19194 L1 loss: 0.0000e+00 L2 loss: 0.60178 Learning rate: 0.002 Mask loss: 0.17743 RPN box loss: 0.01339 RPN score loss: 0.00436 RPN total loss: 0.01774 Total loss: 0.98889 timestamp: 1654957518.8112917 iteration: 55535 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08589 FastRCNN class loss: 0.09564 FastRCNN total loss: 0.18153 L1 loss: 0.0000e+00 L2 loss: 0.60177 Learning rate: 0.002 Mask loss: 0.16292 RPN box loss: 0.02889 RPN score loss: 0.01632 RPN total loss: 0.04521 Total loss: 0.99143 timestamp: 1654957522.1277184 iteration: 55540 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09411 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.1758 L1 loss: 0.0000e+00 L2 loss: 0.60176 Learning rate: 0.002 Mask loss: 0.13546 RPN box loss: 0.02241 RPN score loss: 0.00785 RPN total loss: 0.03025 Total loss: 0.94327 timestamp: 1654957525.3813329 iteration: 55545 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16335 FastRCNN class loss: 0.10511 FastRCNN total loss: 0.26847 L1 loss: 0.0000e+00 L2 loss: 0.60176 Learning rate: 0.002 Mask loss: 0.15545 RPN box loss: 0.02636 RPN score loss: 0.0051 RPN total loss: 0.03146 Total loss: 1.05713 timestamp: 1654957528.6565917 iteration: 55550 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10019 FastRCNN class loss: 0.05293 FastRCNN total loss: 0.15312 L1 loss: 0.0000e+00 L2 loss: 0.60175 Learning rate: 0.002 Mask loss: 0.08286 RPN box loss: 0.00889 RPN score loss: 0.00157 RPN total loss: 0.01046 Total loss: 0.84819 timestamp: 1654957531.9098175 iteration: 55555 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13728 FastRCNN class loss: 0.12258 FastRCNN total loss: 0.25986 L1 loss: 0.0000e+00 L2 loss: 0.60174 Learning rate: 0.002 Mask loss: 0.23517 RPN box loss: 0.02081 RPN score loss: 0.0127 RPN total loss: 0.03351 Total loss: 1.13028 timestamp: 1654957535.0894308 iteration: 55560 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04464 FastRCNN class loss: 0.03296 FastRCNN total loss: 0.0776 L1 loss: 0.0000e+00 L2 loss: 0.60173 Learning rate: 0.002 Mask loss: 0.10286 RPN box loss: 0.00923 RPN score loss: 0.00962 RPN total loss: 0.01885 Total loss: 0.80104 timestamp: 1654957538.3817062 iteration: 55565 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15416 FastRCNN class loss: 0.07085 FastRCNN total loss: 0.22501 L1 loss: 0.0000e+00 L2 loss: 0.60172 Learning rate: 0.002 Mask loss: 0.15459 RPN box loss: 0.01443 RPN score loss: 0.0012 RPN total loss: 0.01564 Total loss: 0.99696 timestamp: 1654957541.569915 iteration: 55570 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05303 FastRCNN class loss: 0.04124 FastRCNN total loss: 0.09427 L1 loss: 0.0000e+00 L2 loss: 0.60171 Learning rate: 0.002 Mask loss: 0.1257 RPN box loss: 0.02171 RPN score loss: 0.00699 RPN total loss: 0.0287 Total loss: 0.85039 timestamp: 1654957544.808175 iteration: 55575 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14462 FastRCNN class loss: 0.09775 FastRCNN total loss: 0.24237 L1 loss: 0.0000e+00 L2 loss: 0.6017 Learning rate: 0.002 Mask loss: 0.10163 RPN box loss: 0.01467 RPN score loss: 0.00195 RPN total loss: 0.01661 Total loss: 0.96232 timestamp: 1654957548.0987735 iteration: 55580 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06465 FastRCNN class loss: 0.10254 FastRCNN total loss: 0.16719 L1 loss: 0.0000e+00 L2 loss: 0.6017 Learning rate: 0.002 Mask loss: 0.12018 RPN box loss: 0.01468 RPN score loss: 0.00499 RPN total loss: 0.01967 Total loss: 0.90874 timestamp: 1654957551.3723218 iteration: 55585 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10903 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.16737 L1 loss: 0.0000e+00 L2 loss: 0.60169 Learning rate: 0.002 Mask loss: 0.09381 RPN box loss: 0.00533 RPN score loss: 0.00139 RPN total loss: 0.00672 Total loss: 0.86959 timestamp: 1654957554.572914 iteration: 55590 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10481 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.17715 L1 loss: 0.0000e+00 L2 loss: 0.60168 Learning rate: 0.002 Mask loss: 0.1188 RPN box loss: 0.02527 RPN score loss: 0.01259 RPN total loss: 0.03786 Total loss: 0.93549 timestamp: 1654957557.8825796 iteration: 55595 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.07385 FastRCNN total loss: 0.14982 L1 loss: 0.0000e+00 L2 loss: 0.60167 Learning rate: 0.002 Mask loss: 0.14562 RPN box loss: 0.01745 RPN score loss: 0.00562 RPN total loss: 0.02307 Total loss: 0.92018 timestamp: 1654957561.176738 iteration: 55600 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10029 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.1834 L1 loss: 0.0000e+00 L2 loss: 0.60167 Learning rate: 0.002 Mask loss: 0.14825 RPN box loss: 0.02392 RPN score loss: 0.00354 RPN total loss: 0.02746 Total loss: 0.96078 timestamp: 1654957564.4536834 iteration: 55605 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06887 FastRCNN class loss: 0.03682 FastRCNN total loss: 0.10569 L1 loss: 0.0000e+00 L2 loss: 0.60166 Learning rate: 0.002 Mask loss: 0.09384 RPN box loss: 0.00317 RPN score loss: 0.00246 RPN total loss: 0.00563 Total loss: 0.80682 timestamp: 1654957567.7356076 iteration: 55610 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07352 FastRCNN class loss: 0.07849 FastRCNN total loss: 0.15201 L1 loss: 0.0000e+00 L2 loss: 0.60165 Learning rate: 0.002 Mask loss: 0.14002 RPN box loss: 0.01739 RPN score loss: 0.00279 RPN total loss: 0.02018 Total loss: 0.91386 timestamp: 1654957570.9636624 iteration: 55615 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12175 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.18804 L1 loss: 0.0000e+00 L2 loss: 0.60164 Learning rate: 0.002 Mask loss: 0.19072 RPN box loss: 0.01455 RPN score loss: 0.00198 RPN total loss: 0.01653 Total loss: 0.99693 timestamp: 1654957574.1988204 iteration: 55620 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13302 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.18881 L1 loss: 0.0000e+00 L2 loss: 0.60163 Learning rate: 0.002 Mask loss: 0.12399 RPN box loss: 0.01895 RPN score loss: 0.00572 RPN total loss: 0.02467 Total loss: 0.93911 timestamp: 1654957577.3770268 iteration: 55625 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12505 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.19032 L1 loss: 0.0000e+00 L2 loss: 0.60163 Learning rate: 0.002 Mask loss: 0.13997 RPN box loss: 0.01199 RPN score loss: 0.00249 RPN total loss: 0.01448 Total loss: 0.9464 timestamp: 1654957580.6589923 iteration: 55630 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09221 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.1825 L1 loss: 0.0000e+00 L2 loss: 0.60162 Learning rate: 0.002 Mask loss: 0.13304 RPN box loss: 0.01055 RPN score loss: 0.00813 RPN total loss: 0.01868 Total loss: 0.93583 timestamp: 1654957583.894321 iteration: 55635 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1298 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.20088 L1 loss: 0.0000e+00 L2 loss: 0.60161 Learning rate: 0.002 Mask loss: 0.18419 RPN box loss: 0.01067 RPN score loss: 0.00255 RPN total loss: 0.01322 Total loss: 0.9999 timestamp: 1654957587.1268935 iteration: 55640 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05361 FastRCNN class loss: 0.05853 FastRCNN total loss: 0.11214 L1 loss: 0.0000e+00 L2 loss: 0.6016 Learning rate: 0.002 Mask loss: 0.10006 RPN box loss: 0.0048 RPN score loss: 0.00174 RPN total loss: 0.00654 Total loss: 0.82033 timestamp: 1654957590.3102465 iteration: 55645 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07616 FastRCNN class loss: 0.04365 FastRCNN total loss: 0.11982 L1 loss: 0.0000e+00 L2 loss: 0.60159 Learning rate: 0.002 Mask loss: 0.12386 RPN box loss: 0.00951 RPN score loss: 0.00296 RPN total loss: 0.01247 Total loss: 0.85773 timestamp: 1654957593.5704105 iteration: 55650 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07198 FastRCNN class loss: 0.05749 FastRCNN total loss: 0.12947 L1 loss: 0.0000e+00 L2 loss: 0.60158 Learning rate: 0.002 Mask loss: 0.15207 RPN box loss: 0.01612 RPN score loss: 0.00305 RPN total loss: 0.01917 Total loss: 0.9023 timestamp: 1654957596.7449493 iteration: 55655 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12085 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.20354 L1 loss: 0.0000e+00 L2 loss: 0.60157 Learning rate: 0.002 Mask loss: 0.17231 RPN box loss: 0.02352 RPN score loss: 0.00804 RPN total loss: 0.03156 Total loss: 1.00898 timestamp: 1654957600.0973113 iteration: 55660 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10832 FastRCNN class loss: 0.0796 FastRCNN total loss: 0.18792 L1 loss: 0.0000e+00 L2 loss: 0.60157 Learning rate: 0.002 Mask loss: 0.14008 RPN box loss: 0.0235 RPN score loss: 0.00212 RPN total loss: 0.02562 Total loss: 0.95519 timestamp: 1654957603.2870376 iteration: 55665 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13263 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.21899 L1 loss: 0.0000e+00 L2 loss: 0.60156 Learning rate: 0.002 Mask loss: 0.14637 RPN box loss: 0.02688 RPN score loss: 0.01364 RPN total loss: 0.04052 Total loss: 1.00745 timestamp: 1654957606.467519 iteration: 55670 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07788 FastRCNN class loss: 0.04157 FastRCNN total loss: 0.11945 L1 loss: 0.0000e+00 L2 loss: 0.60155 Learning rate: 0.002 Mask loss: 0.08739 RPN box loss: 0.00772 RPN score loss: 0.0014 RPN total loss: 0.00911 Total loss: 0.81751 timestamp: 1654957609.752131 iteration: 55675 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04993 FastRCNN class loss: 0.05696 FastRCNN total loss: 0.10689 L1 loss: 0.0000e+00 L2 loss: 0.60154 Learning rate: 0.002 Mask loss: 0.14008 RPN box loss: 0.00402 RPN score loss: 0.00103 RPN total loss: 0.00504 Total loss: 0.85356 timestamp: 1654957612.9533424 iteration: 55680 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11952 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.1999 L1 loss: 0.0000e+00 L2 loss: 0.60154 Learning rate: 0.002 Mask loss: 0.16839 RPN box loss: 0.02144 RPN score loss: 0.00953 RPN total loss: 0.03097 Total loss: 1.0008 timestamp: 1654957616.2074056 iteration: 55685 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12498 FastRCNN class loss: 0.06936 FastRCNN total loss: 0.19434 L1 loss: 0.0000e+00 L2 loss: 0.60152 Learning rate: 0.002 Mask loss: 0.16608 RPN box loss: 0.0167 RPN score loss: 0.00674 RPN total loss: 0.02344 Total loss: 0.98538 timestamp: 1654957619.445501 iteration: 55690 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07251 FastRCNN class loss: 0.08265 FastRCNN total loss: 0.15515 L1 loss: 0.0000e+00 L2 loss: 0.60151 Learning rate: 0.002 Mask loss: 0.11159 RPN box loss: 0.01343 RPN score loss: 0.00294 RPN total loss: 0.01637 Total loss: 0.88463 timestamp: 1654957622.7738433 iteration: 55695 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08155 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.14365 L1 loss: 0.0000e+00 L2 loss: 0.6015 Learning rate: 0.002 Mask loss: 0.10234 RPN box loss: 0.02205 RPN score loss: 0.0116 RPN total loss: 0.03365 Total loss: 0.88114 timestamp: 1654957625.9225762 iteration: 55700 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15557 FastRCNN class loss: 0.09486 FastRCNN total loss: 0.25043 L1 loss: 0.0000e+00 L2 loss: 0.6015 Learning rate: 0.002 Mask loss: 0.14447 RPN box loss: 0.00448 RPN score loss: 0.00931 RPN total loss: 0.01379 Total loss: 1.01019 timestamp: 1654957629.2138338 iteration: 55705 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06912 FastRCNN class loss: 0.04735 FastRCNN total loss: 0.11647 L1 loss: 0.0000e+00 L2 loss: 0.60149 Learning rate: 0.002 Mask loss: 0.13554 RPN box loss: 0.00474 RPN score loss: 0.00427 RPN total loss: 0.00901 Total loss: 0.8625 timestamp: 1654957632.4489267 iteration: 55710 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10222 FastRCNN class loss: 0.06215 FastRCNN total loss: 0.16437 L1 loss: 0.0000e+00 L2 loss: 0.60148 Learning rate: 0.002 Mask loss: 0.19349 RPN box loss: 0.01333 RPN score loss: 0.00971 RPN total loss: 0.02304 Total loss: 0.98239 timestamp: 1654957635.6502302 iteration: 55715 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08542 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.1362 L1 loss: 0.0000e+00 L2 loss: 0.60147 Learning rate: 0.002 Mask loss: 0.12382 RPN box loss: 0.02201 RPN score loss: 0.00386 RPN total loss: 0.02586 Total loss: 0.88735 timestamp: 1654957638.9631064 iteration: 55720 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08647 FastRCNN class loss: 0.03673 FastRCNN total loss: 0.1232 L1 loss: 0.0000e+00 L2 loss: 0.60146 Learning rate: 0.002 Mask loss: 0.0941 RPN box loss: 0.00957 RPN score loss: 0.00058 RPN total loss: 0.01015 Total loss: 0.82891 timestamp: 1654957642.1279075 iteration: 55725 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05792 FastRCNN class loss: 0.04212 FastRCNN total loss: 0.10004 L1 loss: 0.0000e+00 L2 loss: 0.60145 Learning rate: 0.002 Mask loss: 0.11584 RPN box loss: 0.00709 RPN score loss: 0.00787 RPN total loss: 0.01495 Total loss: 0.83229 timestamp: 1654957645.3444948 iteration: 55730 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11316 FastRCNN class loss: 0.0817 FastRCNN total loss: 0.19486 L1 loss: 0.0000e+00 L2 loss: 0.60145 Learning rate: 0.002 Mask loss: 0.12658 RPN box loss: 0.01743 RPN score loss: 0.00113 RPN total loss: 0.01855 Total loss: 0.94144 timestamp: 1654957648.499319 iteration: 55735 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05883 FastRCNN class loss: 0.04568 FastRCNN total loss: 0.10451 L1 loss: 0.0000e+00 L2 loss: 0.60144 Learning rate: 0.002 Mask loss: 0.12075 RPN box loss: 0.02577 RPN score loss: 0.00312 RPN total loss: 0.02889 Total loss: 0.85559 timestamp: 1654957651.741062 iteration: 55740 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07155 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.13243 L1 loss: 0.0000e+00 L2 loss: 0.60143 Learning rate: 0.002 Mask loss: 0.12411 RPN box loss: 0.03111 RPN score loss: 0.01184 RPN total loss: 0.04295 Total loss: 0.90092 timestamp: 1654957654.876365 iteration: 55745 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09526 FastRCNN class loss: 0.05 FastRCNN total loss: 0.14526 L1 loss: 0.0000e+00 L2 loss: 0.60142 Learning rate: 0.002 Mask loss: 0.14152 RPN box loss: 0.00823 RPN score loss: 0.00456 RPN total loss: 0.01278 Total loss: 0.90099 timestamp: 1654957658.1224933 iteration: 55750 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07434 FastRCNN class loss: 0.09036 FastRCNN total loss: 0.16469 L1 loss: 0.0000e+00 L2 loss: 0.60141 Learning rate: 0.002 Mask loss: 0.14758 RPN box loss: 0.04465 RPN score loss: 0.00342 RPN total loss: 0.04807 Total loss: 0.96176 timestamp: 1654957661.337294 iteration: 55755 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06207 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.6014 Learning rate: 0.002 Mask loss: 0.11782 RPN box loss: 0.01595 RPN score loss: 0.00345 RPN total loss: 0.0194 Total loss: 0.88646 timestamp: 1654957664.6142137 iteration: 55760 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06853 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.12387 L1 loss: 0.0000e+00 L2 loss: 0.60139 Learning rate: 0.002 Mask loss: 0.15721 RPN box loss: 0.01305 RPN score loss: 0.00468 RPN total loss: 0.01774 Total loss: 0.90021 timestamp: 1654957667.8377695 iteration: 55765 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06479 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.12182 L1 loss: 0.0000e+00 L2 loss: 0.60138 Learning rate: 0.002 Mask loss: 0.15063 RPN box loss: 0.00491 RPN score loss: 0.00213 RPN total loss: 0.00704 Total loss: 0.88087 timestamp: 1654957671.1269338 iteration: 55770 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08317 FastRCNN class loss: 0.07675 FastRCNN total loss: 0.15993 L1 loss: 0.0000e+00 L2 loss: 0.60137 Learning rate: 0.002 Mask loss: 0.14893 RPN box loss: 0.03888 RPN score loss: 0.00548 RPN total loss: 0.04435 Total loss: 0.95458 timestamp: 1654957674.3260117 iteration: 55775 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07743 FastRCNN class loss: 0.06529 FastRCNN total loss: 0.14272 L1 loss: 0.0000e+00 L2 loss: 0.60137 Learning rate: 0.002 Mask loss: 0.13485 RPN box loss: 0.00779 RPN score loss: 0.00471 RPN total loss: 0.0125 Total loss: 0.89143 timestamp: 1654957677.6442637 iteration: 55780 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05868 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.11639 L1 loss: 0.0000e+00 L2 loss: 0.60136 Learning rate: 0.002 Mask loss: 0.11181 RPN box loss: 0.00712 RPN score loss: 0.00246 RPN total loss: 0.00957 Total loss: 0.83913 timestamp: 1654957680.8860333 iteration: 55785 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07455 FastRCNN class loss: 0.0526 FastRCNN total loss: 0.12715 L1 loss: 0.0000e+00 L2 loss: 0.60135 Learning rate: 0.002 Mask loss: 0.1241 RPN box loss: 0.00529 RPN score loss: 0.00497 RPN total loss: 0.01026 Total loss: 0.86287 timestamp: 1654957684.1950424 iteration: 55790 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09466 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.15417 L1 loss: 0.0000e+00 L2 loss: 0.60134 Learning rate: 0.002 Mask loss: 0.12871 RPN box loss: 0.0147 RPN score loss: 0.01093 RPN total loss: 0.02563 Total loss: 0.90985 timestamp: 1654957687.3574102 iteration: 55795 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05647 FastRCNN class loss: 0.03935 FastRCNN total loss: 0.09582 L1 loss: 0.0000e+00 L2 loss: 0.60132 Learning rate: 0.002 Mask loss: 0.10874 RPN box loss: 0.01296 RPN score loss: 0.00248 RPN total loss: 0.01544 Total loss: 0.82133 timestamp: 1654957690.5834982 iteration: 55800 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18905 FastRCNN class loss: 0.13757 FastRCNN total loss: 0.32661 L1 loss: 0.0000e+00 L2 loss: 0.60131 Learning rate: 0.002 Mask loss: 0.18229 RPN box loss: 0.01803 RPN score loss: 0.00498 RPN total loss: 0.02301 Total loss: 1.13323 timestamp: 1654957693.7671514 iteration: 55805 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1149 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.18768 L1 loss: 0.0000e+00 L2 loss: 0.6013 Learning rate: 0.002 Mask loss: 0.11985 RPN box loss: 0.06234 RPN score loss: 0.00296 RPN total loss: 0.0653 Total loss: 0.97413 timestamp: 1654957696.8992376 iteration: 55810 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12125 FastRCNN class loss: 0.1116 FastRCNN total loss: 0.23285 L1 loss: 0.0000e+00 L2 loss: 0.60129 Learning rate: 0.002 Mask loss: 0.18079 RPN box loss: 0.01745 RPN score loss: 0.01071 RPN total loss: 0.02816 Total loss: 1.0431 timestamp: 1654957700.2118394 iteration: 55815 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08487 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.16127 L1 loss: 0.0000e+00 L2 loss: 0.60129 Learning rate: 0.002 Mask loss: 0.17697 RPN box loss: 0.0211 RPN score loss: 0.01229 RPN total loss: 0.03339 Total loss: 0.97292 timestamp: 1654957703.3787124 iteration: 55820 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12852 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.20107 L1 loss: 0.0000e+00 L2 loss: 0.60128 Learning rate: 0.002 Mask loss: 0.11954 RPN box loss: 0.00536 RPN score loss: 0.00279 RPN total loss: 0.00815 Total loss: 0.93005 timestamp: 1654957706.658259 iteration: 55825 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04682 FastRCNN class loss: 0.05782 FastRCNN total loss: 0.10464 L1 loss: 0.0000e+00 L2 loss: 0.60128 Learning rate: 0.002 Mask loss: 0.1151 RPN box loss: 0.01092 RPN score loss: 0.00561 RPN total loss: 0.01653 Total loss: 0.83755 timestamp: 1654957709.8383577 iteration: 55830 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09664 FastRCNN class loss: 0.08352 FastRCNN total loss: 0.18016 L1 loss: 0.0000e+00 L2 loss: 0.60127 Learning rate: 0.002 Mask loss: 0.14629 RPN box loss: 0.03081 RPN score loss: 0.00466 RPN total loss: 0.03547 Total loss: 0.96319 timestamp: 1654957713.0113218 iteration: 55835 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10523 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.16776 L1 loss: 0.0000e+00 L2 loss: 0.60126 Learning rate: 0.002 Mask loss: 0.12325 RPN box loss: 0.01252 RPN score loss: 0.00143 RPN total loss: 0.01396 Total loss: 0.90622 timestamp: 1654957716.2898915 iteration: 55840 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09092 FastRCNN class loss: 0.05633 FastRCNN total loss: 0.14724 L1 loss: 0.0000e+00 L2 loss: 0.60125 Learning rate: 0.002 Mask loss: 0.28665 RPN box loss: 0.01766 RPN score loss: 0.01039 RPN total loss: 0.02806 Total loss: 1.0632 timestamp: 1654957719.536716 iteration: 55845 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07804 FastRCNN class loss: 0.06862 FastRCNN total loss: 0.14666 L1 loss: 0.0000e+00 L2 loss: 0.60124 Learning rate: 0.002 Mask loss: 0.15098 RPN box loss: 0.01226 RPN score loss: 0.00503 RPN total loss: 0.01729 Total loss: 0.91617 timestamp: 1654957722.7719655 iteration: 55850 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11782 FastRCNN class loss: 0.10982 FastRCNN total loss: 0.22763 L1 loss: 0.0000e+00 L2 loss: 0.60123 Learning rate: 0.002 Mask loss: 0.17686 RPN box loss: 0.02602 RPN score loss: 0.00622 RPN total loss: 0.03224 Total loss: 1.03797 timestamp: 1654957725.9362462 iteration: 55855 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.07857 FastRCNN total loss: 0.1795 L1 loss: 0.0000e+00 L2 loss: 0.60122 Learning rate: 0.002 Mask loss: 0.16082 RPN box loss: 0.01243 RPN score loss: 0.01178 RPN total loss: 0.02421 Total loss: 0.96575 timestamp: 1654957729.2963607 iteration: 55860 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08476 FastRCNN class loss: 0.04436 FastRCNN total loss: 0.12912 L1 loss: 0.0000e+00 L2 loss: 0.60122 Learning rate: 0.002 Mask loss: 0.07921 RPN box loss: 0.00828 RPN score loss: 0.00172 RPN total loss: 0.01001 Total loss: 0.81955 timestamp: 1654957732.4947467 iteration: 55865 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06969 FastRCNN class loss: 0.05714 FastRCNN total loss: 0.12683 L1 loss: 0.0000e+00 L2 loss: 0.60121 Learning rate: 0.002 Mask loss: 0.09475 RPN box loss: 0.00543 RPN score loss: 0.00136 RPN total loss: 0.00679 Total loss: 0.82958 timestamp: 1654957735.7977135 iteration: 55870 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06851 FastRCNN class loss: 0.08816 FastRCNN total loss: 0.15667 L1 loss: 0.0000e+00 L2 loss: 0.6012 Learning rate: 0.002 Mask loss: 0.08685 RPN box loss: 0.00525 RPN score loss: 0.0057 RPN total loss: 0.01096 Total loss: 0.85568 timestamp: 1654957739.0272038 iteration: 55875 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06361 FastRCNN class loss: 0.03994 FastRCNN total loss: 0.10354 L1 loss: 0.0000e+00 L2 loss: 0.60119 Learning rate: 0.002 Mask loss: 0.13056 RPN box loss: 0.00604 RPN score loss: 0.00744 RPN total loss: 0.01348 Total loss: 0.84878 timestamp: 1654957742.3591037 iteration: 55880 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08536 FastRCNN class loss: 0.05087 FastRCNN total loss: 0.13623 L1 loss: 0.0000e+00 L2 loss: 0.60119 Learning rate: 0.002 Mask loss: 0.10605 RPN box loss: 0.02353 RPN score loss: 0.00313 RPN total loss: 0.02666 Total loss: 0.87013 timestamp: 1654957745.6137717 iteration: 55885 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12552 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.2029 L1 loss: 0.0000e+00 L2 loss: 0.60118 Learning rate: 0.002 Mask loss: 0.18864 RPN box loss: 0.00842 RPN score loss: 0.01943 RPN total loss: 0.02784 Total loss: 1.02056 timestamp: 1654957748.9625874 iteration: 55890 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07501 FastRCNN class loss: 0.09009 FastRCNN total loss: 0.16509 L1 loss: 0.0000e+00 L2 loss: 0.60117 Learning rate: 0.002 Mask loss: 0.10671 RPN box loss: 0.0327 RPN score loss: 0.00614 RPN total loss: 0.03884 Total loss: 0.91181 timestamp: 1654957752.2569067 iteration: 55895 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10563 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.16428 L1 loss: 0.0000e+00 L2 loss: 0.60116 Learning rate: 0.002 Mask loss: 0.11075 RPN box loss: 0.0092 RPN score loss: 0.00202 RPN total loss: 0.01122 Total loss: 0.88741 timestamp: 1654957755.4516444 iteration: 55900 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1215 FastRCNN class loss: 0.05866 FastRCNN total loss: 0.18017 L1 loss: 0.0000e+00 L2 loss: 0.60115 Learning rate: 0.002 Mask loss: 0.11122 RPN box loss: 0.00888 RPN score loss: 0.0011 RPN total loss: 0.00998 Total loss: 0.90251 timestamp: 1654957758.8984168 iteration: 55905 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11904 FastRCNN class loss: 0.06701 FastRCNN total loss: 0.18605 L1 loss: 0.0000e+00 L2 loss: 0.60114 Learning rate: 0.002 Mask loss: 0.17628 RPN box loss: 0.02307 RPN score loss: 0.00655 RPN total loss: 0.02961 Total loss: 0.99308 timestamp: 1654957762.0778334 iteration: 55910 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18112 FastRCNN class loss: 0.08694 FastRCNN total loss: 0.26806 L1 loss: 0.0000e+00 L2 loss: 0.60113 Learning rate: 0.002 Mask loss: 0.12402 RPN box loss: 0.0089 RPN score loss: 0.00959 RPN total loss: 0.01848 Total loss: 1.01169 timestamp: 1654957765.4789336 iteration: 55915 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11657 FastRCNN class loss: 0.08295 FastRCNN total loss: 0.19952 L1 loss: 0.0000e+00 L2 loss: 0.60112 Learning rate: 0.002 Mask loss: 0.12702 RPN box loss: 0.01152 RPN score loss: 0.00535 RPN total loss: 0.01687 Total loss: 0.94454 timestamp: 1654957768.6479025 iteration: 55920 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07758 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.13487 L1 loss: 0.0000e+00 L2 loss: 0.60111 Learning rate: 0.002 Mask loss: 0.14033 RPN box loss: 0.0184 RPN score loss: 0.00197 RPN total loss: 0.02037 Total loss: 0.89669 timestamp: 1654957772.0329907 iteration: 55925 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.09027 FastRCNN total loss: 0.17055 L1 loss: 0.0000e+00 L2 loss: 0.60111 Learning rate: 0.002 Mask loss: 0.11481 RPN box loss: 0.01526 RPN score loss: 0.00768 RPN total loss: 0.02294 Total loss: 0.9094 timestamp: 1654957775.214609 iteration: 55930 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12575 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.22169 L1 loss: 0.0000e+00 L2 loss: 0.6011 Learning rate: 0.002 Mask loss: 0.15284 RPN box loss: 0.02131 RPN score loss: 0.00676 RPN total loss: 0.02806 Total loss: 1.00369 timestamp: 1654957778.5042114 iteration: 55935 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11119 FastRCNN class loss: 0.05241 FastRCNN total loss: 0.1636 L1 loss: 0.0000e+00 L2 loss: 0.60109 Learning rate: 0.002 Mask loss: 0.10087 RPN box loss: 0.02346 RPN score loss: 0.00569 RPN total loss: 0.02915 Total loss: 0.89471 timestamp: 1654957781.6769938 iteration: 55940 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0512 FastRCNN class loss: 0.04973 FastRCNN total loss: 0.10093 L1 loss: 0.0000e+00 L2 loss: 0.60108 Learning rate: 0.002 Mask loss: 0.15168 RPN box loss: 0.01487 RPN score loss: 0.00791 RPN total loss: 0.02278 Total loss: 0.87647 timestamp: 1654957785.023761 iteration: 55945 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10744 FastRCNN class loss: 0.09644 FastRCNN total loss: 0.20387 L1 loss: 0.0000e+00 L2 loss: 0.60107 Learning rate: 0.002 Mask loss: 0.151 RPN box loss: 0.02463 RPN score loss: 0.01265 RPN total loss: 0.03728 Total loss: 0.99323 timestamp: 1654957788.2491195 iteration: 55950 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12472 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.19364 L1 loss: 0.0000e+00 L2 loss: 0.60107 Learning rate: 0.002 Mask loss: 0.11468 RPN box loss: 0.02354 RPN score loss: 0.00629 RPN total loss: 0.02983 Total loss: 0.93922 timestamp: 1654957791.3874671 iteration: 55955 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15734 FastRCNN class loss: 0.07146 FastRCNN total loss: 0.22881 L1 loss: 0.0000e+00 L2 loss: 0.60106 Learning rate: 0.002 Mask loss: 0.13003 RPN box loss: 0.01771 RPN score loss: 0.00365 RPN total loss: 0.02137 Total loss: 0.98126 timestamp: 1654957794.6742997 iteration: 55960 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12678 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.19996 L1 loss: 0.0000e+00 L2 loss: 0.60105 Learning rate: 0.002 Mask loss: 0.15272 RPN box loss: 0.00625 RPN score loss: 0.00357 RPN total loss: 0.00982 Total loss: 0.96354 timestamp: 1654957797.9092648 iteration: 55965 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14376 FastRCNN class loss: 0.09802 FastRCNN total loss: 0.24178 L1 loss: 0.0000e+00 L2 loss: 0.60104 Learning rate: 0.002 Mask loss: 0.16533 RPN box loss: 0.01592 RPN score loss: 0.01585 RPN total loss: 0.03177 Total loss: 1.03993 timestamp: 1654957801.173263 iteration: 55970 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07179 FastRCNN class loss: 0.0343 FastRCNN total loss: 0.10609 L1 loss: 0.0000e+00 L2 loss: 0.60103 Learning rate: 0.002 Mask loss: 0.12354 RPN box loss: 0.00714 RPN score loss: 0.00077 RPN total loss: 0.00791 Total loss: 0.83857 timestamp: 1654957804.334143 iteration: 55975 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12012 FastRCNN class loss: 0.10358 FastRCNN total loss: 0.22369 L1 loss: 0.0000e+00 L2 loss: 0.60102 Learning rate: 0.002 Mask loss: 0.18358 RPN box loss: 0.01489 RPN score loss: 0.00451 RPN total loss: 0.0194 Total loss: 1.02769 timestamp: 1654957807.6163194 iteration: 55980 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08352 FastRCNN class loss: 0.04612 FastRCNN total loss: 0.12964 L1 loss: 0.0000e+00 L2 loss: 0.60101 Learning rate: 0.002 Mask loss: 0.15314 RPN box loss: 0.02735 RPN score loss: 0.00201 RPN total loss: 0.02937 Total loss: 0.91317 timestamp: 1654957810.824796 iteration: 55985 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10056 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.16043 L1 loss: 0.0000e+00 L2 loss: 0.601 Learning rate: 0.002 Mask loss: 0.16921 RPN box loss: 0.03255 RPN score loss: 0.00135 RPN total loss: 0.03391 Total loss: 0.96455 timestamp: 1654957814.206785 iteration: 55990 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13598 FastRCNN class loss: 0.0755 FastRCNN total loss: 0.21148 L1 loss: 0.0000e+00 L2 loss: 0.60099 Learning rate: 0.002 Mask loss: 0.10785 RPN box loss: 0.01316 RPN score loss: 0.00261 RPN total loss: 0.01577 Total loss: 0.93609 timestamp: 1654957817.4669065 iteration: 55995 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03262 FastRCNN class loss: 0.03113 FastRCNN total loss: 0.06375 L1 loss: 0.0000e+00 L2 loss: 0.60099 Learning rate: 0.002 Mask loss: 0.10564 RPN box loss: 0.00144 RPN score loss: 0.00094 RPN total loss: 0.00238 Total loss: 0.77276 timestamp: 1654957820.7167137 iteration: 56000 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.064 FastRCNN class loss: 0.04125 FastRCNN total loss: 0.10525 L1 loss: 0.0000e+00 L2 loss: 0.60098 Learning rate: 0.002 Mask loss: 0.12691 RPN box loss: 0.00687 RPN score loss: 0.001 RPN total loss: 0.00787 Total loss: 0.841 timestamp: 1654957824.039776 iteration: 56005 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10441 FastRCNN class loss: 0.05427 FastRCNN total loss: 0.15868 L1 loss: 0.0000e+00 L2 loss: 0.60097 Learning rate: 0.002 Mask loss: 0.08264 RPN box loss: 0.01242 RPN score loss: 0.00095 RPN total loss: 0.01337 Total loss: 0.85566 timestamp: 1654957827.242239 iteration: 56010 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08404 FastRCNN class loss: 0.10647 FastRCNN total loss: 0.19051 L1 loss: 0.0000e+00 L2 loss: 0.60096 Learning rate: 0.002 Mask loss: 0.16088 RPN box loss: 0.0263 RPN score loss: 0.00881 RPN total loss: 0.03512 Total loss: 0.98747 timestamp: 1654957830.5306695 iteration: 56015 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0991 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.17087 L1 loss: 0.0000e+00 L2 loss: 0.60096 Learning rate: 0.002 Mask loss: 0.13309 RPN box loss: 0.00582 RPN score loss: 0.00684 RPN total loss: 0.01265 Total loss: 0.91757 timestamp: 1654957833.751369 iteration: 56020 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13009 FastRCNN class loss: 0.06264 FastRCNN total loss: 0.19273 L1 loss: 0.0000e+00 L2 loss: 0.60095 Learning rate: 0.002 Mask loss: 0.14708 RPN box loss: 0.01802 RPN score loss: 0.0031 RPN total loss: 0.02112 Total loss: 0.96189 timestamp: 1654957837.0389698 iteration: 56025 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.183 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.25765 L1 loss: 0.0000e+00 L2 loss: 0.60094 Learning rate: 0.002 Mask loss: 0.10056 RPN box loss: 0.01603 RPN score loss: 0.00454 RPN total loss: 0.02056 Total loss: 0.97971 timestamp: 1654957840.2783594 iteration: 56030 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07013 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.1291 L1 loss: 0.0000e+00 L2 loss: 0.60093 Learning rate: 0.002 Mask loss: 0.22129 RPN box loss: 0.00925 RPN score loss: 0.00257 RPN total loss: 0.01182 Total loss: 0.96315 timestamp: 1654957843.511634 iteration: 56035 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06287 FastRCNN class loss: 0.09986 FastRCNN total loss: 0.16272 L1 loss: 0.0000e+00 L2 loss: 0.60092 Learning rate: 0.002 Mask loss: 0.14383 RPN box loss: 0.02284 RPN score loss: 0.00769 RPN total loss: 0.03053 Total loss: 0.93801 timestamp: 1654957846.7425127 iteration: 56040 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11748 FastRCNN class loss: 0.08022 FastRCNN total loss: 0.1977 L1 loss: 0.0000e+00 L2 loss: 0.60091 Learning rate: 0.002 Mask loss: 0.16245 RPN box loss: 0.00612 RPN score loss: 0.00438 RPN total loss: 0.01049 Total loss: 0.97155 timestamp: 1654957850.0486326 iteration: 56045 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09365 FastRCNN class loss: 0.075 FastRCNN total loss: 0.16865 L1 loss: 0.0000e+00 L2 loss: 0.6009 Learning rate: 0.002 Mask loss: 0.22763 RPN box loss: 0.01831 RPN score loss: 0.00806 RPN total loss: 0.02637 Total loss: 1.02355 timestamp: 1654957853.3381727 iteration: 56050 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08237 FastRCNN class loss: 0.04593 FastRCNN total loss: 0.12829 L1 loss: 0.0000e+00 L2 loss: 0.60089 Learning rate: 0.002 Mask loss: 0.17311 RPN box loss: 0.03031 RPN score loss: 0.00266 RPN total loss: 0.03297 Total loss: 0.93527 timestamp: 1654957856.5836165 iteration: 56055 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07384 FastRCNN class loss: 0.04914 FastRCNN total loss: 0.12298 L1 loss: 0.0000e+00 L2 loss: 0.60089 Learning rate: 0.002 Mask loss: 0.08799 RPN box loss: 0.01556 RPN score loss: 0.00384 RPN total loss: 0.01941 Total loss: 0.83126 timestamp: 1654957859.7468572 iteration: 56060 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11101 FastRCNN class loss: 0.07109 FastRCNN total loss: 0.1821 L1 loss: 0.0000e+00 L2 loss: 0.60088 Learning rate: 0.002 Mask loss: 0.14272 RPN box loss: 0.02447 RPN score loss: 0.00719 RPN total loss: 0.03166 Total loss: 0.95736 timestamp: 1654957862.9605641 iteration: 56065 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06454 FastRCNN class loss: 0.066 FastRCNN total loss: 0.13054 L1 loss: 0.0000e+00 L2 loss: 0.60087 Learning rate: 0.002 Mask loss: 0.10455 RPN box loss: 0.01128 RPN score loss: 0.00555 RPN total loss: 0.01683 Total loss: 0.85279 timestamp: 1654957866.371455 iteration: 56070 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12661 FastRCNN class loss: 0.1159 FastRCNN total loss: 0.24251 L1 loss: 0.0000e+00 L2 loss: 0.60086 Learning rate: 0.002 Mask loss: 0.14876 RPN box loss: 0.01382 RPN score loss: 0.00664 RPN total loss: 0.02046 Total loss: 1.0126 timestamp: 1654957869.5393581 iteration: 56075 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11446 FastRCNN class loss: 0.07957 FastRCNN total loss: 0.19403 L1 loss: 0.0000e+00 L2 loss: 0.60085 Learning rate: 0.002 Mask loss: 0.12019 RPN box loss: 0.00658 RPN score loss: 0.00405 RPN total loss: 0.01063 Total loss: 0.92569 timestamp: 1654957872.7750928 iteration: 56080 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09134 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.13692 L1 loss: 0.0000e+00 L2 loss: 0.60084 Learning rate: 0.002 Mask loss: 0.09754 RPN box loss: 0.00862 RPN score loss: 0.00177 RPN total loss: 0.01039 Total loss: 0.84569 timestamp: 1654957876.026548 iteration: 56085 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0658 FastRCNN class loss: 0.04817 FastRCNN total loss: 0.11397 L1 loss: 0.0000e+00 L2 loss: 0.60084 Learning rate: 0.002 Mask loss: 0.1121 RPN box loss: 0.0084 RPN score loss: 0.00385 RPN total loss: 0.01225 Total loss: 0.83916 timestamp: 1654957879.194845 iteration: 56090 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10002 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.1636 L1 loss: 0.0000e+00 L2 loss: 0.60083 Learning rate: 0.002 Mask loss: 0.13499 RPN box loss: 0.02418 RPN score loss: 0.00279 RPN total loss: 0.02698 Total loss: 0.92639 timestamp: 1654957882.4469004 iteration: 56095 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10096 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.16115 L1 loss: 0.0000e+00 L2 loss: 0.60082 Learning rate: 0.002 Mask loss: 0.178 RPN box loss: 0.02322 RPN score loss: 0.00221 RPN total loss: 0.02543 Total loss: 0.96539 timestamp: 1654957885.796624 iteration: 56100 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11102 FastRCNN class loss: 0.07854 FastRCNN total loss: 0.18956 L1 loss: 0.0000e+00 L2 loss: 0.60081 Learning rate: 0.002 Mask loss: 0.1451 RPN box loss: 0.01748 RPN score loss: 0.00569 RPN total loss: 0.02317 Total loss: 0.95863 timestamp: 1654957889.0211508 iteration: 56105 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07807 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.1497 L1 loss: 0.0000e+00 L2 loss: 0.6008 Learning rate: 0.002 Mask loss: 0.15922 RPN box loss: 0.01 RPN score loss: 0.00209 RPN total loss: 0.01209 Total loss: 0.92181 timestamp: 1654957892.290498 iteration: 56110 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08904 FastRCNN class loss: 0.04126 FastRCNN total loss: 0.1303 L1 loss: 0.0000e+00 L2 loss: 0.60079 Learning rate: 0.002 Mask loss: 0.06565 RPN box loss: 0.00824 RPN score loss: 0.00118 RPN total loss: 0.00942 Total loss: 0.80616 timestamp: 1654957895.632659 iteration: 56115 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07509 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.1353 L1 loss: 0.0000e+00 L2 loss: 0.60079 Learning rate: 0.002 Mask loss: 0.15988 RPN box loss: 0.01134 RPN score loss: 0.00294 RPN total loss: 0.01428 Total loss: 0.91025 timestamp: 1654957898.864034 iteration: 56120 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12477 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.20911 L1 loss: 0.0000e+00 L2 loss: 0.60078 Learning rate: 0.002 Mask loss: 0.11813 RPN box loss: 0.01323 RPN score loss: 0.00536 RPN total loss: 0.01859 Total loss: 0.94661 timestamp: 1654957902.2533758 iteration: 56125 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0959 FastRCNN class loss: 0.07377 FastRCNN total loss: 0.16966 L1 loss: 0.0000e+00 L2 loss: 0.60077 Learning rate: 0.002 Mask loss: 0.11443 RPN box loss: 0.00624 RPN score loss: 0.00447 RPN total loss: 0.01072 Total loss: 0.89558 timestamp: 1654957905.410844 iteration: 56130 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1513 FastRCNN class loss: 0.08512 FastRCNN total loss: 0.23641 L1 loss: 0.0000e+00 L2 loss: 0.60076 Learning rate: 0.002 Mask loss: 0.13822 RPN box loss: 0.01798 RPN score loss: 0.00652 RPN total loss: 0.0245 Total loss: 0.99989 timestamp: 1654957908.7258108 iteration: 56135 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06464 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.11588 L1 loss: 0.0000e+00 L2 loss: 0.60075 Learning rate: 0.002 Mask loss: 0.11977 RPN box loss: 0.0132 RPN score loss: 0.00443 RPN total loss: 0.01763 Total loss: 0.85403 timestamp: 1654957911.9097688 iteration: 56140 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08306 FastRCNN class loss: 0.05629 FastRCNN total loss: 0.13936 L1 loss: 0.0000e+00 L2 loss: 0.60074 Learning rate: 0.002 Mask loss: 0.08335 RPN box loss: 0.0097 RPN score loss: 0.00268 RPN total loss: 0.01238 Total loss: 0.83582 timestamp: 1654957915.2916794 iteration: 56145 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14323 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.22505 L1 loss: 0.0000e+00 L2 loss: 0.60073 Learning rate: 0.002 Mask loss: 0.13164 RPN box loss: 0.00784 RPN score loss: 0.00337 RPN total loss: 0.01121 Total loss: 0.96863 timestamp: 1654957918.5653474 iteration: 56150 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06498 FastRCNN class loss: 0.04671 FastRCNN total loss: 0.11169 L1 loss: 0.0000e+00 L2 loss: 0.60072 Learning rate: 0.002 Mask loss: 0.09095 RPN box loss: 0.01303 RPN score loss: 0.00499 RPN total loss: 0.01802 Total loss: 0.82138 timestamp: 1654957921.7645688 iteration: 56155 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08993 FastRCNN class loss: 0.07434 FastRCNN total loss: 0.16426 L1 loss: 0.0000e+00 L2 loss: 0.60071 Learning rate: 0.002 Mask loss: 0.10847 RPN box loss: 0.01175 RPN score loss: 0.00467 RPN total loss: 0.01641 Total loss: 0.88986 timestamp: 1654957924.9755886 iteration: 56160 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09301 FastRCNN class loss: 0.06268 FastRCNN total loss: 0.15569 L1 loss: 0.0000e+00 L2 loss: 0.6007 Learning rate: 0.002 Mask loss: 0.09216 RPN box loss: 0.00451 RPN score loss: 0.0018 RPN total loss: 0.00631 Total loss: 0.85486 timestamp: 1654957928.144135 iteration: 56165 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08445 FastRCNN class loss: 0.06108 FastRCNN total loss: 0.14553 L1 loss: 0.0000e+00 L2 loss: 0.6007 Learning rate: 0.002 Mask loss: 0.16114 RPN box loss: 0.01706 RPN score loss: 0.00497 RPN total loss: 0.02203 Total loss: 0.92939 timestamp: 1654957931.5090473 iteration: 56170 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15207 FastRCNN class loss: 0.11951 FastRCNN total loss: 0.27158 L1 loss: 0.0000e+00 L2 loss: 0.60069 Learning rate: 0.002 Mask loss: 0.1304 RPN box loss: 0.01317 RPN score loss: 0.00816 RPN total loss: 0.02133 Total loss: 1.024 timestamp: 1654957934.6210825 iteration: 56175 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13175 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.2062 L1 loss: 0.0000e+00 L2 loss: 0.60068 Learning rate: 0.002 Mask loss: 0.18201 RPN box loss: 0.01558 RPN score loss: 0.00688 RPN total loss: 0.02246 Total loss: 1.01136 timestamp: 1654957937.9449348 iteration: 56180 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06691 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.12261 L1 loss: 0.0000e+00 L2 loss: 0.60067 Learning rate: 0.002 Mask loss: 0.09031 RPN box loss: 0.00581 RPN score loss: 0.0074 RPN total loss: 0.01321 Total loss: 0.8268 timestamp: 1654957941.1632366 iteration: 56185 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14489 FastRCNN class loss: 0.136 FastRCNN total loss: 0.28088 L1 loss: 0.0000e+00 L2 loss: 0.60067 Learning rate: 0.002 Mask loss: 0.17723 RPN box loss: 0.03442 RPN score loss: 0.00829 RPN total loss: 0.04271 Total loss: 1.10149 timestamp: 1654957944.4212863 iteration: 56190 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0735 FastRCNN class loss: 0.05058 FastRCNN total loss: 0.12408 L1 loss: 0.0000e+00 L2 loss: 0.60066 Learning rate: 0.002 Mask loss: 0.17781 RPN box loss: 0.0188 RPN score loss: 0.0056 RPN total loss: 0.0244 Total loss: 0.92695 timestamp: 1654957947.624937 iteration: 56195 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07979 FastRCNN class loss: 0.04027 FastRCNN total loss: 0.12006 L1 loss: 0.0000e+00 L2 loss: 0.60065 Learning rate: 0.002 Mask loss: 0.12649 RPN box loss: 0.00814 RPN score loss: 0.00159 RPN total loss: 0.00972 Total loss: 0.85692 timestamp: 1654957950.9115622 iteration: 56200 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06013 FastRCNN class loss: 0.03995 FastRCNN total loss: 0.10009 L1 loss: 0.0000e+00 L2 loss: 0.60064 Learning rate: 0.002 Mask loss: 0.08914 RPN box loss: 0.00805 RPN score loss: 0.00114 RPN total loss: 0.00919 Total loss: 0.79906 timestamp: 1654957954.147815 iteration: 56205 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.13862 L1 loss: 0.0000e+00 L2 loss: 0.60063 Learning rate: 0.002 Mask loss: 0.11473 RPN box loss: 0.00586 RPN score loss: 0.00382 RPN total loss: 0.00968 Total loss: 0.86365 timestamp: 1654957957.4636624 iteration: 56210 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06356 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.12136 L1 loss: 0.0000e+00 L2 loss: 0.60062 Learning rate: 0.002 Mask loss: 0.11748 RPN box loss: 0.01116 RPN score loss: 0.00403 RPN total loss: 0.01519 Total loss: 0.85465 timestamp: 1654957960.785098 iteration: 56215 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10412 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.16244 L1 loss: 0.0000e+00 L2 loss: 0.60062 Learning rate: 0.002 Mask loss: 0.1302 RPN box loss: 0.02547 RPN score loss: 0.00477 RPN total loss: 0.03024 Total loss: 0.92351 timestamp: 1654957963.9576252 iteration: 56220 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06573 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.14068 L1 loss: 0.0000e+00 L2 loss: 0.60061 Learning rate: 0.002 Mask loss: 0.17011 RPN box loss: 0.00617 RPN score loss: 0.00463 RPN total loss: 0.0108 Total loss: 0.9222 timestamp: 1654957967.3408403 iteration: 56225 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09961 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.1631 L1 loss: 0.0000e+00 L2 loss: 0.6006 Learning rate: 0.002 Mask loss: 0.11534 RPN box loss: 0.00894 RPN score loss: 0.00506 RPN total loss: 0.01399 Total loss: 0.89303 timestamp: 1654957970.501893 iteration: 56230 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12733 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.20089 L1 loss: 0.0000e+00 L2 loss: 0.6006 Learning rate: 0.002 Mask loss: 0.12179 RPN box loss: 0.03242 RPN score loss: 0.00568 RPN total loss: 0.0381 Total loss: 0.96138 timestamp: 1654957973.7322676 iteration: 56235 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07506 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.16016 L1 loss: 0.0000e+00 L2 loss: 0.60059 Learning rate: 0.002 Mask loss: 0.15588 RPN box loss: 0.01097 RPN score loss: 0.0036 RPN total loss: 0.01458 Total loss: 0.93121 timestamp: 1654957976.9535859 iteration: 56240 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09975 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.18378 L1 loss: 0.0000e+00 L2 loss: 0.60058 Learning rate: 0.002 Mask loss: 0.13829 RPN box loss: 0.01566 RPN score loss: 0.0063 RPN total loss: 0.02196 Total loss: 0.94462 timestamp: 1654957980.2376695 iteration: 56245 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09648 FastRCNN class loss: 0.04096 FastRCNN total loss: 0.13744 L1 loss: 0.0000e+00 L2 loss: 0.60058 Learning rate: 0.002 Mask loss: 0.09595 RPN box loss: 0.00468 RPN score loss: 0.00167 RPN total loss: 0.00636 Total loss: 0.84032 timestamp: 1654957983.4487557 iteration: 56250 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08284 FastRCNN class loss: 0.04738 FastRCNN total loss: 0.13022 L1 loss: 0.0000e+00 L2 loss: 0.60057 Learning rate: 0.002 Mask loss: 0.13217 RPN box loss: 0.01065 RPN score loss: 0.00385 RPN total loss: 0.0145 Total loss: 0.87746 timestamp: 1654957986.8109965 iteration: 56255 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10933 FastRCNN class loss: 0.04876 FastRCNN total loss: 0.15809 L1 loss: 0.0000e+00 L2 loss: 0.60056 Learning rate: 0.002 Mask loss: 0.09795 RPN box loss: 0.00485 RPN score loss: 0.00239 RPN total loss: 0.00725 Total loss: 0.86384 timestamp: 1654957990.0429673 iteration: 56260 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09234 FastRCNN class loss: 0.11584 FastRCNN total loss: 0.20818 L1 loss: 0.0000e+00 L2 loss: 0.60055 Learning rate: 0.002 Mask loss: 0.15298 RPN box loss: 0.0276 RPN score loss: 0.00972 RPN total loss: 0.03732 Total loss: 0.99903 timestamp: 1654957993.3949392 iteration: 56265 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1289 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.20233 L1 loss: 0.0000e+00 L2 loss: 0.60054 Learning rate: 0.002 Mask loss: 0.13425 RPN box loss: 0.0088 RPN score loss: 0.00483 RPN total loss: 0.01363 Total loss: 0.95075 timestamp: 1654957996.6724622 iteration: 56270 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09408 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.14796 L1 loss: 0.0000e+00 L2 loss: 0.60053 Learning rate: 0.002 Mask loss: 0.13868 RPN box loss: 0.02126 RPN score loss: 0.00411 RPN total loss: 0.02537 Total loss: 0.91254 timestamp: 1654957999.9050398 iteration: 56275 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10047 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.1627 L1 loss: 0.0000e+00 L2 loss: 0.60052 Learning rate: 0.002 Mask loss: 0.08839 RPN box loss: 0.00922 RPN score loss: 0.00186 RPN total loss: 0.01108 Total loss: 0.86268 timestamp: 1654958003.1664953 iteration: 56280 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.066 FastRCNN class loss: 0.04415 FastRCNN total loss: 0.11015 L1 loss: 0.0000e+00 L2 loss: 0.60051 Learning rate: 0.002 Mask loss: 0.11625 RPN box loss: 0.00483 RPN score loss: 0.00232 RPN total loss: 0.00715 Total loss: 0.83405 timestamp: 1654958006.3862524 iteration: 56285 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10109 FastRCNN class loss: 0.08469 FastRCNN total loss: 0.18579 L1 loss: 0.0000e+00 L2 loss: 0.6005 Learning rate: 0.002 Mask loss: 0.12225 RPN box loss: 0.01076 RPN score loss: 0.01374 RPN total loss: 0.0245 Total loss: 0.93304 timestamp: 1654958009.620859 iteration: 56290 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08837 FastRCNN class loss: 0.05017 FastRCNN total loss: 0.13854 L1 loss: 0.0000e+00 L2 loss: 0.60049 Learning rate: 0.002 Mask loss: 0.17199 RPN box loss: 0.02318 RPN score loss: 0.00653 RPN total loss: 0.02971 Total loss: 0.94073 timestamp: 1654958012.8605022 iteration: 56295 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12848 FastRCNN class loss: 0.07075 FastRCNN total loss: 0.19923 L1 loss: 0.0000e+00 L2 loss: 0.60048 Learning rate: 0.002 Mask loss: 0.1299 RPN box loss: 0.01089 RPN score loss: 0.00398 RPN total loss: 0.01487 Total loss: 0.94448 timestamp: 1654958016.05702 iteration: 56300 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09049 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.16135 L1 loss: 0.0000e+00 L2 loss: 0.60047 Learning rate: 0.002 Mask loss: 0.14865 RPN box loss: 0.01613 RPN score loss: 0.00117 RPN total loss: 0.0173 Total loss: 0.92778 timestamp: 1654958019.246481 iteration: 56305 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.10715 FastRCNN total loss: 0.2003 L1 loss: 0.0000e+00 L2 loss: 0.60047 Learning rate: 0.002 Mask loss: 0.15349 RPN box loss: 0.01912 RPN score loss: 0.0055 RPN total loss: 0.02462 Total loss: 0.97887 timestamp: 1654958022.511557 iteration: 56310 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.20112 L1 loss: 0.0000e+00 L2 loss: 0.60046 Learning rate: 0.002 Mask loss: 0.24048 RPN box loss: 0.02371 RPN score loss: 0.00999 RPN total loss: 0.0337 Total loss: 1.07575 timestamp: 1654958025.7218924 iteration: 56315 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07563 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.13722 L1 loss: 0.0000e+00 L2 loss: 0.60045 Learning rate: 0.002 Mask loss: 0.11558 RPN box loss: 0.0032 RPN score loss: 0.00397 RPN total loss: 0.00717 Total loss: 0.86041 timestamp: 1654958029.0325491 iteration: 56320 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08461 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.20463 L1 loss: 0.0000e+00 L2 loss: 0.60044 Learning rate: 0.002 Mask loss: 0.1273 RPN box loss: 0.01835 RPN score loss: 0.00405 RPN total loss: 0.0224 Total loss: 0.95478 timestamp: 1654958032.464102 iteration: 56325 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08638 FastRCNN class loss: 0.05459 FastRCNN total loss: 0.14097 L1 loss: 0.0000e+00 L2 loss: 0.60044 Learning rate: 0.002 Mask loss: 0.10932 RPN box loss: 0.00954 RPN score loss: 0.00334 RPN total loss: 0.01288 Total loss: 0.8636 timestamp: 1654958035.7163312 iteration: 56330 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1481 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.23111 L1 loss: 0.0000e+00 L2 loss: 0.60043 Learning rate: 0.002 Mask loss: 0.14533 RPN box loss: 0.02516 RPN score loss: 0.00634 RPN total loss: 0.0315 Total loss: 1.00837 timestamp: 1654958038.9812012 iteration: 56335 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12029 FastRCNN class loss: 0.09318 FastRCNN total loss: 0.21348 L1 loss: 0.0000e+00 L2 loss: 0.60042 Learning rate: 0.002 Mask loss: 0.16599 RPN box loss: 0.03948 RPN score loss: 0.00874 RPN total loss: 0.04822 Total loss: 1.0281 timestamp: 1654958042.2409728 iteration: 56340 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04072 FastRCNN class loss: 0.04518 FastRCNN total loss: 0.0859 L1 loss: 0.0000e+00 L2 loss: 0.60041 Learning rate: 0.002 Mask loss: 0.10016 RPN box loss: 0.00469 RPN score loss: 0.00533 RPN total loss: 0.01002 Total loss: 0.79649 timestamp: 1654958045.64768 iteration: 56345 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08583 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.16617 L1 loss: 0.0000e+00 L2 loss: 0.6004 Learning rate: 0.002 Mask loss: 0.15748 RPN box loss: 0.01717 RPN score loss: 0.00266 RPN total loss: 0.01983 Total loss: 0.94388 timestamp: 1654958048.8591485 iteration: 56350 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0761 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.15307 L1 loss: 0.0000e+00 L2 loss: 0.60039 Learning rate: 0.002 Mask loss: 0.09319 RPN box loss: 0.03618 RPN score loss: 0.00585 RPN total loss: 0.04203 Total loss: 0.88869 timestamp: 1654958052.1557662 iteration: 56355 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13437 FastRCNN class loss: 0.12392 FastRCNN total loss: 0.25828 L1 loss: 0.0000e+00 L2 loss: 0.60038 Learning rate: 0.002 Mask loss: 0.13855 RPN box loss: 0.02887 RPN score loss: 0.01497 RPN total loss: 0.04384 Total loss: 1.04106 timestamp: 1654958055.292604 iteration: 56360 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15934 FastRCNN class loss: 0.0684 FastRCNN total loss: 0.22774 L1 loss: 0.0000e+00 L2 loss: 0.60037 Learning rate: 0.002 Mask loss: 0.11734 RPN box loss: 0.00727 RPN score loss: 0.01051 RPN total loss: 0.01778 Total loss: 0.96323 timestamp: 1654958058.6186366 iteration: 56365 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1313 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.20117 L1 loss: 0.0000e+00 L2 loss: 0.60036 Learning rate: 0.002 Mask loss: 0.14511 RPN box loss: 0.02096 RPN score loss: 0.00625 RPN total loss: 0.02721 Total loss: 0.97386 timestamp: 1654958061.8108916 iteration: 56370 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.07162 FastRCNN total loss: 0.14743 L1 loss: 0.0000e+00 L2 loss: 0.60036 Learning rate: 0.002 Mask loss: 0.12518 RPN box loss: 0.01486 RPN score loss: 0.00428 RPN total loss: 0.01914 Total loss: 0.8921 timestamp: 1654958065.0650127 iteration: 56375 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08799 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.13737 L1 loss: 0.0000e+00 L2 loss: 0.60035 Learning rate: 0.002 Mask loss: 0.09757 RPN box loss: 0.00392 RPN score loss: 0.00212 RPN total loss: 0.00603 Total loss: 0.84132 timestamp: 1654958068.3537738 iteration: 56380 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12713 FastRCNN class loss: 0.06126 FastRCNN total loss: 0.18838 L1 loss: 0.0000e+00 L2 loss: 0.60034 Learning rate: 0.002 Mask loss: 0.10102 RPN box loss: 0.01926 RPN score loss: 0.00293 RPN total loss: 0.02218 Total loss: 0.91192 timestamp: 1654958071.524308 iteration: 56385 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10561 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.16367 L1 loss: 0.0000e+00 L2 loss: 0.60033 Learning rate: 0.002 Mask loss: 0.17532 RPN box loss: 0.0082 RPN score loss: 0.00853 RPN total loss: 0.01673 Total loss: 0.95606 timestamp: 1654958074.7975163 iteration: 56390 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05957 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.10304 L1 loss: 0.0000e+00 L2 loss: 0.60032 Learning rate: 0.002 Mask loss: 0.14807 RPN box loss: 0.00825 RPN score loss: 0.00192 RPN total loss: 0.01017 Total loss: 0.8616 timestamp: 1654958077.9927063 iteration: 56395 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07895 FastRCNN class loss: 0.08696 FastRCNN total loss: 0.16592 L1 loss: 0.0000e+00 L2 loss: 0.60032 Learning rate: 0.002 Mask loss: 0.14064 RPN box loss: 0.00558 RPN score loss: 0.01091 RPN total loss: 0.01649 Total loss: 0.92336 timestamp: 1654958081.2693872 iteration: 56400 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09123 FastRCNN class loss: 0.06753 FastRCNN total loss: 0.15876 L1 loss: 0.0000e+00 L2 loss: 0.60031 Learning rate: 0.002 Mask loss: 0.12186 RPN box loss: 0.00948 RPN score loss: 0.00272 RPN total loss: 0.0122 Total loss: 0.89313 timestamp: 1654958084.4339159 iteration: 56405 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08552 FastRCNN class loss: 0.08784 FastRCNN total loss: 0.17336 L1 loss: 0.0000e+00 L2 loss: 0.6003 Learning rate: 0.002 Mask loss: 0.14081 RPN box loss: 0.01261 RPN score loss: 0.00777 RPN total loss: 0.02038 Total loss: 0.93486 timestamp: 1654958087.6279054 iteration: 56410 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06443 FastRCNN class loss: 0.05821 FastRCNN total loss: 0.12265 L1 loss: 0.0000e+00 L2 loss: 0.60029 Learning rate: 0.002 Mask loss: 0.11514 RPN box loss: 0.01048 RPN score loss: 0.00986 RPN total loss: 0.02033 Total loss: 0.85841 timestamp: 1654958090.8168116 iteration: 56415 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08881 FastRCNN class loss: 0.07766 FastRCNN total loss: 0.16647 L1 loss: 0.0000e+00 L2 loss: 0.60028 Learning rate: 0.002 Mask loss: 0.16863 RPN box loss: 0.01613 RPN score loss: 0.00794 RPN total loss: 0.02408 Total loss: 0.95946 timestamp: 1654958094.1273856 iteration: 56420 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08706 FastRCNN class loss: 0.0677 FastRCNN total loss: 0.15477 L1 loss: 0.0000e+00 L2 loss: 0.60027 Learning rate: 0.002 Mask loss: 0.11948 RPN box loss: 0.01012 RPN score loss: 0.00346 RPN total loss: 0.01358 Total loss: 0.8881 timestamp: 1654958097.3411338 iteration: 56425 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13472 FastRCNN class loss: 0.08941 FastRCNN total loss: 0.22413 L1 loss: 0.0000e+00 L2 loss: 0.60027 Learning rate: 0.002 Mask loss: 0.17791 RPN box loss: 0.01325 RPN score loss: 0.00287 RPN total loss: 0.01612 Total loss: 1.01843 timestamp: 1654958100.5665267 iteration: 56430 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09632 FastRCNN class loss: 0.06039 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.60026 Learning rate: 0.002 Mask loss: 0.10799 RPN box loss: 0.0086 RPN score loss: 0.01004 RPN total loss: 0.01864 Total loss: 0.88359 timestamp: 1654958103.7118053 iteration: 56435 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09231 FastRCNN class loss: 0.07041 FastRCNN total loss: 0.16272 L1 loss: 0.0000e+00 L2 loss: 0.60025 Learning rate: 0.002 Mask loss: 0.157 RPN box loss: 0.00734 RPN score loss: 0.00744 RPN total loss: 0.01478 Total loss: 0.93475 timestamp: 1654958106.9938955 iteration: 56440 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08113 FastRCNN class loss: 0.06419 FastRCNN total loss: 0.14532 L1 loss: 0.0000e+00 L2 loss: 0.60024 Learning rate: 0.002 Mask loss: 0.12693 RPN box loss: 0.01155 RPN score loss: 0.00229 RPN total loss: 0.01385 Total loss: 0.88634 timestamp: 1654958110.267152 iteration: 56445 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1153 FastRCNN class loss: 0.06083 FastRCNN total loss: 0.17613 L1 loss: 0.0000e+00 L2 loss: 0.60024 Learning rate: 0.002 Mask loss: 0.12115 RPN box loss: 0.01406 RPN score loss: 0.0021 RPN total loss: 0.01616 Total loss: 0.91368 timestamp: 1654958113.4048555 iteration: 56450 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08511 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.17477 L1 loss: 0.0000e+00 L2 loss: 0.60023 Learning rate: 0.002 Mask loss: 0.15307 RPN box loss: 0.011 RPN score loss: 0.00484 RPN total loss: 0.01584 Total loss: 0.94391 timestamp: 1654958116.6411147 iteration: 56455 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07725 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.13781 L1 loss: 0.0000e+00 L2 loss: 0.60022 Learning rate: 0.002 Mask loss: 0.13734 RPN box loss: 0.00782 RPN score loss: 0.00265 RPN total loss: 0.01047 Total loss: 0.88583 timestamp: 1654958119.8437839 iteration: 56460 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13945 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.2135 L1 loss: 0.0000e+00 L2 loss: 0.60021 Learning rate: 0.002 Mask loss: 0.12935 RPN box loss: 0.0181 RPN score loss: 0.00426 RPN total loss: 0.02236 Total loss: 0.96542 timestamp: 1654958122.9989064 iteration: 56465 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10878 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.17753 L1 loss: 0.0000e+00 L2 loss: 0.6002 Learning rate: 0.002 Mask loss: 0.14304 RPN box loss: 0.00922 RPN score loss: 0.00845 RPN total loss: 0.01767 Total loss: 0.93844 timestamp: 1654958126.2407768 iteration: 56470 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10024 FastRCNN class loss: 0.06608 FastRCNN total loss: 0.16632 L1 loss: 0.0000e+00 L2 loss: 0.60019 Learning rate: 0.002 Mask loss: 0.15626 RPN box loss: 0.00896 RPN score loss: 0.00131 RPN total loss: 0.01027 Total loss: 0.93303 timestamp: 1654958129.5070481 iteration: 56475 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06746 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.12041 L1 loss: 0.0000e+00 L2 loss: 0.60018 Learning rate: 0.002 Mask loss: 0.10151 RPN box loss: 0.01243 RPN score loss: 0.00396 RPN total loss: 0.01639 Total loss: 0.83849 timestamp: 1654958132.6296244 iteration: 56480 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11352 FastRCNN class loss: 0.07382 FastRCNN total loss: 0.18734 L1 loss: 0.0000e+00 L2 loss: 0.60016 Learning rate: 0.002 Mask loss: 0.10176 RPN box loss: 0.00396 RPN score loss: 0.0057 RPN total loss: 0.00966 Total loss: 0.89892 timestamp: 1654958135.9914424 iteration: 56485 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08728 FastRCNN class loss: 0.05309 FastRCNN total loss: 0.14037 L1 loss: 0.0000e+00 L2 loss: 0.60016 Learning rate: 0.002 Mask loss: 0.13003 RPN box loss: 0.00898 RPN score loss: 0.0024 RPN total loss: 0.01138 Total loss: 0.88193 timestamp: 1654958139.2199557 iteration: 56490 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10907 FastRCNN class loss: 0.08367 FastRCNN total loss: 0.19274 L1 loss: 0.0000e+00 L2 loss: 0.60015 Learning rate: 0.002 Mask loss: 0.15718 RPN box loss: 0.02845 RPN score loss: 0.014 RPN total loss: 0.04244 Total loss: 0.9925 timestamp: 1654958142.4387565 iteration: 56495 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.06214 FastRCNN total loss: 0.19814 L1 loss: 0.0000e+00 L2 loss: 0.60014 Learning rate: 0.002 Mask loss: 0.13931 RPN box loss: 0.00565 RPN score loss: 0.00275 RPN total loss: 0.0084 Total loss: 0.94598 timestamp: 1654958145.6019044 iteration: 56500 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08524 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.13875 L1 loss: 0.0000e+00 L2 loss: 0.60013 Learning rate: 0.002 Mask loss: 0.13058 RPN box loss: 0.00563 RPN score loss: 0.00509 RPN total loss: 0.01072 Total loss: 0.88018 timestamp: 1654958148.8026586 iteration: 56505 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.073 FastRCNN class loss: 0.05254 FastRCNN total loss: 0.12554 L1 loss: 0.0000e+00 L2 loss: 0.60012 Learning rate: 0.002 Mask loss: 0.14028 RPN box loss: 0.03004 RPN score loss: 0.01 RPN total loss: 0.04005 Total loss: 0.90599 timestamp: 1654958152.0796833 iteration: 56510 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12794 FastRCNN class loss: 0.07768 FastRCNN total loss: 0.20562 L1 loss: 0.0000e+00 L2 loss: 0.60011 Learning rate: 0.002 Mask loss: 0.10993 RPN box loss: 0.0111 RPN score loss: 0.0074 RPN total loss: 0.01849 Total loss: 0.93416 timestamp: 1654958155.2224205 iteration: 56515 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13227 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.20546 L1 loss: 0.0000e+00 L2 loss: 0.60011 Learning rate: 0.002 Mask loss: 0.15381 RPN box loss: 0.01017 RPN score loss: 0.00122 RPN total loss: 0.0114 Total loss: 0.97077 timestamp: 1654958158.4047232 iteration: 56520 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09341 FastRCNN class loss: 0.05503 FastRCNN total loss: 0.14844 L1 loss: 0.0000e+00 L2 loss: 0.6001 Learning rate: 0.002 Mask loss: 0.1297 RPN box loss: 0.00836 RPN score loss: 0.00165 RPN total loss: 0.01001 Total loss: 0.88825 timestamp: 1654958161.6388812 iteration: 56525 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0858 FastRCNN class loss: 0.07737 FastRCNN total loss: 0.16317 L1 loss: 0.0000e+00 L2 loss: 0.60009 Learning rate: 0.002 Mask loss: 0.14709 RPN box loss: 0.01266 RPN score loss: 0.00219 RPN total loss: 0.01485 Total loss: 0.9252 timestamp: 1654958164.9645782 iteration: 56530 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09824 FastRCNN class loss: 0.08597 FastRCNN total loss: 0.18421 L1 loss: 0.0000e+00 L2 loss: 0.60009 Learning rate: 0.002 Mask loss: 0.10696 RPN box loss: 0.01543 RPN score loss: 0.00309 RPN total loss: 0.01851 Total loss: 0.90977 timestamp: 1654958168.1433432 iteration: 56535 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0761 FastRCNN class loss: 0.09736 FastRCNN total loss: 0.17346 L1 loss: 0.0000e+00 L2 loss: 0.60008 Learning rate: 0.002 Mask loss: 0.18304 RPN box loss: 0.01002 RPN score loss: 0.00216 RPN total loss: 0.01218 Total loss: 0.96876 timestamp: 1654958171.4885762 iteration: 56540 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13238 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.2085 L1 loss: 0.0000e+00 L2 loss: 0.60007 Learning rate: 0.002 Mask loss: 0.15813 RPN box loss: 0.01413 RPN score loss: 0.00632 RPN total loss: 0.02045 Total loss: 0.98716 timestamp: 1654958174.6800416 iteration: 56545 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1503 FastRCNN class loss: 0.12882 FastRCNN total loss: 0.27912 L1 loss: 0.0000e+00 L2 loss: 0.60006 Learning rate: 0.002 Mask loss: 0.20335 RPN box loss: 0.03769 RPN score loss: 0.03062 RPN total loss: 0.0683 Total loss: 1.15084 timestamp: 1654958177.996431 iteration: 56550 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07307 FastRCNN class loss: 0.03466 FastRCNN total loss: 0.10773 L1 loss: 0.0000e+00 L2 loss: 0.60005 Learning rate: 0.002 Mask loss: 0.11256 RPN box loss: 0.01458 RPN score loss: 0.00522 RPN total loss: 0.0198 Total loss: 0.84014 timestamp: 1654958181.2338665 iteration: 56555 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04863 FastRCNN class loss: 0.0402 FastRCNN total loss: 0.08884 L1 loss: 0.0000e+00 L2 loss: 0.60004 Learning rate: 0.002 Mask loss: 0.11314 RPN box loss: 0.00397 RPN score loss: 0.00164 RPN total loss: 0.00561 Total loss: 0.80762 timestamp: 1654958184.4207556 iteration: 56560 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.04342 FastRCNN total loss: 0.1158 L1 loss: 0.0000e+00 L2 loss: 0.60003 Learning rate: 0.002 Mask loss: 0.14518 RPN box loss: 0.00557 RPN score loss: 0.00395 RPN total loss: 0.00952 Total loss: 0.87053 timestamp: 1654958187.7201004 iteration: 56565 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05528 FastRCNN class loss: 0.04489 FastRCNN total loss: 0.10017 L1 loss: 0.0000e+00 L2 loss: 0.60002 Learning rate: 0.002 Mask loss: 0.13016 RPN box loss: 0.00918 RPN score loss: 0.00186 RPN total loss: 0.01104 Total loss: 0.84139 timestamp: 1654958190.9545498 iteration: 56570 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06097 FastRCNN class loss: 0.05366 FastRCNN total loss: 0.11463 L1 loss: 0.0000e+00 L2 loss: 0.60001 Learning rate: 0.002 Mask loss: 0.09405 RPN box loss: 0.00515 RPN score loss: 0.0024 RPN total loss: 0.00755 Total loss: 0.81625 timestamp: 1654958194.3241317 iteration: 56575 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05876 FastRCNN class loss: 0.04802 FastRCNN total loss: 0.10679 L1 loss: 0.0000e+00 L2 loss: 0.60001 Learning rate: 0.002 Mask loss: 0.10688 RPN box loss: 0.00584 RPN score loss: 0.00416 RPN total loss: 0.00999 Total loss: 0.82366 timestamp: 1654958197.546613 iteration: 56580 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09111 FastRCNN class loss: 0.04118 FastRCNN total loss: 0.13228 L1 loss: 0.0000e+00 L2 loss: 0.6 Learning rate: 0.002 Mask loss: 0.09807 RPN box loss: 0.00505 RPN score loss: 0.00174 RPN total loss: 0.00679 Total loss: 0.83714 timestamp: 1654958200.9025466 iteration: 56585 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.077 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.1577 L1 loss: 0.0000e+00 L2 loss: 0.59999 Learning rate: 0.002 Mask loss: 0.13075 RPN box loss: 0.01026 RPN score loss: 0.00675 RPN total loss: 0.01701 Total loss: 0.90545 timestamp: 1654958204.0859866 iteration: 56590 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06368 FastRCNN class loss: 0.0486 FastRCNN total loss: 0.11227 L1 loss: 0.0000e+00 L2 loss: 0.59998 Learning rate: 0.002 Mask loss: 0.15342 RPN box loss: 0.0032 RPN score loss: 0.0027 RPN total loss: 0.0059 Total loss: 0.87158 timestamp: 1654958207.4566457 iteration: 56595 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14796 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.23617 L1 loss: 0.0000e+00 L2 loss: 0.59997 Learning rate: 0.002 Mask loss: 0.13757 RPN box loss: 0.01631 RPN score loss: 0.0047 RPN total loss: 0.02101 Total loss: 0.99471 timestamp: 1654958210.6378582 iteration: 56600 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.19802 L1 loss: 0.0000e+00 L2 loss: 0.59997 Learning rate: 0.002 Mask loss: 0.14225 RPN box loss: 0.02183 RPN score loss: 0.01395 RPN total loss: 0.03578 Total loss: 0.97602 timestamp: 1654958213.8773293 iteration: 56605 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04919 FastRCNN class loss: 0.04505 FastRCNN total loss: 0.09423 L1 loss: 0.0000e+00 L2 loss: 0.59996 Learning rate: 0.002 Mask loss: 0.09264 RPN box loss: 0.00993 RPN score loss: 0.00156 RPN total loss: 0.01149 Total loss: 0.79832 timestamp: 1654958217.0603483 iteration: 56610 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11921 FastRCNN class loss: 0.08002 FastRCNN total loss: 0.19923 L1 loss: 0.0000e+00 L2 loss: 0.59995 Learning rate: 0.002 Mask loss: 0.11519 RPN box loss: 0.02849 RPN score loss: 0.00279 RPN total loss: 0.03127 Total loss: 0.94565 timestamp: 1654958220.334443 iteration: 56615 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08607 FastRCNN class loss: 0.12546 FastRCNN total loss: 0.21153 L1 loss: 0.0000e+00 L2 loss: 0.59994 Learning rate: 0.002 Mask loss: 0.17501 RPN box loss: 0.01296 RPN score loss: 0.00969 RPN total loss: 0.02264 Total loss: 1.00912 timestamp: 1654958223.5469923 iteration: 56620 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11731 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.18612 L1 loss: 0.0000e+00 L2 loss: 0.59993 Learning rate: 0.002 Mask loss: 0.09652 RPN box loss: 0.05568 RPN score loss: 0.00596 RPN total loss: 0.06164 Total loss: 0.94421 timestamp: 1654958226.7392874 iteration: 56625 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0861 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.16091 L1 loss: 0.0000e+00 L2 loss: 0.59992 Learning rate: 0.002 Mask loss: 0.16359 RPN box loss: 0.02874 RPN score loss: 0.00558 RPN total loss: 0.03431 Total loss: 0.95874 timestamp: 1654958230.0282698 iteration: 56630 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07399 FastRCNN class loss: 0.04662 FastRCNN total loss: 0.12061 L1 loss: 0.0000e+00 L2 loss: 0.59991 Learning rate: 0.002 Mask loss: 0.17366 RPN box loss: 0.00909 RPN score loss: 0.0029 RPN total loss: 0.01199 Total loss: 0.90617 timestamp: 1654958233.19371 iteration: 56635 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06664 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.11708 L1 loss: 0.0000e+00 L2 loss: 0.59991 Learning rate: 0.002 Mask loss: 0.10698 RPN box loss: 0.01039 RPN score loss: 0.00805 RPN total loss: 0.01844 Total loss: 0.8424 timestamp: 1654958236.4902184 iteration: 56640 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11981 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.20397 L1 loss: 0.0000e+00 L2 loss: 0.5999 Learning rate: 0.002 Mask loss: 0.17101 RPN box loss: 0.01968 RPN score loss: 0.01391 RPN total loss: 0.03359 Total loss: 1.00847 timestamp: 1654958239.7121646 iteration: 56645 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10034 FastRCNN class loss: 0.09858 FastRCNN total loss: 0.19892 L1 loss: 0.0000e+00 L2 loss: 0.59989 Learning rate: 0.002 Mask loss: 0.15197 RPN box loss: 0.01672 RPN score loss: 0.01036 RPN total loss: 0.02708 Total loss: 0.97786 timestamp: 1654958242.9800494 iteration: 56650 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17613 FastRCNN class loss: 0.07969 FastRCNN total loss: 0.25582 L1 loss: 0.0000e+00 L2 loss: 0.59988 Learning rate: 0.002 Mask loss: 0.12271 RPN box loss: 0.02322 RPN score loss: 0.01332 RPN total loss: 0.03654 Total loss: 1.01494 timestamp: 1654958246.1808543 iteration: 56655 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10919 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.1666 L1 loss: 0.0000e+00 L2 loss: 0.59987 Learning rate: 0.002 Mask loss: 0.09846 RPN box loss: 0.01266 RPN score loss: 0.00746 RPN total loss: 0.02012 Total loss: 0.88505 timestamp: 1654958249.4294295 iteration: 56660 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08537 FastRCNN class loss: 0.04724 FastRCNN total loss: 0.13261 L1 loss: 0.0000e+00 L2 loss: 0.59986 Learning rate: 0.002 Mask loss: 0.10788 RPN box loss: 0.0357 RPN score loss: 0.00077 RPN total loss: 0.03647 Total loss: 0.87682 timestamp: 1654958252.6168349 iteration: 56665 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06142 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.11727 L1 loss: 0.0000e+00 L2 loss: 0.59985 Learning rate: 0.002 Mask loss: 0.12904 RPN box loss: 0.0049 RPN score loss: 0.00133 RPN total loss: 0.00623 Total loss: 0.8524 timestamp: 1654958255.9159846 iteration: 56670 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08618 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.15914 L1 loss: 0.0000e+00 L2 loss: 0.59984 Learning rate: 0.002 Mask loss: 0.12609 RPN box loss: 0.00489 RPN score loss: 0.00212 RPN total loss: 0.00701 Total loss: 0.89208 timestamp: 1654958259.3592887 iteration: 56675 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12234 FastRCNN class loss: 0.0844 FastRCNN total loss: 0.20674 L1 loss: 0.0000e+00 L2 loss: 0.59984 Learning rate: 0.002 Mask loss: 0.13473 RPN box loss: 0.00762 RPN score loss: 0.00099 RPN total loss: 0.00861 Total loss: 0.94992 timestamp: 1654958262.592437 iteration: 56680 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08224 FastRCNN class loss: 0.04788 FastRCNN total loss: 0.13012 L1 loss: 0.0000e+00 L2 loss: 0.59983 Learning rate: 0.002 Mask loss: 0.12658 RPN box loss: 0.0078 RPN score loss: 0.00731 RPN total loss: 0.01512 Total loss: 0.87165 timestamp: 1654958265.876003 iteration: 56685 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0953 FastRCNN class loss: 0.07155 FastRCNN total loss: 0.16685 L1 loss: 0.0000e+00 L2 loss: 0.59982 Learning rate: 0.002 Mask loss: 0.15466 RPN box loss: 0.02168 RPN score loss: 0.0053 RPN total loss: 0.02698 Total loss: 0.94831 timestamp: 1654958269.0920265 iteration: 56690 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13092 FastRCNN class loss: 0.08716 FastRCNN total loss: 0.21808 L1 loss: 0.0000e+00 L2 loss: 0.59981 Learning rate: 0.002 Mask loss: 0.11101 RPN box loss: 0.02303 RPN score loss: 0.00662 RPN total loss: 0.02966 Total loss: 0.95856 timestamp: 1654958272.423851 iteration: 56695 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1312 FastRCNN class loss: 0.09092 FastRCNN total loss: 0.22212 L1 loss: 0.0000e+00 L2 loss: 0.5998 Learning rate: 0.002 Mask loss: 0.21582 RPN box loss: 0.02172 RPN score loss: 0.00686 RPN total loss: 0.02858 Total loss: 1.06632 timestamp: 1654958275.6662211 iteration: 56700 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0552 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.12279 L1 loss: 0.0000e+00 L2 loss: 0.59979 Learning rate: 0.002 Mask loss: 0.15086 RPN box loss: 0.01452 RPN score loss: 0.00112 RPN total loss: 0.01564 Total loss: 0.88908 timestamp: 1654958278.9321334 iteration: 56705 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09307 FastRCNN class loss: 0.08382 FastRCNN total loss: 0.17689 L1 loss: 0.0000e+00 L2 loss: 0.59979 Learning rate: 0.002 Mask loss: 0.1014 RPN box loss: 0.00566 RPN score loss: 0.00259 RPN total loss: 0.00825 Total loss: 0.88632 timestamp: 1654958282.1115282 iteration: 56710 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07715 FastRCNN class loss: 0.06351 FastRCNN total loss: 0.14066 L1 loss: 0.0000e+00 L2 loss: 0.59978 Learning rate: 0.002 Mask loss: 0.16794 RPN box loss: 0.0263 RPN score loss: 0.00752 RPN total loss: 0.03381 Total loss: 0.94219 timestamp: 1654958285.4502876 iteration: 56715 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05175 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.11138 L1 loss: 0.0000e+00 L2 loss: 0.59977 Learning rate: 0.002 Mask loss: 0.14211 RPN box loss: 0.01276 RPN score loss: 0.00302 RPN total loss: 0.01578 Total loss: 0.86904 timestamp: 1654958288.7454317 iteration: 56720 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07437 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.14196 L1 loss: 0.0000e+00 L2 loss: 0.59977 Learning rate: 0.002 Mask loss: 0.11635 RPN box loss: 0.01517 RPN score loss: 0.00242 RPN total loss: 0.01759 Total loss: 0.87567 timestamp: 1654958291.9087007 iteration: 56725 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12 FastRCNN class loss: 0.09777 FastRCNN total loss: 0.21777 L1 loss: 0.0000e+00 L2 loss: 0.59975 Learning rate: 0.002 Mask loss: 0.12743 RPN box loss: 0.01062 RPN score loss: 0.00379 RPN total loss: 0.01441 Total loss: 0.95937 timestamp: 1654958295.1612427 iteration: 56730 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10674 FastRCNN class loss: 0.08749 FastRCNN total loss: 0.19422 L1 loss: 0.0000e+00 L2 loss: 0.59974 Learning rate: 0.002 Mask loss: 0.21731 RPN box loss: 0.02119 RPN score loss: 0.00423 RPN total loss: 0.02542 Total loss: 1.0367 timestamp: 1654958298.3329244 iteration: 56735 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06135 FastRCNN class loss: 0.05185 FastRCNN total loss: 0.1132 L1 loss: 0.0000e+00 L2 loss: 0.59973 Learning rate: 0.002 Mask loss: 0.06432 RPN box loss: 0.01311 RPN score loss: 0.00348 RPN total loss: 0.01659 Total loss: 0.79384 timestamp: 1654958301.6146386 iteration: 56740 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07521 FastRCNN class loss: 0.07397 FastRCNN total loss: 0.14918 L1 loss: 0.0000e+00 L2 loss: 0.59973 Learning rate: 0.002 Mask loss: 0.1971 RPN box loss: 0.02435 RPN score loss: 0.00231 RPN total loss: 0.02666 Total loss: 0.97267 timestamp: 1654958304.8060613 iteration: 56745 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09072 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.13018 L1 loss: 0.0000e+00 L2 loss: 0.59972 Learning rate: 0.002 Mask loss: 0.08045 RPN box loss: 0.02402 RPN score loss: 0.00222 RPN total loss: 0.02624 Total loss: 0.83659 timestamp: 1654958308.1081831 iteration: 56750 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15979 FastRCNN class loss: 0.11037 FastRCNN total loss: 0.27017 L1 loss: 0.0000e+00 L2 loss: 0.59971 Learning rate: 0.002 Mask loss: 0.13296 RPN box loss: 0.01273 RPN score loss: 0.00746 RPN total loss: 0.02019 Total loss: 1.02303 timestamp: 1654958311.2971222 iteration: 56755 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09884 FastRCNN class loss: 0.11322 FastRCNN total loss: 0.21205 L1 loss: 0.0000e+00 L2 loss: 0.5997 Learning rate: 0.002 Mask loss: 0.13263 RPN box loss: 0.01866 RPN score loss: 0.00288 RPN total loss: 0.02154 Total loss: 0.96593 timestamp: 1654958314.5296397 iteration: 56760 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07828 FastRCNN class loss: 0.032 FastRCNN total loss: 0.11028 L1 loss: 0.0000e+00 L2 loss: 0.59969 Learning rate: 0.002 Mask loss: 0.0975 RPN box loss: 0.02558 RPN score loss: 0.00211 RPN total loss: 0.02769 Total loss: 0.83516 timestamp: 1654958317.7586591 iteration: 56765 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07505 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.1395 L1 loss: 0.0000e+00 L2 loss: 0.59968 Learning rate: 0.002 Mask loss: 0.13057 RPN box loss: 0.02543 RPN score loss: 0.00714 RPN total loss: 0.03257 Total loss: 0.90233 timestamp: 1654958321.0765426 iteration: 56770 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10906 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.1764 L1 loss: 0.0000e+00 L2 loss: 0.59968 Learning rate: 0.002 Mask loss: 0.12838 RPN box loss: 0.01782 RPN score loss: 0.0044 RPN total loss: 0.02223 Total loss: 0.92668 timestamp: 1654958324.2633805 iteration: 56775 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06015 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.14864 L1 loss: 0.0000e+00 L2 loss: 0.59967 Learning rate: 0.002 Mask loss: 0.14738 RPN box loss: 0.02083 RPN score loss: 0.00252 RPN total loss: 0.02334 Total loss: 0.91902 timestamp: 1654958327.4956496 iteration: 56780 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04469 FastRCNN class loss: 0.03688 FastRCNN total loss: 0.08157 L1 loss: 0.0000e+00 L2 loss: 0.59966 Learning rate: 0.002 Mask loss: 0.2315 RPN box loss: 0.00404 RPN score loss: 0.00776 RPN total loss: 0.0118 Total loss: 0.92453 timestamp: 1654958330.8087316 iteration: 56785 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0628 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.14893 L1 loss: 0.0000e+00 L2 loss: 0.59965 Learning rate: 0.002 Mask loss: 0.08439 RPN box loss: 0.01199 RPN score loss: 0.00308 RPN total loss: 0.01507 Total loss: 0.84804 timestamp: 1654958334.0234578 iteration: 56790 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08294 FastRCNN class loss: 0.05154 FastRCNN total loss: 0.13448 L1 loss: 0.0000e+00 L2 loss: 0.59964 Learning rate: 0.002 Mask loss: 0.10868 RPN box loss: 0.00632 RPN score loss: 0.00514 RPN total loss: 0.01146 Total loss: 0.85427 timestamp: 1654958337.444193 iteration: 56795 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10165 FastRCNN class loss: 0.08493 FastRCNN total loss: 0.18658 L1 loss: 0.0000e+00 L2 loss: 0.59964 Learning rate: 0.002 Mask loss: 0.12238 RPN box loss: 0.0157 RPN score loss: 0.0057 RPN total loss: 0.0214 Total loss: 0.93 timestamp: 1654958340.659348 iteration: 56800 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04493 FastRCNN class loss: 0.05137 FastRCNN total loss: 0.0963 L1 loss: 0.0000e+00 L2 loss: 0.59963 Learning rate: 0.002 Mask loss: 0.14731 RPN box loss: 0.01041 RPN score loss: 0.00192 RPN total loss: 0.01232 Total loss: 0.85556 timestamp: 1654958343.9889972 iteration: 56805 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08755 FastRCNN class loss: 0.04964 FastRCNN total loss: 0.13719 L1 loss: 0.0000e+00 L2 loss: 0.59962 Learning rate: 0.002 Mask loss: 0.1233 RPN box loss: 0.00541 RPN score loss: 0.00069 RPN total loss: 0.0061 Total loss: 0.86621 timestamp: 1654958347.194644 iteration: 56810 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03652 FastRCNN class loss: 0.04986 FastRCNN total loss: 0.08638 L1 loss: 0.0000e+00 L2 loss: 0.59961 Learning rate: 0.002 Mask loss: 0.13037 RPN box loss: 0.02256 RPN score loss: 0.00078 RPN total loss: 0.02334 Total loss: 0.8397 timestamp: 1654958350.389814 iteration: 56815 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06844 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.14919 L1 loss: 0.0000e+00 L2 loss: 0.5996 Learning rate: 0.002 Mask loss: 0.1555 RPN box loss: 0.0123 RPN score loss: 0.00366 RPN total loss: 0.01595 Total loss: 0.92025 timestamp: 1654958353.5161576 iteration: 56820 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09837 FastRCNN class loss: 0.04259 FastRCNN total loss: 0.14096 L1 loss: 0.0000e+00 L2 loss: 0.59959 Learning rate: 0.002 Mask loss: 0.09433 RPN box loss: 0.00491 RPN score loss: 0.00392 RPN total loss: 0.00883 Total loss: 0.84372 timestamp: 1654958356.7773776 iteration: 56825 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12978 FastRCNN class loss: 0.05551 FastRCNN total loss: 0.1853 L1 loss: 0.0000e+00 L2 loss: 0.59959 Learning rate: 0.002 Mask loss: 0.15364 RPN box loss: 0.02944 RPN score loss: 0.00275 RPN total loss: 0.03219 Total loss: 0.97072 timestamp: 1654958360.0058951 iteration: 56830 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09474 FastRCNN class loss: 0.09544 FastRCNN total loss: 0.19018 L1 loss: 0.0000e+00 L2 loss: 0.59958 Learning rate: 0.002 Mask loss: 0.10056 RPN box loss: 0.01135 RPN score loss: 0.00243 RPN total loss: 0.01377 Total loss: 0.9041 timestamp: 1654958363.2087705 iteration: 56835 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10877 FastRCNN class loss: 0.08479 FastRCNN total loss: 0.19356 L1 loss: 0.0000e+00 L2 loss: 0.59957 Learning rate: 0.002 Mask loss: 0.14274 RPN box loss: 0.02281 RPN score loss: 0.00974 RPN total loss: 0.03255 Total loss: 0.96843 timestamp: 1654958366.3782 iteration: 56840 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06008 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.1154 L1 loss: 0.0000e+00 L2 loss: 0.59956 Learning rate: 0.002 Mask loss: 0.15791 RPN box loss: 0.0094 RPN score loss: 0.00347 RPN total loss: 0.01287 Total loss: 0.88575 timestamp: 1654958369.5990608 iteration: 56845 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0996 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.16731 L1 loss: 0.0000e+00 L2 loss: 0.59955 Learning rate: 0.002 Mask loss: 0.10817 RPN box loss: 0.0092 RPN score loss: 0.00295 RPN total loss: 0.01215 Total loss: 0.88719 timestamp: 1654958372.8908055 iteration: 56850 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06247 FastRCNN class loss: 0.04532 FastRCNN total loss: 0.10779 L1 loss: 0.0000e+00 L2 loss: 0.59954 Learning rate: 0.002 Mask loss: 0.09941 RPN box loss: 0.00691 RPN score loss: 0.00144 RPN total loss: 0.00835 Total loss: 0.81509 timestamp: 1654958376.0711358 iteration: 56855 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05475 FastRCNN class loss: 0.03147 FastRCNN total loss: 0.08622 L1 loss: 0.0000e+00 L2 loss: 0.59953 Learning rate: 0.002 Mask loss: 0.14301 RPN box loss: 0.01159 RPN score loss: 0.0065 RPN total loss: 0.0181 Total loss: 0.84686 timestamp: 1654958379.3059843 iteration: 56860 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06214 FastRCNN class loss: 0.06189 FastRCNN total loss: 0.12403 L1 loss: 0.0000e+00 L2 loss: 0.59953 Learning rate: 0.002 Mask loss: 0.11911 RPN box loss: 0.01657 RPN score loss: 0.00058 RPN total loss: 0.01715 Total loss: 0.85982 timestamp: 1654958382.4261832 iteration: 56865 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11594 FastRCNN class loss: 0.08881 FastRCNN total loss: 0.20475 L1 loss: 0.0000e+00 L2 loss: 0.59952 Learning rate: 0.002 Mask loss: 0.14605 RPN box loss: 0.01364 RPN score loss: 0.00345 RPN total loss: 0.01709 Total loss: 0.9674 timestamp: 1654958385.728884 iteration: 56870 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.04617 FastRCNN total loss: 0.12702 L1 loss: 0.0000e+00 L2 loss: 0.59951 Learning rate: 0.002 Mask loss: 0.13035 RPN box loss: 0.00468 RPN score loss: 0.00424 RPN total loss: 0.00892 Total loss: 0.86579 timestamp: 1654958388.9883308 iteration: 56875 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07241 FastRCNN class loss: 0.04574 FastRCNN total loss: 0.11815 L1 loss: 0.0000e+00 L2 loss: 0.5995 Learning rate: 0.002 Mask loss: 0.10448 RPN box loss: 0.01863 RPN score loss: 0.00224 RPN total loss: 0.02087 Total loss: 0.84301 timestamp: 1654958392.3273199 iteration: 56880 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11748 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.19045 L1 loss: 0.0000e+00 L2 loss: 0.59949 Learning rate: 0.002 Mask loss: 0.1051 RPN box loss: 0.01432 RPN score loss: 0.00796 RPN total loss: 0.02228 Total loss: 0.91733 timestamp: 1654958395.4999495 iteration: 56885 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06416 FastRCNN class loss: 0.0351 FastRCNN total loss: 0.09927 L1 loss: 0.0000e+00 L2 loss: 0.59949 Learning rate: 0.002 Mask loss: 0.09443 RPN box loss: 0.00938 RPN score loss: 0.00482 RPN total loss: 0.0142 Total loss: 0.80739 timestamp: 1654958398.7482655 iteration: 56890 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07794 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.14029 L1 loss: 0.0000e+00 L2 loss: 0.59948 Learning rate: 0.002 Mask loss: 0.08824 RPN box loss: 0.01798 RPN score loss: 0.00729 RPN total loss: 0.02526 Total loss: 0.85328 timestamp: 1654958402.0300887 iteration: 56895 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10006 FastRCNN class loss: 0.08039 FastRCNN total loss: 0.18045 L1 loss: 0.0000e+00 L2 loss: 0.59947 Learning rate: 0.002 Mask loss: 0.14159 RPN box loss: 0.03645 RPN score loss: 0.00466 RPN total loss: 0.04111 Total loss: 0.96262 timestamp: 1654958405.2008753 iteration: 56900 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16012 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.23508 L1 loss: 0.0000e+00 L2 loss: 0.59946 Learning rate: 0.002 Mask loss: 0.14743 RPN box loss: 0.04581 RPN score loss: 0.01173 RPN total loss: 0.05755 Total loss: 1.03953 timestamp: 1654958408.4996953 iteration: 56905 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.05518 FastRCNN total loss: 0.13384 L1 loss: 0.0000e+00 L2 loss: 0.59945 Learning rate: 0.002 Mask loss: 0.09418 RPN box loss: 0.01002 RPN score loss: 0.00093 RPN total loss: 0.01095 Total loss: 0.83842 timestamp: 1654958411.6523073 iteration: 56910 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07153 FastRCNN class loss: 0.07237 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 0.59944 Learning rate: 0.002 Mask loss: 0.12264 RPN box loss: 0.00756 RPN score loss: 0.00145 RPN total loss: 0.00901 Total loss: 0.875 timestamp: 1654958414.9167137 iteration: 56915 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13016 FastRCNN class loss: 0.09379 FastRCNN total loss: 0.22395 L1 loss: 0.0000e+00 L2 loss: 0.59944 Learning rate: 0.002 Mask loss: 0.15504 RPN box loss: 0.0157 RPN score loss: 0.00667 RPN total loss: 0.02237 Total loss: 1.0008 timestamp: 1654958418.1175108 iteration: 56920 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07205 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.12424 L1 loss: 0.0000e+00 L2 loss: 0.59943 Learning rate: 0.002 Mask loss: 0.11897 RPN box loss: 0.01599 RPN score loss: 0.00374 RPN total loss: 0.01974 Total loss: 0.86239 timestamp: 1654958421.4423583 iteration: 56925 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.05197 FastRCNN total loss: 0.13883 L1 loss: 0.0000e+00 L2 loss: 0.59942 Learning rate: 0.002 Mask loss: 0.12599 RPN box loss: 0.0109 RPN score loss: 0.00359 RPN total loss: 0.0145 Total loss: 0.87873 timestamp: 1654958424.745316 iteration: 56930 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11732 FastRCNN class loss: 0.07107 FastRCNN total loss: 0.18839 L1 loss: 0.0000e+00 L2 loss: 0.59941 Learning rate: 0.002 Mask loss: 0.19116 RPN box loss: 0.0168 RPN score loss: 0.00544 RPN total loss: 0.02224 Total loss: 1.0012 timestamp: 1654958428.0303195 iteration: 56935 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08739 FastRCNN class loss: 0.04417 FastRCNN total loss: 0.13156 L1 loss: 0.0000e+00 L2 loss: 0.59941 Learning rate: 0.002 Mask loss: 0.10366 RPN box loss: 0.01112 RPN score loss: 0.00118 RPN total loss: 0.01231 Total loss: 0.84694 timestamp: 1654958431.221139 iteration: 56940 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14651 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.20589 L1 loss: 0.0000e+00 L2 loss: 0.5994 Learning rate: 0.002 Mask loss: 0.16728 RPN box loss: 0.0109 RPN score loss: 0.0124 RPN total loss: 0.0233 Total loss: 0.99587 timestamp: 1654958434.4934433 iteration: 56945 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09707 FastRCNN class loss: 0.0854 FastRCNN total loss: 0.18247 L1 loss: 0.0000e+00 L2 loss: 0.59939 Learning rate: 0.002 Mask loss: 0.16745 RPN box loss: 0.01882 RPN score loss: 0.01036 RPN total loss: 0.02918 Total loss: 0.97849 timestamp: 1654958437.6643164 iteration: 56950 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10848 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.18186 L1 loss: 0.0000e+00 L2 loss: 0.59938 Learning rate: 0.002 Mask loss: 0.18505 RPN box loss: 0.01286 RPN score loss: 0.00335 RPN total loss: 0.01621 Total loss: 0.9825 timestamp: 1654958441.006338 iteration: 56955 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0706 FastRCNN class loss: 0.0606 FastRCNN total loss: 0.1312 L1 loss: 0.0000e+00 L2 loss: 0.59937 Learning rate: 0.002 Mask loss: 0.13382 RPN box loss: 0.00386 RPN score loss: 0.01062 RPN total loss: 0.01448 Total loss: 0.87887 timestamp: 1654958444.3177285 iteration: 56960 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18323 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.2517 L1 loss: 0.0000e+00 L2 loss: 0.59936 Learning rate: 0.002 Mask loss: 0.12517 RPN box loss: 0.00879 RPN score loss: 0.00286 RPN total loss: 0.01165 Total loss: 0.98788 timestamp: 1654958447.5368931 iteration: 56965 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11043 FastRCNN class loss: 0.09429 FastRCNN total loss: 0.20472 L1 loss: 0.0000e+00 L2 loss: 0.59935 Learning rate: 0.002 Mask loss: 0.16316 RPN box loss: 0.01664 RPN score loss: 0.01112 RPN total loss: 0.02776 Total loss: 0.99499 timestamp: 1654958450.83447 iteration: 56970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09759 FastRCNN class loss: 0.09803 FastRCNN total loss: 0.19561 L1 loss: 0.0000e+00 L2 loss: 0.59934 Learning rate: 0.002 Mask loss: 0.17203 RPN box loss: 0.00978 RPN score loss: 0.00296 RPN total loss: 0.01274 Total loss: 0.97973 timestamp: 1654958454.0613334 iteration: 56975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10802 FastRCNN class loss: 0.06979 FastRCNN total loss: 0.17781 L1 loss: 0.0000e+00 L2 loss: 0.59934 Learning rate: 0.002 Mask loss: 0.16631 RPN box loss: 0.01224 RPN score loss: 0.00571 RPN total loss: 0.01795 Total loss: 0.96141 timestamp: 1654958457.429037 iteration: 56980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07729 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.12472 L1 loss: 0.0000e+00 L2 loss: 0.59933 Learning rate: 0.002 Mask loss: 0.12613 RPN box loss: 0.01206 RPN score loss: 0.00608 RPN total loss: 0.01814 Total loss: 0.86832 timestamp: 1654958460.6578753 iteration: 56985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08838 FastRCNN class loss: 0.04499 FastRCNN total loss: 0.13337 L1 loss: 0.0000e+00 L2 loss: 0.59932 Learning rate: 0.002 Mask loss: 0.1252 RPN box loss: 0.01031 RPN score loss: 0.00206 RPN total loss: 0.01237 Total loss: 0.87027 timestamp: 1654958463.9068716 iteration: 56990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07967 FastRCNN class loss: 0.0432 FastRCNN total loss: 0.12287 L1 loss: 0.0000e+00 L2 loss: 0.59931 Learning rate: 0.002 Mask loss: 0.11719 RPN box loss: 0.01294 RPN score loss: 0.00209 RPN total loss: 0.01503 Total loss: 0.8544 timestamp: 1654958467.143832 iteration: 56995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17227 FastRCNN class loss: 0.0642 FastRCNN total loss: 0.23647 L1 loss: 0.0000e+00 L2 loss: 0.5993 Learning rate: 0.002 Mask loss: 0.1165 RPN box loss: 0.01799 RPN score loss: 0.00233 RPN total loss: 0.02033 Total loss: 0.9726 timestamp: 1654958470.5292797 iteration: 57000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11012 FastRCNN class loss: 0.08566 FastRCNN total loss: 0.19579 L1 loss: 0.0000e+00 L2 loss: 0.59929 Learning rate: 0.002 Mask loss: 0.10477 RPN box loss: 0.01214 RPN score loss: 0.00469 RPN total loss: 0.01683 Total loss: 0.91667 timestamp: 1654958473.748501 iteration: 57005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04135 FastRCNN class loss: 0.04632 FastRCNN total loss: 0.08767 L1 loss: 0.0000e+00 L2 loss: 0.59928 Learning rate: 0.002 Mask loss: 0.10055 RPN box loss: 0.02826 RPN score loss: 0.00135 RPN total loss: 0.02961 Total loss: 0.81712 timestamp: 1654958476.960552 iteration: 57010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04932 FastRCNN class loss: 0.05158 FastRCNN total loss: 0.10091 L1 loss: 0.0000e+00 L2 loss: 0.59927 Learning rate: 0.002 Mask loss: 0.11343 RPN box loss: 0.00838 RPN score loss: 0.00129 RPN total loss: 0.00967 Total loss: 0.82328 timestamp: 1654958480.3564808 iteration: 57015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09757 FastRCNN class loss: 0.05107 FastRCNN total loss: 0.14864 L1 loss: 0.0000e+00 L2 loss: 0.59926 Learning rate: 0.002 Mask loss: 0.09202 RPN box loss: 0.02887 RPN score loss: 0.00365 RPN total loss: 0.03252 Total loss: 0.87244 timestamp: 1654958483.5540469 iteration: 57020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05552 FastRCNN class loss: 0.03778 FastRCNN total loss: 0.0933 L1 loss: 0.0000e+00 L2 loss: 0.59926 Learning rate: 0.002 Mask loss: 0.11621 RPN box loss: 0.02159 RPN score loss: 0.00222 RPN total loss: 0.02381 Total loss: 0.83258 timestamp: 1654958486.8205128 iteration: 57025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1137 FastRCNN class loss: 0.05165 FastRCNN total loss: 0.16535 L1 loss: 0.0000e+00 L2 loss: 0.59925 Learning rate: 0.002 Mask loss: 0.07792 RPN box loss: 0.00893 RPN score loss: 0.00697 RPN total loss: 0.0159 Total loss: 0.85842 timestamp: 1654958490.000024 iteration: 57030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1061 FastRCNN class loss: 0.06965 FastRCNN total loss: 0.17575 L1 loss: 0.0000e+00 L2 loss: 0.59924 Learning rate: 0.002 Mask loss: 0.11396 RPN box loss: 0.00505 RPN score loss: 0.00381 RPN total loss: 0.00887 Total loss: 0.89781 timestamp: 1654958493.312093 iteration: 57035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10216 FastRCNN class loss: 0.09394 FastRCNN total loss: 0.1961 L1 loss: 0.0000e+00 L2 loss: 0.59923 Learning rate: 0.002 Mask loss: 0.13075 RPN box loss: 0.01209 RPN score loss: 0.00332 RPN total loss: 0.01541 Total loss: 0.9415 timestamp: 1654958496.4960706 iteration: 57040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0976 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.15195 L1 loss: 0.0000e+00 L2 loss: 0.59923 Learning rate: 0.002 Mask loss: 0.11754 RPN box loss: 0.01134 RPN score loss: 0.00642 RPN total loss: 0.01776 Total loss: 0.88647 timestamp: 1654958499.7390146 iteration: 57045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11653 FastRCNN class loss: 0.10979 FastRCNN total loss: 0.22632 L1 loss: 0.0000e+00 L2 loss: 0.59922 Learning rate: 0.002 Mask loss: 0.19575 RPN box loss: 0.00661 RPN score loss: 0.00551 RPN total loss: 0.01211 Total loss: 1.0334 timestamp: 1654958502.9537218 iteration: 57050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09706 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.18049 L1 loss: 0.0000e+00 L2 loss: 0.59921 Learning rate: 0.002 Mask loss: 0.12677 RPN box loss: 0.03 RPN score loss: 0.00315 RPN total loss: 0.03315 Total loss: 0.93961 timestamp: 1654958506.359818 iteration: 57055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.16696 L1 loss: 0.0000e+00 L2 loss: 0.5992 Learning rate: 0.002 Mask loss: 0.11624 RPN box loss: 0.01786 RPN score loss: 0.00379 RPN total loss: 0.02165 Total loss: 0.90404 timestamp: 1654958509.653895 iteration: 57060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07763 FastRCNN class loss: 0.04786 FastRCNN total loss: 0.12549 L1 loss: 0.0000e+00 L2 loss: 0.59919 Learning rate: 0.002 Mask loss: 0.14921 RPN box loss: 0.01039 RPN score loss: 0.00235 RPN total loss: 0.01274 Total loss: 0.88662 timestamp: 1654958512.85327 iteration: 57065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05849 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.11303 L1 loss: 0.0000e+00 L2 loss: 0.59918 Learning rate: 0.002 Mask loss: 0.13946 RPN box loss: 0.00995 RPN score loss: 0.0031 RPN total loss: 0.01304 Total loss: 0.86472 timestamp: 1654958516.150332 iteration: 57070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07698 FastRCNN class loss: 0.05918 FastRCNN total loss: 0.13615 L1 loss: 0.0000e+00 L2 loss: 0.59918 Learning rate: 0.002 Mask loss: 0.17708 RPN box loss: 0.01199 RPN score loss: 0.00158 RPN total loss: 0.01357 Total loss: 0.92598 timestamp: 1654958519.2952802 iteration: 57075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06446 FastRCNN class loss: 0.04326 FastRCNN total loss: 0.10773 L1 loss: 0.0000e+00 L2 loss: 0.59917 Learning rate: 0.002 Mask loss: 0.17276 RPN box loss: 0.01809 RPN score loss: 0.00351 RPN total loss: 0.02159 Total loss: 0.90126 timestamp: 1654958522.6646774 iteration: 57080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08076 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.1424 L1 loss: 0.0000e+00 L2 loss: 0.59916 Learning rate: 0.002 Mask loss: 0.16485 RPN box loss: 0.00619 RPN score loss: 0.00258 RPN total loss: 0.00877 Total loss: 0.91518 timestamp: 1654958525.808137 iteration: 57085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1084 FastRCNN class loss: 0.11355 FastRCNN total loss: 0.22195 L1 loss: 0.0000e+00 L2 loss: 0.59915 Learning rate: 0.002 Mask loss: 0.1538 RPN box loss: 0.01548 RPN score loss: 0.00273 RPN total loss: 0.01821 Total loss: 0.99311 timestamp: 1654958529.122453 iteration: 57090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12939 FastRCNN class loss: 0.08291 FastRCNN total loss: 0.2123 L1 loss: 0.0000e+00 L2 loss: 0.59914 Learning rate: 0.002 Mask loss: 0.11651 RPN box loss: 0.02088 RPN score loss: 0.00322 RPN total loss: 0.0241 Total loss: 0.95205 timestamp: 1654958532.325882 iteration: 57095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07456 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.13884 L1 loss: 0.0000e+00 L2 loss: 0.59913 Learning rate: 0.002 Mask loss: 0.11362 RPN box loss: 0.02383 RPN score loss: 0.0071 RPN total loss: 0.03094 Total loss: 0.88253 timestamp: 1654958535.626894 iteration: 57100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06469 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.1368 L1 loss: 0.0000e+00 L2 loss: 0.59913 Learning rate: 0.002 Mask loss: 0.18006 RPN box loss: 0.02312 RPN score loss: 0.01069 RPN total loss: 0.0338 Total loss: 0.9498 timestamp: 1654958538.822789 iteration: 57105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06797 FastRCNN class loss: 0.03898 FastRCNN total loss: 0.10695 L1 loss: 0.0000e+00 L2 loss: 0.59912 Learning rate: 0.002 Mask loss: 0.13557 RPN box loss: 0.00168 RPN score loss: 0.00509 RPN total loss: 0.00677 Total loss: 0.84841 timestamp: 1654958542.020084 iteration: 57110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0391 FastRCNN class loss: 0.03605 FastRCNN total loss: 0.07515 L1 loss: 0.0000e+00 L2 loss: 0.59911 Learning rate: 0.002 Mask loss: 0.08262 RPN box loss: 0.00255 RPN score loss: 0.00331 RPN total loss: 0.00587 Total loss: 0.76275 timestamp: 1654958545.2843008 iteration: 57115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10379 FastRCNN class loss: 0.05525 FastRCNN total loss: 0.15905 L1 loss: 0.0000e+00 L2 loss: 0.5991 Learning rate: 0.002 Mask loss: 0.12141 RPN box loss: 0.00889 RPN score loss: 0.002 RPN total loss: 0.01089 Total loss: 0.89044 timestamp: 1654958548.43357 iteration: 57120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08969 FastRCNN class loss: 0.09243 FastRCNN total loss: 0.18212 L1 loss: 0.0000e+00 L2 loss: 0.59909 Learning rate: 0.002 Mask loss: 0.13349 RPN box loss: 0.02406 RPN score loss: 0.00853 RPN total loss: 0.03259 Total loss: 0.94729 timestamp: 1654958551.7568104 iteration: 57125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07994 FastRCNN class loss: 0.06026 FastRCNN total loss: 0.1402 L1 loss: 0.0000e+00 L2 loss: 0.59908 Learning rate: 0.002 Mask loss: 0.14081 RPN box loss: 0.01021 RPN score loss: 0.00304 RPN total loss: 0.01325 Total loss: 0.89335 timestamp: 1654958554.884845 iteration: 57130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12796 FastRCNN class loss: 0.06004 FastRCNN total loss: 0.188 L1 loss: 0.0000e+00 L2 loss: 0.59908 Learning rate: 0.002 Mask loss: 0.12641 RPN box loss: 0.0083 RPN score loss: 0.00091 RPN total loss: 0.00922 Total loss: 0.92271 timestamp: 1654958558.1388361 iteration: 57135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12089 FastRCNN class loss: 0.08489 FastRCNN total loss: 0.20579 L1 loss: 0.0000e+00 L2 loss: 0.59907 Learning rate: 0.002 Mask loss: 0.10152 RPN box loss: 0.03777 RPN score loss: 0.00665 RPN total loss: 0.04442 Total loss: 0.9508 timestamp: 1654958561.3286695 iteration: 57140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08821 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.15821 L1 loss: 0.0000e+00 L2 loss: 0.59906 Learning rate: 0.002 Mask loss: 0.14054 RPN box loss: 0.01058 RPN score loss: 0.00464 RPN total loss: 0.01523 Total loss: 0.91304 timestamp: 1654958564.6044943 iteration: 57145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09721 FastRCNN class loss: 0.07202 FastRCNN total loss: 0.16922 L1 loss: 0.0000e+00 L2 loss: 0.59905 Learning rate: 0.002 Mask loss: 0.16481 RPN box loss: 0.01675 RPN score loss: 0.0046 RPN total loss: 0.02135 Total loss: 0.95444 timestamp: 1654958567.8463953 iteration: 57150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06291 FastRCNN class loss: 0.05373 FastRCNN total loss: 0.11664 L1 loss: 0.0000e+00 L2 loss: 0.59904 Learning rate: 0.002 Mask loss: 0.12495 RPN box loss: 0.00645 RPN score loss: 0.00524 RPN total loss: 0.01168 Total loss: 0.85232 timestamp: 1654958571.1358783 iteration: 57155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07746 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.14885 L1 loss: 0.0000e+00 L2 loss: 0.59903 Learning rate: 0.002 Mask loss: 0.10516 RPN box loss: 0.00831 RPN score loss: 0.00427 RPN total loss: 0.01257 Total loss: 0.86562 timestamp: 1654958574.3430505 iteration: 57160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10956 FastRCNN class loss: 0.13067 FastRCNN total loss: 0.24023 L1 loss: 0.0000e+00 L2 loss: 0.59903 Learning rate: 0.002 Mask loss: 0.16711 RPN box loss: 0.0255 RPN score loss: 0.00525 RPN total loss: 0.03075 Total loss: 1.03712 timestamp: 1654958577.5733893 iteration: 57165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07962 FastRCNN class loss: 0.06735 FastRCNN total loss: 0.14696 L1 loss: 0.0000e+00 L2 loss: 0.59902 Learning rate: 0.002 Mask loss: 0.13091 RPN box loss: 0.01833 RPN score loss: 0.00387 RPN total loss: 0.0222 Total loss: 0.8991 timestamp: 1654958580.750337 iteration: 57170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10621 FastRCNN class loss: 0.06878 FastRCNN total loss: 0.17499 L1 loss: 0.0000e+00 L2 loss: 0.59901 Learning rate: 0.002 Mask loss: 0.15683 RPN box loss: 0.00506 RPN score loss: 0.00124 RPN total loss: 0.00631 Total loss: 0.93715 timestamp: 1654958584.0230935 iteration: 57175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08446 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.17056 L1 loss: 0.0000e+00 L2 loss: 0.59901 Learning rate: 0.002 Mask loss: 0.13532 RPN box loss: 0.0113 RPN score loss: 0.00372 RPN total loss: 0.01502 Total loss: 0.91991 timestamp: 1654958587.2397149 iteration: 57180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10658 FastRCNN class loss: 0.11293 FastRCNN total loss: 0.21951 L1 loss: 0.0000e+00 L2 loss: 0.599 Learning rate: 0.002 Mask loss: 0.11379 RPN box loss: 0.02451 RPN score loss: 0.00292 RPN total loss: 0.02743 Total loss: 0.95973 timestamp: 1654958590.5398943 iteration: 57185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09202 FastRCNN class loss: 0.09076 FastRCNN total loss: 0.18277 L1 loss: 0.0000e+00 L2 loss: 0.59899 Learning rate: 0.002 Mask loss: 0.14009 RPN box loss: 0.00701 RPN score loss: 0.00628 RPN total loss: 0.0133 Total loss: 0.93515 timestamp: 1654958593.816274 iteration: 57190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1025 FastRCNN class loss: 0.07844 FastRCNN total loss: 0.18094 L1 loss: 0.0000e+00 L2 loss: 0.59898 Learning rate: 0.002 Mask loss: 0.10936 RPN box loss: 0.00535 RPN score loss: 0.00195 RPN total loss: 0.00731 Total loss: 0.89659 timestamp: 1654958597.0361814 iteration: 57195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09226 FastRCNN class loss: 0.07602 FastRCNN total loss: 0.16828 L1 loss: 0.0000e+00 L2 loss: 0.59897 Learning rate: 0.002 Mask loss: 0.18054 RPN box loss: 0.00603 RPN score loss: 0.00887 RPN total loss: 0.0149 Total loss: 0.9627 timestamp: 1654958600.3457925 iteration: 57200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10729 FastRCNN class loss: 0.09992 FastRCNN total loss: 0.20721 L1 loss: 0.0000e+00 L2 loss: 0.59897 Learning rate: 0.002 Mask loss: 0.18013 RPN box loss: 0.00848 RPN score loss: 0.0033 RPN total loss: 0.01178 Total loss: 0.99809 timestamp: 1654958603.569272 iteration: 57205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08679 FastRCNN class loss: 0.13012 FastRCNN total loss: 0.21691 L1 loss: 0.0000e+00 L2 loss: 0.59896 Learning rate: 0.002 Mask loss: 0.08733 RPN box loss: 0.00348 RPN score loss: 0.00109 RPN total loss: 0.00457 Total loss: 0.90776 timestamp: 1654958606.8886478 iteration: 57210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04995 FastRCNN class loss: 0.0449 FastRCNN total loss: 0.09485 L1 loss: 0.0000e+00 L2 loss: 0.59895 Learning rate: 0.002 Mask loss: 0.1076 RPN box loss: 0.01252 RPN score loss: 0.00113 RPN total loss: 0.01366 Total loss: 0.81506 timestamp: 1654958610.090399 iteration: 57215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.175 FastRCNN class loss: 0.10462 FastRCNN total loss: 0.27962 L1 loss: 0.0000e+00 L2 loss: 0.59894 Learning rate: 0.002 Mask loss: 0.15689 RPN box loss: 0.02617 RPN score loss: 0.00778 RPN total loss: 0.03395 Total loss: 1.06939 timestamp: 1654958613.3369396 iteration: 57220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05451 FastRCNN class loss: 0.07209 FastRCNN total loss: 0.1266 L1 loss: 0.0000e+00 L2 loss: 0.59893 Learning rate: 0.002 Mask loss: 0.23097 RPN box loss: 0.01089 RPN score loss: 0.00236 RPN total loss: 0.01325 Total loss: 0.96976 timestamp: 1654958616.6799197 iteration: 57225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09097 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.1529 L1 loss: 0.0000e+00 L2 loss: 0.59892 Learning rate: 0.002 Mask loss: 0.11082 RPN box loss: 0.01585 RPN score loss: 0.00281 RPN total loss: 0.01866 Total loss: 0.8813 timestamp: 1654958619.886084 iteration: 57230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15962 FastRCNN class loss: 0.10687 FastRCNN total loss: 0.26649 L1 loss: 0.0000e+00 L2 loss: 0.59891 Learning rate: 0.002 Mask loss: 0.19288 RPN box loss: 0.01591 RPN score loss: 0.00214 RPN total loss: 0.01805 Total loss: 1.07633 timestamp: 1654958623.098866 iteration: 57235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1225 FastRCNN class loss: 0.052 FastRCNN total loss: 0.1745 L1 loss: 0.0000e+00 L2 loss: 0.5989 Learning rate: 0.002 Mask loss: 0.09464 RPN box loss: 0.00599 RPN score loss: 0.00283 RPN total loss: 0.00882 Total loss: 0.87686 timestamp: 1654958626.300059 iteration: 57240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10898 FastRCNN class loss: 0.143 FastRCNN total loss: 0.25198 L1 loss: 0.0000e+00 L2 loss: 0.59889 Learning rate: 0.002 Mask loss: 0.1992 RPN box loss: 0.01289 RPN score loss: 0.0051 RPN total loss: 0.018 Total loss: 1.06806 timestamp: 1654958629.5604823 iteration: 57245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11794 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.1798 L1 loss: 0.0000e+00 L2 loss: 0.59889 Learning rate: 0.002 Mask loss: 0.11264 RPN box loss: 0.00934 RPN score loss: 0.00949 RPN total loss: 0.01883 Total loss: 0.91015 timestamp: 1654958632.7308848 iteration: 57250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12236 FastRCNN class loss: 0.06015 FastRCNN total loss: 0.18251 L1 loss: 0.0000e+00 L2 loss: 0.59888 Learning rate: 0.002 Mask loss: 0.17151 RPN box loss: 0.03991 RPN score loss: 0.00271 RPN total loss: 0.04262 Total loss: 0.99551 timestamp: 1654958635.9538004 iteration: 57255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0918 FastRCNN class loss: 0.0815 FastRCNN total loss: 0.17329 L1 loss: 0.0000e+00 L2 loss: 0.59887 Learning rate: 0.002 Mask loss: 0.13168 RPN box loss: 0.01176 RPN score loss: 0.00601 RPN total loss: 0.01777 Total loss: 0.92162 timestamp: 1654958639.1678038 iteration: 57260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12601 FastRCNN class loss: 0.09244 FastRCNN total loss: 0.21845 L1 loss: 0.0000e+00 L2 loss: 0.59886 Learning rate: 0.002 Mask loss: 0.13433 RPN box loss: 0.04131 RPN score loss: 0.00749 RPN total loss: 0.0488 Total loss: 1.00045 timestamp: 1654958642.513606 iteration: 57265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06701 FastRCNN class loss: 0.042 FastRCNN total loss: 0.10901 L1 loss: 0.0000e+00 L2 loss: 0.59885 Learning rate: 0.002 Mask loss: 0.09112 RPN box loss: 0.01476 RPN score loss: 0.00317 RPN total loss: 0.01793 Total loss: 0.81691 timestamp: 1654958645.721565 iteration: 57270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06285 FastRCNN class loss: 0.07047 FastRCNN total loss: 0.13333 L1 loss: 0.0000e+00 L2 loss: 0.59884 Learning rate: 0.002 Mask loss: 0.15625 RPN box loss: 0.00808 RPN score loss: 0.008 RPN total loss: 0.01608 Total loss: 0.9045 timestamp: 1654958649.0771892 iteration: 57275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08625 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.15982 L1 loss: 0.0000e+00 L2 loss: 0.59883 Learning rate: 0.002 Mask loss: 0.12198 RPN box loss: 0.0106 RPN score loss: 0.00563 RPN total loss: 0.01623 Total loss: 0.89687 timestamp: 1654958652.3654578 iteration: 57280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10278 FastRCNN class loss: 0.08092 FastRCNN total loss: 0.1837 L1 loss: 0.0000e+00 L2 loss: 0.59882 Learning rate: 0.002 Mask loss: 0.10872 RPN box loss: 0.01021 RPN score loss: 0.01238 RPN total loss: 0.02259 Total loss: 0.91383 timestamp: 1654958655.6919165 iteration: 57285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08232 FastRCNN class loss: 0.05371 FastRCNN total loss: 0.13602 L1 loss: 0.0000e+00 L2 loss: 0.59882 Learning rate: 0.002 Mask loss: 0.08917 RPN box loss: 0.01044 RPN score loss: 0.00286 RPN total loss: 0.0133 Total loss: 0.83732 timestamp: 1654958658.981193 iteration: 57290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11102 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.17214 L1 loss: 0.0000e+00 L2 loss: 0.59881 Learning rate: 0.002 Mask loss: 0.12852 RPN box loss: 0.01878 RPN score loss: 0.00298 RPN total loss: 0.02176 Total loss: 0.92124 timestamp: 1654958662.197236 iteration: 57295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05486 FastRCNN class loss: 0.06566 FastRCNN total loss: 0.12052 L1 loss: 0.0000e+00 L2 loss: 0.5988 Learning rate: 0.002 Mask loss: 0.08549 RPN box loss: 0.01413 RPN score loss: 0.00427 RPN total loss: 0.0184 Total loss: 0.82321 timestamp: 1654958665.439494 iteration: 57300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11268 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.19032 L1 loss: 0.0000e+00 L2 loss: 0.59879 Learning rate: 0.002 Mask loss: 0.13451 RPN box loss: 0.00985 RPN score loss: 0.00696 RPN total loss: 0.01682 Total loss: 0.94044 timestamp: 1654958668.709547 iteration: 57305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10227 FastRCNN class loss: 0.0647 FastRCNN total loss: 0.16697 L1 loss: 0.0000e+00 L2 loss: 0.59878 Learning rate: 0.002 Mask loss: 0.11286 RPN box loss: 0.01231 RPN score loss: 0.00512 RPN total loss: 0.01742 Total loss: 0.89605 timestamp: 1654958671.94526 iteration: 57310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.1588 L1 loss: 0.0000e+00 L2 loss: 0.59877 Learning rate: 0.002 Mask loss: 0.119 RPN box loss: 0.01505 RPN score loss: 0.00539 RPN total loss: 0.02045 Total loss: 0.89701 timestamp: 1654958675.14964 iteration: 57315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0563 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.10595 L1 loss: 0.0000e+00 L2 loss: 0.59876 Learning rate: 0.002 Mask loss: 0.14317 RPN box loss: 0.00854 RPN score loss: 0.00382 RPN total loss: 0.01236 Total loss: 0.86024 timestamp: 1654958678.4358833 iteration: 57320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13107 FastRCNN class loss: 0.06492 FastRCNN total loss: 0.19599 L1 loss: 0.0000e+00 L2 loss: 0.59876 Learning rate: 0.002 Mask loss: 0.16297 RPN box loss: 0.0154 RPN score loss: 0.00359 RPN total loss: 0.01899 Total loss: 0.97671 timestamp: 1654958681.6118546 iteration: 57325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09387 FastRCNN class loss: 0.0817 FastRCNN total loss: 0.17557 L1 loss: 0.0000e+00 L2 loss: 0.59875 Learning rate: 0.002 Mask loss: 0.12249 RPN box loss: 0.013 RPN score loss: 0.0105 RPN total loss: 0.0235 Total loss: 0.92031 timestamp: 1654958684.8950887 iteration: 57330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13023 FastRCNN class loss: 0.09161 FastRCNN total loss: 0.22183 L1 loss: 0.0000e+00 L2 loss: 0.59874 Learning rate: 0.002 Mask loss: 0.14283 RPN box loss: 0.02694 RPN score loss: 0.03114 RPN total loss: 0.05808 Total loss: 1.02149 timestamp: 1654958688.2359972 iteration: 57335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09076 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.15585 L1 loss: 0.0000e+00 L2 loss: 0.59873 Learning rate: 0.002 Mask loss: 0.17695 RPN box loss: 0.01025 RPN score loss: 0.005 RPN total loss: 0.01524 Total loss: 0.94678 timestamp: 1654958691.4759252 iteration: 57340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06924 FastRCNN class loss: 0.05167 FastRCNN total loss: 0.12092 L1 loss: 0.0000e+00 L2 loss: 0.59872 Learning rate: 0.002 Mask loss: 0.11274 RPN box loss: 0.01633 RPN score loss: 0.0036 RPN total loss: 0.01993 Total loss: 0.8523 timestamp: 1654958694.7520359 iteration: 57345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07001 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.13409 L1 loss: 0.0000e+00 L2 loss: 0.59871 Learning rate: 0.002 Mask loss: 0.1371 RPN box loss: 0.0097 RPN score loss: 0.0011 RPN total loss: 0.0108 Total loss: 0.8807 timestamp: 1654958697.9462008 iteration: 57350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07069 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.13165 L1 loss: 0.0000e+00 L2 loss: 0.5987 Learning rate: 0.002 Mask loss: 0.15507 RPN box loss: 0.01255 RPN score loss: 0.0042 RPN total loss: 0.01675 Total loss: 0.90217 timestamp: 1654958701.2033923 iteration: 57355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14238 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.21787 L1 loss: 0.0000e+00 L2 loss: 0.59869 Learning rate: 0.002 Mask loss: 0.15821 RPN box loss: 0.01575 RPN score loss: 0.00529 RPN total loss: 0.02104 Total loss: 0.99582 timestamp: 1654958704.3510537 iteration: 57360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06851 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.14599 L1 loss: 0.0000e+00 L2 loss: 0.59869 Learning rate: 0.002 Mask loss: 0.15735 RPN box loss: 0.01414 RPN score loss: 0.00227 RPN total loss: 0.01641 Total loss: 0.91843 timestamp: 1654958707.57528 iteration: 57365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05715 FastRCNN class loss: 0.0396 FastRCNN total loss: 0.09675 L1 loss: 0.0000e+00 L2 loss: 0.59868 Learning rate: 0.002 Mask loss: 0.13818 RPN box loss: 0.00506 RPN score loss: 0.00128 RPN total loss: 0.00633 Total loss: 0.83994 timestamp: 1654958710.8507133 iteration: 57370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12535 FastRCNN class loss: 0.0849 FastRCNN total loss: 0.21025 L1 loss: 0.0000e+00 L2 loss: 0.59867 Learning rate: 0.002 Mask loss: 0.11131 RPN box loss: 0.03292 RPN score loss: 0.00507 RPN total loss: 0.03798 Total loss: 0.95821 timestamp: 1654958714.0995955 iteration: 57375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05524 FastRCNN class loss: 0.03779 FastRCNN total loss: 0.09303 L1 loss: 0.0000e+00 L2 loss: 0.59866 Learning rate: 0.002 Mask loss: 0.12554 RPN box loss: 0.02445 RPN score loss: 0.00515 RPN total loss: 0.02961 Total loss: 0.84684 timestamp: 1654958717.261047 iteration: 57380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08302 FastRCNN class loss: 0.09649 FastRCNN total loss: 0.17951 L1 loss: 0.0000e+00 L2 loss: 0.59866 Learning rate: 0.002 Mask loss: 0.15474 RPN box loss: 0.02592 RPN score loss: 0.01678 RPN total loss: 0.0427 Total loss: 0.9756 timestamp: 1654958720.571986 iteration: 57385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12332 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.20384 L1 loss: 0.0000e+00 L2 loss: 0.59865 Learning rate: 0.002 Mask loss: 0.17122 RPN box loss: 0.01746 RPN score loss: 0.00927 RPN total loss: 0.02673 Total loss: 1.00044 timestamp: 1654958723.799527 iteration: 57390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06598 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.12376 L1 loss: 0.0000e+00 L2 loss: 0.59864 Learning rate: 0.002 Mask loss: 0.14339 RPN box loss: 0.01176 RPN score loss: 0.00255 RPN total loss: 0.01432 Total loss: 0.88011 timestamp: 1654958727.07658 iteration: 57395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07053 FastRCNN class loss: 0.04809 FastRCNN total loss: 0.11862 L1 loss: 0.0000e+00 L2 loss: 0.59863 Learning rate: 0.002 Mask loss: 0.11577 RPN box loss: 0.00445 RPN score loss: 0.00111 RPN total loss: 0.00556 Total loss: 0.83858 timestamp: 1654958730.315832 iteration: 57400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11753 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.18409 L1 loss: 0.0000e+00 L2 loss: 0.59863 Learning rate: 0.002 Mask loss: 0.13691 RPN box loss: 0.00355 RPN score loss: 0.00468 RPN total loss: 0.00823 Total loss: 0.92786 timestamp: 1654958733.4906347 iteration: 57405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07907 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.1463 L1 loss: 0.0000e+00 L2 loss: 0.59862 Learning rate: 0.002 Mask loss: 0.12689 RPN box loss: 0.03044 RPN score loss: 0.00945 RPN total loss: 0.03989 Total loss: 0.9117 timestamp: 1654958736.7233288 iteration: 57410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11623 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.2031 L1 loss: 0.0000e+00 L2 loss: 0.59861 Learning rate: 0.002 Mask loss: 0.12436 RPN box loss: 0.01378 RPN score loss: 0.01643 RPN total loss: 0.03021 Total loss: 0.95628 timestamp: 1654958739.9531276 iteration: 57415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03698 FastRCNN class loss: 0.03736 FastRCNN total loss: 0.07434 L1 loss: 0.0000e+00 L2 loss: 0.5986 Learning rate: 0.002 Mask loss: 0.08277 RPN box loss: 0.01264 RPN score loss: 0.0007 RPN total loss: 0.01333 Total loss: 0.76904 timestamp: 1654958743.3234627 iteration: 57420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09402 FastRCNN class loss: 0.04429 FastRCNN total loss: 0.13831 L1 loss: 0.0000e+00 L2 loss: 0.59859 Learning rate: 0.002 Mask loss: 0.1108 RPN box loss: 0.01633 RPN score loss: 0.00407 RPN total loss: 0.02039 Total loss: 0.8681 timestamp: 1654958746.511275 iteration: 57425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07273 FastRCNN class loss: 0.0389 FastRCNN total loss: 0.11163 L1 loss: 0.0000e+00 L2 loss: 0.59858 Learning rate: 0.002 Mask loss: 0.10989 RPN box loss: 0.00829 RPN score loss: 0.01188 RPN total loss: 0.02016 Total loss: 0.84027 timestamp: 1654958749.8075628 iteration: 57430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08434 FastRCNN class loss: 0.04487 FastRCNN total loss: 0.12922 L1 loss: 0.0000e+00 L2 loss: 0.59857 Learning rate: 0.002 Mask loss: 0.13 RPN box loss: 0.00698 RPN score loss: 0.00468 RPN total loss: 0.01166 Total loss: 0.86945 timestamp: 1654958753.0519514 iteration: 57435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13875 FastRCNN class loss: 0.11665 FastRCNN total loss: 0.25539 L1 loss: 0.0000e+00 L2 loss: 0.59857 Learning rate: 0.002 Mask loss: 0.1572 RPN box loss: 0.014 RPN score loss: 0.00539 RPN total loss: 0.01939 Total loss: 1.03055 timestamp: 1654958756.5186477 iteration: 57440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05093 FastRCNN class loss: 0.06038 FastRCNN total loss: 0.11131 L1 loss: 0.0000e+00 L2 loss: 0.59856 Learning rate: 0.002 Mask loss: 0.09918 RPN box loss: 0.00582 RPN score loss: 0.00759 RPN total loss: 0.01341 Total loss: 0.82246 timestamp: 1654958759.7489922 iteration: 57445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12109 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.17893 L1 loss: 0.0000e+00 L2 loss: 0.59854 Learning rate: 0.002 Mask loss: 0.10315 RPN box loss: 0.00765 RPN score loss: 0.00255 RPN total loss: 0.01021 Total loss: 0.89084 timestamp: 1654958762.955461 iteration: 57450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10151 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.17187 L1 loss: 0.0000e+00 L2 loss: 0.59853 Learning rate: 0.002 Mask loss: 0.20673 RPN box loss: 0.01632 RPN score loss: 0.00592 RPN total loss: 0.02225 Total loss: 0.99938 timestamp: 1654958766.2835877 iteration: 57455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03614 FastRCNN class loss: 0.0438 FastRCNN total loss: 0.07994 L1 loss: 0.0000e+00 L2 loss: 0.59852 Learning rate: 0.002 Mask loss: 0.07963 RPN box loss: 0.00679 RPN score loss: 0.00069 RPN total loss: 0.00748 Total loss: 0.76557 timestamp: 1654958769.46633 iteration: 57460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07403 FastRCNN class loss: 0.05922 FastRCNN total loss: 0.13325 L1 loss: 0.0000e+00 L2 loss: 0.59851 Learning rate: 0.002 Mask loss: 0.10425 RPN box loss: 0.00803 RPN score loss: 0.00158 RPN total loss: 0.00961 Total loss: 0.84562 timestamp: 1654958772.8573072 iteration: 57465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14699 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.21224 L1 loss: 0.0000e+00 L2 loss: 0.5985 Learning rate: 0.002 Mask loss: 0.13297 RPN box loss: 0.0078 RPN score loss: 0.00257 RPN total loss: 0.01037 Total loss: 0.95408 timestamp: 1654958776.0665545 iteration: 57470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09341 FastRCNN class loss: 0.09479 FastRCNN total loss: 0.1882 L1 loss: 0.0000e+00 L2 loss: 0.5985 Learning rate: 0.002 Mask loss: 0.16817 RPN box loss: 0.01729 RPN score loss: 0.00639 RPN total loss: 0.02368 Total loss: 0.97855 timestamp: 1654958779.2608013 iteration: 57475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09872 FastRCNN class loss: 0.11461 FastRCNN total loss: 0.21332 L1 loss: 0.0000e+00 L2 loss: 0.59849 Learning rate: 0.002 Mask loss: 0.11976 RPN box loss: 0.01057 RPN score loss: 0.00543 RPN total loss: 0.01599 Total loss: 0.94756 timestamp: 1654958782.5392675 iteration: 57480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11095 FastRCNN class loss: 0.09382 FastRCNN total loss: 0.20477 L1 loss: 0.0000e+00 L2 loss: 0.59848 Learning rate: 0.002 Mask loss: 0.18981 RPN box loss: 0.03591 RPN score loss: 0.00823 RPN total loss: 0.04414 Total loss: 1.0372 timestamp: 1654958785.7597432 iteration: 57485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1026 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.16838 L1 loss: 0.0000e+00 L2 loss: 0.59847 Learning rate: 0.002 Mask loss: 0.11735 RPN box loss: 0.00742 RPN score loss: 0.0014 RPN total loss: 0.00882 Total loss: 0.89303 timestamp: 1654958788.9939253 iteration: 57490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14513 FastRCNN class loss: 0.0994 FastRCNN total loss: 0.24454 L1 loss: 0.0000e+00 L2 loss: 0.59846 Learning rate: 0.002 Mask loss: 0.19652 RPN box loss: 0.02597 RPN score loss: 0.00724 RPN total loss: 0.03321 Total loss: 1.07273 timestamp: 1654958792.2542984 iteration: 57495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12138 FastRCNN class loss: 0.06962 FastRCNN total loss: 0.19101 L1 loss: 0.0000e+00 L2 loss: 0.59845 Learning rate: 0.002 Mask loss: 0.11271 RPN box loss: 0.01793 RPN score loss: 0.00364 RPN total loss: 0.02157 Total loss: 0.92374 timestamp: 1654958795.6298573 iteration: 57500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11928 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.17886 L1 loss: 0.0000e+00 L2 loss: 0.59844 Learning rate: 0.002 Mask loss: 0.10907 RPN box loss: 0.00727 RPN score loss: 0.00373 RPN total loss: 0.011 Total loss: 0.89737 timestamp: 1654958798.8378627 iteration: 57505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10582 FastRCNN class loss: 0.07674 FastRCNN total loss: 0.18256 L1 loss: 0.0000e+00 L2 loss: 0.59843 Learning rate: 0.002 Mask loss: 0.1374 RPN box loss: 0.01661 RPN score loss: 0.00724 RPN total loss: 0.02386 Total loss: 0.94225 timestamp: 1654958802.1134615 iteration: 57510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04718 FastRCNN class loss: 0.05084 FastRCNN total loss: 0.09803 L1 loss: 0.0000e+00 L2 loss: 0.59842 Learning rate: 0.002 Mask loss: 0.10621 RPN box loss: 0.01761 RPN score loss: 0.0025 RPN total loss: 0.02011 Total loss: 0.82277 timestamp: 1654958805.273034 iteration: 57515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11844 FastRCNN class loss: 0.09058 FastRCNN total loss: 0.20902 L1 loss: 0.0000e+00 L2 loss: 0.59842 Learning rate: 0.002 Mask loss: 0.15474 RPN box loss: 0.01408 RPN score loss: 0.007 RPN total loss: 0.02108 Total loss: 0.98326 timestamp: 1654958808.5141568 iteration: 57520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0843 FastRCNN class loss: 0.06757 FastRCNN total loss: 0.15187 L1 loss: 0.0000e+00 L2 loss: 0.59841 Learning rate: 0.002 Mask loss: 0.1186 RPN box loss: 0.01117 RPN score loss: 0.00164 RPN total loss: 0.01281 Total loss: 0.88169 timestamp: 1654958811.6920776 iteration: 57525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10646 FastRCNN class loss: 0.07048 FastRCNN total loss: 0.17694 L1 loss: 0.0000e+00 L2 loss: 0.5984 Learning rate: 0.002 Mask loss: 0.16375 RPN box loss: 0.00724 RPN score loss: 0.00464 RPN total loss: 0.01188 Total loss: 0.95096 timestamp: 1654958815.1020706 iteration: 57530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14523 FastRCNN class loss: 0.104 FastRCNN total loss: 0.24923 L1 loss: 0.0000e+00 L2 loss: 0.59839 Learning rate: 0.002 Mask loss: 0.17806 RPN box loss: 0.03517 RPN score loss: 0.00534 RPN total loss: 0.04051 Total loss: 1.06619 timestamp: 1654958818.3079324 iteration: 57535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14369 FastRCNN class loss: 0.1188 FastRCNN total loss: 0.26249 L1 loss: 0.0000e+00 L2 loss: 0.59839 Learning rate: 0.002 Mask loss: 0.22249 RPN box loss: 0.02992 RPN score loss: 0.00492 RPN total loss: 0.03485 Total loss: 1.11821 timestamp: 1654958821.7785957 iteration: 57540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08945 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.15383 L1 loss: 0.0000e+00 L2 loss: 0.59838 Learning rate: 0.002 Mask loss: 0.10575 RPN box loss: 0.01669 RPN score loss: 0.00181 RPN total loss: 0.0185 Total loss: 0.87646 timestamp: 1654958824.9890149 iteration: 57545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05543 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.11712 L1 loss: 0.0000e+00 L2 loss: 0.59838 Learning rate: 0.002 Mask loss: 0.19341 RPN box loss: 0.01051 RPN score loss: 0.00543 RPN total loss: 0.01594 Total loss: 0.92485 timestamp: 1654958828.2322843 iteration: 57550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0801 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.13806 L1 loss: 0.0000e+00 L2 loss: 0.59837 Learning rate: 0.002 Mask loss: 0.081 RPN box loss: 0.01859 RPN score loss: 0.00459 RPN total loss: 0.02318 Total loss: 0.84061 timestamp: 1654958831.4198413 iteration: 57555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06224 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.11769 L1 loss: 0.0000e+00 L2 loss: 0.59836 Learning rate: 0.002 Mask loss: 0.15954 RPN box loss: 0.00928 RPN score loss: 0.00762 RPN total loss: 0.0169 Total loss: 0.8925 timestamp: 1654958834.615387 iteration: 57560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12796 FastRCNN class loss: 0.08319 FastRCNN total loss: 0.21114 L1 loss: 0.0000e+00 L2 loss: 0.59835 Learning rate: 0.002 Mask loss: 0.24355 RPN box loss: 0.02151 RPN score loss: 0.00735 RPN total loss: 0.02886 Total loss: 1.0819 timestamp: 1654958837.9893622 iteration: 57565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05635 FastRCNN class loss: 0.04552 FastRCNN total loss: 0.10187 L1 loss: 0.0000e+00 L2 loss: 0.59834 Learning rate: 0.002 Mask loss: 0.10537 RPN box loss: 0.02047 RPN score loss: 0.00951 RPN total loss: 0.02998 Total loss: 0.83557 timestamp: 1654958841.1868627 iteration: 57570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1072 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.17812 L1 loss: 0.0000e+00 L2 loss: 0.59833 Learning rate: 0.002 Mask loss: 0.09054 RPN box loss: 0.0198 RPN score loss: 0.00334 RPN total loss: 0.02314 Total loss: 0.89014 timestamp: 1654958844.498488 iteration: 57575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10854 FastRCNN class loss: 0.08555 FastRCNN total loss: 0.19409 L1 loss: 0.0000e+00 L2 loss: 0.59833 Learning rate: 0.002 Mask loss: 0.13859 RPN box loss: 0.01791 RPN score loss: 0.00782 RPN total loss: 0.02574 Total loss: 0.95674 timestamp: 1654958847.6950269 iteration: 57580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12216 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.19278 L1 loss: 0.0000e+00 L2 loss: 0.59832 Learning rate: 0.002 Mask loss: 0.32717 RPN box loss: 0.04778 RPN score loss: 0.00357 RPN total loss: 0.05135 Total loss: 1.16961 timestamp: 1654958850.9963555 iteration: 57585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07876 FastRCNN class loss: 0.08785 FastRCNN total loss: 0.16661 L1 loss: 0.0000e+00 L2 loss: 0.59831 Learning rate: 0.002 Mask loss: 0.1357 RPN box loss: 0.01015 RPN score loss: 0.00963 RPN total loss: 0.01978 Total loss: 0.92041 timestamp: 1654958854.2009318 iteration: 57590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06572 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.13118 L1 loss: 0.0000e+00 L2 loss: 0.5983 Learning rate: 0.002 Mask loss: 0.11854 RPN box loss: 0.01067 RPN score loss: 0.00522 RPN total loss: 0.01589 Total loss: 0.8639 timestamp: 1654958857.5336747 iteration: 57595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11486 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.19932 L1 loss: 0.0000e+00 L2 loss: 0.59829 Learning rate: 0.002 Mask loss: 0.17353 RPN box loss: 0.01381 RPN score loss: 0.00471 RPN total loss: 0.01853 Total loss: 0.98966 timestamp: 1654958860.7843854 iteration: 57600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12971 FastRCNN class loss: 0.04362 FastRCNN total loss: 0.17332 L1 loss: 0.0000e+00 L2 loss: 0.59828 Learning rate: 0.002 Mask loss: 0.11397 RPN box loss: 0.01281 RPN score loss: 0.00386 RPN total loss: 0.01667 Total loss: 0.90224 timestamp: 1654958864.1796162 iteration: 57605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05233 FastRCNN class loss: 0.05442 FastRCNN total loss: 0.10675 L1 loss: 0.0000e+00 L2 loss: 0.59827 Learning rate: 0.002 Mask loss: 0.07028 RPN box loss: 0.00597 RPN score loss: 0.00127 RPN total loss: 0.00724 Total loss: 0.78255 timestamp: 1654958867.4528904 iteration: 57610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07708 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.13388 L1 loss: 0.0000e+00 L2 loss: 0.59826 Learning rate: 0.002 Mask loss: 0.07066 RPN box loss: 0.01575 RPN score loss: 0.00115 RPN total loss: 0.01689 Total loss: 0.8197 timestamp: 1654958870.6122077 iteration: 57615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10266 FastRCNN class loss: 0.09971 FastRCNN total loss: 0.20237 L1 loss: 0.0000e+00 L2 loss: 0.59826 Learning rate: 0.002 Mask loss: 0.13486 RPN box loss: 0.01684 RPN score loss: 0.01228 RPN total loss: 0.02912 Total loss: 0.96461 timestamp: 1654958873.9766767 iteration: 57620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06138 FastRCNN class loss: 0.04973 FastRCNN total loss: 0.11111 L1 loss: 0.0000e+00 L2 loss: 0.59825 Learning rate: 0.002 Mask loss: 0.11006 RPN box loss: 0.03096 RPN score loss: 0.00407 RPN total loss: 0.03502 Total loss: 0.85445 timestamp: 1654958877.1216319 iteration: 57625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08197 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.1414 L1 loss: 0.0000e+00 L2 loss: 0.59824 Learning rate: 0.002 Mask loss: 0.15884 RPN box loss: 0.00794 RPN score loss: 0.00853 RPN total loss: 0.01647 Total loss: 0.91495 timestamp: 1654958880.3950431 iteration: 57630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10138 FastRCNN class loss: 0.07877 FastRCNN total loss: 0.18015 L1 loss: 0.0000e+00 L2 loss: 0.59823 Learning rate: 0.002 Mask loss: 0.15584 RPN box loss: 0.02131 RPN score loss: 0.00846 RPN total loss: 0.02976 Total loss: 0.96398 timestamp: 1654958883.5692618 iteration: 57635 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14234 FastRCNN class loss: 0.07392 FastRCNN total loss: 0.21626 L1 loss: 0.0000e+00 L2 loss: 0.59822 Learning rate: 0.002 Mask loss: 0.15325 RPN box loss: 0.01353 RPN score loss: 0.00195 RPN total loss: 0.01548 Total loss: 0.98322 timestamp: 1654958886.8104107 iteration: 57640 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10223 FastRCNN class loss: 0.05789 FastRCNN total loss: 0.16013 L1 loss: 0.0000e+00 L2 loss: 0.59821 Learning rate: 0.002 Mask loss: 0.11414 RPN box loss: 0.01521 RPN score loss: 0.00272 RPN total loss: 0.01792 Total loss: 0.8904 timestamp: 1654958890.0162308 iteration: 57645 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07107 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.11739 L1 loss: 0.0000e+00 L2 loss: 0.5982 Learning rate: 0.002 Mask loss: 0.11682 RPN box loss: 0.00413 RPN score loss: 0.00446 RPN total loss: 0.00859 Total loss: 0.84101 timestamp: 1654958893.3722312 iteration: 57650 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04613 FastRCNN class loss: 0.02781 FastRCNN total loss: 0.07395 L1 loss: 0.0000e+00 L2 loss: 0.5982 Learning rate: 0.002 Mask loss: 0.10285 RPN box loss: 0.00202 RPN score loss: 0.00052 RPN total loss: 0.00254 Total loss: 0.77754 timestamp: 1654958896.6909366 iteration: 57655 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08809 FastRCNN class loss: 0.05918 FastRCNN total loss: 0.14727 L1 loss: 0.0000e+00 L2 loss: 0.59819 Learning rate: 0.002 Mask loss: 0.10115 RPN box loss: 0.00625 RPN score loss: 0.00349 RPN total loss: 0.00974 Total loss: 0.85636 timestamp: 1654958899.8424473 iteration: 57660 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09376 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.1441 L1 loss: 0.0000e+00 L2 loss: 0.59818 Learning rate: 0.002 Mask loss: 0.12747 RPN box loss: 0.01934 RPN score loss: 0.00335 RPN total loss: 0.02269 Total loss: 0.89245 timestamp: 1654958903.1475163 iteration: 57665 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0877 FastRCNN class loss: 0.05119 FastRCNN total loss: 0.13889 L1 loss: 0.0000e+00 L2 loss: 0.59818 Learning rate: 0.002 Mask loss: 0.13452 RPN box loss: 0.01032 RPN score loss: 0.00158 RPN total loss: 0.0119 Total loss: 0.88349 timestamp: 1654958906.322202 iteration: 57670 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09467 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.17659 L1 loss: 0.0000e+00 L2 loss: 0.59817 Learning rate: 0.002 Mask loss: 0.15663 RPN box loss: 0.00892 RPN score loss: 0.00681 RPN total loss: 0.01573 Total loss: 0.94711 timestamp: 1654958909.6172798 iteration: 57675 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1844 FastRCNN class loss: 0.11138 FastRCNN total loss: 0.29577 L1 loss: 0.0000e+00 L2 loss: 0.59816 Learning rate: 0.002 Mask loss: 0.13884 RPN box loss: 0.01031 RPN score loss: 0.005 RPN total loss: 0.01531 Total loss: 1.04808 timestamp: 1654958912.8183546 iteration: 57680 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08928 FastRCNN class loss: 0.0355 FastRCNN total loss: 0.12479 L1 loss: 0.0000e+00 L2 loss: 0.59815 Learning rate: 0.002 Mask loss: 0.13576 RPN box loss: 0.02872 RPN score loss: 0.00526 RPN total loss: 0.03397 Total loss: 0.89267 timestamp: 1654958916.0774822 iteration: 57685 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06813 FastRCNN class loss: 0.06144 FastRCNN total loss: 0.12957 L1 loss: 0.0000e+00 L2 loss: 0.59814 Learning rate: 0.002 Mask loss: 0.12894 RPN box loss: 0.01468 RPN score loss: 0.00512 RPN total loss: 0.0198 Total loss: 0.87646 timestamp: 1654958919.2975135 iteration: 57690 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08297 FastRCNN class loss: 0.09338 FastRCNN total loss: 0.17635 L1 loss: 0.0000e+00 L2 loss: 0.59813 Learning rate: 0.002 Mask loss: 0.16545 RPN box loss: 0.01637 RPN score loss: 0.00124 RPN total loss: 0.01761 Total loss: 0.95754 timestamp: 1654958922.5571003 iteration: 57695 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10847 FastRCNN class loss: 0.08014 FastRCNN total loss: 0.18861 L1 loss: 0.0000e+00 L2 loss: 0.59812 Learning rate: 0.002 Mask loss: 0.15016 RPN box loss: 0.01236 RPN score loss: 0.00758 RPN total loss: 0.01994 Total loss: 0.95683 timestamp: 1654958925.8039992 iteration: 57700 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10239 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.17642 L1 loss: 0.0000e+00 L2 loss: 0.59812 Learning rate: 0.002 Mask loss: 0.09982 RPN box loss: 0.00787 RPN score loss: 0.00586 RPN total loss: 0.01372 Total loss: 0.88808 timestamp: 1654958929.1538289 iteration: 57705 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09391 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.16597 L1 loss: 0.0000e+00 L2 loss: 0.59811 Learning rate: 0.002 Mask loss: 0.13742 RPN box loss: 0.0147 RPN score loss: 0.00647 RPN total loss: 0.02117 Total loss: 0.92267 timestamp: 1654958932.3229408 iteration: 57710 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07553 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.14582 L1 loss: 0.0000e+00 L2 loss: 0.5981 Learning rate: 0.002 Mask loss: 0.22113 RPN box loss: 0.0225 RPN score loss: 0.01345 RPN total loss: 0.03595 Total loss: 1.00101 timestamp: 1654958935.5731483 iteration: 57715 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12002 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.17734 L1 loss: 0.0000e+00 L2 loss: 0.59809 Learning rate: 0.002 Mask loss: 0.15414 RPN box loss: 0.00669 RPN score loss: 0.00534 RPN total loss: 0.01204 Total loss: 0.94161 timestamp: 1654958938.7484179 iteration: 57720 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11834 FastRCNN class loss: 0.08874 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 0.59808 Learning rate: 0.002 Mask loss: 0.15002 RPN box loss: 0.01975 RPN score loss: 0.0062 RPN total loss: 0.02595 Total loss: 0.98114 timestamp: 1654958941.909435 iteration: 57725 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05572 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.11551 L1 loss: 0.0000e+00 L2 loss: 0.59808 Learning rate: 0.002 Mask loss: 0.09995 RPN box loss: 0.00631 RPN score loss: 0.00657 RPN total loss: 0.01287 Total loss: 0.82641 timestamp: 1654958945.193233 iteration: 57730 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09342 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.16917 L1 loss: 0.0000e+00 L2 loss: 0.59807 Learning rate: 0.002 Mask loss: 0.16571 RPN box loss: 0.00891 RPN score loss: 0.01101 RPN total loss: 0.01992 Total loss: 0.95287 timestamp: 1654958948.3731458 iteration: 57735 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12947 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.18155 L1 loss: 0.0000e+00 L2 loss: 0.59806 Learning rate: 0.002 Mask loss: 0.09016 RPN box loss: 0.01465 RPN score loss: 0.00422 RPN total loss: 0.01887 Total loss: 0.88865 timestamp: 1654958951.6580923 iteration: 57740 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.08196 FastRCNN total loss: 0.24056 L1 loss: 0.0000e+00 L2 loss: 0.59805 Learning rate: 0.002 Mask loss: 0.07896 RPN box loss: 0.0035 RPN score loss: 0.0051 RPN total loss: 0.0086 Total loss: 0.92616 timestamp: 1654958954.8876712 iteration: 57745 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11718 FastRCNN class loss: 0.0563 FastRCNN total loss: 0.17348 L1 loss: 0.0000e+00 L2 loss: 0.59804 Learning rate: 0.002 Mask loss: 0.10746 RPN box loss: 0.02263 RPN score loss: 0.00354 RPN total loss: 0.02617 Total loss: 0.90514 timestamp: 1654958958.0967126 iteration: 57750 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08607 FastRCNN class loss: 0.05654 FastRCNN total loss: 0.1426 L1 loss: 0.0000e+00 L2 loss: 0.59803 Learning rate: 0.002 Mask loss: 0.12685 RPN box loss: 0.01658 RPN score loss: 0.00296 RPN total loss: 0.01954 Total loss: 0.88702 timestamp: 1654958961.3044615 iteration: 57755 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08131 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.14117 L1 loss: 0.0000e+00 L2 loss: 0.59802 Learning rate: 0.002 Mask loss: 0.12109 RPN box loss: 0.01821 RPN score loss: 0.00281 RPN total loss: 0.02102 Total loss: 0.88129 timestamp: 1654958964.5581448 iteration: 57760 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12265 FastRCNN class loss: 0.09988 FastRCNN total loss: 0.22253 L1 loss: 0.0000e+00 L2 loss: 0.59801 Learning rate: 0.002 Mask loss: 0.16436 RPN box loss: 0.02185 RPN score loss: 0.00827 RPN total loss: 0.03012 Total loss: 1.01502 timestamp: 1654958967.7544165 iteration: 57765 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04855 FastRCNN class loss: 0.05426 FastRCNN total loss: 0.10281 L1 loss: 0.0000e+00 L2 loss: 0.598 Learning rate: 0.002 Mask loss: 0.08926 RPN box loss: 0.00827 RPN score loss: 0.0014 RPN total loss: 0.00967 Total loss: 0.79975 timestamp: 1654958971.0337517 iteration: 57770 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04285 FastRCNN class loss: 0.05991 FastRCNN total loss: 0.10276 L1 loss: 0.0000e+00 L2 loss: 0.598 Learning rate: 0.002 Mask loss: 0.08475 RPN box loss: 0.01379 RPN score loss: 0.00541 RPN total loss: 0.01921 Total loss: 0.80471 timestamp: 1654958974.33939 iteration: 57775 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07022 FastRCNN class loss: 0.0418 FastRCNN total loss: 0.11203 L1 loss: 0.0000e+00 L2 loss: 0.59799 Learning rate: 0.002 Mask loss: 0.11261 RPN box loss: 0.01144 RPN score loss: 0.004 RPN total loss: 0.01544 Total loss: 0.83807 timestamp: 1654958977.5480983 iteration: 57780 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15191 FastRCNN class loss: 0.05674 FastRCNN total loss: 0.20866 L1 loss: 0.0000e+00 L2 loss: 0.59798 Learning rate: 0.002 Mask loss: 0.1446 RPN box loss: 0.01249 RPN score loss: 0.0029 RPN total loss: 0.01539 Total loss: 0.96663 timestamp: 1654958980.8414817 iteration: 57785 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08024 FastRCNN class loss: 0.10176 FastRCNN total loss: 0.182 L1 loss: 0.0000e+00 L2 loss: 0.59798 Learning rate: 0.002 Mask loss: 0.14564 RPN box loss: 0.00793 RPN score loss: 0.00761 RPN total loss: 0.01554 Total loss: 0.94115 timestamp: 1654958984.0010808 iteration: 57790 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10457 FastRCNN class loss: 0.06851 FastRCNN total loss: 0.17308 L1 loss: 0.0000e+00 L2 loss: 0.59797 Learning rate: 0.002 Mask loss: 0.16496 RPN box loss: 0.00611 RPN score loss: 0.00239 RPN total loss: 0.0085 Total loss: 0.94451 timestamp: 1654958987.2835155 iteration: 57795 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0877 FastRCNN class loss: 0.0679 FastRCNN total loss: 0.1556 L1 loss: 0.0000e+00 L2 loss: 0.59796 Learning rate: 0.002 Mask loss: 0.10265 RPN box loss: 0.01369 RPN score loss: 0.00254 RPN total loss: 0.01623 Total loss: 0.87244 timestamp: 1654958990.4955082 iteration: 57800 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05864 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.10921 L1 loss: 0.0000e+00 L2 loss: 0.59795 Learning rate: 0.002 Mask loss: 0.08581 RPN box loss: 0.00324 RPN score loss: 0.00591 RPN total loss: 0.00915 Total loss: 0.80212 timestamp: 1654958993.7338786 iteration: 57805 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10649 FastRCNN class loss: 0.05708 FastRCNN total loss: 0.16357 L1 loss: 0.0000e+00 L2 loss: 0.59794 Learning rate: 0.002 Mask loss: 0.11257 RPN box loss: 0.041 RPN score loss: 0.0013 RPN total loss: 0.04231 Total loss: 0.91638 timestamp: 1654958996.9474447 iteration: 57810 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07109 FastRCNN class loss: 0.03773 FastRCNN total loss: 0.10882 L1 loss: 0.0000e+00 L2 loss: 0.59793 Learning rate: 0.002 Mask loss: 0.10454 RPN box loss: 0.01807 RPN score loss: 0.01117 RPN total loss: 0.02924 Total loss: 0.84054 timestamp: 1654959000.2002065 iteration: 57815 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10256 FastRCNN class loss: 0.06308 FastRCNN total loss: 0.16564 L1 loss: 0.0000e+00 L2 loss: 0.59792 Learning rate: 0.002 Mask loss: 0.10874 RPN box loss: 0.01362 RPN score loss: 0.00604 RPN total loss: 0.01966 Total loss: 0.89196 timestamp: 1654959003.466184 iteration: 57820 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09671 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.15553 L1 loss: 0.0000e+00 L2 loss: 0.59791 Learning rate: 0.002 Mask loss: 0.12673 RPN box loss: 0.01557 RPN score loss: 0.00083 RPN total loss: 0.01641 Total loss: 0.89658 timestamp: 1654959006.8555365 iteration: 57825 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06359 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.13175 L1 loss: 0.0000e+00 L2 loss: 0.5979 Learning rate: 0.002 Mask loss: 0.18292 RPN box loss: 0.01094 RPN score loss: 0.00279 RPN total loss: 0.01374 Total loss: 0.92631 timestamp: 1654959010.1664016 iteration: 57830 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10232 FastRCNN class loss: 0.06137 FastRCNN total loss: 0.16369 L1 loss: 0.0000e+00 L2 loss: 0.59789 Learning rate: 0.002 Mask loss: 0.09903 RPN box loss: 0.00735 RPN score loss: 0.00352 RPN total loss: 0.01087 Total loss: 0.87149 timestamp: 1654959013.514629 iteration: 57835 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1076 FastRCNN class loss: 0.07275 FastRCNN total loss: 0.18035 L1 loss: 0.0000e+00 L2 loss: 0.59789 Learning rate: 0.002 Mask loss: 0.10322 RPN box loss: 0.01133 RPN score loss: 0.00261 RPN total loss: 0.01394 Total loss: 0.8954 timestamp: 1654959016.776162 iteration: 57840 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.082 FastRCNN class loss: 0.0642 FastRCNN total loss: 0.1462 L1 loss: 0.0000e+00 L2 loss: 0.59788 Learning rate: 0.002 Mask loss: 0.14471 RPN box loss: 0.01206 RPN score loss: 0.00525 RPN total loss: 0.01731 Total loss: 0.9061 timestamp: 1654959019.9116583 iteration: 57845 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11276 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.17837 L1 loss: 0.0000e+00 L2 loss: 0.59787 Learning rate: 0.002 Mask loss: 0.11034 RPN box loss: 0.01237 RPN score loss: 0.00166 RPN total loss: 0.01403 Total loss: 0.90062 timestamp: 1654959023.2370188 iteration: 57850 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10604 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.16956 L1 loss: 0.0000e+00 L2 loss: 0.59786 Learning rate: 0.002 Mask loss: 0.13078 RPN box loss: 0.03456 RPN score loss: 0.00432 RPN total loss: 0.03888 Total loss: 0.93708 timestamp: 1654959026.4134834 iteration: 57855 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08647 FastRCNN class loss: 0.04264 FastRCNN total loss: 0.12912 L1 loss: 0.0000e+00 L2 loss: 0.59785 Learning rate: 0.002 Mask loss: 0.10399 RPN box loss: 0.00744 RPN score loss: 0.00538 RPN total loss: 0.01282 Total loss: 0.84378 timestamp: 1654959029.7604141 iteration: 57860 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06199 FastRCNN class loss: 0.03643 FastRCNN total loss: 0.09842 L1 loss: 0.0000e+00 L2 loss: 0.59784 Learning rate: 0.002 Mask loss: 0.09906 RPN box loss: 0.01185 RPN score loss: 0.00187 RPN total loss: 0.01372 Total loss: 0.80905 timestamp: 1654959033.0530932 iteration: 57865 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13004 FastRCNN class loss: 0.07507 FastRCNN total loss: 0.20511 L1 loss: 0.0000e+00 L2 loss: 0.59784 Learning rate: 0.002 Mask loss: 0.13413 RPN box loss: 0.02152 RPN score loss: 0.00698 RPN total loss: 0.0285 Total loss: 0.96558 timestamp: 1654959036.2465858 iteration: 57870 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0764 FastRCNN class loss: 0.05644 FastRCNN total loss: 0.13284 L1 loss: 0.0000e+00 L2 loss: 0.59783 Learning rate: 0.002 Mask loss: 0.13775 RPN box loss: 0.01147 RPN score loss: 0.00231 RPN total loss: 0.01378 Total loss: 0.88219 timestamp: 1654959039.4584389 iteration: 57875 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.04292 FastRCNN total loss: 0.12146 L1 loss: 0.0000e+00 L2 loss: 0.59782 Learning rate: 0.002 Mask loss: 0.11991 RPN box loss: 0.01347 RPN score loss: 0.00206 RPN total loss: 0.01553 Total loss: 0.85472 timestamp: 1654959042.7881756 iteration: 57880 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06582 FastRCNN class loss: 0.04598 FastRCNN total loss: 0.11179 L1 loss: 0.0000e+00 L2 loss: 0.59782 Learning rate: 0.002 Mask loss: 0.15347 RPN box loss: 0.00627 RPN score loss: 0.00601 RPN total loss: 0.01229 Total loss: 0.87536 timestamp: 1654959046.216689 iteration: 57885 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0697 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.13775 L1 loss: 0.0000e+00 L2 loss: 0.59781 Learning rate: 0.002 Mask loss: 0.18675 RPN box loss: 0.01304 RPN score loss: 0.00182 RPN total loss: 0.01486 Total loss: 0.93716 timestamp: 1654959049.3887143 iteration: 57890 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10674 FastRCNN class loss: 0.07329 FastRCNN total loss: 0.18003 L1 loss: 0.0000e+00 L2 loss: 0.5978 Learning rate: 0.002 Mask loss: 0.13873 RPN box loss: 0.02597 RPN score loss: 0.00194 RPN total loss: 0.02791 Total loss: 0.94447 timestamp: 1654959052.656279 iteration: 57895 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09187 FastRCNN class loss: 0.04982 FastRCNN total loss: 0.14169 L1 loss: 0.0000e+00 L2 loss: 0.59779 Learning rate: 0.002 Mask loss: 0.11616 RPN box loss: 0.01748 RPN score loss: 0.00596 RPN total loss: 0.02343 Total loss: 0.87907 timestamp: 1654959055.8451028 iteration: 57900 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06148 FastRCNN class loss: 0.09964 FastRCNN total loss: 0.16112 L1 loss: 0.0000e+00 L2 loss: 0.59778 Learning rate: 0.002 Mask loss: 0.13452 RPN box loss: 0.00509 RPN score loss: 0.00252 RPN total loss: 0.00761 Total loss: 0.90103 timestamp: 1654959059.1299117 iteration: 57905 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08986 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.16605 L1 loss: 0.0000e+00 L2 loss: 0.59777 Learning rate: 0.002 Mask loss: 0.11912 RPN box loss: 0.01798 RPN score loss: 0.00891 RPN total loss: 0.02689 Total loss: 0.90983 timestamp: 1654959062.3002255 iteration: 57910 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08285 FastRCNN class loss: 0.04253 FastRCNN total loss: 0.12538 L1 loss: 0.0000e+00 L2 loss: 0.59776 Learning rate: 0.002 Mask loss: 0.09998 RPN box loss: 0.00516 RPN score loss: 0.0025 RPN total loss: 0.00766 Total loss: 0.83078 timestamp: 1654959065.630146 iteration: 57915 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15115 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.22203 L1 loss: 0.0000e+00 L2 loss: 0.59775 Learning rate: 0.002 Mask loss: 0.1544 RPN box loss: 0.00993 RPN score loss: 0.00403 RPN total loss: 0.01396 Total loss: 0.98814 timestamp: 1654959068.843046 iteration: 57920 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10164 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.15166 L1 loss: 0.0000e+00 L2 loss: 0.59775 Learning rate: 0.002 Mask loss: 0.10614 RPN box loss: 0.0101 RPN score loss: 0.00127 RPN total loss: 0.01137 Total loss: 0.86692 timestamp: 1654959072.2073882 iteration: 57925 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08126 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.13871 L1 loss: 0.0000e+00 L2 loss: 0.59774 Learning rate: 0.002 Mask loss: 0.12399 RPN box loss: 0.01847 RPN score loss: 0.00165 RPN total loss: 0.02012 Total loss: 0.88057 timestamp: 1654959075.4097445 iteration: 57930 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08518 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.13869 L1 loss: 0.0000e+00 L2 loss: 0.59774 Learning rate: 0.002 Mask loss: 0.11763 RPN box loss: 0.01035 RPN score loss: 0.00076 RPN total loss: 0.01112 Total loss: 0.86518 timestamp: 1654959078.7474167 iteration: 57935 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07549 FastRCNN class loss: 0.06552 FastRCNN total loss: 0.14101 L1 loss: 0.0000e+00 L2 loss: 0.59773 Learning rate: 0.002 Mask loss: 0.10563 RPN box loss: 0.00812 RPN score loss: 0.00257 RPN total loss: 0.01069 Total loss: 0.85506 timestamp: 1654959082.0680048 iteration: 57940 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05666 FastRCNN class loss: 0.05608 FastRCNN total loss: 0.11274 L1 loss: 0.0000e+00 L2 loss: 0.59772 Learning rate: 0.002 Mask loss: 0.09787 RPN box loss: 0.00479 RPN score loss: 0.00641 RPN total loss: 0.0112 Total loss: 0.81953 timestamp: 1654959085.3183331 iteration: 57945 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1017 FastRCNN class loss: 0.04949 FastRCNN total loss: 0.15119 L1 loss: 0.0000e+00 L2 loss: 0.59771 Learning rate: 0.002 Mask loss: 0.10323 RPN box loss: 0.01747 RPN score loss: 0.00085 RPN total loss: 0.01832 Total loss: 0.87045 timestamp: 1654959088.6672745 iteration: 57950 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05423 FastRCNN class loss: 0.04211 FastRCNN total loss: 0.09634 L1 loss: 0.0000e+00 L2 loss: 0.5977 Learning rate: 0.002 Mask loss: 0.10585 RPN box loss: 0.00599 RPN score loss: 0.0037 RPN total loss: 0.00969 Total loss: 0.80958 timestamp: 1654959091.8347104 iteration: 57955 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.06298 FastRCNN total loss: 0.17297 L1 loss: 0.0000e+00 L2 loss: 0.5977 Learning rate: 0.002 Mask loss: 0.14588 RPN box loss: 0.02014 RPN score loss: 0.00614 RPN total loss: 0.02628 Total loss: 0.94282 timestamp: 1654959095.079862 iteration: 57960 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13986 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.20555 L1 loss: 0.0000e+00 L2 loss: 0.59769 Learning rate: 0.002 Mask loss: 0.14038 RPN box loss: 0.05743 RPN score loss: 0.00925 RPN total loss: 0.06668 Total loss: 1.01029 timestamp: 1654959098.2578688 iteration: 57965 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05446 FastRCNN class loss: 0.03859 FastRCNN total loss: 0.09305 L1 loss: 0.0000e+00 L2 loss: 0.59768 Learning rate: 0.002 Mask loss: 0.08712 RPN box loss: 0.00955 RPN score loss: 0.00404 RPN total loss: 0.01359 Total loss: 0.79144 timestamp: 1654959101.5395103 iteration: 57970 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09961 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.14413 L1 loss: 0.0000e+00 L2 loss: 0.59767 Learning rate: 0.002 Mask loss: 0.11362 RPN box loss: 0.01497 RPN score loss: 0.00353 RPN total loss: 0.0185 Total loss: 0.87391 timestamp: 1654959104.7729347 iteration: 57975 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10699 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.1742 L1 loss: 0.0000e+00 L2 loss: 0.59766 Learning rate: 0.002 Mask loss: 0.11212 RPN box loss: 0.03249 RPN score loss: 0.00669 RPN total loss: 0.03918 Total loss: 0.92317 timestamp: 1654959107.972169 iteration: 57980 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07268 FastRCNN class loss: 0.05738 FastRCNN total loss: 0.13006 L1 loss: 0.0000e+00 L2 loss: 0.59765 Learning rate: 0.002 Mask loss: 0.12315 RPN box loss: 0.01928 RPN score loss: 0.0025 RPN total loss: 0.02178 Total loss: 0.87264 timestamp: 1654959111.1765447 iteration: 57985 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08186 FastRCNN class loss: 0.08545 FastRCNN total loss: 0.16731 L1 loss: 0.0000e+00 L2 loss: 0.59764 Learning rate: 0.002 Mask loss: 0.12838 RPN box loss: 0.00765 RPN score loss: 0.0052 RPN total loss: 0.01285 Total loss: 0.90619 timestamp: 1654959114.426506 iteration: 57990 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12002 FastRCNN class loss: 0.1001 FastRCNN total loss: 0.22012 L1 loss: 0.0000e+00 L2 loss: 0.59764 Learning rate: 0.002 Mask loss: 0.10733 RPN box loss: 0.00952 RPN score loss: 0.00722 RPN total loss: 0.01675 Total loss: 0.94183 timestamp: 1654959117.7514923 iteration: 57995 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11373 FastRCNN class loss: 0.07202 FastRCNN total loss: 0.18575 L1 loss: 0.0000e+00 L2 loss: 0.59763 Learning rate: 0.002 Mask loss: 0.13368 RPN box loss: 0.02423 RPN score loss: 0.0079 RPN total loss: 0.03213 Total loss: 0.94918 timestamp: 1654959120.8626187 iteration: 58000 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0547 FastRCNN class loss: 0.03609 FastRCNN total loss: 0.09079 L1 loss: 0.0000e+00 L2 loss: 0.59762 Learning rate: 0.002 Mask loss: 0.13107 RPN box loss: 0.00924 RPN score loss: 0.00912 RPN total loss: 0.01836 Total loss: 0.83784 timestamp: 1654959124.1662228 iteration: 58005 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09418 FastRCNN class loss: 0.06206 FastRCNN total loss: 0.15624 L1 loss: 0.0000e+00 L2 loss: 0.59762 Learning rate: 0.002 Mask loss: 0.09042 RPN box loss: 0.01427 RPN score loss: 0.00268 RPN total loss: 0.01695 Total loss: 0.86122 timestamp: 1654959127.3744357 iteration: 58010 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11193 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.18034 L1 loss: 0.0000e+00 L2 loss: 0.59761 Learning rate: 0.002 Mask loss: 0.15216 RPN box loss: 0.0184 RPN score loss: 0.00517 RPN total loss: 0.02357 Total loss: 0.95368 timestamp: 1654959130.6283765 iteration: 58015 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11339 FastRCNN class loss: 0.08776 FastRCNN total loss: 0.20115 L1 loss: 0.0000e+00 L2 loss: 0.5976 Learning rate: 0.002 Mask loss: 0.08965 RPN box loss: 0.01371 RPN score loss: 0.00374 RPN total loss: 0.01745 Total loss: 0.90585 timestamp: 1654959133.8470507 iteration: 58020 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07199 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.13368 L1 loss: 0.0000e+00 L2 loss: 0.59759 Learning rate: 0.002 Mask loss: 0.14884 RPN box loss: 0.02014 RPN score loss: 0.00526 RPN total loss: 0.0254 Total loss: 0.90551 timestamp: 1654959137.2529547 iteration: 58025 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.2085 L1 loss: 0.0000e+00 L2 loss: 0.59758 Learning rate: 0.002 Mask loss: 0.10475 RPN box loss: 0.01749 RPN score loss: 0.00507 RPN total loss: 0.02256 Total loss: 0.93338 timestamp: 1654959140.4243016 iteration: 58030 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17636 FastRCNN class loss: 0.06852 FastRCNN total loss: 0.24488 L1 loss: 0.0000e+00 L2 loss: 0.59757 Learning rate: 0.002 Mask loss: 0.10938 RPN box loss: 0.01246 RPN score loss: 0.00728 RPN total loss: 0.01974 Total loss: 0.97157 timestamp: 1654959143.725807 iteration: 58035 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10265 FastRCNN class loss: 0.10793 FastRCNN total loss: 0.21058 L1 loss: 0.0000e+00 L2 loss: 0.59757 Learning rate: 0.002 Mask loss: 0.17346 RPN box loss: 0.01814 RPN score loss: 0.01525 RPN total loss: 0.03339 Total loss: 1.015 timestamp: 1654959146.9791195 iteration: 58040 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07311 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.12522 L1 loss: 0.0000e+00 L2 loss: 0.59756 Learning rate: 0.002 Mask loss: 0.07415 RPN box loss: 0.00538 RPN score loss: 0.00157 RPN total loss: 0.00696 Total loss: 0.80388 timestamp: 1654959150.1744561 iteration: 58045 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.104 FastRCNN class loss: 0.076 FastRCNN total loss: 0.18 L1 loss: 0.0000e+00 L2 loss: 0.59755 Learning rate: 0.002 Mask loss: 0.13851 RPN box loss: 0.00917 RPN score loss: 0.00527 RPN total loss: 0.01443 Total loss: 0.93049 timestamp: 1654959153.4721422 iteration: 58050 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0535 FastRCNN class loss: 0.05089 FastRCNN total loss: 0.10439 L1 loss: 0.0000e+00 L2 loss: 0.59754 Learning rate: 0.002 Mask loss: 0.10621 RPN box loss: 0.00657 RPN score loss: 0.00234 RPN total loss: 0.00891 Total loss: 0.81706 timestamp: 1654959156.6583796 iteration: 58055 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07264 FastRCNN class loss: 0.04764 FastRCNN total loss: 0.12028 L1 loss: 0.0000e+00 L2 loss: 0.59753 Learning rate: 0.002 Mask loss: 0.13677 RPN box loss: 0.01645 RPN score loss: 0.00268 RPN total loss: 0.01913 Total loss: 0.87372 timestamp: 1654959159.9158137 iteration: 58060 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05724 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.12669 L1 loss: 0.0000e+00 L2 loss: 0.59752 Learning rate: 0.002 Mask loss: 0.07247 RPN box loss: 0.00708 RPN score loss: 0.00189 RPN total loss: 0.00897 Total loss: 0.80566 timestamp: 1654959163.1764383 iteration: 58065 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12631 FastRCNN class loss: 0.08985 FastRCNN total loss: 0.21617 L1 loss: 0.0000e+00 L2 loss: 0.59751 Learning rate: 0.002 Mask loss: 0.14325 RPN box loss: 0.01551 RPN score loss: 0.00287 RPN total loss: 0.01837 Total loss: 0.97531 timestamp: 1654959166.5736825 iteration: 58070 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06276 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.13623 L1 loss: 0.0000e+00 L2 loss: 0.5975 Learning rate: 0.002 Mask loss: 0.16798 RPN box loss: 0.01508 RPN score loss: 0.00164 RPN total loss: 0.01672 Total loss: 0.91844 timestamp: 1654959169.7854488 iteration: 58075 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07702 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.14758 L1 loss: 0.0000e+00 L2 loss: 0.59749 Learning rate: 0.002 Mask loss: 0.16007 RPN box loss: 0.00826 RPN score loss: 0.00275 RPN total loss: 0.011 Total loss: 0.91615 timestamp: 1654959173.1640491 iteration: 58080 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.08923 FastRCNN total loss: 0.20089 L1 loss: 0.0000e+00 L2 loss: 0.59749 Learning rate: 0.002 Mask loss: 0.15325 RPN box loss: 0.0179 RPN score loss: 0.00124 RPN total loss: 0.01914 Total loss: 0.97076 timestamp: 1654959176.3584409 iteration: 58085 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07463 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.12661 L1 loss: 0.0000e+00 L2 loss: 0.59748 Learning rate: 0.002 Mask loss: 0.2139 RPN box loss: 0.00476 RPN score loss: 0.00121 RPN total loss: 0.00597 Total loss: 0.94395 timestamp: 1654959179.6848493 iteration: 58090 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.063 FastRCNN class loss: 0.05137 FastRCNN total loss: 0.11438 L1 loss: 0.0000e+00 L2 loss: 0.59747 Learning rate: 0.002 Mask loss: 0.10687 RPN box loss: 0.0172 RPN score loss: 0.00181 RPN total loss: 0.01901 Total loss: 0.83773 timestamp: 1654959182.9136229 iteration: 58095 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05977 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.12136 L1 loss: 0.0000e+00 L2 loss: 0.59746 Learning rate: 0.002 Mask loss: 0.09531 RPN box loss: 0.02137 RPN score loss: 0.00413 RPN total loss: 0.0255 Total loss: 0.83965 timestamp: 1654959186.2002158 iteration: 58100 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0549 FastRCNN class loss: 0.04318 FastRCNN total loss: 0.09808 L1 loss: 0.0000e+00 L2 loss: 0.59745 Learning rate: 0.002 Mask loss: 0.11381 RPN box loss: 0.00782 RPN score loss: 0.00128 RPN total loss: 0.0091 Total loss: 0.81845 timestamp: 1654959189.3954566 iteration: 58105 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09046 FastRCNN class loss: 0.07696 FastRCNN total loss: 0.16742 L1 loss: 0.0000e+00 L2 loss: 0.59745 Learning rate: 0.002 Mask loss: 0.17369 RPN box loss: 0.02074 RPN score loss: 0.00569 RPN total loss: 0.02643 Total loss: 0.96499 timestamp: 1654959192.6095598 iteration: 58110 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0748 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.12686 L1 loss: 0.0000e+00 L2 loss: 0.59744 Learning rate: 0.002 Mask loss: 0.13206 RPN box loss: 0.01592 RPN score loss: 0.00243 RPN total loss: 0.01835 Total loss: 0.8747 timestamp: 1654959195.9376159 iteration: 58115 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.06192 FastRCNN total loss: 0.17413 L1 loss: 0.0000e+00 L2 loss: 0.59743 Learning rate: 0.002 Mask loss: 0.11196 RPN box loss: 0.02137 RPN score loss: 0.00157 RPN total loss: 0.02294 Total loss: 0.90646 timestamp: 1654959199.1448364 iteration: 58120 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.05066 FastRCNN total loss: 0.12422 L1 loss: 0.0000e+00 L2 loss: 0.59742 Learning rate: 0.002 Mask loss: 0.1087 RPN box loss: 0.01606 RPN score loss: 0.00264 RPN total loss: 0.0187 Total loss: 0.84904 timestamp: 1654959202.480926 iteration: 58125 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13606 FastRCNN class loss: 0.12165 FastRCNN total loss: 0.25771 L1 loss: 0.0000e+00 L2 loss: 0.59742 Learning rate: 0.002 Mask loss: 0.16564 RPN box loss: 0.03746 RPN score loss: 0.00862 RPN total loss: 0.04608 Total loss: 1.06684 timestamp: 1654959205.6639395 iteration: 58130 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12599 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.19581 L1 loss: 0.0000e+00 L2 loss: 0.59741 Learning rate: 0.002 Mask loss: 0.08431 RPN box loss: 0.01267 RPN score loss: 0.00387 RPN total loss: 0.01654 Total loss: 0.89407 timestamp: 1654959208.9459145 iteration: 58135 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08067 FastRCNN class loss: 0.04273 FastRCNN total loss: 0.1234 L1 loss: 0.0000e+00 L2 loss: 0.5974 Learning rate: 0.002 Mask loss: 0.12522 RPN box loss: 0.00916 RPN score loss: 0.0026 RPN total loss: 0.01175 Total loss: 0.85777 timestamp: 1654959212.1320865 iteration: 58140 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0663 FastRCNN class loss: 0.04174 FastRCNN total loss: 0.10804 L1 loss: 0.0000e+00 L2 loss: 0.59739 Learning rate: 0.002 Mask loss: 0.1075 RPN box loss: 0.01809 RPN score loss: 0.01244 RPN total loss: 0.03052 Total loss: 0.84346 timestamp: 1654959215.392216 iteration: 58145 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07015 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.13345 L1 loss: 0.0000e+00 L2 loss: 0.59738 Learning rate: 0.002 Mask loss: 0.20413 RPN box loss: 0.01624 RPN score loss: 0.00772 RPN total loss: 0.02397 Total loss: 0.95893 timestamp: 1654959218.5989225 iteration: 58150 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12231 FastRCNN class loss: 0.14392 FastRCNN total loss: 0.26623 L1 loss: 0.0000e+00 L2 loss: 0.59737 Learning rate: 0.002 Mask loss: 0.13369 RPN box loss: 0.01072 RPN score loss: 0.00592 RPN total loss: 0.01664 Total loss: 1.01393 timestamp: 1654959221.8898685 iteration: 58155 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07849 FastRCNN class loss: 0.03621 FastRCNN total loss: 0.1147 L1 loss: 0.0000e+00 L2 loss: 0.59736 Learning rate: 0.002 Mask loss: 0.12037 RPN box loss: 0.00876 RPN score loss: 0.00362 RPN total loss: 0.01238 Total loss: 0.84482 timestamp: 1654959225.1737578 iteration: 58160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13465 FastRCNN class loss: 0.08048 FastRCNN total loss: 0.21514 L1 loss: 0.0000e+00 L2 loss: 0.59735 Learning rate: 0.002 Mask loss: 0.12836 RPN box loss: 0.0224 RPN score loss: 0.00743 RPN total loss: 0.02983 Total loss: 0.97069 timestamp: 1654959228.3466356 iteration: 58165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05626 FastRCNN class loss: 0.03933 FastRCNN total loss: 0.09559 L1 loss: 0.0000e+00 L2 loss: 0.59734 Learning rate: 0.002 Mask loss: 0.12634 RPN box loss: 0.02083 RPN score loss: 0.00489 RPN total loss: 0.02572 Total loss: 0.84499 timestamp: 1654959231.6018612 iteration: 58170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11569 FastRCNN class loss: 0.06973 FastRCNN total loss: 0.18542 L1 loss: 0.0000e+00 L2 loss: 0.59733 Learning rate: 0.002 Mask loss: 0.18838 RPN box loss: 0.01315 RPN score loss: 0.01593 RPN total loss: 0.02907 Total loss: 1.0002 timestamp: 1654959234.8450267 iteration: 58175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06325 FastRCNN class loss: 0.06333 FastRCNN total loss: 0.12658 L1 loss: 0.0000e+00 L2 loss: 0.59732 Learning rate: 0.002 Mask loss: 0.10554 RPN box loss: 0.00711 RPN score loss: 0.00086 RPN total loss: 0.00796 Total loss: 0.8374 timestamp: 1654959238.182571 iteration: 58180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09156 FastRCNN class loss: 0.11538 FastRCNN total loss: 0.20694 L1 loss: 0.0000e+00 L2 loss: 0.59731 Learning rate: 0.002 Mask loss: 0.11762 RPN box loss: 0.01324 RPN score loss: 0.00696 RPN total loss: 0.02019 Total loss: 0.94207 timestamp: 1654959241.3887262 iteration: 58185 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0754 FastRCNN class loss: 0.0428 FastRCNN total loss: 0.11821 L1 loss: 0.0000e+00 L2 loss: 0.59731 Learning rate: 0.002 Mask loss: 0.12299 RPN box loss: 0.00461 RPN score loss: 0.00342 RPN total loss: 0.00803 Total loss: 0.84654 timestamp: 1654959244.6731877 iteration: 58190 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09951 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.16521 L1 loss: 0.0000e+00 L2 loss: 0.5973 Learning rate: 0.002 Mask loss: 0.11549 RPN box loss: 0.00752 RPN score loss: 0.00357 RPN total loss: 0.01109 Total loss: 0.88909 timestamp: 1654959247.8945718 iteration: 58195 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0693 FastRCNN class loss: 0.03696 FastRCNN total loss: 0.10627 L1 loss: 0.0000e+00 L2 loss: 0.59729 Learning rate: 0.002 Mask loss: 0.11318 RPN box loss: 0.00457 RPN score loss: 0.00183 RPN total loss: 0.0064 Total loss: 0.82314 timestamp: 1654959251.0997362 iteration: 58200 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06515 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.13231 L1 loss: 0.0000e+00 L2 loss: 0.59728 Learning rate: 0.002 Mask loss: 0.1181 RPN box loss: 0.01802 RPN score loss: 0.00705 RPN total loss: 0.02506 Total loss: 0.87276 timestamp: 1654959254.3371162 iteration: 58205 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13373 FastRCNN class loss: 0.07512 FastRCNN total loss: 0.20885 L1 loss: 0.0000e+00 L2 loss: 0.59728 Learning rate: 0.002 Mask loss: 0.12585 RPN box loss: 0.04141 RPN score loss: 0.0083 RPN total loss: 0.04971 Total loss: 0.98169 timestamp: 1654959257.7544801 iteration: 58210 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06656 FastRCNN class loss: 0.05076 FastRCNN total loss: 0.11732 L1 loss: 0.0000e+00 L2 loss: 0.59727 Learning rate: 0.002 Mask loss: 0.12874 RPN box loss: 0.02124 RPN score loss: 0.00798 RPN total loss: 0.02922 Total loss: 0.87255 timestamp: 1654959260.979712 iteration: 58215 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12302 FastRCNN class loss: 0.04088 FastRCNN total loss: 0.16391 L1 loss: 0.0000e+00 L2 loss: 0.59726 Learning rate: 0.002 Mask loss: 0.07692 RPN box loss: 0.0136 RPN score loss: 0.00456 RPN total loss: 0.01815 Total loss: 0.85624 timestamp: 1654959264.249547 iteration: 58220 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0902 FastRCNN class loss: 0.05147 FastRCNN total loss: 0.14168 L1 loss: 0.0000e+00 L2 loss: 0.59725 Learning rate: 0.002 Mask loss: 0.11736 RPN box loss: 0.00682 RPN score loss: 0.0028 RPN total loss: 0.00962 Total loss: 0.86591 timestamp: 1654959267.5464253 iteration: 58225 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07268 FastRCNN class loss: 0.05451 FastRCNN total loss: 0.12719 L1 loss: 0.0000e+00 L2 loss: 0.59724 Learning rate: 0.002 Mask loss: 0.13887 RPN box loss: 0.0116 RPN score loss: 0.00299 RPN total loss: 0.01459 Total loss: 0.87789 timestamp: 1654959270.9112537 iteration: 58230 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08107 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.15124 L1 loss: 0.0000e+00 L2 loss: 0.59724 Learning rate: 0.002 Mask loss: 0.12184 RPN box loss: 0.01279 RPN score loss: 0.00308 RPN total loss: 0.01586 Total loss: 0.88618 timestamp: 1654959274.229186 iteration: 58235 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04888 FastRCNN class loss: 0.05133 FastRCNN total loss: 0.1002 L1 loss: 0.0000e+00 L2 loss: 0.59723 Learning rate: 0.002 Mask loss: 0.10939 RPN box loss: 0.01175 RPN score loss: 0.00125 RPN total loss: 0.013 Total loss: 0.81982 timestamp: 1654959277.440695 iteration: 58240 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08577 FastRCNN class loss: 0.0712 FastRCNN total loss: 0.15697 L1 loss: 0.0000e+00 L2 loss: 0.59722 Learning rate: 0.002 Mask loss: 0.16397 RPN box loss: 0.00862 RPN score loss: 0.00438 RPN total loss: 0.013 Total loss: 0.93116 timestamp: 1654959280.7090993 iteration: 58245 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.14907 L1 loss: 0.0000e+00 L2 loss: 0.59721 Learning rate: 0.002 Mask loss: 0.10462 RPN box loss: 0.01244 RPN score loss: 0.00115 RPN total loss: 0.01359 Total loss: 0.86449 timestamp: 1654959283.899665 iteration: 58250 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17362 FastRCNN class loss: 0.11457 FastRCNN total loss: 0.2882 L1 loss: 0.0000e+00 L2 loss: 0.5972 Learning rate: 0.002 Mask loss: 0.21065 RPN box loss: 0.00736 RPN score loss: 0.00904 RPN total loss: 0.0164 Total loss: 1.11245 timestamp: 1654959287.246219 iteration: 58255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05149 FastRCNN class loss: 0.0376 FastRCNN total loss: 0.08908 L1 loss: 0.0000e+00 L2 loss: 0.5972 Learning rate: 0.002 Mask loss: 0.09044 RPN box loss: 0.00705 RPN score loss: 0.00381 RPN total loss: 0.01086 Total loss: 0.78758 timestamp: 1654959290.4107118 iteration: 58260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08799 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.14398 L1 loss: 0.0000e+00 L2 loss: 0.59719 Learning rate: 0.002 Mask loss: 0.11976 RPN box loss: 0.01166 RPN score loss: 0.00202 RPN total loss: 0.01368 Total loss: 0.87461 timestamp: 1654959293.6195288 iteration: 58265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13703 FastRCNN class loss: 0.06222 FastRCNN total loss: 0.19925 L1 loss: 0.0000e+00 L2 loss: 0.59718 Learning rate: 0.002 Mask loss: 0.15047 RPN box loss: 0.00927 RPN score loss: 0.00295 RPN total loss: 0.01221 Total loss: 0.95912 timestamp: 1654959296.9854674 iteration: 58270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1102 FastRCNN class loss: 0.0805 FastRCNN total loss: 0.1907 L1 loss: 0.0000e+00 L2 loss: 0.59717 Learning rate: 0.002 Mask loss: 0.19743 RPN box loss: 0.02617 RPN score loss: 0.00385 RPN total loss: 0.03002 Total loss: 1.01531 timestamp: 1654959300.1417723 iteration: 58275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09979 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.1912 L1 loss: 0.0000e+00 L2 loss: 0.59716 Learning rate: 0.002 Mask loss: 0.14864 RPN box loss: 0.00652 RPN score loss: 0.00428 RPN total loss: 0.0108 Total loss: 0.9478 timestamp: 1654959303.5438173 iteration: 58280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12845 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.19334 L1 loss: 0.0000e+00 L2 loss: 0.59715 Learning rate: 0.002 Mask loss: 0.12928 RPN box loss: 0.01125 RPN score loss: 0.0027 RPN total loss: 0.01394 Total loss: 0.9337 timestamp: 1654959306.7243063 iteration: 58285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12059 FastRCNN class loss: 0.0468 FastRCNN total loss: 0.16739 L1 loss: 0.0000e+00 L2 loss: 0.59714 Learning rate: 0.002 Mask loss: 0.10373 RPN box loss: 0.01116 RPN score loss: 0.00409 RPN total loss: 0.01526 Total loss: 0.88352 timestamp: 1654959310.0231724 iteration: 58290 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.09007 FastRCNN total loss: 0.22413 L1 loss: 0.0000e+00 L2 loss: 0.59713 Learning rate: 0.002 Mask loss: 0.1941 RPN box loss: 0.01494 RPN score loss: 0.00228 RPN total loss: 0.01723 Total loss: 1.03259 timestamp: 1654959313.2137442 iteration: 58295 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09644 FastRCNN class loss: 0.09544 FastRCNN total loss: 0.19188 L1 loss: 0.0000e+00 L2 loss: 0.59712 Learning rate: 0.002 Mask loss: 0.20244 RPN box loss: 0.03452 RPN score loss: 0.0128 RPN total loss: 0.04732 Total loss: 1.03876 timestamp: 1654959316.5262969 iteration: 58300 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08009 FastRCNN class loss: 0.10566 FastRCNN total loss: 0.18575 L1 loss: 0.0000e+00 L2 loss: 0.59712 Learning rate: 0.002 Mask loss: 0.15979 RPN box loss: 0.04026 RPN score loss: 0.01021 RPN total loss: 0.05047 Total loss: 0.99312 timestamp: 1654959319.7340078 iteration: 58305 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13873 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.20323 L1 loss: 0.0000e+00 L2 loss: 0.59711 Learning rate: 0.002 Mask loss: 0.11011 RPN box loss: 0.03405 RPN score loss: 0.0024 RPN total loss: 0.03645 Total loss: 0.94689 timestamp: 1654959323.0783398 iteration: 58310 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13544 FastRCNN class loss: 0.12014 FastRCNN total loss: 0.25558 L1 loss: 0.0000e+00 L2 loss: 0.5971 Learning rate: 0.002 Mask loss: 0.19465 RPN box loss: 0.02219 RPN score loss: 0.01719 RPN total loss: 0.03938 Total loss: 1.08671 timestamp: 1654959326.3819082 iteration: 58315 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12702 FastRCNN class loss: 0.10804 FastRCNN total loss: 0.23506 L1 loss: 0.0000e+00 L2 loss: 0.59709 Learning rate: 0.002 Mask loss: 0.12604 RPN box loss: 0.0249 RPN score loss: 0.01394 RPN total loss: 0.03884 Total loss: 0.99703 timestamp: 1654959329.5862606 iteration: 58320 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08593 FastRCNN class loss: 0.06653 FastRCNN total loss: 0.15247 L1 loss: 0.0000e+00 L2 loss: 0.59708 Learning rate: 0.002 Mask loss: 0.11402 RPN box loss: 0.00888 RPN score loss: 0.0046 RPN total loss: 0.01347 Total loss: 0.87704 timestamp: 1654959333.0076723 iteration: 58325 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05469 FastRCNN class loss: 0.06058 FastRCNN total loss: 0.11527 L1 loss: 0.0000e+00 L2 loss: 0.59708 Learning rate: 0.002 Mask loss: 0.08798 RPN box loss: 0.00699 RPN score loss: 0.00248 RPN total loss: 0.00946 Total loss: 0.80978 timestamp: 1654959336.200087 iteration: 58330 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.057 FastRCNN class loss: 0.05263 FastRCNN total loss: 0.10964 L1 loss: 0.0000e+00 L2 loss: 0.59707 Learning rate: 0.002 Mask loss: 0.11828 RPN box loss: 0.00692 RPN score loss: 0.00297 RPN total loss: 0.00989 Total loss: 0.83487 timestamp: 1654959339.4801335 iteration: 58335 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05822 FastRCNN class loss: 0.06284 FastRCNN total loss: 0.12106 L1 loss: 0.0000e+00 L2 loss: 0.59706 Learning rate: 0.002 Mask loss: 0.13077 RPN box loss: 0.03038 RPN score loss: 0.00864 RPN total loss: 0.03902 Total loss: 0.88791 timestamp: 1654959342.7061768 iteration: 58340 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09928 FastRCNN class loss: 0.06334 FastRCNN total loss: 0.16262 L1 loss: 0.0000e+00 L2 loss: 0.59705 Learning rate: 0.002 Mask loss: 0.13418 RPN box loss: 0.00625 RPN score loss: 0.00573 RPN total loss: 0.01198 Total loss: 0.90583 timestamp: 1654959345.926028 iteration: 58345 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06162 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.11865 L1 loss: 0.0000e+00 L2 loss: 0.59704 Learning rate: 0.002 Mask loss: 0.14961 RPN box loss: 0.00996 RPN score loss: 0.00235 RPN total loss: 0.01231 Total loss: 0.87761 timestamp: 1654959349.270126 iteration: 58350 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15571 FastRCNN class loss: 0.08429 FastRCNN total loss: 0.24 L1 loss: 0.0000e+00 L2 loss: 0.59703 Learning rate: 0.002 Mask loss: 0.16673 RPN box loss: 0.01543 RPN score loss: 0.00233 RPN total loss: 0.01776 Total loss: 1.02151 timestamp: 1654959352.613743 iteration: 58355 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14325 FastRCNN class loss: 0.07013 FastRCNN total loss: 0.21338 L1 loss: 0.0000e+00 L2 loss: 0.59702 Learning rate: 0.002 Mask loss: 0.14837 RPN box loss: 0.01672 RPN score loss: 0.00339 RPN total loss: 0.02011 Total loss: 0.97888 timestamp: 1654959355.789365 iteration: 58360 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08998 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.16112 L1 loss: 0.0000e+00 L2 loss: 0.59702 Learning rate: 0.002 Mask loss: 0.121 RPN box loss: 0.00907 RPN score loss: 0.00139 RPN total loss: 0.01045 Total loss: 0.88959 timestamp: 1654959359.0081193 iteration: 58365 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04763 FastRCNN class loss: 0.04012 FastRCNN total loss: 0.08775 L1 loss: 0.0000e+00 L2 loss: 0.59701 Learning rate: 0.002 Mask loss: 0.11264 RPN box loss: 0.01484 RPN score loss: 0.00222 RPN total loss: 0.01706 Total loss: 0.81446 timestamp: 1654959362.210272 iteration: 58370 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05894 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.13984 L1 loss: 0.0000e+00 L2 loss: 0.597 Learning rate: 0.002 Mask loss: 0.10053 RPN box loss: 0.01272 RPN score loss: 0.00198 RPN total loss: 0.0147 Total loss: 0.85207 timestamp: 1654959365.4030848 iteration: 58375 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09944 FastRCNN class loss: 0.04508 FastRCNN total loss: 0.14452 L1 loss: 0.0000e+00 L2 loss: 0.59699 Learning rate: 0.002 Mask loss: 0.11158 RPN box loss: 0.00647 RPN score loss: 0.00133 RPN total loss: 0.00779 Total loss: 0.86089 timestamp: 1654959368.6800115 iteration: 58380 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09877 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.17395 L1 loss: 0.0000e+00 L2 loss: 0.59699 Learning rate: 0.002 Mask loss: 0.14414 RPN box loss: 0.00615 RPN score loss: 0.01087 RPN total loss: 0.01702 Total loss: 0.93211 timestamp: 1654959371.8162704 iteration: 58385 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13839 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.21283 L1 loss: 0.0000e+00 L2 loss: 0.59698 Learning rate: 0.002 Mask loss: 0.14618 RPN box loss: 0.00736 RPN score loss: 0.00301 RPN total loss: 0.01038 Total loss: 0.96637 timestamp: 1654959375.056975 iteration: 58390 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06089 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.13688 L1 loss: 0.0000e+00 L2 loss: 0.59697 Learning rate: 0.002 Mask loss: 0.1377 RPN box loss: 0.01079 RPN score loss: 0.0046 RPN total loss: 0.01539 Total loss: 0.88693 timestamp: 1654959378.219743 iteration: 58395 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07972 FastRCNN class loss: 0.03817 FastRCNN total loss: 0.11789 L1 loss: 0.0000e+00 L2 loss: 0.59696 Learning rate: 0.002 Mask loss: 0.10353 RPN box loss: 0.02062 RPN score loss: 0.00128 RPN total loss: 0.0219 Total loss: 0.84028 timestamp: 1654959381.4055982 iteration: 58400 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09909 FastRCNN class loss: 0.08346 FastRCNN total loss: 0.18255 L1 loss: 0.0000e+00 L2 loss: 0.59695 Learning rate: 0.002 Mask loss: 0.17476 RPN box loss: 0.02619 RPN score loss: 0.00815 RPN total loss: 0.03433 Total loss: 0.9886 timestamp: 1654959384.5945537 iteration: 58405 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04339 FastRCNN class loss: 0.0585 FastRCNN total loss: 0.10189 L1 loss: 0.0000e+00 L2 loss: 0.59694 Learning rate: 0.002 Mask loss: 0.1005 RPN box loss: 0.00695 RPN score loss: 0.00209 RPN total loss: 0.00904 Total loss: 0.80837 timestamp: 1654959387.8732333 iteration: 58410 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1062 FastRCNN class loss: 0.12055 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 0.59693 Learning rate: 0.002 Mask loss: 0.1318 RPN box loss: 0.01287 RPN score loss: 0.01383 RPN total loss: 0.0267 Total loss: 0.98219 timestamp: 1654959391.0895407 iteration: 58415 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11234 FastRCNN class loss: 0.09541 FastRCNN total loss: 0.20775 L1 loss: 0.0000e+00 L2 loss: 0.59692 Learning rate: 0.002 Mask loss: 0.14646 RPN box loss: 0.03589 RPN score loss: 0.00603 RPN total loss: 0.04192 Total loss: 0.99306 timestamp: 1654959394.3097246 iteration: 58420 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06042 FastRCNN class loss: 0.08769 FastRCNN total loss: 0.1481 L1 loss: 0.0000e+00 L2 loss: 0.59692 Learning rate: 0.002 Mask loss: 0.14559 RPN box loss: 0.02789 RPN score loss: 0.01176 RPN total loss: 0.03964 Total loss: 0.93026 timestamp: 1654959397.5047429 iteration: 58425 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06347 FastRCNN class loss: 0.04308 FastRCNN total loss: 0.10655 L1 loss: 0.0000e+00 L2 loss: 0.59691 Learning rate: 0.002 Mask loss: 0.07873 RPN box loss: 0.01171 RPN score loss: 0.00124 RPN total loss: 0.01295 Total loss: 0.79513 timestamp: 1654959400.7611778 iteration: 58430 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17577 FastRCNN class loss: 0.07969 FastRCNN total loss: 0.25545 L1 loss: 0.0000e+00 L2 loss: 0.5969 Learning rate: 0.002 Mask loss: 0.18651 RPN box loss: 0.02743 RPN score loss: 0.00486 RPN total loss: 0.03229 Total loss: 1.07115 timestamp: 1654959404.0589204 iteration: 58435 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11621 FastRCNN class loss: 0.08288 FastRCNN total loss: 0.19908 L1 loss: 0.0000e+00 L2 loss: 0.59689 Learning rate: 0.002 Mask loss: 0.15743 RPN box loss: 0.01548 RPN score loss: 0.0098 RPN total loss: 0.02528 Total loss: 0.97868 timestamp: 1654959407.2833629 iteration: 58440 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.04537 FastRCNN total loss: 0.12192 L1 loss: 0.0000e+00 L2 loss: 0.59689 Learning rate: 0.002 Mask loss: 0.1112 RPN box loss: 0.00441 RPN score loss: 0.00523 RPN total loss: 0.00965 Total loss: 0.83966 timestamp: 1654959410.5037577 iteration: 58445 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09731 FastRCNN class loss: 0.05133 FastRCNN total loss: 0.14863 L1 loss: 0.0000e+00 L2 loss: 0.59688 Learning rate: 0.002 Mask loss: 0.08757 RPN box loss: 0.01649 RPN score loss: 0.00186 RPN total loss: 0.01834 Total loss: 0.85143 timestamp: 1654959413.6790195 iteration: 58450 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19103 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.26624 L1 loss: 0.0000e+00 L2 loss: 0.59687 Learning rate: 0.002 Mask loss: 0.17216 RPN box loss: 0.02232 RPN score loss: 0.00254 RPN total loss: 0.02486 Total loss: 1.06013 timestamp: 1654959416.8592982 iteration: 58455 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10582 FastRCNN class loss: 0.1015 FastRCNN total loss: 0.20732 L1 loss: 0.0000e+00 L2 loss: 0.59686 Learning rate: 0.002 Mask loss: 0.12496 RPN box loss: 0.02628 RPN score loss: 0.01187 RPN total loss: 0.03814 Total loss: 0.96728 timestamp: 1654959420.1075132 iteration: 58460 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08902 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.16069 L1 loss: 0.0000e+00 L2 loss: 0.59685 Learning rate: 0.002 Mask loss: 0.19597 RPN box loss: 0.02525 RPN score loss: 0.00569 RPN total loss: 0.03094 Total loss: 0.98445 timestamp: 1654959423.2840378 iteration: 58465 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0535 FastRCNN class loss: 0.03926 FastRCNN total loss: 0.09275 L1 loss: 0.0000e+00 L2 loss: 0.59684 Learning rate: 0.002 Mask loss: 0.09902 RPN box loss: 0.00981 RPN score loss: 0.00127 RPN total loss: 0.01108 Total loss: 0.7997 timestamp: 1654959426.5554414 iteration: 58470 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07939 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.13739 L1 loss: 0.0000e+00 L2 loss: 0.59683 Learning rate: 0.002 Mask loss: 0.15637 RPN box loss: 0.00946 RPN score loss: 0.00587 RPN total loss: 0.01533 Total loss: 0.90592 timestamp: 1654959429.7696373 iteration: 58475 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06695 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.13388 L1 loss: 0.0000e+00 L2 loss: 0.59682 Learning rate: 0.002 Mask loss: 0.10082 RPN box loss: 0.01362 RPN score loss: 0.00119 RPN total loss: 0.01481 Total loss: 0.84634 timestamp: 1654959432.9694767 iteration: 58480 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0955 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.15415 L1 loss: 0.0000e+00 L2 loss: 0.59681 Learning rate: 0.002 Mask loss: 0.13679 RPN box loss: 0.01341 RPN score loss: 0.01914 RPN total loss: 0.03255 Total loss: 0.9203 timestamp: 1654959436.0975122 iteration: 58485 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07628 FastRCNN class loss: 0.06017 FastRCNN total loss: 0.13646 L1 loss: 0.0000e+00 L2 loss: 0.5968 Learning rate: 0.002 Mask loss: 0.10462 RPN box loss: 0.03044 RPN score loss: 0.00258 RPN total loss: 0.03302 Total loss: 0.8709 timestamp: 1654959439.4091768 iteration: 58490 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04876 FastRCNN class loss: 0.05914 FastRCNN total loss: 0.1079 L1 loss: 0.0000e+00 L2 loss: 0.5968 Learning rate: 0.002 Mask loss: 0.09581 RPN box loss: 0.01258 RPN score loss: 0.00182 RPN total loss: 0.0144 Total loss: 0.8149 timestamp: 1654959442.6171813 iteration: 58495 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08188 FastRCNN class loss: 0.04607 FastRCNN total loss: 0.12795 L1 loss: 0.0000e+00 L2 loss: 0.59679 Learning rate: 0.002 Mask loss: 0.07918 RPN box loss: 0.00862 RPN score loss: 0.00195 RPN total loss: 0.01056 Total loss: 0.81449 timestamp: 1654959445.7950945 iteration: 58500 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09606 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.17855 L1 loss: 0.0000e+00 L2 loss: 0.59678 Learning rate: 0.002 Mask loss: 0.17894 RPN box loss: 0.03959 RPN score loss: 0.00946 RPN total loss: 0.04905 Total loss: 1.00332 timestamp: 1654959449.0046365 iteration: 58505 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07538 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.13662 L1 loss: 0.0000e+00 L2 loss: 0.59677 Learning rate: 0.002 Mask loss: 0.15012 RPN box loss: 0.01437 RPN score loss: 0.01229 RPN total loss: 0.02665 Total loss: 0.91017 timestamp: 1654959452.1828032 iteration: 58510 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.07843 FastRCNN total loss: 0.19396 L1 loss: 0.0000e+00 L2 loss: 0.59676 Learning rate: 0.002 Mask loss: 0.18733 RPN box loss: 0.00955 RPN score loss: 0.00381 RPN total loss: 0.01336 Total loss: 0.99141 timestamp: 1654959455.4387615 iteration: 58515 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1064 FastRCNN class loss: 0.05266 FastRCNN total loss: 0.15905 L1 loss: 0.0000e+00 L2 loss: 0.59676 Learning rate: 0.002 Mask loss: 0.08558 RPN box loss: 0.01383 RPN score loss: 0.00809 RPN total loss: 0.02191 Total loss: 0.8633 timestamp: 1654959458.6407437 iteration: 58520 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08737 FastRCNN class loss: 0.04881 FastRCNN total loss: 0.13618 L1 loss: 0.0000e+00 L2 loss: 0.59675 Learning rate: 0.002 Mask loss: 0.10855 RPN box loss: 0.0057 RPN score loss: 0.00179 RPN total loss: 0.00748 Total loss: 0.84896 timestamp: 1654959461.7897358 iteration: 58525 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06063 FastRCNN class loss: 0.04971 FastRCNN total loss: 0.11034 L1 loss: 0.0000e+00 L2 loss: 0.59674 Learning rate: 0.002 Mask loss: 0.0893 RPN box loss: 0.00947 RPN score loss: 0.00164 RPN total loss: 0.01111 Total loss: 0.80749 timestamp: 1654959464.9589624 iteration: 58530 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12613 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.19302 L1 loss: 0.0000e+00 L2 loss: 0.59674 Learning rate: 0.002 Mask loss: 0.12675 RPN box loss: 0.00583 RPN score loss: 0.00375 RPN total loss: 0.00958 Total loss: 0.92609 timestamp: 1654959468.1283538 iteration: 58535 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08006 FastRCNN class loss: 0.09637 FastRCNN total loss: 0.17643 L1 loss: 0.0000e+00 L2 loss: 0.59673 Learning rate: 0.002 Mask loss: 0.19842 RPN box loss: 0.01816 RPN score loss: 0.00166 RPN total loss: 0.01982 Total loss: 0.9914 timestamp: 1654959471.3265479 iteration: 58540 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12674 FastRCNN class loss: 0.08056 FastRCNN total loss: 0.2073 L1 loss: 0.0000e+00 L2 loss: 0.59672 Learning rate: 0.002 Mask loss: 0.10613 RPN box loss: 0.00995 RPN score loss: 0.00199 RPN total loss: 0.01194 Total loss: 0.9221 timestamp: 1654959474.5182686 iteration: 58545 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06414 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.13064 L1 loss: 0.0000e+00 L2 loss: 0.59671 Learning rate: 0.002 Mask loss: 0.13855 RPN box loss: 0.01034 RPN score loss: 0.00319 RPN total loss: 0.01353 Total loss: 0.87943 timestamp: 1654959477.6482856 iteration: 58550 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06837 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.12289 L1 loss: 0.0000e+00 L2 loss: 0.59671 Learning rate: 0.002 Mask loss: 0.16312 RPN box loss: 0.01072 RPN score loss: 0.01138 RPN total loss: 0.02209 Total loss: 0.90481 timestamp: 1654959480.8477325 iteration: 58555 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10487 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.20523 L1 loss: 0.0000e+00 L2 loss: 0.5967 Learning rate: 0.002 Mask loss: 0.19948 RPN box loss: 0.02843 RPN score loss: 0.00875 RPN total loss: 0.03718 Total loss: 1.03859 timestamp: 1654959484.1037374 iteration: 58560 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08573 FastRCNN class loss: 0.0768 FastRCNN total loss: 0.16253 L1 loss: 0.0000e+00 L2 loss: 0.59669 Learning rate: 0.002 Mask loss: 0.16257 RPN box loss: 0.02526 RPN score loss: 0.01071 RPN total loss: 0.03597 Total loss: 0.95777 timestamp: 1654959487.3074918 iteration: 58565 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11202 FastRCNN class loss: 0.06333 FastRCNN total loss: 0.17535 L1 loss: 0.0000e+00 L2 loss: 0.59668 Learning rate: 0.002 Mask loss: 0.11711 RPN box loss: 0.01293 RPN score loss: 0.00161 RPN total loss: 0.01454 Total loss: 0.90368 timestamp: 1654959490.5354662 iteration: 58570 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07393 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.13378 L1 loss: 0.0000e+00 L2 loss: 0.59668 Learning rate: 0.002 Mask loss: 0.10917 RPN box loss: 0.00923 RPN score loss: 0.00258 RPN total loss: 0.01181 Total loss: 0.85143 timestamp: 1654959493.7686267 iteration: 58575 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10193 FastRCNN class loss: 0.07823 FastRCNN total loss: 0.18016 L1 loss: 0.0000e+00 L2 loss: 0.59667 Learning rate: 0.002 Mask loss: 0.1119 RPN box loss: 0.00944 RPN score loss: 0.00653 RPN total loss: 0.01597 Total loss: 0.9047 timestamp: 1654959496.9948797 iteration: 58580 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06679 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.1323 L1 loss: 0.0000e+00 L2 loss: 0.59666 Learning rate: 0.002 Mask loss: 0.11421 RPN box loss: 0.00874 RPN score loss: 0.00264 RPN total loss: 0.01139 Total loss: 0.85457 timestamp: 1654959500.1864328 iteration: 58585 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08395 FastRCNN class loss: 0.07066 FastRCNN total loss: 0.15461 L1 loss: 0.0000e+00 L2 loss: 0.59665 Learning rate: 0.002 Mask loss: 0.13888 RPN box loss: 0.02195 RPN score loss: 0.00694 RPN total loss: 0.02889 Total loss: 0.91904 timestamp: 1654959503.4180267 iteration: 58590 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07976 FastRCNN class loss: 0.09037 FastRCNN total loss: 0.17013 L1 loss: 0.0000e+00 L2 loss: 0.59664 Learning rate: 0.002 Mask loss: 0.18826 RPN box loss: 0.01337 RPN score loss: 0.00766 RPN total loss: 0.02103 Total loss: 0.97606 timestamp: 1654959506.6273742 iteration: 58595 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07826 FastRCNN class loss: 0.06735 FastRCNN total loss: 0.14561 L1 loss: 0.0000e+00 L2 loss: 0.59663 Learning rate: 0.002 Mask loss: 0.15861 RPN box loss: 0.00866 RPN score loss: 0.00433 RPN total loss: 0.01299 Total loss: 0.91385 timestamp: 1654959509.9087517 iteration: 58600 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14139 FastRCNN class loss: 0.13091 FastRCNN total loss: 0.27231 L1 loss: 0.0000e+00 L2 loss: 0.59662 Learning rate: 0.002 Mask loss: 0.17111 RPN box loss: 0.0192 RPN score loss: 0.00877 RPN total loss: 0.02797 Total loss: 1.06801 timestamp: 1654959513.1006713 iteration: 58605 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05353 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.12718 L1 loss: 0.0000e+00 L2 loss: 0.59662 Learning rate: 0.002 Mask loss: 0.12203 RPN box loss: 0.01105 RPN score loss: 0.00542 RPN total loss: 0.01647 Total loss: 0.8623 timestamp: 1654959516.4023798 iteration: 58610 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06635 FastRCNN class loss: 0.04921 FastRCNN total loss: 0.11556 L1 loss: 0.0000e+00 L2 loss: 0.59661 Learning rate: 0.002 Mask loss: 0.13304 RPN box loss: 0.01443 RPN score loss: 0.00627 RPN total loss: 0.0207 Total loss: 0.86591 timestamp: 1654959519.5556111 iteration: 58615 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08086 FastRCNN class loss: 0.06856 FastRCNN total loss: 0.14941 L1 loss: 0.0000e+00 L2 loss: 0.5966 Learning rate: 0.002 Mask loss: 0.13946 RPN box loss: 0.02411 RPN score loss: 0.00602 RPN total loss: 0.03013 Total loss: 0.9156 timestamp: 1654959522.7572813 iteration: 58620 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05712 FastRCNN class loss: 0.06292 FastRCNN total loss: 0.12003 L1 loss: 0.0000e+00 L2 loss: 0.59659 Learning rate: 0.002 Mask loss: 0.09898 RPN box loss: 0.02339 RPN score loss: 0.01053 RPN total loss: 0.03392 Total loss: 0.84953 timestamp: 1654959525.9981394 iteration: 58625 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09629 FastRCNN class loss: 0.05803 FastRCNN total loss: 0.15432 L1 loss: 0.0000e+00 L2 loss: 0.59659 Learning rate: 0.002 Mask loss: 0.15548 RPN box loss: 0.00761 RPN score loss: 0.00235 RPN total loss: 0.00996 Total loss: 0.91634 timestamp: 1654959529.1670108 iteration: 58630 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0818 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.13367 L1 loss: 0.0000e+00 L2 loss: 0.59658 Learning rate: 0.002 Mask loss: 0.10107 RPN box loss: 0.00867 RPN score loss: 0.00033 RPN total loss: 0.009 Total loss: 0.84031 timestamp: 1654959532.339556 iteration: 58635 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1605 FastRCNN class loss: 0.09126 FastRCNN total loss: 0.25176 L1 loss: 0.0000e+00 L2 loss: 0.59657 Learning rate: 0.002 Mask loss: 0.15545 RPN box loss: 0.02321 RPN score loss: 0.01031 RPN total loss: 0.03353 Total loss: 1.03731 timestamp: 1654959535.543562 iteration: 58640 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14109 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.21682 L1 loss: 0.0000e+00 L2 loss: 0.59656 Learning rate: 0.002 Mask loss: 0.15454 RPN box loss: 0.00705 RPN score loss: 0.00228 RPN total loss: 0.00933 Total loss: 0.97724 timestamp: 1654959538.6759589 iteration: 58645 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06713 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.12283 L1 loss: 0.0000e+00 L2 loss: 0.59655 Learning rate: 0.002 Mask loss: 0.12289 RPN box loss: 0.03832 RPN score loss: 0.0046 RPN total loss: 0.04292 Total loss: 0.88519 timestamp: 1654959541.895493 iteration: 58650 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07772 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.13934 L1 loss: 0.0000e+00 L2 loss: 0.59654 Learning rate: 0.002 Mask loss: 0.10841 RPN box loss: 0.0118 RPN score loss: 0.00169 RPN total loss: 0.01349 Total loss: 0.85779 timestamp: 1654959545.1633449 iteration: 58655 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09297 FastRCNN class loss: 0.0779 FastRCNN total loss: 0.17087 L1 loss: 0.0000e+00 L2 loss: 0.59654 Learning rate: 0.002 Mask loss: 0.14485 RPN box loss: 0.01397 RPN score loss: 0.00452 RPN total loss: 0.0185 Total loss: 0.93075 timestamp: 1654959548.3673494 iteration: 58660 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14691 FastRCNN class loss: 0.13563 FastRCNN total loss: 0.28255 L1 loss: 0.0000e+00 L2 loss: 0.59653 Learning rate: 0.002 Mask loss: 0.1674 RPN box loss: 0.01646 RPN score loss: 0.00705 RPN total loss: 0.02351 Total loss: 1.06998 timestamp: 1654959551.578045 iteration: 58665 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07762 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.12786 L1 loss: 0.0000e+00 L2 loss: 0.59651 Learning rate: 0.002 Mask loss: 0.10733 RPN box loss: 0.00673 RPN score loss: 0.00724 RPN total loss: 0.01397 Total loss: 0.84568 timestamp: 1654959554.8130608 iteration: 58670 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14338 FastRCNN class loss: 0.09129 FastRCNN total loss: 0.23467 L1 loss: 0.0000e+00 L2 loss: 0.5965 Learning rate: 0.002 Mask loss: 0.16776 RPN box loss: 0.01178 RPN score loss: 0.00823 RPN total loss: 0.02001 Total loss: 1.01894 timestamp: 1654959557.9933143 iteration: 58675 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09018 FastRCNN class loss: 0.0563 FastRCNN total loss: 0.14648 L1 loss: 0.0000e+00 L2 loss: 0.5965 Learning rate: 0.002 Mask loss: 0.12308 RPN box loss: 0.00845 RPN score loss: 0.00341 RPN total loss: 0.01187 Total loss: 0.87793 timestamp: 1654959561.2110984 iteration: 58680 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08173 FastRCNN class loss: 0.03351 FastRCNN total loss: 0.11524 L1 loss: 0.0000e+00 L2 loss: 0.59649 Learning rate: 0.002 Mask loss: 0.07703 RPN box loss: 0.0098 RPN score loss: 0.00053 RPN total loss: 0.01033 Total loss: 0.79909 timestamp: 1654959564.4295404 iteration: 58685 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1241 FastRCNN class loss: 0.09163 FastRCNN total loss: 0.21573 L1 loss: 0.0000e+00 L2 loss: 0.59648 Learning rate: 0.002 Mask loss: 0.13586 RPN box loss: 0.02028 RPN score loss: 0.00781 RPN total loss: 0.02809 Total loss: 0.97616 timestamp: 1654959567.6325817 iteration: 58690 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06653 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.13045 L1 loss: 0.0000e+00 L2 loss: 0.59648 Learning rate: 0.002 Mask loss: 0.12813 RPN box loss: 0.007 RPN score loss: 0.00165 RPN total loss: 0.00866 Total loss: 0.86371 timestamp: 1654959570.774828 iteration: 58695 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10346 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.16282 L1 loss: 0.0000e+00 L2 loss: 0.59647 Learning rate: 0.002 Mask loss: 0.14667 RPN box loss: 0.01002 RPN score loss: 0.00308 RPN total loss: 0.0131 Total loss: 0.91907 timestamp: 1654959574.0323102 iteration: 58700 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08711 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.14732 L1 loss: 0.0000e+00 L2 loss: 0.59646 Learning rate: 0.002 Mask loss: 0.13635 RPN box loss: 0.01262 RPN score loss: 0.0036 RPN total loss: 0.01621 Total loss: 0.89634 timestamp: 1654959577.232954 iteration: 58705 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.1629 L1 loss: 0.0000e+00 L2 loss: 0.59645 Learning rate: 0.002 Mask loss: 0.11486 RPN box loss: 0.01079 RPN score loss: 0.00393 RPN total loss: 0.01472 Total loss: 0.88893 timestamp: 1654959580.4999495 iteration: 58710 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08368 FastRCNN class loss: 0.04545 FastRCNN total loss: 0.12913 L1 loss: 0.0000e+00 L2 loss: 0.59644 Learning rate: 0.002 Mask loss: 0.12158 RPN box loss: 0.00252 RPN score loss: 0.00155 RPN total loss: 0.00407 Total loss: 0.85121 timestamp: 1654959583.7167754 iteration: 58715 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10474 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.18445 L1 loss: 0.0000e+00 L2 loss: 0.59644 Learning rate: 0.002 Mask loss: 0.13555 RPN box loss: 0.0142 RPN score loss: 0.00861 RPN total loss: 0.02281 Total loss: 0.93925 timestamp: 1654959586.8769848 iteration: 58720 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14492 FastRCNN class loss: 0.07981 FastRCNN total loss: 0.22473 L1 loss: 0.0000e+00 L2 loss: 0.59643 Learning rate: 0.002 Mask loss: 0.14836 RPN box loss: 0.00982 RPN score loss: 0.00556 RPN total loss: 0.01539 Total loss: 0.98491 timestamp: 1654959590.045885 iteration: 58725 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04028 FastRCNN class loss: 0.04459 FastRCNN total loss: 0.08487 L1 loss: 0.0000e+00 L2 loss: 0.59642 Learning rate: 0.002 Mask loss: 0.0952 RPN box loss: 0.00406 RPN score loss: 0.00069 RPN total loss: 0.00475 Total loss: 0.78124 timestamp: 1654959593.3017626 iteration: 58730 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15541 FastRCNN class loss: 0.10653 FastRCNN total loss: 0.26194 L1 loss: 0.0000e+00 L2 loss: 0.59642 Learning rate: 0.002 Mask loss: 0.12963 RPN box loss: 0.037 RPN score loss: 0.00539 RPN total loss: 0.04239 Total loss: 1.03037 timestamp: 1654959596.4656372 iteration: 58735 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09957 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.18998 L1 loss: 0.0000e+00 L2 loss: 0.59641 Learning rate: 0.002 Mask loss: 0.18439 RPN box loss: 0.01271 RPN score loss: 0.01091 RPN total loss: 0.02362 Total loss: 0.9944 timestamp: 1654959599.6286814 iteration: 58740 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14854 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.23466 L1 loss: 0.0000e+00 L2 loss: 0.5964 Learning rate: 0.002 Mask loss: 0.17293 RPN box loss: 0.02161 RPN score loss: 0.00245 RPN total loss: 0.02407 Total loss: 1.02806 timestamp: 1654959602.787535 iteration: 58745 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.02995 FastRCNN total loss: 0.10105 L1 loss: 0.0000e+00 L2 loss: 0.59639 Learning rate: 0.002 Mask loss: 0.11887 RPN box loss: 0.0059 RPN score loss: 0.00301 RPN total loss: 0.00891 Total loss: 0.82522 timestamp: 1654959606.0342135 iteration: 58750 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06564 FastRCNN class loss: 0.08455 FastRCNN total loss: 0.15019 L1 loss: 0.0000e+00 L2 loss: 0.59638 Learning rate: 0.002 Mask loss: 0.17625 RPN box loss: 0.0208 RPN score loss: 0.00846 RPN total loss: 0.02926 Total loss: 0.95208 timestamp: 1654959609.2680438 iteration: 58755 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08506 FastRCNN class loss: 0.06485 FastRCNN total loss: 0.1499 L1 loss: 0.0000e+00 L2 loss: 0.59637 Learning rate: 0.002 Mask loss: 0.11057 RPN box loss: 0.00546 RPN score loss: 0.00047 RPN total loss: 0.00593 Total loss: 0.86277 timestamp: 1654959612.4576626 iteration: 58760 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09909 FastRCNN class loss: 0.04294 FastRCNN total loss: 0.14203 L1 loss: 0.0000e+00 L2 loss: 0.59636 Learning rate: 0.002 Mask loss: 0.11807 RPN box loss: 0.00484 RPN score loss: 0.0009 RPN total loss: 0.00574 Total loss: 0.8622 timestamp: 1654959615.6627607 iteration: 58765 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11106 FastRCNN class loss: 0.109 FastRCNN total loss: 0.22006 L1 loss: 0.0000e+00 L2 loss: 0.59635 Learning rate: 0.002 Mask loss: 0.16439 RPN box loss: 0.02152 RPN score loss: 0.009 RPN total loss: 0.03052 Total loss: 1.01132 timestamp: 1654959618.8859928 iteration: 58770 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05698 FastRCNN class loss: 0.04127 FastRCNN total loss: 0.09825 L1 loss: 0.0000e+00 L2 loss: 0.59634 Learning rate: 0.002 Mask loss: 0.09989 RPN box loss: 0.01842 RPN score loss: 0.00376 RPN total loss: 0.02218 Total loss: 0.81667 timestamp: 1654959622.1377823 iteration: 58775 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13924 FastRCNN class loss: 0.11995 FastRCNN total loss: 0.25919 L1 loss: 0.0000e+00 L2 loss: 0.59633 Learning rate: 0.002 Mask loss: 0.15344 RPN box loss: 0.03177 RPN score loss: 0.00851 RPN total loss: 0.04029 Total loss: 1.04925 timestamp: 1654959625.2974126 iteration: 58780 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07469 FastRCNN class loss: 0.05738 FastRCNN total loss: 0.13207 L1 loss: 0.0000e+00 L2 loss: 0.59632 Learning rate: 0.002 Mask loss: 0.08391 RPN box loss: 0.00712 RPN score loss: 0.00092 RPN total loss: 0.00804 Total loss: 0.82035 timestamp: 1654959628.4791567 iteration: 58785 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.05983 FastRCNN total loss: 0.13779 L1 loss: 0.0000e+00 L2 loss: 0.59631 Learning rate: 0.002 Mask loss: 0.08292 RPN box loss: 0.03479 RPN score loss: 0.00321 RPN total loss: 0.03801 Total loss: 0.85503 timestamp: 1654959631.7387815 iteration: 58790 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08842 FastRCNN class loss: 0.07312 FastRCNN total loss: 0.16154 L1 loss: 0.0000e+00 L2 loss: 0.59631 Learning rate: 0.002 Mask loss: 0.15851 RPN box loss: 0.01478 RPN score loss: 0.00784 RPN total loss: 0.02262 Total loss: 0.93898 timestamp: 1654959634.8846 iteration: 58795 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.13389 L1 loss: 0.0000e+00 L2 loss: 0.5963 Learning rate: 0.002 Mask loss: 0.13556 RPN box loss: 0.01726 RPN score loss: 0.01246 RPN total loss: 0.02972 Total loss: 0.89545 timestamp: 1654959638.0683293 iteration: 58800 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11972 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.17319 L1 loss: 0.0000e+00 L2 loss: 0.59629 Learning rate: 0.002 Mask loss: 0.09621 RPN box loss: 0.00986 RPN score loss: 0.00478 RPN total loss: 0.01464 Total loss: 0.88033 timestamp: 1654959641.2558365 iteration: 58805 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10579 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.18501 L1 loss: 0.0000e+00 L2 loss: 0.59628 Learning rate: 0.002 Mask loss: 0.13254 RPN box loss: 0.00692 RPN score loss: 0.00414 RPN total loss: 0.01106 Total loss: 0.92489 timestamp: 1654959644.4489207 iteration: 58810 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07062 FastRCNN class loss: 0.04754 FastRCNN total loss: 0.11815 L1 loss: 0.0000e+00 L2 loss: 0.59628 Learning rate: 0.002 Mask loss: 0.13469 RPN box loss: 0.00458 RPN score loss: 0.00298 RPN total loss: 0.00756 Total loss: 0.85668 timestamp: 1654959647.6645935 iteration: 58815 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08658 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.15825 L1 loss: 0.0000e+00 L2 loss: 0.59627 Learning rate: 0.002 Mask loss: 0.16865 RPN box loss: 0.0194 RPN score loss: 0.01214 RPN total loss: 0.03154 Total loss: 0.95471 timestamp: 1654959650.8355691 iteration: 58820 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07816 FastRCNN class loss: 0.12496 FastRCNN total loss: 0.20312 L1 loss: 0.0000e+00 L2 loss: 0.59626 Learning rate: 0.002 Mask loss: 0.17071 RPN box loss: 0.0154 RPN score loss: 0.02238 RPN total loss: 0.03778 Total loss: 1.00786 timestamp: 1654959654.0789409 iteration: 58825 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09228 FastRCNN class loss: 0.07672 FastRCNN total loss: 0.169 L1 loss: 0.0000e+00 L2 loss: 0.59625 Learning rate: 0.002 Mask loss: 0.12804 RPN box loss: 0.00312 RPN score loss: 0.00069 RPN total loss: 0.00381 Total loss: 0.8971 timestamp: 1654959657.3053238 iteration: 58830 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08664 FastRCNN class loss: 0.05147 FastRCNN total loss: 0.13811 L1 loss: 0.0000e+00 L2 loss: 0.59624 Learning rate: 0.002 Mask loss: 0.14549 RPN box loss: 0.00982 RPN score loss: 0.00174 RPN total loss: 0.01156 Total loss: 0.89139 timestamp: 1654959660.5358372 iteration: 58835 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07918 FastRCNN class loss: 0.0697 FastRCNN total loss: 0.14888 L1 loss: 0.0000e+00 L2 loss: 0.59623 Learning rate: 0.002 Mask loss: 0.1742 RPN box loss: 0.01003 RPN score loss: 0.00348 RPN total loss: 0.0135 Total loss: 0.9328 timestamp: 1654959663.7333431 iteration: 58840 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09023 FastRCNN class loss: 0.05344 FastRCNN total loss: 0.14367 L1 loss: 0.0000e+00 L2 loss: 0.59622 Learning rate: 0.002 Mask loss: 0.12378 RPN box loss: 0.00986 RPN score loss: 0.00928 RPN total loss: 0.01914 Total loss: 0.8828 timestamp: 1654959666.9702141 iteration: 58845 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06833 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.13274 L1 loss: 0.0000e+00 L2 loss: 0.59621 Learning rate: 0.002 Mask loss: 0.15937 RPN box loss: 0.02092 RPN score loss: 0.00664 RPN total loss: 0.02756 Total loss: 0.91588 timestamp: 1654959670.055598 iteration: 58850 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11835 FastRCNN class loss: 0.05923 FastRCNN total loss: 0.17758 L1 loss: 0.0000e+00 L2 loss: 0.5962 Learning rate: 0.002 Mask loss: 0.08968 RPN box loss: 0.02981 RPN score loss: 0.006 RPN total loss: 0.03581 Total loss: 0.89927 timestamp: 1654959673.2877738 iteration: 58855 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.21716 L1 loss: 0.0000e+00 L2 loss: 0.59619 Learning rate: 0.002 Mask loss: 0.13065 RPN box loss: 0.01996 RPN score loss: 0.00854 RPN total loss: 0.0285 Total loss: 0.97249 timestamp: 1654959676.5042446 iteration: 58860 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08924 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.14724 L1 loss: 0.0000e+00 L2 loss: 0.59618 Learning rate: 0.002 Mask loss: 0.14865 RPN box loss: 0.01717 RPN score loss: 0.00242 RPN total loss: 0.01959 Total loss: 0.91168 timestamp: 1654959679.7893908 iteration: 58865 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08178 FastRCNN class loss: 0.04207 FastRCNN total loss: 0.12385 L1 loss: 0.0000e+00 L2 loss: 0.59618 Learning rate: 0.002 Mask loss: 0.1647 RPN box loss: 0.0092 RPN score loss: 0.00255 RPN total loss: 0.01176 Total loss: 0.89649 timestamp: 1654959683.0092244 iteration: 58870 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13922 FastRCNN class loss: 0.13744 FastRCNN total loss: 0.27665 L1 loss: 0.0000e+00 L2 loss: 0.59617 Learning rate: 0.002 Mask loss: 0.14007 RPN box loss: 0.02873 RPN score loss: 0.00709 RPN total loss: 0.03582 Total loss: 1.04872 timestamp: 1654959686.269343 iteration: 58875 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08699 FastRCNN class loss: 0.04911 FastRCNN total loss: 0.1361 L1 loss: 0.0000e+00 L2 loss: 0.59616 Learning rate: 0.002 Mask loss: 0.09651 RPN box loss: 0.01149 RPN score loss: 0.00314 RPN total loss: 0.01464 Total loss: 0.84341 timestamp: 1654959689.4967923 iteration: 58880 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10691 FastRCNN class loss: 0.13285 FastRCNN total loss: 0.23976 L1 loss: 0.0000e+00 L2 loss: 0.59616 Learning rate: 0.002 Mask loss: 0.16368 RPN box loss: 0.02306 RPN score loss: 0.00972 RPN total loss: 0.03278 Total loss: 1.03239 timestamp: 1654959692.6895752 iteration: 58885 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.0426 FastRCNN total loss: 0.14057 L1 loss: 0.0000e+00 L2 loss: 0.59615 Learning rate: 0.002 Mask loss: 0.11638 RPN box loss: 0.00653 RPN score loss: 0.00258 RPN total loss: 0.00911 Total loss: 0.8622 timestamp: 1654959695.888554 iteration: 58890 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08911 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.14807 L1 loss: 0.0000e+00 L2 loss: 0.59614 Learning rate: 0.002 Mask loss: 0.13351 RPN box loss: 0.01431 RPN score loss: 0.00891 RPN total loss: 0.02322 Total loss: 0.90095 timestamp: 1654959699.1206248 iteration: 58895 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0958 FastRCNN class loss: 0.06835 FastRCNN total loss: 0.16416 L1 loss: 0.0000e+00 L2 loss: 0.59613 Learning rate: 0.002 Mask loss: 0.12718 RPN box loss: 0.02369 RPN score loss: 0.00571 RPN total loss: 0.02941 Total loss: 0.91687 timestamp: 1654959702.302767 iteration: 58900 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07273 FastRCNN class loss: 0.07725 FastRCNN total loss: 0.14999 L1 loss: 0.0000e+00 L2 loss: 0.59612 Learning rate: 0.002 Mask loss: 0.10637 RPN box loss: 0.00498 RPN score loss: 0.0041 RPN total loss: 0.00908 Total loss: 0.86155 timestamp: 1654959705.5396752 iteration: 58905 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07618 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.15888 L1 loss: 0.0000e+00 L2 loss: 0.59611 Learning rate: 0.002 Mask loss: 0.12707 RPN box loss: 0.01315 RPN score loss: 0.00672 RPN total loss: 0.01986 Total loss: 0.90192 timestamp: 1654959708.7630286 iteration: 58910 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11494 FastRCNN class loss: 0.11445 FastRCNN total loss: 0.2294 L1 loss: 0.0000e+00 L2 loss: 0.5961 Learning rate: 0.002 Mask loss: 0.1528 RPN box loss: 0.03384 RPN score loss: 0.0198 RPN total loss: 0.05363 Total loss: 1.03193 timestamp: 1654959711.926265 iteration: 58915 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1766 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.25131 L1 loss: 0.0000e+00 L2 loss: 0.59609 Learning rate: 0.002 Mask loss: 0.14084 RPN box loss: 0.01721 RPN score loss: 0.00497 RPN total loss: 0.02218 Total loss: 1.01043 timestamp: 1654959715.1867173 iteration: 58920 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08132 FastRCNN class loss: 0.07274 FastRCNN total loss: 0.15406 L1 loss: 0.0000e+00 L2 loss: 0.59608 Learning rate: 0.002 Mask loss: 0.12734 RPN box loss: 0.02099 RPN score loss: 0.00414 RPN total loss: 0.02512 Total loss: 0.90262 timestamp: 1654959718.4317806 iteration: 58925 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05406 FastRCNN class loss: 0.04216 FastRCNN total loss: 0.09622 L1 loss: 0.0000e+00 L2 loss: 0.59607 Learning rate: 0.002 Mask loss: 0.09821 RPN box loss: 0.00437 RPN score loss: 0.00289 RPN total loss: 0.00727 Total loss: 0.79777 timestamp: 1654959721.6576858 iteration: 58930 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06252 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.12727 L1 loss: 0.0000e+00 L2 loss: 0.59607 Learning rate: 0.002 Mask loss: 0.09298 RPN box loss: 0.0135 RPN score loss: 0.00132 RPN total loss: 0.01483 Total loss: 0.83114 timestamp: 1654959724.9948976 iteration: 58935 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14957 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.24189 L1 loss: 0.0000e+00 L2 loss: 0.59606 Learning rate: 0.002 Mask loss: 0.19454 RPN box loss: 0.01742 RPN score loss: 0.01606 RPN total loss: 0.03349 Total loss: 1.06598 timestamp: 1654959728.1705647 iteration: 58940 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05561 FastRCNN class loss: 0.07181 FastRCNN total loss: 0.12742 L1 loss: 0.0000e+00 L2 loss: 0.59605 Learning rate: 0.002 Mask loss: 0.13082 RPN box loss: 0.0187 RPN score loss: 0.00352 RPN total loss: 0.02222 Total loss: 0.87651 timestamp: 1654959731.388892 iteration: 58945 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09691 FastRCNN class loss: 0.08129 FastRCNN total loss: 0.17821 L1 loss: 0.0000e+00 L2 loss: 0.59604 Learning rate: 0.002 Mask loss: 0.22163 RPN box loss: 0.01021 RPN score loss: 0.00484 RPN total loss: 0.01505 Total loss: 1.01093 timestamp: 1654959734.5716102 iteration: 58950 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.06624 FastRCNN total loss: 0.132 L1 loss: 0.0000e+00 L2 loss: 0.59603 Learning rate: 0.002 Mask loss: 0.11628 RPN box loss: 0.011 RPN score loss: 0.00911 RPN total loss: 0.02011 Total loss: 0.86443 timestamp: 1654959737.791171 iteration: 58955 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0891 FastRCNN class loss: 0.06517 FastRCNN total loss: 0.15428 L1 loss: 0.0000e+00 L2 loss: 0.59603 Learning rate: 0.002 Mask loss: 0.1138 RPN box loss: 0.0089 RPN score loss: 0.00626 RPN total loss: 0.01516 Total loss: 0.87926 timestamp: 1654959740.989949 iteration: 58960 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12938 FastRCNN class loss: 0.10013 FastRCNN total loss: 0.22951 L1 loss: 0.0000e+00 L2 loss: 0.59602 Learning rate: 0.002 Mask loss: 0.11838 RPN box loss: 0.01422 RPN score loss: 0.00215 RPN total loss: 0.01637 Total loss: 0.96028 timestamp: 1654959744.127151 iteration: 58965 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13899 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.20472 L1 loss: 0.0000e+00 L2 loss: 0.59601 Learning rate: 0.002 Mask loss: 0.13182 RPN box loss: 0.02391 RPN score loss: 0.00217 RPN total loss: 0.02608 Total loss: 0.95863 timestamp: 1654959747.2512903 iteration: 58970 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.107 FastRCNN class loss: 0.05695 FastRCNN total loss: 0.16394 L1 loss: 0.0000e+00 L2 loss: 0.596 Learning rate: 0.002 Mask loss: 0.12701 RPN box loss: 0.02276 RPN score loss: 0.00081 RPN total loss: 0.02357 Total loss: 0.91052 timestamp: 1654959750.543692 iteration: 58975 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11578 FastRCNN class loss: 0.1064 FastRCNN total loss: 0.22217 L1 loss: 0.0000e+00 L2 loss: 0.59599 Learning rate: 0.002 Mask loss: 0.12918 RPN box loss: 0.01193 RPN score loss: 0.00143 RPN total loss: 0.01337 Total loss: 0.96071 timestamp: 1654959753.7009377 iteration: 58980 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07471 FastRCNN class loss: 0.04254 FastRCNN total loss: 0.11725 L1 loss: 0.0000e+00 L2 loss: 0.59599 Learning rate: 0.002 Mask loss: 0.0866 RPN box loss: 0.00942 RPN score loss: 0.00267 RPN total loss: 0.01209 Total loss: 0.81193 timestamp: 1654959756.8602405 iteration: 58985 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0817 FastRCNN class loss: 0.05031 FastRCNN total loss: 0.13201 L1 loss: 0.0000e+00 L2 loss: 0.59598 Learning rate: 0.002 Mask loss: 0.08749 RPN box loss: 0.01899 RPN score loss: 0.00147 RPN total loss: 0.02046 Total loss: 0.83593 timestamp: 1654959760.0551739 iteration: 58990 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09046 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.16103 L1 loss: 0.0000e+00 L2 loss: 0.59597 Learning rate: 0.002 Mask loss: 0.14401 RPN box loss: 0.00778 RPN score loss: 0.00547 RPN total loss: 0.01326 Total loss: 0.91426 timestamp: 1654959763.2704866 iteration: 58995 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06939 FastRCNN class loss: 0.06599 FastRCNN total loss: 0.13538 L1 loss: 0.0000e+00 L2 loss: 0.59597 Learning rate: 0.002 Mask loss: 0.10624 RPN box loss: 0.00997 RPN score loss: 0.01314 RPN total loss: 0.02311 Total loss: 0.8607 timestamp: 1654959766.4904096 iteration: 59000 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07265 FastRCNN class loss: 0.04049 FastRCNN total loss: 0.11314 L1 loss: 0.0000e+00 L2 loss: 0.59596 Learning rate: 0.002 Mask loss: 0.09573 RPN box loss: 0.00307 RPN score loss: 0.00125 RPN total loss: 0.00432 Total loss: 0.80916 timestamp: 1654959769.718793 iteration: 59005 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13816 FastRCNN class loss: 0.08526 FastRCNN total loss: 0.22342 L1 loss: 0.0000e+00 L2 loss: 0.59595 Learning rate: 0.002 Mask loss: 0.1566 RPN box loss: 0.00897 RPN score loss: 0.01127 RPN total loss: 0.02025 Total loss: 0.99622 timestamp: 1654959772.9282033 iteration: 59010 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.08533 FastRCNN total loss: 0.21163 L1 loss: 0.0000e+00 L2 loss: 0.59594 Learning rate: 0.002 Mask loss: 0.10603 RPN box loss: 0.01456 RPN score loss: 0.00304 RPN total loss: 0.0176 Total loss: 0.9312 timestamp: 1654959776.0684328 iteration: 59015 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06325 FastRCNN class loss: 0.06489 FastRCNN total loss: 0.12814 L1 loss: 0.0000e+00 L2 loss: 0.59594 Learning rate: 0.002 Mask loss: 0.14268 RPN box loss: 0.00911 RPN score loss: 0.00462 RPN total loss: 0.01373 Total loss: 0.88049 timestamp: 1654959779.2763176 iteration: 59020 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08166 FastRCNN class loss: 0.05122 FastRCNN total loss: 0.13288 L1 loss: 0.0000e+00 L2 loss: 0.59593 Learning rate: 0.002 Mask loss: 0.12916 RPN box loss: 0.01417 RPN score loss: 0.00281 RPN total loss: 0.01698 Total loss: 0.87495 timestamp: 1654959782.4813836 iteration: 59025 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09997 FastRCNN class loss: 0.0859 FastRCNN total loss: 0.18587 L1 loss: 0.0000e+00 L2 loss: 0.59592 Learning rate: 0.002 Mask loss: 0.12149 RPN box loss: 0.00989 RPN score loss: 0.0069 RPN total loss: 0.01679 Total loss: 0.92007 timestamp: 1654959785.6770115 iteration: 59030 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04861 FastRCNN class loss: 0.03909 FastRCNN total loss: 0.0877 L1 loss: 0.0000e+00 L2 loss: 0.59591 Learning rate: 0.002 Mask loss: 0.10826 RPN box loss: 0.01095 RPN score loss: 0.00484 RPN total loss: 0.01579 Total loss: 0.80766 timestamp: 1654959788.817694 iteration: 59035 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1785 FastRCNN class loss: 0.16213 FastRCNN total loss: 0.34063 L1 loss: 0.0000e+00 L2 loss: 0.5959 Learning rate: 0.002 Mask loss: 0.22181 RPN box loss: 0.02169 RPN score loss: 0.00809 RPN total loss: 0.02978 Total loss: 1.18811 timestamp: 1654959792.0593095 iteration: 59040 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13713 FastRCNN class loss: 0.13973 FastRCNN total loss: 0.27686 L1 loss: 0.0000e+00 L2 loss: 0.59589 Learning rate: 0.002 Mask loss: 0.16424 RPN box loss: 0.01035 RPN score loss: 0.00392 RPN total loss: 0.01428 Total loss: 1.05127 timestamp: 1654959795.278438 iteration: 59045 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16578 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.23749 L1 loss: 0.0000e+00 L2 loss: 0.59588 Learning rate: 0.002 Mask loss: 0.16693 RPN box loss: 0.02055 RPN score loss: 0.00603 RPN total loss: 0.02658 Total loss: 1.0269 timestamp: 1654959798.4822578 iteration: 59050 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08662 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.17066 L1 loss: 0.0000e+00 L2 loss: 0.59588 Learning rate: 0.002 Mask loss: 0.17922 RPN box loss: 0.01426 RPN score loss: 0.00425 RPN total loss: 0.0185 Total loss: 0.96427 timestamp: 1654959801.6343803 iteration: 59055 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07484 FastRCNN class loss: 0.09821 FastRCNN total loss: 0.17306 L1 loss: 0.0000e+00 L2 loss: 0.59587 Learning rate: 0.002 Mask loss: 0.12672 RPN box loss: 0.00934 RPN score loss: 0.00392 RPN total loss: 0.01326 Total loss: 0.90891 timestamp: 1654959804.8134434 iteration: 59060 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09912 FastRCNN class loss: 0.11368 FastRCNN total loss: 0.2128 L1 loss: 0.0000e+00 L2 loss: 0.59586 Learning rate: 0.002 Mask loss: 0.11878 RPN box loss: 0.01727 RPN score loss: 0.00909 RPN total loss: 0.02636 Total loss: 0.9538 timestamp: 1654959808.063424 iteration: 59065 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11325 FastRCNN class loss: 0.06906 FastRCNN total loss: 0.18231 L1 loss: 0.0000e+00 L2 loss: 0.59585 Learning rate: 0.002 Mask loss: 0.11282 RPN box loss: 0.0328 RPN score loss: 0.00444 RPN total loss: 0.03724 Total loss: 0.92821 timestamp: 1654959811.1987085 iteration: 59070 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.13694 L1 loss: 0.0000e+00 L2 loss: 0.59584 Learning rate: 0.002 Mask loss: 0.11691 RPN box loss: 0.00663 RPN score loss: 0.00146 RPN total loss: 0.00809 Total loss: 0.85779 timestamp: 1654959814.4379594 iteration: 59075 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10285 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.17009 L1 loss: 0.0000e+00 L2 loss: 0.59584 Learning rate: 0.002 Mask loss: 0.13169 RPN box loss: 0.01366 RPN score loss: 0.00401 RPN total loss: 0.01767 Total loss: 0.91529 timestamp: 1654959817.6046445 iteration: 59080 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07708 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.13654 L1 loss: 0.0000e+00 L2 loss: 0.59583 Learning rate: 0.002 Mask loss: 0.11323 RPN box loss: 0.00588 RPN score loss: 0.01131 RPN total loss: 0.01719 Total loss: 0.86278 timestamp: 1654959820.7783437 iteration: 59085 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13339 FastRCNN class loss: 0.04579 FastRCNN total loss: 0.17918 L1 loss: 0.0000e+00 L2 loss: 0.59582 Learning rate: 0.002 Mask loss: 0.12655 RPN box loss: 0.02996 RPN score loss: 0.00497 RPN total loss: 0.03493 Total loss: 0.93649 timestamp: 1654959823.9836798 iteration: 59090 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07153 FastRCNN class loss: 0.04482 FastRCNN total loss: 0.11634 L1 loss: 0.0000e+00 L2 loss: 0.59582 Learning rate: 0.002 Mask loss: 0.11659 RPN box loss: 0.00873 RPN score loss: 0.00287 RPN total loss: 0.0116 Total loss: 0.84035 timestamp: 1654959827.1521966 iteration: 59095 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07772 FastRCNN class loss: 0.0726 FastRCNN total loss: 0.15032 L1 loss: 0.0000e+00 L2 loss: 0.59581 Learning rate: 0.002 Mask loss: 0.08153 RPN box loss: 0.00565 RPN score loss: 0.00139 RPN total loss: 0.00704 Total loss: 0.8347 timestamp: 1654959830.3375354 iteration: 59100 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06499 FastRCNN class loss: 0.06397 FastRCNN total loss: 0.12896 L1 loss: 0.0000e+00 L2 loss: 0.5958 Learning rate: 0.002 Mask loss: 0.09552 RPN box loss: 0.00549 RPN score loss: 0.00354 RPN total loss: 0.00903 Total loss: 0.8293 timestamp: 1654959833.4969857 iteration: 59105 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12039 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.18873 L1 loss: 0.0000e+00 L2 loss: 0.59579 Learning rate: 0.002 Mask loss: 0.14993 RPN box loss: 0.04719 RPN score loss: 0.00507 RPN total loss: 0.05226 Total loss: 0.98671 timestamp: 1654959836.7305899 iteration: 59110 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09433 FastRCNN class loss: 0.10572 FastRCNN total loss: 0.20005 L1 loss: 0.0000e+00 L2 loss: 0.59579 Learning rate: 0.002 Mask loss: 0.13921 RPN box loss: 0.02977 RPN score loss: 0.0124 RPN total loss: 0.04217 Total loss: 0.97721 timestamp: 1654959839.9644392 iteration: 59115 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09587 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.16714 L1 loss: 0.0000e+00 L2 loss: 0.59578 Learning rate: 0.002 Mask loss: 0.12182 RPN box loss: 0.02144 RPN score loss: 0.00524 RPN total loss: 0.02668 Total loss: 0.91141 timestamp: 1654959843.1300647 iteration: 59120 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08956 FastRCNN class loss: 0.0532 FastRCNN total loss: 0.14276 L1 loss: 0.0000e+00 L2 loss: 0.59577 Learning rate: 0.002 Mask loss: 0.10826 RPN box loss: 0.00519 RPN score loss: 0.00132 RPN total loss: 0.00651 Total loss: 0.8533 timestamp: 1654959846.3255596 iteration: 59125 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.03797 FastRCNN total loss: 0.11721 L1 loss: 0.0000e+00 L2 loss: 0.59575 Learning rate: 0.002 Mask loss: 0.1006 RPN box loss: 0.01218 RPN score loss: 0.00213 RPN total loss: 0.01431 Total loss: 0.82788 timestamp: 1654959849.4941652 iteration: 59130 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09233 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.17545 L1 loss: 0.0000e+00 L2 loss: 0.59575 Learning rate: 0.002 Mask loss: 0.1791 RPN box loss: 0.00923 RPN score loss: 0.01266 RPN total loss: 0.02189 Total loss: 0.97218 timestamp: 1654959852.7492058 iteration: 59135 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07286 FastRCNN class loss: 0.0707 FastRCNN total loss: 0.14356 L1 loss: 0.0000e+00 L2 loss: 0.59574 Learning rate: 0.002 Mask loss: 0.13849 RPN box loss: 0.01598 RPN score loss: 0.00451 RPN total loss: 0.02048 Total loss: 0.89828 timestamp: 1654959856.0004454 iteration: 59140 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11556 FastRCNN class loss: 0.07945 FastRCNN total loss: 0.19501 L1 loss: 0.0000e+00 L2 loss: 0.59573 Learning rate: 0.002 Mask loss: 0.1131 RPN box loss: 0.01236 RPN score loss: 0.0011 RPN total loss: 0.01346 Total loss: 0.91731 timestamp: 1654959859.2397597 iteration: 59145 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10542 FastRCNN class loss: 0.05872 FastRCNN total loss: 0.16414 L1 loss: 0.0000e+00 L2 loss: 0.59573 Learning rate: 0.002 Mask loss: 0.17523 RPN box loss: 0.04412 RPN score loss: 0.00211 RPN total loss: 0.04623 Total loss: 0.98132 timestamp: 1654959862.4233606 iteration: 59150 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09761 FastRCNN class loss: 0.06748 FastRCNN total loss: 0.16509 L1 loss: 0.0000e+00 L2 loss: 0.59572 Learning rate: 0.002 Mask loss: 0.16929 RPN box loss: 0.00703 RPN score loss: 0.00227 RPN total loss: 0.0093 Total loss: 0.9394 timestamp: 1654959865.6029334 iteration: 59155 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0953 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.16044 L1 loss: 0.0000e+00 L2 loss: 0.59571 Learning rate: 0.002 Mask loss: 0.12412 RPN box loss: 0.00636 RPN score loss: 0.00326 RPN total loss: 0.00962 Total loss: 0.88989 timestamp: 1654959868.862003 iteration: 59160 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0824 FastRCNN class loss: 0.05758 FastRCNN total loss: 0.13999 L1 loss: 0.0000e+00 L2 loss: 0.5957 Learning rate: 0.002 Mask loss: 0.1431 RPN box loss: 0.00812 RPN score loss: 0.00302 RPN total loss: 0.01113 Total loss: 0.88992 timestamp: 1654959872.1026309 iteration: 59165 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09646 FastRCNN class loss: 0.06176 FastRCNN total loss: 0.15821 L1 loss: 0.0000e+00 L2 loss: 0.59569 Learning rate: 0.002 Mask loss: 0.12487 RPN box loss: 0.01123 RPN score loss: 0.01508 RPN total loss: 0.02631 Total loss: 0.90508 timestamp: 1654959875.357588 iteration: 59170 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05072 FastRCNN class loss: 0.04266 FastRCNN total loss: 0.09338 L1 loss: 0.0000e+00 L2 loss: 0.59569 Learning rate: 0.002 Mask loss: 0.06769 RPN box loss: 0.00341 RPN score loss: 0.00095 RPN total loss: 0.00436 Total loss: 0.7611 timestamp: 1654959878.566612 iteration: 59175 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06104 FastRCNN class loss: 0.06264 FastRCNN total loss: 0.12368 L1 loss: 0.0000e+00 L2 loss: 0.59568 Learning rate: 0.002 Mask loss: 0.07509 RPN box loss: 0.01181 RPN score loss: 0.0076 RPN total loss: 0.0194 Total loss: 0.81384 timestamp: 1654959881.753642 iteration: 59180 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08728 FastRCNN class loss: 0.07773 FastRCNN total loss: 0.16501 L1 loss: 0.0000e+00 L2 loss: 0.59567 Learning rate: 0.002 Mask loss: 0.09317 RPN box loss: 0.00793 RPN score loss: 0.00237 RPN total loss: 0.0103 Total loss: 0.86415 timestamp: 1654959884.9555504 iteration: 59185 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10348 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.1746 L1 loss: 0.0000e+00 L2 loss: 0.59566 Learning rate: 0.002 Mask loss: 0.15709 RPN box loss: 0.02902 RPN score loss: 0.0054 RPN total loss: 0.03442 Total loss: 0.96177 timestamp: 1654959888.0798318 iteration: 59190 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07513 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.13488 L1 loss: 0.0000e+00 L2 loss: 0.59565 Learning rate: 0.002 Mask loss: 0.12621 RPN box loss: 0.0101 RPN score loss: 0.00384 RPN total loss: 0.01394 Total loss: 0.87067 timestamp: 1654959891.2933362 iteration: 59195 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06013 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.12211 L1 loss: 0.0000e+00 L2 loss: 0.59564 Learning rate: 0.002 Mask loss: 0.12593 RPN box loss: 0.01702 RPN score loss: 0.00594 RPN total loss: 0.02296 Total loss: 0.86664 timestamp: 1654959894.4681182 iteration: 59200 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12769 FastRCNN class loss: 0.15237 FastRCNN total loss: 0.28006 L1 loss: 0.0000e+00 L2 loss: 0.59563 Learning rate: 0.002 Mask loss: 0.10574 RPN box loss: 0.0314 RPN score loss: 0.00813 RPN total loss: 0.03953 Total loss: 1.02096 timestamp: 1654959897.6039917 iteration: 59205 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09158 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 0.59563 Learning rate: 0.002 Mask loss: 0.13609 RPN box loss: 0.01013 RPN score loss: 0.00374 RPN total loss: 0.01387 Total loss: 0.89805 timestamp: 1654959900.8416348 iteration: 59210 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12487 FastRCNN class loss: 0.04341 FastRCNN total loss: 0.16828 L1 loss: 0.0000e+00 L2 loss: 0.59562 Learning rate: 0.002 Mask loss: 0.07749 RPN box loss: 0.00614 RPN score loss: 0.00929 RPN total loss: 0.01542 Total loss: 0.85681 timestamp: 1654959904.0240128 iteration: 59215 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09189 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.16431 L1 loss: 0.0000e+00 L2 loss: 0.59561 Learning rate: 0.002 Mask loss: 0.10212 RPN box loss: 0.00587 RPN score loss: 0.00099 RPN total loss: 0.00686 Total loss: 0.8689 timestamp: 1654959907.251945 iteration: 59220 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1319 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.18667 L1 loss: 0.0000e+00 L2 loss: 0.5956 Learning rate: 0.002 Mask loss: 0.1313 RPN box loss: 0.01006 RPN score loss: 0.00216 RPN total loss: 0.01222 Total loss: 0.9258 timestamp: 1654959910.4176202 iteration: 59225 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07367 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.14027 L1 loss: 0.0000e+00 L2 loss: 0.59559 Learning rate: 0.002 Mask loss: 0.12921 RPN box loss: 0.00654 RPN score loss: 0.00047 RPN total loss: 0.007 Total loss: 0.87207 timestamp: 1654959913.705804 iteration: 59230 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07331 FastRCNN class loss: 0.06742 FastRCNN total loss: 0.14074 L1 loss: 0.0000e+00 L2 loss: 0.59558 Learning rate: 0.002 Mask loss: 0.08778 RPN box loss: 0.01089 RPN score loss: 0.00439 RPN total loss: 0.01528 Total loss: 0.83938 timestamp: 1654959916.908115 iteration: 59235 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0831 FastRCNN class loss: 0.04053 FastRCNN total loss: 0.12363 L1 loss: 0.0000e+00 L2 loss: 0.59557 Learning rate: 0.002 Mask loss: 0.10744 RPN box loss: 0.00367 RPN score loss: 0.00395 RPN total loss: 0.00762 Total loss: 0.83426 timestamp: 1654959920.0986574 iteration: 59240 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.11508 FastRCNN total loss: 0.20204 L1 loss: 0.0000e+00 L2 loss: 0.59556 Learning rate: 0.002 Mask loss: 0.18692 RPN box loss: 0.01488 RPN score loss: 0.03212 RPN total loss: 0.047 Total loss: 1.03152 timestamp: 1654959923.3028479 iteration: 59245 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11861 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.1939 L1 loss: 0.0000e+00 L2 loss: 0.59555 Learning rate: 0.002 Mask loss: 0.15324 RPN box loss: 0.02153 RPN score loss: 0.00936 RPN total loss: 0.03088 Total loss: 0.97358 timestamp: 1654959926.5285764 iteration: 59250 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.09731 FastRCNN total loss: 0.19875 L1 loss: 0.0000e+00 L2 loss: 0.59554 Learning rate: 0.002 Mask loss: 0.14692 RPN box loss: 0.01307 RPN score loss: 0.00708 RPN total loss: 0.02015 Total loss: 0.96136 timestamp: 1654959929.6909003 iteration: 59255 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07943 FastRCNN class loss: 0.04613 FastRCNN total loss: 0.12556 L1 loss: 0.0000e+00 L2 loss: 0.59553 Learning rate: 0.002 Mask loss: 0.16254 RPN box loss: 0.03451 RPN score loss: 0.00205 RPN total loss: 0.03657 Total loss: 0.9202 timestamp: 1654959932.8499625 iteration: 59260 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08856 FastRCNN class loss: 0.10209 FastRCNN total loss: 0.19064 L1 loss: 0.0000e+00 L2 loss: 0.59552 Learning rate: 0.002 Mask loss: 0.17373 RPN box loss: 0.00693 RPN score loss: 0.00876 RPN total loss: 0.01569 Total loss: 0.97559 timestamp: 1654959936.1086388 iteration: 59265 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09058 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.15126 L1 loss: 0.0000e+00 L2 loss: 0.59551 Learning rate: 0.002 Mask loss: 0.15356 RPN box loss: 0.01973 RPN score loss: 0.01181 RPN total loss: 0.03154 Total loss: 0.93188 timestamp: 1654959939.3780878 iteration: 59270 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09068 FastRCNN class loss: 0.08922 FastRCNN total loss: 0.1799 L1 loss: 0.0000e+00 L2 loss: 0.59551 Learning rate: 0.002 Mask loss: 0.1179 RPN box loss: 0.01743 RPN score loss: 0.00197 RPN total loss: 0.0194 Total loss: 0.91271 timestamp: 1654959942.6213999 iteration: 59275 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07462 FastRCNN class loss: 0.04876 FastRCNN total loss: 0.12337 L1 loss: 0.0000e+00 L2 loss: 0.5955 Learning rate: 0.002 Mask loss: 0.08266 RPN box loss: 0.00782 RPN score loss: 0.00179 RPN total loss: 0.00962 Total loss: 0.81114 timestamp: 1654959945.8468518 iteration: 59280 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09484 FastRCNN class loss: 0.05133 FastRCNN total loss: 0.14617 L1 loss: 0.0000e+00 L2 loss: 0.59549 Learning rate: 0.002 Mask loss: 0.12105 RPN box loss: 0.01087 RPN score loss: 0.00241 RPN total loss: 0.01328 Total loss: 0.87599 timestamp: 1654959949.0367966 iteration: 59285 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14738 FastRCNN class loss: 0.08808 FastRCNN total loss: 0.23546 L1 loss: 0.0000e+00 L2 loss: 0.59548 Learning rate: 0.002 Mask loss: 0.1299 RPN box loss: 0.01052 RPN score loss: 0.00854 RPN total loss: 0.01906 Total loss: 0.9799 timestamp: 1654959952.2634234 iteration: 59290 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12605 FastRCNN class loss: 0.05982 FastRCNN total loss: 0.18587 L1 loss: 0.0000e+00 L2 loss: 0.59548 Learning rate: 0.002 Mask loss: 0.10158 RPN box loss: 0.0046 RPN score loss: 0.00105 RPN total loss: 0.00565 Total loss: 0.88858 timestamp: 1654959955.4744735 iteration: 59295 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06783 FastRCNN class loss: 0.05303 FastRCNN total loss: 0.12086 L1 loss: 0.0000e+00 L2 loss: 0.59547 Learning rate: 0.002 Mask loss: 0.10179 RPN box loss: 0.01327 RPN score loss: 0.00547 RPN total loss: 0.01874 Total loss: 0.83686 timestamp: 1654959958.7091963 iteration: 59300 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.13153 FastRCNN total loss: 0.21019 L1 loss: 0.0000e+00 L2 loss: 0.59546 Learning rate: 0.002 Mask loss: 0.13196 RPN box loss: 0.01609 RPN score loss: 0.00491 RPN total loss: 0.021 Total loss: 0.95862 timestamp: 1654959961.9353187 iteration: 59305 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08486 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.1606 L1 loss: 0.0000e+00 L2 loss: 0.59546 Learning rate: 0.002 Mask loss: 0.11638 RPN box loss: 0.00837 RPN score loss: 0.0027 RPN total loss: 0.01107 Total loss: 0.88351 timestamp: 1654959965.1359718 iteration: 59310 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06218 FastRCNN class loss: 0.03901 FastRCNN total loss: 0.10119 L1 loss: 0.0000e+00 L2 loss: 0.59545 Learning rate: 0.002 Mask loss: 0.10373 RPN box loss: 0.06526 RPN score loss: 0.00379 RPN total loss: 0.06905 Total loss: 0.86942 timestamp: 1654959968.3842392 iteration: 59315 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12654 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.22344 L1 loss: 0.0000e+00 L2 loss: 0.59544 Learning rate: 0.002 Mask loss: 0.14464 RPN box loss: 0.03198 RPN score loss: 0.01019 RPN total loss: 0.04217 Total loss: 1.00569 timestamp: 1654959971.6306446 iteration: 59320 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10618 FastRCNN class loss: 0.04306 FastRCNN total loss: 0.14925 L1 loss: 0.0000e+00 L2 loss: 0.59543 Learning rate: 0.002 Mask loss: 0.12493 RPN box loss: 0.00762 RPN score loss: 0.00158 RPN total loss: 0.0092 Total loss: 0.87881 timestamp: 1654959974.8985705 iteration: 59325 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09316 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.17071 L1 loss: 0.0000e+00 L2 loss: 0.59543 Learning rate: 0.002 Mask loss: 0.20808 RPN box loss: 0.00776 RPN score loss: 0.00471 RPN total loss: 0.01247 Total loss: 0.98668 timestamp: 1654959978.07976 iteration: 59330 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08222 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.14612 L1 loss: 0.0000e+00 L2 loss: 0.59542 Learning rate: 0.002 Mask loss: 0.12143 RPN box loss: 0.01643 RPN score loss: 0.00555 RPN total loss: 0.02198 Total loss: 0.88495 timestamp: 1654959981.3228111 iteration: 59335 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10614 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.18617 L1 loss: 0.0000e+00 L2 loss: 0.59541 Learning rate: 0.002 Mask loss: 0.07768 RPN box loss: 0.00773 RPN score loss: 0.00334 RPN total loss: 0.01107 Total loss: 0.87034 timestamp: 1654959984.535581 iteration: 59340 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.05378 FastRCNN total loss: 0.1433 L1 loss: 0.0000e+00 L2 loss: 0.5954 Learning rate: 0.002 Mask loss: 0.15585 RPN box loss: 0.01979 RPN score loss: 0.00583 RPN total loss: 0.02562 Total loss: 0.92017 timestamp: 1654959987.6982977 iteration: 59345 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0996 FastRCNN class loss: 0.07633 FastRCNN total loss: 0.17593 L1 loss: 0.0000e+00 L2 loss: 0.59539 Learning rate: 0.002 Mask loss: 0.15843 RPN box loss: 0.0119 RPN score loss: 0.00643 RPN total loss: 0.01833 Total loss: 0.94809 timestamp: 1654959990.9149194 iteration: 59350 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14774 FastRCNN class loss: 0.05677 FastRCNN total loss: 0.20451 L1 loss: 0.0000e+00 L2 loss: 0.59539 Learning rate: 0.002 Mask loss: 0.11196 RPN box loss: 0.01996 RPN score loss: 0.00137 RPN total loss: 0.02133 Total loss: 0.93319 timestamp: 1654959994.0488167 iteration: 59355 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.09841 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 0.59538 Learning rate: 0.002 Mask loss: 0.14637 RPN box loss: 0.01745 RPN score loss: 0.00859 RPN total loss: 0.02605 Total loss: 0.95992 timestamp: 1654959997.2665815 iteration: 59360 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11844 FastRCNN class loss: 0.05238 FastRCNN total loss: 0.17082 L1 loss: 0.0000e+00 L2 loss: 0.59537 Learning rate: 0.002 Mask loss: 0.07976 RPN box loss: 0.00695 RPN score loss: 0.00607 RPN total loss: 0.01302 Total loss: 0.85897 timestamp: 1654960000.4718363 iteration: 59365 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13574 FastRCNN class loss: 0.10012 FastRCNN total loss: 0.23586 L1 loss: 0.0000e+00 L2 loss: 0.59536 Learning rate: 0.002 Mask loss: 0.13918 RPN box loss: 0.00804 RPN score loss: 0.00116 RPN total loss: 0.0092 Total loss: 0.97961 timestamp: 1654960003.65457 iteration: 59370 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08817 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.15006 L1 loss: 0.0000e+00 L2 loss: 0.59535 Learning rate: 0.002 Mask loss: 0.15699 RPN box loss: 0.01918 RPN score loss: 0.00604 RPN total loss: 0.02522 Total loss: 0.92762 timestamp: 1654960006.8921046 iteration: 59375 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08383 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.16518 L1 loss: 0.0000e+00 L2 loss: 0.59534 Learning rate: 0.002 Mask loss: 0.13667 RPN box loss: 0.01083 RPN score loss: 0.00764 RPN total loss: 0.01847 Total loss: 0.91567 timestamp: 1654960010.0545154 iteration: 59380 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13784 FastRCNN class loss: 0.07725 FastRCNN total loss: 0.21509 L1 loss: 0.0000e+00 L2 loss: 0.59534 Learning rate: 0.002 Mask loss: 0.12973 RPN box loss: 0.01174 RPN score loss: 0.01221 RPN total loss: 0.02395 Total loss: 0.96411 timestamp: 1654960013.3297973 iteration: 59385 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05847 FastRCNN class loss: 0.07918 FastRCNN total loss: 0.13764 L1 loss: 0.0000e+00 L2 loss: 0.59533 Learning rate: 0.002 Mask loss: 0.12178 RPN box loss: 0.00733 RPN score loss: 0.00277 RPN total loss: 0.0101 Total loss: 0.86486 timestamp: 1654960016.4815967 iteration: 59390 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07219 FastRCNN class loss: 0.05706 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 0.59532 Learning rate: 0.002 Mask loss: 0.11864 RPN box loss: 0.00856 RPN score loss: 0.0018 RPN total loss: 0.01036 Total loss: 0.85357 timestamp: 1654960019.675685 iteration: 59395 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.0952 FastRCNN total loss: 0.20309 L1 loss: 0.0000e+00 L2 loss: 0.59531 Learning rate: 0.002 Mask loss: 0.15188 RPN box loss: 0.02123 RPN score loss: 0.02398 RPN total loss: 0.04521 Total loss: 0.99549 timestamp: 1654960022.854444 iteration: 59400 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08906 FastRCNN class loss: 0.05186 FastRCNN total loss: 0.14091 L1 loss: 0.0000e+00 L2 loss: 0.5953 Learning rate: 0.002 Mask loss: 0.21042 RPN box loss: 0.02178 RPN score loss: 0.00256 RPN total loss: 0.02435 Total loss: 0.97099 timestamp: 1654960026.0554516 iteration: 59405 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05541 FastRCNN class loss: 0.05386 FastRCNN total loss: 0.10927 L1 loss: 0.0000e+00 L2 loss: 0.5953 Learning rate: 0.002 Mask loss: 0.12159 RPN box loss: 0.00971 RPN score loss: 0.0071 RPN total loss: 0.01682 Total loss: 0.84297 timestamp: 1654960029.1849291 iteration: 59410 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07922 FastRCNN class loss: 0.05758 FastRCNN total loss: 0.1368 L1 loss: 0.0000e+00 L2 loss: 0.59529 Learning rate: 0.002 Mask loss: 0.0998 RPN box loss: 0.01252 RPN score loss: 0.0017 RPN total loss: 0.01423 Total loss: 0.84611 timestamp: 1654960032.4214058 iteration: 59415 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.077 FastRCNN class loss: 0.04476 FastRCNN total loss: 0.12176 L1 loss: 0.0000e+00 L2 loss: 0.59528 Learning rate: 0.002 Mask loss: 0.15492 RPN box loss: 0.0081 RPN score loss: 0.00424 RPN total loss: 0.01235 Total loss: 0.88431 timestamp: 1654960035.5450203 iteration: 59420 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07124 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.13608 L1 loss: 0.0000e+00 L2 loss: 0.59527 Learning rate: 0.002 Mask loss: 0.13527 RPN box loss: 0.01249 RPN score loss: 0.01074 RPN total loss: 0.02323 Total loss: 0.88985 timestamp: 1654960038.645268 iteration: 59425 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06965 FastRCNN class loss: 0.05313 FastRCNN total loss: 0.12279 L1 loss: 0.0000e+00 L2 loss: 0.59526 Learning rate: 0.002 Mask loss: 0.14145 RPN box loss: 0.01906 RPN score loss: 0.01424 RPN total loss: 0.0333 Total loss: 0.89279 timestamp: 1654960041.9153686 iteration: 59430 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13584 FastRCNN class loss: 0.09054 FastRCNN total loss: 0.22639 L1 loss: 0.0000e+00 L2 loss: 0.59525 Learning rate: 0.002 Mask loss: 0.13938 RPN box loss: 0.02706 RPN score loss: 0.00399 RPN total loss: 0.03105 Total loss: 0.99207 timestamp: 1654960045.199788 iteration: 59435 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10866 FastRCNN class loss: 0.07781 FastRCNN total loss: 0.18647 L1 loss: 0.0000e+00 L2 loss: 0.59525 Learning rate: 0.002 Mask loss: 0.14536 RPN box loss: 0.01591 RPN score loss: 0.00506 RPN total loss: 0.02096 Total loss: 0.94805 timestamp: 1654960048.4248166 iteration: 59440 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07928 FastRCNN class loss: 0.05988 FastRCNN total loss: 0.13916 L1 loss: 0.0000e+00 L2 loss: 0.59524 Learning rate: 0.002 Mask loss: 0.12752 RPN box loss: 0.01695 RPN score loss: 0.00289 RPN total loss: 0.01984 Total loss: 0.88176 timestamp: 1654960051.5944817 iteration: 59445 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1316 FastRCNN class loss: 0.05381 FastRCNN total loss: 0.18541 L1 loss: 0.0000e+00 L2 loss: 0.59523 Learning rate: 0.002 Mask loss: 0.15785 RPN box loss: 0.02385 RPN score loss: 0.00513 RPN total loss: 0.02897 Total loss: 0.96745 timestamp: 1654960054.7871304 iteration: 59450 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05473 FastRCNN class loss: 0.04432 FastRCNN total loss: 0.09904 L1 loss: 0.0000e+00 L2 loss: 0.59522 Learning rate: 0.002 Mask loss: 0.08801 RPN box loss: 0.00733 RPN score loss: 0.0031 RPN total loss: 0.01043 Total loss: 0.7927 timestamp: 1654960058.009561 iteration: 59455 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10858 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.19193 L1 loss: 0.0000e+00 L2 loss: 0.59521 Learning rate: 0.002 Mask loss: 0.17688 RPN box loss: 0.01 RPN score loss: 0.01037 RPN total loss: 0.02038 Total loss: 0.98439 timestamp: 1654960061.2484946 iteration: 59460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09936 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.18162 L1 loss: 0.0000e+00 L2 loss: 0.5952 Learning rate: 0.002 Mask loss: 0.11989 RPN box loss: 0.02213 RPN score loss: 0.00616 RPN total loss: 0.02829 Total loss: 0.925 timestamp: 1654960064.5069838 iteration: 59465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08656 FastRCNN class loss: 0.06303 FastRCNN total loss: 0.14959 L1 loss: 0.0000e+00 L2 loss: 0.59519 Learning rate: 0.002 Mask loss: 0.12018 RPN box loss: 0.01522 RPN score loss: 0.01665 RPN total loss: 0.03187 Total loss: 0.89683 timestamp: 1654960067.6544805 iteration: 59470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08581 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.14313 L1 loss: 0.0000e+00 L2 loss: 0.59518 Learning rate: 0.002 Mask loss: 0.08877 RPN box loss: 0.01623 RPN score loss: 0.00134 RPN total loss: 0.01757 Total loss: 0.84466 timestamp: 1654960070.8528605 iteration: 59475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13804 FastRCNN class loss: 0.13032 FastRCNN total loss: 0.26835 L1 loss: 0.0000e+00 L2 loss: 0.59518 Learning rate: 0.002 Mask loss: 0.24555 RPN box loss: 0.03189 RPN score loss: 0.07063 RPN total loss: 0.10252 Total loss: 1.2116 timestamp: 1654960074.0331998 iteration: 59480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04199 FastRCNN class loss: 0.0485 FastRCNN total loss: 0.09048 L1 loss: 0.0000e+00 L2 loss: 0.59517 Learning rate: 0.002 Mask loss: 0.13578 RPN box loss: 0.00629 RPN score loss: 0.00418 RPN total loss: 0.01048 Total loss: 0.8319 timestamp: 1654960077.194025 iteration: 59485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11845 FastRCNN class loss: 0.06522 FastRCNN total loss: 0.18367 L1 loss: 0.0000e+00 L2 loss: 0.59516 Learning rate: 0.002 Mask loss: 0.17992 RPN box loss: 0.01306 RPN score loss: 0.00305 RPN total loss: 0.01611 Total loss: 0.97486 timestamp: 1654960080.402543 iteration: 59490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09287 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.14631 L1 loss: 0.0000e+00 L2 loss: 0.59515 Learning rate: 0.002 Mask loss: 0.14615 RPN box loss: 0.00537 RPN score loss: 0.00533 RPN total loss: 0.01071 Total loss: 0.89832 timestamp: 1654960083.5686872 iteration: 59495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12462 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.20085 L1 loss: 0.0000e+00 L2 loss: 0.59514 Learning rate: 0.002 Mask loss: 0.14748 RPN box loss: 0.01066 RPN score loss: 0.00411 RPN total loss: 0.01478 Total loss: 0.95824 timestamp: 1654960086.806383 iteration: 59500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11913 FastRCNN class loss: 0.10477 FastRCNN total loss: 0.22391 L1 loss: 0.0000e+00 L2 loss: 0.59513 Learning rate: 0.002 Mask loss: 0.15852 RPN box loss: 0.01291 RPN score loss: 0.00401 RPN total loss: 0.01691 Total loss: 0.99447 timestamp: 1654960090.0220933 iteration: 59505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10563 FastRCNN class loss: 0.0489 FastRCNN total loss: 0.15453 L1 loss: 0.0000e+00 L2 loss: 0.59512 Learning rate: 0.002 Mask loss: 0.09903 RPN box loss: 0.01336 RPN score loss: 0.00262 RPN total loss: 0.01598 Total loss: 0.86467 timestamp: 1654960093.2401488 iteration: 59510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12446 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.18435 L1 loss: 0.0000e+00 L2 loss: 0.59511 Learning rate: 0.002 Mask loss: 0.12114 RPN box loss: 0.01468 RPN score loss: 0.00515 RPN total loss: 0.01983 Total loss: 0.92043 timestamp: 1654960096.3979795 iteration: 59515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12012 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.20202 L1 loss: 0.0000e+00 L2 loss: 0.5951 Learning rate: 0.002 Mask loss: 0.14626 RPN box loss: 0.01406 RPN score loss: 0.00123 RPN total loss: 0.01529 Total loss: 0.95867 timestamp: 1654960099.631548 iteration: 59520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05852 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.13053 L1 loss: 0.0000e+00 L2 loss: 0.5951 Learning rate: 0.002 Mask loss: 0.12237 RPN box loss: 0.00622 RPN score loss: 0.00914 RPN total loss: 0.01536 Total loss: 0.86335 timestamp: 1654960102.8317113 iteration: 59525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06493 FastRCNN class loss: 0.06134 FastRCNN total loss: 0.12627 L1 loss: 0.0000e+00 L2 loss: 0.59509 Learning rate: 0.002 Mask loss: 0.1224 RPN box loss: 0.02547 RPN score loss: 0.005 RPN total loss: 0.03047 Total loss: 0.87422 timestamp: 1654960106.0508518 iteration: 59530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.124 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.18577 L1 loss: 0.0000e+00 L2 loss: 0.59508 Learning rate: 0.002 Mask loss: 0.11784 RPN box loss: 0.02505 RPN score loss: 0.00423 RPN total loss: 0.02928 Total loss: 0.92797 timestamp: 1654960109.2184935 iteration: 59535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09689 FastRCNN class loss: 0.08587 FastRCNN total loss: 0.18277 L1 loss: 0.0000e+00 L2 loss: 0.59508 Learning rate: 0.002 Mask loss: 0.14713 RPN box loss: 0.01258 RPN score loss: 0.00485 RPN total loss: 0.01742 Total loss: 0.9424 timestamp: 1654960112.4169908 iteration: 59540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08548 FastRCNN class loss: 0.08982 FastRCNN total loss: 0.1753 L1 loss: 0.0000e+00 L2 loss: 0.59507 Learning rate: 0.002 Mask loss: 0.12546 RPN box loss: 0.00965 RPN score loss: 0.00217 RPN total loss: 0.01183 Total loss: 0.90766 timestamp: 1654960115.629831 iteration: 59545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11154 FastRCNN class loss: 0.08246 FastRCNN total loss: 0.194 L1 loss: 0.0000e+00 L2 loss: 0.59506 Learning rate: 0.002 Mask loss: 0.15484 RPN box loss: 0.02566 RPN score loss: 0.00508 RPN total loss: 0.03074 Total loss: 0.97464 timestamp: 1654960118.8024032 iteration: 59550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12295 FastRCNN class loss: 0.0775 FastRCNN total loss: 0.20046 L1 loss: 0.0000e+00 L2 loss: 0.59505 Learning rate: 0.002 Mask loss: 0.1406 RPN box loss: 0.01027 RPN score loss: 0.00675 RPN total loss: 0.01702 Total loss: 0.95313 timestamp: 1654960121.9840317 iteration: 59555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09879 FastRCNN class loss: 0.06136 FastRCNN total loss: 0.16015 L1 loss: 0.0000e+00 L2 loss: 0.59504 Learning rate: 0.002 Mask loss: 0.11645 RPN box loss: 0.01651 RPN score loss: 0.00516 RPN total loss: 0.02168 Total loss: 0.89331 timestamp: 1654960125.2143779 iteration: 59560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09133 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.1555 L1 loss: 0.0000e+00 L2 loss: 0.59503 Learning rate: 0.002 Mask loss: 0.11556 RPN box loss: 0.01117 RPN score loss: 0.00272 RPN total loss: 0.0139 Total loss: 0.87998 timestamp: 1654960128.385732 iteration: 59565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07449 FastRCNN class loss: 0.04647 FastRCNN total loss: 0.12096 L1 loss: 0.0000e+00 L2 loss: 0.59502 Learning rate: 0.002 Mask loss: 0.09648 RPN box loss: 0.01115 RPN score loss: 0.00584 RPN total loss: 0.01699 Total loss: 0.82946 timestamp: 1654960131.5780942 iteration: 59570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08854 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.1652 L1 loss: 0.0000e+00 L2 loss: 0.59502 Learning rate: 0.002 Mask loss: 0.13601 RPN box loss: 0.02092 RPN score loss: 0.00294 RPN total loss: 0.02387 Total loss: 0.92009 timestamp: 1654960134.7749767 iteration: 59575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05665 FastRCNN class loss: 0.06684 FastRCNN total loss: 0.12348 L1 loss: 0.0000e+00 L2 loss: 0.59501 Learning rate: 0.002 Mask loss: 0.11937 RPN box loss: 0.01535 RPN score loss: 0.00694 RPN total loss: 0.02229 Total loss: 0.86016 timestamp: 1654960137.94708 iteration: 59580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12539 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.19129 L1 loss: 0.0000e+00 L2 loss: 0.595 Learning rate: 0.002 Mask loss: 0.11669 RPN box loss: 0.01782 RPN score loss: 0.00439 RPN total loss: 0.02221 Total loss: 0.92519 timestamp: 1654960141.1821659 iteration: 59585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13693 FastRCNN class loss: 0.06344 FastRCNN total loss: 0.20037 L1 loss: 0.0000e+00 L2 loss: 0.59499 Learning rate: 0.002 Mask loss: 0.14104 RPN box loss: 0.00787 RPN score loss: 0.00529 RPN total loss: 0.01316 Total loss: 0.94956 timestamp: 1654960144.3655546 iteration: 59590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13111 FastRCNN class loss: 0.0592 FastRCNN total loss: 0.19031 L1 loss: 0.0000e+00 L2 loss: 0.59498 Learning rate: 0.002 Mask loss: 0.10705 RPN box loss: 0.00816 RPN score loss: 0.00145 RPN total loss: 0.00961 Total loss: 0.90196 timestamp: 1654960147.5182443 iteration: 59595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16504 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.23501 L1 loss: 0.0000e+00 L2 loss: 0.59498 Learning rate: 0.002 Mask loss: 0.11457 RPN box loss: 0.00935 RPN score loss: 0.0025 RPN total loss: 0.01185 Total loss: 0.95641 timestamp: 1654960150.8073986 iteration: 59600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07471 FastRCNN class loss: 0.07819 FastRCNN total loss: 0.1529 L1 loss: 0.0000e+00 L2 loss: 0.59497 Learning rate: 0.002 Mask loss: 0.14262 RPN box loss: 0.00527 RPN score loss: 0.00235 RPN total loss: 0.00762 Total loss: 0.89811 timestamp: 1654960154.0141425 iteration: 59605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10292 FastRCNN class loss: 0.05308 FastRCNN total loss: 0.156 L1 loss: 0.0000e+00 L2 loss: 0.59496 Learning rate: 0.002 Mask loss: 0.13189 RPN box loss: 0.00823 RPN score loss: 0.00383 RPN total loss: 0.01206 Total loss: 0.8949 timestamp: 1654960157.2282507 iteration: 59610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.11402 FastRCNN total loss: 0.23897 L1 loss: 0.0000e+00 L2 loss: 0.59495 Learning rate: 0.002 Mask loss: 0.16209 RPN box loss: 0.03388 RPN score loss: 0.01143 RPN total loss: 0.04531 Total loss: 1.04132 timestamp: 1654960160.4924116 iteration: 59615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.04696 FastRCNN total loss: 0.12914 L1 loss: 0.0000e+00 L2 loss: 0.59494 Learning rate: 0.002 Mask loss: 0.09878 RPN box loss: 0.02001 RPN score loss: 0.00077 RPN total loss: 0.02079 Total loss: 0.84365 timestamp: 1654960163.7293062 iteration: 59620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06675 FastRCNN class loss: 0.02564 FastRCNN total loss: 0.09238 L1 loss: 0.0000e+00 L2 loss: 0.59493 Learning rate: 0.002 Mask loss: 0.08548 RPN box loss: 0.02003 RPN score loss: 0.0011 RPN total loss: 0.02113 Total loss: 0.79393 timestamp: 1654960166.8413253 iteration: 59625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07849 FastRCNN class loss: 0.04636 FastRCNN total loss: 0.12485 L1 loss: 0.0000e+00 L2 loss: 0.59492 Learning rate: 0.002 Mask loss: 0.12273 RPN box loss: 0.00731 RPN score loss: 0.002 RPN total loss: 0.00931 Total loss: 0.85181 timestamp: 1654960170.0826085 iteration: 59630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14215 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.22065 L1 loss: 0.0000e+00 L2 loss: 0.59492 Learning rate: 0.002 Mask loss: 0.15771 RPN box loss: 0.01308 RPN score loss: 0.00323 RPN total loss: 0.01631 Total loss: 0.98958 timestamp: 1654960173.289728 iteration: 59635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07845 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.1448 L1 loss: 0.0000e+00 L2 loss: 0.59491 Learning rate: 0.002 Mask loss: 0.12628 RPN box loss: 0.00862 RPN score loss: 0.00682 RPN total loss: 0.01545 Total loss: 0.88144 timestamp: 1654960176.522767 iteration: 59640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10584 FastRCNN class loss: 0.04531 FastRCNN total loss: 0.15116 L1 loss: 0.0000e+00 L2 loss: 0.5949 Learning rate: 0.002 Mask loss: 0.13637 RPN box loss: 0.01824 RPN score loss: 0.0025 RPN total loss: 0.02074 Total loss: 0.90317 timestamp: 1654960179.6938949 iteration: 59645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12028 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.19721 L1 loss: 0.0000e+00 L2 loss: 0.59489 Learning rate: 0.002 Mask loss: 0.11175 RPN box loss: 0.01748 RPN score loss: 0.00454 RPN total loss: 0.02202 Total loss: 0.92588 timestamp: 1654960182.9473906 iteration: 59650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.05002 FastRCNN total loss: 0.12657 L1 loss: 0.0000e+00 L2 loss: 0.59488 Learning rate: 0.002 Mask loss: 0.13519 RPN box loss: 0.01585 RPN score loss: 0.00643 RPN total loss: 0.02228 Total loss: 0.87892 timestamp: 1654960186.1462762 iteration: 59655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08047 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.14397 L1 loss: 0.0000e+00 L2 loss: 0.59487 Learning rate: 0.002 Mask loss: 0.13144 RPN box loss: 0.01737 RPN score loss: 0.00191 RPN total loss: 0.01928 Total loss: 0.88956 timestamp: 1654960189.3400235 iteration: 59660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08274 FastRCNN class loss: 0.13303 FastRCNN total loss: 0.21577 L1 loss: 0.0000e+00 L2 loss: 0.59486 Learning rate: 0.002 Mask loss: 0.13794 RPN box loss: 0.02077 RPN score loss: 0.00345 RPN total loss: 0.02421 Total loss: 0.97278 timestamp: 1654960192.555517 iteration: 59665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09521 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.18288 L1 loss: 0.0000e+00 L2 loss: 0.59485 Learning rate: 0.002 Mask loss: 0.15862 RPN box loss: 0.01033 RPN score loss: 0.00233 RPN total loss: 0.01266 Total loss: 0.94901 timestamp: 1654960195.6866558 iteration: 59670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08396 FastRCNN class loss: 0.05121 FastRCNN total loss: 0.13517 L1 loss: 0.0000e+00 L2 loss: 0.59485 Learning rate: 0.002 Mask loss: 0.09671 RPN box loss: 0.01141 RPN score loss: 0.00336 RPN total loss: 0.01477 Total loss: 0.8415 timestamp: 1654960198.8894875 iteration: 59675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08936 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.14843 L1 loss: 0.0000e+00 L2 loss: 0.59484 Learning rate: 0.002 Mask loss: 0.16774 RPN box loss: 0.00671 RPN score loss: 0.00195 RPN total loss: 0.00867 Total loss: 0.91968 timestamp: 1654960202.1065247 iteration: 59680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11939 FastRCNN class loss: 0.03832 FastRCNN total loss: 0.1577 L1 loss: 0.0000e+00 L2 loss: 0.59483 Learning rate: 0.002 Mask loss: 0.11892 RPN box loss: 0.00596 RPN score loss: 0.00151 RPN total loss: 0.00747 Total loss: 0.87892 timestamp: 1654960205.2764623 iteration: 59685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.045 FastRCNN total loss: 0.1112 L1 loss: 0.0000e+00 L2 loss: 0.59482 Learning rate: 0.002 Mask loss: 0.13914 RPN box loss: 0.02075 RPN score loss: 0.00229 RPN total loss: 0.02304 Total loss: 0.8682 timestamp: 1654960208.3889885 iteration: 59690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04856 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.10141 L1 loss: 0.0000e+00 L2 loss: 0.59481 Learning rate: 0.002 Mask loss: 0.11288 RPN box loss: 0.00801 RPN score loss: 0.00791 RPN total loss: 0.01592 Total loss: 0.82501 timestamp: 1654960211.502639 iteration: 59695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0988 FastRCNN class loss: 0.04837 FastRCNN total loss: 0.14717 L1 loss: 0.0000e+00 L2 loss: 0.5948 Learning rate: 0.002 Mask loss: 0.09298 RPN box loss: 0.00531 RPN score loss: 0.00187 RPN total loss: 0.00719 Total loss: 0.84214 timestamp: 1654960214.714398 iteration: 59700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14433 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.23406 L1 loss: 0.0000e+00 L2 loss: 0.5948 Learning rate: 0.002 Mask loss: 0.0663 RPN box loss: 0.00757 RPN score loss: 0.00219 RPN total loss: 0.00976 Total loss: 0.90492 timestamp: 1654960217.9423532 iteration: 59705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06822 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.13385 L1 loss: 0.0000e+00 L2 loss: 0.59479 Learning rate: 0.002 Mask loss: 0.10716 RPN box loss: 0.0069 RPN score loss: 0.0016 RPN total loss: 0.0085 Total loss: 0.8443 timestamp: 1654960221.1484919 iteration: 59710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1313 FastRCNN class loss: 0.07035 FastRCNN total loss: 0.20164 L1 loss: 0.0000e+00 L2 loss: 0.59478 Learning rate: 0.002 Mask loss: 0.09449 RPN box loss: 0.01091 RPN score loss: 0.00262 RPN total loss: 0.01353 Total loss: 0.90444 timestamp: 1654960224.373336 iteration: 59715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.07919 FastRCNN total loss: 0.15866 L1 loss: 0.0000e+00 L2 loss: 0.59477 Learning rate: 0.002 Mask loss: 0.14504 RPN box loss: 0.0138 RPN score loss: 0.00938 RPN total loss: 0.02318 Total loss: 0.92165 timestamp: 1654960227.6069076 iteration: 59720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11753 FastRCNN class loss: 0.08633 FastRCNN total loss: 0.20386 L1 loss: 0.0000e+00 L2 loss: 0.59476 Learning rate: 0.002 Mask loss: 0.13883 RPN box loss: 0.01345 RPN score loss: 0.00552 RPN total loss: 0.01896 Total loss: 0.9564 timestamp: 1654960230.7614987 iteration: 59725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11679 FastRCNN class loss: 0.06022 FastRCNN total loss: 0.17701 L1 loss: 0.0000e+00 L2 loss: 0.59475 Learning rate: 0.002 Mask loss: 0.14208 RPN box loss: 0.01738 RPN score loss: 0.00401 RPN total loss: 0.02139 Total loss: 0.93522 timestamp: 1654960233.9296474 iteration: 59730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04251 FastRCNN class loss: 0.03222 FastRCNN total loss: 0.07473 L1 loss: 0.0000e+00 L2 loss: 0.59474 Learning rate: 0.002 Mask loss: 0.09379 RPN box loss: 0.00286 RPN score loss: 0.00202 RPN total loss: 0.00488 Total loss: 0.76813 timestamp: 1654960237.107319 iteration: 59735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04216 FastRCNN class loss: 0.03299 FastRCNN total loss: 0.07515 L1 loss: 0.0000e+00 L2 loss: 0.59473 Learning rate: 0.002 Mask loss: 0.11395 RPN box loss: 0.0053 RPN score loss: 0.00273 RPN total loss: 0.00803 Total loss: 0.79186 timestamp: 1654960240.3221118 iteration: 59740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05943 FastRCNN class loss: 0.09746 FastRCNN total loss: 0.15689 L1 loss: 0.0000e+00 L2 loss: 0.59473 Learning rate: 0.002 Mask loss: 0.14592 RPN box loss: 0.04603 RPN score loss: 0.02417 RPN total loss: 0.0702 Total loss: 0.96774 timestamp: 1654960243.5045521 iteration: 59745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06933 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.12245 L1 loss: 0.0000e+00 L2 loss: 0.59473 Learning rate: 0.002 Mask loss: 0.17498 RPN box loss: 0.01942 RPN score loss: 0.00839 RPN total loss: 0.02781 Total loss: 0.91998 timestamp: 1654960246.6561334 iteration: 59750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08104 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.15279 L1 loss: 0.0000e+00 L2 loss: 0.59472 Learning rate: 0.002 Mask loss: 0.16554 RPN box loss: 0.02057 RPN score loss: 0.00755 RPN total loss: 0.02812 Total loss: 0.94116 timestamp: 1654960249.8103573 iteration: 59755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04407 FastRCNN class loss: 0.05899 FastRCNN total loss: 0.10306 L1 loss: 0.0000e+00 L2 loss: 0.59471 Learning rate: 0.002 Mask loss: 0.11109 RPN box loss: 0.01019 RPN score loss: 0.00276 RPN total loss: 0.01294 Total loss: 0.8218 timestamp: 1654960253.0156636 iteration: 59760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05872 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.12312 L1 loss: 0.0000e+00 L2 loss: 0.5947 Learning rate: 0.002 Mask loss: 0.10399 RPN box loss: 0.01214 RPN score loss: 0.00663 RPN total loss: 0.01877 Total loss: 0.84057 timestamp: 1654960256.2340703 iteration: 59765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07123 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.14853 L1 loss: 0.0000e+00 L2 loss: 0.59469 Learning rate: 0.002 Mask loss: 0.14524 RPN box loss: 0.01125 RPN score loss: 0.00496 RPN total loss: 0.01621 Total loss: 0.90467 timestamp: 1654960259.419627 iteration: 59770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12589 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.19153 L1 loss: 0.0000e+00 L2 loss: 0.59468 Learning rate: 0.002 Mask loss: 0.1277 RPN box loss: 0.01395 RPN score loss: 0.0022 RPN total loss: 0.01615 Total loss: 0.93007 timestamp: 1654960262.5805323 iteration: 59775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13443 FastRCNN class loss: 0.08488 FastRCNN total loss: 0.21932 L1 loss: 0.0000e+00 L2 loss: 0.59467 Learning rate: 0.002 Mask loss: 0.14775 RPN box loss: 0.02556 RPN score loss: 0.00327 RPN total loss: 0.02884 Total loss: 0.99058 timestamp: 1654960265.6831686 iteration: 59780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.11367 FastRCNN total loss: 0.19994 L1 loss: 0.0000e+00 L2 loss: 0.59467 Learning rate: 0.002 Mask loss: 0.12732 RPN box loss: 0.02027 RPN score loss: 0.0053 RPN total loss: 0.02556 Total loss: 0.94749 timestamp: 1654960268.853747 iteration: 59785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08096 FastRCNN class loss: 0.08059 FastRCNN total loss: 0.16155 L1 loss: 0.0000e+00 L2 loss: 0.59466 Learning rate: 0.002 Mask loss: 0.15135 RPN box loss: 0.03135 RPN score loss: 0.00442 RPN total loss: 0.03576 Total loss: 0.94332 timestamp: 1654960272.0917983 iteration: 59790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08425 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.14234 L1 loss: 0.0000e+00 L2 loss: 0.59465 Learning rate: 0.002 Mask loss: 0.12018 RPN box loss: 0.00451 RPN score loss: 0.00195 RPN total loss: 0.00645 Total loss: 0.86362 timestamp: 1654960275.3390872 iteration: 59795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1407 FastRCNN class loss: 0.15922 FastRCNN total loss: 0.29992 L1 loss: 0.0000e+00 L2 loss: 0.59464 Learning rate: 0.002 Mask loss: 0.20415 RPN box loss: 0.03767 RPN score loss: 0.00868 RPN total loss: 0.04636 Total loss: 1.14507 timestamp: 1654960278.5402908 iteration: 59800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07408 FastRCNN class loss: 0.07523 FastRCNN total loss: 0.14931 L1 loss: 0.0000e+00 L2 loss: 0.59463 Learning rate: 0.002 Mask loss: 0.09952 RPN box loss: 0.01612 RPN score loss: 0.00313 RPN total loss: 0.01924 Total loss: 0.8627 timestamp: 1654960281.6994195 iteration: 59805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.04142 FastRCNN total loss: 0.1243 L1 loss: 0.0000e+00 L2 loss: 0.59462 Learning rate: 0.002 Mask loss: 0.09365 RPN box loss: 0.00277 RPN score loss: 0.0018 RPN total loss: 0.00457 Total loss: 0.81714 timestamp: 1654960284.9210243 iteration: 59810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0643 FastRCNN class loss: 0.035 FastRCNN total loss: 0.0993 L1 loss: 0.0000e+00 L2 loss: 0.59461 Learning rate: 0.002 Mask loss: 0.09261 RPN box loss: 0.00644 RPN score loss: 0.00879 RPN total loss: 0.01523 Total loss: 0.80175 timestamp: 1654960288.188776 iteration: 59815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08535 FastRCNN class loss: 0.11084 FastRCNN total loss: 0.19619 L1 loss: 0.0000e+00 L2 loss: 0.59461 Learning rate: 0.002 Mask loss: 0.1237 RPN box loss: 0.01319 RPN score loss: 0.01146 RPN total loss: 0.02464 Total loss: 0.93914 timestamp: 1654960291.412904 iteration: 59820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.06617 FastRCNN total loss: 0.15629 L1 loss: 0.0000e+00 L2 loss: 0.5946 Learning rate: 0.002 Mask loss: 0.15549 RPN box loss: 0.0129 RPN score loss: 0.00305 RPN total loss: 0.01595 Total loss: 0.92233 timestamp: 1654960294.721877 iteration: 59825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1488 FastRCNN class loss: 0.08552 FastRCNN total loss: 0.23432 L1 loss: 0.0000e+00 L2 loss: 0.59459 Learning rate: 0.002 Mask loss: 0.14668 RPN box loss: 0.01026 RPN score loss: 0.00228 RPN total loss: 0.01254 Total loss: 0.98813 timestamp: 1654960298.0424678 iteration: 59830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05024 FastRCNN class loss: 0.0376 FastRCNN total loss: 0.08784 L1 loss: 0.0000e+00 L2 loss: 0.59458 Learning rate: 0.002 Mask loss: 0.12826 RPN box loss: 0.00438 RPN score loss: 0.00168 RPN total loss: 0.00606 Total loss: 0.81674 timestamp: 1654960301.1898105 iteration: 59835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16803 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.25259 L1 loss: 0.0000e+00 L2 loss: 0.59457 Learning rate: 0.002 Mask loss: 0.16986 RPN box loss: 0.01477 RPN score loss: 0.005 RPN total loss: 0.01977 Total loss: 1.03679 timestamp: 1654960304.3872857 iteration: 59840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07001 FastRCNN class loss: 0.05417 FastRCNN total loss: 0.12418 L1 loss: 0.0000e+00 L2 loss: 0.59457 Learning rate: 0.002 Mask loss: 0.13003 RPN box loss: 0.00657 RPN score loss: 0.00246 RPN total loss: 0.00904 Total loss: 0.85781 timestamp: 1654960307.561108 iteration: 59845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07492 FastRCNN class loss: 0.0599 FastRCNN total loss: 0.13482 L1 loss: 0.0000e+00 L2 loss: 0.59456 Learning rate: 0.002 Mask loss: 0.10725 RPN box loss: 0.01435 RPN score loss: 0.00883 RPN total loss: 0.02318 Total loss: 0.85981 timestamp: 1654960310.8067417 iteration: 59850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10244 FastRCNN class loss: 0.06586 FastRCNN total loss: 0.1683 L1 loss: 0.0000e+00 L2 loss: 0.59455 Learning rate: 0.002 Mask loss: 0.1429 RPN box loss: 0.03525 RPN score loss: 0.00597 RPN total loss: 0.04122 Total loss: 0.94697 timestamp: 1654960313.975587 iteration: 59855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1004 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.17074 L1 loss: 0.0000e+00 L2 loss: 0.59455 Learning rate: 0.002 Mask loss: 0.11734 RPN box loss: 0.00857 RPN score loss: 0.00178 RPN total loss: 0.01035 Total loss: 0.89297 timestamp: 1654960317.2422006 iteration: 59860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06259 FastRCNN class loss: 0.04423 FastRCNN total loss: 0.10682 L1 loss: 0.0000e+00 L2 loss: 0.59454 Learning rate: 0.002 Mask loss: 0.11787 RPN box loss: 0.00771 RPN score loss: 0.00133 RPN total loss: 0.00903 Total loss: 0.82827 timestamp: 1654960320.4677453 iteration: 59865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07543 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.14206 L1 loss: 0.0000e+00 L2 loss: 0.59453 Learning rate: 0.002 Mask loss: 0.15884 RPN box loss: 0.00767 RPN score loss: 0.00393 RPN total loss: 0.0116 Total loss: 0.90703 timestamp: 1654960323.6819425 iteration: 59870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08987 FastRCNN class loss: 0.0655 FastRCNN total loss: 0.15537 L1 loss: 0.0000e+00 L2 loss: 0.59452 Learning rate: 0.002 Mask loss: 0.12924 RPN box loss: 0.01131 RPN score loss: 0.00657 RPN total loss: 0.01788 Total loss: 0.89701 timestamp: 1654960326.8998797 iteration: 59875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10511 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.17108 L1 loss: 0.0000e+00 L2 loss: 0.59451 Learning rate: 0.002 Mask loss: 0.13973 RPN box loss: 0.00939 RPN score loss: 0.00508 RPN total loss: 0.01447 Total loss: 0.91979 timestamp: 1654960330.1637216 iteration: 59880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09879 FastRCNN class loss: 0.04696 FastRCNN total loss: 0.14575 L1 loss: 0.0000e+00 L2 loss: 0.5945 Learning rate: 0.002 Mask loss: 0.14131 RPN box loss: 0.00668 RPN score loss: 0.01484 RPN total loss: 0.02152 Total loss: 0.90309 timestamp: 1654960333.4080737 iteration: 59885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06851 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.13666 L1 loss: 0.0000e+00 L2 loss: 0.5945 Learning rate: 0.002 Mask loss: 0.12805 RPN box loss: 0.01076 RPN score loss: 0.0035 RPN total loss: 0.01426 Total loss: 0.87347 timestamp: 1654960336.670379 iteration: 59890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08684 FastRCNN class loss: 0.07892 FastRCNN total loss: 0.16576 L1 loss: 0.0000e+00 L2 loss: 0.59449 Learning rate: 0.002 Mask loss: 0.13428 RPN box loss: 0.01491 RPN score loss: 0.00499 RPN total loss: 0.0199 Total loss: 0.91443 timestamp: 1654960339.9160125 iteration: 59895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10083 FastRCNN class loss: 0.04687 FastRCNN total loss: 0.1477 L1 loss: 0.0000e+00 L2 loss: 0.59448 Learning rate: 0.002 Mask loss: 0.12441 RPN box loss: 0.0062 RPN score loss: 0.00099 RPN total loss: 0.00719 Total loss: 0.87378 timestamp: 1654960343.062873 iteration: 59900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07765 FastRCNN class loss: 0.07975 FastRCNN total loss: 0.1574 L1 loss: 0.0000e+00 L2 loss: 0.59447 Learning rate: 0.002 Mask loss: 0.11608 RPN box loss: 0.00788 RPN score loss: 0.00319 RPN total loss: 0.01107 Total loss: 0.87901 timestamp: 1654960346.266524 iteration: 59905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14675 FastRCNN class loss: 0.11294 FastRCNN total loss: 0.25969 L1 loss: 0.0000e+00 L2 loss: 0.59446 Learning rate: 0.002 Mask loss: 0.25695 RPN box loss: 0.01779 RPN score loss: 0.00665 RPN total loss: 0.02444 Total loss: 1.13554 timestamp: 1654960349.548456 iteration: 59910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10151 FastRCNN class loss: 0.06679 FastRCNN total loss: 0.1683 L1 loss: 0.0000e+00 L2 loss: 0.59445 Learning rate: 0.002 Mask loss: 0.14845 RPN box loss: 0.0091 RPN score loss: 0.0061 RPN total loss: 0.0152 Total loss: 0.9264 timestamp: 1654960352.7398329 iteration: 59915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09054 FastRCNN class loss: 0.05841 FastRCNN total loss: 0.14896 L1 loss: 0.0000e+00 L2 loss: 0.59444 Learning rate: 0.002 Mask loss: 0.16401 RPN box loss: 0.03031 RPN score loss: 0.01319 RPN total loss: 0.04351 Total loss: 0.95092 timestamp: 1654960355.8022072 iteration: 59920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06489 FastRCNN class loss: 0.0339 FastRCNN total loss: 0.09879 L1 loss: 0.0000e+00 L2 loss: 0.59443 Learning rate: 0.002 Mask loss: 0.08916 RPN box loss: 0.01108 RPN score loss: 0.00778 RPN total loss: 0.01886 Total loss: 0.80124 timestamp: 1654960359.0095954 iteration: 59925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14959 FastRCNN class loss: 0.10421 FastRCNN total loss: 0.2538 L1 loss: 0.0000e+00 L2 loss: 0.59442 Learning rate: 0.002 Mask loss: 0.22118 RPN box loss: 0.0167 RPN score loss: 0.00805 RPN total loss: 0.02475 Total loss: 1.09415 timestamp: 1654960362.2330163 iteration: 59930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12565 FastRCNN class loss: 0.0929 FastRCNN total loss: 0.21855 L1 loss: 0.0000e+00 L2 loss: 0.59441 Learning rate: 0.002 Mask loss: 0.1612 RPN box loss: 0.01179 RPN score loss: 0.00378 RPN total loss: 0.01557 Total loss: 0.98974 timestamp: 1654960365.488302 iteration: 59935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11312 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.17876 L1 loss: 0.0000e+00 L2 loss: 0.5944 Learning rate: 0.002 Mask loss: 0.13719 RPN box loss: 0.02126 RPN score loss: 0.00209 RPN total loss: 0.02334 Total loss: 0.9337 timestamp: 1654960368.6936398 iteration: 59940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08824 FastRCNN class loss: 0.0864 FastRCNN total loss: 0.17464 L1 loss: 0.0000e+00 L2 loss: 0.5944 Learning rate: 0.002 Mask loss: 0.16503 RPN box loss: 0.01322 RPN score loss: 0.00214 RPN total loss: 0.01536 Total loss: 0.94943 timestamp: 1654960371.8567977 iteration: 59945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06734 FastRCNN class loss: 0.0589 FastRCNN total loss: 0.12624 L1 loss: 0.0000e+00 L2 loss: 0.59439 Learning rate: 0.002 Mask loss: 0.1177 RPN box loss: 0.01054 RPN score loss: 0.00341 RPN total loss: 0.01395 Total loss: 0.85229 timestamp: 1654960375.0564532 iteration: 59950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1168 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.19849 L1 loss: 0.0000e+00 L2 loss: 0.59438 Learning rate: 0.002 Mask loss: 0.13793 RPN box loss: 0.01619 RPN score loss: 0.00247 RPN total loss: 0.01865 Total loss: 0.94945 timestamp: 1654960378.2888012 iteration: 59955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09598 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.15695 L1 loss: 0.0000e+00 L2 loss: 0.59438 Learning rate: 0.002 Mask loss: 0.15391 RPN box loss: 0.00487 RPN score loss: 0.00255 RPN total loss: 0.00742 Total loss: 0.91266 timestamp: 1654960381.3972692 iteration: 59960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10211 FastRCNN class loss: 0.05111 FastRCNN total loss: 0.15322 L1 loss: 0.0000e+00 L2 loss: 0.59437 Learning rate: 0.002 Mask loss: 0.11829 RPN box loss: 0.01254 RPN score loss: 0.00462 RPN total loss: 0.01715 Total loss: 0.88303 timestamp: 1654960384.6012752 iteration: 59965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06464 FastRCNN class loss: 0.04245 FastRCNN total loss: 0.10708 L1 loss: 0.0000e+00 L2 loss: 0.59436 Learning rate: 0.002 Mask loss: 0.09421 RPN box loss: 0.00496 RPN score loss: 0.00342 RPN total loss: 0.00838 Total loss: 0.80403 timestamp: 1654960387.8235552 iteration: 59970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.16898 L1 loss: 0.0000e+00 L2 loss: 0.59436 Learning rate: 0.002 Mask loss: 0.16107 RPN box loss: 0.01494 RPN score loss: 0.00203 RPN total loss: 0.01697 Total loss: 0.94138 timestamp: 1654960391.0352323 iteration: 59975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05298 FastRCNN class loss: 0.04407 FastRCNN total loss: 0.09705 L1 loss: 0.0000e+00 L2 loss: 0.59435 Learning rate: 0.002 Mask loss: 0.08593 RPN box loss: 0.00637 RPN score loss: 0.00111 RPN total loss: 0.00749 Total loss: 0.78482 timestamp: 1654960394.3090491 iteration: 59980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15674 FastRCNN class loss: 0.09655 FastRCNN total loss: 0.2533 L1 loss: 0.0000e+00 L2 loss: 0.59434 Learning rate: 0.002 Mask loss: 0.112 RPN box loss: 0.0182 RPN score loss: 0.00239 RPN total loss: 0.02058 Total loss: 0.98022 timestamp: 1654960397.541608 iteration: 59985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11846 FastRCNN class loss: 0.07143 FastRCNN total loss: 0.1899 L1 loss: 0.0000e+00 L2 loss: 0.59433 Learning rate: 0.002 Mask loss: 0.17991 RPN box loss: 0.0231 RPN score loss: 0.00879 RPN total loss: 0.03188 Total loss: 0.99602 timestamp: 1654960400.786919 iteration: 59990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11315 FastRCNN class loss: 0.08452 FastRCNN total loss: 0.19767 L1 loss: 0.0000e+00 L2 loss: 0.59432 Learning rate: 0.002 Mask loss: 0.08652 RPN box loss: 0.00446 RPN score loss: 0.00258 RPN total loss: 0.00703 Total loss: 0.88554 timestamp: 1654960404.0525389 iteration: 59995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09969 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.17316 L1 loss: 0.0000e+00 L2 loss: 0.59431 Learning rate: 0.002 Mask loss: 0.22125 RPN box loss: 0.02213 RPN score loss: 0.00545 RPN total loss: 0.02759 Total loss: 1.01631 timestamp: 1654960407.2767928 iteration: 60000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09262 FastRCNN class loss: 0.05742 FastRCNN total loss: 0.15004 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.002 Mask loss: 0.14572 RPN box loss: 0.01394 RPN score loss: 0.00415 RPN total loss: 0.01809 Total loss: 0.90815 Saving checkpoints for 60000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-60000.tlt. ================================= Start evaluation cycle 06 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-60000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.2304s - Throughput: 0.8 imgs/s Running inference on batch 002/125... - Step Time: 0.3491s - Throughput: 11.5 imgs/s Running inference on batch 003/125... - Step Time: 0.3409s - Throughput: 11.7 imgs/s Running inference on batch 004/125... - Step Time: 0.3407s - Throughput: 11.7 imgs/s Running inference on batch 005/125... - Step Time: 0.3451s - Throughput: 11.6 imgs/s Running inference on batch 006/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 007/125... - Step Time: 0.3337s - Throughput: 12.0 imgs/s Running inference on batch 008/125... - Step Time: 0.3490s - Throughput: 11.5 imgs/s Running inference on batch 009/125... - Step Time: 0.3449s - Throughput: 11.6 imgs/s Running inference on batch 010/125... - Step Time: 0.3445s - Throughput: 11.6 imgs/s Running inference on batch 011/125... - Step Time: 0.3468s - Throughput: 11.5 imgs/s Running inference on batch 012/125... - Step Time: 0.3401s - Throughput: 11.8 imgs/s Running inference on batch 013/125... - Step Time: 0.3318s - Throughput: 12.1 imgs/s Running inference on batch 014/125... - Step Time: 0.3312s - Throughput: 12.1 imgs/s Running inference on batch 015/125... - Step Time: 0.3402s - Throughput: 11.8 imgs/s Running inference on batch 016/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 017/125... - Step Time: 0.3319s - Throughput: 12.1 imgs/s Running inference on batch 018/125... - Step Time: 0.3280s - Throughput: 12.2 imgs/s Running inference on batch 019/125... - Step Time: 0.3331s - Throughput: 12.0 imgs/s Running inference on batch 020/125... - Step Time: 0.3414s - Throughput: 11.7 imgs/s Running inference on batch 021/125... - Step Time: 0.3247s - Throughput: 12.3 imgs/s Running inference on batch 022/125... - Step Time: 0.3561s - Throughput: 11.2 imgs/s Running inference on batch 023/125... - Step Time: 0.3363s - Throughput: 11.9 imgs/s Running inference on batch 024/125... - Step Time: 0.3273s - Throughput: 12.2 imgs/s Running inference on batch 025/125... - Step Time: 0.3381s - Throughput: 11.8 imgs/s Running inference on batch 026/125... - Step Time: 0.3435s - Throughput: 11.6 imgs/s Running inference on batch 027/125... - Step Time: 0.3260s - Throughput: 12.3 imgs/s Running inference on batch 028/125... - Step Time: 0.3222s - Throughput: 12.4 imgs/s Running inference on batch 029/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 030/125... - Step Time: 0.3387s - Throughput: 11.8 imgs/s Running inference on batch 031/125... - Step Time: 0.3482s - Throughput: 11.5 imgs/s Running inference on batch 032/125... - Step Time: 0.3464s - Throughput: 11.5 imgs/s Running inference on batch 033/125... - Step Time: 0.3492s - Throughput: 11.5 imgs/s Running inference on batch 034/125... - Step Time: 0.3447s - Throughput: 11.6 imgs/s Running inference on batch 035/125... - Step Time: 0.3313s - Throughput: 12.1 imgs/s Running inference on batch 036/125... - Step Time: 0.3399s - Throughput: 11.8 imgs/s Running inference on batch 037/125... - Step Time: 0.3466s - Throughput: 11.5 imgs/s Running inference on batch 038/125... - Step Time: 0.3419s - Throughput: 11.7 imgs/s Running inference on batch 039/125... - Step Time: 0.3329s - Throughput: 12.0 imgs/s Running inference on batch 040/125... - Step Time: 0.3458s - Throughput: 11.6 imgs/s Running inference on batch 041/125... - Step Time: 0.3459s - Throughput: 11.6 imgs/s Running inference on batch 042/125... - Step Time: 0.3287s - Throughput: 12.2 imgs/s Running inference on batch 043/125... - Step Time: 0.3278s - Throughput: 12.2 imgs/s Running inference on batch 044/125... - Step Time: 0.3262s - Throughput: 12.3 imgs/s Running inference on batch 045/125... - Step Time: 0.3378s - Throughput: 11.8 imgs/s Running inference on batch 046/125... - Step Time: 0.3463s - Throughput: 11.6 imgs/s Running inference on batch 047/125... - Step Time: 0.3397s - Throughput: 11.8 imgs/s Running inference on batch 048/125... - Step Time: 0.3498s - Throughput: 11.4 imgs/s Running inference on batch 049/125... - Step Time: 0.3475s - Throughput: 11.5 imgs/s Running inference on batch 050/125... - Step Time: 0.3337s - Throughput: 12.0 imgs/s Running inference on batch 051/125... - Step Time: 0.3335s - Throughput: 12.0 imgs/s Running inference on batch 052/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 053/125... - Step Time: 0.3432s - Throughput: 11.7 imgs/s Running inference on batch 054/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 055/125... - Step Time: 0.3270s - Throughput: 12.2 imgs/s Running inference on batch 056/125... - Step Time: 0.3425s - Throughput: 11.7 imgs/s Running inference on batch 057/125... - Step Time: 0.3396s - Throughput: 11.8 imgs/s Running inference on batch 058/125... - Step Time: 0.3480s - Throughput: 11.5 imgs/s Running inference on batch 059/125... - Step Time: 0.3355s - Throughput: 11.9 imgs/s Running inference on batch 060/125... - Step Time: 0.3423s - Throughput: 11.7 imgs/s Running inference on batch 061/125... - Step Time: 0.3529s - Throughput: 11.3 imgs/s Running inference on batch 062/125... - Step Time: 0.3504s - Throughput: 11.4 imgs/s Running inference on batch 063/125... - Step Time: 0.3243s - Throughput: 12.3 imgs/s Running inference on batch 064/125... - Step Time: 0.3380s - Throughput: 11.8 imgs/s Running inference on batch 065/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 066/125... - Step Time: 0.3407s - Throughput: 11.7 imgs/s Running inference on batch 067/125... - Step Time: 0.3326s - Throughput: 12.0 imgs/s Running inference on batch 068/125... - Step Time: 0.3398s - Throughput: 11.8 imgs/s Running inference on batch 069/125... - Step Time: 0.3535s - Throughput: 11.3 imgs/s Running inference on batch 070/125... - Step Time: 0.3425s - Throughput: 11.7 imgs/s Running inference on batch 071/125... - Step Time: 0.3310s - Throughput: 12.1 imgs/s Running inference on batch 072/125... - Step Time: 0.3627s - Throughput: 11.0 imgs/s Running inference on batch 073/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 074/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 075/125... - Step Time: 0.3598s - Throughput: 11.1 imgs/s Running inference on batch 076/125... - Step Time: 0.3447s - Throughput: 11.6 imgs/s Running inference on batch 077/125... - Step Time: 0.3561s - Throughput: 11.2 imgs/s Running inference on batch 078/125... - Step Time: 0.3393s - Throughput: 11.8 imgs/s Running inference on batch 079/125... - Step Time: 0.3407s - Throughput: 11.7 imgs/s Running inference on batch 080/125... - Step Time: 0.3440s - Throughput: 11.6 imgs/s Running inference on batch 081/125... - Step Time: 0.2932s - Throughput: 13.6 imgs/s Running inference on batch 082/125... - Step Time: 0.3286s - Throughput: 12.2 imgs/s Running inference on batch 083/125... - Step Time: 0.3329s - Throughput: 12.0 imgs/s Running inference on batch 084/125... - Step Time: 0.3330s - Throughput: 12.0 imgs/s Running inference on batch 085/125... - Step Time: 0.3306s - Throughput: 12.1 imgs/s Running inference on batch 086/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 087/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 088/125... - Step Time: 0.3572s - Throughput: 11.2 imgs/s Running inference on batch 089/125... - Step Time: 0.3445s - Throughput: 11.6 imgs/s Running inference on batch 090/125... - Step Time: 0.3117s - Throughput: 12.8 imgs/s Running inference on batch 091/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 092/125... - Step Time: 0.3505s - Throughput: 11.4 imgs/s Running inference on batch 093/125... - Step Time: 0.3343s - Throughput: 12.0 imgs/s Running inference on batch 094/125... - Step Time: 0.3507s - Throughput: 11.4 imgs/s Running inference on batch 095/125... - Step Time: 0.3295s - 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Throughput: 11.9 imgs/s Running inference on batch 108/125... - Step Time: 0.3346s - Throughput: 12.0 imgs/s Running inference on batch 109/125... - Step Time: 0.3352s - Throughput: 11.9 imgs/s Running inference on batch 110/125... - Step Time: 0.3389s - Throughput: 11.8 imgs/s Running inference on batch 111/125... - Step Time: 0.3413s - Throughput: 11.7 imgs/s Running inference on batch 112/125... - Step Time: 0.3226s - Throughput: 12.4 imgs/s Running inference on batch 113/125... - Step Time: 0.3333s - Throughput: 12.0 imgs/s Running inference on batch 114/125... - Step Time: 0.2930s - Throughput: 13.7 imgs/s Running inference on batch 115/125... - Step Time: 0.3419s - Throughput: 11.7 imgs/s Running inference on batch 116/125... - Step Time: 0.3228s - Throughput: 12.4 imgs/s Running inference on batch 117/125... - Step Time: 0.3401s - Throughput: 11.8 imgs/s Running inference on batch 118/125... - Step Time: 0.3500s - Throughput: 11.4 imgs/s Running inference on batch 119/125... - Step Time: 0.3436s - Throughput: 11.6 imgs/s Running inference on batch 120/125... - Step Time: 0.3347s - Throughput: 12.0 imgs/s Running inference on batch 121/125... - Step Time: 0.3318s - Throughput: 12.1 imgs/s Running inference on batch 122/125... - Step Time: 0.3306s - Throughput: 12.1 imgs/s Running inference on batch 123/125... - Step Time: 0.3379s - Throughput: 11.8 imgs/s Running inference on batch 124/125... - Step Time: 0.3499s - Throughput: 11.4 imgs/s Running inference on batch 125/125... - Step Time: 0.3427s - Throughput: 11.7 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 12.0 samples/sec Total processed steps: 125 Total processing time: 0.0h 24m 30s ==================== Metrics ==================== AP: 0.207912982 AP50: 0.324696720 AP75: 0.200706169 APl: 0.243457198 APm: 0.050809085 APs: 0.006789139 ARl: 0.442283630 ARm: 0.112355202 ARmax1: 0.294430315 ARmax10: 0.374916404 ARmax100: 0.380688131 ARs: 0.022110077 mask_AP: 0.166808918 mask_AP50: 0.284712523 mask_AP75: 0.167072505 mask_APl: 0.198815778 mask_APm: 0.024662532 mask_APs: 0.000884196 mask_ARl: 0.321134657 mask_ARm: 0.058400221 mask_ARmax1: 0.229451612 mask_ARmax10: 0.268077582 mask_ARmax100: 0.271724045 mask_ARs: 0.009903382 ================================= Start training cycle 07 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654961797.4170296 iteration: 60005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10568 FastRCNN class loss: 0.04673 FastRCNN total loss: 0.15241 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.0004 Mask loss: 0.10827 RPN box loss: 0.01386 RPN score loss: 0.00087 RPN total loss: 0.01473 Total loss: 0.8697 timestamp: 1654961800.5896728 iteration: 60010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05257 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.10956 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.0004 Mask loss: 0.1075 RPN box loss: 0.0108 RPN score loss: 0.00083 RPN total loss: 0.01162 Total loss: 0.82298 timestamp: 1654961803.7839477 iteration: 60015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07214 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.12564 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.0004 Mask loss: 0.14464 RPN box loss: 0.00728 RPN score loss: 0.00189 RPN total loss: 0.00917 Total loss: 0.87375 timestamp: 1654961806.8992662 iteration: 60020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12035 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.1861 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.0004 Mask loss: 0.13173 RPN box loss: 0.00841 RPN score loss: 0.00261 RPN total loss: 0.01102 Total loss: 0.92315 timestamp: 1654961810.138383 iteration: 60025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08815 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.13602 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.13369 RPN box loss: 0.01795 RPN score loss: 0.00244 RPN total loss: 0.02038 Total loss: 0.88439 timestamp: 1654961813.3294554 iteration: 60030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07309 FastRCNN class loss: 0.0596 FastRCNN total loss: 0.1327 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.08343 RPN box loss: 0.00723 RPN score loss: 0.00402 RPN total loss: 0.01126 Total loss: 0.82168 timestamp: 1654961816.5729845 iteration: 60035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07331 FastRCNN class loss: 0.0631 FastRCNN total loss: 0.13641 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.14433 RPN box loss: 0.00612 RPN score loss: 0.00121 RPN total loss: 0.00734 Total loss: 0.88237 timestamp: 1654961819.8022459 iteration: 60040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08571 FastRCNN class loss: 0.06508 FastRCNN total loss: 0.15078 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.14163 RPN box loss: 0.00475 RPN score loss: 0.00136 RPN total loss: 0.00612 Total loss: 0.89283 timestamp: 1654961822.9612644 iteration: 60045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16382 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.23974 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.08999 RPN box loss: 0.00691 RPN score loss: 0.00404 RPN total loss: 0.01095 Total loss: 0.93497 timestamp: 1654961826.099461 iteration: 60050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09166 FastRCNN class loss: 0.07595 FastRCNN total loss: 0.16762 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.13052 RPN box loss: 0.01304 RPN score loss: 0.00658 RPN total loss: 0.01963 Total loss: 0.91205 timestamp: 1654961829.3143346 iteration: 60055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0836 FastRCNN class loss: 0.06209 FastRCNN total loss: 0.14569 L1 loss: 0.0000e+00 L2 loss: 0.59429 Learning rate: 0.0004 Mask loss: 0.12141 RPN box loss: 0.01126 RPN score loss: 0.00408 RPN total loss: 0.01534 Total loss: 0.87672 timestamp: 1654961832.487343 iteration: 60060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11312 FastRCNN class loss: 0.11774 FastRCNN total loss: 0.23086 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.0004 Mask loss: 0.18573 RPN box loss: 0.01965 RPN score loss: 0.01021 RPN total loss: 0.02986 Total loss: 1.04073 timestamp: 1654961835.7023852 iteration: 60065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05608 FastRCNN class loss: 0.04867 FastRCNN total loss: 0.10475 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.0004 Mask loss: 0.1371 RPN box loss: 0.01677 RPN score loss: 0.00308 RPN total loss: 0.01986 Total loss: 0.856 timestamp: 1654961838.8968904 iteration: 60070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12555 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.21783 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.0004 Mask loss: 0.11508 RPN box loss: 0.00947 RPN score loss: 0.00327 RPN total loss: 0.01274 Total loss: 0.93993 timestamp: 1654961842.1308703 iteration: 60075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0974 FastRCNN class loss: 0.07194 FastRCNN total loss: 0.16934 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.0004 Mask loss: 0.12362 RPN box loss: 0.00909 RPN score loss: 0.00355 RPN total loss: 0.01264 Total loss: 0.89988 timestamp: 1654961845.3307528 iteration: 60080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05391 FastRCNN class loss: 0.03115 FastRCNN total loss: 0.08506 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.0004 Mask loss: 0.12586 RPN box loss: 0.00535 RPN score loss: 0.00357 RPN total loss: 0.00892 Total loss: 0.81412 timestamp: 1654961848.5241795 iteration: 60085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1093 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.18056 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.0004 Mask loss: 0.16748 RPN box loss: 0.01364 RPN score loss: 0.00285 RPN total loss: 0.01648 Total loss: 0.9588 timestamp: 1654961851.7554865 iteration: 60090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1576 FastRCNN class loss: 0.09551 FastRCNN total loss: 0.25311 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.0004 Mask loss: 0.13019 RPN box loss: 0.0121 RPN score loss: 0.00526 RPN total loss: 0.01736 Total loss: 0.99494 timestamp: 1654961854.9785006 iteration: 60095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06229 FastRCNN class loss: 0.04339 FastRCNN total loss: 0.10568 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.0004 Mask loss: 0.08004 RPN box loss: 0.01062 RPN score loss: 0.00673 RPN total loss: 0.01735 Total loss: 0.79735 timestamp: 1654961858.2004359 iteration: 60100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08132 FastRCNN class loss: 0.04839 FastRCNN total loss: 0.12972 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.0004 Mask loss: 0.0952 RPN box loss: 0.02226 RPN score loss: 0.0062 RPN total loss: 0.02846 Total loss: 0.84765 timestamp: 1654961861.4122658 iteration: 60105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10637 FastRCNN class loss: 0.07216 FastRCNN total loss: 0.17853 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.0004 Mask loss: 0.11805 RPN box loss: 0.0306 RPN score loss: 0.00631 RPN total loss: 0.0369 Total loss: 0.92775 timestamp: 1654961864.5878093 iteration: 60110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07011 FastRCNN class loss: 0.06141 FastRCNN total loss: 0.13152 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.0004 Mask loss: 0.11001 RPN box loss: 0.00382 RPN score loss: 0.00601 RPN total loss: 0.00983 Total loss: 0.84562 timestamp: 1654961867.74514 iteration: 60115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09294 FastRCNN class loss: 0.0595 FastRCNN total loss: 0.15244 L1 loss: 0.0000e+00 L2 loss: 0.59426 Learning rate: 0.0004 Mask loss: 0.14054 RPN box loss: 0.01233 RPN score loss: 0.00469 RPN total loss: 0.01702 Total loss: 0.90426 timestamp: 1654961870.8999414 iteration: 60120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0274 FastRCNN class loss: 0.03021 FastRCNN total loss: 0.05761 L1 loss: 0.0000e+00 L2 loss: 0.59426 Learning rate: 0.0004 Mask loss: 0.08159 RPN box loss: 0.00214 RPN score loss: 0.00076 RPN total loss: 0.00289 Total loss: 0.73636 timestamp: 1654961874.0862892 iteration: 60125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06377 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.13026 L1 loss: 0.0000e+00 L2 loss: 0.59426 Learning rate: 0.0004 Mask loss: 0.11126 RPN box loss: 0.0048 RPN score loss: 0.00149 RPN total loss: 0.00629 Total loss: 0.84207 timestamp: 1654961877.3163238 iteration: 60130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.09233 FastRCNN total loss: 0.1863 L1 loss: 0.0000e+00 L2 loss: 0.59426 Learning rate: 0.0004 Mask loss: 0.14432 RPN box loss: 0.03476 RPN score loss: 0.00591 RPN total loss: 0.04066 Total loss: 0.96554 timestamp: 1654961880.531787 iteration: 60135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08466 FastRCNN class loss: 0.07146 FastRCNN total loss: 0.15612 L1 loss: 0.0000e+00 L2 loss: 0.59426 Learning rate: 0.0004 Mask loss: 0.13742 RPN box loss: 0.01301 RPN score loss: 0.00472 RPN total loss: 0.01773 Total loss: 0.90552 timestamp: 1654961883.6982775 iteration: 60140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.08624 FastRCNN total loss: 0.18646 L1 loss: 0.0000e+00 L2 loss: 0.59426 Learning rate: 0.0004 Mask loss: 0.13342 RPN box loss: 0.01643 RPN score loss: 0.00174 RPN total loss: 0.01817 Total loss: 0.93231 timestamp: 1654961886.9174566 iteration: 60145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.05643 FastRCNN total loss: 0.15796 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.0004 Mask loss: 0.09027 RPN box loss: 0.00386 RPN score loss: 0.00133 RPN total loss: 0.00519 Total loss: 0.84767 timestamp: 1654961890.0241463 iteration: 60150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10582 FastRCNN class loss: 0.08141 FastRCNN total loss: 0.18723 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.0004 Mask loss: 0.11174 RPN box loss: 0.02416 RPN score loss: 0.00246 RPN total loss: 0.02662 Total loss: 0.91984 timestamp: 1654961893.180833 iteration: 60155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09249 FastRCNN class loss: 0.05104 FastRCNN total loss: 0.14353 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.0004 Mask loss: 0.08493 RPN box loss: 0.00905 RPN score loss: 0.00192 RPN total loss: 0.01098 Total loss: 0.83368 timestamp: 1654961896.4226592 iteration: 60160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08573 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.17548 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.0004 Mask loss: 0.14919 RPN box loss: 0.00552 RPN score loss: 0.00405 RPN total loss: 0.00956 Total loss: 0.92848 timestamp: 1654961899.691709 iteration: 60165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07887 FastRCNN class loss: 0.04226 FastRCNN total loss: 0.12113 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.0004 Mask loss: 0.11684 RPN box loss: 0.00567 RPN score loss: 0.00557 RPN total loss: 0.01124 Total loss: 0.84346 timestamp: 1654961902.9216502 iteration: 60170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07257 FastRCNN class loss: 0.07053 FastRCNN total loss: 0.14309 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.0004 Mask loss: 0.22696 RPN box loss: 0.0222 RPN score loss: 0.00782 RPN total loss: 0.03002 Total loss: 0.99432 timestamp: 1654961906.0947309 iteration: 60175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0828 FastRCNN class loss: 0.06799 FastRCNN total loss: 0.15079 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.0004 Mask loss: 0.11912 RPN box loss: 0.00572 RPN score loss: 0.00765 RPN total loss: 0.01337 Total loss: 0.87752 timestamp: 1654961909.243047 iteration: 60180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08611 FastRCNN class loss: 0.04831 FastRCNN total loss: 0.13442 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.0004 Mask loss: 0.16008 RPN box loss: 0.0131 RPN score loss: 0.00313 RPN total loss: 0.01623 Total loss: 0.90497 timestamp: 1654961912.3950186 iteration: 60185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05943 FastRCNN class loss: 0.11768 FastRCNN total loss: 0.1771 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.0004 Mask loss: 0.14044 RPN box loss: 0.01526 RPN score loss: 0.01413 RPN total loss: 0.02939 Total loss: 0.94117 timestamp: 1654961915.6267104 iteration: 60190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05699 FastRCNN class loss: 0.07388 FastRCNN total loss: 0.13087 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.0004 Mask loss: 0.12969 RPN box loss: 0.01173 RPN score loss: 0.00495 RPN total loss: 0.01667 Total loss: 0.87147 timestamp: 1654961918.7937062 iteration: 60195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14384 FastRCNN class loss: 0.08393 FastRCNN total loss: 0.22777 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.0004 Mask loss: 0.17604 RPN box loss: 0.01011 RPN score loss: 0.0049 RPN total loss: 0.015 Total loss: 1.01305 timestamp: 1654961921.95504 iteration: 60200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16183 FastRCNN class loss: 0.08598 FastRCNN total loss: 0.24781 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.0004 Mask loss: 0.12049 RPN box loss: 0.02128 RPN score loss: 0.00369 RPN total loss: 0.02497 Total loss: 0.98751 timestamp: 1654961925.2030156 iteration: 60205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08574 FastRCNN class loss: 0.07891 FastRCNN total loss: 0.16465 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.0004 Mask loss: 0.1197 RPN box loss: 0.00845 RPN score loss: 0.00157 RPN total loss: 0.01002 Total loss: 0.88859 timestamp: 1654961928.331411 iteration: 60210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.16913 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.0004 Mask loss: 0.13614 RPN box loss: 0.01025 RPN score loss: 0.00421 RPN total loss: 0.01446 Total loss: 0.91396 timestamp: 1654961931.5200121 iteration: 60215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09979 FastRCNN class loss: 0.08498 FastRCNN total loss: 0.18476 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.0004 Mask loss: 0.19112 RPN box loss: 0.00972 RPN score loss: 0.0045 RPN total loss: 0.01423 Total loss: 0.98434 timestamp: 1654961934.7930737 iteration: 60220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05594 FastRCNN class loss: 0.04827 FastRCNN total loss: 0.10421 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.0004 Mask loss: 0.09169 RPN box loss: 0.00701 RPN score loss: 0.00346 RPN total loss: 0.01047 Total loss: 0.8006 timestamp: 1654961937.9798543 iteration: 60225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04296 FastRCNN class loss: 0.03616 FastRCNN total loss: 0.07912 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.0004 Mask loss: 0.09942 RPN box loss: 0.01054 RPN score loss: 0.00669 RPN total loss: 0.01723 Total loss: 0.79 timestamp: 1654961941.1103528 iteration: 60230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09701 FastRCNN class loss: 0.06883 FastRCNN total loss: 0.16583 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.0004 Mask loss: 0.178 RPN box loss: 0.01173 RPN score loss: 0.00496 RPN total loss: 0.01668 Total loss: 0.95474 timestamp: 1654961944.3288038 iteration: 60235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07976 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.15653 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.0004 Mask loss: 0.08012 RPN box loss: 0.00712 RPN score loss: 0.00388 RPN total loss: 0.01099 Total loss: 0.84187 timestamp: 1654961947.6000645 iteration: 60240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1114 FastRCNN class loss: 0.05749 FastRCNN total loss: 0.16889 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.0004 Mask loss: 0.10906 RPN box loss: 0.01778 RPN score loss: 0.00283 RPN total loss: 0.02061 Total loss: 0.89278 timestamp: 1654961950.8269303 iteration: 60245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06483 FastRCNN class loss: 0.06986 FastRCNN total loss: 0.1347 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.0004 Mask loss: 0.13147 RPN box loss: 0.00529 RPN score loss: 0.00305 RPN total loss: 0.00834 Total loss: 0.86872 timestamp: 1654961954.067148 iteration: 60250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05723 FastRCNN class loss: 0.04113 FastRCNN total loss: 0.09835 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.0004 Mask loss: 0.09195 RPN box loss: 0.00535 RPN score loss: 0.00194 RPN total loss: 0.00729 Total loss: 0.79182 timestamp: 1654961957.2360444 iteration: 60255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08676 FastRCNN class loss: 0.05117 FastRCNN total loss: 0.13793 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.0004 Mask loss: 0.08294 RPN box loss: 0.00357 RPN score loss: 0.00554 RPN total loss: 0.00911 Total loss: 0.82419 timestamp: 1654961960.4675596 iteration: 60260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0525 FastRCNN class loss: 0.05687 FastRCNN total loss: 0.10937 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.10451 RPN box loss: 0.00477 RPN score loss: 0.00147 RPN total loss: 0.00624 Total loss: 0.81434 timestamp: 1654961963.7043085 iteration: 60265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1088 FastRCNN class loss: 0.08464 FastRCNN total loss: 0.19344 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.12686 RPN box loss: 0.00903 RPN score loss: 0.00547 RPN total loss: 0.0145 Total loss: 0.92901 timestamp: 1654961966.8820813 iteration: 60270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10904 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.17542 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.18326 RPN box loss: 0.00777 RPN score loss: 0.00445 RPN total loss: 0.01222 Total loss: 0.96511 timestamp: 1654961970.062258 iteration: 60275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11515 FastRCNN class loss: 0.05922 FastRCNN total loss: 0.17437 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.13521 RPN box loss: 0.03749 RPN score loss: 0.00085 RPN total loss: 0.03834 Total loss: 0.94212 timestamp: 1654961973.2043223 iteration: 60280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12788 FastRCNN class loss: 0.05634 FastRCNN total loss: 0.18422 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.14654 RPN box loss: 0.00335 RPN score loss: 0.00461 RPN total loss: 0.00796 Total loss: 0.93292 timestamp: 1654961976.373165 iteration: 60285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1195 FastRCNN class loss: 0.0489 FastRCNN total loss: 0.1684 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.08315 RPN box loss: 0.00922 RPN score loss: 0.00309 RPN total loss: 0.01231 Total loss: 0.85807 timestamp: 1654961979.5041444 iteration: 60290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07927 FastRCNN class loss: 0.06642 FastRCNN total loss: 0.14569 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.0004 Mask loss: 0.0989 RPN box loss: 0.00616 RPN score loss: 0.00395 RPN total loss: 0.01011 Total loss: 0.8489 timestamp: 1654961982.6478736 iteration: 60295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11205 FastRCNN class loss: 0.06707 FastRCNN total loss: 0.17913 L1 loss: 0.0000e+00 L2 loss: 0.5942 Learning rate: 0.0004 Mask loss: 0.12537 RPN box loss: 0.01629 RPN score loss: 0.00811 RPN total loss: 0.0244 Total loss: 0.9231 timestamp: 1654961985.843772 iteration: 60300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11756 FastRCNN class loss: 0.0812 FastRCNN total loss: 0.19876 L1 loss: 0.0000e+00 L2 loss: 0.5942 Learning rate: 0.0004 Mask loss: 0.15465 RPN box loss: 0.02431 RPN score loss: 0.00396 RPN total loss: 0.02827 Total loss: 0.97588 timestamp: 1654961988.9781115 iteration: 60305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.06818 FastRCNN total loss: 0.15515 L1 loss: 0.0000e+00 L2 loss: 0.5942 Learning rate: 0.0004 Mask loss: 0.12288 RPN box loss: 0.01372 RPN score loss: 0.0047 RPN total loss: 0.01842 Total loss: 0.89065 timestamp: 1654961992.2513382 iteration: 60310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09888 FastRCNN class loss: 0.06192 FastRCNN total loss: 0.16079 L1 loss: 0.0000e+00 L2 loss: 0.5942 Learning rate: 0.0004 Mask loss: 0.12934 RPN box loss: 0.00924 RPN score loss: 0.00153 RPN total loss: 0.01078 Total loss: 0.89511 timestamp: 1654961995.4754038 iteration: 60315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10728 FastRCNN class loss: 0.05949 FastRCNN total loss: 0.16677 L1 loss: 0.0000e+00 L2 loss: 0.5942 Learning rate: 0.0004 Mask loss: 0.13915 RPN box loss: 0.00766 RPN score loss: 0.00136 RPN total loss: 0.00902 Total loss: 0.90914 timestamp: 1654961998.5962825 iteration: 60320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14011 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.20893 L1 loss: 0.0000e+00 L2 loss: 0.59419 Learning rate: 0.0004 Mask loss: 0.13351 RPN box loss: 0.00799 RPN score loss: 0.0045 RPN total loss: 0.01249 Total loss: 0.94913 timestamp: 1654962001.798739 iteration: 60325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06823 FastRCNN class loss: 0.04234 FastRCNN total loss: 0.11057 L1 loss: 0.0000e+00 L2 loss: 0.59419 Learning rate: 0.0004 Mask loss: 0.11663 RPN box loss: 0.00848 RPN score loss: 0.00572 RPN total loss: 0.0142 Total loss: 0.8356 timestamp: 1654962005.0675318 iteration: 60330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1158 FastRCNN class loss: 0.06619 FastRCNN total loss: 0.18199 L1 loss: 0.0000e+00 L2 loss: 0.59419 Learning rate: 0.0004 Mask loss: 0.1115 RPN box loss: 0.01484 RPN score loss: 0.00411 RPN total loss: 0.01895 Total loss: 0.90663 timestamp: 1654962008.2433465 iteration: 60335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09184 FastRCNN class loss: 0.05292 FastRCNN total loss: 0.14476 L1 loss: 0.0000e+00 L2 loss: 0.59419 Learning rate: 0.0004 Mask loss: 0.11697 RPN box loss: 0.02556 RPN score loss: 0.01083 RPN total loss: 0.0364 Total loss: 0.89231 timestamp: 1654962011.4139087 iteration: 60340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05964 FastRCNN class loss: 0.0482 FastRCNN total loss: 0.10785 L1 loss: 0.0000e+00 L2 loss: 0.59419 Learning rate: 0.0004 Mask loss: 0.15806 RPN box loss: 0.01153 RPN score loss: 0.00094 RPN total loss: 0.01247 Total loss: 0.87257 timestamp: 1654962014.5196276 iteration: 60345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07525 FastRCNN class loss: 0.05001 FastRCNN total loss: 0.12526 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.14181 RPN box loss: 0.00603 RPN score loss: 0.00349 RPN total loss: 0.00951 Total loss: 0.87077 timestamp: 1654962017.7505765 iteration: 60350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13571 FastRCNN class loss: 0.07331 FastRCNN total loss: 0.20902 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.22553 RPN box loss: 0.01449 RPN score loss: 0.00995 RPN total loss: 0.02444 Total loss: 1.05318 timestamp: 1654962020.932545 iteration: 60355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09067 FastRCNN class loss: 0.04458 FastRCNN total loss: 0.13525 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.08774 RPN box loss: 0.0104 RPN score loss: 0.00173 RPN total loss: 0.01213 Total loss: 0.8293 timestamp: 1654962024.0943491 iteration: 60360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09833 FastRCNN class loss: 0.08635 FastRCNN total loss: 0.18468 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.15471 RPN box loss: 0.01496 RPN score loss: 0.00827 RPN total loss: 0.02323 Total loss: 0.95681 timestamp: 1654962027.2637584 iteration: 60365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08259 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.14203 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.09966 RPN box loss: 0.03409 RPN score loss: 0.00327 RPN total loss: 0.03736 Total loss: 0.87323 timestamp: 1654962030.4805975 iteration: 60370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05632 FastRCNN class loss: 0.05098 FastRCNN total loss: 0.1073 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.0972 RPN box loss: 0.01786 RPN score loss: 0.00341 RPN total loss: 0.02127 Total loss: 0.81995 timestamp: 1654962033.6421185 iteration: 60375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07299 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.13573 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.0004 Mask loss: 0.22136 RPN box loss: 0.01037 RPN score loss: 0.00143 RPN total loss: 0.0118 Total loss: 0.96307 timestamp: 1654962036.7861855 iteration: 60380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08465 FastRCNN class loss: 0.08487 FastRCNN total loss: 0.16952 L1 loss: 0.0000e+00 L2 loss: 0.59417 Learning rate: 0.0004 Mask loss: 0.15482 RPN box loss: 0.00981 RPN score loss: 0.00825 RPN total loss: 0.01806 Total loss: 0.93657 timestamp: 1654962040.0145028 iteration: 60385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16366 FastRCNN class loss: 0.13179 FastRCNN total loss: 0.29545 L1 loss: 0.0000e+00 L2 loss: 0.59417 Learning rate: 0.0004 Mask loss: 0.15507 RPN box loss: 0.01748 RPN score loss: 0.02266 RPN total loss: 0.04014 Total loss: 1.08483 timestamp: 1654962043.1989844 iteration: 60390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0692 FastRCNN class loss: 0.03648 FastRCNN total loss: 0.10569 L1 loss: 0.0000e+00 L2 loss: 0.59417 Learning rate: 0.0004 Mask loss: 0.20003 RPN box loss: 0.01078 RPN score loss: 0.00138 RPN total loss: 0.01215 Total loss: 0.91204 timestamp: 1654962046.483769 iteration: 60395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09419 FastRCNN class loss: 0.12284 FastRCNN total loss: 0.21702 L1 loss: 0.0000e+00 L2 loss: 0.59417 Learning rate: 0.0004 Mask loss: 0.12395 RPN box loss: 0.01099 RPN score loss: 0.00237 RPN total loss: 0.01336 Total loss: 0.9485 timestamp: 1654962049.741191 iteration: 60400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04267 FastRCNN class loss: 0.04345 FastRCNN total loss: 0.08612 L1 loss: 0.0000e+00 L2 loss: 0.59417 Learning rate: 0.0004 Mask loss: 0.11692 RPN box loss: 0.00439 RPN score loss: 0.00107 RPN total loss: 0.00545 Total loss: 0.80266 timestamp: 1654962052.9785595 iteration: 60405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04508 FastRCNN class loss: 0.06507 FastRCNN total loss: 0.11015 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.0004 Mask loss: 0.11085 RPN box loss: 0.00599 RPN score loss: 0.00093 RPN total loss: 0.00692 Total loss: 0.82209 timestamp: 1654962056.202053 iteration: 60410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11089 FastRCNN class loss: 0.09305 FastRCNN total loss: 0.20394 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.0004 Mask loss: 0.12429 RPN box loss: 0.02324 RPN score loss: 0.00499 RPN total loss: 0.02823 Total loss: 0.95062 timestamp: 1654962059.4238718 iteration: 60415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.04294 FastRCNN total loss: 0.11209 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.0004 Mask loss: 0.0998 RPN box loss: 0.00627 RPN score loss: 0.00373 RPN total loss: 0.01 Total loss: 0.81606 timestamp: 1654962062.5619745 iteration: 60420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06712 FastRCNN class loss: 0.04852 FastRCNN total loss: 0.11564 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.0004 Mask loss: 0.11387 RPN box loss: 0.01394 RPN score loss: 0.00054 RPN total loss: 0.01448 Total loss: 0.83815 timestamp: 1654962065.7821455 iteration: 60425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0826 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.15753 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.0004 Mask loss: 0.15657 RPN box loss: 0.0216 RPN score loss: 0.01091 RPN total loss: 0.03251 Total loss: 0.94077 timestamp: 1654962068.9319985 iteration: 60430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17275 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.25539 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.0004 Mask loss: 0.15385 RPN box loss: 0.01171 RPN score loss: 0.003 RPN total loss: 0.01472 Total loss: 1.01812 timestamp: 1654962072.2047467 iteration: 60435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08399 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.15117 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.0004 Mask loss: 0.15804 RPN box loss: 0.02484 RPN score loss: 0.0063 RPN total loss: 0.03113 Total loss: 0.93449 timestamp: 1654962075.370941 iteration: 60440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12368 FastRCNN class loss: 0.05438 FastRCNN total loss: 0.17806 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.0004 Mask loss: 0.14376 RPN box loss: 0.00696 RPN score loss: 0.00251 RPN total loss: 0.00947 Total loss: 0.92545 timestamp: 1654962078.5635145 iteration: 60445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10432 FastRCNN class loss: 0.0622 FastRCNN total loss: 0.16652 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.0004 Mask loss: 0.14384 RPN box loss: 0.01589 RPN score loss: 0.0074 RPN total loss: 0.02329 Total loss: 0.9278 timestamp: 1654962081.815249 iteration: 60450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07063 FastRCNN class loss: 0.0527 FastRCNN total loss: 0.12333 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.0004 Mask loss: 0.14664 RPN box loss: 0.00445 RPN score loss: 0.00546 RPN total loss: 0.00991 Total loss: 0.87402 timestamp: 1654962085.0194976 iteration: 60455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.17082 FastRCNN total loss: 0.30311 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.0004 Mask loss: 0.18591 RPN box loss: 0.03791 RPN score loss: 0.01163 RPN total loss: 0.04954 Total loss: 1.1327 timestamp: 1654962088.2733655 iteration: 60460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09718 FastRCNN class loss: 0.08099 FastRCNN total loss: 0.17817 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.0004 Mask loss: 0.15428 RPN box loss: 0.01231 RPN score loss: 0.00663 RPN total loss: 0.01894 Total loss: 0.94554 timestamp: 1654962091.3781316 iteration: 60465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0783 FastRCNN class loss: 0.03829 FastRCNN total loss: 0.11658 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.0959 RPN box loss: 0.0026 RPN score loss: 0.00106 RPN total loss: 0.00366 Total loss: 0.81029 timestamp: 1654962094.5591035 iteration: 60470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07913 FastRCNN class loss: 0.08918 FastRCNN total loss: 0.16831 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.13082 RPN box loss: 0.01682 RPN score loss: 0.01261 RPN total loss: 0.02943 Total loss: 0.92271 timestamp: 1654962097.7426815 iteration: 60475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.05821 FastRCNN total loss: 0.17292 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.12636 RPN box loss: 0.00986 RPN score loss: 0.00571 RPN total loss: 0.01557 Total loss: 0.90899 timestamp: 1654962101.0016587 iteration: 60480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12936 FastRCNN class loss: 0.10052 FastRCNN total loss: 0.22988 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.15476 RPN box loss: 0.01452 RPN score loss: 0.00349 RPN total loss: 0.01801 Total loss: 0.99679 timestamp: 1654962104.1947246 iteration: 60485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1159 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.19167 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.12055 RPN box loss: 0.0143 RPN score loss: 0.00751 RPN total loss: 0.0218 Total loss: 0.92817 timestamp: 1654962107.5171528 iteration: 60490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05212 FastRCNN class loss: 0.03521 FastRCNN total loss: 0.08733 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.10942 RPN box loss: 0.00867 RPN score loss: 0.00585 RPN total loss: 0.01451 Total loss: 0.8054 timestamp: 1654962110.6923509 iteration: 60495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.06971 FastRCNN total loss: 0.18192 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.0004 Mask loss: 0.16275 RPN box loss: 0.00814 RPN score loss: 0.00254 RPN total loss: 0.01068 Total loss: 0.94949 timestamp: 1654962113.908893 iteration: 60500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.06472 FastRCNN total loss: 0.18345 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.0004 Mask loss: 0.12523 RPN box loss: 0.01241 RPN score loss: 0.00196 RPN total loss: 0.01437 Total loss: 0.91718 timestamp: 1654962117.1611967 iteration: 60505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05908 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.10299 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.0004 Mask loss: 0.13904 RPN box loss: 0.00412 RPN score loss: 0.00141 RPN total loss: 0.00553 Total loss: 0.84169 timestamp: 1654962120.321881 iteration: 60510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07928 FastRCNN class loss: 0.07232 FastRCNN total loss: 0.1516 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.0004 Mask loss: 0.1287 RPN box loss: 0.0068 RPN score loss: 0.00433 RPN total loss: 0.01113 Total loss: 0.88555 timestamp: 1654962123.500018 iteration: 60515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09969 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.16803 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.0004 Mask loss: 0.13811 RPN box loss: 0.01782 RPN score loss: 0.00164 RPN total loss: 0.01947 Total loss: 0.91974 timestamp: 1654962126.6531165 iteration: 60520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05039 FastRCNN class loss: 0.03126 FastRCNN total loss: 0.08165 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.0004 Mask loss: 0.1249 RPN box loss: 0.01295 RPN score loss: 0.00438 RPN total loss: 0.01733 Total loss: 0.81801 timestamp: 1654962129.7860355 iteration: 60525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13801 FastRCNN class loss: 0.08443 FastRCNN total loss: 0.22244 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.0004 Mask loss: 0.11983 RPN box loss: 0.0108 RPN score loss: 0.00472 RPN total loss: 0.01553 Total loss: 0.95192 timestamp: 1654962132.9541957 iteration: 60530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08022 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.1366 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.0004 Mask loss: 0.13445 RPN box loss: 0.01885 RPN score loss: 0.00282 RPN total loss: 0.02167 Total loss: 0.88684 timestamp: 1654962136.163486 iteration: 60535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09154 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.1548 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.0004 Mask loss: 0.13963 RPN box loss: 0.0089 RPN score loss: 0.00354 RPN total loss: 0.01244 Total loss: 0.901 timestamp: 1654962139.189673 iteration: 60540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05945 FastRCNN class loss: 0.03854 FastRCNN total loss: 0.09799 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.0004 Mask loss: 0.05641 RPN box loss: 0.00344 RPN score loss: 0.00086 RPN total loss: 0.0043 Total loss: 0.75282 timestamp: 1654962142.4169433 iteration: 60545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09367 FastRCNN class loss: 0.06774 FastRCNN total loss: 0.1614 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.0004 Mask loss: 0.14959 RPN box loss: 0.01426 RPN score loss: 0.01617 RPN total loss: 0.03043 Total loss: 0.93554 timestamp: 1654962145.683956 iteration: 60550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07889 FastRCNN class loss: 0.0514 FastRCNN total loss: 0.13029 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.0004 Mask loss: 0.10697 RPN box loss: 0.01527 RPN score loss: 0.00341 RPN total loss: 0.01868 Total loss: 0.85006 timestamp: 1654962148.9010937 iteration: 60555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06661 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.116 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.0004 Mask loss: 0.13815 RPN box loss: 0.00784 RPN score loss: 0.00498 RPN total loss: 0.01282 Total loss: 0.86108 timestamp: 1654962152.1084914 iteration: 60560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16947 FastRCNN class loss: 0.09794 FastRCNN total loss: 0.26741 L1 loss: 0.0000e+00 L2 loss: 0.59411 Learning rate: 0.0004 Mask loss: 0.19156 RPN box loss: 0.01189 RPN score loss: 0.01087 RPN total loss: 0.02276 Total loss: 1.07586 timestamp: 1654962155.356709 iteration: 60565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04542 FastRCNN class loss: 0.0517 FastRCNN total loss: 0.09712 L1 loss: 0.0000e+00 L2 loss: 0.59411 Learning rate: 0.0004 Mask loss: 0.13708 RPN box loss: 0.00536 RPN score loss: 0.0041 RPN total loss: 0.00946 Total loss: 0.83777 timestamp: 1654962158.5264313 iteration: 60570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09652 FastRCNN class loss: 0.06384 FastRCNN total loss: 0.16036 L1 loss: 0.0000e+00 L2 loss: 0.59411 Learning rate: 0.0004 Mask loss: 0.21481 RPN box loss: 0.0051 RPN score loss: 0.00186 RPN total loss: 0.00696 Total loss: 0.97624 timestamp: 1654962161.6692271 iteration: 60575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08368 FastRCNN class loss: 0.03712 FastRCNN total loss: 0.1208 L1 loss: 0.0000e+00 L2 loss: 0.59411 Learning rate: 0.0004 Mask loss: 0.14248 RPN box loss: 0.01151 RPN score loss: 0.00547 RPN total loss: 0.01698 Total loss: 0.87437 timestamp: 1654962164.7989278 iteration: 60580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09135 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.16535 L1 loss: 0.0000e+00 L2 loss: 0.59411 Learning rate: 0.0004 Mask loss: 0.14167 RPN box loss: 0.01114 RPN score loss: 0.00225 RPN total loss: 0.01339 Total loss: 0.91451 timestamp: 1654962167.9383895 iteration: 60585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11119 FastRCNN class loss: 0.08346 FastRCNN total loss: 0.19464 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.0004 Mask loss: 0.23527 RPN box loss: 0.01284 RPN score loss: 0.01044 RPN total loss: 0.02328 Total loss: 1.0473 timestamp: 1654962171.1453567 iteration: 60590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06342 FastRCNN class loss: 0.0513 FastRCNN total loss: 0.11472 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.0004 Mask loss: 0.13091 RPN box loss: 0.00938 RPN score loss: 0.00265 RPN total loss: 0.01202 Total loss: 0.85176 timestamp: 1654962174.3576336 iteration: 60595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10961 FastRCNN class loss: 0.06953 FastRCNN total loss: 0.17914 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.0004 Mask loss: 0.11143 RPN box loss: 0.00884 RPN score loss: 0.00599 RPN total loss: 0.01484 Total loss: 0.8995 timestamp: 1654962177.5433192 iteration: 60600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16168 FastRCNN class loss: 0.08987 FastRCNN total loss: 0.25155 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.0004 Mask loss: 0.12715 RPN box loss: 0.01766 RPN score loss: 0.01533 RPN total loss: 0.03299 Total loss: 1.00579 timestamp: 1654962180.7873063 iteration: 60605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09951 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.16828 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.0004 Mask loss: 0.10352 RPN box loss: 0.0153 RPN score loss: 0.00914 RPN total loss: 0.02444 Total loss: 0.89034 timestamp: 1654962184.0206416 iteration: 60610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10894 FastRCNN class loss: 0.05474 FastRCNN total loss: 0.16369 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.0004 Mask loss: 0.1118 RPN box loss: 0.01709 RPN score loss: 0.00887 RPN total loss: 0.02596 Total loss: 0.89555 timestamp: 1654962187.17574 iteration: 60615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08552 FastRCNN class loss: 0.07169 FastRCNN total loss: 0.15721 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.0004 Mask loss: 0.14206 RPN box loss: 0.00899 RPN score loss: 0.00842 RPN total loss: 0.0174 Total loss: 0.91076 timestamp: 1654962190.312483 iteration: 60620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09062 FastRCNN class loss: 0.06431 FastRCNN total loss: 0.15492 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.0004 Mask loss: 0.1321 RPN box loss: 0.00552 RPN score loss: 0.00628 RPN total loss: 0.0118 Total loss: 0.89292 timestamp: 1654962193.5211744 iteration: 60625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07758 FastRCNN class loss: 0.05072 FastRCNN total loss: 0.1283 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.0004 Mask loss: 0.11346 RPN box loss: 0.00575 RPN score loss: 0.00268 RPN total loss: 0.00844 Total loss: 0.84428 timestamp: 1654962196.59098 iteration: 60630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11342 FastRCNN class loss: 0.05326 FastRCNN total loss: 0.16668 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.0004 Mask loss: 0.1036 RPN box loss: 0.02328 RPN score loss: 0.01049 RPN total loss: 0.03377 Total loss: 0.89814 timestamp: 1654962199.8090107 iteration: 60635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05316 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.1032 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.0004 Mask loss: 0.10071 RPN box loss: 0.00706 RPN score loss: 0.00581 RPN total loss: 0.01287 Total loss: 0.81087 timestamp: 1654962203.0057852 iteration: 60640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10533 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.20229 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.0004 Mask loss: 0.15662 RPN box loss: 0.02113 RPN score loss: 0.00422 RPN total loss: 0.02535 Total loss: 0.97834 timestamp: 1654962206.131118 iteration: 60645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13601 FastRCNN class loss: 0.08593 FastRCNN total loss: 0.22193 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.14138 RPN box loss: 0.00884 RPN score loss: 0.00335 RPN total loss: 0.01219 Total loss: 0.96958 timestamp: 1654962209.3761923 iteration: 60650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06452 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.11928 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.14579 RPN box loss: 0.00956 RPN score loss: 0.00615 RPN total loss: 0.01571 Total loss: 0.87486 timestamp: 1654962212.588028 iteration: 60655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06435 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.12057 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.10657 RPN box loss: 0.00746 RPN score loss: 0.00509 RPN total loss: 0.01254 Total loss: 0.83376 timestamp: 1654962215.7383442 iteration: 60660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07443 FastRCNN class loss: 0.08971 FastRCNN total loss: 0.16414 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.13591 RPN box loss: 0.01922 RPN score loss: 0.00403 RPN total loss: 0.02325 Total loss: 0.91738 timestamp: 1654962218.9186194 iteration: 60665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06866 FastRCNN class loss: 0.051 FastRCNN total loss: 0.11965 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.1178 RPN box loss: 0.00492 RPN score loss: 0.00196 RPN total loss: 0.00689 Total loss: 0.83842 timestamp: 1654962222.1415336 iteration: 60670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08003 FastRCNN class loss: 0.06496 FastRCNN total loss: 0.14498 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.10329 RPN box loss: 0.00938 RPN score loss: 0.00456 RPN total loss: 0.01394 Total loss: 0.85628 timestamp: 1654962225.357863 iteration: 60675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06006 FastRCNN class loss: 0.04125 FastRCNN total loss: 0.10131 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.0004 Mask loss: 0.13064 RPN box loss: 0.00351 RPN score loss: 0.00248 RPN total loss: 0.00599 Total loss: 0.83202 timestamp: 1654962228.561284 iteration: 60680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1376 FastRCNN class loss: 0.0752 FastRCNN total loss: 0.2128 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.09028 RPN box loss: 0.0157 RPN score loss: 0.00395 RPN total loss: 0.01965 Total loss: 0.9168 timestamp: 1654962231.7396536 iteration: 60685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1439 FastRCNN class loss: 0.08476 FastRCNN total loss: 0.22865 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.14116 RPN box loss: 0.02659 RPN score loss: 0.00337 RPN total loss: 0.02996 Total loss: 0.99385 timestamp: 1654962234.8942287 iteration: 60690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14328 FastRCNN class loss: 0.09463 FastRCNN total loss: 0.23791 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.1862 RPN box loss: 0.01544 RPN score loss: 0.00829 RPN total loss: 0.02374 Total loss: 1.04192 timestamp: 1654962238.1044612 iteration: 60695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11067 FastRCNN class loss: 0.07589 FastRCNN total loss: 0.18656 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.1837 RPN box loss: 0.02373 RPN score loss: 0.00678 RPN total loss: 0.03051 Total loss: 0.99484 timestamp: 1654962241.3122125 iteration: 60700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1621 FastRCNN class loss: 0.07611 FastRCNN total loss: 0.23821 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.16971 RPN box loss: 0.01412 RPN score loss: 0.00486 RPN total loss: 0.01899 Total loss: 1.02098 timestamp: 1654962244.5710747 iteration: 60705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04778 FastRCNN class loss: 0.04148 FastRCNN total loss: 0.08926 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.07193 RPN box loss: 0.00343 RPN score loss: 0.0073 RPN total loss: 0.01073 Total loss: 0.76598 timestamp: 1654962247.7588706 iteration: 60710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05877 FastRCNN class loss: 0.03607 FastRCNN total loss: 0.09484 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.0004 Mask loss: 0.10798 RPN box loss: 0.00499 RPN score loss: 0.00204 RPN total loss: 0.00703 Total loss: 0.80392 timestamp: 1654962250.8835883 iteration: 60715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06526 FastRCNN class loss: 0.04464 FastRCNN total loss: 0.1099 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.0004 Mask loss: 0.10413 RPN box loss: 0.01973 RPN score loss: 0.00301 RPN total loss: 0.02274 Total loss: 0.83084 timestamp: 1654962254.100992 iteration: 60720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19356 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.26222 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.0004 Mask loss: 0.10996 RPN box loss: 0.01441 RPN score loss: 0.00945 RPN total loss: 0.02385 Total loss: 0.99011 timestamp: 1654962257.288166 iteration: 60725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06295 FastRCNN class loss: 0.03349 FastRCNN total loss: 0.09644 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.0004 Mask loss: 0.11441 RPN box loss: 0.01836 RPN score loss: 0.00122 RPN total loss: 0.01958 Total loss: 0.8245 timestamp: 1654962260.4344869 iteration: 60730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08173 FastRCNN class loss: 0.04958 FastRCNN total loss: 0.13131 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.0004 Mask loss: 0.11996 RPN box loss: 0.01596 RPN score loss: 0.0022 RPN total loss: 0.01816 Total loss: 0.86349 timestamp: 1654962263.6585991 iteration: 60735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09612 FastRCNN class loss: 0.07911 FastRCNN total loss: 0.17523 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.0004 Mask loss: 0.09774 RPN box loss: 0.00657 RPN score loss: 0.00138 RPN total loss: 0.00795 Total loss: 0.87498 timestamp: 1654962266.824637 iteration: 60740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0592 FastRCNN class loss: 0.03507 FastRCNN total loss: 0.09426 L1 loss: 0.0000e+00 L2 loss: 0.59405 Learning rate: 0.0004 Mask loss: 0.08484 RPN box loss: 0.006 RPN score loss: 0.00649 RPN total loss: 0.01249 Total loss: 0.78565 timestamp: 1654962270.0353785 iteration: 60745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05043 FastRCNN class loss: 0.05226 FastRCNN total loss: 0.10269 L1 loss: 0.0000e+00 L2 loss: 0.59405 Learning rate: 0.0004 Mask loss: 0.11997 RPN box loss: 0.01394 RPN score loss: 0.00117 RPN total loss: 0.01511 Total loss: 0.83183 timestamp: 1654962273.2236197 iteration: 60750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08714 FastRCNN class loss: 0.09326 FastRCNN total loss: 0.1804 L1 loss: 0.0000e+00 L2 loss: 0.59405 Learning rate: 0.0004 Mask loss: 0.13014 RPN box loss: 0.01521 RPN score loss: 0.01227 RPN total loss: 0.02748 Total loss: 0.93207 timestamp: 1654962276.4029443 iteration: 60755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08472 FastRCNN class loss: 0.09842 FastRCNN total loss: 0.18314 L1 loss: 0.0000e+00 L2 loss: 0.59405 Learning rate: 0.0004 Mask loss: 0.13121 RPN box loss: 0.01598 RPN score loss: 0.00557 RPN total loss: 0.02155 Total loss: 0.92995 timestamp: 1654962279.6469302 iteration: 60760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09278 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.14949 L1 loss: 0.0000e+00 L2 loss: 0.59405 Learning rate: 0.0004 Mask loss: 0.1282 RPN box loss: 0.01138 RPN score loss: 0.0023 RPN total loss: 0.01368 Total loss: 0.88543 timestamp: 1654962282.8038378 iteration: 60765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10569 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.18188 L1 loss: 0.0000e+00 L2 loss: 0.59405 Learning rate: 0.0004 Mask loss: 0.16729 RPN box loss: 0.00634 RPN score loss: 0.00519 RPN total loss: 0.01154 Total loss: 0.95475 timestamp: 1654962285.9492183 iteration: 60770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15714 FastRCNN class loss: 0.08032 FastRCNN total loss: 0.23746 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.0004 Mask loss: 0.14069 RPN box loss: 0.01454 RPN score loss: 0.00303 RPN total loss: 0.01757 Total loss: 0.98977 timestamp: 1654962289.1504467 iteration: 60775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0535 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.11457 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.0004 Mask loss: 0.1117 RPN box loss: 0.01583 RPN score loss: 0.00321 RPN total loss: 0.01903 Total loss: 0.83934 timestamp: 1654962292.3190305 iteration: 60780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05371 FastRCNN class loss: 0.03275 FastRCNN total loss: 0.08646 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.0004 Mask loss: 0.14126 RPN box loss: 0.00465 RPN score loss: 0.00245 RPN total loss: 0.00711 Total loss: 0.82887 timestamp: 1654962295.5192618 iteration: 60785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08127 FastRCNN class loss: 0.06206 FastRCNN total loss: 0.14332 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.0004 Mask loss: 0.15677 RPN box loss: 0.01252 RPN score loss: 0.00821 RPN total loss: 0.02073 Total loss: 0.91486 timestamp: 1654962298.6322978 iteration: 60790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08163 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.16418 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.0004 Mask loss: 0.11022 RPN box loss: 0.01268 RPN score loss: 0.00325 RPN total loss: 0.01593 Total loss: 0.88436 timestamp: 1654962301.761024 iteration: 60795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05197 FastRCNN class loss: 0.05494 FastRCNN total loss: 0.10691 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.0004 Mask loss: 0.14551 RPN box loss: 0.01054 RPN score loss: 0.00405 RPN total loss: 0.01459 Total loss: 0.86104 timestamp: 1654962305.0272079 iteration: 60800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13637 FastRCNN class loss: 0.05561 FastRCNN total loss: 0.19198 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.0004 Mask loss: 0.0994 RPN box loss: 0.01963 RPN score loss: 0.00076 RPN total loss: 0.02038 Total loss: 0.90579 timestamp: 1654962308.2095935 iteration: 60805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12101 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.19501 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.0004 Mask loss: 0.12912 RPN box loss: 0.02013 RPN score loss: 0.00082 RPN total loss: 0.02095 Total loss: 0.93911 timestamp: 1654962311.4060025 iteration: 60810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06381 FastRCNN class loss: 0.03424 FastRCNN total loss: 0.09804 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.0004 Mask loss: 0.12585 RPN box loss: 0.00473 RPN score loss: 0.00245 RPN total loss: 0.00718 Total loss: 0.8251 timestamp: 1654962314.530347 iteration: 60815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06436 FastRCNN class loss: 0.05932 FastRCNN total loss: 0.12367 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.0004 Mask loss: 0.16585 RPN box loss: 0.01281 RPN score loss: 0.0071 RPN total loss: 0.0199 Total loss: 0.90345 timestamp: 1654962317.7833734 iteration: 60820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10253 FastRCNN class loss: 0.08778 FastRCNN total loss: 0.19031 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.0004 Mask loss: 0.16103 RPN box loss: 0.00988 RPN score loss: 0.00467 RPN total loss: 0.01456 Total loss: 0.95992 timestamp: 1654962320.9448957 iteration: 60825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10937 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.17941 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.0004 Mask loss: 0.12953 RPN box loss: 0.01159 RPN score loss: 0.00446 RPN total loss: 0.01605 Total loss: 0.91902 timestamp: 1654962324.1310437 iteration: 60830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08181 FastRCNN class loss: 0.07638 FastRCNN total loss: 0.15818 L1 loss: 0.0000e+00 L2 loss: 0.59402 Learning rate: 0.0004 Mask loss: 0.14026 RPN box loss: 0.00665 RPN score loss: 0.00447 RPN total loss: 0.01112 Total loss: 0.90358 timestamp: 1654962327.2819734 iteration: 60835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06138 FastRCNN class loss: 0.06733 FastRCNN total loss: 0.12871 L1 loss: 0.0000e+00 L2 loss: 0.59402 Learning rate: 0.0004 Mask loss: 0.09686 RPN box loss: 0.00672 RPN score loss: 0.0044 RPN total loss: 0.01112 Total loss: 0.83072 timestamp: 1654962330.4940681 iteration: 60840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10137 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.16864 L1 loss: 0.0000e+00 L2 loss: 0.59402 Learning rate: 0.0004 Mask loss: 0.11984 RPN box loss: 0.01054 RPN score loss: 0.00836 RPN total loss: 0.0189 Total loss: 0.9014 timestamp: 1654962333.6670887 iteration: 60845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05657 FastRCNN class loss: 0.05549 FastRCNN total loss: 0.11207 L1 loss: 0.0000e+00 L2 loss: 0.59402 Learning rate: 0.0004 Mask loss: 0.09856 RPN box loss: 0.00798 RPN score loss: 0.00339 RPN total loss: 0.01137 Total loss: 0.81601 timestamp: 1654962336.8101707 iteration: 60850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08793 FastRCNN class loss: 0.05213 FastRCNN total loss: 0.14006 L1 loss: 0.0000e+00 L2 loss: 0.59402 Learning rate: 0.0004 Mask loss: 0.09565 RPN box loss: 0.01669 RPN score loss: 0.00204 RPN total loss: 0.01873 Total loss: 0.84846 timestamp: 1654962339.9617567 iteration: 60855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09668 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.17398 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.0004 Mask loss: 0.11767 RPN box loss: 0.01109 RPN score loss: 0.00566 RPN total loss: 0.01676 Total loss: 0.90241 timestamp: 1654962343.147538 iteration: 60860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08863 FastRCNN class loss: 0.07099 FastRCNN total loss: 0.15962 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.0004 Mask loss: 0.12068 RPN box loss: 0.01076 RPN score loss: 0.00564 RPN total loss: 0.0164 Total loss: 0.89072 timestamp: 1654962346.323161 iteration: 60865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09373 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.15011 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.0004 Mask loss: 0.13945 RPN box loss: 0.01371 RPN score loss: 0.00271 RPN total loss: 0.01642 Total loss: 0.89999 timestamp: 1654962349.505712 iteration: 60870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11858 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.19452 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.0004 Mask loss: 0.16362 RPN box loss: 0.01169 RPN score loss: 0.00626 RPN total loss: 0.01795 Total loss: 0.9701 timestamp: 1654962352.7026827 iteration: 60875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16855 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.26766 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.0004 Mask loss: 0.15508 RPN box loss: 0.00917 RPN score loss: 0.00632 RPN total loss: 0.01549 Total loss: 1.03223 timestamp: 1654962355.9014163 iteration: 60880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11946 FastRCNN class loss: 0.10887 FastRCNN total loss: 0.22834 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.0004 Mask loss: 0.21544 RPN box loss: 0.02164 RPN score loss: 0.01223 RPN total loss: 0.03387 Total loss: 1.07165 timestamp: 1654962359.0193455 iteration: 60885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0991 FastRCNN class loss: 0.10572 FastRCNN total loss: 0.20482 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.0004 Mask loss: 0.1352 RPN box loss: 0.00809 RPN score loss: 0.00803 RPN total loss: 0.01613 Total loss: 0.95015 timestamp: 1654962362.1777008 iteration: 60890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08577 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.14883 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.0004 Mask loss: 0.17253 RPN box loss: 0.00896 RPN score loss: 0.00723 RPN total loss: 0.01619 Total loss: 0.93155 timestamp: 1654962365.4051464 iteration: 60895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0682 FastRCNN class loss: 0.04389 FastRCNN total loss: 0.1121 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.0004 Mask loss: 0.08765 RPN box loss: 0.00659 RPN score loss: 0.00526 RPN total loss: 0.01185 Total loss: 0.8056 timestamp: 1654962368.6405098 iteration: 60900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08162 FastRCNN class loss: 0.06208 FastRCNN total loss: 0.1437 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.0004 Mask loss: 0.18197 RPN box loss: 0.02148 RPN score loss: 0.01969 RPN total loss: 0.04118 Total loss: 0.96084 timestamp: 1654962371.7602334 iteration: 60905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0655 FastRCNN class loss: 0.04057 FastRCNN total loss: 0.10606 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.0004 Mask loss: 0.08864 RPN box loss: 0.00539 RPN score loss: 0.00484 RPN total loss: 0.01023 Total loss: 0.79893 timestamp: 1654962374.967452 iteration: 60910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1067 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.17022 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.0004 Mask loss: 0.17386 RPN box loss: 0.02055 RPN score loss: 0.01442 RPN total loss: 0.03496 Total loss: 0.97305 timestamp: 1654962378.1356957 iteration: 60915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07652 FastRCNN class loss: 0.07692 FastRCNN total loss: 0.15344 L1 loss: 0.0000e+00 L2 loss: 0.59399 Learning rate: 0.0004 Mask loss: 0.08816 RPN box loss: 0.01687 RPN score loss: 0.00992 RPN total loss: 0.02679 Total loss: 0.86239 timestamp: 1654962381.2725718 iteration: 60920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04101 FastRCNN class loss: 0.0375 FastRCNN total loss: 0.07851 L1 loss: 0.0000e+00 L2 loss: 0.59399 Learning rate: 0.0004 Mask loss: 0.08385 RPN box loss: 0.00782 RPN score loss: 0.00925 RPN total loss: 0.01706 Total loss: 0.77341 timestamp: 1654962384.5008616 iteration: 60925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04344 FastRCNN class loss: 0.04311 FastRCNN total loss: 0.08655 L1 loss: 0.0000e+00 L2 loss: 0.59399 Learning rate: 0.0004 Mask loss: 0.11495 RPN box loss: 0.00441 RPN score loss: 0.00385 RPN total loss: 0.00826 Total loss: 0.80374 timestamp: 1654962387.705438 iteration: 60930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10266 FastRCNN class loss: 0.05852 FastRCNN total loss: 0.16117 L1 loss: 0.0000e+00 L2 loss: 0.59399 Learning rate: 0.0004 Mask loss: 0.10026 RPN box loss: 0.01178 RPN score loss: 0.0023 RPN total loss: 0.01408 Total loss: 0.8695 timestamp: 1654962390.8072326 iteration: 60935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12773 FastRCNN class loss: 0.08731 FastRCNN total loss: 0.21504 L1 loss: 0.0000e+00 L2 loss: 0.59399 Learning rate: 0.0004 Mask loss: 0.15876 RPN box loss: 0.02124 RPN score loss: 0.01322 RPN total loss: 0.03446 Total loss: 1.00225 timestamp: 1654962394.0388947 iteration: 60940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07738 FastRCNN class loss: 0.06806 FastRCNN total loss: 0.14544 L1 loss: 0.0000e+00 L2 loss: 0.59399 Learning rate: 0.0004 Mask loss: 0.11574 RPN box loss: 0.00692 RPN score loss: 0.00487 RPN total loss: 0.0118 Total loss: 0.86696 timestamp: 1654962397.2166407 iteration: 60945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07132 FastRCNN class loss: 0.04202 FastRCNN total loss: 0.11334 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.12896 RPN box loss: 0.00645 RPN score loss: 0.00427 RPN total loss: 0.01072 Total loss: 0.84701 timestamp: 1654962400.4480855 iteration: 60950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13472 FastRCNN class loss: 0.12645 FastRCNN total loss: 0.26117 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.18873 RPN box loss: 0.01967 RPN score loss: 0.00934 RPN total loss: 0.029 Total loss: 1.07289 timestamp: 1654962403.6628127 iteration: 60955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08971 FastRCNN class loss: 0.07673 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.09299 RPN box loss: 0.0152 RPN score loss: 0.00717 RPN total loss: 0.02237 Total loss: 0.87578 timestamp: 1654962406.7872767 iteration: 60960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13881 FastRCNN class loss: 0.09789 FastRCNN total loss: 0.2367 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.14266 RPN box loss: 0.01114 RPN score loss: 0.00533 RPN total loss: 0.01647 Total loss: 0.98981 timestamp: 1654962409.9953616 iteration: 60965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09179 FastRCNN class loss: 0.06412 FastRCNN total loss: 0.15591 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.13191 RPN box loss: 0.012 RPN score loss: 0.00904 RPN total loss: 0.02104 Total loss: 0.90284 timestamp: 1654962413.1591747 iteration: 60970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08663 FastRCNN class loss: 0.05033 FastRCNN total loss: 0.13695 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.1249 RPN box loss: 0.01653 RPN score loss: 0.01412 RPN total loss: 0.03065 Total loss: 0.88647 timestamp: 1654962416.2771862 iteration: 60975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10632 FastRCNN class loss: 0.06964 FastRCNN total loss: 0.17596 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.0004 Mask loss: 0.11817 RPN box loss: 0.01436 RPN score loss: 0.00393 RPN total loss: 0.01829 Total loss: 0.90639 timestamp: 1654962419.4085832 iteration: 60980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08956 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.15117 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.0004 Mask loss: 0.10941 RPN box loss: 0.00791 RPN score loss: 0.0016 RPN total loss: 0.00951 Total loss: 0.86407 timestamp: 1654962422.6079323 iteration: 60985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0437 FastRCNN class loss: 0.0433 FastRCNN total loss: 0.087 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.0004 Mask loss: 0.16995 RPN box loss: 0.00433 RPN score loss: 0.00101 RPN total loss: 0.00534 Total loss: 0.85626 timestamp: 1654962425.7344453 iteration: 60990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1068 FastRCNN class loss: 0.09209 FastRCNN total loss: 0.19888 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.0004 Mask loss: 0.11618 RPN box loss: 0.00863 RPN score loss: 0.00391 RPN total loss: 0.01254 Total loss: 0.92158 timestamp: 1654962428.9016595 iteration: 60995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08135 FastRCNN class loss: 0.06092 FastRCNN total loss: 0.14228 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.0004 Mask loss: 0.13427 RPN box loss: 0.02376 RPN score loss: 0.00899 RPN total loss: 0.03275 Total loss: 0.90327 timestamp: 1654962432.1157482 iteration: 61000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11448 FastRCNN class loss: 0.04548 FastRCNN total loss: 0.15996 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.0004 Mask loss: 0.10781 RPN box loss: 0.01192 RPN score loss: 0.00459 RPN total loss: 0.01651 Total loss: 0.87824 timestamp: 1654962435.3121998 iteration: 61005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09126 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.14324 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.0004 Mask loss: 0.12963 RPN box loss: 0.00952 RPN score loss: 0.0053 RPN total loss: 0.01482 Total loss: 0.88165 timestamp: 1654962438.5280333 iteration: 61010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10088 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.16597 L1 loss: 0.0000e+00 L2 loss: 0.59396 Learning rate: 0.0004 Mask loss: 0.12194 RPN box loss: 0.02715 RPN score loss: 0.00324 RPN total loss: 0.03039 Total loss: 0.91227 timestamp: 1654962441.7876537 iteration: 61015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04541 FastRCNN class loss: 0.03992 FastRCNN total loss: 0.08533 L1 loss: 0.0000e+00 L2 loss: 0.59396 Learning rate: 0.0004 Mask loss: 0.11069 RPN box loss: 0.00336 RPN score loss: 0.00211 RPN total loss: 0.00547 Total loss: 0.79546 timestamp: 1654962445.058797 iteration: 61020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12819 FastRCNN class loss: 0.0995 FastRCNN total loss: 0.22768 L1 loss: 0.0000e+00 L2 loss: 0.59396 Learning rate: 0.0004 Mask loss: 0.22354 RPN box loss: 0.01639 RPN score loss: 0.00944 RPN total loss: 0.02583 Total loss: 1.07101 timestamp: 1654962448.3413494 iteration: 61025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10453 FastRCNN class loss: 0.08702 FastRCNN total loss: 0.19155 L1 loss: 0.0000e+00 L2 loss: 0.59396 Learning rate: 0.0004 Mask loss: 0.08972 RPN box loss: 0.01129 RPN score loss: 0.00465 RPN total loss: 0.01594 Total loss: 0.89117 timestamp: 1654962451.5946934 iteration: 61030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06022 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.12064 L1 loss: 0.0000e+00 L2 loss: 0.59396 Learning rate: 0.0004 Mask loss: 0.13396 RPN box loss: 0.0342 RPN score loss: 0.00746 RPN total loss: 0.04166 Total loss: 0.89022 timestamp: 1654962454.8169703 iteration: 61035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08274 FastRCNN class loss: 0.08011 FastRCNN total loss: 0.16284 L1 loss: 0.0000e+00 L2 loss: 0.59395 Learning rate: 0.0004 Mask loss: 0.15176 RPN box loss: 0.0271 RPN score loss: 0.00531 RPN total loss: 0.03242 Total loss: 0.94097 timestamp: 1654962458.077232 iteration: 61040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14683 FastRCNN class loss: 0.0896 FastRCNN total loss: 0.23643 L1 loss: 0.0000e+00 L2 loss: 0.59395 Learning rate: 0.0004 Mask loss: 0.15618 RPN box loss: 0.01639 RPN score loss: 0.00824 RPN total loss: 0.02463 Total loss: 1.01119 timestamp: 1654962461.2376652 iteration: 61045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10868 FastRCNN class loss: 0.04698 FastRCNN total loss: 0.15565 L1 loss: 0.0000e+00 L2 loss: 0.59395 Learning rate: 0.0004 Mask loss: 0.1122 RPN box loss: 0.00886 RPN score loss: 0.00185 RPN total loss: 0.01072 Total loss: 0.87252 timestamp: 1654962464.3333158 iteration: 61050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07239 FastRCNN class loss: 0.06276 FastRCNN total loss: 0.13515 L1 loss: 0.0000e+00 L2 loss: 0.59395 Learning rate: 0.0004 Mask loss: 0.15089 RPN box loss: 0.03616 RPN score loss: 0.00345 RPN total loss: 0.0396 Total loss: 0.91959 timestamp: 1654962467.5664992 iteration: 61055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09036 FastRCNN class loss: 0.04662 FastRCNN total loss: 0.13698 L1 loss: 0.0000e+00 L2 loss: 0.59395 Learning rate: 0.0004 Mask loss: 0.09505 RPN box loss: 0.00391 RPN score loss: 0.00456 RPN total loss: 0.00847 Total loss: 0.83444 timestamp: 1654962470.721632 iteration: 61060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11497 FastRCNN class loss: 0.07583 FastRCNN total loss: 0.1908 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.0004 Mask loss: 0.11995 RPN box loss: 0.00858 RPN score loss: 0.00325 RPN total loss: 0.01183 Total loss: 0.91652 timestamp: 1654962473.89886 iteration: 61065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10571 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.17462 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.0004 Mask loss: 0.1226 RPN box loss: 0.0134 RPN score loss: 0.00661 RPN total loss: 0.02 Total loss: 0.91116 timestamp: 1654962477.0311716 iteration: 61070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08583 FastRCNN class loss: 0.07848 FastRCNN total loss: 0.1643 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.0004 Mask loss: 0.1481 RPN box loss: 0.02311 RPN score loss: 0.00737 RPN total loss: 0.03049 Total loss: 0.93684 timestamp: 1654962480.2740207 iteration: 61075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09025 FastRCNN class loss: 0.04293 FastRCNN total loss: 0.13317 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.0004 Mask loss: 0.12141 RPN box loss: 0.01403 RPN score loss: 0.00208 RPN total loss: 0.01611 Total loss: 0.86464 timestamp: 1654962483.4819467 iteration: 61080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.03782 FastRCNN total loss: 0.10402 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.0004 Mask loss: 0.11323 RPN box loss: 0.00544 RPN score loss: 0.00247 RPN total loss: 0.00791 Total loss: 0.81909 timestamp: 1654962486.6910203 iteration: 61085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09558 FastRCNN class loss: 0.08866 FastRCNN total loss: 0.18424 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.0004 Mask loss: 0.15771 RPN box loss: 0.00533 RPN score loss: 0.00506 RPN total loss: 0.01039 Total loss: 0.94628 timestamp: 1654962489.882638 iteration: 61090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11428 FastRCNN class loss: 0.0743 FastRCNN total loss: 0.18858 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.0004 Mask loss: 0.15449 RPN box loss: 0.00641 RPN score loss: 0.00247 RPN total loss: 0.00888 Total loss: 0.94589 timestamp: 1654962493.0563507 iteration: 61095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09633 FastRCNN class loss: 0.08232 FastRCNN total loss: 0.17865 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.0004 Mask loss: 0.16369 RPN box loss: 0.0126 RPN score loss: 0.00269 RPN total loss: 0.01529 Total loss: 0.95156 timestamp: 1654962496.237702 iteration: 61100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09129 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.14966 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.0004 Mask loss: 0.16435 RPN box loss: 0.01665 RPN score loss: 0.00512 RPN total loss: 0.02177 Total loss: 0.92971 timestamp: 1654962499.4859161 iteration: 61105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06431 FastRCNN class loss: 0.04393 FastRCNN total loss: 0.10824 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.0004 Mask loss: 0.14074 RPN box loss: 0.01785 RPN score loss: 0.00184 RPN total loss: 0.01969 Total loss: 0.86259 timestamp: 1654962502.676614 iteration: 61110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12995 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.18891 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.0004 Mask loss: 0.15591 RPN box loss: 0.01369 RPN score loss: 0.00662 RPN total loss: 0.02031 Total loss: 0.95906 timestamp: 1654962505.9110153 iteration: 61115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11786 FastRCNN class loss: 0.08037 FastRCNN total loss: 0.19824 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.0004 Mask loss: 0.12636 RPN box loss: 0.009 RPN score loss: 0.00388 RPN total loss: 0.01289 Total loss: 0.93141 timestamp: 1654962509.111441 iteration: 61120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1045 FastRCNN class loss: 0.07465 FastRCNN total loss: 0.17915 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.0004 Mask loss: 0.10001 RPN box loss: 0.00712 RPN score loss: 0.0027 RPN total loss: 0.00982 Total loss: 0.8829 timestamp: 1654962512.318805 iteration: 61125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08896 FastRCNN class loss: 0.05438 FastRCNN total loss: 0.14334 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.0004 Mask loss: 0.12577 RPN box loss: 0.01003 RPN score loss: 0.00455 RPN total loss: 0.01458 Total loss: 0.87762 timestamp: 1654962515.4521737 iteration: 61130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10469 FastRCNN class loss: 0.03264 FastRCNN total loss: 0.13733 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.0004 Mask loss: 0.08033 RPN box loss: 0.00548 RPN score loss: 0.0009 RPN total loss: 0.00639 Total loss: 0.81797 timestamp: 1654962518.7578845 iteration: 61135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05545 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.1025 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.0004 Mask loss: 0.10931 RPN box loss: 0.02144 RPN score loss: 0.00283 RPN total loss: 0.02428 Total loss: 0.83 timestamp: 1654962522.0601497 iteration: 61140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0733 FastRCNN class loss: 0.03696 FastRCNN total loss: 0.11026 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.0004 Mask loss: 0.09951 RPN box loss: 0.00845 RPN score loss: 0.00154 RPN total loss: 0.00999 Total loss: 0.81368 timestamp: 1654962525.2615645 iteration: 61145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12362 FastRCNN class loss: 0.06117 FastRCNN total loss: 0.18479 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.0004 Mask loss: 0.09645 RPN box loss: 0.00617 RPN score loss: 0.00216 RPN total loss: 0.00833 Total loss: 0.88349 timestamp: 1654962528.42524 iteration: 61150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11111 FastRCNN class loss: 0.11077 FastRCNN total loss: 0.22188 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.0004 Mask loss: 0.15647 RPN box loss: 0.0188 RPN score loss: 0.00325 RPN total loss: 0.02205 Total loss: 0.99431 timestamp: 1654962531.6185298 iteration: 61155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.05892 FastRCNN total loss: 0.16233 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.0004 Mask loss: 0.12618 RPN box loss: 0.0106 RPN score loss: 0.00134 RPN total loss: 0.01194 Total loss: 0.89437 timestamp: 1654962534.7513664 iteration: 61160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06499 FastRCNN class loss: 0.0432 FastRCNN total loss: 0.10819 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.0004 Mask loss: 0.09603 RPN box loss: 0.00613 RPN score loss: 0.00203 RPN total loss: 0.00816 Total loss: 0.80629 timestamp: 1654962538.0102954 iteration: 61165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.15304 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.0004 Mask loss: 0.14275 RPN box loss: 0.0068 RPN score loss: 0.00343 RPN total loss: 0.01023 Total loss: 0.89993 timestamp: 1654962541.2165878 iteration: 61170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09585 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.15748 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.0004 Mask loss: 0.12783 RPN box loss: 0.01513 RPN score loss: 0.00235 RPN total loss: 0.01748 Total loss: 0.8967 timestamp: 1654962544.4468255 iteration: 61175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1505 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.21235 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.0004 Mask loss: 0.14614 RPN box loss: 0.01196 RPN score loss: 0.00416 RPN total loss: 0.01613 Total loss: 0.96853 timestamp: 1654962547.6358333 iteration: 61180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10827 FastRCNN class loss: 0.09839 FastRCNN total loss: 0.20666 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.0004 Mask loss: 0.14687 RPN box loss: 0.02587 RPN score loss: 0.00547 RPN total loss: 0.03134 Total loss: 0.97878 timestamp: 1654962550.7890337 iteration: 61185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07997 FastRCNN class loss: 0.07965 FastRCNN total loss: 0.15961 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.0004 Mask loss: 0.19886 RPN box loss: 0.00735 RPN score loss: 0.00306 RPN total loss: 0.01041 Total loss: 0.96279 timestamp: 1654962554.0152438 iteration: 61190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10254 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.17948 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.0004 Mask loss: 0.09775 RPN box loss: 0.0136 RPN score loss: 0.00583 RPN total loss: 0.01943 Total loss: 0.89055 timestamp: 1654962557.2009761 iteration: 61195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07055 FastRCNN class loss: 0.05186 FastRCNN total loss: 0.12242 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.0004 Mask loss: 0.11691 RPN box loss: 0.01805 RPN score loss: 0.00204 RPN total loss: 0.02009 Total loss: 0.85332 timestamp: 1654962560.4383311 iteration: 61200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06118 FastRCNN class loss: 0.05374 FastRCNN total loss: 0.11492 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.0004 Mask loss: 0.10588 RPN box loss: 0.0065 RPN score loss: 0.00281 RPN total loss: 0.00931 Total loss: 0.824 timestamp: 1654962563.6260645 iteration: 61205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07113 FastRCNN class loss: 0.08187 FastRCNN total loss: 0.153 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.0004 Mask loss: 0.15841 RPN box loss: 0.0099 RPN score loss: 0.00835 RPN total loss: 0.01825 Total loss: 0.92356 timestamp: 1654962566.7545295 iteration: 61210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06827 FastRCNN class loss: 0.03254 FastRCNN total loss: 0.10081 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.0004 Mask loss: 0.08772 RPN box loss: 0.01494 RPN score loss: 0.0034 RPN total loss: 0.01834 Total loss: 0.80077 timestamp: 1654962569.9141 iteration: 61215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07242 FastRCNN class loss: 0.05068 FastRCNN total loss: 0.1231 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.0004 Mask loss: 0.12033 RPN box loss: 0.00742 RPN score loss: 0.0016 RPN total loss: 0.00902 Total loss: 0.84635 timestamp: 1654962573.1230633 iteration: 61220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09627 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.16287 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.0004 Mask loss: 0.15758 RPN box loss: 0.02346 RPN score loss: 0.0045 RPN total loss: 0.02796 Total loss: 0.94231 timestamp: 1654962576.2954488 iteration: 61225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07512 FastRCNN class loss: 0.05643 FastRCNN total loss: 0.13155 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.0004 Mask loss: 0.1145 RPN box loss: 0.00714 RPN score loss: 0.0011 RPN total loss: 0.00824 Total loss: 0.84818 timestamp: 1654962579.5125616 iteration: 61230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09441 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.15625 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.0004 Mask loss: 0.12609 RPN box loss: 0.01583 RPN score loss: 0.00273 RPN total loss: 0.01856 Total loss: 0.89479 timestamp: 1654962582.806197 iteration: 61235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11541 FastRCNN class loss: 0.07951 FastRCNN total loss: 0.19493 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.0004 Mask loss: 0.17187 RPN box loss: 0.0107 RPN score loss: 0.00381 RPN total loss: 0.01451 Total loss: 0.97519 timestamp: 1654962585.8693793 iteration: 61240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10891 FastRCNN class loss: 0.08944 FastRCNN total loss: 0.19835 L1 loss: 0.0000e+00 L2 loss: 0.59388 Learning rate: 0.0004 Mask loss: 0.20173 RPN box loss: 0.01188 RPN score loss: 0.00451 RPN total loss: 0.01639 Total loss: 1.01035 timestamp: 1654962589.0208201 iteration: 61245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.096 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 0.59388 Learning rate: 0.0004 Mask loss: 0.11887 RPN box loss: 0.01064 RPN score loss: 0.00648 RPN total loss: 0.01712 Total loss: 0.89371 timestamp: 1654962592.1998956 iteration: 61250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07767 FastRCNN class loss: 0.05053 FastRCNN total loss: 0.12821 L1 loss: 0.0000e+00 L2 loss: 0.59388 Learning rate: 0.0004 Mask loss: 0.10055 RPN box loss: 0.00752 RPN score loss: 0.00647 RPN total loss: 0.01399 Total loss: 0.83663 timestamp: 1654962595.422618 iteration: 61255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08492 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.14936 L1 loss: 0.0000e+00 L2 loss: 0.59388 Learning rate: 0.0004 Mask loss: 0.1149 RPN box loss: 0.02042 RPN score loss: 0.00757 RPN total loss: 0.02799 Total loss: 0.88613 timestamp: 1654962598.6298723 iteration: 61260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12795 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.1983 L1 loss: 0.0000e+00 L2 loss: 0.59388 Learning rate: 0.0004 Mask loss: 0.14453 RPN box loss: 0.00433 RPN score loss: 0.00437 RPN total loss: 0.0087 Total loss: 0.9454 timestamp: 1654962601.8789809 iteration: 61265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10298 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.17904 L1 loss: 0.0000e+00 L2 loss: 0.59387 Learning rate: 0.0004 Mask loss: 0.12479 RPN box loss: 0.00824 RPN score loss: 0.00588 RPN total loss: 0.01412 Total loss: 0.91182 timestamp: 1654962605.097352 iteration: 61270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0585 FastRCNN class loss: 0.03847 FastRCNN total loss: 0.09697 L1 loss: 0.0000e+00 L2 loss: 0.59387 Learning rate: 0.0004 Mask loss: 0.08087 RPN box loss: 0.00443 RPN score loss: 0.00293 RPN total loss: 0.00736 Total loss: 0.77907 timestamp: 1654962608.3659174 iteration: 61275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10322 FastRCNN class loss: 0.07977 FastRCNN total loss: 0.183 L1 loss: 0.0000e+00 L2 loss: 0.59387 Learning rate: 0.0004 Mask loss: 0.09482 RPN box loss: 0.00621 RPN score loss: 0.00193 RPN total loss: 0.00815 Total loss: 0.87983 timestamp: 1654962611.6478124 iteration: 61280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10412 FastRCNN class loss: 0.06793 FastRCNN total loss: 0.17205 L1 loss: 0.0000e+00 L2 loss: 0.59387 Learning rate: 0.0004 Mask loss: 0.16486 RPN box loss: 0.03158 RPN score loss: 0.00228 RPN total loss: 0.03386 Total loss: 0.96464 timestamp: 1654962614.9543824 iteration: 61285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08883 FastRCNN class loss: 0.04754 FastRCNN total loss: 0.13637 L1 loss: 0.0000e+00 L2 loss: 0.59387 Learning rate: 0.0004 Mask loss: 0.15197 RPN box loss: 0.00948 RPN score loss: 0.00104 RPN total loss: 0.01052 Total loss: 0.89272 timestamp: 1654962618.161287 iteration: 61290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09383 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.15997 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.13336 RPN box loss: 0.01257 RPN score loss: 0.00253 RPN total loss: 0.0151 Total loss: 0.9023 timestamp: 1654962621.2875178 iteration: 61295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12732 FastRCNN class loss: 0.07858 FastRCNN total loss: 0.20589 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.10758 RPN box loss: 0.00901 RPN score loss: 0.00193 RPN total loss: 0.01094 Total loss: 0.91827 timestamp: 1654962624.4851308 iteration: 61300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14855 FastRCNN class loss: 0.07577 FastRCNN total loss: 0.22432 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.09939 RPN box loss: 0.00982 RPN score loss: 0.00461 RPN total loss: 0.01443 Total loss: 0.93201 timestamp: 1654962627.6531842 iteration: 61305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07822 FastRCNN class loss: 0.04425 FastRCNN total loss: 0.12247 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.09736 RPN box loss: 0.00963 RPN score loss: 0.00258 RPN total loss: 0.01222 Total loss: 0.82591 timestamp: 1654962630.841085 iteration: 61310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.05204 FastRCNN total loss: 0.15078 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.11484 RPN box loss: 0.00876 RPN score loss: 0.00513 RPN total loss: 0.0139 Total loss: 0.87337 timestamp: 1654962634.0175104 iteration: 61315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14521 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.21744 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.15697 RPN box loss: 0.03576 RPN score loss: 0.0066 RPN total loss: 0.04236 Total loss: 1.01063 timestamp: 1654962637.2259953 iteration: 61320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05614 FastRCNN class loss: 0.04863 FastRCNN total loss: 0.10477 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.0004 Mask loss: 0.08442 RPN box loss: 0.01158 RPN score loss: 0.00324 RPN total loss: 0.01482 Total loss: 0.79787 timestamp: 1654962640.4793093 iteration: 61325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10149 FastRCNN class loss: 0.09634 FastRCNN total loss: 0.19783 L1 loss: 0.0000e+00 L2 loss: 0.59385 Learning rate: 0.0004 Mask loss: 0.17522 RPN box loss: 0.02165 RPN score loss: 0.00646 RPN total loss: 0.02811 Total loss: 0.99501 timestamp: 1654962643.6657906 iteration: 61330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09748 FastRCNN class loss: 0.11187 FastRCNN total loss: 0.20935 L1 loss: 0.0000e+00 L2 loss: 0.59385 Learning rate: 0.0004 Mask loss: 0.16041 RPN box loss: 0.01692 RPN score loss: 0.00393 RPN total loss: 0.02085 Total loss: 0.98446 timestamp: 1654962646.8147388 iteration: 61335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04457 FastRCNN class loss: 0.03819 FastRCNN total loss: 0.08276 L1 loss: 0.0000e+00 L2 loss: 0.59385 Learning rate: 0.0004 Mask loss: 0.10076 RPN box loss: 0.01138 RPN score loss: 0.00147 RPN total loss: 0.01285 Total loss: 0.79022 timestamp: 1654962650.0317914 iteration: 61340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07674 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.15954 L1 loss: 0.0000e+00 L2 loss: 0.59385 Learning rate: 0.0004 Mask loss: 0.09627 RPN box loss: 0.00759 RPN score loss: 0.00641 RPN total loss: 0.014 Total loss: 0.86366 timestamp: 1654962653.2414746 iteration: 61345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11861 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.21565 L1 loss: 0.0000e+00 L2 loss: 0.59385 Learning rate: 0.0004 Mask loss: 0.17018 RPN box loss: 0.0108 RPN score loss: 0.00858 RPN total loss: 0.01938 Total loss: 0.99906 timestamp: 1654962656.401549 iteration: 61350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07598 FastRCNN class loss: 0.04721 FastRCNN total loss: 0.12319 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.09669 RPN box loss: 0.00644 RPN score loss: 0.00218 RPN total loss: 0.00861 Total loss: 0.82234 timestamp: 1654962659.6031275 iteration: 61355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.05717 FastRCNN total loss: 0.17625 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.10725 RPN box loss: 0.0106 RPN score loss: 0.00424 RPN total loss: 0.01483 Total loss: 0.89218 timestamp: 1654962662.8132272 iteration: 61360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08371 FastRCNN class loss: 0.07492 FastRCNN total loss: 0.15864 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.10354 RPN box loss: 0.00606 RPN score loss: 0.00129 RPN total loss: 0.00735 Total loss: 0.86337 timestamp: 1654962665.985176 iteration: 61365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04918 FastRCNN class loss: 0.02307 FastRCNN total loss: 0.07224 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.086 RPN box loss: 0.00972 RPN score loss: 0.00064 RPN total loss: 0.01036 Total loss: 0.76244 timestamp: 1654962669.1225924 iteration: 61370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0778 FastRCNN class loss: 0.05994 FastRCNN total loss: 0.13774 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.12744 RPN box loss: 0.00633 RPN score loss: 0.0031 RPN total loss: 0.00944 Total loss: 0.86846 timestamp: 1654962672.285891 iteration: 61375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09271 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.16336 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.13181 RPN box loss: 0.01072 RPN score loss: 0.00734 RPN total loss: 0.01807 Total loss: 0.90707 timestamp: 1654962675.478107 iteration: 61380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08051 FastRCNN class loss: 0.049 FastRCNN total loss: 0.12951 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.0004 Mask loss: 0.11807 RPN box loss: 0.01097 RPN score loss: 0.01177 RPN total loss: 0.02273 Total loss: 0.86415 timestamp: 1654962678.6597488 iteration: 61385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12667 FastRCNN class loss: 0.05408 FastRCNN total loss: 0.18075 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.0004 Mask loss: 0.09294 RPN box loss: 0.00606 RPN score loss: 0.00705 RPN total loss: 0.01311 Total loss: 0.88063 timestamp: 1654962681.8323245 iteration: 61390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07014 FastRCNN class loss: 0.04216 FastRCNN total loss: 0.1123 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.0004 Mask loss: 0.10364 RPN box loss: 0.01255 RPN score loss: 0.00134 RPN total loss: 0.01389 Total loss: 0.82367 timestamp: 1654962684.995897 iteration: 61395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07595 FastRCNN class loss: 0.06652 FastRCNN total loss: 0.14247 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.0004 Mask loss: 0.11469 RPN box loss: 0.00655 RPN score loss: 0.00405 RPN total loss: 0.0106 Total loss: 0.86159 timestamp: 1654962688.199236 iteration: 61400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11927 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.18214 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.0004 Mask loss: 0.11363 RPN box loss: 0.00545 RPN score loss: 0.00395 RPN total loss: 0.0094 Total loss: 0.899 timestamp: 1654962691.4187615 iteration: 61405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10263 FastRCNN class loss: 0.07863 FastRCNN total loss: 0.18126 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.0004 Mask loss: 0.16461 RPN box loss: 0.03594 RPN score loss: 0.00707 RPN total loss: 0.04301 Total loss: 0.98271 timestamp: 1654962694.600353 iteration: 61410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10183 FastRCNN class loss: 0.08285 FastRCNN total loss: 0.18468 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.0004 Mask loss: 0.10658 RPN box loss: 0.00591 RPN score loss: 0.0044 RPN total loss: 0.01031 Total loss: 0.8954 timestamp: 1654962697.8681054 iteration: 61415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12877 FastRCNN class loss: 0.11966 FastRCNN total loss: 0.24843 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.0004 Mask loss: 0.14036 RPN box loss: 0.02314 RPN score loss: 0.00532 RPN total loss: 0.02846 Total loss: 1.01107 timestamp: 1654962701.1265118 iteration: 61420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04665 FastRCNN class loss: 0.05016 FastRCNN total loss: 0.09682 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.0004 Mask loss: 0.09494 RPN box loss: 0.014 RPN score loss: 0.00116 RPN total loss: 0.01516 Total loss: 0.80074 timestamp: 1654962704.3506725 iteration: 61425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09553 FastRCNN class loss: 0.08316 FastRCNN total loss: 0.17869 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.0004 Mask loss: 0.14593 RPN box loss: 0.03209 RPN score loss: 0.01445 RPN total loss: 0.04654 Total loss: 0.96498 timestamp: 1654962707.488363 iteration: 61430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09488 FastRCNN class loss: 0.09087 FastRCNN total loss: 0.18574 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.0004 Mask loss: 0.15608 RPN box loss: 0.00833 RPN score loss: 0.00457 RPN total loss: 0.01291 Total loss: 0.94855 timestamp: 1654962710.7130206 iteration: 61435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10917 FastRCNN class loss: 0.07581 FastRCNN total loss: 0.18498 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.0004 Mask loss: 0.12215 RPN box loss: 0.01751 RPN score loss: 0.0021 RPN total loss: 0.01961 Total loss: 0.92055 timestamp: 1654962713.9058926 iteration: 61440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07859 FastRCNN class loss: 0.05418 FastRCNN total loss: 0.13277 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.0004 Mask loss: 0.11373 RPN box loss: 0.00967 RPN score loss: 0.00361 RPN total loss: 0.01327 Total loss: 0.85359 timestamp: 1654962717.1116157 iteration: 61445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10916 FastRCNN class loss: 0.06094 FastRCNN total loss: 0.17011 L1 loss: 0.0000e+00 L2 loss: 0.59381 Learning rate: 0.0004 Mask loss: 0.15912 RPN box loss: 0.01629 RPN score loss: 0.00389 RPN total loss: 0.02018 Total loss: 0.94322 timestamp: 1654962720.3133404 iteration: 61450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07005 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.13342 L1 loss: 0.0000e+00 L2 loss: 0.59381 Learning rate: 0.0004 Mask loss: 0.18401 RPN box loss: 0.00951 RPN score loss: 0.00386 RPN total loss: 0.01337 Total loss: 0.92461 timestamp: 1654962723.5502048 iteration: 61455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12153 FastRCNN class loss: 0.07736 FastRCNN total loss: 0.19889 L1 loss: 0.0000e+00 L2 loss: 0.59381 Learning rate: 0.0004 Mask loss: 0.18232 RPN box loss: 0.0102 RPN score loss: 0.00846 RPN total loss: 0.01866 Total loss: 0.99367 timestamp: 1654962726.7725537 iteration: 61460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.07389 FastRCNN total loss: 0.16867 L1 loss: 0.0000e+00 L2 loss: 0.59381 Learning rate: 0.0004 Mask loss: 0.12971 RPN box loss: 0.00507 RPN score loss: 0.00418 RPN total loss: 0.00925 Total loss: 0.90144 timestamp: 1654962729.968403 iteration: 61465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07593 FastRCNN class loss: 0.08811 FastRCNN total loss: 0.16404 L1 loss: 0.0000e+00 L2 loss: 0.59381 Learning rate: 0.0004 Mask loss: 0.14435 RPN box loss: 0.01249 RPN score loss: 0.00569 RPN total loss: 0.01818 Total loss: 0.92038 timestamp: 1654962733.230985 iteration: 61470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.10405 FastRCNN total loss: 0.18937 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.0004 Mask loss: 0.19446 RPN box loss: 0.01655 RPN score loss: 0.00662 RPN total loss: 0.02317 Total loss: 1.0008 timestamp: 1654962736.4823513 iteration: 61475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14215 FastRCNN class loss: 0.06226 FastRCNN total loss: 0.2044 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.0004 Mask loss: 0.13857 RPN box loss: 0.01052 RPN score loss: 0.00374 RPN total loss: 0.01426 Total loss: 0.95104 timestamp: 1654962739.6351323 iteration: 61480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0897 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.15501 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.0004 Mask loss: 0.10268 RPN box loss: 0.01129 RPN score loss: 0.00378 RPN total loss: 0.01507 Total loss: 0.86657 timestamp: 1654962742.7754178 iteration: 61485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09992 FastRCNN class loss: 0.09238 FastRCNN total loss: 0.1923 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.0004 Mask loss: 0.1649 RPN box loss: 0.02572 RPN score loss: 0.00946 RPN total loss: 0.03518 Total loss: 0.98618 timestamp: 1654962745.9960635 iteration: 61490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06326 FastRCNN class loss: 0.04077 FastRCNN total loss: 0.10404 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.0004 Mask loss: 0.09294 RPN box loss: 0.01702 RPN score loss: 0.00171 RPN total loss: 0.01872 Total loss: 0.8095 timestamp: 1654962749.2712283 iteration: 61495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09188 FastRCNN class loss: 0.074 FastRCNN total loss: 0.16588 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.0004 Mask loss: 0.12269 RPN box loss: 0.00622 RPN score loss: 0.00338 RPN total loss: 0.0096 Total loss: 0.89197 timestamp: 1654962752.5539298 iteration: 61500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12553 FastRCNN class loss: 0.0941 FastRCNN total loss: 0.21963 L1 loss: 0.0000e+00 L2 loss: 0.59379 Learning rate: 0.0004 Mask loss: 0.21531 RPN box loss: 0.02171 RPN score loss: 0.01045 RPN total loss: 0.03216 Total loss: 1.0609 timestamp: 1654962755.6726136 iteration: 61505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04177 FastRCNN class loss: 0.03741 FastRCNN total loss: 0.07918 L1 loss: 0.0000e+00 L2 loss: 0.59379 Learning rate: 0.0004 Mask loss: 0.1112 RPN box loss: 0.01641 RPN score loss: 0.00427 RPN total loss: 0.02067 Total loss: 0.80484 timestamp: 1654962758.8512537 iteration: 61510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0467 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.10255 L1 loss: 0.0000e+00 L2 loss: 0.59379 Learning rate: 0.0004 Mask loss: 0.16973 RPN box loss: 0.01217 RPN score loss: 0.00536 RPN total loss: 0.01753 Total loss: 0.8836 timestamp: 1654962762.0290065 iteration: 61515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12342 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.19348 L1 loss: 0.0000e+00 L2 loss: 0.59379 Learning rate: 0.0004 Mask loss: 0.09956 RPN box loss: 0.00721 RPN score loss: 0.00209 RPN total loss: 0.0093 Total loss: 0.89613 timestamp: 1654962765.260471 iteration: 61520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08605 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.16104 L1 loss: 0.0000e+00 L2 loss: 0.59379 Learning rate: 0.0004 Mask loss: 0.14558 RPN box loss: 0.00768 RPN score loss: 0.00624 RPN total loss: 0.01392 Total loss: 0.91433 timestamp: 1654962768.4395509 iteration: 61525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05066 FastRCNN class loss: 0.03906 FastRCNN total loss: 0.08971 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.0004 Mask loss: 0.14815 RPN box loss: 0.00989 RPN score loss: 0.00274 RPN total loss: 0.01262 Total loss: 0.84427 timestamp: 1654962771.7033918 iteration: 61530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10376 FastRCNN class loss: 0.06743 FastRCNN total loss: 0.17119 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.0004 Mask loss: 0.13062 RPN box loss: 0.01814 RPN score loss: 0.00725 RPN total loss: 0.0254 Total loss: 0.92099 timestamp: 1654962774.9141161 iteration: 61535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07867 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.14617 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.0004 Mask loss: 0.15451 RPN box loss: 0.01346 RPN score loss: 0.00275 RPN total loss: 0.01621 Total loss: 0.91067 timestamp: 1654962778.1472054 iteration: 61540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05049 FastRCNN class loss: 0.04581 FastRCNN total loss: 0.0963 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.0004 Mask loss: 0.14542 RPN box loss: 0.00945 RPN score loss: 0.00154 RPN total loss: 0.01099 Total loss: 0.84649 timestamp: 1654962781.3244758 iteration: 61545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.04459 FastRCNN total loss: 0.12314 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.0004 Mask loss: 0.12826 RPN box loss: 0.00971 RPN score loss: 0.00227 RPN total loss: 0.01198 Total loss: 0.85716 timestamp: 1654962784.5153806 iteration: 61550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03539 FastRCNN class loss: 0.02495 FastRCNN total loss: 0.06034 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.0004 Mask loss: 0.09663 RPN box loss: 0.00997 RPN score loss: 0.0022 RPN total loss: 0.01217 Total loss: 0.76292 timestamp: 1654962787.6936672 iteration: 61555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08469 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.14914 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.0004 Mask loss: 0.09592 RPN box loss: 0.01021 RPN score loss: 0.0016 RPN total loss: 0.0118 Total loss: 0.85064 timestamp: 1654962790.9340816 iteration: 61560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08795 FastRCNN class loss: 0.05838 FastRCNN total loss: 0.14633 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.0004 Mask loss: 0.12771 RPN box loss: 0.00394 RPN score loss: 0.00149 RPN total loss: 0.00543 Total loss: 0.87325 timestamp: 1654962794.1121747 iteration: 61565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09422 FastRCNN class loss: 0.07768 FastRCNN total loss: 0.1719 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.0004 Mask loss: 0.12359 RPN box loss: 0.01352 RPN score loss: 0.00608 RPN total loss: 0.01959 Total loss: 0.90885 timestamp: 1654962797.2958584 iteration: 61570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08833 FastRCNN class loss: 0.0951 FastRCNN total loss: 0.18343 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.0004 Mask loss: 0.16927 RPN box loss: 0.01811 RPN score loss: 0.00444 RPN total loss: 0.02255 Total loss: 0.96902 timestamp: 1654962800.3848748 iteration: 61575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10543 FastRCNN class loss: 0.11299 FastRCNN total loss: 0.21841 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.0004 Mask loss: 0.1572 RPN box loss: 0.0237 RPN score loss: 0.0056 RPN total loss: 0.0293 Total loss: 0.99868 timestamp: 1654962803.5803957 iteration: 61580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.12583 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.0004 Mask loss: 0.10551 RPN box loss: 0.00826 RPN score loss: 0.00367 RPN total loss: 0.01193 Total loss: 0.83703 timestamp: 1654962806.7410064 iteration: 61585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11573 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.17644 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.12413 RPN box loss: 0.00533 RPN score loss: 0.00526 RPN total loss: 0.01059 Total loss: 0.90492 timestamp: 1654962809.976473 iteration: 61590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08631 FastRCNN class loss: 0.0566 FastRCNN total loss: 0.14292 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.14575 RPN box loss: 0.02562 RPN score loss: 0.0098 RPN total loss: 0.03542 Total loss: 0.91785 timestamp: 1654962813.1908157 iteration: 61595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04799 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.09935 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.14197 RPN box loss: 0.00749 RPN score loss: 0.00154 RPN total loss: 0.00903 Total loss: 0.84411 timestamp: 1654962816.3760316 iteration: 61600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09628 FastRCNN class loss: 0.10257 FastRCNN total loss: 0.19885 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.17502 RPN box loss: 0.01001 RPN score loss: 0.00234 RPN total loss: 0.01235 Total loss: 0.97997 timestamp: 1654962819.6156626 iteration: 61605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17542 FastRCNN class loss: 0.13 FastRCNN total loss: 0.30543 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.15671 RPN box loss: 0.02634 RPN score loss: 0.00724 RPN total loss: 0.03358 Total loss: 1.08948 timestamp: 1654962822.8026762 iteration: 61610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10991 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.19118 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.13651 RPN box loss: 0.01418 RPN score loss: 0.00298 RPN total loss: 0.01716 Total loss: 0.93861 timestamp: 1654962825.9625006 iteration: 61615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07672 FastRCNN class loss: 0.06034 FastRCNN total loss: 0.13706 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.0004 Mask loss: 0.12685 RPN box loss: 0.00892 RPN score loss: 0.00162 RPN total loss: 0.01055 Total loss: 0.86821 timestamp: 1654962829.1340945 iteration: 61620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12391 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.19971 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.0004 Mask loss: 0.11003 RPN box loss: 0.0108 RPN score loss: 0.00163 RPN total loss: 0.01243 Total loss: 0.91593 timestamp: 1654962832.381321 iteration: 61625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14474 FastRCNN class loss: 0.10285 FastRCNN total loss: 0.24759 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.0004 Mask loss: 0.14037 RPN box loss: 0.09233 RPN score loss: 0.00465 RPN total loss: 0.09699 Total loss: 1.0787 timestamp: 1654962835.5225093 iteration: 61630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05643 FastRCNN class loss: 0.05426 FastRCNN total loss: 0.11069 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.0004 Mask loss: 0.11891 RPN box loss: 0.00886 RPN score loss: 0.005 RPN total loss: 0.01386 Total loss: 0.83721 timestamp: 1654962838.7041593 iteration: 61635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10597 FastRCNN class loss: 0.10884 FastRCNN total loss: 0.21482 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.0004 Mask loss: 0.24848 RPN box loss: 0.03187 RPN score loss: 0.04757 RPN total loss: 0.07944 Total loss: 1.13648 timestamp: 1654962841.9211915 iteration: 61640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09379 FastRCNN class loss: 0.09099 FastRCNN total loss: 0.18478 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.0004 Mask loss: 0.15466 RPN box loss: 0.01588 RPN score loss: 0.00329 RPN total loss: 0.01917 Total loss: 0.95236 timestamp: 1654962845.0983222 iteration: 61645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.096 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.15862 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.0004 Mask loss: 0.14564 RPN box loss: 0.01571 RPN score loss: 0.00552 RPN total loss: 0.02123 Total loss: 0.91923 timestamp: 1654962848.308158 iteration: 61650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09557 FastRCNN class loss: 0.0548 FastRCNN total loss: 0.15037 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.13518 RPN box loss: 0.01135 RPN score loss: 0.01144 RPN total loss: 0.02279 Total loss: 0.90208 timestamp: 1654962851.4182432 iteration: 61655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09075 FastRCNN class loss: 0.05697 FastRCNN total loss: 0.14772 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.10891 RPN box loss: 0.01136 RPN score loss: 0.00626 RPN total loss: 0.01762 Total loss: 0.868 timestamp: 1654962854.6784847 iteration: 61660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12411 FastRCNN class loss: 0.08834 FastRCNN total loss: 0.21245 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.14114 RPN box loss: 0.01334 RPN score loss: 0.00531 RPN total loss: 0.01864 Total loss: 0.96598 timestamp: 1654962857.848355 iteration: 61665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07052 FastRCNN class loss: 0.05458 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.10088 RPN box loss: 0.00802 RPN score loss: 0.00126 RPN total loss: 0.00929 Total loss: 0.82901 timestamp: 1654962861.0014052 iteration: 61670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04707 FastRCNN class loss: 0.05438 FastRCNN total loss: 0.10145 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.09582 RPN box loss: 0.00841 RPN score loss: 0.00346 RPN total loss: 0.01188 Total loss: 0.80288 timestamp: 1654962864.168062 iteration: 61675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15962 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.22597 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.11102 RPN box loss: 0.02451 RPN score loss: 0.00481 RPN total loss: 0.02932 Total loss: 0.96005 timestamp: 1654962867.3707154 iteration: 61680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08043 FastRCNN class loss: 0.0528 FastRCNN total loss: 0.13323 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.10161 RPN box loss: 0.01991 RPN score loss: 0.00358 RPN total loss: 0.02349 Total loss: 0.85207 timestamp: 1654962870.591634 iteration: 61685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09378 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.17185 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.0004 Mask loss: 0.15276 RPN box loss: 0.00455 RPN score loss: 0.00237 RPN total loss: 0.00692 Total loss: 0.92527 timestamp: 1654962873.8063047 iteration: 61690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08762 FastRCNN class loss: 0.0797 FastRCNN total loss: 0.16732 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.0004 Mask loss: 0.13293 RPN box loss: 0.01297 RPN score loss: 0.00278 RPN total loss: 0.01575 Total loss: 0.90972 timestamp: 1654962877.0577018 iteration: 61695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06824 FastRCNN class loss: 0.09333 FastRCNN total loss: 0.16157 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.0004 Mask loss: 0.12244 RPN box loss: 0.00599 RPN score loss: 0.0013 RPN total loss: 0.00729 Total loss: 0.88504 timestamp: 1654962880.255248 iteration: 61700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08939 FastRCNN class loss: 0.0695 FastRCNN total loss: 0.15889 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.0004 Mask loss: 0.11428 RPN box loss: 0.0134 RPN score loss: 0.00104 RPN total loss: 0.01444 Total loss: 0.88135 timestamp: 1654962883.4520745 iteration: 61705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12722 FastRCNN class loss: 0.1085 FastRCNN total loss: 0.23572 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.0004 Mask loss: 0.17854 RPN box loss: 0.01072 RPN score loss: 0.01048 RPN total loss: 0.0212 Total loss: 1.02919 timestamp: 1654962886.626611 iteration: 61710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07197 FastRCNN class loss: 0.08121 FastRCNN total loss: 0.15318 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.0004 Mask loss: 0.1066 RPN box loss: 0.02856 RPN score loss: 0.01045 RPN total loss: 0.03901 Total loss: 0.89251 timestamp: 1654962889.7946603 iteration: 61715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09023 FastRCNN class loss: 0.07258 FastRCNN total loss: 0.1628 L1 loss: 0.0000e+00 L2 loss: 0.59372 Learning rate: 0.0004 Mask loss: 0.1389 RPN box loss: 0.00601 RPN score loss: 0.00201 RPN total loss: 0.00802 Total loss: 0.90345 timestamp: 1654962892.9503822 iteration: 61720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0869 FastRCNN class loss: 0.04752 FastRCNN total loss: 0.13443 L1 loss: 0.0000e+00 L2 loss: 0.59372 Learning rate: 0.0004 Mask loss: 0.10173 RPN box loss: 0.00921 RPN score loss: 0.00462 RPN total loss: 0.01383 Total loss: 0.84371 timestamp: 1654962896.1222887 iteration: 61725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14439 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.23784 L1 loss: 0.0000e+00 L2 loss: 0.59372 Learning rate: 0.0004 Mask loss: 0.19618 RPN box loss: 0.02085 RPN score loss: 0.01353 RPN total loss: 0.03438 Total loss: 1.06212 timestamp: 1654962899.3333354 iteration: 61730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05139 FastRCNN class loss: 0.03516 FastRCNN total loss: 0.08654 L1 loss: 0.0000e+00 L2 loss: 0.59372 Learning rate: 0.0004 Mask loss: 0.14286 RPN box loss: 0.01149 RPN score loss: 0.00209 RPN total loss: 0.01358 Total loss: 0.8367 timestamp: 1654962902.543553 iteration: 61735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09629 FastRCNN class loss: 0.0965 FastRCNN total loss: 0.19279 L1 loss: 0.0000e+00 L2 loss: 0.59372 Learning rate: 0.0004 Mask loss: 0.12255 RPN box loss: 0.01974 RPN score loss: 0.00839 RPN total loss: 0.02813 Total loss: 0.93718 timestamp: 1654962905.7601783 iteration: 61740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1248 FastRCNN class loss: 0.06671 FastRCNN total loss: 0.19151 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.0004 Mask loss: 0.12409 RPN box loss: 0.01286 RPN score loss: 0.0019 RPN total loss: 0.01477 Total loss: 0.92408 timestamp: 1654962908.9865353 iteration: 61745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08071 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.13972 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.0004 Mask loss: 0.10279 RPN box loss: 0.00598 RPN score loss: 0.00813 RPN total loss: 0.01411 Total loss: 0.85033 timestamp: 1654962912.198027 iteration: 61750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08379 FastRCNN class loss: 0.04479 FastRCNN total loss: 0.12858 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.0004 Mask loss: 0.11428 RPN box loss: 0.01357 RPN score loss: 0.00159 RPN total loss: 0.01517 Total loss: 0.85174 timestamp: 1654962915.4243813 iteration: 61755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05527 FastRCNN class loss: 0.04201 FastRCNN total loss: 0.09728 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.0004 Mask loss: 0.09745 RPN box loss: 0.02987 RPN score loss: 0.0055 RPN total loss: 0.03537 Total loss: 0.8238 timestamp: 1654962918.6524184 iteration: 61760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10815 FastRCNN class loss: 0.09638 FastRCNN total loss: 0.20453 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.0004 Mask loss: 0.10137 RPN box loss: 0.01598 RPN score loss: 0.00487 RPN total loss: 0.02085 Total loss: 0.92046 timestamp: 1654962921.8273492 iteration: 61765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09857 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.17304 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.0004 Mask loss: 0.16776 RPN box loss: 0.01472 RPN score loss: 0.01309 RPN total loss: 0.02781 Total loss: 0.96232 timestamp: 1654962924.9237895 iteration: 61770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1265 FastRCNN class loss: 0.05595 FastRCNN total loss: 0.18245 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.0004 Mask loss: 0.13539 RPN box loss: 0.00796 RPN score loss: 0.01339 RPN total loss: 0.02134 Total loss: 0.93288 timestamp: 1654962928.1866174 iteration: 61775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13642 FastRCNN class loss: 0.03997 FastRCNN total loss: 0.17638 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.0004 Mask loss: 0.15925 RPN box loss: 0.01166 RPN score loss: 0.00562 RPN total loss: 0.01729 Total loss: 0.94663 timestamp: 1654962931.4244158 iteration: 61780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13338 FastRCNN class loss: 0.06251 FastRCNN total loss: 0.19588 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.0004 Mask loss: 0.11502 RPN box loss: 0.05898 RPN score loss: 0.0058 RPN total loss: 0.06478 Total loss: 0.96939 timestamp: 1654962934.624758 iteration: 61785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06504 FastRCNN class loss: 0.03979 FastRCNN total loss: 0.10482 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.0004 Mask loss: 0.12006 RPN box loss: 0.00587 RPN score loss: 0.00274 RPN total loss: 0.00861 Total loss: 0.82719 timestamp: 1654962937.837016 iteration: 61790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13054 FastRCNN class loss: 0.07715 FastRCNN total loss: 0.20769 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.0004 Mask loss: 0.14799 RPN box loss: 0.02119 RPN score loss: 0.00287 RPN total loss: 0.02406 Total loss: 0.97343 timestamp: 1654962941.0090446 iteration: 61795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05389 FastRCNN class loss: 0.03619 FastRCNN total loss: 0.09009 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.0004 Mask loss: 0.12556 RPN box loss: 0.01785 RPN score loss: 0.0018 RPN total loss: 0.01964 Total loss: 0.82898 timestamp: 1654962944.2537541 iteration: 61800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11737 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.19492 L1 loss: 0.0000e+00 L2 loss: 0.59369 Learning rate: 0.0004 Mask loss: 0.1626 RPN box loss: 0.01558 RPN score loss: 0.00581 RPN total loss: 0.02139 Total loss: 0.97261 timestamp: 1654962947.3728158 iteration: 61805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07162 FastRCNN class loss: 0.05803 FastRCNN total loss: 0.12965 L1 loss: 0.0000e+00 L2 loss: 0.59369 Learning rate: 0.0004 Mask loss: 0.11098 RPN box loss: 0.00619 RPN score loss: 0.00447 RPN total loss: 0.01065 Total loss: 0.84498 timestamp: 1654962950.4798715 iteration: 61810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11257 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.17039 L1 loss: 0.0000e+00 L2 loss: 0.59369 Learning rate: 0.0004 Mask loss: 0.0895 RPN box loss: 0.00448 RPN score loss: 0.00204 RPN total loss: 0.00653 Total loss: 0.86011 timestamp: 1654962953.6447325 iteration: 61815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13308 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.19246 L1 loss: 0.0000e+00 L2 loss: 0.59369 Learning rate: 0.0004 Mask loss: 0.12476 RPN box loss: 0.01117 RPN score loss: 0.00285 RPN total loss: 0.01403 Total loss: 0.92494 timestamp: 1654962956.8036346 iteration: 61820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10809 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.18853 L1 loss: 0.0000e+00 L2 loss: 0.59369 Learning rate: 0.0004 Mask loss: 0.12563 RPN box loss: 0.00652 RPN score loss: 0.0023 RPN total loss: 0.00883 Total loss: 0.91667 timestamp: 1654962959.9413395 iteration: 61825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11336 FastRCNN class loss: 0.08859 FastRCNN total loss: 0.20195 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.0004 Mask loss: 0.19272 RPN box loss: 0.0161 RPN score loss: 0.00535 RPN total loss: 0.02145 Total loss: 1.0098 timestamp: 1654962963.1900465 iteration: 61830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09117 FastRCNN class loss: 0.04753 FastRCNN total loss: 0.1387 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.0004 Mask loss: 0.11278 RPN box loss: 0.0289 RPN score loss: 0.00334 RPN total loss: 0.03224 Total loss: 0.8774 timestamp: 1654962966.4056494 iteration: 61835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16168 FastRCNN class loss: 0.07645 FastRCNN total loss: 0.23814 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.0004 Mask loss: 0.10261 RPN box loss: 0.00779 RPN score loss: 0.00373 RPN total loss: 0.01151 Total loss: 0.94594 timestamp: 1654962969.6079483 iteration: 61840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07402 FastRCNN class loss: 0.04577 FastRCNN total loss: 0.11979 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.0004 Mask loss: 0.08245 RPN box loss: 0.00733 RPN score loss: 0.00206 RPN total loss: 0.00939 Total loss: 0.80531 timestamp: 1654962972.8359733 iteration: 61845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04806 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.10655 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.0004 Mask loss: 0.0811 RPN box loss: 0.0084 RPN score loss: 0.0056 RPN total loss: 0.014 Total loss: 0.79532 timestamp: 1654962976.1002657 iteration: 61850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08198 FastRCNN class loss: 0.07492 FastRCNN total loss: 0.1569 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.0004 Mask loss: 0.14623 RPN box loss: 0.04541 RPN score loss: 0.00613 RPN total loss: 0.05154 Total loss: 0.94834 timestamp: 1654962979.3758419 iteration: 61855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08418 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.13623 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.0004 Mask loss: 0.1069 RPN box loss: 0.00842 RPN score loss: 0.00085 RPN total loss: 0.00927 Total loss: 0.84607 timestamp: 1654962982.6057136 iteration: 61860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09015 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.15521 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.0004 Mask loss: 0.12365 RPN box loss: 0.0253 RPN score loss: 0.0019 RPN total loss: 0.0272 Total loss: 0.89974 timestamp: 1654962985.7945166 iteration: 61865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08024 FastRCNN class loss: 0.09166 FastRCNN total loss: 0.1719 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.0004 Mask loss: 0.14606 RPN box loss: 0.0104 RPN score loss: 0.0037 RPN total loss: 0.01411 Total loss: 0.92574 timestamp: 1654962988.9762657 iteration: 61870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11099 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.17414 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.0004 Mask loss: 0.16197 RPN box loss: 0.00455 RPN score loss: 0.00818 RPN total loss: 0.01273 Total loss: 0.9425 timestamp: 1654962992.1015918 iteration: 61875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04735 FastRCNN class loss: 0.04652 FastRCNN total loss: 0.09387 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.0004 Mask loss: 0.12052 RPN box loss: 0.00625 RPN score loss: 0.00165 RPN total loss: 0.0079 Total loss: 0.81595 timestamp: 1654962995.2436013 iteration: 61880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04548 FastRCNN class loss: 0.03873 FastRCNN total loss: 0.08421 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.0004 Mask loss: 0.14529 RPN box loss: 0.00612 RPN score loss: 0.00376 RPN total loss: 0.00989 Total loss: 0.83305 timestamp: 1654962998.5544488 iteration: 61885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07469 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.13147 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.0004 Mask loss: 0.19005 RPN box loss: 0.00557 RPN score loss: 0.00294 RPN total loss: 0.00851 Total loss: 0.92369 timestamp: 1654963001.7010574 iteration: 61890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05286 FastRCNN class loss: 0.05553 FastRCNN total loss: 0.10839 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.0004 Mask loss: 0.11507 RPN box loss: 0.00976 RPN score loss: 0.00578 RPN total loss: 0.01554 Total loss: 0.83266 timestamp: 1654963004.928828 iteration: 61895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10391 FastRCNN class loss: 0.06221 FastRCNN total loss: 0.16612 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.0004 Mask loss: 0.14993 RPN box loss: 0.04174 RPN score loss: 0.00359 RPN total loss: 0.04533 Total loss: 0.95504 timestamp: 1654963008.0861206 iteration: 61900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0724 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.12741 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.0004 Mask loss: 0.12634 RPN box loss: 0.00432 RPN score loss: 0.01182 RPN total loss: 0.01614 Total loss: 0.86355 timestamp: 1654963011.2315297 iteration: 61905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09158 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.15563 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.0004 Mask loss: 0.11891 RPN box loss: 0.01406 RPN score loss: 0.00466 RPN total loss: 0.01872 Total loss: 0.88692 timestamp: 1654963014.4389026 iteration: 61910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09846 FastRCNN class loss: 0.12631 FastRCNN total loss: 0.22477 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.0004 Mask loss: 0.21316 RPN box loss: 0.01749 RPN score loss: 0.00574 RPN total loss: 0.02323 Total loss: 1.05482 timestamp: 1654963017.5844822 iteration: 61915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07009 FastRCNN class loss: 0.04515 FastRCNN total loss: 0.11524 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.0004 Mask loss: 0.10525 RPN box loss: 0.00562 RPN score loss: 0.00297 RPN total loss: 0.00859 Total loss: 0.82273 timestamp: 1654963020.759303 iteration: 61920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09246 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.14696 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.0004 Mask loss: 0.10721 RPN box loss: 0.00446 RPN score loss: 0.00576 RPN total loss: 0.01023 Total loss: 0.85805 timestamp: 1654963024.0446134 iteration: 61925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1072 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.15658 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.0004 Mask loss: 0.15952 RPN box loss: 0.00994 RPN score loss: 0.00248 RPN total loss: 0.01242 Total loss: 0.92217 timestamp: 1654963027.1772473 iteration: 61930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.08468 FastRCNN total loss: 0.20376 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.0004 Mask loss: 0.12534 RPN box loss: 0.00281 RPN score loss: 0.00269 RPN total loss: 0.00551 Total loss: 0.92826 timestamp: 1654963030.3424397 iteration: 61935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14103 FastRCNN class loss: 0.08172 FastRCNN total loss: 0.22276 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.0004 Mask loss: 0.16938 RPN box loss: 0.02391 RPN score loss: 0.01511 RPN total loss: 0.03902 Total loss: 1.0248 timestamp: 1654963033.6336455 iteration: 61940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06693 FastRCNN class loss: 0.07631 FastRCNN total loss: 0.14324 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.0004 Mask loss: 0.12936 RPN box loss: 0.00898 RPN score loss: 0.00368 RPN total loss: 0.01266 Total loss: 0.87891 timestamp: 1654963036.8770578 iteration: 61945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06513 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.12046 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.0004 Mask loss: 0.09893 RPN box loss: 0.01155 RPN score loss: 0.00402 RPN total loss: 0.01557 Total loss: 0.8286 timestamp: 1654963040.0268273 iteration: 61950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08973 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.13868 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.0004 Mask loss: 0.13897 RPN box loss: 0.03261 RPN score loss: 0.00534 RPN total loss: 0.03795 Total loss: 0.90924 timestamp: 1654963043.2326415 iteration: 61955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09254 FastRCNN class loss: 0.08441 FastRCNN total loss: 0.17695 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.0004 Mask loss: 0.11026 RPN box loss: 0.00844 RPN score loss: 0.00569 RPN total loss: 0.01412 Total loss: 0.89498 timestamp: 1654963046.3989341 iteration: 61960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04955 FastRCNN class loss: 0.05201 FastRCNN total loss: 0.10156 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.0004 Mask loss: 0.11308 RPN box loss: 0.01144 RPN score loss: 0.00337 RPN total loss: 0.01481 Total loss: 0.82309 timestamp: 1654963049.5648057 iteration: 61965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09982 FastRCNN class loss: 0.09482 FastRCNN total loss: 0.19464 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.0004 Mask loss: 0.1475 RPN box loss: 0.02849 RPN score loss: 0.0059 RPN total loss: 0.03439 Total loss: 0.97017 timestamp: 1654963052.750659 iteration: 61970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07484 FastRCNN class loss: 0.04929 FastRCNN total loss: 0.12413 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.0004 Mask loss: 0.12362 RPN box loss: 0.0112 RPN score loss: 0.00336 RPN total loss: 0.01456 Total loss: 0.85595 timestamp: 1654963056.0065126 iteration: 61975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08427 FastRCNN class loss: 0.10486 FastRCNN total loss: 0.18913 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.0004 Mask loss: 0.17116 RPN box loss: 0.01451 RPN score loss: 0.0112 RPN total loss: 0.02571 Total loss: 0.97963 timestamp: 1654963059.2099423 iteration: 61980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05646 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.12527 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.0004 Mask loss: 0.12877 RPN box loss: 0.0043 RPN score loss: 0.00551 RPN total loss: 0.00981 Total loss: 0.85748 timestamp: 1654963062.4630237 iteration: 61985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09128 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.16446 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.0004 Mask loss: 0.14269 RPN box loss: 0.011 RPN score loss: 0.0051 RPN total loss: 0.0161 Total loss: 0.91688 timestamp: 1654963065.5829172 iteration: 61990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09085 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.1644 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.0004 Mask loss: 0.17437 RPN box loss: 0.0316 RPN score loss: 0.00424 RPN total loss: 0.03584 Total loss: 0.96824 timestamp: 1654963068.7557368 iteration: 61995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08082 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.0004 Mask loss: 0.13134 RPN box loss: 0.02954 RPN score loss: 0.0044 RPN total loss: 0.03394 Total loss: 0.88816 timestamp: 1654963071.920671 iteration: 62000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09428 FastRCNN class loss: 0.07216 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.12331 RPN box loss: 0.00648 RPN score loss: 0.00182 RPN total loss: 0.00831 Total loss: 0.89167 timestamp: 1654963075.0840845 iteration: 62005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0848 FastRCNN class loss: 0.05339 FastRCNN total loss: 0.13819 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.13573 RPN box loss: 0.00329 RPN score loss: 0.00219 RPN total loss: 0.00549 Total loss: 0.87303 timestamp: 1654963078.2628124 iteration: 62010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13151 FastRCNN class loss: 0.07072 FastRCNN total loss: 0.20223 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.23185 RPN box loss: 0.01472 RPN score loss: 0.00522 RPN total loss: 0.01994 Total loss: 1.04765 timestamp: 1654963081.4677398 iteration: 62015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09773 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.16311 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.1527 RPN box loss: 0.01364 RPN score loss: 0.0072 RPN total loss: 0.02084 Total loss: 0.93027 timestamp: 1654963084.6822228 iteration: 62020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10192 FastRCNN class loss: 0.09416 FastRCNN total loss: 0.19609 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.15207 RPN box loss: 0.03637 RPN score loss: 0.00556 RPN total loss: 0.04193 Total loss: 0.98371 timestamp: 1654963087.8962002 iteration: 62025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11585 FastRCNN class loss: 0.09101 FastRCNN total loss: 0.20686 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.13485 RPN box loss: 0.01745 RPN score loss: 0.01012 RPN total loss: 0.02757 Total loss: 0.96289 timestamp: 1654963091.0569758 iteration: 62030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12351 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.2034 L1 loss: 0.0000e+00 L2 loss: 0.59362 Learning rate: 0.0004 Mask loss: 0.14364 RPN box loss: 0.0108 RPN score loss: 0.00321 RPN total loss: 0.01401 Total loss: 0.95466 timestamp: 1654963094.2286475 iteration: 62035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06432 FastRCNN class loss: 0.0409 FastRCNN total loss: 0.10522 L1 loss: 0.0000e+00 L2 loss: 0.59361 Learning rate: 0.0004 Mask loss: 0.082 RPN box loss: 0.01481 RPN score loss: 0.00383 RPN total loss: 0.01864 Total loss: 0.79948 timestamp: 1654963097.4527693 iteration: 62040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0983 FastRCNN class loss: 0.0514 FastRCNN total loss: 0.1497 L1 loss: 0.0000e+00 L2 loss: 0.59361 Learning rate: 0.0004 Mask loss: 0.08959 RPN box loss: 0.01284 RPN score loss: 0.00548 RPN total loss: 0.01832 Total loss: 0.85122 timestamp: 1654963100.6532667 iteration: 62045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.19533 L1 loss: 0.0000e+00 L2 loss: 0.59361 Learning rate: 0.0004 Mask loss: 0.13695 RPN box loss: 0.04584 RPN score loss: 0.00948 RPN total loss: 0.05532 Total loss: 0.98121 timestamp: 1654963103.8752666 iteration: 62050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08719 FastRCNN class loss: 0.03285 FastRCNN total loss: 0.12004 L1 loss: 0.0000e+00 L2 loss: 0.59361 Learning rate: 0.0004 Mask loss: 0.13023 RPN box loss: 0.0071 RPN score loss: 0.0059 RPN total loss: 0.013 Total loss: 0.85688 timestamp: 1654963107.0721023 iteration: 62055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08211 FastRCNN class loss: 0.07762 FastRCNN total loss: 0.15973 L1 loss: 0.0000e+00 L2 loss: 0.59361 Learning rate: 0.0004 Mask loss: 0.14409 RPN box loss: 0.0164 RPN score loss: 0.00367 RPN total loss: 0.02007 Total loss: 0.91749 timestamp: 1654963110.260486 iteration: 62060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14159 FastRCNN class loss: 0.09767 FastRCNN total loss: 0.23926 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.12547 RPN box loss: 0.0068 RPN score loss: 0.0037 RPN total loss: 0.0105 Total loss: 0.96884 timestamp: 1654963113.4641998 iteration: 62065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06425 FastRCNN class loss: 0.07342 FastRCNN total loss: 0.13767 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.1175 RPN box loss: 0.00809 RPN score loss: 0.01069 RPN total loss: 0.01878 Total loss: 0.86754 timestamp: 1654963116.6930873 iteration: 62070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09509 FastRCNN class loss: 0.05121 FastRCNN total loss: 0.1463 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.10512 RPN box loss: 0.00344 RPN score loss: 0.00118 RPN total loss: 0.00462 Total loss: 0.84964 timestamp: 1654963119.8684366 iteration: 62075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07193 FastRCNN class loss: 0.04301 FastRCNN total loss: 0.11495 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.13035 RPN box loss: 0.01221 RPN score loss: 0.00777 RPN total loss: 0.01999 Total loss: 0.85888 timestamp: 1654963123.0695558 iteration: 62080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07021 FastRCNN class loss: 0.03313 FastRCNN total loss: 0.10334 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.08832 RPN box loss: 0.01141 RPN score loss: 0.00268 RPN total loss: 0.01408 Total loss: 0.79934 timestamp: 1654963126.1655724 iteration: 62085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08886 FastRCNN class loss: 0.0593 FastRCNN total loss: 0.14816 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.13645 RPN box loss: 0.00604 RPN score loss: 0.00224 RPN total loss: 0.00827 Total loss: 0.88648 timestamp: 1654963129.3494506 iteration: 62090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.17614 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.0004 Mask loss: 0.15199 RPN box loss: 0.02935 RPN score loss: 0.01394 RPN total loss: 0.04329 Total loss: 0.96502 timestamp: 1654963132.5584948 iteration: 62095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06852 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.13778 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.0004 Mask loss: 0.18528 RPN box loss: 0.00678 RPN score loss: 0.00553 RPN total loss: 0.01231 Total loss: 0.92896 timestamp: 1654963135.771451 iteration: 62100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.17136 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.0004 Mask loss: 0.13163 RPN box loss: 0.01421 RPN score loss: 0.00741 RPN total loss: 0.02162 Total loss: 0.9182 timestamp: 1654963138.9408934 iteration: 62105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10078 FastRCNN class loss: 0.05139 FastRCNN total loss: 0.15217 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.0004 Mask loss: 0.13995 RPN box loss: 0.01092 RPN score loss: 0.00294 RPN total loss: 0.01386 Total loss: 0.89958 timestamp: 1654963142.131858 iteration: 62110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09695 FastRCNN class loss: 0.06598 FastRCNN total loss: 0.16293 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.0004 Mask loss: 0.11248 RPN box loss: 0.01281 RPN score loss: 0.00665 RPN total loss: 0.01946 Total loss: 0.88847 timestamp: 1654963145.3500836 iteration: 62115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13645 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.21471 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.0004 Mask loss: 0.12855 RPN box loss: 0.0163 RPN score loss: 0.00268 RPN total loss: 0.01897 Total loss: 0.95582 timestamp: 1654963148.5213175 iteration: 62120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11494 FastRCNN class loss: 0.05566 FastRCNN total loss: 0.1706 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.0004 Mask loss: 0.12619 RPN box loss: 0.01164 RPN score loss: 0.00552 RPN total loss: 0.01716 Total loss: 0.90754 timestamp: 1654963151.7260056 iteration: 62125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05971 FastRCNN class loss: 0.08529 FastRCNN total loss: 0.145 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.0004 Mask loss: 0.13508 RPN box loss: 0.01163 RPN score loss: 0.00232 RPN total loss: 0.01395 Total loss: 0.88761 timestamp: 1654963154.9573011 iteration: 62130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10346 FastRCNN class loss: 0.04388 FastRCNN total loss: 0.14734 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.0004 Mask loss: 0.07917 RPN box loss: 0.00377 RPN score loss: 0.00145 RPN total loss: 0.00522 Total loss: 0.82532 timestamp: 1654963158.1380997 iteration: 62135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07149 FastRCNN class loss: 0.04515 FastRCNN total loss: 0.11665 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.0004 Mask loss: 0.10744 RPN box loss: 0.008 RPN score loss: 0.00326 RPN total loss: 0.01126 Total loss: 0.82893 timestamp: 1654963161.3098717 iteration: 62140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11275 FastRCNN class loss: 0.07786 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.0004 Mask loss: 0.12655 RPN box loss: 0.01381 RPN score loss: 0.00882 RPN total loss: 0.02263 Total loss: 0.93337 timestamp: 1654963164.5120366 iteration: 62145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.11029 FastRCNN total loss: 0.26167 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.0004 Mask loss: 0.17123 RPN box loss: 0.02995 RPN score loss: 0.011 RPN total loss: 0.04095 Total loss: 1.06743 timestamp: 1654963167.6844168 iteration: 62150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09424 FastRCNN class loss: 0.10436 FastRCNN total loss: 0.1986 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.0004 Mask loss: 0.11234 RPN box loss: 0.02461 RPN score loss: 0.00528 RPN total loss: 0.02989 Total loss: 0.93441 timestamp: 1654963170.8780437 iteration: 62155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.1634 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.0004 Mask loss: 0.13611 RPN box loss: 0.01624 RPN score loss: 0.00554 RPN total loss: 0.02179 Total loss: 0.91487 timestamp: 1654963174.0949876 iteration: 62160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06524 FastRCNN class loss: 0.09402 FastRCNN total loss: 0.15926 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.0004 Mask loss: 0.0911 RPN box loss: 0.0185 RPN score loss: 0.00746 RPN total loss: 0.02595 Total loss: 0.86989 timestamp: 1654963177.253484 iteration: 62165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09007 FastRCNN class loss: 0.04479 FastRCNN total loss: 0.13485 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.0004 Mask loss: 0.13875 RPN box loss: 0.00487 RPN score loss: 0.00458 RPN total loss: 0.00945 Total loss: 0.87662 timestamp: 1654963180.429773 iteration: 62170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08393 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.14295 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.0004 Mask loss: 0.13646 RPN box loss: 0.03096 RPN score loss: 0.00544 RPN total loss: 0.0364 Total loss: 0.90937 timestamp: 1654963183.5168412 iteration: 62175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04673 FastRCNN class loss: 0.05389 FastRCNN total loss: 0.10062 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.0004 Mask loss: 0.11866 RPN box loss: 0.01376 RPN score loss: 0.00248 RPN total loss: 0.01624 Total loss: 0.8291 timestamp: 1654963186.6977348 iteration: 62180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12514 FastRCNN class loss: 0.13638 FastRCNN total loss: 0.26152 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.0004 Mask loss: 0.11406 RPN box loss: 0.01417 RPN score loss: 0.00629 RPN total loss: 0.02046 Total loss: 0.98961 timestamp: 1654963189.915104 iteration: 62185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08576 FastRCNN class loss: 0.03973 FastRCNN total loss: 0.12549 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.0004 Mask loss: 0.11555 RPN box loss: 0.00344 RPN score loss: 0.00496 RPN total loss: 0.00841 Total loss: 0.84302 timestamp: 1654963193.131686 iteration: 62190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11625 FastRCNN class loss: 0.06737 FastRCNN total loss: 0.18362 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.0004 Mask loss: 0.1206 RPN box loss: 0.01998 RPN score loss: 0.00775 RPN total loss: 0.02772 Total loss: 0.92551 timestamp: 1654963196.4171166 iteration: 62195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1264 FastRCNN class loss: 0.06797 FastRCNN total loss: 0.19437 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.0004 Mask loss: 0.25172 RPN box loss: 0.00759 RPN score loss: 0.00284 RPN total loss: 0.01043 Total loss: 1.05008 timestamp: 1654963199.6587062 iteration: 62200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07992 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.1378 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.0004 Mask loss: 0.09145 RPN box loss: 0.00609 RPN score loss: 0.00166 RPN total loss: 0.00775 Total loss: 0.83056 timestamp: 1654963202.8593369 iteration: 62205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04034 FastRCNN class loss: 0.03187 FastRCNN total loss: 0.07222 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.0004 Mask loss: 0.1098 RPN box loss: 0.01108 RPN score loss: 0.00811 RPN total loss: 0.01919 Total loss: 0.79477 timestamp: 1654963206.0298223 iteration: 62210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09621 FastRCNN class loss: 0.08473 FastRCNN total loss: 0.18094 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.0004 Mask loss: 0.19131 RPN box loss: 0.02096 RPN score loss: 0.0141 RPN total loss: 0.03506 Total loss: 1.00087 timestamp: 1654963209.291068 iteration: 62215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07659 FastRCNN class loss: 0.09702 FastRCNN total loss: 0.17361 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.0004 Mask loss: 0.15422 RPN box loss: 0.00928 RPN score loss: 0.00615 RPN total loss: 0.01543 Total loss: 0.9368 timestamp: 1654963212.5356886 iteration: 62220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14286 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.22125 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.0004 Mask loss: 0.09548 RPN box loss: 0.01244 RPN score loss: 0.00474 RPN total loss: 0.01719 Total loss: 0.92747 timestamp: 1654963215.7259471 iteration: 62225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10837 FastRCNN class loss: 0.06547 FastRCNN total loss: 0.17384 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.0004 Mask loss: 0.10184 RPN box loss: 0.02567 RPN score loss: 0.00862 RPN total loss: 0.03429 Total loss: 0.90352 timestamp: 1654963218.9160166 iteration: 62230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.04246 FastRCNN total loss: 0.17657 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.0004 Mask loss: 0.13716 RPN box loss: 0.01133 RPN score loss: 0.0022 RPN total loss: 0.01353 Total loss: 0.92082 timestamp: 1654963222.0921872 iteration: 62235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06018 FastRCNN class loss: 0.06691 FastRCNN total loss: 0.12709 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.0004 Mask loss: 0.09068 RPN box loss: 0.01219 RPN score loss: 0.00889 RPN total loss: 0.02108 Total loss: 0.83239 timestamp: 1654963225.3368554 iteration: 62240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08423 FastRCNN class loss: 0.06931 FastRCNN total loss: 0.15354 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.0004 Mask loss: 0.16088 RPN box loss: 0.01055 RPN score loss: 0.00609 RPN total loss: 0.01664 Total loss: 0.9246 timestamp: 1654963228.6041186 iteration: 62245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05503 FastRCNN class loss: 0.04693 FastRCNN total loss: 0.10195 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.0004 Mask loss: 0.12804 RPN box loss: 0.01 RPN score loss: 0.00168 RPN total loss: 0.01169 Total loss: 0.83522 timestamp: 1654963231.7931578 iteration: 62250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13636 FastRCNN class loss: 0.06325 FastRCNN total loss: 0.1996 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.0004 Mask loss: 0.10591 RPN box loss: 0.03479 RPN score loss: 0.0064 RPN total loss: 0.04119 Total loss: 0.94024 timestamp: 1654963235.0408392 iteration: 62255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07082 FastRCNN class loss: 0.03915 FastRCNN total loss: 0.10997 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.0004 Mask loss: 0.1194 RPN box loss: 0.00687 RPN score loss: 0.00416 RPN total loss: 0.01103 Total loss: 0.83395 timestamp: 1654963238.3128116 iteration: 62260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12085 FastRCNN class loss: 0.11266 FastRCNN total loss: 0.2335 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.0004 Mask loss: 0.21372 RPN box loss: 0.01262 RPN score loss: 0.00626 RPN total loss: 0.01889 Total loss: 1.05965 timestamp: 1654963241.4322739 iteration: 62265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07612 FastRCNN class loss: 0.07409 FastRCNN total loss: 0.15021 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.0004 Mask loss: 0.11222 RPN box loss: 0.02934 RPN score loss: 0.0039 RPN total loss: 0.03324 Total loss: 0.8892 timestamp: 1654963244.6045961 iteration: 62270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10638 FastRCNN class loss: 0.03839 FastRCNN total loss: 0.14476 L1 loss: 0.0000e+00 L2 loss: 0.59353 Learning rate: 0.0004 Mask loss: 0.11893 RPN box loss: 0.01621 RPN score loss: 0.00158 RPN total loss: 0.01779 Total loss: 0.87502 timestamp: 1654963247.7694523 iteration: 62275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03839 FastRCNN class loss: 0.05012 FastRCNN total loss: 0.0885 L1 loss: 0.0000e+00 L2 loss: 0.59353 Learning rate: 0.0004 Mask loss: 0.09104 RPN box loss: 0.01614 RPN score loss: 0.00636 RPN total loss: 0.0225 Total loss: 0.79557 timestamp: 1654963250.9126308 iteration: 62280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06147 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.12743 L1 loss: 0.0000e+00 L2 loss: 0.59353 Learning rate: 0.0004 Mask loss: 0.10457 RPN box loss: 0.00706 RPN score loss: 0.00169 RPN total loss: 0.00875 Total loss: 0.83428 timestamp: 1654963254.077124 iteration: 62285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11517 FastRCNN class loss: 0.08473 FastRCNN total loss: 0.19991 L1 loss: 0.0000e+00 L2 loss: 0.59353 Learning rate: 0.0004 Mask loss: 0.12761 RPN box loss: 0.00843 RPN score loss: 0.00664 RPN total loss: 0.01507 Total loss: 0.93612 timestamp: 1654963257.2611833 iteration: 62290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15382 FastRCNN class loss: 0.06303 FastRCNN total loss: 0.21685 L1 loss: 0.0000e+00 L2 loss: 0.59353 Learning rate: 0.0004 Mask loss: 0.1141 RPN box loss: 0.00648 RPN score loss: 0.00251 RPN total loss: 0.00898 Total loss: 0.93346 timestamp: 1654963260.4415958 iteration: 62295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17223 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.22977 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.0004 Mask loss: 0.14428 RPN box loss: 0.01024 RPN score loss: 0.00225 RPN total loss: 0.01248 Total loss: 0.98006 timestamp: 1654963263.6262147 iteration: 62300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10209 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.1767 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.0004 Mask loss: 0.10261 RPN box loss: 0.00502 RPN score loss: 0.0043 RPN total loss: 0.00932 Total loss: 0.88215 timestamp: 1654963266.8266144 iteration: 62305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07325 FastRCNN class loss: 0.06667 FastRCNN total loss: 0.13992 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.0004 Mask loss: 0.1555 RPN box loss: 0.01098 RPN score loss: 0.00298 RPN total loss: 0.01396 Total loss: 0.9029 timestamp: 1654963269.9841561 iteration: 62310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04312 FastRCNN class loss: 0.04399 FastRCNN total loss: 0.08711 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.0004 Mask loss: 0.0827 RPN box loss: 0.00572 RPN score loss: 0.00269 RPN total loss: 0.0084 Total loss: 0.77173 timestamp: 1654963273.1902144 iteration: 62315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08881 FastRCNN class loss: 0.07162 FastRCNN total loss: 0.16042 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.0004 Mask loss: 0.09461 RPN box loss: 0.01868 RPN score loss: 0.00568 RPN total loss: 0.02436 Total loss: 0.8729 timestamp: 1654963276.3822484 iteration: 62320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09304 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.17061 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.0004 Mask loss: 0.1388 RPN box loss: 0.02016 RPN score loss: 0.01118 RPN total loss: 0.03134 Total loss: 0.93426 timestamp: 1654963279.5992606 iteration: 62325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.15558 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.0004 Mask loss: 0.10581 RPN box loss: 0.0139 RPN score loss: 0.00208 RPN total loss: 0.01598 Total loss: 0.87089 timestamp: 1654963282.8268428 iteration: 62330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06967 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.11877 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.0004 Mask loss: 0.13143 RPN box loss: 0.02027 RPN score loss: 0.00162 RPN total loss: 0.02189 Total loss: 0.8656 timestamp: 1654963286.0975225 iteration: 62335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06481 FastRCNN class loss: 0.04427 FastRCNN total loss: 0.10908 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.0004 Mask loss: 0.10942 RPN box loss: 0.01042 RPN score loss: 0.00644 RPN total loss: 0.01686 Total loss: 0.82887 timestamp: 1654963289.266654 iteration: 62340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08356 FastRCNN class loss: 0.07079 FastRCNN total loss: 0.15435 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.0004 Mask loss: 0.09208 RPN box loss: 0.00562 RPN score loss: 0.00314 RPN total loss: 0.00876 Total loss: 0.84871 timestamp: 1654963292.4842038 iteration: 62345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06659 FastRCNN class loss: 0.0399 FastRCNN total loss: 0.1065 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.0004 Mask loss: 0.12494 RPN box loss: 0.01882 RPN score loss: 0.01112 RPN total loss: 0.02994 Total loss: 0.85488 timestamp: 1654963295.7046583 iteration: 62350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09118 FastRCNN class loss: 0.07611 FastRCNN total loss: 0.16729 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.0004 Mask loss: 0.09715 RPN box loss: 0.00899 RPN score loss: 0.00723 RPN total loss: 0.01622 Total loss: 0.87416 timestamp: 1654963298.8778641 iteration: 62355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12403 FastRCNN class loss: 0.08479 FastRCNN total loss: 0.20882 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.0004 Mask loss: 0.12387 RPN box loss: 0.02012 RPN score loss: 0.01013 RPN total loss: 0.03024 Total loss: 0.95643 timestamp: 1654963302.0148034 iteration: 62360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07521 FastRCNN class loss: 0.04045 FastRCNN total loss: 0.11566 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.0004 Mask loss: 0.20386 RPN box loss: 0.03271 RPN score loss: 0.00197 RPN total loss: 0.03468 Total loss: 0.94771 timestamp: 1654963305.2000277 iteration: 62365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04106 FastRCNN class loss: 0.05359 FastRCNN total loss: 0.09466 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.0004 Mask loss: 0.09446 RPN box loss: 0.02978 RPN score loss: 0.00338 RPN total loss: 0.03316 Total loss: 0.81577 timestamp: 1654963308.3975744 iteration: 62370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04902 FastRCNN class loss: 0.05025 FastRCNN total loss: 0.09927 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.0004 Mask loss: 0.1101 RPN box loss: 0.00758 RPN score loss: 0.00396 RPN total loss: 0.01153 Total loss: 0.8144 timestamp: 1654963311.6167386 iteration: 62375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.098 FastRCNN class loss: 0.09569 FastRCNN total loss: 0.19369 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.0004 Mask loss: 0.16262 RPN box loss: 0.01551 RPN score loss: 0.00531 RPN total loss: 0.02083 Total loss: 0.97063 timestamp: 1654963314.7453635 iteration: 62380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08464 FastRCNN class loss: 0.05662 FastRCNN total loss: 0.14126 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.0004 Mask loss: 0.08383 RPN box loss: 0.00831 RPN score loss: 0.00082 RPN total loss: 0.00914 Total loss: 0.82772 timestamp: 1654963317.9777334 iteration: 62385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11849 FastRCNN class loss: 0.07251 FastRCNN total loss: 0.19101 L1 loss: 0.0000e+00 L2 loss: 0.59349 Learning rate: 0.0004 Mask loss: 0.1192 RPN box loss: 0.02288 RPN score loss: 0.00833 RPN total loss: 0.03121 Total loss: 0.93491 timestamp: 1654963321.1397078 iteration: 62390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09808 FastRCNN class loss: 0.06137 FastRCNN total loss: 0.15944 L1 loss: 0.0000e+00 L2 loss: 0.59349 Learning rate: 0.0004 Mask loss: 0.12304 RPN box loss: 0.01067 RPN score loss: 0.00341 RPN total loss: 0.01408 Total loss: 0.89006 timestamp: 1654963324.3955402 iteration: 62395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08755 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.59349 Learning rate: 0.0004 Mask loss: 0.10095 RPN box loss: 0.00762 RPN score loss: 0.0058 RPN total loss: 0.01342 Total loss: 0.85028 timestamp: 1654963327.6001625 iteration: 62400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09323 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.59349 Learning rate: 0.0004 Mask loss: 0.09332 RPN box loss: 0.04509 RPN score loss: 0.00646 RPN total loss: 0.05155 Total loss: 0.89342 timestamp: 1654963330.8576674 iteration: 62405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11795 FastRCNN class loss: 0.0799 FastRCNN total loss: 0.19785 L1 loss: 0.0000e+00 L2 loss: 0.59349 Learning rate: 0.0004 Mask loss: 0.14954 RPN box loss: 0.00955 RPN score loss: 0.00531 RPN total loss: 0.01487 Total loss: 0.95574 timestamp: 1654963334.1393623 iteration: 62410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07463 FastRCNN class loss: 0.09718 FastRCNN total loss: 0.17182 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.0004 Mask loss: 0.155 RPN box loss: 0.0162 RPN score loss: 0.00393 RPN total loss: 0.02013 Total loss: 0.94042 timestamp: 1654963337.2880917 iteration: 62415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.16488 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.0004 Mask loss: 0.1055 RPN box loss: 0.02186 RPN score loss: 0.00647 RPN total loss: 0.02833 Total loss: 0.89219 timestamp: 1654963340.4972515 iteration: 62420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07979 FastRCNN class loss: 0.05687 FastRCNN total loss: 0.13666 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.0004 Mask loss: 0.14968 RPN box loss: 0.01245 RPN score loss: 0.01848 RPN total loss: 0.03093 Total loss: 0.91075 timestamp: 1654963343.7466938 iteration: 62425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08541 FastRCNN class loss: 0.08172 FastRCNN total loss: 0.16713 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.0004 Mask loss: 0.16062 RPN box loss: 0.03697 RPN score loss: 0.01447 RPN total loss: 0.05144 Total loss: 0.97267 timestamp: 1654963346.9446034 iteration: 62430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09721 FastRCNN class loss: 0.08524 FastRCNN total loss: 0.18245 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.0004 Mask loss: 0.11208 RPN box loss: 0.01502 RPN score loss: 0.003 RPN total loss: 0.01803 Total loss: 0.90604 timestamp: 1654963350.1164725 iteration: 62435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12392 FastRCNN class loss: 0.05794 FastRCNN total loss: 0.18186 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.09526 RPN box loss: 0.00799 RPN score loss: 0.00315 RPN total loss: 0.01114 Total loss: 0.88174 timestamp: 1654963353.2532856 iteration: 62440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14448 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.20925 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.17258 RPN box loss: 0.01172 RPN score loss: 0.00583 RPN total loss: 0.01755 Total loss: 0.99285 timestamp: 1654963356.4174225 iteration: 62445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.18053 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.1593 RPN box loss: 0.02369 RPN score loss: 0.00228 RPN total loss: 0.02597 Total loss: 0.95927 timestamp: 1654963359.6726782 iteration: 62450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08791 FastRCNN class loss: 0.08174 FastRCNN total loss: 0.16965 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.13525 RPN box loss: 0.01543 RPN score loss: 0.01234 RPN total loss: 0.02777 Total loss: 0.92614 timestamp: 1654963362.9198163 iteration: 62455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08883 FastRCNN class loss: 0.06106 FastRCNN total loss: 0.14989 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.1517 RPN box loss: 0.00592 RPN score loss: 0.00386 RPN total loss: 0.00978 Total loss: 0.90484 timestamp: 1654963366.1549752 iteration: 62460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08574 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.14981 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.18185 RPN box loss: 0.01084 RPN score loss: 0.00289 RPN total loss: 0.01373 Total loss: 0.93886 timestamp: 1654963369.3424096 iteration: 62465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10361 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.16261 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.0004 Mask loss: 0.10554 RPN box loss: 0.02462 RPN score loss: 0.00506 RPN total loss: 0.02968 Total loss: 0.8913 timestamp: 1654963372.450432 iteration: 62470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12375 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.19381 L1 loss: 0.0000e+00 L2 loss: 0.59346 Learning rate: 0.0004 Mask loss: 0.13566 RPN box loss: 0.01172 RPN score loss: 0.00127 RPN total loss: 0.01299 Total loss: 0.93592 timestamp: 1654963375.6760108 iteration: 62475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13697 FastRCNN class loss: 0.09304 FastRCNN total loss: 0.23 L1 loss: 0.0000e+00 L2 loss: 0.59346 Learning rate: 0.0004 Mask loss: 0.16988 RPN box loss: 0.00647 RPN score loss: 0.00361 RPN total loss: 0.01008 Total loss: 1.00342 timestamp: 1654963378.9106708 iteration: 62480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11042 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.19173 L1 loss: 0.0000e+00 L2 loss: 0.59346 Learning rate: 0.0004 Mask loss: 0.14289 RPN box loss: 0.02039 RPN score loss: 0.00751 RPN total loss: 0.0279 Total loss: 0.95598 timestamp: 1654963382.07367 iteration: 62485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.14535 L1 loss: 0.0000e+00 L2 loss: 0.59346 Learning rate: 0.0004 Mask loss: 0.09163 RPN box loss: 0.01045 RPN score loss: 0.00224 RPN total loss: 0.01269 Total loss: 0.84313 timestamp: 1654963385.279094 iteration: 62490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07348 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.13005 L1 loss: 0.0000e+00 L2 loss: 0.59346 Learning rate: 0.0004 Mask loss: 0.08187 RPN box loss: 0.00635 RPN score loss: 0.00198 RPN total loss: 0.00833 Total loss: 0.81371 timestamp: 1654963388.4836807 iteration: 62495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10316 FastRCNN class loss: 0.06065 FastRCNN total loss: 0.16382 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.08275 RPN box loss: 0.00695 RPN score loss: 0.00137 RPN total loss: 0.00832 Total loss: 0.84834 timestamp: 1654963391.74925 iteration: 62500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07389 FastRCNN class loss: 0.08493 FastRCNN total loss: 0.15882 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.07947 RPN box loss: 0.01168 RPN score loss: 0.00628 RPN total loss: 0.01796 Total loss: 0.8497 timestamp: 1654963394.9290743 iteration: 62505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10572 FastRCNN class loss: 0.05794 FastRCNN total loss: 0.16367 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.1368 RPN box loss: 0.01841 RPN score loss: 0.00148 RPN total loss: 0.01989 Total loss: 0.91382 timestamp: 1654963398.1396482 iteration: 62510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06766 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.13028 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.11509 RPN box loss: 0.01141 RPN score loss: 0.0021 RPN total loss: 0.01351 Total loss: 0.85233 timestamp: 1654963401.3601248 iteration: 62515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12884 FastRCNN class loss: 0.09001 FastRCNN total loss: 0.21884 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.19511 RPN box loss: 0.02688 RPN score loss: 0.00621 RPN total loss: 0.0331 Total loss: 1.0405 timestamp: 1654963404.5100849 iteration: 62520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07137 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.12024 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.14267 RPN box loss: 0.0154 RPN score loss: 0.0067 RPN total loss: 0.0221 Total loss: 0.87846 timestamp: 1654963407.6134539 iteration: 62525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06185 FastRCNN class loss: 0.05444 FastRCNN total loss: 0.11629 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.13365 RPN box loss: 0.01684 RPN score loss: 0.00432 RPN total loss: 0.02116 Total loss: 0.86455 timestamp: 1654963410.8105783 iteration: 62530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09586 FastRCNN class loss: 0.05538 FastRCNN total loss: 0.15124 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.0004 Mask loss: 0.10668 RPN box loss: 0.01095 RPN score loss: 0.00377 RPN total loss: 0.01471 Total loss: 0.86608 timestamp: 1654963414.1357636 iteration: 62535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.04708 FastRCNN total loss: 0.15708 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.0004 Mask loss: 0.13279 RPN box loss: 0.00585 RPN score loss: 0.00352 RPN total loss: 0.00937 Total loss: 0.89268 timestamp: 1654963417.3246956 iteration: 62540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09246 FastRCNN class loss: 0.07452 FastRCNN total loss: 0.16698 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.0004 Mask loss: 0.18456 RPN box loss: 0.0287 RPN score loss: 0.00443 RPN total loss: 0.03313 Total loss: 0.97811 timestamp: 1654963420.537358 iteration: 62545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05778 FastRCNN class loss: 0.04602 FastRCNN total loss: 0.1038 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.0004 Mask loss: 0.133 RPN box loss: 0.03579 RPN score loss: 0.0064 RPN total loss: 0.04219 Total loss: 0.87244 timestamp: 1654963423.7480707 iteration: 62550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08587 FastRCNN class loss: 0.05055 FastRCNN total loss: 0.13642 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.0004 Mask loss: 0.12572 RPN box loss: 0.00854 RPN score loss: 0.00356 RPN total loss: 0.0121 Total loss: 0.86767 timestamp: 1654963426.9179215 iteration: 62555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1071 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.18197 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.0004 Mask loss: 0.20283 RPN box loss: 0.02484 RPN score loss: 0.00815 RPN total loss: 0.03299 Total loss: 1.01123 timestamp: 1654963430.088324 iteration: 62560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06413 FastRCNN class loss: 0.10688 FastRCNN total loss: 0.17101 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.0004 Mask loss: 0.14191 RPN box loss: 0.02376 RPN score loss: 0.009 RPN total loss: 0.03276 Total loss: 0.93911 timestamp: 1654963433.3132107 iteration: 62565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1254 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.20184 L1 loss: 0.0000e+00 L2 loss: 0.59343 Learning rate: 0.0004 Mask loss: 0.14205 RPN box loss: 0.01373 RPN score loss: 0.00349 RPN total loss: 0.01722 Total loss: 0.95454 timestamp: 1654963436.5442166 iteration: 62570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08141 FastRCNN class loss: 0.04783 FastRCNN total loss: 0.12924 L1 loss: 0.0000e+00 L2 loss: 0.59343 Learning rate: 0.0004 Mask loss: 0.08734 RPN box loss: 0.00649 RPN score loss: 0.00077 RPN total loss: 0.00725 Total loss: 0.81727 timestamp: 1654963439.7645705 iteration: 62575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05849 FastRCNN class loss: 0.06103 FastRCNN total loss: 0.11951 L1 loss: 0.0000e+00 L2 loss: 0.59343 Learning rate: 0.0004 Mask loss: 0.11233 RPN box loss: 0.00504 RPN score loss: 0.00312 RPN total loss: 0.00815 Total loss: 0.83343 timestamp: 1654963443.0025036 iteration: 62580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.10236 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.59343 Learning rate: 0.0004 Mask loss: 0.17332 RPN box loss: 0.02523 RPN score loss: 0.01554 RPN total loss: 0.04077 Total loss: 1.00109 timestamp: 1654963446.2196434 iteration: 62585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1349 FastRCNN class loss: 0.04102 FastRCNN total loss: 0.17592 L1 loss: 0.0000e+00 L2 loss: 0.59343 Learning rate: 0.0004 Mask loss: 0.17472 RPN box loss: 0.01684 RPN score loss: 0.00162 RPN total loss: 0.01846 Total loss: 0.96253 timestamp: 1654963449.3668432 iteration: 62590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12033 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.1836 L1 loss: 0.0000e+00 L2 loss: 0.59342 Learning rate: 0.0004 Mask loss: 0.0908 RPN box loss: 0.0093 RPN score loss: 0.01014 RPN total loss: 0.01945 Total loss: 0.88727 timestamp: 1654963452.5082767 iteration: 62595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13032 FastRCNN class loss: 0.11134 FastRCNN total loss: 0.24166 L1 loss: 0.0000e+00 L2 loss: 0.59342 Learning rate: 0.0004 Mask loss: 0.13476 RPN box loss: 0.01326 RPN score loss: 0.00633 RPN total loss: 0.01959 Total loss: 0.98943 timestamp: 1654963455.7021663 iteration: 62600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08484 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.14543 L1 loss: 0.0000e+00 L2 loss: 0.59342 Learning rate: 0.0004 Mask loss: 0.16262 RPN box loss: 0.00735 RPN score loss: 0.00103 RPN total loss: 0.00838 Total loss: 0.90984 timestamp: 1654963458.9545984 iteration: 62605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09168 FastRCNN class loss: 0.06738 FastRCNN total loss: 0.15907 L1 loss: 0.0000e+00 L2 loss: 0.59342 Learning rate: 0.0004 Mask loss: 0.15045 RPN box loss: 0.00318 RPN score loss: 0.00267 RPN total loss: 0.00585 Total loss: 0.90879 timestamp: 1654963462.136812 iteration: 62610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07667 FastRCNN class loss: 0.0634 FastRCNN total loss: 0.14007 L1 loss: 0.0000e+00 L2 loss: 0.59342 Learning rate: 0.0004 Mask loss: 0.0836 RPN box loss: 0.0073 RPN score loss: 0.00376 RPN total loss: 0.01106 Total loss: 0.82815 timestamp: 1654963465.3409715 iteration: 62615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05597 FastRCNN class loss: 0.05922 FastRCNN total loss: 0.1152 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.0004 Mask loss: 0.15527 RPN box loss: 0.00384 RPN score loss: 0.00742 RPN total loss: 0.01126 Total loss: 0.87514 timestamp: 1654963468.576875 iteration: 62620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1012 FastRCNN class loss: 0.06296 FastRCNN total loss: 0.16416 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.0004 Mask loss: 0.21084 RPN box loss: 0.00621 RPN score loss: 0.00222 RPN total loss: 0.00843 Total loss: 0.97684 timestamp: 1654963471.7984557 iteration: 62625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09386 FastRCNN class loss: 0.05349 FastRCNN total loss: 0.14736 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.0004 Mask loss: 0.13364 RPN box loss: 0.00594 RPN score loss: 0.00721 RPN total loss: 0.01315 Total loss: 0.88756 timestamp: 1654963474.9515996 iteration: 62630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05102 FastRCNN class loss: 0.07179 FastRCNN total loss: 0.12281 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.0004 Mask loss: 0.11001 RPN box loss: 0.0128 RPN score loss: 0.00267 RPN total loss: 0.01547 Total loss: 0.84169 timestamp: 1654963478.0887816 iteration: 62635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05555 FastRCNN class loss: 0.05063 FastRCNN total loss: 0.10619 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.0004 Mask loss: 0.08384 RPN box loss: 0.00947 RPN score loss: 0.0042 RPN total loss: 0.01367 Total loss: 0.79711 timestamp: 1654963481.2409956 iteration: 62640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1164 FastRCNN class loss: 0.07321 FastRCNN total loss: 0.18961 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.0004 Mask loss: 0.12968 RPN box loss: 0.01971 RPN score loss: 0.00572 RPN total loss: 0.02543 Total loss: 0.93812 timestamp: 1654963484.474097 iteration: 62645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04667 FastRCNN class loss: 0.04076 FastRCNN total loss: 0.08743 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.08846 RPN box loss: 0.00404 RPN score loss: 0.00997 RPN total loss: 0.01401 Total loss: 0.7833 timestamp: 1654963487.6877918 iteration: 62650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07388 FastRCNN class loss: 0.05035 FastRCNN total loss: 0.12423 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.10277 RPN box loss: 0.00584 RPN score loss: 0.00279 RPN total loss: 0.00863 Total loss: 0.82903 timestamp: 1654963490.82736 iteration: 62655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05097 FastRCNN class loss: 0.06 FastRCNN total loss: 0.11097 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.13171 RPN box loss: 0.00824 RPN score loss: 0.00227 RPN total loss: 0.01052 Total loss: 0.8466 timestamp: 1654963493.9910426 iteration: 62660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12203 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.20096 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.13371 RPN box loss: 0.01178 RPN score loss: 0.0035 RPN total loss: 0.01528 Total loss: 0.94334 timestamp: 1654963497.140158 iteration: 62665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10914 FastRCNN class loss: 0.09038 FastRCNN total loss: 0.19951 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.11818 RPN box loss: 0.03086 RPN score loss: 0.00588 RPN total loss: 0.03674 Total loss: 0.94783 timestamp: 1654963500.2571287 iteration: 62670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10003 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.1615 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.14912 RPN box loss: 0.01018 RPN score loss: 0.00821 RPN total loss: 0.01839 Total loss: 0.92241 timestamp: 1654963503.4062953 iteration: 62675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08819 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.14653 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.13454 RPN box loss: 0.006 RPN score loss: 0.00348 RPN total loss: 0.00949 Total loss: 0.88395 timestamp: 1654963506.5641932 iteration: 62680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08927 FastRCNN class loss: 0.06321 FastRCNN total loss: 0.15248 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.0004 Mask loss: 0.13212 RPN box loss: 0.00562 RPN score loss: 0.0051 RPN total loss: 0.01072 Total loss: 0.88872 timestamp: 1654963509.7319489 iteration: 62685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.12839 L1 loss: 0.0000e+00 L2 loss: 0.59339 Learning rate: 0.0004 Mask loss: 0.11395 RPN box loss: 0.02351 RPN score loss: 0.00936 RPN total loss: 0.03287 Total loss: 0.8686 timestamp: 1654963512.9236612 iteration: 62690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07374 FastRCNN class loss: 0.10902 FastRCNN total loss: 0.18276 L1 loss: 0.0000e+00 L2 loss: 0.59339 Learning rate: 0.0004 Mask loss: 0.12805 RPN box loss: 0.01541 RPN score loss: 0.00989 RPN total loss: 0.0253 Total loss: 0.9295 timestamp: 1654963516.0923433 iteration: 62695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03731 FastRCNN class loss: 0.03345 FastRCNN total loss: 0.07077 L1 loss: 0.0000e+00 L2 loss: 0.59339 Learning rate: 0.0004 Mask loss: 0.13727 RPN box loss: 0.01424 RPN score loss: 0.00365 RPN total loss: 0.01789 Total loss: 0.81931 timestamp: 1654963519.2863083 iteration: 62700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.05223 FastRCNN total loss: 0.16444 L1 loss: 0.0000e+00 L2 loss: 0.59339 Learning rate: 0.0004 Mask loss: 0.12431 RPN box loss: 0.02529 RPN score loss: 0.00482 RPN total loss: 0.03011 Total loss: 0.91225 timestamp: 1654963522.5571282 iteration: 62705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10433 FastRCNN class loss: 0.0768 FastRCNN total loss: 0.18113 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.0004 Mask loss: 0.12828 RPN box loss: 0.01533 RPN score loss: 0.00539 RPN total loss: 0.02072 Total loss: 0.9235 timestamp: 1654963525.769428 iteration: 62710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06162 FastRCNN class loss: 0.03878 FastRCNN total loss: 0.1004 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.0004 Mask loss: 0.11219 RPN box loss: 0.01319 RPN score loss: 0.0036 RPN total loss: 0.01678 Total loss: 0.82275 timestamp: 1654963528.9984498 iteration: 62715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13127 FastRCNN class loss: 0.09689 FastRCNN total loss: 0.22816 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.0004 Mask loss: 0.10393 RPN box loss: 0.00868 RPN score loss: 0.00337 RPN total loss: 0.01206 Total loss: 0.93753 timestamp: 1654963532.1971462 iteration: 62720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06744 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.14733 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.0004 Mask loss: 0.12279 RPN box loss: 0.01649 RPN score loss: 0.00786 RPN total loss: 0.02436 Total loss: 0.88785 timestamp: 1654963535.3550856 iteration: 62725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06195 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.13613 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.0004 Mask loss: 0.1343 RPN box loss: 0.00648 RPN score loss: 0.00859 RPN total loss: 0.01507 Total loss: 0.87887 timestamp: 1654963538.5895529 iteration: 62730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.16027 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.0004 Mask loss: 0.09684 RPN box loss: 0.01231 RPN score loss: 0.00623 RPN total loss: 0.01853 Total loss: 0.86902 timestamp: 1654963541.795959 iteration: 62735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0535 FastRCNN class loss: 0.05071 FastRCNN total loss: 0.10421 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.0004 Mask loss: 0.12325 RPN box loss: 0.00625 RPN score loss: 0.00865 RPN total loss: 0.01489 Total loss: 0.83573 timestamp: 1654963545.0214164 iteration: 62740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09578 FastRCNN class loss: 0.05383 FastRCNN total loss: 0.14961 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.0004 Mask loss: 0.13704 RPN box loss: 0.01254 RPN score loss: 0.00083 RPN total loss: 0.01337 Total loss: 0.89339 timestamp: 1654963548.2163615 iteration: 62745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08413 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.15202 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.0004 Mask loss: 0.13507 RPN box loss: 0.06983 RPN score loss: 0.0037 RPN total loss: 0.07353 Total loss: 0.95399 timestamp: 1654963551.3737972 iteration: 62750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11321 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.18392 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.0004 Mask loss: 0.12886 RPN box loss: 0.01684 RPN score loss: 0.00209 RPN total loss: 0.01892 Total loss: 0.92507 timestamp: 1654963554.4659395 iteration: 62755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13136 FastRCNN class loss: 0.07061 FastRCNN total loss: 0.20196 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.0004 Mask loss: 0.18168 RPN box loss: 0.0171 RPN score loss: 0.01156 RPN total loss: 0.02866 Total loss: 1.00568 timestamp: 1654963557.6707654 iteration: 62760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09036 FastRCNN class loss: 0.0901 FastRCNN total loss: 0.18046 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.0004 Mask loss: 0.14885 RPN box loss: 0.01615 RPN score loss: 0.00531 RPN total loss: 0.02146 Total loss: 0.94413 timestamp: 1654963560.8976588 iteration: 62765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11782 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.19139 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.13151 RPN box loss: 0.0103 RPN score loss: 0.0025 RPN total loss: 0.0128 Total loss: 0.92906 timestamp: 1654963564.0841568 iteration: 62770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04342 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.1028 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.09928 RPN box loss: 0.01309 RPN score loss: 0.00271 RPN total loss: 0.01581 Total loss: 0.81125 timestamp: 1654963567.340814 iteration: 62775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08018 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.16062 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.13795 RPN box loss: 0.00772 RPN score loss: 0.00421 RPN total loss: 0.01194 Total loss: 0.90387 timestamp: 1654963570.5666962 iteration: 62780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08736 FastRCNN class loss: 0.05069 FastRCNN total loss: 0.13805 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.09467 RPN box loss: 0.01723 RPN score loss: 0.00301 RPN total loss: 0.02025 Total loss: 0.84633 timestamp: 1654963573.7131433 iteration: 62785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05119 FastRCNN class loss: 0.05698 FastRCNN total loss: 0.10817 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.11489 RPN box loss: 0.01926 RPN score loss: 0.00313 RPN total loss: 0.02239 Total loss: 0.83881 timestamp: 1654963576.949396 iteration: 62790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0507 FastRCNN class loss: 0.04104 FastRCNN total loss: 0.09174 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.11655 RPN box loss: 0.01135 RPN score loss: 0.003 RPN total loss: 0.01435 Total loss: 0.81599 timestamp: 1654963580.0812323 iteration: 62795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09076 FastRCNN class loss: 0.0413 FastRCNN total loss: 0.13205 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.0004 Mask loss: 0.1083 RPN box loss: 0.00593 RPN score loss: 0.0019 RPN total loss: 0.00783 Total loss: 0.84154 timestamp: 1654963583.2845812 iteration: 62800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08407 FastRCNN class loss: 0.09644 FastRCNN total loss: 0.18051 L1 loss: 0.0000e+00 L2 loss: 0.59335 Learning rate: 0.0004 Mask loss: 0.1686 RPN box loss: 0.01511 RPN score loss: 0.00469 RPN total loss: 0.0198 Total loss: 0.96226 timestamp: 1654963586.4756753 iteration: 62805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07326 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.13903 L1 loss: 0.0000e+00 L2 loss: 0.59335 Learning rate: 0.0004 Mask loss: 0.09812 RPN box loss: 0.00431 RPN score loss: 0.00372 RPN total loss: 0.00803 Total loss: 0.83852 timestamp: 1654963589.6859677 iteration: 62810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0898 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.16516 L1 loss: 0.0000e+00 L2 loss: 0.59335 Learning rate: 0.0004 Mask loss: 0.12542 RPN box loss: 0.02242 RPN score loss: 0.00538 RPN total loss: 0.0278 Total loss: 0.91173 timestamp: 1654963592.9046922 iteration: 62815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10142 FastRCNN class loss: 0.04351 FastRCNN total loss: 0.14493 L1 loss: 0.0000e+00 L2 loss: 0.59335 Learning rate: 0.0004 Mask loss: 0.11032 RPN box loss: 0.00889 RPN score loss: 0.00149 RPN total loss: 0.01038 Total loss: 0.85897 timestamp: 1654963596.077498 iteration: 62820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12874 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.19037 L1 loss: 0.0000e+00 L2 loss: 0.59335 Learning rate: 0.0004 Mask loss: 0.09066 RPN box loss: 0.00856 RPN score loss: 0.0038 RPN total loss: 0.01236 Total loss: 0.88674 timestamp: 1654963599.2547016 iteration: 62825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.06067 FastRCNN total loss: 0.15473 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.0004 Mask loss: 0.14283 RPN box loss: 0.00843 RPN score loss: 0.00639 RPN total loss: 0.01482 Total loss: 0.90573 timestamp: 1654963602.477416 iteration: 62830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05724 FastRCNN class loss: 0.05765 FastRCNN total loss: 0.11488 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.0004 Mask loss: 0.18308 RPN box loss: 0.02415 RPN score loss: 0.00161 RPN total loss: 0.02576 Total loss: 0.91707 timestamp: 1654963605.6061342 iteration: 62835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07591 FastRCNN class loss: 0.07953 FastRCNN total loss: 0.15544 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.0004 Mask loss: 0.09284 RPN box loss: 0.01856 RPN score loss: 0.00228 RPN total loss: 0.02083 Total loss: 0.86246 timestamp: 1654963608.8081734 iteration: 62840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13296 FastRCNN class loss: 0.11505 FastRCNN total loss: 0.24801 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.0004 Mask loss: 0.1687 RPN box loss: 0.01569 RPN score loss: 0.01224 RPN total loss: 0.02792 Total loss: 1.03797 timestamp: 1654963611.9751463 iteration: 62845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07035 FastRCNN class loss: 0.06095 FastRCNN total loss: 0.1313 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.0004 Mask loss: 0.09709 RPN box loss: 0.01639 RPN score loss: 0.00493 RPN total loss: 0.02132 Total loss: 0.84304 timestamp: 1654963615.2682498 iteration: 62850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08571 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.14549 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.0004 Mask loss: 0.12226 RPN box loss: 0.01301 RPN score loss: 0.00299 RPN total loss: 0.01599 Total loss: 0.87709 timestamp: 1654963618.380144 iteration: 62855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06843 FastRCNN class loss: 0.07742 FastRCNN total loss: 0.14585 L1 loss: 0.0000e+00 L2 loss: 0.59333 Learning rate: 0.0004 Mask loss: 0.15052 RPN box loss: 0.013 RPN score loss: 0.00448 RPN total loss: 0.01749 Total loss: 0.90719 timestamp: 1654963621.6009226 iteration: 62860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08886 FastRCNN class loss: 0.06738 FastRCNN total loss: 0.15624 L1 loss: 0.0000e+00 L2 loss: 0.59333 Learning rate: 0.0004 Mask loss: 0.08515 RPN box loss: 0.01791 RPN score loss: 0.00188 RPN total loss: 0.01979 Total loss: 0.85451 timestamp: 1654963624.7383313 iteration: 62865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06541 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.12487 L1 loss: 0.0000e+00 L2 loss: 0.59333 Learning rate: 0.0004 Mask loss: 0.10814 RPN box loss: 0.00616 RPN score loss: 0.00073 RPN total loss: 0.00689 Total loss: 0.83323 timestamp: 1654963627.8544147 iteration: 62870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07071 FastRCNN class loss: 0.05797 FastRCNN total loss: 0.12868 L1 loss: 0.0000e+00 L2 loss: 0.59333 Learning rate: 0.0004 Mask loss: 0.15184 RPN box loss: 0.03683 RPN score loss: 0.00872 RPN total loss: 0.04555 Total loss: 0.9194 timestamp: 1654963631.0537026 iteration: 62875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09291 FastRCNN class loss: 0.08123 FastRCNN total loss: 0.17414 L1 loss: 0.0000e+00 L2 loss: 0.59333 Learning rate: 0.0004 Mask loss: 0.11549 RPN box loss: 0.01974 RPN score loss: 0.0018 RPN total loss: 0.02155 Total loss: 0.9045 timestamp: 1654963634.2334952 iteration: 62880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08151 FastRCNN class loss: 0.043 FastRCNN total loss: 0.1245 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.0004 Mask loss: 0.0965 RPN box loss: 0.00639 RPN score loss: 0.00218 RPN total loss: 0.00857 Total loss: 0.8229 timestamp: 1654963637.3945432 iteration: 62885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.04944 FastRCNN total loss: 0.1495 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.0004 Mask loss: 0.16554 RPN box loss: 0.0142 RPN score loss: 0.0043 RPN total loss: 0.01849 Total loss: 0.92686 timestamp: 1654963640.5216012 iteration: 62890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.18821 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.0004 Mask loss: 0.13786 RPN box loss: 0.01304 RPN score loss: 0.00302 RPN total loss: 0.01606 Total loss: 0.93545 timestamp: 1654963643.6716256 iteration: 62895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06757 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.13703 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.0004 Mask loss: 0.11289 RPN box loss: 0.04226 RPN score loss: 0.01063 RPN total loss: 0.05289 Total loss: 0.89614 timestamp: 1654963646.8033628 iteration: 62900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08512 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.15562 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.0004 Mask loss: 0.15364 RPN box loss: 0.0178 RPN score loss: 0.00903 RPN total loss: 0.02683 Total loss: 0.92941 timestamp: 1654963649.956493 iteration: 62905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.07354 FastRCNN total loss: 0.16993 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.0004 Mask loss: 0.13296 RPN box loss: 0.01623 RPN score loss: 0.00704 RPN total loss: 0.02327 Total loss: 0.91948 timestamp: 1654963653.1580708 iteration: 62910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09879 FastRCNN class loss: 0.07315 FastRCNN total loss: 0.17195 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.0004 Mask loss: 0.15053 RPN box loss: 0.02242 RPN score loss: 0.0062 RPN total loss: 0.02861 Total loss: 0.9444 timestamp: 1654963656.3282373 iteration: 62915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0868 FastRCNN class loss: 0.0265 FastRCNN total loss: 0.1133 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.0004 Mask loss: 0.09278 RPN box loss: 0.00739 RPN score loss: 0.00036 RPN total loss: 0.00775 Total loss: 0.80714 timestamp: 1654963659.5444946 iteration: 62920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1247 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.19568 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.0004 Mask loss: 0.17666 RPN box loss: 0.02091 RPN score loss: 0.00475 RPN total loss: 0.02566 Total loss: 0.99131 timestamp: 1654963662.770825 iteration: 62925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16072 FastRCNN class loss: 0.08086 FastRCNN total loss: 0.24158 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.0004 Mask loss: 0.16939 RPN box loss: 0.01912 RPN score loss: 0.00214 RPN total loss: 0.02126 Total loss: 1.02554 timestamp: 1654963665.9504056 iteration: 62930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06256 FastRCNN class loss: 0.05296 FastRCNN total loss: 0.11552 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.0004 Mask loss: 0.13639 RPN box loss: 0.03662 RPN score loss: 0.00388 RPN total loss: 0.0405 Total loss: 0.88572 timestamp: 1654963669.164594 iteration: 62935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07603 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.15443 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.0004 Mask loss: 0.13917 RPN box loss: 0.00688 RPN score loss: 0.00355 RPN total loss: 0.01043 Total loss: 0.89734 timestamp: 1654963672.3985307 iteration: 62940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05384 FastRCNN class loss: 0.03627 FastRCNN total loss: 0.0901 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.0004 Mask loss: 0.24052 RPN box loss: 0.01271 RPN score loss: 0.00276 RPN total loss: 0.01547 Total loss: 0.9394 timestamp: 1654963675.6246748 iteration: 62945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09513 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.16383 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.0004 Mask loss: 0.13166 RPN box loss: 0.01481 RPN score loss: 0.01255 RPN total loss: 0.02736 Total loss: 0.91615 timestamp: 1654963678.8758285 iteration: 62950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05105 FastRCNN class loss: 0.0478 FastRCNN total loss: 0.09885 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.0004 Mask loss: 0.09631 RPN box loss: 0.01146 RPN score loss: 0.00167 RPN total loss: 0.01313 Total loss: 0.80159 timestamp: 1654963682.067531 iteration: 62955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09376 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.15259 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.0004 Mask loss: 0.12667 RPN box loss: 0.00485 RPN score loss: 0.00915 RPN total loss: 0.014 Total loss: 0.88656 timestamp: 1654963685.289873 iteration: 62960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04568 FastRCNN class loss: 0.04639 FastRCNN total loss: 0.09207 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.0004 Mask loss: 0.10264 RPN box loss: 0.00628 RPN score loss: 0.00184 RPN total loss: 0.00812 Total loss: 0.79613 timestamp: 1654963688.56568 iteration: 62965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09162 FastRCNN class loss: 0.07749 FastRCNN total loss: 0.1691 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.0004 Mask loss: 0.10127 RPN box loss: 0.02082 RPN score loss: 0.00511 RPN total loss: 0.02594 Total loss: 0.88961 timestamp: 1654963691.7787817 iteration: 62970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10792 FastRCNN class loss: 0.06846 FastRCNN total loss: 0.17638 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.0004 Mask loss: 0.1243 RPN box loss: 0.0147 RPN score loss: 0.00859 RPN total loss: 0.0233 Total loss: 0.91727 timestamp: 1654963694.978683 iteration: 62975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05874 FastRCNN class loss: 0.04107 FastRCNN total loss: 0.09981 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.0004 Mask loss: 0.10714 RPN box loss: 0.00506 RPN score loss: 0.00236 RPN total loss: 0.00741 Total loss: 0.80765 timestamp: 1654963698.1737447 iteration: 62980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14049 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.20612 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.0004 Mask loss: 0.11553 RPN box loss: 0.00523 RPN score loss: 0.00253 RPN total loss: 0.00776 Total loss: 0.9227 timestamp: 1654963701.2898817 iteration: 62985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06823 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.13169 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.0004 Mask loss: 0.15801 RPN box loss: 0.00947 RPN score loss: 0.00558 RPN total loss: 0.01505 Total loss: 0.89804 timestamp: 1654963704.4596336 iteration: 62990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08679 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.14141 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.0004 Mask loss: 0.11694 RPN box loss: 0.01303 RPN score loss: 0.00333 RPN total loss: 0.01636 Total loss: 0.86799 timestamp: 1654963707.6720397 iteration: 62995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06651 FastRCNN class loss: 0.0589 FastRCNN total loss: 0.12541 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.0004 Mask loss: 0.10773 RPN box loss: 0.06219 RPN score loss: 0.00251 RPN total loss: 0.0647 Total loss: 0.89113 timestamp: 1654963710.8961108 iteration: 63000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11151 FastRCNN class loss: 0.09753 FastRCNN total loss: 0.20904 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.0004 Mask loss: 0.14423 RPN box loss: 0.01066 RPN score loss: 0.00708 RPN total loss: 0.01774 Total loss: 0.96429 timestamp: 1654963714.0381954 iteration: 63005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07658 FastRCNN class loss: 0.05488 FastRCNN total loss: 0.13146 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.0004 Mask loss: 0.14388 RPN box loss: 0.00659 RPN score loss: 0.00512 RPN total loss: 0.01171 Total loss: 0.88034 timestamp: 1654963717.25484 iteration: 63010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10885 FastRCNN class loss: 0.1184 FastRCNN total loss: 0.22724 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.0004 Mask loss: 0.23839 RPN box loss: 0.0229 RPN score loss: 0.0086 RPN total loss: 0.0315 Total loss: 1.09042 timestamp: 1654963720.4661655 iteration: 63015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0927 FastRCNN class loss: 0.09858 FastRCNN total loss: 0.19128 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.0004 Mask loss: 0.12075 RPN box loss: 0.01172 RPN score loss: 0.01087 RPN total loss: 0.02259 Total loss: 0.9279 timestamp: 1654963723.7086766 iteration: 63020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06305 FastRCNN class loss: 0.04171 FastRCNN total loss: 0.10476 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.0004 Mask loss: 0.09096 RPN box loss: 0.00371 RPN score loss: 0.00122 RPN total loss: 0.00492 Total loss: 0.79392 timestamp: 1654963726.985105 iteration: 63025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11537 FastRCNN class loss: 0.0653 FastRCNN total loss: 0.18067 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.0004 Mask loss: 0.12712 RPN box loss: 0.01847 RPN score loss: 0.00126 RPN total loss: 0.01973 Total loss: 0.9208 timestamp: 1654963730.0826046 iteration: 63030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0495 FastRCNN class loss: 0.05659 FastRCNN total loss: 0.10609 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.0004 Mask loss: 0.12406 RPN box loss: 0.01402 RPN score loss: 0.00701 RPN total loss: 0.02103 Total loss: 0.84445 timestamp: 1654963733.3554115 iteration: 63035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09149 FastRCNN class loss: 0.0474 FastRCNN total loss: 0.13888 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.0004 Mask loss: 0.1253 RPN box loss: 0.01482 RPN score loss: 0.00143 RPN total loss: 0.01624 Total loss: 0.8737 timestamp: 1654963736.5189517 iteration: 63040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09682 FastRCNN class loss: 0.05847 FastRCNN total loss: 0.15529 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.0004 Mask loss: 0.11168 RPN box loss: 0.01206 RPN score loss: 0.00407 RPN total loss: 0.01614 Total loss: 0.87637 timestamp: 1654963739.7384923 iteration: 63045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16035 FastRCNN class loss: 0.06004 FastRCNN total loss: 0.22039 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.0004 Mask loss: 0.12153 RPN box loss: 0.01199 RPN score loss: 0.00305 RPN total loss: 0.01504 Total loss: 0.95023 timestamp: 1654963743.011331 iteration: 63050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09011 FastRCNN class loss: 0.06462 FastRCNN total loss: 0.15473 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.0004 Mask loss: 0.15267 RPN box loss: 0.01036 RPN score loss: 0.00782 RPN total loss: 0.01818 Total loss: 0.91884 timestamp: 1654963746.2437427 iteration: 63055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09063 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.15119 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.0004 Mask loss: 0.10866 RPN box loss: 0.00691 RPN score loss: 0.00963 RPN total loss: 0.01654 Total loss: 0.86965 timestamp: 1654963749.4169369 iteration: 63060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13598 FastRCNN class loss: 0.05115 FastRCNN total loss: 0.18713 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.0004 Mask loss: 0.11101 RPN box loss: 0.01427 RPN score loss: 0.00263 RPN total loss: 0.0169 Total loss: 0.9083 timestamp: 1654963752.6997535 iteration: 63065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07974 FastRCNN class loss: 0.04344 FastRCNN total loss: 0.12318 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.0004 Mask loss: 0.11241 RPN box loss: 0.00456 RPN score loss: 0.00203 RPN total loss: 0.00658 Total loss: 0.83543 timestamp: 1654963755.8533332 iteration: 63070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11232 FastRCNN class loss: 0.08349 FastRCNN total loss: 0.19581 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.0004 Mask loss: 0.13607 RPN box loss: 0.01467 RPN score loss: 0.00482 RPN total loss: 0.0195 Total loss: 0.94464 timestamp: 1654963759.01476 iteration: 63075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.07025 FastRCNN total loss: 0.17177 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.0004 Mask loss: 0.11975 RPN box loss: 0.02839 RPN score loss: 0.0034 RPN total loss: 0.03179 Total loss: 0.91657 timestamp: 1654963762.1729245 iteration: 63080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10866 FastRCNN class loss: 0.047 FastRCNN total loss: 0.15567 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.0004 Mask loss: 0.12892 RPN box loss: 0.01774 RPN score loss: 0.00188 RPN total loss: 0.01962 Total loss: 0.89746 timestamp: 1654963765.341716 iteration: 63085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12022 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.19661 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.0004 Mask loss: 0.1456 RPN box loss: 0.01865 RPN score loss: 0.00414 RPN total loss: 0.0228 Total loss: 0.95826 timestamp: 1654963768.586906 iteration: 63090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06427 FastRCNN class loss: 0.04407 FastRCNN total loss: 0.10834 L1 loss: 0.0000e+00 L2 loss: 0.59325 Learning rate: 0.0004 Mask loss: 0.13076 RPN box loss: 0.01497 RPN score loss: 0.00166 RPN total loss: 0.01663 Total loss: 0.84899 timestamp: 1654963771.7183764 iteration: 63095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11399 FastRCNN class loss: 0.09288 FastRCNN total loss: 0.20687 L1 loss: 0.0000e+00 L2 loss: 0.59325 Learning rate: 0.0004 Mask loss: 0.21673 RPN box loss: 0.01065 RPN score loss: 0.00405 RPN total loss: 0.0147 Total loss: 1.03156 timestamp: 1654963774.8948715 iteration: 63100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06044 FastRCNN class loss: 0.09095 FastRCNN total loss: 0.15139 L1 loss: 0.0000e+00 L2 loss: 0.59325 Learning rate: 0.0004 Mask loss: 0.16368 RPN box loss: 0.0063 RPN score loss: 0.01133 RPN total loss: 0.01763 Total loss: 0.92595 timestamp: 1654963778.1363702 iteration: 63105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.11153 FastRCNN total loss: 0.22313 L1 loss: 0.0000e+00 L2 loss: 0.59325 Learning rate: 0.0004 Mask loss: 0.16525 RPN box loss: 0.02501 RPN score loss: 0.00485 RPN total loss: 0.02986 Total loss: 1.0115 timestamp: 1654963781.3210304 iteration: 63110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10727 FastRCNN class loss: 0.09235 FastRCNN total loss: 0.19962 L1 loss: 0.0000e+00 L2 loss: 0.59325 Learning rate: 0.0004 Mask loss: 0.13055 RPN box loss: 0.01431 RPN score loss: 0.00281 RPN total loss: 0.01711 Total loss: 0.94053 timestamp: 1654963784.4598348 iteration: 63115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12978 FastRCNN class loss: 0.05828 FastRCNN total loss: 0.18807 L1 loss: 0.0000e+00 L2 loss: 0.59324 Learning rate: 0.0004 Mask loss: 0.12109 RPN box loss: 0.00791 RPN score loss: 0.00925 RPN total loss: 0.01716 Total loss: 0.91957 timestamp: 1654963787.698419 iteration: 63120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09602 FastRCNN class loss: 0.06399 FastRCNN total loss: 0.16001 L1 loss: 0.0000e+00 L2 loss: 0.59324 Learning rate: 0.0004 Mask loss: 0.10755 RPN box loss: 0.01037 RPN score loss: 0.00705 RPN total loss: 0.01742 Total loss: 0.87823 timestamp: 1654963790.88614 iteration: 63125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05504 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.11945 L1 loss: 0.0000e+00 L2 loss: 0.59324 Learning rate: 0.0004 Mask loss: 0.08639 RPN box loss: 0.00746 RPN score loss: 0.00245 RPN total loss: 0.00991 Total loss: 0.80899 timestamp: 1654963794.0488896 iteration: 63130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0208 FastRCNN class loss: 0.03215 FastRCNN total loss: 0.05295 L1 loss: 0.0000e+00 L2 loss: 0.59324 Learning rate: 0.0004 Mask loss: 0.07919 RPN box loss: 0.02367 RPN score loss: 0.00133 RPN total loss: 0.025 Total loss: 0.75037 timestamp: 1654963797.2299867 iteration: 63135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07703 FastRCNN class loss: 0.04959 FastRCNN total loss: 0.12662 L1 loss: 0.0000e+00 L2 loss: 0.59324 Learning rate: 0.0004 Mask loss: 0.12854 RPN box loss: 0.00912 RPN score loss: 0.0049 RPN total loss: 0.01402 Total loss: 0.86241 timestamp: 1654963800.460124 iteration: 63140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08313 FastRCNN class loss: 0.09902 FastRCNN total loss: 0.18214 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.0004 Mask loss: 0.16997 RPN box loss: 0.01566 RPN score loss: 0.01145 RPN total loss: 0.02711 Total loss: 0.97245 timestamp: 1654963803.582032 iteration: 63145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09298 FastRCNN class loss: 0.09383 FastRCNN total loss: 0.18682 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.0004 Mask loss: 0.14902 RPN box loss: 0.01823 RPN score loss: 0.00755 RPN total loss: 0.02578 Total loss: 0.95485 timestamp: 1654963806.7592478 iteration: 63150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10328 FastRCNN class loss: 0.11378 FastRCNN total loss: 0.21705 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.0004 Mask loss: 0.13051 RPN box loss: 0.01123 RPN score loss: 0.00557 RPN total loss: 0.0168 Total loss: 0.9576 timestamp: 1654963809.9222398 iteration: 63155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07539 FastRCNN class loss: 0.05683 FastRCNN total loss: 0.13222 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.0004 Mask loss: 0.12871 RPN box loss: 0.01088 RPN score loss: 0.00194 RPN total loss: 0.01281 Total loss: 0.86697 timestamp: 1654963813.0992243 iteration: 63160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07646 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.15006 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.0004 Mask loss: 0.14423 RPN box loss: 0.01554 RPN score loss: 0.01194 RPN total loss: 0.02747 Total loss: 0.91499 timestamp: 1654963816.2568288 iteration: 63165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1241 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.19403 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.0004 Mask loss: 0.12947 RPN box loss: 0.01415 RPN score loss: 0.00642 RPN total loss: 0.02058 Total loss: 0.9373 timestamp: 1654963819.4533455 iteration: 63170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08295 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.16061 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.13625 RPN box loss: 0.02433 RPN score loss: 0.01102 RPN total loss: 0.03536 Total loss: 0.92544 timestamp: 1654963822.6628969 iteration: 63175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09279 FastRCNN class loss: 0.0925 FastRCNN total loss: 0.18529 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.13375 RPN box loss: 0.00961 RPN score loss: 0.00524 RPN total loss: 0.01485 Total loss: 0.92712 timestamp: 1654963825.8917665 iteration: 63180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09967 FastRCNN class loss: 0.09464 FastRCNN total loss: 0.19431 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.19267 RPN box loss: 0.01496 RPN score loss: 0.00406 RPN total loss: 0.01902 Total loss: 0.99921 timestamp: 1654963829.0129247 iteration: 63185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10349 FastRCNN class loss: 0.10212 FastRCNN total loss: 0.20561 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.13922 RPN box loss: 0.01239 RPN score loss: 0.00746 RPN total loss: 0.01985 Total loss: 0.9579 timestamp: 1654963832.3068461 iteration: 63190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11063 FastRCNN class loss: 0.10093 FastRCNN total loss: 0.21156 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.17023 RPN box loss: 0.02071 RPN score loss: 0.01416 RPN total loss: 0.03487 Total loss: 1.00988 timestamp: 1654963835.5444384 iteration: 63195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11723 FastRCNN class loss: 0.08528 FastRCNN total loss: 0.20251 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.1342 RPN box loss: 0.00867 RPN score loss: 0.00299 RPN total loss: 0.01166 Total loss: 0.94158 timestamp: 1654963838.7639658 iteration: 63200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11732 FastRCNN class loss: 0.07388 FastRCNN total loss: 0.1912 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.0004 Mask loss: 0.15905 RPN box loss: 0.02499 RPN score loss: 0.00726 RPN total loss: 0.03225 Total loss: 0.97571 timestamp: 1654963841.976993 iteration: 63205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08636 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.14873 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.15584 RPN box loss: 0.00764 RPN score loss: 0.0026 RPN total loss: 0.01024 Total loss: 0.90802 timestamp: 1654963845.1769798 iteration: 63210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04992 FastRCNN class loss: 0.05099 FastRCNN total loss: 0.1009 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.09473 RPN box loss: 0.00211 RPN score loss: 0.00094 RPN total loss: 0.00305 Total loss: 0.7919 timestamp: 1654963848.3633208 iteration: 63215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1292 FastRCNN class loss: 0.08365 FastRCNN total loss: 0.21285 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.14539 RPN box loss: 0.0127 RPN score loss: 0.00173 RPN total loss: 0.01443 Total loss: 0.96587 timestamp: 1654963851.6021013 iteration: 63220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10175 FastRCNN class loss: 0.09408 FastRCNN total loss: 0.19583 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.20362 RPN box loss: 0.0145 RPN score loss: 0.00306 RPN total loss: 0.01756 Total loss: 1.01022 timestamp: 1654963854.766448 iteration: 63225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10397 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.15714 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.14279 RPN box loss: 0.00877 RPN score loss: 0.00175 RPN total loss: 0.01052 Total loss: 0.90367 timestamp: 1654963857.9865303 iteration: 63230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08963 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.15986 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.07875 RPN box loss: 0.00528 RPN score loss: 0.00251 RPN total loss: 0.00779 Total loss: 0.83961 timestamp: 1654963861.3165376 iteration: 63235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.12903 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.0004 Mask loss: 0.12172 RPN box loss: 0.01623 RPN score loss: 0.00656 RPN total loss: 0.02279 Total loss: 0.86675 timestamp: 1654963864.5444634 iteration: 63240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1241 FastRCNN class loss: 0.09717 FastRCNN total loss: 0.22127 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.0004 Mask loss: 0.2121 RPN box loss: 0.01193 RPN score loss: 0.00423 RPN total loss: 0.01615 Total loss: 1.04273 timestamp: 1654963867.6940935 iteration: 63245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0732 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.14113 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.0004 Mask loss: 0.09671 RPN box loss: 0.01097 RPN score loss: 0.00663 RPN total loss: 0.01759 Total loss: 0.84863 timestamp: 1654963870.944132 iteration: 63250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10561 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.18341 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.0004 Mask loss: 0.12589 RPN box loss: 0.02176 RPN score loss: 0.00933 RPN total loss: 0.03109 Total loss: 0.93359 timestamp: 1654963874.132632 iteration: 63255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12164 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.18391 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.0004 Mask loss: 0.13005 RPN box loss: 0.01306 RPN score loss: 0.00636 RPN total loss: 0.01942 Total loss: 0.92658 timestamp: 1654963877.3327014 iteration: 63260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07097 FastRCNN class loss: 0.05502 FastRCNN total loss: 0.12599 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.0004 Mask loss: 0.08011 RPN box loss: 0.00559 RPN score loss: 0.00461 RPN total loss: 0.0102 Total loss: 0.80949 timestamp: 1654963880.5287259 iteration: 63265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04801 FastRCNN class loss: 0.04883 FastRCNN total loss: 0.09684 L1 loss: 0.0000e+00 L2 loss: 0.59319 Learning rate: 0.0004 Mask loss: 0.1045 RPN box loss: 0.01253 RPN score loss: 0.00445 RPN total loss: 0.01697 Total loss: 0.81151 timestamp: 1654963883.714676 iteration: 63270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10453 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.18236 L1 loss: 0.0000e+00 L2 loss: 0.59319 Learning rate: 0.0004 Mask loss: 0.17 RPN box loss: 0.01752 RPN score loss: 0.01235 RPN total loss: 0.02986 Total loss: 0.97541 timestamp: 1654963886.953831 iteration: 63275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11821 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.20578 L1 loss: 0.0000e+00 L2 loss: 0.59319 Learning rate: 0.0004 Mask loss: 0.16536 RPN box loss: 0.02054 RPN score loss: 0.00714 RPN total loss: 0.02769 Total loss: 0.99201 timestamp: 1654963890.11329 iteration: 63280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0646 FastRCNN class loss: 0.04753 FastRCNN total loss: 0.11213 L1 loss: 0.0000e+00 L2 loss: 0.59319 Learning rate: 0.0004 Mask loss: 0.08744 RPN box loss: 0.01358 RPN score loss: 0.00296 RPN total loss: 0.01654 Total loss: 0.8093 timestamp: 1654963893.3623383 iteration: 63285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06105 FastRCNN class loss: 0.07235 FastRCNN total loss: 0.13339 L1 loss: 0.0000e+00 L2 loss: 0.59319 Learning rate: 0.0004 Mask loss: 0.14191 RPN box loss: 0.01719 RPN score loss: 0.01018 RPN total loss: 0.02737 Total loss: 0.89586 timestamp: 1654963896.5827577 iteration: 63290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07003 FastRCNN class loss: 0.05516 FastRCNN total loss: 0.1252 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.0004 Mask loss: 0.1291 RPN box loss: 0.02109 RPN score loss: 0.01633 RPN total loss: 0.03741 Total loss: 0.88489 timestamp: 1654963899.7906232 iteration: 63295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07222 FastRCNN class loss: 0.09732 FastRCNN total loss: 0.16953 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.0004 Mask loss: 0.12207 RPN box loss: 0.00741 RPN score loss: 0.00435 RPN total loss: 0.01176 Total loss: 0.89654 timestamp: 1654963902.9840932 iteration: 63300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11521 FastRCNN class loss: 0.10744 FastRCNN total loss: 0.22265 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.0004 Mask loss: 0.12576 RPN box loss: 0.01241 RPN score loss: 0.00551 RPN total loss: 0.01792 Total loss: 0.95951 timestamp: 1654963906.3207328 iteration: 63305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10083 FastRCNN class loss: 0.09207 FastRCNN total loss: 0.1929 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.0004 Mask loss: 0.12756 RPN box loss: 0.01566 RPN score loss: 0.00716 RPN total loss: 0.02283 Total loss: 0.93646 timestamp: 1654963909.4943993 iteration: 63310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11777 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.18822 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.0004 Mask loss: 0.19229 RPN box loss: 0.02155 RPN score loss: 0.00768 RPN total loss: 0.02924 Total loss: 1.00292 timestamp: 1654963912.667414 iteration: 63315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.089 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.17316 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.0004 Mask loss: 0.1614 RPN box loss: 0.01399 RPN score loss: 0.003 RPN total loss: 0.01699 Total loss: 0.94473 timestamp: 1654963915.8588834 iteration: 63320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12566 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.19864 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.0004 Mask loss: 0.14519 RPN box loss: 0.00603 RPN score loss: 0.00586 RPN total loss: 0.01189 Total loss: 0.94889 timestamp: 1654963919.0722094 iteration: 63325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09146 FastRCNN class loss: 0.05713 FastRCNN total loss: 0.14859 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.0004 Mask loss: 0.13478 RPN box loss: 0.00578 RPN score loss: 0.00205 RPN total loss: 0.00783 Total loss: 0.88437 timestamp: 1654963922.2778537 iteration: 63330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12284 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.20612 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.0004 Mask loss: 0.11682 RPN box loss: 0.00926 RPN score loss: 0.00274 RPN total loss: 0.012 Total loss: 0.92811 timestamp: 1654963925.467496 iteration: 63335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1052 FastRCNN class loss: 0.08744 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.0004 Mask loss: 0.13349 RPN box loss: 0.00948 RPN score loss: 0.00529 RPN total loss: 0.01478 Total loss: 0.93408 timestamp: 1654963928.6702237 iteration: 63340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04929 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.09984 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.0004 Mask loss: 0.10494 RPN box loss: 0.00398 RPN score loss: 0.00304 RPN total loss: 0.00702 Total loss: 0.80497 timestamp: 1654963931.9059286 iteration: 63345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10595 FastRCNN class loss: 0.06472 FastRCNN total loss: 0.17067 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.0004 Mask loss: 0.13721 RPN box loss: 0.00453 RPN score loss: 0.00168 RPN total loss: 0.00621 Total loss: 0.90726 timestamp: 1654963935.1255012 iteration: 63350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0651 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.138 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.0004 Mask loss: 0.12157 RPN box loss: 0.01219 RPN score loss: 0.00503 RPN total loss: 0.01722 Total loss: 0.86995 timestamp: 1654963938.2410347 iteration: 63355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09323 FastRCNN class loss: 0.05467 FastRCNN total loss: 0.14789 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.0004 Mask loss: 0.1931 RPN box loss: 0.03688 RPN score loss: 0.01583 RPN total loss: 0.0527 Total loss: 0.98686 timestamp: 1654963941.4257402 iteration: 63360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0909 FastRCNN class loss: 0.07379 FastRCNN total loss: 0.16469 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.0004 Mask loss: 0.11477 RPN box loss: 0.0356 RPN score loss: 0.01264 RPN total loss: 0.04823 Total loss: 0.92086 timestamp: 1654963944.5749176 iteration: 63365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06852 FastRCNN class loss: 0.08466 FastRCNN total loss: 0.15318 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.0004 Mask loss: 0.15085 RPN box loss: 0.00694 RPN score loss: 0.00544 RPN total loss: 0.01237 Total loss: 0.90956 timestamp: 1654963947.776184 iteration: 63370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06917 FastRCNN class loss: 0.0887 FastRCNN total loss: 0.15787 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.0004 Mask loss: 0.15918 RPN box loss: 0.00648 RPN score loss: 0.006 RPN total loss: 0.01248 Total loss: 0.92269 timestamp: 1654963950.9514716 iteration: 63375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08699 FastRCNN class loss: 0.04227 FastRCNN total loss: 0.12926 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.0004 Mask loss: 0.09343 RPN box loss: 0.02312 RPN score loss: 0.00186 RPN total loss: 0.02498 Total loss: 0.84082 timestamp: 1654963954.1369174 iteration: 63380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05853 FastRCNN class loss: 0.04144 FastRCNN total loss: 0.09997 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.10535 RPN box loss: 0.00585 RPN score loss: 0.00123 RPN total loss: 0.00708 Total loss: 0.80555 timestamp: 1654963957.3482778 iteration: 63385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04367 FastRCNN class loss: 0.04447 FastRCNN total loss: 0.08815 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.10677 RPN box loss: 0.01324 RPN score loss: 0.00581 RPN total loss: 0.01905 Total loss: 0.80712 timestamp: 1654963960.476678 iteration: 63390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11492 FastRCNN class loss: 0.07396 FastRCNN total loss: 0.18888 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.13479 RPN box loss: 0.00716 RPN score loss: 0.01026 RPN total loss: 0.01743 Total loss: 0.93424 timestamp: 1654963963.5650864 iteration: 63395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11284 FastRCNN class loss: 0.08439 FastRCNN total loss: 0.19723 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.17083 RPN box loss: 0.01525 RPN score loss: 0.00576 RPN total loss: 0.02101 Total loss: 0.98222 timestamp: 1654963966.8076684 iteration: 63400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1053 FastRCNN class loss: 0.055 FastRCNN total loss: 0.1603 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.12315 RPN box loss: 0.01806 RPN score loss: 0.00093 RPN total loss: 0.01899 Total loss: 0.89558 timestamp: 1654963970.0367677 iteration: 63405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06459 FastRCNN class loss: 0.0494 FastRCNN total loss: 0.11399 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.11984 RPN box loss: 0.02696 RPN score loss: 0.00853 RPN total loss: 0.03549 Total loss: 0.86247 timestamp: 1654963973.2405941 iteration: 63410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06877 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.12829 L1 loss: 0.0000e+00 L2 loss: 0.59315 Learning rate: 0.0004 Mask loss: 0.12252 RPN box loss: 0.01963 RPN score loss: 0.00103 RPN total loss: 0.02066 Total loss: 0.86462 timestamp: 1654963976.4461818 iteration: 63415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07565 FastRCNN class loss: 0.05511 FastRCNN total loss: 0.13076 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.0004 Mask loss: 0.14264 RPN box loss: 0.012 RPN score loss: 0.01379 RPN total loss: 0.02578 Total loss: 0.89232 timestamp: 1654963979.6121607 iteration: 63420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.062 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.11745 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.0004 Mask loss: 0.19945 RPN box loss: 0.00485 RPN score loss: 0.00813 RPN total loss: 0.01297 Total loss: 0.92302 timestamp: 1654963982.8494341 iteration: 63425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10456 FastRCNN class loss: 0.10129 FastRCNN total loss: 0.20585 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.0004 Mask loss: 0.1675 RPN box loss: 0.01182 RPN score loss: 0.00772 RPN total loss: 0.01953 Total loss: 0.98603 timestamp: 1654963986.0769851 iteration: 63430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07673 FastRCNN class loss: 0.04406 FastRCNN total loss: 0.1208 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.0004 Mask loss: 0.0949 RPN box loss: 0.01169 RPN score loss: 0.00237 RPN total loss: 0.01406 Total loss: 0.82289 timestamp: 1654963989.274619 iteration: 63435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07827 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.15402 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.0004 Mask loss: 0.10182 RPN box loss: 0.00769 RPN score loss: 0.00575 RPN total loss: 0.01344 Total loss: 0.86241 timestamp: 1654963992.5148475 iteration: 63440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08107 FastRCNN class loss: 0.06742 FastRCNN total loss: 0.14849 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.0004 Mask loss: 0.16625 RPN box loss: 0.01386 RPN score loss: 0.00311 RPN total loss: 0.01698 Total loss: 0.92485 timestamp: 1654963995.7407308 iteration: 63445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07984 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.14468 L1 loss: 0.0000e+00 L2 loss: 0.59313 Learning rate: 0.0004 Mask loss: 0.1653 RPN box loss: 0.00369 RPN score loss: 0.00404 RPN total loss: 0.00772 Total loss: 0.91083 timestamp: 1654963998.9292421 iteration: 63450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08754 FastRCNN class loss: 0.05542 FastRCNN total loss: 0.14297 L1 loss: 0.0000e+00 L2 loss: 0.59313 Learning rate: 0.0004 Mask loss: 0.1078 RPN box loss: 0.00338 RPN score loss: 0.00161 RPN total loss: 0.00499 Total loss: 0.84889 timestamp: 1654964002.094451 iteration: 63455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06467 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.12007 L1 loss: 0.0000e+00 L2 loss: 0.59313 Learning rate: 0.0004 Mask loss: 0.08598 RPN box loss: 0.00587 RPN score loss: 0.00068 RPN total loss: 0.00656 Total loss: 0.80574 timestamp: 1654964005.2823608 iteration: 63460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08899 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.15877 L1 loss: 0.0000e+00 L2 loss: 0.59313 Learning rate: 0.0004 Mask loss: 0.13782 RPN box loss: 0.02094 RPN score loss: 0.00716 RPN total loss: 0.0281 Total loss: 0.91781 timestamp: 1654964008.4967902 iteration: 63465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14209 FastRCNN class loss: 0.10085 FastRCNN total loss: 0.24294 L1 loss: 0.0000e+00 L2 loss: 0.59313 Learning rate: 0.0004 Mask loss: 0.17714 RPN box loss: 0.01647 RPN score loss: 0.00849 RPN total loss: 0.02495 Total loss: 1.03816 timestamp: 1654964011.6950054 iteration: 63470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09624 FastRCNN class loss: 0.05193 FastRCNN total loss: 0.14817 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.17804 RPN box loss: 0.00746 RPN score loss: 0.00071 RPN total loss: 0.00817 Total loss: 0.9275 timestamp: 1654964014.8603597 iteration: 63475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08631 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.18365 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.18673 RPN box loss: 0.01687 RPN score loss: 0.01263 RPN total loss: 0.0295 Total loss: 0.993 timestamp: 1654964018.0321274 iteration: 63480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12084 FastRCNN class loss: 0.09668 FastRCNN total loss: 0.21752 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.14297 RPN box loss: 0.01039 RPN score loss: 0.00574 RPN total loss: 0.01613 Total loss: 0.96975 timestamp: 1654964021.1536994 iteration: 63485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07121 FastRCNN class loss: 0.09195 FastRCNN total loss: 0.16316 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.12243 RPN box loss: 0.01284 RPN score loss: 0.00648 RPN total loss: 0.01931 Total loss: 0.89802 timestamp: 1654964024.348706 iteration: 63490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08469 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.15987 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.13239 RPN box loss: 0.00615 RPN score loss: 0.0029 RPN total loss: 0.00905 Total loss: 0.89442 timestamp: 1654964027.5043292 iteration: 63495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08615 FastRCNN class loss: 0.06081 FastRCNN total loss: 0.14696 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.09295 RPN box loss: 0.00568 RPN score loss: 0.00252 RPN total loss: 0.0082 Total loss: 0.84122 timestamp: 1654964030.7350414 iteration: 63500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07068 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.12513 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.0004 Mask loss: 0.13425 RPN box loss: 0.01196 RPN score loss: 0.00309 RPN total loss: 0.01504 Total loss: 0.86754 timestamp: 1654964033.9847486 iteration: 63505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0881 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.14668 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.0004 Mask loss: 0.10139 RPN box loss: 0.00576 RPN score loss: 0.0022 RPN total loss: 0.00796 Total loss: 0.84914 timestamp: 1654964037.134497 iteration: 63510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11259 FastRCNN class loss: 0.09205 FastRCNN total loss: 0.20464 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.0004 Mask loss: 0.15914 RPN box loss: 0.04128 RPN score loss: 0.01304 RPN total loss: 0.05432 Total loss: 1.01121 timestamp: 1654964040.2976084 iteration: 63515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06535 FastRCNN class loss: 0.06303 FastRCNN total loss: 0.12838 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.0004 Mask loss: 0.13137 RPN box loss: 0.00958 RPN score loss: 0.00241 RPN total loss: 0.012 Total loss: 0.86486 timestamp: 1654964043.4909616 iteration: 63520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06991 FastRCNN class loss: 0.04912 FastRCNN total loss: 0.11903 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.0004 Mask loss: 0.15594 RPN box loss: 0.00949 RPN score loss: 0.0044 RPN total loss: 0.01389 Total loss: 0.88198 timestamp: 1654964046.7022645 iteration: 63525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08719 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.14673 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.0004 Mask loss: 0.09225 RPN box loss: 0.0056 RPN score loss: 0.00408 RPN total loss: 0.00968 Total loss: 0.84177 timestamp: 1654964049.929988 iteration: 63530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09521 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.1509 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.0004 Mask loss: 0.13268 RPN box loss: 0.00737 RPN score loss: 0.00253 RPN total loss: 0.0099 Total loss: 0.88658 timestamp: 1654964053.1550257 iteration: 63535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07426 FastRCNN class loss: 0.08462 FastRCNN total loss: 0.15888 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.0004 Mask loss: 0.11897 RPN box loss: 0.02097 RPN score loss: 0.00592 RPN total loss: 0.02689 Total loss: 0.89785 timestamp: 1654964056.3736153 iteration: 63540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10818 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.19531 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.0004 Mask loss: 0.16721 RPN box loss: 0.01877 RPN score loss: 0.001 RPN total loss: 0.01977 Total loss: 0.97539 timestamp: 1654964059.509579 iteration: 63545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05702 FastRCNN class loss: 0.04717 FastRCNN total loss: 0.1042 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.0004 Mask loss: 0.0969 RPN box loss: 0.01638 RPN score loss: 0.0027 RPN total loss: 0.01908 Total loss: 0.81327 timestamp: 1654964062.654774 iteration: 63550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07734 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.14182 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.0004 Mask loss: 0.11399 RPN box loss: 0.01036 RPN score loss: 0.00315 RPN total loss: 0.01351 Total loss: 0.86242 timestamp: 1654964065.7535708 iteration: 63555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03926 FastRCNN class loss: 0.05047 FastRCNN total loss: 0.08973 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.0004 Mask loss: 0.14631 RPN box loss: 0.02413 RPN score loss: 0.00349 RPN total loss: 0.02762 Total loss: 0.85675 timestamp: 1654964068.9732425 iteration: 63560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08298 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.13316 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.0004 Mask loss: 0.09251 RPN box loss: 0.00765 RPN score loss: 0.00584 RPN total loss: 0.01348 Total loss: 0.83226 timestamp: 1654964072.1883035 iteration: 63565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10169 FastRCNN class loss: 0.09005 FastRCNN total loss: 0.19174 L1 loss: 0.0000e+00 L2 loss: 0.59309 Learning rate: 0.0004 Mask loss: 0.12195 RPN box loss: 0.01743 RPN score loss: 0.00402 RPN total loss: 0.02146 Total loss: 0.92825 timestamp: 1654964075.3607135 iteration: 63570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0791 FastRCNN class loss: 0.0489 FastRCNN total loss: 0.128 L1 loss: 0.0000e+00 L2 loss: 0.59309 Learning rate: 0.0004 Mask loss: 0.11913 RPN box loss: 0.0256 RPN score loss: 0.00313 RPN total loss: 0.02874 Total loss: 0.86896 timestamp: 1654964078.5457008 iteration: 63575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07095 FastRCNN class loss: 0.04518 FastRCNN total loss: 0.11613 L1 loss: 0.0000e+00 L2 loss: 0.59309 Learning rate: 0.0004 Mask loss: 0.09678 RPN box loss: 0.02194 RPN score loss: 0.00305 RPN total loss: 0.025 Total loss: 0.83099 timestamp: 1654964081.767251 iteration: 63580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09178 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.16842 L1 loss: 0.0000e+00 L2 loss: 0.59309 Learning rate: 0.0004 Mask loss: 0.12722 RPN box loss: 0.01634 RPN score loss: 0.00259 RPN total loss: 0.01892 Total loss: 0.90764 timestamp: 1654964084.9195702 iteration: 63585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08166 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.14102 L1 loss: 0.0000e+00 L2 loss: 0.59309 Learning rate: 0.0004 Mask loss: 0.09543 RPN box loss: 0.01389 RPN score loss: 0.00102 RPN total loss: 0.01491 Total loss: 0.84445 timestamp: 1654964088.1245222 iteration: 63590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07087 FastRCNN class loss: 0.03892 FastRCNN total loss: 0.10979 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.0004 Mask loss: 0.10211 RPN box loss: 0.00413 RPN score loss: 0.00237 RPN total loss: 0.0065 Total loss: 0.81149 timestamp: 1654964091.2901545 iteration: 63595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07071 FastRCNN class loss: 0.11136 FastRCNN total loss: 0.18208 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.0004 Mask loss: 0.19865 RPN box loss: 0.01291 RPN score loss: 0.01222 RPN total loss: 0.02513 Total loss: 0.99893 timestamp: 1654964094.4590013 iteration: 63600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08604 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.15042 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.0004 Mask loss: 0.18457 RPN box loss: 0.01912 RPN score loss: 0.011 RPN total loss: 0.03011 Total loss: 0.95818 timestamp: 1654964097.584786 iteration: 63605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05334 FastRCNN class loss: 0.03655 FastRCNN total loss: 0.08988 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.0004 Mask loss: 0.05345 RPN box loss: 0.00722 RPN score loss: 0.00116 RPN total loss: 0.00839 Total loss: 0.7448 timestamp: 1654964100.7077463 iteration: 63610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05557 FastRCNN class loss: 0.05006 FastRCNN total loss: 0.10562 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.0004 Mask loss: 0.11866 RPN box loss: 0.01022 RPN score loss: 0.00394 RPN total loss: 0.01416 Total loss: 0.83152 timestamp: 1654964103.9310575 iteration: 63615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08955 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.19235 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.0004 Mask loss: 0.13871 RPN box loss: 0.00581 RPN score loss: 0.00304 RPN total loss: 0.00886 Total loss: 0.933 timestamp: 1654964107.149297 iteration: 63620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11448 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.17685 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.10206 RPN box loss: 0.01296 RPN score loss: 0.00389 RPN total loss: 0.01685 Total loss: 0.88884 timestamp: 1654964110.333223 iteration: 63625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08063 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.13097 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.12555 RPN box loss: 0.01271 RPN score loss: 0.00124 RPN total loss: 0.01394 Total loss: 0.86355 timestamp: 1654964113.5321736 iteration: 63630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07097 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.1338 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.10004 RPN box loss: 0.00484 RPN score loss: 0.00324 RPN total loss: 0.00808 Total loss: 0.83498 timestamp: 1654964116.8066263 iteration: 63635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11356 FastRCNN class loss: 0.12299 FastRCNN total loss: 0.23655 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.17844 RPN box loss: 0.02676 RPN score loss: 0.01009 RPN total loss: 0.03686 Total loss: 1.04492 timestamp: 1654964119.960978 iteration: 63640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09411 FastRCNN class loss: 0.04332 FastRCNN total loss: 0.13743 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.09619 RPN box loss: 0.01637 RPN score loss: 0.00096 RPN total loss: 0.01734 Total loss: 0.84403 timestamp: 1654964123.0949707 iteration: 63645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10086 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.17999 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.12193 RPN box loss: 0.01567 RPN score loss: 0.00994 RPN total loss: 0.02561 Total loss: 0.9206 timestamp: 1654964126.30998 iteration: 63650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06331 FastRCNN class loss: 0.0535 FastRCNN total loss: 0.11681 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.11227 RPN box loss: 0.00756 RPN score loss: 0.00616 RPN total loss: 0.01372 Total loss: 0.83586 timestamp: 1654964129.5834467 iteration: 63655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10665 FastRCNN class loss: 0.09143 FastRCNN total loss: 0.19808 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.0004 Mask loss: 0.18689 RPN box loss: 0.01072 RPN score loss: 0.00479 RPN total loss: 0.01552 Total loss: 0.99355 timestamp: 1654964132.811139 iteration: 63660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11798 FastRCNN class loss: 0.08646 FastRCNN total loss: 0.20444 L1 loss: 0.0000e+00 L2 loss: 0.59306 Learning rate: 0.0004 Mask loss: 0.09231 RPN box loss: 0.02363 RPN score loss: 0.01092 RPN total loss: 0.03455 Total loss: 0.92436 timestamp: 1654964135.9735937 iteration: 63665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13017 FastRCNN class loss: 0.09465 FastRCNN total loss: 0.22481 L1 loss: 0.0000e+00 L2 loss: 0.59306 Learning rate: 0.0004 Mask loss: 0.11939 RPN box loss: 0.00693 RPN score loss: 0.00479 RPN total loss: 0.01172 Total loss: 0.94898 timestamp: 1654964139.1766999 iteration: 63670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11288 FastRCNN class loss: 0.04175 FastRCNN total loss: 0.15463 L1 loss: 0.0000e+00 L2 loss: 0.59306 Learning rate: 0.0004 Mask loss: 0.10765 RPN box loss: 0.00702 RPN score loss: 0.00234 RPN total loss: 0.00936 Total loss: 0.86471 timestamp: 1654964142.3278103 iteration: 63675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08632 FastRCNN class loss: 0.10576 FastRCNN total loss: 0.19208 L1 loss: 0.0000e+00 L2 loss: 0.59306 Learning rate: 0.0004 Mask loss: 0.14895 RPN box loss: 0.01582 RPN score loss: 0.00378 RPN total loss: 0.0196 Total loss: 0.95369 timestamp: 1654964145.5499682 iteration: 63680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05233 FastRCNN class loss: 0.04422 FastRCNN total loss: 0.09655 L1 loss: 0.0000e+00 L2 loss: 0.59306 Learning rate: 0.0004 Mask loss: 0.13084 RPN box loss: 0.00723 RPN score loss: 0.00176 RPN total loss: 0.00899 Total loss: 0.82943 timestamp: 1654964148.7070642 iteration: 63685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0595 FastRCNN class loss: 0.05395 FastRCNN total loss: 0.11345 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.0004 Mask loss: 0.12725 RPN box loss: 0.01142 RPN score loss: 0.01899 RPN total loss: 0.03041 Total loss: 0.86417 timestamp: 1654964151.9276886 iteration: 63690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12361 FastRCNN class loss: 0.09139 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.0004 Mask loss: 0.15326 RPN box loss: 0.01509 RPN score loss: 0.00438 RPN total loss: 0.01947 Total loss: 0.98078 timestamp: 1654964155.1535678 iteration: 63695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08848 FastRCNN class loss: 0.04812 FastRCNN total loss: 0.1366 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.0004 Mask loss: 0.11449 RPN box loss: 0.00462 RPN score loss: 0.003 RPN total loss: 0.00762 Total loss: 0.85176 timestamp: 1654964158.372008 iteration: 63700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10796 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.18556 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.0004 Mask loss: 0.15404 RPN box loss: 0.01921 RPN score loss: 0.01452 RPN total loss: 0.03373 Total loss: 0.96637 timestamp: 1654964161.5401669 iteration: 63705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07067 FastRCNN class loss: 0.04746 FastRCNN total loss: 0.11814 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.0004 Mask loss: 0.08494 RPN box loss: 0.00531 RPN score loss: 0.00233 RPN total loss: 0.00765 Total loss: 0.80378 timestamp: 1654964164.7817054 iteration: 63710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08852 FastRCNN class loss: 0.07312 FastRCNN total loss: 0.16164 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.0004 Mask loss: 0.22108 RPN box loss: 0.01585 RPN score loss: 0.00377 RPN total loss: 0.01962 Total loss: 0.99538 timestamp: 1654964167.9490786 iteration: 63715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06515 FastRCNN class loss: 0.05847 FastRCNN total loss: 0.12363 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.0004 Mask loss: 0.10753 RPN box loss: 0.00601 RPN score loss: 0.00511 RPN total loss: 0.01112 Total loss: 0.83532 timestamp: 1654964171.095669 iteration: 63720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.07276 FastRCNN total loss: 0.16046 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.0004 Mask loss: 0.11273 RPN box loss: 0.00796 RPN score loss: 0.00273 RPN total loss: 0.01069 Total loss: 0.87693 timestamp: 1654964174.2698083 iteration: 63725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09066 FastRCNN class loss: 0.07462 FastRCNN total loss: 0.16528 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.0004 Mask loss: 0.18566 RPN box loss: 0.01556 RPN score loss: 0.01246 RPN total loss: 0.02801 Total loss: 0.972 timestamp: 1654964177.5254183 iteration: 63730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.16466 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.0004 Mask loss: 0.17675 RPN box loss: 0.00517 RPN score loss: 0.00452 RPN total loss: 0.00969 Total loss: 0.94414 timestamp: 1654964180.8079042 iteration: 63735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05059 FastRCNN class loss: 0.06395 FastRCNN total loss: 0.11454 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.0004 Mask loss: 0.12289 RPN box loss: 0.01374 RPN score loss: 0.00227 RPN total loss: 0.01601 Total loss: 0.84648 timestamp: 1654964183.9785008 iteration: 63740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06249 FastRCNN class loss: 0.05523 FastRCNN total loss: 0.11773 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.0004 Mask loss: 0.10604 RPN box loss: 0.0064 RPN score loss: 0.00125 RPN total loss: 0.00764 Total loss: 0.82445 timestamp: 1654964187.1938436 iteration: 63745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08568 FastRCNN class loss: 0.05371 FastRCNN total loss: 0.13939 L1 loss: 0.0000e+00 L2 loss: 0.59303 Learning rate: 0.0004 Mask loss: 0.13453 RPN box loss: 0.00563 RPN score loss: 0.00607 RPN total loss: 0.01171 Total loss: 0.87866 timestamp: 1654964190.3632135 iteration: 63750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16594 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.23625 L1 loss: 0.0000e+00 L2 loss: 0.59303 Learning rate: 0.0004 Mask loss: 0.13524 RPN box loss: 0.01778 RPN score loss: 0.00573 RPN total loss: 0.02351 Total loss: 0.98802 timestamp: 1654964193.4909735 iteration: 63755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07701 FastRCNN class loss: 0.03525 FastRCNN total loss: 0.11226 L1 loss: 0.0000e+00 L2 loss: 0.59303 Learning rate: 0.0004 Mask loss: 0.11897 RPN box loss: 0.01123 RPN score loss: 0.00114 RPN total loss: 0.01236 Total loss: 0.83662 timestamp: 1654964196.6799436 iteration: 63760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07239 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.12806 L1 loss: 0.0000e+00 L2 loss: 0.59303 Learning rate: 0.0004 Mask loss: 0.14274 RPN box loss: 0.00891 RPN score loss: 0.00458 RPN total loss: 0.01349 Total loss: 0.87732 timestamp: 1654964199.8495212 iteration: 63765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07365 FastRCNN class loss: 0.04796 FastRCNN total loss: 0.12161 L1 loss: 0.0000e+00 L2 loss: 0.59303 Learning rate: 0.0004 Mask loss: 0.13253 RPN box loss: 0.00427 RPN score loss: 0.0043 RPN total loss: 0.00857 Total loss: 0.85574 timestamp: 1654964203.1186316 iteration: 63770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09557 FastRCNN class loss: 0.05926 FastRCNN total loss: 0.15482 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.0004 Mask loss: 0.12205 RPN box loss: 0.01423 RPN score loss: 0.00201 RPN total loss: 0.01624 Total loss: 0.88614 timestamp: 1654964206.3482778 iteration: 63775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.14538 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.0004 Mask loss: 0.13079 RPN box loss: 0.01129 RPN score loss: 0.00969 RPN total loss: 0.02098 Total loss: 0.89017 timestamp: 1654964209.5144682 iteration: 63780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09146 FastRCNN class loss: 0.0656 FastRCNN total loss: 0.15705 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.0004 Mask loss: 0.07303 RPN box loss: 0.00947 RPN score loss: 0.00298 RPN total loss: 0.01245 Total loss: 0.83555 timestamp: 1654964212.6647599 iteration: 63785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11561 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.19078 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.0004 Mask loss: 0.1726 RPN box loss: 0.00765 RPN score loss: 0.00467 RPN total loss: 0.01232 Total loss: 0.96872 timestamp: 1654964215.9025986 iteration: 63790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11615 FastRCNN class loss: 0.07789 FastRCNN total loss: 0.19404 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.0004 Mask loss: 0.19197 RPN box loss: 0.01645 RPN score loss: 0.0077 RPN total loss: 0.02414 Total loss: 1.00317 timestamp: 1654964219.1503057 iteration: 63795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16957 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.25362 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.0004 Mask loss: 0.11175 RPN box loss: 0.01504 RPN score loss: 0.00405 RPN total loss: 0.01909 Total loss: 0.97748 timestamp: 1654964222.2985406 iteration: 63800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12403 FastRCNN class loss: 0.07416 FastRCNN total loss: 0.19819 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.0004 Mask loss: 0.1283 RPN box loss: 0.01227 RPN score loss: 0.00322 RPN total loss: 0.01549 Total loss: 0.93499 timestamp: 1654964225.5353382 iteration: 63805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09865 FastRCNN class loss: 0.09991 FastRCNN total loss: 0.19856 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.0004 Mask loss: 0.21261 RPN box loss: 0.01442 RPN score loss: 0.00457 RPN total loss: 0.019 Total loss: 1.02318 timestamp: 1654964228.73228 iteration: 63810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10692 FastRCNN class loss: 0.11254 FastRCNN total loss: 0.21946 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.0004 Mask loss: 0.1204 RPN box loss: 0.01691 RPN score loss: 0.00637 RPN total loss: 0.02328 Total loss: 0.95615 timestamp: 1654964231.8953123 iteration: 63815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08945 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.15104 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.0004 Mask loss: 0.09527 RPN box loss: 0.02896 RPN score loss: 0.00207 RPN total loss: 0.03103 Total loss: 0.87035 timestamp: 1654964235.118121 iteration: 63820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09986 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.16561 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.0004 Mask loss: 0.14472 RPN box loss: 0.01393 RPN score loss: 0.00314 RPN total loss: 0.01707 Total loss: 0.9204 timestamp: 1654964238.2859838 iteration: 63825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13592 FastRCNN class loss: 0.09836 FastRCNN total loss: 0.23428 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.0004 Mask loss: 0.16313 RPN box loss: 0.08224 RPN score loss: 0.02044 RPN total loss: 0.10269 Total loss: 1.0931 timestamp: 1654964241.4741983 iteration: 63830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06565 FastRCNN class loss: 0.06854 FastRCNN total loss: 0.13418 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.0004 Mask loss: 0.07865 RPN box loss: 0.00536 RPN score loss: 0.00405 RPN total loss: 0.0094 Total loss: 0.81524 timestamp: 1654964244.7401283 iteration: 63835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11603 FastRCNN class loss: 0.08312 FastRCNN total loss: 0.19915 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.0004 Mask loss: 0.10771 RPN box loss: 0.00842 RPN score loss: 0.00558 RPN total loss: 0.014 Total loss: 0.91386 timestamp: 1654964247.9733305 iteration: 63840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.03734 FastRCNN total loss: 0.10715 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.0004 Mask loss: 0.085 RPN box loss: 0.00385 RPN score loss: 0.009 RPN total loss: 0.01284 Total loss: 0.79799 timestamp: 1654964251.1144218 iteration: 63845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08414 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.15944 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.0004 Mask loss: 0.1692 RPN box loss: 0.00741 RPN score loss: 0.00709 RPN total loss: 0.0145 Total loss: 0.93614 timestamp: 1654964254.3070524 iteration: 63850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12017 FastRCNN class loss: 0.03489 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.0004 Mask loss: 0.08101 RPN box loss: 0.00634 RPN score loss: 0.00281 RPN total loss: 0.00916 Total loss: 0.83822 timestamp: 1654964257.535257 iteration: 63855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.16291 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.0004 Mask loss: 0.13247 RPN box loss: 0.00463 RPN score loss: 0.00132 RPN total loss: 0.00596 Total loss: 0.89434 timestamp: 1654964260.7900875 iteration: 63860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07035 FastRCNN class loss: 0.09149 FastRCNN total loss: 0.16185 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.15047 RPN box loss: 0.00691 RPN score loss: 0.00146 RPN total loss: 0.00837 Total loss: 0.91368 timestamp: 1654964264.0033236 iteration: 63865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04684 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.09533 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.11002 RPN box loss: 0.00614 RPN score loss: 0.00075 RPN total loss: 0.00689 Total loss: 0.80523 timestamp: 1654964267.2324693 iteration: 63870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06829 FastRCNN class loss: 0.06398 FastRCNN total loss: 0.13226 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.14372 RPN box loss: 0.00475 RPN score loss: 0.0038 RPN total loss: 0.00855 Total loss: 0.87753 timestamp: 1654964270.4239197 iteration: 63875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10782 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.18996 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.14453 RPN box loss: 0.01261 RPN score loss: 0.01055 RPN total loss: 0.02317 Total loss: 0.95065 timestamp: 1654964273.6444151 iteration: 63880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09666 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.16458 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.1756 RPN box loss: 0.00813 RPN score loss: 0.00703 RPN total loss: 0.01516 Total loss: 0.94834 timestamp: 1654964276.8812897 iteration: 63885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05205 FastRCNN class loss: 0.053 FastRCNN total loss: 0.10505 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.14322 RPN box loss: 0.00449 RPN score loss: 0.00604 RPN total loss: 0.01053 Total loss: 0.85179 timestamp: 1654964280.0577831 iteration: 63890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08148 FastRCNN class loss: 0.06094 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.0004 Mask loss: 0.19238 RPN box loss: 0.00915 RPN score loss: 0.0099 RPN total loss: 0.01904 Total loss: 0.94683 timestamp: 1654964283.1942077 iteration: 63895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10117 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.16357 L1 loss: 0.0000e+00 L2 loss: 0.59298 Learning rate: 0.0004 Mask loss: 0.14392 RPN box loss: 0.03031 RPN score loss: 0.00561 RPN total loss: 0.03592 Total loss: 0.93639 timestamp: 1654964286.4601088 iteration: 63900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07252 FastRCNN class loss: 0.05592 FastRCNN total loss: 0.12843 L1 loss: 0.0000e+00 L2 loss: 0.59298 Learning rate: 0.0004 Mask loss: 0.1324 RPN box loss: 0.007 RPN score loss: 0.00609 RPN total loss: 0.01309 Total loss: 0.86691 timestamp: 1654964289.6336923 iteration: 63905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.15296 L1 loss: 0.0000e+00 L2 loss: 0.59298 Learning rate: 0.0004 Mask loss: 0.09879 RPN box loss: 0.00701 RPN score loss: 0.00348 RPN total loss: 0.01049 Total loss: 0.85521 timestamp: 1654964292.9134333 iteration: 63910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10867 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.20452 L1 loss: 0.0000e+00 L2 loss: 0.59298 Learning rate: 0.0004 Mask loss: 0.1511 RPN box loss: 0.01459 RPN score loss: 0.00821 RPN total loss: 0.0228 Total loss: 0.97139 timestamp: 1654964296.1632776 iteration: 63915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12801 FastRCNN class loss: 0.08531 FastRCNN total loss: 0.21332 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.0004 Mask loss: 0.09544 RPN box loss: 0.00433 RPN score loss: 0.00524 RPN total loss: 0.00957 Total loss: 0.9113 timestamp: 1654964299.2950392 iteration: 63920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10016 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.1554 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.0004 Mask loss: 0.1659 RPN box loss: 0.006 RPN score loss: 0.00221 RPN total loss: 0.00821 Total loss: 0.92248 timestamp: 1654964302.4598727 iteration: 63925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07034 FastRCNN class loss: 0.05084 FastRCNN total loss: 0.12118 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.0004 Mask loss: 0.11013 RPN box loss: 0.00705 RPN score loss: 0.0044 RPN total loss: 0.01145 Total loss: 0.83574 timestamp: 1654964305.6205444 iteration: 63930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05618 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.11053 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.0004 Mask loss: 0.08168 RPN box loss: 0.01906 RPN score loss: 0.00529 RPN total loss: 0.02435 Total loss: 0.80953 timestamp: 1654964308.8144782 iteration: 63935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12535 FastRCNN class loss: 0.0759 FastRCNN total loss: 0.20125 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.0004 Mask loss: 0.16902 RPN box loss: 0.00564 RPN score loss: 0.00838 RPN total loss: 0.01402 Total loss: 0.97725 timestamp: 1654964311.9711232 iteration: 63940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08506 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.16606 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.0004 Mask loss: 0.1259 RPN box loss: 0.00929 RPN score loss: 0.00629 RPN total loss: 0.01557 Total loss: 0.9005 timestamp: 1654964315.1042087 iteration: 63945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08958 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.16146 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.0004 Mask loss: 0.15787 RPN box loss: 0.00815 RPN score loss: 0.00269 RPN total loss: 0.01084 Total loss: 0.92314 timestamp: 1654964318.2882404 iteration: 63950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10691 FastRCNN class loss: 0.10432 FastRCNN total loss: 0.21123 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.0004 Mask loss: 0.13302 RPN box loss: 0.01035 RPN score loss: 0.0086 RPN total loss: 0.01895 Total loss: 0.95616 timestamp: 1654964321.4307733 iteration: 63955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07294 FastRCNN class loss: 0.0643 FastRCNN total loss: 0.13724 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.0004 Mask loss: 0.16237 RPN box loss: 0.00846 RPN score loss: 0.00348 RPN total loss: 0.01193 Total loss: 0.90451 timestamp: 1654964324.5673816 iteration: 63960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09105 FastRCNN class loss: 0.04963 FastRCNN total loss: 0.14068 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.0004 Mask loss: 0.12091 RPN box loss: 0.00922 RPN score loss: 0.00425 RPN total loss: 0.01347 Total loss: 0.86802 timestamp: 1654964327.8800845 iteration: 63965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11065 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.19271 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.0004 Mask loss: 0.23337 RPN box loss: 0.0123 RPN score loss: 0.00893 RPN total loss: 0.02123 Total loss: 1.04026 timestamp: 1654964330.995835 iteration: 63970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.15663 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.0004 Mask loss: 0.15152 RPN box loss: 0.00651 RPN score loss: 0.00419 RPN total loss: 0.0107 Total loss: 0.9118 timestamp: 1654964334.1775303 iteration: 63975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1109 FastRCNN class loss: 0.07988 FastRCNN total loss: 0.19078 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.0004 Mask loss: 0.13166 RPN box loss: 0.02012 RPN score loss: 0.00984 RPN total loss: 0.02997 Total loss: 0.94536 timestamp: 1654964337.3621876 iteration: 63980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07783 FastRCNN class loss: 0.07521 FastRCNN total loss: 0.15305 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.0004 Mask loss: 0.16504 RPN box loss: 0.01382 RPN score loss: 0.00629 RPN total loss: 0.02011 Total loss: 0.93115 timestamp: 1654964340.5508065 iteration: 63985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.04521 FastRCNN total loss: 0.14375 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.0004 Mask loss: 0.08702 RPN box loss: 0.00813 RPN score loss: 0.00605 RPN total loss: 0.01418 Total loss: 0.8379 timestamp: 1654964343.7277164 iteration: 63990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12556 FastRCNN class loss: 0.08004 FastRCNN total loss: 0.2056 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.0004 Mask loss: 0.14005 RPN box loss: 0.00846 RPN score loss: 0.00375 RPN total loss: 0.01221 Total loss: 0.9508 timestamp: 1654964346.9396384 iteration: 63995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06507 FastRCNN class loss: 0.05022 FastRCNN total loss: 0.11529 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.0004 Mask loss: 0.09463 RPN box loss: 0.01218 RPN score loss: 0.00597 RPN total loss: 0.01816 Total loss: 0.82103 timestamp: 1654964350.0956094 iteration: 64000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13179 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.19557 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.0004 Mask loss: 0.10412 RPN box loss: 0.01006 RPN score loss: 0.00402 RPN total loss: 0.01409 Total loss: 0.90673 timestamp: 1654964353.2150364 iteration: 64005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08774 FastRCNN class loss: 0.12031 FastRCNN total loss: 0.20805 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.0004 Mask loss: 0.11194 RPN box loss: 0.00643 RPN score loss: 0.00415 RPN total loss: 0.01058 Total loss: 0.9235 timestamp: 1654964356.3705983 iteration: 64010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.16313 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.0004 Mask loss: 0.12605 RPN box loss: 0.01935 RPN score loss: 0.00475 RPN total loss: 0.0241 Total loss: 0.90622 timestamp: 1654964359.5895662 iteration: 64015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10258 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.16511 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.0004 Mask loss: 0.09385 RPN box loss: 0.00759 RPN score loss: 0.00828 RPN total loss: 0.01587 Total loss: 0.86777 timestamp: 1654964362.864627 iteration: 64020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07639 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.14248 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.0004 Mask loss: 0.12282 RPN box loss: 0.04237 RPN score loss: 0.01116 RPN total loss: 0.05352 Total loss: 0.91176 timestamp: 1654964366.0398834 iteration: 64025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09091 FastRCNN class loss: 0.04725 FastRCNN total loss: 0.13816 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.0004 Mask loss: 0.12358 RPN box loss: 0.01044 RPN score loss: 0.00618 RPN total loss: 0.01661 Total loss: 0.87128 timestamp: 1654964369.2633095 iteration: 64030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.0795 FastRCNN total loss: 0.17972 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.13734 RPN box loss: 0.00637 RPN score loss: 0.00287 RPN total loss: 0.00924 Total loss: 0.91924 timestamp: 1654964372.5593555 iteration: 64035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11744 FastRCNN class loss: 0.07635 FastRCNN total loss: 0.19379 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.1131 RPN box loss: 0.02088 RPN score loss: 0.00591 RPN total loss: 0.02679 Total loss: 0.92661 timestamp: 1654964375.6900485 iteration: 64040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12123 FastRCNN class loss: 0.11218 FastRCNN total loss: 0.23341 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.21004 RPN box loss: 0.01077 RPN score loss: 0.00647 RPN total loss: 0.01724 Total loss: 1.05362 timestamp: 1654964378.8299809 iteration: 64045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07258 FastRCNN class loss: 0.0512 FastRCNN total loss: 0.12378 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.16741 RPN box loss: 0.01587 RPN score loss: 0.00099 RPN total loss: 0.01686 Total loss: 0.90098 timestamp: 1654964381.9260783 iteration: 64050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0559 FastRCNN class loss: 0.0371 FastRCNN total loss: 0.093 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.10104 RPN box loss: 0.01824 RPN score loss: 0.00069 RPN total loss: 0.01892 Total loss: 0.80589 timestamp: 1654964385.1880634 iteration: 64055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06841 FastRCNN class loss: 0.04176 FastRCNN total loss: 0.11017 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.12436 RPN box loss: 0.02437 RPN score loss: 0.00698 RPN total loss: 0.03135 Total loss: 0.8588 timestamp: 1654964388.4756947 iteration: 64060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18524 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.25549 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.0004 Mask loss: 0.1329 RPN box loss: 0.0188 RPN score loss: 0.00499 RPN total loss: 0.02379 Total loss: 1.00511 timestamp: 1654964391.7172008 iteration: 64065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08849 FastRCNN class loss: 0.04453 FastRCNN total loss: 0.13302 L1 loss: 0.0000e+00 L2 loss: 0.59292 Learning rate: 0.0004 Mask loss: 0.12467 RPN box loss: 0.00555 RPN score loss: 0.00128 RPN total loss: 0.00684 Total loss: 0.85745 timestamp: 1654964394.8840716 iteration: 64070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08008 FastRCNN class loss: 0.04438 FastRCNN total loss: 0.12446 L1 loss: 0.0000e+00 L2 loss: 0.59292 Learning rate: 0.0004 Mask loss: 0.13639 RPN box loss: 0.00373 RPN score loss: 0.00345 RPN total loss: 0.00718 Total loss: 0.86096 timestamp: 1654964398.0839846 iteration: 64075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06523 FastRCNN class loss: 0.06613 FastRCNN total loss: 0.13136 L1 loss: 0.0000e+00 L2 loss: 0.59292 Learning rate: 0.0004 Mask loss: 0.14096 RPN box loss: 0.00788 RPN score loss: 0.00462 RPN total loss: 0.0125 Total loss: 0.87774 timestamp: 1654964401.3611593 iteration: 64080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07582 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.13799 L1 loss: 0.0000e+00 L2 loss: 0.59292 Learning rate: 0.0004 Mask loss: 0.14044 RPN box loss: 0.01133 RPN score loss: 0.00504 RPN total loss: 0.01637 Total loss: 0.88772 timestamp: 1654964404.535935 iteration: 64085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11475 FastRCNN class loss: 0.10417 FastRCNN total loss: 0.21891 L1 loss: 0.0000e+00 L2 loss: 0.59292 Learning rate: 0.0004 Mask loss: 0.18564 RPN box loss: 0.01475 RPN score loss: 0.00575 RPN total loss: 0.0205 Total loss: 1.01797 timestamp: 1654964407.7429435 iteration: 64090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09782 FastRCNN class loss: 0.11611 FastRCNN total loss: 0.21393 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.0004 Mask loss: 0.13957 RPN box loss: 0.01139 RPN score loss: 0.00352 RPN total loss: 0.01491 Total loss: 0.96132 timestamp: 1654964410.9496942 iteration: 64095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0632 FastRCNN class loss: 0.08154 FastRCNN total loss: 0.14473 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.0004 Mask loss: 0.10603 RPN box loss: 0.0072 RPN score loss: 0.00489 RPN total loss: 0.01209 Total loss: 0.85576 timestamp: 1654964414.1317594 iteration: 64100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11356 FastRCNN class loss: 0.0801 FastRCNN total loss: 0.19366 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.0004 Mask loss: 0.12809 RPN box loss: 0.02514 RPN score loss: 0.00627 RPN total loss: 0.0314 Total loss: 0.94606 timestamp: 1654964417.464341 iteration: 64105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09934 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.16679 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.0004 Mask loss: 0.16502 RPN box loss: 0.00604 RPN score loss: 0.00602 RPN total loss: 0.01207 Total loss: 0.93678 timestamp: 1654964420.6559017 iteration: 64110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12521 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.19926 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.0004 Mask loss: 0.12882 RPN box loss: 0.00751 RPN score loss: 0.00369 RPN total loss: 0.0112 Total loss: 0.93219 timestamp: 1654964423.8822324 iteration: 64115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08976 FastRCNN class loss: 0.08421 FastRCNN total loss: 0.17398 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.0004 Mask loss: 0.12535 RPN box loss: 0.01458 RPN score loss: 0.00789 RPN total loss: 0.02247 Total loss: 0.91471 timestamp: 1654964427.1203017 iteration: 64120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11986 FastRCNN class loss: 0.07019 FastRCNN total loss: 0.19005 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.14433 RPN box loss: 0.01409 RPN score loss: 0.00416 RPN total loss: 0.01825 Total loss: 0.94554 timestamp: 1654964430.369135 iteration: 64125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15517 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.22443 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.11743 RPN box loss: 0.02508 RPN score loss: 0.00632 RPN total loss: 0.0314 Total loss: 0.96617 timestamp: 1654964433.5341556 iteration: 64130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12781 FastRCNN class loss: 0.15197 FastRCNN total loss: 0.27978 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.24063 RPN box loss: 0.03046 RPN score loss: 0.07141 RPN total loss: 0.10187 Total loss: 1.21518 timestamp: 1654964436.775225 iteration: 64135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03821 FastRCNN class loss: 0.04346 FastRCNN total loss: 0.08167 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.11117 RPN box loss: 0.02417 RPN score loss: 0.00202 RPN total loss: 0.02618 Total loss: 0.81193 timestamp: 1654964439.9652019 iteration: 64140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12585 FastRCNN class loss: 0.06256 FastRCNN total loss: 0.1884 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.1161 RPN box loss: 0.00801 RPN score loss: 0.00755 RPN total loss: 0.01556 Total loss: 0.91296 timestamp: 1654964443.115958 iteration: 64145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09906 FastRCNN class loss: 0.06449 FastRCNN total loss: 0.16355 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.13359 RPN box loss: 0.03395 RPN score loss: 0.01068 RPN total loss: 0.04463 Total loss: 0.93467 timestamp: 1654964446.2873652 iteration: 64150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12146 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.20579 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.0004 Mask loss: 0.15365 RPN box loss: 0.0185 RPN score loss: 0.00521 RPN total loss: 0.02372 Total loss: 0.97605 timestamp: 1654964449.512558 iteration: 64155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08753 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.15188 L1 loss: 0.0000e+00 L2 loss: 0.59289 Learning rate: 0.0004 Mask loss: 0.1299 RPN box loss: 0.01032 RPN score loss: 0.00481 RPN total loss: 0.01513 Total loss: 0.8898 timestamp: 1654964452.7023013 iteration: 64160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0458 FastRCNN class loss: 0.04545 FastRCNN total loss: 0.09126 L1 loss: 0.0000e+00 L2 loss: 0.59289 Learning rate: 0.0004 Mask loss: 0.08048 RPN box loss: 0.00428 RPN score loss: 0.00086 RPN total loss: 0.00514 Total loss: 0.76977 timestamp: 1654964455.9145303 iteration: 64165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06708 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.12137 L1 loss: 0.0000e+00 L2 loss: 0.59289 Learning rate: 0.0004 Mask loss: 0.15206 RPN box loss: 0.00766 RPN score loss: 0.00583 RPN total loss: 0.01349 Total loss: 0.8798 timestamp: 1654964459.0956478 iteration: 64170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1293 FastRCNN class loss: 0.07746 FastRCNN total loss: 0.20676 L1 loss: 0.0000e+00 L2 loss: 0.59289 Learning rate: 0.0004 Mask loss: 0.15313 RPN box loss: 0.01037 RPN score loss: 0.00802 RPN total loss: 0.01839 Total loss: 0.97117 timestamp: 1654964462.2048724 iteration: 64175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06295 FastRCNN class loss: 0.04706 FastRCNN total loss: 0.11001 L1 loss: 0.0000e+00 L2 loss: 0.59289 Learning rate: 0.0004 Mask loss: 0.10622 RPN box loss: 0.00977 RPN score loss: 0.00288 RPN total loss: 0.01265 Total loss: 0.82177 timestamp: 1654964465.4829931 iteration: 64180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12805 FastRCNN class loss: 0.05923 FastRCNN total loss: 0.18728 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.0004 Mask loss: 0.14076 RPN box loss: 0.00651 RPN score loss: 0.00356 RPN total loss: 0.01007 Total loss: 0.931 timestamp: 1654964468.7584524 iteration: 64185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07436 FastRCNN class loss: 0.02765 FastRCNN total loss: 0.10201 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.0004 Mask loss: 0.12929 RPN box loss: 0.00271 RPN score loss: 0.00157 RPN total loss: 0.00429 Total loss: 0.82847 timestamp: 1654964472.0016863 iteration: 64190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09217 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.18124 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.0004 Mask loss: 0.17693 RPN box loss: 0.01643 RPN score loss: 0.00907 RPN total loss: 0.02551 Total loss: 0.97656 timestamp: 1654964475.14265 iteration: 64195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12934 FastRCNN class loss: 0.10065 FastRCNN total loss: 0.22998 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.0004 Mask loss: 0.15939 RPN box loss: 0.01745 RPN score loss: 0.00645 RPN total loss: 0.0239 Total loss: 1.00615 timestamp: 1654964478.3237493 iteration: 64200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07762 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.14368 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.0004 Mask loss: 0.13006 RPN box loss: 0.01664 RPN score loss: 0.02168 RPN total loss: 0.03833 Total loss: 0.90495 timestamp: 1654964481.5325847 iteration: 64205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07822 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.15892 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.0004 Mask loss: 0.12962 RPN box loss: 0.0084 RPN score loss: 0.0034 RPN total loss: 0.01179 Total loss: 0.8932 timestamp: 1654964484.6888847 iteration: 64210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08574 FastRCNN class loss: 0.04261 FastRCNN total loss: 0.12835 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.0004 Mask loss: 0.09407 RPN box loss: 0.00834 RPN score loss: 0.00417 RPN total loss: 0.01252 Total loss: 0.82781 timestamp: 1654964487.8779757 iteration: 64215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04113 FastRCNN class loss: 0.04037 FastRCNN total loss: 0.0815 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.0004 Mask loss: 0.14088 RPN box loss: 0.00354 RPN score loss: 0.003 RPN total loss: 0.00654 Total loss: 0.82179 timestamp: 1654964491.0957015 iteration: 64220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06245 FastRCNN class loss: 0.04637 FastRCNN total loss: 0.10881 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.0004 Mask loss: 0.10882 RPN box loss: 0.00683 RPN score loss: 0.00451 RPN total loss: 0.01134 Total loss: 0.82185 timestamp: 1654964494.2411005 iteration: 64225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12004 FastRCNN class loss: 0.05428 FastRCNN total loss: 0.17432 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.0004 Mask loss: 0.11487 RPN box loss: 0.01795 RPN score loss: 0.00766 RPN total loss: 0.02561 Total loss: 0.90767 timestamp: 1654964497.4515357 iteration: 64230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12311 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.19373 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.0004 Mask loss: 0.10727 RPN box loss: 0.00388 RPN score loss: 0.00172 RPN total loss: 0.0056 Total loss: 0.89946 timestamp: 1654964500.6656332 iteration: 64235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14227 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.20959 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.1578 RPN box loss: 0.01343 RPN score loss: 0.00304 RPN total loss: 0.01647 Total loss: 0.97672 timestamp: 1654964503.8067617 iteration: 64240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08035 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.16638 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.15822 RPN box loss: 0.01609 RPN score loss: 0.00185 RPN total loss: 0.01794 Total loss: 0.93541 timestamp: 1654964507.0222208 iteration: 64245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06088 FastRCNN class loss: 0.04632 FastRCNN total loss: 0.10721 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.12502 RPN box loss: 0.01099 RPN score loss: 0.0137 RPN total loss: 0.02469 Total loss: 0.84978 timestamp: 1654964510.274348 iteration: 64250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06189 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.1193 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.10859 RPN box loss: 0.00552 RPN score loss: 0.00293 RPN total loss: 0.00845 Total loss: 0.82919 timestamp: 1654964513.455685 iteration: 64255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12176 FastRCNN class loss: 0.0577 FastRCNN total loss: 0.17946 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.09171 RPN box loss: 0.00643 RPN score loss: 0.00441 RPN total loss: 0.01084 Total loss: 0.87487 timestamp: 1654964516.5830622 iteration: 64260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04999 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.12249 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.14117 RPN box loss: 0.00939 RPN score loss: 0.0038 RPN total loss: 0.01319 Total loss: 0.86971 timestamp: 1654964519.800693 iteration: 64265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05605 FastRCNN class loss: 0.08326 FastRCNN total loss: 0.13931 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.10581 RPN box loss: 0.007 RPN score loss: 0.01098 RPN total loss: 0.01798 Total loss: 0.85596 timestamp: 1654964522.978053 iteration: 64270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07736 FastRCNN class loss: 0.08351 FastRCNN total loss: 0.16087 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.0004 Mask loss: 0.14203 RPN box loss: 0.00948 RPN score loss: 0.00791 RPN total loss: 0.01739 Total loss: 0.91315 timestamp: 1654964526.1864913 iteration: 64275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11328 FastRCNN class loss: 0.06402 FastRCNN total loss: 0.1773 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.0004 Mask loss: 0.11275 RPN box loss: 0.01061 RPN score loss: 0.00213 RPN total loss: 0.01274 Total loss: 0.89565 timestamp: 1654964529.4006088 iteration: 64280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07657 FastRCNN class loss: 0.03935 FastRCNN total loss: 0.11593 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.0004 Mask loss: 0.12473 RPN box loss: 0.01057 RPN score loss: 0.0036 RPN total loss: 0.01417 Total loss: 0.84767 timestamp: 1654964532.5909498 iteration: 64285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10151 FastRCNN class loss: 0.08089 FastRCNN total loss: 0.18239 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.0004 Mask loss: 0.19788 RPN box loss: 0.02031 RPN score loss: 0.00299 RPN total loss: 0.0233 Total loss: 0.99643 timestamp: 1654964535.9357717 iteration: 64290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.05123 FastRCNN total loss: 0.14581 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.0004 Mask loss: 0.1521 RPN box loss: 0.01119 RPN score loss: 0.00478 RPN total loss: 0.01597 Total loss: 0.90673 timestamp: 1654964539.121101 iteration: 64295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10039 FastRCNN class loss: 0.04626 FastRCNN total loss: 0.14664 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.0004 Mask loss: 0.11429 RPN box loss: 0.00941 RPN score loss: 0.00488 RPN total loss: 0.01429 Total loss: 0.86807 timestamp: 1654964542.3048234 iteration: 64300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07573 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.13774 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.0004 Mask loss: 0.15311 RPN box loss: 0.00546 RPN score loss: 0.0051 RPN total loss: 0.01057 Total loss: 0.89427 timestamp: 1654964545.4568877 iteration: 64305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05956 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.11698 L1 loss: 0.0000e+00 L2 loss: 0.59284 Learning rate: 0.0004 Mask loss: 0.09864 RPN box loss: 0.00476 RPN score loss: 0.003 RPN total loss: 0.00775 Total loss: 0.81621 timestamp: 1654964548.5594704 iteration: 64310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08665 FastRCNN class loss: 0.09109 FastRCNN total loss: 0.17773 L1 loss: 0.0000e+00 L2 loss: 0.59284 Learning rate: 0.0004 Mask loss: 0.12721 RPN box loss: 0.00739 RPN score loss: 0.00686 RPN total loss: 0.01425 Total loss: 0.91203 timestamp: 1654964551.7495968 iteration: 64315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08701 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.15616 L1 loss: 0.0000e+00 L2 loss: 0.59284 Learning rate: 0.0004 Mask loss: 0.14633 RPN box loss: 0.02761 RPN score loss: 0.00481 RPN total loss: 0.03242 Total loss: 0.92775 timestamp: 1654964554.9551084 iteration: 64320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1254 FastRCNN class loss: 0.08914 FastRCNN total loss: 0.21454 L1 loss: 0.0000e+00 L2 loss: 0.59284 Learning rate: 0.0004 Mask loss: 0.13554 RPN box loss: 0.02828 RPN score loss: 0.00932 RPN total loss: 0.0376 Total loss: 0.98052 timestamp: 1654964558.0228345 iteration: 64325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10301 FastRCNN class loss: 0.09797 FastRCNN total loss: 0.20098 L1 loss: 0.0000e+00 L2 loss: 0.59284 Learning rate: 0.0004 Mask loss: 0.11568 RPN box loss: 0.01374 RPN score loss: 0.0179 RPN total loss: 0.03164 Total loss: 0.94114 timestamp: 1654964561.1882195 iteration: 64330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08761 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.15485 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.0004 Mask loss: 0.1425 RPN box loss: 0.01438 RPN score loss: 0.00141 RPN total loss: 0.01579 Total loss: 0.90597 timestamp: 1654964564.3276396 iteration: 64335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11762 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.1802 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.0004 Mask loss: 0.12605 RPN box loss: 0.02893 RPN score loss: 0.00434 RPN total loss: 0.03327 Total loss: 0.93235 timestamp: 1654964567.494402 iteration: 64340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07446 FastRCNN class loss: 0.02753 FastRCNN total loss: 0.10199 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.0004 Mask loss: 0.0839 RPN box loss: 0.00927 RPN score loss: 0.00171 RPN total loss: 0.01098 Total loss: 0.78971 timestamp: 1654964570.6448956 iteration: 64345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07466 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.13845 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.0004 Mask loss: 0.08205 RPN box loss: 0.01197 RPN score loss: 0.0027 RPN total loss: 0.01467 Total loss: 0.82801 timestamp: 1654964573.809658 iteration: 64350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11963 FastRCNN class loss: 0.08281 FastRCNN total loss: 0.20244 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.0004 Mask loss: 0.17155 RPN box loss: 0.01844 RPN score loss: 0.00579 RPN total loss: 0.02423 Total loss: 0.99105 timestamp: 1654964577.0591667 iteration: 64355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10207 FastRCNN class loss: 0.04607 FastRCNN total loss: 0.14814 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.1568 RPN box loss: 0.00912 RPN score loss: 0.00361 RPN total loss: 0.01273 Total loss: 0.91049 timestamp: 1654964580.1819599 iteration: 64360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05887 FastRCNN class loss: 0.04836 FastRCNN total loss: 0.10723 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.11577 RPN box loss: 0.01356 RPN score loss: 0.00078 RPN total loss: 0.01435 Total loss: 0.83018 timestamp: 1654964583.3868585 iteration: 64365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09442 FastRCNN class loss: 0.0549 FastRCNN total loss: 0.14932 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.10893 RPN box loss: 0.01379 RPN score loss: 0.00168 RPN total loss: 0.01547 Total loss: 0.86654 timestamp: 1654964586.6166897 iteration: 64370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08437 FastRCNN class loss: 0.08025 FastRCNN total loss: 0.16462 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.14329 RPN box loss: 0.00945 RPN score loss: 0.00352 RPN total loss: 0.01298 Total loss: 0.91371 timestamp: 1654964589.7884328 iteration: 64375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12337 FastRCNN class loss: 0.08953 FastRCNN total loss: 0.2129 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.17086 RPN box loss: 0.01114 RPN score loss: 0.00445 RPN total loss: 0.01558 Total loss: 0.99216 timestamp: 1654964592.9229279 iteration: 64380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05488 FastRCNN class loss: 0.05383 FastRCNN total loss: 0.10871 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.10417 RPN box loss: 0.00515 RPN score loss: 0.0065 RPN total loss: 0.01164 Total loss: 0.81734 timestamp: 1654964596.1390755 iteration: 64385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09568 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.1534 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.0004 Mask loss: 0.1404 RPN box loss: 0.03327 RPN score loss: 0.00178 RPN total loss: 0.03505 Total loss: 0.92166 timestamp: 1654964599.3745446 iteration: 64390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06031 FastRCNN class loss: 0.0492 FastRCNN total loss: 0.10951 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.0004 Mask loss: 0.09833 RPN box loss: 0.00993 RPN score loss: 0.00196 RPN total loss: 0.01189 Total loss: 0.81255 timestamp: 1654964602.533114 iteration: 64395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09859 FastRCNN class loss: 0.09107 FastRCNN total loss: 0.18966 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.0004 Mask loss: 0.13696 RPN box loss: 0.01813 RPN score loss: 0.01237 RPN total loss: 0.0305 Total loss: 0.94993 timestamp: 1654964605.6988459 iteration: 64400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06974 FastRCNN class loss: 0.07099 FastRCNN total loss: 0.14073 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.0004 Mask loss: 0.10493 RPN box loss: 0.00971 RPN score loss: 0.00343 RPN total loss: 0.01314 Total loss: 0.85161 timestamp: 1654964608.9034646 iteration: 64405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10145 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.15898 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.0004 Mask loss: 0.21693 RPN box loss: 0.0164 RPN score loss: 0.00145 RPN total loss: 0.01785 Total loss: 0.98656 timestamp: 1654964612.0746624 iteration: 64410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1031 FastRCNN class loss: 0.0775 FastRCNN total loss: 0.1806 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.0004 Mask loss: 0.1643 RPN box loss: 0.014 RPN score loss: 0.00301 RPN total loss: 0.01701 Total loss: 0.95472 timestamp: 1654964615.2775383 iteration: 64415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08958 FastRCNN class loss: 0.06391 FastRCNN total loss: 0.1535 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.0004 Mask loss: 0.18228 RPN box loss: 0.02582 RPN score loss: 0.00917 RPN total loss: 0.03499 Total loss: 0.96358 timestamp: 1654964618.4894493 iteration: 64420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11104 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.17305 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.0004 Mask loss: 0.11349 RPN box loss: 0.00469 RPN score loss: 0.0073 RPN total loss: 0.01198 Total loss: 0.89132 timestamp: 1654964621.5879383 iteration: 64425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0581 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.10887 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.0004 Mask loss: 0.11174 RPN box loss: 0.00978 RPN score loss: 0.00809 RPN total loss: 0.01787 Total loss: 0.83128 timestamp: 1654964624.780926 iteration: 64430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13304 FastRCNN class loss: 0.06479 FastRCNN total loss: 0.19782 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.0004 Mask loss: 0.11766 RPN box loss: 0.00866 RPN score loss: 0.00261 RPN total loss: 0.01127 Total loss: 0.91955 timestamp: 1654964627.9577322 iteration: 64435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08824 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.14872 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.0004 Mask loss: 0.15412 RPN box loss: 0.02197 RPN score loss: 0.0081 RPN total loss: 0.03007 Total loss: 0.92571 timestamp: 1654964631.2056007 iteration: 64440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07058 FastRCNN class loss: 0.07721 FastRCNN total loss: 0.14779 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.0004 Mask loss: 0.13207 RPN box loss: 0.01034 RPN score loss: 0.00542 RPN total loss: 0.01576 Total loss: 0.88841 timestamp: 1654964634.3764029 iteration: 64445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13561 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.21788 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.0004 Mask loss: 0.16261 RPN box loss: 0.018 RPN score loss: 0.00766 RPN total loss: 0.02566 Total loss: 0.99894 timestamp: 1654964637.6185515 iteration: 64450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0521 FastRCNN class loss: 0.0732 FastRCNN total loss: 0.12529 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.0004 Mask loss: 0.11892 RPN box loss: 0.02222 RPN score loss: 0.01348 RPN total loss: 0.03569 Total loss: 0.8727 timestamp: 1654964640.8739393 iteration: 64455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.04342 FastRCNN total loss: 0.10963 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.0004 Mask loss: 0.1606 RPN box loss: 0.01799 RPN score loss: 0.01218 RPN total loss: 0.03017 Total loss: 0.89319 timestamp: 1654964644.035865 iteration: 64460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11031 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.19137 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.0004 Mask loss: 0.15218 RPN box loss: 0.00743 RPN score loss: 0.00244 RPN total loss: 0.00987 Total loss: 0.94622 timestamp: 1654964647.2352738 iteration: 64465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07924 FastRCNN class loss: 0.06216 FastRCNN total loss: 0.1414 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.0004 Mask loss: 0.10939 RPN box loss: 0.01929 RPN score loss: 0.00572 RPN total loss: 0.02501 Total loss: 0.86858 timestamp: 1654964650.418161 iteration: 64470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07973 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.15275 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.0004 Mask loss: 0.15863 RPN box loss: 0.00848 RPN score loss: 0.00201 RPN total loss: 0.01049 Total loss: 0.91466 timestamp: 1654964653.6506796 iteration: 64475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10627 FastRCNN class loss: 0.091 FastRCNN total loss: 0.19727 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.0004 Mask loss: 0.134 RPN box loss: 0.01099 RPN score loss: 0.00534 RPN total loss: 0.01632 Total loss: 0.94038 timestamp: 1654964656.8193276 iteration: 64480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07918 FastRCNN class loss: 0.06671 FastRCNN total loss: 0.14589 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.0004 Mask loss: 0.15119 RPN box loss: 0.01383 RPN score loss: 0.01255 RPN total loss: 0.02638 Total loss: 0.91625 timestamp: 1654964660.0713062 iteration: 64485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09884 FastRCNN class loss: 0.04673 FastRCNN total loss: 0.14557 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.0004 Mask loss: 0.06981 RPN box loss: 0.00809 RPN score loss: 0.00137 RPN total loss: 0.00945 Total loss: 0.81763 timestamp: 1654964663.3191748 iteration: 64490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06719 FastRCNN class loss: 0.04309 FastRCNN total loss: 0.11028 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.0004 Mask loss: 0.07511 RPN box loss: 0.0054 RPN score loss: 0.0026 RPN total loss: 0.00801 Total loss: 0.78618 timestamp: 1654964666.5256763 iteration: 64495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05926 FastRCNN class loss: 0.0449 FastRCNN total loss: 0.10416 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.0004 Mask loss: 0.10572 RPN box loss: 0.01283 RPN score loss: 0.00288 RPN total loss: 0.01571 Total loss: 0.81837 timestamp: 1654964669.7209308 iteration: 64500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06094 FastRCNN class loss: 0.04702 FastRCNN total loss: 0.10796 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.0004 Mask loss: 0.10351 RPN box loss: 0.0053 RPN score loss: 0.00511 RPN total loss: 0.01041 Total loss: 0.81465 timestamp: 1654964673.0169003 iteration: 64505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.12345 FastRCNN total loss: 0.24254 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.0004 Mask loss: 0.16183 RPN box loss: 0.02071 RPN score loss: 0.00684 RPN total loss: 0.02755 Total loss: 1.02469 timestamp: 1654964676.2057033 iteration: 64510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11109 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.17582 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.0004 Mask loss: 0.16705 RPN box loss: 0.0144 RPN score loss: 0.00306 RPN total loss: 0.01746 Total loss: 0.9531 timestamp: 1654964679.4341779 iteration: 64515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1223 FastRCNN class loss: 0.08318 FastRCNN total loss: 0.20548 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.0004 Mask loss: 0.18391 RPN box loss: 0.01754 RPN score loss: 0.00791 RPN total loss: 0.02545 Total loss: 1.00761 timestamp: 1654964682.6180644 iteration: 64520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11645 FastRCNN class loss: 0.05668 FastRCNN total loss: 0.17313 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.0004 Mask loss: 0.13312 RPN box loss: 0.02049 RPN score loss: 0.00747 RPN total loss: 0.02796 Total loss: 0.92698 timestamp: 1654964685.901412 iteration: 64525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.16492 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.0004 Mask loss: 0.16859 RPN box loss: 0.01246 RPN score loss: 0.00329 RPN total loss: 0.01575 Total loss: 0.94202 timestamp: 1654964689.1355557 iteration: 64530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05689 FastRCNN class loss: 0.04078 FastRCNN total loss: 0.09767 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.0004 Mask loss: 0.07308 RPN box loss: 0.0061 RPN score loss: 0.00194 RPN total loss: 0.00804 Total loss: 0.77157 timestamp: 1654964692.3418005 iteration: 64535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07748 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.14134 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.0004 Mask loss: 0.11257 RPN box loss: 0.01832 RPN score loss: 0.00268 RPN total loss: 0.02101 Total loss: 0.86767 timestamp: 1654964695.5358272 iteration: 64540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07051 FastRCNN class loss: 0.10207 FastRCNN total loss: 0.17258 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.17555 RPN box loss: 0.01317 RPN score loss: 0.02008 RPN total loss: 0.03325 Total loss: 0.97414 timestamp: 1654964698.7419596 iteration: 64545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07712 FastRCNN class loss: 0.06999 FastRCNN total loss: 0.14711 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.08994 RPN box loss: 0.00799 RPN score loss: 0.00386 RPN total loss: 0.01185 Total loss: 0.84166 timestamp: 1654964701.932132 iteration: 64550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15048 FastRCNN class loss: 0.05551 FastRCNN total loss: 0.20599 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.11636 RPN box loss: 0.00403 RPN score loss: 0.00584 RPN total loss: 0.00986 Total loss: 0.92498 timestamp: 1654964705.0603456 iteration: 64555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08587 FastRCNN class loss: 0.07675 FastRCNN total loss: 0.16261 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.1291 RPN box loss: 0.0125 RPN score loss: 0.00383 RPN total loss: 0.01633 Total loss: 0.90081 timestamp: 1654964708.2558846 iteration: 64560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1423 FastRCNN class loss: 0.1039 FastRCNN total loss: 0.24621 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.19935 RPN box loss: 0.01553 RPN score loss: 0.01295 RPN total loss: 0.02849 Total loss: 1.06681 timestamp: 1654964711.4422913 iteration: 64565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.07372 FastRCNN total loss: 0.12715 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.14486 RPN box loss: 0.01957 RPN score loss: 0.00747 RPN total loss: 0.02704 Total loss: 0.8918 timestamp: 1654964714.6589758 iteration: 64570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08777 FastRCNN class loss: 0.05561 FastRCNN total loss: 0.14338 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.0004 Mask loss: 0.08911 RPN box loss: 0.04353 RPN score loss: 0.00431 RPN total loss: 0.04784 Total loss: 0.87308 timestamp: 1654964717.8580008 iteration: 64575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06267 FastRCNN class loss: 0.05089 FastRCNN total loss: 0.11356 L1 loss: 0.0000e+00 L2 loss: 0.59275 Learning rate: 0.0004 Mask loss: 0.12048 RPN box loss: 0.00462 RPN score loss: 0.00498 RPN total loss: 0.0096 Total loss: 0.83639 timestamp: 1654964721.0827112 iteration: 64580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07615 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.13765 L1 loss: 0.0000e+00 L2 loss: 0.59275 Learning rate: 0.0004 Mask loss: 0.1341 RPN box loss: 0.01061 RPN score loss: 0.00209 RPN total loss: 0.0127 Total loss: 0.8772 timestamp: 1654964724.2148526 iteration: 64585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02858 FastRCNN class loss: 0.03235 FastRCNN total loss: 0.06094 L1 loss: 0.0000e+00 L2 loss: 0.59275 Learning rate: 0.0004 Mask loss: 0.08341 RPN box loss: 0.00152 RPN score loss: 0.0032 RPN total loss: 0.00471 Total loss: 0.74181 timestamp: 1654964727.4889712 iteration: 64590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04344 FastRCNN class loss: 0.03934 FastRCNN total loss: 0.08278 L1 loss: 0.0000e+00 L2 loss: 0.59275 Learning rate: 0.0004 Mask loss: 0.07647 RPN box loss: 0.00384 RPN score loss: 0.00213 RPN total loss: 0.00598 Total loss: 0.75797 timestamp: 1654964730.636551 iteration: 64595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08544 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.14823 L1 loss: 0.0000e+00 L2 loss: 0.59275 Learning rate: 0.0004 Mask loss: 0.12762 RPN box loss: 0.00751 RPN score loss: 0.00214 RPN total loss: 0.00965 Total loss: 0.87825 timestamp: 1654964733.911975 iteration: 64600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11292 FastRCNN class loss: 0.05774 FastRCNN total loss: 0.17066 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.0004 Mask loss: 0.10978 RPN box loss: 0.0071 RPN score loss: 0.00514 RPN total loss: 0.01224 Total loss: 0.88542 timestamp: 1654964737.0859132 iteration: 64605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05449 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.12563 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.0004 Mask loss: 0.14253 RPN box loss: 0.00757 RPN score loss: 0.00568 RPN total loss: 0.01325 Total loss: 0.87414 timestamp: 1654964740.314639 iteration: 64610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14107 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.23009 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.0004 Mask loss: 0.1286 RPN box loss: 0.00857 RPN score loss: 0.00249 RPN total loss: 0.01107 Total loss: 0.9625 timestamp: 1654964743.455602 iteration: 64615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05969 FastRCNN class loss: 0.07576 FastRCNN total loss: 0.13545 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.0004 Mask loss: 0.13773 RPN box loss: 0.0162 RPN score loss: 0.00913 RPN total loss: 0.02533 Total loss: 0.89125 timestamp: 1654964746.5935707 iteration: 64620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10753 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.17334 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.0004 Mask loss: 0.12866 RPN box loss: 0.01741 RPN score loss: 0.00204 RPN total loss: 0.01945 Total loss: 0.9142 timestamp: 1654964749.7668364 iteration: 64625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14855 FastRCNN class loss: 0.12424 FastRCNN total loss: 0.27279 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.0004 Mask loss: 0.13583 RPN box loss: 0.0095 RPN score loss: 0.00347 RPN total loss: 0.01297 Total loss: 1.01432 timestamp: 1654964752.9964004 iteration: 64630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11047 FastRCNN class loss: 0.07743 FastRCNN total loss: 0.1879 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.0004 Mask loss: 0.15923 RPN box loss: 0.01104 RPN score loss: 0.00431 RPN total loss: 0.01534 Total loss: 0.9552 timestamp: 1654964756.2007709 iteration: 64635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10173 FastRCNN class loss: 0.0603 FastRCNN total loss: 0.16203 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.0004 Mask loss: 0.15227 RPN box loss: 0.01545 RPN score loss: 0.00318 RPN total loss: 0.01863 Total loss: 0.92567 timestamp: 1654964759.4097247 iteration: 64640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08311 FastRCNN class loss: 0.063 FastRCNN total loss: 0.14611 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.0004 Mask loss: 0.12206 RPN box loss: 0.01003 RPN score loss: 0.00477 RPN total loss: 0.01481 Total loss: 0.87571 timestamp: 1654964762.541235 iteration: 64645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05809 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.1288 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.0004 Mask loss: 0.11301 RPN box loss: 0.0165 RPN score loss: 0.00198 RPN total loss: 0.01848 Total loss: 0.85303 timestamp: 1654964765.760704 iteration: 64650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08679 FastRCNN class loss: 0.05712 FastRCNN total loss: 0.14391 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.0004 Mask loss: 0.10891 RPN box loss: 0.01945 RPN score loss: 0.00313 RPN total loss: 0.02257 Total loss: 0.86812 timestamp: 1654964768.965236 iteration: 64655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08681 FastRCNN class loss: 0.04068 FastRCNN total loss: 0.12749 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.0004 Mask loss: 0.12382 RPN box loss: 0.01068 RPN score loss: 0.0013 RPN total loss: 0.01198 Total loss: 0.85602 timestamp: 1654964772.2187068 iteration: 64660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09587 FastRCNN class loss: 0.08833 FastRCNN total loss: 0.1842 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.0004 Mask loss: 0.10362 RPN box loss: 0.02269 RPN score loss: 0.00277 RPN total loss: 0.02546 Total loss: 0.906 timestamp: 1654964775.4084594 iteration: 64665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09753 FastRCNN class loss: 0.12924 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.0004 Mask loss: 0.13614 RPN box loss: 0.01379 RPN score loss: 0.00651 RPN total loss: 0.02031 Total loss: 0.97593 timestamp: 1654964778.6436076 iteration: 64670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06299 FastRCNN class loss: 0.0301 FastRCNN total loss: 0.09309 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.0004 Mask loss: 0.08535 RPN box loss: 0.0024 RPN score loss: 0.00053 RPN total loss: 0.00293 Total loss: 0.7741 timestamp: 1654964781.8755815 iteration: 64675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10707 FastRCNN class loss: 0.0761 FastRCNN total loss: 0.18317 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.0004 Mask loss: 0.1347 RPN box loss: 0.0202 RPN score loss: 0.00735 RPN total loss: 0.02755 Total loss: 0.93813 timestamp: 1654964785.0535085 iteration: 64680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12853 FastRCNN class loss: 0.09441 FastRCNN total loss: 0.22294 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.0004 Mask loss: 0.14466 RPN box loss: 0.00716 RPN score loss: 0.0069 RPN total loss: 0.01406 Total loss: 0.97437 timestamp: 1654964788.2679367 iteration: 64685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11714 FastRCNN class loss: 0.08564 FastRCNN total loss: 0.20279 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.0004 Mask loss: 0.15368 RPN box loss: 0.0094 RPN score loss: 0.00439 RPN total loss: 0.01379 Total loss: 0.96297 timestamp: 1654964791.4370263 iteration: 64690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04657 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.1039 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.0004 Mask loss: 0.13321 RPN box loss: 0.00853 RPN score loss: 0.00233 RPN total loss: 0.01086 Total loss: 0.84068 timestamp: 1654964794.6420724 iteration: 64695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08592 FastRCNN class loss: 0.1132 FastRCNN total loss: 0.19912 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.0004 Mask loss: 0.12809 RPN box loss: 0.00572 RPN score loss: 0.00487 RPN total loss: 0.01059 Total loss: 0.93052 timestamp: 1654964797.8020551 iteration: 64700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13358 FastRCNN class loss: 0.08865 FastRCNN total loss: 0.22222 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.0004 Mask loss: 0.1638 RPN box loss: 0.01387 RPN score loss: 0.01293 RPN total loss: 0.0268 Total loss: 1.00553 timestamp: 1654964800.957258 iteration: 64705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06424 FastRCNN class loss: 0.04655 FastRCNN total loss: 0.11079 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.0004 Mask loss: 0.10448 RPN box loss: 0.01034 RPN score loss: 0.00118 RPN total loss: 0.01152 Total loss: 0.8195 timestamp: 1654964804.1009676 iteration: 64710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11201 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.19792 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.0004 Mask loss: 0.13443 RPN box loss: 0.01795 RPN score loss: 0.00788 RPN total loss: 0.02583 Total loss: 0.95089 timestamp: 1654964807.2560525 iteration: 64715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07445 FastRCNN class loss: 0.05854 FastRCNN total loss: 0.13298 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.0004 Mask loss: 0.12036 RPN box loss: 0.02672 RPN score loss: 0.00208 RPN total loss: 0.02881 Total loss: 0.87486 timestamp: 1654964810.585706 iteration: 64720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04828 FastRCNN class loss: 0.05246 FastRCNN total loss: 0.10074 L1 loss: 0.0000e+00 L2 loss: 0.5927 Learning rate: 0.0004 Mask loss: 0.12009 RPN box loss: 0.00764 RPN score loss: 0.01316 RPN total loss: 0.02081 Total loss: 0.83434 timestamp: 1654964813.790935 iteration: 64725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12146 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.1893 L1 loss: 0.0000e+00 L2 loss: 0.5927 Learning rate: 0.0004 Mask loss: 0.12863 RPN box loss: 0.01995 RPN score loss: 0.00236 RPN total loss: 0.02231 Total loss: 0.93294 timestamp: 1654964816.9800828 iteration: 64730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10816 FastRCNN class loss: 0.09997 FastRCNN total loss: 0.20813 L1 loss: 0.0000e+00 L2 loss: 0.5927 Learning rate: 0.0004 Mask loss: 0.1349 RPN box loss: 0.0138 RPN score loss: 0.00533 RPN total loss: 0.01913 Total loss: 0.95486 timestamp: 1654964820.1635444 iteration: 64735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04385 FastRCNN class loss: 0.03897 FastRCNN total loss: 0.08282 L1 loss: 0.0000e+00 L2 loss: 0.5927 Learning rate: 0.0004 Mask loss: 0.12261 RPN box loss: 0.00741 RPN score loss: 0.00092 RPN total loss: 0.00833 Total loss: 0.80646 timestamp: 1654964823.356359 iteration: 64740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09883 FastRCNN class loss: 0.08369 FastRCNN total loss: 0.18252 L1 loss: 0.0000e+00 L2 loss: 0.5927 Learning rate: 0.0004 Mask loss: 0.10785 RPN box loss: 0.01072 RPN score loss: 0.00232 RPN total loss: 0.01304 Total loss: 0.89611 timestamp: 1654964826.5543585 iteration: 64745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.07252 FastRCNN total loss: 0.16021 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.0004 Mask loss: 0.13879 RPN box loss: 0.00852 RPN score loss: 0.00187 RPN total loss: 0.0104 Total loss: 0.90209 timestamp: 1654964829.6928012 iteration: 64750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08664 FastRCNN class loss: 0.07262 FastRCNN total loss: 0.15926 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.0004 Mask loss: 0.10689 RPN box loss: 0.01944 RPN score loss: 0.00403 RPN total loss: 0.02347 Total loss: 0.88231 timestamp: 1654964832.8560154 iteration: 64755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09723 FastRCNN class loss: 0.06936 FastRCNN total loss: 0.16659 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.0004 Mask loss: 0.15654 RPN box loss: 0.01663 RPN score loss: 0.01467 RPN total loss: 0.0313 Total loss: 0.94712 timestamp: 1654964836.0416143 iteration: 64760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08948 FastRCNN class loss: 0.077 FastRCNN total loss: 0.16648 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.0004 Mask loss: 0.18825 RPN box loss: 0.01707 RPN score loss: 0.0043 RPN total loss: 0.02137 Total loss: 0.96878 timestamp: 1654964839.2581437 iteration: 64765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06947 FastRCNN class loss: 0.03712 FastRCNN total loss: 0.10659 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.0004 Mask loss: 0.09423 RPN box loss: 0.00635 RPN score loss: 0.00199 RPN total loss: 0.00834 Total loss: 0.80186 timestamp: 1654964842.4889996 iteration: 64770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11003 FastRCNN class loss: 0.12199 FastRCNN total loss: 0.23203 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.0004 Mask loss: 0.20826 RPN box loss: 0.01447 RPN score loss: 0.00688 RPN total loss: 0.02135 Total loss: 1.05432 timestamp: 1654964845.6486282 iteration: 64775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11324 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.17013 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.0004 Mask loss: 0.25399 RPN box loss: 0.02146 RPN score loss: 0.00555 RPN total loss: 0.02702 Total loss: 1.04382 timestamp: 1654964848.9153802 iteration: 64780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04764 FastRCNN class loss: 0.05904 FastRCNN total loss: 0.10668 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.0004 Mask loss: 0.11836 RPN box loss: 0.01248 RPN score loss: 0.00646 RPN total loss: 0.01894 Total loss: 0.83666 timestamp: 1654964852.065205 iteration: 64785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07801 FastRCNN class loss: 0.0498 FastRCNN total loss: 0.1278 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.0004 Mask loss: 0.12518 RPN box loss: 0.06749 RPN score loss: 0.00365 RPN total loss: 0.07113 Total loss: 0.9168 timestamp: 1654964855.2502031 iteration: 64790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07412 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.11682 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.0004 Mask loss: 0.14298 RPN box loss: 0.01164 RPN score loss: 0.00085 RPN total loss: 0.01248 Total loss: 0.86497 timestamp: 1654964858.4738898 iteration: 64795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07478 FastRCNN class loss: 0.0622 FastRCNN total loss: 0.13698 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.0004 Mask loss: 0.18599 RPN box loss: 0.00806 RPN score loss: 0.00208 RPN total loss: 0.01014 Total loss: 0.92579 timestamp: 1654964861.7080855 iteration: 64800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10863 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.17432 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.0004 Mask loss: 0.1559 RPN box loss: 0.00738 RPN score loss: 0.00531 RPN total loss: 0.01269 Total loss: 0.93559 timestamp: 1654964864.936303 iteration: 64805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1122 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.18346 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.0004 Mask loss: 0.15054 RPN box loss: 0.01876 RPN score loss: 0.00636 RPN total loss: 0.02512 Total loss: 0.9518 timestamp: 1654964868.128177 iteration: 64810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15362 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.22575 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.0004 Mask loss: 0.11966 RPN box loss: 0.00816 RPN score loss: 0.00188 RPN total loss: 0.01004 Total loss: 0.94812 timestamp: 1654964871.305921 iteration: 64815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03825 FastRCNN class loss: 0.03695 FastRCNN total loss: 0.0752 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.0004 Mask loss: 0.1094 RPN box loss: 0.0051 RPN score loss: 0.00429 RPN total loss: 0.00938 Total loss: 0.78666 timestamp: 1654964874.5391223 iteration: 64820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05112 FastRCNN class loss: 0.05107 FastRCNN total loss: 0.10218 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.0004 Mask loss: 0.08944 RPN box loss: 0.00834 RPN score loss: 0.00819 RPN total loss: 0.01653 Total loss: 0.80082 timestamp: 1654964877.7644882 iteration: 64825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13729 FastRCNN class loss: 0.11207 FastRCNN total loss: 0.24935 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.0004 Mask loss: 0.22644 RPN box loss: 0.01173 RPN score loss: 0.00275 RPN total loss: 0.01447 Total loss: 1.08293 timestamp: 1654964880.9899015 iteration: 64830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10417 FastRCNN class loss: 0.04616 FastRCNN total loss: 0.15033 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.0004 Mask loss: 0.11256 RPN box loss: 0.00943 RPN score loss: 0.00441 RPN total loss: 0.01384 Total loss: 0.8694 timestamp: 1654964884.1642516 iteration: 64835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10204 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.18576 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.0004 Mask loss: 0.13204 RPN box loss: 0.00923 RPN score loss: 0.00731 RPN total loss: 0.01654 Total loss: 0.927 timestamp: 1654964887.3729296 iteration: 64840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06922 FastRCNN class loss: 0.04502 FastRCNN total loss: 0.11424 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.0004 Mask loss: 0.09708 RPN box loss: 0.01241 RPN score loss: 0.00152 RPN total loss: 0.01392 Total loss: 0.81791 timestamp: 1654964890.591339 iteration: 64845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0778 FastRCNN class loss: 0.03452 FastRCNN total loss: 0.11232 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.0004 Mask loss: 0.08831 RPN box loss: 0.0047 RPN score loss: 0.00384 RPN total loss: 0.00854 Total loss: 0.80184 timestamp: 1654964893.7723675 iteration: 64850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06951 FastRCNN class loss: 0.06568 FastRCNN total loss: 0.13519 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.0004 Mask loss: 0.11608 RPN box loss: 0.00847 RPN score loss: 0.00531 RPN total loss: 0.01379 Total loss: 0.85771 timestamp: 1654964897.003839 iteration: 64855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07125 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.12069 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.0004 Mask loss: 0.12409 RPN box loss: 0.0078 RPN score loss: 0.00549 RPN total loss: 0.01329 Total loss: 0.85073 timestamp: 1654964900.215558 iteration: 64860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09584 FastRCNN class loss: 0.09306 FastRCNN total loss: 0.1889 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.0004 Mask loss: 0.14022 RPN box loss: 0.00842 RPN score loss: 0.00691 RPN total loss: 0.01533 Total loss: 0.93711 timestamp: 1654964903.420729 iteration: 64865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12075 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.18481 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.0004 Mask loss: 0.15753 RPN box loss: 0.00821 RPN score loss: 0.01609 RPN total loss: 0.0243 Total loss: 0.95929 timestamp: 1654964906.6308498 iteration: 64870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06363 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.11858 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.0004 Mask loss: 0.09306 RPN box loss: 0.00716 RPN score loss: 0.00216 RPN total loss: 0.00932 Total loss: 0.81362 timestamp: 1654964909.86338 iteration: 64875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08635 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.16443 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.0004 Mask loss: 0.14074 RPN box loss: 0.01181 RPN score loss: 0.00458 RPN total loss: 0.01639 Total loss: 0.91421 timestamp: 1654964913.0327094 iteration: 64880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08043 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.16183 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.0004 Mask loss: 0.17848 RPN box loss: 0.01247 RPN score loss: 0.0033 RPN total loss: 0.01578 Total loss: 0.94873 timestamp: 1654964916.1394806 iteration: 64885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14479 FastRCNN class loss: 0.08816 FastRCNN total loss: 0.23296 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.0004 Mask loss: 0.11493 RPN box loss: 0.03901 RPN score loss: 0.0029 RPN total loss: 0.04191 Total loss: 0.98245 timestamp: 1654964919.3269837 iteration: 64890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10516 FastRCNN class loss: 0.03758 FastRCNN total loss: 0.14274 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.0004 Mask loss: 0.0729 RPN box loss: 0.00463 RPN score loss: 0.0037 RPN total loss: 0.00833 Total loss: 0.81661 timestamp: 1654964922.4659793 iteration: 64895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07525 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.13546 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.13389 RPN box loss: 0.00755 RPN score loss: 0.00182 RPN total loss: 0.00937 Total loss: 0.87136 timestamp: 1654964925.6324973 iteration: 64900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08893 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.14422 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.12141 RPN box loss: 0.00626 RPN score loss: 0.00221 RPN total loss: 0.00848 Total loss: 0.86675 timestamp: 1654964928.797372 iteration: 64905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.08921 FastRCNN total loss: 0.1752 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.11619 RPN box loss: 0.00767 RPN score loss: 0.00134 RPN total loss: 0.00901 Total loss: 0.89304 timestamp: 1654964932.0379124 iteration: 64910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08119 FastRCNN class loss: 0.04566 FastRCNN total loss: 0.12684 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.09706 RPN box loss: 0.00619 RPN score loss: 0.00166 RPN total loss: 0.00785 Total loss: 0.82439 timestamp: 1654964935.2446132 iteration: 64915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07419 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.14625 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.14427 RPN box loss: 0.00886 RPN score loss: 0.00237 RPN total loss: 0.01123 Total loss: 0.89439 timestamp: 1654964938.445047 iteration: 64920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05442 FastRCNN class loss: 0.03233 FastRCNN total loss: 0.08675 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.10961 RPN box loss: 0.00527 RPN score loss: 0.00224 RPN total loss: 0.00751 Total loss: 0.79651 timestamp: 1654964941.6130652 iteration: 64925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10881 FastRCNN class loss: 0.04962 FastRCNN total loss: 0.15843 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.0004 Mask loss: 0.11587 RPN box loss: 0.01497 RPN score loss: 0.00305 RPN total loss: 0.01802 Total loss: 0.88495 timestamp: 1654964944.7708893 iteration: 64930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08941 FastRCNN class loss: 0.08673 FastRCNN total loss: 0.17614 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.0004 Mask loss: 0.13579 RPN box loss: 0.02513 RPN score loss: 0.00596 RPN total loss: 0.03109 Total loss: 0.93566 timestamp: 1654964947.9747803 iteration: 64935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.05559 FastRCNN total loss: 0.13743 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.0004 Mask loss: 0.12084 RPN box loss: 0.01667 RPN score loss: 0.00647 RPN total loss: 0.02314 Total loss: 0.87404 timestamp: 1654964951.1331828 iteration: 64940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13962 FastRCNN class loss: 0.05185 FastRCNN total loss: 0.19147 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.0004 Mask loss: 0.14973 RPN box loss: 0.00774 RPN score loss: 0.00139 RPN total loss: 0.00913 Total loss: 0.94297 timestamp: 1654964954.3434966 iteration: 64945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07705 FastRCNN class loss: 0.09448 FastRCNN total loss: 0.17153 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.0004 Mask loss: 0.14531 RPN box loss: 0.01799 RPN score loss: 0.00627 RPN total loss: 0.02425 Total loss: 0.93372 timestamp: 1654964957.645351 iteration: 64950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12408 FastRCNN class loss: 0.15272 FastRCNN total loss: 0.2768 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.0004 Mask loss: 0.24093 RPN box loss: 0.0217 RPN score loss: 0.01089 RPN total loss: 0.03259 Total loss: 1.14294 timestamp: 1654964960.9011936 iteration: 64955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17932 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.23277 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.0004 Mask loss: 0.14502 RPN box loss: 0.00537 RPN score loss: 0.0041 RPN total loss: 0.00947 Total loss: 0.97989 timestamp: 1654964964.070039 iteration: 64960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05475 FastRCNN class loss: 0.06585 FastRCNN total loss: 0.1206 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.0004 Mask loss: 0.1189 RPN box loss: 0.00793 RPN score loss: 0.0019 RPN total loss: 0.00983 Total loss: 0.84196 timestamp: 1654964967.2885435 iteration: 64965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.03728 FastRCNN total loss: 0.10594 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.0004 Mask loss: 0.12966 RPN box loss: 0.0036 RPN score loss: 0.00064 RPN total loss: 0.00424 Total loss: 0.83246 timestamp: 1654964970.5629878 iteration: 64970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08246 FastRCNN class loss: 0.08418 FastRCNN total loss: 0.16664 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.0004 Mask loss: 0.11776 RPN box loss: 0.01018 RPN score loss: 0.00388 RPN total loss: 0.01405 Total loss: 0.89107 timestamp: 1654964973.7768354 iteration: 64975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10602 FastRCNN class loss: 0.07121 FastRCNN total loss: 0.17723 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.0004 Mask loss: 0.16692 RPN box loss: 0.01869 RPN score loss: 0.0056 RPN total loss: 0.02429 Total loss: 0.96107 timestamp: 1654964976.8929303 iteration: 64980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.09591 FastRCNN total loss: 0.19598 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.0004 Mask loss: 0.13952 RPN box loss: 0.01135 RPN score loss: 0.00386 RPN total loss: 0.01521 Total loss: 0.94333 timestamp: 1654964980.0565655 iteration: 64985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07049 FastRCNN class loss: 0.05701 FastRCNN total loss: 0.1275 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.0004 Mask loss: 0.13486 RPN box loss: 0.02179 RPN score loss: 0.00806 RPN total loss: 0.02985 Total loss: 0.88483 timestamp: 1654964983.1842992 iteration: 64990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10902 FastRCNN class loss: 0.08058 FastRCNN total loss: 0.18961 L1 loss: 0.0000e+00 L2 loss: 0.59261 Learning rate: 0.0004 Mask loss: 0.12452 RPN box loss: 0.02486 RPN score loss: 0.00586 RPN total loss: 0.03072 Total loss: 0.93746 timestamp: 1654964986.4111183 iteration: 64995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0812 FastRCNN class loss: 0.06872 FastRCNN total loss: 0.14992 L1 loss: 0.0000e+00 L2 loss: 0.59261 Learning rate: 0.0004 Mask loss: 0.18027 RPN box loss: 0.00523 RPN score loss: 0.00294 RPN total loss: 0.00817 Total loss: 0.93098 timestamp: 1654964989.6334069 iteration: 65000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08941 FastRCNN class loss: 0.08313 FastRCNN total loss: 0.17254 L1 loss: 0.0000e+00 L2 loss: 0.59261 Learning rate: 0.0004 Mask loss: 0.15497 RPN box loss: 0.01072 RPN score loss: 0.00515 RPN total loss: 0.01588 Total loss: 0.936 timestamp: 1654964992.8270197 iteration: 65005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10447 FastRCNN class loss: 0.10466 FastRCNN total loss: 0.20913 L1 loss: 0.0000e+00 L2 loss: 0.59261 Learning rate: 0.0004 Mask loss: 0.14247 RPN box loss: 0.01326 RPN score loss: 0.02965 RPN total loss: 0.04291 Total loss: 0.98712 timestamp: 1654964996.0474262 iteration: 65010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06017 FastRCNN class loss: 0.05873 FastRCNN total loss: 0.1189 L1 loss: 0.0000e+00 L2 loss: 0.59261 Learning rate: 0.0004 Mask loss: 0.1486 RPN box loss: 0.01024 RPN score loss: 0.00617 RPN total loss: 0.01641 Total loss: 0.87652 timestamp: 1654964999.254598 iteration: 65015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07559 FastRCNN class loss: 0.06497 FastRCNN total loss: 0.14056 L1 loss: 0.0000e+00 L2 loss: 0.5926 Learning rate: 0.0004 Mask loss: 0.16239 RPN box loss: 0.07733 RPN score loss: 0.01071 RPN total loss: 0.08803 Total loss: 0.98359 timestamp: 1654965002.4587755 iteration: 65020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04782 FastRCNN class loss: 0.04712 FastRCNN total loss: 0.09494 L1 loss: 0.0000e+00 L2 loss: 0.5926 Learning rate: 0.0004 Mask loss: 0.07649 RPN box loss: 0.00572 RPN score loss: 0.00083 RPN total loss: 0.00654 Total loss: 0.77058 timestamp: 1654965005.5822644 iteration: 65025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11733 FastRCNN class loss: 0.08498 FastRCNN total loss: 0.20231 L1 loss: 0.0000e+00 L2 loss: 0.5926 Learning rate: 0.0004 Mask loss: 0.18682 RPN box loss: 0.01631 RPN score loss: 0.00412 RPN total loss: 0.02043 Total loss: 1.00216 timestamp: 1654965008.8542788 iteration: 65030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08977 FastRCNN class loss: 0.03696 FastRCNN total loss: 0.12673 L1 loss: 0.0000e+00 L2 loss: 0.5926 Learning rate: 0.0004 Mask loss: 0.1048 RPN box loss: 0.00479 RPN score loss: 0.00333 RPN total loss: 0.00812 Total loss: 0.83224 timestamp: 1654965012.038586 iteration: 65035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10753 FastRCNN class loss: 0.05029 FastRCNN total loss: 0.15781 L1 loss: 0.0000e+00 L2 loss: 0.5926 Learning rate: 0.0004 Mask loss: 0.12795 RPN box loss: 0.02213 RPN score loss: 0.00435 RPN total loss: 0.02648 Total loss: 0.90484 timestamp: 1654965015.224244 iteration: 65040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11042 FastRCNN class loss: 0.09466 FastRCNN total loss: 0.20508 L1 loss: 0.0000e+00 L2 loss: 0.5926 Learning rate: 0.0004 Mask loss: 0.19827 RPN box loss: 0.02512 RPN score loss: 0.01316 RPN total loss: 0.03828 Total loss: 1.03423 timestamp: 1654965018.3777812 iteration: 65045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05148 FastRCNN class loss: 0.04911 FastRCNN total loss: 0.10059 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.0004 Mask loss: 0.05944 RPN box loss: 0.00351 RPN score loss: 0.00172 RPN total loss: 0.00523 Total loss: 0.75785 timestamp: 1654965021.5621474 iteration: 65050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05913 FastRCNN class loss: 0.05641 FastRCNN total loss: 0.11553 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.0004 Mask loss: 0.11515 RPN box loss: 0.00445 RPN score loss: 0.00145 RPN total loss: 0.00591 Total loss: 0.82919 timestamp: 1654965024.7662413 iteration: 65055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10946 FastRCNN class loss: 0.06174 FastRCNN total loss: 0.1712 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.0004 Mask loss: 0.11788 RPN box loss: 0.00899 RPN score loss: 0.00167 RPN total loss: 0.01067 Total loss: 0.89234 timestamp: 1654965027.9029174 iteration: 65060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10096 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.17843 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.0004 Mask loss: 0.11803 RPN box loss: 0.00739 RPN score loss: 0.0065 RPN total loss: 0.01389 Total loss: 0.90293 timestamp: 1654965031.104318 iteration: 65065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10158 FastRCNN class loss: 0.06355 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.0004 Mask loss: 0.11575 RPN box loss: 0.02571 RPN score loss: 0.01374 RPN total loss: 0.03945 Total loss: 0.91292 timestamp: 1654965034.198638 iteration: 65070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11945 FastRCNN class loss: 0.08504 FastRCNN total loss: 0.2045 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.0004 Mask loss: 0.15294 RPN box loss: 0.03226 RPN score loss: 0.00484 RPN total loss: 0.0371 Total loss: 0.98713 timestamp: 1654965037.3661551 iteration: 65075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06469 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.13698 L1 loss: 0.0000e+00 L2 loss: 0.59258 Learning rate: 0.0004 Mask loss: 0.11936 RPN box loss: 0.00531 RPN score loss: 0.00309 RPN total loss: 0.0084 Total loss: 0.85733 timestamp: 1654965040.5770037 iteration: 65080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07606 FastRCNN class loss: 0.05572 FastRCNN total loss: 0.13178 L1 loss: 0.0000e+00 L2 loss: 0.59258 Learning rate: 0.0004 Mask loss: 0.089 RPN box loss: 0.01119 RPN score loss: 0.00339 RPN total loss: 0.01458 Total loss: 0.82794 timestamp: 1654965043.769632 iteration: 65085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06048 FastRCNN class loss: 0.08667 FastRCNN total loss: 0.14715 L1 loss: 0.0000e+00 L2 loss: 0.59258 Learning rate: 0.0004 Mask loss: 0.11292 RPN box loss: 0.00811 RPN score loss: 0.00556 RPN total loss: 0.01367 Total loss: 0.86632 timestamp: 1654965046.9717097 iteration: 65090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08667 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.15557 L1 loss: 0.0000e+00 L2 loss: 0.59258 Learning rate: 0.0004 Mask loss: 0.18612 RPN box loss: 0.00578 RPN score loss: 0.00152 RPN total loss: 0.0073 Total loss: 0.94157 timestamp: 1654965050.1935074 iteration: 65095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11133 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.17722 L1 loss: 0.0000e+00 L2 loss: 0.59258 Learning rate: 0.0004 Mask loss: 0.13279 RPN box loss: 0.01215 RPN score loss: 0.00633 RPN total loss: 0.01848 Total loss: 0.92106 timestamp: 1654965053.4000654 iteration: 65100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05935 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.12103 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.07843 RPN box loss: 0.01353 RPN score loss: 0.01067 RPN total loss: 0.0242 Total loss: 0.81623 timestamp: 1654965056.6190364 iteration: 65105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05841 FastRCNN class loss: 0.0373 FastRCNN total loss: 0.0957 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.09186 RPN box loss: 0.00562 RPN score loss: 0.00196 RPN total loss: 0.00758 Total loss: 0.78771 timestamp: 1654965059.7602832 iteration: 65110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10333 FastRCNN class loss: 0.06902 FastRCNN total loss: 0.17235 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.13893 RPN box loss: 0.02182 RPN score loss: 0.0023 RPN total loss: 0.02412 Total loss: 0.92797 timestamp: 1654965062.970123 iteration: 65115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11747 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.20592 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.13637 RPN box loss: 0.01682 RPN score loss: 0.00221 RPN total loss: 0.01903 Total loss: 0.9539 timestamp: 1654965066.1959355 iteration: 65120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13395 FastRCNN class loss: 0.06851 FastRCNN total loss: 0.20246 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.15302 RPN box loss: 0.00904 RPN score loss: 0.00254 RPN total loss: 0.01158 Total loss: 0.95963 timestamp: 1654965069.3694022 iteration: 65125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04433 FastRCNN class loss: 0.04293 FastRCNN total loss: 0.08726 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.10732 RPN box loss: 0.00487 RPN score loss: 0.00053 RPN total loss: 0.0054 Total loss: 0.79255 timestamp: 1654965072.5614245 iteration: 65130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0637 FastRCNN class loss: 0.06521 FastRCNN total loss: 0.12892 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.0004 Mask loss: 0.11061 RPN box loss: 0.00721 RPN score loss: 0.0049 RPN total loss: 0.01211 Total loss: 0.8442 timestamp: 1654965075.7830126 iteration: 65135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04552 FastRCNN class loss: 0.07434 FastRCNN total loss: 0.11986 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.0004 Mask loss: 0.10358 RPN box loss: 0.00649 RPN score loss: 0.00535 RPN total loss: 0.01184 Total loss: 0.82784 timestamp: 1654965079.0091414 iteration: 65140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08838 FastRCNN class loss: 0.04591 FastRCNN total loss: 0.13429 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.0004 Mask loss: 0.09063 RPN box loss: 0.00492 RPN score loss: 0.00155 RPN total loss: 0.00647 Total loss: 0.82395 timestamp: 1654965082.1289132 iteration: 65145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0759 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.15722 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.0004 Mask loss: 0.12912 RPN box loss: 0.02974 RPN score loss: 0.0039 RPN total loss: 0.03364 Total loss: 0.91253 timestamp: 1654965085.32032 iteration: 65150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08597 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.15313 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.0004 Mask loss: 0.15333 RPN box loss: 0.01505 RPN score loss: 0.00222 RPN total loss: 0.01727 Total loss: 0.91628 timestamp: 1654965088.4651802 iteration: 65155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11129 FastRCNN class loss: 0.0549 FastRCNN total loss: 0.16619 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.0004 Mask loss: 0.09497 RPN box loss: 0.00801 RPN score loss: 0.00219 RPN total loss: 0.0102 Total loss: 0.86392 timestamp: 1654965091.646838 iteration: 65160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08381 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.15417 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.0004 Mask loss: 0.08728 RPN box loss: 0.01218 RPN score loss: 0.00284 RPN total loss: 0.01502 Total loss: 0.84903 timestamp: 1654965094.8027081 iteration: 65165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05883 FastRCNN class loss: 0.04069 FastRCNN total loss: 0.09952 L1 loss: 0.0000e+00 L2 loss: 0.59255 Learning rate: 0.0004 Mask loss: 0.12632 RPN box loss: 0.007 RPN score loss: 0.00152 RPN total loss: 0.00852 Total loss: 0.82692 timestamp: 1654965097.953804 iteration: 65170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09678 FastRCNN class loss: 0.11021 FastRCNN total loss: 0.20699 L1 loss: 0.0000e+00 L2 loss: 0.59255 Learning rate: 0.0004 Mask loss: 0.18624 RPN box loss: 0.01736 RPN score loss: 0.00404 RPN total loss: 0.0214 Total loss: 1.00718 timestamp: 1654965101.1604774 iteration: 65175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08853 FastRCNN class loss: 0.06916 FastRCNN total loss: 0.15769 L1 loss: 0.0000e+00 L2 loss: 0.59255 Learning rate: 0.0004 Mask loss: 0.10252 RPN box loss: 0.02044 RPN score loss: 0.00444 RPN total loss: 0.02488 Total loss: 0.87763 timestamp: 1654965104.3724058 iteration: 65180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16597 FastRCNN class loss: 0.1034 FastRCNN total loss: 0.26937 L1 loss: 0.0000e+00 L2 loss: 0.59255 Learning rate: 0.0004 Mask loss: 0.1605 RPN box loss: 0.01082 RPN score loss: 0.01603 RPN total loss: 0.02684 Total loss: 1.04926 timestamp: 1654965107.5443592 iteration: 65185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09819 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.15794 L1 loss: 0.0000e+00 L2 loss: 0.59255 Learning rate: 0.0004 Mask loss: 0.14506 RPN box loss: 0.00595 RPN score loss: 0.00185 RPN total loss: 0.0078 Total loss: 0.90335 timestamp: 1654965110.806501 iteration: 65190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09185 FastRCNN class loss: 0.056 FastRCNN total loss: 0.14785 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.12511 RPN box loss: 0.01705 RPN score loss: 0.00337 RPN total loss: 0.02042 Total loss: 0.88592 timestamp: 1654965113.9660356 iteration: 65195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14122 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.21808 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.12787 RPN box loss: 0.04758 RPN score loss: 0.00256 RPN total loss: 0.05015 Total loss: 0.98864 timestamp: 1654965117.1066177 iteration: 65200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14037 FastRCNN class loss: 0.07566 FastRCNN total loss: 0.21603 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.16041 RPN box loss: 0.00692 RPN score loss: 0.00247 RPN total loss: 0.0094 Total loss: 0.97838 timestamp: 1654965120.3185902 iteration: 65205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07136 FastRCNN class loss: 0.0593 FastRCNN total loss: 0.13066 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.14961 RPN box loss: 0.00529 RPN score loss: 0.00133 RPN total loss: 0.00662 Total loss: 0.87944 timestamp: 1654965123.561289 iteration: 65210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09724 FastRCNN class loss: 0.06999 FastRCNN total loss: 0.16723 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.14215 RPN box loss: 0.01289 RPN score loss: 0.00418 RPN total loss: 0.01707 Total loss: 0.91899 timestamp: 1654965126.6667125 iteration: 65215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12681 FastRCNN class loss: 0.07812 FastRCNN total loss: 0.20493 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.16157 RPN box loss: 0.01144 RPN score loss: 0.00577 RPN total loss: 0.0172 Total loss: 0.97624 timestamp: 1654965129.8298206 iteration: 65220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12562 FastRCNN class loss: 0.07981 FastRCNN total loss: 0.20543 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.0004 Mask loss: 0.09678 RPN box loss: 0.00948 RPN score loss: 0.01349 RPN total loss: 0.02297 Total loss: 0.91772 timestamp: 1654965132.9750812 iteration: 65225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15031 FastRCNN class loss: 0.10626 FastRCNN total loss: 0.25656 L1 loss: 0.0000e+00 L2 loss: 0.59253 Learning rate: 0.0004 Mask loss: 0.17852 RPN box loss: 0.02615 RPN score loss: 0.01652 RPN total loss: 0.04266 Total loss: 1.07028 timestamp: 1654965136.1838238 iteration: 65230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04893 FastRCNN class loss: 0.07203 FastRCNN total loss: 0.12096 L1 loss: 0.0000e+00 L2 loss: 0.59253 Learning rate: 0.0004 Mask loss: 0.17844 RPN box loss: 0.01124 RPN score loss: 0.01053 RPN total loss: 0.02177 Total loss: 0.9137 timestamp: 1654965139.3761833 iteration: 65235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07082 FastRCNN class loss: 0.06553 FastRCNN total loss: 0.13635 L1 loss: 0.0000e+00 L2 loss: 0.59253 Learning rate: 0.0004 Mask loss: 0.10501 RPN box loss: 0.00642 RPN score loss: 0.00431 RPN total loss: 0.01072 Total loss: 0.84462 timestamp: 1654965142.5534508 iteration: 65240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08462 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.14938 L1 loss: 0.0000e+00 L2 loss: 0.59253 Learning rate: 0.0004 Mask loss: 0.10323 RPN box loss: 0.01677 RPN score loss: 0.01053 RPN total loss: 0.0273 Total loss: 0.87243 timestamp: 1654965145.7771895 iteration: 65245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0583 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.10955 L1 loss: 0.0000e+00 L2 loss: 0.59253 Learning rate: 0.0004 Mask loss: 0.11541 RPN box loss: 0.0173 RPN score loss: 0.00384 RPN total loss: 0.02114 Total loss: 0.83863 timestamp: 1654965148.9615216 iteration: 65250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08191 FastRCNN class loss: 0.06208 FastRCNN total loss: 0.144 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.0004 Mask loss: 0.14167 RPN box loss: 0.00665 RPN score loss: 0.00291 RPN total loss: 0.00956 Total loss: 0.88775 timestamp: 1654965152.1040165 iteration: 65255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14497 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.20257 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.0004 Mask loss: 0.11631 RPN box loss: 0.00723 RPN score loss: 0.00422 RPN total loss: 0.01145 Total loss: 0.92286 timestamp: 1654965155.3179865 iteration: 65260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0639 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.12631 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.0004 Mask loss: 0.13112 RPN box loss: 0.00818 RPN score loss: 0.00258 RPN total loss: 0.01076 Total loss: 0.86071 timestamp: 1654965158.542548 iteration: 65265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06866 FastRCNN class loss: 0.04133 FastRCNN total loss: 0.10998 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.0004 Mask loss: 0.05303 RPN box loss: 0.00249 RPN score loss: 0.00095 RPN total loss: 0.00344 Total loss: 0.75897 timestamp: 1654965161.761247 iteration: 65270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05573 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.10551 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.0004 Mask loss: 0.14644 RPN box loss: 0.01028 RPN score loss: 0.00243 RPN total loss: 0.01271 Total loss: 0.85718 timestamp: 1654965164.9208372 iteration: 65275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07728 FastRCNN class loss: 0.06504 FastRCNN total loss: 0.14232 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.0004 Mask loss: 0.12696 RPN box loss: 0.01474 RPN score loss: 0.00487 RPN total loss: 0.01961 Total loss: 0.8814 timestamp: 1654965168.130093 iteration: 65280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11628 FastRCNN class loss: 0.08829 FastRCNN total loss: 0.20457 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.0004 Mask loss: 0.10066 RPN box loss: 0.01854 RPN score loss: 0.01441 RPN total loss: 0.03295 Total loss: 0.93069 timestamp: 1654965171.3503428 iteration: 65285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11112 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.1619 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.0004 Mask loss: 0.1022 RPN box loss: 0.02305 RPN score loss: 0.00331 RPN total loss: 0.02635 Total loss: 0.88297 timestamp: 1654965174.5669987 iteration: 65290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14073 FastRCNN class loss: 0.04418 FastRCNN total loss: 0.18491 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.0004 Mask loss: 0.08934 RPN box loss: 0.01045 RPN score loss: 0.00395 RPN total loss: 0.0144 Total loss: 0.88116 timestamp: 1654965177.696915 iteration: 65295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08017 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.15519 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.0004 Mask loss: 0.14302 RPN box loss: 0.0178 RPN score loss: 0.00428 RPN total loss: 0.02208 Total loss: 0.91279 timestamp: 1654965180.8897219 iteration: 65300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07062 FastRCNN class loss: 0.0458 FastRCNN total loss: 0.11642 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.0004 Mask loss: 0.15608 RPN box loss: 0.01018 RPN score loss: 0.00396 RPN total loss: 0.01414 Total loss: 0.87915 timestamp: 1654965184.0356324 iteration: 65305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09006 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.15898 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.0004 Mask loss: 0.18104 RPN box loss: 0.0125 RPN score loss: 0.00702 RPN total loss: 0.01952 Total loss: 0.95205 timestamp: 1654965187.255619 iteration: 65310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04932 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.09718 L1 loss: 0.0000e+00 L2 loss: 0.5925 Learning rate: 0.0004 Mask loss: 0.08513 RPN box loss: 0.00252 RPN score loss: 0.00177 RPN total loss: 0.00429 Total loss: 0.77911 timestamp: 1654965190.40554 iteration: 65315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12551 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.18639 L1 loss: 0.0000e+00 L2 loss: 0.5925 Learning rate: 0.0004 Mask loss: 0.14986 RPN box loss: 0.01774 RPN score loss: 0.00304 RPN total loss: 0.02079 Total loss: 0.94955 timestamp: 1654965193.5571208 iteration: 65320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07143 FastRCNN class loss: 0.05523 FastRCNN total loss: 0.12667 L1 loss: 0.0000e+00 L2 loss: 0.5925 Learning rate: 0.0004 Mask loss: 0.12898 RPN box loss: 0.0203 RPN score loss: 0.00187 RPN total loss: 0.02217 Total loss: 0.87032 timestamp: 1654965196.7513807 iteration: 65325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09648 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.1601 L1 loss: 0.0000e+00 L2 loss: 0.5925 Learning rate: 0.0004 Mask loss: 0.11521 RPN box loss: 0.00946 RPN score loss: 0.00593 RPN total loss: 0.01539 Total loss: 0.8832 timestamp: 1654965200.011772 iteration: 65330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12144 FastRCNN class loss: 0.08361 FastRCNN total loss: 0.20505 L1 loss: 0.0000e+00 L2 loss: 0.5925 Learning rate: 0.0004 Mask loss: 0.14427 RPN box loss: 0.01507 RPN score loss: 0.00279 RPN total loss: 0.01786 Total loss: 0.95968 timestamp: 1654965203.1337118 iteration: 65335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06224 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.12665 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.1118 RPN box loss: 0.00672 RPN score loss: 0.00995 RPN total loss: 0.01667 Total loss: 0.84762 timestamp: 1654965206.3395817 iteration: 65340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.05179 FastRCNN total loss: 0.13853 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.10222 RPN box loss: 0.04775 RPN score loss: 0.00921 RPN total loss: 0.05696 Total loss: 0.8902 timestamp: 1654965209.404752 iteration: 65345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06306 FastRCNN class loss: 0.06825 FastRCNN total loss: 0.13131 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.11221 RPN box loss: 0.01619 RPN score loss: 0.00817 RPN total loss: 0.02436 Total loss: 0.86038 timestamp: 1654965212.6091566 iteration: 65350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05404 FastRCNN class loss: 0.04891 FastRCNN total loss: 0.10295 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.10904 RPN box loss: 0.00546 RPN score loss: 0.00572 RPN total loss: 0.01118 Total loss: 0.81566 timestamp: 1654965215.8122137 iteration: 65355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13243 FastRCNN class loss: 0.08228 FastRCNN total loss: 0.21471 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.14607 RPN box loss: 0.0253 RPN score loss: 0.01812 RPN total loss: 0.04342 Total loss: 0.99669 timestamp: 1654965218.958003 iteration: 65360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09117 FastRCNN class loss: 0.04283 FastRCNN total loss: 0.134 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.11137 RPN box loss: 0.02429 RPN score loss: 0.00146 RPN total loss: 0.02574 Total loss: 0.86359 timestamp: 1654965222.1791067 iteration: 65365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03739 FastRCNN class loss: 0.03915 FastRCNN total loss: 0.07654 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.0004 Mask loss: 0.13283 RPN box loss: 0.00367 RPN score loss: 0.00242 RPN total loss: 0.0061 Total loss: 0.80796 timestamp: 1654965225.3075752 iteration: 65370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07131 FastRCNN class loss: 0.05054 FastRCNN total loss: 0.12185 L1 loss: 0.0000e+00 L2 loss: 0.59248 Learning rate: 0.0004 Mask loss: 0.12175 RPN box loss: 0.0071 RPN score loss: 0.00602 RPN total loss: 0.01313 Total loss: 0.84922 timestamp: 1654965228.5188935 iteration: 65375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10483 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.1625 L1 loss: 0.0000e+00 L2 loss: 0.59248 Learning rate: 0.0004 Mask loss: 0.16091 RPN box loss: 0.01705 RPN score loss: 0.0058 RPN total loss: 0.02285 Total loss: 0.93874 timestamp: 1654965231.6498914 iteration: 65380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17651 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.25553 L1 loss: 0.0000e+00 L2 loss: 0.59248 Learning rate: 0.0004 Mask loss: 0.13324 RPN box loss: 0.02119 RPN score loss: 0.00798 RPN total loss: 0.02916 Total loss: 1.01041 timestamp: 1654965234.8448133 iteration: 65385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06761 FastRCNN class loss: 0.04679 FastRCNN total loss: 0.1144 L1 loss: 0.0000e+00 L2 loss: 0.59248 Learning rate: 0.0004 Mask loss: 0.09276 RPN box loss: 0.01987 RPN score loss: 0.00435 RPN total loss: 0.02422 Total loss: 0.82385 timestamp: 1654965238.0341861 iteration: 65390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09542 FastRCNN class loss: 0.07794 FastRCNN total loss: 0.17336 L1 loss: 0.0000e+00 L2 loss: 0.59248 Learning rate: 0.0004 Mask loss: 0.13794 RPN box loss: 0.01825 RPN score loss: 0.00763 RPN total loss: 0.02589 Total loss: 0.92965 timestamp: 1654965241.2133484 iteration: 65395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05 FastRCNN class loss: 0.03561 FastRCNN total loss: 0.0856 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.0004 Mask loss: 0.10433 RPN box loss: 0.00872 RPN score loss: 0.00279 RPN total loss: 0.0115 Total loss: 0.79391 timestamp: 1654965244.4359796 iteration: 65400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09225 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.1521 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.0004 Mask loss: 0.11673 RPN box loss: 0.00676 RPN score loss: 0.00349 RPN total loss: 0.01025 Total loss: 0.87155 timestamp: 1654965247.663798 iteration: 65405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04808 FastRCNN class loss: 0.05964 FastRCNN total loss: 0.10772 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.0004 Mask loss: 0.08279 RPN box loss: 0.01437 RPN score loss: 0.00186 RPN total loss: 0.01623 Total loss: 0.7992 timestamp: 1654965250.8501725 iteration: 65410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06943 FastRCNN class loss: 0.04595 FastRCNN total loss: 0.11538 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.0004 Mask loss: 0.1125 RPN box loss: 0.00393 RPN score loss: 0.0013 RPN total loss: 0.00523 Total loss: 0.82558 timestamp: 1654965254.101172 iteration: 65415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09518 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.1543 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.0004 Mask loss: 0.15723 RPN box loss: 0.00545 RPN score loss: 0.00274 RPN total loss: 0.00819 Total loss: 0.91219 timestamp: 1654965257.344939 iteration: 65420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04935 FastRCNN class loss: 0.03594 FastRCNN total loss: 0.0853 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.0004 Mask loss: 0.08841 RPN box loss: 0.0064 RPN score loss: 0.00683 RPN total loss: 0.01323 Total loss: 0.7794 timestamp: 1654965260.5379212 iteration: 65425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05998 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.14248 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.0004 Mask loss: 0.15784 RPN box loss: 0.01253 RPN score loss: 0.01711 RPN total loss: 0.02964 Total loss: 0.92243 timestamp: 1654965263.6828554 iteration: 65430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09509 FastRCNN class loss: 0.04305 FastRCNN total loss: 0.13814 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.0004 Mask loss: 0.11548 RPN box loss: 0.01238 RPN score loss: 0.00179 RPN total loss: 0.01418 Total loss: 0.86025 timestamp: 1654965266.8987627 iteration: 65435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06513 FastRCNN class loss: 0.05444 FastRCNN total loss: 0.11957 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.0004 Mask loss: 0.12124 RPN box loss: 0.01216 RPN score loss: 0.00241 RPN total loss: 0.01457 Total loss: 0.84784 timestamp: 1654965270.1121495 iteration: 65440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12059 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.19377 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.0004 Mask loss: 0.20618 RPN box loss: 0.01941 RPN score loss: 0.00604 RPN total loss: 0.02545 Total loss: 1.01786 timestamp: 1654965273.249019 iteration: 65445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06635 FastRCNN class loss: 0.04012 FastRCNN total loss: 0.10648 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.0004 Mask loss: 0.11661 RPN box loss: 0.00639 RPN score loss: 0.00157 RPN total loss: 0.00796 Total loss: 0.8235 timestamp: 1654965276.46806 iteration: 65450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09555 FastRCNN class loss: 0.06723 FastRCNN total loss: 0.16278 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.0004 Mask loss: 0.10491 RPN box loss: 0.00646 RPN score loss: 0.0025 RPN total loss: 0.00896 Total loss: 0.86911 timestamp: 1654965279.6500638 iteration: 65455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10927 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.18703 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.0004 Mask loss: 0.1367 RPN box loss: 0.01825 RPN score loss: 0.00665 RPN total loss: 0.02491 Total loss: 0.94108 timestamp: 1654965282.7860277 iteration: 65460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12925 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.19295 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.0004 Mask loss: 0.08958 RPN box loss: 0.01343 RPN score loss: 0.00236 RPN total loss: 0.01579 Total loss: 0.89078 timestamp: 1654965285.9814148 iteration: 65465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07535 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.13114 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.0004 Mask loss: 0.15986 RPN box loss: 0.02345 RPN score loss: 0.0047 RPN total loss: 0.02815 Total loss: 0.9116 timestamp: 1654965289.1724615 iteration: 65470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1103 FastRCNN class loss: 0.06596 FastRCNN total loss: 0.17626 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.0004 Mask loss: 0.14484 RPN box loss: 0.01568 RPN score loss: 0.00371 RPN total loss: 0.01939 Total loss: 0.93294 timestamp: 1654965292.38568 iteration: 65475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09776 FastRCNN class loss: 0.04057 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.0004 Mask loss: 0.12634 RPN box loss: 0.01197 RPN score loss: 0.00266 RPN total loss: 0.01463 Total loss: 0.87174 timestamp: 1654965295.5608783 iteration: 65480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05048 FastRCNN class loss: 0.04597 FastRCNN total loss: 0.09645 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.0004 Mask loss: 0.10003 RPN box loss: 0.00592 RPN score loss: 0.00035 RPN total loss: 0.00627 Total loss: 0.7952 timestamp: 1654965298.7918968 iteration: 65485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07953 FastRCNN class loss: 0.05372 FastRCNN total loss: 0.13325 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.0004 Mask loss: 0.19668 RPN box loss: 0.01086 RPN score loss: 0.00207 RPN total loss: 0.01293 Total loss: 0.9353 timestamp: 1654965301.9404423 iteration: 65490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13123 FastRCNN class loss: 0.11115 FastRCNN total loss: 0.24238 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.0004 Mask loss: 0.14105 RPN box loss: 0.01305 RPN score loss: 0.00503 RPN total loss: 0.01809 Total loss: 0.99396 timestamp: 1654965305.1418555 iteration: 65495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10773 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.19866 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.0004 Mask loss: 0.12451 RPN box loss: 0.03686 RPN score loss: 0.00628 RPN total loss: 0.04314 Total loss: 0.95875 timestamp: 1654965308.359624 iteration: 65500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0612 FastRCNN class loss: 0.03076 FastRCNN total loss: 0.09196 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.0004 Mask loss: 0.09333 RPN box loss: 0.00488 RPN score loss: 0.00068 RPN total loss: 0.00556 Total loss: 0.78329 timestamp: 1654965311.5497775 iteration: 65505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06126 FastRCNN class loss: 0.0626 FastRCNN total loss: 0.12386 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.0004 Mask loss: 0.13772 RPN box loss: 0.0075 RPN score loss: 0.00173 RPN total loss: 0.00923 Total loss: 0.86324 timestamp: 1654965314.7540553 iteration: 65510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10076 FastRCNN class loss: 0.11083 FastRCNN total loss: 0.21159 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.14201 RPN box loss: 0.0135 RPN score loss: 0.00332 RPN total loss: 0.01682 Total loss: 0.96285 timestamp: 1654965317.9945364 iteration: 65515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09062 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.16627 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.15595 RPN box loss: 0.00807 RPN score loss: 0.00944 RPN total loss: 0.01751 Total loss: 0.93216 timestamp: 1654965321.1919792 iteration: 65520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11493 FastRCNN class loss: 0.09286 FastRCNN total loss: 0.20779 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.19109 RPN box loss: 0.00998 RPN score loss: 0.00813 RPN total loss: 0.01812 Total loss: 1.00943 timestamp: 1654965324.34765 iteration: 65525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09059 FastRCNN class loss: 0.06986 FastRCNN total loss: 0.16045 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.09498 RPN box loss: 0.00574 RPN score loss: 0.00104 RPN total loss: 0.00678 Total loss: 0.85464 timestamp: 1654965327.4655678 iteration: 65530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13423 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.20521 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.17569 RPN box loss: 0.01063 RPN score loss: 0.0039 RPN total loss: 0.01453 Total loss: 0.98785 timestamp: 1654965330.7146716 iteration: 65535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07499 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.16846 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.16456 RPN box loss: 0.02411 RPN score loss: 0.01439 RPN total loss: 0.0385 Total loss: 0.96396 timestamp: 1654965333.9212058 iteration: 65540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07459 FastRCNN class loss: 0.06566 FastRCNN total loss: 0.14026 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.0004 Mask loss: 0.13963 RPN box loss: 0.00938 RPN score loss: 0.01442 RPN total loss: 0.0238 Total loss: 0.89611 timestamp: 1654965337.123594 iteration: 65545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12527 FastRCNN class loss: 0.08351 FastRCNN total loss: 0.20878 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.0004 Mask loss: 0.15224 RPN box loss: 0.02899 RPN score loss: 0.00565 RPN total loss: 0.03464 Total loss: 0.98808 timestamp: 1654965340.3699205 iteration: 65550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08377 FastRCNN class loss: 0.04944 FastRCNN total loss: 0.13321 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.0004 Mask loss: 0.07934 RPN box loss: 0.01139 RPN score loss: 0.00153 RPN total loss: 0.01292 Total loss: 0.81789 timestamp: 1654965343.5190587 iteration: 65555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14081 FastRCNN class loss: 0.12891 FastRCNN total loss: 0.26973 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.0004 Mask loss: 0.21439 RPN box loss: 0.01585 RPN score loss: 0.01074 RPN total loss: 0.02658 Total loss: 1.10312 timestamp: 1654965346.7581162 iteration: 65560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0457 FastRCNN class loss: 0.03121 FastRCNN total loss: 0.07692 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.0004 Mask loss: 0.09679 RPN box loss: 0.0035 RPN score loss: 0.00653 RPN total loss: 0.01003 Total loss: 0.77617 timestamp: 1654965350.0354235 iteration: 65565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1225 FastRCNN class loss: 0.06931 FastRCNN total loss: 0.19181 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.0004 Mask loss: 0.14626 RPN box loss: 0.00834 RPN score loss: 0.00237 RPN total loss: 0.01071 Total loss: 0.9412 timestamp: 1654965353.2080817 iteration: 65570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04768 FastRCNN class loss: 0.04871 FastRCNN total loss: 0.09639 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.0004 Mask loss: 0.12111 RPN box loss: 0.01984 RPN score loss: 0.00799 RPN total loss: 0.02782 Total loss: 0.83774 timestamp: 1654965356.473461 iteration: 65575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11785 FastRCNN class loss: 0.0909 FastRCNN total loss: 0.20874 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.0004 Mask loss: 0.10054 RPN box loss: 0.0083 RPN score loss: 0.0038 RPN total loss: 0.01209 Total loss: 0.91379 timestamp: 1654965359.6668303 iteration: 65580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05661 FastRCNN class loss: 0.1059 FastRCNN total loss: 0.1625 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.0004 Mask loss: 0.1162 RPN box loss: 0.02007 RPN score loss: 0.00392 RPN total loss: 0.02399 Total loss: 0.8951 timestamp: 1654965362.9060733 iteration: 65585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09267 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.14857 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.0004 Mask loss: 0.08647 RPN box loss: 0.0142 RPN score loss: 0.00073 RPN total loss: 0.01493 Total loss: 0.84238 timestamp: 1654965366.134673 iteration: 65590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07742 FastRCNN class loss: 0.06836 FastRCNN total loss: 0.14578 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.0004 Mask loss: 0.11137 RPN box loss: 0.0203 RPN score loss: 0.01067 RPN total loss: 0.03097 Total loss: 0.88052 timestamp: 1654965369.3498454 iteration: 65595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07342 FastRCNN class loss: 0.06882 FastRCNN total loss: 0.14224 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.0004 Mask loss: 0.14488 RPN box loss: 0.01385 RPN score loss: 0.00934 RPN total loss: 0.02319 Total loss: 0.90271 timestamp: 1654965372.54476 iteration: 65600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09192 FastRCNN class loss: 0.08723 FastRCNN total loss: 0.17915 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.0004 Mask loss: 0.14402 RPN box loss: 0.01681 RPN score loss: 0.00225 RPN total loss: 0.01905 Total loss: 0.93463 timestamp: 1654965375.704473 iteration: 65605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04839 FastRCNN class loss: 0.03564 FastRCNN total loss: 0.08403 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.0004 Mask loss: 0.09515 RPN box loss: 0.00291 RPN score loss: 0.00296 RPN total loss: 0.00587 Total loss: 0.77746 timestamp: 1654965378.8856423 iteration: 65610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05538 FastRCNN class loss: 0.06078 FastRCNN total loss: 0.11616 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.0004 Mask loss: 0.12392 RPN box loss: 0.02154 RPN score loss: 0.00537 RPN total loss: 0.02691 Total loss: 0.8594 timestamp: 1654965382.1099486 iteration: 65615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10101 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.16636 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.0004 Mask loss: 0.18717 RPN box loss: 0.01079 RPN score loss: 0.003 RPN total loss: 0.01379 Total loss: 0.95972 timestamp: 1654965385.320394 iteration: 65620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11191 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.16536 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.0004 Mask loss: 0.11236 RPN box loss: 0.04056 RPN score loss: 0.00233 RPN total loss: 0.04289 Total loss: 0.91301 timestamp: 1654965388.4640143 iteration: 65625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13518 FastRCNN class loss: 0.09932 FastRCNN total loss: 0.2345 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.0004 Mask loss: 0.13721 RPN box loss: 0.01209 RPN score loss: 0.00274 RPN total loss: 0.01483 Total loss: 0.97894 timestamp: 1654965391.6890895 iteration: 65630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09085 FastRCNN class loss: 0.081 FastRCNN total loss: 0.17184 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.0004 Mask loss: 0.12957 RPN box loss: 0.00792 RPN score loss: 0.00452 RPN total loss: 0.01244 Total loss: 0.90625 timestamp: 1654965394.8476737 iteration: 65635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14803 FastRCNN class loss: 0.06737 FastRCNN total loss: 0.21541 L1 loss: 0.0000e+00 L2 loss: 0.59239 Learning rate: 0.0004 Mask loss: 0.16486 RPN box loss: 0.00646 RPN score loss: 0.00433 RPN total loss: 0.0108 Total loss: 0.98345 timestamp: 1654965398.1341138 iteration: 65640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05971 FastRCNN class loss: 0.05369 FastRCNN total loss: 0.11339 L1 loss: 0.0000e+00 L2 loss: 0.59239 Learning rate: 0.0004 Mask loss: 0.09241 RPN box loss: 0.00469 RPN score loss: 0.00534 RPN total loss: 0.01004 Total loss: 0.80823 timestamp: 1654965401.3060682 iteration: 65645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07108 FastRCNN class loss: 0.03537 FastRCNN total loss: 0.10645 L1 loss: 0.0000e+00 L2 loss: 0.59239 Learning rate: 0.0004 Mask loss: 0.12424 RPN box loss: 0.00771 RPN score loss: 0.00137 RPN total loss: 0.00908 Total loss: 0.83217 timestamp: 1654965404.5119848 iteration: 65650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0521 FastRCNN class loss: 0.04492 FastRCNN total loss: 0.09703 L1 loss: 0.0000e+00 L2 loss: 0.59239 Learning rate: 0.0004 Mask loss: 0.15208 RPN box loss: 0.01006 RPN score loss: 0.00282 RPN total loss: 0.01288 Total loss: 0.85437 timestamp: 1654965407.6887076 iteration: 65655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10112 FastRCNN class loss: 0.07548 FastRCNN total loss: 0.1766 L1 loss: 0.0000e+00 L2 loss: 0.59239 Learning rate: 0.0004 Mask loss: 0.16971 RPN box loss: 0.01423 RPN score loss: 0.00763 RPN total loss: 0.02185 Total loss: 0.96054 timestamp: 1654965410.9078095 iteration: 65660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09094 FastRCNN class loss: 0.08378 FastRCNN total loss: 0.17472 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.12026 RPN box loss: 0.02705 RPN score loss: 0.00701 RPN total loss: 0.03405 Total loss: 0.92142 timestamp: 1654965414.1341927 iteration: 65665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.07455 FastRCNN total loss: 0.19363 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.14449 RPN box loss: 0.02401 RPN score loss: 0.01593 RPN total loss: 0.03994 Total loss: 0.97045 timestamp: 1654965417.3143506 iteration: 65670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07561 FastRCNN class loss: 0.03809 FastRCNN total loss: 0.11369 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.0906 RPN box loss: 0.00566 RPN score loss: 0.00195 RPN total loss: 0.00761 Total loss: 0.80429 timestamp: 1654965420.6108215 iteration: 65675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04566 FastRCNN class loss: 0.04924 FastRCNN total loss: 0.0949 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.13839 RPN box loss: 0.00309 RPN score loss: 0.00124 RPN total loss: 0.00433 Total loss: 0.83 timestamp: 1654965423.8366132 iteration: 65680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1325 FastRCNN class loss: 0.1036 FastRCNN total loss: 0.23611 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.16011 RPN box loss: 0.01962 RPN score loss: 0.00795 RPN total loss: 0.02757 Total loss: 1.01617 timestamp: 1654965427.0339696 iteration: 65685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1124 FastRCNN class loss: 0.06751 FastRCNN total loss: 0.17991 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.17091 RPN box loss: 0.01423 RPN score loss: 0.00488 RPN total loss: 0.01911 Total loss: 0.96231 timestamp: 1654965430.274234 iteration: 65690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06629 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.14964 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.0004 Mask loss: 0.11383 RPN box loss: 0.00956 RPN score loss: 0.00349 RPN total loss: 0.01305 Total loss: 0.8689 timestamp: 1654965433.4170668 iteration: 65695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07846 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.13803 L1 loss: 0.0000e+00 L2 loss: 0.59237 Learning rate: 0.0004 Mask loss: 0.09337 RPN box loss: 0.02102 RPN score loss: 0.01115 RPN total loss: 0.03218 Total loss: 0.85595 timestamp: 1654965436.603924 iteration: 65700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10907 FastRCNN class loss: 0.08777 FastRCNN total loss: 0.19684 L1 loss: 0.0000e+00 L2 loss: 0.59237 Learning rate: 0.0004 Mask loss: 0.13441 RPN box loss: 0.00449 RPN score loss: 0.01131 RPN total loss: 0.0158 Total loss: 0.93942 timestamp: 1654965439.843623 iteration: 65705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06286 FastRCNN class loss: 0.05481 FastRCNN total loss: 0.11767 L1 loss: 0.0000e+00 L2 loss: 0.59237 Learning rate: 0.0004 Mask loss: 0.13273 RPN box loss: 0.00412 RPN score loss: 0.00232 RPN total loss: 0.00644 Total loss: 0.8492 timestamp: 1654965442.9804451 iteration: 65710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11712 FastRCNN class loss: 0.06449 FastRCNN total loss: 0.18161 L1 loss: 0.0000e+00 L2 loss: 0.59237 Learning rate: 0.0004 Mask loss: 0.17392 RPN box loss: 0.01054 RPN score loss: 0.00875 RPN total loss: 0.01929 Total loss: 0.96719 timestamp: 1654965446.2209368 iteration: 65715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05908 FastRCNN class loss: 0.04777 FastRCNN total loss: 0.10685 L1 loss: 0.0000e+00 L2 loss: 0.59237 Learning rate: 0.0004 Mask loss: 0.1255 RPN box loss: 0.01975 RPN score loss: 0.00241 RPN total loss: 0.02216 Total loss: 0.84687 timestamp: 1654965449.4010868 iteration: 65720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05502 FastRCNN class loss: 0.03385 FastRCNN total loss: 0.08887 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.0004 Mask loss: 0.09632 RPN box loss: 0.01108 RPN score loss: 0.00061 RPN total loss: 0.01169 Total loss: 0.78924 timestamp: 1654965452.5690634 iteration: 65725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05067 FastRCNN class loss: 0.0454 FastRCNN total loss: 0.09607 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.0004 Mask loss: 0.11303 RPN box loss: 0.00626 RPN score loss: 0.00353 RPN total loss: 0.0098 Total loss: 0.81125 timestamp: 1654965455.8102224 iteration: 65730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09084 FastRCNN class loss: 0.07168 FastRCNN total loss: 0.16252 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.0004 Mask loss: 0.1223 RPN box loss: 0.01526 RPN score loss: 0.00149 RPN total loss: 0.01675 Total loss: 0.89393 timestamp: 1654965458.926205 iteration: 65735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06302 FastRCNN class loss: 0.04901 FastRCNN total loss: 0.11203 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.0004 Mask loss: 0.1206 RPN box loss: 0.02473 RPN score loss: 0.00244 RPN total loss: 0.02717 Total loss: 0.85217 timestamp: 1654965462.1009305 iteration: 65740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06405 FastRCNN class loss: 0.06126 FastRCNN total loss: 0.12531 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.0004 Mask loss: 0.11981 RPN box loss: 0.03269 RPN score loss: 0.01133 RPN total loss: 0.04402 Total loss: 0.8815 timestamp: 1654965465.2760866 iteration: 65745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07404 FastRCNN class loss: 0.04861 FastRCNN total loss: 0.12265 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.0004 Mask loss: 0.12964 RPN box loss: 0.00777 RPN score loss: 0.00496 RPN total loss: 0.01273 Total loss: 0.85738 timestamp: 1654965468.4420478 iteration: 65750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06786 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.15464 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.0004 Mask loss: 0.15265 RPN box loss: 0.04129 RPN score loss: 0.00371 RPN total loss: 0.045 Total loss: 0.94465 timestamp: 1654965471.662878 iteration: 65755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05453 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.12558 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.0004 Mask loss: 0.11241 RPN box loss: 0.01037 RPN score loss: 0.00257 RPN total loss: 0.01294 Total loss: 0.84328 timestamp: 1654965474.917135 iteration: 65760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05814 FastRCNN class loss: 0.04844 FastRCNN total loss: 0.10658 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.0004 Mask loss: 0.14045 RPN box loss: 0.0236 RPN score loss: 0.00557 RPN total loss: 0.02917 Total loss: 0.86855 timestamp: 1654965478.1452355 iteration: 65765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08551 FastRCNN class loss: 0.06619 FastRCNN total loss: 0.1517 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.0004 Mask loss: 0.13386 RPN box loss: 0.00555 RPN score loss: 0.00426 RPN total loss: 0.00981 Total loss: 0.88772 timestamp: 1654965481.3519719 iteration: 65770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08188 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.16552 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.0004 Mask loss: 0.14907 RPN box loss: 0.03611 RPN score loss: 0.00465 RPN total loss: 0.04076 Total loss: 0.9477 timestamp: 1654965484.5361423 iteration: 65775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07852 FastRCNN class loss: 0.05713 FastRCNN total loss: 0.13565 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.0004 Mask loss: 0.14686 RPN box loss: 0.00579 RPN score loss: 0.00571 RPN total loss: 0.0115 Total loss: 0.88635 timestamp: 1654965487.780499 iteration: 65780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0567 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.11949 L1 loss: 0.0000e+00 L2 loss: 0.59234 Learning rate: 0.0004 Mask loss: 0.1065 RPN box loss: 0.00721 RPN score loss: 0.00134 RPN total loss: 0.00855 Total loss: 0.82688 timestamp: 1654965490.882087 iteration: 65785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06262 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.11243 L1 loss: 0.0000e+00 L2 loss: 0.59234 Learning rate: 0.0004 Mask loss: 0.1294 RPN box loss: 0.00457 RPN score loss: 0.00258 RPN total loss: 0.00715 Total loss: 0.84133 timestamp: 1654965494.201206 iteration: 65790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08407 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.14692 L1 loss: 0.0000e+00 L2 loss: 0.59234 Learning rate: 0.0004 Mask loss: 0.12261 RPN box loss: 0.01409 RPN score loss: 0.00916 RPN total loss: 0.02325 Total loss: 0.88511 timestamp: 1654965497.3685365 iteration: 65795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05106 FastRCNN class loss: 0.03454 FastRCNN total loss: 0.08561 L1 loss: 0.0000e+00 L2 loss: 0.59234 Learning rate: 0.0004 Mask loss: 0.10926 RPN box loss: 0.01023 RPN score loss: 0.00164 RPN total loss: 0.01186 Total loss: 0.79907 timestamp: 1654965500.5726042 iteration: 65800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14603 FastRCNN class loss: 0.12444 FastRCNN total loss: 0.27048 L1 loss: 0.0000e+00 L2 loss: 0.59234 Learning rate: 0.0004 Mask loss: 0.18182 RPN box loss: 0.01816 RPN score loss: 0.00517 RPN total loss: 0.02333 Total loss: 1.06796 timestamp: 1654965503.746811 iteration: 65805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.08244 FastRCNN total loss: 0.19396 L1 loss: 0.0000e+00 L2 loss: 0.59233 Learning rate: 0.0004 Mask loss: 0.11617 RPN box loss: 0.01491 RPN score loss: 0.00358 RPN total loss: 0.01849 Total loss: 0.92095 timestamp: 1654965506.994899 iteration: 65810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13668 FastRCNN class loss: 0.09226 FastRCNN total loss: 0.22895 L1 loss: 0.0000e+00 L2 loss: 0.59233 Learning rate: 0.0004 Mask loss: 0.16835 RPN box loss: 0.01704 RPN score loss: 0.01032 RPN total loss: 0.02735 Total loss: 1.01698 timestamp: 1654965510.1903172 iteration: 65815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09385 FastRCNN class loss: 0.07346 FastRCNN total loss: 0.16731 L1 loss: 0.0000e+00 L2 loss: 0.59233 Learning rate: 0.0004 Mask loss: 0.16752 RPN box loss: 0.02033 RPN score loss: 0.01574 RPN total loss: 0.03606 Total loss: 0.96322 timestamp: 1654965513.3254354 iteration: 65820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12368 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.18545 L1 loss: 0.0000e+00 L2 loss: 0.59233 Learning rate: 0.0004 Mask loss: 0.12011 RPN box loss: 0.0042 RPN score loss: 0.0013 RPN total loss: 0.0055 Total loss: 0.90339 timestamp: 1654965516.551462 iteration: 65825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04604 FastRCNN class loss: 0.0441 FastRCNN total loss: 0.09013 L1 loss: 0.0000e+00 L2 loss: 0.59233 Learning rate: 0.0004 Mask loss: 0.1222 RPN box loss: 0.00856 RPN score loss: 0.00276 RPN total loss: 0.01132 Total loss: 0.81598 timestamp: 1654965519.8515012 iteration: 65830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09576 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.59232 Learning rate: 0.0004 Mask loss: 0.13929 RPN box loss: 0.02573 RPN score loss: 0.00217 RPN total loss: 0.0279 Total loss: 0.94145 timestamp: 1654965522.971547 iteration: 65835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09388 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.15965 L1 loss: 0.0000e+00 L2 loss: 0.59232 Learning rate: 0.0004 Mask loss: 0.11622 RPN box loss: 0.00923 RPN score loss: 0.00369 RPN total loss: 0.01292 Total loss: 0.88111 timestamp: 1654965526.1603823 iteration: 65840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08146 FastRCNN class loss: 0.06117 FastRCNN total loss: 0.14263 L1 loss: 0.0000e+00 L2 loss: 0.59232 Learning rate: 0.0004 Mask loss: 0.30451 RPN box loss: 0.01988 RPN score loss: 0.01058 RPN total loss: 0.03046 Total loss: 1.06993 timestamp: 1654965529.3064492 iteration: 65845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08767 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.15464 L1 loss: 0.0000e+00 L2 loss: 0.59232 Learning rate: 0.0004 Mask loss: 0.14304 RPN box loss: 0.01534 RPN score loss: 0.00263 RPN total loss: 0.01797 Total loss: 0.90796 timestamp: 1654965532.4777803 iteration: 65850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10435 FastRCNN class loss: 0.10503 FastRCNN total loss: 0.20938 L1 loss: 0.0000e+00 L2 loss: 0.59232 Learning rate: 0.0004 Mask loss: 0.17771 RPN box loss: 0.01644 RPN score loss: 0.00393 RPN total loss: 0.02037 Total loss: 0.99979 timestamp: 1654965535.579943 iteration: 65855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08553 FastRCNN class loss: 0.07158 FastRCNN total loss: 0.15711 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.16687 RPN box loss: 0.0116 RPN score loss: 0.01159 RPN total loss: 0.02319 Total loss: 0.93948 timestamp: 1654965538.7394044 iteration: 65860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06343 FastRCNN class loss: 0.04473 FastRCNN total loss: 0.10816 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.07072 RPN box loss: 0.00741 RPN score loss: 0.00096 RPN total loss: 0.00837 Total loss: 0.77957 timestamp: 1654965541.9387565 iteration: 65865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05664 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.10349 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.09448 RPN box loss: 0.00446 RPN score loss: 0.00127 RPN total loss: 0.00573 Total loss: 0.79601 timestamp: 1654965545.1427383 iteration: 65870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06902 FastRCNN class loss: 0.09278 FastRCNN total loss: 0.1618 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.08645 RPN box loss: 0.00449 RPN score loss: 0.00265 RPN total loss: 0.00714 Total loss: 0.84769 timestamp: 1654965548.343862 iteration: 65875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05796 FastRCNN class loss: 0.03678 FastRCNN total loss: 0.09474 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.11936 RPN box loss: 0.01214 RPN score loss: 0.00716 RPN total loss: 0.0193 Total loss: 0.82572 timestamp: 1654965551.5484152 iteration: 65880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10245 FastRCNN class loss: 0.05192 FastRCNN total loss: 0.15437 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.10155 RPN box loss: 0.00834 RPN score loss: 0.00121 RPN total loss: 0.00954 Total loss: 0.85776 timestamp: 1654965554.743639 iteration: 65885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09919 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.16939 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.0004 Mask loss: 0.18089 RPN box loss: 0.00838 RPN score loss: 0.0205 RPN total loss: 0.02888 Total loss: 0.97147 timestamp: 1654965557.977634 iteration: 65890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0777 FastRCNN class loss: 0.08698 FastRCNN total loss: 0.16467 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.0004 Mask loss: 0.1056 RPN box loss: 0.0185 RPN score loss: 0.00443 RPN total loss: 0.02293 Total loss: 0.8855 timestamp: 1654965561.1531117 iteration: 65895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12293 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.18349 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.0004 Mask loss: 0.10632 RPN box loss: 0.00911 RPN score loss: 0.00201 RPN total loss: 0.01112 Total loss: 0.89323 timestamp: 1654965564.3380792 iteration: 65900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11363 FastRCNN class loss: 0.05095 FastRCNN total loss: 0.16459 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.0004 Mask loss: 0.10864 RPN box loss: 0.01186 RPN score loss: 0.00253 RPN total loss: 0.01439 Total loss: 0.87992 timestamp: 1654965567.5710948 iteration: 65905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10252 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.16135 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.0004 Mask loss: 0.17546 RPN box loss: 0.01964 RPN score loss: 0.00699 RPN total loss: 0.02662 Total loss: 0.95573 timestamp: 1654965570.7547657 iteration: 65910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19093 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.26974 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.0004 Mask loss: 0.11168 RPN box loss: 0.00899 RPN score loss: 0.00544 RPN total loss: 0.01442 Total loss: 0.98814 timestamp: 1654965573.9780004 iteration: 65915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08063 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.15562 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.13531 RPN box loss: 0.01245 RPN score loss: 0.00507 RPN total loss: 0.01752 Total loss: 0.90074 timestamp: 1654965577.1801534 iteration: 65920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10494 FastRCNN class loss: 0.06334 FastRCNN total loss: 0.16827 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.14611 RPN box loss: 0.01812 RPN score loss: 0.00146 RPN total loss: 0.01958 Total loss: 0.92626 timestamp: 1654965580.4142597 iteration: 65925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08208 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.17902 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.11747 RPN box loss: 0.01648 RPN score loss: 0.00671 RPN total loss: 0.02318 Total loss: 0.91196 timestamp: 1654965583.5894096 iteration: 65930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11854 FastRCNN class loss: 0.09269 FastRCNN total loss: 0.21123 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.14318 RPN box loss: 0.01554 RPN score loss: 0.0052 RPN total loss: 0.02074 Total loss: 0.96744 timestamp: 1654965586.7289386 iteration: 65935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12107 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.17557 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.10787 RPN box loss: 0.0133 RPN score loss: 0.00261 RPN total loss: 0.01591 Total loss: 0.89164 timestamp: 1654965589.9237905 iteration: 65940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05117 FastRCNN class loss: 0.05169 FastRCNN total loss: 0.10286 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.15485 RPN box loss: 0.01397 RPN score loss: 0.01076 RPN total loss: 0.02474 Total loss: 0.87473 timestamp: 1654965593.138582 iteration: 65945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11087 FastRCNN class loss: 0.08758 FastRCNN total loss: 0.19845 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.0004 Mask loss: 0.14461 RPN box loss: 0.03303 RPN score loss: 0.01136 RPN total loss: 0.0444 Total loss: 0.97974 timestamp: 1654965596.3727183 iteration: 65950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.16506 L1 loss: 0.0000e+00 L2 loss: 0.59228 Learning rate: 0.0004 Mask loss: 0.13038 RPN box loss: 0.01017 RPN score loss: 0.00624 RPN total loss: 0.01641 Total loss: 0.90413 timestamp: 1654965599.5894015 iteration: 65955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15466 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.23889 L1 loss: 0.0000e+00 L2 loss: 0.59228 Learning rate: 0.0004 Mask loss: 0.13097 RPN box loss: 0.01766 RPN score loss: 0.0074 RPN total loss: 0.02506 Total loss: 0.9872 timestamp: 1654965602.7786045 iteration: 65960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11948 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.18146 L1 loss: 0.0000e+00 L2 loss: 0.59228 Learning rate: 0.0004 Mask loss: 0.13064 RPN box loss: 0.00565 RPN score loss: 0.00374 RPN total loss: 0.00939 Total loss: 0.91377 timestamp: 1654965605.8618543 iteration: 65965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09913 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.17349 L1 loss: 0.0000e+00 L2 loss: 0.59228 Learning rate: 0.0004 Mask loss: 0.1521 RPN box loss: 0.01314 RPN score loss: 0.01267 RPN total loss: 0.02581 Total loss: 0.94367 timestamp: 1654965609.04327 iteration: 65970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06407 FastRCNN class loss: 0.03716 FastRCNN total loss: 0.10124 L1 loss: 0.0000e+00 L2 loss: 0.59228 Learning rate: 0.0004 Mask loss: 0.118 RPN box loss: 0.00762 RPN score loss: 0.00072 RPN total loss: 0.00834 Total loss: 0.81985 timestamp: 1654965612.2518942 iteration: 65975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09993 FastRCNN class loss: 0.0942 FastRCNN total loss: 0.19413 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.0004 Mask loss: 0.16813 RPN box loss: 0.01005 RPN score loss: 0.00306 RPN total loss: 0.01311 Total loss: 0.96764 timestamp: 1654965615.4100218 iteration: 65980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07527 FastRCNN class loss: 0.0433 FastRCNN total loss: 0.11857 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.0004 Mask loss: 0.15355 RPN box loss: 0.01899 RPN score loss: 0.00273 RPN total loss: 0.02172 Total loss: 0.88611 timestamp: 1654965618.5813262 iteration: 65985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09597 FastRCNN class loss: 0.06104 FastRCNN total loss: 0.15702 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.0004 Mask loss: 0.17286 RPN box loss: 0.02764 RPN score loss: 0.0048 RPN total loss: 0.03244 Total loss: 0.95459 timestamp: 1654965621.766971 iteration: 65990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10805 FastRCNN class loss: 0.08783 FastRCNN total loss: 0.19588 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.0004 Mask loss: 0.10192 RPN box loss: 0.03957 RPN score loss: 0.00297 RPN total loss: 0.04253 Total loss: 0.9326 timestamp: 1654965625.026018 iteration: 65995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03712 FastRCNN class loss: 0.0227 FastRCNN total loss: 0.05982 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.0004 Mask loss: 0.09585 RPN box loss: 0.00115 RPN score loss: 0.00407 RPN total loss: 0.00522 Total loss: 0.75316 timestamp: 1654965628.276537 iteration: 66000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05279 FastRCNN class loss: 0.044 FastRCNN total loss: 0.09678 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.0004 Mask loss: 0.12266 RPN box loss: 0.01124 RPN score loss: 0.0021 RPN total loss: 0.01333 Total loss: 0.82505 timestamp: 1654965631.427284 iteration: 66005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09845 FastRCNN class loss: 0.06004 FastRCNN total loss: 0.1585 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.08904 RPN box loss: 0.00628 RPN score loss: 0.00225 RPN total loss: 0.00852 Total loss: 0.84832 timestamp: 1654965634.5933378 iteration: 66010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08712 FastRCNN class loss: 0.11711 FastRCNN total loss: 0.20423 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.15581 RPN box loss: 0.01608 RPN score loss: 0.00677 RPN total loss: 0.02285 Total loss: 0.97515 timestamp: 1654965637.7824283 iteration: 66015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11507 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.19044 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.13464 RPN box loss: 0.00618 RPN score loss: 0.00724 RPN total loss: 0.01342 Total loss: 0.93076 timestamp: 1654965640.9524562 iteration: 66020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12611 FastRCNN class loss: 0.06338 FastRCNN total loss: 0.18948 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.14927 RPN box loss: 0.01497 RPN score loss: 0.00304 RPN total loss: 0.01801 Total loss: 0.94903 timestamp: 1654965644.098053 iteration: 66025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16803 FastRCNN class loss: 0.06893 FastRCNN total loss: 0.23696 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.09381 RPN box loss: 0.0137 RPN score loss: 0.00111 RPN total loss: 0.0148 Total loss: 0.93783 timestamp: 1654965647.3111305 iteration: 66030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05907 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.11331 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.22787 RPN box loss: 0.00801 RPN score loss: 0.0034 RPN total loss: 0.01141 Total loss: 0.94484 timestamp: 1654965650.4494274 iteration: 66035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05867 FastRCNN class loss: 0.0956 FastRCNN total loss: 0.15427 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.0004 Mask loss: 0.14065 RPN box loss: 0.02003 RPN score loss: 0.00722 RPN total loss: 0.02725 Total loss: 0.91442 timestamp: 1654965653.5911248 iteration: 66040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09928 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.16847 L1 loss: 0.0000e+00 L2 loss: 0.59225 Learning rate: 0.0004 Mask loss: 0.14707 RPN box loss: 0.00661 RPN score loss: 0.00048 RPN total loss: 0.00709 Total loss: 0.91489 timestamp: 1654965656.7817914 iteration: 66045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.07259 FastRCNN total loss: 0.16176 L1 loss: 0.0000e+00 L2 loss: 0.59225 Learning rate: 0.0004 Mask loss: 0.21422 RPN box loss: 0.0161 RPN score loss: 0.00456 RPN total loss: 0.02066 Total loss: 0.98889 timestamp: 1654965659.9712598 iteration: 66050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0713 FastRCNN class loss: 0.04355 FastRCNN total loss: 0.11485 L1 loss: 0.0000e+00 L2 loss: 0.59225 Learning rate: 0.0004 Mask loss: 0.17378 RPN box loss: 0.02881 RPN score loss: 0.00569 RPN total loss: 0.0345 Total loss: 0.91539 timestamp: 1654965663.1034179 iteration: 66055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05842 FastRCNN class loss: 0.0558 FastRCNN total loss: 0.11422 L1 loss: 0.0000e+00 L2 loss: 0.59225 Learning rate: 0.0004 Mask loss: 0.08835 RPN box loss: 0.01305 RPN score loss: 0.00432 RPN total loss: 0.01737 Total loss: 0.81219 timestamp: 1654965666.349351 iteration: 66060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08858 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.15167 L1 loss: 0.0000e+00 L2 loss: 0.59225 Learning rate: 0.0004 Mask loss: 0.14456 RPN box loss: 0.02252 RPN score loss: 0.00789 RPN total loss: 0.03041 Total loss: 0.91889 timestamp: 1654965669.5778806 iteration: 66065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08107 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.15637 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.10635 RPN box loss: 0.00953 RPN score loss: 0.0018 RPN total loss: 0.01134 Total loss: 0.86631 timestamp: 1654965672.71263 iteration: 66070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12765 FastRCNN class loss: 0.10621 FastRCNN total loss: 0.23387 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.15328 RPN box loss: 0.02162 RPN score loss: 0.00171 RPN total loss: 0.02334 Total loss: 1.00272 timestamp: 1654965675.9017382 iteration: 66075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11315 FastRCNN class loss: 0.0779 FastRCNN total loss: 0.19105 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.11937 RPN box loss: 0.00651 RPN score loss: 0.00537 RPN total loss: 0.01189 Total loss: 0.91455 timestamp: 1654965679.071861 iteration: 66080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0842 FastRCNN class loss: 0.04311 FastRCNN total loss: 0.12731 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.10219 RPN box loss: 0.00974 RPN score loss: 0.00236 RPN total loss: 0.0121 Total loss: 0.83385 timestamp: 1654965682.2101882 iteration: 66085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0414 FastRCNN class loss: 0.054 FastRCNN total loss: 0.09539 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.1099 RPN box loss: 0.00774 RPN score loss: 0.00439 RPN total loss: 0.01213 Total loss: 0.80966 timestamp: 1654965685.3485131 iteration: 66090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08002 FastRCNN class loss: 0.06216 FastRCNN total loss: 0.14218 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.12214 RPN box loss: 0.0228 RPN score loss: 0.00626 RPN total loss: 0.02906 Total loss: 0.88562 timestamp: 1654965688.5870352 iteration: 66095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10286 FastRCNN class loss: 0.06728 FastRCNN total loss: 0.17014 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.0004 Mask loss: 0.15319 RPN box loss: 0.00752 RPN score loss: 0.00196 RPN total loss: 0.00948 Total loss: 0.92505 timestamp: 1654965691.8741717 iteration: 66100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06974 FastRCNN class loss: 0.06269 FastRCNN total loss: 0.13244 L1 loss: 0.0000e+00 L2 loss: 0.59223 Learning rate: 0.0004 Mask loss: 0.14501 RPN box loss: 0.00902 RPN score loss: 0.00568 RPN total loss: 0.0147 Total loss: 0.88438 timestamp: 1654965695.0567434 iteration: 66105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07243 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.14449 L1 loss: 0.0000e+00 L2 loss: 0.59223 Learning rate: 0.0004 Mask loss: 0.15765 RPN box loss: 0.00739 RPN score loss: 0.00184 RPN total loss: 0.00923 Total loss: 0.9036 timestamp: 1654965698.2088814 iteration: 66110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09961 FastRCNN class loss: 0.04536 FastRCNN total loss: 0.14497 L1 loss: 0.0000e+00 L2 loss: 0.59223 Learning rate: 0.0004 Mask loss: 0.06356 RPN box loss: 0.00436 RPN score loss: 0.00176 RPN total loss: 0.00612 Total loss: 0.80688 timestamp: 1654965701.448746 iteration: 66115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06774 FastRCNN class loss: 0.04753 FastRCNN total loss: 0.11527 L1 loss: 0.0000e+00 L2 loss: 0.59223 Learning rate: 0.0004 Mask loss: 0.1512 RPN box loss: 0.01167 RPN score loss: 0.00353 RPN total loss: 0.0152 Total loss: 0.8739 timestamp: 1654965704.681105 iteration: 66120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13698 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.2118 L1 loss: 0.0000e+00 L2 loss: 0.59223 Learning rate: 0.0004 Mask loss: 0.11059 RPN box loss: 0.00987 RPN score loss: 0.00445 RPN total loss: 0.01432 Total loss: 0.92894 timestamp: 1654965707.8574023 iteration: 66125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07764 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.15667 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.0004 Mask loss: 0.11304 RPN box loss: 0.00574 RPN score loss: 0.004 RPN total loss: 0.00974 Total loss: 0.87167 timestamp: 1654965711.0605729 iteration: 66130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13501 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.21876 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.0004 Mask loss: 0.1433 RPN box loss: 0.0176 RPN score loss: 0.00248 RPN total loss: 0.02008 Total loss: 0.97436 timestamp: 1654965714.2553842 iteration: 66135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05984 FastRCNN class loss: 0.04858 FastRCNN total loss: 0.10842 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.0004 Mask loss: 0.11058 RPN box loss: 0.01337 RPN score loss: 0.00191 RPN total loss: 0.01527 Total loss: 0.8265 timestamp: 1654965717.4473786 iteration: 66140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07206 FastRCNN class loss: 0.0442 FastRCNN total loss: 0.11626 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.0004 Mask loss: 0.0867 RPN box loss: 0.00556 RPN score loss: 0.0015 RPN total loss: 0.00707 Total loss: 0.80224 timestamp: 1654965720.7378128 iteration: 66145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12049 FastRCNN class loss: 0.08428 FastRCNN total loss: 0.20477 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.0004 Mask loss: 0.13077 RPN box loss: 0.00663 RPN score loss: 0.0056 RPN total loss: 0.01223 Total loss: 0.93998 timestamp: 1654965723.9712389 iteration: 66150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06179 FastRCNN class loss: 0.0519 FastRCNN total loss: 0.11369 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.0004 Mask loss: 0.08747 RPN box loss: 0.01556 RPN score loss: 0.00218 RPN total loss: 0.01774 Total loss: 0.81111 timestamp: 1654965727.2169657 iteration: 66155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08769 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.16983 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.10869 RPN box loss: 0.01284 RPN score loss: 0.00221 RPN total loss: 0.01504 Total loss: 0.88578 timestamp: 1654965730.3677342 iteration: 66160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11092 FastRCNN class loss: 0.05272 FastRCNN total loss: 0.16364 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.08745 RPN box loss: 0.00354 RPN score loss: 0.00161 RPN total loss: 0.00515 Total loss: 0.84845 timestamp: 1654965733.4870384 iteration: 66165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09256 FastRCNN class loss: 0.06421 FastRCNN total loss: 0.15676 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.147 RPN box loss: 0.01662 RPN score loss: 0.00367 RPN total loss: 0.02029 Total loss: 0.91627 timestamp: 1654965736.7264147 iteration: 66170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1406 FastRCNN class loss: 0.11931 FastRCNN total loss: 0.25991 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.12356 RPN box loss: 0.00881 RPN score loss: 0.0049 RPN total loss: 0.01371 Total loss: 0.9894 timestamp: 1654965739.9394238 iteration: 66175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09657 FastRCNN class loss: 0.07492 FastRCNN total loss: 0.17148 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.16946 RPN box loss: 0.0147 RPN score loss: 0.00465 RPN total loss: 0.01935 Total loss: 0.95249 timestamp: 1654965743.0682092 iteration: 66180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07566 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.13105 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.08425 RPN box loss: 0.00506 RPN score loss: 0.00831 RPN total loss: 0.01337 Total loss: 0.82088 timestamp: 1654965746.2981343 iteration: 66185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10024 FastRCNN class loss: 0.10674 FastRCNN total loss: 0.20698 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.0004 Mask loss: 0.17199 RPN box loss: 0.02771 RPN score loss: 0.00559 RPN total loss: 0.0333 Total loss: 1.00447 timestamp: 1654965749.4696555 iteration: 66190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06451 FastRCNN class loss: 0.05246 FastRCNN total loss: 0.11697 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.0004 Mask loss: 0.16741 RPN box loss: 0.01404 RPN score loss: 0.00372 RPN total loss: 0.01776 Total loss: 0.89435 timestamp: 1654965752.652806 iteration: 66195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10102 FastRCNN class loss: 0.05607 FastRCNN total loss: 0.15709 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.0004 Mask loss: 0.13077 RPN box loss: 0.00661 RPN score loss: 0.00463 RPN total loss: 0.01124 Total loss: 0.8913 timestamp: 1654965755.9457395 iteration: 66200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04007 FastRCNN class loss: 0.03699 FastRCNN total loss: 0.07706 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.0004 Mask loss: 0.08369 RPN box loss: 0.00483 RPN score loss: 0.00176 RPN total loss: 0.00659 Total loss: 0.75953 timestamp: 1654965759.2003174 iteration: 66205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0638 FastRCNN class loss: 0.05534 FastRCNN total loss: 0.11914 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.0004 Mask loss: 0.1119 RPN box loss: 0.00573 RPN score loss: 0.00607 RPN total loss: 0.0118 Total loss: 0.83504 timestamp: 1654965762.4474022 iteration: 66210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0636 FastRCNN class loss: 0.06176 FastRCNN total loss: 0.12536 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.0004 Mask loss: 0.1169 RPN box loss: 0.01071 RPN score loss: 0.00327 RPN total loss: 0.01398 Total loss: 0.84844 timestamp: 1654965765.6428716 iteration: 66215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10312 FastRCNN class loss: 0.05602 FastRCNN total loss: 0.15914 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.13374 RPN box loss: 0.02576 RPN score loss: 0.00367 RPN total loss: 0.02943 Total loss: 0.9145 timestamp: 1654965768.8303404 iteration: 66220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06442 FastRCNN class loss: 0.0769 FastRCNN total loss: 0.14133 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.15692 RPN box loss: 0.0092 RPN score loss: 0.00347 RPN total loss: 0.01268 Total loss: 0.90311 timestamp: 1654965771.9890552 iteration: 66225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08692 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.14465 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.11589 RPN box loss: 0.00726 RPN score loss: 0.00516 RPN total loss: 0.01242 Total loss: 0.86515 timestamp: 1654965775.218531 iteration: 66230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.0821 FastRCNN total loss: 0.20397 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.11867 RPN box loss: 0.0283 RPN score loss: 0.00654 RPN total loss: 0.03484 Total loss: 0.94967 timestamp: 1654965778.3996031 iteration: 66235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06544 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.14041 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.14667 RPN box loss: 0.00676 RPN score loss: 0.00353 RPN total loss: 0.0103 Total loss: 0.88957 timestamp: 1654965781.6266677 iteration: 66240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.16662 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.12091 RPN box loss: 0.01537 RPN score loss: 0.00467 RPN total loss: 0.02004 Total loss: 0.89975 timestamp: 1654965784.8628178 iteration: 66245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10665 FastRCNN class loss: 0.04168 FastRCNN total loss: 0.14833 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.10205 RPN box loss: 0.00263 RPN score loss: 0.00164 RPN total loss: 0.00427 Total loss: 0.84684 timestamp: 1654965788.097443 iteration: 66250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07164 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.11986 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.0004 Mask loss: 0.13341 RPN box loss: 0.00839 RPN score loss: 0.0021 RPN total loss: 0.01049 Total loss: 0.85594 timestamp: 1654965791.2376125 iteration: 66255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09915 FastRCNN class loss: 0.04132 FastRCNN total loss: 0.14047 L1 loss: 0.0000e+00 L2 loss: 0.59218 Learning rate: 0.0004 Mask loss: 0.0945 RPN box loss: 0.00461 RPN score loss: 0.00775 RPN total loss: 0.01236 Total loss: 0.83951 timestamp: 1654965794.506878 iteration: 66260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09655 FastRCNN class loss: 0.11734 FastRCNN total loss: 0.2139 L1 loss: 0.0000e+00 L2 loss: 0.59218 Learning rate: 0.0004 Mask loss: 0.14596 RPN box loss: 0.02318 RPN score loss: 0.00083 RPN total loss: 0.02402 Total loss: 0.97605 timestamp: 1654965797.720268 iteration: 66265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.15219 L1 loss: 0.0000e+00 L2 loss: 0.59218 Learning rate: 0.0004 Mask loss: 0.14352 RPN box loss: 0.00843 RPN score loss: 0.00546 RPN total loss: 0.01389 Total loss: 0.90178 timestamp: 1654965800.9150262 iteration: 66270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08484 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.13528 L1 loss: 0.0000e+00 L2 loss: 0.59218 Learning rate: 0.0004 Mask loss: 0.15287 RPN box loss: 0.0068 RPN score loss: 0.00554 RPN total loss: 0.01234 Total loss: 0.89268 timestamp: 1654965804.0674572 iteration: 66275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09321 FastRCNN class loss: 0.05485 FastRCNN total loss: 0.14806 L1 loss: 0.0000e+00 L2 loss: 0.59218 Learning rate: 0.0004 Mask loss: 0.10003 RPN box loss: 0.01368 RPN score loss: 0.00075 RPN total loss: 0.01443 Total loss: 0.8547 timestamp: 1654965807.292448 iteration: 66280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06529 FastRCNN class loss: 0.04131 FastRCNN total loss: 0.1066 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.0004 Mask loss: 0.11131 RPN box loss: 0.00358 RPN score loss: 0.00175 RPN total loss: 0.00533 Total loss: 0.81541 timestamp: 1654965810.596874 iteration: 66285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08626 FastRCNN class loss: 0.07386 FastRCNN total loss: 0.16012 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.0004 Mask loss: 0.10686 RPN box loss: 0.01221 RPN score loss: 0.01204 RPN total loss: 0.02425 Total loss: 0.8834 timestamp: 1654965813.699956 iteration: 66290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07501 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.13133 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.0004 Mask loss: 0.14533 RPN box loss: 0.02268 RPN score loss: 0.00637 RPN total loss: 0.02906 Total loss: 0.89788 timestamp: 1654965816.905173 iteration: 66295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11523 FastRCNN class loss: 0.06627 FastRCNN total loss: 0.1815 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.0004 Mask loss: 0.11993 RPN box loss: 0.0204 RPN score loss: 0.00774 RPN total loss: 0.02814 Total loss: 0.92174 timestamp: 1654965820.0948951 iteration: 66300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09161 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.15567 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.0004 Mask loss: 0.13963 RPN box loss: 0.01364 RPN score loss: 0.00241 RPN total loss: 0.01605 Total loss: 0.90352 timestamp: 1654965823.2111814 iteration: 66305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08342 FastRCNN class loss: 0.11064 FastRCNN total loss: 0.19406 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.0004 Mask loss: 0.1624 RPN box loss: 0.01118 RPN score loss: 0.00429 RPN total loss: 0.01547 Total loss: 0.96409 timestamp: 1654965826.412918 iteration: 66310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07561 FastRCNN class loss: 0.0672 FastRCNN total loss: 0.14281 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.20939 RPN box loss: 0.02031 RPN score loss: 0.00622 RPN total loss: 0.02653 Total loss: 0.97089 timestamp: 1654965829.6041765 iteration: 66315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07594 FastRCNN class loss: 0.062 FastRCNN total loss: 0.13793 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.12369 RPN box loss: 0.00916 RPN score loss: 0.00235 RPN total loss: 0.01151 Total loss: 0.8653 timestamp: 1654965832.7769303 iteration: 66320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09195 FastRCNN class loss: 0.09676 FastRCNN total loss: 0.18871 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.12625 RPN box loss: 0.01355 RPN score loss: 0.00258 RPN total loss: 0.01613 Total loss: 0.92326 timestamp: 1654965836.0571036 iteration: 66325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08971 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.14005 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.1071 RPN box loss: 0.0077 RPN score loss: 0.00777 RPN total loss: 0.01547 Total loss: 0.85478 timestamp: 1654965839.2282953 iteration: 66330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15346 FastRCNN class loss: 0.0767 FastRCNN total loss: 0.23016 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.14111 RPN box loss: 0.03325 RPN score loss: 0.00351 RPN total loss: 0.03676 Total loss: 1.00019 timestamp: 1654965842.4056518 iteration: 66335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09471 FastRCNN class loss: 0.07614 FastRCNN total loss: 0.17086 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.15364 RPN box loss: 0.03396 RPN score loss: 0.01005 RPN total loss: 0.044 Total loss: 0.96066 timestamp: 1654965845.5953372 iteration: 66340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0516 FastRCNN class loss: 0.042 FastRCNN total loss: 0.0936 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.0004 Mask loss: 0.10086 RPN box loss: 0.00449 RPN score loss: 0.00343 RPN total loss: 0.00792 Total loss: 0.79454 timestamp: 1654965848.774685 iteration: 66345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12081 FastRCNN class loss: 0.0749 FastRCNN total loss: 0.19571 L1 loss: 0.0000e+00 L2 loss: 0.59215 Learning rate: 0.0004 Mask loss: 0.16331 RPN box loss: 0.01667 RPN score loss: 0.00242 RPN total loss: 0.01908 Total loss: 0.97026 timestamp: 1654965851.9400792 iteration: 66350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07971 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.1565 L1 loss: 0.0000e+00 L2 loss: 0.59215 Learning rate: 0.0004 Mask loss: 0.10929 RPN box loss: 0.02701 RPN score loss: 0.00398 RPN total loss: 0.03098 Total loss: 0.88892 timestamp: 1654965855.0798934 iteration: 66355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11476 FastRCNN class loss: 0.10593 FastRCNN total loss: 0.2207 L1 loss: 0.0000e+00 L2 loss: 0.59215 Learning rate: 0.0004 Mask loss: 0.13516 RPN box loss: 0.02235 RPN score loss: 0.01147 RPN total loss: 0.03382 Total loss: 0.98183 timestamp: 1654965858.2834306 iteration: 66360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16056 FastRCNN class loss: 0.06775 FastRCNN total loss: 0.22831 L1 loss: 0.0000e+00 L2 loss: 0.59215 Learning rate: 0.0004 Mask loss: 0.12877 RPN box loss: 0.00833 RPN score loss: 0.00506 RPN total loss: 0.01339 Total loss: 0.96262 timestamp: 1654965861.448732 iteration: 66365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13564 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.20721 L1 loss: 0.0000e+00 L2 loss: 0.59215 Learning rate: 0.0004 Mask loss: 0.1471 RPN box loss: 0.01301 RPN score loss: 0.00735 RPN total loss: 0.02036 Total loss: 0.96681 timestamp: 1654965864.7335646 iteration: 66370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07298 FastRCNN class loss: 0.0603 FastRCNN total loss: 0.13328 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.11865 RPN box loss: 0.00367 RPN score loss: 0.00103 RPN total loss: 0.00471 Total loss: 0.84878 timestamp: 1654965867.907062 iteration: 66375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05844 FastRCNN class loss: 0.04853 FastRCNN total loss: 0.10697 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.08737 RPN box loss: 0.00493 RPN score loss: 0.00104 RPN total loss: 0.00597 Total loss: 0.79245 timestamp: 1654965871.0829926 iteration: 66380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10984 FastRCNN class loss: 0.0604 FastRCNN total loss: 0.17024 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.10441 RPN box loss: 0.013 RPN score loss: 0.00228 RPN total loss: 0.01528 Total loss: 0.88207 timestamp: 1654965874.3312438 iteration: 66385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0715 FastRCNN class loss: 0.05189 FastRCNN total loss: 0.12339 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.16516 RPN box loss: 0.00836 RPN score loss: 0.00626 RPN total loss: 0.01462 Total loss: 0.89531 timestamp: 1654965877.5446758 iteration: 66390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05173 FastRCNN class loss: 0.0435 FastRCNN total loss: 0.09523 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.14568 RPN box loss: 0.00571 RPN score loss: 0.00275 RPN total loss: 0.00847 Total loss: 0.84152 timestamp: 1654965880.759475 iteration: 66395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06325 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.14305 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.12983 RPN box loss: 0.00468 RPN score loss: 0.01469 RPN total loss: 0.01937 Total loss: 0.88439 timestamp: 1654965883.9618845 iteration: 66400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09461 FastRCNN class loss: 0.06486 FastRCNN total loss: 0.15948 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.0004 Mask loss: 0.12198 RPN box loss: 0.00746 RPN score loss: 0.00093 RPN total loss: 0.00839 Total loss: 0.88198 timestamp: 1654965887.166702 iteration: 66405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07661 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.15109 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.0004 Mask loss: 0.1415 RPN box loss: 0.01209 RPN score loss: 0.00765 RPN total loss: 0.01974 Total loss: 0.90446 timestamp: 1654965890.3984885 iteration: 66410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06307 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.11892 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.0004 Mask loss: 0.1173 RPN box loss: 0.01427 RPN score loss: 0.00443 RPN total loss: 0.0187 Total loss: 0.84706 timestamp: 1654965893.6242256 iteration: 66415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08633 FastRCNN class loss: 0.07901 FastRCNN total loss: 0.16534 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.0004 Mask loss: 0.16205 RPN box loss: 0.00987 RPN score loss: 0.00408 RPN total loss: 0.01395 Total loss: 0.93347 timestamp: 1654965896.8354783 iteration: 66420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08094 FastRCNN class loss: 0.05542 FastRCNN total loss: 0.13637 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.0004 Mask loss: 0.12097 RPN box loss: 0.00579 RPN score loss: 0.00261 RPN total loss: 0.0084 Total loss: 0.85786 timestamp: 1654965900.0222597 iteration: 66425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11056 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.19288 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.0004 Mask loss: 0.17448 RPN box loss: 0.01308 RPN score loss: 0.00242 RPN total loss: 0.01549 Total loss: 0.97499 timestamp: 1654965903.3230639 iteration: 66430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09237 FastRCNN class loss: 0.06873 FastRCNN total loss: 0.1611 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.0004 Mask loss: 0.11581 RPN box loss: 0.0081 RPN score loss: 0.00145 RPN total loss: 0.00955 Total loss: 0.87858 timestamp: 1654965906.482068 iteration: 66435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11036 FastRCNN class loss: 0.08584 FastRCNN total loss: 0.1962 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.0004 Mask loss: 0.1716 RPN box loss: 0.0135 RPN score loss: 0.00499 RPN total loss: 0.01849 Total loss: 0.97842 timestamp: 1654965909.6972396 iteration: 66440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07229 FastRCNN class loss: 0.05891 FastRCNN total loss: 0.1312 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.0004 Mask loss: 0.12982 RPN box loss: 0.0078 RPN score loss: 0.00316 RPN total loss: 0.01096 Total loss: 0.8641 timestamp: 1654965912.8913968 iteration: 66445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11087 FastRCNN class loss: 0.06373 FastRCNN total loss: 0.17461 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.0004 Mask loss: 0.12327 RPN box loss: 0.01194 RPN score loss: 0.00157 RPN total loss: 0.01351 Total loss: 0.9035 timestamp: 1654965916.0541744 iteration: 66450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07552 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.15902 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.0004 Mask loss: 0.14849 RPN box loss: 0.00962 RPN score loss: 0.00519 RPN total loss: 0.0148 Total loss: 0.91444 timestamp: 1654965919.2898014 iteration: 66455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06427 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.1246 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.0004 Mask loss: 0.13814 RPN box loss: 0.00659 RPN score loss: 0.00306 RPN total loss: 0.00964 Total loss: 0.8645 timestamp: 1654965922.5735743 iteration: 66460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1418 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.21797 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.0004 Mask loss: 0.12383 RPN box loss: 0.0166 RPN score loss: 0.0085 RPN total loss: 0.0251 Total loss: 0.95902 timestamp: 1654965925.7267435 iteration: 66465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15479 FastRCNN class loss: 0.06106 FastRCNN total loss: 0.21585 L1 loss: 0.0000e+00 L2 loss: 0.59211 Learning rate: 0.0004 Mask loss: 0.13409 RPN box loss: 0.02188 RPN score loss: 0.00514 RPN total loss: 0.02702 Total loss: 0.96908 timestamp: 1654965928.879946 iteration: 66470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09114 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.1555 L1 loss: 0.0000e+00 L2 loss: 0.59211 Learning rate: 0.0004 Mask loss: 0.15465 RPN box loss: 0.00525 RPN score loss: 0.00099 RPN total loss: 0.00624 Total loss: 0.90851 timestamp: 1654965932.1561623 iteration: 66475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05717 FastRCNN class loss: 0.05069 FastRCNN total loss: 0.10785 L1 loss: 0.0000e+00 L2 loss: 0.59211 Learning rate: 0.0004 Mask loss: 0.09761 RPN box loss: 0.00874 RPN score loss: 0.00387 RPN total loss: 0.01261 Total loss: 0.81018 timestamp: 1654965935.290582 iteration: 66480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09831 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.17123 L1 loss: 0.0000e+00 L2 loss: 0.59211 Learning rate: 0.0004 Mask loss: 0.09099 RPN box loss: 0.00375 RPN score loss: 0.00131 RPN total loss: 0.00505 Total loss: 0.85938 timestamp: 1654965938.5004358 iteration: 66485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07436 FastRCNN class loss: 0.05138 FastRCNN total loss: 0.12574 L1 loss: 0.0000e+00 L2 loss: 0.59211 Learning rate: 0.0004 Mask loss: 0.12119 RPN box loss: 0.00677 RPN score loss: 0.00581 RPN total loss: 0.01258 Total loss: 0.85161 timestamp: 1654965941.7387114 iteration: 66490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10384 FastRCNN class loss: 0.0846 FastRCNN total loss: 0.18844 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.0004 Mask loss: 0.15797 RPN box loss: 0.02833 RPN score loss: 0.0104 RPN total loss: 0.03873 Total loss: 0.97725 timestamp: 1654965944.8388782 iteration: 66495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.05895 FastRCNN total loss: 0.19124 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.0004 Mask loss: 0.12924 RPN box loss: 0.00795 RPN score loss: 0.00248 RPN total loss: 0.01043 Total loss: 0.92301 timestamp: 1654965948.059604 iteration: 66500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07406 FastRCNN class loss: 0.05298 FastRCNN total loss: 0.12705 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.0004 Mask loss: 0.12865 RPN box loss: 0.00364 RPN score loss: 0.00354 RPN total loss: 0.00718 Total loss: 0.85498 timestamp: 1654965951.2639809 iteration: 66505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.057 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.11433 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.0004 Mask loss: 0.13926 RPN box loss: 0.01933 RPN score loss: 0.00209 RPN total loss: 0.02142 Total loss: 0.86711 timestamp: 1654965954.4577112 iteration: 66510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13686 FastRCNN class loss: 0.08304 FastRCNN total loss: 0.21989 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.0004 Mask loss: 0.10709 RPN box loss: 0.00939 RPN score loss: 0.00972 RPN total loss: 0.01911 Total loss: 0.93819 timestamp: 1654965957.6293461 iteration: 66515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.072 FastRCNN total loss: 0.19087 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.0004 Mask loss: 0.1372 RPN box loss: 0.00896 RPN score loss: 0.00126 RPN total loss: 0.01022 Total loss: 0.93039 timestamp: 1654965960.7920463 iteration: 66520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09599 FastRCNN class loss: 0.06938 FastRCNN total loss: 0.16537 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.1536 RPN box loss: 0.00522 RPN score loss: 0.00168 RPN total loss: 0.0069 Total loss: 0.91796 timestamp: 1654965963.9735756 iteration: 66525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1113 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.18441 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.14778 RPN box loss: 0.01442 RPN score loss: 0.00355 RPN total loss: 0.01796 Total loss: 0.94224 timestamp: 1654965967.161203 iteration: 66530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.084 FastRCNN class loss: 0.08197 FastRCNN total loss: 0.16597 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.10804 RPN box loss: 0.01086 RPN score loss: 0.00374 RPN total loss: 0.01459 Total loss: 0.88069 timestamp: 1654965970.418067 iteration: 66535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07791 FastRCNN class loss: 0.08753 FastRCNN total loss: 0.16543 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.16667 RPN box loss: 0.00985 RPN score loss: 0.00324 RPN total loss: 0.01309 Total loss: 0.93729 timestamp: 1654965973.6854687 iteration: 66540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.20152 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.16929 RPN box loss: 0.00876 RPN score loss: 0.00382 RPN total loss: 0.01258 Total loss: 0.97548 timestamp: 1654965976.8520162 iteration: 66545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15009 FastRCNN class loss: 0.1243 FastRCNN total loss: 0.27439 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.20364 RPN box loss: 0.0392 RPN score loss: 0.03419 RPN total loss: 0.07339 Total loss: 1.14351 timestamp: 1654965980.1181834 iteration: 66550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06736 FastRCNN class loss: 0.03262 FastRCNN total loss: 0.09998 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.0004 Mask loss: 0.11194 RPN box loss: 0.00894 RPN score loss: 0.00373 RPN total loss: 0.01267 Total loss: 0.81667 timestamp: 1654965983.3757339 iteration: 66555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04656 FastRCNN class loss: 0.03541 FastRCNN total loss: 0.08197 L1 loss: 0.0000e+00 L2 loss: 0.59208 Learning rate: 0.0004 Mask loss: 0.11645 RPN box loss: 0.00368 RPN score loss: 0.00165 RPN total loss: 0.00532 Total loss: 0.79583 timestamp: 1654965986.5513718 iteration: 66560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07317 FastRCNN class loss: 0.04509 FastRCNN total loss: 0.11827 L1 loss: 0.0000e+00 L2 loss: 0.59208 Learning rate: 0.0004 Mask loss: 0.13716 RPN box loss: 0.01595 RPN score loss: 0.00191 RPN total loss: 0.01785 Total loss: 0.86536 timestamp: 1654965989.742454 iteration: 66565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06719 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.12042 L1 loss: 0.0000e+00 L2 loss: 0.59208 Learning rate: 0.0004 Mask loss: 0.12423 RPN box loss: 0.00727 RPN score loss: 0.00121 RPN total loss: 0.00848 Total loss: 0.84522 timestamp: 1654965992.9247494 iteration: 66570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04831 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.10594 L1 loss: 0.0000e+00 L2 loss: 0.59208 Learning rate: 0.0004 Mask loss: 0.09073 RPN box loss: 0.00573 RPN score loss: 0.00348 RPN total loss: 0.00921 Total loss: 0.79795 timestamp: 1654965996.018728 iteration: 66575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04427 FastRCNN class loss: 0.04014 FastRCNN total loss: 0.08441 L1 loss: 0.0000e+00 L2 loss: 0.59208 Learning rate: 0.0004 Mask loss: 0.10393 RPN box loss: 0.00536 RPN score loss: 0.00089 RPN total loss: 0.00625 Total loss: 0.78666 timestamp: 1654965999.272733 iteration: 66580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0554 FastRCNN class loss: 0.03366 FastRCNN total loss: 0.08906 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.10396 RPN box loss: 0.0023 RPN score loss: 0.00182 RPN total loss: 0.00412 Total loss: 0.78922 timestamp: 1654966002.5053601 iteration: 66585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07303 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.15558 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.12941 RPN box loss: 0.00811 RPN score loss: 0.00661 RPN total loss: 0.01472 Total loss: 0.89179 timestamp: 1654966005.703756 iteration: 66590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0694 FastRCNN class loss: 0.05426 FastRCNN total loss: 0.12366 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.14144 RPN box loss: 0.0083 RPN score loss: 0.00189 RPN total loss: 0.01019 Total loss: 0.86736 timestamp: 1654966008.8631604 iteration: 66595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12788 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.19785 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.14628 RPN box loss: 0.01368 RPN score loss: 0.00364 RPN total loss: 0.01732 Total loss: 0.95352 timestamp: 1654966012.1224542 iteration: 66600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09392 FastRCNN class loss: 0.07331 FastRCNN total loss: 0.16722 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.13126 RPN box loss: 0.02369 RPN score loss: 0.00835 RPN total loss: 0.03204 Total loss: 0.92259 timestamp: 1654966015.2729418 iteration: 66605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04617 FastRCNN class loss: 0.04679 FastRCNN total loss: 0.09296 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.08977 RPN box loss: 0.009 RPN score loss: 0.00317 RPN total loss: 0.01216 Total loss: 0.78696 timestamp: 1654966018.4210005 iteration: 66610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10366 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.17883 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.0004 Mask loss: 0.10742 RPN box loss: 0.01835 RPN score loss: 0.00259 RPN total loss: 0.02094 Total loss: 0.89925 timestamp: 1654966021.578852 iteration: 66615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06872 FastRCNN class loss: 0.08624 FastRCNN total loss: 0.15496 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.0004 Mask loss: 0.16181 RPN box loss: 0.01091 RPN score loss: 0.00739 RPN total loss: 0.0183 Total loss: 0.92714 timestamp: 1654966024.8067665 iteration: 66620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10158 FastRCNN class loss: 0.06053 FastRCNN total loss: 0.16211 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.0004 Mask loss: 0.09766 RPN box loss: 0.0081 RPN score loss: 0.00395 RPN total loss: 0.01205 Total loss: 0.86389 timestamp: 1654966028.0255194 iteration: 66625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.15315 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.0004 Mask loss: 0.14743 RPN box loss: 0.02006 RPN score loss: 0.00723 RPN total loss: 0.02729 Total loss: 0.91993 timestamp: 1654966031.2112522 iteration: 66630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05852 FastRCNN class loss: 0.04319 FastRCNN total loss: 0.10172 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.0004 Mask loss: 0.16702 RPN box loss: 0.0063 RPN score loss: 0.00144 RPN total loss: 0.00774 Total loss: 0.86854 timestamp: 1654966034.4113948 iteration: 66635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08616 FastRCNN class loss: 0.0433 FastRCNN total loss: 0.12945 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.0004 Mask loss: 0.08303 RPN box loss: 0.01329 RPN score loss: 0.00749 RPN total loss: 0.02077 Total loss: 0.82531 timestamp: 1654966037.5958717 iteration: 66640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11139 FastRCNN class loss: 0.08347 FastRCNN total loss: 0.19487 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.0004 Mask loss: 0.17146 RPN box loss: 0.01436 RPN score loss: 0.01073 RPN total loss: 0.02509 Total loss: 0.98348 timestamp: 1654966040.7599328 iteration: 66645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.09565 FastRCNN total loss: 0.20622 L1 loss: 0.0000e+00 L2 loss: 0.59205 Learning rate: 0.0004 Mask loss: 0.15524 RPN box loss: 0.02531 RPN score loss: 0.00934 RPN total loss: 0.03465 Total loss: 0.98817 timestamp: 1654966043.967724 iteration: 66650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13973 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.20166 L1 loss: 0.0000e+00 L2 loss: 0.59205 Learning rate: 0.0004 Mask loss: 0.12482 RPN box loss: 0.03974 RPN score loss: 0.01253 RPN total loss: 0.05228 Total loss: 0.97081 timestamp: 1654966047.1887589 iteration: 66655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08346 FastRCNN class loss: 0.05961 FastRCNN total loss: 0.14307 L1 loss: 0.0000e+00 L2 loss: 0.59205 Learning rate: 0.0004 Mask loss: 0.10278 RPN box loss: 0.00539 RPN score loss: 0.00414 RPN total loss: 0.00953 Total loss: 0.84742 timestamp: 1654966050.3647301 iteration: 66660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09469 FastRCNN class loss: 0.0494 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.59205 Learning rate: 0.0004 Mask loss: 0.10145 RPN box loss: 0.01196 RPN score loss: 0.00254 RPN total loss: 0.0145 Total loss: 0.85208 timestamp: 1654966053.5805588 iteration: 66665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06469 FastRCNN class loss: 0.05535 FastRCNN total loss: 0.12004 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.0004 Mask loss: 0.12791 RPN box loss: 0.00462 RPN score loss: 0.00074 RPN total loss: 0.00536 Total loss: 0.84535 timestamp: 1654966056.7356324 iteration: 66670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07862 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.14668 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.0004 Mask loss: 0.12103 RPN box loss: 0.00427 RPN score loss: 0.00158 RPN total loss: 0.00585 Total loss: 0.86561 timestamp: 1654966059.902293 iteration: 66675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.09064 FastRCNN total loss: 0.2003 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.0004 Mask loss: 0.14065 RPN box loss: 0.00779 RPN score loss: 0.00082 RPN total loss: 0.00861 Total loss: 0.94159 timestamp: 1654966063.0440776 iteration: 66680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06402 FastRCNN class loss: 0.04393 FastRCNN total loss: 0.10795 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.0004 Mask loss: 0.1216 RPN box loss: 0.00689 RPN score loss: 0.00502 RPN total loss: 0.01191 Total loss: 0.8335 timestamp: 1654966066.244627 iteration: 66685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09658 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.16094 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.0004 Mask loss: 0.15505 RPN box loss: 0.02311 RPN score loss: 0.00259 RPN total loss: 0.0257 Total loss: 0.93373 timestamp: 1654966069.4151106 iteration: 66690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13141 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.22406 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.0004 Mask loss: 0.11501 RPN box loss: 0.00979 RPN score loss: 0.0084 RPN total loss: 0.0182 Total loss: 0.94931 timestamp: 1654966072.5643766 iteration: 66695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10931 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.17996 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.19496 RPN box loss: 0.01165 RPN score loss: 0.00283 RPN total loss: 0.01448 Total loss: 0.98144 timestamp: 1654966075.7648914 iteration: 66700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05634 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.12082 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.15618 RPN box loss: 0.01097 RPN score loss: 0.00159 RPN total loss: 0.01256 Total loss: 0.8816 timestamp: 1654966079.0093737 iteration: 66705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07582 FastRCNN class loss: 0.07281 FastRCNN total loss: 0.14863 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.10294 RPN box loss: 0.00633 RPN score loss: 0.00307 RPN total loss: 0.0094 Total loss: 0.853 timestamp: 1654966082.2076678 iteration: 66710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07063 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.13469 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.16248 RPN box loss: 0.01641 RPN score loss: 0.00814 RPN total loss: 0.02454 Total loss: 0.91375 timestamp: 1654966085.3274302 iteration: 66715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07182 FastRCNN class loss: 0.06006 FastRCNN total loss: 0.13188 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.14586 RPN box loss: 0.01925 RPN score loss: 0.00552 RPN total loss: 0.02476 Total loss: 0.89453 timestamp: 1654966088.542456 iteration: 66720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06682 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.13899 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.11295 RPN box loss: 0.00924 RPN score loss: 0.00438 RPN total loss: 0.01362 Total loss: 0.85759 timestamp: 1654966091.7454283 iteration: 66725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10192 FastRCNN class loss: 0.08823 FastRCNN total loss: 0.19015 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.0004 Mask loss: 0.12779 RPN box loss: 0.01004 RPN score loss: 0.00422 RPN total loss: 0.01426 Total loss: 0.92422 timestamp: 1654966094.8548822 iteration: 66730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10844 FastRCNN class loss: 0.07615 FastRCNN total loss: 0.18459 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.0004 Mask loss: 0.19124 RPN box loss: 0.01771 RPN score loss: 0.00674 RPN total loss: 0.02445 Total loss: 0.9923 timestamp: 1654966098.0729403 iteration: 66735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05067 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.10124 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.0004 Mask loss: 0.06765 RPN box loss: 0.00912 RPN score loss: 0.0039 RPN total loss: 0.01301 Total loss: 0.77393 timestamp: 1654966101.2824953 iteration: 66740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05466 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.11337 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.0004 Mask loss: 0.16782 RPN box loss: 0.02134 RPN score loss: 0.00148 RPN total loss: 0.02282 Total loss: 0.89603 timestamp: 1654966104.495597 iteration: 66745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08099 FastRCNN class loss: 0.03522 FastRCNN total loss: 0.11621 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.0004 Mask loss: 0.08027 RPN box loss: 0.02126 RPN score loss: 0.00202 RPN total loss: 0.02328 Total loss: 0.81178 timestamp: 1654966107.732621 iteration: 66750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.10555 FastRCNN total loss: 0.24512 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.0004 Mask loss: 0.12752 RPN box loss: 0.00856 RPN score loss: 0.00301 RPN total loss: 0.01157 Total loss: 0.97623 timestamp: 1654966110.8739479 iteration: 66755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08682 FastRCNN class loss: 0.11674 FastRCNN total loss: 0.20356 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.0004 Mask loss: 0.13614 RPN box loss: 0.01545 RPN score loss: 0.00334 RPN total loss: 0.01878 Total loss: 0.95049 timestamp: 1654966114.0859785 iteration: 66760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07843 FastRCNN class loss: 0.03122 FastRCNN total loss: 0.10965 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.0004 Mask loss: 0.08544 RPN box loss: 0.02599 RPN score loss: 0.00164 RPN total loss: 0.02763 Total loss: 0.81474 timestamp: 1654966117.2208817 iteration: 66765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09958 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.17143 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.0004 Mask loss: 0.14224 RPN box loss: 0.01641 RPN score loss: 0.00468 RPN total loss: 0.02109 Total loss: 0.92677 timestamp: 1654966120.4002852 iteration: 66770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.088 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.0004 Mask loss: 0.13796 RPN box loss: 0.01463 RPN score loss: 0.00492 RPN total loss: 0.01955 Total loss: 0.90992 timestamp: 1654966123.5579994 iteration: 66775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07147 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.16105 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.0004 Mask loss: 0.1433 RPN box loss: 0.00976 RPN score loss: 0.00438 RPN total loss: 0.01414 Total loss: 0.9105 timestamp: 1654966126.7609942 iteration: 66780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05335 FastRCNN class loss: 0.04676 FastRCNN total loss: 0.10011 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.0004 Mask loss: 0.23409 RPN box loss: 0.00539 RPN score loss: 0.00307 RPN total loss: 0.00846 Total loss: 0.93466 timestamp: 1654966129.9706516 iteration: 66785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06991 FastRCNN class loss: 0.08621 FastRCNN total loss: 0.15612 L1 loss: 0.0000e+00 L2 loss: 0.592 Learning rate: 0.0004 Mask loss: 0.0869 RPN box loss: 0.01058 RPN score loss: 0.0017 RPN total loss: 0.01228 Total loss: 0.84731 timestamp: 1654966133.1851306 iteration: 66790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09538 FastRCNN class loss: 0.05375 FastRCNN total loss: 0.14913 L1 loss: 0.0000e+00 L2 loss: 0.592 Learning rate: 0.0004 Mask loss: 0.10945 RPN box loss: 0.00693 RPN score loss: 0.00721 RPN total loss: 0.01414 Total loss: 0.86473 timestamp: 1654966136.4125607 iteration: 66795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09831 FastRCNN class loss: 0.07652 FastRCNN total loss: 0.17484 L1 loss: 0.0000e+00 L2 loss: 0.592 Learning rate: 0.0004 Mask loss: 0.12155 RPN box loss: 0.00925 RPN score loss: 0.00621 RPN total loss: 0.01545 Total loss: 0.90384 timestamp: 1654966139.6175556 iteration: 66800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05275 FastRCNN class loss: 0.04908 FastRCNN total loss: 0.10182 L1 loss: 0.0000e+00 L2 loss: 0.592 Learning rate: 0.0004 Mask loss: 0.13633 RPN box loss: 0.00719 RPN score loss: 0.00459 RPN total loss: 0.01178 Total loss: 0.84193 timestamp: 1654966142.896841 iteration: 66805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10102 FastRCNN class loss: 0.06261 FastRCNN total loss: 0.16363 L1 loss: 0.0000e+00 L2 loss: 0.592 Learning rate: 0.0004 Mask loss: 0.11963 RPN box loss: 0.00878 RPN score loss: 0.00209 RPN total loss: 0.01087 Total loss: 0.88613 timestamp: 1654966146.1230688 iteration: 66810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03923 FastRCNN class loss: 0.04299 FastRCNN total loss: 0.08221 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.11804 RPN box loss: 0.02381 RPN score loss: 0.00106 RPN total loss: 0.02486 Total loss: 0.81711 timestamp: 1654966149.3461936 iteration: 66815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06254 FastRCNN class loss: 0.07654 FastRCNN total loss: 0.13907 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.15368 RPN box loss: 0.01156 RPN score loss: 0.00324 RPN total loss: 0.0148 Total loss: 0.89955 timestamp: 1654966152.6028426 iteration: 66820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10204 FastRCNN class loss: 0.05026 FastRCNN total loss: 0.1523 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.09308 RPN box loss: 0.00388 RPN score loss: 0.00337 RPN total loss: 0.00724 Total loss: 0.84462 timestamp: 1654966155.8278797 iteration: 66825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12835 FastRCNN class loss: 0.05813 FastRCNN total loss: 0.18648 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.14936 RPN box loss: 0.02725 RPN score loss: 0.00202 RPN total loss: 0.02928 Total loss: 0.95711 timestamp: 1654966158.9402678 iteration: 66830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07178 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.15796 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.09654 RPN box loss: 0.01302 RPN score loss: 0.00299 RPN total loss: 0.01601 Total loss: 0.86249 timestamp: 1654966162.1274476 iteration: 66835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12406 FastRCNN class loss: 0.08646 FastRCNN total loss: 0.21052 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.14245 RPN box loss: 0.01887 RPN score loss: 0.0035 RPN total loss: 0.02237 Total loss: 0.96733 timestamp: 1654966165.2954588 iteration: 66840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05283 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.09967 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.0004 Mask loss: 0.1478 RPN box loss: 0.01218 RPN score loss: 0.00374 RPN total loss: 0.01592 Total loss: 0.85538 timestamp: 1654966168.5242667 iteration: 66845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09004 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.16144 L1 loss: 0.0000e+00 L2 loss: 0.59198 Learning rate: 0.0004 Mask loss: 0.10631 RPN box loss: 0.00767 RPN score loss: 0.00153 RPN total loss: 0.0092 Total loss: 0.86894 timestamp: 1654966171.7010067 iteration: 66850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09543 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.14431 L1 loss: 0.0000e+00 L2 loss: 0.59198 Learning rate: 0.0004 Mask loss: 0.1054 RPN box loss: 0.0058 RPN score loss: 0.00248 RPN total loss: 0.00828 Total loss: 0.84998 timestamp: 1654966174.941501 iteration: 66855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05453 FastRCNN class loss: 0.03437 FastRCNN total loss: 0.0889 L1 loss: 0.0000e+00 L2 loss: 0.59198 Learning rate: 0.0004 Mask loss: 0.13948 RPN box loss: 0.00697 RPN score loss: 0.00193 RPN total loss: 0.00889 Total loss: 0.82925 timestamp: 1654966178.1507447 iteration: 66860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05559 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.12173 L1 loss: 0.0000e+00 L2 loss: 0.59198 Learning rate: 0.0004 Mask loss: 0.11948 RPN box loss: 0.01273 RPN score loss: 0.00285 RPN total loss: 0.01559 Total loss: 0.84877 timestamp: 1654966181.306173 iteration: 66865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11848 FastRCNN class loss: 0.08337 FastRCNN total loss: 0.20185 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.0004 Mask loss: 0.15941 RPN box loss: 0.01055 RPN score loss: 0.00748 RPN total loss: 0.01803 Total loss: 0.97127 timestamp: 1654966184.5199628 iteration: 66870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08199 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.12987 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.0004 Mask loss: 0.13993 RPN box loss: 0.00643 RPN score loss: 0.0034 RPN total loss: 0.00983 Total loss: 0.8716 timestamp: 1654966187.748589 iteration: 66875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07769 FastRCNN class loss: 0.04712 FastRCNN total loss: 0.12481 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.0004 Mask loss: 0.10636 RPN box loss: 0.01392 RPN score loss: 0.00119 RPN total loss: 0.01511 Total loss: 0.83824 timestamp: 1654966190.9580953 iteration: 66880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13224 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.20072 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.0004 Mask loss: 0.10213 RPN box loss: 0.01006 RPN score loss: 0.00534 RPN total loss: 0.01539 Total loss: 0.91021 timestamp: 1654966194.1040812 iteration: 66885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05304 FastRCNN class loss: 0.03048 FastRCNN total loss: 0.08352 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.0004 Mask loss: 0.08706 RPN box loss: 0.00738 RPN score loss: 0.00688 RPN total loss: 0.01426 Total loss: 0.77681 timestamp: 1654966197.274106 iteration: 66890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08165 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.14775 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.0004 Mask loss: 0.09372 RPN box loss: 0.00785 RPN score loss: 0.00905 RPN total loss: 0.01689 Total loss: 0.85033 timestamp: 1654966200.4328046 iteration: 66895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09205 FastRCNN class loss: 0.08658 FastRCNN total loss: 0.17863 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.0004 Mask loss: 0.14487 RPN box loss: 0.03265 RPN score loss: 0.00421 RPN total loss: 0.03685 Total loss: 0.95232 timestamp: 1654966203.7006834 iteration: 66900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14994 FastRCNN class loss: 0.07237 FastRCNN total loss: 0.22231 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.0004 Mask loss: 0.14794 RPN box loss: 0.04168 RPN score loss: 0.01132 RPN total loss: 0.053 Total loss: 1.01521 timestamp: 1654966206.8924372 iteration: 66905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07389 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.12894 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.0004 Mask loss: 0.0943 RPN box loss: 0.00807 RPN score loss: 0.00136 RPN total loss: 0.00943 Total loss: 0.82462 timestamp: 1654966210.152778 iteration: 66910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06713 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.13529 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.0004 Mask loss: 0.12396 RPN box loss: 0.00651 RPN score loss: 0.00129 RPN total loss: 0.0078 Total loss: 0.85901 timestamp: 1654966213.2864804 iteration: 66915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11237 FastRCNN class loss: 0.1033 FastRCNN total loss: 0.21566 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.0004 Mask loss: 0.15352 RPN box loss: 0.01229 RPN score loss: 0.00569 RPN total loss: 0.01799 Total loss: 0.97913 timestamp: 1654966216.4804232 iteration: 66920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.061 FastRCNN class loss: 0.04401 FastRCNN total loss: 0.105 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.0004 Mask loss: 0.1095 RPN box loss: 0.02533 RPN score loss: 0.00641 RPN total loss: 0.03174 Total loss: 0.83819 timestamp: 1654966219.6639647 iteration: 66925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07439 FastRCNN class loss: 0.05299 FastRCNN total loss: 0.12737 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.1296 RPN box loss: 0.00846 RPN score loss: 0.00087 RPN total loss: 0.00933 Total loss: 0.85826 timestamp: 1654966222.8188298 iteration: 66930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11217 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.2056 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.19598 RPN box loss: 0.01445 RPN score loss: 0.00254 RPN total loss: 0.01699 Total loss: 1.01052 timestamp: 1654966225.9140253 iteration: 66935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10222 FastRCNN class loss: 0.04387 FastRCNN total loss: 0.14609 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.10145 RPN box loss: 0.01782 RPN score loss: 0.00183 RPN total loss: 0.01964 Total loss: 0.85913 timestamp: 1654966229.1527867 iteration: 66940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15249 FastRCNN class loss: 0.06064 FastRCNN total loss: 0.21313 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.16661 RPN box loss: 0.00551 RPN score loss: 0.00754 RPN total loss: 0.01305 Total loss: 0.98474 timestamp: 1654966232.3407063 iteration: 66945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07665 FastRCNN class loss: 0.09213 FastRCNN total loss: 0.16878 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.13624 RPN box loss: 0.01533 RPN score loss: 0.00476 RPN total loss: 0.02009 Total loss: 0.91706 timestamp: 1654966235.5142653 iteration: 66950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09743 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.16829 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.17963 RPN box loss: 0.01282 RPN score loss: 0.00228 RPN total loss: 0.01511 Total loss: 0.95498 timestamp: 1654966238.7342618 iteration: 66955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07931 FastRCNN class loss: 0.05988 FastRCNN total loss: 0.13919 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.0004 Mask loss: 0.11562 RPN box loss: 0.00423 RPN score loss: 0.00999 RPN total loss: 0.01422 Total loss: 0.86098 timestamp: 1654966241.8827279 iteration: 66960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16702 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.22603 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.0004 Mask loss: 0.12485 RPN box loss: 0.00778 RPN score loss: 0.00245 RPN total loss: 0.01023 Total loss: 0.95305 timestamp: 1654966245.1176345 iteration: 66965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11841 FastRCNN class loss: 0.09836 FastRCNN total loss: 0.21677 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.0004 Mask loss: 0.16807 RPN box loss: 0.01327 RPN score loss: 0.01091 RPN total loss: 0.02418 Total loss: 1.00096 timestamp: 1654966248.3646777 iteration: 66970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.09996 FastRCNN total loss: 0.18527 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.0004 Mask loss: 0.17002 RPN box loss: 0.00691 RPN score loss: 0.00255 RPN total loss: 0.00946 Total loss: 0.9567 timestamp: 1654966251.5934224 iteration: 66975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.17449 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.0004 Mask loss: 0.16058 RPN box loss: 0.00774 RPN score loss: 0.00396 RPN total loss: 0.0117 Total loss: 0.93871 timestamp: 1654966254.7846484 iteration: 66980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.15272 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.0004 Mask loss: 0.13121 RPN box loss: 0.01182 RPN score loss: 0.004 RPN total loss: 0.01582 Total loss: 0.89168 timestamp: 1654966258.0104065 iteration: 66985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09439 FastRCNN class loss: 0.04208 FastRCNN total loss: 0.13647 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.0004 Mask loss: 0.12486 RPN box loss: 0.00485 RPN score loss: 0.00329 RPN total loss: 0.00814 Total loss: 0.86141 timestamp: 1654966261.220219 iteration: 66990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06297 FastRCNN class loss: 0.04616 FastRCNN total loss: 0.10914 L1 loss: 0.0000e+00 L2 loss: 0.59193 Learning rate: 0.0004 Mask loss: 0.12123 RPN box loss: 0.01167 RPN score loss: 0.0008 RPN total loss: 0.01248 Total loss: 0.83477 timestamp: 1654966264.4406087 iteration: 66995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1532 FastRCNN class loss: 0.04997 FastRCNN total loss: 0.20317 L1 loss: 0.0000e+00 L2 loss: 0.59193 Learning rate: 0.0004 Mask loss: 0.12566 RPN box loss: 0.01535 RPN score loss: 0.00409 RPN total loss: 0.01944 Total loss: 0.9402 timestamp: 1654966267.64987 iteration: 67000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10258 FastRCNN class loss: 0.07821 FastRCNN total loss: 0.18079 L1 loss: 0.0000e+00 L2 loss: 0.59193 Learning rate: 0.0004 Mask loss: 0.10074 RPN box loss: 0.01174 RPN score loss: 0.00181 RPN total loss: 0.01354 Total loss: 0.887 timestamp: 1654966270.8141186 iteration: 67005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04228 FastRCNN class loss: 0.04436 FastRCNN total loss: 0.08664 L1 loss: 0.0000e+00 L2 loss: 0.59193 Learning rate: 0.0004 Mask loss: 0.09843 RPN box loss: 0.02401 RPN score loss: 0.00529 RPN total loss: 0.0293 Total loss: 0.80629 timestamp: 1654966274.008434 iteration: 67010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06046 FastRCNN class loss: 0.05629 FastRCNN total loss: 0.11675 L1 loss: 0.0000e+00 L2 loss: 0.59193 Learning rate: 0.0004 Mask loss: 0.10869 RPN box loss: 0.01138 RPN score loss: 0.00234 RPN total loss: 0.01371 Total loss: 0.83109 timestamp: 1654966277.186832 iteration: 67015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09272 FastRCNN class loss: 0.04328 FastRCNN total loss: 0.136 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.0004 Mask loss: 0.08737 RPN box loss: 0.01005 RPN score loss: 0.00327 RPN total loss: 0.01332 Total loss: 0.82861 timestamp: 1654966280.34375 iteration: 67020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06881 FastRCNN class loss: 0.04584 FastRCNN total loss: 0.11465 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.0004 Mask loss: 0.12339 RPN box loss: 0.03048 RPN score loss: 0.00275 RPN total loss: 0.03323 Total loss: 0.86318 timestamp: 1654966283.532584 iteration: 67025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10851 FastRCNN class loss: 0.04598 FastRCNN total loss: 0.15449 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.0004 Mask loss: 0.07077 RPN box loss: 0.00872 RPN score loss: 0.00087 RPN total loss: 0.00959 Total loss: 0.82677 timestamp: 1654966286.7024632 iteration: 67030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10898 FastRCNN class loss: 0.0696 FastRCNN total loss: 0.17858 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.0004 Mask loss: 0.11128 RPN box loss: 0.00588 RPN score loss: 0.00233 RPN total loss: 0.00821 Total loss: 0.88998 timestamp: 1654966289.788577 iteration: 67035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11313 FastRCNN class loss: 0.10707 FastRCNN total loss: 0.22019 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.0004 Mask loss: 0.13518 RPN box loss: 0.01422 RPN score loss: 0.00235 RPN total loss: 0.01658 Total loss: 0.96387 timestamp: 1654966293.0140727 iteration: 67040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08013 FastRCNN class loss: 0.05192 FastRCNN total loss: 0.13205 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.0004 Mask loss: 0.12768 RPN box loss: 0.01043 RPN score loss: 0.00792 RPN total loss: 0.01835 Total loss: 0.87 timestamp: 1654966296.1918206 iteration: 67045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10956 FastRCNN class loss: 0.09018 FastRCNN total loss: 0.19973 L1 loss: 0.0000e+00 L2 loss: 0.59191 Learning rate: 0.0004 Mask loss: 0.19251 RPN box loss: 0.00694 RPN score loss: 0.00522 RPN total loss: 0.01217 Total loss: 0.99632 timestamp: 1654966299.4822268 iteration: 67050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10771 FastRCNN class loss: 0.07584 FastRCNN total loss: 0.18355 L1 loss: 0.0000e+00 L2 loss: 0.59191 Learning rate: 0.0004 Mask loss: 0.11879 RPN box loss: 0.02839 RPN score loss: 0.00379 RPN total loss: 0.03218 Total loss: 0.92643 timestamp: 1654966302.7108147 iteration: 67055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06845 FastRCNN class loss: 0.06457 FastRCNN total loss: 0.13303 L1 loss: 0.0000e+00 L2 loss: 0.59191 Learning rate: 0.0004 Mask loss: 0.12108 RPN box loss: 0.01656 RPN score loss: 0.0066 RPN total loss: 0.02316 Total loss: 0.86917 timestamp: 1654966306.0052826 iteration: 67060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07845 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.13196 L1 loss: 0.0000e+00 L2 loss: 0.59191 Learning rate: 0.0004 Mask loss: 0.16753 RPN box loss: 0.0088 RPN score loss: 0.00328 RPN total loss: 0.01208 Total loss: 0.90347 timestamp: 1654966309.2051902 iteration: 67065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.056 FastRCNN class loss: 0.05423 FastRCNN total loss: 0.11023 L1 loss: 0.0000e+00 L2 loss: 0.59191 Learning rate: 0.0004 Mask loss: 0.1349 RPN box loss: 0.00604 RPN score loss: 0.01088 RPN total loss: 0.01693 Total loss: 0.85396 timestamp: 1654966312.3432906 iteration: 67070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07619 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.13346 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.17136 RPN box loss: 0.0165 RPN score loss: 0.00164 RPN total loss: 0.01814 Total loss: 0.91486 timestamp: 1654966315.5527875 iteration: 67075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07284 FastRCNN class loss: 0.04839 FastRCNN total loss: 0.12123 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.17906 RPN box loss: 0.01336 RPN score loss: 0.00691 RPN total loss: 0.02027 Total loss: 0.91246 timestamp: 1654966318.7865198 iteration: 67080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07934 FastRCNN class loss: 0.0578 FastRCNN total loss: 0.13714 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.17255 RPN box loss: 0.00573 RPN score loss: 0.00288 RPN total loss: 0.00861 Total loss: 0.91021 timestamp: 1654966322.0498583 iteration: 67085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11669 FastRCNN class loss: 0.1137 FastRCNN total loss: 0.23039 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.16237 RPN box loss: 0.01613 RPN score loss: 0.00255 RPN total loss: 0.01868 Total loss: 1.00335 timestamp: 1654966325.2449517 iteration: 67090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13324 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.20525 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.11182 RPN box loss: 0.01967 RPN score loss: 0.00388 RPN total loss: 0.02355 Total loss: 0.93252 timestamp: 1654966328.4874616 iteration: 67095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07418 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.13331 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.1163 RPN box loss: 0.01914 RPN score loss: 0.00657 RPN total loss: 0.02571 Total loss: 0.86722 timestamp: 1654966331.665247 iteration: 67100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04699 FastRCNN class loss: 0.07535 FastRCNN total loss: 0.12233 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.0004 Mask loss: 0.17687 RPN box loss: 0.01451 RPN score loss: 0.0104 RPN total loss: 0.02491 Total loss: 0.91601 timestamp: 1654966334.8127573 iteration: 67105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07665 FastRCNN class loss: 0.03955 FastRCNN total loss: 0.1162 L1 loss: 0.0000e+00 L2 loss: 0.59189 Learning rate: 0.0004 Mask loss: 0.12578 RPN box loss: 0.00135 RPN score loss: 0.00348 RPN total loss: 0.00483 Total loss: 0.83871 timestamp: 1654966338.045067 iteration: 67110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04448 FastRCNN class loss: 0.03684 FastRCNN total loss: 0.08132 L1 loss: 0.0000e+00 L2 loss: 0.59189 Learning rate: 0.0004 Mask loss: 0.07836 RPN box loss: 0.00241 RPN score loss: 0.00237 RPN total loss: 0.00478 Total loss: 0.75635 timestamp: 1654966341.2589607 iteration: 67115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11143 FastRCNN class loss: 0.06708 FastRCNN total loss: 0.17851 L1 loss: 0.0000e+00 L2 loss: 0.59189 Learning rate: 0.0004 Mask loss: 0.1257 RPN box loss: 0.02457 RPN score loss: 0.00503 RPN total loss: 0.0296 Total loss: 0.9257 timestamp: 1654966344.4013073 iteration: 67120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10353 FastRCNN class loss: 0.09968 FastRCNN total loss: 0.20322 L1 loss: 0.0000e+00 L2 loss: 0.59189 Learning rate: 0.0004 Mask loss: 0.1297 RPN box loss: 0.0222 RPN score loss: 0.01117 RPN total loss: 0.03337 Total loss: 0.95817 timestamp: 1654966347.616645 iteration: 67125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07706 FastRCNN class loss: 0.06371 FastRCNN total loss: 0.14077 L1 loss: 0.0000e+00 L2 loss: 0.59189 Learning rate: 0.0004 Mask loss: 0.14508 RPN box loss: 0.00774 RPN score loss: 0.00333 RPN total loss: 0.01107 Total loss: 0.8888 timestamp: 1654966350.8548717 iteration: 67130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11555 FastRCNN class loss: 0.05679 FastRCNN total loss: 0.17234 L1 loss: 0.0000e+00 L2 loss: 0.59189 Learning rate: 0.0004 Mask loss: 0.12843 RPN box loss: 0.00964 RPN score loss: 0.00348 RPN total loss: 0.01311 Total loss: 0.90577 timestamp: 1654966354.0316575 iteration: 67135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1079 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.18135 L1 loss: 0.0000e+00 L2 loss: 0.59188 Learning rate: 0.0004 Mask loss: 0.10517 RPN box loss: 0.03471 RPN score loss: 0.00434 RPN total loss: 0.03905 Total loss: 0.91746 timestamp: 1654966357.234552 iteration: 67140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07998 FastRCNN class loss: 0.06347 FastRCNN total loss: 0.14345 L1 loss: 0.0000e+00 L2 loss: 0.59188 Learning rate: 0.0004 Mask loss: 0.14058 RPN box loss: 0.01355 RPN score loss: 0.00286 RPN total loss: 0.01641 Total loss: 0.89232 timestamp: 1654966360.4629557 iteration: 67145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10638 FastRCNN class loss: 0.09627 FastRCNN total loss: 0.20265 L1 loss: 0.0000e+00 L2 loss: 0.59188 Learning rate: 0.0004 Mask loss: 0.15117 RPN box loss: 0.00691 RPN score loss: 0.0086 RPN total loss: 0.01551 Total loss: 0.96121 timestamp: 1654966363.6141965 iteration: 67150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06615 FastRCNN class loss: 0.05422 FastRCNN total loss: 0.12037 L1 loss: 0.0000e+00 L2 loss: 0.59188 Learning rate: 0.0004 Mask loss: 0.12618 RPN box loss: 0.02005 RPN score loss: 0.00217 RPN total loss: 0.02222 Total loss: 0.86065 timestamp: 1654966366.7718096 iteration: 67155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07251 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.15039 L1 loss: 0.0000e+00 L2 loss: 0.59188 Learning rate: 0.0004 Mask loss: 0.10761 RPN box loss: 0.00895 RPN score loss: 0.00293 RPN total loss: 0.01188 Total loss: 0.86176 timestamp: 1654966369.9653704 iteration: 67160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09692 FastRCNN class loss: 0.1191 FastRCNN total loss: 0.21602 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.15812 RPN box loss: 0.02562 RPN score loss: 0.00641 RPN total loss: 0.03203 Total loss: 0.99805 timestamp: 1654966373.1161373 iteration: 67165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09761 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.16601 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.12874 RPN box loss: 0.01654 RPN score loss: 0.00272 RPN total loss: 0.01926 Total loss: 0.90588 timestamp: 1654966376.3261738 iteration: 67170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1365 FastRCNN class loss: 0.08767 FastRCNN total loss: 0.22416 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.15905 RPN box loss: 0.00697 RPN score loss: 0.00119 RPN total loss: 0.00815 Total loss: 0.98324 timestamp: 1654966379.5336533 iteration: 67175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12372 FastRCNN class loss: 0.12175 FastRCNN total loss: 0.24547 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.17017 RPN box loss: 0.01188 RPN score loss: 0.00633 RPN total loss: 0.01821 Total loss: 1.02571 timestamp: 1654966382.720206 iteration: 67180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0845 FastRCNN class loss: 0.10369 FastRCNN total loss: 0.18819 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.1133 RPN box loss: 0.02312 RPN score loss: 0.00335 RPN total loss: 0.02647 Total loss: 0.91982 timestamp: 1654966385.8420074 iteration: 67185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07635 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.16325 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.14024 RPN box loss: 0.00524 RPN score loss: 0.00291 RPN total loss: 0.00815 Total loss: 0.90351 timestamp: 1654966388.9793005 iteration: 67190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10778 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.18034 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.0004 Mask loss: 0.10807 RPN box loss: 0.00432 RPN score loss: 0.00271 RPN total loss: 0.00704 Total loss: 0.88731 timestamp: 1654966392.1131122 iteration: 67195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.14479 L1 loss: 0.0000e+00 L2 loss: 0.59186 Learning rate: 0.0004 Mask loss: 0.18739 RPN box loss: 0.00955 RPN score loss: 0.00401 RPN total loss: 0.01356 Total loss: 0.9376 timestamp: 1654966395.2760153 iteration: 67200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09165 FastRCNN class loss: 0.09593 FastRCNN total loss: 0.18758 L1 loss: 0.0000e+00 L2 loss: 0.59186 Learning rate: 0.0004 Mask loss: 0.1699 RPN box loss: 0.00618 RPN score loss: 0.00079 RPN total loss: 0.00697 Total loss: 0.95631 timestamp: 1654966398.475872 iteration: 67205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10023 FastRCNN class loss: 0.12912 FastRCNN total loss: 0.22935 L1 loss: 0.0000e+00 L2 loss: 0.59186 Learning rate: 0.0004 Mask loss: 0.08266 RPN box loss: 0.00284 RPN score loss: 0.00285 RPN total loss: 0.00569 Total loss: 0.90956 timestamp: 1654966401.6984005 iteration: 67210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07794 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.12607 L1 loss: 0.0000e+00 L2 loss: 0.59186 Learning rate: 0.0004 Mask loss: 0.12269 RPN box loss: 0.04242 RPN score loss: 0.00217 RPN total loss: 0.04459 Total loss: 0.88521 timestamp: 1654966404.8493848 iteration: 67215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1353 FastRCNN class loss: 0.09645 FastRCNN total loss: 0.23175 L1 loss: 0.0000e+00 L2 loss: 0.59186 Learning rate: 0.0004 Mask loss: 0.16242 RPN box loss: 0.01911 RPN score loss: 0.01383 RPN total loss: 0.03294 Total loss: 1.01896 timestamp: 1654966408.0119636 iteration: 67220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06556 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.1278 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.25072 RPN box loss: 0.01325 RPN score loss: 0.00472 RPN total loss: 0.01797 Total loss: 0.98834 timestamp: 1654966411.2288215 iteration: 67225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09799 FastRCNN class loss: 0.06496 FastRCNN total loss: 0.16295 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.10929 RPN box loss: 0.01503 RPN score loss: 0.00372 RPN total loss: 0.01876 Total loss: 0.88285 timestamp: 1654966414.4560182 iteration: 67230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10249 FastRCNN class loss: 0.08593 FastRCNN total loss: 0.18843 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.19451 RPN box loss: 0.01201 RPN score loss: 0.0021 RPN total loss: 0.01411 Total loss: 0.98889 timestamp: 1654966417.6146657 iteration: 67235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14204 FastRCNN class loss: 0.06156 FastRCNN total loss: 0.2036 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.09226 RPN box loss: 0.00717 RPN score loss: 0.00416 RPN total loss: 0.01134 Total loss: 0.89905 timestamp: 1654966420.888499 iteration: 67240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10929 FastRCNN class loss: 0.15937 FastRCNN total loss: 0.26866 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.20861 RPN box loss: 0.01475 RPN score loss: 0.00505 RPN total loss: 0.0198 Total loss: 1.08893 timestamp: 1654966424.06379 iteration: 67245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11148 FastRCNN class loss: 0.05991 FastRCNN total loss: 0.17139 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.11451 RPN box loss: 0.00544 RPN score loss: 0.011 RPN total loss: 0.01644 Total loss: 0.89418 timestamp: 1654966427.2477698 iteration: 67250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09042 FastRCNN class loss: 0.05714 FastRCNN total loss: 0.14756 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.0004 Mask loss: 0.16403 RPN box loss: 0.03555 RPN score loss: 0.00218 RPN total loss: 0.03773 Total loss: 0.94117 timestamp: 1654966430.4418104 iteration: 67255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09113 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.17049 L1 loss: 0.0000e+00 L2 loss: 0.59184 Learning rate: 0.0004 Mask loss: 0.12493 RPN box loss: 0.00815 RPN score loss: 0.00707 RPN total loss: 0.01522 Total loss: 0.90248 timestamp: 1654966433.654661 iteration: 67260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10679 FastRCNN class loss: 0.08438 FastRCNN total loss: 0.19117 L1 loss: 0.0000e+00 L2 loss: 0.59184 Learning rate: 0.0004 Mask loss: 0.13065 RPN box loss: 0.04196 RPN score loss: 0.0075 RPN total loss: 0.04946 Total loss: 0.96312 timestamp: 1654966436.754236 iteration: 67265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05689 FastRCNN class loss: 0.04022 FastRCNN total loss: 0.09711 L1 loss: 0.0000e+00 L2 loss: 0.59184 Learning rate: 0.0004 Mask loss: 0.08538 RPN box loss: 0.01241 RPN score loss: 0.00227 RPN total loss: 0.01469 Total loss: 0.78902 timestamp: 1654966439.957571 iteration: 67270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05704 FastRCNN class loss: 0.05955 FastRCNN total loss: 0.11659 L1 loss: 0.0000e+00 L2 loss: 0.59184 Learning rate: 0.0004 Mask loss: 0.14945 RPN box loss: 0.00406 RPN score loss: 0.00143 RPN total loss: 0.00549 Total loss: 0.86337 timestamp: 1654966443.1695957 iteration: 67275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06296 FastRCNN class loss: 0.08315 FastRCNN total loss: 0.14611 L1 loss: 0.0000e+00 L2 loss: 0.59184 Learning rate: 0.0004 Mask loss: 0.11574 RPN box loss: 0.00588 RPN score loss: 0.00119 RPN total loss: 0.00707 Total loss: 0.86075 timestamp: 1654966446.4534004 iteration: 67280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08642 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.15771 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.11347 RPN box loss: 0.0084 RPN score loss: 0.01003 RPN total loss: 0.01843 Total loss: 0.88144 timestamp: 1654966449.6842215 iteration: 67285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08211 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.13982 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.08711 RPN box loss: 0.00992 RPN score loss: 0.0082 RPN total loss: 0.01812 Total loss: 0.83688 timestamp: 1654966452.9562964 iteration: 67290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08972 FastRCNN class loss: 0.0708 FastRCNN total loss: 0.16052 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.12263 RPN box loss: 0.01418 RPN score loss: 0.00196 RPN total loss: 0.01614 Total loss: 0.89113 timestamp: 1654966456.0962906 iteration: 67295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06186 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.12316 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.08411 RPN box loss: 0.00846 RPN score loss: 0.00428 RPN total loss: 0.01275 Total loss: 0.81185 timestamp: 1654966459.2832901 iteration: 67300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11392 FastRCNN class loss: 0.08635 FastRCNN total loss: 0.20027 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.13761 RPN box loss: 0.00776 RPN score loss: 0.00528 RPN total loss: 0.01304 Total loss: 0.94276 timestamp: 1654966462.4619827 iteration: 67305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08324 FastRCNN class loss: 0.05591 FastRCNN total loss: 0.13915 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.11179 RPN box loss: 0.00762 RPN score loss: 0.00433 RPN total loss: 0.01195 Total loss: 0.85471 timestamp: 1654966465.7360244 iteration: 67310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12062 FastRCNN class loss: 0.05765 FastRCNN total loss: 0.17826 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.0004 Mask loss: 0.12645 RPN box loss: 0.01387 RPN score loss: 0.00427 RPN total loss: 0.01814 Total loss: 0.91469 timestamp: 1654966468.8802512 iteration: 67315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04705 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.1001 L1 loss: 0.0000e+00 L2 loss: 0.59182 Learning rate: 0.0004 Mask loss: 0.14764 RPN box loss: 0.00771 RPN score loss: 0.00287 RPN total loss: 0.01058 Total loss: 0.85014 timestamp: 1654966472.1587915 iteration: 67320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13271 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.2033 L1 loss: 0.0000e+00 L2 loss: 0.59182 Learning rate: 0.0004 Mask loss: 0.16003 RPN box loss: 0.01332 RPN score loss: 0.00336 RPN total loss: 0.01668 Total loss: 0.97183 timestamp: 1654966475.3088734 iteration: 67325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09713 FastRCNN class loss: 0.07972 FastRCNN total loss: 0.17685 L1 loss: 0.0000e+00 L2 loss: 0.59182 Learning rate: 0.0004 Mask loss: 0.11388 RPN box loss: 0.00963 RPN score loss: 0.01224 RPN total loss: 0.02187 Total loss: 0.90442 timestamp: 1654966478.5072236 iteration: 67330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13007 FastRCNN class loss: 0.11654 FastRCNN total loss: 0.24661 L1 loss: 0.0000e+00 L2 loss: 0.59182 Learning rate: 0.0004 Mask loss: 0.15142 RPN box loss: 0.02193 RPN score loss: 0.00983 RPN total loss: 0.03176 Total loss: 1.02161 timestamp: 1654966481.7779398 iteration: 67335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07599 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.1327 L1 loss: 0.0000e+00 L2 loss: 0.59182 Learning rate: 0.0004 Mask loss: 0.15932 RPN box loss: 0.00783 RPN score loss: 0.00359 RPN total loss: 0.01142 Total loss: 0.89526 timestamp: 1654966484.9342458 iteration: 67340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0699 FastRCNN class loss: 0.05507 FastRCNN total loss: 0.12498 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.10592 RPN box loss: 0.01164 RPN score loss: 0.00681 RPN total loss: 0.01846 Total loss: 0.84116 timestamp: 1654966488.1492422 iteration: 67345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07992 FastRCNN class loss: 0.06518 FastRCNN total loss: 0.1451 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.15775 RPN box loss: 0.00643 RPN score loss: 0.00197 RPN total loss: 0.00841 Total loss: 0.90306 timestamp: 1654966491.3153267 iteration: 67350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08255 FastRCNN class loss: 0.06649 FastRCNN total loss: 0.14904 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.14499 RPN box loss: 0.04019 RPN score loss: 0.00185 RPN total loss: 0.04204 Total loss: 0.92788 timestamp: 1654966494.5068185 iteration: 67355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13661 FastRCNN class loss: 0.06829 FastRCNN total loss: 0.2049 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.15639 RPN box loss: 0.01191 RPN score loss: 0.00438 RPN total loss: 0.01628 Total loss: 0.96938 timestamp: 1654966497.6820307 iteration: 67360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.08369 FastRCNN total loss: 0.16688 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.15484 RPN box loss: 0.01263 RPN score loss: 0.00133 RPN total loss: 0.01395 Total loss: 0.92747 timestamp: 1654966500.931737 iteration: 67365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07677 FastRCNN class loss: 0.03746 FastRCNN total loss: 0.11424 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.14852 RPN box loss: 0.00446 RPN score loss: 0.00204 RPN total loss: 0.0065 Total loss: 0.86106 timestamp: 1654966504.1821644 iteration: 67370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13036 FastRCNN class loss: 0.08563 FastRCNN total loss: 0.21599 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.0004 Mask loss: 0.11359 RPN box loss: 0.03425 RPN score loss: 0.00481 RPN total loss: 0.03907 Total loss: 0.96045 timestamp: 1654966507.3803804 iteration: 67375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08656 FastRCNN class loss: 0.04032 FastRCNN total loss: 0.12688 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.0004 Mask loss: 0.12528 RPN box loss: 0.02333 RPN score loss: 0.00846 RPN total loss: 0.03179 Total loss: 0.87575 timestamp: 1654966510.5334423 iteration: 67380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06519 FastRCNN class loss: 0.08027 FastRCNN total loss: 0.14546 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.0004 Mask loss: 0.16904 RPN box loss: 0.02766 RPN score loss: 0.01572 RPN total loss: 0.04338 Total loss: 0.94967 timestamp: 1654966513.6797118 iteration: 67385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12232 FastRCNN class loss: 0.07724 FastRCNN total loss: 0.19956 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.0004 Mask loss: 0.15962 RPN box loss: 0.01073 RPN score loss: 0.00963 RPN total loss: 0.02036 Total loss: 0.97134 timestamp: 1654966516.8959467 iteration: 67390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09089 FastRCNN class loss: 0.05325 FastRCNN total loss: 0.14415 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.0004 Mask loss: 0.15145 RPN box loss: 0.00876 RPN score loss: 0.00195 RPN total loss: 0.01071 Total loss: 0.89811 timestamp: 1654966520.1225767 iteration: 67395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06481 FastRCNN class loss: 0.05161 FastRCNN total loss: 0.11642 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.0004 Mask loss: 0.1104 RPN box loss: 0.00714 RPN score loss: 0.00404 RPN total loss: 0.01118 Total loss: 0.82979 timestamp: 1654966523.3556006 iteration: 67400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10211 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.16998 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.0004 Mask loss: 0.13103 RPN box loss: 0.0028 RPN score loss: 0.00433 RPN total loss: 0.00714 Total loss: 0.89994 timestamp: 1654966526.5126154 iteration: 67405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11385 FastRCNN class loss: 0.08872 FastRCNN total loss: 0.20257 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.0004 Mask loss: 0.13317 RPN box loss: 0.02527 RPN score loss: 0.00723 RPN total loss: 0.0325 Total loss: 0.96004 timestamp: 1654966529.6648915 iteration: 67410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11977 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.19786 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.0004 Mask loss: 0.1223 RPN box loss: 0.01063 RPN score loss: 0.01621 RPN total loss: 0.02685 Total loss: 0.93879 timestamp: 1654966532.8721077 iteration: 67415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04045 FastRCNN class loss: 0.03268 FastRCNN total loss: 0.07313 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.0004 Mask loss: 0.08558 RPN box loss: 0.01196 RPN score loss: 0.00075 RPN total loss: 0.01271 Total loss: 0.76321 timestamp: 1654966536.0450163 iteration: 67420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10882 FastRCNN class loss: 0.05127 FastRCNN total loss: 0.16008 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.0004 Mask loss: 0.11375 RPN box loss: 0.01625 RPN score loss: 0.00406 RPN total loss: 0.02031 Total loss: 0.88594 timestamp: 1654966539.3392878 iteration: 67425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0823 FastRCNN class loss: 0.03804 FastRCNN total loss: 0.12034 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.0004 Mask loss: 0.11257 RPN box loss: 0.00286 RPN score loss: 0.00745 RPN total loss: 0.01031 Total loss: 0.83501 timestamp: 1654966542.4904778 iteration: 67430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06512 FastRCNN class loss: 0.03661 FastRCNN total loss: 0.10173 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.0004 Mask loss: 0.12814 RPN box loss: 0.00867 RPN score loss: 0.00769 RPN total loss: 0.01635 Total loss: 0.83802 timestamp: 1654966545.5644293 iteration: 67435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14809 FastRCNN class loss: 0.12031 FastRCNN total loss: 0.2684 L1 loss: 0.0000e+00 L2 loss: 0.59178 Learning rate: 0.0004 Mask loss: 0.15917 RPN box loss: 0.01039 RPN score loss: 0.00677 RPN total loss: 0.01716 Total loss: 1.03651 timestamp: 1654966548.7807574 iteration: 67440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04473 FastRCNN class loss: 0.04797 FastRCNN total loss: 0.0927 L1 loss: 0.0000e+00 L2 loss: 0.59178 Learning rate: 0.0004 Mask loss: 0.09669 RPN box loss: 0.00362 RPN score loss: 0.0067 RPN total loss: 0.01032 Total loss: 0.79149 timestamp: 1654966551.9301472 iteration: 67445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08038 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.14064 L1 loss: 0.0000e+00 L2 loss: 0.59178 Learning rate: 0.0004 Mask loss: 0.10328 RPN box loss: 0.0046 RPN score loss: 0.00472 RPN total loss: 0.00932 Total loss: 0.84501 timestamp: 1654966555.159074 iteration: 67450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09868 FastRCNN class loss: 0.06933 FastRCNN total loss: 0.16801 L1 loss: 0.0000e+00 L2 loss: 0.59178 Learning rate: 0.0004 Mask loss: 0.21118 RPN box loss: 0.01314 RPN score loss: 0.00366 RPN total loss: 0.0168 Total loss: 0.98777 timestamp: 1654966558.3534696 iteration: 67455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03715 FastRCNN class loss: 0.0438 FastRCNN total loss: 0.08095 L1 loss: 0.0000e+00 L2 loss: 0.59178 Learning rate: 0.0004 Mask loss: 0.07915 RPN box loss: 0.00606 RPN score loss: 0.00151 RPN total loss: 0.00757 Total loss: 0.75944 timestamp: 1654966561.5703619 iteration: 67460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05666 FastRCNN class loss: 0.05572 FastRCNN total loss: 0.11239 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.0004 Mask loss: 0.10137 RPN box loss: 0.0043 RPN score loss: 0.0045 RPN total loss: 0.00881 Total loss: 0.81434 timestamp: 1654966564.7044349 iteration: 67465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1427 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.21615 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.0004 Mask loss: 0.13512 RPN box loss: 0.0082 RPN score loss: 0.00228 RPN total loss: 0.01048 Total loss: 0.95352 timestamp: 1654966567.8650413 iteration: 67470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.09661 FastRCNN total loss: 0.18429 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.0004 Mask loss: 0.15601 RPN box loss: 0.01371 RPN score loss: 0.00758 RPN total loss: 0.0213 Total loss: 0.95337 timestamp: 1654966571.119162 iteration: 67475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08857 FastRCNN class loss: 0.10625 FastRCNN total loss: 0.19481 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.0004 Mask loss: 0.11682 RPN box loss: 0.00944 RPN score loss: 0.00464 RPN total loss: 0.01408 Total loss: 0.91748 timestamp: 1654966574.405919 iteration: 67480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08756 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.16505 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.0004 Mask loss: 0.15989 RPN box loss: 0.03224 RPN score loss: 0.00632 RPN total loss: 0.03856 Total loss: 0.95526 timestamp: 1654966577.6414866 iteration: 67485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08156 FastRCNN class loss: 0.05698 FastRCNN total loss: 0.13854 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.0004 Mask loss: 0.11709 RPN box loss: 0.00573 RPN score loss: 0.00037 RPN total loss: 0.0061 Total loss: 0.85349 timestamp: 1654966580.8309088 iteration: 67490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13979 FastRCNN class loss: 0.09709 FastRCNN total loss: 0.23688 L1 loss: 0.0000e+00 L2 loss: 0.59176 Learning rate: 0.0004 Mask loss: 0.17831 RPN box loss: 0.02605 RPN score loss: 0.00303 RPN total loss: 0.02908 Total loss: 1.03602 timestamp: 1654966584.0353518 iteration: 67495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14131 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.21471 L1 loss: 0.0000e+00 L2 loss: 0.59176 Learning rate: 0.0004 Mask loss: 0.11846 RPN box loss: 0.01148 RPN score loss: 0.00385 RPN total loss: 0.01533 Total loss: 0.94026 timestamp: 1654966587.2533226 iteration: 67500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.07045 FastRCNN total loss: 0.1757 L1 loss: 0.0000e+00 L2 loss: 0.59176 Learning rate: 0.0004 Mask loss: 0.10473 RPN box loss: 0.01077 RPN score loss: 0.00155 RPN total loss: 0.01232 Total loss: 0.88451 timestamp: 1654966590.4273744 iteration: 67505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.078 FastRCNN class loss: 0.07075 FastRCNN total loss: 0.14875 L1 loss: 0.0000e+00 L2 loss: 0.59176 Learning rate: 0.0004 Mask loss: 0.13165 RPN box loss: 0.01742 RPN score loss: 0.00197 RPN total loss: 0.01938 Total loss: 0.89154 timestamp: 1654966593.6223807 iteration: 67510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04677 FastRCNN class loss: 0.04555 FastRCNN total loss: 0.09233 L1 loss: 0.0000e+00 L2 loss: 0.59176 Learning rate: 0.0004 Mask loss: 0.09968 RPN box loss: 0.00553 RPN score loss: 0.00192 RPN total loss: 0.00745 Total loss: 0.79121 timestamp: 1654966596.82395 iteration: 67515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14842 FastRCNN class loss: 0.11159 FastRCNN total loss: 0.26001 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.17553 RPN box loss: 0.02388 RPN score loss: 0.00831 RPN total loss: 0.0322 Total loss: 1.05949 timestamp: 1654966600.0006082 iteration: 67520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07067 FastRCNN class loss: 0.05335 FastRCNN total loss: 0.12402 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.11505 RPN box loss: 0.01202 RPN score loss: 0.00203 RPN total loss: 0.01405 Total loss: 0.84488 timestamp: 1654966603.2077308 iteration: 67525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10275 FastRCNN class loss: 0.06455 FastRCNN total loss: 0.1673 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.16066 RPN box loss: 0.0091 RPN score loss: 0.00273 RPN total loss: 0.01183 Total loss: 0.93154 timestamp: 1654966606.354256 iteration: 67530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1715 FastRCNN class loss: 0.15469 FastRCNN total loss: 0.32619 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.17027 RPN box loss: 0.01973 RPN score loss: 0.00632 RPN total loss: 0.02606 Total loss: 1.11426 timestamp: 1654966609.481619 iteration: 67535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12949 FastRCNN class loss: 0.10876 FastRCNN total loss: 0.23825 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.21425 RPN box loss: 0.02639 RPN score loss: 0.00477 RPN total loss: 0.03116 Total loss: 1.07541 timestamp: 1654966612.7434645 iteration: 67540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05709 FastRCNN class loss: 0.06464 FastRCNN total loss: 0.12174 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.1092 RPN box loss: 0.00638 RPN score loss: 0.00498 RPN total loss: 0.01136 Total loss: 0.83404 timestamp: 1654966615.9256115 iteration: 67545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03999 FastRCNN class loss: 0.05662 FastRCNN total loss: 0.09661 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.0004 Mask loss: 0.19552 RPN box loss: 0.00777 RPN score loss: 0.00615 RPN total loss: 0.01393 Total loss: 0.89781 timestamp: 1654966619.1394787 iteration: 67550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07629 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.1428 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.0004 Mask loss: 0.0777 RPN box loss: 0.0127 RPN score loss: 0.00231 RPN total loss: 0.01501 Total loss: 0.82725 timestamp: 1654966622.273345 iteration: 67555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05548 FastRCNN class loss: 0.05386 FastRCNN total loss: 0.10935 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.0004 Mask loss: 0.15573 RPN box loss: 0.00543 RPN score loss: 0.0074 RPN total loss: 0.01283 Total loss: 0.86964 timestamp: 1654966625.473217 iteration: 67560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12244 FastRCNN class loss: 0.07993 FastRCNN total loss: 0.20237 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.0004 Mask loss: 0.23771 RPN box loss: 0.02032 RPN score loss: 0.00748 RPN total loss: 0.0278 Total loss: 1.05962 timestamp: 1654966628.6946416 iteration: 67565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04948 FastRCNN class loss: 0.04148 FastRCNN total loss: 0.09097 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.0004 Mask loss: 0.1089 RPN box loss: 0.02592 RPN score loss: 0.00645 RPN total loss: 0.03238 Total loss: 0.82398 timestamp: 1654966631.893594 iteration: 67570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08115 FastRCNN class loss: 0.06549 FastRCNN total loss: 0.14663 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.0004 Mask loss: 0.08564 RPN box loss: 0.01548 RPN score loss: 0.00248 RPN total loss: 0.01796 Total loss: 0.84197 timestamp: 1654966635.1027997 iteration: 67575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10172 FastRCNN class loss: 0.06636 FastRCNN total loss: 0.16808 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.0004 Mask loss: 0.12762 RPN box loss: 0.02172 RPN score loss: 0.01088 RPN total loss: 0.03261 Total loss: 0.92004 timestamp: 1654966638.3124418 iteration: 67580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15565 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.23278 L1 loss: 0.0000e+00 L2 loss: 0.59173 Learning rate: 0.0004 Mask loss: 0.33726 RPN box loss: 0.02391 RPN score loss: 0.0056 RPN total loss: 0.02951 Total loss: 1.19128 timestamp: 1654966641.4586978 iteration: 67585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07369 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.13821 L1 loss: 0.0000e+00 L2 loss: 0.59173 Learning rate: 0.0004 Mask loss: 0.13537 RPN box loss: 0.00851 RPN score loss: 0.00543 RPN total loss: 0.01394 Total loss: 0.87926 timestamp: 1654966644.6870031 iteration: 67590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05563 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.11261 L1 loss: 0.0000e+00 L2 loss: 0.59173 Learning rate: 0.0004 Mask loss: 0.11762 RPN box loss: 0.00792 RPN score loss: 0.00476 RPN total loss: 0.01267 Total loss: 0.83464 timestamp: 1654966647.8820202 iteration: 67595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11533 FastRCNN class loss: 0.07852 FastRCNN total loss: 0.19385 L1 loss: 0.0000e+00 L2 loss: 0.59173 Learning rate: 0.0004 Mask loss: 0.17662 RPN box loss: 0.01183 RPN score loss: 0.00429 RPN total loss: 0.01612 Total loss: 0.97833 timestamp: 1654966651.1090474 iteration: 67600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06879 FastRCNN class loss: 0.0517 FastRCNN total loss: 0.12049 L1 loss: 0.0000e+00 L2 loss: 0.59173 Learning rate: 0.0004 Mask loss: 0.11475 RPN box loss: 0.00974 RPN score loss: 0.00645 RPN total loss: 0.01619 Total loss: 0.84315 timestamp: 1654966654.2551706 iteration: 67605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05346 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.11332 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.0004 Mask loss: 0.06267 RPN box loss: 0.00533 RPN score loss: 0.0006 RPN total loss: 0.00594 Total loss: 0.77365 timestamp: 1654966657.4499428 iteration: 67610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07203 FastRCNN class loss: 0.05478 FastRCNN total loss: 0.12681 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.0004 Mask loss: 0.06575 RPN box loss: 0.01586 RPN score loss: 0.00095 RPN total loss: 0.01682 Total loss: 0.8011 timestamp: 1654966660.639631 iteration: 67615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11259 FastRCNN class loss: 0.11606 FastRCNN total loss: 0.22865 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.0004 Mask loss: 0.14591 RPN box loss: 0.01327 RPN score loss: 0.01311 RPN total loss: 0.02637 Total loss: 0.99266 timestamp: 1654966663.866104 iteration: 67620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05551 FastRCNN class loss: 0.04649 FastRCNN total loss: 0.10199 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.0004 Mask loss: 0.11281 RPN box loss: 0.02809 RPN score loss: 0.00723 RPN total loss: 0.03533 Total loss: 0.84185 timestamp: 1654966667.0736027 iteration: 67625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09107 FastRCNN class loss: 0.06008 FastRCNN total loss: 0.15114 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.0004 Mask loss: 0.16041 RPN box loss: 0.01187 RPN score loss: 0.00617 RPN total loss: 0.01805 Total loss: 0.92132 timestamp: 1654966670.3049011 iteration: 67630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09376 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.1655 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.0004 Mask loss: 0.15213 RPN box loss: 0.01964 RPN score loss: 0.01148 RPN total loss: 0.03111 Total loss: 0.94046 timestamp: 1654966673.5443609 iteration: 67635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11308 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.17747 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.0004 Mask loss: 0.14608 RPN box loss: 0.01277 RPN score loss: 0.00162 RPN total loss: 0.01439 Total loss: 0.92965 timestamp: 1654966676.7572284 iteration: 67640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.06261 FastRCNN total loss: 0.17447 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.0004 Mask loss: 0.10464 RPN box loss: 0.01468 RPN score loss: 0.00178 RPN total loss: 0.01646 Total loss: 0.88728 timestamp: 1654966679.8942776 iteration: 67645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06701 FastRCNN class loss: 0.04392 FastRCNN total loss: 0.11093 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.0004 Mask loss: 0.11742 RPN box loss: 0.00396 RPN score loss: 0.00721 RPN total loss: 0.01116 Total loss: 0.83122 timestamp: 1654966683.0936942 iteration: 67650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04231 FastRCNN class loss: 0.02817 FastRCNN total loss: 0.07048 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.0004 Mask loss: 0.10686 RPN box loss: 0.00184 RPN score loss: 0.00111 RPN total loss: 0.00296 Total loss: 0.772 timestamp: 1654966686.236998 iteration: 67655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07678 FastRCNN class loss: 0.06024 FastRCNN total loss: 0.13702 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.0004 Mask loss: 0.09924 RPN box loss: 0.00489 RPN score loss: 0.00553 RPN total loss: 0.01042 Total loss: 0.83838 timestamp: 1654966689.4031682 iteration: 67660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09118 FastRCNN class loss: 0.05159 FastRCNN total loss: 0.14276 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.0004 Mask loss: 0.11074 RPN box loss: 0.00968 RPN score loss: 0.00146 RPN total loss: 0.01114 Total loss: 0.85635 timestamp: 1654966692.5849504 iteration: 67665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07899 FastRCNN class loss: 0.04638 FastRCNN total loss: 0.12537 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.0004 Mask loss: 0.1269 RPN box loss: 0.0109 RPN score loss: 0.00249 RPN total loss: 0.01339 Total loss: 0.85736 timestamp: 1654966695.7420993 iteration: 67670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08752 FastRCNN class loss: 0.08336 FastRCNN total loss: 0.17089 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.0004 Mask loss: 0.15449 RPN box loss: 0.00834 RPN score loss: 0.01081 RPN total loss: 0.01915 Total loss: 0.93623 timestamp: 1654966698.9793267 iteration: 67675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16854 FastRCNN class loss: 0.10817 FastRCNN total loss: 0.27671 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.0004 Mask loss: 0.12254 RPN box loss: 0.00936 RPN score loss: 0.0016 RPN total loss: 0.01096 Total loss: 1.00191 timestamp: 1654966702.221529 iteration: 67680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09423 FastRCNN class loss: 0.04188 FastRCNN total loss: 0.13611 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.0004 Mask loss: 0.13423 RPN box loss: 0.0132 RPN score loss: 0.00607 RPN total loss: 0.01927 Total loss: 0.88131 timestamp: 1654966705.3597426 iteration: 67685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05482 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.10834 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.0004 Mask loss: 0.12741 RPN box loss: 0.02665 RPN score loss: 0.00484 RPN total loss: 0.03149 Total loss: 0.85894 timestamp: 1654966708.5225422 iteration: 67690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10057 FastRCNN class loss: 0.0953 FastRCNN total loss: 0.19587 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.0004 Mask loss: 0.15908 RPN box loss: 0.01521 RPN score loss: 0.00195 RPN total loss: 0.01717 Total loss: 0.96381 timestamp: 1654966711.6710196 iteration: 67695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07826 FastRCNN class loss: 0.07453 FastRCNN total loss: 0.15278 L1 loss: 0.0000e+00 L2 loss: 0.59169 Learning rate: 0.0004 Mask loss: 0.13644 RPN box loss: 0.01236 RPN score loss: 0.00682 RPN total loss: 0.01919 Total loss: 0.9001 timestamp: 1654966714.9180863 iteration: 67700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09453 FastRCNN class loss: 0.07117 FastRCNN total loss: 0.1657 L1 loss: 0.0000e+00 L2 loss: 0.59169 Learning rate: 0.0004 Mask loss: 0.10329 RPN box loss: 0.00712 RPN score loss: 0.00543 RPN total loss: 0.01255 Total loss: 0.87323 timestamp: 1654966718.1049066 iteration: 67705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08115 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.14399 L1 loss: 0.0000e+00 L2 loss: 0.59169 Learning rate: 0.0004 Mask loss: 0.13601 RPN box loss: 0.01231 RPN score loss: 0.00424 RPN total loss: 0.01655 Total loss: 0.88823 timestamp: 1654966721.2482026 iteration: 67710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.06005 FastRCNN total loss: 0.13028 L1 loss: 0.0000e+00 L2 loss: 0.59169 Learning rate: 0.0004 Mask loss: 0.20248 RPN box loss: 0.01641 RPN score loss: 0.01282 RPN total loss: 0.02923 Total loss: 0.95367 timestamp: 1654966724.434818 iteration: 67715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11228 FastRCNN class loss: 0.05666 FastRCNN total loss: 0.16894 L1 loss: 0.0000e+00 L2 loss: 0.59169 Learning rate: 0.0004 Mask loss: 0.14941 RPN box loss: 0.00605 RPN score loss: 0.00204 RPN total loss: 0.00809 Total loss: 0.91812 timestamp: 1654966727.6620438 iteration: 67720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12338 FastRCNN class loss: 0.08866 FastRCNN total loss: 0.21205 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.0004 Mask loss: 0.15185 RPN box loss: 0.01414 RPN score loss: 0.00852 RPN total loss: 0.02266 Total loss: 0.97824 timestamp: 1654966730.9144235 iteration: 67725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05586 FastRCNN class loss: 0.05178 FastRCNN total loss: 0.10764 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.0004 Mask loss: 0.09869 RPN box loss: 0.00457 RPN score loss: 0.00504 RPN total loss: 0.00961 Total loss: 0.80761 timestamp: 1654966734.1188211 iteration: 67730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08877 FastRCNN class loss: 0.06772 FastRCNN total loss: 0.15649 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.0004 Mask loss: 0.16651 RPN box loss: 0.01249 RPN score loss: 0.01001 RPN total loss: 0.0225 Total loss: 0.93718 timestamp: 1654966737.3489087 iteration: 67735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09808 FastRCNN class loss: 0.04039 FastRCNN total loss: 0.13848 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.0004 Mask loss: 0.08914 RPN box loss: 0.01361 RPN score loss: 0.0034 RPN total loss: 0.01701 Total loss: 0.8363 timestamp: 1654966740.5303545 iteration: 67740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13475 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.20404 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.0004 Mask loss: 0.08042 RPN box loss: 0.00317 RPN score loss: 0.00261 RPN total loss: 0.00578 Total loss: 0.88192 timestamp: 1654966743.747443 iteration: 67745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11072 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.18121 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.0004 Mask loss: 0.11149 RPN box loss: 0.02149 RPN score loss: 0.00161 RPN total loss: 0.02311 Total loss: 0.90748 timestamp: 1654966746.9659474 iteration: 67750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08545 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.14747 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.0004 Mask loss: 0.12906 RPN box loss: 0.01485 RPN score loss: 0.00353 RPN total loss: 0.01838 Total loss: 0.88658 timestamp: 1654966750.1143906 iteration: 67755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08157 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.14324 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.0004 Mask loss: 0.13431 RPN box loss: 0.01855 RPN score loss: 0.00886 RPN total loss: 0.02741 Total loss: 0.89664 timestamp: 1654966753.3829386 iteration: 67760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13507 FastRCNN class loss: 0.11581 FastRCNN total loss: 0.25088 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.0004 Mask loss: 0.15625 RPN box loss: 0.02249 RPN score loss: 0.00784 RPN total loss: 0.03033 Total loss: 1.02914 timestamp: 1654966756.5144 iteration: 67765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05149 FastRCNN class loss: 0.04905 FastRCNN total loss: 0.10055 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.0004 Mask loss: 0.08808 RPN box loss: 0.00885 RPN score loss: 0.00232 RPN total loss: 0.01117 Total loss: 0.79147 timestamp: 1654966759.7047648 iteration: 67770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06089 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.13606 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.0004 Mask loss: 0.09527 RPN box loss: 0.01633 RPN score loss: 0.0081 RPN total loss: 0.02443 Total loss: 0.84743 timestamp: 1654966762.930621 iteration: 67775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09031 FastRCNN class loss: 0.04536 FastRCNN total loss: 0.13567 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.0004 Mask loss: 0.13119 RPN box loss: 0.01191 RPN score loss: 0.00405 RPN total loss: 0.01596 Total loss: 0.87448 timestamp: 1654966766.0121574 iteration: 67780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13601 FastRCNN class loss: 0.06299 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.1354 RPN box loss: 0.00731 RPN score loss: 0.00199 RPN total loss: 0.0093 Total loss: 0.93536 timestamp: 1654966769.172798 iteration: 67785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07548 FastRCNN class loss: 0.09422 FastRCNN total loss: 0.1697 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.1466 RPN box loss: 0.00692 RPN score loss: 0.00688 RPN total loss: 0.01381 Total loss: 0.92177 timestamp: 1654966772.3378718 iteration: 67790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09287 FastRCNN class loss: 0.06212 FastRCNN total loss: 0.15499 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.15693 RPN box loss: 0.00438 RPN score loss: 0.00201 RPN total loss: 0.00639 Total loss: 0.90998 timestamp: 1654966775.4646251 iteration: 67795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08905 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.15565 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.09887 RPN box loss: 0.0104 RPN score loss: 0.0008 RPN total loss: 0.0112 Total loss: 0.85738 timestamp: 1654966778.6512988 iteration: 67800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08578 FastRCNN class loss: 0.04836 FastRCNN total loss: 0.13414 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.12114 RPN box loss: 0.01297 RPN score loss: 0.0051 RPN total loss: 0.01807 Total loss: 0.86501 timestamp: 1654966781.8621128 iteration: 67805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10573 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.16209 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.11127 RPN box loss: 0.03922 RPN score loss: 0.00272 RPN total loss: 0.04194 Total loss: 0.90696 timestamp: 1654966785.0078638 iteration: 67810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09785 FastRCNN class loss: 0.03991 FastRCNN total loss: 0.13776 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.0004 Mask loss: 0.10828 RPN box loss: 0.01305 RPN score loss: 0.00729 RPN total loss: 0.02034 Total loss: 0.85804 timestamp: 1654966788.1602454 iteration: 67815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10098 FastRCNN class loss: 0.06383 FastRCNN total loss: 0.16481 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.0004 Mask loss: 0.10377 RPN box loss: 0.00849 RPN score loss: 0.00534 RPN total loss: 0.01383 Total loss: 0.87406 timestamp: 1654966791.3361478 iteration: 67820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09204 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.14151 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.0004 Mask loss: 0.12322 RPN box loss: 0.01286 RPN score loss: 0.00565 RPN total loss: 0.01851 Total loss: 0.87489 timestamp: 1654966794.490571 iteration: 67825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06441 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.13874 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.0004 Mask loss: 0.16487 RPN box loss: 0.01 RPN score loss: 0.00248 RPN total loss: 0.01248 Total loss: 0.90774 timestamp: 1654966797.7514307 iteration: 67830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09019 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.14779 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.0004 Mask loss: 0.09908 RPN box loss: 0.00686 RPN score loss: 0.00411 RPN total loss: 0.01097 Total loss: 0.84949 timestamp: 1654966800.9590552 iteration: 67835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07425 FastRCNN class loss: 0.07652 FastRCNN total loss: 0.15077 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.0004 Mask loss: 0.10608 RPN box loss: 0.00973 RPN score loss: 0.00201 RPN total loss: 0.01174 Total loss: 0.86023 timestamp: 1654966804.1959841 iteration: 67840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07535 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.13105 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.0004 Mask loss: 0.14349 RPN box loss: 0.01141 RPN score loss: 0.00249 RPN total loss: 0.01389 Total loss: 0.88008 timestamp: 1654966807.4168043 iteration: 67845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1146 FastRCNN class loss: 0.07478 FastRCNN total loss: 0.18938 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.0004 Mask loss: 0.10877 RPN box loss: 0.01196 RPN score loss: 0.00232 RPN total loss: 0.01428 Total loss: 0.90407 timestamp: 1654966810.6276212 iteration: 67850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09644 FastRCNN class loss: 0.06225 FastRCNN total loss: 0.15869 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.0004 Mask loss: 0.13058 RPN box loss: 0.03781 RPN score loss: 0.00407 RPN total loss: 0.04188 Total loss: 0.9228 timestamp: 1654966813.829398 iteration: 67855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.0389 FastRCNN total loss: 0.13208 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.0004 Mask loss: 0.10439 RPN box loss: 0.00988 RPN score loss: 0.00362 RPN total loss: 0.0135 Total loss: 0.84161 timestamp: 1654966816.9493558 iteration: 67860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05316 FastRCNN class loss: 0.03725 FastRCNN total loss: 0.09041 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.0004 Mask loss: 0.0941 RPN box loss: 0.009 RPN score loss: 0.00157 RPN total loss: 0.01057 Total loss: 0.78673 timestamp: 1654966820.1813235 iteration: 67865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1202 FastRCNN class loss: 0.07678 FastRCNN total loss: 0.19698 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.0004 Mask loss: 0.13961 RPN box loss: 0.02305 RPN score loss: 0.01062 RPN total loss: 0.03367 Total loss: 0.9619 timestamp: 1654966823.3905737 iteration: 67870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07254 FastRCNN class loss: 0.0556 FastRCNN total loss: 0.12814 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.0004 Mask loss: 0.12996 RPN box loss: 0.00855 RPN score loss: 0.00215 RPN total loss: 0.01071 Total loss: 0.86044 timestamp: 1654966826.6818852 iteration: 67875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07229 FastRCNN class loss: 0.0378 FastRCNN total loss: 0.11009 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.0004 Mask loss: 0.11849 RPN box loss: 0.00871 RPN score loss: 0.00149 RPN total loss: 0.0102 Total loss: 0.83041 timestamp: 1654966829.9137266 iteration: 67880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05285 FastRCNN class loss: 0.04272 FastRCNN total loss: 0.09557 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.0004 Mask loss: 0.15913 RPN box loss: 0.00613 RPN score loss: 0.00623 RPN total loss: 0.01236 Total loss: 0.85869 timestamp: 1654966833.1435144 iteration: 67885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08268 FastRCNN class loss: 0.06252 FastRCNN total loss: 0.1452 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.0004 Mask loss: 0.18421 RPN box loss: 0.00858 RPN score loss: 0.00445 RPN total loss: 0.01302 Total loss: 0.93406 timestamp: 1654966836.297929 iteration: 67890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07707 FastRCNN class loss: 0.06652 FastRCNN total loss: 0.14359 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.0004 Mask loss: 0.13263 RPN box loss: 0.01299 RPN score loss: 0.00468 RPN total loss: 0.01766 Total loss: 0.88551 timestamp: 1654966839.4993093 iteration: 67895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05254 FastRCNN class loss: 0.04962 FastRCNN total loss: 0.10216 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.0004 Mask loss: 0.11202 RPN box loss: 0.01409 RPN score loss: 0.00371 RPN total loss: 0.0178 Total loss: 0.82361 timestamp: 1654966842.7025125 iteration: 67900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0636 FastRCNN class loss: 0.0858 FastRCNN total loss: 0.1494 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.0004 Mask loss: 0.12285 RPN box loss: 0.00496 RPN score loss: 0.00057 RPN total loss: 0.00554 Total loss: 0.86942 timestamp: 1654966845.9038773 iteration: 67905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10868 FastRCNN class loss: 0.08379 FastRCNN total loss: 0.19247 L1 loss: 0.0000e+00 L2 loss: 0.59162 Learning rate: 0.0004 Mask loss: 0.1166 RPN box loss: 0.01524 RPN score loss: 0.00916 RPN total loss: 0.0244 Total loss: 0.9251 timestamp: 1654966849.028625 iteration: 67910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08073 FastRCNN class loss: 0.03959 FastRCNN total loss: 0.12032 L1 loss: 0.0000e+00 L2 loss: 0.59162 Learning rate: 0.0004 Mask loss: 0.09246 RPN box loss: 0.01048 RPN score loss: 0.00312 RPN total loss: 0.0136 Total loss: 0.818 timestamp: 1654966852.197861 iteration: 67915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13253 FastRCNN class loss: 0.07226 FastRCNN total loss: 0.20479 L1 loss: 0.0000e+00 L2 loss: 0.59162 Learning rate: 0.0004 Mask loss: 0.13981 RPN box loss: 0.01705 RPN score loss: 0.00382 RPN total loss: 0.02086 Total loss: 0.95709 timestamp: 1654966855.3481731 iteration: 67920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11211 FastRCNN class loss: 0.05242 FastRCNN total loss: 0.16453 L1 loss: 0.0000e+00 L2 loss: 0.59162 Learning rate: 0.0004 Mask loss: 0.11105 RPN box loss: 0.00708 RPN score loss: 0.00173 RPN total loss: 0.00881 Total loss: 0.876 timestamp: 1654966858.5519822 iteration: 67925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06907 FastRCNN class loss: 0.05383 FastRCNN total loss: 0.1229 L1 loss: 0.0000e+00 L2 loss: 0.59162 Learning rate: 0.0004 Mask loss: 0.11749 RPN box loss: 0.00521 RPN score loss: 0.00627 RPN total loss: 0.01148 Total loss: 0.84348 timestamp: 1654966861.7728066 iteration: 67930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09322 FastRCNN class loss: 0.0537 FastRCNN total loss: 0.14691 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.0004 Mask loss: 0.11816 RPN box loss: 0.01393 RPN score loss: 0.00261 RPN total loss: 0.01655 Total loss: 0.87324 timestamp: 1654966864.990936 iteration: 67935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07234 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.13988 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.0004 Mask loss: 0.10173 RPN box loss: 0.0076 RPN score loss: 0.00159 RPN total loss: 0.00919 Total loss: 0.84242 timestamp: 1654966868.1920986 iteration: 67940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07885 FastRCNN class loss: 0.0558 FastRCNN total loss: 0.13465 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.0004 Mask loss: 0.10035 RPN box loss: 0.00506 RPN score loss: 0.00284 RPN total loss: 0.0079 Total loss: 0.83451 timestamp: 1654966871.3285933 iteration: 67945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09514 FastRCNN class loss: 0.0459 FastRCNN total loss: 0.14104 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.0004 Mask loss: 0.10118 RPN box loss: 0.01521 RPN score loss: 0.00109 RPN total loss: 0.0163 Total loss: 0.85013 timestamp: 1654966874.5429697 iteration: 67950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04704 FastRCNN class loss: 0.0415 FastRCNN total loss: 0.08854 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.0004 Mask loss: 0.10143 RPN box loss: 0.00498 RPN score loss: 0.00137 RPN total loss: 0.00634 Total loss: 0.78792 timestamp: 1654966877.744623 iteration: 67955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09452 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.15966 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.0004 Mask loss: 0.13353 RPN box loss: 0.0261 RPN score loss: 0.00863 RPN total loss: 0.03473 Total loss: 0.91953 timestamp: 1654966880.8940403 iteration: 67960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14848 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.20654 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.0004 Mask loss: 0.14195 RPN box loss: 0.04517 RPN score loss: 0.00616 RPN total loss: 0.05133 Total loss: 0.99141 timestamp: 1654966884.0889091 iteration: 67965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0504 FastRCNN class loss: 0.04489 FastRCNN total loss: 0.09529 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.0004 Mask loss: 0.07928 RPN box loss: 0.01064 RPN score loss: 0.00266 RPN total loss: 0.0133 Total loss: 0.77947 timestamp: 1654966887.2678163 iteration: 67970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08392 FastRCNN class loss: 0.0516 FastRCNN total loss: 0.13552 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.0004 Mask loss: 0.11739 RPN box loss: 0.01062 RPN score loss: 0.00365 RPN total loss: 0.01426 Total loss: 0.85877 timestamp: 1654966890.4976916 iteration: 67975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11352 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.18218 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.0004 Mask loss: 0.11375 RPN box loss: 0.0261 RPN score loss: 0.00294 RPN total loss: 0.02904 Total loss: 0.91657 timestamp: 1654966893.6474476 iteration: 67980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08759 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.15329 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.0004 Mask loss: 0.12403 RPN box loss: 0.01304 RPN score loss: 0.00804 RPN total loss: 0.02108 Total loss: 0.88999 timestamp: 1654966896.8547108 iteration: 67985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07927 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.15881 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.0004 Mask loss: 0.12669 RPN box loss: 0.00615 RPN score loss: 0.00944 RPN total loss: 0.01559 Total loss: 0.89268 timestamp: 1654966899.9769537 iteration: 67990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12666 FastRCNN class loss: 0.08761 FastRCNN total loss: 0.21426 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.11654 RPN box loss: 0.00839 RPN score loss: 0.00648 RPN total loss: 0.01488 Total loss: 0.93727 timestamp: 1654966903.2594993 iteration: 67995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07228 FastRCNN class loss: 0.05664 FastRCNN total loss: 0.12892 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.12146 RPN box loss: 0.01957 RPN score loss: 0.0071 RPN total loss: 0.02666 Total loss: 0.86863 timestamp: 1654966906.40141 iteration: 68000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0538 FastRCNN class loss: 0.03489 FastRCNN total loss: 0.08869 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.13286 RPN box loss: 0.00903 RPN score loss: 0.00617 RPN total loss: 0.0152 Total loss: 0.82833 timestamp: 1654966909.561868 iteration: 68005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09707 FastRCNN class loss: 0.05694 FastRCNN total loss: 0.154 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.08607 RPN box loss: 0.01133 RPN score loss: 0.00234 RPN total loss: 0.01367 Total loss: 0.84533 timestamp: 1654966912.7477958 iteration: 68010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11299 FastRCNN class loss: 0.07083 FastRCNN total loss: 0.18382 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.16899 RPN box loss: 0.02989 RPN score loss: 0.00351 RPN total loss: 0.0334 Total loss: 0.9778 timestamp: 1654966915.9143012 iteration: 68015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10069 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.18923 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.0861 RPN box loss: 0.01991 RPN score loss: 0.00523 RPN total loss: 0.02514 Total loss: 0.89204 timestamp: 1654966919.1677473 iteration: 68020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06894 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.13469 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.0004 Mask loss: 0.12307 RPN box loss: 0.01171 RPN score loss: 0.00582 RPN total loss: 0.01753 Total loss: 0.86687 timestamp: 1654966922.341899 iteration: 68025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1191 FastRCNN class loss: 0.0746 FastRCNN total loss: 0.1937 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.0004 Mask loss: 0.10461 RPN box loss: 0.01534 RPN score loss: 0.00504 RPN total loss: 0.02038 Total loss: 0.91027 timestamp: 1654966925.495441 iteration: 68030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13096 FastRCNN class loss: 0.07731 FastRCNN total loss: 0.20827 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.0004 Mask loss: 0.115 RPN box loss: 0.00902 RPN score loss: 0.00552 RPN total loss: 0.01454 Total loss: 0.92939 timestamp: 1654966928.6795115 iteration: 68035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08441 FastRCNN class loss: 0.11048 FastRCNN total loss: 0.19489 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.0004 Mask loss: 0.16068 RPN box loss: 0.01675 RPN score loss: 0.01699 RPN total loss: 0.03374 Total loss: 0.98089 timestamp: 1654966931.818794 iteration: 68040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07619 FastRCNN class loss: 0.04834 FastRCNN total loss: 0.12453 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.0004 Mask loss: 0.07499 RPN box loss: 0.00346 RPN score loss: 0.0042 RPN total loss: 0.00766 Total loss: 0.79875 timestamp: 1654966935.0445886 iteration: 68045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11706 FastRCNN class loss: 0.07152 FastRCNN total loss: 0.18857 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.0004 Mask loss: 0.13517 RPN box loss: 0.00896 RPN score loss: 0.00313 RPN total loss: 0.01209 Total loss: 0.92741 timestamp: 1654966938.2003925 iteration: 68050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06557 FastRCNN class loss: 0.05115 FastRCNN total loss: 0.11671 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.0004 Mask loss: 0.10581 RPN box loss: 0.00503 RPN score loss: 0.00174 RPN total loss: 0.00677 Total loss: 0.82087 timestamp: 1654966941.38236 iteration: 68055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.04764 FastRCNN total loss: 0.13076 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.0004 Mask loss: 0.13536 RPN box loss: 0.01532 RPN score loss: 0.00275 RPN total loss: 0.01807 Total loss: 0.87577 timestamp: 1654966944.5557027 iteration: 68060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05295 FastRCNN class loss: 0.06273 FastRCNN total loss: 0.11568 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.0004 Mask loss: 0.07447 RPN box loss: 0.00864 RPN score loss: 0.00344 RPN total loss: 0.01207 Total loss: 0.79379 timestamp: 1654966947.733996 iteration: 68065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1188 FastRCNN class loss: 0.11536 FastRCNN total loss: 0.23417 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.0004 Mask loss: 0.13694 RPN box loss: 0.03031 RPN score loss: 0.00565 RPN total loss: 0.03596 Total loss: 0.99864 timestamp: 1654966950.9733438 iteration: 68070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05272 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.12391 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.0004 Mask loss: 0.15843 RPN box loss: 0.01342 RPN score loss: 0.00184 RPN total loss: 0.01526 Total loss: 0.88917 timestamp: 1654966954.1639323 iteration: 68075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07393 FastRCNN class loss: 0.07009 FastRCNN total loss: 0.14401 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.0004 Mask loss: 0.15297 RPN box loss: 0.01513 RPN score loss: 0.0009 RPN total loss: 0.01603 Total loss: 0.90458 timestamp: 1654966957.3347073 iteration: 68080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11444 FastRCNN class loss: 0.08869 FastRCNN total loss: 0.20312 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.0004 Mask loss: 0.15009 RPN box loss: 0.01326 RPN score loss: 0.00207 RPN total loss: 0.01532 Total loss: 0.9601 timestamp: 1654966960.4867795 iteration: 68085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06658 FastRCNN class loss: 0.04842 FastRCNN total loss: 0.115 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.0004 Mask loss: 0.20597 RPN box loss: 0.00834 RPN score loss: 0.00129 RPN total loss: 0.00963 Total loss: 0.92216 timestamp: 1654966963.6120813 iteration: 68090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06566 FastRCNN class loss: 0.04738 FastRCNN total loss: 0.11303 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.0004 Mask loss: 0.1029 RPN box loss: 0.02051 RPN score loss: 0.00223 RPN total loss: 0.02274 Total loss: 0.83024 timestamp: 1654966966.8386304 iteration: 68095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04288 FastRCNN class loss: 0.06578 FastRCNN total loss: 0.10866 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.0004 Mask loss: 0.09343 RPN box loss: 0.01297 RPN score loss: 0.00435 RPN total loss: 0.01732 Total loss: 0.81097 timestamp: 1654966970.0668812 iteration: 68100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05422 FastRCNN class loss: 0.04395 FastRCNN total loss: 0.09818 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.0004 Mask loss: 0.1164 RPN box loss: 0.01002 RPN score loss: 0.00113 RPN total loss: 0.01115 Total loss: 0.81728 timestamp: 1654966973.2053952 iteration: 68105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08393 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.15508 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.0004 Mask loss: 0.16594 RPN box loss: 0.01879 RPN score loss: 0.00844 RPN total loss: 0.02723 Total loss: 0.93981 timestamp: 1654966976.3909552 iteration: 68110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0929 FastRCNN class loss: 0.05555 FastRCNN total loss: 0.14845 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.0004 Mask loss: 0.13847 RPN box loss: 0.01507 RPN score loss: 0.0027 RPN total loss: 0.01777 Total loss: 0.89624 timestamp: 1654966979.6144648 iteration: 68115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10373 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.16393 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.0004 Mask loss: 0.11134 RPN box loss: 0.01479 RPN score loss: 0.00387 RPN total loss: 0.01866 Total loss: 0.88548 timestamp: 1654966982.774522 iteration: 68120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10124 FastRCNN class loss: 0.06684 FastRCNN total loss: 0.16808 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.0004 Mask loss: 0.11705 RPN box loss: 0.01 RPN score loss: 0.00634 RPN total loss: 0.01634 Total loss: 0.89303 timestamp: 1654966985.9729078 iteration: 68125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11029 FastRCNN class loss: 0.12094 FastRCNN total loss: 0.23122 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.0004 Mask loss: 0.16184 RPN box loss: 0.03405 RPN score loss: 0.0094 RPN total loss: 0.04345 Total loss: 1.02806 timestamp: 1654966989.1759822 iteration: 68130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10861 FastRCNN class loss: 0.06526 FastRCNN total loss: 0.17387 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.0004 Mask loss: 0.08557 RPN box loss: 0.01131 RPN score loss: 0.00194 RPN total loss: 0.01325 Total loss: 0.86423 timestamp: 1654966992.4077704 iteration: 68135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06305 FastRCNN class loss: 0.03905 FastRCNN total loss: 0.10211 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.0004 Mask loss: 0.11724 RPN box loss: 0.00384 RPN score loss: 0.00283 RPN total loss: 0.00667 Total loss: 0.81756 timestamp: 1654966995.5411875 iteration: 68140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06081 FastRCNN class loss: 0.05012 FastRCNN total loss: 0.11093 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.0004 Mask loss: 0.10563 RPN box loss: 0.00822 RPN score loss: 0.00398 RPN total loss: 0.0122 Total loss: 0.8203 timestamp: 1654966998.743017 iteration: 68145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06881 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.12906 L1 loss: 0.0000e+00 L2 loss: 0.59154 Learning rate: 0.0004 Mask loss: 0.22954 RPN box loss: 0.02033 RPN score loss: 0.00377 RPN total loss: 0.0241 Total loss: 0.97424 timestamp: 1654967001.9116628 iteration: 68150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.13285 FastRCNN total loss: 0.26045 L1 loss: 0.0000e+00 L2 loss: 0.59154 Learning rate: 0.0004 Mask loss: 0.13051 RPN box loss: 0.00771 RPN score loss: 0.00434 RPN total loss: 0.01205 Total loss: 0.99455 timestamp: 1654967005.1471226 iteration: 68155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04651 FastRCNN class loss: 0.03878 FastRCNN total loss: 0.08529 L1 loss: 0.0000e+00 L2 loss: 0.59154 Learning rate: 0.0004 Mask loss: 0.11832 RPN box loss: 0.00724 RPN score loss: 0.00417 RPN total loss: 0.0114 Total loss: 0.80655 timestamp: 1654967008.3736668 iteration: 68160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12766 FastRCNN class loss: 0.08355 FastRCNN total loss: 0.21121 L1 loss: 0.0000e+00 L2 loss: 0.59154 Learning rate: 0.0004 Mask loss: 0.13023 RPN box loss: 0.0174 RPN score loss: 0.0043 RPN total loss: 0.0217 Total loss: 0.95467 timestamp: 1654967011.5616946 iteration: 68165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06401 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.11712 L1 loss: 0.0000e+00 L2 loss: 0.59154 Learning rate: 0.0004 Mask loss: 0.12694 RPN box loss: 0.00779 RPN score loss: 0.00753 RPN total loss: 0.01532 Total loss: 0.85092 timestamp: 1654967014.7174063 iteration: 68170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09705 FastRCNN class loss: 0.05022 FastRCNN total loss: 0.14726 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.0004 Mask loss: 0.17991 RPN box loss: 0.01733 RPN score loss: 0.01741 RPN total loss: 0.03475 Total loss: 0.95346 timestamp: 1654967017.9236786 iteration: 68175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06964 FastRCNN class loss: 0.07876 FastRCNN total loss: 0.1484 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.0004 Mask loss: 0.11503 RPN box loss: 0.00974 RPN score loss: 0.00192 RPN total loss: 0.01166 Total loss: 0.86662 timestamp: 1654967021.0839684 iteration: 68180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08754 FastRCNN class loss: 0.10307 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.0004 Mask loss: 0.12044 RPN box loss: 0.01166 RPN score loss: 0.00648 RPN total loss: 0.01813 Total loss: 0.92071 timestamp: 1654967024.2457485 iteration: 68185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07092 FastRCNN class loss: 0.04513 FastRCNN total loss: 0.11605 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.0004 Mask loss: 0.11467 RPN box loss: 0.0039 RPN score loss: 0.00154 RPN total loss: 0.00544 Total loss: 0.82769 timestamp: 1654967027.487392 iteration: 68190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0939 FastRCNN class loss: 0.06585 FastRCNN total loss: 0.15975 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.0004 Mask loss: 0.11734 RPN box loss: 0.00705 RPN score loss: 0.00733 RPN total loss: 0.01437 Total loss: 0.88299 timestamp: 1654967030.6621468 iteration: 68195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06189 FastRCNN class loss: 0.03397 FastRCNN total loss: 0.09586 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.0004 Mask loss: 0.1097 RPN box loss: 0.00485 RPN score loss: 0.00468 RPN total loss: 0.00953 Total loss: 0.80662 timestamp: 1654967033.796794 iteration: 68200 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06772 FastRCNN class loss: 0.06684 FastRCNN total loss: 0.13456 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.0004 Mask loss: 0.12432 RPN box loss: 0.02642 RPN score loss: 0.00648 RPN total loss: 0.03291 Total loss: 0.88332 timestamp: 1654967036.9659972 iteration: 68205 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07711 FastRCNN class loss: 0.06612 FastRCNN total loss: 0.14322 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.0004 Mask loss: 0.12602 RPN box loss: 0.01633 RPN score loss: 0.01052 RPN total loss: 0.02685 Total loss: 0.88762 timestamp: 1654967040.177944 iteration: 68210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07352 FastRCNN class loss: 0.05521 FastRCNN total loss: 0.12873 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.0004 Mask loss: 0.11803 RPN box loss: 0.01787 RPN score loss: 0.00083 RPN total loss: 0.0187 Total loss: 0.85697 timestamp: 1654967043.314007 iteration: 68215 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11238 FastRCNN class loss: 0.03672 FastRCNN total loss: 0.1491 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.0004 Mask loss: 0.07688 RPN box loss: 0.00971 RPN score loss: 0.00297 RPN total loss: 0.01268 Total loss: 0.83017 timestamp: 1654967046.4824429 iteration: 68220 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09291 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.15983 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.0004 Mask loss: 0.12318 RPN box loss: 0.00992 RPN score loss: 0.0023 RPN total loss: 0.01222 Total loss: 0.88675 timestamp: 1654967049.7033267 iteration: 68225 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07669 FastRCNN class loss: 0.06354 FastRCNN total loss: 0.14023 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.0004 Mask loss: 0.13013 RPN box loss: 0.01124 RPN score loss: 0.00366 RPN total loss: 0.01489 Total loss: 0.87677 timestamp: 1654967052.9331598 iteration: 68230 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05966 FastRCNN class loss: 0.07052 FastRCNN total loss: 0.13017 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.0004 Mask loss: 0.12448 RPN box loss: 0.00494 RPN score loss: 0.00169 RPN total loss: 0.00662 Total loss: 0.85279 timestamp: 1654967056.1609745 iteration: 68235 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05288 FastRCNN class loss: 0.0504 FastRCNN total loss: 0.10328 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.0004 Mask loss: 0.11485 RPN box loss: 0.00665 RPN score loss: 0.00138 RPN total loss: 0.00803 Total loss: 0.81768 timestamp: 1654967059.3454375 iteration: 68240 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08512 FastRCNN class loss: 0.07008 FastRCNN total loss: 0.15519 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.0004 Mask loss: 0.15079 RPN box loss: 0.00688 RPN score loss: 0.00458 RPN total loss: 0.01147 Total loss: 0.90896 timestamp: 1654967062.621378 iteration: 68245 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08567 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.14505 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.0004 Mask loss: 0.10058 RPN box loss: 0.00852 RPN score loss: 0.00384 RPN total loss: 0.01236 Total loss: 0.8495 timestamp: 1654967065.717466 iteration: 68250 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17666 FastRCNN class loss: 0.12038 FastRCNN total loss: 0.29704 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.0004 Mask loss: 0.21128 RPN box loss: 0.00787 RPN score loss: 0.00687 RPN total loss: 0.01474 Total loss: 1.11456 timestamp: 1654967068.9871562 iteration: 68255 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05576 FastRCNN class loss: 0.0361 FastRCNN total loss: 0.09186 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.0004 Mask loss: 0.09817 RPN box loss: 0.00536 RPN score loss: 0.00407 RPN total loss: 0.00943 Total loss: 0.79097 timestamp: 1654967072.1853755 iteration: 68260 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.05836 FastRCNN total loss: 0.15904 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.0004 Mask loss: 0.12004 RPN box loss: 0.01069 RPN score loss: 0.00353 RPN total loss: 0.01421 Total loss: 0.8848 timestamp: 1654967075.3846312 iteration: 68265 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15012 FastRCNN class loss: 0.05543 FastRCNN total loss: 0.20555 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.0004 Mask loss: 0.12723 RPN box loss: 0.00944 RPN score loss: 0.00479 RPN total loss: 0.01423 Total loss: 0.93851 timestamp: 1654967078.5496712 iteration: 68270 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10732 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.1906 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.0004 Mask loss: 0.19663 RPN box loss: 0.01496 RPN score loss: 0.00928 RPN total loss: 0.02424 Total loss: 1.00297 timestamp: 1654967081.7282848 iteration: 68275 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09264 FastRCNN class loss: 0.08409 FastRCNN total loss: 0.17673 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.0004 Mask loss: 0.14191 RPN box loss: 0.00531 RPN score loss: 0.00152 RPN total loss: 0.00682 Total loss: 0.91696 timestamp: 1654967084.9970758 iteration: 68280 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10545 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.16291 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.0004 Mask loss: 0.11927 RPN box loss: 0.00872 RPN score loss: 0.00293 RPN total loss: 0.01165 Total loss: 0.88532 timestamp: 1654967088.1506057 iteration: 68285 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10854 FastRCNN class loss: 0.04883 FastRCNN total loss: 0.15736 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.0004 Mask loss: 0.09546 RPN box loss: 0.0098 RPN score loss: 0.00286 RPN total loss: 0.01265 Total loss: 0.85698 timestamp: 1654967091.3941858 iteration: 68290 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12225 FastRCNN class loss: 0.08809 FastRCNN total loss: 0.21034 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.0004 Mask loss: 0.20277 RPN box loss: 0.01468 RPN score loss: 0.00165 RPN total loss: 0.01632 Total loss: 1.02093 timestamp: 1654967094.5243797 iteration: 68295 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09721 FastRCNN class loss: 0.09113 FastRCNN total loss: 0.18834 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.0004 Mask loss: 0.17246 RPN box loss: 0.02067 RPN score loss: 0.01422 RPN total loss: 0.03489 Total loss: 0.98719 timestamp: 1654967097.7236621 iteration: 68300 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08839 FastRCNN class loss: 0.11872 FastRCNN total loss: 0.20711 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.0004 Mask loss: 0.15781 RPN box loss: 0.03071 RPN score loss: 0.01085 RPN total loss: 0.04156 Total loss: 0.99797 timestamp: 1654967100.9261587 iteration: 68305 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12293 FastRCNN class loss: 0.06459 FastRCNN total loss: 0.18753 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.0004 Mask loss: 0.09758 RPN box loss: 0.03426 RPN score loss: 0.0006 RPN total loss: 0.03486 Total loss: 0.91146 timestamp: 1654967104.2495577 iteration: 68310 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13712 FastRCNN class loss: 0.12584 FastRCNN total loss: 0.26296 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.0004 Mask loss: 0.18289 RPN box loss: 0.01938 RPN score loss: 0.01769 RPN total loss: 0.03707 Total loss: 1.07441 timestamp: 1654967107.447887 iteration: 68315 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13278 FastRCNN class loss: 0.11243 FastRCNN total loss: 0.24521 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.0004 Mask loss: 0.12544 RPN box loss: 0.02072 RPN score loss: 0.01292 RPN total loss: 0.03364 Total loss: 0.99578 timestamp: 1654967110.6266873 iteration: 68320 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08161 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.14329 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.0004 Mask loss: 0.1181 RPN box loss: 0.0082 RPN score loss: 0.00343 RPN total loss: 0.01163 Total loss: 0.86451 timestamp: 1654967113.8293793 iteration: 68325 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04437 FastRCNN class loss: 0.05315 FastRCNN total loss: 0.09752 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.0004 Mask loss: 0.08843 RPN box loss: 0.00624 RPN score loss: 0.00431 RPN total loss: 0.01055 Total loss: 0.78798 timestamp: 1654967117.0155108 iteration: 68330 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06131 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.13148 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.0004 Mask loss: 0.11738 RPN box loss: 0.0078 RPN score loss: 0.00029 RPN total loss: 0.00809 Total loss: 0.84843 timestamp: 1654967120.2502856 iteration: 68335 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06522 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.12476 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.0004 Mask loss: 0.12631 RPN box loss: 0.02792 RPN score loss: 0.01096 RPN total loss: 0.03887 Total loss: 0.88142 timestamp: 1654967123.4220974 iteration: 68340 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07678 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.13537 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.0004 Mask loss: 0.13019 RPN box loss: 0.0051 RPN score loss: 0.00289 RPN total loss: 0.00799 Total loss: 0.86502 timestamp: 1654967126.6501102 iteration: 68345 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05887 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.11792 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.0004 Mask loss: 0.15217 RPN box loss: 0.00884 RPN score loss: 0.00208 RPN total loss: 0.01092 Total loss: 0.87249 timestamp: 1654967129.7947738 iteration: 68350 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12389 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.20306 L1 loss: 0.0000e+00 L2 loss: 0.59147 Learning rate: 0.0004 Mask loss: 0.14553 RPN box loss: 0.01588 RPN score loss: 0.00333 RPN total loss: 0.0192 Total loss: 0.95927 timestamp: 1654967132.9540546 iteration: 68355 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11295 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.17852 L1 loss: 0.0000e+00 L2 loss: 0.59147 Learning rate: 0.0004 Mask loss: 0.13999 RPN box loss: 0.01473 RPN score loss: 0.00506 RPN total loss: 0.01979 Total loss: 0.92977 timestamp: 1654967136.154238 iteration: 68360 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06796 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.1397 L1 loss: 0.0000e+00 L2 loss: 0.59147 Learning rate: 0.0004 Mask loss: 0.11 RPN box loss: 0.00882 RPN score loss: 0.00167 RPN total loss: 0.01049 Total loss: 0.85166 timestamp: 1654967139.3572059 iteration: 68365 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03911 FastRCNN class loss: 0.04206 FastRCNN total loss: 0.08117 L1 loss: 0.0000e+00 L2 loss: 0.59147 Learning rate: 0.0004 Mask loss: 0.10875 RPN box loss: 0.01434 RPN score loss: 0.00066 RPN total loss: 0.01499 Total loss: 0.79638 timestamp: 1654967142.5223222 iteration: 68370 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06345 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.13825 L1 loss: 0.0000e+00 L2 loss: 0.59147 Learning rate: 0.0004 Mask loss: 0.10834 RPN box loss: 0.00395 RPN score loss: 0.00133 RPN total loss: 0.00528 Total loss: 0.84333 timestamp: 1654967145.7362714 iteration: 68375 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07768 FastRCNN class loss: 0.04426 FastRCNN total loss: 0.12194 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.0004 Mask loss: 0.11661 RPN box loss: 0.00678 RPN score loss: 0.0034 RPN total loss: 0.01019 Total loss: 0.8402 timestamp: 1654967148.9158251 iteration: 68380 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08853 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.0004 Mask loss: 0.13818 RPN box loss: 0.00842 RPN score loss: 0.00931 RPN total loss: 0.01773 Total loss: 0.91211 timestamp: 1654967152.032819 iteration: 68385 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11824 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.18645 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.0004 Mask loss: 0.15218 RPN box loss: 0.0053 RPN score loss: 0.00413 RPN total loss: 0.00943 Total loss: 0.93952 timestamp: 1654967155.2402496 iteration: 68390 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06825 FastRCNN class loss: 0.05909 FastRCNN total loss: 0.12735 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.0004 Mask loss: 0.13812 RPN box loss: 0.01355 RPN score loss: 0.0065 RPN total loss: 0.02004 Total loss: 0.87697 timestamp: 1654967158.3265154 iteration: 68395 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.04223 FastRCNN total loss: 0.13629 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.0004 Mask loss: 0.09055 RPN box loss: 0.0043 RPN score loss: 0.00517 RPN total loss: 0.00947 Total loss: 0.82777 timestamp: 1654967161.4557674 iteration: 68400 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11423 FastRCNN class loss: 0.08909 FastRCNN total loss: 0.20332 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.0004 Mask loss: 0.16536 RPN box loss: 0.03243 RPN score loss: 0.01176 RPN total loss: 0.04419 Total loss: 1.00432 timestamp: 1654967164.6258407 iteration: 68405 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03977 FastRCNN class loss: 0.04651 FastRCNN total loss: 0.08628 L1 loss: 0.0000e+00 L2 loss: 0.59145 Learning rate: 0.0004 Mask loss: 0.09929 RPN box loss: 0.00659 RPN score loss: 0.00147 RPN total loss: 0.00806 Total loss: 0.78509 timestamp: 1654967167.8260365 iteration: 68410 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11875 FastRCNN class loss: 0.1088 FastRCNN total loss: 0.22755 L1 loss: 0.0000e+00 L2 loss: 0.59145 Learning rate: 0.0004 Mask loss: 0.13853 RPN box loss: 0.01783 RPN score loss: 0.01583 RPN total loss: 0.03366 Total loss: 0.99119 timestamp: 1654967170.961951 iteration: 68415 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13284 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.23199 L1 loss: 0.0000e+00 L2 loss: 0.59145 Learning rate: 0.0004 Mask loss: 0.14785 RPN box loss: 0.03397 RPN score loss: 0.00798 RPN total loss: 0.04195 Total loss: 1.01324 timestamp: 1654967174.2066524 iteration: 68420 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06665 FastRCNN class loss: 0.07861 FastRCNN total loss: 0.14526 L1 loss: 0.0000e+00 L2 loss: 0.59145 Learning rate: 0.0004 Mask loss: 0.14613 RPN box loss: 0.0246 RPN score loss: 0.00792 RPN total loss: 0.03252 Total loss: 0.91536 timestamp: 1654967177.3958967 iteration: 68425 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05795 FastRCNN class loss: 0.05052 FastRCNN total loss: 0.10847 L1 loss: 0.0000e+00 L2 loss: 0.59145 Learning rate: 0.0004 Mask loss: 0.07717 RPN box loss: 0.01193 RPN score loss: 0.00109 RPN total loss: 0.01302 Total loss: 0.79011 timestamp: 1654967180.5648065 iteration: 68430 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14683 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.22275 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.17862 RPN box loss: 0.01538 RPN score loss: 0.00215 RPN total loss: 0.01753 Total loss: 1.01034 timestamp: 1654967183.765767 iteration: 68435 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.101 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.17202 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.14706 RPN box loss: 0.01324 RPN score loss: 0.00827 RPN total loss: 0.0215 Total loss: 0.93203 timestamp: 1654967186.930746 iteration: 68440 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06145 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.10703 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.11 RPN box loss: 0.00443 RPN score loss: 0.00464 RPN total loss: 0.00906 Total loss: 0.81753 timestamp: 1654967190.1144564 iteration: 68445 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09808 FastRCNN class loss: 0.05829 FastRCNN total loss: 0.15637 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.0875 RPN box loss: 0.02024 RPN score loss: 0.00606 RPN total loss: 0.0263 Total loss: 0.86161 timestamp: 1654967193.2686317 iteration: 68450 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18471 FastRCNN class loss: 0.07435 FastRCNN total loss: 0.25906 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.16036 RPN box loss: 0.01551 RPN score loss: 0.00151 RPN total loss: 0.01702 Total loss: 1.02788 timestamp: 1654967196.4324856 iteration: 68455 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0962 FastRCNN class loss: 0.09421 FastRCNN total loss: 0.19042 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.1138 RPN box loss: 0.02805 RPN score loss: 0.0127 RPN total loss: 0.04075 Total loss: 0.93641 timestamp: 1654967199.5879765 iteration: 68460 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0699 FastRCNN class loss: 0.07595 FastRCNN total loss: 0.14586 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.18431 RPN box loss: 0.02656 RPN score loss: 0.00503 RPN total loss: 0.0316 Total loss: 0.9532 timestamp: 1654967202.7677839 iteration: 68465 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06226 FastRCNN class loss: 0.03537 FastRCNN total loss: 0.09763 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.0004 Mask loss: 0.09938 RPN box loss: 0.01049 RPN score loss: 0.00491 RPN total loss: 0.0154 Total loss: 0.80385 timestamp: 1654967205.9834504 iteration: 68470 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09168 FastRCNN class loss: 0.0727 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.59143 Learning rate: 0.0004 Mask loss: 0.15769 RPN box loss: 0.00866 RPN score loss: 0.00685 RPN total loss: 0.01551 Total loss: 0.92902 timestamp: 1654967209.2075942 iteration: 68475 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05816 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.11241 L1 loss: 0.0000e+00 L2 loss: 0.59143 Learning rate: 0.0004 Mask loss: 0.09791 RPN box loss: 0.01224 RPN score loss: 0.00157 RPN total loss: 0.01381 Total loss: 0.81555 timestamp: 1654967212.366208 iteration: 68480 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09579 FastRCNN class loss: 0.05863 FastRCNN total loss: 0.15442 L1 loss: 0.0000e+00 L2 loss: 0.59143 Learning rate: 0.0004 Mask loss: 0.13227 RPN box loss: 0.01293 RPN score loss: 0.01434 RPN total loss: 0.02726 Total loss: 0.90538 timestamp: 1654967215.5472844 iteration: 68485 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07879 FastRCNN class loss: 0.05111 FastRCNN total loss: 0.1299 L1 loss: 0.0000e+00 L2 loss: 0.59143 Learning rate: 0.0004 Mask loss: 0.1113 RPN box loss: 0.03818 RPN score loss: 0.00448 RPN total loss: 0.04266 Total loss: 0.87529 timestamp: 1654967218.790759 iteration: 68490 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05339 FastRCNN class loss: 0.06927 FastRCNN total loss: 0.12266 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.0004 Mask loss: 0.10406 RPN box loss: 0.00936 RPN score loss: 0.00278 RPN total loss: 0.01214 Total loss: 0.83028 timestamp: 1654967222.019155 iteration: 68495 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07037 FastRCNN class loss: 0.05311 FastRCNN total loss: 0.12348 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.0004 Mask loss: 0.075 RPN box loss: 0.00811 RPN score loss: 0.00133 RPN total loss: 0.00943 Total loss: 0.79934 timestamp: 1654967225.297041 iteration: 68500 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.06951 FastRCNN total loss: 0.17587 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.0004 Mask loss: 0.16966 RPN box loss: 0.03195 RPN score loss: 0.00237 RPN total loss: 0.03432 Total loss: 0.97126 timestamp: 1654967228.431944 iteration: 68505 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06318 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.12229 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.0004 Mask loss: 0.14076 RPN box loss: 0.01114 RPN score loss: 0.00826 RPN total loss: 0.0194 Total loss: 0.87386 timestamp: 1654967231.6407266 iteration: 68510 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10817 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.18262 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.0004 Mask loss: 0.1849 RPN box loss: 0.00803 RPN score loss: 0.00377 RPN total loss: 0.0118 Total loss: 0.97073 timestamp: 1654967234.8248081 iteration: 68515 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09411 FastRCNN class loss: 0.04321 FastRCNN total loss: 0.13731 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.0004 Mask loss: 0.09227 RPN box loss: 0.00741 RPN score loss: 0.005 RPN total loss: 0.01241 Total loss: 0.83341 timestamp: 1654967237.9969206 iteration: 68520 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08035 FastRCNN class loss: 0.05013 FastRCNN total loss: 0.13048 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.0004 Mask loss: 0.10053 RPN box loss: 0.00542 RPN score loss: 0.0008 RPN total loss: 0.00622 Total loss: 0.82865 timestamp: 1654967241.190632 iteration: 68525 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07142 FastRCNN class loss: 0.05099 FastRCNN total loss: 0.12241 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.0004 Mask loss: 0.08788 RPN box loss: 0.00791 RPN score loss: 0.00213 RPN total loss: 0.01004 Total loss: 0.81174 timestamp: 1654967244.4244268 iteration: 68530 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1362 FastRCNN class loss: 0.07142 FastRCNN total loss: 0.20761 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.0004 Mask loss: 0.12675 RPN box loss: 0.00767 RPN score loss: 0.00281 RPN total loss: 0.01048 Total loss: 0.93626 timestamp: 1654967247.6453402 iteration: 68535 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0775 FastRCNN class loss: 0.08655 FastRCNN total loss: 0.16405 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.0004 Mask loss: 0.18556 RPN box loss: 0.0179 RPN score loss: 0.00148 RPN total loss: 0.01938 Total loss: 0.96039 timestamp: 1654967250.780106 iteration: 68540 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12374 FastRCNN class loss: 0.08527 FastRCNN total loss: 0.20901 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.0004 Mask loss: 0.1003 RPN box loss: 0.00779 RPN score loss: 0.00312 RPN total loss: 0.01091 Total loss: 0.91162 timestamp: 1654967254.0184503 iteration: 68545 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06919 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.13973 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.0004 Mask loss: 0.12935 RPN box loss: 0.01398 RPN score loss: 0.00141 RPN total loss: 0.01539 Total loss: 0.87588 timestamp: 1654967257.1941214 iteration: 68550 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05651 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.12092 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.0004 Mask loss: 0.16013 RPN box loss: 0.00843 RPN score loss: 0.00845 RPN total loss: 0.01688 Total loss: 0.88933 timestamp: 1654967260.3782482 iteration: 68555 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09796 FastRCNN class loss: 0.08988 FastRCNN total loss: 0.18784 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.0004 Mask loss: 0.17679 RPN box loss: 0.02649 RPN score loss: 0.01149 RPN total loss: 0.03798 Total loss: 0.99402 timestamp: 1654967263.591244 iteration: 68560 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10443 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.19155 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.0004 Mask loss: 0.153 RPN box loss: 0.02636 RPN score loss: 0.0112 RPN total loss: 0.03756 Total loss: 0.97351 timestamp: 1654967266.7839806 iteration: 68565 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10612 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.17147 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.0004 Mask loss: 0.11684 RPN box loss: 0.01226 RPN score loss: 0.00062 RPN total loss: 0.01288 Total loss: 0.89259 timestamp: 1654967270.0124521 iteration: 68570 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06971 FastRCNN class loss: 0.06983 FastRCNN total loss: 0.13954 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.0004 Mask loss: 0.10687 RPN box loss: 0.00551 RPN score loss: 0.00422 RPN total loss: 0.00973 Total loss: 0.84753 timestamp: 1654967273.2541978 iteration: 68575 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10651 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.18091 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.0004 Mask loss: 0.10675 RPN box loss: 0.00914 RPN score loss: 0.0059 RPN total loss: 0.01504 Total loss: 0.8941 timestamp: 1654967276.494628 iteration: 68580 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06027 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.11574 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.0004 Mask loss: 0.1128 RPN box loss: 0.0072 RPN score loss: 0.0021 RPN total loss: 0.0093 Total loss: 0.82924 timestamp: 1654967279.6828096 iteration: 68585 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08983 FastRCNN class loss: 0.07047 FastRCNN total loss: 0.16031 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.0004 Mask loss: 0.14931 RPN box loss: 0.00776 RPN score loss: 0.01258 RPN total loss: 0.02034 Total loss: 0.92134 timestamp: 1654967282.897411 iteration: 68590 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07727 FastRCNN class loss: 0.08443 FastRCNN total loss: 0.1617 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.0004 Mask loss: 0.19404 RPN box loss: 0.01136 RPN score loss: 0.00511 RPN total loss: 0.01646 Total loss: 0.96359 timestamp: 1654967286.0660057 iteration: 68595 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07038 FastRCNN class loss: 0.05645 FastRCNN total loss: 0.12684 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.0004 Mask loss: 0.1504 RPN box loss: 0.00315 RPN score loss: 0.00848 RPN total loss: 0.01163 Total loss: 0.88025 timestamp: 1654967289.2327797 iteration: 68600 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10336 FastRCNN class loss: 0.09223 FastRCNN total loss: 0.19559 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.0004 Mask loss: 0.16269 RPN box loss: 0.01797 RPN score loss: 0.00606 RPN total loss: 0.02403 Total loss: 0.9737 timestamp: 1654967292.396052 iteration: 68605 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05422 FastRCNN class loss: 0.06692 FastRCNN total loss: 0.12114 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.0004 Mask loss: 0.12088 RPN box loss: 0.0103 RPN score loss: 0.00535 RPN total loss: 0.01565 Total loss: 0.84905 timestamp: 1654967295.5305526 iteration: 68610 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05379 FastRCNN class loss: 0.03882 FastRCNN total loss: 0.09262 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.12514 RPN box loss: 0.00715 RPN score loss: 0.00358 RPN total loss: 0.01073 Total loss: 0.81987 timestamp: 1654967298.7280777 iteration: 68615 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08176 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.14032 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.1345 RPN box loss: 0.02056 RPN score loss: 0.00384 RPN total loss: 0.0244 Total loss: 0.8906 timestamp: 1654967302.001427 iteration: 68620 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05321 FastRCNN class loss: 0.05101 FastRCNN total loss: 0.10421 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.09931 RPN box loss: 0.01411 RPN score loss: 0.01212 RPN total loss: 0.02623 Total loss: 0.82113 timestamp: 1654967305.2331586 iteration: 68625 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10001 FastRCNN class loss: 0.05688 FastRCNN total loss: 0.15689 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.15454 RPN box loss: 0.00561 RPN score loss: 0.00289 RPN total loss: 0.0085 Total loss: 0.91131 timestamp: 1654967308.4123464 iteration: 68630 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07885 FastRCNN class loss: 0.04808 FastRCNN total loss: 0.12693 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.09799 RPN box loss: 0.00757 RPN score loss: 0.00193 RPN total loss: 0.0095 Total loss: 0.82579 timestamp: 1654967311.5402324 iteration: 68635 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14658 FastRCNN class loss: 0.08167 FastRCNN total loss: 0.22825 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.15078 RPN box loss: 0.03488 RPN score loss: 0.0059 RPN total loss: 0.04078 Total loss: 1.01119 timestamp: 1654967314.6956973 iteration: 68640 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1462 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.22205 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.0004 Mask loss: 0.16177 RPN box loss: 0.00658 RPN score loss: 0.00203 RPN total loss: 0.00861 Total loss: 0.9838 timestamp: 1654967317.853141 iteration: 68645 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06811 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.12622 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.0004 Mask loss: 0.1148 RPN box loss: 0.0359 RPN score loss: 0.00263 RPN total loss: 0.03854 Total loss: 0.87093 timestamp: 1654967321.1129706 iteration: 68650 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07813 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.13942 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.0004 Mask loss: 0.11909 RPN box loss: 0.01373 RPN score loss: 0.00291 RPN total loss: 0.01664 Total loss: 0.86653 timestamp: 1654967324.3028817 iteration: 68655 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10172 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.17622 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.0004 Mask loss: 0.14588 RPN box loss: 0.02474 RPN score loss: 0.00561 RPN total loss: 0.03035 Total loss: 0.94382 timestamp: 1654967327.5164587 iteration: 68660 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1303 FastRCNN class loss: 0.11729 FastRCNN total loss: 0.24758 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.0004 Mask loss: 0.14599 RPN box loss: 0.01277 RPN score loss: 0.00825 RPN total loss: 0.02101 Total loss: 1.00596 timestamp: 1654967330.6840038 iteration: 68665 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06226 FastRCNN class loss: 0.03717 FastRCNN total loss: 0.09944 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.0004 Mask loss: 0.09795 RPN box loss: 0.00451 RPN score loss: 0.00103 RPN total loss: 0.00554 Total loss: 0.79429 timestamp: 1654967333.890876 iteration: 68670 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11042 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.18031 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.0004 Mask loss: 0.15631 RPN box loss: 0.0106 RPN score loss: 0.00831 RPN total loss: 0.01891 Total loss: 0.9469 timestamp: 1654967337.1293323 iteration: 68675 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08618 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.14042 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.0004 Mask loss: 0.12611 RPN box loss: 0.00526 RPN score loss: 0.00452 RPN total loss: 0.00978 Total loss: 0.86767 timestamp: 1654967340.3575113 iteration: 68680 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.0327 FastRCNN total loss: 0.11136 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.0004 Mask loss: 0.07632 RPN box loss: 0.00791 RPN score loss: 0.00232 RPN total loss: 0.01023 Total loss: 0.78928 timestamp: 1654967343.4881387 iteration: 68685 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11991 FastRCNN class loss: 0.08817 FastRCNN total loss: 0.20808 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.0004 Mask loss: 0.13399 RPN box loss: 0.01743 RPN score loss: 0.0048 RPN total loss: 0.02223 Total loss: 0.95565 timestamp: 1654967346.645347 iteration: 68690 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05642 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.11588 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.0004 Mask loss: 0.12668 RPN box loss: 0.00612 RPN score loss: 0.00241 RPN total loss: 0.00853 Total loss: 0.84245 timestamp: 1654967349.8374546 iteration: 68695 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07768 FastRCNN class loss: 0.03998 FastRCNN total loss: 0.11765 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.0004 Mask loss: 0.13316 RPN box loss: 0.01062 RPN score loss: 0.00511 RPN total loss: 0.01572 Total loss: 0.85789 timestamp: 1654967353.1056356 iteration: 68700 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.1375 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.0004 Mask loss: 0.14068 RPN box loss: 0.00962 RPN score loss: 0.00403 RPN total loss: 0.01365 Total loss: 0.88319 timestamp: 1654967356.1991723 iteration: 68705 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09924 FastRCNN class loss: 0.06887 FastRCNN total loss: 0.16811 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.12284 RPN box loss: 0.00959 RPN score loss: 0.00556 RPN total loss: 0.01515 Total loss: 0.89745 timestamp: 1654967359.3610709 iteration: 68710 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07663 FastRCNN class loss: 0.03878 FastRCNN total loss: 0.11541 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.10989 RPN box loss: 0.00225 RPN score loss: 0.00192 RPN total loss: 0.00417 Total loss: 0.82081 timestamp: 1654967362.5273979 iteration: 68715 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.17903 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.12915 RPN box loss: 0.01413 RPN score loss: 0.00516 RPN total loss: 0.01929 Total loss: 0.91881 timestamp: 1654967365.7039697 iteration: 68720 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.133 FastRCNN class loss: 0.08129 FastRCNN total loss: 0.2143 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.14706 RPN box loss: 0.01733 RPN score loss: 0.00366 RPN total loss: 0.021 Total loss: 0.97371 timestamp: 1654967368.8634357 iteration: 68725 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03589 FastRCNN class loss: 0.04926 FastRCNN total loss: 0.08516 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.09578 RPN box loss: 0.00655 RPN score loss: 0.00186 RPN total loss: 0.00842 Total loss: 0.7807 timestamp: 1654967372.0905101 iteration: 68730 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15727 FastRCNN class loss: 0.10968 FastRCNN total loss: 0.26695 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.13104 RPN box loss: 0.03416 RPN score loss: 0.00711 RPN total loss: 0.04127 Total loss: 1.0306 timestamp: 1654967375.275315 iteration: 68735 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07337 FastRCNN class loss: 0.07281 FastRCNN total loss: 0.14618 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.0004 Mask loss: 0.17148 RPN box loss: 0.02007 RPN score loss: 0.01009 RPN total loss: 0.03015 Total loss: 0.93915 timestamp: 1654967378.4628103 iteration: 68740 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13569 FastRCNN class loss: 0.08016 FastRCNN total loss: 0.21586 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.0004 Mask loss: 0.16927 RPN box loss: 0.02018 RPN score loss: 0.00401 RPN total loss: 0.02418 Total loss: 1.00065 timestamp: 1654967381.597996 iteration: 68745 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05875 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.09821 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.0004 Mask loss: 0.11503 RPN box loss: 0.00393 RPN score loss: 0.00195 RPN total loss: 0.00589 Total loss: 0.81047 timestamp: 1654967384.813309 iteration: 68750 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06428 FastRCNN class loss: 0.07629 FastRCNN total loss: 0.14057 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.0004 Mask loss: 0.18089 RPN box loss: 0.01186 RPN score loss: 0.00847 RPN total loss: 0.02033 Total loss: 0.93313 timestamp: 1654967387.9726105 iteration: 68755 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07817 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.13713 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.0004 Mask loss: 0.10087 RPN box loss: 0.00623 RPN score loss: 0.00048 RPN total loss: 0.00671 Total loss: 0.83605 timestamp: 1654967391.1614296 iteration: 68760 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06627 FastRCNN class loss: 0.03235 FastRCNN total loss: 0.09862 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.0004 Mask loss: 0.11447 RPN box loss: 0.00476 RPN score loss: 0.00168 RPN total loss: 0.00644 Total loss: 0.81087 timestamp: 1654967394.4269145 iteration: 68765 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09125 FastRCNN class loss: 0.1154 FastRCNN total loss: 0.20665 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.0004 Mask loss: 0.15265 RPN box loss: 0.01994 RPN score loss: 0.0053 RPN total loss: 0.02524 Total loss: 0.97586 timestamp: 1654967397.64074 iteration: 68770 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06656 FastRCNN class loss: 0.04301 FastRCNN total loss: 0.10957 L1 loss: 0.0000e+00 L2 loss: 0.59133 Learning rate: 0.0004 Mask loss: 0.09543 RPN box loss: 0.0073 RPN score loss: 0.0032 RPN total loss: 0.0105 Total loss: 0.80682 timestamp: 1654967400.8296852 iteration: 68775 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14835 FastRCNN class loss: 0.11486 FastRCNN total loss: 0.26321 L1 loss: 0.0000e+00 L2 loss: 0.59133 Learning rate: 0.0004 Mask loss: 0.1578 RPN box loss: 0.02349 RPN score loss: 0.01326 RPN total loss: 0.03675 Total loss: 1.04909 timestamp: 1654967404.025716 iteration: 68780 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07823 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.1461 L1 loss: 0.0000e+00 L2 loss: 0.59133 Learning rate: 0.0004 Mask loss: 0.08654 RPN box loss: 0.00524 RPN score loss: 0.00471 RPN total loss: 0.00994 Total loss: 0.83391 timestamp: 1654967407.202264 iteration: 68785 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08983 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.14002 L1 loss: 0.0000e+00 L2 loss: 0.59133 Learning rate: 0.0004 Mask loss: 0.07843 RPN box loss: 0.03216 RPN score loss: 0.00248 RPN total loss: 0.03464 Total loss: 0.84442 timestamp: 1654967410.3782766 iteration: 68790 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11808 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.1999 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.0004 Mask loss: 0.16239 RPN box loss: 0.016 RPN score loss: 0.00837 RPN total loss: 0.02436 Total loss: 0.97798 timestamp: 1654967413.4792917 iteration: 68795 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0894 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.15758 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.0004 Mask loss: 0.14249 RPN box loss: 0.00969 RPN score loss: 0.00787 RPN total loss: 0.01756 Total loss: 0.90895 timestamp: 1654967416.6763897 iteration: 68800 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10506 FastRCNN class loss: 0.04903 FastRCNN total loss: 0.15409 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.0004 Mask loss: 0.08926 RPN box loss: 0.00848 RPN score loss: 0.00372 RPN total loss: 0.01221 Total loss: 0.84687 timestamp: 1654967419.866549 iteration: 68805 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.17946 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.0004 Mask loss: 0.13424 RPN box loss: 0.00615 RPN score loss: 0.00361 RPN total loss: 0.00976 Total loss: 0.91478 timestamp: 1654967423.093312 iteration: 68810 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05777 FastRCNN class loss: 0.0469 FastRCNN total loss: 0.10468 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.0004 Mask loss: 0.13317 RPN box loss: 0.00481 RPN score loss: 0.00791 RPN total loss: 0.01272 Total loss: 0.84188 timestamp: 1654967426.3619254 iteration: 68815 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.07322 FastRCNN total loss: 0.16008 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.0004 Mask loss: 0.1661 RPN box loss: 0.01386 RPN score loss: 0.00748 RPN total loss: 0.02134 Total loss: 0.93883 timestamp: 1654967429.5284076 iteration: 68820 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.13295 FastRCNN total loss: 0.23618 L1 loss: 0.0000e+00 L2 loss: 0.59131 Learning rate: 0.0004 Mask loss: 0.17469 RPN box loss: 0.01415 RPN score loss: 0.02415 RPN total loss: 0.0383 Total loss: 1.04048 timestamp: 1654967432.6809113 iteration: 68825 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.16065 L1 loss: 0.0000e+00 L2 loss: 0.59131 Learning rate: 0.0004 Mask loss: 0.13222 RPN box loss: 0.00303 RPN score loss: 0.00121 RPN total loss: 0.00425 Total loss: 0.88844 timestamp: 1654967435.9338121 iteration: 68830 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07161 FastRCNN class loss: 0.05455 FastRCNN total loss: 0.12615 L1 loss: 0.0000e+00 L2 loss: 0.59131 Learning rate: 0.0004 Mask loss: 0.14047 RPN box loss: 0.00817 RPN score loss: 0.00172 RPN total loss: 0.00989 Total loss: 0.86783 timestamp: 1654967439.1280682 iteration: 68835 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06595 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.12227 L1 loss: 0.0000e+00 L2 loss: 0.59131 Learning rate: 0.0004 Mask loss: 0.1696 RPN box loss: 0.00695 RPN score loss: 0.00171 RPN total loss: 0.00866 Total loss: 0.89184 timestamp: 1654967442.3722482 iteration: 68840 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07924 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.13908 L1 loss: 0.0000e+00 L2 loss: 0.59131 Learning rate: 0.0004 Mask loss: 0.12044 RPN box loss: 0.0055 RPN score loss: 0.00805 RPN total loss: 0.01355 Total loss: 0.86438 timestamp: 1654967445.5981972 iteration: 68845 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06053 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.12122 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.0004 Mask loss: 0.1511 RPN box loss: 0.01738 RPN score loss: 0.00526 RPN total loss: 0.02263 Total loss: 0.88625 timestamp: 1654967448.8229423 iteration: 68850 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13214 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.19376 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.0004 Mask loss: 0.08838 RPN box loss: 0.01757 RPN score loss: 0.00598 RPN total loss: 0.02356 Total loss: 0.897 timestamp: 1654967451.927423 iteration: 68855 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13784 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.20164 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.0004 Mask loss: 0.12032 RPN box loss: 0.01345 RPN score loss: 0.00517 RPN total loss: 0.01862 Total loss: 0.93188 timestamp: 1654967455.0630512 iteration: 68860 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0864 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.15153 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.0004 Mask loss: 0.14528 RPN box loss: 0.00735 RPN score loss: 0.00474 RPN total loss: 0.01209 Total loss: 0.9002 timestamp: 1654967458.3098805 iteration: 68865 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08416 FastRCNN class loss: 0.04258 FastRCNN total loss: 0.12674 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.0004 Mask loss: 0.13649 RPN box loss: 0.00388 RPN score loss: 0.00324 RPN total loss: 0.00713 Total loss: 0.86166 timestamp: 1654967461.46585 iteration: 68870 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14133 FastRCNN class loss: 0.13586 FastRCNN total loss: 0.27718 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.0004 Mask loss: 0.14371 RPN box loss: 0.02203 RPN score loss: 0.00818 RPN total loss: 0.03021 Total loss: 1.0424 timestamp: 1654967464.6491616 iteration: 68875 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0818 FastRCNN class loss: 0.04203 FastRCNN total loss: 0.12383 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.09586 RPN box loss: 0.01043 RPN score loss: 0.00118 RPN total loss: 0.01161 Total loss: 0.82259 timestamp: 1654967467.8565242 iteration: 68880 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08335 FastRCNN class loss: 0.12557 FastRCNN total loss: 0.20892 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.15727 RPN box loss: 0.01916 RPN score loss: 0.00778 RPN total loss: 0.02694 Total loss: 0.98442 timestamp: 1654967471.077157 iteration: 68885 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09419 FastRCNN class loss: 0.04467 FastRCNN total loss: 0.13886 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.11508 RPN box loss: 0.00496 RPN score loss: 0.00205 RPN total loss: 0.00701 Total loss: 0.85224 timestamp: 1654967474.2524116 iteration: 68890 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08767 FastRCNN class loss: 0.0546 FastRCNN total loss: 0.14227 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.13445 RPN box loss: 0.0351 RPN score loss: 0.00555 RPN total loss: 0.04066 Total loss: 0.90867 timestamp: 1654967477.4919693 iteration: 68895 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11265 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.18025 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.12959 RPN box loss: 0.01959 RPN score loss: 0.00217 RPN total loss: 0.02176 Total loss: 0.92289 timestamp: 1654967480.6718297 iteration: 68900 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06942 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.1405 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.10898 RPN box loss: 0.00421 RPN score loss: 0.00237 RPN total loss: 0.00658 Total loss: 0.84734 timestamp: 1654967483.906371 iteration: 68905 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07082 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.142 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.0004 Mask loss: 0.11413 RPN box loss: 0.01638 RPN score loss: 0.00442 RPN total loss: 0.0208 Total loss: 0.86821 timestamp: 1654967487.051177 iteration: 68910 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0898 FastRCNN class loss: 0.09862 FastRCNN total loss: 0.18843 L1 loss: 0.0000e+00 L2 loss: 0.59128 Learning rate: 0.0004 Mask loss: 0.15123 RPN box loss: 0.02636 RPN score loss: 0.01773 RPN total loss: 0.04409 Total loss: 0.97503 timestamp: 1654967490.2352903 iteration: 68915 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14476 FastRCNN class loss: 0.07393 FastRCNN total loss: 0.21869 L1 loss: 0.0000e+00 L2 loss: 0.59128 Learning rate: 0.0004 Mask loss: 0.1397 RPN box loss: 0.01335 RPN score loss: 0.00426 RPN total loss: 0.0176 Total loss: 0.96727 timestamp: 1654967493.4440658 iteration: 68920 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.15946 L1 loss: 0.0000e+00 L2 loss: 0.59128 Learning rate: 0.0004 Mask loss: 0.12455 RPN box loss: 0.01903 RPN score loss: 0.00307 RPN total loss: 0.02211 Total loss: 0.8974 timestamp: 1654967496.6229963 iteration: 68925 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03649 FastRCNN class loss: 0.03994 FastRCNN total loss: 0.07643 L1 loss: 0.0000e+00 L2 loss: 0.59128 Learning rate: 0.0004 Mask loss: 0.09536 RPN box loss: 0.0027 RPN score loss: 0.00305 RPN total loss: 0.00575 Total loss: 0.76882 timestamp: 1654967499.8184226 iteration: 68930 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04513 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.11858 L1 loss: 0.0000e+00 L2 loss: 0.59128 Learning rate: 0.0004 Mask loss: 0.09063 RPN box loss: 0.00741 RPN score loss: 0.00152 RPN total loss: 0.00893 Total loss: 0.80941 timestamp: 1654967503.0204446 iteration: 68935 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13219 FastRCNN class loss: 0.08883 FastRCNN total loss: 0.22102 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.0004 Mask loss: 0.19444 RPN box loss: 0.01357 RPN score loss: 0.01076 RPN total loss: 0.02433 Total loss: 1.03106 timestamp: 1654967506.2530186 iteration: 68940 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0612 FastRCNN class loss: 0.06814 FastRCNN total loss: 0.12934 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.0004 Mask loss: 0.11706 RPN box loss: 0.0149 RPN score loss: 0.00316 RPN total loss: 0.01805 Total loss: 0.85573 timestamp: 1654967509.4142115 iteration: 68945 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08862 FastRCNN class loss: 0.07374 FastRCNN total loss: 0.16237 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.0004 Mask loss: 0.22819 RPN box loss: 0.01013 RPN score loss: 0.00322 RPN total loss: 0.01335 Total loss: 0.99518 timestamp: 1654967512.6453686 iteration: 68950 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05424 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.1127 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.0004 Mask loss: 0.1191 RPN box loss: 0.0101 RPN score loss: 0.0051 RPN total loss: 0.0152 Total loss: 0.83827 timestamp: 1654967515.8287902 iteration: 68955 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.05727 FastRCNN total loss: 0.13621 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.0004 Mask loss: 0.11599 RPN box loss: 0.0095 RPN score loss: 0.00706 RPN total loss: 0.01656 Total loss: 0.86002 timestamp: 1654967519.0713656 iteration: 68960 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11309 FastRCNN class loss: 0.09248 FastRCNN total loss: 0.20557 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.0004 Mask loss: 0.11981 RPN box loss: 0.01218 RPN score loss: 0.00545 RPN total loss: 0.01762 Total loss: 0.93427 timestamp: 1654967522.2749104 iteration: 68965 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10327 FastRCNN class loss: 0.04557 FastRCNN total loss: 0.14884 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.13389 RPN box loss: 0.04851 RPN score loss: 0.00162 RPN total loss: 0.05013 Total loss: 0.92412 timestamp: 1654967525.4521792 iteration: 68970 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0884 FastRCNN class loss: 0.05384 FastRCNN total loss: 0.14224 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.11826 RPN box loss: 0.01916 RPN score loss: 0.00168 RPN total loss: 0.02084 Total loss: 0.8726 timestamp: 1654967528.7059853 iteration: 68975 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08305 FastRCNN class loss: 0.09845 FastRCNN total loss: 0.18149 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.12798 RPN box loss: 0.01161 RPN score loss: 0.00244 RPN total loss: 0.01406 Total loss: 0.91479 timestamp: 1654967531.8395529 iteration: 68980 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07531 FastRCNN class loss: 0.04853 FastRCNN total loss: 0.12384 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.08539 RPN box loss: 0.00845 RPN score loss: 0.00098 RPN total loss: 0.00943 Total loss: 0.80992 timestamp: 1654967535.0233803 iteration: 68985 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06603 FastRCNN class loss: 0.04568 FastRCNN total loss: 0.11171 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.0856 RPN box loss: 0.01251 RPN score loss: 0.00185 RPN total loss: 0.01436 Total loss: 0.80292 timestamp: 1654967538.203137 iteration: 68990 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11888 FastRCNN class loss: 0.07293 FastRCNN total loss: 0.19181 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.13489 RPN box loss: 0.01424 RPN score loss: 0.00454 RPN total loss: 0.01878 Total loss: 0.93674 timestamp: 1654967541.3401453 iteration: 68995 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06272 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.13771 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.0004 Mask loss: 0.10381 RPN box loss: 0.00731 RPN score loss: 0.01394 RPN total loss: 0.02125 Total loss: 0.85402 timestamp: 1654967544.5577054 iteration: 69000 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09868 FastRCNN class loss: 0.03229 FastRCNN total loss: 0.13096 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.0004 Mask loss: 0.10151 RPN box loss: 0.00955 RPN score loss: 0.00167 RPN total loss: 0.01122 Total loss: 0.83495 timestamp: 1654967547.722632 iteration: 69005 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11356 FastRCNN class loss: 0.06895 FastRCNN total loss: 0.18252 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.0004 Mask loss: 0.15159 RPN box loss: 0.0094 RPN score loss: 0.00629 RPN total loss: 0.0157 Total loss: 0.94106 timestamp: 1654967551.0000973 iteration: 69010 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13274 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.223 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.0004 Mask loss: 0.09949 RPN box loss: 0.01235 RPN score loss: 0.00326 RPN total loss: 0.01561 Total loss: 0.92935 timestamp: 1654967554.1212204 iteration: 69015 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07056 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.13955 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.0004 Mask loss: 0.14541 RPN box loss: 0.00943 RPN score loss: 0.00657 RPN total loss: 0.016 Total loss: 0.8922 timestamp: 1654967557.314898 iteration: 69020 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10114 FastRCNN class loss: 0.05176 FastRCNN total loss: 0.15289 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.0004 Mask loss: 0.13239 RPN box loss: 0.01298 RPN score loss: 0.00271 RPN total loss: 0.01569 Total loss: 0.89222 timestamp: 1654967560.5396075 iteration: 69025 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06367 FastRCNN class loss: 0.07832 FastRCNN total loss: 0.14198 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.0004 Mask loss: 0.12036 RPN box loss: 0.00965 RPN score loss: 0.00843 RPN total loss: 0.01808 Total loss: 0.87166 timestamp: 1654967563.6784687 iteration: 69030 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05163 FastRCNN class loss: 0.04467 FastRCNN total loss: 0.0963 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.0004 Mask loss: 0.11266 RPN box loss: 0.00673 RPN score loss: 0.00136 RPN total loss: 0.00809 Total loss: 0.80829 timestamp: 1654967566.803989 iteration: 69035 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14907 FastRCNN class loss: 0.15403 FastRCNN total loss: 0.3031 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.0004 Mask loss: 0.22276 RPN box loss: 0.01867 RPN score loss: 0.00529 RPN total loss: 0.02396 Total loss: 1.14107 timestamp: 1654967570.0021155 iteration: 69040 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10875 FastRCNN class loss: 0.1474 FastRCNN total loss: 0.25616 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.0004 Mask loss: 0.15571 RPN box loss: 0.01476 RPN score loss: 0.0015 RPN total loss: 0.01625 Total loss: 1.01936 timestamp: 1654967573.1978614 iteration: 69045 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14389 FastRCNN class loss: 0.08041 FastRCNN total loss: 0.22429 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.0004 Mask loss: 0.17387 RPN box loss: 0.01591 RPN score loss: 0.00555 RPN total loss: 0.02146 Total loss: 1.01086 timestamp: 1654967576.4234774 iteration: 69050 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12822 FastRCNN class loss: 0.10407 FastRCNN total loss: 0.23229 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.0004 Mask loss: 0.18408 RPN box loss: 0.02776 RPN score loss: 0.00383 RPN total loss: 0.03159 Total loss: 1.03919 timestamp: 1654967579.672594 iteration: 69055 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05961 FastRCNN class loss: 0.09065 FastRCNN total loss: 0.15026 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.0004 Mask loss: 0.11917 RPN box loss: 0.00835 RPN score loss: 0.00116 RPN total loss: 0.00952 Total loss: 0.87019 timestamp: 1654967582.8705437 iteration: 69060 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11069 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.20034 L1 loss: 0.0000e+00 L2 loss: 0.59123 Learning rate: 0.0004 Mask loss: 0.11293 RPN box loss: 0.00656 RPN score loss: 0.00526 RPN total loss: 0.01182 Total loss: 0.91632 timestamp: 1654967586.116676 iteration: 69065 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11153 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.18269 L1 loss: 0.0000e+00 L2 loss: 0.59123 Learning rate: 0.0004 Mask loss: 0.10558 RPN box loss: 0.02867 RPN score loss: 0.00188 RPN total loss: 0.03055 Total loss: 0.91006 timestamp: 1654967589.2783296 iteration: 69070 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07393 FastRCNN class loss: 0.05607 FastRCNN total loss: 0.13 L1 loss: 0.0000e+00 L2 loss: 0.59123 Learning rate: 0.0004 Mask loss: 0.11879 RPN box loss: 0.01348 RPN score loss: 0.00154 RPN total loss: 0.01502 Total loss: 0.85504 timestamp: 1654967592.4661312 iteration: 69075 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10199 FastRCNN class loss: 0.06034 FastRCNN total loss: 0.16233 L1 loss: 0.0000e+00 L2 loss: 0.59123 Learning rate: 0.0004 Mask loss: 0.13801 RPN box loss: 0.00901 RPN score loss: 0.00339 RPN total loss: 0.01241 Total loss: 0.90397 timestamp: 1654967595.6367626 iteration: 69080 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07352 FastRCNN class loss: 0.04853 FastRCNN total loss: 0.12204 L1 loss: 0.0000e+00 L2 loss: 0.59123 Learning rate: 0.0004 Mask loss: 0.11022 RPN box loss: 0.00525 RPN score loss: 0.00491 RPN total loss: 0.01016 Total loss: 0.83365 timestamp: 1654967598.8205876 iteration: 69085 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15675 FastRCNN class loss: 0.04504 FastRCNN total loss: 0.20178 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.1199 RPN box loss: 0.02048 RPN score loss: 0.00471 RPN total loss: 0.02519 Total loss: 0.9381 timestamp: 1654967601.9811995 iteration: 69090 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06347 FastRCNN class loss: 0.04065 FastRCNN total loss: 0.10412 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.12083 RPN box loss: 0.00659 RPN score loss: 0.00343 RPN total loss: 0.01002 Total loss: 0.8262 timestamp: 1654967605.1931524 iteration: 69095 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09345 FastRCNN class loss: 0.06501 FastRCNN total loss: 0.15846 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.08153 RPN box loss: 0.00543 RPN score loss: 0.00107 RPN total loss: 0.00649 Total loss: 0.8377 timestamp: 1654967608.378669 iteration: 69100 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05986 FastRCNN class loss: 0.06229 FastRCNN total loss: 0.12216 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.09873 RPN box loss: 0.00432 RPN score loss: 0.00058 RPN total loss: 0.0049 Total loss: 0.817 timestamp: 1654967611.505111 iteration: 69105 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11403 FastRCNN class loss: 0.06332 FastRCNN total loss: 0.17735 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.1458 RPN box loss: 0.04491 RPN score loss: 0.00656 RPN total loss: 0.05148 Total loss: 0.96585 timestamp: 1654967614.7506478 iteration: 69110 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08293 FastRCNN class loss: 0.10428 FastRCNN total loss: 0.18721 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.137 RPN box loss: 0.024 RPN score loss: 0.01001 RPN total loss: 0.034 Total loss: 0.94943 timestamp: 1654967617.9369402 iteration: 69115 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07194 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.14612 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.0004 Mask loss: 0.12119 RPN box loss: 0.02011 RPN score loss: 0.00687 RPN total loss: 0.02698 Total loss: 0.88551 timestamp: 1654967621.1499734 iteration: 69120 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07139 FastRCNN class loss: 0.05369 FastRCNN total loss: 0.12508 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.0004 Mask loss: 0.10797 RPN box loss: 0.00515 RPN score loss: 0.00163 RPN total loss: 0.00678 Total loss: 0.83104 timestamp: 1654967624.3710446 iteration: 69125 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08222 FastRCNN class loss: 0.03496 FastRCNN total loss: 0.11718 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.0004 Mask loss: 0.10061 RPN box loss: 0.00978 RPN score loss: 0.0022 RPN total loss: 0.01198 Total loss: 0.82099 timestamp: 1654967627.569983 iteration: 69130 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.07106 FastRCNN total loss: 0.16243 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.0004 Mask loss: 0.17524 RPN box loss: 0.00797 RPN score loss: 0.00988 RPN total loss: 0.01785 Total loss: 0.94672 timestamp: 1654967630.8035748 iteration: 69135 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08313 FastRCNN class loss: 0.05592 FastRCNN total loss: 0.13905 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.0004 Mask loss: 0.14281 RPN box loss: 0.00898 RPN score loss: 0.00342 RPN total loss: 0.0124 Total loss: 0.88546 timestamp: 1654967634.0141575 iteration: 69140 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07418 FastRCNN class loss: 0.07446 FastRCNN total loss: 0.14864 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.0004 Mask loss: 0.11077 RPN box loss: 0.01002 RPN score loss: 0.00489 RPN total loss: 0.01492 Total loss: 0.86554 timestamp: 1654967637.282804 iteration: 69145 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0954 FastRCNN class loss: 0.06539 FastRCNN total loss: 0.16079 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.0004 Mask loss: 0.17348 RPN box loss: 0.01775 RPN score loss: 0.00207 RPN total loss: 0.01982 Total loss: 0.94531 timestamp: 1654967640.497386 iteration: 69150 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08096 FastRCNN class loss: 0.05315 FastRCNN total loss: 0.13411 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.18595 RPN box loss: 0.00638 RPN score loss: 0.00398 RPN total loss: 0.01036 Total loss: 0.92163 timestamp: 1654967643.7442315 iteration: 69155 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10651 FastRCNN class loss: 0.05538 FastRCNN total loss: 0.16189 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.12172 RPN box loss: 0.00572 RPN score loss: 0.00059 RPN total loss: 0.00631 Total loss: 0.88113 timestamp: 1654967646.948102 iteration: 69160 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06737 FastRCNN class loss: 0.05869 FastRCNN total loss: 0.12606 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.14926 RPN box loss: 0.00457 RPN score loss: 0.00055 RPN total loss: 0.00511 Total loss: 0.87163 timestamp: 1654967650.1131892 iteration: 69165 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09977 FastRCNN class loss: 0.05731 FastRCNN total loss: 0.15707 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.12112 RPN box loss: 0.01081 RPN score loss: 0.01264 RPN total loss: 0.02344 Total loss: 0.89284 timestamp: 1654967653.252394 iteration: 69170 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07279 FastRCNN class loss: 0.05113 FastRCNN total loss: 0.12392 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.06074 RPN box loss: 0.00398 RPN score loss: 0.00139 RPN total loss: 0.00537 Total loss: 0.78122 timestamp: 1654967656.4329064 iteration: 69175 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06307 FastRCNN class loss: 0.05369 FastRCNN total loss: 0.11676 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.08132 RPN box loss: 0.01249 RPN score loss: 0.0103 RPN total loss: 0.02279 Total loss: 0.81207 timestamp: 1654967659.624765 iteration: 69180 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07536 FastRCNN class loss: 0.06912 FastRCNN total loss: 0.14447 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.0004 Mask loss: 0.09086 RPN box loss: 0.00574 RPN score loss: 0.00791 RPN total loss: 0.01365 Total loss: 0.84018 timestamp: 1654967662.7574131 iteration: 69185 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11036 FastRCNN class loss: 0.06456 FastRCNN total loss: 0.17492 L1 loss: 0.0000e+00 L2 loss: 0.59119 Learning rate: 0.0004 Mask loss: 0.1692 RPN box loss: 0.0305 RPN score loss: 0.00833 RPN total loss: 0.03883 Total loss: 0.97414 timestamp: 1654967665.931257 iteration: 69190 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06599 FastRCNN class loss: 0.05298 FastRCNN total loss: 0.11897 L1 loss: 0.0000e+00 L2 loss: 0.59119 Learning rate: 0.0004 Mask loss: 0.12063 RPN box loss: 0.00734 RPN score loss: 0.00276 RPN total loss: 0.0101 Total loss: 0.8409 timestamp: 1654967669.0709188 iteration: 69195 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0379 FastRCNN class loss: 0.06493 FastRCNN total loss: 0.10283 L1 loss: 0.0000e+00 L2 loss: 0.59119 Learning rate: 0.0004 Mask loss: 0.11727 RPN box loss: 0.01626 RPN score loss: 0.00457 RPN total loss: 0.02083 Total loss: 0.83212 timestamp: 1654967672.1716895 iteration: 69200 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14739 FastRCNN class loss: 0.17136 FastRCNN total loss: 0.31875 L1 loss: 0.0000e+00 L2 loss: 0.59119 Learning rate: 0.0004 Mask loss: 0.11348 RPN box loss: 0.02333 RPN score loss: 0.0039 RPN total loss: 0.02723 Total loss: 1.05064 timestamp: 1654967675.424401 iteration: 69205 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09837 FastRCNN class loss: 0.05278 FastRCNN total loss: 0.15114 L1 loss: 0.0000e+00 L2 loss: 0.59119 Learning rate: 0.0004 Mask loss: 0.11764 RPN box loss: 0.04581 RPN score loss: 0.00188 RPN total loss: 0.04769 Total loss: 0.90766 timestamp: 1654967678.5897825 iteration: 69210 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10842 FastRCNN class loss: 0.04446 FastRCNN total loss: 0.15289 L1 loss: 0.0000e+00 L2 loss: 0.59119 Learning rate: 0.0004 Mask loss: 0.07794 RPN box loss: 0.00568 RPN score loss: 0.006 RPN total loss: 0.01169 Total loss: 0.8337 timestamp: 1654967681.7248843 iteration: 69215 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08949 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.16145 L1 loss: 0.0000e+00 L2 loss: 0.59118 Learning rate: 0.0004 Mask loss: 0.09702 RPN box loss: 0.00796 RPN score loss: 0.00056 RPN total loss: 0.00852 Total loss: 0.85817 timestamp: 1654967684.9079628 iteration: 69220 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.04668 FastRCNN total loss: 0.16139 L1 loss: 0.0000e+00 L2 loss: 0.59118 Learning rate: 0.0004 Mask loss: 0.12132 RPN box loss: 0.01026 RPN score loss: 0.00276 RPN total loss: 0.01302 Total loss: 0.88692 timestamp: 1654967688.0952995 iteration: 69225 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07225 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.13074 L1 loss: 0.0000e+00 L2 loss: 0.59118 Learning rate: 0.0004 Mask loss: 0.13222 RPN box loss: 0.00822 RPN score loss: 0.00415 RPN total loss: 0.01238 Total loss: 0.86651 timestamp: 1654967691.276812 iteration: 69230 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08876 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.15989 L1 loss: 0.0000e+00 L2 loss: 0.59118 Learning rate: 0.0004 Mask loss: 0.11191 RPN box loss: 0.00827 RPN score loss: 0.00637 RPN total loss: 0.01464 Total loss: 0.87761 timestamp: 1654967694.494479 iteration: 69235 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07693 FastRCNN class loss: 0.04494 FastRCNN total loss: 0.12188 L1 loss: 0.0000e+00 L2 loss: 0.59118 Learning rate: 0.0004 Mask loss: 0.10868 RPN box loss: 0.0031 RPN score loss: 0.00458 RPN total loss: 0.00768 Total loss: 0.82942 timestamp: 1654967697.6573973 iteration: 69240 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07709 FastRCNN class loss: 0.1119 FastRCNN total loss: 0.18899 L1 loss: 0.0000e+00 L2 loss: 0.59117 Learning rate: 0.0004 Mask loss: 0.19203 RPN box loss: 0.01305 RPN score loss: 0.02318 RPN total loss: 0.03623 Total loss: 1.00842 timestamp: 1654967700.825672 iteration: 69245 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13226 FastRCNN class loss: 0.06443 FastRCNN total loss: 0.19669 L1 loss: 0.0000e+00 L2 loss: 0.59117 Learning rate: 0.0004 Mask loss: 0.1384 RPN box loss: 0.01639 RPN score loss: 0.00529 RPN total loss: 0.02168 Total loss: 0.94794 timestamp: 1654967704.033105 iteration: 69250 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10262 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.18556 L1 loss: 0.0000e+00 L2 loss: 0.59117 Learning rate: 0.0004 Mask loss: 0.13989 RPN box loss: 0.04786 RPN score loss: 0.00693 RPN total loss: 0.05478 Total loss: 0.9714 timestamp: 1654967707.2090905 iteration: 69255 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06561 FastRCNN class loss: 0.03836 FastRCNN total loss: 0.10396 L1 loss: 0.0000e+00 L2 loss: 0.59117 Learning rate: 0.0004 Mask loss: 0.15518 RPN box loss: 0.01435 RPN score loss: 0.00584 RPN total loss: 0.02019 Total loss: 0.8705 timestamp: 1654967710.4271154 iteration: 69260 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11825 FastRCNN class loss: 0.08847 FastRCNN total loss: 0.20672 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.0004 Mask loss: 0.16012 RPN box loss: 0.00673 RPN score loss: 0.00898 RPN total loss: 0.01572 Total loss: 0.97372 timestamp: 1654967713.5685484 iteration: 69265 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07795 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.13944 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.0004 Mask loss: 0.15457 RPN box loss: 0.01971 RPN score loss: 0.0123 RPN total loss: 0.03201 Total loss: 0.91718 timestamp: 1654967716.770979 iteration: 69270 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.07979 FastRCNN total loss: 0.14756 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.0004 Mask loss: 0.11177 RPN box loss: 0.01419 RPN score loss: 0.00301 RPN total loss: 0.0172 Total loss: 0.86769 timestamp: 1654967720.0503337 iteration: 69275 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05917 FastRCNN class loss: 0.05443 FastRCNN total loss: 0.1136 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.0004 Mask loss: 0.08161 RPN box loss: 0.00653 RPN score loss: 0.00151 RPN total loss: 0.00804 Total loss: 0.7944 timestamp: 1654967723.2022884 iteration: 69280 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.072 FastRCNN class loss: 0.04783 FastRCNN total loss: 0.11983 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.0004 Mask loss: 0.10529 RPN box loss: 0.00715 RPN score loss: 0.00221 RPN total loss: 0.00936 Total loss: 0.82564 timestamp: 1654967726.3986816 iteration: 69285 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1145 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.17559 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.0004 Mask loss: 0.115 RPN box loss: 0.00841 RPN score loss: 0.00867 RPN total loss: 0.01708 Total loss: 0.89883 timestamp: 1654967729.6417632 iteration: 69290 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10702 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.16688 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.09916 RPN box loss: 0.00432 RPN score loss: 0.00183 RPN total loss: 0.00614 Total loss: 0.86333 timestamp: 1654967732.9056292 iteration: 69295 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06154 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.12082 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.09754 RPN box loss: 0.01212 RPN score loss: 0.00329 RPN total loss: 0.01541 Total loss: 0.82493 timestamp: 1654967736.1042712 iteration: 69300 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06558 FastRCNN class loss: 0.10031 FastRCNN total loss: 0.16589 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.11143 RPN box loss: 0.01176 RPN score loss: 0.00289 RPN total loss: 0.01465 Total loss: 0.88313 timestamp: 1654967739.2966416 iteration: 69305 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07929 FastRCNN class loss: 0.07121 FastRCNN total loss: 0.1505 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.11072 RPN box loss: 0.0053 RPN score loss: 0.00316 RPN total loss: 0.00846 Total loss: 0.86084 timestamp: 1654967742.5216289 iteration: 69310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0545 FastRCNN class loss: 0.03606 FastRCNN total loss: 0.09056 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.09914 RPN box loss: 0.05995 RPN score loss: 0.00469 RPN total loss: 0.06464 Total loss: 0.8455 timestamp: 1654967745.7189245 iteration: 69315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1116 FastRCNN class loss: 0.10669 FastRCNN total loss: 0.21829 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.1518 RPN box loss: 0.01121 RPN score loss: 0.0061 RPN total loss: 0.01731 Total loss: 0.97855 timestamp: 1654967748.85277 iteration: 69320 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10055 FastRCNN class loss: 0.04198 FastRCNN total loss: 0.14254 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.1339 RPN box loss: 0.00453 RPN score loss: 0.00294 RPN total loss: 0.00747 Total loss: 0.87505 timestamp: 1654967752.0301363 iteration: 69325 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08325 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.15924 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.0004 Mask loss: 0.192 RPN box loss: 0.00504 RPN score loss: 0.00405 RPN total loss: 0.0091 Total loss: 0.95147 timestamp: 1654967755.2133627 iteration: 69330 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06578 FastRCNN class loss: 0.05509 FastRCNN total loss: 0.12086 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.10952 RPN box loss: 0.01516 RPN score loss: 0.00565 RPN total loss: 0.02081 Total loss: 0.84234 timestamp: 1654967758.4680815 iteration: 69335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10256 FastRCNN class loss: 0.09425 FastRCNN total loss: 0.19681 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.07638 RPN box loss: 0.00712 RPN score loss: 0.00108 RPN total loss: 0.0082 Total loss: 0.87253 timestamp: 1654967761.5942702 iteration: 69340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07872 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.12977 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.14835 RPN box loss: 0.01656 RPN score loss: 0.00781 RPN total loss: 0.02437 Total loss: 0.89364 timestamp: 1654967764.8181179 iteration: 69345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08069 FastRCNN class loss: 0.07303 FastRCNN total loss: 0.15372 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.14707 RPN box loss: 0.01104 RPN score loss: 0.00437 RPN total loss: 0.01541 Total loss: 0.90735 timestamp: 1654967767.9707768 iteration: 69350 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13122 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.19154 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.11658 RPN box loss: 0.01799 RPN score loss: 0.00184 RPN total loss: 0.01982 Total loss: 0.91909 timestamp: 1654967771.1693187 iteration: 69355 throughput: 25.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0874 FastRCNN class loss: 0.11078 FastRCNN total loss: 0.19818 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.14447 RPN box loss: 0.00926 RPN score loss: 0.00529 RPN total loss: 0.01455 Total loss: 0.94834 timestamp: 1654967774.3790302 iteration: 69360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12193 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.18034 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.0004 Mask loss: 0.07962 RPN box loss: 0.00555 RPN score loss: 0.01066 RPN total loss: 0.01621 Total loss: 0.86731 timestamp: 1654967777.5900774 iteration: 69365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.08881 FastRCNN total loss: 0.2113 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.0004 Mask loss: 0.13974 RPN box loss: 0.00805 RPN score loss: 0.00142 RPN total loss: 0.00948 Total loss: 0.95165 timestamp: 1654967780.779401 iteration: 69370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07986 FastRCNN class loss: 0.05335 FastRCNN total loss: 0.13321 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.0004 Mask loss: 0.15343 RPN box loss: 0.01118 RPN score loss: 0.0085 RPN total loss: 0.01968 Total loss: 0.89746 timestamp: 1654967784.0089731 iteration: 69375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07422 FastRCNN class loss: 0.08559 FastRCNN total loss: 0.15981 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.0004 Mask loss: 0.13437 RPN box loss: 0.02675 RPN score loss: 0.00363 RPN total loss: 0.03038 Total loss: 0.91569 timestamp: 1654967787.1200304 iteration: 69380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10683 FastRCNN class loss: 0.07406 FastRCNN total loss: 0.18089 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.0004 Mask loss: 0.13009 RPN box loss: 0.0107 RPN score loss: 0.00913 RPN total loss: 0.01983 Total loss: 0.92194 timestamp: 1654967790.3397355 iteration: 69385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05862 FastRCNN class loss: 0.07832 FastRCNN total loss: 0.13693 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.0004 Mask loss: 0.11335 RPN box loss: 0.00691 RPN score loss: 0.00793 RPN total loss: 0.01484 Total loss: 0.85625 timestamp: 1654967793.5310335 iteration: 69390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05918 FastRCNN class loss: 0.05315 FastRCNN total loss: 0.11233 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.0004 Mask loss: 0.11582 RPN box loss: 0.01005 RPN score loss: 0.00221 RPN total loss: 0.01226 Total loss: 0.83154 timestamp: 1654967796.8113909 iteration: 69395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11472 FastRCNN class loss: 0.08535 FastRCNN total loss: 0.20008 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.0004 Mask loss: 0.14283 RPN box loss: 0.01989 RPN score loss: 0.01851 RPN total loss: 0.0384 Total loss: 0.97242 timestamp: 1654967799.9703293 iteration: 69400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06003 FastRCNN class loss: 0.0432 FastRCNN total loss: 0.10323 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.0004 Mask loss: 0.19603 RPN box loss: 0.01079 RPN score loss: 0.00227 RPN total loss: 0.01306 Total loss: 0.90345 timestamp: 1654967803.102848 iteration: 69405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0728 FastRCNN class loss: 0.07333 FastRCNN total loss: 0.14613 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.0004 Mask loss: 0.1332 RPN box loss: 0.0257 RPN score loss: 0.00476 RPN total loss: 0.03046 Total loss: 0.90091 timestamp: 1654967806.2752934 iteration: 69410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08623 FastRCNN class loss: 0.06568 FastRCNN total loss: 0.15191 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.0004 Mask loss: 0.09891 RPN box loss: 0.01039 RPN score loss: 0.00125 RPN total loss: 0.01165 Total loss: 0.85359 timestamp: 1654967809.4968216 iteration: 69415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07952 FastRCNN class loss: 0.04397 FastRCNN total loss: 0.12348 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.0004 Mask loss: 0.15036 RPN box loss: 0.00781 RPN score loss: 0.00682 RPN total loss: 0.01462 Total loss: 0.87958 timestamp: 1654967812.629353 iteration: 69420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07746 FastRCNN class loss: 0.05821 FastRCNN total loss: 0.13568 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.0004 Mask loss: 0.14134 RPN box loss: 0.01557 RPN score loss: 0.00642 RPN total loss: 0.02199 Total loss: 0.89012 timestamp: 1654967815.8028457 iteration: 69425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0651 FastRCNN class loss: 0.05637 FastRCNN total loss: 0.12146 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.0004 Mask loss: 0.1456 RPN box loss: 0.01534 RPN score loss: 0.00955 RPN total loss: 0.02489 Total loss: 0.88306 timestamp: 1654967818.95989 iteration: 69430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.128 FastRCNN class loss: 0.07721 FastRCNN total loss: 0.20521 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.0004 Mask loss: 0.12125 RPN box loss: 0.02389 RPN score loss: 0.00685 RPN total loss: 0.03074 Total loss: 0.94831 timestamp: 1654967822.0904984 iteration: 69435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13835 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.22812 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.0004 Mask loss: 0.15667 RPN box loss: 0.01509 RPN score loss: 0.00415 RPN total loss: 0.01924 Total loss: 0.99515 timestamp: 1654967825.2847798 iteration: 69440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07408 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.1271 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.0004 Mask loss: 0.1347 RPN box loss: 0.01141 RPN score loss: 0.0056 RPN total loss: 0.01701 Total loss: 0.86992 timestamp: 1654967828.4688642 iteration: 69445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10447 FastRCNN class loss: 0.05118 FastRCNN total loss: 0.15565 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.0004 Mask loss: 0.15081 RPN box loss: 0.02577 RPN score loss: 0.00616 RPN total loss: 0.03193 Total loss: 0.9295 timestamp: 1654967831.656863 iteration: 69450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06911 FastRCNN class loss: 0.04491 FastRCNN total loss: 0.11402 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.0004 Mask loss: 0.08742 RPN box loss: 0.00347 RPN score loss: 0.00048 RPN total loss: 0.00396 Total loss: 0.7965 timestamp: 1654967834.8101509 iteration: 69455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08166 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.15569 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.0004 Mask loss: 0.16888 RPN box loss: 0.00983 RPN score loss: 0.00941 RPN total loss: 0.01923 Total loss: 0.9349 timestamp: 1654967838.0255408 iteration: 69460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10485 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.17567 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.0004 Mask loss: 0.11262 RPN box loss: 0.01624 RPN score loss: 0.00485 RPN total loss: 0.02109 Total loss: 0.90049 timestamp: 1654967841.2234676 iteration: 69465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07347 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.0004 Mask loss: 0.11734 RPN box loss: 0.01188 RPN score loss: 0.01297 RPN total loss: 0.02485 Total loss: 0.87078 timestamp: 1654967844.4256778 iteration: 69470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06713 FastRCNN class loss: 0.06268 FastRCNN total loss: 0.12981 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.0004 Mask loss: 0.08387 RPN box loss: 0.00914 RPN score loss: 0.00216 RPN total loss: 0.01129 Total loss: 0.81607 timestamp: 1654967847.5875382 iteration: 69475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12009 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.23164 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.0004 Mask loss: 0.23488 RPN box loss: 0.03219 RPN score loss: 0.06952 RPN total loss: 0.10171 Total loss: 1.15932 timestamp: 1654967850.7699902 iteration: 69480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05947 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.11471 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.0004 Mask loss: 0.13647 RPN box loss: 0.01511 RPN score loss: 0.00605 RPN total loss: 0.02116 Total loss: 0.86343 timestamp: 1654967853.9336934 iteration: 69485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11219 FastRCNN class loss: 0.06674 FastRCNN total loss: 0.17893 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.0004 Mask loss: 0.16733 RPN box loss: 0.01049 RPN score loss: 0.00253 RPN total loss: 0.01302 Total loss: 0.95037 timestamp: 1654967857.0767639 iteration: 69490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08687 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.14483 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.0004 Mask loss: 0.14797 RPN box loss: 0.00495 RPN score loss: 0.0009 RPN total loss: 0.00584 Total loss: 0.88973 timestamp: 1654967860.2539935 iteration: 69495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13747 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.21311 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.0004 Mask loss: 0.15007 RPN box loss: 0.01056 RPN score loss: 0.00451 RPN total loss: 0.01507 Total loss: 0.96933 timestamp: 1654967863.3969457 iteration: 69500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10892 FastRCNN class loss: 0.08923 FastRCNN total loss: 0.19815 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.0004 Mask loss: 0.14588 RPN box loss: 0.00803 RPN score loss: 0.00364 RPN total loss: 0.01168 Total loss: 0.94679 timestamp: 1654967866.5679796 iteration: 69505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06985 FastRCNN class loss: 0.04874 FastRCNN total loss: 0.11858 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.0004 Mask loss: 0.09808 RPN box loss: 0.01354 RPN score loss: 0.00392 RPN total loss: 0.01747 Total loss: 0.82521 timestamp: 1654967869.803168 iteration: 69510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1131 FastRCNN class loss: 0.05314 FastRCNN total loss: 0.16623 L1 loss: 0.0000e+00 L2 loss: 0.59108 Learning rate: 0.0004 Mask loss: 0.10899 RPN box loss: 0.01434 RPN score loss: 0.00262 RPN total loss: 0.01696 Total loss: 0.88326 timestamp: 1654967873.0025542 iteration: 69515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10147 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.18396 L1 loss: 0.0000e+00 L2 loss: 0.59108 Learning rate: 0.0004 Mask loss: 0.143 RPN box loss: 0.01193 RPN score loss: 0.00314 RPN total loss: 0.01507 Total loss: 0.93311 timestamp: 1654967876.2540667 iteration: 69520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06487 FastRCNN class loss: 0.06142 FastRCNN total loss: 0.12629 L1 loss: 0.0000e+00 L2 loss: 0.59108 Learning rate: 0.0004 Mask loss: 0.12557 RPN box loss: 0.01091 RPN score loss: 0.00213 RPN total loss: 0.01304 Total loss: 0.85598 timestamp: 1654967879.4282928 iteration: 69525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05952 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.11762 L1 loss: 0.0000e+00 L2 loss: 0.59108 Learning rate: 0.0004 Mask loss: 0.11349 RPN box loss: 0.02593 RPN score loss: 0.00625 RPN total loss: 0.03218 Total loss: 0.85436 timestamp: 1654967882.6391656 iteration: 69530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10153 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 0.59108 Learning rate: 0.0004 Mask loss: 0.12045 RPN box loss: 0.01971 RPN score loss: 0.01318 RPN total loss: 0.03289 Total loss: 0.90656 timestamp: 1654967885.868312 iteration: 69535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08412 FastRCNN class loss: 0.08552 FastRCNN total loss: 0.16964 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.0004 Mask loss: 0.14171 RPN box loss: 0.00759 RPN score loss: 0.00504 RPN total loss: 0.01263 Total loss: 0.91506 timestamp: 1654967889.046612 iteration: 69540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09598 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.18242 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.0004 Mask loss: 0.1359 RPN box loss: 0.01056 RPN score loss: 0.00115 RPN total loss: 0.01171 Total loss: 0.92111 timestamp: 1654967892.297641 iteration: 69545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11069 FastRCNN class loss: 0.08605 FastRCNN total loss: 0.19673 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.0004 Mask loss: 0.14817 RPN box loss: 0.03366 RPN score loss: 0.00439 RPN total loss: 0.03805 Total loss: 0.97403 timestamp: 1654967895.5260506 iteration: 69550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08867 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.16992 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.0004 Mask loss: 0.13371 RPN box loss: 0.00905 RPN score loss: 0.0046 RPN total loss: 0.01365 Total loss: 0.90835 timestamp: 1654967898.7725036 iteration: 69555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11067 FastRCNN class loss: 0.05821 FastRCNN total loss: 0.16888 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.0004 Mask loss: 0.11015 RPN box loss: 0.0098 RPN score loss: 0.00367 RPN total loss: 0.01347 Total loss: 0.88356 timestamp: 1654967901.9697132 iteration: 69560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09171 FastRCNN class loss: 0.06723 FastRCNN total loss: 0.15894 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.0004 Mask loss: 0.11131 RPN box loss: 0.00926 RPN score loss: 0.00259 RPN total loss: 0.01184 Total loss: 0.87316 timestamp: 1654967905.1159754 iteration: 69565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07046 FastRCNN class loss: 0.04244 FastRCNN total loss: 0.11291 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.09532 RPN box loss: 0.01053 RPN score loss: 0.00921 RPN total loss: 0.01974 Total loss: 0.81903 timestamp: 1654967908.3183694 iteration: 69570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0902 FastRCNN class loss: 0.08136 FastRCNN total loss: 0.17156 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.13839 RPN box loss: 0.01672 RPN score loss: 0.00265 RPN total loss: 0.01937 Total loss: 0.92038 timestamp: 1654967911.581589 iteration: 69575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07742 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.16353 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.12019 RPN box loss: 0.02564 RPN score loss: 0.00313 RPN total loss: 0.02877 Total loss: 0.90354 timestamp: 1654967914.7124076 iteration: 69580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10217 FastRCNN class loss: 0.07844 FastRCNN total loss: 0.18061 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.12539 RPN box loss: 0.01375 RPN score loss: 0.00453 RPN total loss: 0.01827 Total loss: 0.91534 timestamp: 1654967917.9455018 iteration: 69585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12259 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.18653 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.12554 RPN box loss: 0.00922 RPN score loss: 0.00876 RPN total loss: 0.01798 Total loss: 0.92111 timestamp: 1654967921.1226852 iteration: 69590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09056 FastRCNN class loss: 0.05602 FastRCNN total loss: 0.14658 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.10797 RPN box loss: 0.00567 RPN score loss: 0.00199 RPN total loss: 0.00767 Total loss: 0.85327 timestamp: 1654967924.348791 iteration: 69595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14941 FastRCNN class loss: 0.07427 FastRCNN total loss: 0.22368 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.0004 Mask loss: 0.11269 RPN box loss: 0.00752 RPN score loss: 0.00254 RPN total loss: 0.01007 Total loss: 0.9375 timestamp: 1654967927.5588088 iteration: 69600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06995 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.134 L1 loss: 0.0000e+00 L2 loss: 0.59105 Learning rate: 0.0004 Mask loss: 0.14607 RPN box loss: 0.00521 RPN score loss: 0.00445 RPN total loss: 0.00966 Total loss: 0.88079 timestamp: 1654967930.757083 iteration: 69605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09184 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.14754 L1 loss: 0.0000e+00 L2 loss: 0.59105 Learning rate: 0.0004 Mask loss: 0.12938 RPN box loss: 0.00721 RPN score loss: 0.00393 RPN total loss: 0.01113 Total loss: 0.87911 timestamp: 1654967933.9894946 iteration: 69610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1344 FastRCNN class loss: 0.10539 FastRCNN total loss: 0.2398 L1 loss: 0.0000e+00 L2 loss: 0.59105 Learning rate: 0.0004 Mask loss: 0.1666 RPN box loss: 0.04352 RPN score loss: 0.01438 RPN total loss: 0.0579 Total loss: 1.05534 timestamp: 1654967937.1601675 iteration: 69615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10094 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.15219 L1 loss: 0.0000e+00 L2 loss: 0.59105 Learning rate: 0.0004 Mask loss: 0.10206 RPN box loss: 0.0166 RPN score loss: 0.00145 RPN total loss: 0.01805 Total loss: 0.86335 timestamp: 1654967940.406654 iteration: 69620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04076 FastRCNN class loss: 0.02271 FastRCNN total loss: 0.06347 L1 loss: 0.0000e+00 L2 loss: 0.59105 Learning rate: 0.0004 Mask loss: 0.08145 RPN box loss: 0.01544 RPN score loss: 0.00467 RPN total loss: 0.02012 Total loss: 0.75609 timestamp: 1654967943.6811063 iteration: 69625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06773 FastRCNN class loss: 0.04525 FastRCNN total loss: 0.11298 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.0004 Mask loss: 0.12026 RPN box loss: 0.00465 RPN score loss: 0.00249 RPN total loss: 0.00715 Total loss: 0.83143 timestamp: 1654967946.8990352 iteration: 69630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12558 FastRCNN class loss: 0.08629 FastRCNN total loss: 0.21187 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.0004 Mask loss: 0.15318 RPN box loss: 0.0177 RPN score loss: 0.00374 RPN total loss: 0.02144 Total loss: 0.97753 timestamp: 1654967950.0998178 iteration: 69635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09075 FastRCNN class loss: 0.0529 FastRCNN total loss: 0.14365 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.0004 Mask loss: 0.13829 RPN box loss: 0.00471 RPN score loss: 0.00408 RPN total loss: 0.00879 Total loss: 0.88177 timestamp: 1654967953.3321538 iteration: 69640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09676 FastRCNN class loss: 0.04251 FastRCNN total loss: 0.13926 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.0004 Mask loss: 0.12932 RPN box loss: 0.01557 RPN score loss: 0.00351 RPN total loss: 0.01908 Total loss: 0.8787 timestamp: 1654967956.4834504 iteration: 69645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11222 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.18003 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.0004 Mask loss: 0.09807 RPN box loss: 0.00947 RPN score loss: 0.00761 RPN total loss: 0.01707 Total loss: 0.88621 timestamp: 1654967959.717927 iteration: 69650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06381 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.11486 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.0004 Mask loss: 0.12302 RPN box loss: 0.01056 RPN score loss: 0.00882 RPN total loss: 0.01938 Total loss: 0.84831 timestamp: 1654967962.9601905 iteration: 69655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08336 FastRCNN class loss: 0.06023 FastRCNN total loss: 0.14359 L1 loss: 0.0000e+00 L2 loss: 0.59103 Learning rate: 0.0004 Mask loss: 0.12366 RPN box loss: 0.01435 RPN score loss: 0.00314 RPN total loss: 0.01749 Total loss: 0.87578 timestamp: 1654967966.2014878 iteration: 69660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06965 FastRCNN class loss: 0.10246 FastRCNN total loss: 0.17211 L1 loss: 0.0000e+00 L2 loss: 0.59103 Learning rate: 0.0004 Mask loss: 0.12586 RPN box loss: 0.01086 RPN score loss: 0.00398 RPN total loss: 0.01484 Total loss: 0.90384 timestamp: 1654967969.3888514 iteration: 69665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09354 FastRCNN class loss: 0.10001 FastRCNN total loss: 0.19355 L1 loss: 0.0000e+00 L2 loss: 0.59103 Learning rate: 0.0004 Mask loss: 0.15358 RPN box loss: 0.00909 RPN score loss: 0.00215 RPN total loss: 0.01124 Total loss: 0.9494 timestamp: 1654967972.510756 iteration: 69670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1056 FastRCNN class loss: 0.05651 FastRCNN total loss: 0.16211 L1 loss: 0.0000e+00 L2 loss: 0.59103 Learning rate: 0.0004 Mask loss: 0.09429 RPN box loss: 0.01075 RPN score loss: 0.00433 RPN total loss: 0.01509 Total loss: 0.86251 timestamp: 1654967975.635767 iteration: 69675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.05412 FastRCNN total loss: 0.13908 L1 loss: 0.0000e+00 L2 loss: 0.59103 Learning rate: 0.0004 Mask loss: 0.16974 RPN box loss: 0.00873 RPN score loss: 0.00201 RPN total loss: 0.01074 Total loss: 0.91059 timestamp: 1654967978.777365 iteration: 69680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10639 FastRCNN class loss: 0.04109 FastRCNN total loss: 0.14748 L1 loss: 0.0000e+00 L2 loss: 0.59102 Learning rate: 0.0004 Mask loss: 0.11857 RPN box loss: 0.00393 RPN score loss: 0.00561 RPN total loss: 0.00954 Total loss: 0.86662 timestamp: 1654967982.0250182 iteration: 69685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07013 FastRCNN class loss: 0.05001 FastRCNN total loss: 0.12014 L1 loss: 0.0000e+00 L2 loss: 0.59102 Learning rate: 0.0004 Mask loss: 0.15182 RPN box loss: 0.00767 RPN score loss: 0.00192 RPN total loss: 0.00959 Total loss: 0.87256 timestamp: 1654967985.216283 iteration: 69690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04696 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.09774 L1 loss: 0.0000e+00 L2 loss: 0.59102 Learning rate: 0.0004 Mask loss: 0.12576 RPN box loss: 0.00744 RPN score loss: 0.00195 RPN total loss: 0.00939 Total loss: 0.82392 timestamp: 1654967988.3934026 iteration: 69695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08253 FastRCNN class loss: 0.05098 FastRCNN total loss: 0.13351 L1 loss: 0.0000e+00 L2 loss: 0.59102 Learning rate: 0.0004 Mask loss: 0.09136 RPN box loss: 0.00487 RPN score loss: 0.00095 RPN total loss: 0.00583 Total loss: 0.82171 timestamp: 1654967991.6566157 iteration: 69700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13423 FastRCNN class loss: 0.08275 FastRCNN total loss: 0.21698 L1 loss: 0.0000e+00 L2 loss: 0.59102 Learning rate: 0.0004 Mask loss: 0.06213 RPN box loss: 0.00533 RPN score loss: 0.00239 RPN total loss: 0.00772 Total loss: 0.87786 timestamp: 1654967994.9336212 iteration: 69705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08243 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.14918 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.09919 RPN box loss: 0.0041 RPN score loss: 0.0011 RPN total loss: 0.0052 Total loss: 0.84459 timestamp: 1654967998.1355844 iteration: 69710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10825 FastRCNN class loss: 0.06503 FastRCNN total loss: 0.17328 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.09526 RPN box loss: 0.0089 RPN score loss: 0.0028 RPN total loss: 0.0117 Total loss: 0.87125 timestamp: 1654968001.298464 iteration: 69715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0811 FastRCNN class loss: 0.09687 FastRCNN total loss: 0.17796 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.15438 RPN box loss: 0.01085 RPN score loss: 0.00454 RPN total loss: 0.01539 Total loss: 0.93875 timestamp: 1654968004.4757032 iteration: 69720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11834 FastRCNN class loss: 0.09535 FastRCNN total loss: 0.21369 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.1518 RPN box loss: 0.01729 RPN score loss: 0.00792 RPN total loss: 0.02522 Total loss: 0.98172 timestamp: 1654968007.704114 iteration: 69725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11069 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.178 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.13183 RPN box loss: 0.00709 RPN score loss: 0.00294 RPN total loss: 0.01003 Total loss: 0.91088 timestamp: 1654968010.9593432 iteration: 69730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05743 FastRCNN class loss: 0.03631 FastRCNN total loss: 0.09374 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.09734 RPN box loss: 0.00282 RPN score loss: 0.0099 RPN total loss: 0.01272 Total loss: 0.79481 timestamp: 1654968014.2649436 iteration: 69735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04913 FastRCNN class loss: 0.03398 FastRCNN total loss: 0.08311 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.0004 Mask loss: 0.11228 RPN box loss: 0.00627 RPN score loss: 0.0028 RPN total loss: 0.00907 Total loss: 0.79546 timestamp: 1654968017.458909 iteration: 69740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04856 FastRCNN class loss: 0.086 FastRCNN total loss: 0.13456 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.14744 RPN box loss: 0.04195 RPN score loss: 0.01615 RPN total loss: 0.05809 Total loss: 0.93109 timestamp: 1654968020.6322134 iteration: 69745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0681 FastRCNN class loss: 0.04216 FastRCNN total loss: 0.11026 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.16355 RPN box loss: 0.0184 RPN score loss: 0.00681 RPN total loss: 0.02521 Total loss: 0.89003 timestamp: 1654968023.7535925 iteration: 69750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08192 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.15856 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.16094 RPN box loss: 0.01833 RPN score loss: 0.00624 RPN total loss: 0.02458 Total loss: 0.93507 timestamp: 1654968026.9043112 iteration: 69755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03485 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.09225 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.10647 RPN box loss: 0.00589 RPN score loss: 0.002 RPN total loss: 0.00789 Total loss: 0.79761 timestamp: 1654968030.0709984 iteration: 69760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0599 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.12581 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.10644 RPN box loss: 0.00913 RPN score loss: 0.00416 RPN total loss: 0.01329 Total loss: 0.83654 timestamp: 1654968033.2632294 iteration: 69765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10355 FastRCNN class loss: 0.09507 FastRCNN total loss: 0.19862 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.16137 RPN box loss: 0.00878 RPN score loss: 0.00623 RPN total loss: 0.01502 Total loss: 0.966 timestamp: 1654968036.4272532 iteration: 69770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12221 FastRCNN class loss: 0.05154 FastRCNN total loss: 0.17375 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.0004 Mask loss: 0.12756 RPN box loss: 0.01239 RPN score loss: 0.0017 RPN total loss: 0.0141 Total loss: 0.9064 timestamp: 1654968039.6262546 iteration: 69775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10633 FastRCNN class loss: 0.08137 FastRCNN total loss: 0.1877 L1 loss: 0.0000e+00 L2 loss: 0.59099 Learning rate: 0.0004 Mask loss: 0.14561 RPN box loss: 0.03125 RPN score loss: 0.00329 RPN total loss: 0.03453 Total loss: 0.95884 timestamp: 1654968042.8108943 iteration: 69780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07804 FastRCNN class loss: 0.10628 FastRCNN total loss: 0.18432 L1 loss: 0.0000e+00 L2 loss: 0.59099 Learning rate: 0.0004 Mask loss: 0.11896 RPN box loss: 0.01749 RPN score loss: 0.00396 RPN total loss: 0.02146 Total loss: 0.91573 timestamp: 1654968046.0096478 iteration: 69785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06831 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.14288 L1 loss: 0.0000e+00 L2 loss: 0.59099 Learning rate: 0.0004 Mask loss: 0.15205 RPN box loss: 0.02861 RPN score loss: 0.00554 RPN total loss: 0.03415 Total loss: 0.92007 timestamp: 1654968049.118109 iteration: 69790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08741 FastRCNN class loss: 0.05208 FastRCNN total loss: 0.13948 L1 loss: 0.0000e+00 L2 loss: 0.59099 Learning rate: 0.0004 Mask loss: 0.12316 RPN box loss: 0.0046 RPN score loss: 0.00182 RPN total loss: 0.00642 Total loss: 0.86005 timestamp: 1654968052.2601566 iteration: 69795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09716 FastRCNN class loss: 0.13576 FastRCNN total loss: 0.23293 L1 loss: 0.0000e+00 L2 loss: 0.59099 Learning rate: 0.0004 Mask loss: 0.18059 RPN box loss: 0.03514 RPN score loss: 0.00991 RPN total loss: 0.04505 Total loss: 1.04955 timestamp: 1654968055.5045836 iteration: 69800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06709 FastRCNN class loss: 0.05828 FastRCNN total loss: 0.12537 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.0004 Mask loss: 0.09097 RPN box loss: 0.00686 RPN score loss: 0.00545 RPN total loss: 0.01231 Total loss: 0.81964 timestamp: 1654968058.7798126 iteration: 69805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05649 FastRCNN class loss: 0.04045 FastRCNN total loss: 0.09695 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.0004 Mask loss: 0.09071 RPN box loss: 0.00291 RPN score loss: 0.00158 RPN total loss: 0.00449 Total loss: 0.78313 timestamp: 1654968062.0271509 iteration: 69810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04599 FastRCNN class loss: 0.0359 FastRCNN total loss: 0.0819 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.0004 Mask loss: 0.08981 RPN box loss: 0.00565 RPN score loss: 0.00445 RPN total loss: 0.0101 Total loss: 0.77279 timestamp: 1654968065.232927 iteration: 69815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07531 FastRCNN class loss: 0.09743 FastRCNN total loss: 0.17274 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.0004 Mask loss: 0.12722 RPN box loss: 0.01508 RPN score loss: 0.00762 RPN total loss: 0.02269 Total loss: 0.91362 timestamp: 1654968068.58285 iteration: 69820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0768 FastRCNN class loss: 0.05591 FastRCNN total loss: 0.13271 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.0004 Mask loss: 0.1426 RPN box loss: 0.01277 RPN score loss: 0.00312 RPN total loss: 0.01589 Total loss: 0.88217 timestamp: 1654968071.716669 iteration: 69825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12459 FastRCNN class loss: 0.08485 FastRCNN total loss: 0.20945 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.0004 Mask loss: 0.14016 RPN box loss: 0.01004 RPN score loss: 0.00259 RPN total loss: 0.01263 Total loss: 0.95321 timestamp: 1654968074.8760512 iteration: 69830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05664 FastRCNN class loss: 0.03402 FastRCNN total loss: 0.09066 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.13809 RPN box loss: 0.00374 RPN score loss: 0.00135 RPN total loss: 0.00509 Total loss: 0.82481 timestamp: 1654968078.174975 iteration: 69835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14142 FastRCNN class loss: 0.09132 FastRCNN total loss: 0.23274 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.19087 RPN box loss: 0.01431 RPN score loss: 0.00434 RPN total loss: 0.01866 Total loss: 1.03324 timestamp: 1654968081.3225625 iteration: 69840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0607 FastRCNN class loss: 0.04854 FastRCNN total loss: 0.10924 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.1243 RPN box loss: 0.00515 RPN score loss: 0.00617 RPN total loss: 0.01132 Total loss: 0.83583 timestamp: 1654968084.5261514 iteration: 69845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07672 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.14301 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.10407 RPN box loss: 0.02659 RPN score loss: 0.00939 RPN total loss: 0.03598 Total loss: 0.87402 timestamp: 1654968087.66259 iteration: 69850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08605 FastRCNN class loss: 0.05489 FastRCNN total loss: 0.14094 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.12301 RPN box loss: 0.0219 RPN score loss: 0.00611 RPN total loss: 0.02802 Total loss: 0.88294 timestamp: 1654968090.920529 iteration: 69855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09684 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.16113 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.11813 RPN box loss: 0.00756 RPN score loss: 0.00285 RPN total loss: 0.01041 Total loss: 0.88064 timestamp: 1654968094.062935 iteration: 69860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06173 FastRCNN class loss: 0.0506 FastRCNN total loss: 0.11234 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.11793 RPN box loss: 0.00621 RPN score loss: 0.00148 RPN total loss: 0.00769 Total loss: 0.82892 timestamp: 1654968097.2660034 iteration: 69865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06613 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.12781 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.0004 Mask loss: 0.15268 RPN box loss: 0.00517 RPN score loss: 0.00301 RPN total loss: 0.00818 Total loss: 0.87962 timestamp: 1654968100.5148787 iteration: 69870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08453 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.1463 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.0004 Mask loss: 0.1281 RPN box loss: 0.0121 RPN score loss: 0.00474 RPN total loss: 0.01684 Total loss: 0.88221 timestamp: 1654968103.7055688 iteration: 69875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08864 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.15117 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.0004 Mask loss: 0.13282 RPN box loss: 0.00524 RPN score loss: 0.00284 RPN total loss: 0.00809 Total loss: 0.88303 timestamp: 1654968106.8916528 iteration: 69880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10806 FastRCNN class loss: 0.05508 FastRCNN total loss: 0.16315 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.0004 Mask loss: 0.14263 RPN box loss: 0.00431 RPN score loss: 0.01138 RPN total loss: 0.01569 Total loss: 0.91242 timestamp: 1654968110.0866807 iteration: 69885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05304 FastRCNN class loss: 0.06361 FastRCNN total loss: 0.11665 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.0004 Mask loss: 0.12561 RPN box loss: 0.00699 RPN score loss: 0.0042 RPN total loss: 0.01119 Total loss: 0.8444 timestamp: 1654968113.248987 iteration: 69890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08093 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.15395 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.0004 Mask loss: 0.1314 RPN box loss: 0.01251 RPN score loss: 0.00728 RPN total loss: 0.01979 Total loss: 0.89611 timestamp: 1654968116.4159021 iteration: 69895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07775 FastRCNN class loss: 0.05306 FastRCNN total loss: 0.13081 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.0004 Mask loss: 0.12082 RPN box loss: 0.00442 RPN score loss: 0.00105 RPN total loss: 0.00547 Total loss: 0.84805 timestamp: 1654968119.5624356 iteration: 69900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07561 FastRCNN class loss: 0.07939 FastRCNN total loss: 0.155 L1 loss: 0.0000e+00 L2 loss: 0.59095 Learning rate: 0.0004 Mask loss: 0.11139 RPN box loss: 0.00661 RPN score loss: 0.00966 RPN total loss: 0.01627 Total loss: 0.87362 timestamp: 1654968122.7394114 iteration: 69905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10797 FastRCNN class loss: 0.10462 FastRCNN total loss: 0.2126 L1 loss: 0.0000e+00 L2 loss: 0.59095 Learning rate: 0.0004 Mask loss: 0.24887 RPN box loss: 0.01698 RPN score loss: 0.00961 RPN total loss: 0.02659 Total loss: 1.07901 timestamp: 1654968125.9874086 iteration: 69910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11966 FastRCNN class loss: 0.06363 FastRCNN total loss: 0.18329 L1 loss: 0.0000e+00 L2 loss: 0.59095 Learning rate: 0.0004 Mask loss: 0.15448 RPN box loss: 0.00813 RPN score loss: 0.00551 RPN total loss: 0.01365 Total loss: 0.94236 timestamp: 1654968129.239394 iteration: 69915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12282 FastRCNN class loss: 0.05719 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 0.59095 Learning rate: 0.0004 Mask loss: 0.15102 RPN box loss: 0.02814 RPN score loss: 0.01129 RPN total loss: 0.03943 Total loss: 0.96141 timestamp: 1654968132.4191504 iteration: 69920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06502 FastRCNN class loss: 0.03926 FastRCNN total loss: 0.10429 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.08194 RPN box loss: 0.00621 RPN score loss: 0.00592 RPN total loss: 0.01213 Total loss: 0.7893 timestamp: 1654968135.6261113 iteration: 69925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1343 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.22148 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.22051 RPN box loss: 0.0137 RPN score loss: 0.00619 RPN total loss: 0.0199 Total loss: 1.05282 timestamp: 1654968138.8634925 iteration: 69930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1272 FastRCNN class loss: 0.08681 FastRCNN total loss: 0.21401 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.16001 RPN box loss: 0.01148 RPN score loss: 0.00527 RPN total loss: 0.01675 Total loss: 0.98171 timestamp: 1654968142.071241 iteration: 69935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10834 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.17953 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.14139 RPN box loss: 0.01772 RPN score loss: 0.00115 RPN total loss: 0.01887 Total loss: 0.93073 timestamp: 1654968145.284786 iteration: 69940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08203 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.16378 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.16452 RPN box loss: 0.01197 RPN score loss: 0.00862 RPN total loss: 0.02058 Total loss: 0.93982 timestamp: 1654968148.5053463 iteration: 69945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06593 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.12097 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.11535 RPN box loss: 0.00806 RPN score loss: 0.00122 RPN total loss: 0.00928 Total loss: 0.83654 timestamp: 1654968151.699323 iteration: 69950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10659 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.17871 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.0004 Mask loss: 0.135 RPN box loss: 0.01326 RPN score loss: 0.00137 RPN total loss: 0.01463 Total loss: 0.91927 timestamp: 1654968154.8252761 iteration: 69955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05289 FastRCNN class loss: 0.05489 FastRCNN total loss: 0.10777 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.0004 Mask loss: 0.14217 RPN box loss: 0.00346 RPN score loss: 0.00171 RPN total loss: 0.00517 Total loss: 0.84604 timestamp: 1654968158.0399528 iteration: 69960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1063 FastRCNN class loss: 0.04918 FastRCNN total loss: 0.15549 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.0004 Mask loss: 0.11575 RPN box loss: 0.0153 RPN score loss: 0.00375 RPN total loss: 0.01905 Total loss: 0.88121 timestamp: 1654968161.1995115 iteration: 69965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05767 FastRCNN class loss: 0.03755 FastRCNN total loss: 0.09522 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.0004 Mask loss: 0.09349 RPN box loss: 0.00405 RPN score loss: 0.00272 RPN total loss: 0.00677 Total loss: 0.78641 timestamp: 1654968164.3902295 iteration: 69970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08829 FastRCNN class loss: 0.06615 FastRCNN total loss: 0.15444 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.0004 Mask loss: 0.16484 RPN box loss: 0.01051 RPN score loss: 0.0045 RPN total loss: 0.01501 Total loss: 0.92521 timestamp: 1654968167.5649447 iteration: 69975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0539 FastRCNN class loss: 0.04154 FastRCNN total loss: 0.09544 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.0004 Mask loss: 0.09047 RPN box loss: 0.00556 RPN score loss: 0.00091 RPN total loss: 0.00648 Total loss: 0.78331 timestamp: 1654968170.7613223 iteration: 69980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14579 FastRCNN class loss: 0.09855 FastRCNN total loss: 0.24434 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.0004 Mask loss: 0.11213 RPN box loss: 0.02415 RPN score loss: 0.00359 RPN total loss: 0.02773 Total loss: 0.97512 timestamp: 1654968173.9000258 iteration: 69985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.06567 FastRCNN total loss: 0.17263 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.0004 Mask loss: 0.16828 RPN box loss: 0.01932 RPN score loss: 0.00909 RPN total loss: 0.0284 Total loss: 0.96023 timestamp: 1654968177.1328506 iteration: 69990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09139 FastRCNN class loss: 0.08072 FastRCNN total loss: 0.17211 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.0004 Mask loss: 0.08914 RPN box loss: 0.00385 RPN score loss: 0.00273 RPN total loss: 0.00658 Total loss: 0.85876 timestamp: 1654968180.3550253 iteration: 69995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10107 FastRCNN class loss: 0.06649 FastRCNN total loss: 0.16756 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.0004 Mask loss: 0.21327 RPN box loss: 0.01877 RPN score loss: 0.00534 RPN total loss: 0.02412 Total loss: 0.99587 timestamp: 1654968183.5887637 iteration: 70000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07684 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.14075 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.0004 Mask loss: 0.15126 RPN box loss: 0.01264 RPN score loss: 0.00585 RPN total loss: 0.01848 Total loss: 0.90142 Saving checkpoints for 70000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-70000.tlt. ================================= Start evaluation cycle 07 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-70000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.7935s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.3618s - Throughput: 11.1 imgs/s Running inference on batch 003/125... - Step Time: 0.3447s - Throughput: 11.6 imgs/s Running inference on batch 004/125... - Step Time: 0.3532s - Throughput: 11.3 imgs/s Running inference on batch 005/125... - Step Time: 0.3401s - Throughput: 11.8 imgs/s Running inference on batch 006/125... - Step Time: 0.3415s - Throughput: 11.7 imgs/s Running inference on batch 007/125... - Step Time: 0.3511s - Throughput: 11.4 imgs/s Running inference on batch 008/125... - Step Time: 0.3065s - Throughput: 13.0 imgs/s Running inference on batch 009/125... - Step Time: 0.3438s - Throughput: 11.6 imgs/s Running inference on batch 010/125... - Step Time: 0.3121s - Throughput: 12.8 imgs/s Running inference on batch 011/125... - Step Time: 0.3402s - Throughput: 11.8 imgs/s Running inference on batch 012/125... - Step Time: 0.3059s - Throughput: 13.1 imgs/s Running inference on batch 013/125... - Step Time: 0.3390s - Throughput: 11.8 imgs/s Running inference on batch 014/125... - Step Time: 0.3362s - Throughput: 11.9 imgs/s Running inference on batch 015/125... - Step Time: 0.3131s - Throughput: 12.8 imgs/s Running inference on batch 016/125... - Step Time: 0.3322s - Throughput: 12.0 imgs/s Running inference on batch 017/125... - Step Time: 0.3336s - Throughput: 12.0 imgs/s Running inference on batch 018/125... - Step Time: 0.3374s - Throughput: 11.9 imgs/s Running inference on batch 019/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 020/125... - Step Time: 0.3417s - Throughput: 11.7 imgs/s Running inference on batch 021/125... - Step Time: 0.3334s - Throughput: 12.0 imgs/s Running inference on batch 022/125... - Step Time: 0.3128s - Throughput: 12.8 imgs/s Running inference on batch 023/125... - Step Time: 0.3434s - Throughput: 11.6 imgs/s Running inference on batch 024/125... - Step Time: 0.3325s - Throughput: 12.0 imgs/s Running inference on batch 025/125... - Step Time: 0.3403s - Throughput: 11.8 imgs/s Running inference on batch 026/125... - Step Time: 0.3337s - Throughput: 12.0 imgs/s Running inference on batch 027/125... - Step Time: 0.3023s - Throughput: 13.2 imgs/s Running inference on batch 028/125... - Step Time: 0.3261s - Throughput: 12.3 imgs/s Running inference on batch 029/125... - Step Time: 0.3450s - Throughput: 11.6 imgs/s Running inference on batch 030/125... - Step Time: 0.3403s - Throughput: 11.8 imgs/s Running inference on batch 031/125... - Step Time: 0.3529s - Throughput: 11.3 imgs/s Running inference on batch 032/125... - Step Time: 0.3479s - Throughput: 11.5 imgs/s Running inference on batch 033/125... - Step Time: 0.3452s - Throughput: 11.6 imgs/s Running inference on batch 034/125... - Step Time: 0.3432s - Throughput: 11.7 imgs/s Running inference on batch 035/125... - Step Time: 0.3244s - Throughput: 12.3 imgs/s Running inference on batch 036/125... - Step Time: 0.3518s - Throughput: 11.4 imgs/s Running inference on batch 037/125... - Step Time: 0.3445s - Throughput: 11.6 imgs/s Running inference on batch 038/125... - Step Time: 0.3465s - Throughput: 11.5 imgs/s Running inference on batch 039/125... - Step Time: 0.3136s - Throughput: 12.8 imgs/s Running inference on batch 040/125... - Step Time: 0.3350s - Throughput: 11.9 imgs/s Running inference on batch 041/125... - Step Time: 0.3466s - Throughput: 11.5 imgs/s Running inference on batch 042/125... - Step Time: 0.2991s - Throughput: 13.4 imgs/s Running inference on batch 043/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 044/125... - Step Time: 0.3331s - Throughput: 12.0 imgs/s Running inference on batch 045/125... - Step Time: 0.3397s - Throughput: 11.8 imgs/s Running inference on batch 046/125... - Step Time: 0.3498s - Throughput: 11.4 imgs/s Running inference on batch 047/125... - Step Time: 0.3505s - Throughput: 11.4 imgs/s Running inference on batch 048/125... - Step Time: 0.3520s - Throughput: 11.4 imgs/s Running inference on batch 049/125... - Step Time: 0.3368s - Throughput: 11.9 imgs/s Running inference on batch 050/125... - Step Time: 0.3339s - Throughput: 12.0 imgs/s Running inference on batch 051/125... - Step Time: 0.3386s - Throughput: 11.8 imgs/s Running inference on batch 052/125... - Step Time: 0.3417s - Throughput: 11.7 imgs/s Running inference on batch 053/125... - Step Time: 0.3413s - Throughput: 11.7 imgs/s Running inference on batch 054/125... - Step Time: 0.3398s - Throughput: 11.8 imgs/s Running inference on batch 055/125... - Step Time: 0.3287s - Throughput: 12.2 imgs/s Running inference on batch 056/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 057/125... - Step Time: 0.3400s - Throughput: 11.8 imgs/s Running inference on batch 058/125... - Step Time: 0.3402s - Throughput: 11.8 imgs/s Running inference on batch 059/125... - Step Time: 0.3354s - 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Throughput: 11.4 imgs/s Running inference on batch 120/125... - Step Time: 0.3396s - Throughput: 11.8 imgs/s Running inference on batch 121/125... - Step Time: 0.3291s - Throughput: 12.2 imgs/s Running inference on batch 122/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 123/125... - Step Time: 0.3359s - Throughput: 11.9 imgs/s Running inference on batch 124/125... - Step Time: 0.3553s - Throughput: 11.3 imgs/s Running inference on batch 125/125... - Step Time: 0.3358s - Throughput: 11.9 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 11.7 samples/sec Total processed steps: 125 Total processing time: 0.0h 24m 23s ==================== Metrics ==================== AP: 0.209833443 AP50: 0.329022795 AP75: 0.206755862 APl: 0.246728152 APm: 0.044402558 APs: 0.002647776 ARl: 0.450230062 ARm: 0.103827044 ARmax1: 0.298158705 ARmax10: 0.381395280 ARmax100: 0.386314541 ARs: 0.019573843 mask_AP: 0.171210110 mask_AP50: 0.289908290 mask_AP75: 0.174835399 mask_APl: 0.202703640 mask_APm: 0.027543951 mask_APs: 0.000132487 mask_ARl: 0.319115371 mask_ARm: 0.061924137 mask_ARmax1: 0.228403062 mask_ARmax10: 0.267466098 mask_ARmax100: 0.270373017 mask_ARs: 0.007971015 ================================= Start training cycle 08 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654969348.981082 iteration: 70005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08701 FastRCNN class loss: 0.04583 FastRCNN total loss: 0.13284 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.0004 Mask loss: 0.11266 RPN box loss: 0.01035 RPN score loss: 0.00204 RPN total loss: 0.01238 Total loss: 0.84879 timestamp: 1654969352.1083016 iteration: 70010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05331 FastRCNN class loss: 0.05918 FastRCNN total loss: 0.1125 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.0004 Mask loss: 0.10518 RPN box loss: 0.01098 RPN score loss: 0.00301 RPN total loss: 0.01399 Total loss: 0.82258 timestamp: 1654969355.2560213 iteration: 70015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06805 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.12661 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.0004 Mask loss: 0.14679 RPN box loss: 0.0072 RPN score loss: 0.0032 RPN total loss: 0.0104 Total loss: 0.87471 timestamp: 1654969358.4221628 iteration: 70020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11255 FastRCNN class loss: 0.05114 FastRCNN total loss: 0.1637 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.0004 Mask loss: 0.13233 RPN box loss: 0.00627 RPN score loss: 0.00076 RPN total loss: 0.00703 Total loss: 0.89397 timestamp: 1654969361.6091728 iteration: 70025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09178 FastRCNN class loss: 0.05025 FastRCNN total loss: 0.14203 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.0004 Mask loss: 0.13457 RPN box loss: 0.01616 RPN score loss: 0.00481 RPN total loss: 0.02098 Total loss: 0.88849 timestamp: 1654969364.807654 iteration: 70030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07012 FastRCNN class loss: 0.0588 FastRCNN total loss: 0.12891 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.0004 Mask loss: 0.08143 RPN box loss: 0.00686 RPN score loss: 0.00331 RPN total loss: 0.01017 Total loss: 0.81142 timestamp: 1654969368.0209715 iteration: 70035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0617 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.12004 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.0004 Mask loss: 0.15529 RPN box loss: 0.00628 RPN score loss: 0.00164 RPN total loss: 0.00792 Total loss: 0.87415 timestamp: 1654969371.2083926 iteration: 70040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10122 FastRCNN class loss: 0.06624 FastRCNN total loss: 0.16746 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.0004 Mask loss: 0.13836 RPN box loss: 0.00487 RPN score loss: 0.00264 RPN total loss: 0.00751 Total loss: 0.90423 timestamp: 1654969374.376724 iteration: 70045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15959 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.22309 L1 loss: 0.0000e+00 L2 loss: 0.5909 Learning rate: 0.0004 Mask loss: 0.08896 RPN box loss: 0.01404 RPN score loss: 0.00526 RPN total loss: 0.0193 Total loss: 0.92226 timestamp: 1654969377.6778212 iteration: 70050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08456 FastRCNN class loss: 0.07385 FastRCNN total loss: 0.15842 L1 loss: 0.0000e+00 L2 loss: 0.5909 Learning rate: 0.0004 Mask loss: 0.14905 RPN box loss: 0.00872 RPN score loss: 0.00136 RPN total loss: 0.01008 Total loss: 0.90845 timestamp: 1654969380.888683 iteration: 70055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.04919 FastRCNN total loss: 0.11497 L1 loss: 0.0000e+00 L2 loss: 0.5909 Learning rate: 0.0004 Mask loss: 0.10755 RPN box loss: 0.00689 RPN score loss: 0.00349 RPN total loss: 0.01038 Total loss: 0.8238 timestamp: 1654969384.0621202 iteration: 70060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1173 FastRCNN class loss: 0.11478 FastRCNN total loss: 0.23208 L1 loss: 0.0000e+00 L2 loss: 0.5909 Learning rate: 0.0004 Mask loss: 0.18037 RPN box loss: 0.02023 RPN score loss: 0.01075 RPN total loss: 0.03098 Total loss: 1.03432 timestamp: 1654969387.3004434 iteration: 70065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07565 FastRCNN class loss: 0.05702 FastRCNN total loss: 0.13267 L1 loss: 0.0000e+00 L2 loss: 0.5909 Learning rate: 0.0004 Mask loss: 0.13721 RPN box loss: 0.01544 RPN score loss: 0.00123 RPN total loss: 0.01667 Total loss: 0.87745 timestamp: 1654969390.5505064 iteration: 70070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09875 FastRCNN class loss: 0.07737 FastRCNN total loss: 0.17612 L1 loss: 0.0000e+00 L2 loss: 0.5909 Learning rate: 0.0004 Mask loss: 0.10819 RPN box loss: 0.01019 RPN score loss: 0.00471 RPN total loss: 0.0149 Total loss: 0.8901 timestamp: 1654969393.734873 iteration: 70075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10702 FastRCNN class loss: 0.06837 FastRCNN total loss: 0.1754 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.0004 Mask loss: 0.13458 RPN box loss: 0.00965 RPN score loss: 0.00682 RPN total loss: 0.01647 Total loss: 0.91734 timestamp: 1654969396.9635437 iteration: 70080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06415 FastRCNN class loss: 0.02945 FastRCNN total loss: 0.0936 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.0004 Mask loss: 0.12244 RPN box loss: 0.00459 RPN score loss: 0.00213 RPN total loss: 0.00672 Total loss: 0.81366 timestamp: 1654969400.2292273 iteration: 70085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10378 FastRCNN class loss: 0.077 FastRCNN total loss: 0.18078 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.0004 Mask loss: 0.16289 RPN box loss: 0.01256 RPN score loss: 0.00635 RPN total loss: 0.01891 Total loss: 0.95348 timestamp: 1654969403.4402738 iteration: 70090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15081 FastRCNN class loss: 0.0925 FastRCNN total loss: 0.2433 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.0004 Mask loss: 0.12952 RPN box loss: 0.01212 RPN score loss: 0.00607 RPN total loss: 0.01819 Total loss: 0.9819 timestamp: 1654969406.6580744 iteration: 70095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06642 FastRCNN class loss: 0.03936 FastRCNN total loss: 0.10578 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.0004 Mask loss: 0.08153 RPN box loss: 0.00512 RPN score loss: 0.00224 RPN total loss: 0.00736 Total loss: 0.78556 timestamp: 1654969409.8846338 iteration: 70100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08919 FastRCNN class loss: 0.04131 FastRCNN total loss: 0.1305 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.0004 Mask loss: 0.09663 RPN box loss: 0.02073 RPN score loss: 0.00337 RPN total loss: 0.0241 Total loss: 0.84211 timestamp: 1654969413.1302922 iteration: 70105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08106 FastRCNN class loss: 0.06245 FastRCNN total loss: 0.14351 L1 loss: 0.0000e+00 L2 loss: 0.59088 Learning rate: 0.0004 Mask loss: 0.11746 RPN box loss: 0.03272 RPN score loss: 0.00766 RPN total loss: 0.04038 Total loss: 0.89224 timestamp: 1654969416.3260677 iteration: 70110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08013 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.147 L1 loss: 0.0000e+00 L2 loss: 0.59088 Learning rate: 0.0004 Mask loss: 0.10723 RPN box loss: 0.0044 RPN score loss: 0.0066 RPN total loss: 0.011 Total loss: 0.85611 timestamp: 1654969419.635046 iteration: 70115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09661 FastRCNN class loss: 0.05693 FastRCNN total loss: 0.15355 L1 loss: 0.0000e+00 L2 loss: 0.59088 Learning rate: 0.0004 Mask loss: 0.14243 RPN box loss: 0.00987 RPN score loss: 0.00363 RPN total loss: 0.0135 Total loss: 0.90036 timestamp: 1654969422.899936 iteration: 70120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02773 FastRCNN class loss: 0.028 FastRCNN total loss: 0.05573 L1 loss: 0.0000e+00 L2 loss: 0.59088 Learning rate: 0.0004 Mask loss: 0.08358 RPN box loss: 0.00201 RPN score loss: 0.00165 RPN total loss: 0.00366 Total loss: 0.73385 timestamp: 1654969426.0889883 iteration: 70125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04997 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.11437 L1 loss: 0.0000e+00 L2 loss: 0.59088 Learning rate: 0.0004 Mask loss: 0.10805 RPN box loss: 0.00484 RPN score loss: 0.00407 RPN total loss: 0.00891 Total loss: 0.82221 timestamp: 1654969429.229877 iteration: 70130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07801 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.15238 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.0004 Mask loss: 0.13661 RPN box loss: 0.03493 RPN score loss: 0.00589 RPN total loss: 0.04083 Total loss: 0.92068 timestamp: 1654969432.526139 iteration: 70135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07735 FastRCNN class loss: 0.05605 FastRCNN total loss: 0.1334 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.0004 Mask loss: 0.1347 RPN box loss: 0.007 RPN score loss: 0.00259 RPN total loss: 0.00959 Total loss: 0.86857 timestamp: 1654969435.724759 iteration: 70140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10581 FastRCNN class loss: 0.08643 FastRCNN total loss: 0.19224 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.0004 Mask loss: 0.13659 RPN box loss: 0.01645 RPN score loss: 0.00118 RPN total loss: 0.01763 Total loss: 0.93734 timestamp: 1654969438.9260256 iteration: 70145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08115 FastRCNN class loss: 0.05414 FastRCNN total loss: 0.13529 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.0004 Mask loss: 0.08556 RPN box loss: 0.00389 RPN score loss: 0.00257 RPN total loss: 0.00646 Total loss: 0.81818 timestamp: 1654969442.1584103 iteration: 70150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09647 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.18097 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.0004 Mask loss: 0.10761 RPN box loss: 0.02335 RPN score loss: 0.00218 RPN total loss: 0.02553 Total loss: 0.90498 timestamp: 1654969445.3718677 iteration: 70155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08482 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.13531 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.0004 Mask loss: 0.08425 RPN box loss: 0.00316 RPN score loss: 0.00214 RPN total loss: 0.0053 Total loss: 0.81573 timestamp: 1654969448.5629072 iteration: 70160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07912 FastRCNN class loss: 0.09231 FastRCNN total loss: 0.17143 L1 loss: 0.0000e+00 L2 loss: 0.59086 Learning rate: 0.0004 Mask loss: 0.14684 RPN box loss: 0.00542 RPN score loss: 0.00161 RPN total loss: 0.00702 Total loss: 0.91616 timestamp: 1654969451.7882679 iteration: 70165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07113 FastRCNN class loss: 0.0382 FastRCNN total loss: 0.10933 L1 loss: 0.0000e+00 L2 loss: 0.59086 Learning rate: 0.0004 Mask loss: 0.11771 RPN box loss: 0.00256 RPN score loss: 0.00337 RPN total loss: 0.00593 Total loss: 0.82383 timestamp: 1654969455.0221024 iteration: 70170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07132 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.13696 L1 loss: 0.0000e+00 L2 loss: 0.59086 Learning rate: 0.0004 Mask loss: 0.21734 RPN box loss: 0.01875 RPN score loss: 0.00773 RPN total loss: 0.02649 Total loss: 0.97165 timestamp: 1654969458.249951 iteration: 70175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06954 FastRCNN class loss: 0.06778 FastRCNN total loss: 0.13732 L1 loss: 0.0000e+00 L2 loss: 0.59086 Learning rate: 0.0004 Mask loss: 0.11597 RPN box loss: 0.00578 RPN score loss: 0.00133 RPN total loss: 0.00711 Total loss: 0.85127 timestamp: 1654969461.526194 iteration: 70180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09439 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.14378 L1 loss: 0.0000e+00 L2 loss: 0.59086 Learning rate: 0.0004 Mask loss: 0.14424 RPN box loss: 0.00727 RPN score loss: 0.0034 RPN total loss: 0.01067 Total loss: 0.88955 timestamp: 1654969464.7139063 iteration: 70185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06499 FastRCNN class loss: 0.11104 FastRCNN total loss: 0.17603 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.0004 Mask loss: 0.13145 RPN box loss: 0.01627 RPN score loss: 0.015 RPN total loss: 0.03126 Total loss: 0.9296 timestamp: 1654969468.033105 iteration: 70190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05124 FastRCNN class loss: 0.07559 FastRCNN total loss: 0.12684 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.0004 Mask loss: 0.12205 RPN box loss: 0.00947 RPN score loss: 0.00325 RPN total loss: 0.01272 Total loss: 0.85246 timestamp: 1654969471.2574348 iteration: 70195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1301 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.21778 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.0004 Mask loss: 0.16674 RPN box loss: 0.00868 RPN score loss: 0.00749 RPN total loss: 0.01618 Total loss: 0.99155 timestamp: 1654969474.5104728 iteration: 70200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16596 FastRCNN class loss: 0.08841 FastRCNN total loss: 0.25437 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.0004 Mask loss: 0.12376 RPN box loss: 0.03524 RPN score loss: 0.00267 RPN total loss: 0.03791 Total loss: 1.00689 timestamp: 1654969477.63371 iteration: 70205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07598 FastRCNN class loss: 0.09052 FastRCNN total loss: 0.1665 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.0004 Mask loss: 0.10854 RPN box loss: 0.01003 RPN score loss: 0.00146 RPN total loss: 0.0115 Total loss: 0.87739 timestamp: 1654969480.842127 iteration: 70210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08887 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.16524 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.0004 Mask loss: 0.1364 RPN box loss: 0.01041 RPN score loss: 0.00305 RPN total loss: 0.01346 Total loss: 0.90595 timestamp: 1654969484.009348 iteration: 70215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0925 FastRCNN class loss: 0.07484 FastRCNN total loss: 0.16734 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.0004 Mask loss: 0.19088 RPN box loss: 0.00755 RPN score loss: 0.00521 RPN total loss: 0.01276 Total loss: 0.96182 timestamp: 1654969487.2369688 iteration: 70220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03813 FastRCNN class loss: 0.04641 FastRCNN total loss: 0.08453 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.0004 Mask loss: 0.08423 RPN box loss: 0.00442 RPN score loss: 0.0028 RPN total loss: 0.00722 Total loss: 0.76683 timestamp: 1654969490.5190248 iteration: 70225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03801 FastRCNN class loss: 0.04259 FastRCNN total loss: 0.08059 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.0004 Mask loss: 0.0974 RPN box loss: 0.00986 RPN score loss: 0.00308 RPN total loss: 0.01295 Total loss: 0.78178 timestamp: 1654969493.7075737 iteration: 70230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08894 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.15492 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.0004 Mask loss: 0.16711 RPN box loss: 0.00951 RPN score loss: 0.00229 RPN total loss: 0.0118 Total loss: 0.92467 timestamp: 1654969496.9471185 iteration: 70235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08976 FastRCNN class loss: 0.07602 FastRCNN total loss: 0.16578 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.0004 Mask loss: 0.08281 RPN box loss: 0.00703 RPN score loss: 0.00521 RPN total loss: 0.01224 Total loss: 0.85168 timestamp: 1654969500.1303985 iteration: 70240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.04233 FastRCNN total loss: 0.12729 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.0004 Mask loss: 0.10317 RPN box loss: 0.00691 RPN score loss: 0.00546 RPN total loss: 0.01237 Total loss: 0.83367 timestamp: 1654969503.4553056 iteration: 70245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05718 FastRCNN class loss: 0.06437 FastRCNN total loss: 0.12155 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.12988 RPN box loss: 0.00517 RPN score loss: 0.00687 RPN total loss: 0.01204 Total loss: 0.85431 timestamp: 1654969506.6976912 iteration: 70250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06232 FastRCNN class loss: 0.03993 FastRCNN total loss: 0.10225 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.09175 RPN box loss: 0.00656 RPN score loss: 0.00185 RPN total loss: 0.00841 Total loss: 0.79323 timestamp: 1654969509.8642967 iteration: 70255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09486 FastRCNN class loss: 0.05 FastRCNN total loss: 0.14486 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.08297 RPN box loss: 0.00821 RPN score loss: 0.00375 RPN total loss: 0.01196 Total loss: 0.83062 timestamp: 1654969513.062191 iteration: 70260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04355 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.10059 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.10456 RPN box loss: 0.00399 RPN score loss: 0.00133 RPN total loss: 0.00532 Total loss: 0.8013 timestamp: 1654969516.2208002 iteration: 70265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10741 FastRCNN class loss: 0.08047 FastRCNN total loss: 0.18788 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.13081 RPN box loss: 0.00928 RPN score loss: 0.00687 RPN total loss: 0.01615 Total loss: 0.92567 timestamp: 1654969519.4441447 iteration: 70270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.06671 FastRCNN total loss: 0.14987 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.18597 RPN box loss: 0.0102 RPN score loss: 0.00416 RPN total loss: 0.01436 Total loss: 0.94103 timestamp: 1654969522.7226646 iteration: 70275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09731 FastRCNN class loss: 0.07154 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.0004 Mask loss: 0.13642 RPN box loss: 0.01615 RPN score loss: 0.0031 RPN total loss: 0.01925 Total loss: 0.91534 timestamp: 1654969525.8614182 iteration: 70280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.116 FastRCNN class loss: 0.05178 FastRCNN total loss: 0.16778 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.0004 Mask loss: 0.13966 RPN box loss: 0.00351 RPN score loss: 0.00203 RPN total loss: 0.00555 Total loss: 0.90381 timestamp: 1654969529.0720823 iteration: 70285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11412 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.16097 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.0004 Mask loss: 0.08008 RPN box loss: 0.01193 RPN score loss: 0.00444 RPN total loss: 0.01637 Total loss: 0.84824 timestamp: 1654969532.297951 iteration: 70290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08412 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.14389 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.0004 Mask loss: 0.09676 RPN box loss: 0.01118 RPN score loss: 0.00508 RPN total loss: 0.01626 Total loss: 0.84774 timestamp: 1654969535.539577 iteration: 70295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08014 FastRCNN class loss: 0.06522 FastRCNN total loss: 0.14536 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.0004 Mask loss: 0.12567 RPN box loss: 0.01389 RPN score loss: 0.00497 RPN total loss: 0.01887 Total loss: 0.88071 timestamp: 1654969538.7380848 iteration: 70300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11042 FastRCNN class loss: 0.08281 FastRCNN total loss: 0.19323 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.0004 Mask loss: 0.1521 RPN box loss: 0.02502 RPN score loss: 0.00232 RPN total loss: 0.02735 Total loss: 0.96349 timestamp: 1654969541.9441507 iteration: 70305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08093 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.14363 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.0004 Mask loss: 0.11791 RPN box loss: 0.01184 RPN score loss: 0.00592 RPN total loss: 0.01776 Total loss: 0.87012 timestamp: 1654969545.1360621 iteration: 70310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10129 FastRCNN class loss: 0.0609 FastRCNN total loss: 0.16219 L1 loss: 0.0000e+00 L2 loss: 0.59081 Learning rate: 0.0004 Mask loss: 0.125 RPN box loss: 0.00862 RPN score loss: 0.00135 RPN total loss: 0.00996 Total loss: 0.88797 timestamp: 1654969548.3529441 iteration: 70315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10881 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.16017 L1 loss: 0.0000e+00 L2 loss: 0.59081 Learning rate: 0.0004 Mask loss: 0.13974 RPN box loss: 0.0191 RPN score loss: 0.00353 RPN total loss: 0.02263 Total loss: 0.91336 timestamp: 1654969551.5012248 iteration: 70320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11875 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.17554 L1 loss: 0.0000e+00 L2 loss: 0.59081 Learning rate: 0.0004 Mask loss: 0.12094 RPN box loss: 0.0081 RPN score loss: 0.00218 RPN total loss: 0.01027 Total loss: 0.89756 timestamp: 1654969554.6775184 iteration: 70325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06837 FastRCNN class loss: 0.04357 FastRCNN total loss: 0.11195 L1 loss: 0.0000e+00 L2 loss: 0.59081 Learning rate: 0.0004 Mask loss: 0.11354 RPN box loss: 0.0074 RPN score loss: 0.00221 RPN total loss: 0.0096 Total loss: 0.8259 timestamp: 1654969557.8796735 iteration: 70330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.112 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.17645 L1 loss: 0.0000e+00 L2 loss: 0.59081 Learning rate: 0.0004 Mask loss: 0.11382 RPN box loss: 0.00523 RPN score loss: 0.00234 RPN total loss: 0.00757 Total loss: 0.88864 timestamp: 1654969561.040004 iteration: 70335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09651 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.1543 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.0004 Mask loss: 0.1191 RPN box loss: 0.02487 RPN score loss: 0.00975 RPN total loss: 0.03462 Total loss: 0.89882 timestamp: 1654969564.2140212 iteration: 70340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05982 FastRCNN class loss: 0.04749 FastRCNN total loss: 0.10731 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.0004 Mask loss: 0.15421 RPN box loss: 0.01162 RPN score loss: 0.00104 RPN total loss: 0.01266 Total loss: 0.86498 timestamp: 1654969567.436655 iteration: 70345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07815 FastRCNN class loss: 0.04695 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.0004 Mask loss: 0.1374 RPN box loss: 0.0058 RPN score loss: 0.00137 RPN total loss: 0.00717 Total loss: 0.86047 timestamp: 1654969570.60277 iteration: 70350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11419 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.19794 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.0004 Mask loss: 0.23147 RPN box loss: 0.0108 RPN score loss: 0.00848 RPN total loss: 0.01929 Total loss: 1.03949 timestamp: 1654969573.825443 iteration: 70355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0883 FastRCNN class loss: 0.04104 FastRCNN total loss: 0.12934 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.0004 Mask loss: 0.09999 RPN box loss: 0.00526 RPN score loss: 0.00649 RPN total loss: 0.01175 Total loss: 0.83188 timestamp: 1654969577.0135574 iteration: 70360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09815 FastRCNN class loss: 0.09117 FastRCNN total loss: 0.18932 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.0004 Mask loss: 0.14461 RPN box loss: 0.01296 RPN score loss: 0.00828 RPN total loss: 0.02124 Total loss: 0.94596 timestamp: 1654969580.2020636 iteration: 70365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.13756 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.0004 Mask loss: 0.10009 RPN box loss: 0.03309 RPN score loss: 0.00465 RPN total loss: 0.03774 Total loss: 0.86619 timestamp: 1654969583.379898 iteration: 70370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05387 FastRCNN class loss: 0.05121 FastRCNN total loss: 0.10508 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.0004 Mask loss: 0.09622 RPN box loss: 0.0184 RPN score loss: 0.00076 RPN total loss: 0.01916 Total loss: 0.81126 timestamp: 1654969586.6093585 iteration: 70375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0748 FastRCNN class loss: 0.06276 FastRCNN total loss: 0.13756 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.0004 Mask loss: 0.21381 RPN box loss: 0.00861 RPN score loss: 0.00068 RPN total loss: 0.00929 Total loss: 0.95144 timestamp: 1654969589.810755 iteration: 70380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06088 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.13095 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.0004 Mask loss: 0.14927 RPN box loss: 0.01586 RPN score loss: 0.00628 RPN total loss: 0.02214 Total loss: 0.89315 timestamp: 1654969593.02392 iteration: 70385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.14792 FastRCNN total loss: 0.28198 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.0004 Mask loss: 0.15197 RPN box loss: 0.01538 RPN score loss: 0.01947 RPN total loss: 0.03485 Total loss: 1.05958 timestamp: 1654969596.2159722 iteration: 70390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06763 FastRCNN class loss: 0.03875 FastRCNN total loss: 0.10639 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.0004 Mask loss: 0.19829 RPN box loss: 0.01187 RPN score loss: 0.00202 RPN total loss: 0.01389 Total loss: 0.90936 timestamp: 1654969599.4390655 iteration: 70395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05858 FastRCNN class loss: 0.08137 FastRCNN total loss: 0.13995 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.0004 Mask loss: 0.11933 RPN box loss: 0.00588 RPN score loss: 0.00393 RPN total loss: 0.00981 Total loss: 0.85988 timestamp: 1654969602.669743 iteration: 70400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03832 FastRCNN class loss: 0.0409 FastRCNN total loss: 0.07921 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.0004 Mask loss: 0.11322 RPN box loss: 0.00385 RPN score loss: 0.00219 RPN total loss: 0.00604 Total loss: 0.78925 timestamp: 1654969605.8450541 iteration: 70405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04909 FastRCNN class loss: 0.06893 FastRCNN total loss: 0.11802 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.0004 Mask loss: 0.11118 RPN box loss: 0.00572 RPN score loss: 0.00187 RPN total loss: 0.0076 Total loss: 0.82758 timestamp: 1654969609.0771096 iteration: 70410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10117 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.20306 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.0004 Mask loss: 0.12692 RPN box loss: 0.02309 RPN score loss: 0.00495 RPN total loss: 0.02804 Total loss: 0.9488 timestamp: 1654969612.2688735 iteration: 70415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07686 FastRCNN class loss: 0.04945 FastRCNN total loss: 0.12631 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.0004 Mask loss: 0.09255 RPN box loss: 0.0058 RPN score loss: 0.00374 RPN total loss: 0.00955 Total loss: 0.81918 timestamp: 1654969615.5265222 iteration: 70420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08837 FastRCNN class loss: 0.04603 FastRCNN total loss: 0.1344 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.0004 Mask loss: 0.10715 RPN box loss: 0.01316 RPN score loss: 0.00067 RPN total loss: 0.01384 Total loss: 0.84616 timestamp: 1654969618.7353668 iteration: 70425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04578 FastRCNN class loss: 0.06165 FastRCNN total loss: 0.10742 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.0004 Mask loss: 0.15252 RPN box loss: 0.02085 RPN score loss: 0.01222 RPN total loss: 0.03307 Total loss: 0.88379 timestamp: 1654969621.9352417 iteration: 70430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13099 FastRCNN class loss: 0.08547 FastRCNN total loss: 0.21646 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.0004 Mask loss: 0.15257 RPN box loss: 0.00522 RPN score loss: 0.00483 RPN total loss: 0.01005 Total loss: 0.96985 timestamp: 1654969625.158006 iteration: 70435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06805 FastRCNN class loss: 0.05802 FastRCNN total loss: 0.12607 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.0004 Mask loss: 0.15914 RPN box loss: 0.0149 RPN score loss: 0.00722 RPN total loss: 0.02212 Total loss: 0.8981 timestamp: 1654969628.333046 iteration: 70440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10825 FastRCNN class loss: 0.04777 FastRCNN total loss: 0.15602 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.0004 Mask loss: 0.13864 RPN box loss: 0.00599 RPN score loss: 0.00226 RPN total loss: 0.00825 Total loss: 0.89367 timestamp: 1654969631.598182 iteration: 70445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11447 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.17753 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.0004 Mask loss: 0.14344 RPN box loss: 0.01424 RPN score loss: 0.00672 RPN total loss: 0.02095 Total loss: 0.93269 timestamp: 1654969634.8610127 iteration: 70450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05764 FastRCNN class loss: 0.04414 FastRCNN total loss: 0.10178 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.0004 Mask loss: 0.13363 RPN box loss: 0.00411 RPN score loss: 0.00206 RPN total loss: 0.00617 Total loss: 0.83234 timestamp: 1654969638.012485 iteration: 70455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14583 FastRCNN class loss: 0.15919 FastRCNN total loss: 0.30502 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.0004 Mask loss: 0.18268 RPN box loss: 0.02659 RPN score loss: 0.00561 RPN total loss: 0.0322 Total loss: 1.11066 timestamp: 1654969641.1746278 iteration: 70460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.083 FastRCNN class loss: 0.07875 FastRCNN total loss: 0.16175 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.0004 Mask loss: 0.144 RPN box loss: 0.01104 RPN score loss: 0.00587 RPN total loss: 0.01692 Total loss: 0.91343 timestamp: 1654969644.3856406 iteration: 70465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06777 FastRCNN class loss: 0.03305 FastRCNN total loss: 0.10081 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.0004 Mask loss: 0.09748 RPN box loss: 0.00394 RPN score loss: 0.00152 RPN total loss: 0.00545 Total loss: 0.79451 timestamp: 1654969647.5674238 iteration: 70470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07687 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.15756 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.0004 Mask loss: 0.13132 RPN box loss: 0.01554 RPN score loss: 0.01632 RPN total loss: 0.03186 Total loss: 0.9115 timestamp: 1654969650.7668118 iteration: 70475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11941 FastRCNN class loss: 0.0746 FastRCNN total loss: 0.19401 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.0004 Mask loss: 0.11839 RPN box loss: 0.00926 RPN score loss: 0.00382 RPN total loss: 0.01308 Total loss: 0.91624 timestamp: 1654969653.9416444 iteration: 70480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1063 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.20592 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.14983 RPN box loss: 0.01571 RPN score loss: 0.00628 RPN total loss: 0.02199 Total loss: 0.9685 timestamp: 1654969657.1395853 iteration: 70485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.104 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.18239 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.14396 RPN box loss: 0.00956 RPN score loss: 0.00723 RPN total loss: 0.01679 Total loss: 0.93389 timestamp: 1654969660.2915294 iteration: 70490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07375 FastRCNN class loss: 0.0381 FastRCNN total loss: 0.11185 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.10023 RPN box loss: 0.02236 RPN score loss: 0.00778 RPN total loss: 0.03014 Total loss: 0.83298 timestamp: 1654969663.4779196 iteration: 70495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10294 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.16512 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.16078 RPN box loss: 0.00795 RPN score loss: 0.00377 RPN total loss: 0.01172 Total loss: 0.92836 timestamp: 1654969666.6909497 iteration: 70500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.17502 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.13691 RPN box loss: 0.01123 RPN score loss: 0.00209 RPN total loss: 0.01333 Total loss: 0.91601 timestamp: 1654969669.9321282 iteration: 70505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05943 FastRCNN class loss: 0.04877 FastRCNN total loss: 0.1082 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.12343 RPN box loss: 0.00291 RPN score loss: 0.00294 RPN total loss: 0.00585 Total loss: 0.82823 timestamp: 1654969673.1271374 iteration: 70510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11044 FastRCNN class loss: 0.07804 FastRCNN total loss: 0.18849 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.0004 Mask loss: 0.12452 RPN box loss: 0.00665 RPN score loss: 0.00427 RPN total loss: 0.01092 Total loss: 0.91468 timestamp: 1654969676.3831184 iteration: 70515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07646 FastRCNN class loss: 0.08645 FastRCNN total loss: 0.16291 L1 loss: 0.0000e+00 L2 loss: 0.59074 Learning rate: 0.0004 Mask loss: 0.13798 RPN box loss: 0.02312 RPN score loss: 0.00173 RPN total loss: 0.02485 Total loss: 0.91648 timestamp: 1654969679.6033742 iteration: 70520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05368 FastRCNN class loss: 0.02897 FastRCNN total loss: 0.08265 L1 loss: 0.0000e+00 L2 loss: 0.59074 Learning rate: 0.0004 Mask loss: 0.12618 RPN box loss: 0.01216 RPN score loss: 0.00125 RPN total loss: 0.01342 Total loss: 0.81299 timestamp: 1654969682.7943854 iteration: 70525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12881 FastRCNN class loss: 0.07876 FastRCNN total loss: 0.20757 L1 loss: 0.0000e+00 L2 loss: 0.59074 Learning rate: 0.0004 Mask loss: 0.11114 RPN box loss: 0.0079 RPN score loss: 0.00219 RPN total loss: 0.0101 Total loss: 0.91954 timestamp: 1654969685.8772302 iteration: 70530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06934 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.11908 L1 loss: 0.0000e+00 L2 loss: 0.59074 Learning rate: 0.0004 Mask loss: 0.14228 RPN box loss: 0.01953 RPN score loss: 0.00123 RPN total loss: 0.02076 Total loss: 0.87286 timestamp: 1654969689.1240048 iteration: 70535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10574 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.16774 L1 loss: 0.0000e+00 L2 loss: 0.59074 Learning rate: 0.0004 Mask loss: 0.14063 RPN box loss: 0.00914 RPN score loss: 0.0009 RPN total loss: 0.01004 Total loss: 0.90915 timestamp: 1654969692.339088 iteration: 70540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05652 FastRCNN class loss: 0.03654 FastRCNN total loss: 0.09306 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.0004 Mask loss: 0.06007 RPN box loss: 0.003 RPN score loss: 0.00161 RPN total loss: 0.00461 Total loss: 0.74848 timestamp: 1654969695.5250409 iteration: 70545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11667 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.18674 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.0004 Mask loss: 0.14603 RPN box loss: 0.03072 RPN score loss: 0.01084 RPN total loss: 0.04156 Total loss: 0.96506 timestamp: 1654969698.7402613 iteration: 70550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07789 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.13665 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.0004 Mask loss: 0.11192 RPN box loss: 0.0128 RPN score loss: 0.0043 RPN total loss: 0.01709 Total loss: 0.8564 timestamp: 1654969701.9556134 iteration: 70555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06314 FastRCNN class loss: 0.04765 FastRCNN total loss: 0.1108 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.0004 Mask loss: 0.1357 RPN box loss: 0.00727 RPN score loss: 0.0083 RPN total loss: 0.01557 Total loss: 0.85279 timestamp: 1654969705.1367075 iteration: 70560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14364 FastRCNN class loss: 0.09668 FastRCNN total loss: 0.24033 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.0004 Mask loss: 0.18944 RPN box loss: 0.00903 RPN score loss: 0.0086 RPN total loss: 0.01764 Total loss: 1.03813 timestamp: 1654969708.2955298 iteration: 70565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.056 FastRCNN class loss: 0.04861 FastRCNN total loss: 0.1046 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.0004 Mask loss: 0.13647 RPN box loss: 0.00555 RPN score loss: 0.00244 RPN total loss: 0.00799 Total loss: 0.83979 timestamp: 1654969711.5182025 iteration: 70570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07178 FastRCNN class loss: 0.06751 FastRCNN total loss: 0.13929 L1 loss: 0.0000e+00 L2 loss: 0.59072 Learning rate: 0.0004 Mask loss: 0.21238 RPN box loss: 0.00535 RPN score loss: 0.00504 RPN total loss: 0.01039 Total loss: 0.95278 timestamp: 1654969714.7397141 iteration: 70575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05464 FastRCNN class loss: 0.04485 FastRCNN total loss: 0.09948 L1 loss: 0.0000e+00 L2 loss: 0.59072 Learning rate: 0.0004 Mask loss: 0.14099 RPN box loss: 0.00387 RPN score loss: 0.00227 RPN total loss: 0.00614 Total loss: 0.83733 timestamp: 1654969717.939314 iteration: 70580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07936 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.14048 L1 loss: 0.0000e+00 L2 loss: 0.59072 Learning rate: 0.0004 Mask loss: 0.12026 RPN box loss: 0.01451 RPN score loss: 0.00379 RPN total loss: 0.01831 Total loss: 0.86977 timestamp: 1654969721.1048179 iteration: 70585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11237 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.19427 L1 loss: 0.0000e+00 L2 loss: 0.59072 Learning rate: 0.0004 Mask loss: 0.229 RPN box loss: 0.00652 RPN score loss: 0.00438 RPN total loss: 0.0109 Total loss: 1.02489 timestamp: 1654969724.3124864 iteration: 70590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06345 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.11793 L1 loss: 0.0000e+00 L2 loss: 0.59072 Learning rate: 0.0004 Mask loss: 0.13463 RPN box loss: 0.00856 RPN score loss: 0.00499 RPN total loss: 0.01354 Total loss: 0.85682 timestamp: 1654969727.4627292 iteration: 70595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10188 FastRCNN class loss: 0.06443 FastRCNN total loss: 0.16631 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.11728 RPN box loss: 0.00896 RPN score loss: 0.00538 RPN total loss: 0.01435 Total loss: 0.88865 timestamp: 1654969730.632244 iteration: 70600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14438 FastRCNN class loss: 0.08793 FastRCNN total loss: 0.23231 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.12708 RPN box loss: 0.01695 RPN score loss: 0.0091 RPN total loss: 0.02605 Total loss: 0.97616 timestamp: 1654969733.8088655 iteration: 70605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08798 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.17068 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.09885 RPN box loss: 0.01132 RPN score loss: 0.00666 RPN total loss: 0.01798 Total loss: 0.87823 timestamp: 1654969737.0456464 iteration: 70610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09405 FastRCNN class loss: 0.05293 FastRCNN total loss: 0.14698 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.1069 RPN box loss: 0.01711 RPN score loss: 0.01034 RPN total loss: 0.02745 Total loss: 0.87204 timestamp: 1654969740.2464223 iteration: 70615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08215 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.1574 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.14601 RPN box loss: 0.00767 RPN score loss: 0.00484 RPN total loss: 0.01251 Total loss: 0.90663 timestamp: 1654969743.4713886 iteration: 70620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09165 FastRCNN class loss: 0.0594 FastRCNN total loss: 0.15105 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.12622 RPN box loss: 0.00497 RPN score loss: 0.00891 RPN total loss: 0.01388 Total loss: 0.88185 timestamp: 1654969746.7031565 iteration: 70625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08109 FastRCNN class loss: 0.05392 FastRCNN total loss: 0.135 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.0004 Mask loss: 0.10682 RPN box loss: 0.00532 RPN score loss: 0.00374 RPN total loss: 0.00907 Total loss: 0.8416 timestamp: 1654969749.9097226 iteration: 70630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10084 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.15651 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.0004 Mask loss: 0.10594 RPN box loss: 0.01451 RPN score loss: 0.00338 RPN total loss: 0.0179 Total loss: 0.87105 timestamp: 1654969753.0884473 iteration: 70635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05144 FastRCNN class loss: 0.05123 FastRCNN total loss: 0.10268 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.0004 Mask loss: 0.10475 RPN box loss: 0.00695 RPN score loss: 0.00115 RPN total loss: 0.0081 Total loss: 0.80623 timestamp: 1654969756.3427908 iteration: 70640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10758 FastRCNN class loss: 0.10374 FastRCNN total loss: 0.21132 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.0004 Mask loss: 0.16135 RPN box loss: 0.02047 RPN score loss: 0.00457 RPN total loss: 0.02504 Total loss: 0.98841 timestamp: 1654969759.531146 iteration: 70645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12679 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.20749 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.0004 Mask loss: 0.14033 RPN box loss: 0.00777 RPN score loss: 0.0058 RPN total loss: 0.01356 Total loss: 0.95208 timestamp: 1654969762.6680546 iteration: 70650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06621 FastRCNN class loss: 0.05453 FastRCNN total loss: 0.12074 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.0004 Mask loss: 0.13059 RPN box loss: 0.01358 RPN score loss: 0.00779 RPN total loss: 0.02137 Total loss: 0.8634 timestamp: 1654969765.9656918 iteration: 70655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0517 FastRCNN class loss: 0.05259 FastRCNN total loss: 0.10429 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.0004 Mask loss: 0.10632 RPN box loss: 0.00729 RPN score loss: 0.00229 RPN total loss: 0.00958 Total loss: 0.81089 timestamp: 1654969769.1270754 iteration: 70660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07558 FastRCNN class loss: 0.09025 FastRCNN total loss: 0.16582 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.1317 RPN box loss: 0.01087 RPN score loss: 0.00942 RPN total loss: 0.02028 Total loss: 0.9085 timestamp: 1654969772.4181864 iteration: 70665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07183 FastRCNN class loss: 0.04784 FastRCNN total loss: 0.11967 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.12628 RPN box loss: 0.00432 RPN score loss: 0.00124 RPN total loss: 0.00556 Total loss: 0.84221 timestamp: 1654969775.5781777 iteration: 70670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06368 FastRCNN class loss: 0.05709 FastRCNN total loss: 0.12077 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.09584 RPN box loss: 0.01394 RPN score loss: 0.00321 RPN total loss: 0.01714 Total loss: 0.82444 timestamp: 1654969778.7605357 iteration: 70675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05078 FastRCNN class loss: 0.04056 FastRCNN total loss: 0.09134 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.12342 RPN box loss: 0.0052 RPN score loss: 0.00131 RPN total loss: 0.00651 Total loss: 0.81196 timestamp: 1654969781.9757538 iteration: 70680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12407 FastRCNN class loss: 0.06955 FastRCNN total loss: 0.19361 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.0869 RPN box loss: 0.01491 RPN score loss: 0.00466 RPN total loss: 0.01957 Total loss: 0.89077 timestamp: 1654969785.1222353 iteration: 70685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11998 FastRCNN class loss: 0.07526 FastRCNN total loss: 0.19524 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.14671 RPN box loss: 0.02498 RPN score loss: 0.00394 RPN total loss: 0.02892 Total loss: 0.96155 timestamp: 1654969788.3648186 iteration: 70690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16092 FastRCNN class loss: 0.10739 FastRCNN total loss: 0.26832 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.0004 Mask loss: 0.16515 RPN box loss: 0.01798 RPN score loss: 0.00458 RPN total loss: 0.02256 Total loss: 1.04671 timestamp: 1654969791.596736 iteration: 70695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10962 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.187 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.0004 Mask loss: 0.20564 RPN box loss: 0.02249 RPN score loss: 0.00223 RPN total loss: 0.02472 Total loss: 1.00804 timestamp: 1654969794.7299557 iteration: 70700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14518 FastRCNN class loss: 0.07543 FastRCNN total loss: 0.22061 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.0004 Mask loss: 0.15796 RPN box loss: 0.01285 RPN score loss: 0.00813 RPN total loss: 0.02098 Total loss: 0.99022 timestamp: 1654969797.8976326 iteration: 70705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04659 FastRCNN class loss: 0.04024 FastRCNN total loss: 0.08683 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.0004 Mask loss: 0.0786 RPN box loss: 0.00321 RPN score loss: 0.00141 RPN total loss: 0.00462 Total loss: 0.76074 timestamp: 1654969801.0639634 iteration: 70710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06136 FastRCNN class loss: 0.0399 FastRCNN total loss: 0.10126 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.0004 Mask loss: 0.11102 RPN box loss: 0.00525 RPN score loss: 0.0057 RPN total loss: 0.01095 Total loss: 0.81392 timestamp: 1654969804.2691174 iteration: 70715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06423 FastRCNN class loss: 0.04601 FastRCNN total loss: 0.11024 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.0004 Mask loss: 0.11045 RPN box loss: 0.00715 RPN score loss: 0.0021 RPN total loss: 0.00925 Total loss: 0.82062 timestamp: 1654969807.5073829 iteration: 70720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2371 FastRCNN class loss: 0.0653 FastRCNN total loss: 0.3024 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.0004 Mask loss: 0.10349 RPN box loss: 0.01725 RPN score loss: 0.00926 RPN total loss: 0.02651 Total loss: 1.02308 timestamp: 1654969810.7094955 iteration: 70725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06303 FastRCNN class loss: 0.03369 FastRCNN total loss: 0.09672 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.0004 Mask loss: 0.11153 RPN box loss: 0.01791 RPN score loss: 0.00271 RPN total loss: 0.02061 Total loss: 0.81954 timestamp: 1654969813.9336593 iteration: 70730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07579 FastRCNN class loss: 0.05623 FastRCNN total loss: 0.13202 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.0004 Mask loss: 0.11857 RPN box loss: 0.01555 RPN score loss: 0.00389 RPN total loss: 0.01944 Total loss: 0.8607 timestamp: 1654969817.1648302 iteration: 70735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.06882 FastRCNN total loss: 0.17148 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.0004 Mask loss: 0.10217 RPN box loss: 0.0058 RPN score loss: 0.00176 RPN total loss: 0.00756 Total loss: 0.87189 timestamp: 1654969820.33181 iteration: 70740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05023 FastRCNN class loss: 0.03416 FastRCNN total loss: 0.08439 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.0004 Mask loss: 0.08755 RPN box loss: 0.00486 RPN score loss: 0.00795 RPN total loss: 0.01281 Total loss: 0.77542 timestamp: 1654969823.5379903 iteration: 70745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0491 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.10545 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.0004 Mask loss: 0.11892 RPN box loss: 0.00876 RPN score loss: 0.00213 RPN total loss: 0.01089 Total loss: 0.82593 timestamp: 1654969826.7023053 iteration: 70750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.07521 FastRCNN total loss: 0.15101 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.0004 Mask loss: 0.12827 RPN box loss: 0.02211 RPN score loss: 0.0091 RPN total loss: 0.03121 Total loss: 0.90115 timestamp: 1654969829.8438547 iteration: 70755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07241 FastRCNN class loss: 0.08814 FastRCNN total loss: 0.16055 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.0004 Mask loss: 0.13241 RPN box loss: 0.01071 RPN score loss: 0.00244 RPN total loss: 0.01314 Total loss: 0.89676 timestamp: 1654969833.102576 iteration: 70760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0971 FastRCNN class loss: 0.06267 FastRCNN total loss: 0.15978 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.0004 Mask loss: 0.1252 RPN box loss: 0.01013 RPN score loss: 0.00255 RPN total loss: 0.01268 Total loss: 0.88832 timestamp: 1654969836.3349457 iteration: 70765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17449 FastRCNN class loss: 0.07019 FastRCNN total loss: 0.24468 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.0004 Mask loss: 0.18764 RPN box loss: 0.01185 RPN score loss: 0.00285 RPN total loss: 0.0147 Total loss: 1.03769 timestamp: 1654969839.5042467 iteration: 70770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13918 FastRCNN class loss: 0.08794 FastRCNN total loss: 0.22712 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.0004 Mask loss: 0.13817 RPN box loss: 0.01771 RPN score loss: 0.00308 RPN total loss: 0.02079 Total loss: 0.97673 timestamp: 1654969842.7326076 iteration: 70775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07493 FastRCNN class loss: 0.05932 FastRCNN total loss: 0.13426 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.0004 Mask loss: 0.11343 RPN box loss: 0.01441 RPN score loss: 0.00233 RPN total loss: 0.01674 Total loss: 0.85508 timestamp: 1654969845.9501529 iteration: 70780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05011 FastRCNN class loss: 0.03248 FastRCNN total loss: 0.08259 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.0004 Mask loss: 0.14053 RPN box loss: 0.00398 RPN score loss: 0.00082 RPN total loss: 0.0048 Total loss: 0.81858 timestamp: 1654969849.1392763 iteration: 70785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.13984 L1 loss: 0.0000e+00 L2 loss: 0.59065 Learning rate: 0.0004 Mask loss: 0.15564 RPN box loss: 0.01148 RPN score loss: 0.00597 RPN total loss: 0.01745 Total loss: 0.90358 timestamp: 1654969852.2669652 iteration: 70790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06859 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.1321 L1 loss: 0.0000e+00 L2 loss: 0.59065 Learning rate: 0.0004 Mask loss: 0.10063 RPN box loss: 0.0081 RPN score loss: 0.00305 RPN total loss: 0.01114 Total loss: 0.83452 timestamp: 1654969855.5779967 iteration: 70795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06567 FastRCNN class loss: 0.05922 FastRCNN total loss: 0.12489 L1 loss: 0.0000e+00 L2 loss: 0.59065 Learning rate: 0.0004 Mask loss: 0.133 RPN box loss: 0.00676 RPN score loss: 0.00327 RPN total loss: 0.01003 Total loss: 0.85857 timestamp: 1654969858.794282 iteration: 70800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15488 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.21145 L1 loss: 0.0000e+00 L2 loss: 0.59065 Learning rate: 0.0004 Mask loss: 0.10064 RPN box loss: 0.00482 RPN score loss: 0.00286 RPN total loss: 0.00769 Total loss: 0.91043 timestamp: 1654969861.9990997 iteration: 70805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12564 FastRCNN class loss: 0.07533 FastRCNN total loss: 0.20097 L1 loss: 0.0000e+00 L2 loss: 0.59065 Learning rate: 0.0004 Mask loss: 0.13508 RPN box loss: 0.02016 RPN score loss: 0.00377 RPN total loss: 0.02393 Total loss: 0.95062 timestamp: 1654969865.187321 iteration: 70810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06688 FastRCNN class loss: 0.03217 FastRCNN total loss: 0.09906 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.0004 Mask loss: 0.12389 RPN box loss: 0.00486 RPN score loss: 0.00062 RPN total loss: 0.00548 Total loss: 0.81907 timestamp: 1654969868.3956761 iteration: 70815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08408 FastRCNN class loss: 0.07214 FastRCNN total loss: 0.15622 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.0004 Mask loss: 0.17305 RPN box loss: 0.01361 RPN score loss: 0.00399 RPN total loss: 0.01759 Total loss: 0.9375 timestamp: 1654969871.659527 iteration: 70820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09284 FastRCNN class loss: 0.0963 FastRCNN total loss: 0.18914 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.0004 Mask loss: 0.16179 RPN box loss: 0.00913 RPN score loss: 0.0027 RPN total loss: 0.01183 Total loss: 0.95339 timestamp: 1654969874.8034246 iteration: 70825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11049 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.18821 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.0004 Mask loss: 0.12652 RPN box loss: 0.01156 RPN score loss: 0.00436 RPN total loss: 0.01592 Total loss: 0.92129 timestamp: 1654969877.963687 iteration: 70830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07843 FastRCNN class loss: 0.08473 FastRCNN total loss: 0.16316 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.0004 Mask loss: 0.1299 RPN box loss: 0.00464 RPN score loss: 0.00568 RPN total loss: 0.01032 Total loss: 0.89401 timestamp: 1654969881.1336522 iteration: 70835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05588 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.12164 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.0004 Mask loss: 0.09641 RPN box loss: 0.00594 RPN score loss: 0.00439 RPN total loss: 0.01033 Total loss: 0.81901 timestamp: 1654969884.266443 iteration: 70840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08513 FastRCNN class loss: 0.05613 FastRCNN total loss: 0.14126 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.0004 Mask loss: 0.12159 RPN box loss: 0.00808 RPN score loss: 0.00872 RPN total loss: 0.0168 Total loss: 0.87028 timestamp: 1654969887.4660988 iteration: 70845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05416 FastRCNN class loss: 0.06512 FastRCNN total loss: 0.11927 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.0004 Mask loss: 0.10098 RPN box loss: 0.0079 RPN score loss: 0.00203 RPN total loss: 0.00994 Total loss: 0.82082 timestamp: 1654969890.718296 iteration: 70850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07066 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.12981 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.0004 Mask loss: 0.10342 RPN box loss: 0.0122 RPN score loss: 0.00216 RPN total loss: 0.01435 Total loss: 0.83822 timestamp: 1654969893.9510784 iteration: 70855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.085 FastRCNN total loss: 0.17267 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.0004 Mask loss: 0.10722 RPN box loss: 0.00678 RPN score loss: 0.00123 RPN total loss: 0.00801 Total loss: 0.87853 timestamp: 1654969897.1239638 iteration: 70860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06834 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.15513 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.0004 Mask loss: 0.12817 RPN box loss: 0.00694 RPN score loss: 0.00602 RPN total loss: 0.01296 Total loss: 0.88689 timestamp: 1654969900.3477263 iteration: 70865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08332 FastRCNN class loss: 0.05654 FastRCNN total loss: 0.13986 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.0004 Mask loss: 0.15358 RPN box loss: 0.01151 RPN score loss: 0.00486 RPN total loss: 0.01637 Total loss: 0.90044 timestamp: 1654969903.5118756 iteration: 70870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11108 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.19002 L1 loss: 0.0000e+00 L2 loss: 0.59062 Learning rate: 0.0004 Mask loss: 0.15081 RPN box loss: 0.01149 RPN score loss: 0.00527 RPN total loss: 0.01675 Total loss: 0.94821 timestamp: 1654969906.6900234 iteration: 70875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15502 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.25096 L1 loss: 0.0000e+00 L2 loss: 0.59062 Learning rate: 0.0004 Mask loss: 0.15435 RPN box loss: 0.01018 RPN score loss: 0.00634 RPN total loss: 0.01652 Total loss: 1.01246 timestamp: 1654969909.8966057 iteration: 70880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13631 FastRCNN class loss: 0.1206 FastRCNN total loss: 0.25691 L1 loss: 0.0000e+00 L2 loss: 0.59062 Learning rate: 0.0004 Mask loss: 0.23887 RPN box loss: 0.01803 RPN score loss: 0.00742 RPN total loss: 0.02545 Total loss: 1.11185 timestamp: 1654969913.126139 iteration: 70885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08955 FastRCNN class loss: 0.09943 FastRCNN total loss: 0.18898 L1 loss: 0.0000e+00 L2 loss: 0.59062 Learning rate: 0.0004 Mask loss: 0.13549 RPN box loss: 0.02094 RPN score loss: 0.00969 RPN total loss: 0.03064 Total loss: 0.94572 timestamp: 1654969916.3791006 iteration: 70890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07861 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.13915 L1 loss: 0.0000e+00 L2 loss: 0.59062 Learning rate: 0.0004 Mask loss: 0.16251 RPN box loss: 0.0072 RPN score loss: 0.00717 RPN total loss: 0.01437 Total loss: 0.90665 timestamp: 1654969919.6095638 iteration: 70895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0795 FastRCNN class loss: 0.04699 FastRCNN total loss: 0.12649 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.0004 Mask loss: 0.09217 RPN box loss: 0.01781 RPN score loss: 0.00241 RPN total loss: 0.02022 Total loss: 0.82949 timestamp: 1654969922.825571 iteration: 70900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10413 FastRCNN class loss: 0.07543 FastRCNN total loss: 0.17956 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.0004 Mask loss: 0.18432 RPN box loss: 0.0219 RPN score loss: 0.01898 RPN total loss: 0.04088 Total loss: 0.99537 timestamp: 1654969926.0542254 iteration: 70905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0703 FastRCNN class loss: 0.04144 FastRCNN total loss: 0.11174 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.0004 Mask loss: 0.08507 RPN box loss: 0.00531 RPN score loss: 0.00243 RPN total loss: 0.00774 Total loss: 0.79517 timestamp: 1654969929.23209 iteration: 70910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11043 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.17215 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.0004 Mask loss: 0.16228 RPN box loss: 0.02286 RPN score loss: 0.01289 RPN total loss: 0.03574 Total loss: 0.96078 timestamp: 1654969932.412445 iteration: 70915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06255 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.12966 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.0004 Mask loss: 0.08641 RPN box loss: 0.01113 RPN score loss: 0.01019 RPN total loss: 0.02131 Total loss: 0.828 timestamp: 1654969935.595778 iteration: 70920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03869 FastRCNN class loss: 0.03811 FastRCNN total loss: 0.0768 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.0004 Mask loss: 0.08206 RPN box loss: 0.00485 RPN score loss: 0.00824 RPN total loss: 0.01309 Total loss: 0.76256 timestamp: 1654969938.7982142 iteration: 70925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05489 FastRCNN class loss: 0.04381 FastRCNN total loss: 0.0987 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.11685 RPN box loss: 0.00458 RPN score loss: 0.00147 RPN total loss: 0.00605 Total loss: 0.8122 timestamp: 1654969941.9698539 iteration: 70930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08976 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.14877 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.10127 RPN box loss: 0.01154 RPN score loss: 0.00273 RPN total loss: 0.01427 Total loss: 0.85491 timestamp: 1654969945.205367 iteration: 70935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11501 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.20269 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.15671 RPN box loss: 0.02115 RPN score loss: 0.0109 RPN total loss: 0.03205 Total loss: 0.98205 timestamp: 1654969948.3382792 iteration: 70940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08764 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.14709 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.10615 RPN box loss: 0.00584 RPN score loss: 0.00113 RPN total loss: 0.00697 Total loss: 0.85081 timestamp: 1654969951.5657723 iteration: 70945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05757 FastRCNN class loss: 0.03985 FastRCNN total loss: 0.09742 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.12382 RPN box loss: 0.00525 RPN score loss: 0.00587 RPN total loss: 0.01112 Total loss: 0.82296 timestamp: 1654969954.71817 iteration: 70950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12361 FastRCNN class loss: 0.12092 FastRCNN total loss: 0.24453 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.1963 RPN box loss: 0.01934 RPN score loss: 0.00833 RPN total loss: 0.02767 Total loss: 1.0591 timestamp: 1654969957.932971 iteration: 70955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08426 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.1551 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.0004 Mask loss: 0.08728 RPN box loss: 0.01419 RPN score loss: 0.00551 RPN total loss: 0.0197 Total loss: 0.85268 timestamp: 1654969961.1721687 iteration: 70960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11153 FastRCNN class loss: 0.10265 FastRCNN total loss: 0.21417 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.0004 Mask loss: 0.14259 RPN box loss: 0.0124 RPN score loss: 0.00537 RPN total loss: 0.01777 Total loss: 0.96513 timestamp: 1654969964.4030662 iteration: 70965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08949 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.15009 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.0004 Mask loss: 0.13571 RPN box loss: 0.01805 RPN score loss: 0.00347 RPN total loss: 0.02152 Total loss: 0.89792 timestamp: 1654969967.6204565 iteration: 70970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10033 FastRCNN class loss: 0.06304 FastRCNN total loss: 0.16337 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.0004 Mask loss: 0.12639 RPN box loss: 0.01666 RPN score loss: 0.00623 RPN total loss: 0.02289 Total loss: 0.90324 timestamp: 1654969970.8110938 iteration: 70975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08022 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.15253 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.0004 Mask loss: 0.12282 RPN box loss: 0.01399 RPN score loss: 0.00557 RPN total loss: 0.01956 Total loss: 0.8855 timestamp: 1654969973.995541 iteration: 70980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08933 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.15121 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.0004 Mask loss: 0.10719 RPN box loss: 0.00822 RPN score loss: 0.00171 RPN total loss: 0.00993 Total loss: 0.85893 timestamp: 1654969977.1130972 iteration: 70985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03706 FastRCNN class loss: 0.03172 FastRCNN total loss: 0.06878 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.0004 Mask loss: 0.16274 RPN box loss: 0.00248 RPN score loss: 0.00176 RPN total loss: 0.00424 Total loss: 0.82635 timestamp: 1654969980.2891867 iteration: 70990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.18355 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.0004 Mask loss: 0.10233 RPN box loss: 0.00708 RPN score loss: 0.00389 RPN total loss: 0.01096 Total loss: 0.88742 timestamp: 1654969983.5050654 iteration: 70995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0961 FastRCNN class loss: 0.0591 FastRCNN total loss: 0.15519 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.0004 Mask loss: 0.12889 RPN box loss: 0.01711 RPN score loss: 0.0071 RPN total loss: 0.02421 Total loss: 0.89887 timestamp: 1654969986.7008245 iteration: 71000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1504 FastRCNN class loss: 0.04627 FastRCNN total loss: 0.19668 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.0004 Mask loss: 0.10602 RPN box loss: 0.0114 RPN score loss: 0.00718 RPN total loss: 0.01858 Total loss: 0.91186 timestamp: 1654969989.7855258 iteration: 71005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10064 FastRCNN class loss: 0.05196 FastRCNN total loss: 0.1526 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.0004 Mask loss: 0.12712 RPN box loss: 0.00713 RPN score loss: 0.00596 RPN total loss: 0.01309 Total loss: 0.88339 timestamp: 1654969993.096165 iteration: 71010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10491 FastRCNN class loss: 0.05803 FastRCNN total loss: 0.16293 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.0004 Mask loss: 0.12961 RPN box loss: 0.01994 RPN score loss: 0.00369 RPN total loss: 0.02363 Total loss: 0.90676 timestamp: 1654969996.3285053 iteration: 71015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.045 FastRCNN class loss: 0.02901 FastRCNN total loss: 0.07401 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.0004 Mask loss: 0.10797 RPN box loss: 0.00293 RPN score loss: 0.00423 RPN total loss: 0.00716 Total loss: 0.77971 timestamp: 1654969999.5050745 iteration: 71020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13837 FastRCNN class loss: 0.0937 FastRCNN total loss: 0.23207 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.0004 Mask loss: 0.21227 RPN box loss: 0.01364 RPN score loss: 0.01626 RPN total loss: 0.02989 Total loss: 1.0648 timestamp: 1654970002.76123 iteration: 71025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12315 FastRCNN class loss: 0.08379 FastRCNN total loss: 0.20694 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.0004 Mask loss: 0.09016 RPN box loss: 0.01135 RPN score loss: 0.00499 RPN total loss: 0.01634 Total loss: 0.90401 timestamp: 1654970005.945175 iteration: 71030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05116 FastRCNN class loss: 0.06065 FastRCNN total loss: 0.1118 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.0004 Mask loss: 0.13577 RPN box loss: 0.03253 RPN score loss: 0.00558 RPN total loss: 0.03811 Total loss: 0.87625 timestamp: 1654970009.125208 iteration: 71035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0747 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.14909 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.0004 Mask loss: 0.14809 RPN box loss: 0.02379 RPN score loss: 0.00474 RPN total loss: 0.02853 Total loss: 0.91627 timestamp: 1654970012.326711 iteration: 71040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1453 FastRCNN class loss: 0.07813 FastRCNN total loss: 0.22343 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.0004 Mask loss: 0.15329 RPN box loss: 0.00881 RPN score loss: 0.00857 RPN total loss: 0.01738 Total loss: 0.98466 timestamp: 1654970015.5172496 iteration: 71045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09224 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.14262 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.0004 Mask loss: 0.11202 RPN box loss: 0.01134 RPN score loss: 0.00225 RPN total loss: 0.01359 Total loss: 0.85879 timestamp: 1654970018.6527727 iteration: 71050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05578 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.12224 L1 loss: 0.0000e+00 L2 loss: 0.59056 Learning rate: 0.0004 Mask loss: 0.15274 RPN box loss: 0.03566 RPN score loss: 0.00354 RPN total loss: 0.0392 Total loss: 0.90475 timestamp: 1654970021.8656266 iteration: 71055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08341 FastRCNN class loss: 0.04374 FastRCNN total loss: 0.12714 L1 loss: 0.0000e+00 L2 loss: 0.59056 Learning rate: 0.0004 Mask loss: 0.09248 RPN box loss: 0.0036 RPN score loss: 0.00462 RPN total loss: 0.00822 Total loss: 0.8184 timestamp: 1654970025.030627 iteration: 71060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11289 FastRCNN class loss: 0.07513 FastRCNN total loss: 0.18803 L1 loss: 0.0000e+00 L2 loss: 0.59056 Learning rate: 0.0004 Mask loss: 0.11938 RPN box loss: 0.00837 RPN score loss: 0.00401 RPN total loss: 0.01238 Total loss: 0.91034 timestamp: 1654970028.281541 iteration: 71065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07881 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.1431 L1 loss: 0.0000e+00 L2 loss: 0.59056 Learning rate: 0.0004 Mask loss: 0.12094 RPN box loss: 0.01145 RPN score loss: 0.00876 RPN total loss: 0.0202 Total loss: 0.8748 timestamp: 1654970031.4788399 iteration: 71070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08916 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.15638 L1 loss: 0.0000e+00 L2 loss: 0.59056 Learning rate: 0.0004 Mask loss: 0.14672 RPN box loss: 0.02155 RPN score loss: 0.0061 RPN total loss: 0.02764 Total loss: 0.9213 timestamp: 1654970034.726521 iteration: 71075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07224 FastRCNN class loss: 0.03979 FastRCNN total loss: 0.11203 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.11603 RPN box loss: 0.01364 RPN score loss: 0.00198 RPN total loss: 0.01562 Total loss: 0.83424 timestamp: 1654970037.938081 iteration: 71080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07171 FastRCNN class loss: 0.03789 FastRCNN total loss: 0.1096 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.11162 RPN box loss: 0.00539 RPN score loss: 0.00339 RPN total loss: 0.00878 Total loss: 0.82055 timestamp: 1654970041.0770276 iteration: 71085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09756 FastRCNN class loss: 0.08573 FastRCNN total loss: 0.18329 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.15814 RPN box loss: 0.00531 RPN score loss: 0.00394 RPN total loss: 0.00925 Total loss: 0.94123 timestamp: 1654970044.2459927 iteration: 71090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10689 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.18296 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.15004 RPN box loss: 0.00735 RPN score loss: 0.00336 RPN total loss: 0.01071 Total loss: 0.93426 timestamp: 1654970047.466507 iteration: 71095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09953 FastRCNN class loss: 0.07375 FastRCNN total loss: 0.17328 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.14953 RPN box loss: 0.021 RPN score loss: 0.00243 RPN total loss: 0.02342 Total loss: 0.93679 timestamp: 1654970050.6343434 iteration: 71100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07957 FastRCNN class loss: 0.04948 FastRCNN total loss: 0.12905 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.16784 RPN box loss: 0.0122 RPN score loss: 0.00375 RPN total loss: 0.01595 Total loss: 0.90338 timestamp: 1654970053.8778622 iteration: 71105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0572 FastRCNN class loss: 0.05565 FastRCNN total loss: 0.11284 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.0004 Mask loss: 0.13678 RPN box loss: 0.01673 RPN score loss: 0.00246 RPN total loss: 0.01919 Total loss: 0.85936 timestamp: 1654970057.0667143 iteration: 71110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14469 FastRCNN class loss: 0.0609 FastRCNN total loss: 0.20559 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.0004 Mask loss: 0.15697 RPN box loss: 0.0134 RPN score loss: 0.00541 RPN total loss: 0.01882 Total loss: 0.97192 timestamp: 1654970060.3404968 iteration: 71115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11934 FastRCNN class loss: 0.07281 FastRCNN total loss: 0.19214 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.0004 Mask loss: 0.12377 RPN box loss: 0.00762 RPN score loss: 0.00355 RPN total loss: 0.01117 Total loss: 0.91763 timestamp: 1654970063.5701704 iteration: 71120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.06809 FastRCNN total loss: 0.17925 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.0004 Mask loss: 0.10259 RPN box loss: 0.00653 RPN score loss: 0.0011 RPN total loss: 0.00762 Total loss: 0.88001 timestamp: 1654970066.742631 iteration: 71125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09089 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.14563 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.0004 Mask loss: 0.13036 RPN box loss: 0.01593 RPN score loss: 0.00778 RPN total loss: 0.02371 Total loss: 0.89024 timestamp: 1654970069.9340687 iteration: 71130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09954 FastRCNN class loss: 0.02946 FastRCNN total loss: 0.129 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.0004 Mask loss: 0.07724 RPN box loss: 0.00529 RPN score loss: 0.00117 RPN total loss: 0.00646 Total loss: 0.80324 timestamp: 1654970073.1263583 iteration: 71135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05481 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.10716 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.0004 Mask loss: 0.11802 RPN box loss: 0.02143 RPN score loss: 0.00235 RPN total loss: 0.02379 Total loss: 0.83949 timestamp: 1654970076.2789226 iteration: 71140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06889 FastRCNN class loss: 0.04507 FastRCNN total loss: 0.11397 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.0004 Mask loss: 0.09576 RPN box loss: 0.00813 RPN score loss: 0.00118 RPN total loss: 0.00931 Total loss: 0.80957 timestamp: 1654970079.552466 iteration: 71145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12389 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.18313 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.0004 Mask loss: 0.09726 RPN box loss: 0.00602 RPN score loss: 0.00211 RPN total loss: 0.00812 Total loss: 0.87905 timestamp: 1654970082.704427 iteration: 71150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12958 FastRCNN class loss: 0.11191 FastRCNN total loss: 0.2415 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.0004 Mask loss: 0.15539 RPN box loss: 0.02644 RPN score loss: 0.00783 RPN total loss: 0.03427 Total loss: 1.02168 timestamp: 1654970085.85845 iteration: 71155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.052 FastRCNN total loss: 0.1513 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.0004 Mask loss: 0.12352 RPN box loss: 0.0065 RPN score loss: 0.00347 RPN total loss: 0.00996 Total loss: 0.87532 timestamp: 1654970088.9779334 iteration: 71160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06033 FastRCNN class loss: 0.04037 FastRCNN total loss: 0.1007 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.0004 Mask loss: 0.09294 RPN box loss: 0.00576 RPN score loss: 0.00151 RPN total loss: 0.00727 Total loss: 0.79143 timestamp: 1654970092.166635 iteration: 71165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.06356 FastRCNN total loss: 0.15241 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.0004 Mask loss: 0.13688 RPN box loss: 0.00696 RPN score loss: 0.00519 RPN total loss: 0.01215 Total loss: 0.89196 timestamp: 1654970095.31118 iteration: 71170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07634 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.14355 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.0004 Mask loss: 0.11266 RPN box loss: 0.01735 RPN score loss: 0.00268 RPN total loss: 0.02003 Total loss: 0.86676 timestamp: 1654970098.504285 iteration: 71175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1471 FastRCNN class loss: 0.06521 FastRCNN total loss: 0.21231 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.0004 Mask loss: 0.14124 RPN box loss: 0.01456 RPN score loss: 0.00307 RPN total loss: 0.01762 Total loss: 0.9617 timestamp: 1654970101.6652262 iteration: 71180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12788 FastRCNN class loss: 0.11917 FastRCNN total loss: 0.24705 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.0004 Mask loss: 0.1422 RPN box loss: 0.02249 RPN score loss: 0.00206 RPN total loss: 0.02455 Total loss: 1.00432 timestamp: 1654970104.9425652 iteration: 71185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.07925 FastRCNN total loss: 0.16421 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.0004 Mask loss: 0.153 RPN box loss: 0.0093 RPN score loss: 0.0016 RPN total loss: 0.0109 Total loss: 0.91862 timestamp: 1654970108.1252956 iteration: 71190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10255 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.1766 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.0004 Mask loss: 0.09778 RPN box loss: 0.0137 RPN score loss: 0.00415 RPN total loss: 0.01785 Total loss: 0.88275 timestamp: 1654970111.3732967 iteration: 71195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0749 FastRCNN class loss: 0.05467 FastRCNN total loss: 0.12957 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.0004 Mask loss: 0.10825 RPN box loss: 0.01056 RPN score loss: 0.00283 RPN total loss: 0.01339 Total loss: 0.84172 timestamp: 1654970114.5466573 iteration: 71200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06352 FastRCNN class loss: 0.05232 FastRCNN total loss: 0.11584 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.0004 Mask loss: 0.105 RPN box loss: 0.00658 RPN score loss: 0.0023 RPN total loss: 0.00888 Total loss: 0.82023 timestamp: 1654970117.7812874 iteration: 71205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07734 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.15606 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.0004 Mask loss: 0.18117 RPN box loss: 0.00737 RPN score loss: 0.00858 RPN total loss: 0.01595 Total loss: 0.94369 timestamp: 1654970121.0054784 iteration: 71210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05919 FastRCNN class loss: 0.03184 FastRCNN total loss: 0.09103 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.0004 Mask loss: 0.08582 RPN box loss: 0.0131 RPN score loss: 0.00273 RPN total loss: 0.01583 Total loss: 0.78318 timestamp: 1654970124.2307777 iteration: 71215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0683 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.11955 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.0004 Mask loss: 0.12042 RPN box loss: 0.01367 RPN score loss: 0.00092 RPN total loss: 0.01458 Total loss: 0.84506 timestamp: 1654970127.4132385 iteration: 71220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10632 FastRCNN class loss: 0.06903 FastRCNN total loss: 0.17536 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.0004 Mask loss: 0.15297 RPN box loss: 0.02243 RPN score loss: 0.004 RPN total loss: 0.02643 Total loss: 0.94527 timestamp: 1654970130.561023 iteration: 71225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08775 FastRCNN class loss: 0.06013 FastRCNN total loss: 0.14788 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.0004 Mask loss: 0.11812 RPN box loss: 0.00527 RPN score loss: 0.00191 RPN total loss: 0.00718 Total loss: 0.86368 timestamp: 1654970133.7266073 iteration: 71230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08796 FastRCNN class loss: 0.05562 FastRCNN total loss: 0.14358 L1 loss: 0.0000e+00 L2 loss: 0.5905 Learning rate: 0.0004 Mask loss: 0.12605 RPN box loss: 0.01593 RPN score loss: 0.0047 RPN total loss: 0.02063 Total loss: 0.88076 timestamp: 1654970137.0123081 iteration: 71235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10049 FastRCNN class loss: 0.08359 FastRCNN total loss: 0.18408 L1 loss: 0.0000e+00 L2 loss: 0.5905 Learning rate: 0.0004 Mask loss: 0.17487 RPN box loss: 0.01 RPN score loss: 0.01037 RPN total loss: 0.02038 Total loss: 0.96983 timestamp: 1654970140.2207687 iteration: 71240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1069 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.19408 L1 loss: 0.0000e+00 L2 loss: 0.5905 Learning rate: 0.0004 Mask loss: 0.2076 RPN box loss: 0.01268 RPN score loss: 0.00582 RPN total loss: 0.01851 Total loss: 1.01069 timestamp: 1654970143.3882012 iteration: 71245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0947 FastRCNN class loss: 0.06286 FastRCNN total loss: 0.15756 L1 loss: 0.0000e+00 L2 loss: 0.5905 Learning rate: 0.0004 Mask loss: 0.11347 RPN box loss: 0.00597 RPN score loss: 0.00551 RPN total loss: 0.01148 Total loss: 0.87301 timestamp: 1654970146.5310798 iteration: 71250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06399 FastRCNN class loss: 0.043 FastRCNN total loss: 0.10699 L1 loss: 0.0000e+00 L2 loss: 0.5905 Learning rate: 0.0004 Mask loss: 0.09884 RPN box loss: 0.01739 RPN score loss: 0.00255 RPN total loss: 0.01994 Total loss: 0.81626 timestamp: 1654970149.681311 iteration: 71255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10524 FastRCNN class loss: 0.06818 FastRCNN total loss: 0.17342 L1 loss: 0.0000e+00 L2 loss: 0.59049 Learning rate: 0.0004 Mask loss: 0.10651 RPN box loss: 0.01884 RPN score loss: 0.00301 RPN total loss: 0.02185 Total loss: 0.89227 timestamp: 1654970152.8186212 iteration: 71260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13106 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.20582 L1 loss: 0.0000e+00 L2 loss: 0.59049 Learning rate: 0.0004 Mask loss: 0.13389 RPN box loss: 0.00401 RPN score loss: 0.00338 RPN total loss: 0.00739 Total loss: 0.93759 timestamp: 1654970156.0763888 iteration: 71265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08944 FastRCNN class loss: 0.06795 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.59049 Learning rate: 0.0004 Mask loss: 0.12651 RPN box loss: 0.0181 RPN score loss: 0.00253 RPN total loss: 0.02063 Total loss: 0.89502 timestamp: 1654970159.2482564 iteration: 71270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04448 FastRCNN class loss: 0.04382 FastRCNN total loss: 0.08831 L1 loss: 0.0000e+00 L2 loss: 0.59049 Learning rate: 0.0004 Mask loss: 0.0804 RPN box loss: 0.00353 RPN score loss: 0.00169 RPN total loss: 0.00521 Total loss: 0.76441 timestamp: 1654970162.4229283 iteration: 71275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.07959 FastRCNN total loss: 0.16098 L1 loss: 0.0000e+00 L2 loss: 0.59049 Learning rate: 0.0004 Mask loss: 0.09201 RPN box loss: 0.00508 RPN score loss: 0.00218 RPN total loss: 0.00726 Total loss: 0.85074 timestamp: 1654970165.6054478 iteration: 71280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13761 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.20334 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.16928 RPN box loss: 0.01625 RPN score loss: 0.00154 RPN total loss: 0.01778 Total loss: 0.98089 timestamp: 1654970168.7782567 iteration: 71285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08853 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.14148 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.13552 RPN box loss: 0.00919 RPN score loss: 0.00347 RPN total loss: 0.01266 Total loss: 0.88014 timestamp: 1654970171.991389 iteration: 71290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08205 FastRCNN class loss: 0.05083 FastRCNN total loss: 0.13288 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.13341 RPN box loss: 0.00533 RPN score loss: 0.00659 RPN total loss: 0.01192 Total loss: 0.86869 timestamp: 1654970175.1804945 iteration: 71295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10075 FastRCNN class loss: 0.08483 FastRCNN total loss: 0.18558 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.10194 RPN box loss: 0.00842 RPN score loss: 0.00761 RPN total loss: 0.01603 Total loss: 0.89404 timestamp: 1654970178.3519087 iteration: 71300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15128 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.23082 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.09946 RPN box loss: 0.00916 RPN score loss: 0.00618 RPN total loss: 0.01534 Total loss: 0.9361 timestamp: 1654970181.5740814 iteration: 71305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08321 FastRCNN class loss: 0.03593 FastRCNN total loss: 0.11915 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.10075 RPN box loss: 0.009 RPN score loss: 0.00448 RPN total loss: 0.01348 Total loss: 0.82386 timestamp: 1654970184.7907438 iteration: 71310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07982 FastRCNN class loss: 0.05757 FastRCNN total loss: 0.13739 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.0004 Mask loss: 0.11329 RPN box loss: 0.00701 RPN score loss: 0.00648 RPN total loss: 0.01349 Total loss: 0.85465 timestamp: 1654970188.0063732 iteration: 71315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1674 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.23926 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.0004 Mask loss: 0.1568 RPN box loss: 0.0329 RPN score loss: 0.0063 RPN total loss: 0.0392 Total loss: 1.02573 timestamp: 1654970191.217469 iteration: 71320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05141 FastRCNN class loss: 0.04973 FastRCNN total loss: 0.10114 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.0004 Mask loss: 0.08713 RPN box loss: 0.01135 RPN score loss: 0.00436 RPN total loss: 0.01571 Total loss: 0.79445 timestamp: 1654970194.4188366 iteration: 71325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1085 FastRCNN class loss: 0.1001 FastRCNN total loss: 0.20859 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.0004 Mask loss: 0.17682 RPN box loss: 0.02023 RPN score loss: 0.00653 RPN total loss: 0.02676 Total loss: 1.00265 timestamp: 1654970197.6936827 iteration: 71330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.11708 FastRCNN total loss: 0.21187 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.0004 Mask loss: 0.15631 RPN box loss: 0.01652 RPN score loss: 0.00136 RPN total loss: 0.01788 Total loss: 0.97652 timestamp: 1654970200.8520246 iteration: 71335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04778 FastRCNN class loss: 0.03585 FastRCNN total loss: 0.08363 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.0004 Mask loss: 0.09767 RPN box loss: 0.01183 RPN score loss: 0.00109 RPN total loss: 0.01292 Total loss: 0.78469 timestamp: 1654970204.0079286 iteration: 71340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06763 FastRCNN class loss: 0.07599 FastRCNN total loss: 0.14362 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.0004 Mask loss: 0.09359 RPN box loss: 0.01028 RPN score loss: 0.00357 RPN total loss: 0.01386 Total loss: 0.84154 timestamp: 1654970207.2246318 iteration: 71345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11425 FastRCNN class loss: 0.09475 FastRCNN total loss: 0.209 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.0004 Mask loss: 0.17166 RPN box loss: 0.00657 RPN score loss: 0.0039 RPN total loss: 0.01047 Total loss: 0.9816 timestamp: 1654970210.346464 iteration: 71350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06678 FastRCNN class loss: 0.04359 FastRCNN total loss: 0.11037 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.0004 Mask loss: 0.0938 RPN box loss: 0.00699 RPN score loss: 0.00144 RPN total loss: 0.00843 Total loss: 0.80306 timestamp: 1654970213.5036151 iteration: 71355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13405 FastRCNN class loss: 0.05442 FastRCNN total loss: 0.18847 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.0004 Mask loss: 0.11339 RPN box loss: 0.01074 RPN score loss: 0.0062 RPN total loss: 0.01694 Total loss: 0.90926 timestamp: 1654970216.754813 iteration: 71360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08542 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.15403 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.0004 Mask loss: 0.10392 RPN box loss: 0.00788 RPN score loss: 0.00241 RPN total loss: 0.01028 Total loss: 0.85869 timestamp: 1654970219.9642787 iteration: 71365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05489 FastRCNN class loss: 0.02627 FastRCNN total loss: 0.08117 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.0004 Mask loss: 0.0857 RPN box loss: 0.00934 RPN score loss: 0.00056 RPN total loss: 0.0099 Total loss: 0.76722 timestamp: 1654970223.1269014 iteration: 71370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09502 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.1543 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.0004 Mask loss: 0.12877 RPN box loss: 0.01093 RPN score loss: 0.002 RPN total loss: 0.01293 Total loss: 0.88646 timestamp: 1654970226.431436 iteration: 71375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.16242 L1 loss: 0.0000e+00 L2 loss: 0.59045 Learning rate: 0.0004 Mask loss: 0.12881 RPN box loss: 0.00867 RPN score loss: 0.00811 RPN total loss: 0.01678 Total loss: 0.89847 timestamp: 1654970229.5875666 iteration: 71380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11023 FastRCNN class loss: 0.0651 FastRCNN total loss: 0.17533 L1 loss: 0.0000e+00 L2 loss: 0.59045 Learning rate: 0.0004 Mask loss: 0.12941 RPN box loss: 0.01635 RPN score loss: 0.00616 RPN total loss: 0.02251 Total loss: 0.9177 timestamp: 1654970232.726948 iteration: 71385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10199 FastRCNN class loss: 0.04877 FastRCNN total loss: 0.15075 L1 loss: 0.0000e+00 L2 loss: 0.59045 Learning rate: 0.0004 Mask loss: 0.09259 RPN box loss: 0.00602 RPN score loss: 0.0008 RPN total loss: 0.00682 Total loss: 0.84061 timestamp: 1654970235.9720166 iteration: 71390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06812 FastRCNN class loss: 0.04442 FastRCNN total loss: 0.11255 L1 loss: 0.0000e+00 L2 loss: 0.59045 Learning rate: 0.0004 Mask loss: 0.10288 RPN box loss: 0.01187 RPN score loss: 0.00159 RPN total loss: 0.01346 Total loss: 0.81933 timestamp: 1654970239.2148771 iteration: 71395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08493 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.15798 L1 loss: 0.0000e+00 L2 loss: 0.59045 Learning rate: 0.0004 Mask loss: 0.10858 RPN box loss: 0.00459 RPN score loss: 0.00295 RPN total loss: 0.00754 Total loss: 0.86454 timestamp: 1654970242.45253 iteration: 71400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.04052 FastRCNN total loss: 0.1219 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.11193 RPN box loss: 0.06095 RPN score loss: 0.00505 RPN total loss: 0.066 Total loss: 0.89028 timestamp: 1654970245.6430204 iteration: 71405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09762 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.17075 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.16348 RPN box loss: 0.03435 RPN score loss: 0.01043 RPN total loss: 0.04478 Total loss: 0.96946 timestamp: 1654970248.7953775 iteration: 71410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09311 FastRCNN class loss: 0.08076 FastRCNN total loss: 0.17387 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.11149 RPN box loss: 0.00545 RPN score loss: 0.00577 RPN total loss: 0.01123 Total loss: 0.88702 timestamp: 1654970251.9716527 iteration: 71415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1277 FastRCNN class loss: 0.11674 FastRCNN total loss: 0.24444 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.13751 RPN box loss: 0.02215 RPN score loss: 0.00511 RPN total loss: 0.02726 Total loss: 0.99965 timestamp: 1654970255.2169523 iteration: 71420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05192 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.10173 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.09269 RPN box loss: 0.01408 RPN score loss: 0.00054 RPN total loss: 0.01462 Total loss: 0.79948 timestamp: 1654970258.408235 iteration: 71425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06761 FastRCNN class loss: 0.0772 FastRCNN total loss: 0.1448 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.14296 RPN box loss: 0.02777 RPN score loss: 0.01041 RPN total loss: 0.03818 Total loss: 0.91638 timestamp: 1654970261.625744 iteration: 71430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0935 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.18181 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.0004 Mask loss: 0.15385 RPN box loss: 0.00759 RPN score loss: 0.00294 RPN total loss: 0.01053 Total loss: 0.93662 timestamp: 1654970264.818476 iteration: 71435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0856 FastRCNN class loss: 0.0717 FastRCNN total loss: 0.1573 L1 loss: 0.0000e+00 L2 loss: 0.59043 Learning rate: 0.0004 Mask loss: 0.12267 RPN box loss: 0.00821 RPN score loss: 0.00088 RPN total loss: 0.00909 Total loss: 0.87949 timestamp: 1654970268.0490706 iteration: 71440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07255 FastRCNN class loss: 0.04825 FastRCNN total loss: 0.1208 L1 loss: 0.0000e+00 L2 loss: 0.59043 Learning rate: 0.0004 Mask loss: 0.11082 RPN box loss: 0.00971 RPN score loss: 0.00318 RPN total loss: 0.01289 Total loss: 0.83495 timestamp: 1654970271.3020642 iteration: 71445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09535 FastRCNN class loss: 0.05667 FastRCNN total loss: 0.15202 L1 loss: 0.0000e+00 L2 loss: 0.59043 Learning rate: 0.0004 Mask loss: 0.14614 RPN box loss: 0.00701 RPN score loss: 0.00619 RPN total loss: 0.0132 Total loss: 0.90179 timestamp: 1654970274.4948642 iteration: 71450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.12082 L1 loss: 0.0000e+00 L2 loss: 0.59043 Learning rate: 0.0004 Mask loss: 0.16128 RPN box loss: 0.00936 RPN score loss: 0.0038 RPN total loss: 0.01316 Total loss: 0.88568 timestamp: 1654970277.7603295 iteration: 71455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.136 FastRCNN class loss: 0.08252 FastRCNN total loss: 0.21852 L1 loss: 0.0000e+00 L2 loss: 0.59043 Learning rate: 0.0004 Mask loss: 0.18377 RPN box loss: 0.01014 RPN score loss: 0.00537 RPN total loss: 0.0155 Total loss: 1.00822 timestamp: 1654970280.9755886 iteration: 71460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08216 FastRCNN class loss: 0.06493 FastRCNN total loss: 0.14709 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.0004 Mask loss: 0.12407 RPN box loss: 0.00508 RPN score loss: 0.00659 RPN total loss: 0.01167 Total loss: 0.87325 timestamp: 1654970284.2100098 iteration: 71465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07905 FastRCNN class loss: 0.09259 FastRCNN total loss: 0.17164 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.0004 Mask loss: 0.14282 RPN box loss: 0.0117 RPN score loss: 0.00552 RPN total loss: 0.01722 Total loss: 0.92211 timestamp: 1654970287.412024 iteration: 71470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08345 FastRCNN class loss: 0.11218 FastRCNN total loss: 0.19563 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.0004 Mask loss: 0.19296 RPN box loss: 0.01564 RPN score loss: 0.00838 RPN total loss: 0.02401 Total loss: 1.00302 timestamp: 1654970290.6279585 iteration: 71475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13267 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.19397 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.0004 Mask loss: 0.13887 RPN box loss: 0.00949 RPN score loss: 0.00311 RPN total loss: 0.01259 Total loss: 0.93585 timestamp: 1654970293.7453444 iteration: 71480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09095 FastRCNN class loss: 0.05426 FastRCNN total loss: 0.14521 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.0004 Mask loss: 0.10569 RPN box loss: 0.0093 RPN score loss: 0.00349 RPN total loss: 0.01279 Total loss: 0.85411 timestamp: 1654970296.9868622 iteration: 71485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.08759 FastRCNN total loss: 0.1992 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.0004 Mask loss: 0.17333 RPN box loss: 0.0302 RPN score loss: 0.00649 RPN total loss: 0.03669 Total loss: 0.99963 timestamp: 1654970300.2038484 iteration: 71490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06713 FastRCNN class loss: 0.04594 FastRCNN total loss: 0.11307 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.0004 Mask loss: 0.09051 RPN box loss: 0.01645 RPN score loss: 0.002 RPN total loss: 0.01845 Total loss: 0.81244 timestamp: 1654970303.4994266 iteration: 71495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08444 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.14289 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.0004 Mask loss: 0.11725 RPN box loss: 0.00565 RPN score loss: 0.00576 RPN total loss: 0.01141 Total loss: 0.86197 timestamp: 1654970306.7908492 iteration: 71500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10334 FastRCNN class loss: 0.08921 FastRCNN total loss: 0.19254 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.0004 Mask loss: 0.20888 RPN box loss: 0.02052 RPN score loss: 0.01066 RPN total loss: 0.03118 Total loss: 1.02301 timestamp: 1654970310.0033095 iteration: 71505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04376 FastRCNN class loss: 0.03765 FastRCNN total loss: 0.08141 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.0004 Mask loss: 0.10716 RPN box loss: 0.01633 RPN score loss: 0.00272 RPN total loss: 0.01905 Total loss: 0.79803 timestamp: 1654970313.2165902 iteration: 71510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05134 FastRCNN class loss: 0.05626 FastRCNN total loss: 0.10759 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.0004 Mask loss: 0.16505 RPN box loss: 0.01106 RPN score loss: 0.00534 RPN total loss: 0.0164 Total loss: 0.87944 timestamp: 1654970316.3974948 iteration: 71515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12134 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.18464 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.0004 Mask loss: 0.10117 RPN box loss: 0.00584 RPN score loss: 0.00204 RPN total loss: 0.00788 Total loss: 0.8841 timestamp: 1654970319.5948503 iteration: 71520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10924 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.18114 L1 loss: 0.0000e+00 L2 loss: 0.5904 Learning rate: 0.0004 Mask loss: 0.14152 RPN box loss: 0.00952 RPN score loss: 0.00733 RPN total loss: 0.01685 Total loss: 0.92992 timestamp: 1654970322.7797866 iteration: 71525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05892 FastRCNN class loss: 0.04064 FastRCNN total loss: 0.09956 L1 loss: 0.0000e+00 L2 loss: 0.5904 Learning rate: 0.0004 Mask loss: 0.14979 RPN box loss: 0.00904 RPN score loss: 0.00332 RPN total loss: 0.01236 Total loss: 0.8521 timestamp: 1654970325.9877539 iteration: 71530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07519 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.13599 L1 loss: 0.0000e+00 L2 loss: 0.5904 Learning rate: 0.0004 Mask loss: 0.13271 RPN box loss: 0.01683 RPN score loss: 0.00432 RPN total loss: 0.02114 Total loss: 0.88024 timestamp: 1654970329.2233665 iteration: 71535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.07149 FastRCNN total loss: 0.15435 L1 loss: 0.0000e+00 L2 loss: 0.5904 Learning rate: 0.0004 Mask loss: 0.14503 RPN box loss: 0.01003 RPN score loss: 0.0025 RPN total loss: 0.01253 Total loss: 0.90231 timestamp: 1654970332.3778183 iteration: 71540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05509 FastRCNN class loss: 0.03985 FastRCNN total loss: 0.09493 L1 loss: 0.0000e+00 L2 loss: 0.5904 Learning rate: 0.0004 Mask loss: 0.13241 RPN box loss: 0.00401 RPN score loss: 0.00287 RPN total loss: 0.00688 Total loss: 0.82462 timestamp: 1654970335.580251 iteration: 71545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06512 FastRCNN class loss: 0.04512 FastRCNN total loss: 0.11024 L1 loss: 0.0000e+00 L2 loss: 0.5904 Learning rate: 0.0004 Mask loss: 0.1008 RPN box loss: 0.00838 RPN score loss: 0.00346 RPN total loss: 0.01184 Total loss: 0.81327 timestamp: 1654970338.7398279 iteration: 71550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03113 FastRCNN class loss: 0.0228 FastRCNN total loss: 0.05393 L1 loss: 0.0000e+00 L2 loss: 0.59039 Learning rate: 0.0004 Mask loss: 0.09734 RPN box loss: 0.00753 RPN score loss: 0.00434 RPN total loss: 0.01187 Total loss: 0.75353 timestamp: 1654970341.9579728 iteration: 71555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09139 FastRCNN class loss: 0.05484 FastRCNN total loss: 0.14623 L1 loss: 0.0000e+00 L2 loss: 0.59039 Learning rate: 0.0004 Mask loss: 0.10228 RPN box loss: 0.00725 RPN score loss: 0.00335 RPN total loss: 0.01059 Total loss: 0.84949 timestamp: 1654970345.213732 iteration: 71560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07724 FastRCNN class loss: 0.06186 FastRCNN total loss: 0.1391 L1 loss: 0.0000e+00 L2 loss: 0.59039 Learning rate: 0.0004 Mask loss: 0.12513 RPN box loss: 0.00394 RPN score loss: 0.00191 RPN total loss: 0.00585 Total loss: 0.86047 timestamp: 1654970348.4060838 iteration: 71565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06129 FastRCNN class loss: 0.07069 FastRCNN total loss: 0.13198 L1 loss: 0.0000e+00 L2 loss: 0.59039 Learning rate: 0.0004 Mask loss: 0.11824 RPN box loss: 0.01398 RPN score loss: 0.00531 RPN total loss: 0.01929 Total loss: 0.8599 timestamp: 1654970351.5734618 iteration: 71570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08616 FastRCNN class loss: 0.07107 FastRCNN total loss: 0.15723 L1 loss: 0.0000e+00 L2 loss: 0.59039 Learning rate: 0.0004 Mask loss: 0.15255 RPN box loss: 0.01539 RPN score loss: 0.00398 RPN total loss: 0.01937 Total loss: 0.91954 timestamp: 1654970354.7545164 iteration: 71575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10473 FastRCNN class loss: 0.10663 FastRCNN total loss: 0.21136 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.16022 RPN box loss: 0.02319 RPN score loss: 0.00557 RPN total loss: 0.02876 Total loss: 0.99072 timestamp: 1654970357.99212 iteration: 71580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07863 FastRCNN class loss: 0.05401 FastRCNN total loss: 0.13264 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.10598 RPN box loss: 0.00754 RPN score loss: 0.00479 RPN total loss: 0.01233 Total loss: 0.84133 timestamp: 1654970361.1715584 iteration: 71585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10243 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.1634 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.12224 RPN box loss: 0.00606 RPN score loss: 0.00463 RPN total loss: 0.01069 Total loss: 0.88672 timestamp: 1654970364.3337963 iteration: 71590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10122 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.15361 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.1422 RPN box loss: 0.02605 RPN score loss: 0.00776 RPN total loss: 0.03381 Total loss: 0.92 timestamp: 1654970367.5300918 iteration: 71595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04407 FastRCNN class loss: 0.04699 FastRCNN total loss: 0.09106 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.1424 RPN box loss: 0.00703 RPN score loss: 0.0005 RPN total loss: 0.00753 Total loss: 0.83136 timestamp: 1654970370.79811 iteration: 71600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09423 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.19498 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.1537 RPN box loss: 0.01065 RPN score loss: 0.00226 RPN total loss: 0.01291 Total loss: 0.95196 timestamp: 1654970373.98281 iteration: 71605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17172 FastRCNN class loss: 0.1222 FastRCNN total loss: 0.29392 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.15684 RPN box loss: 0.01948 RPN score loss: 0.00773 RPN total loss: 0.0272 Total loss: 1.06835 timestamp: 1654970377.192226 iteration: 71610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10326 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.18429 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.0004 Mask loss: 0.14111 RPN box loss: 0.01347 RPN score loss: 0.00274 RPN total loss: 0.01621 Total loss: 0.93199 timestamp: 1654970380.3984208 iteration: 71615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06936 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.12932 L1 loss: 0.0000e+00 L2 loss: 0.59037 Learning rate: 0.0004 Mask loss: 0.12611 RPN box loss: 0.02353 RPN score loss: 0.0014 RPN total loss: 0.02493 Total loss: 0.87073 timestamp: 1654970383.6339128 iteration: 71620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09715 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.16278 L1 loss: 0.0000e+00 L2 loss: 0.59037 Learning rate: 0.0004 Mask loss: 0.10755 RPN box loss: 0.01021 RPN score loss: 0.00222 RPN total loss: 0.01242 Total loss: 0.87313 timestamp: 1654970386.8433273 iteration: 71625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12596 FastRCNN class loss: 0.10031 FastRCNN total loss: 0.22627 L1 loss: 0.0000e+00 L2 loss: 0.59037 Learning rate: 0.0004 Mask loss: 0.13831 RPN box loss: 0.08272 RPN score loss: 0.00614 RPN total loss: 0.08886 Total loss: 1.04381 timestamp: 1654970390.0366592 iteration: 71630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04318 FastRCNN class loss: 0.0433 FastRCNN total loss: 0.08648 L1 loss: 0.0000e+00 L2 loss: 0.59037 Learning rate: 0.0004 Mask loss: 0.10791 RPN box loss: 0.01235 RPN score loss: 0.00692 RPN total loss: 0.01927 Total loss: 0.80402 timestamp: 1654970393.251932 iteration: 71635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10187 FastRCNN class loss: 0.10402 FastRCNN total loss: 0.20589 L1 loss: 0.0000e+00 L2 loss: 0.59037 Learning rate: 0.0004 Mask loss: 0.2495 RPN box loss: 0.03175 RPN score loss: 0.04631 RPN total loss: 0.07806 Total loss: 1.12381 timestamp: 1654970396.492065 iteration: 71640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08789 FastRCNN class loss: 0.0921 FastRCNN total loss: 0.18 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.1575 RPN box loss: 0.01659 RPN score loss: 0.00182 RPN total loss: 0.01841 Total loss: 0.94627 timestamp: 1654970399.6637821 iteration: 71645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11257 FastRCNN class loss: 0.06273 FastRCNN total loss: 0.17529 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.14222 RPN box loss: 0.00903 RPN score loss: 0.00435 RPN total loss: 0.01338 Total loss: 0.92126 timestamp: 1654970402.8866649 iteration: 71650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06929 FastRCNN class loss: 0.04743 FastRCNN total loss: 0.11672 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.13315 RPN box loss: 0.00585 RPN score loss: 0.0146 RPN total loss: 0.02045 Total loss: 0.86068 timestamp: 1654970406.1132832 iteration: 71655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10572 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.16397 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.10867 RPN box loss: 0.0113 RPN score loss: 0.00355 RPN total loss: 0.01485 Total loss: 0.87785 timestamp: 1654970409.3927805 iteration: 71660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11891 FastRCNN class loss: 0.08035 FastRCNN total loss: 0.19926 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.13469 RPN box loss: 0.01117 RPN score loss: 0.00696 RPN total loss: 0.01813 Total loss: 0.94244 timestamp: 1654970412.6182888 iteration: 71665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06204 FastRCNN class loss: 0.0486 FastRCNN total loss: 0.11064 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.10161 RPN box loss: 0.00449 RPN score loss: 0.00206 RPN total loss: 0.00654 Total loss: 0.80915 timestamp: 1654970415.7659194 iteration: 71670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04233 FastRCNN class loss: 0.05607 FastRCNN total loss: 0.0984 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.0004 Mask loss: 0.09286 RPN box loss: 0.01008 RPN score loss: 0.0021 RPN total loss: 0.01219 Total loss: 0.7938 timestamp: 1654970418.8978956 iteration: 71675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16568 FastRCNN class loss: 0.06416 FastRCNN total loss: 0.22984 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.0004 Mask loss: 0.1113 RPN box loss: 0.02392 RPN score loss: 0.00278 RPN total loss: 0.0267 Total loss: 0.9582 timestamp: 1654970422.017162 iteration: 71680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07115 FastRCNN class loss: 0.05359 FastRCNN total loss: 0.12474 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.0004 Mask loss: 0.0939 RPN box loss: 0.0189 RPN score loss: 0.00257 RPN total loss: 0.02147 Total loss: 0.83046 timestamp: 1654970425.2201905 iteration: 71685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09845 FastRCNN class loss: 0.0983 FastRCNN total loss: 0.19675 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.0004 Mask loss: 0.1541 RPN box loss: 0.00766 RPN score loss: 0.00387 RPN total loss: 0.01153 Total loss: 0.95272 timestamp: 1654970428.4060473 iteration: 71690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07561 FastRCNN class loss: 0.07107 FastRCNN total loss: 0.14668 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.0004 Mask loss: 0.13538 RPN box loss: 0.01239 RPN score loss: 0.00589 RPN total loss: 0.01828 Total loss: 0.89069 timestamp: 1654970431.5608783 iteration: 71695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07382 FastRCNN class loss: 0.09495 FastRCNN total loss: 0.16878 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.0004 Mask loss: 0.11902 RPN box loss: 0.00884 RPN score loss: 0.00074 RPN total loss: 0.00959 Total loss: 0.88773 timestamp: 1654970434.7170577 iteration: 71700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08789 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.15963 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.0004 Mask loss: 0.11011 RPN box loss: 0.01296 RPN score loss: 0.00239 RPN total loss: 0.01534 Total loss: 0.87543 timestamp: 1654970437.9553952 iteration: 71705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11935 FastRCNN class loss: 0.1077 FastRCNN total loss: 0.22705 L1 loss: 0.0000e+00 L2 loss: 0.59034 Learning rate: 0.0004 Mask loss: 0.15769 RPN box loss: 0.01012 RPN score loss: 0.01287 RPN total loss: 0.02299 Total loss: 0.99807 timestamp: 1654970441.226333 iteration: 71710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06889 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.15721 L1 loss: 0.0000e+00 L2 loss: 0.59034 Learning rate: 0.0004 Mask loss: 0.10773 RPN box loss: 0.03528 RPN score loss: 0.01598 RPN total loss: 0.05127 Total loss: 0.90655 timestamp: 1654970444.4785275 iteration: 71715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09624 FastRCNN class loss: 0.07584 FastRCNN total loss: 0.17208 L1 loss: 0.0000e+00 L2 loss: 0.59034 Learning rate: 0.0004 Mask loss: 0.13618 RPN box loss: 0.00505 RPN score loss: 0.00446 RPN total loss: 0.00951 Total loss: 0.90811 timestamp: 1654970447.724205 iteration: 71720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09058 FastRCNN class loss: 0.04882 FastRCNN total loss: 0.1394 L1 loss: 0.0000e+00 L2 loss: 0.59034 Learning rate: 0.0004 Mask loss: 0.10219 RPN box loss: 0.00818 RPN score loss: 0.00328 RPN total loss: 0.01146 Total loss: 0.84338 timestamp: 1654970450.8730168 iteration: 71725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11178 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.19839 L1 loss: 0.0000e+00 L2 loss: 0.59034 Learning rate: 0.0004 Mask loss: 0.19163 RPN box loss: 0.01558 RPN score loss: 0.01288 RPN total loss: 0.02846 Total loss: 1.00882 timestamp: 1654970454.1008296 iteration: 71730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05975 FastRCNN class loss: 0.04823 FastRCNN total loss: 0.10798 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.0004 Mask loss: 0.15214 RPN box loss: 0.01594 RPN score loss: 0.00124 RPN total loss: 0.01718 Total loss: 0.86763 timestamp: 1654970457.35795 iteration: 71735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10017 FastRCNN class loss: 0.08501 FastRCNN total loss: 0.18518 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.0004 Mask loss: 0.12513 RPN box loss: 0.0194 RPN score loss: 0.00402 RPN total loss: 0.02342 Total loss: 0.92406 timestamp: 1654970460.4628818 iteration: 71740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14456 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.20506 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.0004 Mask loss: 0.14485 RPN box loss: 0.01136 RPN score loss: 0.00737 RPN total loss: 0.01873 Total loss: 0.95896 timestamp: 1654970463.5789359 iteration: 71745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07659 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.14136 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.0004 Mask loss: 0.10644 RPN box loss: 0.00576 RPN score loss: 0.00175 RPN total loss: 0.0075 Total loss: 0.84564 timestamp: 1654970466.7136936 iteration: 71750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07638 FastRCNN class loss: 0.0425 FastRCNN total loss: 0.11888 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.0004 Mask loss: 0.10343 RPN box loss: 0.01201 RPN score loss: 0.00262 RPN total loss: 0.01463 Total loss: 0.82727 timestamp: 1654970469.9102995 iteration: 71755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06386 FastRCNN class loss: 0.039 FastRCNN total loss: 0.10286 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.0004 Mask loss: 0.09654 RPN box loss: 0.0296 RPN score loss: 0.00803 RPN total loss: 0.03763 Total loss: 0.82736 timestamp: 1654970473.1095052 iteration: 71760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08708 FastRCNN class loss: 0.09112 FastRCNN total loss: 0.1782 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.0004 Mask loss: 0.10645 RPN box loss: 0.01505 RPN score loss: 0.0061 RPN total loss: 0.02115 Total loss: 0.89613 timestamp: 1654970476.251123 iteration: 71765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1062 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.18221 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.0004 Mask loss: 0.17016 RPN box loss: 0.02938 RPN score loss: 0.01048 RPN total loss: 0.03986 Total loss: 0.98256 timestamp: 1654970479.5082715 iteration: 71770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0855 FastRCNN class loss: 0.04944 FastRCNN total loss: 0.13494 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.0004 Mask loss: 0.12051 RPN box loss: 0.0179 RPN score loss: 0.00909 RPN total loss: 0.02699 Total loss: 0.87276 timestamp: 1654970482.696722 iteration: 71775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10039 FastRCNN class loss: 0.05131 FastRCNN total loss: 0.1517 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.0004 Mask loss: 0.16272 RPN box loss: 0.01778 RPN score loss: 0.00277 RPN total loss: 0.02055 Total loss: 0.92528 timestamp: 1654970485.8783412 iteration: 71780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1334 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.19666 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.0004 Mask loss: 0.12173 RPN box loss: 0.06139 RPN score loss: 0.00414 RPN total loss: 0.06552 Total loss: 0.97423 timestamp: 1654970489.0338821 iteration: 71785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06304 FastRCNN class loss: 0.04085 FastRCNN total loss: 0.10389 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.0004 Mask loss: 0.11736 RPN box loss: 0.00503 RPN score loss: 0.00234 RPN total loss: 0.00738 Total loss: 0.81894 timestamp: 1654970492.193026 iteration: 71790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13162 FastRCNN class loss: 0.07876 FastRCNN total loss: 0.21038 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.0004 Mask loss: 0.14464 RPN box loss: 0.02036 RPN score loss: 0.00365 RPN total loss: 0.02402 Total loss: 0.96935 timestamp: 1654970495.451065 iteration: 71795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05175 FastRCNN class loss: 0.03811 FastRCNN total loss: 0.08986 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.0004 Mask loss: 0.12034 RPN box loss: 0.01716 RPN score loss: 0.00154 RPN total loss: 0.0187 Total loss: 0.81921 timestamp: 1654970498.652396 iteration: 71800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11479 FastRCNN class loss: 0.06952 FastRCNN total loss: 0.18431 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.0004 Mask loss: 0.15702 RPN box loss: 0.03227 RPN score loss: 0.00206 RPN total loss: 0.03433 Total loss: 0.96598 timestamp: 1654970501.7696493 iteration: 71805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07227 FastRCNN class loss: 0.05813 FastRCNN total loss: 0.1304 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.0004 Mask loss: 0.1099 RPN box loss: 0.00684 RPN score loss: 0.00077 RPN total loss: 0.00761 Total loss: 0.83822 timestamp: 1654970504.9611738 iteration: 71810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10259 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.17047 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.0004 Mask loss: 0.0871 RPN box loss: 0.00745 RPN score loss: 0.00234 RPN total loss: 0.00979 Total loss: 0.85766 timestamp: 1654970508.2593985 iteration: 71815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13901 FastRCNN class loss: 0.05372 FastRCNN total loss: 0.19273 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.0004 Mask loss: 0.12821 RPN box loss: 0.00954 RPN score loss: 0.00251 RPN total loss: 0.01205 Total loss: 0.92329 timestamp: 1654970511.4445403 iteration: 71820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10982 FastRCNN class loss: 0.07784 FastRCNN total loss: 0.18766 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.0004 Mask loss: 0.12586 RPN box loss: 0.00618 RPN score loss: 0.00165 RPN total loss: 0.00782 Total loss: 0.91165 timestamp: 1654970514.6720266 iteration: 71825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11731 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.20633 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.0004 Mask loss: 0.19347 RPN box loss: 0.01508 RPN score loss: 0.0045 RPN total loss: 0.01957 Total loss: 1.00967 timestamp: 1654970517.8413312 iteration: 71830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09391 FastRCNN class loss: 0.04673 FastRCNN total loss: 0.14064 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.0004 Mask loss: 0.10781 RPN box loss: 0.00595 RPN score loss: 0.00263 RPN total loss: 0.00858 Total loss: 0.84733 timestamp: 1654970521.1147459 iteration: 71835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1591 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.23057 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.0004 Mask loss: 0.10099 RPN box loss: 0.00768 RPN score loss: 0.00509 RPN total loss: 0.01278 Total loss: 0.93464 timestamp: 1654970524.3138332 iteration: 71840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07393 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.1234 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.0004 Mask loss: 0.08443 RPN box loss: 0.00686 RPN score loss: 0.00212 RPN total loss: 0.00898 Total loss: 0.80711 timestamp: 1654970527.553581 iteration: 71845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04297 FastRCNN class loss: 0.05618 FastRCNN total loss: 0.09915 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.0004 Mask loss: 0.08159 RPN box loss: 0.00625 RPN score loss: 0.00229 RPN total loss: 0.00855 Total loss: 0.77959 timestamp: 1654970530.7157986 iteration: 71850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07643 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.14714 L1 loss: 0.0000e+00 L2 loss: 0.59029 Learning rate: 0.0004 Mask loss: 0.13776 RPN box loss: 0.04202 RPN score loss: 0.00273 RPN total loss: 0.04474 Total loss: 0.91993 timestamp: 1654970533.9257138 iteration: 71855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06657 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.13221 L1 loss: 0.0000e+00 L2 loss: 0.59029 Learning rate: 0.0004 Mask loss: 0.11106 RPN box loss: 0.00603 RPN score loss: 0.00183 RPN total loss: 0.00785 Total loss: 0.84141 timestamp: 1654970537.1401567 iteration: 71860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09523 FastRCNN class loss: 0.06432 FastRCNN total loss: 0.15956 L1 loss: 0.0000e+00 L2 loss: 0.59029 Learning rate: 0.0004 Mask loss: 0.12839 RPN box loss: 0.0232 RPN score loss: 0.00164 RPN total loss: 0.02484 Total loss: 0.90307 timestamp: 1654970540.344079 iteration: 71865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09796 FastRCNN class loss: 0.08373 FastRCNN total loss: 0.18169 L1 loss: 0.0000e+00 L2 loss: 0.59029 Learning rate: 0.0004 Mask loss: 0.15164 RPN box loss: 0.01502 RPN score loss: 0.00337 RPN total loss: 0.01839 Total loss: 0.94201 timestamp: 1654970543.506549 iteration: 71870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11016 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.17233 L1 loss: 0.0000e+00 L2 loss: 0.59029 Learning rate: 0.0004 Mask loss: 0.15974 RPN box loss: 0.00427 RPN score loss: 0.00757 RPN total loss: 0.01184 Total loss: 0.9342 timestamp: 1654970546.7558074 iteration: 71875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05503 FastRCNN class loss: 0.04576 FastRCNN total loss: 0.10079 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.0004 Mask loss: 0.12214 RPN box loss: 0.00574 RPN score loss: 0.00243 RPN total loss: 0.00818 Total loss: 0.82139 timestamp: 1654970549.9554636 iteration: 71880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04244 FastRCNN class loss: 0.04388 FastRCNN total loss: 0.08632 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.0004 Mask loss: 0.15067 RPN box loss: 0.01114 RPN score loss: 0.00159 RPN total loss: 0.01273 Total loss: 0.84001 timestamp: 1654970553.138693 iteration: 71885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07063 FastRCNN class loss: 0.05073 FastRCNN total loss: 0.12136 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.0004 Mask loss: 0.19973 RPN box loss: 0.00662 RPN score loss: 0.00332 RPN total loss: 0.00994 Total loss: 0.9213 timestamp: 1654970556.2761447 iteration: 71890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0444 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.09856 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.0004 Mask loss: 0.1177 RPN box loss: 0.00773 RPN score loss: 0.00325 RPN total loss: 0.01098 Total loss: 0.81751 timestamp: 1654970559.594801 iteration: 71895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0873 FastRCNN class loss: 0.07097 FastRCNN total loss: 0.15828 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.0004 Mask loss: 0.16522 RPN box loss: 0.03258 RPN score loss: 0.00788 RPN total loss: 0.04045 Total loss: 0.95423 timestamp: 1654970562.7775207 iteration: 71900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06612 FastRCNN class loss: 0.05177 FastRCNN total loss: 0.11789 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.0004 Mask loss: 0.12622 RPN box loss: 0.01372 RPN score loss: 0.01183 RPN total loss: 0.02555 Total loss: 0.85994 timestamp: 1654970565.9725995 iteration: 71905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08018 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.13844 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.11912 RPN box loss: 0.01578 RPN score loss: 0.00558 RPN total loss: 0.02136 Total loss: 0.86919 timestamp: 1654970569.1254485 iteration: 71910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09396 FastRCNN class loss: 0.11743 FastRCNN total loss: 0.21138 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.21177 RPN box loss: 0.01649 RPN score loss: 0.00507 RPN total loss: 0.02156 Total loss: 1.03499 timestamp: 1654970572.3421926 iteration: 71915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.086 FastRCNN class loss: 0.03836 FastRCNN total loss: 0.12436 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.10136 RPN box loss: 0.00548 RPN score loss: 0.00084 RPN total loss: 0.00632 Total loss: 0.82231 timestamp: 1654970575.563037 iteration: 71920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08925 FastRCNN class loss: 0.05423 FastRCNN total loss: 0.14347 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.10594 RPN box loss: 0.00378 RPN score loss: 0.00303 RPN total loss: 0.00681 Total loss: 0.8465 timestamp: 1654970578.869562 iteration: 71925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09612 FastRCNN class loss: 0.04727 FastRCNN total loss: 0.14339 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.15454 RPN box loss: 0.00952 RPN score loss: 0.00352 RPN total loss: 0.01304 Total loss: 0.90125 timestamp: 1654970582.045269 iteration: 71930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.08797 FastRCNN total loss: 0.17469 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.12649 RPN box loss: 0.00858 RPN score loss: 0.00835 RPN total loss: 0.01693 Total loss: 0.90837 timestamp: 1654970585.1568341 iteration: 71935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12865 FastRCNN class loss: 0.07532 FastRCNN total loss: 0.20397 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.0004 Mask loss: 0.16478 RPN box loss: 0.02281 RPN score loss: 0.01364 RPN total loss: 0.03645 Total loss: 0.99547 timestamp: 1654970588.3927536 iteration: 71940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09377 FastRCNN class loss: 0.07804 FastRCNN total loss: 0.1718 L1 loss: 0.0000e+00 L2 loss: 0.59026 Learning rate: 0.0004 Mask loss: 0.13141 RPN box loss: 0.00964 RPN score loss: 0.00322 RPN total loss: 0.01286 Total loss: 0.90634 timestamp: 1654970591.6000104 iteration: 71945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06737 FastRCNN class loss: 0.05507 FastRCNN total loss: 0.12243 L1 loss: 0.0000e+00 L2 loss: 0.59026 Learning rate: 0.0004 Mask loss: 0.09544 RPN box loss: 0.011 RPN score loss: 0.00115 RPN total loss: 0.01215 Total loss: 0.82028 timestamp: 1654970594.8544514 iteration: 71950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09072 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.13786 L1 loss: 0.0000e+00 L2 loss: 0.59026 Learning rate: 0.0004 Mask loss: 0.13836 RPN box loss: 0.03096 RPN score loss: 0.00333 RPN total loss: 0.03429 Total loss: 0.90077 timestamp: 1654970598.0462704 iteration: 71955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07822 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.14075 L1 loss: 0.0000e+00 L2 loss: 0.59026 Learning rate: 0.0004 Mask loss: 0.11689 RPN box loss: 0.00963 RPN score loss: 0.00305 RPN total loss: 0.01268 Total loss: 0.86057 timestamp: 1654970601.2317574 iteration: 71960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0444 FastRCNN class loss: 0.05139 FastRCNN total loss: 0.09579 L1 loss: 0.0000e+00 L2 loss: 0.59026 Learning rate: 0.0004 Mask loss: 0.1164 RPN box loss: 0.01071 RPN score loss: 0.00089 RPN total loss: 0.0116 Total loss: 0.81404 timestamp: 1654970604.3770173 iteration: 71965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.0777 FastRCNN total loss: 0.15127 L1 loss: 0.0000e+00 L2 loss: 0.59025 Learning rate: 0.0004 Mask loss: 0.12997 RPN box loss: 0.01119 RPN score loss: 0.00233 RPN total loss: 0.01351 Total loss: 0.88501 timestamp: 1654970607.5569236 iteration: 71970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08288 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.13733 L1 loss: 0.0000e+00 L2 loss: 0.59025 Learning rate: 0.0004 Mask loss: 0.11889 RPN box loss: 0.01021 RPN score loss: 0.00228 RPN total loss: 0.01249 Total loss: 0.85896 timestamp: 1654970610.7253268 iteration: 71975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06837 FastRCNN class loss: 0.09403 FastRCNN total loss: 0.1624 L1 loss: 0.0000e+00 L2 loss: 0.59025 Learning rate: 0.0004 Mask loss: 0.16641 RPN box loss: 0.0102 RPN score loss: 0.01272 RPN total loss: 0.02292 Total loss: 0.94197 timestamp: 1654970613.8780286 iteration: 71980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05517 FastRCNN class loss: 0.0733 FastRCNN total loss: 0.12847 L1 loss: 0.0000e+00 L2 loss: 0.59025 Learning rate: 0.0004 Mask loss: 0.12724 RPN box loss: 0.00422 RPN score loss: 0.00659 RPN total loss: 0.01081 Total loss: 0.85676 timestamp: 1654970617.0970545 iteration: 71985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.17393 L1 loss: 0.0000e+00 L2 loss: 0.59025 Learning rate: 0.0004 Mask loss: 0.14655 RPN box loss: 0.01514 RPN score loss: 0.0089 RPN total loss: 0.02403 Total loss: 0.93476 timestamp: 1654970620.4039214 iteration: 71990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.18458 L1 loss: 0.0000e+00 L2 loss: 0.59025 Learning rate: 0.0004 Mask loss: 0.17223 RPN box loss: 0.02837 RPN score loss: 0.00447 RPN total loss: 0.03284 Total loss: 0.9799 timestamp: 1654970623.6022632 iteration: 71995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07022 FastRCNN class loss: 0.04377 FastRCNN total loss: 0.11399 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.12468 RPN box loss: 0.02942 RPN score loss: 0.00502 RPN total loss: 0.03444 Total loss: 0.86335 timestamp: 1654970626.8394785 iteration: 72000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07647 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.14772 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.1012 RPN box loss: 0.00762 RPN score loss: 0.00237 RPN total loss: 0.00999 Total loss: 0.84916 timestamp: 1654970630.0640862 iteration: 72005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.1317 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.12974 RPN box loss: 0.00317 RPN score loss: 0.00174 RPN total loss: 0.00491 Total loss: 0.85659 timestamp: 1654970633.3113225 iteration: 72010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12767 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.19184 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.23352 RPN box loss: 0.01452 RPN score loss: 0.00455 RPN total loss: 0.01908 Total loss: 1.03467 timestamp: 1654970636.5037832 iteration: 72015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08738 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.15658 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.14299 RPN box loss: 0.01633 RPN score loss: 0.00488 RPN total loss: 0.0212 Total loss: 0.91101 timestamp: 1654970639.7496712 iteration: 72020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08852 FastRCNN class loss: 0.08048 FastRCNN total loss: 0.169 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.14738 RPN box loss: 0.01399 RPN score loss: 0.00436 RPN total loss: 0.01834 Total loss: 0.92495 timestamp: 1654970642.9259562 iteration: 72025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12196 FastRCNN class loss: 0.0901 FastRCNN total loss: 0.21206 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.0004 Mask loss: 0.13352 RPN box loss: 0.01389 RPN score loss: 0.00651 RPN total loss: 0.0204 Total loss: 0.95622 timestamp: 1654970646.1461606 iteration: 72030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13481 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.21847 L1 loss: 0.0000e+00 L2 loss: 0.59023 Learning rate: 0.0004 Mask loss: 0.13827 RPN box loss: 0.01146 RPN score loss: 0.00482 RPN total loss: 0.01627 Total loss: 0.96325 timestamp: 1654970649.3977785 iteration: 72035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04411 FastRCNN class loss: 0.03779 FastRCNN total loss: 0.0819 L1 loss: 0.0000e+00 L2 loss: 0.59023 Learning rate: 0.0004 Mask loss: 0.08442 RPN box loss: 0.01007 RPN score loss: 0.0035 RPN total loss: 0.01357 Total loss: 0.77013 timestamp: 1654970652.5554714 iteration: 72040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0975 FastRCNN class loss: 0.04954 FastRCNN total loss: 0.14704 L1 loss: 0.0000e+00 L2 loss: 0.59023 Learning rate: 0.0004 Mask loss: 0.09503 RPN box loss: 0.01145 RPN score loss: 0.00872 RPN total loss: 0.02016 Total loss: 0.85246 timestamp: 1654970655.68982 iteration: 72045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10598 FastRCNN class loss: 0.06649 FastRCNN total loss: 0.17247 L1 loss: 0.0000e+00 L2 loss: 0.59023 Learning rate: 0.0004 Mask loss: 0.12823 RPN box loss: 0.0201 RPN score loss: 0.00631 RPN total loss: 0.02641 Total loss: 0.91733 timestamp: 1654970658.8794916 iteration: 72050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09271 FastRCNN class loss: 0.03222 FastRCNN total loss: 0.12493 L1 loss: 0.0000e+00 L2 loss: 0.59023 Learning rate: 0.0004 Mask loss: 0.127 RPN box loss: 0.00684 RPN score loss: 0.00799 RPN total loss: 0.01484 Total loss: 0.85699 timestamp: 1654970662.108113 iteration: 72055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08214 FastRCNN class loss: 0.07742 FastRCNN total loss: 0.15957 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.14833 RPN box loss: 0.0151 RPN score loss: 0.00296 RPN total loss: 0.01807 Total loss: 0.91619 timestamp: 1654970665.306352 iteration: 72060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12452 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.20947 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.12192 RPN box loss: 0.0051 RPN score loss: 0.00746 RPN total loss: 0.01256 Total loss: 0.93418 timestamp: 1654970668.501816 iteration: 72065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06786 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.13934 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.11957 RPN box loss: 0.00728 RPN score loss: 0.00711 RPN total loss: 0.01439 Total loss: 0.86352 timestamp: 1654970671.6882603 iteration: 72070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09569 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.14547 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.106 RPN box loss: 0.00352 RPN score loss: 0.00307 RPN total loss: 0.00658 Total loss: 0.84828 timestamp: 1654970674.820573 iteration: 72075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07551 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.12373 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.13794 RPN box loss: 0.01052 RPN score loss: 0.00896 RPN total loss: 0.01948 Total loss: 0.87136 timestamp: 1654970678.0238419 iteration: 72080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06664 FastRCNN class loss: 0.03966 FastRCNN total loss: 0.1063 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.08891 RPN box loss: 0.00954 RPN score loss: 0.00168 RPN total loss: 0.01122 Total loss: 0.79664 timestamp: 1654970681.2652292 iteration: 72085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08306 FastRCNN class loss: 0.05873 FastRCNN total loss: 0.14179 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.0004 Mask loss: 0.13954 RPN box loss: 0.00593 RPN score loss: 0.00239 RPN total loss: 0.00832 Total loss: 0.87987 timestamp: 1654970684.4770403 iteration: 72090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10231 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.172 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.0004 Mask loss: 0.14707 RPN box loss: 0.03152 RPN score loss: 0.01392 RPN total loss: 0.04544 Total loss: 0.95473 timestamp: 1654970687.6501126 iteration: 72095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06723 FastRCNN class loss: 0.06361 FastRCNN total loss: 0.13084 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.0004 Mask loss: 0.17782 RPN box loss: 0.00697 RPN score loss: 0.00152 RPN total loss: 0.00849 Total loss: 0.90736 timestamp: 1654970690.8446634 iteration: 72100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08922 FastRCNN class loss: 0.071 FastRCNN total loss: 0.16023 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.0004 Mask loss: 0.11136 RPN box loss: 0.02557 RPN score loss: 0.00486 RPN total loss: 0.03043 Total loss: 0.89222 timestamp: 1654970694.030525 iteration: 72105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10987 FastRCNN class loss: 0.05456 FastRCNN total loss: 0.16443 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.0004 Mask loss: 0.13672 RPN box loss: 0.01674 RPN score loss: 0.00347 RPN total loss: 0.02021 Total loss: 0.91157 timestamp: 1654970697.2950099 iteration: 72110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11486 FastRCNN class loss: 0.07045 FastRCNN total loss: 0.18531 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.0004 Mask loss: 0.10439 RPN box loss: 0.01714 RPN score loss: 0.00522 RPN total loss: 0.02236 Total loss: 0.90227 timestamp: 1654970700.539112 iteration: 72115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1313 FastRCNN class loss: 0.07409 FastRCNN total loss: 0.20539 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.0004 Mask loss: 0.1225 RPN box loss: 0.01636 RPN score loss: 0.00383 RPN total loss: 0.02019 Total loss: 0.93829 timestamp: 1654970703.713821 iteration: 72120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11536 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.1705 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.0004 Mask loss: 0.13189 RPN box loss: 0.00703 RPN score loss: 0.00372 RPN total loss: 0.01076 Total loss: 0.90335 timestamp: 1654970706.9625862 iteration: 72125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06413 FastRCNN class loss: 0.07485 FastRCNN total loss: 0.13898 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.0004 Mask loss: 0.12978 RPN box loss: 0.01024 RPN score loss: 0.00576 RPN total loss: 0.016 Total loss: 0.87496 timestamp: 1654970710.1808448 iteration: 72130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0803 FastRCNN class loss: 0.03868 FastRCNN total loss: 0.11898 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.0004 Mask loss: 0.07996 RPN box loss: 0.00369 RPN score loss: 0.00752 RPN total loss: 0.01121 Total loss: 0.80034 timestamp: 1654970713.42103 iteration: 72135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.04629 FastRCNN total loss: 0.11206 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.0004 Mask loss: 0.10779 RPN box loss: 0.00795 RPN score loss: 0.00439 RPN total loss: 0.01234 Total loss: 0.82239 timestamp: 1654970716.629378 iteration: 72140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0973 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.17804 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.0004 Mask loss: 0.13729 RPN box loss: 0.01577 RPN score loss: 0.00469 RPN total loss: 0.02046 Total loss: 0.92599 timestamp: 1654970719.7988513 iteration: 72145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15305 FastRCNN class loss: 0.11153 FastRCNN total loss: 0.26458 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.0004 Mask loss: 0.17073 RPN box loss: 0.02929 RPN score loss: 0.00968 RPN total loss: 0.03897 Total loss: 1.06448 timestamp: 1654970723.005476 iteration: 72150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08992 FastRCNN class loss: 0.10902 FastRCNN total loss: 0.19895 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.0004 Mask loss: 0.11281 RPN box loss: 0.0234 RPN score loss: 0.00471 RPN total loss: 0.02811 Total loss: 0.93007 timestamp: 1654970726.140901 iteration: 72155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10325 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.1667 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.0004 Mask loss: 0.13719 RPN box loss: 0.01646 RPN score loss: 0.00691 RPN total loss: 0.02337 Total loss: 0.91746 timestamp: 1654970729.333384 iteration: 72160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06418 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.1551 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.0004 Mask loss: 0.092 RPN box loss: 0.01725 RPN score loss: 0.00679 RPN total loss: 0.02405 Total loss: 0.86134 timestamp: 1654970732.5510774 iteration: 72165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09059 FastRCNN class loss: 0.044 FastRCNN total loss: 0.13459 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.0004 Mask loss: 0.13894 RPN box loss: 0.00483 RPN score loss: 0.0059 RPN total loss: 0.01073 Total loss: 0.87445 timestamp: 1654970735.6903002 iteration: 72170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.06089 FastRCNN total loss: 0.17255 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.0004 Mask loss: 0.12898 RPN box loss: 0.03124 RPN score loss: 0.00252 RPN total loss: 0.03377 Total loss: 0.92548 timestamp: 1654970738.8051789 iteration: 72175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04579 FastRCNN class loss: 0.0561 FastRCNN total loss: 0.10188 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.0004 Mask loss: 0.11533 RPN box loss: 0.00932 RPN score loss: 0.0024 RPN total loss: 0.01172 Total loss: 0.81912 timestamp: 1654970741.972476 iteration: 72180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09525 FastRCNN class loss: 0.12075 FastRCNN total loss: 0.21601 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.0004 Mask loss: 0.10225 RPN box loss: 0.01336 RPN score loss: 0.00638 RPN total loss: 0.01974 Total loss: 0.92819 timestamp: 1654970745.2354782 iteration: 72185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07054 FastRCNN class loss: 0.03898 FastRCNN total loss: 0.10952 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.0004 Mask loss: 0.11797 RPN box loss: 0.00308 RPN score loss: 0.00748 RPN total loss: 0.01056 Total loss: 0.82823 timestamp: 1654970748.4206157 iteration: 72190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10534 FastRCNN class loss: 0.07191 FastRCNN total loss: 0.17725 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.0004 Mask loss: 0.11916 RPN box loss: 0.01099 RPN score loss: 0.00736 RPN total loss: 0.01835 Total loss: 0.90494 timestamp: 1654970751.5984156 iteration: 72195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09651 FastRCNN class loss: 0.05268 FastRCNN total loss: 0.14918 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.0004 Mask loss: 0.23646 RPN box loss: 0.00602 RPN score loss: 0.00487 RPN total loss: 0.01089 Total loss: 0.98671 timestamp: 1654970754.8090284 iteration: 72200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03924 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.09614 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.0004 Mask loss: 0.08797 RPN box loss: 0.00435 RPN score loss: 0.00226 RPN total loss: 0.00661 Total loss: 0.7809 timestamp: 1654970758.0024312 iteration: 72205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04653 FastRCNN class loss: 0.03639 FastRCNN total loss: 0.08292 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.0004 Mask loss: 0.10982 RPN box loss: 0.01006 RPN score loss: 0.00177 RPN total loss: 0.01183 Total loss: 0.79475 timestamp: 1654970761.136111 iteration: 72210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09419 FastRCNN class loss: 0.08407 FastRCNN total loss: 0.17826 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.0004 Mask loss: 0.1984 RPN box loss: 0.01935 RPN score loss: 0.01301 RPN total loss: 0.03236 Total loss: 0.9992 timestamp: 1654970764.341154 iteration: 72215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.079 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.16866 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.0004 Mask loss: 0.15132 RPN box loss: 0.00504 RPN score loss: 0.00498 RPN total loss: 0.01002 Total loss: 0.92017 timestamp: 1654970767.6201892 iteration: 72220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11758 FastRCNN class loss: 0.0625 FastRCNN total loss: 0.18008 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.0004 Mask loss: 0.09351 RPN box loss: 0.0124 RPN score loss: 0.00246 RPN total loss: 0.01486 Total loss: 0.87863 timestamp: 1654970770.8308125 iteration: 72225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10129 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.16347 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.0004 Mask loss: 0.10245 RPN box loss: 0.0162 RPN score loss: 0.00638 RPN total loss: 0.02259 Total loss: 0.87868 timestamp: 1654970774.0439284 iteration: 72230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13238 FastRCNN class loss: 0.03947 FastRCNN total loss: 0.17184 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.0004 Mask loss: 0.13692 RPN box loss: 0.01122 RPN score loss: 0.00206 RPN total loss: 0.01328 Total loss: 0.91221 timestamp: 1654970777.1938028 iteration: 72235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05721 FastRCNN class loss: 0.06827 FastRCNN total loss: 0.12548 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.0004 Mask loss: 0.09566 RPN box loss: 0.01158 RPN score loss: 0.00884 RPN total loss: 0.02042 Total loss: 0.83173 timestamp: 1654970780.3553963 iteration: 72240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09202 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.16304 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.0004 Mask loss: 0.1604 RPN box loss: 0.01015 RPN score loss: 0.00259 RPN total loss: 0.01273 Total loss: 0.92634 timestamp: 1654970783.5849326 iteration: 72245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06109 FastRCNN class loss: 0.05111 FastRCNN total loss: 0.1122 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.0004 Mask loss: 0.125 RPN box loss: 0.0097 RPN score loss: 0.00196 RPN total loss: 0.01166 Total loss: 0.83902 timestamp: 1654970786.8320918 iteration: 72250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12052 FastRCNN class loss: 0.0625 FastRCNN total loss: 0.18302 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.0004 Mask loss: 0.12016 RPN box loss: 0.03263 RPN score loss: 0.00668 RPN total loss: 0.03931 Total loss: 0.93265 timestamp: 1654970790.0241306 iteration: 72255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06396 FastRCNN class loss: 0.03832 FastRCNN total loss: 0.10228 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.0004 Mask loss: 0.11604 RPN box loss: 0.00512 RPN score loss: 0.00423 RPN total loss: 0.00936 Total loss: 0.81784 timestamp: 1654970793.2775266 iteration: 72260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11214 FastRCNN class loss: 0.10322 FastRCNN total loss: 0.21536 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.0004 Mask loss: 0.20911 RPN box loss: 0.01067 RPN score loss: 0.00709 RPN total loss: 0.01775 Total loss: 1.03238 timestamp: 1654970796.452346 iteration: 72265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09164 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.16453 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.0004 Mask loss: 0.11448 RPN box loss: 0.0262 RPN score loss: 0.0055 RPN total loss: 0.0317 Total loss: 0.90086 timestamp: 1654970799.6400208 iteration: 72270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13008 FastRCNN class loss: 0.05396 FastRCNN total loss: 0.18403 L1 loss: 0.0000e+00 L2 loss: 0.59015 Learning rate: 0.0004 Mask loss: 0.12939 RPN box loss: 0.01666 RPN score loss: 0.00237 RPN total loss: 0.01903 Total loss: 0.92261 timestamp: 1654970802.7891028 iteration: 72275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04154 FastRCNN class loss: 0.05389 FastRCNN total loss: 0.09542 L1 loss: 0.0000e+00 L2 loss: 0.59015 Learning rate: 0.0004 Mask loss: 0.08723 RPN box loss: 0.00491 RPN score loss: 0.00891 RPN total loss: 0.01382 Total loss: 0.78663 timestamp: 1654970805.978907 iteration: 72280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05742 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.12229 L1 loss: 0.0000e+00 L2 loss: 0.59015 Learning rate: 0.0004 Mask loss: 0.10102 RPN box loss: 0.00704 RPN score loss: 0.00347 RPN total loss: 0.01051 Total loss: 0.82397 timestamp: 1654970809.1290393 iteration: 72285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13238 FastRCNN class loss: 0.10464 FastRCNN total loss: 0.23702 L1 loss: 0.0000e+00 L2 loss: 0.59015 Learning rate: 0.0004 Mask loss: 0.12871 RPN box loss: 0.00892 RPN score loss: 0.00389 RPN total loss: 0.01281 Total loss: 0.96869 timestamp: 1654970812.3250117 iteration: 72290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14084 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.19774 L1 loss: 0.0000e+00 L2 loss: 0.59015 Learning rate: 0.0004 Mask loss: 0.11387 RPN box loss: 0.00613 RPN score loss: 0.00365 RPN total loss: 0.00978 Total loss: 0.91153 timestamp: 1654970815.6199706 iteration: 72295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12412 FastRCNN class loss: 0.07024 FastRCNN total loss: 0.19436 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.0004 Mask loss: 0.14079 RPN box loss: 0.00809 RPN score loss: 0.0027 RPN total loss: 0.01078 Total loss: 0.93608 timestamp: 1654970818.796612 iteration: 72300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09127 FastRCNN class loss: 0.06887 FastRCNN total loss: 0.16013 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.0004 Mask loss: 0.10128 RPN box loss: 0.00526 RPN score loss: 0.0012 RPN total loss: 0.00645 Total loss: 0.85801 timestamp: 1654970821.93776 iteration: 72305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07274 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.14216 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.0004 Mask loss: 0.16279 RPN box loss: 0.01042 RPN score loss: 0.00359 RPN total loss: 0.01401 Total loss: 0.9091 timestamp: 1654970825.1205318 iteration: 72310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03958 FastRCNN class loss: 0.05418 FastRCNN total loss: 0.09376 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.0004 Mask loss: 0.08483 RPN box loss: 0.00745 RPN score loss: 0.0023 RPN total loss: 0.00975 Total loss: 0.77847 timestamp: 1654970828.3654058 iteration: 72315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07922 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.15249 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.0004 Mask loss: 0.09577 RPN box loss: 0.01457 RPN score loss: 0.00512 RPN total loss: 0.01969 Total loss: 0.85809 timestamp: 1654970831.5340838 iteration: 72320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12033 FastRCNN class loss: 0.07853 FastRCNN total loss: 0.19887 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.0004 Mask loss: 0.13991 RPN box loss: 0.01287 RPN score loss: 0.00927 RPN total loss: 0.02213 Total loss: 0.95105 timestamp: 1654970834.7731001 iteration: 72325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09747 FastRCNN class loss: 0.05171 FastRCNN total loss: 0.14918 L1 loss: 0.0000e+00 L2 loss: 0.59013 Learning rate: 0.0004 Mask loss: 0.10572 RPN box loss: 0.01452 RPN score loss: 0.00307 RPN total loss: 0.01758 Total loss: 0.86262 timestamp: 1654970837.9620037 iteration: 72330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08052 FastRCNN class loss: 0.05326 FastRCNN total loss: 0.13378 L1 loss: 0.0000e+00 L2 loss: 0.59013 Learning rate: 0.0004 Mask loss: 0.13667 RPN box loss: 0.01906 RPN score loss: 0.00251 RPN total loss: 0.02157 Total loss: 0.88216 timestamp: 1654970841.19372 iteration: 72335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09405 FastRCNN class loss: 0.04599 FastRCNN total loss: 0.14004 L1 loss: 0.0000e+00 L2 loss: 0.59013 Learning rate: 0.0004 Mask loss: 0.10009 RPN box loss: 0.01187 RPN score loss: 0.00708 RPN total loss: 0.01895 Total loss: 0.84922 timestamp: 1654970844.4129958 iteration: 72340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07881 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.15712 L1 loss: 0.0000e+00 L2 loss: 0.59013 Learning rate: 0.0004 Mask loss: 0.09368 RPN box loss: 0.00565 RPN score loss: 0.00359 RPN total loss: 0.00925 Total loss: 0.85017 timestamp: 1654970847.6709874 iteration: 72345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05552 FastRCNN class loss: 0.04034 FastRCNN total loss: 0.09586 L1 loss: 0.0000e+00 L2 loss: 0.59013 Learning rate: 0.0004 Mask loss: 0.14558 RPN box loss: 0.00324 RPN score loss: 0.00617 RPN total loss: 0.00941 Total loss: 0.84098 timestamp: 1654970850.7744844 iteration: 72350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08508 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.15263 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.0004 Mask loss: 0.09347 RPN box loss: 0.00809 RPN score loss: 0.00694 RPN total loss: 0.01503 Total loss: 0.85125 timestamp: 1654970854.0343637 iteration: 72355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.151 FastRCNN class loss: 0.0808 FastRCNN total loss: 0.2318 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.0004 Mask loss: 0.12085 RPN box loss: 0.02184 RPN score loss: 0.00926 RPN total loss: 0.03109 Total loss: 0.97387 timestamp: 1654970857.2002015 iteration: 72360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09987 FastRCNN class loss: 0.03965 FastRCNN total loss: 0.13952 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.0004 Mask loss: 0.18324 RPN box loss: 0.00711 RPN score loss: 0.00101 RPN total loss: 0.00812 Total loss: 0.92101 timestamp: 1654970860.3537533 iteration: 72365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0476 FastRCNN class loss: 0.05213 FastRCNN total loss: 0.09972 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.0004 Mask loss: 0.09324 RPN box loss: 0.02475 RPN score loss: 0.00298 RPN total loss: 0.02773 Total loss: 0.81082 timestamp: 1654970863.5731483 iteration: 72370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04882 FastRCNN class loss: 0.04673 FastRCNN total loss: 0.09555 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.0004 Mask loss: 0.10628 RPN box loss: 0.00718 RPN score loss: 0.00417 RPN total loss: 0.01135 Total loss: 0.8033 timestamp: 1654970866.8459117 iteration: 72375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0738 FastRCNN class loss: 0.08505 FastRCNN total loss: 0.15885 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.0004 Mask loss: 0.15398 RPN box loss: 0.01423 RPN score loss: 0.00503 RPN total loss: 0.01927 Total loss: 0.92221 timestamp: 1654970870.0764296 iteration: 72380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09019 FastRCNN class loss: 0.06799 FastRCNN total loss: 0.15819 L1 loss: 0.0000e+00 L2 loss: 0.59011 Learning rate: 0.0004 Mask loss: 0.08421 RPN box loss: 0.00691 RPN score loss: 0.00064 RPN total loss: 0.00755 Total loss: 0.84006 timestamp: 1654970873.2975888 iteration: 72385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08414 FastRCNN class loss: 0.06684 FastRCNN total loss: 0.15098 L1 loss: 0.0000e+00 L2 loss: 0.59011 Learning rate: 0.0004 Mask loss: 0.11777 RPN box loss: 0.06471 RPN score loss: 0.01207 RPN total loss: 0.07679 Total loss: 0.93565 timestamp: 1654970876.4822671 iteration: 72390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07128 FastRCNN class loss: 0.04731 FastRCNN total loss: 0.11859 L1 loss: 0.0000e+00 L2 loss: 0.59011 Learning rate: 0.0004 Mask loss: 0.12607 RPN box loss: 0.00705 RPN score loss: 0.00492 RPN total loss: 0.01196 Total loss: 0.84673 timestamp: 1654970879.647553 iteration: 72395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09683 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.15128 L1 loss: 0.0000e+00 L2 loss: 0.59011 Learning rate: 0.0004 Mask loss: 0.10316 RPN box loss: 0.00891 RPN score loss: 0.00432 RPN total loss: 0.01323 Total loss: 0.85777 timestamp: 1654970882.938518 iteration: 72400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10053 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.16122 L1 loss: 0.0000e+00 L2 loss: 0.59011 Learning rate: 0.0004 Mask loss: 0.09201 RPN box loss: 0.04294 RPN score loss: 0.0058 RPN total loss: 0.04875 Total loss: 0.89209 timestamp: 1654970886.205604 iteration: 72405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.089 FastRCNN class loss: 0.07478 FastRCNN total loss: 0.16379 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.0004 Mask loss: 0.14556 RPN box loss: 0.00958 RPN score loss: 0.00377 RPN total loss: 0.01335 Total loss: 0.91281 timestamp: 1654970889.4787169 iteration: 72410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08173 FastRCNN class loss: 0.09183 FastRCNN total loss: 0.17356 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.0004 Mask loss: 0.15986 RPN box loss: 0.01139 RPN score loss: 0.00816 RPN total loss: 0.01956 Total loss: 0.94308 timestamp: 1654970892.6723034 iteration: 72415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08957 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.15519 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.0004 Mask loss: 0.10496 RPN box loss: 0.0205 RPN score loss: 0.005 RPN total loss: 0.0255 Total loss: 0.87575 timestamp: 1654970895.849381 iteration: 72420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08616 FastRCNN class loss: 0.04654 FastRCNN total loss: 0.13269 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.0004 Mask loss: 0.131 RPN box loss: 0.01252 RPN score loss: 0.01289 RPN total loss: 0.02541 Total loss: 0.8792 timestamp: 1654970899.067855 iteration: 72425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11992 FastRCNN class loss: 0.08523 FastRCNN total loss: 0.20515 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.0004 Mask loss: 0.17004 RPN box loss: 0.04529 RPN score loss: 0.01405 RPN total loss: 0.05934 Total loss: 1.02464 timestamp: 1654970902.2609596 iteration: 72430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.18246 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.0004 Mask loss: 0.1165 RPN box loss: 0.01142 RPN score loss: 0.00361 RPN total loss: 0.01504 Total loss: 0.90409 timestamp: 1654970905.4835012 iteration: 72435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10921 FastRCNN class loss: 0.05052 FastRCNN total loss: 0.15972 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.09435 RPN box loss: 0.00724 RPN score loss: 0.00408 RPN total loss: 0.01132 Total loss: 0.85549 timestamp: 1654970908.6849854 iteration: 72440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12798 FastRCNN class loss: 0.06454 FastRCNN total loss: 0.19252 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.17886 RPN box loss: 0.01081 RPN score loss: 0.00376 RPN total loss: 0.01457 Total loss: 0.97604 timestamp: 1654970911.8943603 iteration: 72445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09818 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.16667 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.15972 RPN box loss: 0.02399 RPN score loss: 0.00428 RPN total loss: 0.02826 Total loss: 0.94475 timestamp: 1654970915.1506307 iteration: 72450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08661 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.1678 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.13143 RPN box loss: 0.01292 RPN score loss: 0.01414 RPN total loss: 0.02705 Total loss: 0.91637 timestamp: 1654970918.3431048 iteration: 72455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08284 FastRCNN class loss: 0.05357 FastRCNN total loss: 0.13641 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.12897 RPN box loss: 0.00463 RPN score loss: 0.00252 RPN total loss: 0.00715 Total loss: 0.86263 timestamp: 1654970921.5360627 iteration: 72460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.063 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.12548 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.17081 RPN box loss: 0.01252 RPN score loss: 0.00173 RPN total loss: 0.01424 Total loss: 0.90062 timestamp: 1654970924.7391543 iteration: 72465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08814 FastRCNN class loss: 0.04975 FastRCNN total loss: 0.1379 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.0004 Mask loss: 0.10217 RPN box loss: 0.00503 RPN score loss: 0.00094 RPN total loss: 0.00597 Total loss: 0.83612 timestamp: 1654970927.9397275 iteration: 72470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13941 FastRCNN class loss: 0.08037 FastRCNN total loss: 0.21978 L1 loss: 0.0000e+00 L2 loss: 0.59008 Learning rate: 0.0004 Mask loss: 0.1395 RPN box loss: 0.01099 RPN score loss: 0.00453 RPN total loss: 0.01552 Total loss: 0.96489 timestamp: 1654970931.1427333 iteration: 72475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12701 FastRCNN class loss: 0.09145 FastRCNN total loss: 0.21846 L1 loss: 0.0000e+00 L2 loss: 0.59008 Learning rate: 0.0004 Mask loss: 0.16482 RPN box loss: 0.00512 RPN score loss: 0.00579 RPN total loss: 0.01092 Total loss: 0.98428 timestamp: 1654970934.2921576 iteration: 72480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07405 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.13975 L1 loss: 0.0000e+00 L2 loss: 0.59008 Learning rate: 0.0004 Mask loss: 0.13761 RPN box loss: 0.00575 RPN score loss: 0.00822 RPN total loss: 0.01397 Total loss: 0.8814 timestamp: 1654970937.5129495 iteration: 72485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08498 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.14363 L1 loss: 0.0000e+00 L2 loss: 0.59008 Learning rate: 0.0004 Mask loss: 0.09333 RPN box loss: 0.01074 RPN score loss: 0.00276 RPN total loss: 0.0135 Total loss: 0.84053 timestamp: 1654970940.7137237 iteration: 72490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07303 FastRCNN class loss: 0.05637 FastRCNN total loss: 0.1294 L1 loss: 0.0000e+00 L2 loss: 0.59008 Learning rate: 0.0004 Mask loss: 0.07919 RPN box loss: 0.00816 RPN score loss: 0.00137 RPN total loss: 0.00953 Total loss: 0.80819 timestamp: 1654970943.8789976 iteration: 72495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09488 FastRCNN class loss: 0.05888 FastRCNN total loss: 0.15375 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.08205 RPN box loss: 0.01315 RPN score loss: 0.00261 RPN total loss: 0.01576 Total loss: 0.84163 timestamp: 1654970947.0425377 iteration: 72500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06627 FastRCNN class loss: 0.08741 FastRCNN total loss: 0.15368 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.07665 RPN box loss: 0.00885 RPN score loss: 0.00519 RPN total loss: 0.01403 Total loss: 0.83444 timestamp: 1654970950.1984916 iteration: 72505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10682 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.16544 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.13669 RPN box loss: 0.01819 RPN score loss: 0.00242 RPN total loss: 0.02062 Total loss: 0.91281 timestamp: 1654970953.3604321 iteration: 72510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05989 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.1253 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.11854 RPN box loss: 0.01005 RPN score loss: 0.00421 RPN total loss: 0.01426 Total loss: 0.84818 timestamp: 1654970956.573206 iteration: 72515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10931 FastRCNN class loss: 0.08692 FastRCNN total loss: 0.19622 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.17667 RPN box loss: 0.0193 RPN score loss: 0.0066 RPN total loss: 0.02589 Total loss: 0.98885 timestamp: 1654970959.7900033 iteration: 72520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10017 FastRCNN class loss: 0.05727 FastRCNN total loss: 0.15744 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.14739 RPN box loss: 0.01482 RPN score loss: 0.00661 RPN total loss: 0.02143 Total loss: 0.91633 timestamp: 1654970963.0517967 iteration: 72525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05362 FastRCNN class loss: 0.05705 FastRCNN total loss: 0.11067 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.13936 RPN box loss: 0.01575 RPN score loss: 0.00322 RPN total loss: 0.01897 Total loss: 0.85907 timestamp: 1654970966.3013418 iteration: 72530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05633 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.11612 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.0004 Mask loss: 0.10474 RPN box loss: 0.00913 RPN score loss: 0.00251 RPN total loss: 0.01164 Total loss: 0.82257 timestamp: 1654970969.569823 iteration: 72535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10637 FastRCNN class loss: 0.05042 FastRCNN total loss: 0.15679 L1 loss: 0.0000e+00 L2 loss: 0.59006 Learning rate: 0.0004 Mask loss: 0.14951 RPN box loss: 0.00865 RPN score loss: 0.00752 RPN total loss: 0.01617 Total loss: 0.91253 timestamp: 1654970972.790567 iteration: 72540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08732 FastRCNN class loss: 0.07097 FastRCNN total loss: 0.15829 L1 loss: 0.0000e+00 L2 loss: 0.59006 Learning rate: 0.0004 Mask loss: 0.16786 RPN box loss: 0.01013 RPN score loss: 0.00441 RPN total loss: 0.01454 Total loss: 0.93075 timestamp: 1654970975.967613 iteration: 72545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06153 FastRCNN class loss: 0.04461 FastRCNN total loss: 0.10614 L1 loss: 0.0000e+00 L2 loss: 0.59006 Learning rate: 0.0004 Mask loss: 0.13586 RPN box loss: 0.0363 RPN score loss: 0.00888 RPN total loss: 0.04518 Total loss: 0.87725 timestamp: 1654970979.155099 iteration: 72550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09755 FastRCNN class loss: 0.05193 FastRCNN total loss: 0.14948 L1 loss: 0.0000e+00 L2 loss: 0.59006 Learning rate: 0.0004 Mask loss: 0.12658 RPN box loss: 0.00832 RPN score loss: 0.00206 RPN total loss: 0.01038 Total loss: 0.87651 timestamp: 1654970982.364538 iteration: 72555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1045 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.17512 L1 loss: 0.0000e+00 L2 loss: 0.59006 Learning rate: 0.0004 Mask loss: 0.19629 RPN box loss: 0.02071 RPN score loss: 0.00717 RPN total loss: 0.02788 Total loss: 0.98934 timestamp: 1654970985.5150704 iteration: 72560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06748 FastRCNN class loss: 0.10456 FastRCNN total loss: 0.17204 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.0004 Mask loss: 0.13095 RPN box loss: 0.01655 RPN score loss: 0.00282 RPN total loss: 0.01937 Total loss: 0.91241 timestamp: 1654970988.7441332 iteration: 72565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11204 FastRCNN class loss: 0.07707 FastRCNN total loss: 0.1891 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.0004 Mask loss: 0.13848 RPN box loss: 0.01157 RPN score loss: 0.0022 RPN total loss: 0.01377 Total loss: 0.9314 timestamp: 1654970991.9230208 iteration: 72570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08904 FastRCNN class loss: 0.04508 FastRCNN total loss: 0.13412 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.0004 Mask loss: 0.08668 RPN box loss: 0.00619 RPN score loss: 0.00258 RPN total loss: 0.00877 Total loss: 0.81961 timestamp: 1654970995.106377 iteration: 72575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05408 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.11417 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.0004 Mask loss: 0.10521 RPN box loss: 0.00517 RPN score loss: 0.00465 RPN total loss: 0.00983 Total loss: 0.81925 timestamp: 1654970998.344115 iteration: 72580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10293 FastRCNN class loss: 0.10543 FastRCNN total loss: 0.20835 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.0004 Mask loss: 0.17739 RPN box loss: 0.024 RPN score loss: 0.01413 RPN total loss: 0.03813 Total loss: 1.01392 timestamp: 1654971001.5890071 iteration: 72585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12488 FastRCNN class loss: 0.03744 FastRCNN total loss: 0.16231 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.0004 Mask loss: 0.19335 RPN box loss: 0.01687 RPN score loss: 0.0044 RPN total loss: 0.02127 Total loss: 0.96698 timestamp: 1654971004.7692287 iteration: 72590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11907 FastRCNN class loss: 0.05558 FastRCNN total loss: 0.17465 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.0004 Mask loss: 0.08896 RPN box loss: 0.00835 RPN score loss: 0.00348 RPN total loss: 0.01183 Total loss: 0.86548 timestamp: 1654971008.0113125 iteration: 72595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14312 FastRCNN class loss: 0.09726 FastRCNN total loss: 0.24037 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.0004 Mask loss: 0.13625 RPN box loss: 0.00991 RPN score loss: 0.01023 RPN total loss: 0.02014 Total loss: 0.98681 timestamp: 1654971011.2094305 iteration: 72600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10089 FastRCNN class loss: 0.05736 FastRCNN total loss: 0.15825 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.0004 Mask loss: 0.17745 RPN box loss: 0.00804 RPN score loss: 0.00692 RPN total loss: 0.01496 Total loss: 0.9407 timestamp: 1654971014.4286804 iteration: 72605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08665 FastRCNN class loss: 0.07015 FastRCNN total loss: 0.15679 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.0004 Mask loss: 0.1494 RPN box loss: 0.00312 RPN score loss: 0.00507 RPN total loss: 0.00818 Total loss: 0.90442 timestamp: 1654971017.5738552 iteration: 72610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07594 FastRCNN class loss: 0.06897 FastRCNN total loss: 0.14492 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.0004 Mask loss: 0.08665 RPN box loss: 0.00576 RPN score loss: 0.0016 RPN total loss: 0.00736 Total loss: 0.82896 timestamp: 1654971020.7731397 iteration: 72615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05037 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.11482 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.0004 Mask loss: 0.15352 RPN box loss: 0.00418 RPN score loss: 0.01461 RPN total loss: 0.01878 Total loss: 0.87716 timestamp: 1654971023.9833384 iteration: 72620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08842 FastRCNN class loss: 0.05941 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.0004 Mask loss: 0.17692 RPN box loss: 0.00896 RPN score loss: 0.00131 RPN total loss: 0.01027 Total loss: 0.92506 timestamp: 1654971027.1214423 iteration: 72625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08969 FastRCNN class loss: 0.05294 FastRCNN total loss: 0.14264 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.0004 Mask loss: 0.13053 RPN box loss: 0.00559 RPN score loss: 0.00436 RPN total loss: 0.00995 Total loss: 0.87314 timestamp: 1654971030.2792406 iteration: 72630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05963 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.1354 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.0004 Mask loss: 0.11174 RPN box loss: 0.01943 RPN score loss: 0.00317 RPN total loss: 0.02261 Total loss: 0.85978 timestamp: 1654971033.5084233 iteration: 72635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.05085 FastRCNN total loss: 0.10427 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.0004 Mask loss: 0.08284 RPN box loss: 0.0097 RPN score loss: 0.00332 RPN total loss: 0.01302 Total loss: 0.79015 timestamp: 1654971036.7198238 iteration: 72640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11555 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.19557 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.0004 Mask loss: 0.13024 RPN box loss: 0.01895 RPN score loss: 0.00579 RPN total loss: 0.02474 Total loss: 0.94057 timestamp: 1654971039.8865292 iteration: 72645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05592 FastRCNN class loss: 0.04621 FastRCNN total loss: 0.10212 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.08471 RPN box loss: 0.00209 RPN score loss: 0.00655 RPN total loss: 0.00863 Total loss: 0.78549 timestamp: 1654971042.9617481 iteration: 72650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09994 FastRCNN class loss: 0.04952 FastRCNN total loss: 0.14947 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.10026 RPN box loss: 0.0059 RPN score loss: 0.00267 RPN total loss: 0.00857 Total loss: 0.84832 timestamp: 1654971046.164208 iteration: 72655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05494 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.11674 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.13314 RPN box loss: 0.00862 RPN score loss: 0.00461 RPN total loss: 0.01323 Total loss: 0.85312 timestamp: 1654971049.3723512 iteration: 72660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12108 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.19607 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.13092 RPN box loss: 0.01156 RPN score loss: 0.00262 RPN total loss: 0.01418 Total loss: 0.93119 timestamp: 1654971052.6264322 iteration: 72665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09859 FastRCNN class loss: 0.08406 FastRCNN total loss: 0.18264 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.12871 RPN box loss: 0.03146 RPN score loss: 0.00584 RPN total loss: 0.0373 Total loss: 0.93867 timestamp: 1654971055.762413 iteration: 72670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08008 FastRCNN class loss: 0.05662 FastRCNN total loss: 0.1367 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.15482 RPN box loss: 0.00845 RPN score loss: 0.00883 RPN total loss: 0.01728 Total loss: 0.89882 timestamp: 1654971059.0047045 iteration: 72675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10706 FastRCNN class loss: 0.05978 FastRCNN total loss: 0.16684 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.12865 RPN box loss: 0.00413 RPN score loss: 0.00287 RPN total loss: 0.007 Total loss: 0.8925 timestamp: 1654971062.2447433 iteration: 72680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09096 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.15009 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.0004 Mask loss: 0.13509 RPN box loss: 0.00556 RPN score loss: 0.00519 RPN total loss: 0.01075 Total loss: 0.88594 timestamp: 1654971065.4736354 iteration: 72685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06075 FastRCNN class loss: 0.07851 FastRCNN total loss: 0.13926 L1 loss: 0.0000e+00 L2 loss: 0.59001 Learning rate: 0.0004 Mask loss: 0.12931 RPN box loss: 0.06043 RPN score loss: 0.00473 RPN total loss: 0.06516 Total loss: 0.92375 timestamp: 1654971068.68369 iteration: 72690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11052 FastRCNN class loss: 0.11293 FastRCNN total loss: 0.22346 L1 loss: 0.0000e+00 L2 loss: 0.59001 Learning rate: 0.0004 Mask loss: 0.13504 RPN box loss: 0.04214 RPN score loss: 0.00912 RPN total loss: 0.05126 Total loss: 0.99977 timestamp: 1654971071.863842 iteration: 72695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0398 FastRCNN class loss: 0.03708 FastRCNN total loss: 0.07688 L1 loss: 0.0000e+00 L2 loss: 0.59001 Learning rate: 0.0004 Mask loss: 0.15486 RPN box loss: 0.00959 RPN score loss: 0.00653 RPN total loss: 0.01612 Total loss: 0.83787 timestamp: 1654971075.0479283 iteration: 72700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09126 FastRCNN class loss: 0.06039 FastRCNN total loss: 0.15165 L1 loss: 0.0000e+00 L2 loss: 0.59001 Learning rate: 0.0004 Mask loss: 0.13616 RPN box loss: 0.01184 RPN score loss: 0.00465 RPN total loss: 0.01649 Total loss: 0.89431 timestamp: 1654971078.2536623 iteration: 72705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09304 FastRCNN class loss: 0.06682 FastRCNN total loss: 0.15987 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.0004 Mask loss: 0.12479 RPN box loss: 0.01219 RPN score loss: 0.0044 RPN total loss: 0.01659 Total loss: 0.89125 timestamp: 1654971081.479526 iteration: 72710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0556 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.10347 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.0004 Mask loss: 0.10779 RPN box loss: 0.01242 RPN score loss: 0.00627 RPN total loss: 0.01869 Total loss: 0.81995 timestamp: 1654971084.6410153 iteration: 72715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13609 FastRCNN class loss: 0.09892 FastRCNN total loss: 0.23501 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.0004 Mask loss: 0.10538 RPN box loss: 0.00767 RPN score loss: 0.00374 RPN total loss: 0.0114 Total loss: 0.9418 timestamp: 1654971087.8408446 iteration: 72720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06432 FastRCNN class loss: 0.08488 FastRCNN total loss: 0.14921 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.0004 Mask loss: 0.12655 RPN box loss: 0.01523 RPN score loss: 0.00727 RPN total loss: 0.0225 Total loss: 0.88826 timestamp: 1654971091.0035043 iteration: 72725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06596 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.13789 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.0004 Mask loss: 0.1347 RPN box loss: 0.01222 RPN score loss: 0.00839 RPN total loss: 0.02061 Total loss: 0.8832 timestamp: 1654971094.158234 iteration: 72730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0989 FastRCNN class loss: 0.059 FastRCNN total loss: 0.1579 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.0004 Mask loss: 0.09483 RPN box loss: 0.01149 RPN score loss: 0.00552 RPN total loss: 0.01701 Total loss: 0.85973 timestamp: 1654971097.3347614 iteration: 72735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07343 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.13586 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.12471 RPN box loss: 0.00842 RPN score loss: 0.00704 RPN total loss: 0.01545 Total loss: 0.86602 timestamp: 1654971100.62329 iteration: 72740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09542 FastRCNN class loss: 0.05134 FastRCNN total loss: 0.14676 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.13729 RPN box loss: 0.0463 RPN score loss: 0.00558 RPN total loss: 0.05188 Total loss: 0.92593 timestamp: 1654971103.8453262 iteration: 72745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07764 FastRCNN class loss: 0.06607 FastRCNN total loss: 0.14371 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.13195 RPN box loss: 0.06762 RPN score loss: 0.00251 RPN total loss: 0.07013 Total loss: 0.93578 timestamp: 1654971106.9615834 iteration: 72750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10805 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.17244 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.12478 RPN box loss: 0.01502 RPN score loss: 0.00622 RPN total loss: 0.02124 Total loss: 0.90845 timestamp: 1654971110.2066185 iteration: 72755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.06994 FastRCNN total loss: 0.18354 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.18443 RPN box loss: 0.01655 RPN score loss: 0.01687 RPN total loss: 0.03342 Total loss: 0.99139 timestamp: 1654971113.5749469 iteration: 72760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09292 FastRCNN class loss: 0.07181 FastRCNN total loss: 0.16473 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.14951 RPN box loss: 0.00925 RPN score loss: 0.00662 RPN total loss: 0.01587 Total loss: 0.9201 timestamp: 1654971116.7252676 iteration: 72765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12159 FastRCNN class loss: 0.07898 FastRCNN total loss: 0.20056 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.0004 Mask loss: 0.14494 RPN box loss: 0.01415 RPN score loss: 0.00634 RPN total loss: 0.0205 Total loss: 0.95598 timestamp: 1654971119.9215398 iteration: 72770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04624 FastRCNN class loss: 0.05676 FastRCNN total loss: 0.103 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.09866 RPN box loss: 0.0123 RPN score loss: 0.00143 RPN total loss: 0.01373 Total loss: 0.80537 timestamp: 1654971123.190569 iteration: 72775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0811 FastRCNN class loss: 0.07609 FastRCNN total loss: 0.15719 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.13829 RPN box loss: 0.00775 RPN score loss: 0.005 RPN total loss: 0.01275 Total loss: 0.89822 timestamp: 1654971126.4232879 iteration: 72780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08682 FastRCNN class loss: 0.05008 FastRCNN total loss: 0.13691 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.09478 RPN box loss: 0.01623 RPN score loss: 0.00116 RPN total loss: 0.0174 Total loss: 0.83907 timestamp: 1654971129.5959089 iteration: 72785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07778 FastRCNN class loss: 0.06136 FastRCNN total loss: 0.13914 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.10292 RPN box loss: 0.01865 RPN score loss: 0.00128 RPN total loss: 0.01993 Total loss: 0.85197 timestamp: 1654971132.797294 iteration: 72790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05792 FastRCNN class loss: 0.04218 FastRCNN total loss: 0.1001 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.11334 RPN box loss: 0.00798 RPN score loss: 0.00238 RPN total loss: 0.01036 Total loss: 0.81378 timestamp: 1654971135.9790323 iteration: 72795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08437 FastRCNN class loss: 0.04141 FastRCNN total loss: 0.12578 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.11821 RPN box loss: 0.00615 RPN score loss: 0.00299 RPN total loss: 0.00914 Total loss: 0.8431 timestamp: 1654971139.2067692 iteration: 72800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08908 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.18043 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.0004 Mask loss: 0.16723 RPN box loss: 0.01481 RPN score loss: 0.00173 RPN total loss: 0.01654 Total loss: 0.95418 timestamp: 1654971142.4138272 iteration: 72805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06881 FastRCNN class loss: 0.0671 FastRCNN total loss: 0.13591 L1 loss: 0.0000e+00 L2 loss: 0.58997 Learning rate: 0.0004 Mask loss: 0.09303 RPN box loss: 0.00521 RPN score loss: 0.00064 RPN total loss: 0.00585 Total loss: 0.82477 timestamp: 1654971145.5925367 iteration: 72810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08565 FastRCNN class loss: 0.07162 FastRCNN total loss: 0.15727 L1 loss: 0.0000e+00 L2 loss: 0.58997 Learning rate: 0.0004 Mask loss: 0.13192 RPN box loss: 0.02229 RPN score loss: 0.00271 RPN total loss: 0.025 Total loss: 0.90417 timestamp: 1654971148.7579513 iteration: 72815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09336 FastRCNN class loss: 0.05503 FastRCNN total loss: 0.14839 L1 loss: 0.0000e+00 L2 loss: 0.58997 Learning rate: 0.0004 Mask loss: 0.11065 RPN box loss: 0.00992 RPN score loss: 0.00191 RPN total loss: 0.01184 Total loss: 0.86084 timestamp: 1654971151.9100552 iteration: 72820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13253 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.19446 L1 loss: 0.0000e+00 L2 loss: 0.58997 Learning rate: 0.0004 Mask loss: 0.08966 RPN box loss: 0.00817 RPN score loss: 0.00253 RPN total loss: 0.0107 Total loss: 0.88478 timestamp: 1654971155.1226878 iteration: 72825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09826 FastRCNN class loss: 0.05738 FastRCNN total loss: 0.15564 L1 loss: 0.0000e+00 L2 loss: 0.58997 Learning rate: 0.0004 Mask loss: 0.14147 RPN box loss: 0.00766 RPN score loss: 0.00377 RPN total loss: 0.01143 Total loss: 0.89851 timestamp: 1654971158.3070729 iteration: 72830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05213 FastRCNN class loss: 0.0479 FastRCNN total loss: 0.10003 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.0004 Mask loss: 0.17294 RPN box loss: 0.02089 RPN score loss: 0.00236 RPN total loss: 0.02325 Total loss: 0.88618 timestamp: 1654971161.4651163 iteration: 72835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.16069 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.0004 Mask loss: 0.09312 RPN box loss: 0.01509 RPN score loss: 0.00175 RPN total loss: 0.01683 Total loss: 0.8606 timestamp: 1654971164.6374946 iteration: 72840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13136 FastRCNN class loss: 0.11484 FastRCNN total loss: 0.2462 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.0004 Mask loss: 0.16515 RPN box loss: 0.01626 RPN score loss: 0.00839 RPN total loss: 0.02466 Total loss: 1.02597 timestamp: 1654971167.816683 iteration: 72845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.1408 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.0004 Mask loss: 0.10279 RPN box loss: 0.01592 RPN score loss: 0.00366 RPN total loss: 0.01958 Total loss: 0.85313 timestamp: 1654971170.9627466 iteration: 72850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09835 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.16426 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.0004 Mask loss: 0.12691 RPN box loss: 0.01169 RPN score loss: 0.00858 RPN total loss: 0.02027 Total loss: 0.90139 timestamp: 1654971174.1561441 iteration: 72855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06468 FastRCNN class loss: 0.08652 FastRCNN total loss: 0.1512 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.0004 Mask loss: 0.1476 RPN box loss: 0.01193 RPN score loss: 0.00559 RPN total loss: 0.01751 Total loss: 0.90627 timestamp: 1654971177.321258 iteration: 72860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08563 FastRCNN class loss: 0.0622 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.58995 Learning rate: 0.0004 Mask loss: 0.08664 RPN box loss: 0.01453 RPN score loss: 0.00327 RPN total loss: 0.0178 Total loss: 0.84223 timestamp: 1654971180.545791 iteration: 72865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07434 FastRCNN class loss: 0.05866 FastRCNN total loss: 0.13301 L1 loss: 0.0000e+00 L2 loss: 0.58995 Learning rate: 0.0004 Mask loss: 0.10773 RPN box loss: 0.00725 RPN score loss: 0.00128 RPN total loss: 0.00853 Total loss: 0.83922 timestamp: 1654971183.7705247 iteration: 72870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07018 FastRCNN class loss: 0.04666 FastRCNN total loss: 0.11685 L1 loss: 0.0000e+00 L2 loss: 0.58995 Learning rate: 0.0004 Mask loss: 0.15244 RPN box loss: 0.00884 RPN score loss: 0.00939 RPN total loss: 0.01823 Total loss: 0.87746 timestamp: 1654971186.956167 iteration: 72875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08701 FastRCNN class loss: 0.07865 FastRCNN total loss: 0.16566 L1 loss: 0.0000e+00 L2 loss: 0.58995 Learning rate: 0.0004 Mask loss: 0.10956 RPN box loss: 0.01903 RPN score loss: 0.00267 RPN total loss: 0.0217 Total loss: 0.88687 timestamp: 1654971190.2126358 iteration: 72880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07189 FastRCNN class loss: 0.04053 FastRCNN total loss: 0.11242 L1 loss: 0.0000e+00 L2 loss: 0.58995 Learning rate: 0.0004 Mask loss: 0.09875 RPN box loss: 0.00417 RPN score loss: 0.00099 RPN total loss: 0.00515 Total loss: 0.80627 timestamp: 1654971193.3835876 iteration: 72885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09164 FastRCNN class loss: 0.05066 FastRCNN total loss: 0.1423 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.16968 RPN box loss: 0.01449 RPN score loss: 0.00192 RPN total loss: 0.0164 Total loss: 0.91832 timestamp: 1654971196.6367455 iteration: 72890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11139 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.18578 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.13866 RPN box loss: 0.01286 RPN score loss: 0.00341 RPN total loss: 0.01627 Total loss: 0.93066 timestamp: 1654971199.83238 iteration: 72895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06501 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.13395 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.11859 RPN box loss: 0.03913 RPN score loss: 0.00937 RPN total loss: 0.0485 Total loss: 0.89098 timestamp: 1654971202.9886134 iteration: 72900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.06269 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.15245 RPN box loss: 0.0167 RPN score loss: 0.00629 RPN total loss: 0.02299 Total loss: 0.90947 timestamp: 1654971206.1379292 iteration: 72905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10359 FastRCNN class loss: 0.06659 FastRCNN total loss: 0.17018 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.13084 RPN box loss: 0.07731 RPN score loss: 0.00497 RPN total loss: 0.08228 Total loss: 0.97324 timestamp: 1654971209.3866847 iteration: 72910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09263 FastRCNN class loss: 0.07753 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.15773 RPN box loss: 0.01756 RPN score loss: 0.0074 RPN total loss: 0.02496 Total loss: 0.94278 timestamp: 1654971212.5533834 iteration: 72915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04016 FastRCNN class loss: 0.02825 FastRCNN total loss: 0.06841 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.0004 Mask loss: 0.09014 RPN box loss: 0.0086 RPN score loss: 0.00077 RPN total loss: 0.00937 Total loss: 0.75786 timestamp: 1654971215.7608862 iteration: 72920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12383 FastRCNN class loss: 0.0768 FastRCNN total loss: 0.20063 L1 loss: 0.0000e+00 L2 loss: 0.58993 Learning rate: 0.0004 Mask loss: 0.17146 RPN box loss: 0.01803 RPN score loss: 0.00326 RPN total loss: 0.0213 Total loss: 0.98332 timestamp: 1654971218.9883115 iteration: 72925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13936 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.21757 L1 loss: 0.0000e+00 L2 loss: 0.58993 Learning rate: 0.0004 Mask loss: 0.16813 RPN box loss: 0.01504 RPN score loss: 0.00332 RPN total loss: 0.01836 Total loss: 0.99399 timestamp: 1654971222.208951 iteration: 72930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06321 FastRCNN class loss: 0.04578 FastRCNN total loss: 0.10899 L1 loss: 0.0000e+00 L2 loss: 0.58993 Learning rate: 0.0004 Mask loss: 0.1381 RPN box loss: 0.0376 RPN score loss: 0.00563 RPN total loss: 0.04323 Total loss: 0.88024 timestamp: 1654971225.400516 iteration: 72935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.14523 L1 loss: 0.0000e+00 L2 loss: 0.58993 Learning rate: 0.0004 Mask loss: 0.13804 RPN box loss: 0.0068 RPN score loss: 0.00667 RPN total loss: 0.01347 Total loss: 0.88666 timestamp: 1654971228.6116507 iteration: 72940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04748 FastRCNN class loss: 0.03276 FastRCNN total loss: 0.08024 L1 loss: 0.0000e+00 L2 loss: 0.58993 Learning rate: 0.0004 Mask loss: 0.20253 RPN box loss: 0.01307 RPN score loss: 0.00272 RPN total loss: 0.01579 Total loss: 0.88849 timestamp: 1654971231.8130124 iteration: 72945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06318 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.1276 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.0004 Mask loss: 0.13156 RPN box loss: 0.01746 RPN score loss: 0.01535 RPN total loss: 0.03281 Total loss: 0.88189 timestamp: 1654971235.0425987 iteration: 72950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06464 FastRCNN class loss: 0.0503 FastRCNN total loss: 0.11494 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.0004 Mask loss: 0.09778 RPN box loss: 0.01114 RPN score loss: 0.00317 RPN total loss: 0.01431 Total loss: 0.81695 timestamp: 1654971238.1524115 iteration: 72955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.088 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.15391 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.0004 Mask loss: 0.11995 RPN box loss: 0.00844 RPN score loss: 0.00546 RPN total loss: 0.0139 Total loss: 0.87769 timestamp: 1654971241.3496134 iteration: 72960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04919 FastRCNN class loss: 0.04677 FastRCNN total loss: 0.09595 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.0004 Mask loss: 0.10028 RPN box loss: 0.00559 RPN score loss: 0.0037 RPN total loss: 0.00929 Total loss: 0.79544 timestamp: 1654971244.5747044 iteration: 72965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.07921 FastRCNN total loss: 0.17122 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.0004 Mask loss: 0.1048 RPN box loss: 0.02093 RPN score loss: 0.00415 RPN total loss: 0.02508 Total loss: 0.89102 timestamp: 1654971247.7478895 iteration: 72970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11045 FastRCNN class loss: 0.06498 FastRCNN total loss: 0.17544 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.0004 Mask loss: 0.12781 RPN box loss: 0.01409 RPN score loss: 0.00416 RPN total loss: 0.01826 Total loss: 0.91142 timestamp: 1654971250.890843 iteration: 72975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07722 FastRCNN class loss: 0.04369 FastRCNN total loss: 0.12092 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.0004 Mask loss: 0.10595 RPN box loss: 0.00449 RPN score loss: 0.00431 RPN total loss: 0.0088 Total loss: 0.82558 timestamp: 1654971254.0821612 iteration: 72980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15147 FastRCNN class loss: 0.07531 FastRCNN total loss: 0.22678 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.0004 Mask loss: 0.11931 RPN box loss: 0.00884 RPN score loss: 0.00271 RPN total loss: 0.01154 Total loss: 0.94755 timestamp: 1654971257.3394227 iteration: 72985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07436 FastRCNN class loss: 0.06719 FastRCNN total loss: 0.14155 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.0004 Mask loss: 0.16127 RPN box loss: 0.00904 RPN score loss: 0.00421 RPN total loss: 0.01325 Total loss: 0.90598 timestamp: 1654971260.549039 iteration: 72990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07309 FastRCNN class loss: 0.05468 FastRCNN total loss: 0.12777 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.0004 Mask loss: 0.12264 RPN box loss: 0.00784 RPN score loss: 0.00166 RPN total loss: 0.0095 Total loss: 0.84982 timestamp: 1654971263.7314446 iteration: 72995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0686 FastRCNN class loss: 0.04925 FastRCNN total loss: 0.11786 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.0004 Mask loss: 0.1093 RPN box loss: 0.06219 RPN score loss: 0.00383 RPN total loss: 0.06602 Total loss: 0.88308 timestamp: 1654971266.9356554 iteration: 73000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09319 FastRCNN class loss: 0.08683 FastRCNN total loss: 0.18002 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.0004 Mask loss: 0.14475 RPN box loss: 0.00869 RPN score loss: 0.00778 RPN total loss: 0.01647 Total loss: 0.93114 timestamp: 1654971270.1142187 iteration: 73005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0636 FastRCNN class loss: 0.04263 FastRCNN total loss: 0.10623 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.0004 Mask loss: 0.14956 RPN box loss: 0.00858 RPN score loss: 0.00516 RPN total loss: 0.01373 Total loss: 0.85943 timestamp: 1654971273.3056421 iteration: 73010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0893 FastRCNN class loss: 0.11635 FastRCNN total loss: 0.20565 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.0004 Mask loss: 0.23966 RPN box loss: 0.02129 RPN score loss: 0.00735 RPN total loss: 0.02864 Total loss: 1.06386 timestamp: 1654971276.5228617 iteration: 73015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09659 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.16858 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.0004 Mask loss: 0.11279 RPN box loss: 0.00736 RPN score loss: 0.00587 RPN total loss: 0.01323 Total loss: 0.8845 timestamp: 1654971279.6969073 iteration: 73020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05608 FastRCNN class loss: 0.03974 FastRCNN total loss: 0.09582 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.0004 Mask loss: 0.09024 RPN box loss: 0.00383 RPN score loss: 0.00093 RPN total loss: 0.00476 Total loss: 0.78072 timestamp: 1654971282.8438153 iteration: 73025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11065 FastRCNN class loss: 0.066 FastRCNN total loss: 0.17665 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.0004 Mask loss: 0.12881 RPN box loss: 0.01616 RPN score loss: 0.00162 RPN total loss: 0.01778 Total loss: 0.91314 timestamp: 1654971286.059301 iteration: 73030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04687 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.10449 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.0004 Mask loss: 0.12495 RPN box loss: 0.01146 RPN score loss: 0.01057 RPN total loss: 0.02203 Total loss: 0.84136 timestamp: 1654971289.2027571 iteration: 73035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0765 FastRCNN class loss: 0.05182 FastRCNN total loss: 0.12832 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.0004 Mask loss: 0.10955 RPN box loss: 0.01507 RPN score loss: 0.00495 RPN total loss: 0.02001 Total loss: 0.84777 timestamp: 1654971292.3915784 iteration: 73040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10379 FastRCNN class loss: 0.06411 FastRCNN total loss: 0.16789 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.0004 Mask loss: 0.11214 RPN box loss: 0.01284 RPN score loss: 0.00373 RPN total loss: 0.01657 Total loss: 0.8865 timestamp: 1654971295.591897 iteration: 73045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11885 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.18601 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.0004 Mask loss: 0.12504 RPN box loss: 0.00668 RPN score loss: 0.01333 RPN total loss: 0.02001 Total loss: 0.92095 timestamp: 1654971298.8039763 iteration: 73050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07375 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.14192 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.0004 Mask loss: 0.14078 RPN box loss: 0.01263 RPN score loss: 0.0078 RPN total loss: 0.02043 Total loss: 0.89302 timestamp: 1654971301.9642997 iteration: 73055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08189 FastRCNN class loss: 0.04932 FastRCNN total loss: 0.13122 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.0004 Mask loss: 0.11069 RPN box loss: 0.00505 RPN score loss: 0.00898 RPN total loss: 0.01404 Total loss: 0.84583 timestamp: 1654971305.1595805 iteration: 73060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13532 FastRCNN class loss: 0.05597 FastRCNN total loss: 0.19129 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.0004 Mask loss: 0.11518 RPN box loss: 0.01408 RPN score loss: 0.00407 RPN total loss: 0.01816 Total loss: 0.91452 timestamp: 1654971308.388169 iteration: 73065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07354 FastRCNN class loss: 0.04589 FastRCNN total loss: 0.11943 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.1025 RPN box loss: 0.00453 RPN score loss: 0.00133 RPN total loss: 0.00586 Total loss: 0.81768 timestamp: 1654971311.6223645 iteration: 73070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0999 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.17471 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.13126 RPN box loss: 0.01185 RPN score loss: 0.00645 RPN total loss: 0.0183 Total loss: 0.91415 timestamp: 1654971314.839376 iteration: 73075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10595 FastRCNN class loss: 0.07287 FastRCNN total loss: 0.17881 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.11836 RPN box loss: 0.02614 RPN score loss: 0.00231 RPN total loss: 0.02845 Total loss: 0.9155 timestamp: 1654971318.0468707 iteration: 73080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08324 FastRCNN class loss: 0.04901 FastRCNN total loss: 0.13226 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.14477 RPN box loss: 0.00409 RPN score loss: 0.00105 RPN total loss: 0.00514 Total loss: 0.87205 timestamp: 1654971321.2202232 iteration: 73085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09844 FastRCNN class loss: 0.0803 FastRCNN total loss: 0.17874 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.1411 RPN box loss: 0.01689 RPN score loss: 0.00442 RPN total loss: 0.02131 Total loss: 0.93103 timestamp: 1654971324.4724972 iteration: 73090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06996 FastRCNN class loss: 0.04356 FastRCNN total loss: 0.11353 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.12301 RPN box loss: 0.01101 RPN score loss: 0.00844 RPN total loss: 0.01945 Total loss: 0.84587 timestamp: 1654971327.6657655 iteration: 73095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11051 FastRCNN class loss: 0.0891 FastRCNN total loss: 0.19961 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.0004 Mask loss: 0.20262 RPN box loss: 0.01037 RPN score loss: 0.00463 RPN total loss: 0.015 Total loss: 1.00711 timestamp: 1654971330.9160838 iteration: 73100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05894 FastRCNN class loss: 0.08847 FastRCNN total loss: 0.14741 L1 loss: 0.0000e+00 L2 loss: 0.58987 Learning rate: 0.0004 Mask loss: 0.16452 RPN box loss: 0.0082 RPN score loss: 0.01091 RPN total loss: 0.0191 Total loss: 0.9209 timestamp: 1654971334.1763563 iteration: 73105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09159 FastRCNN class loss: 0.11942 FastRCNN total loss: 0.21101 L1 loss: 0.0000e+00 L2 loss: 0.58987 Learning rate: 0.0004 Mask loss: 0.17175 RPN box loss: 0.02085 RPN score loss: 0.00595 RPN total loss: 0.0268 Total loss: 0.99943 timestamp: 1654971337.3341713 iteration: 73110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12789 FastRCNN class loss: 0.10141 FastRCNN total loss: 0.2293 L1 loss: 0.0000e+00 L2 loss: 0.58987 Learning rate: 0.0004 Mask loss: 0.1343 RPN box loss: 0.01745 RPN score loss: 0.0029 RPN total loss: 0.02035 Total loss: 0.97382 timestamp: 1654971340.5758934 iteration: 73115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10532 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.16449 L1 loss: 0.0000e+00 L2 loss: 0.58987 Learning rate: 0.0004 Mask loss: 0.11307 RPN box loss: 0.01853 RPN score loss: 0.00919 RPN total loss: 0.02771 Total loss: 0.89513 timestamp: 1654971343.7678628 iteration: 73120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09451 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.15819 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.0004 Mask loss: 0.11078 RPN box loss: 0.00793 RPN score loss: 0.00725 RPN total loss: 0.01518 Total loss: 0.87401 timestamp: 1654971346.9667833 iteration: 73125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0479 FastRCNN class loss: 0.05338 FastRCNN total loss: 0.10129 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.0004 Mask loss: 0.08634 RPN box loss: 0.00715 RPN score loss: 0.00118 RPN total loss: 0.00833 Total loss: 0.78582 timestamp: 1654971350.1679306 iteration: 73130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02731 FastRCNN class loss: 0.03207 FastRCNN total loss: 0.05938 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.0004 Mask loss: 0.0781 RPN box loss: 0.01308 RPN score loss: 0.00171 RPN total loss: 0.01479 Total loss: 0.74213 timestamp: 1654971353.3959942 iteration: 73135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0618 FastRCNN class loss: 0.05636 FastRCNN total loss: 0.11816 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.0004 Mask loss: 0.12201 RPN box loss: 0.00972 RPN score loss: 0.00733 RPN total loss: 0.01705 Total loss: 0.84708 timestamp: 1654971356.584089 iteration: 73140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08419 FastRCNN class loss: 0.09058 FastRCNN total loss: 0.17478 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.0004 Mask loss: 0.16973 RPN box loss: 0.01647 RPN score loss: 0.00945 RPN total loss: 0.02591 Total loss: 0.96027 timestamp: 1654971359.7845142 iteration: 73145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09878 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.18972 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.0004 Mask loss: 0.15003 RPN box loss: 0.01928 RPN score loss: 0.00841 RPN total loss: 0.02769 Total loss: 0.9573 timestamp: 1654971363.0005617 iteration: 73150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.11097 FastRCNN total loss: 0.21596 L1 loss: 0.0000e+00 L2 loss: 0.58985 Learning rate: 0.0004 Mask loss: 0.13616 RPN box loss: 0.01053 RPN score loss: 0.00692 RPN total loss: 0.01745 Total loss: 0.95943 timestamp: 1654971366.236898 iteration: 73155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07621 FastRCNN class loss: 0.05337 FastRCNN total loss: 0.12958 L1 loss: 0.0000e+00 L2 loss: 0.58985 Learning rate: 0.0004 Mask loss: 0.11251 RPN box loss: 0.01072 RPN score loss: 0.00365 RPN total loss: 0.01437 Total loss: 0.84631 timestamp: 1654971369.4602458 iteration: 73160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0671 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.13935 L1 loss: 0.0000e+00 L2 loss: 0.58985 Learning rate: 0.0004 Mask loss: 0.14404 RPN box loss: 0.01835 RPN score loss: 0.01335 RPN total loss: 0.0317 Total loss: 0.90495 timestamp: 1654971372.6473818 iteration: 73165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09187 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.1535 L1 loss: 0.0000e+00 L2 loss: 0.58985 Learning rate: 0.0004 Mask loss: 0.1371 RPN box loss: 0.00734 RPN score loss: 0.00636 RPN total loss: 0.0137 Total loss: 0.89415 timestamp: 1654971375.8819766 iteration: 73170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09068 FastRCNN class loss: 0.08447 FastRCNN total loss: 0.17515 L1 loss: 0.0000e+00 L2 loss: 0.58985 Learning rate: 0.0004 Mask loss: 0.13517 RPN box loss: 0.02339 RPN score loss: 0.01134 RPN total loss: 0.03473 Total loss: 0.9349 timestamp: 1654971379.064877 iteration: 73175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08914 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.18224 L1 loss: 0.0000e+00 L2 loss: 0.58985 Learning rate: 0.0004 Mask loss: 0.13249 RPN box loss: 0.01106 RPN score loss: 0.00622 RPN total loss: 0.01728 Total loss: 0.92186 timestamp: 1654971382.2560558 iteration: 73180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0991 FastRCNN class loss: 0.09788 FastRCNN total loss: 0.19698 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.19236 RPN box loss: 0.01252 RPN score loss: 0.0022 RPN total loss: 0.01472 Total loss: 0.9939 timestamp: 1654971385.425357 iteration: 73185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09164 FastRCNN class loss: 0.10647 FastRCNN total loss: 0.19811 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.1498 RPN box loss: 0.01881 RPN score loss: 0.0053 RPN total loss: 0.02411 Total loss: 0.96186 timestamp: 1654971388.52742 iteration: 73190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09705 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.19311 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.17392 RPN box loss: 0.02029 RPN score loss: 0.01596 RPN total loss: 0.03626 Total loss: 0.99313 timestamp: 1654971391.756753 iteration: 73195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12276 FastRCNN class loss: 0.08538 FastRCNN total loss: 0.20814 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.13663 RPN box loss: 0.00884 RPN score loss: 0.00151 RPN total loss: 0.01035 Total loss: 0.94496 timestamp: 1654971394.967684 iteration: 73200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10776 FastRCNN class loss: 0.07867 FastRCNN total loss: 0.18643 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.1664 RPN box loss: 0.02753 RPN score loss: 0.00516 RPN total loss: 0.03269 Total loss: 0.97536 timestamp: 1654971398.1812472 iteration: 73205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10349 FastRCNN class loss: 0.07281 FastRCNN total loss: 0.1763 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.16524 RPN box loss: 0.01203 RPN score loss: 0.00335 RPN total loss: 0.01537 Total loss: 0.94675 timestamp: 1654971401.3688796 iteration: 73210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04942 FastRCNN class loss: 0.04956 FastRCNN total loss: 0.09898 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.0004 Mask loss: 0.09741 RPN box loss: 0.00182 RPN score loss: 0.00069 RPN total loss: 0.00251 Total loss: 0.78873 timestamp: 1654971404.4888391 iteration: 73215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13486 FastRCNN class loss: 0.09707 FastRCNN total loss: 0.23193 L1 loss: 0.0000e+00 L2 loss: 0.58983 Learning rate: 0.0004 Mask loss: 0.1373 RPN box loss: 0.01377 RPN score loss: 0.00162 RPN total loss: 0.01539 Total loss: 0.97445 timestamp: 1654971407.7066772 iteration: 73220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.21971 L1 loss: 0.0000e+00 L2 loss: 0.58983 Learning rate: 0.0004 Mask loss: 0.20064 RPN box loss: 0.01796 RPN score loss: 0.00529 RPN total loss: 0.02325 Total loss: 1.03344 timestamp: 1654971410.90032 iteration: 73225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08602 FastRCNN class loss: 0.05188 FastRCNN total loss: 0.1379 L1 loss: 0.0000e+00 L2 loss: 0.58983 Learning rate: 0.0004 Mask loss: 0.14816 RPN box loss: 0.01096 RPN score loss: 0.00111 RPN total loss: 0.01207 Total loss: 0.88796 timestamp: 1654971414.041576 iteration: 73230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09955 FastRCNN class loss: 0.08156 FastRCNN total loss: 0.18111 L1 loss: 0.0000e+00 L2 loss: 0.58983 Learning rate: 0.0004 Mask loss: 0.07939 RPN box loss: 0.00698 RPN score loss: 0.00318 RPN total loss: 0.01015 Total loss: 0.86048 timestamp: 1654971417.2392592 iteration: 73235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07151 FastRCNN class loss: 0.05768 FastRCNN total loss: 0.12919 L1 loss: 0.0000e+00 L2 loss: 0.58983 Learning rate: 0.0004 Mask loss: 0.1322 RPN box loss: 0.01402 RPN score loss: 0.00521 RPN total loss: 0.01923 Total loss: 0.87044 timestamp: 1654971420.4205735 iteration: 73240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10175 FastRCNN class loss: 0.07315 FastRCNN total loss: 0.1749 L1 loss: 0.0000e+00 L2 loss: 0.58983 Learning rate: 0.0004 Mask loss: 0.20184 RPN box loss: 0.00756 RPN score loss: 0.00566 RPN total loss: 0.01322 Total loss: 0.97979 timestamp: 1654971423.6042032 iteration: 73245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07642 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.14197 L1 loss: 0.0000e+00 L2 loss: 0.58982 Learning rate: 0.0004 Mask loss: 0.09534 RPN box loss: 0.01308 RPN score loss: 0.00897 RPN total loss: 0.02205 Total loss: 0.84918 timestamp: 1654971426.7776618 iteration: 73250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09157 FastRCNN class loss: 0.08163 FastRCNN total loss: 0.1732 L1 loss: 0.0000e+00 L2 loss: 0.58982 Learning rate: 0.0004 Mask loss: 0.12835 RPN box loss: 0.02084 RPN score loss: 0.00634 RPN total loss: 0.02718 Total loss: 0.91855 timestamp: 1654971429.9477894 iteration: 73255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15139 FastRCNN class loss: 0.08414 FastRCNN total loss: 0.23553 L1 loss: 0.0000e+00 L2 loss: 0.58982 Learning rate: 0.0004 Mask loss: 0.14007 RPN box loss: 0.00723 RPN score loss: 0.00386 RPN total loss: 0.01109 Total loss: 0.97651 timestamp: 1654971433.1722684 iteration: 73260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06973 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.11646 L1 loss: 0.0000e+00 L2 loss: 0.58982 Learning rate: 0.0004 Mask loss: 0.08419 RPN box loss: 0.00545 RPN score loss: 0.0046 RPN total loss: 0.01006 Total loss: 0.80052 timestamp: 1654971436.359682 iteration: 73265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0708 FastRCNN class loss: 0.0575 FastRCNN total loss: 0.1283 L1 loss: 0.0000e+00 L2 loss: 0.58982 Learning rate: 0.0004 Mask loss: 0.10605 RPN box loss: 0.01217 RPN score loss: 0.0047 RPN total loss: 0.01687 Total loss: 0.84103 timestamp: 1654971439.556582 iteration: 73270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10664 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.17893 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.0004 Mask loss: 0.17104 RPN box loss: 0.01162 RPN score loss: 0.00478 RPN total loss: 0.0164 Total loss: 0.95618 timestamp: 1654971442.6863444 iteration: 73275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12317 FastRCNN class loss: 0.08114 FastRCNN total loss: 0.20431 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.0004 Mask loss: 0.16479 RPN box loss: 0.02355 RPN score loss: 0.00876 RPN total loss: 0.03231 Total loss: 0.99122 timestamp: 1654971445.9357347 iteration: 73280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05782 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.10756 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.0004 Mask loss: 0.08814 RPN box loss: 0.01027 RPN score loss: 0.00177 RPN total loss: 0.01203 Total loss: 0.79754 timestamp: 1654971449.101553 iteration: 73285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06183 FastRCNN class loss: 0.07331 FastRCNN total loss: 0.13514 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.0004 Mask loss: 0.13128 RPN box loss: 0.02751 RPN score loss: 0.00403 RPN total loss: 0.03155 Total loss: 0.88778 timestamp: 1654971452.2720666 iteration: 73290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08966 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.14934 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.0004 Mask loss: 0.134 RPN box loss: 0.00989 RPN score loss: 0.00884 RPN total loss: 0.01873 Total loss: 0.89188 timestamp: 1654971455.460699 iteration: 73295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07342 FastRCNN class loss: 0.10339 FastRCNN total loss: 0.17681 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.0004 Mask loss: 0.12014 RPN box loss: 0.00726 RPN score loss: 0.00141 RPN total loss: 0.00867 Total loss: 0.89543 timestamp: 1654971458.6204388 iteration: 73300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11649 FastRCNN class loss: 0.10048 FastRCNN total loss: 0.21697 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.0004 Mask loss: 0.12307 RPN box loss: 0.01145 RPN score loss: 0.00593 RPN total loss: 0.01738 Total loss: 0.94722 timestamp: 1654971461.8503368 iteration: 73305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09405 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.1878 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.0004 Mask loss: 0.12413 RPN box loss: 0.01219 RPN score loss: 0.00463 RPN total loss: 0.01682 Total loss: 0.91855 timestamp: 1654971465.0627897 iteration: 73310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10014 FastRCNN class loss: 0.07169 FastRCNN total loss: 0.17183 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.0004 Mask loss: 0.21095 RPN box loss: 0.02246 RPN score loss: 0.00912 RPN total loss: 0.03158 Total loss: 1.00417 timestamp: 1654971468.253654 iteration: 73315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07374 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.14479 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.0004 Mask loss: 0.15614 RPN box loss: 0.00823 RPN score loss: 0.00202 RPN total loss: 0.01025 Total loss: 0.90098 timestamp: 1654971471.4007263 iteration: 73320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11842 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.18935 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.0004 Mask loss: 0.14795 RPN box loss: 0.00561 RPN score loss: 0.0022 RPN total loss: 0.00781 Total loss: 0.93491 timestamp: 1654971474.6078598 iteration: 73325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07472 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.135 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.13491 RPN box loss: 0.00562 RPN score loss: 0.00324 RPN total loss: 0.00886 Total loss: 0.86856 timestamp: 1654971477.8170536 iteration: 73330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11721 FastRCNN class loss: 0.08494 FastRCNN total loss: 0.20215 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.11703 RPN box loss: 0.00874 RPN score loss: 0.00413 RPN total loss: 0.01287 Total loss: 0.92184 timestamp: 1654971480.9201257 iteration: 73335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10815 FastRCNN class loss: 0.0879 FastRCNN total loss: 0.19606 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.13321 RPN box loss: 0.00903 RPN score loss: 0.00463 RPN total loss: 0.01366 Total loss: 0.93271 timestamp: 1654971484.1710763 iteration: 73340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04632 FastRCNN class loss: 0.05343 FastRCNN total loss: 0.09975 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.10134 RPN box loss: 0.00413 RPN score loss: 0.00335 RPN total loss: 0.00748 Total loss: 0.79835 timestamp: 1654971487.4366496 iteration: 73345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11257 FastRCNN class loss: 0.06383 FastRCNN total loss: 0.1764 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.1363 RPN box loss: 0.0027 RPN score loss: 0.00296 RPN total loss: 0.00566 Total loss: 0.90815 timestamp: 1654971490.6127155 iteration: 73350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06448 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.14217 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.1181 RPN box loss: 0.01315 RPN score loss: 0.00907 RPN total loss: 0.02222 Total loss: 0.87227 timestamp: 1654971493.8390856 iteration: 73355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08648 FastRCNN class loss: 0.05644 FastRCNN total loss: 0.14292 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.0004 Mask loss: 0.20388 RPN box loss: 0.02572 RPN score loss: 0.01128 RPN total loss: 0.037 Total loss: 0.97358 timestamp: 1654971497.0862525 iteration: 73360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0835 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.15944 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.0004 Mask loss: 0.11334 RPN box loss: 0.0339 RPN score loss: 0.00942 RPN total loss: 0.04332 Total loss: 0.90588 timestamp: 1654971500.308527 iteration: 73365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07102 FastRCNN class loss: 0.09007 FastRCNN total loss: 0.1611 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.0004 Mask loss: 0.15224 RPN box loss: 0.00667 RPN score loss: 0.00687 RPN total loss: 0.01355 Total loss: 0.91666 timestamp: 1654971503.5474973 iteration: 73370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06535 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.14248 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.0004 Mask loss: 0.15138 RPN box loss: 0.0067 RPN score loss: 0.0059 RPN total loss: 0.0126 Total loss: 0.89624 timestamp: 1654971506.718879 iteration: 73375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08978 FastRCNN class loss: 0.04337 FastRCNN total loss: 0.13316 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.0004 Mask loss: 0.09431 RPN box loss: 0.0229 RPN score loss: 0.00328 RPN total loss: 0.02618 Total loss: 0.84344 timestamp: 1654971509.9281785 iteration: 73380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12353 FastRCNN class loss: 0.04735 FastRCNN total loss: 0.17088 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.0004 Mask loss: 0.1195 RPN box loss: 0.00975 RPN score loss: 0.00221 RPN total loss: 0.01196 Total loss: 0.89212 timestamp: 1654971513.181035 iteration: 73385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05314 FastRCNN class loss: 0.04567 FastRCNN total loss: 0.09882 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.0004 Mask loss: 0.11142 RPN box loss: 0.01222 RPN score loss: 0.00135 RPN total loss: 0.01357 Total loss: 0.81357 timestamp: 1654971516.3582482 iteration: 73390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10639 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.17615 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.0004 Mask loss: 0.13332 RPN box loss: 0.00635 RPN score loss: 0.00246 RPN total loss: 0.00881 Total loss: 0.90804 timestamp: 1654971519.5796492 iteration: 73395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12142 FastRCNN class loss: 0.08953 FastRCNN total loss: 0.21095 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.0004 Mask loss: 0.1781 RPN box loss: 0.02029 RPN score loss: 0.00399 RPN total loss: 0.02428 Total loss: 1.0031 timestamp: 1654971522.79904 iteration: 73400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10855 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.16697 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.0004 Mask loss: 0.11793 RPN box loss: 0.01473 RPN score loss: 0.0005 RPN total loss: 0.01523 Total loss: 0.8899 timestamp: 1654971525.9765704 iteration: 73405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07434 FastRCNN class loss: 0.04613 FastRCNN total loss: 0.12046 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.0004 Mask loss: 0.10018 RPN box loss: 0.04773 RPN score loss: 0.01011 RPN total loss: 0.05784 Total loss: 0.86825 timestamp: 1654971529.2468693 iteration: 73410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06186 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.12082 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.0004 Mask loss: 0.11447 RPN box loss: 0.02023 RPN score loss: 0.00613 RPN total loss: 0.02637 Total loss: 0.85143 timestamp: 1654971532.44619 iteration: 73415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07368 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.13465 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.0004 Mask loss: 0.14616 RPN box loss: 0.01053 RPN score loss: 0.0126 RPN total loss: 0.02313 Total loss: 0.8937 timestamp: 1654971535.6545079 iteration: 73420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05784 FastRCNN class loss: 0.05306 FastRCNN total loss: 0.1109 L1 loss: 0.0000e+00 L2 loss: 0.58976 Learning rate: 0.0004 Mask loss: 0.2015 RPN box loss: 0.00521 RPN score loss: 0.00324 RPN total loss: 0.00845 Total loss: 0.9106 timestamp: 1654971538.9546866 iteration: 73425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11278 FastRCNN class loss: 0.10545 FastRCNN total loss: 0.21823 L1 loss: 0.0000e+00 L2 loss: 0.58976 Learning rate: 0.0004 Mask loss: 0.17029 RPN box loss: 0.01154 RPN score loss: 0.01182 RPN total loss: 0.02336 Total loss: 1.00164 timestamp: 1654971542.1187005 iteration: 73430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06919 FastRCNN class loss: 0.0451 FastRCNN total loss: 0.11429 L1 loss: 0.0000e+00 L2 loss: 0.58976 Learning rate: 0.0004 Mask loss: 0.0943 RPN box loss: 0.01323 RPN score loss: 0.0043 RPN total loss: 0.01753 Total loss: 0.81588 timestamp: 1654971545.3588421 iteration: 73435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06807 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.13948 L1 loss: 0.0000e+00 L2 loss: 0.58976 Learning rate: 0.0004 Mask loss: 0.10278 RPN box loss: 0.00553 RPN score loss: 0.00662 RPN total loss: 0.01215 Total loss: 0.84417 timestamp: 1654971548.612376 iteration: 73440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.13468 L1 loss: 0.0000e+00 L2 loss: 0.58976 Learning rate: 0.0004 Mask loss: 0.1667 RPN box loss: 0.01074 RPN score loss: 0.00304 RPN total loss: 0.01378 Total loss: 0.90491 timestamp: 1654971551.8162513 iteration: 73445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07956 FastRCNN class loss: 0.05877 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.15831 RPN box loss: 0.00423 RPN score loss: 0.00458 RPN total loss: 0.0088 Total loss: 0.8952 timestamp: 1654971555.1129475 iteration: 73450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08516 FastRCNN class loss: 0.04288 FastRCNN total loss: 0.12803 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.10631 RPN box loss: 0.00687 RPN score loss: 0.00413 RPN total loss: 0.011 Total loss: 0.8351 timestamp: 1654971558.3252385 iteration: 73455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06959 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.12699 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.08939 RPN box loss: 0.00642 RPN score loss: 0.00304 RPN total loss: 0.00946 Total loss: 0.81559 timestamp: 1654971561.5152938 iteration: 73460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08831 FastRCNN class loss: 0.07528 FastRCNN total loss: 0.1636 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.13961 RPN box loss: 0.01764 RPN score loss: 0.00818 RPN total loss: 0.02581 Total loss: 0.91877 timestamp: 1654971564.7485745 iteration: 73465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13296 FastRCNN class loss: 0.10454 FastRCNN total loss: 0.2375 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.16933 RPN box loss: 0.01691 RPN score loss: 0.00798 RPN total loss: 0.0249 Total loss: 1.02148 timestamp: 1654971567.996114 iteration: 73470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.14685 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.16711 RPN box loss: 0.00658 RPN score loss: 0.00206 RPN total loss: 0.00863 Total loss: 0.91234 timestamp: 1654971571.1895587 iteration: 73475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07057 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.1547 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.0004 Mask loss: 0.17758 RPN box loss: 0.01676 RPN score loss: 0.01182 RPN total loss: 0.02858 Total loss: 0.95061 timestamp: 1654971574.4778066 iteration: 73480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11456 FastRCNN class loss: 0.09614 FastRCNN total loss: 0.2107 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.0004 Mask loss: 0.14416 RPN box loss: 0.01021 RPN score loss: 0.00827 RPN total loss: 0.01848 Total loss: 0.96308 timestamp: 1654971577.606547 iteration: 73485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07572 FastRCNN class loss: 0.09675 FastRCNN total loss: 0.17246 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.0004 Mask loss: 0.1268 RPN box loss: 0.0126 RPN score loss: 0.00437 RPN total loss: 0.01696 Total loss: 0.90597 timestamp: 1654971580.8025472 iteration: 73490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08033 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.15064 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.0004 Mask loss: 0.1307 RPN box loss: 0.00645 RPN score loss: 0.00303 RPN total loss: 0.00947 Total loss: 0.88056 timestamp: 1654971583.9585385 iteration: 73495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07823 FastRCNN class loss: 0.06026 FastRCNN total loss: 0.13849 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.0004 Mask loss: 0.09069 RPN box loss: 0.00649 RPN score loss: 0.00261 RPN total loss: 0.0091 Total loss: 0.82802 timestamp: 1654971587.1346278 iteration: 73500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07535 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.12579 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.0004 Mask loss: 0.13468 RPN box loss: 0.0115 RPN score loss: 0.00323 RPN total loss: 0.01473 Total loss: 0.86495 timestamp: 1654971590.344323 iteration: 73505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08617 FastRCNN class loss: 0.05803 FastRCNN total loss: 0.1442 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.0004 Mask loss: 0.10206 RPN box loss: 0.00543 RPN score loss: 0.00602 RPN total loss: 0.01145 Total loss: 0.84745 timestamp: 1654971593.5186846 iteration: 73510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10948 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.18704 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.0004 Mask loss: 0.15707 RPN box loss: 0.04074 RPN score loss: 0.01157 RPN total loss: 0.0523 Total loss: 0.98614 timestamp: 1654971596.642512 iteration: 73515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07667 FastRCNN class loss: 0.07397 FastRCNN total loss: 0.15065 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.0004 Mask loss: 0.13096 RPN box loss: 0.00861 RPN score loss: 0.00486 RPN total loss: 0.01347 Total loss: 0.88481 timestamp: 1654971599.849299 iteration: 73520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.05309 FastRCNN total loss: 0.13163 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.0004 Mask loss: 0.14625 RPN box loss: 0.00497 RPN score loss: 0.00133 RPN total loss: 0.0063 Total loss: 0.87392 timestamp: 1654971603.0656965 iteration: 73525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07199 FastRCNN class loss: 0.05075 FastRCNN total loss: 0.12274 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.0004 Mask loss: 0.0925 RPN box loss: 0.01509 RPN score loss: 0.00259 RPN total loss: 0.01768 Total loss: 0.82265 timestamp: 1654971606.2196653 iteration: 73530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.19093 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.0004 Mask loss: 0.14019 RPN box loss: 0.01063 RPN score loss: 0.00313 RPN total loss: 0.01376 Total loss: 0.93461 timestamp: 1654971609.3927722 iteration: 73535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0803 FastRCNN class loss: 0.09014 FastRCNN total loss: 0.17044 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.0004 Mask loss: 0.13455 RPN box loss: 0.01303 RPN score loss: 0.00637 RPN total loss: 0.0194 Total loss: 0.91412 timestamp: 1654971612.6096373 iteration: 73540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10517 FastRCNN class loss: 0.08317 FastRCNN total loss: 0.18834 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.0004 Mask loss: 0.1591 RPN box loss: 0.01842 RPN score loss: 0.00143 RPN total loss: 0.01985 Total loss: 0.95701 timestamp: 1654971615.825752 iteration: 73545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04897 FastRCNN class loss: 0.04337 FastRCNN total loss: 0.09234 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.0004 Mask loss: 0.09372 RPN box loss: 0.01424 RPN score loss: 0.00357 RPN total loss: 0.0178 Total loss: 0.79359 timestamp: 1654971619.0826201 iteration: 73550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09023 FastRCNN class loss: 0.06985 FastRCNN total loss: 0.16008 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.0004 Mask loss: 0.118 RPN box loss: 0.01152 RPN score loss: 0.00191 RPN total loss: 0.01343 Total loss: 0.88122 timestamp: 1654971622.3282413 iteration: 73555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.043 FastRCNN class loss: 0.04914 FastRCNN total loss: 0.09214 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.0004 Mask loss: 0.15524 RPN box loss: 0.02315 RPN score loss: 0.00199 RPN total loss: 0.02513 Total loss: 0.86223 timestamp: 1654971625.5487785 iteration: 73560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06086 FastRCNN class loss: 0.05867 FastRCNN total loss: 0.11953 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.0004 Mask loss: 0.09781 RPN box loss: 0.00496 RPN score loss: 0.00685 RPN total loss: 0.01181 Total loss: 0.81887 timestamp: 1654971628.7946155 iteration: 73565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10028 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.18296 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.0004 Mask loss: 0.11725 RPN box loss: 0.02226 RPN score loss: 0.00817 RPN total loss: 0.03043 Total loss: 0.92035 timestamp: 1654971632.0202117 iteration: 73570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06982 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.11925 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.11269 RPN box loss: 0.02806 RPN score loss: 0.00305 RPN total loss: 0.03111 Total loss: 0.85277 timestamp: 1654971635.2173388 iteration: 73575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05837 FastRCNN class loss: 0.045 FastRCNN total loss: 0.10337 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.09238 RPN box loss: 0.00544 RPN score loss: 0.00207 RPN total loss: 0.00751 Total loss: 0.79298 timestamp: 1654971638.3808534 iteration: 73580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.06963 FastRCNN total loss: 0.1697 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.11173 RPN box loss: 0.00762 RPN score loss: 0.00162 RPN total loss: 0.00924 Total loss: 0.88039 timestamp: 1654971641.627278 iteration: 73585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08226 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.13538 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.09671 RPN box loss: 0.01418 RPN score loss: 0.00226 RPN total loss: 0.01644 Total loss: 0.83824 timestamp: 1654971644.7994506 iteration: 73590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09147 FastRCNN class loss: 0.04617 FastRCNN total loss: 0.13764 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.12377 RPN box loss: 0.00657 RPN score loss: 0.00323 RPN total loss: 0.00981 Total loss: 0.86092 timestamp: 1654971647.9476895 iteration: 73595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07048 FastRCNN class loss: 0.10859 FastRCNN total loss: 0.17906 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.19929 RPN box loss: 0.01195 RPN score loss: 0.0119 RPN total loss: 0.02386 Total loss: 0.99192 timestamp: 1654971651.1436956 iteration: 73600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10759 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.18877 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.0004 Mask loss: 0.18583 RPN box loss: 0.0151 RPN score loss: 0.00851 RPN total loss: 0.0236 Total loss: 0.9879 timestamp: 1654971654.3483212 iteration: 73605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05262 FastRCNN class loss: 0.03235 FastRCNN total loss: 0.08497 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.0004 Mask loss: 0.05391 RPN box loss: 0.00726 RPN score loss: 0.0006 RPN total loss: 0.00785 Total loss: 0.73644 timestamp: 1654971657.550916 iteration: 73610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0663 FastRCNN class loss: 0.04535 FastRCNN total loss: 0.11165 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.0004 Mask loss: 0.12281 RPN box loss: 0.01067 RPN score loss: 0.00212 RPN total loss: 0.0128 Total loss: 0.83696 timestamp: 1654971660.7696896 iteration: 73615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09737 FastRCNN class loss: 0.10204 FastRCNN total loss: 0.19941 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.0004 Mask loss: 0.14157 RPN box loss: 0.00573 RPN score loss: 0.00228 RPN total loss: 0.00801 Total loss: 0.93869 timestamp: 1654971663.9630876 iteration: 73620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10577 FastRCNN class loss: 0.06393 FastRCNN total loss: 0.16971 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.0004 Mask loss: 0.10155 RPN box loss: 0.02091 RPN score loss: 0.00492 RPN total loss: 0.02583 Total loss: 0.88679 timestamp: 1654971667.1507692 iteration: 73625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.04951 FastRCNN total loss: 0.13348 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.0004 Mask loss: 0.12346 RPN box loss: 0.01287 RPN score loss: 0.00198 RPN total loss: 0.01486 Total loss: 0.86149 timestamp: 1654971670.4180894 iteration: 73630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0829 FastRCNN class loss: 0.0548 FastRCNN total loss: 0.1377 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.0004 Mask loss: 0.10458 RPN box loss: 0.01087 RPN score loss: 0.00251 RPN total loss: 0.01338 Total loss: 0.84535 timestamp: 1654971673.6875184 iteration: 73635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1135 FastRCNN class loss: 0.11823 FastRCNN total loss: 0.23173 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.17818 RPN box loss: 0.02653 RPN score loss: 0.01082 RPN total loss: 0.03735 Total loss: 1.03695 timestamp: 1654971676.841131 iteration: 73640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10542 FastRCNN class loss: 0.05717 FastRCNN total loss: 0.1626 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.10008 RPN box loss: 0.02013 RPN score loss: 0.0035 RPN total loss: 0.02362 Total loss: 0.876 timestamp: 1654971680.0552328 iteration: 73645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12847 FastRCNN class loss: 0.0914 FastRCNN total loss: 0.21988 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.13124 RPN box loss: 0.0128 RPN score loss: 0.01062 RPN total loss: 0.02343 Total loss: 0.96423 timestamp: 1654971683.2374492 iteration: 73650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05672 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.10883 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.11414 RPN box loss: 0.00799 RPN score loss: 0.00882 RPN total loss: 0.01681 Total loss: 0.82947 timestamp: 1654971686.43187 iteration: 73655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10055 FastRCNN class loss: 0.09292 FastRCNN total loss: 0.19347 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.18141 RPN box loss: 0.01134 RPN score loss: 0.0083 RPN total loss: 0.01964 Total loss: 0.98421 timestamp: 1654971689.620111 iteration: 73660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11141 FastRCNN class loss: 0.08812 FastRCNN total loss: 0.19954 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.0937 RPN box loss: 0.01932 RPN score loss: 0.01073 RPN total loss: 0.03004 Total loss: 0.91297 timestamp: 1654971692.756552 iteration: 73665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11287 FastRCNN class loss: 0.09952 FastRCNN total loss: 0.21239 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.0004 Mask loss: 0.11871 RPN box loss: 0.00644 RPN score loss: 0.00581 RPN total loss: 0.01226 Total loss: 0.93304 timestamp: 1654971696.0506725 iteration: 73670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11583 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.1641 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.0004 Mask loss: 0.10168 RPN box loss: 0.00709 RPN score loss: 0.00222 RPN total loss: 0.00931 Total loss: 0.86478 timestamp: 1654971699.2393856 iteration: 73675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08625 FastRCNN class loss: 0.1049 FastRCNN total loss: 0.19115 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.0004 Mask loss: 0.14014 RPN box loss: 0.01601 RPN score loss: 0.00841 RPN total loss: 0.02442 Total loss: 0.94539 timestamp: 1654971702.4507241 iteration: 73680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06563 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.11321 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.0004 Mask loss: 0.14378 RPN box loss: 0.0066 RPN score loss: 0.00118 RPN total loss: 0.00778 Total loss: 0.85445 timestamp: 1654971705.6442099 iteration: 73685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06493 FastRCNN class loss: 0.05399 FastRCNN total loss: 0.11892 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.0004 Mask loss: 0.13868 RPN box loss: 0.0101 RPN score loss: 0.01887 RPN total loss: 0.02897 Total loss: 0.87625 timestamp: 1654971708.8942304 iteration: 73690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17009 FastRCNN class loss: 0.10636 FastRCNN total loss: 0.27645 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.0004 Mask loss: 0.15028 RPN box loss: 0.01641 RPN score loss: 0.00265 RPN total loss: 0.01906 Total loss: 1.03547 timestamp: 1654971712.0748165 iteration: 73695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08576 FastRCNN class loss: 0.05343 FastRCNN total loss: 0.1392 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.0004 Mask loss: 0.10998 RPN box loss: 0.00719 RPN score loss: 0.00337 RPN total loss: 0.01056 Total loss: 0.84941 timestamp: 1654971715.217705 iteration: 73700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09697 FastRCNN class loss: 0.0714 FastRCNN total loss: 0.16838 L1 loss: 0.0000e+00 L2 loss: 0.58967 Learning rate: 0.0004 Mask loss: 0.15116 RPN box loss: 0.03713 RPN score loss: 0.0162 RPN total loss: 0.05333 Total loss: 0.96254 timestamp: 1654971718.4235241 iteration: 73705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06937 FastRCNN class loss: 0.04866 FastRCNN total loss: 0.11803 L1 loss: 0.0000e+00 L2 loss: 0.58967 Learning rate: 0.0004 Mask loss: 0.08449 RPN box loss: 0.00518 RPN score loss: 0.00383 RPN total loss: 0.00901 Total loss: 0.8012 timestamp: 1654971721.6514087 iteration: 73710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08065 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.14957 L1 loss: 0.0000e+00 L2 loss: 0.58967 Learning rate: 0.0004 Mask loss: 0.21278 RPN box loss: 0.01562 RPN score loss: 0.00287 RPN total loss: 0.01849 Total loss: 0.97051 timestamp: 1654971724.8183053 iteration: 73715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06841 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.12886 L1 loss: 0.0000e+00 L2 loss: 0.58967 Learning rate: 0.0004 Mask loss: 0.10783 RPN box loss: 0.00615 RPN score loss: 0.00754 RPN total loss: 0.01369 Total loss: 0.84004 timestamp: 1654971727.9703944 iteration: 73720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0867 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.1579 L1 loss: 0.0000e+00 L2 loss: 0.58967 Learning rate: 0.0004 Mask loss: 0.1093 RPN box loss: 0.00636 RPN score loss: 0.00328 RPN total loss: 0.00964 Total loss: 0.86649 timestamp: 1654971731.129026 iteration: 73725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09869 FastRCNN class loss: 0.07528 FastRCNN total loss: 0.17396 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.18182 RPN box loss: 0.0153 RPN score loss: 0.01663 RPN total loss: 0.03193 Total loss: 0.97737 timestamp: 1654971734.3232841 iteration: 73730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08132 FastRCNN class loss: 0.06873 FastRCNN total loss: 0.15006 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.16455 RPN box loss: 0.00696 RPN score loss: 0.00429 RPN total loss: 0.01125 Total loss: 0.91551 timestamp: 1654971737.5035715 iteration: 73735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05516 FastRCNN class loss: 0.06572 FastRCNN total loss: 0.12088 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.12493 RPN box loss: 0.01465 RPN score loss: 0.00213 RPN total loss: 0.01679 Total loss: 0.85225 timestamp: 1654971740.7998822 iteration: 73740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06442 FastRCNN class loss: 0.04768 FastRCNN total loss: 0.1121 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.10292 RPN box loss: 0.00579 RPN score loss: 0.00103 RPN total loss: 0.00682 Total loss: 0.8115 timestamp: 1654971743.9676027 iteration: 73745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08803 FastRCNN class loss: 0.05734 FastRCNN total loss: 0.14538 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.13368 RPN box loss: 0.00565 RPN score loss: 0.00557 RPN total loss: 0.01122 Total loss: 0.87993 timestamp: 1654971747.1984546 iteration: 73750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13747 FastRCNN class loss: 0.07123 FastRCNN total loss: 0.20869 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.1347 RPN box loss: 0.01704 RPN score loss: 0.00796 RPN total loss: 0.025 Total loss: 0.95805 timestamp: 1654971750.3811438 iteration: 73755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07938 FastRCNN class loss: 0.04651 FastRCNN total loss: 0.12588 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.0004 Mask loss: 0.12936 RPN box loss: 0.00849 RPN score loss: 0.00075 RPN total loss: 0.00923 Total loss: 0.85413 timestamp: 1654971753.5099127 iteration: 73760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06593 FastRCNN class loss: 0.05718 FastRCNN total loss: 0.12311 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.0004 Mask loss: 0.1417 RPN box loss: 0.00737 RPN score loss: 0.00458 RPN total loss: 0.01195 Total loss: 0.86641 timestamp: 1654971756.6673465 iteration: 73765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07667 FastRCNN class loss: 0.05076 FastRCNN total loss: 0.12743 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.0004 Mask loss: 0.12743 RPN box loss: 0.0041 RPN score loss: 0.00525 RPN total loss: 0.00935 Total loss: 0.85386 timestamp: 1654971759.8287935 iteration: 73770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.06389 FastRCNN total loss: 0.14455 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.0004 Mask loss: 0.11737 RPN box loss: 0.02701 RPN score loss: 0.00442 RPN total loss: 0.03143 Total loss: 0.883 timestamp: 1654971763.0062606 iteration: 73775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07474 FastRCNN class loss: 0.05853 FastRCNN total loss: 0.13327 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.0004 Mask loss: 0.11795 RPN box loss: 0.00927 RPN score loss: 0.01605 RPN total loss: 0.02531 Total loss: 0.86617 timestamp: 1654971766.1934688 iteration: 73780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08856 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.164 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.0004 Mask loss: 0.07953 RPN box loss: 0.01661 RPN score loss: 0.0018 RPN total loss: 0.01841 Total loss: 0.85158 timestamp: 1654971769.413248 iteration: 73785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11134 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.1849 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.0004 Mask loss: 0.16633 RPN box loss: 0.00675 RPN score loss: 0.00689 RPN total loss: 0.01364 Total loss: 0.95451 timestamp: 1654971772.625842 iteration: 73790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11021 FastRCNN class loss: 0.0756 FastRCNN total loss: 0.18581 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.0004 Mask loss: 0.19392 RPN box loss: 0.01602 RPN score loss: 0.00773 RPN total loss: 0.02375 Total loss: 0.99312 timestamp: 1654971775.782047 iteration: 73795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15327 FastRCNN class loss: 0.08962 FastRCNN total loss: 0.24289 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.0004 Mask loss: 0.11389 RPN box loss: 0.01438 RPN score loss: 0.00217 RPN total loss: 0.01655 Total loss: 0.96297 timestamp: 1654971779.0405786 iteration: 73800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10901 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.17959 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.0004 Mask loss: 0.127 RPN box loss: 0.02061 RPN score loss: 0.00093 RPN total loss: 0.02154 Total loss: 0.91778 timestamp: 1654971782.1816514 iteration: 73805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11531 FastRCNN class loss: 0.10527 FastRCNN total loss: 0.22058 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.0004 Mask loss: 0.2173 RPN box loss: 0.0191 RPN score loss: 0.00531 RPN total loss: 0.02441 Total loss: 1.05194 timestamp: 1654971785.3796961 iteration: 73810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11127 FastRCNN class loss: 0.12052 FastRCNN total loss: 0.23178 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.0004 Mask loss: 0.11691 RPN box loss: 0.02041 RPN score loss: 0.01038 RPN total loss: 0.03079 Total loss: 0.96913 timestamp: 1654971788.5975776 iteration: 73815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06903 FastRCNN class loss: 0.05879 FastRCNN total loss: 0.12782 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.0937 RPN box loss: 0.02578 RPN score loss: 0.00318 RPN total loss: 0.02895 Total loss: 0.84011 timestamp: 1654971791.8021538 iteration: 73820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07934 FastRCNN class loss: 0.06603 FastRCNN total loss: 0.14537 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.14852 RPN box loss: 0.01311 RPN score loss: 0.00211 RPN total loss: 0.01521 Total loss: 0.89874 timestamp: 1654971795.0289865 iteration: 73825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11519 FastRCNN class loss: 0.10021 FastRCNN total loss: 0.2154 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.15652 RPN box loss: 0.05958 RPN score loss: 0.01065 RPN total loss: 0.07023 Total loss: 1.03178 timestamp: 1654971798.2541504 iteration: 73830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05378 FastRCNN class loss: 0.06236 FastRCNN total loss: 0.11614 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.08025 RPN box loss: 0.00707 RPN score loss: 0.00178 RPN total loss: 0.00885 Total loss: 0.79487 timestamp: 1654971801.4462304 iteration: 73835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10345 FastRCNN class loss: 0.0889 FastRCNN total loss: 0.19235 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.10407 RPN box loss: 0.00847 RPN score loss: 0.00344 RPN total loss: 0.0119 Total loss: 0.89795 timestamp: 1654971804.5981686 iteration: 73840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06922 FastRCNN class loss: 0.03591 FastRCNN total loss: 0.10513 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.08999 RPN box loss: 0.00748 RPN score loss: 0.00131 RPN total loss: 0.00879 Total loss: 0.79354 timestamp: 1654971807.8169131 iteration: 73845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0636 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.13557 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.0004 Mask loss: 0.16068 RPN box loss: 0.00717 RPN score loss: 0.00237 RPN total loss: 0.00954 Total loss: 0.89541 timestamp: 1654971811.0370467 iteration: 73850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10145 FastRCNN class loss: 0.0384 FastRCNN total loss: 0.13986 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.0004 Mask loss: 0.08188 RPN box loss: 0.00646 RPN score loss: 0.00137 RPN total loss: 0.00782 Total loss: 0.81918 timestamp: 1654971814.2607908 iteration: 73855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.14898 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.0004 Mask loss: 0.12971 RPN box loss: 0.00438 RPN score loss: 0.00228 RPN total loss: 0.00666 Total loss: 0.87497 timestamp: 1654971817.4061246 iteration: 73860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06029 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.14748 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.0004 Mask loss: 0.14569 RPN box loss: 0.00678 RPN score loss: 0.00173 RPN total loss: 0.00851 Total loss: 0.8913 timestamp: 1654971820.6974187 iteration: 73865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04255 FastRCNN class loss: 0.04732 FastRCNN total loss: 0.08987 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.0004 Mask loss: 0.1089 RPN box loss: 0.00569 RPN score loss: 0.00215 RPN total loss: 0.00783 Total loss: 0.79622 timestamp: 1654971823.908436 iteration: 73870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06081 FastRCNN class loss: 0.06041 FastRCNN total loss: 0.12122 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.0004 Mask loss: 0.14654 RPN box loss: 0.00458 RPN score loss: 0.00159 RPN total loss: 0.00617 Total loss: 0.86356 timestamp: 1654971827.036623 iteration: 73875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08814 FastRCNN class loss: 0.06562 FastRCNN total loss: 0.15375 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.0004 Mask loss: 0.13345 RPN box loss: 0.00996 RPN score loss: 0.00837 RPN total loss: 0.01833 Total loss: 0.89515 timestamp: 1654971830.2176156 iteration: 73880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10703 FastRCNN class loss: 0.05964 FastRCNN total loss: 0.16667 L1 loss: 0.0000e+00 L2 loss: 0.58961 Learning rate: 0.0004 Mask loss: 0.16831 RPN box loss: 0.00608 RPN score loss: 0.00511 RPN total loss: 0.01118 Total loss: 0.93578 timestamp: 1654971833.4372084 iteration: 73885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05772 FastRCNN class loss: 0.05028 FastRCNN total loss: 0.108 L1 loss: 0.0000e+00 L2 loss: 0.58961 Learning rate: 0.0004 Mask loss: 0.15773 RPN box loss: 0.00275 RPN score loss: 0.00735 RPN total loss: 0.0101 Total loss: 0.86544 timestamp: 1654971836.7320087 iteration: 73890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.14352 L1 loss: 0.0000e+00 L2 loss: 0.58961 Learning rate: 0.0004 Mask loss: 0.19127 RPN box loss: 0.0093 RPN score loss: 0.00694 RPN total loss: 0.01624 Total loss: 0.94064 timestamp: 1654971839.904531 iteration: 73895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10775 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.16823 L1 loss: 0.0000e+00 L2 loss: 0.58961 Learning rate: 0.0004 Mask loss: 0.14916 RPN box loss: 0.02878 RPN score loss: 0.00235 RPN total loss: 0.03113 Total loss: 0.93814 timestamp: 1654971843.1131322 iteration: 73900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06227 FastRCNN class loss: 0.05296 FastRCNN total loss: 0.11523 L1 loss: 0.0000e+00 L2 loss: 0.58961 Learning rate: 0.0004 Mask loss: 0.12751 RPN box loss: 0.00693 RPN score loss: 0.00488 RPN total loss: 0.01181 Total loss: 0.84416 timestamp: 1654971846.3231 iteration: 73905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08915 FastRCNN class loss: 0.07271 FastRCNN total loss: 0.16185 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.0004 Mask loss: 0.10058 RPN box loss: 0.01835 RPN score loss: 0.00211 RPN total loss: 0.02046 Total loss: 0.8725 timestamp: 1654971849.4525368 iteration: 73910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11553 FastRCNN class loss: 0.09557 FastRCNN total loss: 0.2111 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.0004 Mask loss: 0.15324 RPN box loss: 0.01381 RPN score loss: 0.00869 RPN total loss: 0.0225 Total loss: 0.97644 timestamp: 1654971852.6966958 iteration: 73915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.116 FastRCNN class loss: 0.08613 FastRCNN total loss: 0.20213 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.0004 Mask loss: 0.0975 RPN box loss: 0.00619 RPN score loss: 0.00438 RPN total loss: 0.01057 Total loss: 0.8998 timestamp: 1654971855.8549087 iteration: 73920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10481 FastRCNN class loss: 0.0512 FastRCNN total loss: 0.15601 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.0004 Mask loss: 0.16595 RPN box loss: 0.00923 RPN score loss: 0.00357 RPN total loss: 0.0128 Total loss: 0.92435 timestamp: 1654971859.0922365 iteration: 73925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07376 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.14097 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.0004 Mask loss: 0.11107 RPN box loss: 0.00592 RPN score loss: 0.00249 RPN total loss: 0.00841 Total loss: 0.85005 timestamp: 1654971862.2679136 iteration: 73930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0576 FastRCNN class loss: 0.06515 FastRCNN total loss: 0.12276 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.0004 Mask loss: 0.08639 RPN box loss: 0.0167 RPN score loss: 0.00686 RPN total loss: 0.02356 Total loss: 0.82231 timestamp: 1654971865.4205115 iteration: 73935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11926 FastRCNN class loss: 0.07718 FastRCNN total loss: 0.19644 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.0004 Mask loss: 0.17506 RPN box loss: 0.00528 RPN score loss: 0.00777 RPN total loss: 0.01305 Total loss: 0.97414 timestamp: 1654971868.6238666 iteration: 73940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.07478 FastRCNN total loss: 0.15563 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.0004 Mask loss: 0.12334 RPN box loss: 0.00868 RPN score loss: 0.00528 RPN total loss: 0.01396 Total loss: 0.88252 timestamp: 1654971871.8448079 iteration: 73945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08481 FastRCNN class loss: 0.06372 FastRCNN total loss: 0.14853 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.0004 Mask loss: 0.15817 RPN box loss: 0.00699 RPN score loss: 0.00193 RPN total loss: 0.00893 Total loss: 0.90522 timestamp: 1654971874.9497306 iteration: 73950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.11363 FastRCNN total loss: 0.21399 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.0004 Mask loss: 0.12221 RPN box loss: 0.00823 RPN score loss: 0.01344 RPN total loss: 0.02167 Total loss: 0.94747 timestamp: 1654971878.1037138 iteration: 73955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06973 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.12923 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.0004 Mask loss: 0.15431 RPN box loss: 0.00864 RPN score loss: 0.00203 RPN total loss: 0.01066 Total loss: 0.8838 timestamp: 1654971881.3331277 iteration: 73960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1041 FastRCNN class loss: 0.04876 FastRCNN total loss: 0.15286 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.0004 Mask loss: 0.13098 RPN box loss: 0.01444 RPN score loss: 0.00266 RPN total loss: 0.01709 Total loss: 0.89052 timestamp: 1654971884.4849102 iteration: 73965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12145 FastRCNN class loss: 0.08945 FastRCNN total loss: 0.2109 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.0004 Mask loss: 0.22063 RPN box loss: 0.01632 RPN score loss: 0.007 RPN total loss: 0.02333 Total loss: 1.04444 timestamp: 1654971887.613576 iteration: 73970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.077 FastRCNN class loss: 0.05696 FastRCNN total loss: 0.13395 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.0004 Mask loss: 0.14079 RPN box loss: 0.00677 RPN score loss: 0.00673 RPN total loss: 0.0135 Total loss: 0.87783 timestamp: 1654971890.7648954 iteration: 73975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10196 FastRCNN class loss: 0.08498 FastRCNN total loss: 0.18694 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.0004 Mask loss: 0.1207 RPN box loss: 0.01692 RPN score loss: 0.01278 RPN total loss: 0.0297 Total loss: 0.92692 timestamp: 1654971893.9501867 iteration: 73980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07842 FastRCNN class loss: 0.05626 FastRCNN total loss: 0.13468 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.0004 Mask loss: 0.1753 RPN box loss: 0.01518 RPN score loss: 0.00668 RPN total loss: 0.02186 Total loss: 0.92142 timestamp: 1654971897.1124506 iteration: 73985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10772 FastRCNN class loss: 0.05132 FastRCNN total loss: 0.15905 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.0004 Mask loss: 0.08993 RPN box loss: 0.00908 RPN score loss: 0.00242 RPN total loss: 0.01151 Total loss: 0.85006 timestamp: 1654971900.3407938 iteration: 73990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11037 FastRCNN class loss: 0.091 FastRCNN total loss: 0.20138 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.0004 Mask loss: 0.14846 RPN box loss: 0.00906 RPN score loss: 0.0045 RPN total loss: 0.01356 Total loss: 0.95298 timestamp: 1654971903.5855527 iteration: 73995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0571 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.11342 L1 loss: 0.0000e+00 L2 loss: 0.58957 Learning rate: 0.0004 Mask loss: 0.09934 RPN box loss: 0.00894 RPN score loss: 0.00674 RPN total loss: 0.01568 Total loss: 0.81801 timestamp: 1654971906.7959425 iteration: 74000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17241 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.24001 L1 loss: 0.0000e+00 L2 loss: 0.58957 Learning rate: 0.0004 Mask loss: 0.10439 RPN box loss: 0.01783 RPN score loss: 0.00452 RPN total loss: 0.02235 Total loss: 0.95632 timestamp: 1654971909.8787396 iteration: 74005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08395 FastRCNN class loss: 0.11498 FastRCNN total loss: 0.19893 L1 loss: 0.0000e+00 L2 loss: 0.58957 Learning rate: 0.0004 Mask loss: 0.11075 RPN box loss: 0.00629 RPN score loss: 0.00465 RPN total loss: 0.01094 Total loss: 0.91019 timestamp: 1654971913.0962539 iteration: 74010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.07868 FastRCNN total loss: 0.17931 L1 loss: 0.0000e+00 L2 loss: 0.58957 Learning rate: 0.0004 Mask loss: 0.12984 RPN box loss: 0.02362 RPN score loss: 0.00944 RPN total loss: 0.03305 Total loss: 0.93178 timestamp: 1654971916.272276 iteration: 74015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10219 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.15999 L1 loss: 0.0000e+00 L2 loss: 0.58957 Learning rate: 0.0004 Mask loss: 0.09244 RPN box loss: 0.00704 RPN score loss: 0.00848 RPN total loss: 0.01552 Total loss: 0.85751 timestamp: 1654971919.51517 iteration: 74020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0784 FastRCNN class loss: 0.07003 FastRCNN total loss: 0.14844 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.13621 RPN box loss: 0.04121 RPN score loss: 0.00394 RPN total loss: 0.04516 Total loss: 0.91937 timestamp: 1654971922.712299 iteration: 74025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10988 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.16435 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.11317 RPN box loss: 0.00647 RPN score loss: 0.00576 RPN total loss: 0.01223 Total loss: 0.87932 timestamp: 1654971925.856071 iteration: 74030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10836 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.18832 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.13772 RPN box loss: 0.00654 RPN score loss: 0.0039 RPN total loss: 0.01044 Total loss: 0.92604 timestamp: 1654971929.0602674 iteration: 74035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11135 FastRCNN class loss: 0.06395 FastRCNN total loss: 0.1753 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.12015 RPN box loss: 0.02085 RPN score loss: 0.00283 RPN total loss: 0.02368 Total loss: 0.90869 timestamp: 1654971932.1966984 iteration: 74040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12151 FastRCNN class loss: 0.11361 FastRCNN total loss: 0.23513 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.19727 RPN box loss: 0.01331 RPN score loss: 0.013 RPN total loss: 0.02631 Total loss: 1.04826 timestamp: 1654971935.3396893 iteration: 74045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08336 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.13571 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.16715 RPN box loss: 0.0178 RPN score loss: 0.00337 RPN total loss: 0.02117 Total loss: 0.91358 timestamp: 1654971938.554001 iteration: 74050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04332 FastRCNN class loss: 0.03418 FastRCNN total loss: 0.07751 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.0004 Mask loss: 0.09247 RPN box loss: 0.00401 RPN score loss: 0.00181 RPN total loss: 0.00582 Total loss: 0.76535 timestamp: 1654971941.7760253 iteration: 74055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07775 FastRCNN class loss: 0.04465 FastRCNN total loss: 0.1224 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.0004 Mask loss: 0.11778 RPN box loss: 0.0225 RPN score loss: 0.00621 RPN total loss: 0.02871 Total loss: 0.85844 timestamp: 1654971944.9955158 iteration: 74060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17135 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.24055 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.0004 Mask loss: 0.12209 RPN box loss: 0.01754 RPN score loss: 0.00274 RPN total loss: 0.02028 Total loss: 0.97248 timestamp: 1654971948.2349842 iteration: 74065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08005 FastRCNN class loss: 0.04792 FastRCNN total loss: 0.12797 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.0004 Mask loss: 0.13379 RPN box loss: 0.01338 RPN score loss: 0.00288 RPN total loss: 0.01626 Total loss: 0.86757 timestamp: 1654971951.4541247 iteration: 74070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07514 FastRCNN class loss: 0.04122 FastRCNN total loss: 0.11637 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.0004 Mask loss: 0.13533 RPN box loss: 0.0038 RPN score loss: 0.0023 RPN total loss: 0.00609 Total loss: 0.84734 timestamp: 1654971954.7480712 iteration: 74075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06608 FastRCNN class loss: 0.05446 FastRCNN total loss: 0.12054 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.0004 Mask loss: 0.13335 RPN box loss: 0.0087 RPN score loss: 0.00524 RPN total loss: 0.01394 Total loss: 0.85738 timestamp: 1654971957.847251 iteration: 74080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07699 FastRCNN class loss: 0.06601 FastRCNN total loss: 0.143 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.0004 Mask loss: 0.14162 RPN box loss: 0.01048 RPN score loss: 0.00259 RPN total loss: 0.01308 Total loss: 0.88724 timestamp: 1654971961.0979645 iteration: 74085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.099 FastRCNN class loss: 0.09839 FastRCNN total loss: 0.19739 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.0004 Mask loss: 0.18157 RPN box loss: 0.01357 RPN score loss: 0.0099 RPN total loss: 0.02346 Total loss: 0.99197 timestamp: 1654971964.2988474 iteration: 74090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.08287 FastRCNN total loss: 0.17248 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.0004 Mask loss: 0.14014 RPN box loss: 0.00642 RPN score loss: 0.00587 RPN total loss: 0.01229 Total loss: 0.91445 timestamp: 1654971967.5182009 iteration: 74095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04399 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.11355 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.0004 Mask loss: 0.10474 RPN box loss: 0.00756 RPN score loss: 0.00525 RPN total loss: 0.01281 Total loss: 0.82064 timestamp: 1654971970.7460506 iteration: 74100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1041 FastRCNN class loss: 0.07072 FastRCNN total loss: 0.17482 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.0004 Mask loss: 0.13339 RPN box loss: 0.02944 RPN score loss: 0.00747 RPN total loss: 0.03691 Total loss: 0.93466 timestamp: 1654971973.9310856 iteration: 74105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11375 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.19482 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.0004 Mask loss: 0.15507 RPN box loss: 0.00685 RPN score loss: 0.00479 RPN total loss: 0.01164 Total loss: 0.95107 timestamp: 1654971977.1700156 iteration: 74110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09195 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.0004 Mask loss: 0.13444 RPN box loss: 0.00732 RPN score loss: 0.00422 RPN total loss: 0.01154 Total loss: 0.89991 timestamp: 1654971980.3530478 iteration: 74115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1016 FastRCNN class loss: 0.09707 FastRCNN total loss: 0.19868 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.1308 RPN box loss: 0.01267 RPN score loss: 0.0066 RPN total loss: 0.01927 Total loss: 0.93828 timestamp: 1654971983.6878462 iteration: 74120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11419 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.18375 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.14323 RPN box loss: 0.01373 RPN score loss: 0.00829 RPN total loss: 0.02202 Total loss: 0.93854 timestamp: 1654971986.8558974 iteration: 74125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15827 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.22569 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.11891 RPN box loss: 0.02359 RPN score loss: 0.00644 RPN total loss: 0.03003 Total loss: 0.96416 timestamp: 1654971990.1267178 iteration: 74130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12623 FastRCNN class loss: 0.15107 FastRCNN total loss: 0.2773 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.23334 RPN box loss: 0.03001 RPN score loss: 0.06758 RPN total loss: 0.0976 Total loss: 1.19777 timestamp: 1654971993.2732193 iteration: 74135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03676 FastRCNN class loss: 0.04126 FastRCNN total loss: 0.07802 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.11103 RPN box loss: 0.02193 RPN score loss: 0.00157 RPN total loss: 0.0235 Total loss: 0.80208 timestamp: 1654971996.4798274 iteration: 74140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1328 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.19376 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.11263 RPN box loss: 0.00878 RPN score loss: 0.00267 RPN total loss: 0.01146 Total loss: 0.90737 timestamp: 1654971999.7032712 iteration: 74145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09905 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.17091 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.0004 Mask loss: 0.13622 RPN box loss: 0.02414 RPN score loss: 0.00747 RPN total loss: 0.0316 Total loss: 0.92826 timestamp: 1654972002.9015963 iteration: 74150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08703 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.1535 L1 loss: 0.0000e+00 L2 loss: 0.58952 Learning rate: 0.0004 Mask loss: 0.14681 RPN box loss: 0.01459 RPN score loss: 0.0133 RPN total loss: 0.0279 Total loss: 0.91773 timestamp: 1654972006.0869482 iteration: 74155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08366 FastRCNN class loss: 0.05982 FastRCNN total loss: 0.14347 L1 loss: 0.0000e+00 L2 loss: 0.58952 Learning rate: 0.0004 Mask loss: 0.1279 RPN box loss: 0.01034 RPN score loss: 0.00183 RPN total loss: 0.01217 Total loss: 0.87307 timestamp: 1654972009.2418895 iteration: 74160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05652 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.11199 L1 loss: 0.0000e+00 L2 loss: 0.58952 Learning rate: 0.0004 Mask loss: 0.07744 RPN box loss: 0.00635 RPN score loss: 0.00295 RPN total loss: 0.00929 Total loss: 0.78825 timestamp: 1654972012.4482832 iteration: 74165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07995 FastRCNN class loss: 0.04746 FastRCNN total loss: 0.12742 L1 loss: 0.0000e+00 L2 loss: 0.58952 Learning rate: 0.0004 Mask loss: 0.15463 RPN box loss: 0.00983 RPN score loss: 0.00953 RPN total loss: 0.01936 Total loss: 0.89092 timestamp: 1654972015.633007 iteration: 74170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1504 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.23073 L1 loss: 0.0000e+00 L2 loss: 0.58952 Learning rate: 0.0004 Mask loss: 0.16135 RPN box loss: 0.01014 RPN score loss: 0.00765 RPN total loss: 0.01779 Total loss: 0.99939 timestamp: 1654972018.7928355 iteration: 74175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05281 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.10827 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.0004 Mask loss: 0.10772 RPN box loss: 0.00776 RPN score loss: 0.00184 RPN total loss: 0.0096 Total loss: 0.8151 timestamp: 1654972021.9632595 iteration: 74180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11294 FastRCNN class loss: 0.04655 FastRCNN total loss: 0.15949 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.0004 Mask loss: 0.13265 RPN box loss: 0.0085 RPN score loss: 0.00641 RPN total loss: 0.01491 Total loss: 0.89655 timestamp: 1654972025.1626208 iteration: 74185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03886 FastRCNN class loss: 0.02422 FastRCNN total loss: 0.06307 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.0004 Mask loss: 0.12668 RPN box loss: 0.00223 RPN score loss: 0.00367 RPN total loss: 0.00589 Total loss: 0.78516 timestamp: 1654972028.3046584 iteration: 74190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09695 FastRCNN class loss: 0.09027 FastRCNN total loss: 0.18721 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.0004 Mask loss: 0.17221 RPN box loss: 0.01565 RPN score loss: 0.00402 RPN total loss: 0.01967 Total loss: 0.9686 timestamp: 1654972031.4908102 iteration: 74195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13335 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.2339 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.0004 Mask loss: 0.1595 RPN box loss: 0.01735 RPN score loss: 0.00504 RPN total loss: 0.0224 Total loss: 1.00531 timestamp: 1654972034.6121693 iteration: 74200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0898 FastRCNN class loss: 0.06985 FastRCNN total loss: 0.15965 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.0004 Mask loss: 0.12416 RPN box loss: 0.01519 RPN score loss: 0.02116 RPN total loss: 0.03635 Total loss: 0.90966 timestamp: 1654972037.811605 iteration: 74205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09148 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.16246 L1 loss: 0.0000e+00 L2 loss: 0.5895 Learning rate: 0.0004 Mask loss: 0.14025 RPN box loss: 0.00773 RPN score loss: 0.00202 RPN total loss: 0.00976 Total loss: 0.90197 timestamp: 1654972041.0278842 iteration: 74210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.04315 FastRCNN total loss: 0.14378 L1 loss: 0.0000e+00 L2 loss: 0.5895 Learning rate: 0.0004 Mask loss: 0.09089 RPN box loss: 0.00697 RPN score loss: 0.00494 RPN total loss: 0.01191 Total loss: 0.83608 timestamp: 1654972044.2420907 iteration: 74215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04304 FastRCNN class loss: 0.04022 FastRCNN total loss: 0.08326 L1 loss: 0.0000e+00 L2 loss: 0.5895 Learning rate: 0.0004 Mask loss: 0.14446 RPN box loss: 0.00326 RPN score loss: 0.00154 RPN total loss: 0.0048 Total loss: 0.82201 timestamp: 1654972047.48484 iteration: 74220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06869 FastRCNN class loss: 0.05251 FastRCNN total loss: 0.1212 L1 loss: 0.0000e+00 L2 loss: 0.5895 Learning rate: 0.0004 Mask loss: 0.11114 RPN box loss: 0.00715 RPN score loss: 0.00413 RPN total loss: 0.01128 Total loss: 0.83312 timestamp: 1654972050.7196183 iteration: 74225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10884 FastRCNN class loss: 0.05755 FastRCNN total loss: 0.16639 L1 loss: 0.0000e+00 L2 loss: 0.5895 Learning rate: 0.0004 Mask loss: 0.10504 RPN box loss: 0.01044 RPN score loss: 0.00543 RPN total loss: 0.01586 Total loss: 0.87679 timestamp: 1654972054.0041065 iteration: 74230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12791 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.1924 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.09724 RPN box loss: 0.00457 RPN score loss: 0.0032 RPN total loss: 0.00777 Total loss: 0.8869 timestamp: 1654972057.2033048 iteration: 74235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.21016 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.16058 RPN box loss: 0.01228 RPN score loss: 0.00176 RPN total loss: 0.01404 Total loss: 0.97428 timestamp: 1654972060.324237 iteration: 74240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07605 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.16196 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.16185 RPN box loss: 0.01461 RPN score loss: 0.0038 RPN total loss: 0.01841 Total loss: 0.93171 timestamp: 1654972063.505252 iteration: 74245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06117 FastRCNN class loss: 0.03866 FastRCNN total loss: 0.09983 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.11709 RPN box loss: 0.0126 RPN score loss: 0.0078 RPN total loss: 0.0204 Total loss: 0.82681 timestamp: 1654972066.6985817 iteration: 74250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06626 FastRCNN class loss: 0.05775 FastRCNN total loss: 0.12401 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.11114 RPN box loss: 0.00553 RPN score loss: 0.00226 RPN total loss: 0.00779 Total loss: 0.83243 timestamp: 1654972069.8250601 iteration: 74255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13002 FastRCNN class loss: 0.05626 FastRCNN total loss: 0.18628 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.09306 RPN box loss: 0.00632 RPN score loss: 0.00504 RPN total loss: 0.01136 Total loss: 0.88018 timestamp: 1654972073.036105 iteration: 74260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05761 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.13733 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.0004 Mask loss: 0.1405 RPN box loss: 0.00786 RPN score loss: 0.00203 RPN total loss: 0.00989 Total loss: 0.8772 timestamp: 1654972076.215673 iteration: 74265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06507 FastRCNN class loss: 0.08424 FastRCNN total loss: 0.14931 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.0004 Mask loss: 0.09799 RPN box loss: 0.0108 RPN score loss: 0.00885 RPN total loss: 0.01964 Total loss: 0.85643 timestamp: 1654972079.3960845 iteration: 74270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07711 FastRCNN class loss: 0.06965 FastRCNN total loss: 0.14677 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.0004 Mask loss: 0.14284 RPN box loss: 0.00888 RPN score loss: 0.00527 RPN total loss: 0.01415 Total loss: 0.89325 timestamp: 1654972082.5969896 iteration: 74275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12258 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.18905 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.0004 Mask loss: 0.11997 RPN box loss: 0.00865 RPN score loss: 0.00128 RPN total loss: 0.00993 Total loss: 0.90843 timestamp: 1654972085.7802725 iteration: 74280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09077 FastRCNN class loss: 0.0383 FastRCNN total loss: 0.12907 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.0004 Mask loss: 0.12125 RPN box loss: 0.00948 RPN score loss: 0.00594 RPN total loss: 0.01541 Total loss: 0.85521 timestamp: 1654972089.028062 iteration: 74285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.07947 FastRCNN total loss: 0.18014 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.0004 Mask loss: 0.17114 RPN box loss: 0.01945 RPN score loss: 0.00414 RPN total loss: 0.0236 Total loss: 0.96436 timestamp: 1654972092.2624185 iteration: 74290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08347 FastRCNN class loss: 0.04941 FastRCNN total loss: 0.13287 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.0004 Mask loss: 0.1447 RPN box loss: 0.01143 RPN score loss: 0.00248 RPN total loss: 0.01392 Total loss: 0.88096 timestamp: 1654972095.4767108 iteration: 74295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08581 FastRCNN class loss: 0.04896 FastRCNN total loss: 0.13477 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.0004 Mask loss: 0.11529 RPN box loss: 0.00896 RPN score loss: 0.00212 RPN total loss: 0.01109 Total loss: 0.85062 timestamp: 1654972098.601782 iteration: 74300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08507 FastRCNN class loss: 0.06008 FastRCNN total loss: 0.14514 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.0004 Mask loss: 0.14568 RPN box loss: 0.00883 RPN score loss: 0.00593 RPN total loss: 0.01477 Total loss: 0.89506 timestamp: 1654972101.7860322 iteration: 74305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06675 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.1231 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.0004 Mask loss: 0.1021 RPN box loss: 0.0037 RPN score loss: 0.00599 RPN total loss: 0.00968 Total loss: 0.82436 timestamp: 1654972104.9704356 iteration: 74310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09607 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.17456 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.0004 Mask loss: 0.12912 RPN box loss: 0.01561 RPN score loss: 0.00245 RPN total loss: 0.01807 Total loss: 0.91122 timestamp: 1654972108.169246 iteration: 74315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.06175 FastRCNN total loss: 0.14494 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.0004 Mask loss: 0.14366 RPN box loss: 0.02459 RPN score loss: 0.0083 RPN total loss: 0.03289 Total loss: 0.91096 timestamp: 1654972111.3959007 iteration: 74320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13169 FastRCNN class loss: 0.08892 FastRCNN total loss: 0.2206 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.0004 Mask loss: 0.13904 RPN box loss: 0.02729 RPN score loss: 0.00969 RPN total loss: 0.03698 Total loss: 0.98609 timestamp: 1654972114.591342 iteration: 74325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09783 FastRCNN class loss: 0.08722 FastRCNN total loss: 0.18506 L1 loss: 0.0000e+00 L2 loss: 0.58946 Learning rate: 0.0004 Mask loss: 0.11258 RPN box loss: 0.0132 RPN score loss: 0.01699 RPN total loss: 0.03019 Total loss: 0.91729 timestamp: 1654972117.716344 iteration: 74330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.06884 FastRCNN total loss: 0.14749 L1 loss: 0.0000e+00 L2 loss: 0.58946 Learning rate: 0.0004 Mask loss: 0.13414 RPN box loss: 0.01983 RPN score loss: 0.00228 RPN total loss: 0.02211 Total loss: 0.89321 timestamp: 1654972120.869976 iteration: 74335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13635 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.20021 L1 loss: 0.0000e+00 L2 loss: 0.58946 Learning rate: 0.0004 Mask loss: 0.127 RPN box loss: 0.02871 RPN score loss: 0.00441 RPN total loss: 0.03312 Total loss: 0.94979 timestamp: 1654972124.0523803 iteration: 74340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0818 FastRCNN class loss: 0.02417 FastRCNN total loss: 0.10597 L1 loss: 0.0000e+00 L2 loss: 0.58946 Learning rate: 0.0004 Mask loss: 0.08878 RPN box loss: 0.00964 RPN score loss: 0.0025 RPN total loss: 0.01214 Total loss: 0.79635 timestamp: 1654972127.2589846 iteration: 74345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07389 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.14101 L1 loss: 0.0000e+00 L2 loss: 0.58946 Learning rate: 0.0004 Mask loss: 0.09112 RPN box loss: 0.01531 RPN score loss: 0.00154 RPN total loss: 0.01685 Total loss: 0.83844 timestamp: 1654972130.5077882 iteration: 74350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12764 FastRCNN class loss: 0.09246 FastRCNN total loss: 0.2201 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.0004 Mask loss: 0.18153 RPN box loss: 0.02127 RPN score loss: 0.01611 RPN total loss: 0.03738 Total loss: 1.02847 timestamp: 1654972133.6991336 iteration: 74355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0855 FastRCNN class loss: 0.05223 FastRCNN total loss: 0.13773 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.0004 Mask loss: 0.15054 RPN box loss: 0.00795 RPN score loss: 0.00242 RPN total loss: 0.01036 Total loss: 0.88809 timestamp: 1654972136.887164 iteration: 74360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06797 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.12247 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.0004 Mask loss: 0.1101 RPN box loss: 0.01224 RPN score loss: 0.00145 RPN total loss: 0.01369 Total loss: 0.83571 timestamp: 1654972140.085314 iteration: 74365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09448 FastRCNN class loss: 0.04315 FastRCNN total loss: 0.13763 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.0004 Mask loss: 0.11039 RPN box loss: 0.01732 RPN score loss: 0.00305 RPN total loss: 0.02037 Total loss: 0.85784 timestamp: 1654972143.2499979 iteration: 74370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0833 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.16137 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.0004 Mask loss: 0.14179 RPN box loss: 0.00924 RPN score loss: 0.00682 RPN total loss: 0.01606 Total loss: 0.90867 timestamp: 1654972146.4136062 iteration: 74375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11193 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.19078 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.0004 Mask loss: 0.15431 RPN box loss: 0.01159 RPN score loss: 0.00308 RPN total loss: 0.01466 Total loss: 0.94919 timestamp: 1654972149.6370049 iteration: 74380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05022 FastRCNN class loss: 0.05466 FastRCNN total loss: 0.10488 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.10362 RPN box loss: 0.0049 RPN score loss: 0.00507 RPN total loss: 0.00997 Total loss: 0.80792 timestamp: 1654972152.880136 iteration: 74385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07742 FastRCNN class loss: 0.06822 FastRCNN total loss: 0.14564 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.14543 RPN box loss: 0.00724 RPN score loss: 0.00508 RPN total loss: 0.01231 Total loss: 0.89283 timestamp: 1654972156.0653083 iteration: 74390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09188 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.14736 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.10491 RPN box loss: 0.00786 RPN score loss: 0.00128 RPN total loss: 0.00914 Total loss: 0.85085 timestamp: 1654972159.2738788 iteration: 74395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08452 FastRCNN class loss: 0.09225 FastRCNN total loss: 0.17677 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.14838 RPN box loss: 0.01467 RPN score loss: 0.00509 RPN total loss: 0.01975 Total loss: 0.93434 timestamp: 1654972162.4805508 iteration: 74400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06446 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.13575 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.09992 RPN box loss: 0.00907 RPN score loss: 0.00407 RPN total loss: 0.01313 Total loss: 0.83824 timestamp: 1654972165.7216933 iteration: 74405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08211 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.13354 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.21776 RPN box loss: 0.01653 RPN score loss: 0.00163 RPN total loss: 0.01816 Total loss: 0.9589 timestamp: 1654972168.8910418 iteration: 74410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09942 FastRCNN class loss: 0.07123 FastRCNN total loss: 0.17065 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.0004 Mask loss: 0.16701 RPN box loss: 0.01279 RPN score loss: 0.00399 RPN total loss: 0.01678 Total loss: 0.94388 timestamp: 1654972172.116538 iteration: 74415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09758 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.16896 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.0004 Mask loss: 0.18776 RPN box loss: 0.03253 RPN score loss: 0.00887 RPN total loss: 0.04139 Total loss: 0.98754 timestamp: 1654972175.3710704 iteration: 74420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09907 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.15853 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.0004 Mask loss: 0.10776 RPN box loss: 0.00376 RPN score loss: 0.00086 RPN total loss: 0.00462 Total loss: 0.86034 timestamp: 1654972178.5766587 iteration: 74425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05915 FastRCNN class loss: 0.05031 FastRCNN total loss: 0.10947 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.0004 Mask loss: 0.10894 RPN box loss: 0.0103 RPN score loss: 0.00581 RPN total loss: 0.01611 Total loss: 0.82394 timestamp: 1654972181.8604224 iteration: 74430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12494 FastRCNN class loss: 0.06594 FastRCNN total loss: 0.19089 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.0004 Mask loss: 0.11791 RPN box loss: 0.02013 RPN score loss: 0.00286 RPN total loss: 0.02299 Total loss: 0.92122 timestamp: 1654972185.0341818 iteration: 74435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.16841 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.0004 Mask loss: 0.15869 RPN box loss: 0.03551 RPN score loss: 0.00676 RPN total loss: 0.04226 Total loss: 0.95878 timestamp: 1654972188.2202067 iteration: 74440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07269 FastRCNN class loss: 0.07133 FastRCNN total loss: 0.14402 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.0004 Mask loss: 0.12548 RPN box loss: 0.00927 RPN score loss: 0.00627 RPN total loss: 0.01553 Total loss: 0.87446 timestamp: 1654972191.4507523 iteration: 74445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12196 FastRCNN class loss: 0.08841 FastRCNN total loss: 0.21037 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.16308 RPN box loss: 0.01806 RPN score loss: 0.00841 RPN total loss: 0.02646 Total loss: 0.98934 timestamp: 1654972194.5902114 iteration: 74450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05288 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.12682 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.12296 RPN box loss: 0.02039 RPN score loss: 0.01524 RPN total loss: 0.03563 Total loss: 0.87483 timestamp: 1654972197.7959282 iteration: 74455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07361 FastRCNN class loss: 0.0483 FastRCNN total loss: 0.12191 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.15722 RPN box loss: 0.00914 RPN score loss: 0.01787 RPN total loss: 0.02701 Total loss: 0.89556 timestamp: 1654972201.0553453 iteration: 74460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.08422 FastRCNN total loss: 0.19652 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.14732 RPN box loss: 0.00716 RPN score loss: 0.00585 RPN total loss: 0.01301 Total loss: 0.94627 timestamp: 1654972204.2039688 iteration: 74465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07662 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.14238 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.10539 RPN box loss: 0.01818 RPN score loss: 0.00452 RPN total loss: 0.0227 Total loss: 0.8599 timestamp: 1654972207.356673 iteration: 74470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.08159 FastRCNN total loss: 0.17669 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.1595 RPN box loss: 0.00854 RPN score loss: 0.00797 RPN total loss: 0.0165 Total loss: 0.94211 timestamp: 1654972210.5591624 iteration: 74475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10798 FastRCNN class loss: 0.09376 FastRCNN total loss: 0.20174 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.0004 Mask loss: 0.12835 RPN box loss: 0.00632 RPN score loss: 0.0044 RPN total loss: 0.01072 Total loss: 0.93023 timestamp: 1654972213.7573173 iteration: 74480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07425 FastRCNN class loss: 0.06596 FastRCNN total loss: 0.14021 L1 loss: 0.0000e+00 L2 loss: 0.58941 Learning rate: 0.0004 Mask loss: 0.14518 RPN box loss: 0.0138 RPN score loss: 0.00568 RPN total loss: 0.01948 Total loss: 0.89429 timestamp: 1654972216.893426 iteration: 74485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08124 FastRCNN class loss: 0.04525 FastRCNN total loss: 0.1265 L1 loss: 0.0000e+00 L2 loss: 0.58941 Learning rate: 0.0004 Mask loss: 0.07216 RPN box loss: 0.00805 RPN score loss: 0.00129 RPN total loss: 0.00934 Total loss: 0.79741 timestamp: 1654972220.057364 iteration: 74490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06274 FastRCNN class loss: 0.04637 FastRCNN total loss: 0.10911 L1 loss: 0.0000e+00 L2 loss: 0.58941 Learning rate: 0.0004 Mask loss: 0.07628 RPN box loss: 0.00548 RPN score loss: 0.00111 RPN total loss: 0.0066 Total loss: 0.7814 timestamp: 1654972223.2961526 iteration: 74495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05802 FastRCNN class loss: 0.04511 FastRCNN total loss: 0.10313 L1 loss: 0.0000e+00 L2 loss: 0.58941 Learning rate: 0.0004 Mask loss: 0.10755 RPN box loss: 0.013 RPN score loss: 0.00551 RPN total loss: 0.01851 Total loss: 0.8186 timestamp: 1654972226.4213848 iteration: 74500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06055 FastRCNN class loss: 0.04511 FastRCNN total loss: 0.10566 L1 loss: 0.0000e+00 L2 loss: 0.58941 Learning rate: 0.0004 Mask loss: 0.10164 RPN box loss: 0.00462 RPN score loss: 0.0052 RPN total loss: 0.00983 Total loss: 0.80653 timestamp: 1654972229.60172 iteration: 74505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0826 FastRCNN class loss: 0.08452 FastRCNN total loss: 0.16712 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.15167 RPN box loss: 0.02708 RPN score loss: 0.00393 RPN total loss: 0.03101 Total loss: 0.93921 timestamp: 1654972232.7632725 iteration: 74510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1202 FastRCNN class loss: 0.06236 FastRCNN total loss: 0.18256 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.16249 RPN box loss: 0.01439 RPN score loss: 0.00189 RPN total loss: 0.01628 Total loss: 0.95073 timestamp: 1654972235.9830532 iteration: 74515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13364 FastRCNN class loss: 0.07422 FastRCNN total loss: 0.20786 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.18108 RPN box loss: 0.01603 RPN score loss: 0.00893 RPN total loss: 0.02495 Total loss: 1.0033 timestamp: 1654972239.2333868 iteration: 74520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11393 FastRCNN class loss: 0.05706 FastRCNN total loss: 0.17099 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.13578 RPN box loss: 0.01404 RPN score loss: 0.0075 RPN total loss: 0.02154 Total loss: 0.91771 timestamp: 1654972242.4226289 iteration: 74525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08779 FastRCNN class loss: 0.07808 FastRCNN total loss: 0.16587 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.17233 RPN box loss: 0.01227 RPN score loss: 0.00116 RPN total loss: 0.01342 Total loss: 0.94102 timestamp: 1654972245.5935912 iteration: 74530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0424 FastRCNN class loss: 0.03579 FastRCNN total loss: 0.07819 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.07834 RPN box loss: 0.00658 RPN score loss: 0.00115 RPN total loss: 0.00773 Total loss: 0.75365 timestamp: 1654972248.7939143 iteration: 74535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07243 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.1365 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.0004 Mask loss: 0.11269 RPN box loss: 0.0181 RPN score loss: 0.00274 RPN total loss: 0.02084 Total loss: 0.85943 timestamp: 1654972251.9651823 iteration: 74540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06477 FastRCNN class loss: 0.0953 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.0004 Mask loss: 0.16622 RPN box loss: 0.01267 RPN score loss: 0.0219 RPN total loss: 0.03457 Total loss: 0.95025 timestamp: 1654972255.0922046 iteration: 74545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08167 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.16218 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.0004 Mask loss: 0.08699 RPN box loss: 0.00644 RPN score loss: 0.00301 RPN total loss: 0.00945 Total loss: 0.84801 timestamp: 1654972258.279517 iteration: 74550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13904 FastRCNN class loss: 0.05459 FastRCNN total loss: 0.19363 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.0004 Mask loss: 0.11678 RPN box loss: 0.00378 RPN score loss: 0.00344 RPN total loss: 0.00722 Total loss: 0.90703 timestamp: 1654972261.4760664 iteration: 74555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07059 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.13991 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.0004 Mask loss: 0.12408 RPN box loss: 0.01145 RPN score loss: 0.00334 RPN total loss: 0.01479 Total loss: 0.86816 timestamp: 1654972264.634356 iteration: 74560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16947 FastRCNN class loss: 0.12055 FastRCNN total loss: 0.29001 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.0004 Mask loss: 0.19899 RPN box loss: 0.01173 RPN score loss: 0.01133 RPN total loss: 0.02306 Total loss: 1.10145 timestamp: 1654972267.9021263 iteration: 74565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04649 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.1124 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.0004 Mask loss: 0.13269 RPN box loss: 0.01701 RPN score loss: 0.00591 RPN total loss: 0.02292 Total loss: 0.8574 timestamp: 1654972271.1232889 iteration: 74570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07784 FastRCNN class loss: 0.04724 FastRCNN total loss: 0.12507 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.0004 Mask loss: 0.08909 RPN box loss: 0.04821 RPN score loss: 0.00611 RPN total loss: 0.05431 Total loss: 0.85786 timestamp: 1654972274.3427212 iteration: 74575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07799 FastRCNN class loss: 0.05114 FastRCNN total loss: 0.12913 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.0004 Mask loss: 0.11866 RPN box loss: 0.00383 RPN score loss: 0.00464 RPN total loss: 0.00847 Total loss: 0.84565 timestamp: 1654972277.528096 iteration: 74580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06647 FastRCNN class loss: 0.05065 FastRCNN total loss: 0.11712 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.0004 Mask loss: 0.12505 RPN box loss: 0.00824 RPN score loss: 0.00461 RPN total loss: 0.01285 Total loss: 0.84441 timestamp: 1654972280.7111409 iteration: 74585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03482 FastRCNN class loss: 0.0285 FastRCNN total loss: 0.06331 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.0004 Mask loss: 0.08319 RPN box loss: 0.00112 RPN score loss: 0.00296 RPN total loss: 0.00408 Total loss: 0.73996 timestamp: 1654972283.8056564 iteration: 74590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05424 FastRCNN class loss: 0.0382 FastRCNN total loss: 0.09244 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.0004 Mask loss: 0.07444 RPN box loss: 0.0027 RPN score loss: 0.00102 RPN total loss: 0.00371 Total loss: 0.75997 timestamp: 1654972287.008724 iteration: 74595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.05335 FastRCNN total loss: 0.14285 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.0004 Mask loss: 0.12255 RPN box loss: 0.00658 RPN score loss: 0.00224 RPN total loss: 0.00882 Total loss: 0.8636 timestamp: 1654972290.2133956 iteration: 74600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.05719 FastRCNN total loss: 0.16366 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.0004 Mask loss: 0.12048 RPN box loss: 0.00434 RPN score loss: 0.00395 RPN total loss: 0.00829 Total loss: 0.88181 timestamp: 1654972293.4262707 iteration: 74605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04948 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.12007 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.0004 Mask loss: 0.13445 RPN box loss: 0.00836 RPN score loss: 0.00684 RPN total loss: 0.01521 Total loss: 0.8591 timestamp: 1654972296.6097064 iteration: 74610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13774 FastRCNN class loss: 0.08996 FastRCNN total loss: 0.2277 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.0004 Mask loss: 0.12425 RPN box loss: 0.00815 RPN score loss: 0.00395 RPN total loss: 0.0121 Total loss: 0.95342 timestamp: 1654972299.7618635 iteration: 74615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07307 FastRCNN class loss: 0.08047 FastRCNN total loss: 0.15353 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.0004 Mask loss: 0.14061 RPN box loss: 0.01545 RPN score loss: 0.00916 RPN total loss: 0.02462 Total loss: 0.90813 timestamp: 1654972302.9601557 iteration: 74620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11781 FastRCNN class loss: 0.07485 FastRCNN total loss: 0.19266 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.0004 Mask loss: 0.12104 RPN box loss: 0.0097 RPN score loss: 0.00537 RPN total loss: 0.01507 Total loss: 0.91813 timestamp: 1654972306.195827 iteration: 74625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14525 FastRCNN class loss: 0.12769 FastRCNN total loss: 0.27293 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.0004 Mask loss: 0.1392 RPN box loss: 0.01907 RPN score loss: 0.00536 RPN total loss: 0.02444 Total loss: 1.02594 timestamp: 1654972309.3869529 iteration: 74630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11086 FastRCNN class loss: 0.07367 FastRCNN total loss: 0.18453 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.0004 Mask loss: 0.16 RPN box loss: 0.01137 RPN score loss: 0.00821 RPN total loss: 0.01957 Total loss: 0.95347 timestamp: 1654972312.582268 iteration: 74635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09623 FastRCNN class loss: 0.05588 FastRCNN total loss: 0.15211 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.0004 Mask loss: 0.14594 RPN box loss: 0.01532 RPN score loss: 0.0061 RPN total loss: 0.02142 Total loss: 0.90882 timestamp: 1654972315.7276764 iteration: 74640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07786 FastRCNN class loss: 0.06078 FastRCNN total loss: 0.13863 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.0004 Mask loss: 0.12465 RPN box loss: 0.01042 RPN score loss: 0.00605 RPN total loss: 0.01647 Total loss: 0.86912 timestamp: 1654972318.9193609 iteration: 74645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09394 FastRCNN class loss: 0.09282 FastRCNN total loss: 0.18677 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.0004 Mask loss: 0.11817 RPN box loss: 0.00754 RPN score loss: 0.00406 RPN total loss: 0.0116 Total loss: 0.90589 timestamp: 1654972322.1027288 iteration: 74650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09066 FastRCNN class loss: 0.05541 FastRCNN total loss: 0.14607 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.0004 Mask loss: 0.10221 RPN box loss: 0.01052 RPN score loss: 0.00368 RPN total loss: 0.0142 Total loss: 0.85183 timestamp: 1654972325.3088574 iteration: 74655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08026 FastRCNN class loss: 0.04507 FastRCNN total loss: 0.12534 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.0004 Mask loss: 0.11909 RPN box loss: 0.01217 RPN score loss: 0.00092 RPN total loss: 0.01309 Total loss: 0.84687 timestamp: 1654972328.495231 iteration: 74660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09344 FastRCNN class loss: 0.09851 FastRCNN total loss: 0.19195 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.0004 Mask loss: 0.10004 RPN box loss: 0.01586 RPN score loss: 0.0078 RPN total loss: 0.02366 Total loss: 0.90501 timestamp: 1654972331.8236656 iteration: 74665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.13355 FastRCNN total loss: 0.22812 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.0004 Mask loss: 0.13448 RPN box loss: 0.01371 RPN score loss: 0.00548 RPN total loss: 0.01919 Total loss: 0.97115 timestamp: 1654972335.1008062 iteration: 74670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04852 FastRCNN class loss: 0.0308 FastRCNN total loss: 0.07932 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.0004 Mask loss: 0.08319 RPN box loss: 0.00724 RPN score loss: 0.00254 RPN total loss: 0.00977 Total loss: 0.76163 timestamp: 1654972338.217732 iteration: 74675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10605 FastRCNN class loss: 0.08012 FastRCNN total loss: 0.18617 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.0004 Mask loss: 0.13645 RPN box loss: 0.02091 RPN score loss: 0.00836 RPN total loss: 0.02927 Total loss: 0.94125 timestamp: 1654972341.44516 iteration: 74680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14411 FastRCNN class loss: 0.10303 FastRCNN total loss: 0.24714 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.0004 Mask loss: 0.15243 RPN box loss: 0.01932 RPN score loss: 0.00852 RPN total loss: 0.02784 Total loss: 1.01675 timestamp: 1654972344.7146533 iteration: 74685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.1663 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.0004 Mask loss: 0.15417 RPN box loss: 0.01115 RPN score loss: 0.00559 RPN total loss: 0.01675 Total loss: 0.92656 timestamp: 1654972347.844494 iteration: 74690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04495 FastRCNN class loss: 0.05683 FastRCNN total loss: 0.10178 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.13329 RPN box loss: 0.00815 RPN score loss: 0.00172 RPN total loss: 0.00987 Total loss: 0.83429 timestamp: 1654972351.107594 iteration: 74695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07067 FastRCNN class loss: 0.09949 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.12259 RPN box loss: 0.00576 RPN score loss: 0.00743 RPN total loss: 0.01319 Total loss: 0.89528 timestamp: 1654972354.342491 iteration: 74700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15131 FastRCNN class loss: 0.10047 FastRCNN total loss: 0.25178 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.17393 RPN box loss: 0.01463 RPN score loss: 0.00865 RPN total loss: 0.02328 Total loss: 1.03833 timestamp: 1654972357.4681354 iteration: 74705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0738 FastRCNN class loss: 0.0441 FastRCNN total loss: 0.1179 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.10213 RPN box loss: 0.01004 RPN score loss: 0.00124 RPN total loss: 0.01128 Total loss: 0.82065 timestamp: 1654972360.627733 iteration: 74710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10355 FastRCNN class loss: 0.08674 FastRCNN total loss: 0.19029 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.13825 RPN box loss: 0.02167 RPN score loss: 0.00866 RPN total loss: 0.03033 Total loss: 0.94821 timestamp: 1654972363.8556235 iteration: 74715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11894 FastRCNN class loss: 0.0547 FastRCNN total loss: 0.17363 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.11948 RPN box loss: 0.00459 RPN score loss: 0.00201 RPN total loss: 0.0066 Total loss: 0.88904 timestamp: 1654972367.0651307 iteration: 74720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08016 FastRCNN class loss: 0.05428 FastRCNN total loss: 0.13444 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.0004 Mask loss: 0.12303 RPN box loss: 0.00833 RPN score loss: 0.00533 RPN total loss: 0.01366 Total loss: 0.86046 timestamp: 1654972370.2265887 iteration: 74725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11567 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.18015 L1 loss: 0.0000e+00 L2 loss: 0.58933 Learning rate: 0.0004 Mask loss: 0.12544 RPN box loss: 0.01904 RPN score loss: 0.00391 RPN total loss: 0.02296 Total loss: 0.91787 timestamp: 1654972373.3992314 iteration: 74730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12377 FastRCNN class loss: 0.09768 FastRCNN total loss: 0.22145 L1 loss: 0.0000e+00 L2 loss: 0.58933 Learning rate: 0.0004 Mask loss: 0.138 RPN box loss: 0.01282 RPN score loss: 0.00532 RPN total loss: 0.01814 Total loss: 0.96693 timestamp: 1654972376.599474 iteration: 74735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04645 FastRCNN class loss: 0.0406 FastRCNN total loss: 0.08706 L1 loss: 0.0000e+00 L2 loss: 0.58933 Learning rate: 0.0004 Mask loss: 0.12057 RPN box loss: 0.00728 RPN score loss: 0.00143 RPN total loss: 0.00871 Total loss: 0.80567 timestamp: 1654972379.7360961 iteration: 74740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10946 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.19362 L1 loss: 0.0000e+00 L2 loss: 0.58933 Learning rate: 0.0004 Mask loss: 0.11371 RPN box loss: 0.0181 RPN score loss: 0.00354 RPN total loss: 0.02164 Total loss: 0.9183 timestamp: 1654972382.9343047 iteration: 74745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09904 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.1715 L1 loss: 0.0000e+00 L2 loss: 0.58933 Learning rate: 0.0004 Mask loss: 0.13423 RPN box loss: 0.01368 RPN score loss: 0.00322 RPN total loss: 0.0169 Total loss: 0.91196 timestamp: 1654972386.249224 iteration: 74750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0804 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.15854 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.11182 RPN box loss: 0.00791 RPN score loss: 0.00405 RPN total loss: 0.01195 Total loss: 0.87164 timestamp: 1654972389.430999 iteration: 74755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04637 FastRCNN class loss: 0.05939 FastRCNN total loss: 0.10576 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.14621 RPN box loss: 0.01095 RPN score loss: 0.00929 RPN total loss: 0.02024 Total loss: 0.86153 timestamp: 1654972392.5780072 iteration: 74760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08959 FastRCNN class loss: 0.06482 FastRCNN total loss: 0.15442 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.17725 RPN box loss: 0.0171 RPN score loss: 0.00716 RPN total loss: 0.02425 Total loss: 0.94525 timestamp: 1654972395.7878683 iteration: 74765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07009 FastRCNN class loss: 0.05093 FastRCNN total loss: 0.12102 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.09653 RPN box loss: 0.00555 RPN score loss: 0.00825 RPN total loss: 0.0138 Total loss: 0.82066 timestamp: 1654972399.0179665 iteration: 74770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10504 FastRCNN class loss: 0.11715 FastRCNN total loss: 0.22219 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.20134 RPN box loss: 0.01415 RPN score loss: 0.0055 RPN total loss: 0.01965 Total loss: 1.0325 timestamp: 1654972402.207393 iteration: 74775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10677 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.1643 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.23313 RPN box loss: 0.01924 RPN score loss: 0.00568 RPN total loss: 0.02493 Total loss: 1.01168 timestamp: 1654972405.378752 iteration: 74780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05302 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.11056 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.0004 Mask loss: 0.11518 RPN box loss: 0.00802 RPN score loss: 0.00808 RPN total loss: 0.0161 Total loss: 0.83115 timestamp: 1654972408.5710568 iteration: 74785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0724 FastRCNN class loss: 0.04951 FastRCNN total loss: 0.12191 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.0004 Mask loss: 0.1205 RPN box loss: 0.06586 RPN score loss: 0.0072 RPN total loss: 0.07305 Total loss: 0.90477 timestamp: 1654972411.758744 iteration: 74790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06432 FastRCNN class loss: 0.04512 FastRCNN total loss: 0.10944 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.0004 Mask loss: 0.14634 RPN box loss: 0.01116 RPN score loss: 0.00227 RPN total loss: 0.01343 Total loss: 0.85853 timestamp: 1654972414.95989 iteration: 74795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06952 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.13015 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.0004 Mask loss: 0.181 RPN box loss: 0.00785 RPN score loss: 0.00725 RPN total loss: 0.01511 Total loss: 0.91556 timestamp: 1654972418.1591535 iteration: 74800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09512 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.16473 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.0004 Mask loss: 0.14768 RPN box loss: 0.00953 RPN score loss: 0.00406 RPN total loss: 0.01359 Total loss: 0.91531 timestamp: 1654972421.4174712 iteration: 74805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0891 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.15377 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.0004 Mask loss: 0.14507 RPN box loss: 0.01834 RPN score loss: 0.00503 RPN total loss: 0.02337 Total loss: 0.91152 timestamp: 1654972424.5469398 iteration: 74810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12722 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.18906 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.0004 Mask loss: 0.11355 RPN box loss: 0.01703 RPN score loss: 0.0021 RPN total loss: 0.01913 Total loss: 0.91106 timestamp: 1654972427.7137587 iteration: 74815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03963 FastRCNN class loss: 0.03569 FastRCNN total loss: 0.07533 L1 loss: 0.0000e+00 L2 loss: 0.5893 Learning rate: 0.0004 Mask loss: 0.11304 RPN box loss: 0.0047 RPN score loss: 0.00459 RPN total loss: 0.00929 Total loss: 0.78696 timestamp: 1654972430.8259022 iteration: 74820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04632 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.0913 L1 loss: 0.0000e+00 L2 loss: 0.5893 Learning rate: 0.0004 Mask loss: 0.08493 RPN box loss: 0.00847 RPN score loss: 0.00328 RPN total loss: 0.01175 Total loss: 0.77728 timestamp: 1654972434.0558014 iteration: 74825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1361 FastRCNN class loss: 0.10804 FastRCNN total loss: 0.24413 L1 loss: 0.0000e+00 L2 loss: 0.5893 Learning rate: 0.0004 Mask loss: 0.22861 RPN box loss: 0.01184 RPN score loss: 0.00349 RPN total loss: 0.01533 Total loss: 1.07738 timestamp: 1654972437.2844574 iteration: 74830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0893 FastRCNN class loss: 0.04196 FastRCNN total loss: 0.13126 L1 loss: 0.0000e+00 L2 loss: 0.5893 Learning rate: 0.0004 Mask loss: 0.10864 RPN box loss: 0.00528 RPN score loss: 0.0043 RPN total loss: 0.00958 Total loss: 0.83878 timestamp: 1654972440.4841132 iteration: 74835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09352 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.17496 L1 loss: 0.0000e+00 L2 loss: 0.5893 Learning rate: 0.0004 Mask loss: 0.13341 RPN box loss: 0.0095 RPN score loss: 0.00802 RPN total loss: 0.01752 Total loss: 0.91518 timestamp: 1654972443.658496 iteration: 74840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06792 FastRCNN class loss: 0.04379 FastRCNN total loss: 0.11171 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.0004 Mask loss: 0.09999 RPN box loss: 0.01013 RPN score loss: 0.00109 RPN total loss: 0.01122 Total loss: 0.81222 timestamp: 1654972446.8938246 iteration: 74845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08653 FastRCNN class loss: 0.03341 FastRCNN total loss: 0.11995 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.0004 Mask loss: 0.11416 RPN box loss: 0.00607 RPN score loss: 0.00175 RPN total loss: 0.00781 Total loss: 0.83122 timestamp: 1654972450.1189222 iteration: 74850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.16515 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.0004 Mask loss: 0.1097 RPN box loss: 0.00714 RPN score loss: 0.00542 RPN total loss: 0.01257 Total loss: 0.87671 timestamp: 1654972453.3150742 iteration: 74855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06613 FastRCNN class loss: 0.04549 FastRCNN total loss: 0.11162 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.0004 Mask loss: 0.13533 RPN box loss: 0.00568 RPN score loss: 0.00423 RPN total loss: 0.0099 Total loss: 0.84615 timestamp: 1654972456.5065587 iteration: 74860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10303 FastRCNN class loss: 0.08557 FastRCNN total loss: 0.1886 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.0004 Mask loss: 0.14495 RPN box loss: 0.01048 RPN score loss: 0.00321 RPN total loss: 0.01369 Total loss: 0.93653 timestamp: 1654972459.7708774 iteration: 74865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10454 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.16783 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.0004 Mask loss: 0.15719 RPN box loss: 0.00723 RPN score loss: 0.01508 RPN total loss: 0.02231 Total loss: 0.93662 timestamp: 1654972462.9471338 iteration: 74870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08669 FastRCNN class loss: 0.05341 FastRCNN total loss: 0.1401 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.0004 Mask loss: 0.09615 RPN box loss: 0.00758 RPN score loss: 0.0023 RPN total loss: 0.00987 Total loss: 0.8354 timestamp: 1654972466.158733 iteration: 74875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0954 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.17502 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.0004 Mask loss: 0.13997 RPN box loss: 0.01115 RPN score loss: 0.00318 RPN total loss: 0.01433 Total loss: 0.91861 timestamp: 1654972469.333817 iteration: 74880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09003 FastRCNN class loss: 0.07849 FastRCNN total loss: 0.16852 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.0004 Mask loss: 0.17352 RPN box loss: 0.01235 RPN score loss: 0.00332 RPN total loss: 0.01567 Total loss: 0.94699 timestamp: 1654972472.5523582 iteration: 74885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1238 FastRCNN class loss: 0.09315 FastRCNN total loss: 0.21694 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.0004 Mask loss: 0.11492 RPN box loss: 0.0327 RPN score loss: 0.00211 RPN total loss: 0.0348 Total loss: 0.95595 timestamp: 1654972475.7671366 iteration: 74890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09213 FastRCNN class loss: 0.0367 FastRCNN total loss: 0.12883 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.0004 Mask loss: 0.07165 RPN box loss: 0.00386 RPN score loss: 0.00343 RPN total loss: 0.00729 Total loss: 0.79705 timestamp: 1654972479.015624 iteration: 74895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06433 FastRCNN class loss: 0.0579 FastRCNN total loss: 0.12223 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.0004 Mask loss: 0.13271 RPN box loss: 0.00739 RPN score loss: 0.00359 RPN total loss: 0.01099 Total loss: 0.8552 timestamp: 1654972482.3160603 iteration: 74900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13069 FastRCNN class loss: 0.06605 FastRCNN total loss: 0.19674 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.11893 RPN box loss: 0.00805 RPN score loss: 0.00365 RPN total loss: 0.0117 Total loss: 0.91665 timestamp: 1654972485.5130477 iteration: 74905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09771 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.17533 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.1173 RPN box loss: 0.01775 RPN score loss: 0.0031 RPN total loss: 0.02085 Total loss: 0.90276 timestamp: 1654972488.723469 iteration: 74910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06029 FastRCNN class loss: 0.04564 FastRCNN total loss: 0.10593 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.09665 RPN box loss: 0.00551 RPN score loss: 0.00327 RPN total loss: 0.00878 Total loss: 0.80064 timestamp: 1654972491.8740904 iteration: 74915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0741 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.14545 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.13694 RPN box loss: 0.00631 RPN score loss: 0.00351 RPN total loss: 0.00982 Total loss: 0.88149 timestamp: 1654972495.1092603 iteration: 74920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07126 FastRCNN class loss: 0.03265 FastRCNN total loss: 0.10391 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.11153 RPN box loss: 0.00504 RPN score loss: 0.00389 RPN total loss: 0.00894 Total loss: 0.81365 timestamp: 1654972498.3387463 iteration: 74925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10581 FastRCNN class loss: 0.04991 FastRCNN total loss: 0.15572 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.11006 RPN box loss: 0.00712 RPN score loss: 0.00216 RPN total loss: 0.00929 Total loss: 0.86434 timestamp: 1654972501.6121383 iteration: 74930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.07286 FastRCNN total loss: 0.14644 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.0004 Mask loss: 0.13537 RPN box loss: 0.02788 RPN score loss: 0.00648 RPN total loss: 0.03436 Total loss: 0.90544 timestamp: 1654972504.8905423 iteration: 74935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06693 FastRCNN class loss: 0.06521 FastRCNN total loss: 0.13214 L1 loss: 0.0000e+00 L2 loss: 0.58926 Learning rate: 0.0004 Mask loss: 0.12529 RPN box loss: 0.00781 RPN score loss: 0.0068 RPN total loss: 0.01461 Total loss: 0.8613 timestamp: 1654972508.0849712 iteration: 74940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12914 FastRCNN class loss: 0.04705 FastRCNN total loss: 0.17619 L1 loss: 0.0000e+00 L2 loss: 0.58926 Learning rate: 0.0004 Mask loss: 0.14906 RPN box loss: 0.00757 RPN score loss: 0.00185 RPN total loss: 0.00942 Total loss: 0.92394 timestamp: 1654972511.2327921 iteration: 74945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09521 FastRCNN class loss: 0.09321 FastRCNN total loss: 0.18842 L1 loss: 0.0000e+00 L2 loss: 0.58926 Learning rate: 0.0004 Mask loss: 0.15016 RPN box loss: 0.01571 RPN score loss: 0.00455 RPN total loss: 0.02025 Total loss: 0.94809 timestamp: 1654972514.4228446 iteration: 74950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10952 FastRCNN class loss: 0.15283 FastRCNN total loss: 0.26236 L1 loss: 0.0000e+00 L2 loss: 0.58926 Learning rate: 0.0004 Mask loss: 0.21889 RPN box loss: 0.01875 RPN score loss: 0.00876 RPN total loss: 0.02751 Total loss: 1.098 timestamp: 1654972517.6395357 iteration: 74955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15272 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.20725 L1 loss: 0.0000e+00 L2 loss: 0.58926 Learning rate: 0.0004 Mask loss: 0.13375 RPN box loss: 0.01398 RPN score loss: 0.00235 RPN total loss: 0.01634 Total loss: 0.9466 timestamp: 1654972520.8649359 iteration: 74960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08016 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.15371 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.0004 Mask loss: 0.13064 RPN box loss: 0.01596 RPN score loss: 0.00115 RPN total loss: 0.01711 Total loss: 0.89072 timestamp: 1654972524.0664866 iteration: 74965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07094 FastRCNN class loss: 0.03618 FastRCNN total loss: 0.10712 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.0004 Mask loss: 0.12542 RPN box loss: 0.00407 RPN score loss: 0.00161 RPN total loss: 0.00568 Total loss: 0.82747 timestamp: 1654972527.3146276 iteration: 74970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.075 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.15729 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.0004 Mask loss: 0.11693 RPN box loss: 0.00956 RPN score loss: 0.0046 RPN total loss: 0.01416 Total loss: 0.87763 timestamp: 1654972530.484115 iteration: 74975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.099 FastRCNN class loss: 0.0794 FastRCNN total loss: 0.1784 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.0004 Mask loss: 0.16781 RPN box loss: 0.01077 RPN score loss: 0.00967 RPN total loss: 0.02044 Total loss: 0.9559 timestamp: 1654972533.6855915 iteration: 74980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08593 FastRCNN class loss: 0.10074 FastRCNN total loss: 0.18667 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.0004 Mask loss: 0.15144 RPN box loss: 0.01289 RPN score loss: 0.00388 RPN total loss: 0.01677 Total loss: 0.94413 timestamp: 1654972536.8512855 iteration: 74985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06972 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.12555 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.0004 Mask loss: 0.12789 RPN box loss: 0.02062 RPN score loss: 0.00473 RPN total loss: 0.02536 Total loss: 0.86805 timestamp: 1654972540.0040085 iteration: 74990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.16879 L1 loss: 0.0000e+00 L2 loss: 0.58924 Learning rate: 0.0004 Mask loss: 0.11654 RPN box loss: 0.02339 RPN score loss: 0.0062 RPN total loss: 0.02959 Total loss: 0.90417 timestamp: 1654972543.164854 iteration: 74995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07402 FastRCNN class loss: 0.07179 FastRCNN total loss: 0.14581 L1 loss: 0.0000e+00 L2 loss: 0.58924 Learning rate: 0.0004 Mask loss: 0.17184 RPN box loss: 0.01 RPN score loss: 0.00199 RPN total loss: 0.01199 Total loss: 0.91888 timestamp: 1654972546.3472302 iteration: 75000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11691 FastRCNN class loss: 0.09535 FastRCNN total loss: 0.21226 L1 loss: 0.0000e+00 L2 loss: 0.58924 Learning rate: 0.0004 Mask loss: 0.16671 RPN box loss: 0.01613 RPN score loss: 0.00527 RPN total loss: 0.0214 Total loss: 0.98961 timestamp: 1654972549.5679846 iteration: 75005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08873 FastRCNN class loss: 0.09534 FastRCNN total loss: 0.18407 L1 loss: 0.0000e+00 L2 loss: 0.58924 Learning rate: 0.0004 Mask loss: 0.1375 RPN box loss: 0.0171 RPN score loss: 0.02102 RPN total loss: 0.03813 Total loss: 0.94893 timestamp: 1654972552.7892678 iteration: 75010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05746 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.11556 L1 loss: 0.0000e+00 L2 loss: 0.58924 Learning rate: 0.0004 Mask loss: 0.14819 RPN box loss: 0.01005 RPN score loss: 0.00126 RPN total loss: 0.0113 Total loss: 0.86429 timestamp: 1654972555.9370153 iteration: 75015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05764 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.11718 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.15923 RPN box loss: 0.07381 RPN score loss: 0.01028 RPN total loss: 0.0841 Total loss: 0.94974 timestamp: 1654972559.1349077 iteration: 75020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0732 FastRCNN class loss: 0.05179 FastRCNN total loss: 0.12499 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.07438 RPN box loss: 0.00726 RPN score loss: 0.00107 RPN total loss: 0.00833 Total loss: 0.79694 timestamp: 1654972562.2667673 iteration: 75025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10646 FastRCNN class loss: 0.08493 FastRCNN total loss: 0.19139 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.1931 RPN box loss: 0.02975 RPN score loss: 0.00372 RPN total loss: 0.03347 Total loss: 1.0072 timestamp: 1654972565.495983 iteration: 75030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08634 FastRCNN class loss: 0.0387 FastRCNN total loss: 0.12505 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.10268 RPN box loss: 0.00491 RPN score loss: 0.00195 RPN total loss: 0.00686 Total loss: 0.82382 timestamp: 1654972568.6467862 iteration: 75035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0737 FastRCNN class loss: 0.04171 FastRCNN total loss: 0.11541 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.11716 RPN box loss: 0.00574 RPN score loss: 0.00571 RPN total loss: 0.01145 Total loss: 0.83325 timestamp: 1654972571.8369896 iteration: 75040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09683 FastRCNN class loss: 0.08922 FastRCNN total loss: 0.18604 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.19244 RPN box loss: 0.01654 RPN score loss: 0.01039 RPN total loss: 0.02693 Total loss: 0.99464 timestamp: 1654972575.053581 iteration: 75045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06449 FastRCNN class loss: 0.04779 FastRCNN total loss: 0.11228 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.0004 Mask loss: 0.05979 RPN box loss: 0.01009 RPN score loss: 0.00157 RPN total loss: 0.01166 Total loss: 0.77296 timestamp: 1654972578.2125285 iteration: 75050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06124 FastRCNN class loss: 0.05375 FastRCNN total loss: 0.11499 L1 loss: 0.0000e+00 L2 loss: 0.58922 Learning rate: 0.0004 Mask loss: 0.1151 RPN box loss: 0.00469 RPN score loss: 0.00118 RPN total loss: 0.00586 Total loss: 0.82518 timestamp: 1654972581.392065 iteration: 75055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10677 FastRCNN class loss: 0.05913 FastRCNN total loss: 0.1659 L1 loss: 0.0000e+00 L2 loss: 0.58922 Learning rate: 0.0004 Mask loss: 0.11939 RPN box loss: 0.00909 RPN score loss: 0.00236 RPN total loss: 0.01145 Total loss: 0.88596 timestamp: 1654972584.5803878 iteration: 75060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10348 FastRCNN class loss: 0.07351 FastRCNN total loss: 0.17699 L1 loss: 0.0000e+00 L2 loss: 0.58922 Learning rate: 0.0004 Mask loss: 0.11809 RPN box loss: 0.00615 RPN score loss: 0.0052 RPN total loss: 0.01135 Total loss: 0.89565 timestamp: 1654972587.7621057 iteration: 75065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10407 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.17495 L1 loss: 0.0000e+00 L2 loss: 0.58922 Learning rate: 0.0004 Mask loss: 0.11632 RPN box loss: 0.02569 RPN score loss: 0.00918 RPN total loss: 0.03487 Total loss: 0.91536 timestamp: 1654972590.9506905 iteration: 75070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11478 FastRCNN class loss: 0.09198 FastRCNN total loss: 0.20676 L1 loss: 0.0000e+00 L2 loss: 0.58922 Learning rate: 0.0004 Mask loss: 0.14795 RPN box loss: 0.02896 RPN score loss: 0.00641 RPN total loss: 0.03537 Total loss: 0.9793 timestamp: 1654972594.1562667 iteration: 75075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06549 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.12996 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.0004 Mask loss: 0.10894 RPN box loss: 0.00526 RPN score loss: 0.00143 RPN total loss: 0.00669 Total loss: 0.83481 timestamp: 1654972597.3775735 iteration: 75080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07716 FastRCNN class loss: 0.05492 FastRCNN total loss: 0.13208 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.0004 Mask loss: 0.10063 RPN box loss: 0.00764 RPN score loss: 0.00322 RPN total loss: 0.01086 Total loss: 0.83278 timestamp: 1654972600.5212102 iteration: 75085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06893 FastRCNN class loss: 0.08869 FastRCNN total loss: 0.15762 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.0004 Mask loss: 0.11512 RPN box loss: 0.00811 RPN score loss: 0.00412 RPN total loss: 0.01223 Total loss: 0.87418 timestamp: 1654972603.7051795 iteration: 75090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08793 FastRCNN class loss: 0.06156 FastRCNN total loss: 0.14949 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.0004 Mask loss: 0.18929 RPN box loss: 0.00589 RPN score loss: 0.00092 RPN total loss: 0.0068 Total loss: 0.9348 timestamp: 1654972606.9003935 iteration: 75095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12337 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.19954 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.0004 Mask loss: 0.145 RPN box loss: 0.01144 RPN score loss: 0.00862 RPN total loss: 0.02005 Total loss: 0.95381 timestamp: 1654972610.0855825 iteration: 75100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05929 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.11897 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.0004 Mask loss: 0.07651 RPN box loss: 0.01003 RPN score loss: 0.00902 RPN total loss: 0.01904 Total loss: 0.80373 timestamp: 1654972613.2363608 iteration: 75105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05321 FastRCNN class loss: 0.03223 FastRCNN total loss: 0.08544 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.08971 RPN box loss: 0.00549 RPN score loss: 0.00121 RPN total loss: 0.0067 Total loss: 0.77105 timestamp: 1654972616.3889241 iteration: 75110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09813 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.16576 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.14678 RPN box loss: 0.0166 RPN score loss: 0.00117 RPN total loss: 0.01777 Total loss: 0.91951 timestamp: 1654972619.5954788 iteration: 75115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11439 FastRCNN class loss: 0.08313 FastRCNN total loss: 0.19752 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.14097 RPN box loss: 0.01373 RPN score loss: 0.00255 RPN total loss: 0.01628 Total loss: 0.94397 timestamp: 1654972622.8148928 iteration: 75120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12062 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.18536 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.15858 RPN box loss: 0.0048 RPN score loss: 0.00334 RPN total loss: 0.00814 Total loss: 0.94129 timestamp: 1654972626.0246902 iteration: 75125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07071 FastRCNN class loss: 0.04059 FastRCNN total loss: 0.1113 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.10636 RPN box loss: 0.00504 RPN score loss: 0.00263 RPN total loss: 0.00766 Total loss: 0.81452 timestamp: 1654972629.2222264 iteration: 75130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07319 FastRCNN class loss: 0.06672 FastRCNN total loss: 0.13991 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.11653 RPN box loss: 0.00762 RPN score loss: 0.004 RPN total loss: 0.01162 Total loss: 0.85727 timestamp: 1654972632.493987 iteration: 75135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04014 FastRCNN class loss: 0.06971 FastRCNN total loss: 0.10984 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.0004 Mask loss: 0.10654 RPN box loss: 0.00914 RPN score loss: 0.00293 RPN total loss: 0.01207 Total loss: 0.81765 timestamp: 1654972635.7109723 iteration: 75140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07518 FastRCNN class loss: 0.04967 FastRCNN total loss: 0.12484 L1 loss: 0.0000e+00 L2 loss: 0.58919 Learning rate: 0.0004 Mask loss: 0.08795 RPN box loss: 0.00581 RPN score loss: 0.00166 RPN total loss: 0.00747 Total loss: 0.80946 timestamp: 1654972638.8726246 iteration: 75145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06779 FastRCNN class loss: 0.06357 FastRCNN total loss: 0.13136 L1 loss: 0.0000e+00 L2 loss: 0.58919 Learning rate: 0.0004 Mask loss: 0.12593 RPN box loss: 0.02688 RPN score loss: 0.00425 RPN total loss: 0.03113 Total loss: 0.87761 timestamp: 1654972642.094575 iteration: 75150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.58919 Learning rate: 0.0004 Mask loss: 0.15094 RPN box loss: 0.0151 RPN score loss: 0.00301 RPN total loss: 0.01811 Total loss: 0.90658 timestamp: 1654972645.206039 iteration: 75155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07211 FastRCNN class loss: 0.04537 FastRCNN total loss: 0.11749 L1 loss: 0.0000e+00 L2 loss: 0.58919 Learning rate: 0.0004 Mask loss: 0.08965 RPN box loss: 0.00501 RPN score loss: 0.00379 RPN total loss: 0.0088 Total loss: 0.80512 timestamp: 1654972648.4105432 iteration: 75160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09735 FastRCNN class loss: 0.08383 FastRCNN total loss: 0.18119 L1 loss: 0.0000e+00 L2 loss: 0.58919 Learning rate: 0.0004 Mask loss: 0.0953 RPN box loss: 0.01148 RPN score loss: 0.00178 RPN total loss: 0.01326 Total loss: 0.87893 timestamp: 1654972651.5805593 iteration: 75165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05651 FastRCNN class loss: 0.03681 FastRCNN total loss: 0.09332 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.11176 RPN box loss: 0.00418 RPN score loss: 0.00443 RPN total loss: 0.00861 Total loss: 0.80288 timestamp: 1654972654.8395321 iteration: 75170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09615 FastRCNN class loss: 0.10811 FastRCNN total loss: 0.20425 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.18117 RPN box loss: 0.01699 RPN score loss: 0.00836 RPN total loss: 0.02535 Total loss: 0.99995 timestamp: 1654972658.0759163 iteration: 75175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0836 FastRCNN class loss: 0.0638 FastRCNN total loss: 0.14739 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.10331 RPN box loss: 0.01994 RPN score loss: 0.0034 RPN total loss: 0.02334 Total loss: 0.86323 timestamp: 1654972661.3289099 iteration: 75180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14645 FastRCNN class loss: 0.08929 FastRCNN total loss: 0.23575 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.15005 RPN box loss: 0.00878 RPN score loss: 0.00612 RPN total loss: 0.0149 Total loss: 0.98988 timestamp: 1654972664.5170732 iteration: 75185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08854 FastRCNN class loss: 0.05319 FastRCNN total loss: 0.14173 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.1285 RPN box loss: 0.00392 RPN score loss: 0.00276 RPN total loss: 0.00669 Total loss: 0.86609 timestamp: 1654972667.7161098 iteration: 75190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09363 FastRCNN class loss: 0.05511 FastRCNN total loss: 0.14874 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.12199 RPN box loss: 0.01659 RPN score loss: 0.00283 RPN total loss: 0.01942 Total loss: 0.87933 timestamp: 1654972670.902202 iteration: 75195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12499 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.19898 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.0004 Mask loss: 0.11136 RPN box loss: 0.01766 RPN score loss: 0.00565 RPN total loss: 0.02331 Total loss: 0.92283 timestamp: 1654972674.0719306 iteration: 75200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12056 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.18773 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.0004 Mask loss: 0.1439 RPN box loss: 0.01268 RPN score loss: 0.00465 RPN total loss: 0.01733 Total loss: 0.93813 timestamp: 1654972677.3153093 iteration: 75205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06987 FastRCNN class loss: 0.05682 FastRCNN total loss: 0.12668 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.0004 Mask loss: 0.14803 RPN box loss: 0.00581 RPN score loss: 0.00114 RPN total loss: 0.00694 Total loss: 0.87083 timestamp: 1654972680.4852824 iteration: 75210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12248 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.18886 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.0004 Mask loss: 0.14881 RPN box loss: 0.01899 RPN score loss: 0.00466 RPN total loss: 0.02365 Total loss: 0.95049 timestamp: 1654972683.6990323 iteration: 75215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11359 FastRCNN class loss: 0.06313 FastRCNN total loss: 0.17672 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.0004 Mask loss: 0.13151 RPN box loss: 0.02154 RPN score loss: 0.0122 RPN total loss: 0.03374 Total loss: 0.93114 timestamp: 1654972686.9040349 iteration: 75220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12171 FastRCNN class loss: 0.07742 FastRCNN total loss: 0.19913 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.0004 Mask loss: 0.08698 RPN box loss: 0.01095 RPN score loss: 0.00898 RPN total loss: 0.01993 Total loss: 0.8952 timestamp: 1654972690.0559058 iteration: 75225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14202 FastRCNN class loss: 0.10667 FastRCNN total loss: 0.2487 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.0004 Mask loss: 0.17513 RPN box loss: 0.02433 RPN score loss: 0.01619 RPN total loss: 0.04052 Total loss: 1.05352 timestamp: 1654972693.2941995 iteration: 75230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06104 FastRCNN class loss: 0.069 FastRCNN total loss: 0.13004 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.0004 Mask loss: 0.17078 RPN box loss: 0.0124 RPN score loss: 0.01109 RPN total loss: 0.0235 Total loss: 0.91348 timestamp: 1654972696.57884 iteration: 75235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07569 FastRCNN class loss: 0.06437 FastRCNN total loss: 0.14006 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.0004 Mask loss: 0.10566 RPN box loss: 0.00643 RPN score loss: 0.00198 RPN total loss: 0.00841 Total loss: 0.8433 timestamp: 1654972699.7984452 iteration: 75240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06509 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.1374 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.0004 Mask loss: 0.09709 RPN box loss: 0.00822 RPN score loss: 0.00547 RPN total loss: 0.01369 Total loss: 0.83733 timestamp: 1654972703.026201 iteration: 75245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05334 FastRCNN class loss: 0.04631 FastRCNN total loss: 0.09965 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.0004 Mask loss: 0.10899 RPN box loss: 0.01544 RPN score loss: 0.00358 RPN total loss: 0.01902 Total loss: 0.81682 timestamp: 1654972706.2698843 iteration: 75250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08941 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.14925 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.0004 Mask loss: 0.14117 RPN box loss: 0.00658 RPN score loss: 0.00321 RPN total loss: 0.00979 Total loss: 0.88937 timestamp: 1654972709.4891455 iteration: 75255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16198 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.22274 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.0004 Mask loss: 0.11919 RPN box loss: 0.00515 RPN score loss: 0.00554 RPN total loss: 0.01069 Total loss: 0.94177 timestamp: 1654972712.6808813 iteration: 75260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06348 FastRCNN class loss: 0.06094 FastRCNN total loss: 0.12442 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.0004 Mask loss: 0.13413 RPN box loss: 0.00998 RPN score loss: 0.00604 RPN total loss: 0.01602 Total loss: 0.86373 timestamp: 1654972715.873676 iteration: 75265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07315 FastRCNN class loss: 0.04436 FastRCNN total loss: 0.11751 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.0004 Mask loss: 0.05257 RPN box loss: 0.00264 RPN score loss: 0.00077 RPN total loss: 0.00341 Total loss: 0.76264 timestamp: 1654972719.0858047 iteration: 75270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.05672 FastRCNN total loss: 0.13088 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.0004 Mask loss: 0.14513 RPN box loss: 0.01049 RPN score loss: 0.00363 RPN total loss: 0.01412 Total loss: 0.87927 timestamp: 1654972722.268766 iteration: 75275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06657 FastRCNN class loss: 0.07091 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.0004 Mask loss: 0.12604 RPN box loss: 0.01402 RPN score loss: 0.00378 RPN total loss: 0.0178 Total loss: 0.87046 timestamp: 1654972725.406574 iteration: 75280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10936 FastRCNN class loss: 0.07715 FastRCNN total loss: 0.18651 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.0004 Mask loss: 0.10009 RPN box loss: 0.01829 RPN score loss: 0.01172 RPN total loss: 0.03001 Total loss: 0.90575 timestamp: 1654972728.6025646 iteration: 75285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09133 FastRCNN class loss: 0.05438 FastRCNN total loss: 0.14571 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.0004 Mask loss: 0.1124 RPN box loss: 0.01 RPN score loss: 0.00234 RPN total loss: 0.01235 Total loss: 0.8596 timestamp: 1654972731.7652335 iteration: 75290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14643 FastRCNN class loss: 0.04529 FastRCNN total loss: 0.19172 L1 loss: 0.0000e+00 L2 loss: 0.58914 Learning rate: 0.0004 Mask loss: 0.09124 RPN box loss: 0.01027 RPN score loss: 0.00447 RPN total loss: 0.01474 Total loss: 0.88685 timestamp: 1654972734.9722116 iteration: 75295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10154 FastRCNN class loss: 0.09061 FastRCNN total loss: 0.19215 L1 loss: 0.0000e+00 L2 loss: 0.58914 Learning rate: 0.0004 Mask loss: 0.15329 RPN box loss: 0.01002 RPN score loss: 0.00149 RPN total loss: 0.01152 Total loss: 0.9461 timestamp: 1654972738.1788576 iteration: 75300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06228 FastRCNN class loss: 0.04876 FastRCNN total loss: 0.11103 L1 loss: 0.0000e+00 L2 loss: 0.58914 Learning rate: 0.0004 Mask loss: 0.16195 RPN box loss: 0.01042 RPN score loss: 0.00218 RPN total loss: 0.01259 Total loss: 0.87472 timestamp: 1654972741.3610573 iteration: 75305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08166 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.14713 L1 loss: 0.0000e+00 L2 loss: 0.58914 Learning rate: 0.0004 Mask loss: 0.17437 RPN box loss: 0.01221 RPN score loss: 0.00729 RPN total loss: 0.01949 Total loss: 0.93013 timestamp: 1654972744.5386424 iteration: 75310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0391 FastRCNN class loss: 0.04476 FastRCNN total loss: 0.08386 L1 loss: 0.0000e+00 L2 loss: 0.58914 Learning rate: 0.0004 Mask loss: 0.08513 RPN box loss: 0.00251 RPN score loss: 0.0009 RPN total loss: 0.0034 Total loss: 0.76152 timestamp: 1654972747.718894 iteration: 75315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08807 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.13796 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.0004 Mask loss: 0.15997 RPN box loss: 0.00623 RPN score loss: 0.00293 RPN total loss: 0.00917 Total loss: 0.89624 timestamp: 1654972750.8658102 iteration: 75320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0736 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.13812 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.0004 Mask loss: 0.13494 RPN box loss: 0.01842 RPN score loss: 0.00336 RPN total loss: 0.02177 Total loss: 0.88397 timestamp: 1654972754.0760028 iteration: 75325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0945 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.1611 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.0004 Mask loss: 0.11961 RPN box loss: 0.0054 RPN score loss: 0.00613 RPN total loss: 0.01153 Total loss: 0.88138 timestamp: 1654972757.2992785 iteration: 75330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12806 FastRCNN class loss: 0.09162 FastRCNN total loss: 0.21968 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.0004 Mask loss: 0.14905 RPN box loss: 0.02121 RPN score loss: 0.00667 RPN total loss: 0.02788 Total loss: 0.98574 timestamp: 1654972760.4647887 iteration: 75335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06444 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.1235 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.0004 Mask loss: 0.11212 RPN box loss: 0.00678 RPN score loss: 0.00207 RPN total loss: 0.00884 Total loss: 0.83359 timestamp: 1654972763.63555 iteration: 75340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10239 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.16116 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.0004 Mask loss: 0.10348 RPN box loss: 0.04246 RPN score loss: 0.00803 RPN total loss: 0.05049 Total loss: 0.90425 timestamp: 1654972766.805965 iteration: 75345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0666 FastRCNN class loss: 0.06314 FastRCNN total loss: 0.12975 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.0004 Mask loss: 0.10792 RPN box loss: 0.01401 RPN score loss: 0.00739 RPN total loss: 0.0214 Total loss: 0.84819 timestamp: 1654972769.9605532 iteration: 75350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05858 FastRCNN class loss: 0.048 FastRCNN total loss: 0.10658 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.0004 Mask loss: 0.11216 RPN box loss: 0.00992 RPN score loss: 0.00939 RPN total loss: 0.01931 Total loss: 0.82718 timestamp: 1654972773.1577835 iteration: 75355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13871 FastRCNN class loss: 0.08998 FastRCNN total loss: 0.22869 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.0004 Mask loss: 0.15048 RPN box loss: 0.02526 RPN score loss: 0.01619 RPN total loss: 0.04145 Total loss: 1.00975 timestamp: 1654972776.3464563 iteration: 75360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08148 FastRCNN class loss: 0.04287 FastRCNN total loss: 0.12434 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.0004 Mask loss: 0.10698 RPN box loss: 0.02343 RPN score loss: 0.00404 RPN total loss: 0.02747 Total loss: 0.84791 timestamp: 1654972779.5384057 iteration: 75365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03999 FastRCNN class loss: 0.04261 FastRCNN total loss: 0.0826 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.0004 Mask loss: 0.14162 RPN box loss: 0.0042 RPN score loss: 0.00411 RPN total loss: 0.00831 Total loss: 0.82164 timestamp: 1654972782.7762809 iteration: 75370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07761 FastRCNN class loss: 0.05379 FastRCNN total loss: 0.13141 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.0004 Mask loss: 0.12216 RPN box loss: 0.00648 RPN score loss: 0.00316 RPN total loss: 0.00964 Total loss: 0.85232 timestamp: 1654972785.9810517 iteration: 75375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09189 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.15467 L1 loss: 0.0000e+00 L2 loss: 0.58911 Learning rate: 0.0004 Mask loss: 0.15451 RPN box loss: 0.01743 RPN score loss: 0.00846 RPN total loss: 0.02589 Total loss: 0.92419 timestamp: 1654972789.1917129 iteration: 75380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13365 FastRCNN class loss: 0.08388 FastRCNN total loss: 0.21753 L1 loss: 0.0000e+00 L2 loss: 0.58911 Learning rate: 0.0004 Mask loss: 0.12369 RPN box loss: 0.00923 RPN score loss: 0.00703 RPN total loss: 0.01626 Total loss: 0.94659 timestamp: 1654972792.4185476 iteration: 75385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08823 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.13651 L1 loss: 0.0000e+00 L2 loss: 0.58911 Learning rate: 0.0004 Mask loss: 0.10582 RPN box loss: 0.00876 RPN score loss: 0.0024 RPN total loss: 0.01117 Total loss: 0.84261 timestamp: 1654972795.6077366 iteration: 75390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.17329 L1 loss: 0.0000e+00 L2 loss: 0.58911 Learning rate: 0.0004 Mask loss: 0.13707 RPN box loss: 0.01705 RPN score loss: 0.00311 RPN total loss: 0.02016 Total loss: 0.91962 timestamp: 1654972798.790528 iteration: 75395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04187 FastRCNN class loss: 0.03442 FastRCNN total loss: 0.07629 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.0004 Mask loss: 0.10749 RPN box loss: 0.01136 RPN score loss: 0.00514 RPN total loss: 0.0165 Total loss: 0.78939 timestamp: 1654972801.966786 iteration: 75400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10111 FastRCNN class loss: 0.05111 FastRCNN total loss: 0.15223 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.0004 Mask loss: 0.11972 RPN box loss: 0.00832 RPN score loss: 0.0015 RPN total loss: 0.00982 Total loss: 0.87088 timestamp: 1654972805.187037 iteration: 75405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04804 FastRCNN class loss: 0.06341 FastRCNN total loss: 0.11145 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.0004 Mask loss: 0.0828 RPN box loss: 0.0145 RPN score loss: 0.00156 RPN total loss: 0.01606 Total loss: 0.79941 timestamp: 1654972808.4315057 iteration: 75410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07074 FastRCNN class loss: 0.04468 FastRCNN total loss: 0.11541 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.0004 Mask loss: 0.11974 RPN box loss: 0.00386 RPN score loss: 0.00107 RPN total loss: 0.00493 Total loss: 0.82919 timestamp: 1654972811.6818235 iteration: 75415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09441 FastRCNN class loss: 0.06247 FastRCNN total loss: 0.15688 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.0004 Mask loss: 0.15268 RPN box loss: 0.00482 RPN score loss: 0.00169 RPN total loss: 0.00651 Total loss: 0.90517 timestamp: 1654972814.8490531 iteration: 75420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06922 FastRCNN class loss: 0.03583 FastRCNN total loss: 0.10505 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.0004 Mask loss: 0.1009 RPN box loss: 0.01657 RPN score loss: 0.00536 RPN total loss: 0.02193 Total loss: 0.81698 timestamp: 1654972817.9987833 iteration: 75425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0876 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.15742 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.1417 RPN box loss: 0.01215 RPN score loss: 0.01152 RPN total loss: 0.02367 Total loss: 0.91188 timestamp: 1654972821.124344 iteration: 75430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08931 FastRCNN class loss: 0.03535 FastRCNN total loss: 0.12467 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.11904 RPN box loss: 0.01337 RPN score loss: 0.00111 RPN total loss: 0.01448 Total loss: 0.84728 timestamp: 1654972824.3485072 iteration: 75435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06064 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.11532 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.11271 RPN box loss: 0.00976 RPN score loss: 0.00599 RPN total loss: 0.01575 Total loss: 0.83288 timestamp: 1654972827.573353 iteration: 75440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10492 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.17709 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.19053 RPN box loss: 0.01822 RPN score loss: 0.00681 RPN total loss: 0.02503 Total loss: 0.98173 timestamp: 1654972830.7819052 iteration: 75445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05706 FastRCNN class loss: 0.04326 FastRCNN total loss: 0.10032 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.11218 RPN box loss: 0.00678 RPN score loss: 0.00271 RPN total loss: 0.00949 Total loss: 0.81108 timestamp: 1654972834.0646849 iteration: 75450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07602 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.12841 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.09969 RPN box loss: 0.00801 RPN score loss: 0.00075 RPN total loss: 0.00876 Total loss: 0.82594 timestamp: 1654972837.3557029 iteration: 75455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10707 FastRCNN class loss: 0.07571 FastRCNN total loss: 0.18279 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.0004 Mask loss: 0.13765 RPN box loss: 0.01763 RPN score loss: 0.00696 RPN total loss: 0.02459 Total loss: 0.93411 timestamp: 1654972840.5565827 iteration: 75460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09916 FastRCNN class loss: 0.06143 FastRCNN total loss: 0.16059 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.0004 Mask loss: 0.09232 RPN box loss: 0.01639 RPN score loss: 0.00325 RPN total loss: 0.01965 Total loss: 0.86164 timestamp: 1654972843.7381787 iteration: 75465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07419 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.12706 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.0004 Mask loss: 0.16184 RPN box loss: 0.02259 RPN score loss: 0.00595 RPN total loss: 0.02854 Total loss: 0.90653 timestamp: 1654972846.9243474 iteration: 75470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0952 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.1676 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.0004 Mask loss: 0.1622 RPN box loss: 0.01371 RPN score loss: 0.00536 RPN total loss: 0.01908 Total loss: 0.93796 timestamp: 1654972850.177136 iteration: 75475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1001 FastRCNN class loss: 0.03978 FastRCNN total loss: 0.13987 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.0004 Mask loss: 0.12423 RPN box loss: 0.01129 RPN score loss: 0.00229 RPN total loss: 0.01357 Total loss: 0.86676 timestamp: 1654972853.315588 iteration: 75480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06589 FastRCNN class loss: 0.04073 FastRCNN total loss: 0.10662 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.0004 Mask loss: 0.09544 RPN box loss: 0.0062 RPN score loss: 0.00081 RPN total loss: 0.00701 Total loss: 0.79815 timestamp: 1654972856.5091376 iteration: 75485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09016 FastRCNN class loss: 0.06691 FastRCNN total loss: 0.15707 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.0004 Mask loss: 0.19658 RPN box loss: 0.00547 RPN score loss: 0.00146 RPN total loss: 0.00693 Total loss: 0.94965 timestamp: 1654972859.7759035 iteration: 75490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11979 FastRCNN class loss: 0.10927 FastRCNN total loss: 0.22905 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.0004 Mask loss: 0.14228 RPN box loss: 0.01482 RPN score loss: 0.00361 RPN total loss: 0.01843 Total loss: 0.97884 timestamp: 1654972863.031875 iteration: 75495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10258 FastRCNN class loss: 0.08542 FastRCNN total loss: 0.188 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.0004 Mask loss: 0.1214 RPN box loss: 0.03213 RPN score loss: 0.00889 RPN total loss: 0.04101 Total loss: 0.93948 timestamp: 1654972866.287027 iteration: 75500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0598 FastRCNN class loss: 0.03137 FastRCNN total loss: 0.09117 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.0004 Mask loss: 0.09324 RPN box loss: 0.00397 RPN score loss: 0.00343 RPN total loss: 0.0074 Total loss: 0.78088 timestamp: 1654972869.4071238 iteration: 75505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0595 FastRCNN class loss: 0.06093 FastRCNN total loss: 0.12043 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.0004 Mask loss: 0.13177 RPN box loss: 0.00656 RPN score loss: 0.00163 RPN total loss: 0.00819 Total loss: 0.84945 timestamp: 1654972872.5897818 iteration: 75510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.11165 FastRCNN total loss: 0.22221 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.0004 Mask loss: 0.13987 RPN box loss: 0.01729 RPN score loss: 0.00493 RPN total loss: 0.02222 Total loss: 0.97338 timestamp: 1654972875.7446496 iteration: 75515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.06462 FastRCNN total loss: 0.14379 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.0004 Mask loss: 0.15128 RPN box loss: 0.00821 RPN score loss: 0.01231 RPN total loss: 0.02052 Total loss: 0.90465 timestamp: 1654972878.9515796 iteration: 75520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1074 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.19588 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.0004 Mask loss: 0.1885 RPN box loss: 0.01035 RPN score loss: 0.00856 RPN total loss: 0.01891 Total loss: 0.99235 timestamp: 1654972882.1471117 iteration: 75525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09687 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.16321 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.0004 Mask loss: 0.0894 RPN box loss: 0.00694 RPN score loss: 0.0013 RPN total loss: 0.00824 Total loss: 0.84991 timestamp: 1654972885.4256434 iteration: 75530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09814 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.16266 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.0004 Mask loss: 0.1637 RPN box loss: 0.01112 RPN score loss: 0.00291 RPN total loss: 0.01403 Total loss: 0.92944 timestamp: 1654972888.6744049 iteration: 75535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07262 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.15682 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.0004 Mask loss: 0.16027 RPN box loss: 0.02251 RPN score loss: 0.01696 RPN total loss: 0.03947 Total loss: 0.94562 timestamp: 1654972891.8594487 iteration: 75540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.06416 FastRCNN total loss: 0.13997 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.0004 Mask loss: 0.13155 RPN box loss: 0.00878 RPN score loss: 0.00637 RPN total loss: 0.01515 Total loss: 0.87572 timestamp: 1654972895.0339632 iteration: 75545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12847 FastRCNN class loss: 0.09963 FastRCNN total loss: 0.2281 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.0004 Mask loss: 0.14512 RPN box loss: 0.0221 RPN score loss: 0.00762 RPN total loss: 0.02973 Total loss: 0.992 timestamp: 1654972898.2003639 iteration: 75550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08781 FastRCNN class loss: 0.05613 FastRCNN total loss: 0.14394 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.0004 Mask loss: 0.07949 RPN box loss: 0.00619 RPN score loss: 0.00401 RPN total loss: 0.0102 Total loss: 0.82269 timestamp: 1654972901.3723361 iteration: 75555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1358 FastRCNN class loss: 0.11601 FastRCNN total loss: 0.25182 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.0004 Mask loss: 0.21713 RPN box loss: 0.01422 RPN score loss: 0.00956 RPN total loss: 0.02378 Total loss: 1.08177 timestamp: 1654972904.5264287 iteration: 75560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04618 FastRCNN class loss: 0.02783 FastRCNN total loss: 0.07401 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.0004 Mask loss: 0.09276 RPN box loss: 0.01094 RPN score loss: 0.00941 RPN total loss: 0.02035 Total loss: 0.77617 timestamp: 1654972907.7347353 iteration: 75565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12863 FastRCNN class loss: 0.06356 FastRCNN total loss: 0.19218 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.0004 Mask loss: 0.14998 RPN box loss: 0.01286 RPN score loss: 0.00215 RPN total loss: 0.015 Total loss: 0.94621 timestamp: 1654972910.992966 iteration: 75570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05616 FastRCNN class loss: 0.05682 FastRCNN total loss: 0.11298 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.0004 Mask loss: 0.11949 RPN box loss: 0.01448 RPN score loss: 0.00906 RPN total loss: 0.02355 Total loss: 0.84507 timestamp: 1654972914.1776414 iteration: 75575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.08609 FastRCNN total loss: 0.22596 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.0004 Mask loss: 0.09854 RPN box loss: 0.00713 RPN score loss: 0.00285 RPN total loss: 0.00998 Total loss: 0.92353 timestamp: 1654972917.3279116 iteration: 75580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06032 FastRCNN class loss: 0.10007 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.0004 Mask loss: 0.11922 RPN box loss: 0.01237 RPN score loss: 0.00435 RPN total loss: 0.01672 Total loss: 0.88539 timestamp: 1654972920.5281203 iteration: 75585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09566 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.15257 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.0004 Mask loss: 0.08491 RPN box loss: 0.01459 RPN score loss: 0.00161 RPN total loss: 0.0162 Total loss: 0.84272 timestamp: 1654972923.7246032 iteration: 75590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08363 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.15396 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.0004 Mask loss: 0.11161 RPN box loss: 0.01848 RPN score loss: 0.01127 RPN total loss: 0.02975 Total loss: 0.88436 timestamp: 1654972926.9447865 iteration: 75595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07878 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.15485 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.0004 Mask loss: 0.14999 RPN box loss: 0.01397 RPN score loss: 0.00551 RPN total loss: 0.01948 Total loss: 0.91336 timestamp: 1654972930.2051122 iteration: 75600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11607 FastRCNN class loss: 0.1338 FastRCNN total loss: 0.24987 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.0004 Mask loss: 0.17173 RPN box loss: 0.01415 RPN score loss: 0.00563 RPN total loss: 0.01978 Total loss: 1.03042 timestamp: 1654972933.4550023 iteration: 75605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06397 FastRCNN class loss: 0.03366 FastRCNN total loss: 0.09763 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.0004 Mask loss: 0.09915 RPN box loss: 0.00451 RPN score loss: 0.0015 RPN total loss: 0.00601 Total loss: 0.79183 timestamp: 1654972936.6128328 iteration: 75610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0616 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.12586 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.0004 Mask loss: 0.13465 RPN box loss: 0.01865 RPN score loss: 0.00217 RPN total loss: 0.02082 Total loss: 0.87036 timestamp: 1654972939.8283336 iteration: 75615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10979 FastRCNN class loss: 0.06532 FastRCNN total loss: 0.17511 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.0004 Mask loss: 0.19266 RPN box loss: 0.01066 RPN score loss: 0.00314 RPN total loss: 0.01379 Total loss: 0.97059 timestamp: 1654972943.0653622 iteration: 75620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11073 FastRCNN class loss: 0.05206 FastRCNN total loss: 0.16279 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.0004 Mask loss: 0.1148 RPN box loss: 0.03938 RPN score loss: 0.00233 RPN total loss: 0.04171 Total loss: 0.90833 timestamp: 1654972946.293496 iteration: 75625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11162 FastRCNN class loss: 0.06312 FastRCNN total loss: 0.17474 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.0004 Mask loss: 0.14952 RPN box loss: 0.00929 RPN score loss: 0.00653 RPN total loss: 0.01582 Total loss: 0.92911 timestamp: 1654972949.4673252 iteration: 75630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.19092 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.0004 Mask loss: 0.13077 RPN box loss: 0.00963 RPN score loss: 0.00217 RPN total loss: 0.0118 Total loss: 0.92251 timestamp: 1654972952.663715 iteration: 75635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13025 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.19508 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.0004 Mask loss: 0.15494 RPN box loss: 0.00708 RPN score loss: 0.001 RPN total loss: 0.00807 Total loss: 0.94712 timestamp: 1654972955.8096817 iteration: 75640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05487 FastRCNN class loss: 0.04447 FastRCNN total loss: 0.09934 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.09038 RPN box loss: 0.00195 RPN score loss: 0.00224 RPN total loss: 0.00419 Total loss: 0.78293 timestamp: 1654972958.9844744 iteration: 75645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05794 FastRCNN class loss: 0.03602 FastRCNN total loss: 0.09397 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.11712 RPN box loss: 0.0091 RPN score loss: 0.00114 RPN total loss: 0.01024 Total loss: 0.81035 timestamp: 1654972962.2105463 iteration: 75650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05388 FastRCNN class loss: 0.0504 FastRCNN total loss: 0.10428 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.16082 RPN box loss: 0.00886 RPN score loss: 0.00452 RPN total loss: 0.01338 Total loss: 0.8675 timestamp: 1654972965.4492674 iteration: 75655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10564 FastRCNN class loss: 0.07689 FastRCNN total loss: 0.18253 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.17243 RPN box loss: 0.01382 RPN score loss: 0.00452 RPN total loss: 0.01834 Total loss: 0.96232 timestamp: 1654972968.5928335 iteration: 75660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08435 FastRCNN class loss: 0.0715 FastRCNN total loss: 0.15585 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.13494 RPN box loss: 0.02282 RPN score loss: 0.00403 RPN total loss: 0.02685 Total loss: 0.90666 timestamp: 1654972971.8856046 iteration: 75665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12241 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.18982 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.14999 RPN box loss: 0.02972 RPN score loss: 0.01615 RPN total loss: 0.04587 Total loss: 0.97469 timestamp: 1654972975.0366113 iteration: 75670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07341 FastRCNN class loss: 0.04006 FastRCNN total loss: 0.11347 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.0004 Mask loss: 0.0861 RPN box loss: 0.00527 RPN score loss: 0.00212 RPN total loss: 0.00739 Total loss: 0.79598 timestamp: 1654972978.2600887 iteration: 75675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05091 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.10409 L1 loss: 0.0000e+00 L2 loss: 0.58901 Learning rate: 0.0004 Mask loss: 0.14651 RPN box loss: 0.00275 RPN score loss: 0.00099 RPN total loss: 0.00374 Total loss: 0.84336 timestamp: 1654972981.5120926 iteration: 75680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12343 FastRCNN class loss: 0.08626 FastRCNN total loss: 0.20969 L1 loss: 0.0000e+00 L2 loss: 0.58901 Learning rate: 0.0004 Mask loss: 0.1663 RPN box loss: 0.02354 RPN score loss: 0.00555 RPN total loss: 0.02909 Total loss: 0.9941 timestamp: 1654972984.7493062 iteration: 75685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10719 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.17914 L1 loss: 0.0000e+00 L2 loss: 0.58901 Learning rate: 0.0004 Mask loss: 0.16373 RPN box loss: 0.01256 RPN score loss: 0.00225 RPN total loss: 0.01481 Total loss: 0.94669 timestamp: 1654972987.8693223 iteration: 75690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06271 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.14444 L1 loss: 0.0000e+00 L2 loss: 0.58901 Learning rate: 0.0004 Mask loss: 0.12014 RPN box loss: 0.0064 RPN score loss: 0.00368 RPN total loss: 0.01008 Total loss: 0.86367 timestamp: 1654972991.092997 iteration: 75695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08389 FastRCNN class loss: 0.05904 FastRCNN total loss: 0.14293 L1 loss: 0.0000e+00 L2 loss: 0.58901 Learning rate: 0.0004 Mask loss: 0.10493 RPN box loss: 0.01036 RPN score loss: 0.01204 RPN total loss: 0.0224 Total loss: 0.85927 timestamp: 1654972994.3004174 iteration: 75700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14804 FastRCNN class loss: 0.08157 FastRCNN total loss: 0.22961 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.0004 Mask loss: 0.13607 RPN box loss: 0.00403 RPN score loss: 0.00988 RPN total loss: 0.01391 Total loss: 0.9686 timestamp: 1654972997.508465 iteration: 75705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06451 FastRCNN class loss: 0.05673 FastRCNN total loss: 0.12124 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.0004 Mask loss: 0.13299 RPN box loss: 0.00405 RPN score loss: 0.00233 RPN total loss: 0.00637 Total loss: 0.84961 timestamp: 1654973000.6810586 iteration: 75710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12086 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.18236 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.0004 Mask loss: 0.189 RPN box loss: 0.01026 RPN score loss: 0.00992 RPN total loss: 0.02018 Total loss: 0.98054 timestamp: 1654973003.9076095 iteration: 75715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06386 FastRCNN class loss: 0.05156 FastRCNN total loss: 0.11542 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.0004 Mask loss: 0.13077 RPN box loss: 0.01907 RPN score loss: 0.00629 RPN total loss: 0.02536 Total loss: 0.86054 timestamp: 1654973007.1691065 iteration: 75720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05969 FastRCNN class loss: 0.03787 FastRCNN total loss: 0.09755 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.0004 Mask loss: 0.09498 RPN box loss: 0.0117 RPN score loss: 0.00161 RPN total loss: 0.01331 Total loss: 0.79484 timestamp: 1654973010.3157256 iteration: 75725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0609 FastRCNN class loss: 0.04422 FastRCNN total loss: 0.10512 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.0004 Mask loss: 0.11845 RPN box loss: 0.00563 RPN score loss: 0.00374 RPN total loss: 0.00937 Total loss: 0.82194 timestamp: 1654973013.5595162 iteration: 75730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09288 FastRCNN class loss: 0.08185 FastRCNN total loss: 0.17473 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.0004 Mask loss: 0.10665 RPN box loss: 0.01473 RPN score loss: 0.0019 RPN total loss: 0.01663 Total loss: 0.88701 timestamp: 1654973016.7406929 iteration: 75735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04824 FastRCNN class loss: 0.04136 FastRCNN total loss: 0.0896 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.0004 Mask loss: 0.1182 RPN box loss: 0.03086 RPN score loss: 0.00116 RPN total loss: 0.03202 Total loss: 0.82881 timestamp: 1654973019.937222 iteration: 75740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06733 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.12938 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.0004 Mask loss: 0.12046 RPN box loss: 0.03049 RPN score loss: 0.01195 RPN total loss: 0.04244 Total loss: 0.88127 timestamp: 1654973023.1846836 iteration: 75745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07331 FastRCNN class loss: 0.04665 FastRCNN total loss: 0.11996 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.0004 Mask loss: 0.1329 RPN box loss: 0.00749 RPN score loss: 0.00372 RPN total loss: 0.01121 Total loss: 0.85306 timestamp: 1654973026.3664918 iteration: 75750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06546 FastRCNN class loss: 0.08191 FastRCNN total loss: 0.14737 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.0004 Mask loss: 0.15405 RPN box loss: 0.01118 RPN score loss: 0.007 RPN total loss: 0.01818 Total loss: 0.90858 timestamp: 1654973029.5112817 iteration: 75755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04484 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.11912 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.0004 Mask loss: 0.10973 RPN box loss: 0.01142 RPN score loss: 0.00254 RPN total loss: 0.01396 Total loss: 0.8318 timestamp: 1654973032.6638157 iteration: 75760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05767 FastRCNN class loss: 0.04884 FastRCNN total loss: 0.1065 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.0004 Mask loss: 0.15036 RPN box loss: 0.01313 RPN score loss: 0.00401 RPN total loss: 0.01714 Total loss: 0.863 timestamp: 1654973035.8665254 iteration: 75765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06476 FastRCNN class loss: 0.05815 FastRCNN total loss: 0.12291 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.0004 Mask loss: 0.13124 RPN box loss: 0.00392 RPN score loss: 0.0028 RPN total loss: 0.00671 Total loss: 0.84984 timestamp: 1654973039.0592995 iteration: 75770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08495 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.16412 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.0004 Mask loss: 0.14519 RPN box loss: 0.03482 RPN score loss: 0.00637 RPN total loss: 0.04119 Total loss: 0.93948 timestamp: 1654973042.2364464 iteration: 75775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07041 FastRCNN class loss: 0.06094 FastRCNN total loss: 0.13135 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.0004 Mask loss: 0.14008 RPN box loss: 0.00577 RPN score loss: 0.00564 RPN total loss: 0.01141 Total loss: 0.87181 timestamp: 1654973045.47484 iteration: 75780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05636 FastRCNN class loss: 0.05881 FastRCNN total loss: 0.11517 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.0004 Mask loss: 0.1036 RPN box loss: 0.00757 RPN score loss: 0.00144 RPN total loss: 0.009 Total loss: 0.81675 timestamp: 1654973048.6605163 iteration: 75785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06671 FastRCNN class loss: 0.0531 FastRCNN total loss: 0.11981 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.0004 Mask loss: 0.13533 RPN box loss: 0.00691 RPN score loss: 0.00406 RPN total loss: 0.01096 Total loss: 0.85508 timestamp: 1654973051.8936205 iteration: 75790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0821 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.14658 L1 loss: 0.0000e+00 L2 loss: 0.58897 Learning rate: 0.0004 Mask loss: 0.11934 RPN box loss: 0.01404 RPN score loss: 0.00895 RPN total loss: 0.02299 Total loss: 0.87789 timestamp: 1654973055.0382047 iteration: 75795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06902 FastRCNN class loss: 0.03919 FastRCNN total loss: 0.10821 L1 loss: 0.0000e+00 L2 loss: 0.58897 Learning rate: 0.0004 Mask loss: 0.1195 RPN box loss: 0.01523 RPN score loss: 0.003 RPN total loss: 0.01823 Total loss: 0.83491 timestamp: 1654973058.2240632 iteration: 75800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17741 FastRCNN class loss: 0.11705 FastRCNN total loss: 0.29445 L1 loss: 0.0000e+00 L2 loss: 0.58897 Learning rate: 0.0004 Mask loss: 0.17854 RPN box loss: 0.01714 RPN score loss: 0.00514 RPN total loss: 0.02228 Total loss: 1.08424 timestamp: 1654973061.3880997 iteration: 75805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11026 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.19087 L1 loss: 0.0000e+00 L2 loss: 0.58897 Learning rate: 0.0004 Mask loss: 0.11555 RPN box loss: 0.01378 RPN score loss: 0.00422 RPN total loss: 0.018 Total loss: 0.91339 timestamp: 1654973064.6024852 iteration: 75810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11738 FastRCNN class loss: 0.0908 FastRCNN total loss: 0.20818 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.0004 Mask loss: 0.16676 RPN box loss: 0.0122 RPN score loss: 0.00631 RPN total loss: 0.01851 Total loss: 0.98241 timestamp: 1654973067.796561 iteration: 75815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09513 FastRCNN class loss: 0.07075 FastRCNN total loss: 0.16588 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.0004 Mask loss: 0.1682 RPN box loss: 0.01955 RPN score loss: 0.00814 RPN total loss: 0.02769 Total loss: 0.95074 timestamp: 1654973071.0305471 iteration: 75820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12714 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.19399 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.0004 Mask loss: 0.11913 RPN box loss: 0.00416 RPN score loss: 0.0036 RPN total loss: 0.00777 Total loss: 0.90985 timestamp: 1654973074.2297006 iteration: 75825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05193 FastRCNN class loss: 0.04489 FastRCNN total loss: 0.09682 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.0004 Mask loss: 0.12351 RPN box loss: 0.00941 RPN score loss: 0.00211 RPN total loss: 0.01152 Total loss: 0.8208 timestamp: 1654973077.4268103 iteration: 75830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.16966 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.0004 Mask loss: 0.14246 RPN box loss: 0.02606 RPN score loss: 0.00676 RPN total loss: 0.03282 Total loss: 0.93389 timestamp: 1654973080.608562 iteration: 75835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0982 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.15838 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.0004 Mask loss: 0.11942 RPN box loss: 0.00895 RPN score loss: 0.00167 RPN total loss: 0.01063 Total loss: 0.87738 timestamp: 1654973083.8218844 iteration: 75840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0906 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.14729 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.31561 RPN box loss: 0.0189 RPN score loss: 0.00972 RPN total loss: 0.02862 Total loss: 1.08047 timestamp: 1654973087.057371 iteration: 75845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.15188 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.14566 RPN box loss: 0.01656 RPN score loss: 0.00538 RPN total loss: 0.02194 Total loss: 0.90844 timestamp: 1654973090.230473 iteration: 75850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10661 FastRCNN class loss: 0.10536 FastRCNN total loss: 0.21197 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.17802 RPN box loss: 0.02365 RPN score loss: 0.00715 RPN total loss: 0.0308 Total loss: 1.00975 timestamp: 1654973093.4648762 iteration: 75855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0817 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.15258 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.16992 RPN box loss: 0.01185 RPN score loss: 0.01163 RPN total loss: 0.02348 Total loss: 0.93492 timestamp: 1654973096.6195772 iteration: 75860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06154 FastRCNN class loss: 0.04321 FastRCNN total loss: 0.10475 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.0721 RPN box loss: 0.00702 RPN score loss: 0.00121 RPN total loss: 0.00824 Total loss: 0.77404 timestamp: 1654973099.8423035 iteration: 75865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05367 FastRCNN class loss: 0.04325 FastRCNN total loss: 0.09692 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.0874 RPN box loss: 0.00415 RPN score loss: 0.00263 RPN total loss: 0.00678 Total loss: 0.78005 timestamp: 1654973103.0371637 iteration: 75870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06882 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.14771 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.0004 Mask loss: 0.08528 RPN box loss: 0.00436 RPN score loss: 0.00548 RPN total loss: 0.00984 Total loss: 0.83177 timestamp: 1654973106.2573164 iteration: 75875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04865 FastRCNN class loss: 0.03445 FastRCNN total loss: 0.0831 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.0004 Mask loss: 0.12508 RPN box loss: 0.01051 RPN score loss: 0.00527 RPN total loss: 0.01577 Total loss: 0.81289 timestamp: 1654973109.4635587 iteration: 75880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09249 FastRCNN class loss: 0.04836 FastRCNN total loss: 0.14085 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.0004 Mask loss: 0.10684 RPN box loss: 0.01952 RPN score loss: 0.0005 RPN total loss: 0.02002 Total loss: 0.85665 timestamp: 1654973112.6474357 iteration: 75885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09929 FastRCNN class loss: 0.07269 FastRCNN total loss: 0.17197 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.0004 Mask loss: 0.17407 RPN box loss: 0.00821 RPN score loss: 0.01712 RPN total loss: 0.02533 Total loss: 0.96032 timestamp: 1654973115.8521786 iteration: 75890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.08773 FastRCNN total loss: 0.16991 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.0004 Mask loss: 0.11099 RPN box loss: 0.0172 RPN score loss: 0.00382 RPN total loss: 0.02102 Total loss: 0.89086 timestamp: 1654973119.1123726 iteration: 75895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.0551 FastRCNN total loss: 0.12891 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.0004 Mask loss: 0.10435 RPN box loss: 0.01081 RPN score loss: 0.00374 RPN total loss: 0.01454 Total loss: 0.83674 timestamp: 1654973122.284706 iteration: 75900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10523 FastRCNN class loss: 0.06777 FastRCNN total loss: 0.173 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.0004 Mask loss: 0.11075 RPN box loss: 0.0071 RPN score loss: 0.00148 RPN total loss: 0.00858 Total loss: 0.88127 timestamp: 1654973125.475764 iteration: 75905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.14603 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.0004 Mask loss: 0.16813 RPN box loss: 0.04042 RPN score loss: 0.00416 RPN total loss: 0.04459 Total loss: 0.94768 timestamp: 1654973128.6673656 iteration: 75910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.207 FastRCNN class loss: 0.07685 FastRCNN total loss: 0.28385 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.0004 Mask loss: 0.10937 RPN box loss: 0.0096 RPN score loss: 0.00505 RPN total loss: 0.01465 Total loss: 0.9968 timestamp: 1654973131.8261502 iteration: 75915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07552 FastRCNN class loss: 0.07121 FastRCNN total loss: 0.14672 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.0004 Mask loss: 0.13218 RPN box loss: 0.01227 RPN score loss: 0.00577 RPN total loss: 0.01804 Total loss: 0.88588 timestamp: 1654973134.9131625 iteration: 75920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08393 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.14597 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.0004 Mask loss: 0.14144 RPN box loss: 0.01472 RPN score loss: 0.00487 RPN total loss: 0.01959 Total loss: 0.89593 timestamp: 1654973138.1267607 iteration: 75925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08424 FastRCNN class loss: 0.09159 FastRCNN total loss: 0.17583 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.0004 Mask loss: 0.11229 RPN box loss: 0.01171 RPN score loss: 0.00704 RPN total loss: 0.01875 Total loss: 0.8958 timestamp: 1654973141.3081386 iteration: 75930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12754 FastRCNN class loss: 0.10128 FastRCNN total loss: 0.22881 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.0004 Mask loss: 0.1474 RPN box loss: 0.01477 RPN score loss: 0.00537 RPN total loss: 0.02013 Total loss: 0.98528 timestamp: 1654973144.4444582 iteration: 75935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.112 FastRCNN class loss: 0.05486 FastRCNN total loss: 0.16686 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.0004 Mask loss: 0.10467 RPN box loss: 0.01366 RPN score loss: 0.00315 RPN total loss: 0.01681 Total loss: 0.87726 timestamp: 1654973147.7225637 iteration: 75940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06364 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.12212 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.0004 Mask loss: 0.1421 RPN box loss: 0.00985 RPN score loss: 0.00713 RPN total loss: 0.01698 Total loss: 0.87012 timestamp: 1654973150.896106 iteration: 75945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08458 FastRCNN class loss: 0.09249 FastRCNN total loss: 0.17707 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.0004 Mask loss: 0.14043 RPN box loss: 0.02448 RPN score loss: 0.01137 RPN total loss: 0.03585 Total loss: 0.94227 timestamp: 1654973154.1037087 iteration: 75950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09923 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.15881 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.0004 Mask loss: 0.12221 RPN box loss: 0.01013 RPN score loss: 0.00356 RPN total loss: 0.0137 Total loss: 0.88364 timestamp: 1654973157.2239087 iteration: 75955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16925 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.25253 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.0004 Mask loss: 0.13459 RPN box loss: 0.01735 RPN score loss: 0.00508 RPN total loss: 0.02243 Total loss: 0.99846 timestamp: 1654973160.4858563 iteration: 75960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.17554 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.0004 Mask loss: 0.12433 RPN box loss: 0.00572 RPN score loss: 0.00491 RPN total loss: 0.01062 Total loss: 0.8994 timestamp: 1654973163.6923 iteration: 75965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14599 FastRCNN class loss: 0.10452 FastRCNN total loss: 0.25051 L1 loss: 0.0000e+00 L2 loss: 0.58891 Learning rate: 0.0004 Mask loss: 0.17014 RPN box loss: 0.01486 RPN score loss: 0.01958 RPN total loss: 0.03444 Total loss: 1.044 timestamp: 1654973166.857882 iteration: 75970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.03817 FastRCNN total loss: 0.09914 L1 loss: 0.0000e+00 L2 loss: 0.58891 Learning rate: 0.0004 Mask loss: 0.11899 RPN box loss: 0.00734 RPN score loss: 0.0006 RPN total loss: 0.00793 Total loss: 0.81498 timestamp: 1654973169.999782 iteration: 75975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10763 FastRCNN class loss: 0.08749 FastRCNN total loss: 0.19512 L1 loss: 0.0000e+00 L2 loss: 0.58891 Learning rate: 0.0004 Mask loss: 0.16483 RPN box loss: 0.01017 RPN score loss: 0.00511 RPN total loss: 0.01528 Total loss: 0.96414 timestamp: 1654973173.1903186 iteration: 75980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.0484 FastRCNN total loss: 0.12649 L1 loss: 0.0000e+00 L2 loss: 0.58891 Learning rate: 0.0004 Mask loss: 0.1527 RPN box loss: 0.00334 RPN score loss: 0.00727 RPN total loss: 0.01061 Total loss: 0.87871 timestamp: 1654973176.4396303 iteration: 75985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07155 FastRCNN class loss: 0.05534 FastRCNN total loss: 0.12689 L1 loss: 0.0000e+00 L2 loss: 0.58891 Learning rate: 0.0004 Mask loss: 0.16653 RPN box loss: 0.00908 RPN score loss: 0.00137 RPN total loss: 0.01044 Total loss: 0.89277 timestamp: 1654973179.672719 iteration: 75990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1333 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.2124 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.10858 RPN box loss: 0.01148 RPN score loss: 0.00295 RPN total loss: 0.01443 Total loss: 0.92431 timestamp: 1654973182.807774 iteration: 75995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03661 FastRCNN class loss: 0.02458 FastRCNN total loss: 0.06119 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.09908 RPN box loss: 0.00119 RPN score loss: 0.00211 RPN total loss: 0.0033 Total loss: 0.75247 timestamp: 1654973186.0437624 iteration: 76000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06029 FastRCNN class loss: 0.04174 FastRCNN total loss: 0.10203 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.12403 RPN box loss: 0.00482 RPN score loss: 0.00278 RPN total loss: 0.0076 Total loss: 0.82257 timestamp: 1654973189.1844485 iteration: 76005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10281 FastRCNN class loss: 0.06171 FastRCNN total loss: 0.16452 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.08376 RPN box loss: 0.00575 RPN score loss: 0.00491 RPN total loss: 0.01066 Total loss: 0.84784 timestamp: 1654973192.4390242 iteration: 76010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08001 FastRCNN class loss: 0.11761 FastRCNN total loss: 0.19762 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.16227 RPN box loss: 0.01485 RPN score loss: 0.00543 RPN total loss: 0.02028 Total loss: 0.96908 timestamp: 1654973195.6050882 iteration: 76015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09487 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.1653 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.13514 RPN box loss: 0.00597 RPN score loss: 0.00765 RPN total loss: 0.01362 Total loss: 0.90296 timestamp: 1654973198.8041227 iteration: 76020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11142 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.17762 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.14815 RPN box loss: 0.01454 RPN score loss: 0.00339 RPN total loss: 0.01793 Total loss: 0.9326 timestamp: 1654973202.0206106 iteration: 76025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17714 FastRCNN class loss: 0.08149 FastRCNN total loss: 0.25863 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.0004 Mask loss: 0.09491 RPN box loss: 0.01343 RPN score loss: 0.0038 RPN total loss: 0.01723 Total loss: 0.95966 timestamp: 1654973205.2199981 iteration: 76030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05541 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.10975 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.0004 Mask loss: 0.22582 RPN box loss: 0.00963 RPN score loss: 0.0024 RPN total loss: 0.01203 Total loss: 0.93649 timestamp: 1654973208.4316072 iteration: 76035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05933 FastRCNN class loss: 0.08571 FastRCNN total loss: 0.14504 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.0004 Mask loss: 0.14049 RPN box loss: 0.01968 RPN score loss: 0.00719 RPN total loss: 0.02687 Total loss: 0.90129 timestamp: 1654973211.5806806 iteration: 76040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10847 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.17873 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.0004 Mask loss: 0.15101 RPN box loss: 0.00662 RPN score loss: 0.00129 RPN total loss: 0.00792 Total loss: 0.92655 timestamp: 1654973214.7216897 iteration: 76045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10777 FastRCNN class loss: 0.07008 FastRCNN total loss: 0.17785 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.0004 Mask loss: 0.22122 RPN box loss: 0.0225 RPN score loss: 0.0066 RPN total loss: 0.0291 Total loss: 1.01706 timestamp: 1654973217.9716094 iteration: 76050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07366 FastRCNN class loss: 0.04338 FastRCNN total loss: 0.11704 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.0004 Mask loss: 0.1729 RPN box loss: 0.02803 RPN score loss: 0.00228 RPN total loss: 0.03031 Total loss: 0.90914 timestamp: 1654973221.208166 iteration: 76055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04951 FastRCNN class loss: 0.05307 FastRCNN total loss: 0.10258 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.0004 Mask loss: 0.08843 RPN box loss: 0.02921 RPN score loss: 0.00302 RPN total loss: 0.03223 Total loss: 0.81212 timestamp: 1654973224.4791214 iteration: 76060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09324 FastRCNN class loss: 0.07086 FastRCNN total loss: 0.1641 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.0004 Mask loss: 0.1508 RPN box loss: 0.02317 RPN score loss: 0.00623 RPN total loss: 0.0294 Total loss: 0.93318 timestamp: 1654973227.7217436 iteration: 76065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07756 FastRCNN class loss: 0.06507 FastRCNN total loss: 0.14263 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.0004 Mask loss: 0.10656 RPN box loss: 0.00882 RPN score loss: 0.00261 RPN total loss: 0.01143 Total loss: 0.8495 timestamp: 1654973230.9241104 iteration: 76070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16096 FastRCNN class loss: 0.09069 FastRCNN total loss: 0.25164 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.0004 Mask loss: 0.15427 RPN box loss: 0.02176 RPN score loss: 0.00355 RPN total loss: 0.02532 Total loss: 1.02011 timestamp: 1654973234.1426358 iteration: 76075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11155 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.18751 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.0004 Mask loss: 0.11873 RPN box loss: 0.00578 RPN score loss: 0.00439 RPN total loss: 0.01018 Total loss: 0.9053 timestamp: 1654973237.2814882 iteration: 76080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07945 FastRCNN class loss: 0.04181 FastRCNN total loss: 0.12126 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.0004 Mask loss: 0.0997 RPN box loss: 0.0086 RPN score loss: 0.00376 RPN total loss: 0.01236 Total loss: 0.82219 timestamp: 1654973240.4212215 iteration: 76085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04961 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.10313 L1 loss: 0.0000e+00 L2 loss: 0.58887 Learning rate: 0.0004 Mask loss: 0.10743 RPN box loss: 0.02239 RPN score loss: 0.00754 RPN total loss: 0.02993 Total loss: 0.82936 timestamp: 1654973243.6595263 iteration: 76090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08325 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.14632 L1 loss: 0.0000e+00 L2 loss: 0.58887 Learning rate: 0.0004 Mask loss: 0.11993 RPN box loss: 0.02229 RPN score loss: 0.0014 RPN total loss: 0.02368 Total loss: 0.87881 timestamp: 1654973246.793679 iteration: 76095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09561 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.1619 L1 loss: 0.0000e+00 L2 loss: 0.58887 Learning rate: 0.0004 Mask loss: 0.1658 RPN box loss: 0.0074 RPN score loss: 0.0042 RPN total loss: 0.0116 Total loss: 0.92817 timestamp: 1654973249.9837787 iteration: 76100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05693 FastRCNN class loss: 0.05997 FastRCNN total loss: 0.1169 L1 loss: 0.0000e+00 L2 loss: 0.58887 Learning rate: 0.0004 Mask loss: 0.12985 RPN box loss: 0.01383 RPN score loss: 0.00665 RPN total loss: 0.02048 Total loss: 0.85609 timestamp: 1654973253.1107433 iteration: 76105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09259 FastRCNN class loss: 0.06925 FastRCNN total loss: 0.16185 L1 loss: 0.0000e+00 L2 loss: 0.58887 Learning rate: 0.0004 Mask loss: 0.15529 RPN box loss: 0.00781 RPN score loss: 0.00739 RPN total loss: 0.0152 Total loss: 0.92121 timestamp: 1654973256.3553452 iteration: 76110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09042 FastRCNN class loss: 0.04152 FastRCNN total loss: 0.13194 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.0004 Mask loss: 0.06588 RPN box loss: 0.00424 RPN score loss: 0.00213 RPN total loss: 0.00638 Total loss: 0.79306 timestamp: 1654973259.545315 iteration: 76115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06179 FastRCNN class loss: 0.04177 FastRCNN total loss: 0.10356 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.0004 Mask loss: 0.15037 RPN box loss: 0.01133 RPN score loss: 0.00688 RPN total loss: 0.01822 Total loss: 0.86101 timestamp: 1654973262.8269365 iteration: 76120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09436 FastRCNN class loss: 0.08067 FastRCNN total loss: 0.17503 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.0004 Mask loss: 0.11496 RPN box loss: 0.00946 RPN score loss: 0.00595 RPN total loss: 0.01541 Total loss: 0.89426 timestamp: 1654973266.0847929 iteration: 76125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09197 FastRCNN class loss: 0.09055 FastRCNN total loss: 0.18252 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.0004 Mask loss: 0.11227 RPN box loss: 0.00585 RPN score loss: 0.0044 RPN total loss: 0.01025 Total loss: 0.89389 timestamp: 1654973269.2574215 iteration: 76130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13537 FastRCNN class loss: 0.08758 FastRCNN total loss: 0.22295 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.0004 Mask loss: 0.13637 RPN box loss: 0.01659 RPN score loss: 0.00263 RPN total loss: 0.01921 Total loss: 0.96739 timestamp: 1654973272.5229666 iteration: 76135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09374 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.15552 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.0004 Mask loss: 0.11229 RPN box loss: 0.0141 RPN score loss: 0.00372 RPN total loss: 0.01782 Total loss: 0.87448 timestamp: 1654973275.7220466 iteration: 76140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06967 FastRCNN class loss: 0.04203 FastRCNN total loss: 0.1117 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.0004 Mask loss: 0.08968 RPN box loss: 0.00541 RPN score loss: 0.00241 RPN total loss: 0.00783 Total loss: 0.79806 timestamp: 1654973278.9200613 iteration: 76145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12529 FastRCNN class loss: 0.08407 FastRCNN total loss: 0.20935 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.0004 Mask loss: 0.13328 RPN box loss: 0.00803 RPN score loss: 0.00264 RPN total loss: 0.01067 Total loss: 0.94215 timestamp: 1654973282.1081364 iteration: 76150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07036 FastRCNN class loss: 0.04327 FastRCNN total loss: 0.11363 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.0004 Mask loss: 0.09088 RPN box loss: 0.01421 RPN score loss: 0.0008 RPN total loss: 0.015 Total loss: 0.80837 timestamp: 1654973285.351044 iteration: 76155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08215 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.15458 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.0004 Mask loss: 0.10979 RPN box loss: 0.01189 RPN score loss: 0.00184 RPN total loss: 0.01372 Total loss: 0.86694 timestamp: 1654973288.5770507 iteration: 76160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10676 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.15945 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.0004 Mask loss: 0.08562 RPN box loss: 0.00488 RPN score loss: 0.00225 RPN total loss: 0.00713 Total loss: 0.84105 timestamp: 1654973291.758232 iteration: 76165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09392 FastRCNN class loss: 0.06523 FastRCNN total loss: 0.15915 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.0004 Mask loss: 0.15005 RPN box loss: 0.01131 RPN score loss: 0.01009 RPN total loss: 0.02141 Total loss: 0.91945 timestamp: 1654973294.9057121 iteration: 76170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12339 FastRCNN class loss: 0.12081 FastRCNN total loss: 0.2442 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.0004 Mask loss: 0.12693 RPN box loss: 0.00947 RPN score loss: 0.00465 RPN total loss: 0.01412 Total loss: 0.9741 timestamp: 1654973298.0338745 iteration: 76175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14084 FastRCNN class loss: 0.07291 FastRCNN total loss: 0.21374 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.0004 Mask loss: 0.19009 RPN box loss: 0.01117 RPN score loss: 0.00712 RPN total loss: 0.01829 Total loss: 1.01097 timestamp: 1654973301.2984772 iteration: 76180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07244 FastRCNN class loss: 0.05018 FastRCNN total loss: 0.12262 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.0004 Mask loss: 0.08283 RPN box loss: 0.00484 RPN score loss: 0.00336 RPN total loss: 0.0082 Total loss: 0.80249 timestamp: 1654973304.4909334 iteration: 76185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09555 FastRCNN class loss: 0.09892 FastRCNN total loss: 0.19447 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.0004 Mask loss: 0.16656 RPN box loss: 0.02724 RPN score loss: 0.00868 RPN total loss: 0.03591 Total loss: 0.98579 timestamp: 1654973307.6549115 iteration: 76190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05171 FastRCNN class loss: 0.05074 FastRCNN total loss: 0.10245 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.0004 Mask loss: 0.1672 RPN box loss: 0.013 RPN score loss: 0.0035 RPN total loss: 0.0165 Total loss: 0.87499 timestamp: 1654973310.8978302 iteration: 76195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0682 FastRCNN class loss: 0.03983 FastRCNN total loss: 0.10802 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.0004 Mask loss: 0.1211 RPN box loss: 0.00593 RPN score loss: 0.00296 RPN total loss: 0.00889 Total loss: 0.82685 timestamp: 1654973314.121708 iteration: 76200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04052 FastRCNN class loss: 0.04434 FastRCNN total loss: 0.08486 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.0004 Mask loss: 0.0835 RPN box loss: 0.00481 RPN score loss: 0.00044 RPN total loss: 0.00525 Total loss: 0.76245 timestamp: 1654973317.279246 iteration: 76205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04832 FastRCNN class loss: 0.05819 FastRCNN total loss: 0.10651 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.0004 Mask loss: 0.10406 RPN box loss: 0.00652 RPN score loss: 0.00406 RPN total loss: 0.01058 Total loss: 0.80998 timestamp: 1654973320.5625558 iteration: 76210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06254 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.12305 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.0004 Mask loss: 0.1149 RPN box loss: 0.01079 RPN score loss: 0.00215 RPN total loss: 0.01293 Total loss: 0.83972 timestamp: 1654973323.8520756 iteration: 76215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0899 FastRCNN class loss: 0.05184 FastRCNN total loss: 0.14174 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.0004 Mask loss: 0.1156 RPN box loss: 0.03302 RPN score loss: 0.00503 RPN total loss: 0.03805 Total loss: 0.88422 timestamp: 1654973327.039037 iteration: 76220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06719 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.14726 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.0004 Mask loss: 0.16062 RPN box loss: 0.00456 RPN score loss: 0.00278 RPN total loss: 0.00735 Total loss: 0.90406 timestamp: 1654973330.1859686 iteration: 76225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08651 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.14355 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.0004 Mask loss: 0.11215 RPN box loss: 0.00691 RPN score loss: 0.00464 RPN total loss: 0.01155 Total loss: 0.85607 timestamp: 1654973333.405145 iteration: 76230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10956 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.19247 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.1214 RPN box loss: 0.02974 RPN score loss: 0.00792 RPN total loss: 0.03766 Total loss: 0.94036 timestamp: 1654973336.5136077 iteration: 76235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06016 FastRCNN class loss: 0.07072 FastRCNN total loss: 0.13088 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.1438 RPN box loss: 0.0093 RPN score loss: 0.0044 RPN total loss: 0.0137 Total loss: 0.87721 timestamp: 1654973339.7324839 iteration: 76240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10379 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.18 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.13191 RPN box loss: 0.0154 RPN score loss: 0.0052 RPN total loss: 0.0206 Total loss: 0.92133 timestamp: 1654973342.8639917 iteration: 76245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.0399 FastRCNN total loss: 0.12407 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.10344 RPN box loss: 0.00307 RPN score loss: 0.00082 RPN total loss: 0.00389 Total loss: 0.82023 timestamp: 1654973346.1405199 iteration: 76250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06044 FastRCNN class loss: 0.0449 FastRCNN total loss: 0.10533 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.13209 RPN box loss: 0.00819 RPN score loss: 0.00595 RPN total loss: 0.01414 Total loss: 0.84038 timestamp: 1654973349.4150894 iteration: 76255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09543 FastRCNN class loss: 0.04855 FastRCNN total loss: 0.14398 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.09674 RPN box loss: 0.00379 RPN score loss: 0.00153 RPN total loss: 0.00533 Total loss: 0.83487 timestamp: 1654973352.6665082 iteration: 76260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09903 FastRCNN class loss: 0.11469 FastRCNN total loss: 0.21372 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.13878 RPN box loss: 0.02292 RPN score loss: 0.00165 RPN total loss: 0.02457 Total loss: 0.96589 timestamp: 1654973355.7804165 iteration: 76265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08042 FastRCNN class loss: 0.0677 FastRCNN total loss: 0.14812 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.0004 Mask loss: 0.14233 RPN box loss: 0.00756 RPN score loss: 0.00518 RPN total loss: 0.01274 Total loss: 0.89201 timestamp: 1654973358.956459 iteration: 76270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07678 FastRCNN class loss: 0.04737 FastRCNN total loss: 0.12415 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.0004 Mask loss: 0.14797 RPN box loss: 0.00741 RPN score loss: 0.00612 RPN total loss: 0.01352 Total loss: 0.87446 timestamp: 1654973362.1625032 iteration: 76275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10224 FastRCNN class loss: 0.06066 FastRCNN total loss: 0.1629 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.0004 Mask loss: 0.0953 RPN box loss: 0.01165 RPN score loss: 0.0039 RPN total loss: 0.01555 Total loss: 0.86257 timestamp: 1654973365.3218586 iteration: 76280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0636 FastRCNN class loss: 0.03788 FastRCNN total loss: 0.10148 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.0004 Mask loss: 0.1195 RPN box loss: 0.0075 RPN score loss: 0.00148 RPN total loss: 0.00898 Total loss: 0.81878 timestamp: 1654973368.5948987 iteration: 76285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10663 FastRCNN class loss: 0.07708 FastRCNN total loss: 0.1837 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.0004 Mask loss: 0.11912 RPN box loss: 0.00964 RPN score loss: 0.01054 RPN total loss: 0.02017 Total loss: 0.9118 timestamp: 1654973371.8100977 iteration: 76290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08806 FastRCNN class loss: 0.06391 FastRCNN total loss: 0.15197 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.0004 Mask loss: 0.1475 RPN box loss: 0.02001 RPN score loss: 0.00663 RPN total loss: 0.02664 Total loss: 0.91491 timestamp: 1654973374.9354572 iteration: 76295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14923 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.21663 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.0004 Mask loss: 0.12723 RPN box loss: 0.01891 RPN score loss: 0.00384 RPN total loss: 0.02275 Total loss: 0.95542 timestamp: 1654973378.1230702 iteration: 76300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08836 FastRCNN class loss: 0.05814 FastRCNN total loss: 0.1465 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.0004 Mask loss: 0.1403 RPN box loss: 0.01163 RPN score loss: 0.00366 RPN total loss: 0.01529 Total loss: 0.8909 timestamp: 1654973381.29733 iteration: 76305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07547 FastRCNN class loss: 0.09867 FastRCNN total loss: 0.17414 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.0004 Mask loss: 0.15693 RPN box loss: 0.01134 RPN score loss: 0.00398 RPN total loss: 0.01533 Total loss: 0.93519 timestamp: 1654973384.4935832 iteration: 76310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.075 FastRCNN class loss: 0.07528 FastRCNN total loss: 0.15028 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.0004 Mask loss: 0.21091 RPN box loss: 0.02009 RPN score loss: 0.00681 RPN total loss: 0.0269 Total loss: 0.97689 timestamp: 1654973387.73396 iteration: 76315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.081 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.14085 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.0004 Mask loss: 0.10933 RPN box loss: 0.00704 RPN score loss: 0.00376 RPN total loss: 0.01081 Total loss: 0.84978 timestamp: 1654973390.9178894 iteration: 76320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08769 FastRCNN class loss: 0.11685 FastRCNN total loss: 0.20453 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.0004 Mask loss: 0.13136 RPN box loss: 0.02847 RPN score loss: 0.00184 RPN total loss: 0.03032 Total loss: 0.955 timestamp: 1654973394.0979133 iteration: 76325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11292 FastRCNN class loss: 0.05089 FastRCNN total loss: 0.16381 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.0004 Mask loss: 0.109 RPN box loss: 0.00663 RPN score loss: 0.00329 RPN total loss: 0.00991 Total loss: 0.87152 timestamp: 1654973397.3221147 iteration: 76330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13926 FastRCNN class loss: 0.07771 FastRCNN total loss: 0.21698 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.0004 Mask loss: 0.13585 RPN box loss: 0.03064 RPN score loss: 0.00611 RPN total loss: 0.03675 Total loss: 0.97837 timestamp: 1654973400.4933841 iteration: 76335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06788 FastRCNN class loss: 0.06884 FastRCNN total loss: 0.13672 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.0004 Mask loss: 0.14148 RPN box loss: 0.03512 RPN score loss: 0.00608 RPN total loss: 0.0412 Total loss: 0.90818 timestamp: 1654973403.6811268 iteration: 76340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04853 FastRCNN class loss: 0.03777 FastRCNN total loss: 0.0863 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.0004 Mask loss: 0.10028 RPN box loss: 0.00459 RPN score loss: 0.00058 RPN total loss: 0.00518 Total loss: 0.78055 timestamp: 1654973406.9431808 iteration: 76345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08819 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.15944 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.0004 Mask loss: 0.16192 RPN box loss: 0.01379 RPN score loss: 0.00284 RPN total loss: 0.01663 Total loss: 0.92678 timestamp: 1654973410.1610231 iteration: 76350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07394 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.15642 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.0004 Mask loss: 0.09432 RPN box loss: 0.02348 RPN score loss: 0.00562 RPN total loss: 0.0291 Total loss: 0.86862 timestamp: 1654973413.4069614 iteration: 76355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10565 FastRCNN class loss: 0.10154 FastRCNN total loss: 0.20719 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.0004 Mask loss: 0.13251 RPN box loss: 0.02182 RPN score loss: 0.01073 RPN total loss: 0.03255 Total loss: 0.96103 timestamp: 1654973416.6218925 iteration: 76360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18176 FastRCNN class loss: 0.06318 FastRCNN total loss: 0.24494 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.0004 Mask loss: 0.11385 RPN box loss: 0.0065 RPN score loss: 0.00228 RPN total loss: 0.00878 Total loss: 0.95635 timestamp: 1654973419.8728335 iteration: 76365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13961 FastRCNN class loss: 0.07491 FastRCNN total loss: 0.21452 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.0004 Mask loss: 0.1455 RPN box loss: 0.00946 RPN score loss: 0.00599 RPN total loss: 0.01546 Total loss: 0.96425 timestamp: 1654973423.1048734 iteration: 76370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07266 FastRCNN class loss: 0.06363 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.0004 Mask loss: 0.12003 RPN box loss: 0.00383 RPN score loss: 0.00266 RPN total loss: 0.0065 Total loss: 0.85159 timestamp: 1654973426.3113546 iteration: 76375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05722 FastRCNN class loss: 0.04863 FastRCNN total loss: 0.10584 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.0004 Mask loss: 0.08355 RPN box loss: 0.00431 RPN score loss: 0.00065 RPN total loss: 0.00496 Total loss: 0.78314 timestamp: 1654973429.4234695 iteration: 76380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10991 FastRCNN class loss: 0.06753 FastRCNN total loss: 0.17744 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.0004 Mask loss: 0.10747 RPN box loss: 0.01317 RPN score loss: 0.00258 RPN total loss: 0.01575 Total loss: 0.88944 timestamp: 1654973432.6798866 iteration: 76385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0648 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.11951 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.0004 Mask loss: 0.13578 RPN box loss: 0.00732 RPN score loss: 0.00341 RPN total loss: 0.01073 Total loss: 0.8548 timestamp: 1654973435.8941967 iteration: 76390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04106 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.08559 L1 loss: 0.0000e+00 L2 loss: 0.58877 Learning rate: 0.0004 Mask loss: 0.14308 RPN box loss: 0.0057 RPN score loss: 0.00382 RPN total loss: 0.00952 Total loss: 0.82696 timestamp: 1654973439.0830266 iteration: 76395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09132 FastRCNN class loss: 0.09862 FastRCNN total loss: 0.18994 L1 loss: 0.0000e+00 L2 loss: 0.58877 Learning rate: 0.0004 Mask loss: 0.13999 RPN box loss: 0.00515 RPN score loss: 0.00753 RPN total loss: 0.01268 Total loss: 0.93138 timestamp: 1654973442.313856 iteration: 76400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.14473 L1 loss: 0.0000e+00 L2 loss: 0.58877 Learning rate: 0.0004 Mask loss: 0.11989 RPN box loss: 0.01319 RPN score loss: 0.00476 RPN total loss: 0.01795 Total loss: 0.87135 timestamp: 1654973445.50002 iteration: 76405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07857 FastRCNN class loss: 0.07614 FastRCNN total loss: 0.15471 L1 loss: 0.0000e+00 L2 loss: 0.58877 Learning rate: 0.0004 Mask loss: 0.14197 RPN box loss: 0.01167 RPN score loss: 0.01035 RPN total loss: 0.02202 Total loss: 0.90747 timestamp: 1654973448.6729507 iteration: 76410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06615 FastRCNN class loss: 0.06171 FastRCNN total loss: 0.12786 L1 loss: 0.0000e+00 L2 loss: 0.58877 Learning rate: 0.0004 Mask loss: 0.1195 RPN box loss: 0.01296 RPN score loss: 0.0048 RPN total loss: 0.01776 Total loss: 0.85389 timestamp: 1654973451.932751 iteration: 76415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08861 FastRCNN class loss: 0.07386 FastRCNN total loss: 0.16247 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.16432 RPN box loss: 0.00859 RPN score loss: 0.00313 RPN total loss: 0.01172 Total loss: 0.92727 timestamp: 1654973455.1482704 iteration: 76420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08366 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.15101 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.12688 RPN box loss: 0.0085 RPN score loss: 0.00319 RPN total loss: 0.01169 Total loss: 0.87835 timestamp: 1654973458.3824387 iteration: 76425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10285 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.1836 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.17446 RPN box loss: 0.01263 RPN score loss: 0.00334 RPN total loss: 0.01597 Total loss: 0.96279 timestamp: 1654973461.5974543 iteration: 76430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08252 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.14653 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.10983 RPN box loss: 0.00788 RPN score loss: 0.0115 RPN total loss: 0.01938 Total loss: 0.8645 timestamp: 1654973464.7804193 iteration: 76435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10695 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.18634 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.16473 RPN box loss: 0.01429 RPN score loss: 0.00305 RPN total loss: 0.01734 Total loss: 0.95716 timestamp: 1654973468.0085104 iteration: 76440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07332 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.12827 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.13089 RPN box loss: 0.00754 RPN score loss: 0.00298 RPN total loss: 0.01053 Total loss: 0.85845 timestamp: 1654973471.1755917 iteration: 76445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09626 FastRCNN class loss: 0.06587 FastRCNN total loss: 0.16213 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.13232 RPN box loss: 0.00949 RPN score loss: 0.00147 RPN total loss: 0.01095 Total loss: 0.89416 timestamp: 1654973474.3709652 iteration: 76450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08412 FastRCNN class loss: 0.09102 FastRCNN total loss: 0.17514 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.0004 Mask loss: 0.14948 RPN box loss: 0.00656 RPN score loss: 0.00871 RPN total loss: 0.01527 Total loss: 0.92865 timestamp: 1654973477.5688617 iteration: 76455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06313 FastRCNN class loss: 0.05864 FastRCNN total loss: 0.12177 L1 loss: 0.0000e+00 L2 loss: 0.58875 Learning rate: 0.0004 Mask loss: 0.14123 RPN box loss: 0.00665 RPN score loss: 0.00496 RPN total loss: 0.01161 Total loss: 0.86336 timestamp: 1654973480.7559617 iteration: 76460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13839 FastRCNN class loss: 0.07415 FastRCNN total loss: 0.21254 L1 loss: 0.0000e+00 L2 loss: 0.58875 Learning rate: 0.0004 Mask loss: 0.12707 RPN box loss: 0.01627 RPN score loss: 0.00165 RPN total loss: 0.01792 Total loss: 0.94628 timestamp: 1654973484.0120091 iteration: 76465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13788 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 0.58875 Learning rate: 0.0004 Mask loss: 0.12791 RPN box loss: 0.02236 RPN score loss: 0.00143 RPN total loss: 0.02379 Total loss: 0.941 timestamp: 1654973487.194409 iteration: 76470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07302 FastRCNN class loss: 0.06053 FastRCNN total loss: 0.13354 L1 loss: 0.0000e+00 L2 loss: 0.58875 Learning rate: 0.0004 Mask loss: 0.15424 RPN box loss: 0.00617 RPN score loss: 0.00054 RPN total loss: 0.00671 Total loss: 0.88324 timestamp: 1654973490.3718271 iteration: 76475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06478 FastRCNN class loss: 0.05359 FastRCNN total loss: 0.11838 L1 loss: 0.0000e+00 L2 loss: 0.58875 Learning rate: 0.0004 Mask loss: 0.09536 RPN box loss: 0.00941 RPN score loss: 0.00372 RPN total loss: 0.01313 Total loss: 0.81562 timestamp: 1654973493.602703 iteration: 76480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12115 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.19398 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.0004 Mask loss: 0.09313 RPN box loss: 0.0033 RPN score loss: 0.00256 RPN total loss: 0.00586 Total loss: 0.88171 timestamp: 1654973496.813597 iteration: 76485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08046 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.13475 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.0004 Mask loss: 0.12444 RPN box loss: 0.00626 RPN score loss: 0.00123 RPN total loss: 0.00749 Total loss: 0.85542 timestamp: 1654973500.056302 iteration: 76490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12691 FastRCNN class loss: 0.08303 FastRCNN total loss: 0.20994 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.0004 Mask loss: 0.15284 RPN box loss: 0.0084 RPN score loss: 0.01098 RPN total loss: 0.01938 Total loss: 0.9709 timestamp: 1654973503.2640102 iteration: 76495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12089 FastRCNN class loss: 0.05563 FastRCNN total loss: 0.17652 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.0004 Mask loss: 0.13244 RPN box loss: 0.00827 RPN score loss: 0.00646 RPN total loss: 0.01473 Total loss: 0.91243 timestamp: 1654973506.4298103 iteration: 76500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08508 FastRCNN class loss: 0.04605 FastRCNN total loss: 0.13112 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.0004 Mask loss: 0.12682 RPN box loss: 0.00357 RPN score loss: 0.00354 RPN total loss: 0.00711 Total loss: 0.85379 timestamp: 1654973509.550039 iteration: 76505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05419 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.10825 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.0004 Mask loss: 0.13893 RPN box loss: 0.0176 RPN score loss: 0.00255 RPN total loss: 0.02015 Total loss: 0.85606 timestamp: 1654973512.8459089 iteration: 76510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11069 FastRCNN class loss: 0.0921 FastRCNN total loss: 0.2028 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.0004 Mask loss: 0.10528 RPN box loss: 0.00792 RPN score loss: 0.00589 RPN total loss: 0.01381 Total loss: 0.91062 timestamp: 1654973516.0573776 iteration: 76515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11764 FastRCNN class loss: 0.07124 FastRCNN total loss: 0.18888 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.0004 Mask loss: 0.13837 RPN box loss: 0.00903 RPN score loss: 0.00111 RPN total loss: 0.01014 Total loss: 0.92612 timestamp: 1654973519.2858398 iteration: 76520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11043 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.17849 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.0004 Mask loss: 0.15695 RPN box loss: 0.00504 RPN score loss: 0.00125 RPN total loss: 0.00629 Total loss: 0.93045 timestamp: 1654973522.4757245 iteration: 76525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09147 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.16775 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.0004 Mask loss: 0.14612 RPN box loss: 0.01079 RPN score loss: 0.00658 RPN total loss: 0.01736 Total loss: 0.91996 timestamp: 1654973525.726168 iteration: 76530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.08415 FastRCNN total loss: 0.17925 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.0004 Mask loss: 0.10605 RPN box loss: 0.01076 RPN score loss: 0.0041 RPN total loss: 0.01486 Total loss: 0.88889 timestamp: 1654973528.9248946 iteration: 76535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06272 FastRCNN class loss: 0.09674 FastRCNN total loss: 0.15946 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.0004 Mask loss: 0.16751 RPN box loss: 0.00907 RPN score loss: 0.00267 RPN total loss: 0.01175 Total loss: 0.92744 timestamp: 1654973532.142122 iteration: 76540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11125 FastRCNN class loss: 0.06884 FastRCNN total loss: 0.18009 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.0004 Mask loss: 0.1618 RPN box loss: 0.00906 RPN score loss: 0.00573 RPN total loss: 0.01479 Total loss: 0.94541 timestamp: 1654973535.4178698 iteration: 76545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14195 FastRCNN class loss: 0.12874 FastRCNN total loss: 0.27069 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.0004 Mask loss: 0.19823 RPN box loss: 0.03741 RPN score loss: 0.03045 RPN total loss: 0.06786 Total loss: 1.1255 timestamp: 1654973538.5677636 iteration: 76550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07872 FastRCNN class loss: 0.0328 FastRCNN total loss: 0.11152 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.0004 Mask loss: 0.10947 RPN box loss: 0.00382 RPN score loss: 0.00338 RPN total loss: 0.0072 Total loss: 0.81691 timestamp: 1654973541.8244267 iteration: 76555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04703 FastRCNN class loss: 0.04063 FastRCNN total loss: 0.08766 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.0004 Mask loss: 0.12301 RPN box loss: 0.01438 RPN score loss: 0.00175 RPN total loss: 0.01612 Total loss: 0.81551 timestamp: 1654973545.1928508 iteration: 76560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05266 FastRCNN class loss: 0.03727 FastRCNN total loss: 0.08994 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.0004 Mask loss: 0.14402 RPN box loss: 0.00559 RPN score loss: 0.00204 RPN total loss: 0.00763 Total loss: 0.83031 timestamp: 1654973548.4945679 iteration: 76565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04448 FastRCNN class loss: 0.04423 FastRCNN total loss: 0.08872 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.0004 Mask loss: 0.1186 RPN box loss: 0.0074 RPN score loss: 0.00272 RPN total loss: 0.01012 Total loss: 0.80615 timestamp: 1654973551.6666968 iteration: 76570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0469 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.10293 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.0004 Mask loss: 0.09303 RPN box loss: 0.00543 RPN score loss: 0.00103 RPN total loss: 0.00646 Total loss: 0.79113 timestamp: 1654973554.9084718 iteration: 76575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04765 FastRCNN class loss: 0.04481 FastRCNN total loss: 0.09246 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.0004 Mask loss: 0.10302 RPN box loss: 0.00496 RPN score loss: 0.00328 RPN total loss: 0.00824 Total loss: 0.79243 timestamp: 1654973558.0370255 iteration: 76580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07079 FastRCNN class loss: 0.04163 FastRCNN total loss: 0.11242 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.0004 Mask loss: 0.09985 RPN box loss: 0.00469 RPN score loss: 0.00039 RPN total loss: 0.00508 Total loss: 0.80606 timestamp: 1654973561.2530928 iteration: 76585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06984 FastRCNN class loss: 0.08477 FastRCNN total loss: 0.15461 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.0004 Mask loss: 0.12996 RPN box loss: 0.00773 RPN score loss: 0.00787 RPN total loss: 0.0156 Total loss: 0.88888 timestamp: 1654973564.4101708 iteration: 76590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06582 FastRCNN class loss: 0.05129 FastRCNN total loss: 0.11711 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.0004 Mask loss: 0.14134 RPN box loss: 0.00604 RPN score loss: 0.00311 RPN total loss: 0.00914 Total loss: 0.85631 timestamp: 1654973567.5531008 iteration: 76595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13546 FastRCNN class loss: 0.07926 FastRCNN total loss: 0.21472 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.0004 Mask loss: 0.13896 RPN box loss: 0.01124 RPN score loss: 0.00418 RPN total loss: 0.01542 Total loss: 0.95781 timestamp: 1654973570.8442204 iteration: 76600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.15632 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.0004 Mask loss: 0.12731 RPN box loss: 0.01645 RPN score loss: 0.00832 RPN total loss: 0.02477 Total loss: 0.8971 timestamp: 1654973574.0096524 iteration: 76605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04258 FastRCNN class loss: 0.04894 FastRCNN total loss: 0.09153 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.0004 Mask loss: 0.08868 RPN box loss: 0.00892 RPN score loss: 0.00133 RPN total loss: 0.01025 Total loss: 0.77916 timestamp: 1654973577.2457461 iteration: 76610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10443 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.17763 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.0004 Mask loss: 0.10832 RPN box loss: 0.01869 RPN score loss: 0.00946 RPN total loss: 0.02815 Total loss: 0.9028 timestamp: 1654973580.4138005 iteration: 76615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07308 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.17084 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.0004 Mask loss: 0.1575 RPN box loss: 0.01106 RPN score loss: 0.01051 RPN total loss: 0.02157 Total loss: 0.93861 timestamp: 1654973583.6141245 iteration: 76620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09994 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.16679 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.0004 Mask loss: 0.09256 RPN box loss: 0.04934 RPN score loss: 0.00273 RPN total loss: 0.05206 Total loss: 0.90011 timestamp: 1654973586.7987726 iteration: 76625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06951 FastRCNN class loss: 0.06776 FastRCNN total loss: 0.13727 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.0004 Mask loss: 0.14596 RPN box loss: 0.01684 RPN score loss: 0.00959 RPN total loss: 0.02643 Total loss: 0.89836 timestamp: 1654973590.018986 iteration: 76630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04729 FastRCNN class loss: 0.04113 FastRCNN total loss: 0.08841 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.0004 Mask loss: 0.16236 RPN box loss: 0.00378 RPN score loss: 0.00476 RPN total loss: 0.00854 Total loss: 0.848 timestamp: 1654973593.2068539 iteration: 76635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05499 FastRCNN class loss: 0.05419 FastRCNN total loss: 0.10918 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.0004 Mask loss: 0.08668 RPN box loss: 0.00291 RPN score loss: 0.00825 RPN total loss: 0.01116 Total loss: 0.79571 timestamp: 1654973596.4926245 iteration: 76640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13189 FastRCNN class loss: 0.08489 FastRCNN total loss: 0.21678 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.0004 Mask loss: 0.16672 RPN box loss: 0.02933 RPN score loss: 0.00871 RPN total loss: 0.03805 Total loss: 1.01024 timestamp: 1654973599.7228458 iteration: 76645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11513 FastRCNN class loss: 0.09745 FastRCNN total loss: 0.21258 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.0004 Mask loss: 0.15342 RPN box loss: 0.02457 RPN score loss: 0.01182 RPN total loss: 0.03639 Total loss: 0.99109 timestamp: 1654973602.8538399 iteration: 76650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17851 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.25815 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.0004 Mask loss: 0.11879 RPN box loss: 0.01926 RPN score loss: 0.01248 RPN total loss: 0.03174 Total loss: 0.99736 timestamp: 1654973606.0396953 iteration: 76655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0817 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.14523 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.0004 Mask loss: 0.09388 RPN box loss: 0.00823 RPN score loss: 0.00531 RPN total loss: 0.01354 Total loss: 0.84133 timestamp: 1654973609.2202196 iteration: 76660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.16566 L1 loss: 0.0000e+00 L2 loss: 0.58868 Learning rate: 0.0004 Mask loss: 0.10236 RPN box loss: 0.0149 RPN score loss: 0.00195 RPN total loss: 0.01685 Total loss: 0.87355 timestamp: 1654973612.450991 iteration: 76665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05203 FastRCNN class loss: 0.05071 FastRCNN total loss: 0.10274 L1 loss: 0.0000e+00 L2 loss: 0.58868 Learning rate: 0.0004 Mask loss: 0.12919 RPN box loss: 0.00436 RPN score loss: 0.00174 RPN total loss: 0.0061 Total loss: 0.82671 timestamp: 1654973615.6495278 iteration: 76670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08392 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.14409 L1 loss: 0.0000e+00 L2 loss: 0.58868 Learning rate: 0.0004 Mask loss: 0.12512 RPN box loss: 0.00387 RPN score loss: 0.00535 RPN total loss: 0.00922 Total loss: 0.86711 timestamp: 1654973618.8193457 iteration: 76675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10424 FastRCNN class loss: 0.09265 FastRCNN total loss: 0.19689 L1 loss: 0.0000e+00 L2 loss: 0.58868 Learning rate: 0.0004 Mask loss: 0.13921 RPN box loss: 0.00796 RPN score loss: 0.00086 RPN total loss: 0.00882 Total loss: 0.93359 timestamp: 1654973622.0046687 iteration: 76680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07353 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.12409 L1 loss: 0.0000e+00 L2 loss: 0.58868 Learning rate: 0.0004 Mask loss: 0.11674 RPN box loss: 0.0063 RPN score loss: 0.00272 RPN total loss: 0.00902 Total loss: 0.83853 timestamp: 1654973625.182062 iteration: 76685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07107 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.13426 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.16142 RPN box loss: 0.02256 RPN score loss: 0.00868 RPN total loss: 0.03124 Total loss: 0.9156 timestamp: 1654973628.297025 iteration: 76690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.124 FastRCNN class loss: 0.08788 FastRCNN total loss: 0.21188 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.11557 RPN box loss: 0.00858 RPN score loss: 0.00668 RPN total loss: 0.01525 Total loss: 0.93138 timestamp: 1654973631.5395033 iteration: 76695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11287 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.19579 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.20674 RPN box loss: 0.01486 RPN score loss: 0.0055 RPN total loss: 0.02036 Total loss: 1.01156 timestamp: 1654973634.7280521 iteration: 76700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05328 FastRCNN class loss: 0.0614 FastRCNN total loss: 0.11468 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.15862 RPN box loss: 0.0098 RPN score loss: 0.00081 RPN total loss: 0.01061 Total loss: 0.87258 timestamp: 1654973637.884359 iteration: 76705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07016 FastRCNN class loss: 0.06478 FastRCNN total loss: 0.13493 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.10214 RPN box loss: 0.00581 RPN score loss: 0.00254 RPN total loss: 0.00835 Total loss: 0.83409 timestamp: 1654973641.0841358 iteration: 76710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08359 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.14464 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.17474 RPN box loss: 0.02023 RPN score loss: 0.00436 RPN total loss: 0.02459 Total loss: 0.93264 timestamp: 1654973644.3412838 iteration: 76715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0586 FastRCNN class loss: 0.06403 FastRCNN total loss: 0.12263 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.0004 Mask loss: 0.1457 RPN box loss: 0.00976 RPN score loss: 0.00274 RPN total loss: 0.01251 Total loss: 0.8695 timestamp: 1654973647.5590575 iteration: 76720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06473 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.13252 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.0004 Mask loss: 0.11944 RPN box loss: 0.00565 RPN score loss: 0.00156 RPN total loss: 0.00721 Total loss: 0.84784 timestamp: 1654973650.8240316 iteration: 76725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12245 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.19912 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.0004 Mask loss: 0.12818 RPN box loss: 0.01501 RPN score loss: 0.0025 RPN total loss: 0.01751 Total loss: 0.93347 timestamp: 1654973653.984303 iteration: 76730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09528 FastRCNN class loss: 0.09531 FastRCNN total loss: 0.19059 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.0004 Mask loss: 0.18414 RPN box loss: 0.01364 RPN score loss: 0.00548 RPN total loss: 0.01912 Total loss: 0.98251 timestamp: 1654973657.13594 iteration: 76735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05028 FastRCNN class loss: 0.049 FastRCNN total loss: 0.09928 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.0004 Mask loss: 0.06571 RPN box loss: 0.00894 RPN score loss: 0.00446 RPN total loss: 0.0134 Total loss: 0.76705 timestamp: 1654973660.3893714 iteration: 76740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06206 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.12857 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.0004 Mask loss: 0.16487 RPN box loss: 0.02066 RPN score loss: 0.00179 RPN total loss: 0.02246 Total loss: 0.90455 timestamp: 1654973663.6604564 iteration: 76745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.085 FastRCNN class loss: 0.03447 FastRCNN total loss: 0.11947 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.0004 Mask loss: 0.07855 RPN box loss: 0.01174 RPN score loss: 0.00127 RPN total loss: 0.013 Total loss: 0.79968 timestamp: 1654973666.8478093 iteration: 76750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10521 FastRCNN class loss: 0.09602 FastRCNN total loss: 0.20122 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.0004 Mask loss: 0.12172 RPN box loss: 0.00536 RPN score loss: 0.00191 RPN total loss: 0.00726 Total loss: 0.91886 timestamp: 1654973670.0303237 iteration: 76755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.09162 FastRCNN total loss: 0.18802 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.0004 Mask loss: 0.13209 RPN box loss: 0.00482 RPN score loss: 0.00442 RPN total loss: 0.00924 Total loss: 0.918 timestamp: 1654973673.256644 iteration: 76760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08061 FastRCNN class loss: 0.03543 FastRCNN total loss: 0.11605 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.0004 Mask loss: 0.09204 RPN box loss: 0.02472 RPN score loss: 0.00078 RPN total loss: 0.0255 Total loss: 0.82224 timestamp: 1654973676.4667246 iteration: 76765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09152 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.14923 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.0004 Mask loss: 0.13046 RPN box loss: 0.025 RPN score loss: 0.00705 RPN total loss: 0.03205 Total loss: 0.90039 timestamp: 1654973679.6412582 iteration: 76770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08878 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.16491 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.0004 Mask loss: 0.13479 RPN box loss: 0.00719 RPN score loss: 0.00491 RPN total loss: 0.0121 Total loss: 0.90044 timestamp: 1654973682.8851075 iteration: 76775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06497 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.14548 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.0004 Mask loss: 0.14529 RPN box loss: 0.0104 RPN score loss: 0.00314 RPN total loss: 0.01354 Total loss: 0.89295 timestamp: 1654973686.086413 iteration: 76780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04666 FastRCNN class loss: 0.03858 FastRCNN total loss: 0.08524 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.0004 Mask loss: 0.24702 RPN box loss: 0.00344 RPN score loss: 0.004 RPN total loss: 0.00744 Total loss: 0.92835 timestamp: 1654973689.297851 iteration: 76785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08842 FastRCNN class loss: 0.08509 FastRCNN total loss: 0.17351 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.0004 Mask loss: 0.07933 RPN box loss: 0.01076 RPN score loss: 0.00177 RPN total loss: 0.01253 Total loss: 0.854 timestamp: 1654973692.482291 iteration: 76790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08591 FastRCNN class loss: 0.0538 FastRCNN total loss: 0.13971 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.0004 Mask loss: 0.11399 RPN box loss: 0.0062 RPN score loss: 0.00363 RPN total loss: 0.00983 Total loss: 0.85217 timestamp: 1654973695.7518811 iteration: 76795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0772 FastRCNN class loss: 0.08524 FastRCNN total loss: 0.16244 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.0004 Mask loss: 0.11429 RPN box loss: 0.01094 RPN score loss: 0.00502 RPN total loss: 0.01596 Total loss: 0.88133 timestamp: 1654973698.9623334 iteration: 76800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05734 FastRCNN class loss: 0.04475 FastRCNN total loss: 0.10209 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.0004 Mask loss: 0.14083 RPN box loss: 0.00712 RPN score loss: 0.00067 RPN total loss: 0.00779 Total loss: 0.83935 timestamp: 1654973702.1112695 iteration: 76805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09022 FastRCNN class loss: 0.06292 FastRCNN total loss: 0.15315 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.11222 RPN box loss: 0.00757 RPN score loss: 0.00111 RPN total loss: 0.00868 Total loss: 0.86268 timestamp: 1654973705.2608578 iteration: 76810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03616 FastRCNN class loss: 0.03289 FastRCNN total loss: 0.06905 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.11051 RPN box loss: 0.0257 RPN score loss: 0.00141 RPN total loss: 0.02711 Total loss: 0.79531 timestamp: 1654973708.465439 iteration: 76815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05263 FastRCNN class loss: 0.08348 FastRCNN total loss: 0.13611 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.13797 RPN box loss: 0.01108 RPN score loss: 0.00332 RPN total loss: 0.0144 Total loss: 0.87712 timestamp: 1654973711.5670316 iteration: 76820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09075 FastRCNN class loss: 0.04975 FastRCNN total loss: 0.1405 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.09555 RPN box loss: 0.00329 RPN score loss: 0.00305 RPN total loss: 0.00633 Total loss: 0.83101 timestamp: 1654973714.7119997 iteration: 76825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1146 FastRCNN class loss: 0.06521 FastRCNN total loss: 0.17981 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.14619 RPN box loss: 0.02441 RPN score loss: 0.00535 RPN total loss: 0.02976 Total loss: 0.94439 timestamp: 1654973717.9282465 iteration: 76830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11972 FastRCNN class loss: 0.09883 FastRCNN total loss: 0.21854 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.10922 RPN box loss: 0.01333 RPN score loss: 0.00187 RPN total loss: 0.0152 Total loss: 0.93159 timestamp: 1654973721.1534283 iteration: 76835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10223 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.17184 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.0004 Mask loss: 0.13587 RPN box loss: 0.01587 RPN score loss: 0.00588 RPN total loss: 0.02175 Total loss: 0.91809 timestamp: 1654973724.3325946 iteration: 76840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04924 FastRCNN class loss: 0.05197 FastRCNN total loss: 0.10121 L1 loss: 0.0000e+00 L2 loss: 0.58862 Learning rate: 0.0004 Mask loss: 0.15513 RPN box loss: 0.0088 RPN score loss: 0.00207 RPN total loss: 0.01087 Total loss: 0.85583 timestamp: 1654973727.4279654 iteration: 76845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08131 FastRCNN class loss: 0.06931 FastRCNN total loss: 0.15062 L1 loss: 0.0000e+00 L2 loss: 0.58862 Learning rate: 0.0004 Mask loss: 0.10651 RPN box loss: 0.00782 RPN score loss: 0.00124 RPN total loss: 0.00906 Total loss: 0.85482 timestamp: 1654973730.6667871 iteration: 76850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07779 FastRCNN class loss: 0.04773 FastRCNN total loss: 0.12552 L1 loss: 0.0000e+00 L2 loss: 0.58862 Learning rate: 0.0004 Mask loss: 0.10398 RPN box loss: 0.00585 RPN score loss: 0.00224 RPN total loss: 0.00809 Total loss: 0.82621 timestamp: 1654973733.9267206 iteration: 76855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05524 FastRCNN class loss: 0.03245 FastRCNN total loss: 0.08769 L1 loss: 0.0000e+00 L2 loss: 0.58862 Learning rate: 0.0004 Mask loss: 0.13525 RPN box loss: 0.00675 RPN score loss: 0.00373 RPN total loss: 0.01048 Total loss: 0.82204 timestamp: 1654973737.1396043 iteration: 76860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0618 FastRCNN class loss: 0.05481 FastRCNN total loss: 0.11661 L1 loss: 0.0000e+00 L2 loss: 0.58862 Learning rate: 0.0004 Mask loss: 0.11918 RPN box loss: 0.0174 RPN score loss: 0.00107 RPN total loss: 0.01847 Total loss: 0.84288 timestamp: 1654973740.3864534 iteration: 76865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11363 FastRCNN class loss: 0.09929 FastRCNN total loss: 0.21292 L1 loss: 0.0000e+00 L2 loss: 0.58861 Learning rate: 0.0004 Mask loss: 0.14748 RPN box loss: 0.01349 RPN score loss: 0.00313 RPN total loss: 0.01663 Total loss: 0.96564 timestamp: 1654973743.5961757 iteration: 76870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08554 FastRCNN class loss: 0.04183 FastRCNN total loss: 0.12737 L1 loss: 0.0000e+00 L2 loss: 0.58861 Learning rate: 0.0004 Mask loss: 0.14189 RPN box loss: 0.00913 RPN score loss: 0.00263 RPN total loss: 0.01176 Total loss: 0.86963 timestamp: 1654973746.8240576 iteration: 76875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06657 FastRCNN class loss: 0.04367 FastRCNN total loss: 0.11025 L1 loss: 0.0000e+00 L2 loss: 0.58861 Learning rate: 0.0004 Mask loss: 0.10094 RPN box loss: 0.01275 RPN score loss: 0.00214 RPN total loss: 0.01489 Total loss: 0.8147 timestamp: 1654973750.0683122 iteration: 76880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13161 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.20401 L1 loss: 0.0000e+00 L2 loss: 0.58861 Learning rate: 0.0004 Mask loss: 0.10362 RPN box loss: 0.00966 RPN score loss: 0.00585 RPN total loss: 0.01551 Total loss: 0.91175 timestamp: 1654973753.2448227 iteration: 76885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05691 FastRCNN class loss: 0.0289 FastRCNN total loss: 0.0858 L1 loss: 0.0000e+00 L2 loss: 0.58861 Learning rate: 0.0004 Mask loss: 0.08863 RPN box loss: 0.00645 RPN score loss: 0.00759 RPN total loss: 0.01403 Total loss: 0.77707 timestamp: 1654973756.5284643 iteration: 76890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07914 FastRCNN class loss: 0.06357 FastRCNN total loss: 0.14271 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.09276 RPN box loss: 0.00757 RPN score loss: 0.005 RPN total loss: 0.01258 Total loss: 0.83666 timestamp: 1654973759.7346413 iteration: 76895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07964 FastRCNN class loss: 0.07924 FastRCNN total loss: 0.15888 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.13757 RPN box loss: 0.03308 RPN score loss: 0.00433 RPN total loss: 0.03741 Total loss: 0.92246 timestamp: 1654973762.9416606 iteration: 76900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10791 FastRCNN class loss: 0.06613 FastRCNN total loss: 0.17404 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.14212 RPN box loss: 0.03418 RPN score loss: 0.00941 RPN total loss: 0.04359 Total loss: 0.94835 timestamp: 1654973766.2255745 iteration: 76905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.05299 FastRCNN total loss: 0.12715 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.09534 RPN box loss: 0.00795 RPN score loss: 0.0021 RPN total loss: 0.01005 Total loss: 0.82114 timestamp: 1654973769.514395 iteration: 76910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06044 FastRCNN class loss: 0.07218 FastRCNN total loss: 0.13262 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.11905 RPN box loss: 0.00859 RPN score loss: 0.00108 RPN total loss: 0.00967 Total loss: 0.84994 timestamp: 1654973772.7230425 iteration: 76915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10688 FastRCNN class loss: 0.09711 FastRCNN total loss: 0.20399 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.15452 RPN box loss: 0.01172 RPN score loss: 0.00606 RPN total loss: 0.01778 Total loss: 0.96489 timestamp: 1654973775.9211447 iteration: 76920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05802 FastRCNN class loss: 0.04249 FastRCNN total loss: 0.10051 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.0004 Mask loss: 0.11043 RPN box loss: 0.02458 RPN score loss: 0.00438 RPN total loss: 0.02896 Total loss: 0.8285 timestamp: 1654973779.0487504 iteration: 76925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07401 FastRCNN class loss: 0.05112 FastRCNN total loss: 0.12513 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.12239 RPN box loss: 0.0081 RPN score loss: 0.00062 RPN total loss: 0.00873 Total loss: 0.84484 timestamp: 1654973782.214665 iteration: 76930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.123 FastRCNN class loss: 0.09483 FastRCNN total loss: 0.21783 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.19121 RPN box loss: 0.01395 RPN score loss: 0.00438 RPN total loss: 0.01833 Total loss: 1.01596 timestamp: 1654973785.466602 iteration: 76935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08726 FastRCNN class loss: 0.04526 FastRCNN total loss: 0.13252 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.10412 RPN box loss: 0.01278 RPN score loss: 0.00135 RPN total loss: 0.01413 Total loss: 0.83936 timestamp: 1654973788.6590877 iteration: 76940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14212 FastRCNN class loss: 0.06634 FastRCNN total loss: 0.20847 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.15841 RPN box loss: 0.00786 RPN score loss: 0.01025 RPN total loss: 0.0181 Total loss: 0.97357 timestamp: 1654973791.8337631 iteration: 76945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07317 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.15202 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.14999 RPN box loss: 0.01507 RPN score loss: 0.00946 RPN total loss: 0.02453 Total loss: 0.91512 timestamp: 1654973795.0771217 iteration: 76950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10798 FastRCNN class loss: 0.07647 FastRCNN total loss: 0.18445 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.1792 RPN box loss: 0.01017 RPN score loss: 0.00763 RPN total loss: 0.0178 Total loss: 0.97004 timestamp: 1654973798.2628531 iteration: 76955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07262 FastRCNN class loss: 0.05808 FastRCNN total loss: 0.1307 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.0004 Mask loss: 0.11392 RPN box loss: 0.00415 RPN score loss: 0.01013 RPN total loss: 0.01428 Total loss: 0.84749 timestamp: 1654973801.4609947 iteration: 76960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17606 FastRCNN class loss: 0.06316 FastRCNN total loss: 0.23922 L1 loss: 0.0000e+00 L2 loss: 0.58858 Learning rate: 0.0004 Mask loss: 0.12373 RPN box loss: 0.00718 RPN score loss: 0.00405 RPN total loss: 0.01123 Total loss: 0.96276 timestamp: 1654973804.6549494 iteration: 76965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10895 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.20234 L1 loss: 0.0000e+00 L2 loss: 0.58858 Learning rate: 0.0004 Mask loss: 0.16027 RPN box loss: 0.01083 RPN score loss: 0.00864 RPN total loss: 0.01947 Total loss: 0.97066 timestamp: 1654973807.9076383 iteration: 76970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08518 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.15987 L1 loss: 0.0000e+00 L2 loss: 0.58858 Learning rate: 0.0004 Mask loss: 0.15631 RPN box loss: 0.01105 RPN score loss: 0.00172 RPN total loss: 0.01277 Total loss: 0.91753 timestamp: 1654973811.0780766 iteration: 76975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10511 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.17708 L1 loss: 0.0000e+00 L2 loss: 0.58858 Learning rate: 0.0004 Mask loss: 0.15728 RPN box loss: 0.00666 RPN score loss: 0.00424 RPN total loss: 0.0109 Total loss: 0.93384 timestamp: 1654973814.3350182 iteration: 76980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09228 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.15884 L1 loss: 0.0000e+00 L2 loss: 0.58858 Learning rate: 0.0004 Mask loss: 0.12841 RPN box loss: 0.0094 RPN score loss: 0.00417 RPN total loss: 0.01358 Total loss: 0.8894 timestamp: 1654973817.5493965 iteration: 76985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09927 FastRCNN class loss: 0.04313 FastRCNN total loss: 0.1424 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.0004 Mask loss: 0.12376 RPN box loss: 0.0048 RPN score loss: 0.00468 RPN total loss: 0.00948 Total loss: 0.86422 timestamp: 1654973820.726694 iteration: 76990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06889 FastRCNN class loss: 0.04555 FastRCNN total loss: 0.11443 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.0004 Mask loss: 0.12181 RPN box loss: 0.01237 RPN score loss: 0.00215 RPN total loss: 0.01451 Total loss: 0.83933 timestamp: 1654973823.9652295 iteration: 76995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15571 FastRCNN class loss: 0.05473 FastRCNN total loss: 0.21044 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.0004 Mask loss: 0.1238 RPN box loss: 0.0153 RPN score loss: 0.00172 RPN total loss: 0.01702 Total loss: 0.93983 timestamp: 1654973827.071504 iteration: 77000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11683 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.19907 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.0004 Mask loss: 0.10828 RPN box loss: 0.01429 RPN score loss: 0.00308 RPN total loss: 0.01738 Total loss: 0.91329 timestamp: 1654973830.2535937 iteration: 77005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0458 FastRCNN class loss: 0.04712 FastRCNN total loss: 0.09293 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.0004 Mask loss: 0.09866 RPN box loss: 0.02378 RPN score loss: 0.00143 RPN total loss: 0.02521 Total loss: 0.80536 timestamp: 1654973833.4094274 iteration: 77010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0588 FastRCNN class loss: 0.06012 FastRCNN total loss: 0.11893 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.0004 Mask loss: 0.10861 RPN box loss: 0.01152 RPN score loss: 0.00449 RPN total loss: 0.01601 Total loss: 0.83212 timestamp: 1654973836.6436694 iteration: 77015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0856 FastRCNN class loss: 0.04257 FastRCNN total loss: 0.12817 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.0004 Mask loss: 0.0886 RPN box loss: 0.02531 RPN score loss: 0.00701 RPN total loss: 0.03232 Total loss: 0.83766 timestamp: 1654973839.8040562 iteration: 77020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04974 FastRCNN class loss: 0.04141 FastRCNN total loss: 0.09115 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.0004 Mask loss: 0.12992 RPN box loss: 0.01907 RPN score loss: 0.00198 RPN total loss: 0.02105 Total loss: 0.83068 timestamp: 1654973843.0409973 iteration: 77025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12161 FastRCNN class loss: 0.05128 FastRCNN total loss: 0.17289 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.0004 Mask loss: 0.07498 RPN box loss: 0.0084 RPN score loss: 0.00114 RPN total loss: 0.00954 Total loss: 0.84598 timestamp: 1654973846.2246969 iteration: 77030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.06572 FastRCNN total loss: 0.1763 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.0004 Mask loss: 0.11124 RPN box loss: 0.00566 RPN score loss: 0.00378 RPN total loss: 0.00944 Total loss: 0.88554 timestamp: 1654973849.400052 iteration: 77035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09279 FastRCNN class loss: 0.09792 FastRCNN total loss: 0.19071 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.0004 Mask loss: 0.12782 RPN box loss: 0.01103 RPN score loss: 0.00533 RPN total loss: 0.01637 Total loss: 0.92345 timestamp: 1654973852.605879 iteration: 77040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07784 FastRCNN class loss: 0.05588 FastRCNN total loss: 0.13373 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.0004 Mask loss: 0.12592 RPN box loss: 0.01053 RPN score loss: 0.00566 RPN total loss: 0.01619 Total loss: 0.8644 timestamp: 1654973855.7633748 iteration: 77045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12006 FastRCNN class loss: 0.11585 FastRCNN total loss: 0.23592 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.0004 Mask loss: 0.21736 RPN box loss: 0.00609 RPN score loss: 0.00789 RPN total loss: 0.01398 Total loss: 1.05581 timestamp: 1654973858.9471023 iteration: 77050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11535 FastRCNN class loss: 0.09768 FastRCNN total loss: 0.21303 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.0004 Mask loss: 0.10857 RPN box loss: 0.01237 RPN score loss: 0.00464 RPN total loss: 0.01701 Total loss: 0.92716 timestamp: 1654973862.1205618 iteration: 77055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07842 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.1432 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.0004 Mask loss: 0.12084 RPN box loss: 0.0196 RPN score loss: 0.00315 RPN total loss: 0.02275 Total loss: 0.87534 timestamp: 1654973865.392344 iteration: 77060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06022 FastRCNN class loss: 0.0455 FastRCNN total loss: 0.10572 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.0004 Mask loss: 0.14786 RPN box loss: 0.01017 RPN score loss: 0.00193 RPN total loss: 0.0121 Total loss: 0.85423 timestamp: 1654973868.5899742 iteration: 77065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04307 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.0915 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.0004 Mask loss: 0.13736 RPN box loss: 0.00326 RPN score loss: 0.00475 RPN total loss: 0.00801 Total loss: 0.82542 timestamp: 1654973871.7876809 iteration: 77070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08432 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.15037 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.0004 Mask loss: 0.17128 RPN box loss: 0.01568 RPN score loss: 0.00163 RPN total loss: 0.01731 Total loss: 0.92751 timestamp: 1654973874.9677305 iteration: 77075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06888 FastRCNN class loss: 0.04773 FastRCNN total loss: 0.11661 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.15903 RPN box loss: 0.01221 RPN score loss: 0.00542 RPN total loss: 0.01763 Total loss: 0.88182 timestamp: 1654973878.168809 iteration: 77080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07181 FastRCNN class loss: 0.0586 FastRCNN total loss: 0.13041 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.16775 RPN box loss: 0.00575 RPN score loss: 0.0074 RPN total loss: 0.01316 Total loss: 0.89986 timestamp: 1654973881.3953831 iteration: 77085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11554 FastRCNN class loss: 0.10904 FastRCNN total loss: 0.22458 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.16474 RPN box loss: 0.01133 RPN score loss: 0.00272 RPN total loss: 0.01404 Total loss: 0.99191 timestamp: 1654973884.639871 iteration: 77090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12435 FastRCNN class loss: 0.07074 FastRCNN total loss: 0.19509 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.11069 RPN box loss: 0.01907 RPN score loss: 0.00211 RPN total loss: 0.02118 Total loss: 0.9155 timestamp: 1654973887.8348489 iteration: 77095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06472 FastRCNN class loss: 0.05466 FastRCNN total loss: 0.11938 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.11551 RPN box loss: 0.00809 RPN score loss: 0.00957 RPN total loss: 0.01765 Total loss: 0.84109 timestamp: 1654973890.987467 iteration: 77100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06757 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.1354 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.18389 RPN box loss: 0.01871 RPN score loss: 0.01496 RPN total loss: 0.03368 Total loss: 0.94151 timestamp: 1654973894.1811223 iteration: 77105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07671 FastRCNN class loss: 0.03354 FastRCNN total loss: 0.11026 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.0004 Mask loss: 0.12912 RPN box loss: 0.00128 RPN score loss: 0.00207 RPN total loss: 0.00335 Total loss: 0.83127 timestamp: 1654973897.395346 iteration: 77110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0431 FastRCNN class loss: 0.03131 FastRCNN total loss: 0.07442 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.0004 Mask loss: 0.08038 RPN box loss: 0.00245 RPN score loss: 0.00374 RPN total loss: 0.0062 Total loss: 0.74952 timestamp: 1654973900.5823188 iteration: 77115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07326 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.12915 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.0004 Mask loss: 0.12429 RPN box loss: 0.00977 RPN score loss: 0.00124 RPN total loss: 0.01101 Total loss: 0.85298 timestamp: 1654973903.7653809 iteration: 77120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11074 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.20043 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.0004 Mask loss: 0.1299 RPN box loss: 0.01131 RPN score loss: 0.01422 RPN total loss: 0.02554 Total loss: 0.9444 timestamp: 1654973906.9850316 iteration: 77125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07814 FastRCNN class loss: 0.06751 FastRCNN total loss: 0.14565 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.0004 Mask loss: 0.1343 RPN box loss: 0.00799 RPN score loss: 0.00347 RPN total loss: 0.01145 Total loss: 0.87993 timestamp: 1654973910.1718001 iteration: 77130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10937 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.1678 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.0004 Mask loss: 0.12963 RPN box loss: 0.0088 RPN score loss: 0.00092 RPN total loss: 0.00972 Total loss: 0.89568 timestamp: 1654973913.3633213 iteration: 77135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11461 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.19086 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.0004 Mask loss: 0.09876 RPN box loss: 0.03207 RPN score loss: 0.00441 RPN total loss: 0.03649 Total loss: 0.91463 timestamp: 1654973916.5315216 iteration: 77140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07962 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.13735 L1 loss: 0.0000e+00 L2 loss: 0.58852 Learning rate: 0.0004 Mask loss: 0.13486 RPN box loss: 0.01156 RPN score loss: 0.00263 RPN total loss: 0.0142 Total loss: 0.87492 timestamp: 1654973919.6949103 iteration: 77145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08973 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.17315 L1 loss: 0.0000e+00 L2 loss: 0.58852 Learning rate: 0.0004 Mask loss: 0.14143 RPN box loss: 0.01096 RPN score loss: 0.00626 RPN total loss: 0.01722 Total loss: 0.92032 timestamp: 1654973922.887398 iteration: 77150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06194 FastRCNN class loss: 0.05765 FastRCNN total loss: 0.11959 L1 loss: 0.0000e+00 L2 loss: 0.58852 Learning rate: 0.0004 Mask loss: 0.12498 RPN box loss: 0.00674 RPN score loss: 0.00166 RPN total loss: 0.0084 Total loss: 0.84149 timestamp: 1654973926.0542533 iteration: 77155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06768 FastRCNN class loss: 0.06959 FastRCNN total loss: 0.13727 L1 loss: 0.0000e+00 L2 loss: 0.58852 Learning rate: 0.0004 Mask loss: 0.10307 RPN box loss: 0.00886 RPN score loss: 0.00254 RPN total loss: 0.0114 Total loss: 0.84026 timestamp: 1654973929.243165 iteration: 77160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09611 FastRCNN class loss: 0.11879 FastRCNN total loss: 0.2149 L1 loss: 0.0000e+00 L2 loss: 0.58852 Learning rate: 0.0004 Mask loss: 0.15707 RPN box loss: 0.02501 RPN score loss: 0.00582 RPN total loss: 0.03083 Total loss: 0.99131 timestamp: 1654973932.4350162 iteration: 77165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07914 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.12678 RPN box loss: 0.02018 RPN score loss: 0.00478 RPN total loss: 0.02496 Total loss: 0.87774 timestamp: 1654973935.6251369 iteration: 77170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13719 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.21259 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.16079 RPN box loss: 0.00497 RPN score loss: 0.00159 RPN total loss: 0.00656 Total loss: 0.96846 timestamp: 1654973938.7906733 iteration: 77175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.11758 FastRCNN total loss: 0.23655 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.16866 RPN box loss: 0.01161 RPN score loss: 0.00494 RPN total loss: 0.01656 Total loss: 1.01028 timestamp: 1654973941.9694765 iteration: 77180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08103 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.17223 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.11106 RPN box loss: 0.02265 RPN score loss: 0.00276 RPN total loss: 0.02541 Total loss: 0.89721 timestamp: 1654973945.1869228 iteration: 77185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07595 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.16093 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.13826 RPN box loss: 0.00496 RPN score loss: 0.00335 RPN total loss: 0.00831 Total loss: 0.89601 timestamp: 1654973948.4611568 iteration: 77190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09965 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.16547 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.10503 RPN box loss: 0.00431 RPN score loss: 0.0026 RPN total loss: 0.00691 Total loss: 0.86592 timestamp: 1654973951.6468446 iteration: 77195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08783 FastRCNN class loss: 0.07191 FastRCNN total loss: 0.15974 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.0004 Mask loss: 0.1748 RPN box loss: 0.00511 RPN score loss: 0.00691 RPN total loss: 0.01201 Total loss: 0.93506 timestamp: 1654973954.9012074 iteration: 77200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07343 FastRCNN class loss: 0.08688 FastRCNN total loss: 0.16031 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.0004 Mask loss: 0.17554 RPN box loss: 0.0068 RPN score loss: 0.00244 RPN total loss: 0.00925 Total loss: 0.93361 timestamp: 1654973958.0995736 iteration: 77205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08565 FastRCNN class loss: 0.12192 FastRCNN total loss: 0.20757 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.0004 Mask loss: 0.08445 RPN box loss: 0.0027 RPN score loss: 0.00232 RPN total loss: 0.00502 Total loss: 0.88555 timestamp: 1654973961.30139 iteration: 77210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.04645 FastRCNN total loss: 0.12026 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.0004 Mask loss: 0.12693 RPN box loss: 0.00717 RPN score loss: 0.00392 RPN total loss: 0.01109 Total loss: 0.84678 timestamp: 1654973964.5403652 iteration: 77215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13171 FastRCNN class loss: 0.08642 FastRCNN total loss: 0.21813 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.0004 Mask loss: 0.16289 RPN box loss: 0.01321 RPN score loss: 0.01296 RPN total loss: 0.02616 Total loss: 0.99568 timestamp: 1654973967.7241337 iteration: 77220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06126 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.12444 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.0004 Mask loss: 0.22157 RPN box loss: 0.01227 RPN score loss: 0.00256 RPN total loss: 0.01483 Total loss: 0.94934 timestamp: 1654973970.9738455 iteration: 77225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10346 FastRCNN class loss: 0.06126 FastRCNN total loss: 0.16472 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.0004 Mask loss: 0.11754 RPN box loss: 0.00621 RPN score loss: 0.00211 RPN total loss: 0.00832 Total loss: 0.87908 timestamp: 1654973974.157425 iteration: 77230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08758 FastRCNN class loss: 0.09079 FastRCNN total loss: 0.17837 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.0004 Mask loss: 0.17463 RPN box loss: 0.01258 RPN score loss: 0.00426 RPN total loss: 0.01684 Total loss: 0.95834 timestamp: 1654973977.4817681 iteration: 77235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09482 FastRCNN class loss: 0.05107 FastRCNN total loss: 0.14589 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.0004 Mask loss: 0.09256 RPN box loss: 0.00625 RPN score loss: 0.00435 RPN total loss: 0.0106 Total loss: 0.83754 timestamp: 1654973980.6514735 iteration: 77240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10454 FastRCNN class loss: 0.13072 FastRCNN total loss: 0.23525 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.0004 Mask loss: 0.20307 RPN box loss: 0.01409 RPN score loss: 0.00537 RPN total loss: 0.01947 Total loss: 1.04629 timestamp: 1654973983.8598664 iteration: 77245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.06084 FastRCNN total loss: 0.1727 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.0004 Mask loss: 0.11026 RPN box loss: 0.00795 RPN score loss: 0.00586 RPN total loss: 0.01382 Total loss: 0.88527 timestamp: 1654973987.0883698 iteration: 77250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11155 FastRCNN class loss: 0.0684 FastRCNN total loss: 0.17995 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.0004 Mask loss: 0.15584 RPN box loss: 0.01867 RPN score loss: 0.00189 RPN total loss: 0.02056 Total loss: 0.94484 timestamp: 1654973990.290009 iteration: 77255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08227 FastRCNN class loss: 0.09231 FastRCNN total loss: 0.17458 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.0004 Mask loss: 0.1294 RPN box loss: 0.01065 RPN score loss: 0.00408 RPN total loss: 0.01473 Total loss: 0.90719 timestamp: 1654973993.514575 iteration: 77260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.08878 FastRCNN total loss: 0.20031 L1 loss: 0.0000e+00 L2 loss: 0.58848 Learning rate: 0.0004 Mask loss: 0.13153 RPN box loss: 0.04114 RPN score loss: 0.00827 RPN total loss: 0.04941 Total loss: 0.96973 timestamp: 1654973996.7031102 iteration: 77265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.04384 FastRCNN total loss: 0.10625 L1 loss: 0.0000e+00 L2 loss: 0.58848 Learning rate: 0.0004 Mask loss: 0.084 RPN box loss: 0.01211 RPN score loss: 0.0015 RPN total loss: 0.01362 Total loss: 0.79235 timestamp: 1654973999.9319706 iteration: 77270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04681 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.11109 L1 loss: 0.0000e+00 L2 loss: 0.58848 Learning rate: 0.0004 Mask loss: 0.14056 RPN box loss: 0.00483 RPN score loss: 0.0023 RPN total loss: 0.00713 Total loss: 0.84726 timestamp: 1654974003.1485305 iteration: 77275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06214 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.14095 L1 loss: 0.0000e+00 L2 loss: 0.58848 Learning rate: 0.0004 Mask loss: 0.11645 RPN box loss: 0.00596 RPN score loss: 0.00137 RPN total loss: 0.00734 Total loss: 0.85321 timestamp: 1654974006.363492 iteration: 77280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08719 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.15207 L1 loss: 0.0000e+00 L2 loss: 0.58848 Learning rate: 0.0004 Mask loss: 0.11436 RPN box loss: 0.00771 RPN score loss: 0.00629 RPN total loss: 0.014 Total loss: 0.86891 timestamp: 1654974009.549374 iteration: 77285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06506 FastRCNN class loss: 0.0529 FastRCNN total loss: 0.11797 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.091 RPN box loss: 0.01008 RPN score loss: 0.00378 RPN total loss: 0.01385 Total loss: 0.8113 timestamp: 1654974012.7310922 iteration: 77290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09531 FastRCNN class loss: 0.0556 FastRCNN total loss: 0.15091 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.11244 RPN box loss: 0.0106 RPN score loss: 0.00274 RPN total loss: 0.01334 Total loss: 0.86516 timestamp: 1654974015.890915 iteration: 77295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05379 FastRCNN class loss: 0.05485 FastRCNN total loss: 0.10865 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.08485 RPN box loss: 0.00788 RPN score loss: 0.00474 RPN total loss: 0.01262 Total loss: 0.79458 timestamp: 1654974019.0831015 iteration: 77300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09091 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.16266 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.13265 RPN box loss: 0.0082 RPN score loss: 0.00389 RPN total loss: 0.01209 Total loss: 0.89588 timestamp: 1654974022.2194383 iteration: 77305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0788 FastRCNN class loss: 0.0516 FastRCNN total loss: 0.1304 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.10927 RPN box loss: 0.00673 RPN score loss: 0.00465 RPN total loss: 0.01138 Total loss: 0.83952 timestamp: 1654974025.4314294 iteration: 77310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10188 FastRCNN class loss: 0.0632 FastRCNN total loss: 0.16509 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.12298 RPN box loss: 0.01219 RPN score loss: 0.00404 RPN total loss: 0.01623 Total loss: 0.89277 timestamp: 1654974028.6707304 iteration: 77315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05478 FastRCNN class loss: 0.04763 FastRCNN total loss: 0.10241 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.0004 Mask loss: 0.13884 RPN box loss: 0.00745 RPN score loss: 0.00189 RPN total loss: 0.00935 Total loss: 0.83906 timestamp: 1654974031.9225252 iteration: 77320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14399 FastRCNN class loss: 0.07737 FastRCNN total loss: 0.22135 L1 loss: 0.0000e+00 L2 loss: 0.58846 Learning rate: 0.0004 Mask loss: 0.15762 RPN box loss: 0.01752 RPN score loss: 0.00317 RPN total loss: 0.02069 Total loss: 0.98812 timestamp: 1654974035.0813744 iteration: 77325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08204 FastRCNN class loss: 0.07504 FastRCNN total loss: 0.15708 L1 loss: 0.0000e+00 L2 loss: 0.58846 Learning rate: 0.0004 Mask loss: 0.11918 RPN box loss: 0.00746 RPN score loss: 0.00974 RPN total loss: 0.0172 Total loss: 0.88193 timestamp: 1654974038.291561 iteration: 77330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1149 FastRCNN class loss: 0.09034 FastRCNN total loss: 0.20524 L1 loss: 0.0000e+00 L2 loss: 0.58846 Learning rate: 0.0004 Mask loss: 0.14617 RPN box loss: 0.02522 RPN score loss: 0.03106 RPN total loss: 0.05628 Total loss: 0.99615 timestamp: 1654974041.5413423 iteration: 77335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07495 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.13145 L1 loss: 0.0000e+00 L2 loss: 0.58846 Learning rate: 0.0004 Mask loss: 0.16191 RPN box loss: 0.00731 RPN score loss: 0.00242 RPN total loss: 0.00973 Total loss: 0.89155 timestamp: 1654974044.6902661 iteration: 77340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07988 FastRCNN class loss: 0.04997 FastRCNN total loss: 0.12984 L1 loss: 0.0000e+00 L2 loss: 0.58846 Learning rate: 0.0004 Mask loss: 0.10441 RPN box loss: 0.02896 RPN score loss: 0.0018 RPN total loss: 0.03076 Total loss: 0.85347 timestamp: 1654974047.8863502 iteration: 77345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07839 FastRCNN class loss: 0.05886 FastRCNN total loss: 0.13725 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.15777 RPN box loss: 0.00664 RPN score loss: 0.00656 RPN total loss: 0.0132 Total loss: 0.89668 timestamp: 1654974051.0808284 iteration: 77350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08333 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.14916 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.145 RPN box loss: 0.03837 RPN score loss: 0.00296 RPN total loss: 0.04133 Total loss: 0.92395 timestamp: 1654974054.2872841 iteration: 77355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13978 FastRCNN class loss: 0.07533 FastRCNN total loss: 0.21511 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.16139 RPN box loss: 0.00548 RPN score loss: 0.00319 RPN total loss: 0.00867 Total loss: 0.97362 timestamp: 1654974057.4559186 iteration: 77360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06236 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.13776 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.15381 RPN box loss: 0.01351 RPN score loss: 0.00194 RPN total loss: 0.01545 Total loss: 0.89547 timestamp: 1654974060.6775813 iteration: 77365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.03316 FastRCNN total loss: 0.1078 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.15853 RPN box loss: 0.00375 RPN score loss: 0.00228 RPN total loss: 0.00603 Total loss: 0.86081 timestamp: 1654974063.9068794 iteration: 77370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12577 FastRCNN class loss: 0.08307 FastRCNN total loss: 0.20884 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.11362 RPN box loss: 0.03377 RPN score loss: 0.00899 RPN total loss: 0.04276 Total loss: 0.95367 timestamp: 1654974067.084074 iteration: 77375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06062 FastRCNN class loss: 0.0443 FastRCNN total loss: 0.10492 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.0004 Mask loss: 0.12724 RPN box loss: 0.01674 RPN score loss: 0.0053 RPN total loss: 0.02204 Total loss: 0.84264 timestamp: 1654974070.3100967 iteration: 77380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07388 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.15682 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.0004 Mask loss: 0.14961 RPN box loss: 0.01685 RPN score loss: 0.01202 RPN total loss: 0.02887 Total loss: 0.92375 timestamp: 1654974073.4383707 iteration: 77385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09438 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.16634 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.0004 Mask loss: 0.14533 RPN box loss: 0.01285 RPN score loss: 0.01415 RPN total loss: 0.027 Total loss: 0.92712 timestamp: 1654974076.65449 iteration: 77390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05814 FastRCNN class loss: 0.05467 FastRCNN total loss: 0.11282 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.0004 Mask loss: 0.14066 RPN box loss: 0.0081 RPN score loss: 0.00168 RPN total loss: 0.00979 Total loss: 0.85171 timestamp: 1654974079.8865237 iteration: 77395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06579 FastRCNN class loss: 0.04909 FastRCNN total loss: 0.11488 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.0004 Mask loss: 0.10776 RPN box loss: 0.00733 RPN score loss: 0.00197 RPN total loss: 0.0093 Total loss: 0.82038 timestamp: 1654974083.0814533 iteration: 77400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09856 FastRCNN class loss: 0.06271 FastRCNN total loss: 0.16127 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.0004 Mask loss: 0.12127 RPN box loss: 0.00504 RPN score loss: 0.00506 RPN total loss: 0.0101 Total loss: 0.88107 timestamp: 1654974086.358797 iteration: 77405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09314 FastRCNN class loss: 0.07586 FastRCNN total loss: 0.169 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.0004 Mask loss: 0.13046 RPN box loss: 0.02494 RPN score loss: 0.01046 RPN total loss: 0.03541 Total loss: 0.9233 timestamp: 1654974089.5099404 iteration: 77410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11857 FastRCNN class loss: 0.09256 FastRCNN total loss: 0.21113 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.0004 Mask loss: 0.11651 RPN box loss: 0.00978 RPN score loss: 0.01562 RPN total loss: 0.0254 Total loss: 0.94147 timestamp: 1654974092.672613 iteration: 77415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04261 FastRCNN class loss: 0.03065 FastRCNN total loss: 0.07327 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.0004 Mask loss: 0.08408 RPN box loss: 0.01161 RPN score loss: 0.00191 RPN total loss: 0.01352 Total loss: 0.75929 timestamp: 1654974095.854007 iteration: 77420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08729 FastRCNN class loss: 0.05063 FastRCNN total loss: 0.13792 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.0004 Mask loss: 0.1117 RPN box loss: 0.01622 RPN score loss: 0.00496 RPN total loss: 0.02117 Total loss: 0.85922 timestamp: 1654974099.0616763 iteration: 77425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0764 FastRCNN class loss: 0.03624 FastRCNN total loss: 0.11264 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.0004 Mask loss: 0.11377 RPN box loss: 0.00449 RPN score loss: 0.01143 RPN total loss: 0.01592 Total loss: 0.83076 timestamp: 1654974102.325213 iteration: 77430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06734 FastRCNN class loss: 0.04058 FastRCNN total loss: 0.10792 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.0004 Mask loss: 0.13707 RPN box loss: 0.00565 RPN score loss: 0.00617 RPN total loss: 0.01182 Total loss: 0.84524 timestamp: 1654974105.4884417 iteration: 77435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13849 FastRCNN class loss: 0.11629 FastRCNN total loss: 0.25478 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.0004 Mask loss: 0.16171 RPN box loss: 0.0164 RPN score loss: 0.00643 RPN total loss: 0.02283 Total loss: 1.02775 timestamp: 1654974108.7223215 iteration: 77440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0502 FastRCNN class loss: 0.05588 FastRCNN total loss: 0.10608 L1 loss: 0.0000e+00 L2 loss: 0.58842 Learning rate: 0.0004 Mask loss: 0.09593 RPN box loss: 0.00355 RPN score loss: 0.00745 RPN total loss: 0.011 Total loss: 0.80143 timestamp: 1654974111.9030201 iteration: 77445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07756 FastRCNN class loss: 0.044 FastRCNN total loss: 0.12156 L1 loss: 0.0000e+00 L2 loss: 0.58842 Learning rate: 0.0004 Mask loss: 0.10079 RPN box loss: 0.01928 RPN score loss: 0.00146 RPN total loss: 0.02074 Total loss: 0.83152 timestamp: 1654974115.0583885 iteration: 77450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08235 FastRCNN class loss: 0.06396 FastRCNN total loss: 0.14631 L1 loss: 0.0000e+00 L2 loss: 0.58842 Learning rate: 0.0004 Mask loss: 0.19798 RPN box loss: 0.01355 RPN score loss: 0.00325 RPN total loss: 0.01679 Total loss: 0.94951 timestamp: 1654974118.296323 iteration: 77455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04097 FastRCNN class loss: 0.04426 FastRCNN total loss: 0.08523 L1 loss: 0.0000e+00 L2 loss: 0.58842 Learning rate: 0.0004 Mask loss: 0.07872 RPN box loss: 0.00618 RPN score loss: 0.00175 RPN total loss: 0.00793 Total loss: 0.7603 timestamp: 1654974121.534105 iteration: 77460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09398 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.15516 L1 loss: 0.0000e+00 L2 loss: 0.58842 Learning rate: 0.0004 Mask loss: 0.10251 RPN box loss: 0.00614 RPN score loss: 0.00451 RPN total loss: 0.01065 Total loss: 0.85675 timestamp: 1654974124.7640328 iteration: 77465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13801 FastRCNN class loss: 0.07314 FastRCNN total loss: 0.21115 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.13273 RPN box loss: 0.00808 RPN score loss: 0.00303 RPN total loss: 0.0111 Total loss: 0.94339 timestamp: 1654974127.9235098 iteration: 77470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08224 FastRCNN class loss: 0.09198 FastRCNN total loss: 0.17422 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.1628 RPN box loss: 0.01549 RPN score loss: 0.00869 RPN total loss: 0.02417 Total loss: 0.94961 timestamp: 1654974131.1471539 iteration: 77475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0795 FastRCNN class loss: 0.1064 FastRCNN total loss: 0.1859 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.11966 RPN box loss: 0.00933 RPN score loss: 0.00417 RPN total loss: 0.0135 Total loss: 0.90747 timestamp: 1654974134.3208635 iteration: 77480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10782 FastRCNN class loss: 0.08165 FastRCNN total loss: 0.18947 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.14548 RPN box loss: 0.03003 RPN score loss: 0.00788 RPN total loss: 0.03792 Total loss: 0.96128 timestamp: 1654974137.5020103 iteration: 77485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08378 FastRCNN class loss: 0.05792 FastRCNN total loss: 0.1417 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.11722 RPN box loss: 0.00568 RPN score loss: 0.00389 RPN total loss: 0.00956 Total loss: 0.8569 timestamp: 1654974140.7386017 iteration: 77490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14966 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.22781 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.17743 RPN box loss: 0.02225 RPN score loss: 0.00217 RPN total loss: 0.02442 Total loss: 1.01806 timestamp: 1654974143.9760911 iteration: 77495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12981 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.19553 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.0004 Mask loss: 0.10671 RPN box loss: 0.00947 RPN score loss: 0.00403 RPN total loss: 0.0135 Total loss: 0.90415 timestamp: 1654974147.1503456 iteration: 77500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09662 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.16847 L1 loss: 0.0000e+00 L2 loss: 0.5884 Learning rate: 0.0004 Mask loss: 0.10258 RPN box loss: 0.00995 RPN score loss: 0.00217 RPN total loss: 0.01211 Total loss: 0.87156 timestamp: 1654974150.3497932 iteration: 77505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.07805 FastRCNN total loss: 0.16404 L1 loss: 0.0000e+00 L2 loss: 0.5884 Learning rate: 0.0004 Mask loss: 0.13893 RPN box loss: 0.01361 RPN score loss: 0.00448 RPN total loss: 0.01809 Total loss: 0.90946 timestamp: 1654974153.5815687 iteration: 77510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04569 FastRCNN class loss: 0.0487 FastRCNN total loss: 0.09439 L1 loss: 0.0000e+00 L2 loss: 0.5884 Learning rate: 0.0004 Mask loss: 0.09515 RPN box loss: 0.00484 RPN score loss: 0.00187 RPN total loss: 0.00672 Total loss: 0.78466 timestamp: 1654974156.6737814 iteration: 77515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14304 FastRCNN class loss: 0.09575 FastRCNN total loss: 0.23878 L1 loss: 0.0000e+00 L2 loss: 0.5884 Learning rate: 0.0004 Mask loss: 0.16261 RPN box loss: 0.01911 RPN score loss: 0.01351 RPN total loss: 0.03262 Total loss: 1.02241 timestamp: 1654974159.8425605 iteration: 77520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07543 FastRCNN class loss: 0.05874 FastRCNN total loss: 0.13417 L1 loss: 0.0000e+00 L2 loss: 0.5884 Learning rate: 0.0004 Mask loss: 0.12173 RPN box loss: 0.01582 RPN score loss: 0.00188 RPN total loss: 0.0177 Total loss: 0.86199 timestamp: 1654974163.080998 iteration: 77525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08659 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.152 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.1463 RPN box loss: 0.01543 RPN score loss: 0.00122 RPN total loss: 0.01665 Total loss: 0.90334 timestamp: 1654974166.262322 iteration: 77530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13816 FastRCNN class loss: 0.10657 FastRCNN total loss: 0.24473 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.16909 RPN box loss: 0.02846 RPN score loss: 0.0036 RPN total loss: 0.03206 Total loss: 1.03428 timestamp: 1654974169.408264 iteration: 77535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.16728 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.2184 RPN box loss: 0.01216 RPN score loss: 0.00247 RPN total loss: 0.01463 Total loss: 0.98869 timestamp: 1654974172.5201557 iteration: 77540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.05164 FastRCNN total loss: 0.1208 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.10311 RPN box loss: 0.01264 RPN score loss: 0.0027 RPN total loss: 0.01533 Total loss: 0.82763 timestamp: 1654974175.725676 iteration: 77545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05261 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.10993 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.19091 RPN box loss: 0.00708 RPN score loss: 0.00494 RPN total loss: 0.01201 Total loss: 0.90124 timestamp: 1654974178.934982 iteration: 77550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06924 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.13329 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.07552 RPN box loss: 0.01295 RPN score loss: 0.00225 RPN total loss: 0.0152 Total loss: 0.81239 timestamp: 1654974182.1686893 iteration: 77555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05724 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.10759 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.0004 Mask loss: 0.15875 RPN box loss: 0.00543 RPN score loss: 0.00692 RPN total loss: 0.01236 Total loss: 0.86708 timestamp: 1654974185.3857138 iteration: 77560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10892 FastRCNN class loss: 0.06672 FastRCNN total loss: 0.17564 L1 loss: 0.0000e+00 L2 loss: 0.58838 Learning rate: 0.0004 Mask loss: 0.22064 RPN box loss: 0.01669 RPN score loss: 0.00572 RPN total loss: 0.02241 Total loss: 1.00708 timestamp: 1654974188.5482643 iteration: 77565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04574 FastRCNN class loss: 0.04545 FastRCNN total loss: 0.09119 L1 loss: 0.0000e+00 L2 loss: 0.58838 Learning rate: 0.0004 Mask loss: 0.09927 RPN box loss: 0.0249 RPN score loss: 0.00691 RPN total loss: 0.03181 Total loss: 0.81065 timestamp: 1654974191.7566388 iteration: 77570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09008 FastRCNN class loss: 0.06818 FastRCNN total loss: 0.15826 L1 loss: 0.0000e+00 L2 loss: 0.58838 Learning rate: 0.0004 Mask loss: 0.08416 RPN box loss: 0.01406 RPN score loss: 0.00188 RPN total loss: 0.01594 Total loss: 0.84674 timestamp: 1654974194.9351246 iteration: 77575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12194 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.19638 L1 loss: 0.0000e+00 L2 loss: 0.58838 Learning rate: 0.0004 Mask loss: 0.14107 RPN box loss: 0.00994 RPN score loss: 0.01098 RPN total loss: 0.02092 Total loss: 0.94675 timestamp: 1654974198.0853376 iteration: 77580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1144 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.18485 L1 loss: 0.0000e+00 L2 loss: 0.58838 Learning rate: 0.0004 Mask loss: 0.33648 RPN box loss: 0.04502 RPN score loss: 0.005 RPN total loss: 0.05001 Total loss: 1.15971 timestamp: 1654974201.3288062 iteration: 77585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07642 FastRCNN class loss: 0.07457 FastRCNN total loss: 0.151 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.13285 RPN box loss: 0.00836 RPN score loss: 0.00621 RPN total loss: 0.01457 Total loss: 0.88679 timestamp: 1654974204.5203204 iteration: 77590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04965 FastRCNN class loss: 0.05892 FastRCNN total loss: 0.10856 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.12004 RPN box loss: 0.00786 RPN score loss: 0.00913 RPN total loss: 0.01699 Total loss: 0.83396 timestamp: 1654974207.6513665 iteration: 77595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09974 FastRCNN class loss: 0.08252 FastRCNN total loss: 0.18226 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.16538 RPN box loss: 0.01146 RPN score loss: 0.00602 RPN total loss: 0.01748 Total loss: 0.9535 timestamp: 1654974210.8092697 iteration: 77600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09938 FastRCNN class loss: 0.04972 FastRCNN total loss: 0.14911 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.11432 RPN box loss: 0.01304 RPN score loss: 0.00101 RPN total loss: 0.01405 Total loss: 0.86585 timestamp: 1654974213.9773061 iteration: 77605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05809 FastRCNN class loss: 0.06418 FastRCNN total loss: 0.12228 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.06665 RPN box loss: 0.00862 RPN score loss: 0.0052 RPN total loss: 0.01382 Total loss: 0.79112 timestamp: 1654974217.1420062 iteration: 77610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07313 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.13419 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.07489 RPN box loss: 0.01501 RPN score loss: 0.00157 RPN total loss: 0.01658 Total loss: 0.81402 timestamp: 1654974220.4470987 iteration: 77615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09913 FastRCNN class loss: 0.09679 FastRCNN total loss: 0.19592 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.0004 Mask loss: 0.13701 RPN box loss: 0.01079 RPN score loss: 0.01273 RPN total loss: 0.02352 Total loss: 0.94481 timestamp: 1654974223.6809008 iteration: 77620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05866 FastRCNN class loss: 0.04788 FastRCNN total loss: 0.10654 L1 loss: 0.0000e+00 L2 loss: 0.58836 Learning rate: 0.0004 Mask loss: 0.11171 RPN box loss: 0.0283 RPN score loss: 0.00415 RPN total loss: 0.03245 Total loss: 0.83907 timestamp: 1654974226.8821445 iteration: 77625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08006 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.13625 L1 loss: 0.0000e+00 L2 loss: 0.58836 Learning rate: 0.0004 Mask loss: 0.15382 RPN box loss: 0.00677 RPN score loss: 0.00441 RPN total loss: 0.01118 Total loss: 0.8896 timestamp: 1654974230.0727186 iteration: 77630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09482 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.16479 L1 loss: 0.0000e+00 L2 loss: 0.58836 Learning rate: 0.0004 Mask loss: 0.15202 RPN box loss: 0.01943 RPN score loss: 0.00587 RPN total loss: 0.0253 Total loss: 0.93047 timestamp: 1654974233.2477689 iteration: 77635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10686 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.17195 L1 loss: 0.0000e+00 L2 loss: 0.58836 Learning rate: 0.0004 Mask loss: 0.15193 RPN box loss: 0.0119 RPN score loss: 0.00243 RPN total loss: 0.01432 Total loss: 0.92656 timestamp: 1654974236.5368006 iteration: 77640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09438 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.15623 L1 loss: 0.0000e+00 L2 loss: 0.58836 Learning rate: 0.0004 Mask loss: 0.10993 RPN box loss: 0.01052 RPN score loss: 0.00196 RPN total loss: 0.01249 Total loss: 0.867 timestamp: 1654974239.73789 iteration: 77645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05969 FastRCNN class loss: 0.03979 FastRCNN total loss: 0.09948 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.0004 Mask loss: 0.10964 RPN box loss: 0.00394 RPN score loss: 0.00357 RPN total loss: 0.00751 Total loss: 0.80498 timestamp: 1654974242.9113688 iteration: 77650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04035 FastRCNN class loss: 0.02837 FastRCNN total loss: 0.06872 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.0004 Mask loss: 0.10394 RPN box loss: 0.0018 RPN score loss: 0.00502 RPN total loss: 0.00682 Total loss: 0.76783 timestamp: 1654974246.1946406 iteration: 77655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08113 FastRCNN class loss: 0.05604 FastRCNN total loss: 0.13716 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.0004 Mask loss: 0.09028 RPN box loss: 0.00339 RPN score loss: 0.00127 RPN total loss: 0.00467 Total loss: 0.82046 timestamp: 1654974249.3947237 iteration: 77660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08405 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.13293 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.0004 Mask loss: 0.1105 RPN box loss: 0.00948 RPN score loss: 0.00202 RPN total loss: 0.01149 Total loss: 0.84327 timestamp: 1654974252.5993361 iteration: 77665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08777 FastRCNN class loss: 0.04401 FastRCNN total loss: 0.13178 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.0004 Mask loss: 0.12999 RPN box loss: 0.00663 RPN score loss: 0.00338 RPN total loss: 0.01001 Total loss: 0.86013 timestamp: 1654974255.8318138 iteration: 77670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07562 FastRCNN class loss: 0.08502 FastRCNN total loss: 0.16064 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.0004 Mask loss: 0.15701 RPN box loss: 0.00621 RPN score loss: 0.00331 RPN total loss: 0.00951 Total loss: 0.91551 timestamp: 1654974259.0431054 iteration: 77675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16443 FastRCNN class loss: 0.11246 FastRCNN total loss: 0.2769 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.0004 Mask loss: 0.1274 RPN box loss: 0.0084 RPN score loss: 0.00416 RPN total loss: 0.01256 Total loss: 1.0052 timestamp: 1654974262.2657561 iteration: 77680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08745 FastRCNN class loss: 0.04576 FastRCNN total loss: 0.13321 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.0004 Mask loss: 0.13435 RPN box loss: 0.01369 RPN score loss: 0.00534 RPN total loss: 0.01903 Total loss: 0.87493 timestamp: 1654974265.4365056 iteration: 77685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05534 FastRCNN class loss: 0.04463 FastRCNN total loss: 0.09998 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.0004 Mask loss: 0.11809 RPN box loss: 0.01392 RPN score loss: 0.00506 RPN total loss: 0.01898 Total loss: 0.82538 timestamp: 1654974268.7175872 iteration: 77690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08161 FastRCNN class loss: 0.08803 FastRCNN total loss: 0.16964 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.0004 Mask loss: 0.15795 RPN box loss: 0.01171 RPN score loss: 0.00175 RPN total loss: 0.01345 Total loss: 0.92939 timestamp: 1654974271.9515772 iteration: 77695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08004 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.16042 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.0004 Mask loss: 0.12077 RPN box loss: 0.01191 RPN score loss: 0.00609 RPN total loss: 0.01801 Total loss: 0.88754 timestamp: 1654974275.168147 iteration: 77700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09692 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.16869 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.0004 Mask loss: 0.10223 RPN box loss: 0.00771 RPN score loss: 0.00432 RPN total loss: 0.01203 Total loss: 0.87129 timestamp: 1654974278.3782578 iteration: 77705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07767 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.14129 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.0004 Mask loss: 0.13612 RPN box loss: 0.01148 RPN score loss: 0.00461 RPN total loss: 0.01608 Total loss: 0.88182 timestamp: 1654974281.5999906 iteration: 77710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06991 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.13138 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.0004 Mask loss: 0.19538 RPN box loss: 0.01811 RPN score loss: 0.01113 RPN total loss: 0.02924 Total loss: 0.94433 timestamp: 1654974284.8550792 iteration: 77715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10824 FastRCNN class loss: 0.05564 FastRCNN total loss: 0.16388 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.0004 Mask loss: 0.15233 RPN box loss: 0.00593 RPN score loss: 0.00191 RPN total loss: 0.00784 Total loss: 0.91238 timestamp: 1654974288.0530481 iteration: 77720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14227 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.22945 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.0004 Mask loss: 0.14398 RPN box loss: 0.0137 RPN score loss: 0.00466 RPN total loss: 0.01836 Total loss: 0.98012 timestamp: 1654974291.2458415 iteration: 77725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04716 FastRCNN class loss: 0.06356 FastRCNN total loss: 0.11073 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.0004 Mask loss: 0.10348 RPN box loss: 0.0064 RPN score loss: 0.00563 RPN total loss: 0.01202 Total loss: 0.81455 timestamp: 1654974294.4158149 iteration: 77730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09941 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.17868 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.0004 Mask loss: 0.17387 RPN box loss: 0.00764 RPN score loss: 0.01048 RPN total loss: 0.01812 Total loss: 0.95901 timestamp: 1654974297.7025495 iteration: 77735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11996 FastRCNN class loss: 0.04273 FastRCNN total loss: 0.1627 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.0004 Mask loss: 0.09217 RPN box loss: 0.01121 RPN score loss: 0.00628 RPN total loss: 0.01749 Total loss: 0.86069 timestamp: 1654974300.8245428 iteration: 77740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13317 FastRCNN class loss: 0.07145 FastRCNN total loss: 0.20462 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.0004 Mask loss: 0.08089 RPN box loss: 0.00312 RPN score loss: 0.00153 RPN total loss: 0.00465 Total loss: 0.87848 timestamp: 1654974304.100944 iteration: 77745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09473 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.15877 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.0004 Mask loss: 0.10815 RPN box loss: 0.00742 RPN score loss: 0.00201 RPN total loss: 0.00944 Total loss: 0.86468 timestamp: 1654974307.2748418 iteration: 77750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08228 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.13285 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.0004 Mask loss: 0.12467 RPN box loss: 0.01372 RPN score loss: 0.00429 RPN total loss: 0.01801 Total loss: 0.86385 timestamp: 1654974310.401057 iteration: 77755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07263 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.13122 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.0004 Mask loss: 0.12985 RPN box loss: 0.01644 RPN score loss: 0.0142 RPN total loss: 0.03064 Total loss: 0.88003 timestamp: 1654974313.6172504 iteration: 77760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13721 FastRCNN class loss: 0.08334 FastRCNN total loss: 0.22055 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.0004 Mask loss: 0.1429 RPN box loss: 0.02081 RPN score loss: 0.01218 RPN total loss: 0.03299 Total loss: 0.98475 timestamp: 1654974316.755559 iteration: 77765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05276 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.1002 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.08531 RPN box loss: 0.00832 RPN score loss: 0.00571 RPN total loss: 0.01403 Total loss: 0.78785 timestamp: 1654974319.9132445 iteration: 77770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06144 FastRCNN class loss: 0.0797 FastRCNN total loss: 0.14114 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.08912 RPN box loss: 0.01603 RPN score loss: 0.00487 RPN total loss: 0.0209 Total loss: 0.83947 timestamp: 1654974323.096555 iteration: 77775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08051 FastRCNN class loss: 0.04322 FastRCNN total loss: 0.12373 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.12443 RPN box loss: 0.01194 RPN score loss: 0.00331 RPN total loss: 0.01525 Total loss: 0.85173 timestamp: 1654974326.384872 iteration: 77780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12964 FastRCNN class loss: 0.06273 FastRCNN total loss: 0.19237 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.13036 RPN box loss: 0.00646 RPN score loss: 0.00177 RPN total loss: 0.00823 Total loss: 0.91926 timestamp: 1654974329.5863764 iteration: 77785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07209 FastRCNN class loss: 0.08786 FastRCNN total loss: 0.15995 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.14742 RPN box loss: 0.00685 RPN score loss: 0.00656 RPN total loss: 0.01341 Total loss: 0.90908 timestamp: 1654974332.7536335 iteration: 77790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09457 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.15478 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.16876 RPN box loss: 0.00656 RPN score loss: 0.00135 RPN total loss: 0.00792 Total loss: 0.91977 timestamp: 1654974335.9879234 iteration: 77795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07311 FastRCNN class loss: 0.0671 FastRCNN total loss: 0.14021 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.0004 Mask loss: 0.09492 RPN box loss: 0.01162 RPN score loss: 0.00085 RPN total loss: 0.01247 Total loss: 0.8359 timestamp: 1654974339.1985435 iteration: 77800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0737 FastRCNN class loss: 0.04574 FastRCNN total loss: 0.11944 L1 loss: 0.0000e+00 L2 loss: 0.5883 Learning rate: 0.0004 Mask loss: 0.11415 RPN box loss: 0.00939 RPN score loss: 0.00588 RPN total loss: 0.01527 Total loss: 0.83716 timestamp: 1654974342.4432766 iteration: 77805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.16153 L1 loss: 0.0000e+00 L2 loss: 0.5883 Learning rate: 0.0004 Mask loss: 0.11435 RPN box loss: 0.03916 RPN score loss: 0.00258 RPN total loss: 0.04174 Total loss: 0.90592 timestamp: 1654974345.656871 iteration: 77810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08108 FastRCNN class loss: 0.04035 FastRCNN total loss: 0.12143 L1 loss: 0.0000e+00 L2 loss: 0.5883 Learning rate: 0.0004 Mask loss: 0.11142 RPN box loss: 0.01157 RPN score loss: 0.00774 RPN total loss: 0.01931 Total loss: 0.84046 timestamp: 1654974348.8351977 iteration: 77815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09734 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.15998 L1 loss: 0.0000e+00 L2 loss: 0.5883 Learning rate: 0.0004 Mask loss: 0.10692 RPN box loss: 0.00902 RPN score loss: 0.00751 RPN total loss: 0.01653 Total loss: 0.87173 timestamp: 1654974352.025881 iteration: 77820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08446 FastRCNN class loss: 0.04323 FastRCNN total loss: 0.12769 L1 loss: 0.0000e+00 L2 loss: 0.5883 Learning rate: 0.0004 Mask loss: 0.11664 RPN box loss: 0.0173 RPN score loss: 0.00177 RPN total loss: 0.01908 Total loss: 0.8517 timestamp: 1654974355.221717 iteration: 77825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05855 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.12843 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.0004 Mask loss: 0.16061 RPN box loss: 0.00903 RPN score loss: 0.00575 RPN total loss: 0.01477 Total loss: 0.8921 timestamp: 1654974358.4715538 iteration: 77830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0717 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.1282 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.0004 Mask loss: 0.10353 RPN box loss: 0.00866 RPN score loss: 0.00253 RPN total loss: 0.01119 Total loss: 0.83121 timestamp: 1654974361.5607936 iteration: 77835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06088 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.12679 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.0004 Mask loss: 0.10365 RPN box loss: 0.00944 RPN score loss: 0.00183 RPN total loss: 0.01127 Total loss: 0.82999 timestamp: 1654974364.7733862 iteration: 77840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09685 FastRCNN class loss: 0.05822 FastRCNN total loss: 0.15507 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.0004 Mask loss: 0.1327 RPN box loss: 0.01913 RPN score loss: 0.00624 RPN total loss: 0.02537 Total loss: 0.90143 timestamp: 1654974368.0374658 iteration: 77845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10898 FastRCNN class loss: 0.07653 FastRCNN total loss: 0.1855 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.0004 Mask loss: 0.10571 RPN box loss: 0.01181 RPN score loss: 0.00489 RPN total loss: 0.0167 Total loss: 0.8962 timestamp: 1654974371.203844 iteration: 77850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09178 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.15944 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.0004 Mask loss: 0.12757 RPN box loss: 0.03619 RPN score loss: 0.00418 RPN total loss: 0.04038 Total loss: 0.91568 timestamp: 1654974374.3934634 iteration: 77855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08026 FastRCNN class loss: 0.04628 FastRCNN total loss: 0.12654 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.0004 Mask loss: 0.10709 RPN box loss: 0.00873 RPN score loss: 0.00473 RPN total loss: 0.01345 Total loss: 0.83536 timestamp: 1654974377.5329566 iteration: 77860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04802 FastRCNN class loss: 0.03406 FastRCNN total loss: 0.08207 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.0004 Mask loss: 0.09635 RPN box loss: 0.0079 RPN score loss: 0.00217 RPN total loss: 0.01007 Total loss: 0.77678 timestamp: 1654974380.7560086 iteration: 77865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1153 FastRCNN class loss: 0.07312 FastRCNN total loss: 0.18842 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.0004 Mask loss: 0.13689 RPN box loss: 0.01819 RPN score loss: 0.00486 RPN total loss: 0.02305 Total loss: 0.93664 timestamp: 1654974384.0253532 iteration: 77870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06956 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.12461 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.0004 Mask loss: 0.12484 RPN box loss: 0.00712 RPN score loss: 0.00119 RPN total loss: 0.00831 Total loss: 0.84603 timestamp: 1654974387.2175052 iteration: 77875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06681 FastRCNN class loss: 0.03645 FastRCNN total loss: 0.10327 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.0004 Mask loss: 0.11247 RPN box loss: 0.00977 RPN score loss: 0.00189 RPN total loss: 0.01166 Total loss: 0.81567 timestamp: 1654974390.4538393 iteration: 77880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04705 FastRCNN class loss: 0.03914 FastRCNN total loss: 0.08619 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.0004 Mask loss: 0.14676 RPN box loss: 0.00613 RPN score loss: 0.00581 RPN total loss: 0.01194 Total loss: 0.83317 timestamp: 1654974393.6486561 iteration: 77885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07847 FastRCNN class loss: 0.06338 FastRCNN total loss: 0.14185 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.0004 Mask loss: 0.18156 RPN box loss: 0.01101 RPN score loss: 0.00176 RPN total loss: 0.01277 Total loss: 0.92446 timestamp: 1654974396.8689253 iteration: 77890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08769 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.15434 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.0004 Mask loss: 0.12786 RPN box loss: 0.0157 RPN score loss: 0.00743 RPN total loss: 0.02313 Total loss: 0.8936 timestamp: 1654974400.0905266 iteration: 77895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06349 FastRCNN class loss: 0.05271 FastRCNN total loss: 0.1162 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.0004 Mask loss: 0.11565 RPN box loss: 0.01947 RPN score loss: 0.00409 RPN total loss: 0.02356 Total loss: 0.84368 timestamp: 1654974403.286191 iteration: 77900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06151 FastRCNN class loss: 0.0884 FastRCNN total loss: 0.1499 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.0004 Mask loss: 0.11894 RPN box loss: 0.00501 RPN score loss: 0.00116 RPN total loss: 0.00617 Total loss: 0.86327 timestamp: 1654974406.465362 iteration: 77905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11376 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.19742 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.0004 Mask loss: 0.11803 RPN box loss: 0.01415 RPN score loss: 0.01067 RPN total loss: 0.02482 Total loss: 0.92854 timestamp: 1654974409.6787822 iteration: 77910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08843 FastRCNN class loss: 0.04621 FastRCNN total loss: 0.13464 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.0004 Mask loss: 0.09693 RPN box loss: 0.00973 RPN score loss: 0.00711 RPN total loss: 0.01684 Total loss: 0.83668 timestamp: 1654974412.8565862 iteration: 77915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13769 FastRCNN class loss: 0.07837 FastRCNN total loss: 0.21606 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.0004 Mask loss: 0.14072 RPN box loss: 0.02077 RPN score loss: 0.00183 RPN total loss: 0.0226 Total loss: 0.96764 timestamp: 1654974416.0694602 iteration: 77920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11912 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.17036 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.0004 Mask loss: 0.11578 RPN box loss: 0.00581 RPN score loss: 0.00124 RPN total loss: 0.00705 Total loss: 0.88144 timestamp: 1654974419.2665153 iteration: 77925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04811 FastRCNN class loss: 0.05654 FastRCNN total loss: 0.10465 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.0004 Mask loss: 0.12198 RPN box loss: 0.01716 RPN score loss: 0.00093 RPN total loss: 0.01809 Total loss: 0.83298 timestamp: 1654974422.5060058 iteration: 77930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09115 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.14655 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.0004 Mask loss: 0.11821 RPN box loss: 0.01088 RPN score loss: 0.00192 RPN total loss: 0.0128 Total loss: 0.86582 timestamp: 1654974425.6328144 iteration: 77935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07486 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.13177 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.0004 Mask loss: 0.10144 RPN box loss: 0.00739 RPN score loss: 0.00199 RPN total loss: 0.00939 Total loss: 0.83086 timestamp: 1654974428.870605 iteration: 77940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04853 FastRCNN class loss: 0.05395 FastRCNN total loss: 0.10248 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.0004 Mask loss: 0.10083 RPN box loss: 0.00528 RPN score loss: 0.00194 RPN total loss: 0.00722 Total loss: 0.79878 timestamp: 1654974432.104641 iteration: 77945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10537 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.15552 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.10115 RPN box loss: 0.01378 RPN score loss: 0.0029 RPN total loss: 0.01669 Total loss: 0.86161 timestamp: 1654974435.3686733 iteration: 77950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04993 FastRCNN class loss: 0.04136 FastRCNN total loss: 0.09129 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.10556 RPN box loss: 0.00547 RPN score loss: 0.00159 RPN total loss: 0.00706 Total loss: 0.79216 timestamp: 1654974438.6016107 iteration: 77955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.16628 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.12772 RPN box loss: 0.01825 RPN score loss: 0.00637 RPN total loss: 0.02461 Total loss: 0.90686 timestamp: 1654974441.7527833 iteration: 77960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14754 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.20241 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.1408 RPN box loss: 0.04238 RPN score loss: 0.00711 RPN total loss: 0.04949 Total loss: 0.98095 timestamp: 1654974445.0694964 iteration: 77965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05853 FastRCNN class loss: 0.04051 FastRCNN total loss: 0.09904 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.08367 RPN box loss: 0.01601 RPN score loss: 0.00698 RPN total loss: 0.02299 Total loss: 0.79394 timestamp: 1654974448.2319956 iteration: 77970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09505 FastRCNN class loss: 0.03883 FastRCNN total loss: 0.13388 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.10389 RPN box loss: 0.015 RPN score loss: 0.00341 RPN total loss: 0.0184 Total loss: 0.84442 timestamp: 1654974451.4401932 iteration: 77975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10479 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.16954 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.0004 Mask loss: 0.11031 RPN box loss: 0.02581 RPN score loss: 0.00259 RPN total loss: 0.0284 Total loss: 0.89648 timestamp: 1654974454.59513 iteration: 77980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08123 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.13963 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.0004 Mask loss: 0.12825 RPN box loss: 0.01665 RPN score loss: 0.00409 RPN total loss: 0.02074 Total loss: 0.87687 timestamp: 1654974457.8331242 iteration: 77985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08798 FastRCNN class loss: 0.08654 FastRCNN total loss: 0.17452 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.0004 Mask loss: 0.12572 RPN box loss: 0.00616 RPN score loss: 0.0077 RPN total loss: 0.01385 Total loss: 0.90234 timestamp: 1654974461.0362985 iteration: 77990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12384 FastRCNN class loss: 0.10517 FastRCNN total loss: 0.22902 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.0004 Mask loss: 0.1141 RPN box loss: 0.00696 RPN score loss: 0.00602 RPN total loss: 0.01298 Total loss: 0.94434 timestamp: 1654974464.2386255 iteration: 77995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0801 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.13486 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.0004 Mask loss: 0.12487 RPN box loss: 0.01843 RPN score loss: 0.00654 RPN total loss: 0.02497 Total loss: 0.87293 timestamp: 1654974467.3573701 iteration: 78000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07171 FastRCNN class loss: 0.0374 FastRCNN total loss: 0.10911 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.0004 Mask loss: 0.13518 RPN box loss: 0.00842 RPN score loss: 0.00641 RPN total loss: 0.01482 Total loss: 0.84735 timestamp: 1654974470.5576956 iteration: 78005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09034 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.16211 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.0004 Mask loss: 0.0882 RPN box loss: 0.01082 RPN score loss: 0.00213 RPN total loss: 0.01295 Total loss: 0.85149 timestamp: 1654974473.670476 iteration: 78010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09896 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.17334 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.16481 RPN box loss: 0.02765 RPN score loss: 0.00281 RPN total loss: 0.03047 Total loss: 0.95685 timestamp: 1654974476.7677336 iteration: 78015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08803 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.17165 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.08769 RPN box loss: 0.01937 RPN score loss: 0.00657 RPN total loss: 0.02594 Total loss: 0.87352 timestamp: 1654974480.0073118 iteration: 78020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06738 FastRCNN class loss: 0.07263 FastRCNN total loss: 0.14001 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.14527 RPN box loss: 0.01154 RPN score loss: 0.00554 RPN total loss: 0.01708 Total loss: 0.89059 timestamp: 1654974483.1640124 iteration: 78025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1732 FastRCNN class loss: 0.09226 FastRCNN total loss: 0.26546 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.124 RPN box loss: 0.0151 RPN score loss: 0.00457 RPN total loss: 0.01966 Total loss: 0.99735 timestamp: 1654974486.3935368 iteration: 78030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11551 FastRCNN class loss: 0.0695 FastRCNN total loss: 0.18501 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.11337 RPN box loss: 0.01034 RPN score loss: 0.00669 RPN total loss: 0.01704 Total loss: 0.90364 timestamp: 1654974489.501928 iteration: 78035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08159 FastRCNN class loss: 0.11029 FastRCNN total loss: 0.19188 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.16377 RPN box loss: 0.01558 RPN score loss: 0.01543 RPN total loss: 0.03101 Total loss: 0.97489 timestamp: 1654974492.6809497 iteration: 78040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07612 FastRCNN class loss: 0.04916 FastRCNN total loss: 0.12528 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.0004 Mask loss: 0.07557 RPN box loss: 0.0035 RPN score loss: 0.00189 RPN total loss: 0.00539 Total loss: 0.79447 timestamp: 1654974495.8589098 iteration: 78045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10261 FastRCNN class loss: 0.07718 FastRCNN total loss: 0.17979 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.0004 Mask loss: 0.13893 RPN box loss: 0.00881 RPN score loss: 0.00298 RPN total loss: 0.0118 Total loss: 0.91874 timestamp: 1654974499.0489564 iteration: 78050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09241 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.15251 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.0004 Mask loss: 0.11764 RPN box loss: 0.00739 RPN score loss: 0.00102 RPN total loss: 0.00841 Total loss: 0.86678 timestamp: 1654974502.2449775 iteration: 78055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07649 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.12587 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.0004 Mask loss: 0.1353 RPN box loss: 0.01498 RPN score loss: 0.00539 RPN total loss: 0.02037 Total loss: 0.86976 timestamp: 1654974505.4390836 iteration: 78060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04695 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.11096 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.0004 Mask loss: 0.07377 RPN box loss: 0.00855 RPN score loss: 0.0016 RPN total loss: 0.01015 Total loss: 0.78309 timestamp: 1654974508.6239552 iteration: 78065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14184 FastRCNN class loss: 0.11956 FastRCNN total loss: 0.2614 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.0004 Mask loss: 0.14537 RPN box loss: 0.01794 RPN score loss: 0.00575 RPN total loss: 0.02369 Total loss: 1.01868 timestamp: 1654974511.8394516 iteration: 78070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0555 FastRCNN class loss: 0.08152 FastRCNN total loss: 0.13702 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.0004 Mask loss: 0.1583 RPN box loss: 0.01252 RPN score loss: 0.00222 RPN total loss: 0.01475 Total loss: 0.89828 timestamp: 1654974515.0688186 iteration: 78075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.14043 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.0004 Mask loss: 0.15035 RPN box loss: 0.01485 RPN score loss: 0.00172 RPN total loss: 0.01657 Total loss: 0.89556 timestamp: 1654974518.2365012 iteration: 78080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.09297 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.0004 Mask loss: 0.1488 RPN box loss: 0.01344 RPN score loss: 0.00375 RPN total loss: 0.01719 Total loss: 0.94778 timestamp: 1654974521.3901591 iteration: 78085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05939 FastRCNN class loss: 0.03895 FastRCNN total loss: 0.09834 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.0004 Mask loss: 0.22109 RPN box loss: 0.00879 RPN score loss: 0.0049 RPN total loss: 0.01369 Total loss: 0.92132 timestamp: 1654974524.543446 iteration: 78090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05613 FastRCNN class loss: 0.04907 FastRCNN total loss: 0.10521 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.0004 Mask loss: 0.10696 RPN box loss: 0.01526 RPN score loss: 0.00121 RPN total loss: 0.01647 Total loss: 0.81685 timestamp: 1654974527.8040495 iteration: 78095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04289 FastRCNN class loss: 0.06064 FastRCNN total loss: 0.10352 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.0004 Mask loss: 0.09151 RPN box loss: 0.0121 RPN score loss: 0.00315 RPN total loss: 0.01525 Total loss: 0.79849 timestamp: 1654974530.8963454 iteration: 78100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05482 FastRCNN class loss: 0.04671 FastRCNN total loss: 0.10153 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.0004 Mask loss: 0.1133 RPN box loss: 0.0051 RPN score loss: 0.00146 RPN total loss: 0.00656 Total loss: 0.8096 timestamp: 1654974534.1393554 iteration: 78105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06677 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.13394 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.0004 Mask loss: 0.1684 RPN box loss: 0.02273 RPN score loss: 0.00693 RPN total loss: 0.02966 Total loss: 0.9202 timestamp: 1654974537.448103 iteration: 78110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10158 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.15827 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.0004 Mask loss: 0.1373 RPN box loss: 0.01411 RPN score loss: 0.00397 RPN total loss: 0.01808 Total loss: 0.90185 timestamp: 1654974540.6242783 iteration: 78115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10426 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.16533 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.0004 Mask loss: 0.11116 RPN box loss: 0.0141 RPN score loss: 0.00117 RPN total loss: 0.01527 Total loss: 0.87996 timestamp: 1654974543.8201337 iteration: 78120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07929 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.13608 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.0004 Mask loss: 0.12549 RPN box loss: 0.00651 RPN score loss: 0.00088 RPN total loss: 0.00739 Total loss: 0.85715 timestamp: 1654974547.0330346 iteration: 78125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10311 FastRCNN class loss: 0.11192 FastRCNN total loss: 0.21502 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.0004 Mask loss: 0.16053 RPN box loss: 0.03372 RPN score loss: 0.01352 RPN total loss: 0.04724 Total loss: 1.01099 timestamp: 1654974550.2456017 iteration: 78130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10386 FastRCNN class loss: 0.05931 FastRCNN total loss: 0.16317 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.0004 Mask loss: 0.08581 RPN box loss: 0.01063 RPN score loss: 0.00472 RPN total loss: 0.01535 Total loss: 0.85253 timestamp: 1654974553.5085745 iteration: 78135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07077 FastRCNN class loss: 0.04577 FastRCNN total loss: 0.11654 L1 loss: 0.0000e+00 L2 loss: 0.58819 Learning rate: 0.0004 Mask loss: 0.1162 RPN box loss: 0.00412 RPN score loss: 0.00526 RPN total loss: 0.00938 Total loss: 0.83031 timestamp: 1654974556.7158983 iteration: 78140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0819 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.12948 L1 loss: 0.0000e+00 L2 loss: 0.58819 Learning rate: 0.0004 Mask loss: 0.10874 RPN box loss: 0.01394 RPN score loss: 0.00618 RPN total loss: 0.02012 Total loss: 0.84653 timestamp: 1654974559.965439 iteration: 78145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.059 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.12338 L1 loss: 0.0000e+00 L2 loss: 0.58819 Learning rate: 0.0004 Mask loss: 0.20023 RPN box loss: 0.01487 RPN score loss: 0.00696 RPN total loss: 0.02183 Total loss: 0.93364 timestamp: 1654974563.1567035 iteration: 78150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12855 FastRCNN class loss: 0.14263 FastRCNN total loss: 0.27118 L1 loss: 0.0000e+00 L2 loss: 0.58819 Learning rate: 0.0004 Mask loss: 0.12714 RPN box loss: 0.00721 RPN score loss: 0.0051 RPN total loss: 0.01231 Total loss: 0.99882 timestamp: 1654974566.357746 iteration: 78155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05379 FastRCNN class loss: 0.04254 FastRCNN total loss: 0.09633 L1 loss: 0.0000e+00 L2 loss: 0.58819 Learning rate: 0.0004 Mask loss: 0.12326 RPN box loss: 0.0073 RPN score loss: 0.00496 RPN total loss: 0.01227 Total loss: 0.82004 timestamp: 1654974569.5556412 iteration: 78160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13515 FastRCNN class loss: 0.08971 FastRCNN total loss: 0.22486 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.0004 Mask loss: 0.13049 RPN box loss: 0.02121 RPN score loss: 0.0031 RPN total loss: 0.02431 Total loss: 0.96784 timestamp: 1654974572.8404377 iteration: 78165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05116 FastRCNN class loss: 0.04098 FastRCNN total loss: 0.09214 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.0004 Mask loss: 0.12266 RPN box loss: 0.01867 RPN score loss: 0.00186 RPN total loss: 0.02053 Total loss: 0.82352 timestamp: 1654974576.0353699 iteration: 78170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.05035 FastRCNN total loss: 0.13707 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.0004 Mask loss: 0.17872 RPN box loss: 0.01603 RPN score loss: 0.01634 RPN total loss: 0.03237 Total loss: 0.93634 timestamp: 1654974579.3051534 iteration: 78175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06343 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.13844 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.0004 Mask loss: 0.11178 RPN box loss: 0.00954 RPN score loss: 0.00143 RPN total loss: 0.01097 Total loss: 0.84936 timestamp: 1654974582.518382 iteration: 78180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08792 FastRCNN class loss: 0.11039 FastRCNN total loss: 0.1983 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.0004 Mask loss: 0.12048 RPN box loss: 0.01153 RPN score loss: 0.01101 RPN total loss: 0.02255 Total loss: 0.92951 timestamp: 1654974585.7546787 iteration: 78185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08848 FastRCNN class loss: 0.0563 FastRCNN total loss: 0.14478 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.0004 Mask loss: 0.11719 RPN box loss: 0.00764 RPN score loss: 0.00238 RPN total loss: 0.01002 Total loss: 0.86017 timestamp: 1654974588.9391317 iteration: 78190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08445 FastRCNN class loss: 0.06158 FastRCNN total loss: 0.14603 L1 loss: 0.0000e+00 L2 loss: 0.58817 Learning rate: 0.0004 Mask loss: 0.11722 RPN box loss: 0.00709 RPN score loss: 0.00503 RPN total loss: 0.01212 Total loss: 0.86354 timestamp: 1654974592.1835 iteration: 78195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06839 FastRCNN class loss: 0.03589 FastRCNN total loss: 0.10429 L1 loss: 0.0000e+00 L2 loss: 0.58817 Learning rate: 0.0004 Mask loss: 0.11018 RPN box loss: 0.01308 RPN score loss: 0.00373 RPN total loss: 0.01681 Total loss: 0.81944 timestamp: 1654974595.2781813 iteration: 78200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06545 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.12882 L1 loss: 0.0000e+00 L2 loss: 0.58817 Learning rate: 0.0004 Mask loss: 0.11803 RPN box loss: 0.01551 RPN score loss: 0.00572 RPN total loss: 0.02123 Total loss: 0.85625 timestamp: 1654974598.5146406 iteration: 78205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0808 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.14508 L1 loss: 0.0000e+00 L2 loss: 0.58817 Learning rate: 0.0004 Mask loss: 0.11923 RPN box loss: 0.01482 RPN score loss: 0.00985 RPN total loss: 0.02467 Total loss: 0.87715 timestamp: 1654974601.6748915 iteration: 78210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09086 FastRCNN class loss: 0.05133 FastRCNN total loss: 0.14218 L1 loss: 0.0000e+00 L2 loss: 0.58817 Learning rate: 0.0004 Mask loss: 0.12288 RPN box loss: 0.0133 RPN score loss: 0.0013 RPN total loss: 0.0146 Total loss: 0.86782 timestamp: 1654974604.959762 iteration: 78215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11001 FastRCNN class loss: 0.03823 FastRCNN total loss: 0.14823 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.0004 Mask loss: 0.07922 RPN box loss: 0.00904 RPN score loss: 0.00281 RPN total loss: 0.01185 Total loss: 0.82747 timestamp: 1654974608.2249691 iteration: 78220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08747 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.15461 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.0004 Mask loss: 0.1181 RPN box loss: 0.00999 RPN score loss: 0.0039 RPN total loss: 0.01389 Total loss: 0.87477 timestamp: 1654974611.412785 iteration: 78225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06481 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.11952 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.0004 Mask loss: 0.12976 RPN box loss: 0.00914 RPN score loss: 0.00352 RPN total loss: 0.01266 Total loss: 0.8501 timestamp: 1654974614.6379032 iteration: 78230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05932 FastRCNN class loss: 0.07052 FastRCNN total loss: 0.12984 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.0004 Mask loss: 0.12336 RPN box loss: 0.00487 RPN score loss: 0.00267 RPN total loss: 0.00754 Total loss: 0.8489 timestamp: 1654974617.823973 iteration: 78235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04686 FastRCNN class loss: 0.04788 FastRCNN total loss: 0.09474 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.0004 Mask loss: 0.11084 RPN box loss: 0.00701 RPN score loss: 0.00138 RPN total loss: 0.00839 Total loss: 0.80212 timestamp: 1654974621.0835505 iteration: 78240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08848 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.15963 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.0004 Mask loss: 0.15504 RPN box loss: 0.00695 RPN score loss: 0.00302 RPN total loss: 0.00998 Total loss: 0.9128 timestamp: 1654974624.2821116 iteration: 78245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.14108 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.0004 Mask loss: 0.10209 RPN box loss: 0.00847 RPN score loss: 0.00323 RPN total loss: 0.01171 Total loss: 0.84302 timestamp: 1654974627.4239252 iteration: 78250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15445 FastRCNN class loss: 0.11243 FastRCNN total loss: 0.26688 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.0004 Mask loss: 0.21082 RPN box loss: 0.0067 RPN score loss: 0.01158 RPN total loss: 0.01828 Total loss: 1.08413 timestamp: 1654974630.5889895 iteration: 78255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05345 FastRCNN class loss: 0.03361 FastRCNN total loss: 0.08707 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.0004 Mask loss: 0.09248 RPN box loss: 0.0055 RPN score loss: 0.00409 RPN total loss: 0.00959 Total loss: 0.77729 timestamp: 1654974633.8089192 iteration: 78260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07969 FastRCNN class loss: 0.04935 FastRCNN total loss: 0.12903 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.0004 Mask loss: 0.11444 RPN box loss: 0.01017 RPN score loss: 0.00241 RPN total loss: 0.01258 Total loss: 0.84419 timestamp: 1654974636.9664307 iteration: 78265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.04872 FastRCNN total loss: 0.17367 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.0004 Mask loss: 0.12424 RPN box loss: 0.00929 RPN score loss: 0.00243 RPN total loss: 0.01171 Total loss: 0.89777 timestamp: 1654974640.1113815 iteration: 78270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10197 FastRCNN class loss: 0.08174 FastRCNN total loss: 0.18371 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.0004 Mask loss: 0.202 RPN box loss: 0.01467 RPN score loss: 0.00506 RPN total loss: 0.01974 Total loss: 0.9936 timestamp: 1654974643.322345 iteration: 78275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08853 FastRCNN class loss: 0.08863 FastRCNN total loss: 0.17716 L1 loss: 0.0000e+00 L2 loss: 0.58814 Learning rate: 0.0004 Mask loss: 0.14748 RPN box loss: 0.00552 RPN score loss: 0.00337 RPN total loss: 0.00889 Total loss: 0.92166 timestamp: 1654974646.5352688 iteration: 78280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09659 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.16072 L1 loss: 0.0000e+00 L2 loss: 0.58814 Learning rate: 0.0004 Mask loss: 0.12584 RPN box loss: 0.00716 RPN score loss: 0.00229 RPN total loss: 0.00945 Total loss: 0.88416 timestamp: 1654974649.717002 iteration: 78285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10034 FastRCNN class loss: 0.04564 FastRCNN total loss: 0.14598 L1 loss: 0.0000e+00 L2 loss: 0.58814 Learning rate: 0.0004 Mask loss: 0.10064 RPN box loss: 0.00966 RPN score loss: 0.00477 RPN total loss: 0.01443 Total loss: 0.8492 timestamp: 1654974652.9053998 iteration: 78290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15205 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.25234 L1 loss: 0.0000e+00 L2 loss: 0.58814 Learning rate: 0.0004 Mask loss: 0.20707 RPN box loss: 0.01578 RPN score loss: 0.00258 RPN total loss: 0.01836 Total loss: 1.06591 timestamp: 1654974656.0426776 iteration: 78295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10014 FastRCNN class loss: 0.09597 FastRCNN total loss: 0.19611 L1 loss: 0.0000e+00 L2 loss: 0.58814 Learning rate: 0.0004 Mask loss: 0.171 RPN box loss: 0.01891 RPN score loss: 0.00861 RPN total loss: 0.02752 Total loss: 0.98276 timestamp: 1654974659.238725 iteration: 78300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08874 FastRCNN class loss: 0.11425 FastRCNN total loss: 0.20299 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.15907 RPN box loss: 0.03035 RPN score loss: 0.00954 RPN total loss: 0.03989 Total loss: 0.99009 timestamp: 1654974662.4356306 iteration: 78305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14132 FastRCNN class loss: 0.07106 FastRCNN total loss: 0.21238 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.09869 RPN box loss: 0.0336 RPN score loss: 0.00579 RPN total loss: 0.03939 Total loss: 0.93858 timestamp: 1654974665.5963771 iteration: 78310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13991 FastRCNN class loss: 0.11839 FastRCNN total loss: 0.2583 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.18184 RPN box loss: 0.01828 RPN score loss: 0.01826 RPN total loss: 0.03654 Total loss: 1.06481 timestamp: 1654974668.8327425 iteration: 78315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13533 FastRCNN class loss: 0.10836 FastRCNN total loss: 0.24369 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.12756 RPN box loss: 0.01967 RPN score loss: 0.01075 RPN total loss: 0.03042 Total loss: 0.9898 timestamp: 1654974672.038117 iteration: 78320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0843 FastRCNN class loss: 0.06175 FastRCNN total loss: 0.14605 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.11369 RPN box loss: 0.00795 RPN score loss: 0.00555 RPN total loss: 0.0135 Total loss: 0.86136 timestamp: 1654974675.2158659 iteration: 78325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05137 FastRCNN class loss: 0.06023 FastRCNN total loss: 0.11159 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.08551 RPN box loss: 0.00639 RPN score loss: 0.00213 RPN total loss: 0.00851 Total loss: 0.79374 timestamp: 1654974678.4233558 iteration: 78330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06082 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.11516 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.0004 Mask loss: 0.11184 RPN box loss: 0.00627 RPN score loss: 0.00259 RPN total loss: 0.00886 Total loss: 0.82399 timestamp: 1654974681.6013935 iteration: 78335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06654 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.12622 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.0004 Mask loss: 0.13997 RPN box loss: 0.00881 RPN score loss: 0.00543 RPN total loss: 0.01424 Total loss: 0.86856 timestamp: 1654974684.7906291 iteration: 78340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.05686 FastRCNN total loss: 0.1419 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.0004 Mask loss: 0.13803 RPN box loss: 0.0059 RPN score loss: 0.00268 RPN total loss: 0.00859 Total loss: 0.87663 timestamp: 1654974687.9223526 iteration: 78345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05675 FastRCNN class loss: 0.05421 FastRCNN total loss: 0.11095 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.0004 Mask loss: 0.14232 RPN box loss: 0.00804 RPN score loss: 0.00177 RPN total loss: 0.00981 Total loss: 0.85121 timestamp: 1654974691.130806 iteration: 78350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14933 FastRCNN class loss: 0.09116 FastRCNN total loss: 0.24048 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.0004 Mask loss: 0.15203 RPN box loss: 0.0133 RPN score loss: 0.00365 RPN total loss: 0.01695 Total loss: 0.99759 timestamp: 1654974694.3154373 iteration: 78355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11208 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.17413 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.0004 Mask loss: 0.13703 RPN box loss: 0.01406 RPN score loss: 0.00405 RPN total loss: 0.01811 Total loss: 0.91739 timestamp: 1654974697.5266168 iteration: 78360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06678 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.12721 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.0004 Mask loss: 0.11326 RPN box loss: 0.00887 RPN score loss: 0.00165 RPN total loss: 0.01052 Total loss: 0.8391 timestamp: 1654974700.744308 iteration: 78365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03475 FastRCNN class loss: 0.0378 FastRCNN total loss: 0.07255 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.0004 Mask loss: 0.1096 RPN box loss: 0.0149 RPN score loss: 0.00096 RPN total loss: 0.01586 Total loss: 0.78613 timestamp: 1654974703.902172 iteration: 78370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06093 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.13203 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.0004 Mask loss: 0.10622 RPN box loss: 0.01424 RPN score loss: 0.00187 RPN total loss: 0.01611 Total loss: 0.84248 timestamp: 1654974707.1640384 iteration: 78375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0831 FastRCNN class loss: 0.04769 FastRCNN total loss: 0.13079 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.0004 Mask loss: 0.11669 RPN box loss: 0.0071 RPN score loss: 0.00584 RPN total loss: 0.01294 Total loss: 0.84853 timestamp: 1654974710.3206859 iteration: 78380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10366 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.17661 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.0004 Mask loss: 0.13961 RPN box loss: 0.00415 RPN score loss: 0.00984 RPN total loss: 0.014 Total loss: 0.91833 timestamp: 1654974713.5066779 iteration: 78385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10646 FastRCNN class loss: 0.06314 FastRCNN total loss: 0.1696 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.0004 Mask loss: 0.14978 RPN box loss: 0.00521 RPN score loss: 0.00335 RPN total loss: 0.00856 Total loss: 0.91605 timestamp: 1654974716.7229657 iteration: 78390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05487 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.11387 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.0004 Mask loss: 0.13136 RPN box loss: 0.00882 RPN score loss: 0.00737 RPN total loss: 0.01618 Total loss: 0.84952 timestamp: 1654974719.9381952 iteration: 78395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08964 FastRCNN class loss: 0.03908 FastRCNN total loss: 0.12872 L1 loss: 0.0000e+00 L2 loss: 0.5881 Learning rate: 0.0004 Mask loss: 0.08991 RPN box loss: 0.00373 RPN score loss: 0.00237 RPN total loss: 0.0061 Total loss: 0.81284 timestamp: 1654974723.1379652 iteration: 78400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10945 FastRCNN class loss: 0.09294 FastRCNN total loss: 0.20239 L1 loss: 0.0000e+00 L2 loss: 0.5881 Learning rate: 0.0004 Mask loss: 0.1616 RPN box loss: 0.03082 RPN score loss: 0.01113 RPN total loss: 0.04195 Total loss: 0.99404 timestamp: 1654974726.4650204 iteration: 78405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05491 FastRCNN class loss: 0.048 FastRCNN total loss: 0.10291 L1 loss: 0.0000e+00 L2 loss: 0.5881 Learning rate: 0.0004 Mask loss: 0.09626 RPN box loss: 0.00787 RPN score loss: 0.00251 RPN total loss: 0.01038 Total loss: 0.79765 timestamp: 1654974729.751965 iteration: 78410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10584 FastRCNN class loss: 0.11315 FastRCNN total loss: 0.21899 L1 loss: 0.0000e+00 L2 loss: 0.5881 Learning rate: 0.0004 Mask loss: 0.12552 RPN box loss: 0.01187 RPN score loss: 0.01325 RPN total loss: 0.02512 Total loss: 0.95772 timestamp: 1654974732.9585717 iteration: 78415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1237 FastRCNN class loss: 0.0953 FastRCNN total loss: 0.219 L1 loss: 0.0000e+00 L2 loss: 0.5881 Learning rate: 0.0004 Mask loss: 0.14471 RPN box loss: 0.03303 RPN score loss: 0.00644 RPN total loss: 0.03947 Total loss: 0.99128 timestamp: 1654974736.1796646 iteration: 78420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05994 FastRCNN class loss: 0.07759 FastRCNN total loss: 0.13753 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.14236 RPN box loss: 0.02295 RPN score loss: 0.00838 RPN total loss: 0.03133 Total loss: 0.89931 timestamp: 1654974739.4158356 iteration: 78425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05982 FastRCNN class loss: 0.04069 FastRCNN total loss: 0.10051 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.07674 RPN box loss: 0.00877 RPN score loss: 0.0009 RPN total loss: 0.00967 Total loss: 0.77501 timestamp: 1654974742.5676396 iteration: 78430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14063 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.21607 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.17691 RPN box loss: 0.0154 RPN score loss: 0.00227 RPN total loss: 0.01767 Total loss: 0.99874 timestamp: 1654974745.7358084 iteration: 78435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09108 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.16111 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.14927 RPN box loss: 0.01465 RPN score loss: 0.01247 RPN total loss: 0.02712 Total loss: 0.92559 timestamp: 1654974748.921481 iteration: 78440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04728 FastRCNN class loss: 0.03871 FastRCNN total loss: 0.08599 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.10274 RPN box loss: 0.00539 RPN score loss: 0.00243 RPN total loss: 0.00782 Total loss: 0.78465 timestamp: 1654974752.0545456 iteration: 78445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10428 FastRCNN class loss: 0.05701 FastRCNN total loss: 0.16129 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.08409 RPN box loss: 0.02006 RPN score loss: 0.00257 RPN total loss: 0.02263 Total loss: 0.8561 timestamp: 1654974755.2411916 iteration: 78450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1912 FastRCNN class loss: 0.07235 FastRCNN total loss: 0.26355 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.0004 Mask loss: 0.1822 RPN box loss: 0.01489 RPN score loss: 0.00177 RPN total loss: 0.01665 Total loss: 1.05049 timestamp: 1654974758.4852974 iteration: 78455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06713 FastRCNN class loss: 0.06463 FastRCNN total loss: 0.13176 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.0004 Mask loss: 0.11302 RPN box loss: 0.04052 RPN score loss: 0.01573 RPN total loss: 0.05625 Total loss: 0.88911 timestamp: 1654974761.655657 iteration: 78460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.07624 FastRCNN total loss: 0.14647 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.0004 Mask loss: 0.18291 RPN box loss: 0.02639 RPN score loss: 0.01045 RPN total loss: 0.03684 Total loss: 0.9543 timestamp: 1654974764.8393192 iteration: 78465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05945 FastRCNN class loss: 0.03966 FastRCNN total loss: 0.09911 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.0004 Mask loss: 0.09545 RPN box loss: 0.01078 RPN score loss: 0.00104 RPN total loss: 0.01182 Total loss: 0.79446 timestamp: 1654974768.0880487 iteration: 78470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08741 FastRCNN class loss: 0.06529 FastRCNN total loss: 0.15269 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.0004 Mask loss: 0.15469 RPN box loss: 0.00994 RPN score loss: 0.00744 RPN total loss: 0.01738 Total loss: 0.91284 timestamp: 1654974771.206388 iteration: 78475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06559 FastRCNN class loss: 0.05866 FastRCNN total loss: 0.12426 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.0004 Mask loss: 0.09496 RPN box loss: 0.01064 RPN score loss: 0.00534 RPN total loss: 0.01598 Total loss: 0.82328 timestamp: 1654974774.3682094 iteration: 78480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.15209 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.0004 Mask loss: 0.13648 RPN box loss: 0.01321 RPN score loss: 0.01468 RPN total loss: 0.02789 Total loss: 0.90453 timestamp: 1654974777.5654886 iteration: 78485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0865 FastRCNN class loss: 0.05439 FastRCNN total loss: 0.14089 L1 loss: 0.0000e+00 L2 loss: 0.58807 Learning rate: 0.0004 Mask loss: 0.1164 RPN box loss: 0.0229 RPN score loss: 0.00652 RPN total loss: 0.02943 Total loss: 0.87479 timestamp: 1654974780.7231188 iteration: 78490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04548 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.10169 L1 loss: 0.0000e+00 L2 loss: 0.58807 Learning rate: 0.0004 Mask loss: 0.0954 RPN box loss: 0.01288 RPN score loss: 0.00149 RPN total loss: 0.01437 Total loss: 0.79953 timestamp: 1654974783.8392944 iteration: 78495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07064 FastRCNN class loss: 0.05693 FastRCNN total loss: 0.12757 L1 loss: 0.0000e+00 L2 loss: 0.58807 Learning rate: 0.0004 Mask loss: 0.07806 RPN box loss: 0.00802 RPN score loss: 0.00458 RPN total loss: 0.01261 Total loss: 0.8063 timestamp: 1654974787.1835825 iteration: 78500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.17871 L1 loss: 0.0000e+00 L2 loss: 0.58807 Learning rate: 0.0004 Mask loss: 0.17553 RPN box loss: 0.03365 RPN score loss: 0.00118 RPN total loss: 0.03483 Total loss: 0.97714 timestamp: 1654974790.3201659 iteration: 78505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06382 FastRCNN class loss: 0.0577 FastRCNN total loss: 0.12151 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.14123 RPN box loss: 0.0106 RPN score loss: 0.0055 RPN total loss: 0.0161 Total loss: 0.86691 timestamp: 1654974793.4687302 iteration: 78510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.16702 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.18849 RPN box loss: 0.00646 RPN score loss: 0.00447 RPN total loss: 0.01093 Total loss: 0.95451 timestamp: 1654974796.6785038 iteration: 78515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10984 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.15836 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.09231 RPN box loss: 0.05216 RPN score loss: 0.00579 RPN total loss: 0.05796 Total loss: 0.89669 timestamp: 1654974799.8443437 iteration: 78520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08061 FastRCNN class loss: 0.04871 FastRCNN total loss: 0.12932 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.10884 RPN box loss: 0.00544 RPN score loss: 0.00485 RPN total loss: 0.01029 Total loss: 0.83652 timestamp: 1654974803.0190513 iteration: 78525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06128 FastRCNN class loss: 0.04688 FastRCNN total loss: 0.10816 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.08673 RPN box loss: 0.00818 RPN score loss: 0.00282 RPN total loss: 0.011 Total loss: 0.79395 timestamp: 1654974806.2081997 iteration: 78530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14214 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.21019 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.12202 RPN box loss: 0.0131 RPN score loss: 0.00491 RPN total loss: 0.01801 Total loss: 0.93828 timestamp: 1654974809.3611727 iteration: 78535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06612 FastRCNN class loss: 0.08689 FastRCNN total loss: 0.15301 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.0004 Mask loss: 0.17739 RPN box loss: 0.01686 RPN score loss: 0.00111 RPN total loss: 0.01798 Total loss: 0.93643 timestamp: 1654974812.5738175 iteration: 78540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11664 FastRCNN class loss: 0.08062 FastRCNN total loss: 0.19727 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.10115 RPN box loss: 0.00801 RPN score loss: 0.00281 RPN total loss: 0.01082 Total loss: 0.89729 timestamp: 1654974815.8021004 iteration: 78545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08549 FastRCNN class loss: 0.06449 FastRCNN total loss: 0.14999 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.13078 RPN box loss: 0.00569 RPN score loss: 0.00472 RPN total loss: 0.0104 Total loss: 0.87923 timestamp: 1654974818.9306436 iteration: 78550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05461 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.11424 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.15913 RPN box loss: 0.00863 RPN score loss: 0.01035 RPN total loss: 0.01898 Total loss: 0.8804 timestamp: 1654974822.1066377 iteration: 78555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09599 FastRCNN class loss: 0.09235 FastRCNN total loss: 0.18833 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.1825 RPN box loss: 0.02407 RPN score loss: 0.01157 RPN total loss: 0.03564 Total loss: 0.99452 timestamp: 1654974825.3559563 iteration: 78560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09524 FastRCNN class loss: 0.0883 FastRCNN total loss: 0.18354 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.15432 RPN box loss: 0.0205 RPN score loss: 0.0115 RPN total loss: 0.03199 Total loss: 0.95791 timestamp: 1654974828.568878 iteration: 78565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09913 FastRCNN class loss: 0.06116 FastRCNN total loss: 0.16029 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.11445 RPN box loss: 0.01177 RPN score loss: 0.00347 RPN total loss: 0.01525 Total loss: 0.87804 timestamp: 1654974831.8709002 iteration: 78570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06217 FastRCNN class loss: 0.07272 FastRCNN total loss: 0.13488 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.0004 Mask loss: 0.10461 RPN box loss: 0.0051 RPN score loss: 0.00173 RPN total loss: 0.00683 Total loss: 0.83436 timestamp: 1654974835.09988 iteration: 78575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09723 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.17163 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.0004 Mask loss: 0.10618 RPN box loss: 0.00827 RPN score loss: 0.00595 RPN total loss: 0.01421 Total loss: 0.88007 timestamp: 1654974838.3109431 iteration: 78580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05805 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.11645 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.0004 Mask loss: 0.11485 RPN box loss: 0.00673 RPN score loss: 0.00289 RPN total loss: 0.00962 Total loss: 0.82896 timestamp: 1654974841.524637 iteration: 78585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07961 FastRCNN class loss: 0.08872 FastRCNN total loss: 0.16833 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.0004 Mask loss: 0.13696 RPN box loss: 0.01994 RPN score loss: 0.00803 RPN total loss: 0.02797 Total loss: 0.9213 timestamp: 1654974844.6584554 iteration: 78590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09229 FastRCNN class loss: 0.08011 FastRCNN total loss: 0.1724 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.0004 Mask loss: 0.1907 RPN box loss: 0.01533 RPN score loss: 0.00551 RPN total loss: 0.02084 Total loss: 0.97198 timestamp: 1654974847.8918219 iteration: 78595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07659 FastRCNN class loss: 0.05677 FastRCNN total loss: 0.13336 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.0004 Mask loss: 0.1506 RPN box loss: 0.00333 RPN score loss: 0.00214 RPN total loss: 0.00548 Total loss: 0.87747 timestamp: 1654974851.1033864 iteration: 78600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12621 FastRCNN class loss: 0.12119 FastRCNN total loss: 0.2474 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.0004 Mask loss: 0.159 RPN box loss: 0.01486 RPN score loss: 0.00904 RPN total loss: 0.0239 Total loss: 1.01834 timestamp: 1654974854.4040349 iteration: 78605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05607 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.1208 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.12697 RPN box loss: 0.00989 RPN score loss: 0.00438 RPN total loss: 0.01426 Total loss: 0.85008 timestamp: 1654974857.5666127 iteration: 78610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05035 FastRCNN class loss: 0.04476 FastRCNN total loss: 0.0951 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.12384 RPN box loss: 0.00615 RPN score loss: 0.00611 RPN total loss: 0.01226 Total loss: 0.81924 timestamp: 1654974860.7716706 iteration: 78615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08288 FastRCNN class loss: 0.06132 FastRCNN total loss: 0.1442 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.13181 RPN box loss: 0.02028 RPN score loss: 0.00482 RPN total loss: 0.0251 Total loss: 0.88914 timestamp: 1654974863.9704733 iteration: 78620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05394 FastRCNN class loss: 0.04186 FastRCNN total loss: 0.0958 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.0911 RPN box loss: 0.01296 RPN score loss: 0.01139 RPN total loss: 0.02435 Total loss: 0.79928 timestamp: 1654974867.1734915 iteration: 78625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10001 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.1614 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.1486 RPN box loss: 0.00473 RPN score loss: 0.00254 RPN total loss: 0.00727 Total loss: 0.90529 timestamp: 1654974870.3272133 iteration: 78630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0685 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.11335 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.09212 RPN box loss: 0.00775 RPN score loss: 0.0037 RPN total loss: 0.01146 Total loss: 0.80496 timestamp: 1654974873.477424 iteration: 78635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14275 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.22996 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.0004 Mask loss: 0.15347 RPN box loss: 0.01711 RPN score loss: 0.00848 RPN total loss: 0.02559 Total loss: 0.99704 timestamp: 1654974876.6588414 iteration: 78640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13028 FastRCNN class loss: 0.07584 FastRCNN total loss: 0.20613 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.0004 Mask loss: 0.15153 RPN box loss: 0.00667 RPN score loss: 0.00197 RPN total loss: 0.00863 Total loss: 0.95431 timestamp: 1654974879.799791 iteration: 78645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0597 FastRCNN class loss: 0.05236 FastRCNN total loss: 0.11206 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.0004 Mask loss: 0.10328 RPN box loss: 0.03453 RPN score loss: 0.00889 RPN total loss: 0.04343 Total loss: 0.84678 timestamp: 1654974883.0339556 iteration: 78650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08037 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.1532 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.0004 Mask loss: 0.10853 RPN box loss: 0.01107 RPN score loss: 0.00178 RPN total loss: 0.01286 Total loss: 0.8626 timestamp: 1654974886.2816925 iteration: 78655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.17273 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.0004 Mask loss: 0.1446 RPN box loss: 0.02278 RPN score loss: 0.00317 RPN total loss: 0.02594 Total loss: 0.93129 timestamp: 1654974889.5115743 iteration: 78660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1627 FastRCNN class loss: 0.13292 FastRCNN total loss: 0.29562 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.0004 Mask loss: 0.15599 RPN box loss: 0.01738 RPN score loss: 0.00806 RPN total loss: 0.02544 Total loss: 1.06506 timestamp: 1654974892.740636 iteration: 78665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06125 FastRCNN class loss: 0.04 FastRCNN total loss: 0.10124 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.0004 Mask loss: 0.10019 RPN box loss: 0.00521 RPN score loss: 0.00424 RPN total loss: 0.00945 Total loss: 0.79891 timestamp: 1654974895.9237356 iteration: 78670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13082 FastRCNN class loss: 0.08974 FastRCNN total loss: 0.22056 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.0004 Mask loss: 0.16945 RPN box loss: 0.00894 RPN score loss: 0.0054 RPN total loss: 0.01434 Total loss: 0.99236 timestamp: 1654974899.1235442 iteration: 78675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08121 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.1445 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.0004 Mask loss: 0.1265 RPN box loss: 0.00601 RPN score loss: 0.00303 RPN total loss: 0.00904 Total loss: 0.86805 timestamp: 1654974902.29246 iteration: 78680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07118 FastRCNN class loss: 0.0356 FastRCNN total loss: 0.10678 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.0004 Mask loss: 0.07613 RPN box loss: 0.0078 RPN score loss: 0.00048 RPN total loss: 0.00828 Total loss: 0.7792 timestamp: 1654974905.464847 iteration: 78685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1227 FastRCNN class loss: 0.09732 FastRCNN total loss: 0.22002 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.0004 Mask loss: 0.1521 RPN box loss: 0.01799 RPN score loss: 0.00794 RPN total loss: 0.02592 Total loss: 0.98605 timestamp: 1654974908.6578481 iteration: 78690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05154 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.10608 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.0004 Mask loss: 0.1262 RPN box loss: 0.00501 RPN score loss: 0.00058 RPN total loss: 0.00559 Total loss: 0.82587 timestamp: 1654974911.960151 iteration: 78695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07926 FastRCNN class loss: 0.05271 FastRCNN total loss: 0.13197 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.0004 Mask loss: 0.13957 RPN box loss: 0.00929 RPN score loss: 0.0069 RPN total loss: 0.01619 Total loss: 0.87574 timestamp: 1654974915.2401588 iteration: 78700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08895 FastRCNN class loss: 0.05158 FastRCNN total loss: 0.14052 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.14212 RPN box loss: 0.00961 RPN score loss: 0.00418 RPN total loss: 0.0138 Total loss: 0.88444 timestamp: 1654974918.4438612 iteration: 78705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09238 FastRCNN class loss: 0.05966 FastRCNN total loss: 0.15205 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.12312 RPN box loss: 0.01021 RPN score loss: 0.00269 RPN total loss: 0.0129 Total loss: 0.87608 timestamp: 1654974921.6310644 iteration: 78710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09675 FastRCNN class loss: 0.03598 FastRCNN total loss: 0.13273 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.10423 RPN box loss: 0.00409 RPN score loss: 0.00257 RPN total loss: 0.00666 Total loss: 0.83163 timestamp: 1654974924.854246 iteration: 78715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09301 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.16514 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.12985 RPN box loss: 0.01175 RPN score loss: 0.00836 RPN total loss: 0.02011 Total loss: 0.9031 timestamp: 1654974928.0791078 iteration: 78720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12182 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.20104 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.1412 RPN box loss: 0.0168 RPN score loss: 0.00286 RPN total loss: 0.01966 Total loss: 0.94991 timestamp: 1654974931.2921057 iteration: 78725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04498 FastRCNN class loss: 0.05202 FastRCNN total loss: 0.097 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.09262 RPN box loss: 0.00495 RPN score loss: 0.00281 RPN total loss: 0.00776 Total loss: 0.78537 timestamp: 1654974934.5426755 iteration: 78730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16192 FastRCNN class loss: 0.09853 FastRCNN total loss: 0.26045 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.0004 Mask loss: 0.12465 RPN box loss: 0.03515 RPN score loss: 0.00673 RPN total loss: 0.04188 Total loss: 1.01498 timestamp: 1654974937.6912413 iteration: 78735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07077 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.14103 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.0004 Mask loss: 0.16256 RPN box loss: 0.01855 RPN score loss: 0.00823 RPN total loss: 0.02678 Total loss: 0.91836 timestamp: 1654974940.9106545 iteration: 78740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14351 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.22015 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.0004 Mask loss: 0.17023 RPN box loss: 0.01961 RPN score loss: 0.00503 RPN total loss: 0.02464 Total loss: 1.00301 timestamp: 1654974944.0828876 iteration: 78745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06379 FastRCNN class loss: 0.03919 FastRCNN total loss: 0.10299 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.0004 Mask loss: 0.11519 RPN box loss: 0.00472 RPN score loss: 0.00159 RPN total loss: 0.0063 Total loss: 0.81247 timestamp: 1654974947.269884 iteration: 78750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05152 FastRCNN class loss: 0.08333 FastRCNN total loss: 0.13485 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.0004 Mask loss: 0.17574 RPN box loss: 0.01087 RPN score loss: 0.01021 RPN total loss: 0.02108 Total loss: 0.91967 timestamp: 1654974950.469776 iteration: 78755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06688 FastRCNN class loss: 0.05947 FastRCNN total loss: 0.12636 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.0004 Mask loss: 0.10812 RPN box loss: 0.00478 RPN score loss: 0.0022 RPN total loss: 0.00698 Total loss: 0.82944 timestamp: 1654974953.7372603 iteration: 78760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06027 FastRCNN class loss: 0.03963 FastRCNN total loss: 0.0999 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.0004 Mask loss: 0.11433 RPN box loss: 0.00449 RPN score loss: 0.00114 RPN total loss: 0.00563 Total loss: 0.80785 timestamp: 1654974956.9536211 iteration: 78765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09623 FastRCNN class loss: 0.12718 FastRCNN total loss: 0.22341 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.0004 Mask loss: 0.14704 RPN box loss: 0.02051 RPN score loss: 0.00599 RPN total loss: 0.02649 Total loss: 0.98492 timestamp: 1654974960.12602 iteration: 78770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06662 FastRCNN class loss: 0.03649 FastRCNN total loss: 0.10312 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.0004 Mask loss: 0.10236 RPN box loss: 0.00941 RPN score loss: 0.00435 RPN total loss: 0.01375 Total loss: 0.80722 timestamp: 1654974963.3341098 iteration: 78775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12304 FastRCNN class loss: 0.10453 FastRCNN total loss: 0.22757 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.0004 Mask loss: 0.14992 RPN box loss: 0.02764 RPN score loss: 0.00855 RPN total loss: 0.03619 Total loss: 1.00165 timestamp: 1654974966.4830606 iteration: 78780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07617 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.13849 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.0004 Mask loss: 0.08551 RPN box loss: 0.00551 RPN score loss: 0.00125 RPN total loss: 0.00676 Total loss: 0.81874 timestamp: 1654974969.6386337 iteration: 78785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0899 FastRCNN class loss: 0.05355 FastRCNN total loss: 0.14345 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.0004 Mask loss: 0.07731 RPN box loss: 0.01765 RPN score loss: 0.0027 RPN total loss: 0.02035 Total loss: 0.82909 timestamp: 1654974972.7278137 iteration: 78790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09907 FastRCNN class loss: 0.08746 FastRCNN total loss: 0.18653 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.0004 Mask loss: 0.1635 RPN box loss: 0.01217 RPN score loss: 0.00802 RPN total loss: 0.02019 Total loss: 0.9582 timestamp: 1654974975.904864 iteration: 78795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.05868 FastRCNN total loss: 0.1693 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.0004 Mask loss: 0.14012 RPN box loss: 0.01048 RPN score loss: 0.00499 RPN total loss: 0.01547 Total loss: 0.91285 timestamp: 1654974979.1702397 iteration: 78800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.06324 FastRCNN total loss: 0.19735 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.0004 Mask loss: 0.09961 RPN box loss: 0.00728 RPN score loss: 0.00393 RPN total loss: 0.01121 Total loss: 0.89614 timestamp: 1654974982.2895994 iteration: 78805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09876 FastRCNN class loss: 0.0731 FastRCNN total loss: 0.17186 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.0004 Mask loss: 0.12154 RPN box loss: 0.00759 RPN score loss: 0.00163 RPN total loss: 0.00922 Total loss: 0.89059 timestamp: 1654974985.505885 iteration: 78810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06572 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.11759 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.0004 Mask loss: 0.1303 RPN box loss: 0.0068 RPN score loss: 0.00308 RPN total loss: 0.00988 Total loss: 0.84573 timestamp: 1654974988.6483006 iteration: 78815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07361 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.14182 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.0004 Mask loss: 0.16616 RPN box loss: 0.01366 RPN score loss: 0.00753 RPN total loss: 0.02119 Total loss: 0.91713 timestamp: 1654974991.87946 iteration: 78820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.12223 FastRCNN total loss: 0.2032 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.0004 Mask loss: 0.16935 RPN box loss: 0.01412 RPN score loss: 0.02022 RPN total loss: 0.03433 Total loss: 0.99485 timestamp: 1654974995.1058342 iteration: 78825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08577 FastRCNN class loss: 0.07293 FastRCNN total loss: 0.1587 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.0004 Mask loss: 0.13384 RPN box loss: 0.00292 RPN score loss: 0.00109 RPN total loss: 0.004 Total loss: 0.88451 timestamp: 1654974998.3234906 iteration: 78830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07318 FastRCNN class loss: 0.05662 FastRCNN total loss: 0.1298 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.0004 Mask loss: 0.13955 RPN box loss: 0.00809 RPN score loss: 0.00612 RPN total loss: 0.01421 Total loss: 0.87152 timestamp: 1654975001.5691552 iteration: 78835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08017 FastRCNN class loss: 0.05337 FastRCNN total loss: 0.13355 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.0004 Mask loss: 0.17826 RPN box loss: 0.00837 RPN score loss: 0.00242 RPN total loss: 0.01079 Total loss: 0.91055 timestamp: 1654975004.7322078 iteration: 78840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07915 FastRCNN class loss: 0.0558 FastRCNN total loss: 0.13495 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.0004 Mask loss: 0.11698 RPN box loss: 0.00784 RPN score loss: 0.00581 RPN total loss: 0.01365 Total loss: 0.85353 timestamp: 1654975007.881165 iteration: 78845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05488 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.12277 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.0004 Mask loss: 0.14574 RPN box loss: 0.01644 RPN score loss: 0.00266 RPN total loss: 0.01911 Total loss: 0.87557 timestamp: 1654975011.0435362 iteration: 78850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13815 FastRCNN class loss: 0.06272 FastRCNN total loss: 0.20087 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.0004 Mask loss: 0.08923 RPN box loss: 0.0176 RPN score loss: 0.00443 RPN total loss: 0.02203 Total loss: 0.90009 timestamp: 1654975014.2232473 iteration: 78855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14577 FastRCNN class loss: 0.06111 FastRCNN total loss: 0.20687 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.0004 Mask loss: 0.11521 RPN box loss: 0.01129 RPN score loss: 0.00721 RPN total loss: 0.0185 Total loss: 0.92853 timestamp: 1654975017.443591 iteration: 78860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.05919 FastRCNN total loss: 0.14335 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.0004 Mask loss: 0.14505 RPN box loss: 0.01171 RPN score loss: 0.00248 RPN total loss: 0.0142 Total loss: 0.89055 timestamp: 1654975020.6569443 iteration: 78865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06888 FastRCNN class loss: 0.03678 FastRCNN total loss: 0.10566 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.0004 Mask loss: 0.16179 RPN box loss: 0.00912 RPN score loss: 0.00328 RPN total loss: 0.01241 Total loss: 0.8678 timestamp: 1654975023.8329487 iteration: 78870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.12125 FastRCNN total loss: 0.2282 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.0004 Mask loss: 0.15581 RPN box loss: 0.01934 RPN score loss: 0.00766 RPN total loss: 0.02701 Total loss: 0.99897 timestamp: 1654975027.0133748 iteration: 78875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07014 FastRCNN class loss: 0.0453 FastRCNN total loss: 0.11544 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.0004 Mask loss: 0.09549 RPN box loss: 0.00819 RPN score loss: 0.00371 RPN total loss: 0.0119 Total loss: 0.81078 timestamp: 1654975030.27724 iteration: 78880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09246 FastRCNN class loss: 0.11916 FastRCNN total loss: 0.21162 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.0004 Mask loss: 0.15484 RPN box loss: 0.01814 RPN score loss: 0.0079 RPN total loss: 0.02604 Total loss: 0.98044 timestamp: 1654975033.5445695 iteration: 78885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12438 FastRCNN class loss: 0.04746 FastRCNN total loss: 0.17184 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.0004 Mask loss: 0.11619 RPN box loss: 0.00476 RPN score loss: 0.00314 RPN total loss: 0.0079 Total loss: 0.88388 timestamp: 1654975036.6992147 iteration: 78890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08797 FastRCNN class loss: 0.05722 FastRCNN total loss: 0.1452 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.0004 Mask loss: 0.13266 RPN box loss: 0.03225 RPN score loss: 0.00385 RPN total loss: 0.0361 Total loss: 0.9019 timestamp: 1654975039.8925483 iteration: 78895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08812 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.14924 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.0004 Mask loss: 0.13094 RPN box loss: 0.01328 RPN score loss: 0.00723 RPN total loss: 0.0205 Total loss: 0.88863 timestamp: 1654975043.1248872 iteration: 78900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08752 FastRCNN class loss: 0.08057 FastRCNN total loss: 0.16809 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.0004 Mask loss: 0.11461 RPN box loss: 0.00615 RPN score loss: 0.00254 RPN total loss: 0.00869 Total loss: 0.87932 timestamp: 1654975046.3027937 iteration: 78905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07829 FastRCNN class loss: 0.08546 FastRCNN total loss: 0.16375 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.0004 Mask loss: 0.12666 RPN box loss: 0.00936 RPN score loss: 0.01297 RPN total loss: 0.02234 Total loss: 0.90069 timestamp: 1654975049.4672375 iteration: 78910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1241 FastRCNN class loss: 0.10943 FastRCNN total loss: 0.23353 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.0004 Mask loss: 0.15707 RPN box loss: 0.02889 RPN score loss: 0.02366 RPN total loss: 0.05255 Total loss: 1.03108 timestamp: 1654975052.6896832 iteration: 78915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12707 FastRCNN class loss: 0.06133 FastRCNN total loss: 0.1884 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.0004 Mask loss: 0.13431 RPN box loss: 0.00952 RPN score loss: 0.00608 RPN total loss: 0.01559 Total loss: 0.92624 timestamp: 1654975055.9406488 iteration: 78920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08737 FastRCNN class loss: 0.09201 FastRCNN total loss: 0.17938 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.0004 Mask loss: 0.12038 RPN box loss: 0.01561 RPN score loss: 0.0029 RPN total loss: 0.01851 Total loss: 0.9062 timestamp: 1654975059.0988955 iteration: 78925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04561 FastRCNN class loss: 0.03639 FastRCNN total loss: 0.082 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.0004 Mask loss: 0.0945 RPN box loss: 0.00236 RPN score loss: 0.00306 RPN total loss: 0.00542 Total loss: 0.76986 timestamp: 1654975062.3150032 iteration: 78930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08264 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.14904 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.0004 Mask loss: 0.09096 RPN box loss: 0.00847 RPN score loss: 0.00177 RPN total loss: 0.01023 Total loss: 0.83817 timestamp: 1654975065.5058403 iteration: 78935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12036 FastRCNN class loss: 0.09097 FastRCNN total loss: 0.21133 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.0004 Mask loss: 0.1942 RPN box loss: 0.01334 RPN score loss: 0.01005 RPN total loss: 0.0234 Total loss: 1.01686 timestamp: 1654975068.7229006 iteration: 78940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07143 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.14198 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.0004 Mask loss: 0.12482 RPN box loss: 0.01504 RPN score loss: 0.00365 RPN total loss: 0.01869 Total loss: 0.87341 timestamp: 1654975071.9200525 iteration: 78945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09261 FastRCNN class loss: 0.08019 FastRCNN total loss: 0.1728 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.0004 Mask loss: 0.22276 RPN box loss: 0.00978 RPN score loss: 0.00249 RPN total loss: 0.01228 Total loss: 0.99576 timestamp: 1654975075.1117067 iteration: 78950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05219 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.11601 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.0004 Mask loss: 0.12055 RPN box loss: 0.01011 RPN score loss: 0.00573 RPN total loss: 0.01584 Total loss: 0.84031 timestamp: 1654975078.3072925 iteration: 78955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0571 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.12061 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.0004 Mask loss: 0.11976 RPN box loss: 0.00552 RPN score loss: 0.00441 RPN total loss: 0.00992 Total loss: 0.8382 timestamp: 1654975081.474219 iteration: 78960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13014 FastRCNN class loss: 0.08858 FastRCNN total loss: 0.21872 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.0004 Mask loss: 0.12104 RPN box loss: 0.01179 RPN score loss: 0.00634 RPN total loss: 0.01813 Total loss: 0.94581 timestamp: 1654975084.688009 iteration: 78965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10727 FastRCNN class loss: 0.0494 FastRCNN total loss: 0.15668 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.0004 Mask loss: 0.12999 RPN box loss: 0.04807 RPN score loss: 0.00356 RPN total loss: 0.05163 Total loss: 0.9262 timestamp: 1654975087.9245584 iteration: 78970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09963 FastRCNN class loss: 0.05519 FastRCNN total loss: 0.15482 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.118 RPN box loss: 0.01828 RPN score loss: 0.0024 RPN total loss: 0.02068 Total loss: 0.88142 timestamp: 1654975091.1576552 iteration: 78975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09434 FastRCNN class loss: 0.09561 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.12963 RPN box loss: 0.01068 RPN score loss: 0.00127 RPN total loss: 0.01195 Total loss: 0.91944 timestamp: 1654975094.3434868 iteration: 78980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07245 FastRCNN class loss: 0.04593 FastRCNN total loss: 0.11838 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.08654 RPN box loss: 0.0085 RPN score loss: 0.0045 RPN total loss: 0.01301 Total loss: 0.80585 timestamp: 1654975097.5965068 iteration: 78985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0788 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.12885 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.08334 RPN box loss: 0.01253 RPN score loss: 0.00264 RPN total loss: 0.01517 Total loss: 0.81527 timestamp: 1654975100.8256874 iteration: 78990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10276 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.17219 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.13006 RPN box loss: 0.01002 RPN score loss: 0.00923 RPN total loss: 0.01925 Total loss: 0.90941 timestamp: 1654975104.12475 iteration: 78995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06102 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.1345 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.10476 RPN box loss: 0.00678 RPN score loss: 0.01184 RPN total loss: 0.01862 Total loss: 0.84578 timestamp: 1654975107.3096993 iteration: 79000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09647 FastRCNN class loss: 0.03033 FastRCNN total loss: 0.1268 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.0004 Mask loss: 0.1006 RPN box loss: 0.00839 RPN score loss: 0.00145 RPN total loss: 0.00984 Total loss: 0.82515 timestamp: 1654975110.5471125 iteration: 79005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0972 FastRCNN class loss: 0.07554 FastRCNN total loss: 0.17274 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.0004 Mask loss: 0.14403 RPN box loss: 0.00974 RPN score loss: 0.00515 RPN total loss: 0.01489 Total loss: 0.91957 timestamp: 1654975113.7694118 iteration: 79010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12614 FastRCNN class loss: 0.08503 FastRCNN total loss: 0.21117 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.0004 Mask loss: 0.09887 RPN box loss: 0.01242 RPN score loss: 0.00379 RPN total loss: 0.01622 Total loss: 0.91416 timestamp: 1654975116.9283006 iteration: 79015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06878 FastRCNN class loss: 0.06873 FastRCNN total loss: 0.13751 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.0004 Mask loss: 0.13714 RPN box loss: 0.00914 RPN score loss: 0.00414 RPN total loss: 0.01327 Total loss: 0.87583 timestamp: 1654975120.110871 iteration: 79020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09818 FastRCNN class loss: 0.05453 FastRCNN total loss: 0.15271 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.0004 Mask loss: 0.12821 RPN box loss: 0.01091 RPN score loss: 0.00383 RPN total loss: 0.01474 Total loss: 0.88356 timestamp: 1654975123.32667 iteration: 79025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07716 FastRCNN class loss: 0.08211 FastRCNN total loss: 0.15928 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.0004 Mask loss: 0.11691 RPN box loss: 0.01174 RPN score loss: 0.00325 RPN total loss: 0.01499 Total loss: 0.87907 timestamp: 1654975126.505624 iteration: 79030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0487 FastRCNN class loss: 0.04102 FastRCNN total loss: 0.08972 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.0004 Mask loss: 0.10967 RPN box loss: 0.00824 RPN score loss: 0.00096 RPN total loss: 0.00921 Total loss: 0.7965 timestamp: 1654975129.6793857 iteration: 79035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14011 FastRCNN class loss: 0.15101 FastRCNN total loss: 0.29112 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.0004 Mask loss: 0.21742 RPN box loss: 0.01721 RPN score loss: 0.00819 RPN total loss: 0.0254 Total loss: 1.12183 timestamp: 1654975132.8543406 iteration: 79040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10878 FastRCNN class loss: 0.15125 FastRCNN total loss: 0.26003 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.0004 Mask loss: 0.15622 RPN box loss: 0.01185 RPN score loss: 0.00502 RPN total loss: 0.01687 Total loss: 1.021 timestamp: 1654975136.0194542 iteration: 79045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14716 FastRCNN class loss: 0.09029 FastRCNN total loss: 0.23745 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.0004 Mask loss: 0.1797 RPN box loss: 0.01511 RPN score loss: 0.01009 RPN total loss: 0.0252 Total loss: 1.03024 timestamp: 1654975139.1867585 iteration: 79050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08552 FastRCNN class loss: 0.08188 FastRCNN total loss: 0.1674 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.0004 Mask loss: 0.16597 RPN box loss: 0.01196 RPN score loss: 0.00206 RPN total loss: 0.01402 Total loss: 0.93528 timestamp: 1654975142.4370327 iteration: 79055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06338 FastRCNN class loss: 0.08758 FastRCNN total loss: 0.15096 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.0004 Mask loss: 0.12215 RPN box loss: 0.00877 RPN score loss: 0.00151 RPN total loss: 0.01028 Total loss: 0.87128 timestamp: 1654975145.612483 iteration: 79060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11689 FastRCNN class loss: 0.11394 FastRCNN total loss: 0.23082 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.0004 Mask loss: 0.12064 RPN box loss: 0.01568 RPN score loss: 0.00433 RPN total loss: 0.02002 Total loss: 0.95936 timestamp: 1654975148.7862985 iteration: 79065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09962 FastRCNN class loss: 0.06708 FastRCNN total loss: 0.16671 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.0004 Mask loss: 0.11198 RPN box loss: 0.0189 RPN score loss: 0.00229 RPN total loss: 0.02119 Total loss: 0.88776 timestamp: 1654975151.9763143 iteration: 79070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07288 FastRCNN class loss: 0.05347 FastRCNN total loss: 0.12636 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.0004 Mask loss: 0.11726 RPN box loss: 0.01362 RPN score loss: 0.00641 RPN total loss: 0.02002 Total loss: 0.85152 timestamp: 1654975155.1755266 iteration: 79075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10055 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.16709 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.0004 Mask loss: 0.12888 RPN box loss: 0.01242 RPN score loss: 0.00255 RPN total loss: 0.01497 Total loss: 0.89881 timestamp: 1654975158.4229486 iteration: 79080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.086 FastRCNN class loss: 0.0494 FastRCNN total loss: 0.1354 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.0004 Mask loss: 0.11279 RPN box loss: 0.00531 RPN score loss: 0.00546 RPN total loss: 0.01077 Total loss: 0.84685 timestamp: 1654975161.5945017 iteration: 79085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13757 FastRCNN class loss: 0.04033 FastRCNN total loss: 0.1779 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.0004 Mask loss: 0.12852 RPN box loss: 0.02491 RPN score loss: 0.00318 RPN total loss: 0.02809 Total loss: 0.92239 timestamp: 1654975164.8186102 iteration: 79090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05379 FastRCNN class loss: 0.03566 FastRCNN total loss: 0.08945 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.0004 Mask loss: 0.11961 RPN box loss: 0.01472 RPN score loss: 0.00221 RPN total loss: 0.01693 Total loss: 0.81386 timestamp: 1654975167.92924 iteration: 79095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06423 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.1262 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.0004 Mask loss: 0.07576 RPN box loss: 0.0042 RPN score loss: 0.00096 RPN total loss: 0.00517 Total loss: 0.79501 timestamp: 1654975171.0954547 iteration: 79100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05898 FastRCNN class loss: 0.0593 FastRCNN total loss: 0.11828 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.0004 Mask loss: 0.0977 RPN box loss: 0.00436 RPN score loss: 0.00352 RPN total loss: 0.00788 Total loss: 0.81173 timestamp: 1654975174.2410367 iteration: 79105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.17333 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.0004 Mask loss: 0.15044 RPN box loss: 0.04441 RPN score loss: 0.00553 RPN total loss: 0.04994 Total loss: 0.96158 timestamp: 1654975177.3873591 iteration: 79110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08731 FastRCNN class loss: 0.11107 FastRCNN total loss: 0.19838 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.0004 Mask loss: 0.1396 RPN box loss: 0.02136 RPN score loss: 0.01001 RPN total loss: 0.03137 Total loss: 0.95722 timestamp: 1654975180.6698885 iteration: 79115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0713 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.13293 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.0004 Mask loss: 0.10945 RPN box loss: 0.01688 RPN score loss: 0.00842 RPN total loss: 0.0253 Total loss: 0.85554 timestamp: 1654975183.8996994 iteration: 79120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06899 FastRCNN class loss: 0.05311 FastRCNN total loss: 0.12211 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.0004 Mask loss: 0.1078 RPN box loss: 0.00514 RPN score loss: 0.00099 RPN total loss: 0.00613 Total loss: 0.82391 timestamp: 1654975187.0489428 iteration: 79125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08827 FastRCNN class loss: 0.03389 FastRCNN total loss: 0.12217 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.09971 RPN box loss: 0.00954 RPN score loss: 0.00351 RPN total loss: 0.01305 Total loss: 0.82279 timestamp: 1654975190.194041 iteration: 79130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08443 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.15948 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.17005 RPN box loss: 0.00821 RPN score loss: 0.00863 RPN total loss: 0.01683 Total loss: 0.93422 timestamp: 1654975193.4495966 iteration: 79135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08715 FastRCNN class loss: 0.06974 FastRCNN total loss: 0.15689 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.14222 RPN box loss: 0.01299 RPN score loss: 0.00245 RPN total loss: 0.01545 Total loss: 0.90242 timestamp: 1654975196.5941226 iteration: 79140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12627 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.19739 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.1169 RPN box loss: 0.00922 RPN score loss: 0.00153 RPN total loss: 0.01075 Total loss: 0.91291 timestamp: 1654975199.8042471 iteration: 79145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08341 FastRCNN class loss: 0.06238 FastRCNN total loss: 0.14579 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.16489 RPN box loss: 0.0402 RPN score loss: 0.00628 RPN total loss: 0.04648 Total loss: 0.94502 timestamp: 1654975203.0448341 iteration: 79150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08231 FastRCNN class loss: 0.04899 FastRCNN total loss: 0.1313 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.18639 RPN box loss: 0.00643 RPN score loss: 0.00351 RPN total loss: 0.00994 Total loss: 0.9155 timestamp: 1654975206.1860812 iteration: 79155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09547 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.15893 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.0004 Mask loss: 0.13053 RPN box loss: 0.00806 RPN score loss: 0.00094 RPN total loss: 0.009 Total loss: 0.88631 timestamp: 1654975209.3577116 iteration: 79160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07003 FastRCNN class loss: 0.05927 FastRCNN total loss: 0.1293 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.0004 Mask loss: 0.14063 RPN box loss: 0.0049 RPN score loss: 0.00294 RPN total loss: 0.00785 Total loss: 0.86562 timestamp: 1654975212.5338423 iteration: 79165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09165 FastRCNN class loss: 0.06046 FastRCNN total loss: 0.15211 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.0004 Mask loss: 0.12286 RPN box loss: 0.01 RPN score loss: 0.01273 RPN total loss: 0.02273 Total loss: 0.88555 timestamp: 1654975215.7447863 iteration: 79170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05293 FastRCNN class loss: 0.04509 FastRCNN total loss: 0.09802 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.0004 Mask loss: 0.06148 RPN box loss: 0.00391 RPN score loss: 0.0018 RPN total loss: 0.00571 Total loss: 0.75306 timestamp: 1654975218.9928691 iteration: 79175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09285 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.15773 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.0004 Mask loss: 0.07278 RPN box loss: 0.01613 RPN score loss: 0.00377 RPN total loss: 0.0199 Total loss: 0.83826 timestamp: 1654975222.2019107 iteration: 79180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07549 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.14206 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.0004 Mask loss: 0.09175 RPN box loss: 0.00603 RPN score loss: 0.00372 RPN total loss: 0.00976 Total loss: 0.83141 timestamp: 1654975225.3847725 iteration: 79185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11766 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.18654 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.0004 Mask loss: 0.1715 RPN box loss: 0.02824 RPN score loss: 0.01058 RPN total loss: 0.03881 Total loss: 0.9847 timestamp: 1654975228.545588 iteration: 79190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07036 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.11996 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.0004 Mask loss: 0.1228 RPN box loss: 0.00684 RPN score loss: 0.00703 RPN total loss: 0.01387 Total loss: 0.84448 timestamp: 1654975231.7059276 iteration: 79195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04716 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.11079 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.0004 Mask loss: 0.11562 RPN box loss: 0.01743 RPN score loss: 0.00595 RPN total loss: 0.02338 Total loss: 0.83763 timestamp: 1654975234.9061563 iteration: 79200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13587 FastRCNN class loss: 0.17121 FastRCNN total loss: 0.30709 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.0004 Mask loss: 0.11985 RPN box loss: 0.01745 RPN score loss: 0.01234 RPN total loss: 0.02979 Total loss: 1.04457 timestamp: 1654975238.0818799 iteration: 79205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09233 FastRCNN class loss: 0.05343 FastRCNN total loss: 0.14577 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.0004 Mask loss: 0.12428 RPN box loss: 0.00943 RPN score loss: 0.00429 RPN total loss: 0.01372 Total loss: 0.87161 timestamp: 1654975241.2163806 iteration: 79210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.04197 FastRCNN total loss: 0.14129 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.0004 Mask loss: 0.07623 RPN box loss: 0.00786 RPN score loss: 0.00424 RPN total loss: 0.0121 Total loss: 0.81746 timestamp: 1654975244.325467 iteration: 79215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.15307 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.0004 Mask loss: 0.09515 RPN box loss: 0.00768 RPN score loss: 0.00055 RPN total loss: 0.00823 Total loss: 0.84429 timestamp: 1654975247.5165832 iteration: 79220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10077 FastRCNN class loss: 0.04832 FastRCNN total loss: 0.14908 L1 loss: 0.0000e+00 L2 loss: 0.58783 Learning rate: 0.0004 Mask loss: 0.1187 RPN box loss: 0.01032 RPN score loss: 0.00219 RPN total loss: 0.01252 Total loss: 0.86814 timestamp: 1654975250.6471088 iteration: 79225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06466 FastRCNN class loss: 0.0629 FastRCNN total loss: 0.12756 L1 loss: 0.0000e+00 L2 loss: 0.58783 Learning rate: 0.0004 Mask loss: 0.12877 RPN box loss: 0.00619 RPN score loss: 0.00234 RPN total loss: 0.00853 Total loss: 0.85268 timestamp: 1654975253.825423 iteration: 79230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07767 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.15505 L1 loss: 0.0000e+00 L2 loss: 0.58783 Learning rate: 0.0004 Mask loss: 0.09802 RPN box loss: 0.00923 RPN score loss: 0.00383 RPN total loss: 0.01306 Total loss: 0.85396 timestamp: 1654975257.0031588 iteration: 79235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07079 FastRCNN class loss: 0.04805 FastRCNN total loss: 0.11883 L1 loss: 0.0000e+00 L2 loss: 0.58783 Learning rate: 0.0004 Mask loss: 0.10387 RPN box loss: 0.0031 RPN score loss: 0.00702 RPN total loss: 0.01012 Total loss: 0.82065 timestamp: 1654975260.1822224 iteration: 79240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08827 FastRCNN class loss: 0.11055 FastRCNN total loss: 0.19882 L1 loss: 0.0000e+00 L2 loss: 0.58783 Learning rate: 0.0004 Mask loss: 0.18943 RPN box loss: 0.02134 RPN score loss: 0.02329 RPN total loss: 0.04464 Total loss: 1.02071 timestamp: 1654975263.365936 iteration: 79245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11251 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.18038 L1 loss: 0.0000e+00 L2 loss: 0.58782 Learning rate: 0.0004 Mask loss: 0.13813 RPN box loss: 0.00815 RPN score loss: 0.00728 RPN total loss: 0.01543 Total loss: 0.92177 timestamp: 1654975266.6127837 iteration: 79250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09152 FastRCNN class loss: 0.08647 FastRCNN total loss: 0.17799 L1 loss: 0.0000e+00 L2 loss: 0.58782 Learning rate: 0.0004 Mask loss: 0.13816 RPN box loss: 0.01176 RPN score loss: 0.00915 RPN total loss: 0.02092 Total loss: 0.92488 timestamp: 1654975269.7852216 iteration: 79255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05871 FastRCNN class loss: 0.04025 FastRCNN total loss: 0.09896 L1 loss: 0.0000e+00 L2 loss: 0.58782 Learning rate: 0.0004 Mask loss: 0.14396 RPN box loss: 0.01004 RPN score loss: 0.00456 RPN total loss: 0.01461 Total loss: 0.84534 timestamp: 1654975273.038884 iteration: 79260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12126 FastRCNN class loss: 0.08377 FastRCNN total loss: 0.20503 L1 loss: 0.0000e+00 L2 loss: 0.58782 Learning rate: 0.0004 Mask loss: 0.17389 RPN box loss: 0.00702 RPN score loss: 0.00696 RPN total loss: 0.01398 Total loss: 0.98071 timestamp: 1654975276.2441368 iteration: 79265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07267 FastRCNN class loss: 0.05991 FastRCNN total loss: 0.13258 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.0004 Mask loss: 0.15911 RPN box loss: 0.01969 RPN score loss: 0.01132 RPN total loss: 0.03102 Total loss: 0.91051 timestamp: 1654975279.4831455 iteration: 79270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06827 FastRCNN class loss: 0.08825 FastRCNN total loss: 0.15651 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.0004 Mask loss: 0.12035 RPN box loss: 0.01673 RPN score loss: 0.00444 RPN total loss: 0.02118 Total loss: 0.88585 timestamp: 1654975282.6916718 iteration: 79275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06278 FastRCNN class loss: 0.05017 FastRCNN total loss: 0.11295 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.0004 Mask loss: 0.08439 RPN box loss: 0.00747 RPN score loss: 0.00129 RPN total loss: 0.00876 Total loss: 0.79391 timestamp: 1654975285.8900757 iteration: 79280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07891 FastRCNN class loss: 0.04504 FastRCNN total loss: 0.12395 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.0004 Mask loss: 0.10502 RPN box loss: 0.0147 RPN score loss: 0.00268 RPN total loss: 0.01738 Total loss: 0.83416 timestamp: 1654975289.052762 iteration: 79285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10581 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.17034 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.0004 Mask loss: 0.11834 RPN box loss: 0.0119 RPN score loss: 0.00777 RPN total loss: 0.01967 Total loss: 0.89616 timestamp: 1654975292.2306542 iteration: 79290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.06971 FastRCNN total loss: 0.16542 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.0004 Mask loss: 0.10277 RPN box loss: 0.00537 RPN score loss: 0.00338 RPN total loss: 0.00875 Total loss: 0.86474 timestamp: 1654975295.4313443 iteration: 79295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05502 FastRCNN class loss: 0.04866 FastRCNN total loss: 0.10368 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.09633 RPN box loss: 0.00793 RPN score loss: 0.00386 RPN total loss: 0.01179 Total loss: 0.7996 timestamp: 1654975298.6385016 iteration: 79300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06319 FastRCNN class loss: 0.11049 FastRCNN total loss: 0.17368 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.11441 RPN box loss: 0.01134 RPN score loss: 0.00418 RPN total loss: 0.01552 Total loss: 0.89142 timestamp: 1654975301.8085103 iteration: 79305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06662 FastRCNN class loss: 0.05821 FastRCNN total loss: 0.12483 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.11564 RPN box loss: 0.01163 RPN score loss: 0.00437 RPN total loss: 0.016 Total loss: 0.84427 timestamp: 1654975304.9684122 iteration: 79310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05146 FastRCNN class loss: 0.03713 FastRCNN total loss: 0.08859 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.10125 RPN box loss: 0.05856 RPN score loss: 0.00125 RPN total loss: 0.05981 Total loss: 0.83746 timestamp: 1654975308.14316 iteration: 79315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10849 FastRCNN class loss: 0.1055 FastRCNN total loss: 0.21399 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.14893 RPN box loss: 0.01123 RPN score loss: 0.00626 RPN total loss: 0.01749 Total loss: 0.96821 timestamp: 1654975311.3693604 iteration: 79320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.03642 FastRCNN total loss: 0.13287 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.13309 RPN box loss: 0.00326 RPN score loss: 0.00091 RPN total loss: 0.00418 Total loss: 0.85793 timestamp: 1654975314.5392396 iteration: 79325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08023 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.15111 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.19581 RPN box loss: 0.00632 RPN score loss: 0.00745 RPN total loss: 0.01377 Total loss: 0.94849 timestamp: 1654975317.7098925 iteration: 79330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08863 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.14881 L1 loss: 0.0000e+00 L2 loss: 0.5878 Learning rate: 0.0004 Mask loss: 0.12775 RPN box loss: 0.01389 RPN score loss: 0.00729 RPN total loss: 0.02118 Total loss: 0.88553 timestamp: 1654975320.9448736 iteration: 79335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1043 FastRCNN class loss: 0.08755 FastRCNN total loss: 0.19185 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.07564 RPN box loss: 0.00676 RPN score loss: 0.00352 RPN total loss: 0.01028 Total loss: 0.86556 timestamp: 1654975324.0968783 iteration: 79340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08197 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.13212 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.14743 RPN box loss: 0.0169 RPN score loss: 0.00687 RPN total loss: 0.02377 Total loss: 0.89111 timestamp: 1654975327.283238 iteration: 79345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07559 FastRCNN class loss: 0.07182 FastRCNN total loss: 0.14741 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.14742 RPN box loss: 0.01133 RPN score loss: 0.0016 RPN total loss: 0.01292 Total loss: 0.89555 timestamp: 1654975330.549929 iteration: 79350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12705 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.19316 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.1206 RPN box loss: 0.0183 RPN score loss: 0.00205 RPN total loss: 0.02035 Total loss: 0.9219 timestamp: 1654975333.7361379 iteration: 79355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.11295 FastRCNN total loss: 0.1997 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.14002 RPN box loss: 0.00943 RPN score loss: 0.00503 RPN total loss: 0.01446 Total loss: 0.94196 timestamp: 1654975336.957306 iteration: 79360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11906 FastRCNN class loss: 0.05839 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.07919 RPN box loss: 0.00567 RPN score loss: 0.00591 RPN total loss: 0.01158 Total loss: 0.856 timestamp: 1654975340.1893816 iteration: 79365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07705 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.14182 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.0004 Mask loss: 0.12712 RPN box loss: 0.00358 RPN score loss: 0.00352 RPN total loss: 0.00709 Total loss: 0.86382 timestamp: 1654975343.2718055 iteration: 79370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07222 FastRCNN class loss: 0.05063 FastRCNN total loss: 0.12285 L1 loss: 0.0000e+00 L2 loss: 0.58778 Learning rate: 0.0004 Mask loss: 0.14744 RPN box loss: 0.01723 RPN score loss: 0.01114 RPN total loss: 0.02836 Total loss: 0.88644 timestamp: 1654975346.4143958 iteration: 79375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07533 FastRCNN class loss: 0.08376 FastRCNN total loss: 0.15909 L1 loss: 0.0000e+00 L2 loss: 0.58778 Learning rate: 0.0004 Mask loss: 0.13759 RPN box loss: 0.02405 RPN score loss: 0.0037 RPN total loss: 0.02776 Total loss: 0.91223 timestamp: 1654975349.6047027 iteration: 79380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10149 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.17515 L1 loss: 0.0000e+00 L2 loss: 0.58778 Learning rate: 0.0004 Mask loss: 0.12544 RPN box loss: 0.01088 RPN score loss: 0.01199 RPN total loss: 0.02287 Total loss: 0.91123 timestamp: 1654975352.7821655 iteration: 79385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05886 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.13197 L1 loss: 0.0000e+00 L2 loss: 0.58778 Learning rate: 0.0004 Mask loss: 0.11278 RPN box loss: 0.00633 RPN score loss: 0.00113 RPN total loss: 0.00747 Total loss: 0.83999 timestamp: 1654975355.9493642 iteration: 79390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06512 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.11797 L1 loss: 0.0000e+00 L2 loss: 0.58778 Learning rate: 0.0004 Mask loss: 0.11436 RPN box loss: 0.01037 RPN score loss: 0.0012 RPN total loss: 0.01157 Total loss: 0.83167 timestamp: 1654975359.1508026 iteration: 79395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.08207 FastRCNN total loss: 0.19759 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.0004 Mask loss: 0.14579 RPN box loss: 0.01877 RPN score loss: 0.01402 RPN total loss: 0.03279 Total loss: 0.96394 timestamp: 1654975362.3681636 iteration: 79400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.04541 FastRCNN total loss: 0.10782 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.0004 Mask loss: 0.18678 RPN box loss: 0.00935 RPN score loss: 0.00421 RPN total loss: 0.01356 Total loss: 0.89593 timestamp: 1654975365.6199784 iteration: 79405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05862 FastRCNN class loss: 0.06115 FastRCNN total loss: 0.11977 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.0004 Mask loss: 0.12754 RPN box loss: 0.02383 RPN score loss: 0.00569 RPN total loss: 0.02952 Total loss: 0.8646 timestamp: 1654975368.7497416 iteration: 79410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09706 FastRCNN class loss: 0.06153 FastRCNN total loss: 0.15859 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.0004 Mask loss: 0.09374 RPN box loss: 0.00683 RPN score loss: 0.00137 RPN total loss: 0.0082 Total loss: 0.8483 timestamp: 1654975371.961402 iteration: 79415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05647 FastRCNN class loss: 0.04214 FastRCNN total loss: 0.09861 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.0004 Mask loss: 0.15931 RPN box loss: 0.00806 RPN score loss: 0.00203 RPN total loss: 0.01008 Total loss: 0.85577 timestamp: 1654975375.1482673 iteration: 79420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07325 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.13508 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.0004 Mask loss: 0.14063 RPN box loss: 0.01656 RPN score loss: 0.00395 RPN total loss: 0.02051 Total loss: 0.88399 timestamp: 1654975378.3365085 iteration: 79425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07086 FastRCNN class loss: 0.06116 FastRCNN total loss: 0.13202 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.0004 Mask loss: 0.14152 RPN box loss: 0.01548 RPN score loss: 0.01024 RPN total loss: 0.02572 Total loss: 0.88703 timestamp: 1654975381.5643075 iteration: 79430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13707 FastRCNN class loss: 0.07824 FastRCNN total loss: 0.21531 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.0004 Mask loss: 0.12277 RPN box loss: 0.02398 RPN score loss: 0.0064 RPN total loss: 0.03037 Total loss: 0.95621 timestamp: 1654975384.7848742 iteration: 79435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11167 FastRCNN class loss: 0.08125 FastRCNN total loss: 0.19292 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.0004 Mask loss: 0.15334 RPN box loss: 0.01057 RPN score loss: 0.00355 RPN total loss: 0.01413 Total loss: 0.94815 timestamp: 1654975387.92595 iteration: 79440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07565 FastRCNN class loss: 0.05775 FastRCNN total loss: 0.1334 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.0004 Mask loss: 0.14931 RPN box loss: 0.00887 RPN score loss: 0.00203 RPN total loss: 0.0109 Total loss: 0.88136 timestamp: 1654975391.1486099 iteration: 79445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09879 FastRCNN class loss: 0.04847 FastRCNN total loss: 0.14725 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.0004 Mask loss: 0.15322 RPN box loss: 0.02459 RPN score loss: 0.00629 RPN total loss: 0.03089 Total loss: 0.91912 timestamp: 1654975394.288963 iteration: 79450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.0439 FastRCNN total loss: 0.09732 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.0004 Mask loss: 0.09072 RPN box loss: 0.00659 RPN score loss: 0.00098 RPN total loss: 0.00757 Total loss: 0.78335 timestamp: 1654975397.4719856 iteration: 79455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08945 FastRCNN class loss: 0.07123 FastRCNN total loss: 0.16068 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.0004 Mask loss: 0.15511 RPN box loss: 0.00925 RPN score loss: 0.00762 RPN total loss: 0.01687 Total loss: 0.92041 timestamp: 1654975400.6052756 iteration: 79460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09955 FastRCNN class loss: 0.07019 FastRCNN total loss: 0.16974 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.0004 Mask loss: 0.11085 RPN box loss: 0.02346 RPN score loss: 0.00341 RPN total loss: 0.02688 Total loss: 0.89522 timestamp: 1654975403.790679 iteration: 79465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07652 FastRCNN class loss: 0.05135 FastRCNN total loss: 0.12788 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.0004 Mask loss: 0.11399 RPN box loss: 0.0105 RPN score loss: 0.01101 RPN total loss: 0.02151 Total loss: 0.85113 timestamp: 1654975406.972956 iteration: 79470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06473 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.12177 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.0004 Mask loss: 0.07981 RPN box loss: 0.00831 RPN score loss: 0.00227 RPN total loss: 0.01058 Total loss: 0.79991 timestamp: 1654975410.1826708 iteration: 79475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12521 FastRCNN class loss: 0.11272 FastRCNN total loss: 0.23794 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.0004 Mask loss: 0.24485 RPN box loss: 0.03817 RPN score loss: 0.04223 RPN total loss: 0.08039 Total loss: 1.15092 timestamp: 1654975413.4038126 iteration: 79480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04095 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.09231 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.13621 RPN box loss: 0.0045 RPN score loss: 0.00318 RPN total loss: 0.00768 Total loss: 0.82395 timestamp: 1654975416.6200995 iteration: 79485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10631 FastRCNN class loss: 0.07241 FastRCNN total loss: 0.17872 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.17596 RPN box loss: 0.0087 RPN score loss: 0.00206 RPN total loss: 0.01076 Total loss: 0.95319 timestamp: 1654975419.7887595 iteration: 79490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10565 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.16165 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.13877 RPN box loss: 0.00646 RPN score loss: 0.00285 RPN total loss: 0.00931 Total loss: 0.89747 timestamp: 1654975422.9458978 iteration: 79495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12437 FastRCNN class loss: 0.07909 FastRCNN total loss: 0.20346 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.15092 RPN box loss: 0.01037 RPN score loss: 0.0055 RPN total loss: 0.01587 Total loss: 0.95799 timestamp: 1654975426.1077833 iteration: 79500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.0885 FastRCNN total loss: 0.18913 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.14436 RPN box loss: 0.01245 RPN score loss: 0.00373 RPN total loss: 0.01618 Total loss: 0.93741 timestamp: 1654975429.3367424 iteration: 79505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06412 FastRCNN class loss: 0.04384 FastRCNN total loss: 0.10796 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.09836 RPN box loss: 0.01161 RPN score loss: 0.00369 RPN total loss: 0.0153 Total loss: 0.80936 timestamp: 1654975432.5505297 iteration: 79510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08479 FastRCNN class loss: 0.05385 FastRCNN total loss: 0.13863 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.0004 Mask loss: 0.11719 RPN box loss: 0.0121 RPN score loss: 0.00226 RPN total loss: 0.01436 Total loss: 0.85792 timestamp: 1654975435.7958415 iteration: 79515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10284 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.18552 L1 loss: 0.0000e+00 L2 loss: 0.58773 Learning rate: 0.0004 Mask loss: 0.13996 RPN box loss: 0.0108 RPN score loss: 0.00346 RPN total loss: 0.01425 Total loss: 0.92746 timestamp: 1654975438.993124 iteration: 79520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05655 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.12102 L1 loss: 0.0000e+00 L2 loss: 0.58773 Learning rate: 0.0004 Mask loss: 0.11471 RPN box loss: 0.00632 RPN score loss: 0.0038 RPN total loss: 0.01012 Total loss: 0.83358 timestamp: 1654975442.1477163 iteration: 79525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05239 FastRCNN class loss: 0.05872 FastRCNN total loss: 0.1111 L1 loss: 0.0000e+00 L2 loss: 0.58773 Learning rate: 0.0004 Mask loss: 0.11472 RPN box loss: 0.02513 RPN score loss: 0.00511 RPN total loss: 0.03024 Total loss: 0.84379 timestamp: 1654975445.3259158 iteration: 79530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10458 FastRCNN class loss: 0.05888 FastRCNN total loss: 0.16346 L1 loss: 0.0000e+00 L2 loss: 0.58773 Learning rate: 0.0004 Mask loss: 0.11984 RPN box loss: 0.01902 RPN score loss: 0.00388 RPN total loss: 0.0229 Total loss: 0.89393 timestamp: 1654975448.5502985 iteration: 79535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08299 FastRCNN class loss: 0.07558 FastRCNN total loss: 0.15857 L1 loss: 0.0000e+00 L2 loss: 0.58773 Learning rate: 0.0004 Mask loss: 0.14315 RPN box loss: 0.0102 RPN score loss: 0.00676 RPN total loss: 0.01697 Total loss: 0.90642 timestamp: 1654975451.7653327 iteration: 79540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07776 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.16412 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.0004 Mask loss: 0.11981 RPN box loss: 0.01025 RPN score loss: 0.00219 RPN total loss: 0.01244 Total loss: 0.88409 timestamp: 1654975455.001309 iteration: 79545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10396 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.1796 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.0004 Mask loss: 0.15897 RPN box loss: 0.02276 RPN score loss: 0.00501 RPN total loss: 0.02777 Total loss: 0.95407 timestamp: 1654975458.1993644 iteration: 79550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11056 FastRCNN class loss: 0.08428 FastRCNN total loss: 0.19483 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.0004 Mask loss: 0.14238 RPN box loss: 0.00722 RPN score loss: 0.00659 RPN total loss: 0.01381 Total loss: 0.93875 timestamp: 1654975461.441799 iteration: 79555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10926 FastRCNN class loss: 0.05623 FastRCNN total loss: 0.16549 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.0004 Mask loss: 0.11082 RPN box loss: 0.00941 RPN score loss: 0.00338 RPN total loss: 0.01279 Total loss: 0.87681 timestamp: 1654975464.5735493 iteration: 79560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07182 FastRCNN class loss: 0.06879 FastRCNN total loss: 0.14061 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.0004 Mask loss: 0.11185 RPN box loss: 0.00883 RPN score loss: 0.00717 RPN total loss: 0.016 Total loss: 0.85617 timestamp: 1654975467.7392724 iteration: 79565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06064 FastRCNN class loss: 0.03871 FastRCNN total loss: 0.09935 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.0004 Mask loss: 0.09443 RPN box loss: 0.01101 RPN score loss: 0.00109 RPN total loss: 0.0121 Total loss: 0.7936 timestamp: 1654975470.9323611 iteration: 79570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08897 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.17354 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.14013 RPN box loss: 0.01677 RPN score loss: 0.00205 RPN total loss: 0.01882 Total loss: 0.9202 timestamp: 1654975474.141573 iteration: 79575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07221 FastRCNN class loss: 0.08426 FastRCNN total loss: 0.15647 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.11699 RPN box loss: 0.02555 RPN score loss: 0.00339 RPN total loss: 0.02895 Total loss: 0.89012 timestamp: 1654975477.2495573 iteration: 79580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.20093 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.12071 RPN box loss: 0.01474 RPN score loss: 0.00328 RPN total loss: 0.01803 Total loss: 0.92738 timestamp: 1654975480.483537 iteration: 79585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11772 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.18885 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.13999 RPN box loss: 0.01025 RPN score loss: 0.00816 RPN total loss: 0.0184 Total loss: 0.93496 timestamp: 1654975483.620957 iteration: 79590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09151 FastRCNN class loss: 0.04635 FastRCNN total loss: 0.13785 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.10798 RPN box loss: 0.00512 RPN score loss: 0.00278 RPN total loss: 0.0079 Total loss: 0.84144 timestamp: 1654975486.8325906 iteration: 79595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14852 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.21977 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.11235 RPN box loss: 0.00689 RPN score loss: 0.00511 RPN total loss: 0.01201 Total loss: 0.93184 timestamp: 1654975489.9581144 iteration: 79600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06162 FastRCNN class loss: 0.06404 FastRCNN total loss: 0.12566 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.0004 Mask loss: 0.14361 RPN box loss: 0.00522 RPN score loss: 0.01002 RPN total loss: 0.01524 Total loss: 0.87222 timestamp: 1654975493.2367926 iteration: 79605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08562 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.13495 L1 loss: 0.0000e+00 L2 loss: 0.5877 Learning rate: 0.0004 Mask loss: 0.12391 RPN box loss: 0.00559 RPN score loss: 0.00541 RPN total loss: 0.011 Total loss: 0.85756 timestamp: 1654975496.5020711 iteration: 79610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08922 FastRCNN class loss: 0.08447 FastRCNN total loss: 0.17369 L1 loss: 0.0000e+00 L2 loss: 0.5877 Learning rate: 0.0004 Mask loss: 0.15728 RPN box loss: 0.00884 RPN score loss: 0.0112 RPN total loss: 0.02004 Total loss: 0.93871 timestamp: 1654975499.6493368 iteration: 79615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08127 FastRCNN class loss: 0.04686 FastRCNN total loss: 0.12813 L1 loss: 0.0000e+00 L2 loss: 0.5877 Learning rate: 0.0004 Mask loss: 0.09566 RPN box loss: 0.0173 RPN score loss: 0.00211 RPN total loss: 0.01941 Total loss: 0.8309 timestamp: 1654975502.8103518 iteration: 79620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04905 FastRCNN class loss: 0.02594 FastRCNN total loss: 0.07499 L1 loss: 0.0000e+00 L2 loss: 0.5877 Learning rate: 0.0004 Mask loss: 0.0868 RPN box loss: 0.01798 RPN score loss: 0.00154 RPN total loss: 0.01952 Total loss: 0.76901 timestamp: 1654975506.058579 iteration: 79625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07968 FastRCNN class loss: 0.04098 FastRCNN total loss: 0.12066 L1 loss: 0.0000e+00 L2 loss: 0.5877 Learning rate: 0.0004 Mask loss: 0.12639 RPN box loss: 0.00779 RPN score loss: 0.00237 RPN total loss: 0.01015 Total loss: 0.8449 timestamp: 1654975509.247682 iteration: 79630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12961 FastRCNN class loss: 0.08537 FastRCNN total loss: 0.21498 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.0004 Mask loss: 0.15064 RPN box loss: 0.01695 RPN score loss: 0.00454 RPN total loss: 0.02149 Total loss: 0.9748 timestamp: 1654975512.4437459 iteration: 79635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06379 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.12673 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.0004 Mask loss: 0.13468 RPN box loss: 0.00816 RPN score loss: 0.00678 RPN total loss: 0.01495 Total loss: 0.86405 timestamp: 1654975515.705403 iteration: 79640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11555 FastRCNN class loss: 0.04955 FastRCNN total loss: 0.1651 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.0004 Mask loss: 0.1161 RPN box loss: 0.02011 RPN score loss: 0.0072 RPN total loss: 0.02731 Total loss: 0.89621 timestamp: 1654975518.9627576 iteration: 79645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13417 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.2067 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.0004 Mask loss: 0.11621 RPN box loss: 0.01563 RPN score loss: 0.00519 RPN total loss: 0.02082 Total loss: 0.93141 timestamp: 1654975522.1461797 iteration: 79650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05639 FastRCNN class loss: 0.04534 FastRCNN total loss: 0.10173 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.0004 Mask loss: 0.1209 RPN box loss: 0.01321 RPN score loss: 0.0086 RPN total loss: 0.02181 Total loss: 0.83213 timestamp: 1654975525.3796391 iteration: 79655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08276 FastRCNN class loss: 0.06365 FastRCNN total loss: 0.14642 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.0004 Mask loss: 0.13027 RPN box loss: 0.01262 RPN score loss: 0.00476 RPN total loss: 0.01739 Total loss: 0.88176 timestamp: 1654975528.6651778 iteration: 79660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.1218 FastRCNN total loss: 0.20316 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.0004 Mask loss: 0.135 RPN box loss: 0.01677 RPN score loss: 0.00396 RPN total loss: 0.02073 Total loss: 0.94658 timestamp: 1654975531.8743477 iteration: 79665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08641 FastRCNN class loss: 0.09764 FastRCNN total loss: 0.18405 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.0004 Mask loss: 0.14796 RPN box loss: 0.00884 RPN score loss: 0.00165 RPN total loss: 0.01049 Total loss: 0.93018 timestamp: 1654975535.0626876 iteration: 79670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10207 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.0004 Mask loss: 0.09228 RPN box loss: 0.01076 RPN score loss: 0.00263 RPN total loss: 0.01339 Total loss: 0.84581 timestamp: 1654975538.306673 iteration: 79675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08565 FastRCNN class loss: 0.0527 FastRCNN total loss: 0.13835 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.0004 Mask loss: 0.16903 RPN box loss: 0.00611 RPN score loss: 0.00153 RPN total loss: 0.00764 Total loss: 0.90269 timestamp: 1654975541.5237951 iteration: 79680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08944 FastRCNN class loss: 0.03312 FastRCNN total loss: 0.12256 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.0004 Mask loss: 0.11661 RPN box loss: 0.00341 RPN score loss: 0.00191 RPN total loss: 0.00533 Total loss: 0.83218 timestamp: 1654975544.7464323 iteration: 79685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05232 FastRCNN class loss: 0.03975 FastRCNN total loss: 0.09207 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.0004 Mask loss: 0.14793 RPN box loss: 0.00992 RPN score loss: 0.0009 RPN total loss: 0.01082 Total loss: 0.83849 timestamp: 1654975547.915136 iteration: 79690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05369 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.11254 L1 loss: 0.0000e+00 L2 loss: 0.58767 Learning rate: 0.0004 Mask loss: 0.13073 RPN box loss: 0.00868 RPN score loss: 0.00101 RPN total loss: 0.00968 Total loss: 0.84063 timestamp: 1654975551.0797832 iteration: 79695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09658 FastRCNN class loss: 0.04765 FastRCNN total loss: 0.14422 L1 loss: 0.0000e+00 L2 loss: 0.58767 Learning rate: 0.0004 Mask loss: 0.08688 RPN box loss: 0.00333 RPN score loss: 0.00172 RPN total loss: 0.00506 Total loss: 0.82382 timestamp: 1654975554.2590113 iteration: 79700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13146 FastRCNN class loss: 0.08571 FastRCNN total loss: 0.21716 L1 loss: 0.0000e+00 L2 loss: 0.58767 Learning rate: 0.0004 Mask loss: 0.06589 RPN box loss: 0.0047 RPN score loss: 0.00281 RPN total loss: 0.00751 Total loss: 0.87824 timestamp: 1654975557.506154 iteration: 79705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05022 FastRCNN class loss: 0.05866 FastRCNN total loss: 0.10888 L1 loss: 0.0000e+00 L2 loss: 0.58767 Learning rate: 0.0004 Mask loss: 0.11111 RPN box loss: 0.00455 RPN score loss: 0.00191 RPN total loss: 0.00646 Total loss: 0.81412 timestamp: 1654975560.731943 iteration: 79710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10681 FastRCNN class loss: 0.06391 FastRCNN total loss: 0.17071 L1 loss: 0.0000e+00 L2 loss: 0.58767 Learning rate: 0.0004 Mask loss: 0.09637 RPN box loss: 0.00923 RPN score loss: 0.00702 RPN total loss: 0.01625 Total loss: 0.87099 timestamp: 1654975563.8942277 iteration: 79715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.069 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.1454 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.0004 Mask loss: 0.14699 RPN box loss: 0.01199 RPN score loss: 0.00938 RPN total loss: 0.02137 Total loss: 0.90142 timestamp: 1654975567.1170504 iteration: 79720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11293 FastRCNN class loss: 0.09992 FastRCNN total loss: 0.21285 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.0004 Mask loss: 0.14929 RPN box loss: 0.01701 RPN score loss: 0.00823 RPN total loss: 0.02524 Total loss: 0.97504 timestamp: 1654975570.3661437 iteration: 79725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10903 FastRCNN class loss: 0.06084 FastRCNN total loss: 0.16987 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.0004 Mask loss: 0.14437 RPN box loss: 0.01632 RPN score loss: 0.00288 RPN total loss: 0.01919 Total loss: 0.92109 timestamp: 1654975573.577073 iteration: 79730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05752 FastRCNN class loss: 0.03606 FastRCNN total loss: 0.09358 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.0004 Mask loss: 0.0962 RPN box loss: 0.00284 RPN score loss: 0.00049 RPN total loss: 0.00332 Total loss: 0.78076 timestamp: 1654975576.819022 iteration: 79735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05335 FastRCNN class loss: 0.0348 FastRCNN total loss: 0.08815 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.0004 Mask loss: 0.11418 RPN box loss: 0.00546 RPN score loss: 0.00228 RPN total loss: 0.00774 Total loss: 0.79773 timestamp: 1654975580.0427825 iteration: 79740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04574 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.12747 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.0004 Mask loss: 0.14095 RPN box loss: 0.03986 RPN score loss: 0.01714 RPN total loss: 0.05701 Total loss: 0.91309 timestamp: 1654975583.2526703 iteration: 79745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06378 FastRCNN class loss: 0.04403 FastRCNN total loss: 0.10782 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.16546 RPN box loss: 0.01743 RPN score loss: 0.00298 RPN total loss: 0.02041 Total loss: 0.88134 timestamp: 1654975586.5627995 iteration: 79750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08465 FastRCNN class loss: 0.07638 FastRCNN total loss: 0.16103 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.15844 RPN box loss: 0.01851 RPN score loss: 0.00551 RPN total loss: 0.02402 Total loss: 0.93114 timestamp: 1654975589.7482512 iteration: 79755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03039 FastRCNN class loss: 0.05228 FastRCNN total loss: 0.08266 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.09941 RPN box loss: 0.00572 RPN score loss: 0.00213 RPN total loss: 0.00785 Total loss: 0.77757 timestamp: 1654975592.9475963 iteration: 79760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04972 FastRCNN class loss: 0.06434 FastRCNN total loss: 0.11405 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.10453 RPN box loss: 0.00731 RPN score loss: 0.00363 RPN total loss: 0.01094 Total loss: 0.81717 timestamp: 1654975596.1181114 iteration: 79765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.08651 FastRCNN total loss: 0.1829 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.16364 RPN box loss: 0.00775 RPN score loss: 0.00626 RPN total loss: 0.01401 Total loss: 0.9482 timestamp: 1654975599.269771 iteration: 79770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14636 FastRCNN class loss: 0.06866 FastRCNN total loss: 0.21502 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.12188 RPN box loss: 0.00756 RPN score loss: 0.00487 RPN total loss: 0.01242 Total loss: 0.93697 timestamp: 1654975602.4176755 iteration: 79775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12008 FastRCNN class loss: 0.06348 FastRCNN total loss: 0.18356 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.0004 Mask loss: 0.14418 RPN box loss: 0.0228 RPN score loss: 0.00503 RPN total loss: 0.02782 Total loss: 0.94321 timestamp: 1654975605.6207445 iteration: 79780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06327 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.15932 L1 loss: 0.0000e+00 L2 loss: 0.58764 Learning rate: 0.0004 Mask loss: 0.13225 RPN box loss: 0.02008 RPN score loss: 0.00462 RPN total loss: 0.0247 Total loss: 0.90392 timestamp: 1654975608.8361082 iteration: 79785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0953 FastRCNN class loss: 0.08895 FastRCNN total loss: 0.18425 L1 loss: 0.0000e+00 L2 loss: 0.58764 Learning rate: 0.0004 Mask loss: 0.15286 RPN box loss: 0.02843 RPN score loss: 0.00931 RPN total loss: 0.03774 Total loss: 0.96249 timestamp: 1654975611.9573672 iteration: 79790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08127 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.13431 L1 loss: 0.0000e+00 L2 loss: 0.58764 Learning rate: 0.0004 Mask loss: 0.11876 RPN box loss: 0.00446 RPN score loss: 0.00164 RPN total loss: 0.00609 Total loss: 0.8468 timestamp: 1654975615.1578653 iteration: 79795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14489 FastRCNN class loss: 0.12922 FastRCNN total loss: 0.27411 L1 loss: 0.0000e+00 L2 loss: 0.58764 Learning rate: 0.0004 Mask loss: 0.1965 RPN box loss: 0.04005 RPN score loss: 0.01745 RPN total loss: 0.0575 Total loss: 1.11574 timestamp: 1654975618.4112916 iteration: 79800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06476 FastRCNN class loss: 0.05581 FastRCNN total loss: 0.12057 L1 loss: 0.0000e+00 L2 loss: 0.58764 Learning rate: 0.0004 Mask loss: 0.09402 RPN box loss: 0.01449 RPN score loss: 0.00207 RPN total loss: 0.01656 Total loss: 0.81879 timestamp: 1654975621.596232 iteration: 79805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06361 FastRCNN class loss: 0.03804 FastRCNN total loss: 0.10164 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.0004 Mask loss: 0.10243 RPN box loss: 0.00222 RPN score loss: 0.00268 RPN total loss: 0.0049 Total loss: 0.79661 timestamp: 1654975624.8132412 iteration: 79810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06345 FastRCNN class loss: 0.0456 FastRCNN total loss: 0.10905 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.0004 Mask loss: 0.09543 RPN box loss: 0.00563 RPN score loss: 0.005 RPN total loss: 0.01063 Total loss: 0.80274 timestamp: 1654975627.9724915 iteration: 79815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07611 FastRCNN class loss: 0.0967 FastRCNN total loss: 0.17282 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.0004 Mask loss: 0.12593 RPN box loss: 0.01126 RPN score loss: 0.00981 RPN total loss: 0.02107 Total loss: 0.90745 timestamp: 1654975631.179264 iteration: 79820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.05488 FastRCNN total loss: 0.12726 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.0004 Mask loss: 0.14717 RPN box loss: 0.01171 RPN score loss: 0.00371 RPN total loss: 0.01542 Total loss: 0.87749 timestamp: 1654975634.2595065 iteration: 79825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12838 FastRCNN class loss: 0.09094 FastRCNN total loss: 0.21932 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.0004 Mask loss: 0.15278 RPN box loss: 0.00956 RPN score loss: 0.00329 RPN total loss: 0.01285 Total loss: 0.97257 timestamp: 1654975637.4145749 iteration: 79830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0511 FastRCNN class loss: 0.03489 FastRCNN total loss: 0.08599 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.0004 Mask loss: 0.13145 RPN box loss: 0.00385 RPN score loss: 0.00242 RPN total loss: 0.00627 Total loss: 0.81135 timestamp: 1654975640.622272 iteration: 79835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16131 FastRCNN class loss: 0.08374 FastRCNN total loss: 0.24505 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.16832 RPN box loss: 0.01428 RPN score loss: 0.00134 RPN total loss: 0.01562 Total loss: 1.01662 timestamp: 1654975643.8092887 iteration: 79840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05765 FastRCNN class loss: 0.05036 FastRCNN total loss: 0.108 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.13002 RPN box loss: 0.00408 RPN score loss: 0.00487 RPN total loss: 0.00895 Total loss: 0.8346 timestamp: 1654975647.0226853 iteration: 79845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07625 FastRCNN class loss: 0.05564 FastRCNN total loss: 0.13189 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.10601 RPN box loss: 0.02547 RPN score loss: 0.01415 RPN total loss: 0.03962 Total loss: 0.86514 timestamp: 1654975650.193269 iteration: 79850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08755 FastRCNN class loss: 0.06325 FastRCNN total loss: 0.1508 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.12271 RPN box loss: 0.01138 RPN score loss: 0.00375 RPN total loss: 0.01513 Total loss: 0.87627 timestamp: 1654975653.4205735 iteration: 79855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09723 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.16312 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.11832 RPN box loss: 0.00826 RPN score loss: 0.00391 RPN total loss: 0.01218 Total loss: 0.88123 timestamp: 1654975656.6220407 iteration: 79860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06667 FastRCNN class loss: 0.04015 FastRCNN total loss: 0.10682 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.11819 RPN box loss: 0.00475 RPN score loss: 0.00227 RPN total loss: 0.00702 Total loss: 0.81965 timestamp: 1654975659.8992944 iteration: 79865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.06126 FastRCNN total loss: 0.12703 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.14936 RPN box loss: 0.00526 RPN score loss: 0.0044 RPN total loss: 0.00966 Total loss: 0.87367 timestamp: 1654975663.152213 iteration: 79870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09439 FastRCNN class loss: 0.0631 FastRCNN total loss: 0.1575 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.0004 Mask loss: 0.13017 RPN box loss: 0.01167 RPN score loss: 0.00699 RPN total loss: 0.01866 Total loss: 0.89394 timestamp: 1654975666.278737 iteration: 79875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0902 FastRCNN class loss: 0.05549 FastRCNN total loss: 0.1457 L1 loss: 0.0000e+00 L2 loss: 0.58761 Learning rate: 0.0004 Mask loss: 0.13777 RPN box loss: 0.00547 RPN score loss: 0.00413 RPN total loss: 0.0096 Total loss: 0.88068 timestamp: 1654975669.4954553 iteration: 79880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1053 FastRCNN class loss: 0.05554 FastRCNN total loss: 0.16084 L1 loss: 0.0000e+00 L2 loss: 0.58761 Learning rate: 0.0004 Mask loss: 0.15211 RPN box loss: 0.00438 RPN score loss: 0.01075 RPN total loss: 0.01512 Total loss: 0.91568 timestamp: 1654975672.6726258 iteration: 79885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07427 FastRCNN class loss: 0.09086 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 0.58761 Learning rate: 0.0004 Mask loss: 0.13306 RPN box loss: 0.01018 RPN score loss: 0.00175 RPN total loss: 0.01193 Total loss: 0.89773 timestamp: 1654975675.8584425 iteration: 79890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0915 FastRCNN class loss: 0.06874 FastRCNN total loss: 0.16024 L1 loss: 0.0000e+00 L2 loss: 0.58761 Learning rate: 0.0004 Mask loss: 0.13097 RPN box loss: 0.01366 RPN score loss: 0.00693 RPN total loss: 0.02059 Total loss: 0.89941 timestamp: 1654975679.0786188 iteration: 79895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08266 FastRCNN class loss: 0.04798 FastRCNN total loss: 0.13065 L1 loss: 0.0000e+00 L2 loss: 0.58761 Learning rate: 0.0004 Mask loss: 0.12065 RPN box loss: 0.00459 RPN score loss: 0.00292 RPN total loss: 0.00751 Total loss: 0.84641 timestamp: 1654975682.3329062 iteration: 79900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07797 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.15972 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.0004 Mask loss: 0.1153 RPN box loss: 0.00629 RPN score loss: 0.00457 RPN total loss: 0.01086 Total loss: 0.87348 timestamp: 1654975685.5243332 iteration: 79905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13298 FastRCNN class loss: 0.09898 FastRCNN total loss: 0.23196 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.0004 Mask loss: 0.26024 RPN box loss: 0.0144 RPN score loss: 0.00789 RPN total loss: 0.02229 Total loss: 1.10208 timestamp: 1654975688.7548897 iteration: 79910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11756 FastRCNN class loss: 0.06824 FastRCNN total loss: 0.1858 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.0004 Mask loss: 0.15897 RPN box loss: 0.00631 RPN score loss: 0.01028 RPN total loss: 0.01659 Total loss: 0.94895 timestamp: 1654975692.048046 iteration: 79915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12029 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.18147 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.0004 Mask loss: 0.15593 RPN box loss: 0.02565 RPN score loss: 0.01031 RPN total loss: 0.03596 Total loss: 0.96095 timestamp: 1654975695.2284768 iteration: 79920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07183 FastRCNN class loss: 0.04005 FastRCNN total loss: 0.11188 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.0004 Mask loss: 0.08948 RPN box loss: 0.00928 RPN score loss: 0.00905 RPN total loss: 0.01833 Total loss: 0.80728 timestamp: 1654975698.503336 iteration: 79925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.20706 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.0004 Mask loss: 0.222 RPN box loss: 0.0133 RPN score loss: 0.0057 RPN total loss: 0.019 Total loss: 1.03566 timestamp: 1654975701.7779267 iteration: 79930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12871 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.21206 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.15518 RPN box loss: 0.01261 RPN score loss: 0.0033 RPN total loss: 0.01591 Total loss: 0.97074 timestamp: 1654975705.001825 iteration: 79935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10205 FastRCNN class loss: 0.06857 FastRCNN total loss: 0.17062 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.14212 RPN box loss: 0.01546 RPN score loss: 0.00344 RPN total loss: 0.01891 Total loss: 0.91924 timestamp: 1654975708.162146 iteration: 79940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.1743 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.18026 RPN box loss: 0.01405 RPN score loss: 0.00547 RPN total loss: 0.01952 Total loss: 0.96167 timestamp: 1654975711.322725 iteration: 79945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06698 FastRCNN class loss: 0.04524 FastRCNN total loss: 0.11222 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.11232 RPN box loss: 0.01241 RPN score loss: 0.00317 RPN total loss: 0.01558 Total loss: 0.8277 timestamp: 1654975714.5817826 iteration: 79950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09707 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.15955 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.13509 RPN box loss: 0.01319 RPN score loss: 0.00205 RPN total loss: 0.01524 Total loss: 0.89747 timestamp: 1654975717.8720937 iteration: 79955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05036 FastRCNN class loss: 0.05508 FastRCNN total loss: 0.10544 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.14457 RPN box loss: 0.00299 RPN score loss: 0.00503 RPN total loss: 0.00802 Total loss: 0.84561 timestamp: 1654975720.984039 iteration: 79960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08728 FastRCNN class loss: 0.048 FastRCNN total loss: 0.13528 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.0004 Mask loss: 0.1149 RPN box loss: 0.01253 RPN score loss: 0.00172 RPN total loss: 0.01425 Total loss: 0.85202 timestamp: 1654975724.1956813 iteration: 79965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06786 FastRCNN class loss: 0.04284 FastRCNN total loss: 0.1107 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.0004 Mask loss: 0.09445 RPN box loss: 0.00496 RPN score loss: 0.00203 RPN total loss: 0.00699 Total loss: 0.79972 timestamp: 1654975727.3883176 iteration: 79970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.0598 FastRCNN total loss: 0.14922 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.0004 Mask loss: 0.15773 RPN box loss: 0.01016 RPN score loss: 0.00212 RPN total loss: 0.01228 Total loss: 0.90681 timestamp: 1654975730.6174538 iteration: 79975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05331 FastRCNN class loss: 0.04253 FastRCNN total loss: 0.09584 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.0004 Mask loss: 0.08858 RPN box loss: 0.00557 RPN score loss: 0.00083 RPN total loss: 0.0064 Total loss: 0.7784 timestamp: 1654975733.8327196 iteration: 79980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14591 FastRCNN class loss: 0.09707 FastRCNN total loss: 0.24298 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.0004 Mask loss: 0.10821 RPN box loss: 0.02181 RPN score loss: 0.00217 RPN total loss: 0.02399 Total loss: 0.96275 timestamp: 1654975737.0929887 iteration: 79985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10569 FastRCNN class loss: 0.06895 FastRCNN total loss: 0.17463 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.0004 Mask loss: 0.16719 RPN box loss: 0.01705 RPN score loss: 0.01001 RPN total loss: 0.02707 Total loss: 0.95646 timestamp: 1654975740.282128 iteration: 79990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09595 FastRCNN class loss: 0.08147 FastRCNN total loss: 0.17742 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.0004 Mask loss: 0.08734 RPN box loss: 0.00385 RPN score loss: 0.00076 RPN total loss: 0.00462 Total loss: 0.85695 timestamp: 1654975743.5637593 iteration: 79995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10461 FastRCNN class loss: 0.07191 FastRCNN total loss: 0.17651 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 0.0004 Mask loss: 0.22016 RPN box loss: 0.01677 RPN score loss: 0.00468 RPN total loss: 0.02145 Total loss: 1.0057 timestamp: 1654975746.715849 iteration: 80000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.15711 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 0.0004 Mask loss: 0.1452 RPN box loss: 0.01114 RPN score loss: 0.00448 RPN total loss: 0.01561 Total loss: 0.9055 Saving checkpoints for 80000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-80000.tlt. ================================= Start evaluation cycle 08 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-80000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 6.0466s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.3372s - Throughput: 11.9 imgs/s Running inference on batch 003/125... - Step Time: 0.3387s - Throughput: 11.8 imgs/s Running inference on batch 004/125... - Step Time: 0.3461s - Throughput: 11.6 imgs/s Running inference on batch 005/125... - Step Time: 0.2681s - Throughput: 14.9 imgs/s Running inference on batch 006/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 007/125... - Step Time: 0.3451s - Throughput: 11.6 imgs/s Running inference on batch 008/125... - Step Time: 0.3426s - Throughput: 11.7 imgs/s Running inference on batch 009/125... - Step Time: 0.3452s - Throughput: 11.6 imgs/s Running inference on batch 010/125... - Step Time: 0.3415s - Throughput: 11.7 imgs/s Running inference on batch 011/125... - Step Time: 0.3493s - Throughput: 11.5 imgs/s Running inference on batch 012/125... - Step Time: 0.3400s - Throughput: 11.8 imgs/s Running inference on batch 013/125... - Step Time: 0.3301s - Throughput: 12.1 imgs/s Running inference on batch 014/125... - Step Time: 0.3324s - Throughput: 12.0 imgs/s Running inference on batch 015/125... - Step Time: 0.3365s - Throughput: 11.9 imgs/s Running inference on batch 016/125... - Step Time: 0.3241s - Throughput: 12.3 imgs/s Running inference on batch 017/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 018/125... - Step Time: 0.3250s - Throughput: 12.3 imgs/s Running inference on batch 019/125... - Step Time: 0.3441s - Throughput: 11.6 imgs/s Running inference on batch 020/125... - Step Time: 0.3448s - Throughput: 11.6 imgs/s Running inference on batch 021/125... - Step Time: 0.3379s - Throughput: 11.8 imgs/s Running inference on batch 022/125... - Step Time: 0.3440s - Throughput: 11.6 imgs/s Running inference on batch 023/125... - Step Time: 0.3408s - Throughput: 11.7 imgs/s Running inference on batch 024/125... - Step Time: 0.3330s - Throughput: 12.0 imgs/s Running inference on batch 025/125... - Step Time: 0.3707s - Throughput: 10.8 imgs/s Running inference on batch 026/125... - Step Time: 0.3328s - Throughput: 12.0 imgs/s Running inference on batch 027/125... - Step Time: 0.3287s - Throughput: 12.2 imgs/s Running inference on batch 028/125... - Step Time: 0.3271s - Throughput: 12.2 imgs/s Running inference on batch 029/125... - Step Time: 0.3356s - Throughput: 11.9 imgs/s Running inference on batch 030/125... - Step Time: 0.3418s - Throughput: 11.7 imgs/s Running inference on batch 031/125... - Step Time: 0.3497s - Throughput: 11.4 imgs/s Running inference on batch 032/125... - Step Time: 0.3522s - Throughput: 11.4 imgs/s Running inference on batch 033/125... - Step Time: 0.3544s - Throughput: 11.3 imgs/s Running inference on batch 034/125... - Step Time: 0.3380s - Throughput: 11.8 imgs/s Running inference on batch 035/125... - Step Time: 0.3248s - Throughput: 12.3 imgs/s Running inference on batch 036/125... - Step Time: 0.3437s - Throughput: 11.6 imgs/s Running inference on batch 037/125... - Step Time: 0.3387s - Throughput: 11.8 imgs/s Running inference on batch 038/125... - Step Time: 0.3515s - Throughput: 11.4 imgs/s Running inference on batch 039/125... - Step Time: 0.3379s - Throughput: 11.8 imgs/s Running inference on batch 040/125... - Step Time: 0.3699s - Throughput: 10.8 imgs/s Running inference on batch 041/125... - Step Time: 0.3456s - Throughput: 11.6 imgs/s Running inference on batch 042/125... - Step Time: 0.3374s - Throughput: 11.9 imgs/s Running inference on batch 043/125... - Step Time: 0.3369s - Throughput: 11.9 imgs/s Running inference on batch 044/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 045/125... - Step Time: 0.3269s - Throughput: 12.2 imgs/s Running inference on batch 046/125... - Step Time: 0.3496s - Throughput: 11.4 imgs/s Running inference on batch 047/125... - Step Time: 0.3364s - 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Throughput: 13.0 imgs/s Running inference on batch 120/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 121/125... - Step Time: 0.3290s - Throughput: 12.2 imgs/s Running inference on batch 122/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 123/125... - Step Time: 0.3297s - Throughput: 12.1 imgs/s Running inference on batch 124/125... - Step Time: 0.3479s - Throughput: 11.5 imgs/s Running inference on batch 125/125... - Step Time: 0.3395s - Throughput: 11.8 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 11.9 samples/sec Total processed steps: 125 Total processing time: 0.0h 24m 24s ==================== Metrics ==================== AP: 0.211538330 AP50: 0.332726896 AP75: 0.210990414 APl: 0.247734681 APm: 0.051906105 APs: 0.002245298 ARl: 0.447363824 ARm: 0.100243405 ARmax1: 0.294633538 ARmax10: 0.379808873 ARmax100: 0.384864748 ARs: 0.025646998 mask_AP: 0.171836346 mask_AP50: 0.293315411 mask_AP75: 0.175835297 mask_APl: 0.203552112 mask_APm: 0.027523451 mask_APs: 0.000306273 mask_ARl: 0.324963212 mask_ARm: 0.062791049 mask_ARmax1: 0.223751709 mask_ARmax10: 0.272662848 mask_ARmax100: 0.275637686 mask_ARs: 0.010386473 ================================= Start training cycle 09 ================================= Using Dataset Sharding with Horovod *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Training Compute Statistics] 543.0 GFLOPS/image Checkpoint is missing variable [l2/kernel] Checkpoint is missing variable [l2/bias] Checkpoint is missing variable [l3/kernel] Checkpoint is missing variable [l3/bias] Checkpoint is missing variable [l4/kernel] Checkpoint is missing variable [l4/bias] Checkpoint is missing variable [l5/kernel] Checkpoint is missing variable [l5/bias] Checkpoint is missing variable [post_hoc_d2/kernel] Checkpoint is missing variable [post_hoc_d2/bias] Checkpoint is missing variable [post_hoc_d3/kernel] Checkpoint is missing variable [post_hoc_d3/bias] Checkpoint is missing variable [post_hoc_d4/kernel] Checkpoint is missing variable [post_hoc_d4/bias] Checkpoint is missing variable [post_hoc_d5/kernel] Checkpoint is missing variable [post_hoc_d5/bias] Checkpoint is missing variable [rpn/kernel] Checkpoint is missing variable [rpn/bias] Checkpoint is missing variable [rpn-class/kernel] Checkpoint is missing variable [rpn-class/bias] Checkpoint is missing variable [rpn-box/kernel] Checkpoint is missing variable [rpn-box/bias] Checkpoint is missing variable [fc6/kernel] Checkpoint is missing variable [fc6/bias] Checkpoint is missing variable [fc7/kernel] Checkpoint is missing variable [fc7/bias] Checkpoint is missing variable [class-predict/kernel] Checkpoint is missing variable [class-predict/bias] Checkpoint is missing variable [box-predict/kernel] Checkpoint is missing variable [box-predict/bias] Checkpoint is missing variable [mask-conv-l0/kernel] Checkpoint is missing variable [mask-conv-l0/bias] Checkpoint is missing variable [mask-conv-l1/kernel] Checkpoint is missing variable [mask-conv-l1/bias] Checkpoint is missing variable [mask-conv-l2/kernel] Checkpoint is missing variable [mask-conv-l2/bias] Checkpoint is missing variable [mask-conv-l3/kernel] Checkpoint is missing variable [mask-conv-l3/bias] Checkpoint is missing variable [conv5-mask/kernel] Checkpoint is missing variable [conv5-mask/bias] Checkpoint is missing variable [mask_fcn_logits/kernel] Checkpoint is missing variable [mask_fcn_logits/bias] # ============================================= # Restart Training # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # timestamp: 1654976931.3458548 iteration: 80005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07943 FastRCNN class loss: 0.04425 FastRCNN total loss: 0.12367 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.11007 RPN box loss: 0.01042 RPN score loss: 0.00123 RPN total loss: 0.01165 Total loss: 0.83296 timestamp: 1654976934.5495858 iteration: 80010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04648 FastRCNN class loss: 0.05327 FastRCNN total loss: 0.09975 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.10461 RPN box loss: 0.01101 RPN score loss: 0.00151 RPN total loss: 0.01251 Total loss: 0.80444 timestamp: 1654976937.7356124 iteration: 80015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06707 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.12289 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.14814 RPN box loss: 0.00694 RPN score loss: 0.0014 RPN total loss: 0.00833 Total loss: 0.86694 timestamp: 1654976940.9470131 iteration: 80020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10375 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.16309 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.12732 RPN box loss: 0.00672 RPN score loss: 0.00121 RPN total loss: 0.00793 Total loss: 0.88592 timestamp: 1654976944.091101 iteration: 80025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07462 FastRCNN class loss: 0.04472 FastRCNN total loss: 0.11933 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.12525 RPN box loss: 0.00526 RPN score loss: 0.00284 RPN total loss: 0.0081 Total loss: 0.84026 timestamp: 1654976947.263307 iteration: 80030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06795 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.12362 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.08485 RPN box loss: 0.00819 RPN score loss: 0.00335 RPN total loss: 0.01154 Total loss: 0.80758 timestamp: 1654976950.5040033 iteration: 80035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06006 FastRCNN class loss: 0.05327 FastRCNN total loss: 0.11333 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.15629 RPN box loss: 0.00619 RPN score loss: 0.00306 RPN total loss: 0.00925 Total loss: 0.86644 timestamp: 1654976953.7052631 iteration: 80040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10705 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.16953 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.14633 RPN box loss: 0.00428 RPN score loss: 0.00065 RPN total loss: 0.00493 Total loss: 0.90837 timestamp: 1654976956.87696 iteration: 80045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13823 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.19905 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.089 RPN box loss: 0.00884 RPN score loss: 0.00382 RPN total loss: 0.01266 Total loss: 0.88828 timestamp: 1654976960.0110025 iteration: 80050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07683 FastRCNN class loss: 0.063 FastRCNN total loss: 0.13982 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.12304 RPN box loss: 0.0129 RPN score loss: 0.00157 RPN total loss: 0.01447 Total loss: 0.86491 timestamp: 1654976963.2249095 iteration: 80055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05594 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.10422 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.11218 RPN box loss: 0.01048 RPN score loss: 0.00257 RPN total loss: 0.01305 Total loss: 0.81701 timestamp: 1654976966.4141102 iteration: 80060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.10843 FastRCNN total loss: 0.22192 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.17921 RPN box loss: 0.01978 RPN score loss: 0.00999 RPN total loss: 0.02977 Total loss: 1.01846 timestamp: 1654976969.601721 iteration: 80065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04837 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.10646 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13931 RPN box loss: 0.01572 RPN score loss: 0.00092 RPN total loss: 0.01664 Total loss: 0.84999 timestamp: 1654976972.77643 iteration: 80070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10212 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.17332 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.10793 RPN box loss: 0.0097 RPN score loss: 0.00301 RPN total loss: 0.01271 Total loss: 0.88152 timestamp: 1654976976.0528352 iteration: 80075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1103 FastRCNN class loss: 0.06854 FastRCNN total loss: 0.17884 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13217 RPN box loss: 0.00992 RPN score loss: 0.00373 RPN total loss: 0.01365 Total loss: 0.91223 timestamp: 1654976979.2608151 iteration: 80080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05903 FastRCNN class loss: 0.02521 FastRCNN total loss: 0.08425 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.12577 RPN box loss: 0.00487 RPN score loss: 0.00281 RPN total loss: 0.00768 Total loss: 0.80527 timestamp: 1654976982.5305915 iteration: 80085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09062 FastRCNN class loss: 0.0695 FastRCNN total loss: 0.16012 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.15759 RPN box loss: 0.01263 RPN score loss: 0.00517 RPN total loss: 0.01779 Total loss: 0.92308 timestamp: 1654976985.7937758 iteration: 80090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12914 FastRCNN class loss: 0.08872 FastRCNN total loss: 0.21786 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13638 RPN box loss: 0.011 RPN score loss: 0.00812 RPN total loss: 0.01912 Total loss: 0.96093 timestamp: 1654976988.9851623 iteration: 80095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06106 FastRCNN class loss: 0.04466 FastRCNN total loss: 0.10572 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.08608 RPN box loss: 0.00663 RPN score loss: 0.00189 RPN total loss: 0.00852 Total loss: 0.78789 timestamp: 1654976992.1835687 iteration: 80100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09091 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.13987 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.0947 RPN box loss: 0.01277 RPN score loss: 0.00368 RPN total loss: 0.01645 Total loss: 0.83858 timestamp: 1654976995.3733158 iteration: 80105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0738 FastRCNN class loss: 0.06311 FastRCNN total loss: 0.13691 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.11225 RPN box loss: 0.03198 RPN score loss: 0.00214 RPN total loss: 0.03411 Total loss: 0.87084 timestamp: 1654976998.582073 iteration: 80110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06147 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.11562 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.1008 RPN box loss: 0.00325 RPN score loss: 0.00161 RPN total loss: 0.00486 Total loss: 0.80885 timestamp: 1654977001.7307303 iteration: 80115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.07142 FastRCNN total loss: 0.21883 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.16285 RPN box loss: 0.00788 RPN score loss: 0.0016 RPN total loss: 0.00948 Total loss: 0.97872 timestamp: 1654977004.9548442 iteration: 80120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03376 FastRCNN class loss: 0.02999 FastRCNN total loss: 0.06375 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.0798 RPN box loss: 0.00367 RPN score loss: 0.00145 RPN total loss: 0.00513 Total loss: 0.73624 timestamp: 1654977008.1969151 iteration: 80125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05329 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.11303 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.1021 RPN box loss: 0.00521 RPN score loss: 0.00444 RPN total loss: 0.00965 Total loss: 0.81235 timestamp: 1654977011.3244677 iteration: 80130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09767 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.18524 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.16147 RPN box loss: 0.03269 RPN score loss: 0.00583 RPN total loss: 0.03852 Total loss: 0.9728 timestamp: 1654977014.564965 iteration: 80135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1107 FastRCNN class loss: 0.07946 FastRCNN total loss: 0.19016 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13385 RPN box loss: 0.01336 RPN score loss: 0.01051 RPN total loss: 0.02387 Total loss: 0.93544 timestamp: 1654977017.7393327 iteration: 80140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11082 FastRCNN class loss: 0.08 FastRCNN total loss: 0.19082 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13507 RPN box loss: 0.01575 RPN score loss: 0.0027 RPN total loss: 0.01845 Total loss: 0.93191 timestamp: 1654977020.967613 iteration: 80145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07867 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.13488 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.08769 RPN box loss: 0.00382 RPN score loss: 0.00342 RPN total loss: 0.00724 Total loss: 0.81737 timestamp: 1654977024.1313899 iteration: 80150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1041 FastRCNN class loss: 0.08825 FastRCNN total loss: 0.19234 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.10605 RPN box loss: 0.02246 RPN score loss: 0.00266 RPN total loss: 0.02512 Total loss: 0.91108 timestamp: 1654977027.364401 iteration: 80155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08374 FastRCNN class loss: 0.04953 FastRCNN total loss: 0.13328 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.08518 RPN box loss: 0.0091 RPN score loss: 0.00096 RPN total loss: 0.01006 Total loss: 0.81608 timestamp: 1654977030.5483866 iteration: 80160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07633 FastRCNN class loss: 0.08596 FastRCNN total loss: 0.16229 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.14544 RPN box loss: 0.00479 RPN score loss: 0.00101 RPN total loss: 0.0058 Total loss: 0.9011 timestamp: 1654977033.7124615 iteration: 80165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06386 FastRCNN class loss: 0.03908 FastRCNN total loss: 0.10294 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.10972 RPN box loss: 0.00348 RPN score loss: 0.00478 RPN total loss: 0.00825 Total loss: 0.80848 timestamp: 1654977036.9550512 iteration: 80170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.07363 FastRCNN total loss: 0.15962 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.2398 RPN box loss: 0.01555 RPN score loss: 0.00575 RPN total loss: 0.0213 Total loss: 1.00829 timestamp: 1654977040.1968565 iteration: 80175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0655 FastRCNN class loss: 0.0674 FastRCNN total loss: 0.13289 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.12115 RPN box loss: 0.00542 RPN score loss: 0.00319 RPN total loss: 0.00861 Total loss: 0.85022 timestamp: 1654977043.322544 iteration: 80180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07712 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.12711 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.15539 RPN box loss: 0.01077 RPN score loss: 0.00624 RPN total loss: 0.01701 Total loss: 0.88707 timestamp: 1654977046.5206618 iteration: 80185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05873 FastRCNN class loss: 0.11565 FastRCNN total loss: 0.17438 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13299 RPN box loss: 0.02004 RPN score loss: 0.01631 RPN total loss: 0.03635 Total loss: 0.93129 timestamp: 1654977049.6984942 iteration: 80190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06046 FastRCNN class loss: 0.07034 FastRCNN total loss: 0.1308 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.13332 RPN box loss: 0.01391 RPN score loss: 0.00495 RPN total loss: 0.01886 Total loss: 0.87054 timestamp: 1654977052.8623085 iteration: 80195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10357 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.18677 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.15809 RPN box loss: 0.00972 RPN score loss: 0.00607 RPN total loss: 0.01579 Total loss: 0.94822 timestamp: 1654977056.0423675 iteration: 80200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14851 FastRCNN class loss: 0.0968 FastRCNN total loss: 0.24531 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.11833 RPN box loss: 0.00805 RPN score loss: 0.00268 RPN total loss: 0.01072 Total loss: 0.96193 timestamp: 1654977059.2449875 iteration: 80205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06701 FastRCNN class loss: 0.0804 FastRCNN total loss: 0.14741 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.10439 RPN box loss: 0.01055 RPN score loss: 0.00198 RPN total loss: 0.01253 Total loss: 0.8519 timestamp: 1654977062.4020007 iteration: 80210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08509 FastRCNN class loss: 0.06678 FastRCNN total loss: 0.15187 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.12884 RPN box loss: 0.01049 RPN score loss: 0.00424 RPN total loss: 0.01474 Total loss: 0.88301 timestamp: 1654977065.592357 iteration: 80215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10861 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.19172 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.17948 RPN box loss: 0.0082 RPN score loss: 0.00163 RPN total loss: 0.00983 Total loss: 0.9686 timestamp: 1654977068.7659805 iteration: 80220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04319 FastRCNN class loss: 0.0475 FastRCNN total loss: 0.09069 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.08316 RPN box loss: 0.00498 RPN score loss: 0.00224 RPN total loss: 0.00722 Total loss: 0.76864 timestamp: 1654977071.977127 iteration: 80225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04251 FastRCNN class loss: 0.03859 FastRCNN total loss: 0.0811 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 4.0000e-05 Mask loss: 0.09792 RPN box loss: 0.00974 RPN score loss: 0.00416 RPN total loss: 0.0139 Total loss: 0.78048 timestamp: 1654977075.1557982 iteration: 80230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09337 FastRCNN class loss: 0.07048 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.17556 RPN box loss: 0.00956 RPN score loss: 0.0022 RPN total loss: 0.01176 Total loss: 0.93872 timestamp: 1654977078.3495996 iteration: 80235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08469 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.08583 RPN box loss: 0.00702 RPN score loss: 0.00663 RPN total loss: 0.01365 Total loss: 0.84745 timestamp: 1654977081.5348768 iteration: 80240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08766 FastRCNN class loss: 0.04756 FastRCNN total loss: 0.13522 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.10217 RPN box loss: 0.00757 RPN score loss: 0.00289 RPN total loss: 0.01046 Total loss: 0.83542 timestamp: 1654977084.711714 iteration: 80245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09338 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.16449 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12807 RPN box loss: 0.00581 RPN score loss: 0.00178 RPN total loss: 0.00759 Total loss: 0.88772 timestamp: 1654977087.9135835 iteration: 80250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06078 FastRCNN class loss: 0.04768 FastRCNN total loss: 0.10846 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09661 RPN box loss: 0.00899 RPN score loss: 0.00082 RPN total loss: 0.00981 Total loss: 0.80245 timestamp: 1654977091.1503396 iteration: 80255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09212 FastRCNN class loss: 0.0547 FastRCNN total loss: 0.14682 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.08343 RPN box loss: 0.00693 RPN score loss: 0.00353 RPN total loss: 0.01046 Total loss: 0.82828 timestamp: 1654977094.3766627 iteration: 80260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05184 FastRCNN class loss: 0.05933 FastRCNN total loss: 0.11118 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09408 RPN box loss: 0.00465 RPN score loss: 0.00119 RPN total loss: 0.00585 Total loss: 0.79867 timestamp: 1654977097.5727036 iteration: 80265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10147 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12908 RPN box loss: 0.00875 RPN score loss: 0.00466 RPN total loss: 0.01341 Total loss: 0.90751 timestamp: 1654977100.7683048 iteration: 80270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10399 FastRCNN class loss: 0.06411 FastRCNN total loss: 0.1681 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.17451 RPN box loss: 0.00801 RPN score loss: 0.00509 RPN total loss: 0.0131 Total loss: 0.94327 timestamp: 1654977103.937652 iteration: 80275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1005 FastRCNN class loss: 0.0674 FastRCNN total loss: 0.16791 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13667 RPN box loss: 0.01434 RPN score loss: 0.00225 RPN total loss: 0.01659 Total loss: 0.90873 timestamp: 1654977107.156497 iteration: 80280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11449 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.16771 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13909 RPN box loss: 0.0034 RPN score loss: 0.00262 RPN total loss: 0.00601 Total loss: 0.90038 timestamp: 1654977110.2869883 iteration: 80285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10415 FastRCNN class loss: 0.04472 FastRCNN total loss: 0.14887 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.07701 RPN box loss: 0.01069 RPN score loss: 0.00726 RPN total loss: 0.01795 Total loss: 0.83138 timestamp: 1654977113.5215294 iteration: 80290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0595 FastRCNN class loss: 0.06371 FastRCNN total loss: 0.12321 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09261 RPN box loss: 0.00544 RPN score loss: 0.00341 RPN total loss: 0.00885 Total loss: 0.81223 timestamp: 1654977116.6881626 iteration: 80295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07775 FastRCNN class loss: 0.07254 FastRCNN total loss: 0.1503 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12726 RPN box loss: 0.01317 RPN score loss: 0.00198 RPN total loss: 0.01514 Total loss: 0.88026 timestamp: 1654977119.888176 iteration: 80300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12349 FastRCNN class loss: 0.08459 FastRCNN total loss: 0.20808 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15923 RPN box loss: 0.01791 RPN score loss: 0.00393 RPN total loss: 0.02184 Total loss: 0.97671 timestamp: 1654977122.994746 iteration: 80305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07741 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.13551 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11408 RPN box loss: 0.00988 RPN score loss: 0.00526 RPN total loss: 0.01514 Total loss: 0.85229 timestamp: 1654977126.2330117 iteration: 80310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09505 FastRCNN class loss: 0.056 FastRCNN total loss: 0.15105 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.1297 RPN box loss: 0.00829 RPN score loss: 0.00545 RPN total loss: 0.01375 Total loss: 0.88206 timestamp: 1654977129.4023416 iteration: 80315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10463 FastRCNN class loss: 0.0527 FastRCNN total loss: 0.15733 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13404 RPN box loss: 0.02058 RPN score loss: 0.0035 RPN total loss: 0.02408 Total loss: 0.90301 timestamp: 1654977132.5937736 iteration: 80320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10588 FastRCNN class loss: 0.05615 FastRCNN total loss: 0.16203 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12844 RPN box loss: 0.0071 RPN score loss: 0.00383 RPN total loss: 0.01094 Total loss: 0.88897 timestamp: 1654977135.8879337 iteration: 80325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07431 FastRCNN class loss: 0.03963 FastRCNN total loss: 0.11395 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11559 RPN box loss: 0.00746 RPN score loss: 0.00219 RPN total loss: 0.00965 Total loss: 0.82675 timestamp: 1654977139.1090024 iteration: 80330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.087 FastRCNN class loss: 0.05316 FastRCNN total loss: 0.14015 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.10642 RPN box loss: 0.00737 RPN score loss: 0.00186 RPN total loss: 0.00923 Total loss: 0.84337 timestamp: 1654977142.3577836 iteration: 80335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0967 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.15184 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11761 RPN box loss: 0.02362 RPN score loss: 0.01026 RPN total loss: 0.03388 Total loss: 0.89089 timestamp: 1654977145.5205097 iteration: 80340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04558 FastRCNN class loss: 0.05342 FastRCNN total loss: 0.099 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15699 RPN box loss: 0.00761 RPN score loss: 0.0014 RPN total loss: 0.00901 Total loss: 0.85257 timestamp: 1654977148.6625714 iteration: 80345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06152 FastRCNN class loss: 0.04817 FastRCNN total loss: 0.10969 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13758 RPN box loss: 0.00568 RPN score loss: 0.00208 RPN total loss: 0.00775 Total loss: 0.84258 timestamp: 1654977151.9264228 iteration: 80350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10947 FastRCNN class loss: 0.08509 FastRCNN total loss: 0.19457 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.22747 RPN box loss: 0.01052 RPN score loss: 0.00896 RPN total loss: 0.01948 Total loss: 1.02907 timestamp: 1654977155.0765927 iteration: 80355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.0387 FastRCNN total loss: 0.1211 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09851 RPN box loss: 0.00723 RPN score loss: 0.00781 RPN total loss: 0.01503 Total loss: 0.82221 timestamp: 1654977158.2282062 iteration: 80360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10068 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.19188 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.14241 RPN box loss: 0.00976 RPN score loss: 0.00903 RPN total loss: 0.01879 Total loss: 0.94065 timestamp: 1654977161.4687078 iteration: 80365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08396 FastRCNN class loss: 0.05025 FastRCNN total loss: 0.13421 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.10502 RPN box loss: 0.0154 RPN score loss: 0.00118 RPN total loss: 0.01658 Total loss: 0.84336 timestamp: 1654977164.6656575 iteration: 80370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06049 FastRCNN class loss: 0.05449 FastRCNN total loss: 0.11498 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09063 RPN box loss: 0.01787 RPN score loss: 0.00092 RPN total loss: 0.01879 Total loss: 0.81197 timestamp: 1654977167.943586 iteration: 80375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06837 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.12521 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.20163 RPN box loss: 0.00821 RPN score loss: 0.00095 RPN total loss: 0.00916 Total loss: 0.92356 timestamp: 1654977171.14558 iteration: 80380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0634 FastRCNN class loss: 0.06585 FastRCNN total loss: 0.12924 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.14585 RPN box loss: 0.01597 RPN score loss: 0.00737 RPN total loss: 0.02334 Total loss: 0.88599 timestamp: 1654977174.3009796 iteration: 80385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16293 FastRCNN class loss: 0.13727 FastRCNN total loss: 0.3002 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15949 RPN box loss: 0.01899 RPN score loss: 0.02378 RPN total loss: 0.04276 Total loss: 1.09001 timestamp: 1654977177.4983277 iteration: 80390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.0451 FastRCNN total loss: 0.14155 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.18518 RPN box loss: 0.00997 RPN score loss: 0.0008 RPN total loss: 0.01077 Total loss: 0.92506 timestamp: 1654977180.6906402 iteration: 80395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06576 FastRCNN class loss: 0.11212 FastRCNN total loss: 0.17788 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12632 RPN box loss: 0.0088 RPN score loss: 0.00229 RPN total loss: 0.01109 Total loss: 0.90286 timestamp: 1654977183.9073613 iteration: 80400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.10391 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12225 RPN box loss: 0.00231 RPN score loss: 0.004 RPN total loss: 0.00631 Total loss: 0.82003 timestamp: 1654977187.0930917 iteration: 80405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0464 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.10899 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11195 RPN box loss: 0.00576 RPN score loss: 0.00107 RPN total loss: 0.00683 Total loss: 0.81533 timestamp: 1654977190.3407204 iteration: 80410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10759 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.20423 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12429 RPN box loss: 0.02239 RPN score loss: 0.00663 RPN total loss: 0.02902 Total loss: 0.9451 timestamp: 1654977193.489638 iteration: 80415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.04242 FastRCNN total loss: 0.1148 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.10009 RPN box loss: 0.00955 RPN score loss: 0.00486 RPN total loss: 0.01441 Total loss: 0.81686 timestamp: 1654977196.7502863 iteration: 80420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09423 FastRCNN class loss: 0.04415 FastRCNN total loss: 0.13838 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.10932 RPN box loss: 0.01023 RPN score loss: 0.00302 RPN total loss: 0.01325 Total loss: 0.84851 timestamp: 1654977199.9963756 iteration: 80425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04212 FastRCNN class loss: 0.06092 FastRCNN total loss: 0.10304 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15028 RPN box loss: 0.0067 RPN score loss: 0.01194 RPN total loss: 0.01864 Total loss: 0.85952 timestamp: 1654977203.200158 iteration: 80430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1447 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.22827 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15352 RPN box loss: 0.01243 RPN score loss: 0.00327 RPN total loss: 0.0157 Total loss: 0.98505 timestamp: 1654977206.4217668 iteration: 80435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07915 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.1531 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15968 RPN box loss: 0.02641 RPN score loss: 0.00829 RPN total loss: 0.0347 Total loss: 0.93503 timestamp: 1654977209.6516647 iteration: 80440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09549 FastRCNN class loss: 0.04966 FastRCNN total loss: 0.14515 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15257 RPN box loss: 0.00602 RPN score loss: 0.00145 RPN total loss: 0.00747 Total loss: 0.89275 timestamp: 1654977212.8517797 iteration: 80445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11438 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.17471 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.1423 RPN box loss: 0.01408 RPN score loss: 0.00893 RPN total loss: 0.02301 Total loss: 0.92757 timestamp: 1654977216.057075 iteration: 80450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06935 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.11969 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13966 RPN box loss: 0.00503 RPN score loss: 0.0069 RPN total loss: 0.01193 Total loss: 0.85884 timestamp: 1654977219.2518508 iteration: 80455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12805 FastRCNN class loss: 0.14432 FastRCNN total loss: 0.27237 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.16754 RPN box loss: 0.03005 RPN score loss: 0.01256 RPN total loss: 0.04261 Total loss: 1.07007 timestamp: 1654977222.4403384 iteration: 80460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07466 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.1458 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.14634 RPN box loss: 0.01227 RPN score loss: 0.0061 RPN total loss: 0.01837 Total loss: 0.89807 timestamp: 1654977225.5907824 iteration: 80465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0737 FastRCNN class loss: 0.03395 FastRCNN total loss: 0.10765 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09632 RPN box loss: 0.00284 RPN score loss: 0.00329 RPN total loss: 0.00613 Total loss: 0.79767 timestamp: 1654977228.8563638 iteration: 80470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10943 FastRCNN class loss: 0.09709 FastRCNN total loss: 0.20653 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13725 RPN box loss: 0.03035 RPN score loss: 0.00905 RPN total loss: 0.0394 Total loss: 0.97073 timestamp: 1654977232.0807872 iteration: 80475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1204 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.18116 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12179 RPN box loss: 0.01015 RPN score loss: 0.0013 RPN total loss: 0.01145 Total loss: 0.90195 timestamp: 1654977235.3148878 iteration: 80480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10449 FastRCNN class loss: 0.0955 FastRCNN total loss: 0.2 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15357 RPN box loss: 0.01495 RPN score loss: 0.0023 RPN total loss: 0.01724 Total loss: 0.95836 timestamp: 1654977238.551836 iteration: 80485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1026 FastRCNN class loss: 0.05949 FastRCNN total loss: 0.16209 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11502 RPN box loss: 0.00863 RPN score loss: 0.0086 RPN total loss: 0.01723 Total loss: 0.8819 timestamp: 1654977241.756109 iteration: 80490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06057 FastRCNN class loss: 0.03003 FastRCNN total loss: 0.0906 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.09815 RPN box loss: 0.01815 RPN score loss: 0.01029 RPN total loss: 0.02844 Total loss: 0.80474 timestamp: 1654977245.0381093 iteration: 80495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08582 FastRCNN class loss: 0.0558 FastRCNN total loss: 0.14162 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.00705 RPN score loss: 0.00226 RPN total loss: 0.00931 Total loss: 0.89489 timestamp: 1654977248.28695 iteration: 80500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11806 FastRCNN class loss: 0.05559 FastRCNN total loss: 0.17365 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.1388 RPN box loss: 0.0109 RPN score loss: 0.0036 RPN total loss: 0.0145 Total loss: 0.9145 timestamp: 1654977251.535449 iteration: 80505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04265 FastRCNN class loss: 0.04112 FastRCNN total loss: 0.08378 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12479 RPN box loss: 0.00334 RPN score loss: 0.00213 RPN total loss: 0.00547 Total loss: 0.8016 timestamp: 1654977254.749664 iteration: 80510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08728 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.1481 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11683 RPN box loss: 0.0053 RPN score loss: 0.0009 RPN total loss: 0.0062 Total loss: 0.85869 timestamp: 1654977257.943526 iteration: 80515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0858 FastRCNN class loss: 0.06663 FastRCNN total loss: 0.15243 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13099 RPN box loss: 0.01643 RPN score loss: 0.00286 RPN total loss: 0.01929 Total loss: 0.89027 timestamp: 1654977261.217988 iteration: 80520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0531 FastRCNN class loss: 0.03032 FastRCNN total loss: 0.08343 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.12768 RPN box loss: 0.01191 RPN score loss: 0.0032 RPN total loss: 0.01511 Total loss: 0.81377 timestamp: 1654977264.4272587 iteration: 80525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12832 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.20512 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.11293 RPN box loss: 0.00968 RPN score loss: 0.00208 RPN total loss: 0.01175 Total loss: 0.91736 timestamp: 1654977267.6443205 iteration: 80530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.05973 FastRCNN total loss: 0.13769 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13855 RPN box loss: 0.01672 RPN score loss: 0.00277 RPN total loss: 0.01949 Total loss: 0.88329 timestamp: 1654977270.8582509 iteration: 80535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0939 FastRCNN class loss: 0.06706 FastRCNN total loss: 0.16096 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 4.0000e-05 Mask loss: 0.13103 RPN box loss: 0.00437 RPN score loss: 0.00438 RPN total loss: 0.00875 Total loss: 0.88829 timestamp: 1654977274.0332422 iteration: 80540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06104 FastRCNN class loss: 0.03924 FastRCNN total loss: 0.10028 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.05943 RPN box loss: 0.00279 RPN score loss: 0.00074 RPN total loss: 0.00353 Total loss: 0.75079 timestamp: 1654977277.2289565 iteration: 80545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11996 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.19634 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.15805 RPN box loss: 0.02825 RPN score loss: 0.01218 RPN total loss: 0.04043 Total loss: 0.98238 timestamp: 1654977280.4791634 iteration: 80550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07424 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.13049 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11332 RPN box loss: 0.01225 RPN score loss: 0.00379 RPN total loss: 0.01604 Total loss: 0.84739 timestamp: 1654977283.680863 iteration: 80555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05858 FastRCNN class loss: 0.04088 FastRCNN total loss: 0.09946 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13797 RPN box loss: 0.0069 RPN score loss: 0.00436 RPN total loss: 0.01126 Total loss: 0.83624 timestamp: 1654977286.942122 iteration: 80560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15733 FastRCNN class loss: 0.0997 FastRCNN total loss: 0.25703 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.19879 RPN box loss: 0.012 RPN score loss: 0.00982 RPN total loss: 0.02182 Total loss: 1.0652 timestamp: 1654977290.1691546 iteration: 80565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05426 FastRCNN class loss: 0.04922 FastRCNN total loss: 0.10348 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13907 RPN box loss: 0.00569 RPN score loss: 0.00131 RPN total loss: 0.007 Total loss: 0.8371 timestamp: 1654977293.29472 iteration: 80570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08854 FastRCNN class loss: 0.05405 FastRCNN total loss: 0.14259 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.20173 RPN box loss: 0.00335 RPN score loss: 0.00799 RPN total loss: 0.01134 Total loss: 0.94321 timestamp: 1654977296.5138829 iteration: 80575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.091 FastRCNN class loss: 0.04794 FastRCNN total loss: 0.13895 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13709 RPN box loss: 0.01223 RPN score loss: 0.00215 RPN total loss: 0.01438 Total loss: 0.87797 timestamp: 1654977299.7247927 iteration: 80580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.0673 FastRCNN total loss: 0.14757 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13534 RPN box loss: 0.01107 RPN score loss: 0.00206 RPN total loss: 0.01313 Total loss: 0.8836 timestamp: 1654977302.9472773 iteration: 80585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.112 FastRCNN class loss: 0.08913 FastRCNN total loss: 0.20112 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.22253 RPN box loss: 0.01198 RPN score loss: 0.00793 RPN total loss: 0.01992 Total loss: 1.03113 timestamp: 1654977306.1867838 iteration: 80590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06477 FastRCNN class loss: 0.05264 FastRCNN total loss: 0.11741 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13208 RPN box loss: 0.00775 RPN score loss: 0.00278 RPN total loss: 0.01053 Total loss: 0.84757 timestamp: 1654977309.3365014 iteration: 80595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09622 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.1698 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11184 RPN box loss: 0.0086 RPN score loss: 0.00749 RPN total loss: 0.01609 Total loss: 0.88527 timestamp: 1654977312.532699 iteration: 80600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13805 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.21823 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12517 RPN box loss: 0.01399 RPN score loss: 0.00921 RPN total loss: 0.0232 Total loss: 0.95415 timestamp: 1654977315.7629519 iteration: 80605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08447 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.14179 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10214 RPN box loss: 0.00657 RPN score loss: 0.00699 RPN total loss: 0.01356 Total loss: 0.84504 timestamp: 1654977318.9342008 iteration: 80610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09832 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.15297 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10631 RPN box loss: 0.00974 RPN score loss: 0.00817 RPN total loss: 0.01791 Total loss: 0.86474 timestamp: 1654977322.217523 iteration: 80615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06445 FastRCNN class loss: 0.06458 FastRCNN total loss: 0.12902 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13936 RPN box loss: 0.01176 RPN score loss: 0.00395 RPN total loss: 0.01571 Total loss: 0.87165 timestamp: 1654977325.360263 iteration: 80620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07311 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.13656 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12378 RPN box loss: 0.00528 RPN score loss: 0.00651 RPN total loss: 0.01179 Total loss: 0.85968 timestamp: 1654977328.5754898 iteration: 80625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07876 FastRCNN class loss: 0.06202 FastRCNN total loss: 0.14078 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10731 RPN box loss: 0.00445 RPN score loss: 0.00189 RPN total loss: 0.00634 Total loss: 0.84198 timestamp: 1654977331.7560542 iteration: 80630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09749 FastRCNN class loss: 0.0626 FastRCNN total loss: 0.16009 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.09837 RPN box loss: 0.01373 RPN score loss: 0.00328 RPN total loss: 0.01701 Total loss: 0.86302 timestamp: 1654977334.8404496 iteration: 80635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05189 FastRCNN class loss: 0.04906 FastRCNN total loss: 0.10095 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10059 RPN box loss: 0.0065 RPN score loss: 0.00057 RPN total loss: 0.00707 Total loss: 0.79616 timestamp: 1654977337.9941065 iteration: 80640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10356 FastRCNN class loss: 0.10531 FastRCNN total loss: 0.20886 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.16122 RPN box loss: 0.01866 RPN score loss: 0.00167 RPN total loss: 0.02033 Total loss: 0.97796 timestamp: 1654977341.1655695 iteration: 80645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15237 FastRCNN class loss: 0.08254 FastRCNN total loss: 0.23491 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.15816 RPN box loss: 0.01006 RPN score loss: 0.00465 RPN total loss: 0.01471 Total loss: 0.99534 timestamp: 1654977344.3496802 iteration: 80650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07874 FastRCNN class loss: 0.05655 FastRCNN total loss: 0.13529 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.14399 RPN box loss: 0.01144 RPN score loss: 0.0083 RPN total loss: 0.01974 Total loss: 0.88657 timestamp: 1654977347.508364 iteration: 80655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04889 FastRCNN class loss: 0.05459 FastRCNN total loss: 0.10348 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10184 RPN box loss: 0.00735 RPN score loss: 0.00501 RPN total loss: 0.01235 Total loss: 0.80522 timestamp: 1654977350.7549496 iteration: 80660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08415 FastRCNN class loss: 0.09781 FastRCNN total loss: 0.18196 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.14164 RPN box loss: 0.01422 RPN score loss: 0.00648 RPN total loss: 0.02071 Total loss: 0.93185 timestamp: 1654977353.9074934 iteration: 80665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07535 FastRCNN class loss: 0.05158 FastRCNN total loss: 0.12693 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13245 RPN box loss: 0.00405 RPN score loss: 0.00151 RPN total loss: 0.00556 Total loss: 0.85249 timestamp: 1654977357.0782309 iteration: 80670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07649 FastRCNN class loss: 0.05587 FastRCNN total loss: 0.13237 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.09901 RPN box loss: 0.01359 RPN score loss: 0.00239 RPN total loss: 0.01598 Total loss: 0.83491 timestamp: 1654977360.2347965 iteration: 80675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0573 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.10001 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12671 RPN box loss: 0.0029 RPN score loss: 0.00064 RPN total loss: 0.00354 Total loss: 0.81782 timestamp: 1654977363.420524 iteration: 80680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10812 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.17914 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.08183 RPN box loss: 0.01395 RPN score loss: 0.00417 RPN total loss: 0.01812 Total loss: 0.86664 timestamp: 1654977366.5715032 iteration: 80685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11519 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.18536 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12845 RPN box loss: 0.02216 RPN score loss: 0.00285 RPN total loss: 0.02501 Total loss: 0.92637 timestamp: 1654977369.733233 iteration: 80690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14628 FastRCNN class loss: 0.10244 FastRCNN total loss: 0.24872 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.15634 RPN box loss: 0.0165 RPN score loss: 0.00685 RPN total loss: 0.02335 Total loss: 1.01596 timestamp: 1654977372.9521093 iteration: 80695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09463 FastRCNN class loss: 0.06999 FastRCNN total loss: 0.16461 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.17473 RPN box loss: 0.02332 RPN score loss: 0.00302 RPN total loss: 0.02634 Total loss: 0.95323 timestamp: 1654977376.1471589 iteration: 80700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09577 FastRCNN class loss: 0.05905 FastRCNN total loss: 0.15482 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.1507 RPN box loss: 0.00734 RPN score loss: 0.00339 RPN total loss: 0.01073 Total loss: 0.9038 timestamp: 1654977379.3822901 iteration: 80705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04602 FastRCNN class loss: 0.04047 FastRCNN total loss: 0.08649 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.07777 RPN box loss: 0.00318 RPN score loss: 0.00258 RPN total loss: 0.00577 Total loss: 0.75757 timestamp: 1654977382.573323 iteration: 80710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05651 FastRCNN class loss: 0.03696 FastRCNN total loss: 0.09347 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.1116 RPN box loss: 0.00498 RPN score loss: 0.00217 RPN total loss: 0.00715 Total loss: 0.79977 timestamp: 1654977385.8120608 iteration: 80715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06287 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.10991 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.1095 RPN box loss: 0.01076 RPN score loss: 0.00294 RPN total loss: 0.0137 Total loss: 0.82066 timestamp: 1654977389.0241487 iteration: 80720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19111 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.25715 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11318 RPN box loss: 0.01191 RPN score loss: 0.01044 RPN total loss: 0.02235 Total loss: 0.98022 timestamp: 1654977392.2667139 iteration: 80725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05979 FastRCNN class loss: 0.03426 FastRCNN total loss: 0.09405 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11444 RPN box loss: 0.01733 RPN score loss: 0.00303 RPN total loss: 0.02036 Total loss: 0.81639 timestamp: 1654977395.50693 iteration: 80730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06683 FastRCNN class loss: 0.05334 FastRCNN total loss: 0.12018 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11984 RPN box loss: 0.01648 RPN score loss: 0.00514 RPN total loss: 0.02162 Total loss: 0.84919 timestamp: 1654977398.763699 iteration: 80735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08235 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.15078 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.09908 RPN box loss: 0.00579 RPN score loss: 0.00131 RPN total loss: 0.0071 Total loss: 0.8445 timestamp: 1654977401.9174802 iteration: 80740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.051 FastRCNN class loss: 0.0314 FastRCNN total loss: 0.0824 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.08703 RPN box loss: 0.00365 RPN score loss: 0.00387 RPN total loss: 0.00752 Total loss: 0.7645 timestamp: 1654977405.253648 iteration: 80745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05129 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.11166 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11952 RPN box loss: 0.00937 RPN score loss: 0.00307 RPN total loss: 0.01244 Total loss: 0.83117 timestamp: 1654977408.4685447 iteration: 80750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08278 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.16339 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12918 RPN box loss: 0.01809 RPN score loss: 0.01096 RPN total loss: 0.02904 Total loss: 0.90916 timestamp: 1654977411.7305799 iteration: 80755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06743 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.15356 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13375 RPN box loss: 0.01064 RPN score loss: 0.00571 RPN total loss: 0.01635 Total loss: 0.8912 timestamp: 1654977414.9435096 iteration: 80760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.16498 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12615 RPN box loss: 0.0092 RPN score loss: 0.00155 RPN total loss: 0.01075 Total loss: 0.88942 timestamp: 1654977418.1988409 iteration: 80765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13836 FastRCNN class loss: 0.06883 FastRCNN total loss: 0.20718 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.17731 RPN box loss: 0.00794 RPN score loss: 0.00156 RPN total loss: 0.00949 Total loss: 0.98154 timestamp: 1654977421.4811149 iteration: 80770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.08272 FastRCNN total loss: 0.22259 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.14214 RPN box loss: 0.01755 RPN score loss: 0.00411 RPN total loss: 0.02166 Total loss: 0.97394 timestamp: 1654977424.6578236 iteration: 80775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05677 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.12058 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11115 RPN box loss: 0.01322 RPN score loss: 0.00421 RPN total loss: 0.01742 Total loss: 0.8367 timestamp: 1654977427.867927 iteration: 80780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04573 FastRCNN class loss: 0.02922 FastRCNN total loss: 0.07495 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13949 RPN box loss: 0.00346 RPN score loss: 0.00165 RPN total loss: 0.00512 Total loss: 0.8071 timestamp: 1654977431.016202 iteration: 80785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0837 FastRCNN class loss: 0.06357 FastRCNN total loss: 0.14727 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.15367 RPN box loss: 0.01075 RPN score loss: 0.00518 RPN total loss: 0.01593 Total loss: 0.90442 timestamp: 1654977434.173326 iteration: 80790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07301 FastRCNN class loss: 0.07711 FastRCNN total loss: 0.15012 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10897 RPN box loss: 0.01068 RPN score loss: 0.00589 RPN total loss: 0.01657 Total loss: 0.86321 timestamp: 1654977437.453715 iteration: 80795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04946 FastRCNN class loss: 0.05246 FastRCNN total loss: 0.10192 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.1293 RPN box loss: 0.00649 RPN score loss: 0.00562 RPN total loss: 0.01211 Total loss: 0.83088 timestamp: 1654977440.6543655 iteration: 80800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12853 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.18753 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10052 RPN box loss: 0.00993 RPN score loss: 0.00859 RPN total loss: 0.01851 Total loss: 0.89411 timestamp: 1654977443.8284392 iteration: 80805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09446 FastRCNN class loss: 0.07191 FastRCNN total loss: 0.16637 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.13535 RPN box loss: 0.01497 RPN score loss: 0.00164 RPN total loss: 0.0166 Total loss: 0.90588 timestamp: 1654977447.078351 iteration: 80810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07348 FastRCNN class loss: 0.03031 FastRCNN total loss: 0.10379 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12273 RPN box loss: 0.00296 RPN score loss: 0.00092 RPN total loss: 0.00388 Total loss: 0.81795 timestamp: 1654977450.281271 iteration: 80815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08396 FastRCNN class loss: 0.06879 FastRCNN total loss: 0.15275 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.17395 RPN box loss: 0.01367 RPN score loss: 0.00405 RPN total loss: 0.01772 Total loss: 0.93197 timestamp: 1654977453.4778612 iteration: 80820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11837 FastRCNN class loss: 0.08654 FastRCNN total loss: 0.20491 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.16357 RPN box loss: 0.00984 RPN score loss: 0.00254 RPN total loss: 0.01239 Total loss: 0.96841 timestamp: 1654977456.6857867 iteration: 80825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10436 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.17881 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12869 RPN box loss: 0.01013 RPN score loss: 0.00549 RPN total loss: 0.01561 Total loss: 0.91066 timestamp: 1654977459.8353758 iteration: 80830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0743 FastRCNN class loss: 0.08312 FastRCNN total loss: 0.15742 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12513 RPN box loss: 0.00481 RPN score loss: 0.0041 RPN total loss: 0.00891 Total loss: 0.879 timestamp: 1654977463.0043404 iteration: 80835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04492 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.10546 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10062 RPN box loss: 0.00353 RPN score loss: 0.00411 RPN total loss: 0.00764 Total loss: 0.80126 timestamp: 1654977466.2467422 iteration: 80840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08615 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.14838 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.12075 RPN box loss: 0.00566 RPN score loss: 0.00721 RPN total loss: 0.01287 Total loss: 0.86955 timestamp: 1654977469.4365046 iteration: 80845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04805 FastRCNN class loss: 0.05604 FastRCNN total loss: 0.10409 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.09589 RPN box loss: 0.01162 RPN score loss: 0.00385 RPN total loss: 0.01547 Total loss: 0.803 timestamp: 1654977472.6570046 iteration: 80850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07433 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.12966 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10686 RPN box loss: 0.01013 RPN score loss: 0.0062 RPN total loss: 0.01634 Total loss: 0.84041 timestamp: 1654977475.8746552 iteration: 80855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08117 FastRCNN class loss: 0.06839 FastRCNN total loss: 0.14957 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.10718 RPN box loss: 0.00826 RPN score loss: 0.00404 RPN total loss: 0.0123 Total loss: 0.85659 timestamp: 1654977479.058857 iteration: 80860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08547 FastRCNN class loss: 0.07726 FastRCNN total loss: 0.16273 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 4.0000e-05 Mask loss: 0.11289 RPN box loss: 0.00807 RPN score loss: 0.00387 RPN total loss: 0.01194 Total loss: 0.8751 timestamp: 1654977482.2255373 iteration: 80865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.16136 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1494 RPN box loss: 0.00792 RPN score loss: 0.00335 RPN total loss: 0.01127 Total loss: 0.90957 timestamp: 1654977485.4775543 iteration: 80870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11684 FastRCNN class loss: 0.07593 FastRCNN total loss: 0.19277 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.14801 RPN box loss: 0.01055 RPN score loss: 0.00874 RPN total loss: 0.01929 Total loss: 0.94762 timestamp: 1654977488.6788087 iteration: 80875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13305 FastRCNN class loss: 0.09417 FastRCNN total loss: 0.22721 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1368 RPN box loss: 0.00788 RPN score loss: 0.00639 RPN total loss: 0.01426 Total loss: 0.96582 timestamp: 1654977491.8781717 iteration: 80880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11731 FastRCNN class loss: 0.10442 FastRCNN total loss: 0.22173 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.21581 RPN box loss: 0.02124 RPN score loss: 0.00866 RPN total loss: 0.02989 Total loss: 1.05498 timestamp: 1654977495.155258 iteration: 80885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09363 FastRCNN class loss: 0.09444 FastRCNN total loss: 0.18807 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.13343 RPN box loss: 0.01975 RPN score loss: 0.00585 RPN total loss: 0.0256 Total loss: 0.93464 timestamp: 1654977498.346985 iteration: 80890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07258 FastRCNN class loss: 0.05623 FastRCNN total loss: 0.12881 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1544 RPN box loss: 0.00607 RPN score loss: 0.00787 RPN total loss: 0.01395 Total loss: 0.8847 timestamp: 1654977501.525139 iteration: 80895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07159 FastRCNN class loss: 0.04344 FastRCNN total loss: 0.11503 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.08557 RPN box loss: 0.01424 RPN score loss: 0.00373 RPN total loss: 0.01797 Total loss: 0.80612 timestamp: 1654977504.7467408 iteration: 80900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09354 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.1601 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.20119 RPN box loss: 0.02127 RPN score loss: 0.01644 RPN total loss: 0.03771 Total loss: 0.98654 timestamp: 1654977507.9601464 iteration: 80905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0592 FastRCNN class loss: 0.04034 FastRCNN total loss: 0.09955 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.08072 RPN box loss: 0.00788 RPN score loss: 0.00063 RPN total loss: 0.00851 Total loss: 0.77632 timestamp: 1654977511.1237738 iteration: 80910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11032 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.18062 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.16877 RPN box loss: 0.02026 RPN score loss: 0.01553 RPN total loss: 0.03579 Total loss: 0.97272 timestamp: 1654977514.3104353 iteration: 80915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0749 FastRCNN class loss: 0.08187 FastRCNN total loss: 0.15676 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.08685 RPN box loss: 0.01466 RPN score loss: 0.00722 RPN total loss: 0.02188 Total loss: 0.85303 timestamp: 1654977517.5157163 iteration: 80920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04563 FastRCNN class loss: 0.0381 FastRCNN total loss: 0.08373 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.07924 RPN box loss: 0.03059 RPN score loss: 0.00285 RPN total loss: 0.03344 Total loss: 0.78394 timestamp: 1654977520.755094 iteration: 80925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05221 FastRCNN class loss: 0.04208 FastRCNN total loss: 0.09429 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11443 RPN box loss: 0.00436 RPN score loss: 0.00313 RPN total loss: 0.00749 Total loss: 0.80375 timestamp: 1654977523.9734318 iteration: 80930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07783 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.13089 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.09921 RPN box loss: 0.0108 RPN score loss: 0.00125 RPN total loss: 0.01205 Total loss: 0.82969 timestamp: 1654977527.2201517 iteration: 80935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09411 FastRCNN class loss: 0.07953 FastRCNN total loss: 0.17364 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15218 RPN box loss: 0.01649 RPN score loss: 0.01071 RPN total loss: 0.0272 Total loss: 0.94056 timestamp: 1654977530.3741457 iteration: 80940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08825 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.15422 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1081 RPN box loss: 0.00648 RPN score loss: 0.00198 RPN total loss: 0.00846 Total loss: 0.85832 timestamp: 1654977533.570189 iteration: 80945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05267 FastRCNN class loss: 0.03366 FastRCNN total loss: 0.08633 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12098 RPN box loss: 0.00488 RPN score loss: 0.00366 RPN total loss: 0.00855 Total loss: 0.8034 timestamp: 1654977536.7041566 iteration: 80950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10221 FastRCNN class loss: 0.10668 FastRCNN total loss: 0.20889 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.18686 RPN box loss: 0.01901 RPN score loss: 0.0052 RPN total loss: 0.02421 Total loss: 1.00751 timestamp: 1654977539.8931272 iteration: 80955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09366 FastRCNN class loss: 0.08085 FastRCNN total loss: 0.17451 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.09093 RPN box loss: 0.01378 RPN score loss: 0.00995 RPN total loss: 0.02372 Total loss: 0.8767 timestamp: 1654977543.0629714 iteration: 80960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10736 FastRCNN class loss: 0.11009 FastRCNN total loss: 0.21744 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.14155 RPN box loss: 0.01213 RPN score loss: 0.00576 RPN total loss: 0.01789 Total loss: 0.96443 timestamp: 1654977546.3150811 iteration: 80965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08765 FastRCNN class loss: 0.05668 FastRCNN total loss: 0.14433 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12687 RPN box loss: 0.00839 RPN score loss: 0.00691 RPN total loss: 0.0153 Total loss: 0.87404 timestamp: 1654977549.465585 iteration: 80970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09516 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12401 RPN box loss: 0.01474 RPN score loss: 0.00616 RPN total loss: 0.02091 Total loss: 0.88986 timestamp: 1654977552.685314 iteration: 80975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07467 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.14201 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11557 RPN box loss: 0.01028 RPN score loss: 0.00227 RPN total loss: 0.01256 Total loss: 0.85768 timestamp: 1654977555.8985426 iteration: 80980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08247 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.14548 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.10046 RPN box loss: 0.00636 RPN score loss: 0.0014 RPN total loss: 0.00776 Total loss: 0.84125 timestamp: 1654977559.1333055 iteration: 80985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04198 FastRCNN class loss: 0.03787 FastRCNN total loss: 0.07985 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15691 RPN box loss: 0.00492 RPN score loss: 0.0059 RPN total loss: 0.01083 Total loss: 0.83513 timestamp: 1654977562.2974408 iteration: 80990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10857 FastRCNN class loss: 0.0813 FastRCNN total loss: 0.18988 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.10548 RPN box loss: 0.00676 RPN score loss: 0.00306 RPN total loss: 0.00982 Total loss: 0.89272 timestamp: 1654977565.5418472 iteration: 80995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.15251 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12735 RPN box loss: 0.01887 RPN score loss: 0.00947 RPN total loss: 0.02834 Total loss: 0.89574 timestamp: 1654977568.7636762 iteration: 81000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.0446 FastRCNN total loss: 0.19671 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.10259 RPN box loss: 0.01204 RPN score loss: 0.00583 RPN total loss: 0.01787 Total loss: 0.90472 timestamp: 1654977571.9062269 iteration: 81005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09744 FastRCNN class loss: 0.04647 FastRCNN total loss: 0.14391 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.13062 RPN box loss: 0.00755 RPN score loss: 0.00709 RPN total loss: 0.01464 Total loss: 0.87671 timestamp: 1654977575.114156 iteration: 81010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10906 FastRCNN class loss: 0.05254 FastRCNN total loss: 0.1616 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12428 RPN box loss: 0.01702 RPN score loss: 0.00712 RPN total loss: 0.02414 Total loss: 0.89756 timestamp: 1654977578.2946968 iteration: 81015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05305 FastRCNN class loss: 0.03567 FastRCNN total loss: 0.08873 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11023 RPN box loss: 0.00389 RPN score loss: 0.0012 RPN total loss: 0.00509 Total loss: 0.79159 timestamp: 1654977581.5093834 iteration: 81020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11167 FastRCNN class loss: 0.08908 FastRCNN total loss: 0.20075 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.21655 RPN box loss: 0.01448 RPN score loss: 0.00825 RPN total loss: 0.02273 Total loss: 1.02758 timestamp: 1654977584.6847022 iteration: 81025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09959 FastRCNN class loss: 0.06701 FastRCNN total loss: 0.16661 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.08691 RPN box loss: 0.00597 RPN score loss: 0.00345 RPN total loss: 0.00943 Total loss: 0.85048 timestamp: 1654977587.9713414 iteration: 81030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05041 FastRCNN class loss: 0.06031 FastRCNN total loss: 0.11073 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.13442 RPN box loss: 0.03009 RPN score loss: 0.00708 RPN total loss: 0.03717 Total loss: 0.86986 timestamp: 1654977591.186979 iteration: 81035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07931 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.16008 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15611 RPN box loss: 0.02525 RPN score loss: 0.00619 RPN total loss: 0.03143 Total loss: 0.93516 timestamp: 1654977594.405283 iteration: 81040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13117 FastRCNN class loss: 0.08015 FastRCNN total loss: 0.21133 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.14726 RPN box loss: 0.00739 RPN score loss: 0.00815 RPN total loss: 0.01554 Total loss: 0.96166 timestamp: 1654977597.678559 iteration: 81045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08716 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.13168 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11042 RPN box loss: 0.00995 RPN score loss: 0.00149 RPN total loss: 0.01144 Total loss: 0.84108 timestamp: 1654977600.8385408 iteration: 81050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05236 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.11726 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15966 RPN box loss: 0.03481 RPN score loss: 0.00306 RPN total loss: 0.03788 Total loss: 0.90234 timestamp: 1654977604.0306182 iteration: 81055 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07365 FastRCNN class loss: 0.0426 FastRCNN total loss: 0.11625 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.09413 RPN box loss: 0.00461 RPN score loss: 0.00129 RPN total loss: 0.0059 Total loss: 0.80382 timestamp: 1654977607.1924627 iteration: 81060 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10583 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.1718 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11265 RPN box loss: 0.00697 RPN score loss: 0.00588 RPN total loss: 0.01285 Total loss: 0.88485 timestamp: 1654977610.335139 iteration: 81065 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06952 FastRCNN class loss: 0.06035 FastRCNN total loss: 0.12987 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12788 RPN box loss: 0.00988 RPN score loss: 0.00252 RPN total loss: 0.0124 Total loss: 0.85769 timestamp: 1654977613.5242093 iteration: 81070 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0875 FastRCNN class loss: 0.07386 FastRCNN total loss: 0.16136 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.14152 RPN box loss: 0.02102 RPN score loss: 0.00624 RPN total loss: 0.02726 Total loss: 0.91768 timestamp: 1654977616.7644982 iteration: 81075 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07377 FastRCNN class loss: 0.0413 FastRCNN total loss: 0.11507 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1147 RPN box loss: 0.01303 RPN score loss: 0.00335 RPN total loss: 0.01639 Total loss: 0.83369 timestamp: 1654977619.9550774 iteration: 81080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.04383 FastRCNN total loss: 0.11299 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11416 RPN box loss: 0.00515 RPN score loss: 0.00219 RPN total loss: 0.00734 Total loss: 0.82203 timestamp: 1654977623.170326 iteration: 81085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11457 FastRCNN class loss: 0.08462 FastRCNN total loss: 0.19919 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.16746 RPN box loss: 0.00456 RPN score loss: 0.00375 RPN total loss: 0.00831 Total loss: 0.9625 timestamp: 1654977626.507874 iteration: 81090 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08401 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.15221 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15127 RPN box loss: 0.00569 RPN score loss: 0.00204 RPN total loss: 0.00773 Total loss: 0.89874 timestamp: 1654977629.6981206 iteration: 81095 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08879 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.17157 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15906 RPN box loss: 0.01177 RPN score loss: 0.00342 RPN total loss: 0.01519 Total loss: 0.93336 timestamp: 1654977632.884608 iteration: 81100 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08413 FastRCNN class loss: 0.04047 FastRCNN total loss: 0.1246 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.16498 RPN box loss: 0.03158 RPN score loss: 0.00631 RPN total loss: 0.03789 Total loss: 0.91502 timestamp: 1654977636.062171 iteration: 81105 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06967 FastRCNN class loss: 0.04402 FastRCNN total loss: 0.11368 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.13986 RPN box loss: 0.01572 RPN score loss: 0.00267 RPN total loss: 0.01839 Total loss: 0.85946 timestamp: 1654977639.2609725 iteration: 81110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14589 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.20113 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15779 RPN box loss: 0.01628 RPN score loss: 0.00445 RPN total loss: 0.02073 Total loss: 0.96718 timestamp: 1654977642.4802535 iteration: 81115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11624 FastRCNN class loss: 0.07873 FastRCNN total loss: 0.19497 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12646 RPN box loss: 0.00606 RPN score loss: 0.00173 RPN total loss: 0.00779 Total loss: 0.91676 timestamp: 1654977645.6810112 iteration: 81120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.15779 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.09104 RPN box loss: 0.00827 RPN score loss: 0.00541 RPN total loss: 0.01367 Total loss: 0.85005 timestamp: 1654977648.9509861 iteration: 81125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0827 FastRCNN class loss: 0.04732 FastRCNN total loss: 0.13002 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1315 RPN box loss: 0.01344 RPN score loss: 0.00675 RPN total loss: 0.02019 Total loss: 0.86925 timestamp: 1654977652.2324035 iteration: 81130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0991 FastRCNN class loss: 0.02685 FastRCNN total loss: 0.12595 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.07934 RPN box loss: 0.00552 RPN score loss: 0.00501 RPN total loss: 0.01053 Total loss: 0.80335 timestamp: 1654977655.4242249 iteration: 81135 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05143 FastRCNN class loss: 0.04349 FastRCNN total loss: 0.09492 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1135 RPN box loss: 0.0214 RPN score loss: 0.00173 RPN total loss: 0.02313 Total loss: 0.81908 timestamp: 1654977658.6239414 iteration: 81140 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07605 FastRCNN class loss: 0.04123 FastRCNN total loss: 0.11728 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.09805 RPN box loss: 0.0086 RPN score loss: 0.00181 RPN total loss: 0.01041 Total loss: 0.81328 timestamp: 1654977661.7993078 iteration: 81145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12626 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.1879 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.09795 RPN box loss: 0.00569 RPN score loss: 0.00419 RPN total loss: 0.00988 Total loss: 0.88326 timestamp: 1654977664.9574165 iteration: 81150 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11623 FastRCNN class loss: 0.11 FastRCNN total loss: 0.22624 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15526 RPN box loss: 0.0182 RPN score loss: 0.00264 RPN total loss: 0.02085 Total loss: 0.98988 timestamp: 1654977668.1804805 iteration: 81155 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09399 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.15947 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.1279 RPN box loss: 0.00669 RPN score loss: 0.00492 RPN total loss: 0.01161 Total loss: 0.88651 timestamp: 1654977671.3858771 iteration: 81160 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.04628 FastRCNN total loss: 0.13396 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.10211 RPN box loss: 0.01013 RPN score loss: 0.00138 RPN total loss: 0.01151 Total loss: 0.83511 timestamp: 1654977674.6296945 iteration: 81165 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07356 FastRCNN class loss: 0.05666 FastRCNN total loss: 0.13023 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.12942 RPN box loss: 0.00601 RPN score loss: 0.00317 RPN total loss: 0.00918 Total loss: 0.85637 timestamp: 1654977677.8793483 iteration: 81170 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08203 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.137 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.11616 RPN box loss: 0.01369 RPN score loss: 0.00244 RPN total loss: 0.01613 Total loss: 0.85682 timestamp: 1654977681.11007 iteration: 81175 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14023 FastRCNN class loss: 0.05551 FastRCNN total loss: 0.19574 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.13671 RPN box loss: 0.01336 RPN score loss: 0.0023 RPN total loss: 0.01566 Total loss: 0.93564 timestamp: 1654977684.3480434 iteration: 81180 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12198 FastRCNN class loss: 0.09951 FastRCNN total loss: 0.22148 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.13822 RPN box loss: 0.02223 RPN score loss: 0.00473 RPN total loss: 0.02696 Total loss: 0.9742 timestamp: 1654977687.5532475 iteration: 81185 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07676 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.15561 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 4.0000e-05 Mask loss: 0.15602 RPN box loss: 0.00917 RPN score loss: 0.00154 RPN total loss: 0.01071 Total loss: 0.90988 timestamp: 1654977690.746079 iteration: 81190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1063 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.17572 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09815 RPN box loss: 0.01355 RPN score loss: 0.00303 RPN total loss: 0.01658 Total loss: 0.87798 timestamp: 1654977693.984356 iteration: 81195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07829 FastRCNN class loss: 0.05047 FastRCNN total loss: 0.12876 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11175 RPN box loss: 0.01067 RPN score loss: 0.00447 RPN total loss: 0.01514 Total loss: 0.84318 timestamp: 1654977697.1751354 iteration: 81200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06669 FastRCNN class loss: 0.05757 FastRCNN total loss: 0.12426 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.10408 RPN box loss: 0.00649 RPN score loss: 0.00144 RPN total loss: 0.00793 Total loss: 0.82381 timestamp: 1654977700.4375584 iteration: 81205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.15411 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.16141 RPN box loss: 0.03771 RPN score loss: 0.0098 RPN total loss: 0.04751 Total loss: 0.95057 timestamp: 1654977703.6976202 iteration: 81210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05705 FastRCNN class loss: 0.02997 FastRCNN total loss: 0.08702 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.08888 RPN box loss: 0.01225 RPN score loss: 0.00191 RPN total loss: 0.01416 Total loss: 0.77759 timestamp: 1654977706.8666933 iteration: 81215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06302 FastRCNN class loss: 0.04979 FastRCNN total loss: 0.11281 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.12464 RPN box loss: 0.00509 RPN score loss: 0.00387 RPN total loss: 0.00896 Total loss: 0.83395 timestamp: 1654977710.0989513 iteration: 81220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10413 FastRCNN class loss: 0.06655 FastRCNN total loss: 0.17068 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.15321 RPN box loss: 0.02151 RPN score loss: 0.00495 RPN total loss: 0.02646 Total loss: 0.93788 timestamp: 1654977713.318597 iteration: 81225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0683 FastRCNN class loss: 0.055 FastRCNN total loss: 0.1233 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11043 RPN box loss: 0.00509 RPN score loss: 0.00075 RPN total loss: 0.00584 Total loss: 0.8271 timestamp: 1654977716.520061 iteration: 81230 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09128 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.15556 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.13004 RPN box loss: 0.01416 RPN score loss: 0.00209 RPN total loss: 0.01626 Total loss: 0.88938 timestamp: 1654977719.8047633 iteration: 81235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10302 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.17935 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.1591 RPN box loss: 0.01156 RPN score loss: 0.00823 RPN total loss: 0.01978 Total loss: 0.94576 timestamp: 1654977722.989018 iteration: 81240 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10453 FastRCNN class loss: 0.09185 FastRCNN total loss: 0.19638 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.20796 RPN box loss: 0.01269 RPN score loss: 0.0028 RPN total loss: 0.01549 Total loss: 1.00736 timestamp: 1654977726.194565 iteration: 81245 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09239 FastRCNN class loss: 0.06443 FastRCNN total loss: 0.15682 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11734 RPN box loss: 0.00945 RPN score loss: 0.00325 RPN total loss: 0.0127 Total loss: 0.87439 timestamp: 1654977729.3226943 iteration: 81250 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05089 FastRCNN class loss: 0.04301 FastRCNN total loss: 0.0939 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09779 RPN box loss: 0.00802 RPN score loss: 0.00116 RPN total loss: 0.00918 Total loss: 0.78841 timestamp: 1654977732.5738518 iteration: 81255 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07785 FastRCNN class loss: 0.05799 FastRCNN total loss: 0.13584 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11308 RPN box loss: 0.01768 RPN score loss: 0.01059 RPN total loss: 0.02827 Total loss: 0.86473 timestamp: 1654977735.8331275 iteration: 81260 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11146 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.19031 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.14065 RPN box loss: 0.00495 RPN score loss: 0.00305 RPN total loss: 0.008 Total loss: 0.92649 timestamp: 1654977739.098212 iteration: 81265 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10939 FastRCNN class loss: 0.08549 FastRCNN total loss: 0.19488 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.13169 RPN box loss: 0.01615 RPN score loss: 0.00306 RPN total loss: 0.01921 Total loss: 0.93331 timestamp: 1654977742.3427062 iteration: 81270 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0667 FastRCNN class loss: 0.04189 FastRCNN total loss: 0.1086 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.08402 RPN box loss: 0.00413 RPN score loss: 0.00121 RPN total loss: 0.00533 Total loss: 0.78549 timestamp: 1654977745.5683706 iteration: 81275 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08025 FastRCNN class loss: 0.07486 FastRCNN total loss: 0.15512 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09232 RPN box loss: 0.00626 RPN score loss: 0.00248 RPN total loss: 0.00874 Total loss: 0.84371 timestamp: 1654977748.7772515 iteration: 81280 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11401 FastRCNN class loss: 0.06191 FastRCNN total loss: 0.17592 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.16618 RPN box loss: 0.01524 RPN score loss: 0.00115 RPN total loss: 0.01639 Total loss: 0.94602 timestamp: 1654977751.9604628 iteration: 81285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07395 FastRCNN class loss: 0.05417 FastRCNN total loss: 0.12813 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.14487 RPN box loss: 0.00668 RPN score loss: 0.00288 RPN total loss: 0.00957 Total loss: 0.8701 timestamp: 1654977755.2128108 iteration: 81290 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07167 FastRCNN class loss: 0.04997 FastRCNN total loss: 0.12165 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.12984 RPN box loss: 0.00537 RPN score loss: 0.00183 RPN total loss: 0.0072 Total loss: 0.84622 timestamp: 1654977758.4188442 iteration: 81295 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10157 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.18405 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.10282 RPN box loss: 0.00806 RPN score loss: 0.00674 RPN total loss: 0.0148 Total loss: 0.88919 timestamp: 1654977761.6106136 iteration: 81300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14204 FastRCNN class loss: 0.08766 FastRCNN total loss: 0.2297 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09979 RPN box loss: 0.00821 RPN score loss: 0.00266 RPN total loss: 0.01087 Total loss: 0.92789 timestamp: 1654977764.7927969 iteration: 81305 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07274 FastRCNN class loss: 0.04165 FastRCNN total loss: 0.11439 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09816 RPN box loss: 0.00647 RPN score loss: 0.00126 RPN total loss: 0.00774 Total loss: 0.80782 timestamp: 1654977767.9463134 iteration: 81310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08131 FastRCNN class loss: 0.05561 FastRCNN total loss: 0.13692 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11755 RPN box loss: 0.00774 RPN score loss: 0.00685 RPN total loss: 0.01459 Total loss: 0.8566 timestamp: 1654977771.1433094 iteration: 81315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13654 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.22129 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.14865 RPN box loss: 0.02892 RPN score loss: 0.01598 RPN total loss: 0.0449 Total loss: 1.00237 timestamp: 1654977774.2900739 iteration: 81320 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04574 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.10171 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09281 RPN box loss: 0.01169 RPN score loss: 0.00752 RPN total loss: 0.01921 Total loss: 0.80125 timestamp: 1654977777.6002097 iteration: 81325 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09346 FastRCNN class loss: 0.11406 FastRCNN total loss: 0.20752 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.18249 RPN box loss: 0.0223 RPN score loss: 0.00933 RPN total loss: 0.03164 Total loss: 1.00918 timestamp: 1654977780.7745452 iteration: 81330 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10915 FastRCNN class loss: 0.12553 FastRCNN total loss: 0.23468 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.15798 RPN box loss: 0.00786 RPN score loss: 0.0017 RPN total loss: 0.00956 Total loss: 0.98974 timestamp: 1654977784.0439737 iteration: 81335 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05925 FastRCNN class loss: 0.04428 FastRCNN total loss: 0.10353 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09822 RPN box loss: 0.00937 RPN score loss: 0.00263 RPN total loss: 0.012 Total loss: 0.80127 timestamp: 1654977787.245702 iteration: 81340 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0538 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.12294 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09991 RPN box loss: 0.00964 RPN score loss: 0.00438 RPN total loss: 0.01403 Total loss: 0.82441 timestamp: 1654977790.3490465 iteration: 81345 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13664 FastRCNN class loss: 0.09503 FastRCNN total loss: 0.23167 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.17785 RPN box loss: 0.00851 RPN score loss: 0.00583 RPN total loss: 0.01434 Total loss: 1.01139 timestamp: 1654977793.5513864 iteration: 81350 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07181 FastRCNN class loss: 0.04814 FastRCNN total loss: 0.11995 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.0924 RPN box loss: 0.00827 RPN score loss: 0.00176 RPN total loss: 0.01003 Total loss: 0.80991 timestamp: 1654977796.722889 iteration: 81355 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.106 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.16124 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.10592 RPN box loss: 0.00569 RPN score loss: 0.00151 RPN total loss: 0.0072 Total loss: 0.86189 timestamp: 1654977799.9781954 iteration: 81360 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0801 FastRCNN class loss: 0.06882 FastRCNN total loss: 0.14891 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09939 RPN box loss: 0.00723 RPN score loss: 0.00163 RPN total loss: 0.00886 Total loss: 0.84469 timestamp: 1654977803.1896327 iteration: 81365 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06159 FastRCNN class loss: 0.02534 FastRCNN total loss: 0.08693 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.0875 RPN box loss: 0.0125 RPN score loss: 0.00457 RPN total loss: 0.01707 Total loss: 0.77902 timestamp: 1654977806.3848488 iteration: 81370 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08047 FastRCNN class loss: 0.06426 FastRCNN total loss: 0.14473 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.1284 RPN box loss: 0.00878 RPN score loss: 0.00653 RPN total loss: 0.01532 Total loss: 0.87598 timestamp: 1654977809.5266955 iteration: 81375 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.07845 FastRCNN total loss: 0.16341 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.12817 RPN box loss: 0.00592 RPN score loss: 0.00484 RPN total loss: 0.01077 Total loss: 0.88988 timestamp: 1654977812.7548728 iteration: 81380 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09605 FastRCNN class loss: 0.06303 FastRCNN total loss: 0.15908 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11027 RPN box loss: 0.01183 RPN score loss: 0.01321 RPN total loss: 0.02504 Total loss: 0.88192 timestamp: 1654977815.9736345 iteration: 81385 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09831 FastRCNN class loss: 0.04791 FastRCNN total loss: 0.14622 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.0896 RPN box loss: 0.00584 RPN score loss: 0.00221 RPN total loss: 0.00805 Total loss: 0.8314 timestamp: 1654977819.2495818 iteration: 81390 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06544 FastRCNN class loss: 0.04047 FastRCNN total loss: 0.10591 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.09998 RPN box loss: 0.00472 RPN score loss: 0.00522 RPN total loss: 0.00994 Total loss: 0.80337 timestamp: 1654977822.447821 iteration: 81395 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0782 FastRCNN class loss: 0.06777 FastRCNN total loss: 0.14597 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.12565 RPN box loss: 0.00501 RPN score loss: 0.00139 RPN total loss: 0.0064 Total loss: 0.86554 timestamp: 1654977825.657398 iteration: 81400 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08639 FastRCNN class loss: 0.04446 FastRCNN total loss: 0.13085 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11658 RPN box loss: 0.01824 RPN score loss: 0.00646 RPN total loss: 0.0247 Total loss: 0.85965 timestamp: 1654977828.8000307 iteration: 81405 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09325 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.16605 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.15843 RPN box loss: 0.03195 RPN score loss: 0.00821 RPN total loss: 0.04015 Total loss: 0.95216 timestamp: 1654977832.0271666 iteration: 81410 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08919 FastRCNN class loss: 0.07158 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.10406 RPN box loss: 0.00786 RPN score loss: 0.00502 RPN total loss: 0.01288 Total loss: 0.86524 timestamp: 1654977835.2066445 iteration: 81415 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13609 FastRCNN class loss: 0.11579 FastRCNN total loss: 0.25189 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.1371 RPN box loss: 0.01607 RPN score loss: 0.00677 RPN total loss: 0.02284 Total loss: 0.99936 timestamp: 1654977838.4536262 iteration: 81420 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05435 FastRCNN class loss: 0.04687 FastRCNN total loss: 0.10122 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.0912 RPN box loss: 0.0131 RPN score loss: 0.00082 RPN total loss: 0.01393 Total loss: 0.79388 timestamp: 1654977841.6100404 iteration: 81425 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06854 FastRCNN class loss: 0.07879 FastRCNN total loss: 0.14732 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.13731 RPN box loss: 0.02721 RPN score loss: 0.01443 RPN total loss: 0.04164 Total loss: 0.9138 timestamp: 1654977844.8111048 iteration: 81430 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08929 FastRCNN class loss: 0.08805 FastRCNN total loss: 0.17734 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.15725 RPN box loss: 0.00751 RPN score loss: 0.00148 RPN total loss: 0.00899 Total loss: 0.93111 timestamp: 1654977848.0371356 iteration: 81435 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09926 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.17344 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.12636 RPN box loss: 0.01528 RPN score loss: 0.00378 RPN total loss: 0.01906 Total loss: 0.90639 timestamp: 1654977851.2723067 iteration: 81440 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06105 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.11109 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11541 RPN box loss: 0.00443 RPN score loss: 0.00178 RPN total loss: 0.0062 Total loss: 0.82023 timestamp: 1654977854.4177248 iteration: 81445 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07625 FastRCNN class loss: 0.06091 FastRCNN total loss: 0.13716 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.14285 RPN box loss: 0.00849 RPN score loss: 0.00256 RPN total loss: 0.01105 Total loss: 0.87858 timestamp: 1654977857.6669905 iteration: 81450 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05806 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.11497 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.15635 RPN box loss: 0.00898 RPN score loss: 0.00337 RPN total loss: 0.01235 Total loss: 0.87119 timestamp: 1654977860.879529 iteration: 81455 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11379 FastRCNN class loss: 0.08564 FastRCNN total loss: 0.19943 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.18306 RPN box loss: 0.00996 RPN score loss: 0.00518 RPN total loss: 0.01514 Total loss: 0.98516 timestamp: 1654977864.121084 iteration: 81460 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08784 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.15459 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.12538 RPN box loss: 0.00595 RPN score loss: 0.00344 RPN total loss: 0.00939 Total loss: 0.87689 timestamp: 1654977867.2956703 iteration: 81465 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07386 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.16966 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.14519 RPN box loss: 0.01131 RPN score loss: 0.00285 RPN total loss: 0.01416 Total loss: 0.91654 timestamp: 1654977870.6122441 iteration: 81470 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09058 FastRCNN class loss: 0.11269 FastRCNN total loss: 0.20327 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.19546 RPN box loss: 0.0153 RPN score loss: 0.00662 RPN total loss: 0.02192 Total loss: 1.00817 timestamp: 1654977873.803947 iteration: 81475 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13051 FastRCNN class loss: 0.0636 FastRCNN total loss: 0.19412 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.14324 RPN box loss: 0.00978 RPN score loss: 0.00294 RPN total loss: 0.01271 Total loss: 0.93759 timestamp: 1654977877.0102677 iteration: 81480 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0944 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.1559 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.10083 RPN box loss: 0.00994 RPN score loss: 0.00403 RPN total loss: 0.01397 Total loss: 0.85823 timestamp: 1654977880.2022934 iteration: 81485 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10443 FastRCNN class loss: 0.09975 FastRCNN total loss: 0.20418 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.16312 RPN box loss: 0.023 RPN score loss: 0.00921 RPN total loss: 0.03221 Total loss: 0.98704 timestamp: 1654977883.2985692 iteration: 81490 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06366 FastRCNN class loss: 0.04654 FastRCNN total loss: 0.1102 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.08621 RPN box loss: 0.01549 RPN score loss: 0.003 RPN total loss: 0.01849 Total loss: 0.80242 timestamp: 1654977886.4705412 iteration: 81495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08829 FastRCNN class loss: 0.06617 FastRCNN total loss: 0.15447 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.11922 RPN box loss: 0.00619 RPN score loss: 0.00383 RPN total loss: 0.01002 Total loss: 0.87123 timestamp: 1654977889.690045 iteration: 81500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10251 FastRCNN class loss: 0.09576 FastRCNN total loss: 0.19827 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 4.0000e-05 Mask loss: 0.21222 RPN box loss: 0.02049 RPN score loss: 0.00982 RPN total loss: 0.03031 Total loss: 1.02833 timestamp: 1654977892.837392 iteration: 81505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04501 FastRCNN class loss: 0.03592 FastRCNN total loss: 0.08093 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.1096 RPN box loss: 0.01621 RPN score loss: 0.0008 RPN total loss: 0.01701 Total loss: 0.79508 timestamp: 1654977896.0965953 iteration: 81510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04509 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.09547 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.16643 RPN box loss: 0.01074 RPN score loss: 0.00678 RPN total loss: 0.01752 Total loss: 0.86694 timestamp: 1654977899.2942672 iteration: 81515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12105 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.19654 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09849 RPN box loss: 0.00513 RPN score loss: 0.00499 RPN total loss: 0.01012 Total loss: 0.89268 timestamp: 1654977902.603578 iteration: 81520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08359 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.14745 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.142 RPN box loss: 0.00718 RPN score loss: 0.00746 RPN total loss: 0.01464 Total loss: 0.89162 timestamp: 1654977905.7329395 iteration: 81525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05397 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.10371 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14836 RPN box loss: 0.00893 RPN score loss: 0.00285 RPN total loss: 0.01178 Total loss: 0.85137 timestamp: 1654977908.9140513 iteration: 81530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13099 FastRCNN class loss: 0.06783 FastRCNN total loss: 0.19883 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13414 RPN box loss: 0.00913 RPN score loss: 0.00464 RPN total loss: 0.01378 Total loss: 0.93427 timestamp: 1654977912.0990314 iteration: 81535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08276 FastRCNN class loss: 0.06141 FastRCNN total loss: 0.14417 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14357 RPN box loss: 0.01623 RPN score loss: 0.00446 RPN total loss: 0.0207 Total loss: 0.89596 timestamp: 1654977915.2272875 iteration: 81540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04964 FastRCNN class loss: 0.04441 FastRCNN total loss: 0.09405 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13019 RPN box loss: 0.00959 RPN score loss: 0.00123 RPN total loss: 0.01082 Total loss: 0.82259 timestamp: 1654977918.4426334 iteration: 81545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06421 FastRCNN class loss: 0.04951 FastRCNN total loss: 0.11372 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09973 RPN box loss: 0.01038 RPN score loss: 0.00097 RPN total loss: 0.01135 Total loss: 0.81233 timestamp: 1654977921.6605518 iteration: 81550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0556 FastRCNN class loss: 0.0295 FastRCNN total loss: 0.0851 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.0989 RPN box loss: 0.01067 RPN score loss: 0.00178 RPN total loss: 0.01245 Total loss: 0.78397 timestamp: 1654977924.8526452 iteration: 81555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10179 FastRCNN class loss: 0.05639 FastRCNN total loss: 0.15818 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09836 RPN box loss: 0.00705 RPN score loss: 0.00266 RPN total loss: 0.00972 Total loss: 0.85378 timestamp: 1654977928.0505016 iteration: 81560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06762 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.12608 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.12626 RPN box loss: 0.00385 RPN score loss: 0.00197 RPN total loss: 0.00583 Total loss: 0.84569 timestamp: 1654977931.2835732 iteration: 81565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08289 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.15782 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.12383 RPN box loss: 0.01094 RPN score loss: 0.00894 RPN total loss: 0.01988 Total loss: 0.88904 timestamp: 1654977934.400604 iteration: 81570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09701 FastRCNN class loss: 0.10157 FastRCNN total loss: 0.19858 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.16478 RPN box loss: 0.01551 RPN score loss: 0.00451 RPN total loss: 0.02003 Total loss: 0.97091 timestamp: 1654977937.626332 iteration: 81575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08694 FastRCNN class loss: 0.10826 FastRCNN total loss: 0.1952 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15477 RPN box loss: 0.02267 RPN score loss: 0.00406 RPN total loss: 0.02673 Total loss: 0.96422 timestamp: 1654977940.8926105 iteration: 81580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04515 FastRCNN class loss: 0.05466 FastRCNN total loss: 0.09981 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09985 RPN box loss: 0.00801 RPN score loss: 0.00307 RPN total loss: 0.01108 Total loss: 0.79826 timestamp: 1654977944.0707746 iteration: 81585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.05764 FastRCNN total loss: 0.13947 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11958 RPN box loss: 0.00522 RPN score loss: 0.00799 RPN total loss: 0.01322 Total loss: 0.85979 timestamp: 1654977947.249623 iteration: 81590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.05031 FastRCNN total loss: 0.14041 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14366 RPN box loss: 0.02677 RPN score loss: 0.01199 RPN total loss: 0.03876 Total loss: 0.91035 timestamp: 1654977950.4287145 iteration: 81595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06455 FastRCNN class loss: 0.05237 FastRCNN total loss: 0.11692 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14494 RPN box loss: 0.01843 RPN score loss: 0.00172 RPN total loss: 0.02015 Total loss: 0.86954 timestamp: 1654977953.6550746 iteration: 81600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09253 FastRCNN class loss: 0.10106 FastRCNN total loss: 0.1936 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15787 RPN box loss: 0.00998 RPN score loss: 0.00098 RPN total loss: 0.01096 Total loss: 0.94995 timestamp: 1654977956.9105644 iteration: 81605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17279 FastRCNN class loss: 0.13365 FastRCNN total loss: 0.30645 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15431 RPN box loss: 0.01897 RPN score loss: 0.00797 RPN total loss: 0.02694 Total loss: 1.07522 timestamp: 1654977960.0724134 iteration: 81610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11217 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.18915 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13082 RPN box loss: 0.01651 RPN score loss: 0.00262 RPN total loss: 0.01913 Total loss: 0.92663 timestamp: 1654977963.2818356 iteration: 81615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07628 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.14342 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.12519 RPN box loss: 0.01787 RPN score loss: 0.00107 RPN total loss: 0.01894 Total loss: 0.87507 timestamp: 1654977966.4816506 iteration: 81620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0945 FastRCNN class loss: 0.06605 FastRCNN total loss: 0.16055 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11048 RPN box loss: 0.00992 RPN score loss: 0.00268 RPN total loss: 0.0126 Total loss: 0.87116 timestamp: 1654977969.746205 iteration: 81625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12794 FastRCNN class loss: 0.09407 FastRCNN total loss: 0.22201 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13976 RPN box loss: 0.0791 RPN score loss: 0.00502 RPN total loss: 0.08412 Total loss: 1.03341 timestamp: 1654977972.8828933 iteration: 81630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05182 FastRCNN class loss: 0.05367 FastRCNN total loss: 0.1055 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11657 RPN box loss: 0.00907 RPN score loss: 0.0044 RPN total loss: 0.01347 Total loss: 0.82306 timestamp: 1654977976.0618365 iteration: 81635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10835 FastRCNN class loss: 0.10047 FastRCNN total loss: 0.20882 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.24947 RPN box loss: 0.03054 RPN score loss: 0.04793 RPN total loss: 0.07847 Total loss: 1.12428 timestamp: 1654977979.231265 iteration: 81640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08801 FastRCNN class loss: 0.09128 FastRCNN total loss: 0.17929 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15628 RPN box loss: 0.01554 RPN score loss: 0.00274 RPN total loss: 0.01828 Total loss: 0.94137 timestamp: 1654977982.4225605 iteration: 81645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11646 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.18038 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14729 RPN box loss: 0.0145 RPN score loss: 0.0059 RPN total loss: 0.02039 Total loss: 0.93559 timestamp: 1654977985.7171967 iteration: 81650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06888 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.11892 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13315 RPN box loss: 0.00553 RPN score loss: 0.00919 RPN total loss: 0.01471 Total loss: 0.8543 timestamp: 1654977988.9175196 iteration: 81655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11137 FastRCNN class loss: 0.04941 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10563 RPN box loss: 0.00913 RPN score loss: 0.00683 RPN total loss: 0.01596 Total loss: 0.86988 timestamp: 1654977992.1012878 iteration: 81660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10003 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13445 RPN box loss: 0.01351 RPN score loss: 0.00639 RPN total loss: 0.0199 Total loss: 0.92189 timestamp: 1654977995.2260685 iteration: 81665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06899 FastRCNN class loss: 0.04964 FastRCNN total loss: 0.11863 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10306 RPN box loss: 0.00406 RPN score loss: 0.00374 RPN total loss: 0.00781 Total loss: 0.81702 timestamp: 1654977998.3543084 iteration: 81670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06165 FastRCNN class loss: 0.05609 FastRCNN total loss: 0.11775 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09649 RPN box loss: 0.00899 RPN score loss: 0.00093 RPN total loss: 0.00991 Total loss: 0.81167 timestamp: 1654978001.545587 iteration: 81675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14762 FastRCNN class loss: 0.06443 FastRCNN total loss: 0.21205 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11002 RPN box loss: 0.01129 RPN score loss: 0.00724 RPN total loss: 0.01853 Total loss: 0.92812 timestamp: 1654978004.7496822 iteration: 81680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07898 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.13071 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09882 RPN box loss: 0.01974 RPN score loss: 0.0013 RPN total loss: 0.02104 Total loss: 0.83809 timestamp: 1654978007.9319088 iteration: 81685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09929 FastRCNN class loss: 0.08215 FastRCNN total loss: 0.18144 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15925 RPN box loss: 0.00613 RPN score loss: 0.00129 RPN total loss: 0.00742 Total loss: 0.93563 timestamp: 1654978011.1146832 iteration: 81690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07646 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.14451 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13728 RPN box loss: 0.00854 RPN score loss: 0.00378 RPN total loss: 0.01232 Total loss: 0.88162 timestamp: 1654978014.2952294 iteration: 81695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07015 FastRCNN class loss: 0.08443 FastRCNN total loss: 0.15459 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11777 RPN box loss: 0.00673 RPN score loss: 0.0084 RPN total loss: 0.01513 Total loss: 0.87501 timestamp: 1654978017.5256884 iteration: 81700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08844 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.16056 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10883 RPN box loss: 0.01287 RPN score loss: 0.00229 RPN total loss: 0.01515 Total loss: 0.87206 timestamp: 1654978020.7208133 iteration: 81705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11832 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.21171 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15113 RPN box loss: 0.00946 RPN score loss: 0.01449 RPN total loss: 0.02394 Total loss: 0.9743 timestamp: 1654978023.968129 iteration: 81710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05346 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.13703 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10746 RPN box loss: 0.02691 RPN score loss: 0.01054 RPN total loss: 0.03745 Total loss: 0.86947 timestamp: 1654978027.1288188 iteration: 81715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07943 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.15144 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.13736 RPN box loss: 0.00584 RPN score loss: 0.00475 RPN total loss: 0.01059 Total loss: 0.88691 timestamp: 1654978030.3217175 iteration: 81720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.06067 FastRCNN total loss: 0.17384 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10933 RPN box loss: 0.00845 RPN score loss: 0.00378 RPN total loss: 0.01222 Total loss: 0.88291 timestamp: 1654978033.4879189 iteration: 81725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11091 FastRCNN class loss: 0.07308 FastRCNN total loss: 0.18399 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.18843 RPN box loss: 0.01441 RPN score loss: 0.01369 RPN total loss: 0.0281 Total loss: 0.98804 timestamp: 1654978036.611432 iteration: 81730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04262 FastRCNN class loss: 0.03817 FastRCNN total loss: 0.08079 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14612 RPN box loss: 0.0115 RPN score loss: 0.00169 RPN total loss: 0.01319 Total loss: 0.82762 timestamp: 1654978039.831843 iteration: 81735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10142 FastRCNN class loss: 0.08427 FastRCNN total loss: 0.18569 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.12098 RPN box loss: 0.01823 RPN score loss: 0.00803 RPN total loss: 0.02626 Total loss: 0.92045 timestamp: 1654978043.035727 iteration: 81740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14034 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.20268 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14462 RPN box loss: 0.01064 RPN score loss: 0.00336 RPN total loss: 0.014 Total loss: 0.94882 timestamp: 1654978046.1987374 iteration: 81745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06498 FastRCNN class loss: 0.05419 FastRCNN total loss: 0.11918 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.1042 RPN box loss: 0.00714 RPN score loss: 0.00159 RPN total loss: 0.00873 Total loss: 0.81962 timestamp: 1654978049.3750467 iteration: 81750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08337 FastRCNN class loss: 0.04661 FastRCNN total loss: 0.12997 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10772 RPN box loss: 0.00955 RPN score loss: 0.0019 RPN total loss: 0.01145 Total loss: 0.83666 timestamp: 1654978052.606804 iteration: 81755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03484 FastRCNN class loss: 0.03316 FastRCNN total loss: 0.068 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.09287 RPN box loss: 0.00876 RPN score loss: 0.00231 RPN total loss: 0.01106 Total loss: 0.75945 timestamp: 1654978055.8184116 iteration: 81760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08202 FastRCNN class loss: 0.09156 FastRCNN total loss: 0.17357 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.1022 RPN box loss: 0.0145 RPN score loss: 0.00516 RPN total loss: 0.01966 Total loss: 0.88296 timestamp: 1654978059.0313294 iteration: 81765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11319 FastRCNN class loss: 0.06842 FastRCNN total loss: 0.18161 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.17365 RPN box loss: 0.02827 RPN score loss: 0.01067 RPN total loss: 0.03894 Total loss: 0.98173 timestamp: 1654978062.2050343 iteration: 81770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09302 FastRCNN class loss: 0.04841 FastRCNN total loss: 0.14143 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10855 RPN box loss: 0.01503 RPN score loss: 0.00888 RPN total loss: 0.0239 Total loss: 0.8614 timestamp: 1654978065.4054132 iteration: 81775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10238 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.15115 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.1585 RPN box loss: 0.01639 RPN score loss: 0.00395 RPN total loss: 0.02034 Total loss: 0.91751 timestamp: 1654978068.5962 iteration: 81780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10805 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.16639 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.12422 RPN box loss: 0.01432 RPN score loss: 0.005 RPN total loss: 0.01932 Total loss: 0.89745 timestamp: 1654978071.8129473 iteration: 81785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06078 FastRCNN class loss: 0.03844 FastRCNN total loss: 0.09922 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11839 RPN box loss: 0.005 RPN score loss: 0.00077 RPN total loss: 0.00577 Total loss: 0.81091 timestamp: 1654978074.9973054 iteration: 81790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12253 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.20078 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.1454 RPN box loss: 0.01339 RPN score loss: 0.00405 RPN total loss: 0.01743 Total loss: 0.95113 timestamp: 1654978078.193291 iteration: 81795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04208 FastRCNN class loss: 0.03659 FastRCNN total loss: 0.07867 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.11641 RPN box loss: 0.01749 RPN score loss: 0.00188 RPN total loss: 0.01937 Total loss: 0.80197 timestamp: 1654978081.530902 iteration: 81800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.098 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.16756 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.15487 RPN box loss: 0.03247 RPN score loss: 0.00351 RPN total loss: 0.03598 Total loss: 0.94592 timestamp: 1654978084.6413636 iteration: 81805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05722 FastRCNN class loss: 0.05095 FastRCNN total loss: 0.10817 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.10674 RPN box loss: 0.01116 RPN score loss: 0.00251 RPN total loss: 0.01368 Total loss: 0.8161 timestamp: 1654978087.8174899 iteration: 81810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08192 FastRCNN class loss: 0.05563 FastRCNN total loss: 0.13756 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.0845 RPN box loss: 0.00671 RPN score loss: 0.00145 RPN total loss: 0.00817 Total loss: 0.81774 timestamp: 1654978091.0427742 iteration: 81815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14088 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.2 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 4.0000e-05 Mask loss: 0.14427 RPN box loss: 0.02128 RPN score loss: 0.00322 RPN total loss: 0.0245 Total loss: 0.95628 timestamp: 1654978094.251106 iteration: 81820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11938 FastRCNN class loss: 0.09152 FastRCNN total loss: 0.2109 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12191 RPN box loss: 0.00699 RPN score loss: 0.00364 RPN total loss: 0.01063 Total loss: 0.93096 timestamp: 1654978097.4260137 iteration: 81825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1177 FastRCNN class loss: 0.08033 FastRCNN total loss: 0.19803 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.18078 RPN box loss: 0.01473 RPN score loss: 0.01202 RPN total loss: 0.02675 Total loss: 0.99307 timestamp: 1654978100.6015813 iteration: 81830 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08327 FastRCNN class loss: 0.03741 FastRCNN total loss: 0.12068 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11232 RPN box loss: 0.0269 RPN score loss: 0.00256 RPN total loss: 0.02945 Total loss: 0.84997 timestamp: 1654978103.7589564 iteration: 81835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15478 FastRCNN class loss: 0.06718 FastRCNN total loss: 0.22197 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10186 RPN box loss: 0.0069 RPN score loss: 0.00341 RPN total loss: 0.01031 Total loss: 0.92165 timestamp: 1654978107.0194242 iteration: 81840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05954 FastRCNN class loss: 0.05513 FastRCNN total loss: 0.11467 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.08064 RPN box loss: 0.01089 RPN score loss: 0.0022 RPN total loss: 0.01309 Total loss: 0.79591 timestamp: 1654978110.1792269 iteration: 81845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04741 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.10926 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.08136 RPN box loss: 0.00616 RPN score loss: 0.00331 RPN total loss: 0.00946 Total loss: 0.7876 timestamp: 1654978113.4371185 iteration: 81850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07374 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.14335 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14568 RPN box loss: 0.04266 RPN score loss: 0.00678 RPN total loss: 0.04945 Total loss: 0.926 timestamp: 1654978116.6396794 iteration: 81855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06306 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.1225 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10892 RPN box loss: 0.00555 RPN score loss: 0.00294 RPN total loss: 0.00849 Total loss: 0.82742 timestamp: 1654978119.7781212 iteration: 81860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08615 FastRCNN class loss: 0.05892 FastRCNN total loss: 0.14507 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12708 RPN box loss: 0.01941 RPN score loss: 0.00409 RPN total loss: 0.0235 Total loss: 0.88317 timestamp: 1654978122.9927702 iteration: 81865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07298 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.15375 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13821 RPN box loss: 0.00964 RPN score loss: 0.00339 RPN total loss: 0.01303 Total loss: 0.89251 timestamp: 1654978126.0749598 iteration: 81870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10052 FastRCNN class loss: 0.06868 FastRCNN total loss: 0.1692 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.15049 RPN box loss: 0.00385 RPN score loss: 0.00799 RPN total loss: 0.01184 Total loss: 0.91905 timestamp: 1654978129.2204328 iteration: 81875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0552 FastRCNN class loss: 0.04564 FastRCNN total loss: 0.10083 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11866 RPN box loss: 0.00592 RPN score loss: 0.00274 RPN total loss: 0.00865 Total loss: 0.81566 timestamp: 1654978132.411613 iteration: 81880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04714 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.09647 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14911 RPN box loss: 0.00986 RPN score loss: 0.00135 RPN total loss: 0.01121 Total loss: 0.84431 timestamp: 1654978135.6634705 iteration: 81885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07761 FastRCNN class loss: 0.04679 FastRCNN total loss: 0.12441 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.19109 RPN box loss: 0.00891 RPN score loss: 0.00558 RPN total loss: 0.01449 Total loss: 0.9175 timestamp: 1654978138.8236637 iteration: 81890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03676 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.08902 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12051 RPN box loss: 0.0059 RPN score loss: 0.00288 RPN total loss: 0.00878 Total loss: 0.80582 timestamp: 1654978142.06795 iteration: 81895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.16625 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.15136 RPN box loss: 0.03993 RPN score loss: 0.00472 RPN total loss: 0.04465 Total loss: 0.94977 timestamp: 1654978145.2382848 iteration: 81900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07088 FastRCNN class loss: 0.05401 FastRCNN total loss: 0.12489 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12305 RPN box loss: 0.01366 RPN score loss: 0.01182 RPN total loss: 0.02548 Total loss: 0.86093 timestamp: 1654978148.446084 iteration: 81905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07473 FastRCNN class loss: 0.05133 FastRCNN total loss: 0.12606 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11784 RPN box loss: 0.0151 RPN score loss: 0.0051 RPN total loss: 0.0202 Total loss: 0.85161 timestamp: 1654978151.642945 iteration: 81910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09025 FastRCNN class loss: 0.11912 FastRCNN total loss: 0.20937 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.20946 RPN box loss: 0.01686 RPN score loss: 0.00478 RPN total loss: 0.02164 Total loss: 1.02798 timestamp: 1654978154.832653 iteration: 81915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07826 FastRCNN class loss: 0.03684 FastRCNN total loss: 0.11509 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10188 RPN box loss: 0.00421 RPN score loss: 0.00168 RPN total loss: 0.00589 Total loss: 0.81037 timestamp: 1654978158.0937567 iteration: 81920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09149 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.14654 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.1041 RPN box loss: 0.00387 RPN score loss: 0.00472 RPN total loss: 0.00859 Total loss: 0.84673 timestamp: 1654978161.2979696 iteration: 81925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.04444 FastRCNN total loss: 0.13579 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.15286 RPN box loss: 0.00999 RPN score loss: 0.00297 RPN total loss: 0.01297 Total loss: 0.88913 timestamp: 1654978164.476209 iteration: 81930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09864 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.17759 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12162 RPN box loss: 0.00871 RPN score loss: 0.00163 RPN total loss: 0.01034 Total loss: 0.89707 timestamp: 1654978167.6132967 iteration: 81935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11858 FastRCNN class loss: 0.0781 FastRCNN total loss: 0.19667 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.16205 RPN box loss: 0.02077 RPN score loss: 0.01328 RPN total loss: 0.03405 Total loss: 0.98028 timestamp: 1654978170.816478 iteration: 81940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08634 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.1639 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.1336 RPN box loss: 0.01 RPN score loss: 0.00501 RPN total loss: 0.01501 Total loss: 0.90002 timestamp: 1654978174.0435617 iteration: 81945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06688 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.11983 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.09442 RPN box loss: 0.01087 RPN score loss: 0.00197 RPN total loss: 0.01285 Total loss: 0.81461 timestamp: 1654978177.20525 iteration: 81950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0895 FastRCNN class loss: 0.04186 FastRCNN total loss: 0.13136 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13367 RPN box loss: 0.02935 RPN score loss: 0.0017 RPN total loss: 0.03106 Total loss: 0.8836 timestamp: 1654978180.4795942 iteration: 81955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09759 FastRCNN class loss: 0.08176 FastRCNN total loss: 0.17935 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10962 RPN box loss: 0.00975 RPN score loss: 0.00348 RPN total loss: 0.01323 Total loss: 0.88971 timestamp: 1654978183.6533065 iteration: 81960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04813 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.10116 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11843 RPN box loss: 0.02723 RPN score loss: 0.00219 RPN total loss: 0.02943 Total loss: 0.83652 timestamp: 1654978186.833983 iteration: 81965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08453 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.16788 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13796 RPN box loss: 0.02276 RPN score loss: 0.0028 RPN total loss: 0.02556 Total loss: 0.91891 timestamp: 1654978190.054839 iteration: 81970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07324 FastRCNN class loss: 0.04753 FastRCNN total loss: 0.12077 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12294 RPN box loss: 0.00972 RPN score loss: 0.00127 RPN total loss: 0.01098 Total loss: 0.8422 timestamp: 1654978193.3042014 iteration: 81975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08251 FastRCNN class loss: 0.10382 FastRCNN total loss: 0.18633 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.17523 RPN box loss: 0.01307 RPN score loss: 0.00892 RPN total loss: 0.022 Total loss: 0.97106 timestamp: 1654978196.5063887 iteration: 81980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05747 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.12931 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12698 RPN box loss: 0.00335 RPN score loss: 0.00585 RPN total loss: 0.00921 Total loss: 0.853 timestamp: 1654978199.7665393 iteration: 81985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0802 FastRCNN class loss: 0.06608 FastRCNN total loss: 0.14628 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14516 RPN box loss: 0.01513 RPN score loss: 0.00811 RPN total loss: 0.02324 Total loss: 0.90218 timestamp: 1654978202.9538667 iteration: 81990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08577 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.15743 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.16941 RPN box loss: 0.03058 RPN score loss: 0.00381 RPN total loss: 0.03439 Total loss: 0.94875 timestamp: 1654978206.1501317 iteration: 81995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06511 FastRCNN class loss: 0.04216 FastRCNN total loss: 0.10726 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12072 RPN box loss: 0.0382 RPN score loss: 0.00256 RPN total loss: 0.04076 Total loss: 0.85625 timestamp: 1654978209.3754873 iteration: 82000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09284 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.15788 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13429 RPN box loss: 0.0038 RPN score loss: 0.0024 RPN total loss: 0.00621 Total loss: 0.88589 timestamp: 1654978212.5824392 iteration: 82005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07448 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.12452 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13287 RPN box loss: 0.0032 RPN score loss: 0.00254 RPN total loss: 0.00574 Total loss: 0.85063 timestamp: 1654978215.7700365 iteration: 82010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09837 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.16038 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.21261 RPN box loss: 0.00915 RPN score loss: 0.00245 RPN total loss: 0.01159 Total loss: 0.97209 timestamp: 1654978219.0695782 iteration: 82015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09161 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.15641 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14325 RPN box loss: 0.01485 RPN score loss: 0.00865 RPN total loss: 0.0235 Total loss: 0.91066 timestamp: 1654978222.2534962 iteration: 82020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08639 FastRCNN class loss: 0.0932 FastRCNN total loss: 0.17959 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14317 RPN box loss: 0.01533 RPN score loss: 0.00868 RPN total loss: 0.02402 Total loss: 0.93428 timestamp: 1654978225.4846857 iteration: 82025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11315 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.20032 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12866 RPN box loss: 0.02161 RPN score loss: 0.00575 RPN total loss: 0.02736 Total loss: 0.94385 timestamp: 1654978228.652122 iteration: 82030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11305 FastRCNN class loss: 0.072 FastRCNN total loss: 0.18505 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14179 RPN box loss: 0.01095 RPN score loss: 0.00337 RPN total loss: 0.01432 Total loss: 0.92866 timestamp: 1654978231.8457918 iteration: 82035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05751 FastRCNN class loss: 0.03983 FastRCNN total loss: 0.09734 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.07991 RPN box loss: 0.0102 RPN score loss: 0.00336 RPN total loss: 0.01356 Total loss: 0.77832 timestamp: 1654978235.0996897 iteration: 82040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10272 FastRCNN class loss: 0.06113 FastRCNN total loss: 0.16385 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.09008 RPN box loss: 0.00995 RPN score loss: 0.00489 RPN total loss: 0.01484 Total loss: 0.85628 timestamp: 1654978238.3891897 iteration: 82045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09891 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.17005 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13907 RPN box loss: 0.01985 RPN score loss: 0.00888 RPN total loss: 0.02873 Total loss: 0.92535 timestamp: 1654978241.501381 iteration: 82050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07009 FastRCNN class loss: 0.03279 FastRCNN total loss: 0.10288 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12973 RPN box loss: 0.00682 RPN score loss: 0.00416 RPN total loss: 0.01097 Total loss: 0.8311 timestamp: 1654978244.7173247 iteration: 82055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08297 FastRCNN class loss: 0.07733 FastRCNN total loss: 0.1603 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14738 RPN box loss: 0.01359 RPN score loss: 0.00583 RPN total loss: 0.01942 Total loss: 0.9146 timestamp: 1654978247.907275 iteration: 82060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12231 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.20448 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11996 RPN box loss: 0.00478 RPN score loss: 0.00649 RPN total loss: 0.01127 Total loss: 0.92322 timestamp: 1654978251.092721 iteration: 82065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08199 FastRCNN class loss: 0.0796 FastRCNN total loss: 0.16158 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11829 RPN box loss: 0.00584 RPN score loss: 0.00584 RPN total loss: 0.01169 Total loss: 0.87907 timestamp: 1654978254.3420873 iteration: 82070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11143 FastRCNN class loss: 0.04514 FastRCNN total loss: 0.15657 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10777 RPN box loss: 0.00304 RPN score loss: 0.00087 RPN total loss: 0.00391 Total loss: 0.85576 timestamp: 1654978257.5446827 iteration: 82075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07075 FastRCNN class loss: 0.04022 FastRCNN total loss: 0.11097 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13635 RPN box loss: 0.01089 RPN score loss: 0.00624 RPN total loss: 0.01713 Total loss: 0.85195 timestamp: 1654978260.7802534 iteration: 82080 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04443 FastRCNN class loss: 0.03541 FastRCNN total loss: 0.07984 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.0904 RPN box loss: 0.02467 RPN score loss: 0.00375 RPN total loss: 0.02842 Total loss: 0.78617 timestamp: 1654978263.9778972 iteration: 82085 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09614 FastRCNN class loss: 0.05797 FastRCNN total loss: 0.15412 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.14558 RPN box loss: 0.00474 RPN score loss: 0.0014 RPN total loss: 0.00614 Total loss: 0.89334 timestamp: 1654978267.1564493 iteration: 82090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08357 FastRCNN class loss: 0.07798 FastRCNN total loss: 0.16155 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.144 RPN box loss: 0.02641 RPN score loss: 0.01281 RPN total loss: 0.03921 Total loss: 0.93227 timestamp: 1654978270.373375 iteration: 82095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06637 FastRCNN class loss: 0.05772 FastRCNN total loss: 0.12409 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.17898 RPN box loss: 0.00662 RPN score loss: 0.00659 RPN total loss: 0.01321 Total loss: 0.90379 timestamp: 1654978273.500261 iteration: 82100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08579 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.15527 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.1215 RPN box loss: 0.01331 RPN score loss: 0.00397 RPN total loss: 0.01728 Total loss: 0.88155 timestamp: 1654978276.7159479 iteration: 82105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08982 FastRCNN class loss: 0.0543 FastRCNN total loss: 0.14412 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13998 RPN box loss: 0.01078 RPN score loss: 0.00253 RPN total loss: 0.01331 Total loss: 0.88491 timestamp: 1654978279.8735037 iteration: 82110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11611 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.18098 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10665 RPN box loss: 0.0287 RPN score loss: 0.00372 RPN total loss: 0.03242 Total loss: 0.90756 timestamp: 1654978283.125439 iteration: 82115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12762 FastRCNN class loss: 0.0777 FastRCNN total loss: 0.20532 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12456 RPN box loss: 0.01566 RPN score loss: 0.00214 RPN total loss: 0.0178 Total loss: 0.93518 timestamp: 1654978286.3312242 iteration: 82120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10212 FastRCNN class loss: 0.05342 FastRCNN total loss: 0.15554 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.13195 RPN box loss: 0.00668 RPN score loss: 0.00396 RPN total loss: 0.01063 Total loss: 0.88563 timestamp: 1654978289.505739 iteration: 82125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05473 FastRCNN class loss: 0.07855 FastRCNN total loss: 0.13328 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12659 RPN box loss: 0.00723 RPN score loss: 0.00284 RPN total loss: 0.01007 Total loss: 0.85744 timestamp: 1654978292.6734467 iteration: 82130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09076 FastRCNN class loss: 0.04422 FastRCNN total loss: 0.13498 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.08214 RPN box loss: 0.00613 RPN score loss: 0.00185 RPN total loss: 0.00798 Total loss: 0.81261 timestamp: 1654978295.822765 iteration: 82135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07849 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.1224 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.10653 RPN box loss: 0.00843 RPN score loss: 0.00112 RPN total loss: 0.00955 Total loss: 0.82599 timestamp: 1654978299.089425 iteration: 82140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09815 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.17285 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.12505 RPN box loss: 0.01272 RPN score loss: 0.00472 RPN total loss: 0.01744 Total loss: 0.90285 timestamp: 1654978302.2853076 iteration: 82145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15188 FastRCNN class loss: 0.10221 FastRCNN total loss: 0.25409 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.17335 RPN box loss: 0.0291 RPN score loss: 0.01132 RPN total loss: 0.04042 Total loss: 1.05536 timestamp: 1654978305.599058 iteration: 82150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10123 FastRCNN class loss: 0.11117 FastRCNN total loss: 0.2124 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 4.0000e-05 Mask loss: 0.11726 RPN box loss: 0.02164 RPN score loss: 0.00872 RPN total loss: 0.03036 Total loss: 0.94752 timestamp: 1654978308.7683506 iteration: 82155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09412 FastRCNN class loss: 0.06189 FastRCNN total loss: 0.156 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13918 RPN box loss: 0.02661 RPN score loss: 0.00323 RPN total loss: 0.02984 Total loss: 0.91252 timestamp: 1654978311.9320462 iteration: 82160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04667 FastRCNN class loss: 0.06543 FastRCNN total loss: 0.1121 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.08926 RPN box loss: 0.01371 RPN score loss: 0.00622 RPN total loss: 0.01993 Total loss: 0.8088 timestamp: 1654978315.0751011 iteration: 82165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10234 FastRCNN class loss: 0.0509 FastRCNN total loss: 0.15324 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.14298 RPN box loss: 0.00389 RPN score loss: 0.00139 RPN total loss: 0.00528 Total loss: 0.889 timestamp: 1654978318.3105474 iteration: 82170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.16865 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13991 RPN box loss: 0.02643 RPN score loss: 0.00437 RPN total loss: 0.03079 Total loss: 0.92686 timestamp: 1654978321.509047 iteration: 82175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04254 FastRCNN class loss: 0.04924 FastRCNN total loss: 0.09178 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11838 RPN box loss: 0.0092 RPN score loss: 0.00254 RPN total loss: 0.01174 Total loss: 0.8094 timestamp: 1654978324.6184816 iteration: 82180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.13829 FastRCNN total loss: 0.25391 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10857 RPN box loss: 0.01489 RPN score loss: 0.0075 RPN total loss: 0.02239 Total loss: 0.97237 timestamp: 1654978327.8258562 iteration: 82185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08039 FastRCNN class loss: 0.04162 FastRCNN total loss: 0.12201 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.12064 RPN box loss: 0.00314 RPN score loss: 0.00973 RPN total loss: 0.01288 Total loss: 0.84303 timestamp: 1654978331.0223594 iteration: 82190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0979 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.17286 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10877 RPN box loss: 0.01359 RPN score loss: 0.00666 RPN total loss: 0.02026 Total loss: 0.88939 timestamp: 1654978334.2289116 iteration: 82195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11398 FastRCNN class loss: 0.07309 FastRCNN total loss: 0.18707 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.21779 RPN box loss: 0.00764 RPN score loss: 0.0028 RPN total loss: 0.01044 Total loss: 1.0028 timestamp: 1654978337.4783943 iteration: 82200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05527 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.11067 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09276 RPN box loss: 0.00556 RPN score loss: 0.00503 RPN total loss: 0.0106 Total loss: 0.80152 timestamp: 1654978340.72904 iteration: 82205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05538 FastRCNN class loss: 0.03284 FastRCNN total loss: 0.08822 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10102 RPN box loss: 0.0206 RPN score loss: 0.00141 RPN total loss: 0.02201 Total loss: 0.79876 timestamp: 1654978343.8829503 iteration: 82210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08536 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.1642 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.18453 RPN box loss: 0.0229 RPN score loss: 0.01057 RPN total loss: 0.03347 Total loss: 0.96971 timestamp: 1654978346.9837391 iteration: 82215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06691 FastRCNN class loss: 0.07041 FastRCNN total loss: 0.13732 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13623 RPN box loss: 0.00811 RPN score loss: 0.00458 RPN total loss: 0.01269 Total loss: 0.87375 timestamp: 1654978350.1760466 iteration: 82220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09351 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.16243 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09448 RPN box loss: 0.01416 RPN score loss: 0.00329 RPN total loss: 0.01745 Total loss: 0.86186 timestamp: 1654978353.3764856 iteration: 82225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09927 FastRCNN class loss: 0.05812 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10385 RPN box loss: 0.01592 RPN score loss: 0.00843 RPN total loss: 0.02435 Total loss: 0.87309 timestamp: 1654978356.6354966 iteration: 82230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12943 FastRCNN class loss: 0.04171 FastRCNN total loss: 0.17114 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13286 RPN box loss: 0.00996 RPN score loss: 0.00368 RPN total loss: 0.01365 Total loss: 0.90514 timestamp: 1654978359.824809 iteration: 82235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05847 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.1256 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09218 RPN box loss: 0.01155 RPN score loss: 0.00848 RPN total loss: 0.02003 Total loss: 0.82531 timestamp: 1654978363.0254521 iteration: 82240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07015 FastRCNN class loss: 0.0653 FastRCNN total loss: 0.13545 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.15242 RPN box loss: 0.00874 RPN score loss: 0.00272 RPN total loss: 0.01146 Total loss: 0.88684 timestamp: 1654978366.201998 iteration: 82245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05222 FastRCNN class loss: 0.05016 FastRCNN total loss: 0.10238 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.12652 RPN box loss: 0.00907 RPN score loss: 0.00109 RPN total loss: 0.01016 Total loss: 0.82656 timestamp: 1654978369.3823307 iteration: 82250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.19239 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11074 RPN box loss: 0.02155 RPN score loss: 0.00576 RPN total loss: 0.02731 Total loss: 0.91795 timestamp: 1654978372.4913578 iteration: 82255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06494 FastRCNN class loss: 0.04499 FastRCNN total loss: 0.10994 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11903 RPN box loss: 0.00551 RPN score loss: 0.00439 RPN total loss: 0.0099 Total loss: 0.82637 timestamp: 1654978375.7719765 iteration: 82260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13072 FastRCNN class loss: 0.11438 FastRCNN total loss: 0.2451 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.20389 RPN box loss: 0.01059 RPN score loss: 0.00546 RPN total loss: 0.01605 Total loss: 1.05255 timestamp: 1654978378.9368346 iteration: 82265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06932 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.13492 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10967 RPN box loss: 0.02615 RPN score loss: 0.00579 RPN total loss: 0.03193 Total loss: 0.86402 timestamp: 1654978382.1327455 iteration: 82270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11229 FastRCNN class loss: 0.05158 FastRCNN total loss: 0.16387 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.12852 RPN box loss: 0.00437 RPN score loss: 0.00193 RPN total loss: 0.0063 Total loss: 0.88619 timestamp: 1654978385.2796707 iteration: 82275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03493 FastRCNN class loss: 0.05266 FastRCNN total loss: 0.08759 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.08564 RPN box loss: 0.00876 RPN score loss: 0.01047 RPN total loss: 0.01923 Total loss: 0.77996 timestamp: 1654978388.4652596 iteration: 82280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06139 FastRCNN class loss: 0.06087 FastRCNN total loss: 0.12225 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10122 RPN box loss: 0.00694 RPN score loss: 0.00135 RPN total loss: 0.0083 Total loss: 0.81927 timestamp: 1654978391.641761 iteration: 82285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.138 FastRCNN class loss: 0.08833 FastRCNN total loss: 0.22633 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11305 RPN box loss: 0.00491 RPN score loss: 0.00371 RPN total loss: 0.00863 Total loss: 0.93551 timestamp: 1654978394.877494 iteration: 82290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13192 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.18698 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11064 RPN box loss: 0.00603 RPN score loss: 0.00241 RPN total loss: 0.00845 Total loss: 0.89356 timestamp: 1654978398.0191479 iteration: 82295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14757 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.21318 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.15983 RPN box loss: 0.01731 RPN score loss: 0.00349 RPN total loss: 0.02079 Total loss: 0.98131 timestamp: 1654978401.2082202 iteration: 82300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10385 FastRCNN class loss: 0.07427 FastRCNN total loss: 0.17812 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10609 RPN box loss: 0.00578 RPN score loss: 0.00066 RPN total loss: 0.00645 Total loss: 0.87816 timestamp: 1654978404.3886492 iteration: 82305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07107 FastRCNN class loss: 0.06773 FastRCNN total loss: 0.1388 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.16023 RPN box loss: 0.01026 RPN score loss: 0.00561 RPN total loss: 0.01588 Total loss: 0.9024 timestamp: 1654978407.629355 iteration: 82310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03994 FastRCNN class loss: 0.04193 FastRCNN total loss: 0.08187 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.08587 RPN box loss: 0.00566 RPN score loss: 0.00339 RPN total loss: 0.00905 Total loss: 0.76428 timestamp: 1654978410.8416884 iteration: 82315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06612 FastRCNN class loss: 0.0717 FastRCNN total loss: 0.13782 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09854 RPN box loss: 0.01486 RPN score loss: 0.00453 RPN total loss: 0.01939 Total loss: 0.84324 timestamp: 1654978414.1329474 iteration: 82320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0732 FastRCNN class loss: 0.07424 FastRCNN total loss: 0.14744 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.1376 RPN box loss: 0.01655 RPN score loss: 0.01461 RPN total loss: 0.03116 Total loss: 0.9037 timestamp: 1654978417.3027062 iteration: 82325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08736 FastRCNN class loss: 0.05457 FastRCNN total loss: 0.14192 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10712 RPN box loss: 0.01425 RPN score loss: 0.00249 RPN total loss: 0.01674 Total loss: 0.85328 timestamp: 1654978420.4590359 iteration: 82330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06922 FastRCNN class loss: 0.06374 FastRCNN total loss: 0.13296 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13857 RPN box loss: 0.00861 RPN score loss: 0.00699 RPN total loss: 0.0156 Total loss: 0.87463 timestamp: 1654978423.6791587 iteration: 82335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08985 FastRCNN class loss: 0.04232 FastRCNN total loss: 0.13217 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10283 RPN box loss: 0.01231 RPN score loss: 0.00528 RPN total loss: 0.01759 Total loss: 0.84009 timestamp: 1654978426.9492996 iteration: 82340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07913 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.1504 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.08706 RPN box loss: 0.00477 RPN score loss: 0.00258 RPN total loss: 0.00735 Total loss: 0.83231 timestamp: 1654978430.173514 iteration: 82345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07338 FastRCNN class loss: 0.04466 FastRCNN total loss: 0.11804 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.1462 RPN box loss: 0.00342 RPN score loss: 0.00552 RPN total loss: 0.00894 Total loss: 0.86069 timestamp: 1654978433.4001653 iteration: 82350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08603 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.15834 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09634 RPN box loss: 0.00543 RPN score loss: 0.00763 RPN total loss: 0.01306 Total loss: 0.85524 timestamp: 1654978436.572417 iteration: 82355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11227 FastRCNN class loss: 0.07689 FastRCNN total loss: 0.18915 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.12206 RPN box loss: 0.02471 RPN score loss: 0.00656 RPN total loss: 0.03127 Total loss: 0.92998 timestamp: 1654978439.6889365 iteration: 82360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09087 FastRCNN class loss: 0.03897 FastRCNN total loss: 0.12984 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.20011 RPN box loss: 0.00676 RPN score loss: 0.00118 RPN total loss: 0.00794 Total loss: 0.9254 timestamp: 1654978442.9089122 iteration: 82365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04647 FastRCNN class loss: 0.05427 FastRCNN total loss: 0.10074 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09476 RPN box loss: 0.02232 RPN score loss: 0.00203 RPN total loss: 0.02435 Total loss: 0.80735 timestamp: 1654978446.0997727 iteration: 82370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0466 FastRCNN class loss: 0.04506 FastRCNN total loss: 0.09166 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10633 RPN box loss: 0.00711 RPN score loss: 0.00409 RPN total loss: 0.0112 Total loss: 0.79669 timestamp: 1654978449.3162787 iteration: 82375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07981 FastRCNN class loss: 0.0789 FastRCNN total loss: 0.15871 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.15144 RPN box loss: 0.01537 RPN score loss: 0.0045 RPN total loss: 0.01987 Total loss: 0.91753 timestamp: 1654978452.5307543 iteration: 82380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07305 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.13866 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.08195 RPN box loss: 0.00678 RPN score loss: 0.00088 RPN total loss: 0.00766 Total loss: 0.81577 timestamp: 1654978455.7327728 iteration: 82385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10025 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.16947 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11849 RPN box loss: 0.0264 RPN score loss: 0.00568 RPN total loss: 0.03207 Total loss: 0.90753 timestamp: 1654978458.9313288 iteration: 82390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10612 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.18045 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.132 RPN box loss: 0.00761 RPN score loss: 0.0013 RPN total loss: 0.00891 Total loss: 0.90886 timestamp: 1654978462.105172 iteration: 82395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06928 FastRCNN class loss: 0.04545 FastRCNN total loss: 0.11473 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09101 RPN box loss: 0.02837 RPN score loss: 0.00717 RPN total loss: 0.03554 Total loss: 0.82878 timestamp: 1654978465.3235614 iteration: 82400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08871 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.146 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09397 RPN box loss: 0.04183 RPN score loss: 0.00614 RPN total loss: 0.04796 Total loss: 0.87543 timestamp: 1654978468.532148 iteration: 82405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11815 FastRCNN class loss: 0.0522 FastRCNN total loss: 0.17035 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13687 RPN box loss: 0.00861 RPN score loss: 0.00345 RPN total loss: 0.01206 Total loss: 0.90678 timestamp: 1654978471.7194018 iteration: 82410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07874 FastRCNN class loss: 0.08753 FastRCNN total loss: 0.16627 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.15847 RPN box loss: 0.01161 RPN score loss: 0.00188 RPN total loss: 0.01348 Total loss: 0.92572 timestamp: 1654978474.9191372 iteration: 82415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09204 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.15865 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.10603 RPN box loss: 0.01983 RPN score loss: 0.00355 RPN total loss: 0.02338 Total loss: 0.87556 timestamp: 1654978478.104585 iteration: 82420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07538 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.13349 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13713 RPN box loss: 0.01181 RPN score loss: 0.01324 RPN total loss: 0.02505 Total loss: 0.88317 timestamp: 1654978481.2819695 iteration: 82425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09935 FastRCNN class loss: 0.08383 FastRCNN total loss: 0.18318 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.16455 RPN box loss: 0.03659 RPN score loss: 0.01015 RPN total loss: 0.04674 Total loss: 0.98196 timestamp: 1654978484.5190315 iteration: 82430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0814 FastRCNN class loss: 0.07837 FastRCNN total loss: 0.15977 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.11419 RPN box loss: 0.0182 RPN score loss: 0.00136 RPN total loss: 0.01955 Total loss: 0.881 timestamp: 1654978487.677499 iteration: 82435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11587 FastRCNN class loss: 0.04921 FastRCNN total loss: 0.16509 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.09874 RPN box loss: 0.01013 RPN score loss: 0.0006 RPN total loss: 0.01073 Total loss: 0.86205 timestamp: 1654978490.884365 iteration: 82440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11959 FastRCNN class loss: 0.06492 FastRCNN total loss: 0.18451 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.16792 RPN box loss: 0.01061 RPN score loss: 0.00677 RPN total loss: 0.01738 Total loss: 0.95731 timestamp: 1654978494.0655358 iteration: 82445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0873 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.15736 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.15489 RPN box loss: 0.0237 RPN score loss: 0.00465 RPN total loss: 0.02836 Total loss: 0.9281 timestamp: 1654978497.2860353 iteration: 82450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05623 FastRCNN class loss: 0.06747 FastRCNN total loss: 0.1237 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.13186 RPN box loss: 0.01328 RPN score loss: 0.0327 RPN total loss: 0.04598 Total loss: 0.88903 timestamp: 1654978500.5187843 iteration: 82455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08651 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.14155 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.14741 RPN box loss: 0.00561 RPN score loss: 0.00232 RPN total loss: 0.00793 Total loss: 0.88439 timestamp: 1654978503.7226133 iteration: 82460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06758 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.13513 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 4.0000e-05 Mask loss: 0.17163 RPN box loss: 0.01086 RPN score loss: 0.00462 RPN total loss: 0.01548 Total loss: 0.90974 timestamp: 1654978506.9490998 iteration: 82465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11755 FastRCNN class loss: 0.06332 FastRCNN total loss: 0.18087 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10858 RPN box loss: 0.02455 RPN score loss: 0.00374 RPN total loss: 0.02829 Total loss: 0.90524 timestamp: 1654978510.1555848 iteration: 82470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12092 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.1903 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13267 RPN box loss: 0.01155 RPN score loss: 0.00388 RPN total loss: 0.01543 Total loss: 0.9259 timestamp: 1654978513.4180422 iteration: 82475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10522 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.16017 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13515 RPN box loss: 0.00516 RPN score loss: 0.00201 RPN total loss: 0.00717 Total loss: 0.88999 timestamp: 1654978516.613178 iteration: 82480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09698 FastRCNN class loss: 0.07291 FastRCNN total loss: 0.16989 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.14805 RPN box loss: 0.0185 RPN score loss: 0.00862 RPN total loss: 0.02711 Total loss: 0.93254 timestamp: 1654978519.8122776 iteration: 82485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08703 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.14666 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08948 RPN box loss: 0.00974 RPN score loss: 0.00471 RPN total loss: 0.01445 Total loss: 0.83808 timestamp: 1654978523.0236497 iteration: 82490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07018 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.12709 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08014 RPN box loss: 0.00568 RPN score loss: 0.00085 RPN total loss: 0.00653 Total loss: 0.80125 timestamp: 1654978526.187391 iteration: 82495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08641 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.14178 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08587 RPN box loss: 0.00701 RPN score loss: 0.00439 RPN total loss: 0.0114 Total loss: 0.82654 timestamp: 1654978529.4197469 iteration: 82500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06686 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.15196 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.0746 RPN box loss: 0.00923 RPN score loss: 0.00925 RPN total loss: 0.01848 Total loss: 0.83254 timestamp: 1654978532.6303513 iteration: 82505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09327 FastRCNN class loss: 0.05528 FastRCNN total loss: 0.14855 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13102 RPN box loss: 0.01726 RPN score loss: 0.00351 RPN total loss: 0.02077 Total loss: 0.88784 timestamp: 1654978535.844898 iteration: 82510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05823 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.11777 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.11478 RPN box loss: 0.01107 RPN score loss: 0.00134 RPN total loss: 0.01241 Total loss: 0.83245 timestamp: 1654978539.0135148 iteration: 82515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.0878 FastRCNN total loss: 0.19279 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.18179 RPN box loss: 0.01871 RPN score loss: 0.00953 RPN total loss: 0.02824 Total loss: 0.99031 timestamp: 1654978542.19276 iteration: 82520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08102 FastRCNN class loss: 0.05508 FastRCNN total loss: 0.1361 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13422 RPN box loss: 0.01236 RPN score loss: 0.00932 RPN total loss: 0.02168 Total loss: 0.87949 timestamp: 1654978545.421317 iteration: 82525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06355 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.13465 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12287 RPN box loss: 0.0298 RPN score loss: 0.0051 RPN total loss: 0.03491 Total loss: 0.87992 timestamp: 1654978548.6782243 iteration: 82530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08118 FastRCNN class loss: 0.05959 FastRCNN total loss: 0.14077 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10941 RPN box loss: 0.00821 RPN score loss: 0.00186 RPN total loss: 0.01006 Total loss: 0.84774 timestamp: 1654978551.9119306 iteration: 82535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10211 FastRCNN class loss: 0.05156 FastRCNN total loss: 0.15367 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13047 RPN box loss: 0.00396 RPN score loss: 0.00579 RPN total loss: 0.00975 Total loss: 0.88138 timestamp: 1654978555.1253455 iteration: 82540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08209 FastRCNN class loss: 0.06263 FastRCNN total loss: 0.14472 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.18376 RPN box loss: 0.02816 RPN score loss: 0.00568 RPN total loss: 0.03383 Total loss: 0.9498 timestamp: 1654978558.280215 iteration: 82545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07729 FastRCNN class loss: 0.04179 FastRCNN total loss: 0.11908 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13584 RPN box loss: 0.00761 RPN score loss: 0.00333 RPN total loss: 0.01094 Total loss: 0.85335 timestamp: 1654978561.4067528 iteration: 82550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08729 FastRCNN class loss: 0.05667 FastRCNN total loss: 0.14396 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12776 RPN box loss: 0.00714 RPN score loss: 0.00146 RPN total loss: 0.0086 Total loss: 0.86781 timestamp: 1654978564.6045337 iteration: 82555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.16255 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.16025 RPN box loss: 0.02304 RPN score loss: 0.00597 RPN total loss: 0.02901 Total loss: 0.93931 timestamp: 1654978567.804038 iteration: 82560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08071 FastRCNN class loss: 0.09515 FastRCNN total loss: 0.17586 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13214 RPN box loss: 0.01389 RPN score loss: 0.00395 RPN total loss: 0.01784 Total loss: 0.91333 timestamp: 1654978571.0021608 iteration: 82565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11124 FastRCNN class loss: 0.07993 FastRCNN total loss: 0.19117 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13793 RPN box loss: 0.01215 RPN score loss: 0.00283 RPN total loss: 0.01498 Total loss: 0.93157 timestamp: 1654978574.277563 iteration: 82570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06353 FastRCNN class loss: 0.04147 FastRCNN total loss: 0.105 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.09437 RPN box loss: 0.00605 RPN score loss: 0.00057 RPN total loss: 0.00663 Total loss: 0.79349 timestamp: 1654978577.4758174 iteration: 82575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05307 FastRCNN class loss: 0.05787 FastRCNN total loss: 0.11093 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10409 RPN box loss: 0.0052 RPN score loss: 0.00498 RPN total loss: 0.01017 Total loss: 0.81269 timestamp: 1654978580.7238917 iteration: 82580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09885 FastRCNN class loss: 0.11166 FastRCNN total loss: 0.21051 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.17128 RPN box loss: 0.02326 RPN score loss: 0.01651 RPN total loss: 0.03977 Total loss: 1.00906 timestamp: 1654978583.9135244 iteration: 82585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11684 FastRCNN class loss: 0.03273 FastRCNN total loss: 0.14957 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.18222 RPN box loss: 0.01727 RPN score loss: 0.00206 RPN total loss: 0.01933 Total loss: 0.9386 timestamp: 1654978587.0814543 iteration: 82590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11248 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.16717 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08904 RPN box loss: 0.00833 RPN score loss: 0.00741 RPN total loss: 0.01573 Total loss: 0.85944 timestamp: 1654978590.2866902 iteration: 82595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14777 FastRCNN class loss: 0.09961 FastRCNN total loss: 0.24738 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13831 RPN box loss: 0.00898 RPN score loss: 0.00907 RPN total loss: 0.01805 Total loss: 0.99122 timestamp: 1654978593.4883108 iteration: 82600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09254 FastRCNN class loss: 0.05377 FastRCNN total loss: 0.14631 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.17159 RPN box loss: 0.00703 RPN score loss: 0.0034 RPN total loss: 0.01043 Total loss: 0.91582 timestamp: 1654978596.6123755 iteration: 82605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06556 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.1273 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13925 RPN box loss: 0.00802 RPN score loss: 0.00076 RPN total loss: 0.00877 Total loss: 0.86281 timestamp: 1654978599.7956882 iteration: 82610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07634 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.14684 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08101 RPN box loss: 0.00168 RPN score loss: 0.00124 RPN total loss: 0.00292 Total loss: 0.81827 timestamp: 1654978602.987115 iteration: 82615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09497 FastRCNN class loss: 0.08428 FastRCNN total loss: 0.17924 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.17433 RPN box loss: 0.009 RPN score loss: 0.0099 RPN total loss: 0.0189 Total loss: 0.95996 timestamp: 1654978606.2567172 iteration: 82620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09116 FastRCNN class loss: 0.06905 FastRCNN total loss: 0.16021 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.18185 RPN box loss: 0.00835 RPN score loss: 0.00126 RPN total loss: 0.00961 Total loss: 0.93915 timestamp: 1654978609.5306482 iteration: 82625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07497 FastRCNN class loss: 0.05218 FastRCNN total loss: 0.12715 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12198 RPN box loss: 0.00536 RPN score loss: 0.00407 RPN total loss: 0.00943 Total loss: 0.84605 timestamp: 1654978612.700177 iteration: 82630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04454 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.10621 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10645 RPN box loss: 0.01143 RPN score loss: 0.00398 RPN total loss: 0.01541 Total loss: 0.81556 timestamp: 1654978615.8860207 iteration: 82635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05369 FastRCNN class loss: 0.05438 FastRCNN total loss: 0.10806 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08442 RPN box loss: 0.00979 RPN score loss: 0.00194 RPN total loss: 0.01173 Total loss: 0.7917 timestamp: 1654978619.0732691 iteration: 82640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11151 FastRCNN class loss: 0.07635 FastRCNN total loss: 0.18787 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12577 RPN box loss: 0.01172 RPN score loss: 0.00596 RPN total loss: 0.01768 Total loss: 0.91881 timestamp: 1654978622.2810726 iteration: 82645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06049 FastRCNN class loss: 0.04318 FastRCNN total loss: 0.10367 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.08483 RPN box loss: 0.00242 RPN score loss: 0.00523 RPN total loss: 0.00765 Total loss: 0.78364 timestamp: 1654978625.495238 iteration: 82650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09889 FastRCNN class loss: 0.04618 FastRCNN total loss: 0.14507 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10531 RPN box loss: 0.00567 RPN score loss: 0.00123 RPN total loss: 0.0069 Total loss: 0.84477 timestamp: 1654978628.6397262 iteration: 82655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05479 FastRCNN class loss: 0.05971 FastRCNN total loss: 0.1145 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13533 RPN box loss: 0.00857 RPN score loss: 0.00266 RPN total loss: 0.01124 Total loss: 0.84855 timestamp: 1654978631.775495 iteration: 82660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10626 FastRCNN class loss: 0.0577 FastRCNN total loss: 0.16396 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13382 RPN box loss: 0.01123 RPN score loss: 0.00351 RPN total loss: 0.01474 Total loss: 0.9 timestamp: 1654978634.9482453 iteration: 82665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11514 FastRCNN class loss: 0.08948 FastRCNN total loss: 0.20462 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12724 RPN box loss: 0.01419 RPN score loss: 0.00603 RPN total loss: 0.02022 Total loss: 0.93957 timestamp: 1654978638.19252 iteration: 82670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.13772 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.15117 RPN box loss: 0.00791 RPN score loss: 0.00754 RPN total loss: 0.01545 Total loss: 0.89182 timestamp: 1654978641.353677 iteration: 82675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10783 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.16921 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13339 RPN box loss: 0.00393 RPN score loss: 0.00127 RPN total loss: 0.0052 Total loss: 0.89529 timestamp: 1654978644.581347 iteration: 82680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08622 FastRCNN class loss: 0.06157 FastRCNN total loss: 0.14779 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13427 RPN box loss: 0.0056 RPN score loss: 0.00484 RPN total loss: 0.01044 Total loss: 0.87998 timestamp: 1654978647.7816384 iteration: 82685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05199 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.12255 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.11926 RPN box loss: 0.01687 RPN score loss: 0.00667 RPN total loss: 0.02355 Total loss: 0.85284 timestamp: 1654978650.9668782 iteration: 82690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07824 FastRCNN class loss: 0.11101 FastRCNN total loss: 0.18925 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.1277 RPN box loss: 0.01306 RPN score loss: 0.00946 RPN total loss: 0.02252 Total loss: 0.92696 timestamp: 1654978654.222944 iteration: 82695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03073 FastRCNN class loss: 0.02908 FastRCNN total loss: 0.05981 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12474 RPN box loss: 0.01274 RPN score loss: 0.00392 RPN total loss: 0.01667 Total loss: 0.78871 timestamp: 1654978657.420342 iteration: 82700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09858 FastRCNN class loss: 0.0505 FastRCNN total loss: 0.14908 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.1212 RPN box loss: 0.03218 RPN score loss: 0.00661 RPN total loss: 0.03879 Total loss: 0.89656 timestamp: 1654978660.566461 iteration: 82705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08504 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.15476 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12591 RPN box loss: 0.01133 RPN score loss: 0.00397 RPN total loss: 0.0153 Total loss: 0.88345 timestamp: 1654978663.6943343 iteration: 82710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05446 FastRCNN class loss: 0.04657 FastRCNN total loss: 0.10103 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10991 RPN box loss: 0.01291 RPN score loss: 0.00462 RPN total loss: 0.01752 Total loss: 0.81596 timestamp: 1654978666.9189308 iteration: 82715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12463 FastRCNN class loss: 0.0942 FastRCNN total loss: 0.21883 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10649 RPN box loss: 0.00687 RPN score loss: 0.00539 RPN total loss: 0.01226 Total loss: 0.92506 timestamp: 1654978670.0886915 iteration: 82720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06894 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.1508 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13168 RPN box loss: 0.01292 RPN score loss: 0.0106 RPN total loss: 0.02352 Total loss: 0.89349 timestamp: 1654978673.2802308 iteration: 82725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06622 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.14137 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13459 RPN box loss: 0.01125 RPN score loss: 0.01141 RPN total loss: 0.02266 Total loss: 0.88611 timestamp: 1654978676.4817393 iteration: 82730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09439 FastRCNN class loss: 0.05835 FastRCNN total loss: 0.15274 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.09554 RPN box loss: 0.0122 RPN score loss: 0.00533 RPN total loss: 0.01753 Total loss: 0.8533 timestamp: 1654978679.6971304 iteration: 82735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05415 FastRCNN class loss: 0.05566 FastRCNN total loss: 0.10981 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.1254 RPN box loss: 0.0044 RPN score loss: 0.0011 RPN total loss: 0.0055 Total loss: 0.82819 timestamp: 1654978682.8985507 iteration: 82740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09753 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.15762 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.14288 RPN box loss: 0.01117 RPN score loss: 0.00211 RPN total loss: 0.01328 Total loss: 0.90126 timestamp: 1654978686.1482122 iteration: 82745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07072 FastRCNN class loss: 0.06887 FastRCNN total loss: 0.13959 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13312 RPN box loss: 0.06552 RPN score loss: 0.00256 RPN total loss: 0.06809 Total loss: 0.92828 timestamp: 1654978689.3432732 iteration: 82750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10851 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.17573 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.12472 RPN box loss: 0.00754 RPN score loss: 0.00211 RPN total loss: 0.00965 Total loss: 0.89758 timestamp: 1654978692.5456357 iteration: 82755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1122 FastRCNN class loss: 0.0729 FastRCNN total loss: 0.1851 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.17887 RPN box loss: 0.01643 RPN score loss: 0.01238 RPN total loss: 0.0288 Total loss: 0.98026 timestamp: 1654978695.8125572 iteration: 82760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09615 FastRCNN class loss: 0.08856 FastRCNN total loss: 0.18471 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.15179 RPN box loss: 0.01065 RPN score loss: 0.00688 RPN total loss: 0.01753 Total loss: 0.94151 timestamp: 1654978699.0044847 iteration: 82765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11302 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.19453 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13357 RPN box loss: 0.0059 RPN score loss: 0.0055 RPN total loss: 0.0114 Total loss: 0.92699 timestamp: 1654978702.2189622 iteration: 82770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04242 FastRCNN class loss: 0.06471 FastRCNN total loss: 0.10713 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10204 RPN box loss: 0.00946 RPN score loss: 0.00426 RPN total loss: 0.01372 Total loss: 0.81038 timestamp: 1654978705.4633794 iteration: 82775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.14761 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.13419 RPN box loss: 0.00765 RPN score loss: 0.00346 RPN total loss: 0.01111 Total loss: 0.8804 timestamp: 1654978708.6545815 iteration: 82780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08084 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.136 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.09638 RPN box loss: 0.01483 RPN score loss: 0.00051 RPN total loss: 0.01534 Total loss: 0.83519 timestamp: 1654978711.9247046 iteration: 82785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06354 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.11868 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.10237 RPN box loss: 0.0167 RPN score loss: 0.00132 RPN total loss: 0.01802 Total loss: 0.82656 timestamp: 1654978715.0993938 iteration: 82790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04964 FastRCNN class loss: 0.03924 FastRCNN total loss: 0.08888 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.11343 RPN box loss: 0.01055 RPN score loss: 0.00318 RPN total loss: 0.01373 Total loss: 0.80353 timestamp: 1654978718.3523457 iteration: 82795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08254 FastRCNN class loss: 0.04166 FastRCNN total loss: 0.1242 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 4.0000e-05 Mask loss: 0.1171 RPN box loss: 0.00604 RPN score loss: 0.00171 RPN total loss: 0.00776 Total loss: 0.83653 timestamp: 1654978721.4905992 iteration: 82800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.08443 FastRCNN total loss: 0.16297 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.16765 RPN box loss: 0.01389 RPN score loss: 0.00424 RPN total loss: 0.01812 Total loss: 0.93623 timestamp: 1654978724.8219607 iteration: 82805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05323 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.11828 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.08978 RPN box loss: 0.00498 RPN score loss: 0.00355 RPN total loss: 0.00853 Total loss: 0.80407 timestamp: 1654978728.04514 iteration: 82810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.074 FastRCNN total loss: 0.15492 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.13214 RPN box loss: 0.02196 RPN score loss: 0.00226 RPN total loss: 0.02422 Total loss: 0.89876 timestamp: 1654978731.3171706 iteration: 82815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08505 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.14106 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10962 RPN box loss: 0.01014 RPN score loss: 0.00184 RPN total loss: 0.01198 Total loss: 0.85015 timestamp: 1654978734.5836298 iteration: 82820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.18588 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.09145 RPN box loss: 0.00989 RPN score loss: 0.00204 RPN total loss: 0.01193 Total loss: 0.87674 timestamp: 1654978737.755091 iteration: 82825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10318 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.16505 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.1424 RPN box loss: 0.0111 RPN score loss: 0.00295 RPN total loss: 0.01405 Total loss: 0.90899 timestamp: 1654978740.9422433 iteration: 82830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.05919 FastRCNN total loss: 0.12017 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.1656 RPN box loss: 0.01696 RPN score loss: 0.00125 RPN total loss: 0.01822 Total loss: 0.89148 timestamp: 1654978744.0871081 iteration: 82835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09617 FastRCNN class loss: 0.06912 FastRCNN total loss: 0.16529 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.09186 RPN box loss: 0.00409 RPN score loss: 0.00524 RPN total loss: 0.00932 Total loss: 0.85396 timestamp: 1654978747.3722398 iteration: 82840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12942 FastRCNN class loss: 0.11257 FastRCNN total loss: 0.24199 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.16797 RPN box loss: 0.0158 RPN score loss: 0.00831 RPN total loss: 0.0241 Total loss: 1.02155 timestamp: 1654978750.5570278 iteration: 82845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07875 FastRCNN class loss: 0.0583 FastRCNN total loss: 0.13705 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.1021 RPN box loss: 0.01504 RPN score loss: 0.00566 RPN total loss: 0.02069 Total loss: 0.84733 timestamp: 1654978753.7564843 iteration: 82850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09354 FastRCNN class loss: 0.06288 FastRCNN total loss: 0.15642 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12316 RPN box loss: 0.00953 RPN score loss: 0.00249 RPN total loss: 0.01202 Total loss: 0.87909 timestamp: 1654978757.0111368 iteration: 82855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06709 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.14799 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.15232 RPN box loss: 0.01035 RPN score loss: 0.00472 RPN total loss: 0.01507 Total loss: 0.90286 timestamp: 1654978760.1789708 iteration: 82860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09087 FastRCNN class loss: 0.07784 FastRCNN total loss: 0.16871 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.09361 RPN box loss: 0.00889 RPN score loss: 0.0064 RPN total loss: 0.01529 Total loss: 0.86508 timestamp: 1654978763.4359186 iteration: 82865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06921 FastRCNN class loss: 0.06047 FastRCNN total loss: 0.12969 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10773 RPN box loss: 0.00721 RPN score loss: 0.00199 RPN total loss: 0.00921 Total loss: 0.83411 timestamp: 1654978766.5664394 iteration: 82870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0614 FastRCNN class loss: 0.04069 FastRCNN total loss: 0.10209 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.14797 RPN box loss: 0.00902 RPN score loss: 0.00466 RPN total loss: 0.01368 Total loss: 0.85122 timestamp: 1654978769.7739482 iteration: 82875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08437 FastRCNN class loss: 0.08176 FastRCNN total loss: 0.16613 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11074 RPN box loss: 0.01973 RPN score loss: 0.00166 RPN total loss: 0.02138 Total loss: 0.88573 timestamp: 1654978772.9522996 iteration: 82880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07119 FastRCNN class loss: 0.04107 FastRCNN total loss: 0.11226 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.09651 RPN box loss: 0.00425 RPN score loss: 0.00138 RPN total loss: 0.00563 Total loss: 0.80188 timestamp: 1654978776.1378572 iteration: 82885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09382 FastRCNN class loss: 0.04521 FastRCNN total loss: 0.13904 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.16611 RPN box loss: 0.0094 RPN score loss: 0.00155 RPN total loss: 0.01095 Total loss: 0.90358 timestamp: 1654978779.2660496 iteration: 82890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10108 FastRCNN class loss: 0.07172 FastRCNN total loss: 0.1728 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.13919 RPN box loss: 0.01118 RPN score loss: 0.00085 RPN total loss: 0.01203 Total loss: 0.9115 timestamp: 1654978782.4326339 iteration: 82895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0648 FastRCNN class loss: 0.06902 FastRCNN total loss: 0.13382 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11604 RPN box loss: 0.03614 RPN score loss: 0.00966 RPN total loss: 0.0458 Total loss: 0.88314 timestamp: 1654978785.6106675 iteration: 82900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08635 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.14918 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.15336 RPN box loss: 0.01483 RPN score loss: 0.00984 RPN total loss: 0.02468 Total loss: 0.9147 timestamp: 1654978788.8170066 iteration: 82905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09837 FastRCNN class loss: 0.07934 FastRCNN total loss: 0.17771 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12413 RPN box loss: 0.0135 RPN score loss: 0.00641 RPN total loss: 0.01991 Total loss: 0.90923 timestamp: 1654978792.0356982 iteration: 82910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09811 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.17259 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.15386 RPN box loss: 0.01721 RPN score loss: 0.00584 RPN total loss: 0.02305 Total loss: 0.93699 timestamp: 1654978795.1803129 iteration: 82915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05832 FastRCNN class loss: 0.02483 FastRCNN total loss: 0.08314 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.08943 RPN box loss: 0.00861 RPN score loss: 0.00138 RPN total loss: 0.00999 Total loss: 0.77005 timestamp: 1654978798.3792388 iteration: 82920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13187 FastRCNN class loss: 0.06871 FastRCNN total loss: 0.20058 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.16916 RPN box loss: 0.0178 RPN score loss: 0.00282 RPN total loss: 0.02062 Total loss: 0.97785 timestamp: 1654978801.5453422 iteration: 82925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13582 FastRCNN class loss: 0.08014 FastRCNN total loss: 0.21595 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.16867 RPN box loss: 0.01506 RPN score loss: 0.00239 RPN total loss: 0.01745 Total loss: 0.98955 timestamp: 1654978804.6926591 iteration: 82930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05537 FastRCNN class loss: 0.05204 FastRCNN total loss: 0.10741 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.13772 RPN box loss: 0.03806 RPN score loss: 0.00356 RPN total loss: 0.04163 Total loss: 0.87424 timestamp: 1654978807.9000146 iteration: 82935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06686 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.13679 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.13811 RPN box loss: 0.00664 RPN score loss: 0.00302 RPN total loss: 0.00965 Total loss: 0.87203 timestamp: 1654978811.0791006 iteration: 82940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05892 FastRCNN class loss: 0.03606 FastRCNN total loss: 0.09498 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.23145 RPN box loss: 0.00549 RPN score loss: 0.00678 RPN total loss: 0.01227 Total loss: 0.92619 timestamp: 1654978814.270288 iteration: 82945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06231 FastRCNN class loss: 0.05673 FastRCNN total loss: 0.11904 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12829 RPN box loss: 0.01687 RPN score loss: 0.01566 RPN total loss: 0.03254 Total loss: 0.86735 timestamp: 1654978817.4409442 iteration: 82950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0798 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.14937 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10231 RPN box loss: 0.00786 RPN score loss: 0.00974 RPN total loss: 0.0176 Total loss: 0.85675 timestamp: 1654978820.6343682 iteration: 82955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09341 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.15905 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12459 RPN box loss: 0.00871 RPN score loss: 0.00793 RPN total loss: 0.01665 Total loss: 0.88777 timestamp: 1654978823.865599 iteration: 82960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05341 FastRCNN class loss: 0.04922 FastRCNN total loss: 0.10262 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10211 RPN box loss: 0.00509 RPN score loss: 0.00114 RPN total loss: 0.00623 Total loss: 0.79844 timestamp: 1654978827.0901086 iteration: 82965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0992 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.17883 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10459 RPN box loss: 0.01981 RPN score loss: 0.00436 RPN total loss: 0.02417 Total loss: 0.89506 timestamp: 1654978830.253007 iteration: 82970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12069 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.19516 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12611 RPN box loss: 0.01132 RPN score loss: 0.00379 RPN total loss: 0.01511 Total loss: 0.92387 timestamp: 1654978833.471372 iteration: 82975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08674 FastRCNN class loss: 0.04298 FastRCNN total loss: 0.12972 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10252 RPN box loss: 0.00252 RPN score loss: 0.00028 RPN total loss: 0.0028 Total loss: 0.82251 timestamp: 1654978836.671685 iteration: 82980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13849 FastRCNN class loss: 0.06683 FastRCNN total loss: 0.20531 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11944 RPN box loss: 0.0045 RPN score loss: 0.00124 RPN total loss: 0.00574 Total loss: 0.91797 timestamp: 1654978839.8505383 iteration: 82985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.049 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.1044 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.14058 RPN box loss: 0.0059 RPN score loss: 0.0017 RPN total loss: 0.0076 Total loss: 0.84005 timestamp: 1654978843.0428715 iteration: 82990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08888 FastRCNN class loss: 0.05264 FastRCNN total loss: 0.14152 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.1256 RPN box loss: 0.01058 RPN score loss: 0.00255 RPN total loss: 0.01313 Total loss: 0.86773 timestamp: 1654978846.2717283 iteration: 82995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07459 FastRCNN class loss: 0.05427 FastRCNN total loss: 0.12886 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11234 RPN box loss: 0.06171 RPN score loss: 0.00303 RPN total loss: 0.06474 Total loss: 0.89342 timestamp: 1654978849.4317842 iteration: 83000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09053 FastRCNN class loss: 0.10085 FastRCNN total loss: 0.19138 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.14323 RPN box loss: 0.00447 RPN score loss: 0.00545 RPN total loss: 0.00992 Total loss: 0.932 timestamp: 1654978852.6637702 iteration: 83005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.049 FastRCNN class loss: 0.04665 FastRCNN total loss: 0.09565 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.13673 RPN box loss: 0.00853 RPN score loss: 0.0056 RPN total loss: 0.01413 Total loss: 0.834 timestamp: 1654978855.8254445 iteration: 83010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08668 FastRCNN class loss: 0.11213 FastRCNN total loss: 0.1988 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.23099 RPN box loss: 0.02164 RPN score loss: 0.01185 RPN total loss: 0.0335 Total loss: 1.05077 timestamp: 1654978859.079456 iteration: 83015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.06461 FastRCNN total loss: 0.15634 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10868 RPN box loss: 0.00682 RPN score loss: 0.00947 RPN total loss: 0.01629 Total loss: 0.86878 timestamp: 1654978862.300947 iteration: 83020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0668 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.11503 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.08952 RPN box loss: 0.00368 RPN score loss: 0.00048 RPN total loss: 0.00416 Total loss: 0.79619 timestamp: 1654978865.4663527 iteration: 83025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10443 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.17248 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12749 RPN box loss: 0.0159 RPN score loss: 0.00163 RPN total loss: 0.01752 Total loss: 0.90497 timestamp: 1654978868.650801 iteration: 83030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04901 FastRCNN class loss: 0.05554 FastRCNN total loss: 0.10455 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12673 RPN box loss: 0.00776 RPN score loss: 0.0063 RPN total loss: 0.01406 Total loss: 0.83282 timestamp: 1654978871.8228338 iteration: 83035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09101 FastRCNN class loss: 0.0481 FastRCNN total loss: 0.13912 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12603 RPN box loss: 0.01412 RPN score loss: 0.00072 RPN total loss: 0.01484 Total loss: 0.86746 timestamp: 1654978875.0934153 iteration: 83040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10779 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.15904 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11805 RPN box loss: 0.01294 RPN score loss: 0.00374 RPN total loss: 0.01668 Total loss: 0.88124 timestamp: 1654978878.3073044 iteration: 83045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12818 FastRCNN class loss: 0.06682 FastRCNN total loss: 0.195 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12418 RPN box loss: 0.00605 RPN score loss: 0.00166 RPN total loss: 0.00771 Total loss: 0.91437 timestamp: 1654978881.5181108 iteration: 83050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10201 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.17101 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.16023 RPN box loss: 0.01232 RPN score loss: 0.00651 RPN total loss: 0.01882 Total loss: 0.93754 timestamp: 1654978884.7626348 iteration: 83055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08619 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.1423 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10964 RPN box loss: 0.00568 RPN score loss: 0.00789 RPN total loss: 0.01357 Total loss: 0.85298 timestamp: 1654978887.9500744 iteration: 83060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12916 FastRCNN class loss: 0.05275 FastRCNN total loss: 0.18191 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.12232 RPN box loss: 0.01171 RPN score loss: 0.00633 RPN total loss: 0.01804 Total loss: 0.90975 timestamp: 1654978891.192979 iteration: 83065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11168 FastRCNN class loss: 0.04743 FastRCNN total loss: 0.1591 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.10685 RPN box loss: 0.00475 RPN score loss: 0.00223 RPN total loss: 0.00699 Total loss: 0.86042 timestamp: 1654978894.444994 iteration: 83070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12416 FastRCNN class loss: 0.09099 FastRCNN total loss: 0.21515 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.1369 RPN box loss: 0.01232 RPN score loss: 0.00381 RPN total loss: 0.01613 Total loss: 0.95565 timestamp: 1654978897.6824706 iteration: 83075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.07919 FastRCNN total loss: 0.17955 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11612 RPN box loss: 0.01054 RPN score loss: 0.00321 RPN total loss: 0.01374 Total loss: 0.8969 timestamp: 1654978900.847542 iteration: 83080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08159 FastRCNN class loss: 0.04605 FastRCNN total loss: 0.12764 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.14264 RPN box loss: 0.0029 RPN score loss: 0.00142 RPN total loss: 0.00432 Total loss: 0.86208 timestamp: 1654978904.0620546 iteration: 83085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.096 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.1718 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.14029 RPN box loss: 0.01776 RPN score loss: 0.00841 RPN total loss: 0.02617 Total loss: 0.92573 timestamp: 1654978907.2363553 iteration: 83090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06311 FastRCNN class loss: 0.03905 FastRCNN total loss: 0.10217 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.11992 RPN box loss: 0.0105 RPN score loss: 0.00147 RPN total loss: 0.01196 Total loss: 0.82153 timestamp: 1654978910.453376 iteration: 83095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07993 FastRCNN class loss: 0.0719 FastRCNN total loss: 0.15183 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.20471 RPN box loss: 0.01035 RPN score loss: 0.00238 RPN total loss: 0.01273 Total loss: 0.95675 timestamp: 1654978913.6777773 iteration: 83100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0562 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.13732 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.15543 RPN box loss: 0.00646 RPN score loss: 0.0106 RPN total loss: 0.01706 Total loss: 0.89728 timestamp: 1654978916.9766161 iteration: 83105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10598 FastRCNN class loss: 0.10891 FastRCNN total loss: 0.21489 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.1674 RPN box loss: 0.02367 RPN score loss: 0.0045 RPN total loss: 0.02817 Total loss: 0.99794 timestamp: 1654978920.1772113 iteration: 83110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10287 FastRCNN class loss: 0.09154 FastRCNN total loss: 0.19441 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 4.0000e-05 Mask loss: 0.13329 RPN box loss: 0.01209 RPN score loss: 0.00209 RPN total loss: 0.01419 Total loss: 0.92936 timestamp: 1654978923.306662 iteration: 83115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1004 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.15899 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11614 RPN box loss: 0.01765 RPN score loss: 0.00864 RPN total loss: 0.02629 Total loss: 0.8889 timestamp: 1654978926.4847462 iteration: 83120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08952 FastRCNN class loss: 0.06808 FastRCNN total loss: 0.1576 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.10605 RPN box loss: 0.0083 RPN score loss: 0.00639 RPN total loss: 0.01469 Total loss: 0.86581 timestamp: 1654978929.635946 iteration: 83125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05601 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.11447 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.08608 RPN box loss: 0.00814 RPN score loss: 0.00184 RPN total loss: 0.00998 Total loss: 0.79801 timestamp: 1654978932.858016 iteration: 83130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03191 FastRCNN class loss: 0.02965 FastRCNN total loss: 0.06155 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.07371 RPN box loss: 0.02375 RPN score loss: 0.00198 RPN total loss: 0.02572 Total loss: 0.74847 timestamp: 1654978936.0419936 iteration: 83135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08665 FastRCNN class loss: 0.05359 FastRCNN total loss: 0.14023 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13382 RPN box loss: 0.00814 RPN score loss: 0.00373 RPN total loss: 0.01187 Total loss: 0.8734 timestamp: 1654978939.207556 iteration: 83140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08606 FastRCNN class loss: 0.08877 FastRCNN total loss: 0.17483 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.16757 RPN box loss: 0.01602 RPN score loss: 0.00983 RPN total loss: 0.02585 Total loss: 0.95572 timestamp: 1654978942.440235 iteration: 83145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10937 FastRCNN class loss: 0.09417 FastRCNN total loss: 0.20354 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.15671 RPN box loss: 0.02652 RPN score loss: 0.00732 RPN total loss: 0.03383 Total loss: 0.98155 timestamp: 1654978945.6504326 iteration: 83150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.10885 FastRCNN total loss: 0.19482 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.12886 RPN box loss: 0.00907 RPN score loss: 0.0073 RPN total loss: 0.01637 Total loss: 0.92752 timestamp: 1654978948.8710046 iteration: 83155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07396 FastRCNN class loss: 0.04739 FastRCNN total loss: 0.12134 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.12129 RPN box loss: 0.01018 RPN score loss: 0.00164 RPN total loss: 0.01181 Total loss: 0.84192 timestamp: 1654978952.056041 iteration: 83160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06014 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.13125 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14114 RPN box loss: 0.01298 RPN score loss: 0.01049 RPN total loss: 0.02347 Total loss: 0.88334 timestamp: 1654978955.2439997 iteration: 83165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08825 FastRCNN class loss: 0.063 FastRCNN total loss: 0.15125 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13883 RPN box loss: 0.00776 RPN score loss: 0.00824 RPN total loss: 0.016 Total loss: 0.89355 timestamp: 1654978958.498179 iteration: 83170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07665 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.14888 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13075 RPN box loss: 0.02152 RPN score loss: 0.0058 RPN total loss: 0.02732 Total loss: 0.89442 timestamp: 1654978961.718388 iteration: 83175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08284 FastRCNN class loss: 0.09304 FastRCNN total loss: 0.17588 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13713 RPN box loss: 0.02006 RPN score loss: 0.00588 RPN total loss: 0.02594 Total loss: 0.92642 timestamp: 1654978964.9468048 iteration: 83180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09324 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.18368 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.19481 RPN box loss: 0.01485 RPN score loss: 0.00508 RPN total loss: 0.01993 Total loss: 0.9859 timestamp: 1654978968.1791298 iteration: 83185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11418 FastRCNN class loss: 0.11781 FastRCNN total loss: 0.23199 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14378 RPN box loss: 0.01198 RPN score loss: 0.0102 RPN total loss: 0.02218 Total loss: 0.98542 timestamp: 1654978971.3350215 iteration: 83190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07613 FastRCNN class loss: 0.09396 FastRCNN total loss: 0.17008 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.16388 RPN box loss: 0.02045 RPN score loss: 0.01798 RPN total loss: 0.03842 Total loss: 0.95986 timestamp: 1654978974.5528166 iteration: 83195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12354 FastRCNN class loss: 0.09073 FastRCNN total loss: 0.21428 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13335 RPN box loss: 0.0086 RPN score loss: 0.00279 RPN total loss: 0.01139 Total loss: 0.94649 timestamp: 1654978977.7875724 iteration: 83200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11525 FastRCNN class loss: 0.08321 FastRCNN total loss: 0.19846 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.156 RPN box loss: 0.022 RPN score loss: 0.00395 RPN total loss: 0.02595 Total loss: 0.96788 timestamp: 1654978981.0713813 iteration: 83205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10145 FastRCNN class loss: 0.06268 FastRCNN total loss: 0.16412 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14823 RPN box loss: 0.00949 RPN score loss: 0.00632 RPN total loss: 0.01581 Total loss: 0.91563 timestamp: 1654978984.3125803 iteration: 83210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03679 FastRCNN class loss: 0.04875 FastRCNN total loss: 0.08554 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.09377 RPN box loss: 0.0016 RPN score loss: 0.00026 RPN total loss: 0.00186 Total loss: 0.76863 timestamp: 1654978987.484548 iteration: 83215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12487 FastRCNN class loss: 0.09019 FastRCNN total loss: 0.21506 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14916 RPN box loss: 0.01127 RPN score loss: 0.0041 RPN total loss: 0.01537 Total loss: 0.96706 timestamp: 1654978990.762078 iteration: 83220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09011 FastRCNN class loss: 0.08032 FastRCNN total loss: 0.17043 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.18914 RPN box loss: 0.01455 RPN score loss: 0.0032 RPN total loss: 0.01775 Total loss: 0.96479 timestamp: 1654978993.9203799 iteration: 83225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08122 FastRCNN class loss: 0.04745 FastRCNN total loss: 0.12867 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14239 RPN box loss: 0.01042 RPN score loss: 0.00601 RPN total loss: 0.01644 Total loss: 0.87497 timestamp: 1654978997.0971317 iteration: 83230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09083 FastRCNN class loss: 0.06903 FastRCNN total loss: 0.15986 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.07581 RPN box loss: 0.00505 RPN score loss: 0.0034 RPN total loss: 0.00845 Total loss: 0.83159 timestamp: 1654979000.3245583 iteration: 83235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06877 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.12852 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.12395 RPN box loss: 0.0142 RPN score loss: 0.00387 RPN total loss: 0.01807 Total loss: 0.85801 timestamp: 1654979003.4500718 iteration: 83240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.17196 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.20161 RPN box loss: 0.00677 RPN score loss: 0.00308 RPN total loss: 0.00985 Total loss: 0.97089 timestamp: 1654979006.635941 iteration: 83245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05487 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.10982 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.0941 RPN box loss: 0.0089 RPN score loss: 0.00768 RPN total loss: 0.01659 Total loss: 0.80798 timestamp: 1654979009.8703651 iteration: 83250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09303 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.17393 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.1335 RPN box loss: 0.02043 RPN score loss: 0.005 RPN total loss: 0.02543 Total loss: 0.92033 timestamp: 1654979013.0274012 iteration: 83255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13386 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.20967 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13064 RPN box loss: 0.00758 RPN score loss: 0.00441 RPN total loss: 0.01199 Total loss: 0.93977 timestamp: 1654979016.2173803 iteration: 83260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06907 FastRCNN class loss: 0.0537 FastRCNN total loss: 0.12277 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.08516 RPN box loss: 0.00463 RPN score loss: 0.00428 RPN total loss: 0.00892 Total loss: 0.80431 timestamp: 1654979019.4502997 iteration: 83265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07621 FastRCNN class loss: 0.0535 FastRCNN total loss: 0.12971 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.10098 RPN box loss: 0.01073 RPN score loss: 0.0025 RPN total loss: 0.01324 Total loss: 0.83139 timestamp: 1654979022.6089506 iteration: 83270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10415 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.1812 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.1728 RPN box loss: 0.01691 RPN score loss: 0.01045 RPN total loss: 0.02736 Total loss: 0.96883 timestamp: 1654979025.7401729 iteration: 83275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11512 FastRCNN class loss: 0.08242 FastRCNN total loss: 0.19754 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.15904 RPN box loss: 0.02687 RPN score loss: 0.0058 RPN total loss: 0.03267 Total loss: 0.97672 timestamp: 1654979028.9721274 iteration: 83280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06863 FastRCNN class loss: 0.05767 FastRCNN total loss: 0.1263 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.08774 RPN box loss: 0.00944 RPN score loss: 0.00184 RPN total loss: 0.01128 Total loss: 0.81279 timestamp: 1654979032.1606722 iteration: 83285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06985 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.14297 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13844 RPN box loss: 0.02613 RPN score loss: 0.00409 RPN total loss: 0.03022 Total loss: 0.89911 timestamp: 1654979035.3497777 iteration: 83290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09018 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.15069 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13634 RPN box loss: 0.01624 RPN score loss: 0.00847 RPN total loss: 0.02471 Total loss: 0.89921 timestamp: 1654979038.5640953 iteration: 83295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07423 FastRCNN class loss: 0.10375 FastRCNN total loss: 0.17798 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.12444 RPN box loss: 0.0068 RPN score loss: 0.0011 RPN total loss: 0.0079 Total loss: 0.89778 timestamp: 1654979041.689059 iteration: 83300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08723 FastRCNN class loss: 0.07849 FastRCNN total loss: 0.16573 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.10629 RPN box loss: 0.01184 RPN score loss: 0.0067 RPN total loss: 0.01854 Total loss: 0.87802 timestamp: 1654979044.8788207 iteration: 83305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10024 FastRCNN class loss: 0.09659 FastRCNN total loss: 0.19683 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.12363 RPN box loss: 0.012 RPN score loss: 0.0072 RPN total loss: 0.0192 Total loss: 0.92714 timestamp: 1654979048.0936139 iteration: 83310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09998 FastRCNN class loss: 0.07256 FastRCNN total loss: 0.17254 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.19859 RPN box loss: 0.02139 RPN score loss: 0.00454 RPN total loss: 0.02593 Total loss: 0.98453 timestamp: 1654979051.2676017 iteration: 83315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0786 FastRCNN class loss: 0.08595 FastRCNN total loss: 0.16455 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.15837 RPN box loss: 0.00829 RPN score loss: 0.00299 RPN total loss: 0.01127 Total loss: 0.92166 timestamp: 1654979054.445311 iteration: 83320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12142 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.19771 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14745 RPN box loss: 0.00555 RPN score loss: 0.0017 RPN total loss: 0.00725 Total loss: 0.93988 timestamp: 1654979057.5921035 iteration: 83325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07181 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.13587 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13236 RPN box loss: 0.00589 RPN score loss: 0.00197 RPN total loss: 0.00786 Total loss: 0.86356 timestamp: 1654979060.7979891 iteration: 83330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11687 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.1969 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11592 RPN box loss: 0.00824 RPN score loss: 0.00251 RPN total loss: 0.01075 Total loss: 0.91104 timestamp: 1654979064.02383 iteration: 83335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09721 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.17357 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13265 RPN box loss: 0.0087 RPN score loss: 0.0087 RPN total loss: 0.0174 Total loss: 0.91109 timestamp: 1654979067.2696536 iteration: 83340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04157 FastRCNN class loss: 0.053 FastRCNN total loss: 0.09457 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.10383 RPN box loss: 0.00384 RPN score loss: 0.00406 RPN total loss: 0.00789 Total loss: 0.79377 timestamp: 1654979070.5091078 iteration: 83345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.0628 FastRCNN total loss: 0.17342 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.1351 RPN box loss: 0.00274 RPN score loss: 0.00161 RPN total loss: 0.00435 Total loss: 0.90035 timestamp: 1654979073.7544544 iteration: 83350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06636 FastRCNN class loss: 0.07656 FastRCNN total loss: 0.14293 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.12491 RPN box loss: 0.01358 RPN score loss: 0.00377 RPN total loss: 0.01735 Total loss: 0.87265 timestamp: 1654979077.0613947 iteration: 83355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0952 FastRCNN class loss: 0.05433 FastRCNN total loss: 0.14953 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.19828 RPN box loss: 0.03408 RPN score loss: 0.00819 RPN total loss: 0.04227 Total loss: 0.97755 timestamp: 1654979080.2944953 iteration: 83360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08631 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.16762 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11505 RPN box loss: 0.03247 RPN score loss: 0.00682 RPN total loss: 0.03929 Total loss: 0.90942 timestamp: 1654979083.5871358 iteration: 83365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06365 FastRCNN class loss: 0.08243 FastRCNN total loss: 0.14608 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.15111 RPN box loss: 0.00642 RPN score loss: 0.00595 RPN total loss: 0.01237 Total loss: 0.89703 timestamp: 1654979086.8432958 iteration: 83370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08115 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.16166 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.15904 RPN box loss: 0.01119 RPN score loss: 0.0062 RPN total loss: 0.0174 Total loss: 0.92557 timestamp: 1654979090.0460966 iteration: 83375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.0454 FastRCNN total loss: 0.12852 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.09111 RPN box loss: 0.0226 RPN score loss: 0.0021 RPN total loss: 0.0247 Total loss: 0.8318 timestamp: 1654979093.213688 iteration: 83380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10151 FastRCNN class loss: 0.0436 FastRCNN total loss: 0.1451 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11138 RPN box loss: 0.0061 RPN score loss: 0.00132 RPN total loss: 0.00742 Total loss: 0.85137 timestamp: 1654979096.4145381 iteration: 83385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05567 FastRCNN class loss: 0.0502 FastRCNN total loss: 0.10587 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11233 RPN box loss: 0.01232 RPN score loss: 0.00177 RPN total loss: 0.0141 Total loss: 0.81976 timestamp: 1654979099.6404717 iteration: 83390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0899 FastRCNN class loss: 0.07285 FastRCNN total loss: 0.16275 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.14579 RPN box loss: 0.0068 RPN score loss: 0.00859 RPN total loss: 0.01539 Total loss: 0.91139 timestamp: 1654979102.8886065 iteration: 83395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10577 FastRCNN class loss: 0.07801 FastRCNN total loss: 0.18378 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.17411 RPN box loss: 0.02123 RPN score loss: 0.00237 RPN total loss: 0.0236 Total loss: 0.96896 timestamp: 1654979106.132615 iteration: 83400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10862 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.17121 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11558 RPN box loss: 0.00951 RPN score loss: 0.00222 RPN total loss: 0.01173 Total loss: 0.88599 timestamp: 1654979109.2954836 iteration: 83405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05329 FastRCNN class loss: 0.04479 FastRCNN total loss: 0.09808 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11688 RPN box loss: 0.0238 RPN score loss: 0.00569 RPN total loss: 0.02949 Total loss: 0.83191 timestamp: 1654979112.462857 iteration: 83410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05361 FastRCNN class loss: 0.06513 FastRCNN total loss: 0.11874 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.11357 RPN box loss: 0.0116 RPN score loss: 0.00123 RPN total loss: 0.01283 Total loss: 0.83261 timestamp: 1654979115.721419 iteration: 83415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06927 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.1281 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.13804 RPN box loss: 0.01204 RPN score loss: 0.01161 RPN total loss: 0.02365 Total loss: 0.87725 timestamp: 1654979118.8503263 iteration: 83420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0554 FastRCNN class loss: 0.05798 FastRCNN total loss: 0.11337 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 4.0000e-05 Mask loss: 0.18445 RPN box loss: 0.00556 RPN score loss: 0.00396 RPN total loss: 0.00952 Total loss: 0.89481 timestamp: 1654979122.0211515 iteration: 83425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10223 FastRCNN class loss: 0.09418 FastRCNN total loss: 0.19641 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.17105 RPN box loss: 0.01207 RPN score loss: 0.00912 RPN total loss: 0.02119 Total loss: 0.97612 timestamp: 1654979125.2694705 iteration: 83430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06447 FastRCNN class loss: 0.04684 FastRCNN total loss: 0.11131 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09223 RPN box loss: 0.01261 RPN score loss: 0.0063 RPN total loss: 0.01891 Total loss: 0.80992 timestamp: 1654979128.4319544 iteration: 83435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09287 FastRCNN class loss: 0.08826 FastRCNN total loss: 0.18113 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10533 RPN box loss: 0.008 RPN score loss: 0.00899 RPN total loss: 0.01699 Total loss: 0.89092 timestamp: 1654979131.6776092 iteration: 83440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07415 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.14523 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.16971 RPN box loss: 0.0132 RPN score loss: 0.00231 RPN total loss: 0.01551 Total loss: 0.91791 timestamp: 1654979134.8817065 iteration: 83445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08227 FastRCNN class loss: 0.0602 FastRCNN total loss: 0.14247 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.15833 RPN box loss: 0.00383 RPN score loss: 0.00447 RPN total loss: 0.00831 Total loss: 0.89658 timestamp: 1654979138.0479252 iteration: 83450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08911 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.13544 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10777 RPN box loss: 0.00331 RPN score loss: 0.00307 RPN total loss: 0.00638 Total loss: 0.83705 timestamp: 1654979141.303137 iteration: 83455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07804 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.13705 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09016 RPN box loss: 0.0089 RPN score loss: 0.00171 RPN total loss: 0.0106 Total loss: 0.82528 timestamp: 1654979144.4990044 iteration: 83460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0779 FastRCNN class loss: 0.06348 FastRCNN total loss: 0.14138 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.13081 RPN box loss: 0.01577 RPN score loss: 0.00622 RPN total loss: 0.02199 Total loss: 0.88165 timestamp: 1654979147.6636927 iteration: 83465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14454 FastRCNN class loss: 0.09973 FastRCNN total loss: 0.24427 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.17116 RPN box loss: 0.01691 RPN score loss: 0.00614 RPN total loss: 0.02305 Total loss: 1.02595 timestamp: 1654979150.9445505 iteration: 83470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08031 FastRCNN class loss: 0.03736 FastRCNN total loss: 0.11767 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.16787 RPN box loss: 0.00592 RPN score loss: 0.00487 RPN total loss: 0.01079 Total loss: 0.88379 timestamp: 1654979154.1408055 iteration: 83475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08074 FastRCNN class loss: 0.09338 FastRCNN total loss: 0.17413 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.18436 RPN box loss: 0.01382 RPN score loss: 0.01453 RPN total loss: 0.02836 Total loss: 0.97431 timestamp: 1654979157.34452 iteration: 83480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11212 FastRCNN class loss: 0.09988 FastRCNN total loss: 0.212 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.13683 RPN box loss: 0.0177 RPN score loss: 0.00922 RPN total loss: 0.02693 Total loss: 0.96322 timestamp: 1654979160.5247183 iteration: 83485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07759 FastRCNN class loss: 0.08943 FastRCNN total loss: 0.16701 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12213 RPN box loss: 0.01253 RPN score loss: 0.00531 RPN total loss: 0.01784 Total loss: 0.89444 timestamp: 1654979163.712206 iteration: 83490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07343 FastRCNN class loss: 0.06851 FastRCNN total loss: 0.14195 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.1257 RPN box loss: 0.00663 RPN score loss: 0.00191 RPN total loss: 0.00854 Total loss: 0.86365 timestamp: 1654979166.9854548 iteration: 83495 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07582 FastRCNN class loss: 0.06207 FastRCNN total loss: 0.13789 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.08871 RPN box loss: 0.00489 RPN score loss: 0.00399 RPN total loss: 0.00888 Total loss: 0.82294 timestamp: 1654979170.1960237 iteration: 83500 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07022 FastRCNN class loss: 0.05103 FastRCNN total loss: 0.12125 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.13169 RPN box loss: 0.0109 RPN score loss: 0.00264 RPN total loss: 0.01354 Total loss: 0.85394 timestamp: 1654979173.386699 iteration: 83505 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08883 FastRCNN class loss: 0.0587 FastRCNN total loss: 0.14753 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10156 RPN box loss: 0.00497 RPN score loss: 0.00116 RPN total loss: 0.00613 Total loss: 0.84268 timestamp: 1654979176.6215534 iteration: 83510 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11085 FastRCNN class loss: 0.08017 FastRCNN total loss: 0.19102 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.04033 RPN score loss: 0.01572 RPN total loss: 0.05605 Total loss: 0.99094 timestamp: 1654979179.8423157 iteration: 83515 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06084 FastRCNN class loss: 0.0485 FastRCNN total loss: 0.10934 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12553 RPN box loss: 0.01084 RPN score loss: 0.01005 RPN total loss: 0.02089 Total loss: 0.84322 timestamp: 1654979183.0558224 iteration: 83520 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05973 FastRCNN class loss: 0.03829 FastRCNN total loss: 0.09802 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.15143 RPN box loss: 0.00736 RPN score loss: 0.0032 RPN total loss: 0.01057 Total loss: 0.84747 timestamp: 1654979186.2021897 iteration: 83525 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08121 FastRCNN class loss: 0.05254 FastRCNN total loss: 0.13376 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09142 RPN box loss: 0.01409 RPN score loss: 0.001 RPN total loss: 0.01509 Total loss: 0.82772 timestamp: 1654979189.37644 iteration: 83530 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08125 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.13878 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.13942 RPN box loss: 0.00669 RPN score loss: 0.00101 RPN total loss: 0.0077 Total loss: 0.87336 timestamp: 1654979192.661589 iteration: 83535 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.09227 FastRCNN total loss: 0.17643 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.13885 RPN box loss: 0.01272 RPN score loss: 0.00687 RPN total loss: 0.01959 Total loss: 0.92234 timestamp: 1654979195.8399754 iteration: 83540 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08645 FastRCNN class loss: 0.08486 FastRCNN total loss: 0.17132 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.16506 RPN box loss: 0.00841 RPN score loss: 0.00229 RPN total loss: 0.0107 Total loss: 0.93454 timestamp: 1654979199.0578618 iteration: 83545 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04819 FastRCNN class loss: 0.04501 FastRCNN total loss: 0.0932 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09481 RPN box loss: 0.01405 RPN score loss: 0.00115 RPN total loss: 0.0152 Total loss: 0.79068 timestamp: 1654979202.231848 iteration: 83550 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08519 FastRCNN class loss: 0.05755 FastRCNN total loss: 0.14274 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10749 RPN box loss: 0.00638 RPN score loss: 0.00184 RPN total loss: 0.00822 Total loss: 0.84592 timestamp: 1654979205.4610147 iteration: 83555 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03916 FastRCNN class loss: 0.04514 FastRCNN total loss: 0.0843 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.14732 RPN box loss: 0.02256 RPN score loss: 0.00208 RPN total loss: 0.02465 Total loss: 0.84373 timestamp: 1654979208.7342536 iteration: 83560 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07395 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.12988 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09554 RPN box loss: 0.00438 RPN score loss: 0.006 RPN total loss: 0.01038 Total loss: 0.82327 timestamp: 1654979211.8648648 iteration: 83565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.07759 FastRCNN total loss: 0.17807 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12364 RPN box loss: 0.01833 RPN score loss: 0.01233 RPN total loss: 0.03066 Total loss: 0.91983 timestamp: 1654979215.0613215 iteration: 83570 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07249 FastRCNN class loss: 0.05261 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12188 RPN box loss: 0.04188 RPN score loss: 0.00353 RPN total loss: 0.04541 Total loss: 0.87985 timestamp: 1654979218.293042 iteration: 83575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06869 FastRCNN class loss: 0.04607 FastRCNN total loss: 0.11476 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09078 RPN box loss: 0.00522 RPN score loss: 0.00329 RPN total loss: 0.00851 Total loss: 0.80151 timestamp: 1654979221.5328612 iteration: 83580 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09981 FastRCNN class loss: 0.06596 FastRCNN total loss: 0.16578 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.11128 RPN box loss: 0.00623 RPN score loss: 0.00409 RPN total loss: 0.01032 Total loss: 0.87484 timestamp: 1654979224.7224822 iteration: 83585 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07759 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09361 RPN box loss: 0.01179 RPN score loss: 0.00096 RPN total loss: 0.01275 Total loss: 0.8313 timestamp: 1654979228.0012865 iteration: 83590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10978 FastRCNN class loss: 0.04772 FastRCNN total loss: 0.1575 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12693 RPN box loss: 0.00556 RPN score loss: 0.00217 RPN total loss: 0.00773 Total loss: 0.87962 timestamp: 1654979231.2598453 iteration: 83595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07039 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.19832 RPN box loss: 0.01137 RPN score loss: 0.01078 RPN total loss: 0.02215 Total loss: 0.98986 timestamp: 1654979234.5250702 iteration: 83600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08939 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.16575 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.17784 RPN box loss: 0.01785 RPN score loss: 0.00843 RPN total loss: 0.02628 Total loss: 0.95733 timestamp: 1654979237.7326097 iteration: 83605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05763 FastRCNN class loss: 0.03255 FastRCNN total loss: 0.09018 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.05529 RPN box loss: 0.00753 RPN score loss: 0.0052 RPN total loss: 0.01273 Total loss: 0.74566 timestamp: 1654979240.9822884 iteration: 83610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07599 FastRCNN class loss: 0.04581 FastRCNN total loss: 0.1218 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.11303 RPN box loss: 0.00799 RPN score loss: 0.00072 RPN total loss: 0.00871 Total loss: 0.831 timestamp: 1654979244.156199 iteration: 83615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.10076 FastRCNN total loss: 0.19473 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.14113 RPN box loss: 0.00537 RPN score loss: 0.00201 RPN total loss: 0.00738 Total loss: 0.9307 timestamp: 1654979247.3645663 iteration: 83620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10482 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.16308 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10229 RPN box loss: 0.02042 RPN score loss: 0.00414 RPN total loss: 0.02456 Total loss: 0.87739 timestamp: 1654979250.5438983 iteration: 83625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07963 FastRCNN class loss: 0.0543 FastRCNN total loss: 0.13394 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12882 RPN box loss: 0.01229 RPN score loss: 0.00115 RPN total loss: 0.01344 Total loss: 0.86365 timestamp: 1654979253.6535761 iteration: 83630 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07857 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.15471 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12899 RPN box loss: 0.01098 RPN score loss: 0.00298 RPN total loss: 0.01395 Total loss: 0.88511 timestamp: 1654979256.8381336 iteration: 83635 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12726 FastRCNN class loss: 0.12456 FastRCNN total loss: 0.25182 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.18399 RPN box loss: 0.0255 RPN score loss: 0.01358 RPN total loss: 0.03908 Total loss: 1.06235 timestamp: 1654979260.0456505 iteration: 83640 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.0466 FastRCNN total loss: 0.13332 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09808 RPN box loss: 0.01576 RPN score loss: 0.00051 RPN total loss: 0.01627 Total loss: 0.83513 timestamp: 1654979263.2297142 iteration: 83645 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09652 FastRCNN class loss: 0.08691 FastRCNN total loss: 0.18343 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.1264 RPN box loss: 0.01204 RPN score loss: 0.00936 RPN total loss: 0.02139 Total loss: 0.91869 timestamp: 1654979266.4503603 iteration: 83650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0726 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.13001 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.11963 RPN box loss: 0.00796 RPN score loss: 0.006 RPN total loss: 0.01395 Total loss: 0.85106 timestamp: 1654979269.7604365 iteration: 83655 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10138 FastRCNN class loss: 0.08665 FastRCNN total loss: 0.18803 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.18337 RPN box loss: 0.01017 RPN score loss: 0.00682 RPN total loss: 0.01699 Total loss: 0.97585 timestamp: 1654979272.9387484 iteration: 83660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10809 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.19089 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.09466 RPN box loss: 0.01803 RPN score loss: 0.00822 RPN total loss: 0.02625 Total loss: 0.89927 timestamp: 1654979276.0968268 iteration: 83665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10549 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.19815 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.11968 RPN box loss: 0.00643 RPN score loss: 0.00638 RPN total loss: 0.0128 Total loss: 0.91809 timestamp: 1654979279.3240309 iteration: 83670 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10919 FastRCNN class loss: 0.04573 FastRCNN total loss: 0.15492 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10205 RPN box loss: 0.00681 RPN score loss: 0.00273 RPN total loss: 0.00954 Total loss: 0.85397 timestamp: 1654979282.5290015 iteration: 83675 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09434 FastRCNN class loss: 0.09748 FastRCNN total loss: 0.19182 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.14281 RPN box loss: 0.01141 RPN score loss: 0.00913 RPN total loss: 0.02054 Total loss: 0.94263 timestamp: 1654979285.733536 iteration: 83680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0597 FastRCNN class loss: 0.05069 FastRCNN total loss: 0.11039 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.13736 RPN box loss: 0.00969 RPN score loss: 0.00113 RPN total loss: 0.01083 Total loss: 0.84604 timestamp: 1654979288.9114091 iteration: 83685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04943 FastRCNN class loss: 0.04952 FastRCNN total loss: 0.09895 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12579 RPN box loss: 0.01038 RPN score loss: 0.01765 RPN total loss: 0.02803 Total loss: 0.84023 timestamp: 1654979292.1423926 iteration: 83690 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15922 FastRCNN class loss: 0.1097 FastRCNN total loss: 0.26891 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.14427 RPN box loss: 0.01582 RPN score loss: 0.00243 RPN total loss: 0.01825 Total loss: 1.01889 timestamp: 1654979295.2970645 iteration: 83695 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08927 FastRCNN class loss: 0.04493 FastRCNN total loss: 0.1342 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.1115 RPN box loss: 0.00404 RPN score loss: 0.0022 RPN total loss: 0.00624 Total loss: 0.8394 timestamp: 1654979298.5129929 iteration: 83700 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10627 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.18219 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.15718 RPN box loss: 0.01816 RPN score loss: 0.01405 RPN total loss: 0.03221 Total loss: 0.95904 timestamp: 1654979301.7270832 iteration: 83705 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07921 FastRCNN class loss: 0.04573 FastRCNN total loss: 0.12494 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.08224 RPN box loss: 0.00476 RPN score loss: 0.00518 RPN total loss: 0.00994 Total loss: 0.80457 timestamp: 1654979304.870154 iteration: 83710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08575 FastRCNN class loss: 0.07375 FastRCNN total loss: 0.1595 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.2076 RPN box loss: 0.01583 RPN score loss: 0.00335 RPN total loss: 0.01917 Total loss: 0.97373 timestamp: 1654979308.0258412 iteration: 83715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06606 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.1256 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10935 RPN box loss: 0.00719 RPN score loss: 0.00439 RPN total loss: 0.01158 Total loss: 0.83399 timestamp: 1654979311.1598408 iteration: 83720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09498 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.16239 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.11426 RPN box loss: 0.00629 RPN score loss: 0.00258 RPN total loss: 0.00887 Total loss: 0.87298 timestamp: 1654979314.384853 iteration: 83725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09723 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.19309 RPN box loss: 0.01032 RPN score loss: 0.01087 RPN total loss: 0.02119 Total loss: 0.97362 timestamp: 1654979317.6630113 iteration: 83730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09246 FastRCNN class loss: 0.08207 FastRCNN total loss: 0.17452 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.17311 RPN box loss: 0.00578 RPN score loss: 0.00359 RPN total loss: 0.00937 Total loss: 0.94446 timestamp: 1654979320.8567483 iteration: 83735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05455 FastRCNN class loss: 0.06695 FastRCNN total loss: 0.1215 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.12802 RPN box loss: 0.01252 RPN score loss: 0.004 RPN total loss: 0.01652 Total loss: 0.8535 timestamp: 1654979324.1308188 iteration: 83740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07277 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.13269 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.10422 RPN box loss: 0.00545 RPN score loss: 0.0015 RPN total loss: 0.00696 Total loss: 0.83133 timestamp: 1654979327.3041637 iteration: 83745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10316 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.16048 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 4.0000e-05 Mask loss: 0.14039 RPN box loss: 0.00579 RPN score loss: 0.00199 RPN total loss: 0.00779 Total loss: 0.89612 timestamp: 1654979330.4908695 iteration: 83750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14749 FastRCNN class loss: 0.0737 FastRCNN total loss: 0.22118 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.13028 RPN box loss: 0.0164 RPN score loss: 0.00546 RPN total loss: 0.02186 Total loss: 0.96077 timestamp: 1654979333.648213 iteration: 83755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07488 FastRCNN class loss: 0.04178 FastRCNN total loss: 0.11666 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12918 RPN box loss: 0.01051 RPN score loss: 0.00157 RPN total loss: 0.01208 Total loss: 0.84537 timestamp: 1654979336.7900972 iteration: 83760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07106 FastRCNN class loss: 0.0596 FastRCNN total loss: 0.13066 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.14242 RPN box loss: 0.0148 RPN score loss: 0.00482 RPN total loss: 0.01962 Total loss: 0.88015 timestamp: 1654979340.077616 iteration: 83765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09343 FastRCNN class loss: 0.05513 FastRCNN total loss: 0.14856 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.13532 RPN box loss: 0.0044 RPN score loss: 0.00581 RPN total loss: 0.01021 Total loss: 0.88154 timestamp: 1654979343.2589889 iteration: 83770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.05645 FastRCNN total loss: 0.15681 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.1348 RPN box loss: 0.02678 RPN score loss: 0.0032 RPN total loss: 0.02999 Total loss: 0.90906 timestamp: 1654979346.4811182 iteration: 83775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08924 FastRCNN class loss: 0.0632 FastRCNN total loss: 0.15244 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12972 RPN box loss: 0.00929 RPN score loss: 0.01032 RPN total loss: 0.01961 Total loss: 0.88923 timestamp: 1654979349.6198714 iteration: 83780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08511 FastRCNN class loss: 0.07568 FastRCNN total loss: 0.16079 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.07607 RPN box loss: 0.01617 RPN score loss: 0.00186 RPN total loss: 0.01803 Total loss: 0.84235 timestamp: 1654979352.791098 iteration: 83785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1073 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.1827 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.17464 RPN box loss: 0.00862 RPN score loss: 0.01538 RPN total loss: 0.024 Total loss: 0.96879 timestamp: 1654979355.9330132 iteration: 83790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11389 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.18508 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.19121 RPN box loss: 0.01594 RPN score loss: 0.00823 RPN total loss: 0.02417 Total loss: 0.98791 timestamp: 1654979359.0879765 iteration: 83795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13673 FastRCNN class loss: 0.07792 FastRCNN total loss: 0.21465 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.10416 RPN box loss: 0.01482 RPN score loss: 0.00229 RPN total loss: 0.01711 Total loss: 0.92338 timestamp: 1654979362.3272395 iteration: 83800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11141 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.17906 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12596 RPN box loss: 0.01179 RPN score loss: 0.0019 RPN total loss: 0.01369 Total loss: 0.90617 timestamp: 1654979365.527398 iteration: 83805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11377 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.214 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.22133 RPN box loss: 0.01621 RPN score loss: 0.00614 RPN total loss: 0.02235 Total loss: 1.04513 timestamp: 1654979368.7143972 iteration: 83810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0878 FastRCNN class loss: 0.10054 FastRCNN total loss: 0.18834 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.10755 RPN box loss: 0.01198 RPN score loss: 0.00207 RPN total loss: 0.01405 Total loss: 0.8974 timestamp: 1654979371.9041667 iteration: 83815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06299 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.12465 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.09797 RPN box loss: 0.0257 RPN score loss: 0.00268 RPN total loss: 0.02838 Total loss: 0.83845 timestamp: 1654979375.1208034 iteration: 83820 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07235 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.13622 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.136 RPN box loss: 0.03356 RPN score loss: 0.0012 RPN total loss: 0.03476 Total loss: 0.89444 timestamp: 1654979378.2613199 iteration: 83825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12759 FastRCNN class loss: 0.10215 FastRCNN total loss: 0.22974 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.1527 RPN box loss: 0.05861 RPN score loss: 0.01147 RPN total loss: 0.07008 Total loss: 1.03997 timestamp: 1654979381.4693456 iteration: 83830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04933 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.10982 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.07959 RPN box loss: 0.00629 RPN score loss: 0.00356 RPN total loss: 0.00985 Total loss: 0.78671 timestamp: 1654979384.6564217 iteration: 83835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10127 FastRCNN class loss: 0.08424 FastRCNN total loss: 0.18551 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.0996 RPN box loss: 0.00894 RPN score loss: 0.00381 RPN total loss: 0.01275 Total loss: 0.88531 timestamp: 1654979387.89661 iteration: 83840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.059 FastRCNN class loss: 0.03803 FastRCNN total loss: 0.09703 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.08712 RPN box loss: 0.00714 RPN score loss: 0.00377 RPN total loss: 0.01091 Total loss: 0.78252 timestamp: 1654979391.0712588 iteration: 83845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07525 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.14191 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.13899 RPN box loss: 0.0104 RPN score loss: 0.00482 RPN total loss: 0.01521 Total loss: 0.88356 timestamp: 1654979394.225089 iteration: 83850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11049 FastRCNN class loss: 0.04087 FastRCNN total loss: 0.15136 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.0814 RPN box loss: 0.00501 RPN score loss: 0.00198 RPN total loss: 0.00698 Total loss: 0.82719 timestamp: 1654979397.399319 iteration: 83855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08766 FastRCNN class loss: 0.06466 FastRCNN total loss: 0.15232 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.13307 RPN box loss: 0.00463 RPN score loss: 0.00086 RPN total loss: 0.00549 Total loss: 0.87834 timestamp: 1654979400.58006 iteration: 83860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05453 FastRCNN class loss: 0.0811 FastRCNN total loss: 0.13563 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.13883 RPN box loss: 0.00691 RPN score loss: 0.00226 RPN total loss: 0.00916 Total loss: 0.87107 timestamp: 1654979403.825765 iteration: 83865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04736 FastRCNN class loss: 0.0461 FastRCNN total loss: 0.09346 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.11666 RPN box loss: 0.00579 RPN score loss: 0.00251 RPN total loss: 0.0083 Total loss: 0.80586 timestamp: 1654979407.033041 iteration: 83870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07379 FastRCNN class loss: 0.06252 FastRCNN total loss: 0.13631 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.13465 RPN box loss: 0.00667 RPN score loss: 0.00277 RPN total loss: 0.00945 Total loss: 0.86786 timestamp: 1654979410.4090452 iteration: 83875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09057 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.15836 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.14012 RPN box loss: 0.01221 RPN score loss: 0.00747 RPN total loss: 0.01968 Total loss: 0.90561 timestamp: 1654979413.6604996 iteration: 83880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10491 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.17166 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.16853 RPN box loss: 0.00655 RPN score loss: 0.00608 RPN total loss: 0.01262 Total loss: 0.94027 timestamp: 1654979416.8605368 iteration: 83885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05301 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.10316 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.15885 RPN box loss: 0.00279 RPN score loss: 0.00465 RPN total loss: 0.00745 Total loss: 0.8569 timestamp: 1654979420.0650344 iteration: 83890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07622 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.13575 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.19006 RPN box loss: 0.00861 RPN score loss: 0.00645 RPN total loss: 0.01506 Total loss: 0.92832 timestamp: 1654979423.2236974 iteration: 83895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09426 FastRCNN class loss: 0.05765 FastRCNN total loss: 0.15191 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.14608 RPN box loss: 0.02878 RPN score loss: 0.00095 RPN total loss: 0.02973 Total loss: 0.91517 timestamp: 1654979426.3407438 iteration: 83900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07193 FastRCNN class loss: 0.05042 FastRCNN total loss: 0.12235 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12346 RPN box loss: 0.02621 RPN score loss: 0.00416 RPN total loss: 0.03037 Total loss: 0.86363 timestamp: 1654979429.485327 iteration: 83905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07476 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.13883 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.10201 RPN box loss: 0.009 RPN score loss: 0.00142 RPN total loss: 0.01043 Total loss: 0.83872 timestamp: 1654979432.693181 iteration: 83910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08713 FastRCNN class loss: 0.0886 FastRCNN total loss: 0.17573 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.1526 RPN box loss: 0.01243 RPN score loss: 0.00517 RPN total loss: 0.0176 Total loss: 0.93338 timestamp: 1654979435.9188302 iteration: 83915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09973 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.18366 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.09484 RPN box loss: 0.00634 RPN score loss: 0.00577 RPN total loss: 0.01211 Total loss: 0.87806 timestamp: 1654979439.1407936 iteration: 83920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12909 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.18959 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.17437 RPN box loss: 0.01429 RPN score loss: 0.00774 RPN total loss: 0.02203 Total loss: 0.97344 timestamp: 1654979442.3089638 iteration: 83925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08217 FastRCNN class loss: 0.05509 FastRCNN total loss: 0.13727 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.11128 RPN box loss: 0.00594 RPN score loss: 0.00216 RPN total loss: 0.0081 Total loss: 0.84409 timestamp: 1654979445.5426636 iteration: 83930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05555 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.10833 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.08107 RPN box loss: 0.01705 RPN score loss: 0.00357 RPN total loss: 0.02062 Total loss: 0.79747 timestamp: 1654979448.7704713 iteration: 83935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12748 FastRCNN class loss: 0.07265 FastRCNN total loss: 0.20013 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.17597 RPN box loss: 0.00537 RPN score loss: 0.00561 RPN total loss: 0.01098 Total loss: 0.97453 timestamp: 1654979451.9316342 iteration: 83940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08423 FastRCNN class loss: 0.06113 FastRCNN total loss: 0.14536 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12863 RPN box loss: 0.01294 RPN score loss: 0.0067 RPN total loss: 0.01964 Total loss: 0.88107 timestamp: 1654979455.14802 iteration: 83945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0784 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.1447 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.15483 RPN box loss: 0.01102 RPN score loss: 0.00172 RPN total loss: 0.01274 Total loss: 0.89971 timestamp: 1654979458.2934024 iteration: 83950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.11409 FastRCNN total loss: 0.21689 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.11721 RPN box loss: 0.00863 RPN score loss: 0.00891 RPN total loss: 0.01754 Total loss: 0.93909 timestamp: 1654979461.4988463 iteration: 83955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10411 FastRCNN class loss: 0.07766 FastRCNN total loss: 0.18177 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.15825 RPN box loss: 0.0068 RPN score loss: 0.00307 RPN total loss: 0.00986 Total loss: 0.93733 timestamp: 1654979464.7233465 iteration: 83960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07636 FastRCNN class loss: 0.06215 FastRCNN total loss: 0.13851 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.11738 RPN box loss: 0.00966 RPN score loss: 0.00376 RPN total loss: 0.01341 Total loss: 0.85675 timestamp: 1654979467.9495068 iteration: 83965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10131 FastRCNN class loss: 0.08464 FastRCNN total loss: 0.18595 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.21042 RPN box loss: 0.01141 RPN score loss: 0.01127 RPN total loss: 0.02268 Total loss: 1.0065 timestamp: 1654979471.1275883 iteration: 83970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09153 FastRCNN class loss: 0.07334 FastRCNN total loss: 0.16487 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.14791 RPN box loss: 0.01273 RPN score loss: 0.00464 RPN total loss: 0.01737 Total loss: 0.9176 timestamp: 1654979474.4348218 iteration: 83975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08595 FastRCNN class loss: 0.08886 FastRCNN total loss: 0.17481 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12099 RPN box loss: 0.01607 RPN score loss: 0.00755 RPN total loss: 0.02362 Total loss: 0.90687 timestamp: 1654979477.6326475 iteration: 83980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07162 FastRCNN class loss: 0.05955 FastRCNN total loss: 0.13117 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.14359 RPN box loss: 0.01509 RPN score loss: 0.00691 RPN total loss: 0.02201 Total loss: 0.88422 timestamp: 1654979480.7753386 iteration: 83985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.05218 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.09041 RPN box loss: 0.00885 RPN score loss: 0.00248 RPN total loss: 0.01133 Total loss: 0.84926 timestamp: 1654979483.9854228 iteration: 83990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11163 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.19483 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.14087 RPN box loss: 0.00858 RPN score loss: 0.00798 RPN total loss: 0.01656 Total loss: 0.93971 timestamp: 1654979487.233148 iteration: 83995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0709 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.13221 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.09819 RPN box loss: 0.01005 RPN score loss: 0.00545 RPN total loss: 0.0155 Total loss: 0.83334 timestamp: 1654979490.3990748 iteration: 84000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12716 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.19504 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.10674 RPN box loss: 0.00941 RPN score loss: 0.00661 RPN total loss: 0.01601 Total loss: 0.90524 timestamp: 1654979493.6138957 iteration: 84005 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08529 FastRCNN class loss: 0.10944 FastRCNN total loss: 0.19474 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.10904 RPN box loss: 0.00599 RPN score loss: 0.00564 RPN total loss: 0.01163 Total loss: 0.90285 timestamp: 1654979496.764285 iteration: 84010 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07646 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.14359 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12079 RPN box loss: 0.02112 RPN score loss: 0.00577 RPN total loss: 0.0269 Total loss: 0.87873 timestamp: 1654979499.9271307 iteration: 84015 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12226 FastRCNN class loss: 0.06026 FastRCNN total loss: 0.18252 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.09328 RPN box loss: 0.00614 RPN score loss: 0.00743 RPN total loss: 0.01357 Total loss: 0.87681 timestamp: 1654979503.121483 iteration: 84020 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07404 FastRCNN class loss: 0.07407 FastRCNN total loss: 0.14811 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12175 RPN box loss: 0.03864 RPN score loss: 0.01084 RPN total loss: 0.04948 Total loss: 0.90678 timestamp: 1654979506.3429942 iteration: 84025 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09423 FastRCNN class loss: 0.0465 FastRCNN total loss: 0.14073 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12203 RPN box loss: 0.01005 RPN score loss: 0.00247 RPN total loss: 0.01252 Total loss: 0.86273 timestamp: 1654979509.611553 iteration: 84030 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10089 FastRCNN class loss: 0.068 FastRCNN total loss: 0.16888 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.1354 RPN box loss: 0.00414 RPN score loss: 0.00186 RPN total loss: 0.006 Total loss: 0.89772 timestamp: 1654979512.8454514 iteration: 84035 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11612 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.1867 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.11755 RPN box loss: 0.01958 RPN score loss: 0.00377 RPN total loss: 0.02335 Total loss: 0.91504 timestamp: 1654979516.023986 iteration: 84040 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11504 FastRCNN class loss: 0.11277 FastRCNN total loss: 0.22781 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.19821 RPN box loss: 0.01044 RPN score loss: 0.01405 RPN total loss: 0.02449 Total loss: 1.03795 timestamp: 1654979519.1229575 iteration: 84045 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08546 FastRCNN class loss: 0.04383 FastRCNN total loss: 0.12928 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.16538 RPN box loss: 0.01207 RPN score loss: 0.00729 RPN total loss: 0.01936 Total loss: 0.90148 timestamp: 1654979522.2999973 iteration: 84050 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04799 FastRCNN class loss: 0.03852 FastRCNN total loss: 0.08651 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.09834 RPN box loss: 0.00405 RPN score loss: 0.00288 RPN total loss: 0.00693 Total loss: 0.77922 timestamp: 1654979525.4236012 iteration: 84055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07108 FastRCNN class loss: 0.03877 FastRCNN total loss: 0.10985 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.12102 RPN box loss: 0.02187 RPN score loss: 0.00581 RPN total loss: 0.02769 Total loss: 0.84599 timestamp: 1654979528.6064236 iteration: 84060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16978 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.24092 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 4.0000e-05 Mask loss: 0.11672 RPN box loss: 0.01635 RPN score loss: 0.00286 RPN total loss: 0.0192 Total loss: 0.96429 timestamp: 1654979531.8368595 iteration: 84065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07301 FastRCNN class loss: 0.04348 FastRCNN total loss: 0.11649 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12883 RPN box loss: 0.01336 RPN score loss: 0.00498 RPN total loss: 0.01834 Total loss: 0.8511 timestamp: 1654979535.0293305 iteration: 84070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07564 FastRCNN class loss: 0.03848 FastRCNN total loss: 0.11412 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13794 RPN box loss: 0.0037 RPN score loss: 0.00535 RPN total loss: 0.00905 Total loss: 0.84855 timestamp: 1654979538.2068408 iteration: 84075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0644 FastRCNN class loss: 0.05868 FastRCNN total loss: 0.12309 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13409 RPN box loss: 0.00896 RPN score loss: 0.00475 RPN total loss: 0.01371 Total loss: 0.85833 timestamp: 1654979541.3666196 iteration: 84080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.06899 FastRCNN total loss: 0.16379 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14177 RPN box loss: 0.01065 RPN score loss: 0.00564 RPN total loss: 0.01629 Total loss: 0.90929 timestamp: 1654979544.5310936 iteration: 84085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11484 FastRCNN class loss: 0.10383 FastRCNN total loss: 0.21868 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.18261 RPN box loss: 0.01389 RPN score loss: 0.00657 RPN total loss: 0.02046 Total loss: 1.00919 timestamp: 1654979547.7212958 iteration: 84090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08564 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.17284 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13512 RPN box loss: 0.00515 RPN score loss: 0.00349 RPN total loss: 0.00863 Total loss: 0.90404 timestamp: 1654979550.9065213 iteration: 84095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06836 FastRCNN class loss: 0.08102 FastRCNN total loss: 0.14938 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.1036 RPN box loss: 0.0055 RPN score loss: 0.0012 RPN total loss: 0.0067 Total loss: 0.84712 timestamp: 1654979554.099739 iteration: 84100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09821 FastRCNN class loss: 0.04815 FastRCNN total loss: 0.14635 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11116 RPN box loss: 0.0203 RPN score loss: 0.0053 RPN total loss: 0.0256 Total loss: 0.87055 timestamp: 1654979557.3352275 iteration: 84105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.114 FastRCNN class loss: 0.08338 FastRCNN total loss: 0.19738 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.16562 RPN box loss: 0.00649 RPN score loss: 0.00475 RPN total loss: 0.01124 Total loss: 0.96168 timestamp: 1654979560.588111 iteration: 84110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12291 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.20454 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13053 RPN box loss: 0.00758 RPN score loss: 0.00674 RPN total loss: 0.01432 Total loss: 0.93683 timestamp: 1654979563.7583528 iteration: 84115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09486 FastRCNN class loss: 0.08708 FastRCNN total loss: 0.18194 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12265 RPN box loss: 0.01199 RPN score loss: 0.0064 RPN total loss: 0.01839 Total loss: 0.91043 timestamp: 1654979566.9817348 iteration: 84120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10575 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.17634 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14398 RPN box loss: 0.01369 RPN score loss: 0.00479 RPN total loss: 0.01847 Total loss: 0.92623 timestamp: 1654979570.1795683 iteration: 84125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16541 FastRCNN class loss: 0.06547 FastRCNN total loss: 0.23088 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11586 RPN box loss: 0.02341 RPN score loss: 0.00801 RPN total loss: 0.03143 Total loss: 0.96561 timestamp: 1654979573.328262 iteration: 84130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13905 FastRCNN class loss: 0.15165 FastRCNN total loss: 0.2907 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.24161 RPN box loss: 0.03441 RPN score loss: 0.04141 RPN total loss: 0.07582 Total loss: 1.19557 timestamp: 1654979576.5264013 iteration: 84135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03554 FastRCNN class loss: 0.04782 FastRCNN total loss: 0.08336 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.1185 RPN box loss: 0.00777 RPN score loss: 0.00263 RPN total loss: 0.0104 Total loss: 0.7997 timestamp: 1654979579.739013 iteration: 84140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12859 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.18822 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10876 RPN box loss: 0.00837 RPN score loss: 0.00259 RPN total loss: 0.01096 Total loss: 0.89537 timestamp: 1654979582.914133 iteration: 84145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11119 FastRCNN class loss: 0.07326 FastRCNN total loss: 0.18445 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13799 RPN box loss: 0.02323 RPN score loss: 0.00952 RPN total loss: 0.03275 Total loss: 0.94263 timestamp: 1654979586.0684068 iteration: 84150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09049 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.15717 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14569 RPN box loss: 0.01417 RPN score loss: 0.00648 RPN total loss: 0.02065 Total loss: 0.91096 timestamp: 1654979589.2428327 iteration: 84155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09752 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.1581 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12596 RPN box loss: 0.03035 RPN score loss: 0.00182 RPN total loss: 0.03217 Total loss: 0.90368 timestamp: 1654979592.503603 iteration: 84160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04256 FastRCNN class loss: 0.04641 FastRCNN total loss: 0.08897 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.07881 RPN box loss: 0.00269 RPN score loss: 0.00171 RPN total loss: 0.0044 Total loss: 0.75962 timestamp: 1654979595.7013526 iteration: 84165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06318 FastRCNN class loss: 0.0461 FastRCNN total loss: 0.10928 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.15152 RPN box loss: 0.00482 RPN score loss: 0.00832 RPN total loss: 0.01314 Total loss: 0.86139 timestamp: 1654979598.892933 iteration: 84170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1333 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.21495 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.16149 RPN box loss: 0.01659 RPN score loss: 0.00684 RPN total loss: 0.02343 Total loss: 0.98731 timestamp: 1654979602.0897033 iteration: 84175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05212 FastRCNN class loss: 0.05055 FastRCNN total loss: 0.10267 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10556 RPN box loss: 0.00767 RPN score loss: 0.00339 RPN total loss: 0.01106 Total loss: 0.80673 timestamp: 1654979605.3171217 iteration: 84180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14235 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.20363 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14872 RPN box loss: 0.00612 RPN score loss: 0.00324 RPN total loss: 0.00936 Total loss: 0.94915 timestamp: 1654979608.4471657 iteration: 84185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04204 FastRCNN class loss: 0.02572 FastRCNN total loss: 0.06775 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13135 RPN box loss: 0.00227 RPN score loss: 0.00034 RPN total loss: 0.00262 Total loss: 0.78917 timestamp: 1654979611.7462587 iteration: 84190 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09638 FastRCNN class loss: 0.08734 FastRCNN total loss: 0.18372 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.15282 RPN box loss: 0.01495 RPN score loss: 0.00276 RPN total loss: 0.01771 Total loss: 0.9417 timestamp: 1654979614.951404 iteration: 84195 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12734 FastRCNN class loss: 0.10598 FastRCNN total loss: 0.23332 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.15991 RPN box loss: 0.01638 RPN score loss: 0.00577 RPN total loss: 0.02215 Total loss: 1.00282 timestamp: 1654979618.1898975 iteration: 84200 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08681 FastRCNN class loss: 0.07488 FastRCNN total loss: 0.16169 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12226 RPN box loss: 0.01439 RPN score loss: 0.02115 RPN total loss: 0.03554 Total loss: 0.90693 timestamp: 1654979621.3981292 iteration: 84205 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08064 FastRCNN class loss: 0.07375 FastRCNN total loss: 0.15439 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13546 RPN box loss: 0.00803 RPN score loss: 0.00219 RPN total loss: 0.01022 Total loss: 0.88751 timestamp: 1654979624.6807532 iteration: 84210 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.04425 FastRCNN total loss: 0.13434 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.093 RPN box loss: 0.00594 RPN score loss: 0.0046 RPN total loss: 0.01054 Total loss: 0.82532 timestamp: 1654979627.8439074 iteration: 84215 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03486 FastRCNN class loss: 0.03477 FastRCNN total loss: 0.06963 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12794 RPN box loss: 0.00331 RPN score loss: 0.00307 RPN total loss: 0.00637 Total loss: 0.79138 timestamp: 1654979631.046782 iteration: 84220 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0675 FastRCNN class loss: 0.04693 FastRCNN total loss: 0.11443 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11064 RPN box loss: 0.00706 RPN score loss: 0.00055 RPN total loss: 0.00761 Total loss: 0.82012 timestamp: 1654979634.2385275 iteration: 84225 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09984 FastRCNN class loss: 0.05617 FastRCNN total loss: 0.15601 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10552 RPN box loss: 0.00943 RPN score loss: 0.00642 RPN total loss: 0.01586 Total loss: 0.86482 timestamp: 1654979637.382097 iteration: 84230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13452 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.19468 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10627 RPN box loss: 0.00661 RPN score loss: 0.0015 RPN total loss: 0.00812 Total loss: 0.8965 timestamp: 1654979640.59578 iteration: 84235 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12949 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.19236 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.15818 RPN box loss: 0.01109 RPN score loss: 0.00268 RPN total loss: 0.01376 Total loss: 0.95175 timestamp: 1654979643.7711465 iteration: 84240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08098 FastRCNN class loss: 0.08102 FastRCNN total loss: 0.162 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.16188 RPN box loss: 0.01495 RPN score loss: 0.00187 RPN total loss: 0.01682 Total loss: 0.92814 timestamp: 1654979646.9139667 iteration: 84245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06072 FastRCNN class loss: 0.03934 FastRCNN total loss: 0.10006 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12475 RPN box loss: 0.0098 RPN score loss: 0.00938 RPN total loss: 0.01918 Total loss: 0.83144 timestamp: 1654979650.0992944 iteration: 84250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06196 FastRCNN class loss: 0.04911 FastRCNN total loss: 0.11107 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11804 RPN box loss: 0.00465 RPN score loss: 0.00691 RPN total loss: 0.01156 Total loss: 0.82811 timestamp: 1654979653.3393023 iteration: 84255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09869 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.16858 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.08973 RPN box loss: 0.00984 RPN score loss: 0.00347 RPN total loss: 0.01331 Total loss: 0.85906 timestamp: 1654979656.504992 iteration: 84260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0566 FastRCNN class loss: 0.10034 FastRCNN total loss: 0.15694 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14376 RPN box loss: 0.00835 RPN score loss: 0.00126 RPN total loss: 0.00961 Total loss: 0.89775 timestamp: 1654979659.7251391 iteration: 84265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05719 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.13494 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.09819 RPN box loss: 0.00937 RPN score loss: 0.00808 RPN total loss: 0.01745 Total loss: 0.83802 timestamp: 1654979662.9603739 iteration: 84270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06007 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.12721 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13909 RPN box loss: 0.00719 RPN score loss: 0.00472 RPN total loss: 0.0119 Total loss: 0.86565 timestamp: 1654979666.1476548 iteration: 84275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07247 FastRCNN class loss: 0.06039 FastRCNN total loss: 0.13286 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12078 RPN box loss: 0.00717 RPN score loss: 0.00081 RPN total loss: 0.00798 Total loss: 0.84906 timestamp: 1654979669.3293476 iteration: 84280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08668 FastRCNN class loss: 0.03757 FastRCNN total loss: 0.12424 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12348 RPN box loss: 0.00872 RPN score loss: 0.00343 RPN total loss: 0.01215 Total loss: 0.84732 timestamp: 1654979672.5837157 iteration: 84285 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.17701 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.17547 RPN box loss: 0.01843 RPN score loss: 0.0027 RPN total loss: 0.02114 Total loss: 0.96106 timestamp: 1654979675.812151 iteration: 84290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06277 FastRCNN class loss: 0.04324 FastRCNN total loss: 0.10601 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.1449 RPN box loss: 0.01142 RPN score loss: 0.00249 RPN total loss: 0.01391 Total loss: 0.85226 timestamp: 1654979679.081359 iteration: 84295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.04602 FastRCNN total loss: 0.13868 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11147 RPN box loss: 0.00812 RPN score loss: 0.00196 RPN total loss: 0.01008 Total loss: 0.84767 timestamp: 1654979682.3578298 iteration: 84300 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.14574 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14982 RPN box loss: 0.00471 RPN score loss: 0.00492 RPN total loss: 0.00963 Total loss: 0.89263 timestamp: 1654979685.5582578 iteration: 84305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06288 FastRCNN class loss: 0.05594 FastRCNN total loss: 0.11881 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10789 RPN box loss: 0.00386 RPN score loss: 0.00192 RPN total loss: 0.00579 Total loss: 0.81993 timestamp: 1654979688.7448366 iteration: 84310 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0887 FastRCNN class loss: 0.07943 FastRCNN total loss: 0.16813 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12712 RPN box loss: 0.01506 RPN score loss: 0.00287 RPN total loss: 0.01793 Total loss: 0.90062 timestamp: 1654979691.9991236 iteration: 84315 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.05693 FastRCNN total loss: 0.14982 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14405 RPN box loss: 0.02613 RPN score loss: 0.00499 RPN total loss: 0.03112 Total loss: 0.91243 timestamp: 1654979695.1524909 iteration: 84320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11528 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.20008 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13651 RPN box loss: 0.02658 RPN score loss: 0.01041 RPN total loss: 0.03699 Total loss: 0.96102 timestamp: 1654979698.3084157 iteration: 84325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09955 FastRCNN class loss: 0.0914 FastRCNN total loss: 0.19095 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11085 RPN box loss: 0.0128 RPN score loss: 0.01801 RPN total loss: 0.03081 Total loss: 0.92005 timestamp: 1654979701.4584599 iteration: 84330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07834 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.1414 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14319 RPN box loss: 0.01135 RPN score loss: 0.00139 RPN total loss: 0.01274 Total loss: 0.88477 timestamp: 1654979704.6785254 iteration: 84335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.05822 FastRCNN total loss: 0.18009 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.12358 RPN box loss: 0.02827 RPN score loss: 0.00395 RPN total loss: 0.03221 Total loss: 0.92332 timestamp: 1654979707.7945793 iteration: 84340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07487 FastRCNN class loss: 0.02672 FastRCNN total loss: 0.10159 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.08864 RPN box loss: 0.00887 RPN score loss: 0.0007 RPN total loss: 0.00957 Total loss: 0.78724 timestamp: 1654979711.0666227 iteration: 84345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07578 FastRCNN class loss: 0.07169 FastRCNN total loss: 0.14747 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.09107 RPN box loss: 0.01462 RPN score loss: 0.00511 RPN total loss: 0.01973 Total loss: 0.84571 timestamp: 1654979714.2282226 iteration: 84350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1079 FastRCNN class loss: 0.08451 FastRCNN total loss: 0.19241 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.16824 RPN box loss: 0.01778 RPN score loss: 0.00544 RPN total loss: 0.02322 Total loss: 0.9713 timestamp: 1654979717.4481065 iteration: 84355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09464 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.15067 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14793 RPN box loss: 0.00781 RPN score loss: 0.00472 RPN total loss: 0.01252 Total loss: 0.89855 timestamp: 1654979720.557629 iteration: 84360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06293 FastRCNN class loss: 0.04727 FastRCNN total loss: 0.11019 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.11114 RPN box loss: 0.01279 RPN score loss: 0.0006 RPN total loss: 0.01339 Total loss: 0.82216 timestamp: 1654979723.7979536 iteration: 84365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07629 FastRCNN class loss: 0.04389 FastRCNN total loss: 0.12018 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10978 RPN box loss: 0.02663 RPN score loss: 0.0034 RPN total loss: 0.03003 Total loss: 0.84742 timestamp: 1654979726.9990528 iteration: 84370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07478 FastRCNN class loss: 0.07488 FastRCNN total loss: 0.14965 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.13709 RPN box loss: 0.00806 RPN score loss: 0.00271 RPN total loss: 0.01077 Total loss: 0.88495 timestamp: 1654979730.20812 iteration: 84375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11822 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.20978 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.16211 RPN box loss: 0.01305 RPN score loss: 0.00311 RPN total loss: 0.01616 Total loss: 0.97548 timestamp: 1654979733.4570768 iteration: 84380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05127 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.1072 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10411 RPN box loss: 0.00465 RPN score loss: 0.00577 RPN total loss: 0.01042 Total loss: 0.80917 timestamp: 1654979736.6882448 iteration: 84385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07545 FastRCNN class loss: 0.07079 FastRCNN total loss: 0.14624 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.1416 RPN box loss: 0.00615 RPN score loss: 0.00148 RPN total loss: 0.00763 Total loss: 0.88291 timestamp: 1654979739.9187846 iteration: 84390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09295 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.15025 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.10795 RPN box loss: 0.0069 RPN score loss: 0.00395 RPN total loss: 0.01085 Total loss: 0.85649 timestamp: 1654979743.103573 iteration: 84395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10212 FastRCNN class loss: 0.08799 FastRCNN total loss: 0.19011 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 4.0000e-05 Mask loss: 0.14879 RPN box loss: 0.0185 RPN score loss: 0.01343 RPN total loss: 0.03193 Total loss: 0.95826 timestamp: 1654979746.2753873 iteration: 84400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07445 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.15275 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10458 RPN box loss: 0.01034 RPN score loss: 0.0051 RPN total loss: 0.01544 Total loss: 0.86021 timestamp: 1654979749.49699 iteration: 84405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08279 FastRCNN class loss: 0.05683 FastRCNN total loss: 0.13962 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.22506 RPN box loss: 0.01626 RPN score loss: 0.00114 RPN total loss: 0.01741 Total loss: 0.96952 timestamp: 1654979752.690304 iteration: 84410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09766 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.16545 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.15859 RPN box loss: 0.01249 RPN score loss: 0.00426 RPN total loss: 0.01674 Total loss: 0.92822 timestamp: 1654979755.8539627 iteration: 84415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.14864 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.17629 RPN box loss: 0.02117 RPN score loss: 0.00987 RPN total loss: 0.03103 Total loss: 0.94341 timestamp: 1654979759.070402 iteration: 84420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08122 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.14474 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10373 RPN box loss: 0.0039 RPN score loss: 0.00386 RPN total loss: 0.00776 Total loss: 0.84366 timestamp: 1654979762.2632496 iteration: 84425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0545 FastRCNN class loss: 0.04912 FastRCNN total loss: 0.10363 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10173 RPN box loss: 0.00885 RPN score loss: 0.00587 RPN total loss: 0.01472 Total loss: 0.80751 timestamp: 1654979765.4858124 iteration: 84430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.06431 FastRCNN total loss: 0.18926 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11448 RPN box loss: 0.01113 RPN score loss: 0.00258 RPN total loss: 0.0137 Total loss: 0.90487 timestamp: 1654979768.7415533 iteration: 84435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10466 FastRCNN class loss: 0.06014 FastRCNN total loss: 0.16481 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.16453 RPN box loss: 0.03483 RPN score loss: 0.00729 RPN total loss: 0.04212 Total loss: 0.9589 timestamp: 1654979771.9369943 iteration: 84440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05631 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.11959 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12499 RPN box loss: 0.00814 RPN score loss: 0.00451 RPN total loss: 0.01265 Total loss: 0.84466 timestamp: 1654979775.1666903 iteration: 84445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1194 FastRCNN class loss: 0.07417 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.15876 RPN box loss: 0.01717 RPN score loss: 0.00868 RPN total loss: 0.02584 Total loss: 0.9656 timestamp: 1654979778.303921 iteration: 84450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05199 FastRCNN class loss: 0.07669 FastRCNN total loss: 0.12868 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12516 RPN box loss: 0.01886 RPN score loss: 0.01386 RPN total loss: 0.03272 Total loss: 0.87399 timestamp: 1654979781.5392497 iteration: 84455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06446 FastRCNN class loss: 0.05001 FastRCNN total loss: 0.11447 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.16396 RPN box loss: 0.00532 RPN score loss: 0.01688 RPN total loss: 0.0222 Total loss: 0.88807 timestamp: 1654979784.7336497 iteration: 84460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11368 FastRCNN class loss: 0.07797 FastRCNN total loss: 0.19166 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.14713 RPN box loss: 0.00709 RPN score loss: 0.00353 RPN total loss: 0.01062 Total loss: 0.93685 timestamp: 1654979787.839322 iteration: 84465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09234 FastRCNN class loss: 0.06281 FastRCNN total loss: 0.15515 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.1009 RPN box loss: 0.02421 RPN score loss: 0.01333 RPN total loss: 0.03754 Total loss: 0.88102 timestamp: 1654979791.0129902 iteration: 84470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09678 FastRCNN class loss: 0.08285 FastRCNN total loss: 0.17963 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.15902 RPN box loss: 0.00834 RPN score loss: 0.00253 RPN total loss: 0.01087 Total loss: 0.93695 timestamp: 1654979794.2616093 iteration: 84475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12213 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.21746 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.13534 RPN box loss: 0.00917 RPN score loss: 0.00925 RPN total loss: 0.01842 Total loss: 0.95865 timestamp: 1654979797.3881187 iteration: 84480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07204 FastRCNN class loss: 0.05819 FastRCNN total loss: 0.13024 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.14528 RPN box loss: 0.01295 RPN score loss: 0.01054 RPN total loss: 0.02349 Total loss: 0.88644 timestamp: 1654979800.58841 iteration: 84485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08953 FastRCNN class loss: 0.04821 FastRCNN total loss: 0.13774 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.07087 RPN box loss: 0.00811 RPN score loss: 0.00226 RPN total loss: 0.01038 Total loss: 0.80642 timestamp: 1654979803.7512321 iteration: 84490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05743 FastRCNN class loss: 0.04103 FastRCNN total loss: 0.09846 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.07483 RPN box loss: 0.00478 RPN score loss: 0.00309 RPN total loss: 0.00787 Total loss: 0.76859 timestamp: 1654979806.9032767 iteration: 84495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06871 FastRCNN class loss: 0.0501 FastRCNN total loss: 0.11881 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10717 RPN box loss: 0.00836 RPN score loss: 0.00383 RPN total loss: 0.0122 Total loss: 0.8256 timestamp: 1654979810.0854254 iteration: 84500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07325 FastRCNN class loss: 0.04552 FastRCNN total loss: 0.11877 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10366 RPN box loss: 0.00909 RPN score loss: 0.00183 RPN total loss: 0.01092 Total loss: 0.82079 timestamp: 1654979813.2937171 iteration: 84505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07893 FastRCNN class loss: 0.09218 FastRCNN total loss: 0.1711 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.15247 RPN box loss: 0.02519 RPN score loss: 0.00847 RPN total loss: 0.03367 Total loss: 0.94467 timestamp: 1654979816.451971 iteration: 84510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08549 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.14802 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.17547 RPN box loss: 0.01497 RPN score loss: 0.00501 RPN total loss: 0.01999 Total loss: 0.93091 timestamp: 1654979819.623331 iteration: 84515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12794 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.21049 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.17274 RPN box loss: 0.01796 RPN score loss: 0.0019 RPN total loss: 0.01987 Total loss: 0.99053 timestamp: 1654979822.8285203 iteration: 84520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08882 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.14168 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.1313 RPN box loss: 0.01238 RPN score loss: 0.00785 RPN total loss: 0.02023 Total loss: 0.88064 timestamp: 1654979826.0305693 iteration: 84525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09432 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.16144 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.17504 RPN box loss: 0.01874 RPN score loss: 0.00583 RPN total loss: 0.02457 Total loss: 0.94849 timestamp: 1654979829.2666876 iteration: 84530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04951 FastRCNN class loss: 0.0362 FastRCNN total loss: 0.08571 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.07688 RPN box loss: 0.00663 RPN score loss: 0.00074 RPN total loss: 0.00737 Total loss: 0.75738 timestamp: 1654979832.4703004 iteration: 84535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06492 FastRCNN class loss: 0.0602 FastRCNN total loss: 0.12512 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10939 RPN box loss: 0.01742 RPN score loss: 0.00236 RPN total loss: 0.01979 Total loss: 0.84174 timestamp: 1654979835.678433 iteration: 84540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06541 FastRCNN class loss: 0.10623 FastRCNN total loss: 0.17163 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.16542 RPN box loss: 0.01223 RPN score loss: 0.02041 RPN total loss: 0.03264 Total loss: 0.95713 timestamp: 1654979838.9167614 iteration: 84545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.16197 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.08657 RPN box loss: 0.0064 RPN score loss: 0.00379 RPN total loss: 0.0102 Total loss: 0.84617 timestamp: 1654979842.220103 iteration: 84550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12519 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.17824 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10902 RPN box loss: 0.00385 RPN score loss: 0.00558 RPN total loss: 0.00942 Total loss: 0.88411 timestamp: 1654979845.4003196 iteration: 84555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07219 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.13462 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12166 RPN box loss: 0.01085 RPN score loss: 0.00346 RPN total loss: 0.01431 Total loss: 0.85802 timestamp: 1654979848.5305955 iteration: 84560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11385 FastRCNN class loss: 0.10372 FastRCNN total loss: 0.21757 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.19687 RPN box loss: 0.01283 RPN score loss: 0.01258 RPN total loss: 0.02541 Total loss: 1.02728 timestamp: 1654979851.801635 iteration: 84565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04494 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.10704 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.13397 RPN box loss: 0.01682 RPN score loss: 0.00716 RPN total loss: 0.02398 Total loss: 0.85242 timestamp: 1654979854.9902139 iteration: 84570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09223 FastRCNN class loss: 0.05521 FastRCNN total loss: 0.14745 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.09319 RPN box loss: 0.04752 RPN score loss: 0.00724 RPN total loss: 0.05476 Total loss: 0.88283 timestamp: 1654979858.212574 iteration: 84575 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07914 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.13265 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11816 RPN box loss: 0.0039 RPN score loss: 0.00443 RPN total loss: 0.00833 Total loss: 0.84656 timestamp: 1654979861.3963816 iteration: 84580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05093 FastRCNN class loss: 0.04252 FastRCNN total loss: 0.09345 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11444 RPN box loss: 0.00717 RPN score loss: 0.00273 RPN total loss: 0.0099 Total loss: 0.80522 timestamp: 1654979864.547303 iteration: 84585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02378 FastRCNN class loss: 0.03069 FastRCNN total loss: 0.05447 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.09275 RPN box loss: 0.00141 RPN score loss: 0.00111 RPN total loss: 0.00252 Total loss: 0.73717 timestamp: 1654979867.806928 iteration: 84590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04462 FastRCNN class loss: 0.03647 FastRCNN total loss: 0.08109 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.07717 RPN box loss: 0.00363 RPN score loss: 0.00168 RPN total loss: 0.00531 Total loss: 0.751 timestamp: 1654979870.985601 iteration: 84595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08243 FastRCNN class loss: 0.06508 FastRCNN total loss: 0.14751 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12828 RPN box loss: 0.00753 RPN score loss: 0.00178 RPN total loss: 0.00931 Total loss: 0.87253 timestamp: 1654979874.1754196 iteration: 84600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09848 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.15824 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10981 RPN box loss: 0.00686 RPN score loss: 0.00536 RPN total loss: 0.01223 Total loss: 0.86771 timestamp: 1654979877.359068 iteration: 84605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05102 FastRCNN class loss: 0.06111 FastRCNN total loss: 0.11214 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12175 RPN box loss: 0.00712 RPN score loss: 0.00561 RPN total loss: 0.01273 Total loss: 0.83405 timestamp: 1654979880.5718315 iteration: 84610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13538 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.21743 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12218 RPN box loss: 0.00803 RPN score loss: 0.00127 RPN total loss: 0.0093 Total loss: 0.93633 timestamp: 1654979883.7530324 iteration: 84615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06934 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.14784 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.13778 RPN box loss: 0.01354 RPN score loss: 0.01277 RPN total loss: 0.02631 Total loss: 0.89935 timestamp: 1654979886.9384212 iteration: 84620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09517 FastRCNN class loss: 0.06699 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11565 RPN box loss: 0.00896 RPN score loss: 0.00461 RPN total loss: 0.01357 Total loss: 0.87881 timestamp: 1654979890.122797 iteration: 84625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14224 FastRCNN class loss: 0.13093 FastRCNN total loss: 0.27316 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.13322 RPN box loss: 0.00648 RPN score loss: 0.00226 RPN total loss: 0.00874 Total loss: 1.00255 timestamp: 1654979893.3452835 iteration: 84630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.06692 FastRCNN total loss: 0.17988 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.16292 RPN box loss: 0.01023 RPN score loss: 0.00576 RPN total loss: 0.01598 Total loss: 0.94621 timestamp: 1654979896.5423443 iteration: 84635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09144 FastRCNN class loss: 0.05866 FastRCNN total loss: 0.15009 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.14565 RPN box loss: 0.01511 RPN score loss: 0.00237 RPN total loss: 0.01749 Total loss: 0.90065 timestamp: 1654979899.745821 iteration: 84640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06904 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.13016 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12408 RPN box loss: 0.01036 RPN score loss: 0.00418 RPN total loss: 0.01454 Total loss: 0.85621 timestamp: 1654979902.9575925 iteration: 84645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07613 FastRCNN class loss: 0.08438 FastRCNN total loss: 0.16051 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11005 RPN box loss: 0.01534 RPN score loss: 0.00263 RPN total loss: 0.01796 Total loss: 0.87594 timestamp: 1654979906.111343 iteration: 84650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08234 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.13278 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10193 RPN box loss: 0.00871 RPN score loss: 0.00309 RPN total loss: 0.0118 Total loss: 0.83393 timestamp: 1654979909.2318242 iteration: 84655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08244 FastRCNN class loss: 0.039 FastRCNN total loss: 0.12144 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11954 RPN box loss: 0.01061 RPN score loss: 0.0006 RPN total loss: 0.01121 Total loss: 0.83962 timestamp: 1654979912.4432633 iteration: 84660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09203 FastRCNN class loss: 0.08961 FastRCNN total loss: 0.18164 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.1011 RPN box loss: 0.01432 RPN score loss: 0.0084 RPN total loss: 0.02272 Total loss: 0.89289 timestamp: 1654979915.6888576 iteration: 84665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09067 FastRCNN class loss: 0.13837 FastRCNN total loss: 0.22904 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.13581 RPN box loss: 0.01336 RPN score loss: 0.00572 RPN total loss: 0.01908 Total loss: 0.97136 timestamp: 1654979918.843521 iteration: 84670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04907 FastRCNN class loss: 0.03057 FastRCNN total loss: 0.07964 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.08582 RPN box loss: 0.00292 RPN score loss: 0.00172 RPN total loss: 0.00464 Total loss: 0.75752 timestamp: 1654979922.0645804 iteration: 84675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08728 FastRCNN class loss: 0.07363 FastRCNN total loss: 0.16092 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12384 RPN box loss: 0.00541 RPN score loss: 0.00682 RPN total loss: 0.01224 Total loss: 0.88442 timestamp: 1654979925.2765226 iteration: 84680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12044 FastRCNN class loss: 0.07631 FastRCNN total loss: 0.19675 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.14484 RPN box loss: 0.02377 RPN score loss: 0.01067 RPN total loss: 0.03444 Total loss: 0.96346 timestamp: 1654979928.3766446 iteration: 84685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08974 FastRCNN class loss: 0.06955 FastRCNN total loss: 0.15929 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.15159 RPN box loss: 0.01073 RPN score loss: 0.00437 RPN total loss: 0.0151 Total loss: 0.91341 timestamp: 1654979931.6018162 iteration: 84690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0455 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.10791 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11919 RPN box loss: 0.0152 RPN score loss: 0.00731 RPN total loss: 0.02251 Total loss: 0.83704 timestamp: 1654979934.8382525 iteration: 84695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0675 FastRCNN class loss: 0.09283 FastRCNN total loss: 0.16033 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.11792 RPN box loss: 0.00905 RPN score loss: 0.0031 RPN total loss: 0.01214 Total loss: 0.87782 timestamp: 1654979937.9574585 iteration: 84700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12682 FastRCNN class loss: 0.0913 FastRCNN total loss: 0.21812 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.16249 RPN box loss: 0.01262 RPN score loss: 0.01188 RPN total loss: 0.0245 Total loss: 0.99255 timestamp: 1654979941.2001946 iteration: 84705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05633 FastRCNN class loss: 0.03624 FastRCNN total loss: 0.09257 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.10576 RPN box loss: 0.00627 RPN score loss: 0.00153 RPN total loss: 0.0078 Total loss: 0.79355 timestamp: 1654979944.4042304 iteration: 84710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08829 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.16316 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.13222 RPN box loss: 0.02181 RPN score loss: 0.00787 RPN total loss: 0.02969 Total loss: 0.91249 timestamp: 1654979947.5736141 iteration: 84715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11274 FastRCNN class loss: 0.05442 FastRCNN total loss: 0.16716 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 4.0000e-05 Mask loss: 0.12152 RPN box loss: 0.00463 RPN score loss: 0.0056 RPN total loss: 0.01023 Total loss: 0.88634 timestamp: 1654979950.7389047 iteration: 84720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07651 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.13128 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12888 RPN box loss: 0.00808 RPN score loss: 0.00732 RPN total loss: 0.0154 Total loss: 0.86299 timestamp: 1654979953.914503 iteration: 84725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.131 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.19406 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13059 RPN box loss: 0.00925 RPN score loss: 0.00552 RPN total loss: 0.01477 Total loss: 0.92684 timestamp: 1654979957.1567438 iteration: 84730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09072 FastRCNN class loss: 0.09034 FastRCNN total loss: 0.18106 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13271 RPN box loss: 0.01219 RPN score loss: 0.0065 RPN total loss: 0.01869 Total loss: 0.91988 timestamp: 1654979960.441487 iteration: 84735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04818 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.09269 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12908 RPN box loss: 0.00758 RPN score loss: 0.0036 RPN total loss: 0.01118 Total loss: 0.82038 timestamp: 1654979963.6293743 iteration: 84740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11225 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.18847 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11011 RPN box loss: 0.01634 RPN score loss: 0.00209 RPN total loss: 0.01843 Total loss: 0.90444 timestamp: 1654979966.7641358 iteration: 84745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.08181 FastRCNN total loss: 0.16583 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13742 RPN box loss: 0.00797 RPN score loss: 0.00107 RPN total loss: 0.00904 Total loss: 0.89971 timestamp: 1654979969.9042227 iteration: 84750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09153 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.15864 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.1037 RPN box loss: 0.01786 RPN score loss: 0.00303 RPN total loss: 0.02089 Total loss: 0.87065 timestamp: 1654979973.14899 iteration: 84755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0845 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.14685 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.15247 RPN box loss: 0.01606 RPN score loss: 0.01192 RPN total loss: 0.02798 Total loss: 0.91472 timestamp: 1654979976.3066025 iteration: 84760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08535 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.1572 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.18077 RPN box loss: 0.01428 RPN score loss: 0.00616 RPN total loss: 0.02044 Total loss: 0.94583 timestamp: 1654979979.495813 iteration: 84765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05219 FastRCNN class loss: 0.03902 FastRCNN total loss: 0.09122 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.08838 RPN box loss: 0.00299 RPN score loss: 0.00621 RPN total loss: 0.0092 Total loss: 0.77621 timestamp: 1654979982.672385 iteration: 84770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09239 FastRCNN class loss: 0.10693 FastRCNN total loss: 0.19932 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.19844 RPN box loss: 0.02398 RPN score loss: 0.00825 RPN total loss: 0.03223 Total loss: 1.01741 timestamp: 1654979985.9414098 iteration: 84775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11069 FastRCNN class loss: 0.06023 FastRCNN total loss: 0.17092 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.22866 RPN box loss: 0.01673 RPN score loss: 0.00718 RPN total loss: 0.0239 Total loss: 1.0109 timestamp: 1654979989.0856886 iteration: 84780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04648 FastRCNN class loss: 0.055 FastRCNN total loss: 0.10148 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11793 RPN box loss: 0.00772 RPN score loss: 0.00443 RPN total loss: 0.01215 Total loss: 0.81899 timestamp: 1654979992.2671342 iteration: 84785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07681 FastRCNN class loss: 0.05659 FastRCNN total loss: 0.1334 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12002 RPN box loss: 0.0607 RPN score loss: 0.00535 RPN total loss: 0.06605 Total loss: 0.90689 timestamp: 1654979995.3950377 iteration: 84790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06638 FastRCNN class loss: 0.04584 FastRCNN total loss: 0.11222 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14883 RPN box loss: 0.012 RPN score loss: 0.00187 RPN total loss: 0.01387 Total loss: 0.86235 timestamp: 1654979998.628559 iteration: 84795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.13619 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.19034 RPN box loss: 0.00772 RPN score loss: 0.00244 RPN total loss: 0.01016 Total loss: 0.92411 timestamp: 1654980001.8004353 iteration: 84800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.15827 RPN box loss: 0.01009 RPN score loss: 0.00401 RPN total loss: 0.01411 Total loss: 0.96689 timestamp: 1654980005.0309136 iteration: 84805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09268 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.15697 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14103 RPN box loss: 0.01754 RPN score loss: 0.00775 RPN total loss: 0.02529 Total loss: 0.91072 timestamp: 1654980008.2103126 iteration: 84810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13023 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.19342 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11187 RPN box loss: 0.01615 RPN score loss: 0.00121 RPN total loss: 0.01737 Total loss: 0.91008 timestamp: 1654980011.4263797 iteration: 84815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03141 FastRCNN class loss: 0.03463 FastRCNN total loss: 0.06603 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11148 RPN box loss: 0.00464 RPN score loss: 0.00462 RPN total loss: 0.00926 Total loss: 0.77419 timestamp: 1654980014.6350958 iteration: 84820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04444 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.09078 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.08307 RPN box loss: 0.00744 RPN score loss: 0.0051 RPN total loss: 0.01254 Total loss: 0.77381 timestamp: 1654980017.8459094 iteration: 84825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13118 FastRCNN class loss: 0.11683 FastRCNN total loss: 0.24801 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.22813 RPN box loss: 0.01065 RPN score loss: 0.00488 RPN total loss: 0.01552 Total loss: 1.07909 timestamp: 1654980020.9784977 iteration: 84830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10555 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.16154 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11037 RPN box loss: 0.01076 RPN score loss: 0.00343 RPN total loss: 0.01418 Total loss: 0.87352 timestamp: 1654980024.128169 iteration: 84835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08441 FastRCNN class loss: 0.07945 FastRCNN total loss: 0.16386 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12749 RPN box loss: 0.00861 RPN score loss: 0.01226 RPN total loss: 0.02087 Total loss: 0.89964 timestamp: 1654980027.3237095 iteration: 84840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06292 FastRCNN class loss: 0.04016 FastRCNN total loss: 0.10308 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.09879 RPN box loss: 0.00764 RPN score loss: 0.00386 RPN total loss: 0.0115 Total loss: 0.80078 timestamp: 1654980030.5776727 iteration: 84845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05511 FastRCNN class loss: 0.02767 FastRCNN total loss: 0.08278 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.09262 RPN box loss: 0.00502 RPN score loss: 0.00319 RPN total loss: 0.00822 Total loss: 0.77103 timestamp: 1654980033.8226888 iteration: 84850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08355 FastRCNN class loss: 0.07011 FastRCNN total loss: 0.15366 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11195 RPN box loss: 0.00862 RPN score loss: 0.00459 RPN total loss: 0.01321 Total loss: 0.86624 timestamp: 1654980036.971877 iteration: 84855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06636 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.1181 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12838 RPN box loss: 0.00722 RPN score loss: 0.01099 RPN total loss: 0.01821 Total loss: 0.8521 timestamp: 1654980040.1524243 iteration: 84860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08714 FastRCNN class loss: 0.09254 FastRCNN total loss: 0.17968 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14204 RPN box loss: 0.00968 RPN score loss: 0.00572 RPN total loss: 0.01541 Total loss: 0.92455 timestamp: 1654980043.3615358 iteration: 84865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10386 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.15708 RPN box loss: 0.00711 RPN score loss: 0.0149 RPN total loss: 0.02201 Total loss: 0.9309 timestamp: 1654980046.5765417 iteration: 84870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06043 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.11996 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.09255 RPN box loss: 0.00679 RPN score loss: 0.00169 RPN total loss: 0.00848 Total loss: 0.80842 timestamp: 1654980049.705715 iteration: 84875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.07651 FastRCNN total loss: 0.1816 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13582 RPN box loss: 0.0106 RPN score loss: 0.00696 RPN total loss: 0.01756 Total loss: 0.9224 timestamp: 1654980052.961979 iteration: 84880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09214 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.17618 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.17602 RPN box loss: 0.01149 RPN score loss: 0.00276 RPN total loss: 0.01425 Total loss: 0.95387 timestamp: 1654980056.1604805 iteration: 84885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11026 FastRCNN class loss: 0.07081 FastRCNN total loss: 0.18106 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.10631 RPN box loss: 0.03235 RPN score loss: 0.00281 RPN total loss: 0.03516 Total loss: 0.90995 timestamp: 1654980059.3373754 iteration: 84890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07705 FastRCNN class loss: 0.03494 FastRCNN total loss: 0.11199 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.0676 RPN box loss: 0.00408 RPN score loss: 0.00176 RPN total loss: 0.00584 Total loss: 0.77284 timestamp: 1654980062.6154506 iteration: 84895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07508 FastRCNN class loss: 0.05608 FastRCNN total loss: 0.13116 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13191 RPN box loss: 0.00793 RPN score loss: 0.00409 RPN total loss: 0.01203 Total loss: 0.86251 timestamp: 1654980065.784044 iteration: 84900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06965 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.13017 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11855 RPN box loss: 0.00597 RPN score loss: 0.00185 RPN total loss: 0.00781 Total loss: 0.84396 timestamp: 1654980068.9971578 iteration: 84905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09908 FastRCNN class loss: 0.08034 FastRCNN total loss: 0.17942 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11942 RPN box loss: 0.01879 RPN score loss: 0.00347 RPN total loss: 0.02226 Total loss: 0.90852 timestamp: 1654980072.2064607 iteration: 84910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06887 FastRCNN class loss: 0.04785 FastRCNN total loss: 0.11672 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.09546 RPN box loss: 0.00582 RPN score loss: 0.00088 RPN total loss: 0.0067 Total loss: 0.80631 timestamp: 1654980075.3884277 iteration: 84915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.07203 FastRCNN total loss: 0.14182 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14084 RPN box loss: 0.00548 RPN score loss: 0.00245 RPN total loss: 0.00792 Total loss: 0.878 timestamp: 1654980078.5355177 iteration: 84920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06939 FastRCNN class loss: 0.03061 FastRCNN total loss: 0.1 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.1121 RPN box loss: 0.00471 RPN score loss: 0.0006 RPN total loss: 0.00531 Total loss: 0.80483 timestamp: 1654980081.7589326 iteration: 84925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09403 FastRCNN class loss: 0.04772 FastRCNN total loss: 0.14174 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11437 RPN box loss: 0.01461 RPN score loss: 0.00225 RPN total loss: 0.01686 Total loss: 0.86039 timestamp: 1654980084.9475853 iteration: 84930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07612 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.14813 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13759 RPN box loss: 0.02655 RPN score loss: 0.00669 RPN total loss: 0.03324 Total loss: 0.90638 timestamp: 1654980088.1113505 iteration: 84935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08714 FastRCNN class loss: 0.06375 FastRCNN total loss: 0.1509 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12007 RPN box loss: 0.01026 RPN score loss: 0.00103 RPN total loss: 0.0113 Total loss: 0.86969 timestamp: 1654980091.2813554 iteration: 84940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13399 FastRCNN class loss: 0.04291 FastRCNN total loss: 0.17691 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.1477 RPN box loss: 0.01018 RPN score loss: 0.00098 RPN total loss: 0.01116 Total loss: 0.92318 timestamp: 1654980094.4779139 iteration: 84945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0845 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.16392 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13283 RPN box loss: 0.01342 RPN score loss: 0.00457 RPN total loss: 0.01799 Total loss: 0.90215 timestamp: 1654980097.6383476 iteration: 84950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13278 FastRCNN class loss: 0.17881 FastRCNN total loss: 0.31159 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.21116 RPN box loss: 0.01576 RPN score loss: 0.0121 RPN total loss: 0.02786 Total loss: 1.13804 timestamp: 1654980100.8800821 iteration: 84955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14775 FastRCNN class loss: 0.05707 FastRCNN total loss: 0.20481 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13395 RPN box loss: 0.01388 RPN score loss: 0.00165 RPN total loss: 0.01553 Total loss: 0.94172 timestamp: 1654980104.0865788 iteration: 84960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05309 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.12117 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11878 RPN box loss: 0.00771 RPN score loss: 0.00153 RPN total loss: 0.00925 Total loss: 0.83661 timestamp: 1654980107.2699769 iteration: 84965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06821 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.11673 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14419 RPN box loss: 0.00356 RPN score loss: 0.00061 RPN total loss: 0.00417 Total loss: 0.8525 timestamp: 1654980110.4930277 iteration: 84970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07547 FastRCNN class loss: 0.08245 FastRCNN total loss: 0.15792 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11815 RPN box loss: 0.0091 RPN score loss: 0.00773 RPN total loss: 0.01684 Total loss: 0.88032 timestamp: 1654980113.68359 iteration: 84975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.1643 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.15104 RPN box loss: 0.00926 RPN score loss: 0.01099 RPN total loss: 0.02025 Total loss: 0.92301 timestamp: 1654980116.9229064 iteration: 84980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08387 FastRCNN class loss: 0.09052 FastRCNN total loss: 0.17438 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14053 RPN box loss: 0.0101 RPN score loss: 0.00447 RPN total loss: 0.01456 Total loss: 0.91689 timestamp: 1654980120.0827255 iteration: 84985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06564 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.12039 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.13256 RPN box loss: 0.01177 RPN score loss: 0.00323 RPN total loss: 0.01499 Total loss: 0.85536 timestamp: 1654980123.2875528 iteration: 84990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12968 FastRCNN class loss: 0.07911 FastRCNN total loss: 0.20879 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.12732 RPN box loss: 0.0353 RPN score loss: 0.00364 RPN total loss: 0.03894 Total loss: 0.96247 timestamp: 1654980126.4837472 iteration: 84995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07433 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.14618 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.17157 RPN box loss: 0.00881 RPN score loss: 0.00309 RPN total loss: 0.0119 Total loss: 0.91707 timestamp: 1654980129.68358 iteration: 85000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07149 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.13825 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.15245 RPN box loss: 0.0089 RPN score loss: 0.00239 RPN total loss: 0.01129 Total loss: 0.88941 timestamp: 1654980132.8952131 iteration: 85005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10893 FastRCNN class loss: 0.10263 FastRCNN total loss: 0.21156 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.14463 RPN box loss: 0.01023 RPN score loss: 0.02649 RPN total loss: 0.03672 Total loss: 0.98033 timestamp: 1654980136.0376842 iteration: 85010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06495 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.12469 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.15744 RPN box loss: 0.00979 RPN score loss: 0.00214 RPN total loss: 0.01193 Total loss: 0.88148 timestamp: 1654980139.2503743 iteration: 85015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0638 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.12708 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.16604 RPN box loss: 0.04391 RPN score loss: 0.01088 RPN total loss: 0.05479 Total loss: 0.93532 timestamp: 1654980142.4167101 iteration: 85020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07069 FastRCNN class loss: 0.04676 FastRCNN total loss: 0.11745 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.07254 RPN box loss: 0.0067 RPN score loss: 0.00227 RPN total loss: 0.00897 Total loss: 0.78637 timestamp: 1654980145.5932271 iteration: 85025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.22488 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.19029 RPN box loss: 0.0135 RPN score loss: 0.0087 RPN total loss: 0.02219 Total loss: 1.02478 timestamp: 1654980148.818958 iteration: 85030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1007 FastRCNN class loss: 0.0411 FastRCNN total loss: 0.14181 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.10587 RPN box loss: 0.00684 RPN score loss: 0.00076 RPN total loss: 0.0076 Total loss: 0.84269 timestamp: 1654980152.000392 iteration: 85035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0694 FastRCNN class loss: 0.04427 FastRCNN total loss: 0.11367 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 4.0000e-05 Mask loss: 0.11617 RPN box loss: 0.00555 RPN score loss: 0.0049 RPN total loss: 0.01045 Total loss: 0.82771 timestamp: 1654980155.2508557 iteration: 85040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10124 FastRCNN class loss: 0.0888 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.19812 RPN box loss: 0.01618 RPN score loss: 0.00835 RPN total loss: 0.02452 Total loss: 1.00009 timestamp: 1654980158.4769669 iteration: 85045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06029 FastRCNN class loss: 0.0508 FastRCNN total loss: 0.11109 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.06039 RPN box loss: 0.00655 RPN score loss: 0.0013 RPN total loss: 0.00785 Total loss: 0.76675 timestamp: 1654980161.6246493 iteration: 85050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05952 FastRCNN class loss: 0.05694 FastRCNN total loss: 0.11646 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11377 RPN box loss: 0.00447 RPN score loss: 0.00163 RPN total loss: 0.0061 Total loss: 0.82374 timestamp: 1654980164.8003297 iteration: 85055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11306 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.17474 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11979 RPN box loss: 0.00908 RPN score loss: 0.0017 RPN total loss: 0.01078 Total loss: 0.89272 timestamp: 1654980168.0408878 iteration: 85060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11536 FastRCNN class loss: 0.07236 FastRCNN total loss: 0.18771 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.12303 RPN box loss: 0.00494 RPN score loss: 0.00811 RPN total loss: 0.01305 Total loss: 0.91121 timestamp: 1654980171.2719383 iteration: 85065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09862 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.16431 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11419 RPN box loss: 0.02477 RPN score loss: 0.00988 RPN total loss: 0.03465 Total loss: 0.90057 timestamp: 1654980174.4906073 iteration: 85070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10166 FastRCNN class loss: 0.07939 FastRCNN total loss: 0.18105 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14307 RPN box loss: 0.01713 RPN score loss: 0.00485 RPN total loss: 0.02199 Total loss: 0.93351 timestamp: 1654980177.6887758 iteration: 85075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0643 FastRCNN class loss: 0.06906 FastRCNN total loss: 0.13337 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11223 RPN box loss: 0.00533 RPN score loss: 0.00164 RPN total loss: 0.00697 Total loss: 0.83999 timestamp: 1654980180.8887236 iteration: 85080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08032 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.13343 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.1067 RPN box loss: 0.01701 RPN score loss: 0.00554 RPN total loss: 0.02254 Total loss: 0.85009 timestamp: 1654980184.136086 iteration: 85085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06693 FastRCNN class loss: 0.08578 FastRCNN total loss: 0.15271 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11575 RPN box loss: 0.00703 RPN score loss: 0.0033 RPN total loss: 0.01033 Total loss: 0.86621 timestamp: 1654980187.2588573 iteration: 85090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08489 FastRCNN class loss: 0.0617 FastRCNN total loss: 0.1466 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.19349 RPN box loss: 0.00553 RPN score loss: 0.00124 RPN total loss: 0.00677 Total loss: 0.93427 timestamp: 1654980190.3613539 iteration: 85095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13791 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.20926 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14643 RPN box loss: 0.01409 RPN score loss: 0.00632 RPN total loss: 0.02041 Total loss: 0.96352 timestamp: 1654980193.5830457 iteration: 85100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06119 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.11775 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.07607 RPN box loss: 0.01008 RPN score loss: 0.00928 RPN total loss: 0.01936 Total loss: 0.8006 timestamp: 1654980196.8402174 iteration: 85105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04713 FastRCNN class loss: 0.0392 FastRCNN total loss: 0.08633 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.09051 RPN box loss: 0.00617 RPN score loss: 0.00105 RPN total loss: 0.00722 Total loss: 0.77148 timestamp: 1654980200.0748463 iteration: 85110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11402 FastRCNN class loss: 0.06251 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14383 RPN box loss: 0.02181 RPN score loss: 0.00431 RPN total loss: 0.02612 Total loss: 0.9339 timestamp: 1654980203.304404 iteration: 85115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.20226 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14753 RPN box loss: 0.01217 RPN score loss: 0.01015 RPN total loss: 0.02232 Total loss: 0.95953 timestamp: 1654980206.4618351 iteration: 85120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12331 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.19905 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.15323 RPN box loss: 0.00809 RPN score loss: 0.00286 RPN total loss: 0.01096 Total loss: 0.95065 timestamp: 1654980209.6529052 iteration: 85125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04374 FastRCNN class loss: 0.04745 FastRCNN total loss: 0.0912 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11259 RPN box loss: 0.00486 RPN score loss: 0.00282 RPN total loss: 0.00768 Total loss: 0.79887 timestamp: 1654980212.8949876 iteration: 85130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06439 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.12373 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11118 RPN box loss: 0.00685 RPN score loss: 0.00642 RPN total loss: 0.01326 Total loss: 0.83559 timestamp: 1654980216.0824118 iteration: 85135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04053 FastRCNN class loss: 0.06708 FastRCNN total loss: 0.10761 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.1086 RPN box loss: 0.00786 RPN score loss: 0.00439 RPN total loss: 0.01225 Total loss: 0.81587 timestamp: 1654980219.3070023 iteration: 85140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07654 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.12497 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.09517 RPN box loss: 0.00598 RPN score loss: 0.00103 RPN total loss: 0.00702 Total loss: 0.81457 timestamp: 1654980222.470803 iteration: 85145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08205 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.16184 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.1273 RPN box loss: 0.00873 RPN score loss: 0.00472 RPN total loss: 0.01345 Total loss: 0.89001 timestamp: 1654980225.6280985 iteration: 85150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08039 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.15023 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.15397 RPN box loss: 0.01459 RPN score loss: 0.00357 RPN total loss: 0.01816 Total loss: 0.90977 timestamp: 1654980228.780733 iteration: 85155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07008 FastRCNN class loss: 0.04202 FastRCNN total loss: 0.11209 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.09103 RPN box loss: 0.00454 RPN score loss: 0.00399 RPN total loss: 0.00852 Total loss: 0.79906 timestamp: 1654980231.9875808 iteration: 85160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07699 FastRCNN class loss: 0.06414 FastRCNN total loss: 0.14114 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.09111 RPN box loss: 0.01419 RPN score loss: 0.00241 RPN total loss: 0.0166 Total loss: 0.83626 timestamp: 1654980235.2626946 iteration: 85165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0587 FastRCNN class loss: 0.04068 FastRCNN total loss: 0.09938 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11108 RPN box loss: 0.00359 RPN score loss: 0.00423 RPN total loss: 0.00782 Total loss: 0.80569 timestamp: 1654980238.536916 iteration: 85170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08921 FastRCNN class loss: 0.0877 FastRCNN total loss: 0.1769 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.18988 RPN box loss: 0.0131 RPN score loss: 0.00235 RPN total loss: 0.01545 Total loss: 0.96964 timestamp: 1654980241.7881544 iteration: 85175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08122 FastRCNN class loss: 0.05628 FastRCNN total loss: 0.1375 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.09646 RPN box loss: 0.01142 RPN score loss: 0.00383 RPN total loss: 0.01525 Total loss: 0.83661 timestamp: 1654980245.0220327 iteration: 85180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1208 FastRCNN class loss: 0.10054 FastRCNN total loss: 0.22134 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.15077 RPN box loss: 0.0092 RPN score loss: 0.00413 RPN total loss: 0.01333 Total loss: 0.97286 timestamp: 1654980248.2875707 iteration: 85185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0653 FastRCNN class loss: 0.05031 FastRCNN total loss: 0.11561 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.12283 RPN box loss: 0.00473 RPN score loss: 0.00285 RPN total loss: 0.00758 Total loss: 0.83344 timestamp: 1654980251.4414027 iteration: 85190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07688 FastRCNN class loss: 0.06294 FastRCNN total loss: 0.13982 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11301 RPN box loss: 0.0079 RPN score loss: 0.00129 RPN total loss: 0.00919 Total loss: 0.84944 timestamp: 1654980254.6346502 iteration: 85195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14036 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.21952 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.12503 RPN box loss: 0.04429 RPN score loss: 0.0029 RPN total loss: 0.04719 Total loss: 0.97915 timestamp: 1654980257.7936718 iteration: 85200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12844 FastRCNN class loss: 0.07204 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14348 RPN box loss: 0.01014 RPN score loss: 0.00572 RPN total loss: 0.01586 Total loss: 0.94723 timestamp: 1654980260.9836473 iteration: 85205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06007 FastRCNN class loss: 0.05301 FastRCNN total loss: 0.11308 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.15084 RPN box loss: 0.00553 RPN score loss: 0.00067 RPN total loss: 0.0062 Total loss: 0.85753 timestamp: 1654980264.1256459 iteration: 85210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11901 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.17837 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13859 RPN box loss: 0.01842 RPN score loss: 0.0027 RPN total loss: 0.02112 Total loss: 0.92549 timestamp: 1654980267.3271024 iteration: 85215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11689 FastRCNN class loss: 0.06099 FastRCNN total loss: 0.17789 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13291 RPN box loss: 0.02214 RPN score loss: 0.0073 RPN total loss: 0.02945 Total loss: 0.92766 timestamp: 1654980270.6046474 iteration: 85220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11153 FastRCNN class loss: 0.07647 FastRCNN total loss: 0.188 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.08596 RPN box loss: 0.00946 RPN score loss: 0.00521 RPN total loss: 0.01466 Total loss: 0.87603 timestamp: 1654980273.7604818 iteration: 85225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10629 FastRCNN class loss: 0.08421 FastRCNN total loss: 0.19051 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.16055 RPN box loss: 0.0179 RPN score loss: 0.01738 RPN total loss: 0.03528 Total loss: 0.97375 timestamp: 1654980276.9314775 iteration: 85230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06447 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.13744 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.17577 RPN box loss: 0.01126 RPN score loss: 0.01154 RPN total loss: 0.0228 Total loss: 0.92343 timestamp: 1654980280.1894686 iteration: 85235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.14121 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10625 RPN box loss: 0.00579 RPN score loss: 0.00458 RPN total loss: 0.01036 Total loss: 0.84524 timestamp: 1654980283.333464 iteration: 85240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06861 FastRCNN class loss: 0.07817 FastRCNN total loss: 0.14678 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10212 RPN box loss: 0.00952 RPN score loss: 0.01078 RPN total loss: 0.0203 Total loss: 0.85661 timestamp: 1654980286.5471797 iteration: 85245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06062 FastRCNN class loss: 0.05131 FastRCNN total loss: 0.11193 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11175 RPN box loss: 0.0303 RPN score loss: 0.00247 RPN total loss: 0.03277 Total loss: 0.84386 timestamp: 1654980289.7489254 iteration: 85250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08928 FastRCNN class loss: 0.06073 FastRCNN total loss: 0.15001 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14212 RPN box loss: 0.00637 RPN score loss: 0.00239 RPN total loss: 0.00876 Total loss: 0.8883 timestamp: 1654980292.9377868 iteration: 85255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14016 FastRCNN class loss: 0.05853 FastRCNN total loss: 0.19869 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11928 RPN box loss: 0.00659 RPN score loss: 0.00488 RPN total loss: 0.01147 Total loss: 0.91685 timestamp: 1654980296.1353867 iteration: 85260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07341 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.13417 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13182 RPN box loss: 0.00764 RPN score loss: 0.00257 RPN total loss: 0.01021 Total loss: 0.8636 timestamp: 1654980299.3278513 iteration: 85265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08234 FastRCNN class loss: 0.04568 FastRCNN total loss: 0.12802 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.05477 RPN box loss: 0.00267 RPN score loss: 0.0017 RPN total loss: 0.00437 Total loss: 0.77457 timestamp: 1654980302.536175 iteration: 85270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07014 FastRCNN class loss: 0.06414 FastRCNN total loss: 0.13428 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14535 RPN box loss: 0.01056 RPN score loss: 0.00258 RPN total loss: 0.01314 Total loss: 0.88018 timestamp: 1654980305.7401886 iteration: 85275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06579 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.12985 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.12654 RPN box loss: 0.01275 RPN score loss: 0.00287 RPN total loss: 0.01561 Total loss: 0.85942 timestamp: 1654980308.9320936 iteration: 85280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08256 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.15486 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.09404 RPN box loss: 0.01728 RPN score loss: 0.01109 RPN total loss: 0.02837 Total loss: 0.86468 timestamp: 1654980312.174044 iteration: 85285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11214 FastRCNN class loss: 0.05031 FastRCNN total loss: 0.16246 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10224 RPN box loss: 0.0222 RPN score loss: 0.00047 RPN total loss: 0.02267 Total loss: 0.87477 timestamp: 1654980315.4061098 iteration: 85290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1266 FastRCNN class loss: 0.04373 FastRCNN total loss: 0.17033 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.08967 RPN box loss: 0.01105 RPN score loss: 0.00791 RPN total loss: 0.01896 Total loss: 0.86636 timestamp: 1654980318.6453977 iteration: 85295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06708 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.13647 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13792 RPN box loss: 0.0098 RPN score loss: 0.00084 RPN total loss: 0.01063 Total loss: 0.87243 timestamp: 1654980321.8517911 iteration: 85300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06327 FastRCNN class loss: 0.04085 FastRCNN total loss: 0.10412 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.15325 RPN box loss: 0.01034 RPN score loss: 0.00195 RPN total loss: 0.0123 Total loss: 0.85707 timestamp: 1654980325.0235052 iteration: 85305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.14086 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.17007 RPN box loss: 0.01543 RPN score loss: 0.00842 RPN total loss: 0.02386 Total loss: 0.92219 timestamp: 1654980328.2113454 iteration: 85310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.037 FastRCNN class loss: 0.04726 FastRCNN total loss: 0.08426 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.08402 RPN box loss: 0.00238 RPN score loss: 0.00327 RPN total loss: 0.00565 Total loss: 0.76133 timestamp: 1654980331.3851213 iteration: 85315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10457 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.16084 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.14806 RPN box loss: 0.01211 RPN score loss: 0.00118 RPN total loss: 0.01329 Total loss: 0.9096 timestamp: 1654980334.5158246 iteration: 85320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06596 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.12873 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13812 RPN box loss: 0.01908 RPN score loss: 0.00035 RPN total loss: 0.01944 Total loss: 0.8737 timestamp: 1654980337.6666768 iteration: 85325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06617 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.12026 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13311 RPN box loss: 0.00757 RPN score loss: 0.00488 RPN total loss: 0.01246 Total loss: 0.85324 timestamp: 1654980340.8432398 iteration: 85330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10886 FastRCNN class loss: 0.08028 FastRCNN total loss: 0.18914 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13555 RPN box loss: 0.01298 RPN score loss: 0.00612 RPN total loss: 0.0191 Total loss: 0.93119 timestamp: 1654980344.0115771 iteration: 85335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08089 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.15206 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11695 RPN box loss: 0.00701 RPN score loss: 0.00288 RPN total loss: 0.00989 Total loss: 0.86631 timestamp: 1654980347.1448443 iteration: 85340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07714 FastRCNN class loss: 0.05698 FastRCNN total loss: 0.13413 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10134 RPN box loss: 0.01979 RPN score loss: 0.00773 RPN total loss: 0.02752 Total loss: 0.85039 timestamp: 1654980350.316635 iteration: 85345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04974 FastRCNN class loss: 0.05067 FastRCNN total loss: 0.10041 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10379 RPN box loss: 0.01479 RPN score loss: 0.00583 RPN total loss: 0.02061 Total loss: 0.81222 timestamp: 1654980353.520506 iteration: 85350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05404 FastRCNN class loss: 0.04414 FastRCNN total loss: 0.09818 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10767 RPN box loss: 0.00891 RPN score loss: 0.01062 RPN total loss: 0.01953 Total loss: 0.81278 timestamp: 1654980356.7004237 iteration: 85355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15014 FastRCNN class loss: 0.08667 FastRCNN total loss: 0.2368 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.1472 RPN box loss: 0.01785 RPN score loss: 0.01583 RPN total loss: 0.03368 Total loss: 1.00509 timestamp: 1654980359.8186274 iteration: 85360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07881 FastRCNN class loss: 0.04342 FastRCNN total loss: 0.12223 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.10504 RPN box loss: 0.02291 RPN score loss: 0.0006 RPN total loss: 0.0235 Total loss: 0.83818 timestamp: 1654980363.0756805 iteration: 85365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03123 FastRCNN class loss: 0.03938 FastRCNN total loss: 0.07062 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.13991 RPN box loss: 0.00326 RPN score loss: 0.00157 RPN total loss: 0.00484 Total loss: 0.80277 timestamp: 1654980366.2524045 iteration: 85370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07923 FastRCNN class loss: 0.0511 FastRCNN total loss: 0.13033 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 4.0000e-05 Mask loss: 0.11902 RPN box loss: 0.00662 RPN score loss: 0.0109 RPN total loss: 0.01752 Total loss: 0.85428 timestamp: 1654980369.4756198 iteration: 85375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0932 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.161 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.16883 RPN box loss: 0.02684 RPN score loss: 0.00302 RPN total loss: 0.02985 Total loss: 0.94709 timestamp: 1654980372.7120728 iteration: 85380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14914 FastRCNN class loss: 0.06955 FastRCNN total loss: 0.21869 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11783 RPN box loss: 0.011 RPN score loss: 0.00488 RPN total loss: 0.01588 Total loss: 0.9398 timestamp: 1654980375.941231 iteration: 85385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07123 FastRCNN class loss: 0.0416 FastRCNN total loss: 0.11283 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09725 RPN box loss: 0.01833 RPN score loss: 0.00188 RPN total loss: 0.0202 Total loss: 0.81768 timestamp: 1654980379.1021166 iteration: 85390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0864 FastRCNN class loss: 0.08305 FastRCNN total loss: 0.16945 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13407 RPN box loss: 0.02033 RPN score loss: 0.00543 RPN total loss: 0.02576 Total loss: 0.91669 timestamp: 1654980382.239711 iteration: 85395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04687 FastRCNN class loss: 0.03733 FastRCNN total loss: 0.0842 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.10393 RPN box loss: 0.00957 RPN score loss: 0.00405 RPN total loss: 0.01362 Total loss: 0.78915 timestamp: 1654980385.3459694 iteration: 85400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08449 FastRCNN class loss: 0.05675 FastRCNN total loss: 0.14124 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11802 RPN box loss: 0.00652 RPN score loss: 0.00113 RPN total loss: 0.00765 Total loss: 0.85432 timestamp: 1654980388.5647426 iteration: 85405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05114 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.11826 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.08707 RPN box loss: 0.01451 RPN score loss: 0.00235 RPN total loss: 0.01686 Total loss: 0.80959 timestamp: 1654980391.7359111 iteration: 85410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06671 FastRCNN class loss: 0.03431 FastRCNN total loss: 0.10102 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.1142 RPN box loss: 0.0041 RPN score loss: 0.00039 RPN total loss: 0.00449 Total loss: 0.80711 timestamp: 1654980394.9301212 iteration: 85415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13123 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.18894 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.15429 RPN box loss: 0.00536 RPN score loss: 0.00542 RPN total loss: 0.01079 Total loss: 0.94142 timestamp: 1654980398.1366382 iteration: 85420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04614 FastRCNN class loss: 0.03562 FastRCNN total loss: 0.08176 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.08978 RPN box loss: 0.00562 RPN score loss: 0.00683 RPN total loss: 0.01245 Total loss: 0.7714 timestamp: 1654980401.3360586 iteration: 85425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.15286 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14827 RPN box loss: 0.01164 RPN score loss: 0.01204 RPN total loss: 0.02369 Total loss: 0.91222 timestamp: 1654980404.5136144 iteration: 85430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.055 FastRCNN class loss: 0.03281 FastRCNN total loss: 0.08782 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11712 RPN box loss: 0.01337 RPN score loss: 0.00107 RPN total loss: 0.01444 Total loss: 0.80678 timestamp: 1654980407.7061095 iteration: 85435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06225 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.11509 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11122 RPN box loss: 0.00899 RPN score loss: 0.00178 RPN total loss: 0.01077 Total loss: 0.82449 timestamp: 1654980410.9205382 iteration: 85440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10914 FastRCNN class loss: 0.073 FastRCNN total loss: 0.18214 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.19779 RPN box loss: 0.0175 RPN score loss: 0.00708 RPN total loss: 0.02458 Total loss: 0.99192 timestamp: 1654980414.1162767 iteration: 85445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05441 FastRCNN class loss: 0.03975 FastRCNN total loss: 0.09415 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11164 RPN box loss: 0.0065 RPN score loss: 0.003 RPN total loss: 0.00949 Total loss: 0.80269 timestamp: 1654980417.3832572 iteration: 85450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08208 FastRCNN class loss: 0.05867 FastRCNN total loss: 0.14076 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.10237 RPN box loss: 0.00248 RPN score loss: 0.00129 RPN total loss: 0.00377 Total loss: 0.8343 timestamp: 1654980420.5767179 iteration: 85455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.09321 FastRCNN total loss: 0.21719 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14527 RPN box loss: 0.01656 RPN score loss: 0.00831 RPN total loss: 0.02487 Total loss: 0.97473 timestamp: 1654980423.7525911 iteration: 85460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10139 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.16083 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09047 RPN box loss: 0.0172 RPN score loss: 0.00326 RPN total loss: 0.02046 Total loss: 0.85915 timestamp: 1654980426.9820585 iteration: 85465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08739 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.14948 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.15564 RPN box loss: 0.02125 RPN score loss: 0.00415 RPN total loss: 0.0254 Total loss: 0.91793 timestamp: 1654980430.1451364 iteration: 85470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10191 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.17504 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.15721 RPN box loss: 0.01158 RPN score loss: 0.00727 RPN total loss: 0.01885 Total loss: 0.9385 timestamp: 1654980433.3216522 iteration: 85475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08912 FastRCNN class loss: 0.0373 FastRCNN total loss: 0.12642 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.12174 RPN box loss: 0.01039 RPN score loss: 0.0034 RPN total loss: 0.01379 Total loss: 0.84935 timestamp: 1654980436.4364486 iteration: 85480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04643 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.08589 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09696 RPN box loss: 0.00575 RPN score loss: 0.00119 RPN total loss: 0.00695 Total loss: 0.7772 timestamp: 1654980439.6116142 iteration: 85485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0922 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.15173 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.22618 RPN box loss: 0.01023 RPN score loss: 0.00241 RPN total loss: 0.01264 Total loss: 0.97795 timestamp: 1654980442.82246 iteration: 85490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11223 FastRCNN class loss: 0.11173 FastRCNN total loss: 0.22395 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13508 RPN box loss: 0.01173 RPN score loss: 0.00356 RPN total loss: 0.01529 Total loss: 0.96172 timestamp: 1654980446.0117815 iteration: 85495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10041 FastRCNN class loss: 0.09316 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.12262 RPN box loss: 0.03614 RPN score loss: 0.00626 RPN total loss: 0.0424 Total loss: 0.94599 timestamp: 1654980449.2368321 iteration: 85500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06463 FastRCNN class loss: 0.04002 FastRCNN total loss: 0.10465 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09702 RPN box loss: 0.00371 RPN score loss: 0.00104 RPN total loss: 0.00476 Total loss: 0.79383 timestamp: 1654980452.4189558 iteration: 85505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05448 FastRCNN class loss: 0.06214 FastRCNN total loss: 0.11662 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13131 RPN box loss: 0.00737 RPN score loss: 0.00081 RPN total loss: 0.00817 Total loss: 0.8435 timestamp: 1654980455.621595 iteration: 85510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09944 FastRCNN class loss: 0.10066 FastRCNN total loss: 0.2001 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14668 RPN box loss: 0.01628 RPN score loss: 0.00463 RPN total loss: 0.02091 Total loss: 0.95509 timestamp: 1654980458.8183599 iteration: 85515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07159 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.13565 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14457 RPN box loss: 0.00779 RPN score loss: 0.01019 RPN total loss: 0.01798 Total loss: 0.8856 timestamp: 1654980461.9914258 iteration: 85520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11313 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.20457 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.19459 RPN box loss: 0.0099 RPN score loss: 0.00915 RPN total loss: 0.01906 Total loss: 1.00561 timestamp: 1654980465.185563 iteration: 85525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09314 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.16205 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.08875 RPN box loss: 0.00678 RPN score loss: 0.00091 RPN total loss: 0.0077 Total loss: 0.8459 timestamp: 1654980468.3483014 iteration: 85530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11111 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.17275 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.17276 RPN box loss: 0.00956 RPN score loss: 0.00561 RPN total loss: 0.01517 Total loss: 0.94808 timestamp: 1654980471.563935 iteration: 85535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07562 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.1653 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.15936 RPN box loss: 0.02171 RPN score loss: 0.01248 RPN total loss: 0.03419 Total loss: 0.94625 timestamp: 1654980474.7306895 iteration: 85540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07978 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.1467 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13568 RPN box loss: 0.00809 RPN score loss: 0.00735 RPN total loss: 0.01544 Total loss: 0.88522 timestamp: 1654980477.957951 iteration: 85545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14263 FastRCNN class loss: 0.09403 FastRCNN total loss: 0.23666 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.15175 RPN box loss: 0.02401 RPN score loss: 0.00579 RPN total loss: 0.0298 Total loss: 1.00561 timestamp: 1654980481.1051595 iteration: 85550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13825 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.19793 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.07925 RPN box loss: 0.02013 RPN score loss: 0.00088 RPN total loss: 0.02101 Total loss: 0.88559 timestamp: 1654980484.2432692 iteration: 85555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13267 FastRCNN class loss: 0.11911 FastRCNN total loss: 0.25178 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.21492 RPN box loss: 0.01255 RPN score loss: 0.00976 RPN total loss: 0.02231 Total loss: 1.07641 timestamp: 1654980487.3803434 iteration: 85560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05046 FastRCNN class loss: 0.03172 FastRCNN total loss: 0.08218 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09739 RPN box loss: 0.00985 RPN score loss: 0.01209 RPN total loss: 0.02193 Total loss: 0.78891 timestamp: 1654980490.5909564 iteration: 85565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.17628 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.17089 RPN box loss: 0.00893 RPN score loss: 0.00446 RPN total loss: 0.01339 Total loss: 0.94796 timestamp: 1654980493.777951 iteration: 85570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0438 FastRCNN class loss: 0.04739 FastRCNN total loss: 0.0912 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.12788 RPN box loss: 0.00793 RPN score loss: 0.00993 RPN total loss: 0.01786 Total loss: 0.82434 timestamp: 1654980496.9394894 iteration: 85575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12873 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.21694 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09665 RPN box loss: 0.00687 RPN score loss: 0.00293 RPN total loss: 0.0098 Total loss: 0.91079 timestamp: 1654980500.1652813 iteration: 85580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06502 FastRCNN class loss: 0.10011 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11668 RPN box loss: 0.02028 RPN score loss: 0.005 RPN total loss: 0.02528 Total loss: 0.89449 timestamp: 1654980503.3548982 iteration: 85585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09325 FastRCNN class loss: 0.06181 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09274 RPN box loss: 0.0116 RPN score loss: 0.00075 RPN total loss: 0.01235 Total loss: 0.84755 timestamp: 1654980506.6283383 iteration: 85590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08243 FastRCNN class loss: 0.07279 FastRCNN total loss: 0.15522 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11377 RPN box loss: 0.01833 RPN score loss: 0.01298 RPN total loss: 0.03131 Total loss: 0.8877 timestamp: 1654980509.8316536 iteration: 85595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07175 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.13945 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14413 RPN box loss: 0.01316 RPN score loss: 0.00481 RPN total loss: 0.01797 Total loss: 0.88894 timestamp: 1654980513.0109053 iteration: 85600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09957 FastRCNN class loss: 0.0859 FastRCNN total loss: 0.18547 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14773 RPN box loss: 0.00923 RPN score loss: 0.00312 RPN total loss: 0.01234 Total loss: 0.93294 timestamp: 1654980516.1876292 iteration: 85605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04786 FastRCNN class loss: 0.03716 FastRCNN total loss: 0.08502 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09564 RPN box loss: 0.00298 RPN score loss: 0.00105 RPN total loss: 0.00404 Total loss: 0.77209 timestamp: 1654980519.4672773 iteration: 85610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06234 FastRCNN class loss: 0.06432 FastRCNN total loss: 0.12666 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13171 RPN box loss: 0.01709 RPN score loss: 0.00253 RPN total loss: 0.01962 Total loss: 0.86538 timestamp: 1654980522.7061355 iteration: 85615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09834 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.15678 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.18493 RPN box loss: 0.00988 RPN score loss: 0.00158 RPN total loss: 0.01146 Total loss: 0.94057 timestamp: 1654980525.951323 iteration: 85620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11359 FastRCNN class loss: 0.05786 FastRCNN total loss: 0.17145 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.12859 RPN box loss: 0.04226 RPN score loss: 0.00133 RPN total loss: 0.04359 Total loss: 0.93103 timestamp: 1654980529.1253285 iteration: 85625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11121 FastRCNN class loss: 0.08801 FastRCNN total loss: 0.19922 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13331 RPN box loss: 0.01041 RPN score loss: 0.00237 RPN total loss: 0.01278 Total loss: 0.9327 timestamp: 1654980532.3135207 iteration: 85630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.089 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.17033 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13265 RPN box loss: 0.00788 RPN score loss: 0.00722 RPN total loss: 0.0151 Total loss: 0.90548 timestamp: 1654980535.5137637 iteration: 85635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16754 FastRCNN class loss: 0.05591 FastRCNN total loss: 0.22345 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.15868 RPN box loss: 0.00973 RPN score loss: 0.00627 RPN total loss: 0.016 Total loss: 0.98552 timestamp: 1654980538.746732 iteration: 85640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0553 FastRCNN class loss: 0.04799 FastRCNN total loss: 0.1033 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.09612 RPN box loss: 0.00597 RPN score loss: 0.00066 RPN total loss: 0.00663 Total loss: 0.79344 timestamp: 1654980541.9135137 iteration: 85645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05738 FastRCNN class loss: 0.03696 FastRCNN total loss: 0.09434 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11583 RPN box loss: 0.00986 RPN score loss: 0.00376 RPN total loss: 0.01362 Total loss: 0.81119 timestamp: 1654980545.184209 iteration: 85650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04478 FastRCNN class loss: 0.04246 FastRCNN total loss: 0.08724 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13162 RPN box loss: 0.01002 RPN score loss: 0.002 RPN total loss: 0.01203 Total loss: 0.81828 timestamp: 1654980548.413895 iteration: 85655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.06775 FastRCNN total loss: 0.1566 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.16173 RPN box loss: 0.00955 RPN score loss: 0.00425 RPN total loss: 0.01381 Total loss: 0.91953 timestamp: 1654980551.6125844 iteration: 85660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.15244 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.13473 RPN box loss: 0.02182 RPN score loss: 0.00229 RPN total loss: 0.02411 Total loss: 0.89867 timestamp: 1654980554.8935065 iteration: 85665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10875 FastRCNN class loss: 0.07382 FastRCNN total loss: 0.18257 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.1188 RPN box loss: 0.02047 RPN score loss: 0.01521 RPN total loss: 0.03568 Total loss: 0.92444 timestamp: 1654980558.0953076 iteration: 85670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06243 FastRCNN class loss: 0.03613 FastRCNN total loss: 0.09856 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.08611 RPN box loss: 0.00545 RPN score loss: 0.00097 RPN total loss: 0.00642 Total loss: 0.77849 timestamp: 1654980561.314986 iteration: 85675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04849 FastRCNN class loss: 0.04842 FastRCNN total loss: 0.09691 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.14345 RPN box loss: 0.00293 RPN score loss: 0.00364 RPN total loss: 0.00657 Total loss: 0.83432 timestamp: 1654980564.5201132 iteration: 85680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11175 FastRCNN class loss: 0.09098 FastRCNN total loss: 0.20273 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.16341 RPN box loss: 0.02298 RPN score loss: 0.00851 RPN total loss: 0.03149 Total loss: 0.98502 timestamp: 1654980567.7394233 iteration: 85685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09666 FastRCNN class loss: 0.07215 FastRCNN total loss: 0.16881 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.16331 RPN box loss: 0.01284 RPN score loss: 0.00441 RPN total loss: 0.01724 Total loss: 0.93675 timestamp: 1654980570.8758762 iteration: 85690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06755 FastRCNN class loss: 0.08448 FastRCNN total loss: 0.15203 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.11276 RPN box loss: 0.00854 RPN score loss: 0.00621 RPN total loss: 0.01475 Total loss: 0.86694 timestamp: 1654980574.0398169 iteration: 85695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07611 FastRCNN class loss: 0.06348 FastRCNN total loss: 0.13959 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 4.0000e-05 Mask loss: 0.10143 RPN box loss: 0.01152 RPN score loss: 0.01244 RPN total loss: 0.02396 Total loss: 0.85238 timestamp: 1654980577.2810655 iteration: 85700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13818 FastRCNN class loss: 0.08403 FastRCNN total loss: 0.22221 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13152 RPN box loss: 0.00559 RPN score loss: 0.0042 RPN total loss: 0.00979 Total loss: 0.95091 timestamp: 1654980580.4374125 iteration: 85705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06653 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.12393 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13374 RPN box loss: 0.00398 RPN score loss: 0.00246 RPN total loss: 0.00644 Total loss: 0.8515 timestamp: 1654980583.6600037 iteration: 85710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10635 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.17025 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.17494 RPN box loss: 0.00952 RPN score loss: 0.00844 RPN total loss: 0.01796 Total loss: 0.95054 timestamp: 1654980586.8864598 iteration: 85715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0757 FastRCNN class loss: 0.0513 FastRCNN total loss: 0.127 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13423 RPN box loss: 0.01865 RPN score loss: 0.00422 RPN total loss: 0.02287 Total loss: 0.87149 timestamp: 1654980590.091001 iteration: 85720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06008 FastRCNN class loss: 0.03624 FastRCNN total loss: 0.09632 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.09354 RPN box loss: 0.01076 RPN score loss: 0.00173 RPN total loss: 0.01249 Total loss: 0.78975 timestamp: 1654980593.300117 iteration: 85725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04836 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.09227 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11462 RPN box loss: 0.00583 RPN score loss: 0.00306 RPN total loss: 0.00889 Total loss: 0.80317 timestamp: 1654980596.4580636 iteration: 85730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08714 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.15758 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11538 RPN box loss: 0.01454 RPN score loss: 0.00262 RPN total loss: 0.01716 Total loss: 0.87751 timestamp: 1654980599.615077 iteration: 85735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05929 FastRCNN class loss: 0.04131 FastRCNN total loss: 0.1006 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.1246 RPN box loss: 0.00734 RPN score loss: 0.00308 RPN total loss: 0.01043 Total loss: 0.82302 timestamp: 1654980602.7960894 iteration: 85740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05327 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.11633 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.1173 RPN box loss: 0.02647 RPN score loss: 0.01004 RPN total loss: 0.03651 Total loss: 0.85755 timestamp: 1654980606.0722675 iteration: 85745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06677 FastRCNN class loss: 0.04835 FastRCNN total loss: 0.11513 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13014 RPN box loss: 0.00669 RPN score loss: 0.00426 RPN total loss: 0.01096 Total loss: 0.84362 timestamp: 1654980609.3127692 iteration: 85750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06872 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.15025 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.15382 RPN box loss: 0.01018 RPN score loss: 0.00582 RPN total loss: 0.016 Total loss: 0.90745 timestamp: 1654980612.5577712 iteration: 85755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04915 FastRCNN class loss: 0.05799 FastRCNN total loss: 0.10715 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.0988 RPN box loss: 0.01067 RPN score loss: 0.00604 RPN total loss: 0.01671 Total loss: 0.81005 timestamp: 1654980615.806676 iteration: 85760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07362 FastRCNN class loss: 0.0513 FastRCNN total loss: 0.12492 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.15334 RPN box loss: 0.0234 RPN score loss: 0.0071 RPN total loss: 0.0305 Total loss: 0.89615 timestamp: 1654980619.067867 iteration: 85765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06093 FastRCNN class loss: 0.06385 FastRCNN total loss: 0.12477 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13455 RPN box loss: 0.00456 RPN score loss: 0.00357 RPN total loss: 0.00812 Total loss: 0.85485 timestamp: 1654980622.2097988 iteration: 85770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08342 FastRCNN class loss: 0.08269 FastRCNN total loss: 0.16612 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.15366 RPN box loss: 0.03471 RPN score loss: 0.00444 RPN total loss: 0.03915 Total loss: 0.94631 timestamp: 1654980625.4882677 iteration: 85775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06273 FastRCNN class loss: 0.05292 FastRCNN total loss: 0.11565 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.14325 RPN box loss: 0.00548 RPN score loss: 0.00625 RPN total loss: 0.01173 Total loss: 0.85802 timestamp: 1654980628.7012377 iteration: 85780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05775 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.11906 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.10478 RPN box loss: 0.00655 RPN score loss: 0.00137 RPN total loss: 0.00791 Total loss: 0.81914 timestamp: 1654980631.901699 iteration: 85785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05936 FastRCNN class loss: 0.04693 FastRCNN total loss: 0.10629 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12886 RPN box loss: 0.00455 RPN score loss: 0.00466 RPN total loss: 0.00921 Total loss: 0.83176 timestamp: 1654980635.1136143 iteration: 85790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.13908 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11937 RPN box loss: 0.01986 RPN score loss: 0.01059 RPN total loss: 0.03046 Total loss: 0.87631 timestamp: 1654980638.3915286 iteration: 85795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04742 FastRCNN class loss: 0.03204 FastRCNN total loss: 0.07945 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11401 RPN box loss: 0.01083 RPN score loss: 0.00121 RPN total loss: 0.01204 Total loss: 0.7929 timestamp: 1654980641.5286143 iteration: 85800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13381 FastRCNN class loss: 0.11103 FastRCNN total loss: 0.24484 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.16068 RPN box loss: 0.01849 RPN score loss: 0.0055 RPN total loss: 0.024 Total loss: 1.01691 timestamp: 1654980644.744477 iteration: 85805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10893 FastRCNN class loss: 0.081 FastRCNN total loss: 0.18993 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11765 RPN box loss: 0.014 RPN score loss: 0.00876 RPN total loss: 0.02276 Total loss: 0.91774 timestamp: 1654980647.9709616 iteration: 85810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11637 FastRCNN class loss: 0.11171 FastRCNN total loss: 0.22809 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.17076 RPN box loss: 0.01311 RPN score loss: 0.00816 RPN total loss: 0.02126 Total loss: 1.0075 timestamp: 1654980651.1826713 iteration: 85815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09186 FastRCNN class loss: 0.07382 FastRCNN total loss: 0.16568 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.16374 RPN box loss: 0.01942 RPN score loss: 0.00761 RPN total loss: 0.02703 Total loss: 0.94384 timestamp: 1654980654.4080555 iteration: 85820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11082 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.17729 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.1205 RPN box loss: 0.00476 RPN score loss: 0.00237 RPN total loss: 0.00714 Total loss: 0.89232 timestamp: 1654980657.579456 iteration: 85825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05054 FastRCNN class loss: 0.04664 FastRCNN total loss: 0.09717 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12344 RPN box loss: 0.0091 RPN score loss: 0.00065 RPN total loss: 0.00976 Total loss: 0.81776 timestamp: 1654980660.8722074 iteration: 85830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09028 FastRCNN class loss: 0.07727 FastRCNN total loss: 0.16755 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.14123 RPN box loss: 0.02615 RPN score loss: 0.00377 RPN total loss: 0.02993 Total loss: 0.9261 timestamp: 1654980664.0393772 iteration: 85835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11732 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.17677 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11276 RPN box loss: 0.03031 RPN score loss: 0.00091 RPN total loss: 0.03122 Total loss: 0.90814 timestamp: 1654980667.2865553 iteration: 85840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09687 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.1552 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.27598 RPN box loss: 0.0172 RPN score loss: 0.00926 RPN total loss: 0.02646 Total loss: 1.04503 timestamp: 1654980670.436028 iteration: 85845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06634 FastRCNN class loss: 0.05785 FastRCNN total loss: 0.12419 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13649 RPN box loss: 0.0121 RPN score loss: 0.00215 RPN total loss: 0.01425 Total loss: 0.86231 timestamp: 1654980673.5910585 iteration: 85850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10739 FastRCNN class loss: 0.11166 FastRCNN total loss: 0.21905 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.17409 RPN box loss: 0.02277 RPN score loss: 0.00734 RPN total loss: 0.03011 Total loss: 1.01065 timestamp: 1654980676.802217 iteration: 85855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07485 FastRCNN class loss: 0.0662 FastRCNN total loss: 0.14105 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.17174 RPN box loss: 0.01151 RPN score loss: 0.0121 RPN total loss: 0.02362 Total loss: 0.92379 timestamp: 1654980679.9623244 iteration: 85860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05394 FastRCNN class loss: 0.04291 FastRCNN total loss: 0.09685 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.07037 RPN box loss: 0.0075 RPN score loss: 0.00222 RPN total loss: 0.00972 Total loss: 0.76433 timestamp: 1654980683.224093 iteration: 85865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05201 FastRCNN class loss: 0.05904 FastRCNN total loss: 0.11105 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.0957 RPN box loss: 0.00605 RPN score loss: 0.00172 RPN total loss: 0.00777 Total loss: 0.80191 timestamp: 1654980686.4044545 iteration: 85870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0571 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.13151 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.09255 RPN box loss: 0.01126 RPN score loss: 0.0018 RPN total loss: 0.01306 Total loss: 0.8245 timestamp: 1654980689.5170064 iteration: 85875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0488 FastRCNN class loss: 0.03786 FastRCNN total loss: 0.08667 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11203 RPN box loss: 0.00404 RPN score loss: 0.00736 RPN total loss: 0.0114 Total loss: 0.79748 timestamp: 1654980692.7084594 iteration: 85880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08635 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.1353 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.10639 RPN box loss: 0.01898 RPN score loss: 0.00072 RPN total loss: 0.0197 Total loss: 0.84878 timestamp: 1654980695.862385 iteration: 85885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1063 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.18377 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.18158 RPN box loss: 0.0079 RPN score loss: 0.01922 RPN total loss: 0.02712 Total loss: 0.97986 timestamp: 1654980699.1062348 iteration: 85890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07573 FastRCNN class loss: 0.08985 FastRCNN total loss: 0.16558 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.10981 RPN box loss: 0.01513 RPN score loss: 0.00422 RPN total loss: 0.01935 Total loss: 0.88212 timestamp: 1654980702.3371098 iteration: 85895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1245 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.17897 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11277 RPN box loss: 0.00624 RPN score loss: 0.00139 RPN total loss: 0.00763 Total loss: 0.88676 timestamp: 1654980705.5226078 iteration: 85900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10542 FastRCNN class loss: 0.05113 FastRCNN total loss: 0.15656 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.10546 RPN box loss: 0.01127 RPN score loss: 0.00109 RPN total loss: 0.01235 Total loss: 0.86176 timestamp: 1654980708.683999 iteration: 85905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0996 FastRCNN class loss: 0.05751 FastRCNN total loss: 0.15712 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.1704 RPN box loss: 0.03682 RPN score loss: 0.00678 RPN total loss: 0.0436 Total loss: 0.95851 timestamp: 1654980711.8739057 iteration: 85910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18009 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.26141 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.10884 RPN box loss: 0.00695 RPN score loss: 0.00487 RPN total loss: 0.01182 Total loss: 0.96945 timestamp: 1654980715.1248584 iteration: 85915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10455 FastRCNN class loss: 0.07767 FastRCNN total loss: 0.18222 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12147 RPN box loss: 0.01034 RPN score loss: 0.00459 RPN total loss: 0.01493 Total loss: 0.906 timestamp: 1654980718.280638 iteration: 85920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.074 FastRCNN class loss: 0.05661 FastRCNN total loss: 0.13061 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13458 RPN box loss: 0.0146 RPN score loss: 0.00361 RPN total loss: 0.01821 Total loss: 0.87078 timestamp: 1654980721.4251173 iteration: 85925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08798 FastRCNN class loss: 0.08329 FastRCNN total loss: 0.17127 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11149 RPN box loss: 0.01145 RPN score loss: 0.00778 RPN total loss: 0.01923 Total loss: 0.88937 timestamp: 1654980724.7758775 iteration: 85930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11761 FastRCNN class loss: 0.09706 FastRCNN total loss: 0.21467 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.14356 RPN box loss: 0.01293 RPN score loss: 0.00695 RPN total loss: 0.01988 Total loss: 0.9655 timestamp: 1654980727.9366462 iteration: 85935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1059 FastRCNN class loss: 0.05227 FastRCNN total loss: 0.15817 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.11331 RPN box loss: 0.02148 RPN score loss: 0.00509 RPN total loss: 0.02657 Total loss: 0.88544 timestamp: 1654980731.1478229 iteration: 85940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0531 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.10812 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.13603 RPN box loss: 0.00955 RPN score loss: 0.00725 RPN total loss: 0.01679 Total loss: 0.84832 timestamp: 1654980734.3787246 iteration: 85945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10695 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.19633 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.14974 RPN box loss: 0.03049 RPN score loss: 0.0094 RPN total loss: 0.03989 Total loss: 0.97334 timestamp: 1654980737.6479137 iteration: 85950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.06366 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12285 RPN box loss: 0.00978 RPN score loss: 0.00339 RPN total loss: 0.01318 Total loss: 0.88707 timestamp: 1654980740.8562639 iteration: 85955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13156 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.20402 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12422 RPN box loss: 0.01555 RPN score loss: 0.00238 RPN total loss: 0.01792 Total loss: 0.93355 timestamp: 1654980744.1114295 iteration: 85960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09441 FastRCNN class loss: 0.06593 FastRCNN total loss: 0.16033 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12666 RPN box loss: 0.00585 RPN score loss: 0.00298 RPN total loss: 0.00884 Total loss: 0.88321 timestamp: 1654980747.250555 iteration: 85965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1004 FastRCNN class loss: 0.07324 FastRCNN total loss: 0.17364 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.14806 RPN box loss: 0.01199 RPN score loss: 0.01154 RPN total loss: 0.02352 Total loss: 0.9326 timestamp: 1654980750.4506218 iteration: 85970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06996 FastRCNN class loss: 0.04126 FastRCNN total loss: 0.11123 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.12189 RPN box loss: 0.00729 RPN score loss: 0.00052 RPN total loss: 0.00781 Total loss: 0.82831 timestamp: 1654980753.6305046 iteration: 85975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09302 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.18007 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.17042 RPN box loss: 0.00633 RPN score loss: 0.00305 RPN total loss: 0.00937 Total loss: 0.94724 timestamp: 1654980756.7990859 iteration: 85980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07965 FastRCNN class loss: 0.05054 FastRCNN total loss: 0.13019 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.15229 RPN box loss: 0.01511 RPN score loss: 0.0039 RPN total loss: 0.01901 Total loss: 0.88887 timestamp: 1654980759.9227338 iteration: 85985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07135 FastRCNN class loss: 0.05765 FastRCNN total loss: 0.12901 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.17045 RPN box loss: 0.02752 RPN score loss: 0.00461 RPN total loss: 0.03213 Total loss: 0.91897 timestamp: 1654980763.1474621 iteration: 85990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1161 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.19764 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 4.0000e-05 Mask loss: 0.10672 RPN box loss: 0.01451 RPN score loss: 0.00409 RPN total loss: 0.0186 Total loss: 0.91035 timestamp: 1654980766.2406032 iteration: 85995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03823 FastRCNN class loss: 0.0214 FastRCNN total loss: 0.05964 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.09743 RPN box loss: 0.00115 RPN score loss: 0.00064 RPN total loss: 0.00179 Total loss: 0.74625 timestamp: 1654980769.4505012 iteration: 86000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0543 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.10064 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12274 RPN box loss: 0.01037 RPN score loss: 0.00078 RPN total loss: 0.01115 Total loss: 0.82191 timestamp: 1654980772.6231544 iteration: 86005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11155 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.17433 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.09313 RPN box loss: 0.0074 RPN score loss: 0.0033 RPN total loss: 0.0107 Total loss: 0.86555 timestamp: 1654980775.8312657 iteration: 86010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07359 FastRCNN class loss: 0.10437 FastRCNN total loss: 0.17797 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.1515 RPN box loss: 0.01793 RPN score loss: 0.00398 RPN total loss: 0.02191 Total loss: 0.93877 timestamp: 1654980779.0059223 iteration: 86015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09809 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.1688 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13081 RPN box loss: 0.00587 RPN score loss: 0.00853 RPN total loss: 0.0144 Total loss: 0.90139 timestamp: 1654980782.2994823 iteration: 86020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13643 FastRCNN class loss: 0.08422 FastRCNN total loss: 0.22065 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.15167 RPN box loss: 0.02138 RPN score loss: 0.00333 RPN total loss: 0.0247 Total loss: 0.9844 timestamp: 1654980785.4977643 iteration: 86025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18088 FastRCNN class loss: 0.07796 FastRCNN total loss: 0.25884 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.10063 RPN box loss: 0.03347 RPN score loss: 0.00573 RPN total loss: 0.0392 Total loss: 0.98605 timestamp: 1654980788.760709 iteration: 86030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0472 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.10202 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.22392 RPN box loss: 0.00773 RPN score loss: 0.0043 RPN total loss: 0.01204 Total loss: 0.92535 timestamp: 1654980791.96574 iteration: 86035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05433 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.14052 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13898 RPN box loss: 0.01825 RPN score loss: 0.00724 RPN total loss: 0.02549 Total loss: 0.89237 timestamp: 1654980795.175308 iteration: 86040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12607 FastRCNN class loss: 0.07929 FastRCNN total loss: 0.20536 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.16353 RPN box loss: 0.00745 RPN score loss: 0.00249 RPN total loss: 0.00994 Total loss: 0.96621 timestamp: 1654980798.3299203 iteration: 86045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09605 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.1627 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.20369 RPN box loss: 0.01596 RPN score loss: 0.00708 RPN total loss: 0.02304 Total loss: 0.97681 timestamp: 1654980801.5391254 iteration: 86050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07221 FastRCNN class loss: 0.04521 FastRCNN total loss: 0.11742 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.17119 RPN box loss: 0.02738 RPN score loss: 0.00294 RPN total loss: 0.03032 Total loss: 0.90632 timestamp: 1654980804.7134504 iteration: 86055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04643 FastRCNN class loss: 0.0498 FastRCNN total loss: 0.09624 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.08952 RPN box loss: 0.02841 RPN score loss: 0.00287 RPN total loss: 0.03128 Total loss: 0.80442 timestamp: 1654980807.8726523 iteration: 86060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09422 FastRCNN class loss: 0.07291 FastRCNN total loss: 0.16712 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14944 RPN box loss: 0.0222 RPN score loss: 0.01212 RPN total loss: 0.03431 Total loss: 0.93826 timestamp: 1654980811.0440388 iteration: 86065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05243 FastRCNN class loss: 0.05608 FastRCNN total loss: 0.10851 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.09879 RPN box loss: 0.00921 RPN score loss: 0.00083 RPN total loss: 0.01004 Total loss: 0.80472 timestamp: 1654980814.2333767 iteration: 86070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13422 FastRCNN class loss: 0.0919 FastRCNN total loss: 0.22612 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.15074 RPN box loss: 0.01881 RPN score loss: 0.00415 RPN total loss: 0.02296 Total loss: 0.98721 timestamp: 1654980817.3401577 iteration: 86075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10749 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.17998 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11608 RPN box loss: 0.0055 RPN score loss: 0.00382 RPN total loss: 0.00932 Total loss: 0.89276 timestamp: 1654980820.5599728 iteration: 86080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.04118 FastRCNN total loss: 0.10358 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.09825 RPN box loss: 0.01001 RPN score loss: 0.00068 RPN total loss: 0.01069 Total loss: 0.79991 timestamp: 1654980823.7327874 iteration: 86085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04543 FastRCNN class loss: 0.04987 FastRCNN total loss: 0.0953 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.10244 RPN box loss: 0.0053 RPN score loss: 0.00321 RPN total loss: 0.00851 Total loss: 0.79363 timestamp: 1654980826.9360538 iteration: 86090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08632 FastRCNN class loss: 0.06508 FastRCNN total loss: 0.15139 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11685 RPN box loss: 0.01084 RPN score loss: 0.00157 RPN total loss: 0.01241 Total loss: 0.86804 timestamp: 1654980830.1286848 iteration: 86095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.06886 FastRCNN total loss: 0.16343 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14692 RPN box loss: 0.00695 RPN score loss: 0.00173 RPN total loss: 0.00868 Total loss: 0.9064 timestamp: 1654980833.289457 iteration: 86100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05634 FastRCNN class loss: 0.05408 FastRCNN total loss: 0.11041 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13026 RPN box loss: 0.01327 RPN score loss: 0.00655 RPN total loss: 0.01982 Total loss: 0.84787 timestamp: 1654980836.4681876 iteration: 86105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.16895 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.1631 RPN box loss: 0.00791 RPN score loss: 0.00227 RPN total loss: 0.01018 Total loss: 0.92962 timestamp: 1654980839.642163 iteration: 86110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09976 FastRCNN class loss: 0.0453 FastRCNN total loss: 0.14506 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.06823 RPN box loss: 0.00624 RPN score loss: 0.00135 RPN total loss: 0.00759 Total loss: 0.80827 timestamp: 1654980842.8051724 iteration: 86115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06364 FastRCNN class loss: 0.04264 FastRCNN total loss: 0.10629 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14556 RPN box loss: 0.01172 RPN score loss: 0.00458 RPN total loss: 0.0163 Total loss: 0.85553 timestamp: 1654980845.9778035 iteration: 86120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11503 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.19251 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11579 RPN box loss: 0.00895 RPN score loss: 0.00447 RPN total loss: 0.01342 Total loss: 0.90909 timestamp: 1654980849.173471 iteration: 86125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06562 FastRCNN class loss: 0.07732 FastRCNN total loss: 0.14295 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.10755 RPN box loss: 0.00492 RPN score loss: 0.00244 RPN total loss: 0.00736 Total loss: 0.84524 timestamp: 1654980852.3782735 iteration: 86130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13236 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.2159 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14069 RPN box loss: 0.01392 RPN score loss: 0.00376 RPN total loss: 0.01768 Total loss: 0.96165 timestamp: 1654980855.5764947 iteration: 86135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06171 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.11916 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11456 RPN box loss: 0.01106 RPN score loss: 0.00176 RPN total loss: 0.01282 Total loss: 0.83391 timestamp: 1654980858.8300827 iteration: 86140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08434 FastRCNN class loss: 0.04514 FastRCNN total loss: 0.12948 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.08369 RPN box loss: 0.00917 RPN score loss: 0.00275 RPN total loss: 0.01192 Total loss: 0.81247 timestamp: 1654980862.0777133 iteration: 86145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13051 FastRCNN class loss: 0.08729 FastRCNN total loss: 0.2178 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12377 RPN box loss: 0.00647 RPN score loss: 0.00499 RPN total loss: 0.01147 Total loss: 0.94042 timestamp: 1654980865.2210238 iteration: 86150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0507 FastRCNN class loss: 0.04362 FastRCNN total loss: 0.09432 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.08572 RPN box loss: 0.01593 RPN score loss: 0.00219 RPN total loss: 0.01811 Total loss: 0.78554 timestamp: 1654980868.423693 iteration: 86155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0844 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.16003 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.10932 RPN box loss: 0.01192 RPN score loss: 0.00419 RPN total loss: 0.01611 Total loss: 0.87284 timestamp: 1654980871.6740952 iteration: 86160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10526 FastRCNN class loss: 0.05008 FastRCNN total loss: 0.15533 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.09098 RPN box loss: 0.00434 RPN score loss: 0.00037 RPN total loss: 0.00471 Total loss: 0.83841 timestamp: 1654980874.852577 iteration: 86165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07649 FastRCNN class loss: 0.05325 FastRCNN total loss: 0.12974 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12765 RPN box loss: 0.0161 RPN score loss: 0.00644 RPN total loss: 0.02254 Total loss: 0.86732 timestamp: 1654980878.0006268 iteration: 86170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1409 FastRCNN class loss: 0.12331 FastRCNN total loss: 0.26421 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12649 RPN box loss: 0.00814 RPN score loss: 0.00588 RPN total loss: 0.01402 Total loss: 0.9921 timestamp: 1654980881.1042645 iteration: 86175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12554 FastRCNN class loss: 0.08298 FastRCNN total loss: 0.20852 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.19087 RPN box loss: 0.01114 RPN score loss: 0.00649 RPN total loss: 0.01763 Total loss: 1.00439 timestamp: 1654980884.306315 iteration: 86180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05767 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.10786 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.07922 RPN box loss: 0.00477 RPN score loss: 0.00273 RPN total loss: 0.0075 Total loss: 0.78196 timestamp: 1654980887.4881723 iteration: 86185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11436 FastRCNN class loss: 0.10627 FastRCNN total loss: 0.22063 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.16554 RPN box loss: 0.03102 RPN score loss: 0.00618 RPN total loss: 0.0372 Total loss: 1.01075 timestamp: 1654980890.627709 iteration: 86190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05024 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.10062 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.16231 RPN box loss: 0.01221 RPN score loss: 0.00381 RPN total loss: 0.01603 Total loss: 0.86633 timestamp: 1654980893.818886 iteration: 86195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07021 FastRCNN class loss: 0.04092 FastRCNN total loss: 0.11114 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12811 RPN box loss: 0.0059 RPN score loss: 0.00245 RPN total loss: 0.00836 Total loss: 0.83498 timestamp: 1654980897.0257845 iteration: 86200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0468 FastRCNN class loss: 0.03493 FastRCNN total loss: 0.08173 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.08883 RPN box loss: 0.00716 RPN score loss: 0.00104 RPN total loss: 0.00819 Total loss: 0.76613 timestamp: 1654980900.2827373 iteration: 86205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07532 FastRCNN class loss: 0.04842 FastRCNN total loss: 0.12374 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11487 RPN box loss: 0.00777 RPN score loss: 0.00505 RPN total loss: 0.01282 Total loss: 0.8388 timestamp: 1654980903.561797 iteration: 86210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05591 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.11583 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11782 RPN box loss: 0.01043 RPN score loss: 0.00253 RPN total loss: 0.01296 Total loss: 0.83399 timestamp: 1654980906.7379758 iteration: 86215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08651 FastRCNN class loss: 0.05554 FastRCNN total loss: 0.14204 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11694 RPN box loss: 0.03152 RPN score loss: 0.00632 RPN total loss: 0.03784 Total loss: 0.8842 timestamp: 1654980909.93491 iteration: 86220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06357 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.12838 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.01565 RPN score loss: 0.00419 RPN total loss: 0.01984 Total loss: 0.892 timestamp: 1654980913.0941584 iteration: 86225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08614 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.14557 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11115 RPN box loss: 0.00731 RPN score loss: 0.00533 RPN total loss: 0.01264 Total loss: 0.85674 timestamp: 1654980916.3315833 iteration: 86230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11532 FastRCNN class loss: 0.0799 FastRCNN total loss: 0.19522 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12379 RPN box loss: 0.00883 RPN score loss: 0.00587 RPN total loss: 0.0147 Total loss: 0.92109 timestamp: 1654980919.4763772 iteration: 86235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06607 FastRCNN class loss: 0.06136 FastRCNN total loss: 0.12743 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13952 RPN box loss: 0.01031 RPN score loss: 0.00298 RPN total loss: 0.01328 Total loss: 0.86761 timestamp: 1654980922.7010703 iteration: 86240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10005 FastRCNN class loss: 0.0793 FastRCNN total loss: 0.17935 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13109 RPN box loss: 0.01587 RPN score loss: 0.00448 RPN total loss: 0.02035 Total loss: 0.91817 timestamp: 1654980925.848732 iteration: 86245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09215 FastRCNN class loss: 0.04053 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.10178 RPN box loss: 0.00277 RPN score loss: 0.00176 RPN total loss: 0.00453 Total loss: 0.82636 timestamp: 1654980928.985606 iteration: 86250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05833 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.10122 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13397 RPN box loss: 0.00817 RPN score loss: 0.00116 RPN total loss: 0.00933 Total loss: 0.83189 timestamp: 1654980932.1287754 iteration: 86255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.04666 FastRCNN total loss: 0.12048 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.0928 RPN box loss: 0.00397 RPN score loss: 0.00048 RPN total loss: 0.00446 Total loss: 0.80511 timestamp: 1654980935.3847373 iteration: 86260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09585 FastRCNN class loss: 0.11416 FastRCNN total loss: 0.21001 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13954 RPN box loss: 0.02205 RPN score loss: 0.00149 RPN total loss: 0.02354 Total loss: 0.96047 timestamp: 1654980938.5767655 iteration: 86265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08551 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.15201 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14333 RPN box loss: 0.00835 RPN score loss: 0.00679 RPN total loss: 0.01514 Total loss: 0.89786 timestamp: 1654980941.7801719 iteration: 86270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09683 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.15515 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14896 RPN box loss: 0.01399 RPN score loss: 0.00683 RPN total loss: 0.02081 Total loss: 0.9123 timestamp: 1654980944.976845 iteration: 86275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10122 FastRCNN class loss: 0.05217 FastRCNN total loss: 0.15339 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.09952 RPN box loss: 0.01091 RPN score loss: 0.00064 RPN total loss: 0.01155 Total loss: 0.85183 timestamp: 1654980948.194735 iteration: 86280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06575 FastRCNN class loss: 0.03663 FastRCNN total loss: 0.10238 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12126 RPN box loss: 0.0041 RPN score loss: 0.00368 RPN total loss: 0.00778 Total loss: 0.81879 timestamp: 1654980951.4778345 iteration: 86285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09142 FastRCNN class loss: 0.08551 FastRCNN total loss: 0.17693 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.11316 RPN box loss: 0.00982 RPN score loss: 0.00852 RPN total loss: 0.01834 Total loss: 0.8958 timestamp: 1654980954.6387973 iteration: 86290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07762 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.13945 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.14692 RPN box loss: 0.01949 RPN score loss: 0.0067 RPN total loss: 0.02619 Total loss: 0.89994 timestamp: 1654980957.845181 iteration: 86295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.06141 FastRCNN total loss: 0.17818 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.12025 RPN box loss: 0.00828 RPN score loss: 0.00451 RPN total loss: 0.01279 Total loss: 0.89859 timestamp: 1654980961.055345 iteration: 86300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.14421 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13852 RPN box loss: 0.00729 RPN score loss: 0.00248 RPN total loss: 0.00978 Total loss: 0.87989 timestamp: 1654980964.2976294 iteration: 86305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0929 FastRCNN class loss: 0.10384 FastRCNN total loss: 0.19674 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.15982 RPN box loss: 0.01543 RPN score loss: 0.00448 RPN total loss: 0.0199 Total loss: 0.96384 timestamp: 1654980967.6016955 iteration: 86310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07257 FastRCNN class loss: 0.0701 FastRCNN total loss: 0.14267 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.21267 RPN box loss: 0.01917 RPN score loss: 0.0069 RPN total loss: 0.02607 Total loss: 0.96878 timestamp: 1654980970.7861135 iteration: 86315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06681 FastRCNN class loss: 0.057 FastRCNN total loss: 0.12382 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.10393 RPN box loss: 0.00558 RPN score loss: 0.00327 RPN total loss: 0.00885 Total loss: 0.82398 timestamp: 1654980974.0445952 iteration: 86320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09478 FastRCNN class loss: 0.11967 FastRCNN total loss: 0.21445 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 4.0000e-05 Mask loss: 0.13416 RPN box loss: 0.02786 RPN score loss: 0.00516 RPN total loss: 0.03302 Total loss: 0.96901 timestamp: 1654980977.304119 iteration: 86325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08438 FastRCNN class loss: 0.04852 FastRCNN total loss: 0.1329 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.11469 RPN box loss: 0.00897 RPN score loss: 0.00478 RPN total loss: 0.01375 Total loss: 0.84871 timestamp: 1654980980.5406897 iteration: 86330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12874 FastRCNN class loss: 0.07424 FastRCNN total loss: 0.20298 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13801 RPN box loss: 0.03144 RPN score loss: 0.00221 RPN total loss: 0.03365 Total loss: 0.96201 timestamp: 1654980983.6534188 iteration: 86335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08443 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.14896 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14721 RPN box loss: 0.02142 RPN score loss: 0.00809 RPN total loss: 0.02952 Total loss: 0.91306 timestamp: 1654980986.874856 iteration: 86340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04612 FastRCNN class loss: 0.03907 FastRCNN total loss: 0.08519 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.1013 RPN box loss: 0.0043 RPN score loss: 0.00101 RPN total loss: 0.00531 Total loss: 0.77917 timestamp: 1654980990.1100254 iteration: 86345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.18746 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.1633 RPN box loss: 0.01542 RPN score loss: 0.00187 RPN total loss: 0.01729 Total loss: 0.95542 timestamp: 1654980993.3480144 iteration: 86350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08014 FastRCNN class loss: 0.0768 FastRCNN total loss: 0.15694 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10614 RPN box loss: 0.02623 RPN score loss: 0.00561 RPN total loss: 0.03183 Total loss: 0.88228 timestamp: 1654980996.5950274 iteration: 86355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11422 FastRCNN class loss: 0.09967 FastRCNN total loss: 0.21389 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13575 RPN box loss: 0.02101 RPN score loss: 0.00927 RPN total loss: 0.03028 Total loss: 0.96729 timestamp: 1654980999.85905 iteration: 86360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17006 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.24206 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.1139 RPN box loss: 0.00607 RPN score loss: 0.00196 RPN total loss: 0.00803 Total loss: 0.95136 timestamp: 1654981003.0882783 iteration: 86365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13923 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.2128 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14409 RPN box loss: 0.0072 RPN score loss: 0.00536 RPN total loss: 0.01257 Total loss: 0.95683 timestamp: 1654981006.2772596 iteration: 86370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06839 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.13094 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12062 RPN box loss: 0.00441 RPN score loss: 0.00177 RPN total loss: 0.00618 Total loss: 0.84511 timestamp: 1654981009.488383 iteration: 86375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07631 FastRCNN class loss: 0.04417 FastRCNN total loss: 0.12048 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.08609 RPN box loss: 0.0054 RPN score loss: 0.00112 RPN total loss: 0.00651 Total loss: 0.80045 timestamp: 1654981012.697045 iteration: 86380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10726 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.17127 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10504 RPN box loss: 0.01235 RPN score loss: 0.00165 RPN total loss: 0.01399 Total loss: 0.87768 timestamp: 1654981015.8983173 iteration: 86385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06097 FastRCNN class loss: 0.05264 FastRCNN total loss: 0.11362 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.15815 RPN box loss: 0.00817 RPN score loss: 0.00356 RPN total loss: 0.01173 Total loss: 0.87087 timestamp: 1654981019.0829163 iteration: 86390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04444 FastRCNN class loss: 0.04104 FastRCNN total loss: 0.08548 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14963 RPN box loss: 0.0055 RPN score loss: 0.0012 RPN total loss: 0.0067 Total loss: 0.82919 timestamp: 1654981022.327781 iteration: 86395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05452 FastRCNN class loss: 0.07042 FastRCNN total loss: 0.12494 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12456 RPN box loss: 0.00536 RPN score loss: 0.00537 RPN total loss: 0.01073 Total loss: 0.84761 timestamp: 1654981025.5737908 iteration: 86400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09473 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.16004 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12257 RPN box loss: 0.00596 RPN score loss: 0.00523 RPN total loss: 0.01119 Total loss: 0.88118 timestamp: 1654981028.8216634 iteration: 86405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07489 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.15706 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13753 RPN box loss: 0.01154 RPN score loss: 0.00785 RPN total loss: 0.01939 Total loss: 0.90136 timestamp: 1654981031.974278 iteration: 86410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06166 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.12326 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.11528 RPN box loss: 0.0127 RPN score loss: 0.00821 RPN total loss: 0.02091 Total loss: 0.84683 timestamp: 1654981035.2252188 iteration: 86415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09248 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.16797 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.16603 RPN box loss: 0.00876 RPN score loss: 0.00339 RPN total loss: 0.01215 Total loss: 0.93353 timestamp: 1654981038.4084263 iteration: 86420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07523 FastRCNN class loss: 0.06196 FastRCNN total loss: 0.13719 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12908 RPN box loss: 0.00794 RPN score loss: 0.00292 RPN total loss: 0.01086 Total loss: 0.8645 timestamp: 1654981041.6517646 iteration: 86425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10046 FastRCNN class loss: 0.08421 FastRCNN total loss: 0.18467 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.17232 RPN box loss: 0.01263 RPN score loss: 0.00278 RPN total loss: 0.01541 Total loss: 0.95977 timestamp: 1654981044.9181504 iteration: 86430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07889 FastRCNN class loss: 0.06424 FastRCNN total loss: 0.14313 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.11051 RPN box loss: 0.008 RPN score loss: 0.00168 RPN total loss: 0.00969 Total loss: 0.8507 timestamp: 1654981048.102365 iteration: 86435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07905 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.1459 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.15154 RPN box loss: 0.00617 RPN score loss: 0.01047 RPN total loss: 0.01664 Total loss: 0.90145 timestamp: 1654981051.3019252 iteration: 86440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07185 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.12682 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13006 RPN box loss: 0.00707 RPN score loss: 0.00287 RPN total loss: 0.00994 Total loss: 0.85419 timestamp: 1654981054.4467404 iteration: 86445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09553 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.15903 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13234 RPN box loss: 0.009 RPN score loss: 0.00105 RPN total loss: 0.01004 Total loss: 0.88879 timestamp: 1654981057.6363292 iteration: 86450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07193 FastRCNN class loss: 0.09049 FastRCNN total loss: 0.16242 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14972 RPN box loss: 0.00835 RPN score loss: 0.00381 RPN total loss: 0.01217 Total loss: 0.91167 timestamp: 1654981060.8477726 iteration: 86455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06009 FastRCNN class loss: 0.05509 FastRCNN total loss: 0.11518 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14141 RPN box loss: 0.00659 RPN score loss: 0.00181 RPN total loss: 0.0084 Total loss: 0.85236 timestamp: 1654981064.0368028 iteration: 86460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14241 FastRCNN class loss: 0.0803 FastRCNN total loss: 0.22271 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12677 RPN box loss: 0.01589 RPN score loss: 0.00121 RPN total loss: 0.0171 Total loss: 0.95395 timestamp: 1654981067.2585483 iteration: 86465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.19958 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14094 RPN box loss: 0.00804 RPN score loss: 0.00227 RPN total loss: 0.01031 Total loss: 0.9382 timestamp: 1654981070.4656627 iteration: 86470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08264 FastRCNN class loss: 0.05785 FastRCNN total loss: 0.14049 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.1512 RPN box loss: 0.00614 RPN score loss: 0.00264 RPN total loss: 0.00878 Total loss: 0.88784 timestamp: 1654981073.6524584 iteration: 86475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0593 FastRCNN class loss: 0.05602 FastRCNN total loss: 0.11532 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.09685 RPN box loss: 0.00833 RPN score loss: 0.00391 RPN total loss: 0.01223 Total loss: 0.81177 timestamp: 1654981076.8515055 iteration: 86480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09674 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.1722 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.09209 RPN box loss: 0.0036 RPN score loss: 0.00412 RPN total loss: 0.00772 Total loss: 0.85938 timestamp: 1654981079.9862547 iteration: 86485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.04995 FastRCNN total loss: 0.12912 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12222 RPN box loss: 0.00596 RPN score loss: 0.00181 RPN total loss: 0.00777 Total loss: 0.84647 timestamp: 1654981083.2268581 iteration: 86490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11862 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.19626 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.15489 RPN box loss: 0.00781 RPN score loss: 0.00851 RPN total loss: 0.01632 Total loss: 0.95484 timestamp: 1654981086.3980305 iteration: 86495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12215 FastRCNN class loss: 0.06175 FastRCNN total loss: 0.1839 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13504 RPN box loss: 0.00779 RPN score loss: 0.00222 RPN total loss: 0.01001 Total loss: 0.91632 timestamp: 1654981089.6230624 iteration: 86500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07192 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.12005 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12493 RPN box loss: 0.00363 RPN score loss: 0.00312 RPN total loss: 0.00675 Total loss: 0.8391 timestamp: 1654981092.8393917 iteration: 86505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07007 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.13095 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.16458 RPN box loss: 0.02742 RPN score loss: 0.00759 RPN total loss: 0.035 Total loss: 0.91789 timestamp: 1654981096.0673106 iteration: 86510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11236 FastRCNN class loss: 0.08571 FastRCNN total loss: 0.19807 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10217 RPN box loss: 0.00687 RPN score loss: 0.00915 RPN total loss: 0.01602 Total loss: 0.90363 timestamp: 1654981099.3310893 iteration: 86515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12044 FastRCNN class loss: 0.07941 FastRCNN total loss: 0.19985 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13054 RPN box loss: 0.0052 RPN score loss: 0.00427 RPN total loss: 0.00947 Total loss: 0.92723 timestamp: 1654981102.5827727 iteration: 86520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09111 FastRCNN class loss: 0.05396 FastRCNN total loss: 0.14507 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12369 RPN box loss: 0.00676 RPN score loss: 0.00218 RPN total loss: 0.00894 Total loss: 0.86506 timestamp: 1654981105.7926357 iteration: 86525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07446 FastRCNN class loss: 0.07344 FastRCNN total loss: 0.1479 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14116 RPN box loss: 0.01363 RPN score loss: 0.00197 RPN total loss: 0.0156 Total loss: 0.89203 timestamp: 1654981108.9804509 iteration: 86530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08607 FastRCNN class loss: 0.08274 FastRCNN total loss: 0.16881 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10593 RPN box loss: 0.00983 RPN score loss: 0.00361 RPN total loss: 0.01344 Total loss: 0.87555 timestamp: 1654981112.1196175 iteration: 86535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0772 FastRCNN class loss: 0.10462 FastRCNN total loss: 0.18182 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.1602 RPN box loss: 0.00834 RPN score loss: 0.00282 RPN total loss: 0.01117 Total loss: 0.94055 timestamp: 1654981115.3218634 iteration: 86540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1069 FastRCNN class loss: 0.07151 FastRCNN total loss: 0.1784 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.16023 RPN box loss: 0.00812 RPN score loss: 0.00676 RPN total loss: 0.01488 Total loss: 0.94088 timestamp: 1654981118.5128827 iteration: 86545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11687 FastRCNN class loss: 0.12801 FastRCNN total loss: 0.24488 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.2087 RPN box loss: 0.01961 RPN score loss: 0.02357 RPN total loss: 0.04318 Total loss: 1.08412 timestamp: 1654981121.7798142 iteration: 86550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04713 FastRCNN class loss: 0.03705 FastRCNN total loss: 0.08418 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.11155 RPN box loss: 0.00212 RPN score loss: 0.00188 RPN total loss: 0.00399 Total loss: 0.78709 timestamp: 1654981125.049597 iteration: 86555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06415 FastRCNN class loss: 0.04406 FastRCNN total loss: 0.10821 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.11581 RPN box loss: 0.01391 RPN score loss: 0.00271 RPN total loss: 0.01662 Total loss: 0.82801 timestamp: 1654981128.2433002 iteration: 86560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06167 FastRCNN class loss: 0.04334 FastRCNN total loss: 0.10501 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13584 RPN box loss: 0.00534 RPN score loss: 0.00683 RPN total loss: 0.01217 Total loss: 0.84038 timestamp: 1654981131.5058303 iteration: 86565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05752 FastRCNN class loss: 0.04663 FastRCNN total loss: 0.10415 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12727 RPN box loss: 0.00701 RPN score loss: 0.00437 RPN total loss: 0.01138 Total loss: 0.83017 timestamp: 1654981134.6331663 iteration: 86570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04552 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.09489 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.09567 RPN box loss: 0.00541 RPN score loss: 0.00154 RPN total loss: 0.00694 Total loss: 0.78487 timestamp: 1654981137.857229 iteration: 86575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04474 FastRCNN class loss: 0.04475 FastRCNN total loss: 0.08949 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10548 RPN box loss: 0.00529 RPN score loss: 0.00079 RPN total loss: 0.00608 Total loss: 0.78842 timestamp: 1654981141.0082703 iteration: 86580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06617 FastRCNN class loss: 0.03763 FastRCNN total loss: 0.1038 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10023 RPN box loss: 0.00473 RPN score loss: 0.00121 RPN total loss: 0.00594 Total loss: 0.79734 timestamp: 1654981144.1252584 iteration: 86585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06767 FastRCNN class loss: 0.08501 FastRCNN total loss: 0.15268 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.12656 RPN box loss: 0.00757 RPN score loss: 0.00705 RPN total loss: 0.01462 Total loss: 0.88122 timestamp: 1654981147.2908752 iteration: 86590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06188 FastRCNN class loss: 0.05177 FastRCNN total loss: 0.11365 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14606 RPN box loss: 0.00298 RPN score loss: 0.00257 RPN total loss: 0.00556 Total loss: 0.85263 timestamp: 1654981150.51331 iteration: 86595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11965 FastRCNN class loss: 0.08025 FastRCNN total loss: 0.1999 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13259 RPN box loss: 0.01304 RPN score loss: 0.00283 RPN total loss: 0.01587 Total loss: 0.93573 timestamp: 1654981153.7156532 iteration: 86600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10043 FastRCNN class loss: 0.09065 FastRCNN total loss: 0.19109 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13736 RPN box loss: 0.02005 RPN score loss: 0.01124 RPN total loss: 0.03129 Total loss: 0.9471 timestamp: 1654981156.882853 iteration: 86605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03686 FastRCNN class loss: 0.04124 FastRCNN total loss: 0.0781 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.08705 RPN box loss: 0.00723 RPN score loss: 0.00116 RPN total loss: 0.0084 Total loss: 0.76091 timestamp: 1654981160.0376325 iteration: 86610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10775 FastRCNN class loss: 0.07278 FastRCNN total loss: 0.18053 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.10666 RPN box loss: 0.01682 RPN score loss: 0.00248 RPN total loss: 0.0193 Total loss: 0.89386 timestamp: 1654981163.265377 iteration: 86615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06249 FastRCNN class loss: 0.08989 FastRCNN total loss: 0.15238 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.16417 RPN box loss: 0.00879 RPN score loss: 0.00937 RPN total loss: 0.01816 Total loss: 0.92208 timestamp: 1654981166.4328623 iteration: 86620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.07334 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.08834 RPN box loss: 0.04719 RPN score loss: 0.00352 RPN total loss: 0.05071 Total loss: 0.89527 timestamp: 1654981169.625925 iteration: 86625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07778 FastRCNN class loss: 0.0672 FastRCNN total loss: 0.14498 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.13793 RPN box loss: 0.01591 RPN score loss: 0.008 RPN total loss: 0.02391 Total loss: 0.89419 timestamp: 1654981172.8980517 iteration: 86630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06482 FastRCNN class loss: 0.0384 FastRCNN total loss: 0.10323 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.17083 RPN box loss: 0.00574 RPN score loss: 0.00138 RPN total loss: 0.00712 Total loss: 0.86854 timestamp: 1654981176.1189668 iteration: 86635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08476 FastRCNN class loss: 0.05653 FastRCNN total loss: 0.14128 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.09375 RPN box loss: 0.00496 RPN score loss: 0.00645 RPN total loss: 0.0114 Total loss: 0.8338 timestamp: 1654981179.3499558 iteration: 86640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09758 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.17113 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.1557 RPN box loss: 0.01855 RPN score loss: 0.01137 RPN total loss: 0.02992 Total loss: 0.94412 timestamp: 1654981182.5679176 iteration: 86645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07978 FastRCNN class loss: 0.08798 FastRCNN total loss: 0.16776 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.14707 RPN box loss: 0.01515 RPN score loss: 0.01023 RPN total loss: 0.02538 Total loss: 0.92758 timestamp: 1654981185.747399 iteration: 86650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15305 FastRCNN class loss: 0.07266 FastRCNN total loss: 0.2257 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 4.0000e-05 Mask loss: 0.11739 RPN box loss: 0.02206 RPN score loss: 0.01229 RPN total loss: 0.03434 Total loss: 0.9648 timestamp: 1654981188.900011 iteration: 86655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.17697 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10504 RPN box loss: 0.01154 RPN score loss: 0.00526 RPN total loss: 0.0168 Total loss: 0.88617 timestamp: 1654981192.1345885 iteration: 86660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08725 FastRCNN class loss: 0.04639 FastRCNN total loss: 0.13364 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10356 RPN box loss: 0.01231 RPN score loss: 0.00197 RPN total loss: 0.01428 Total loss: 0.83884 timestamp: 1654981195.3602931 iteration: 86665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05247 FastRCNN class loss: 0.04887 FastRCNN total loss: 0.10134 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.12793 RPN box loss: 0.00433 RPN score loss: 0.00136 RPN total loss: 0.00569 Total loss: 0.82233 timestamp: 1654981198.5784369 iteration: 86670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08158 FastRCNN class loss: 0.05353 FastRCNN total loss: 0.13511 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.12309 RPN box loss: 0.00391 RPN score loss: 0.00262 RPN total loss: 0.00654 Total loss: 0.8521 timestamp: 1654981201.7459443 iteration: 86675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10363 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.18978 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13713 RPN box loss: 0.00759 RPN score loss: 0.00106 RPN total loss: 0.00865 Total loss: 0.92293 timestamp: 1654981204.925283 iteration: 86680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05647 FastRCNN class loss: 0.03878 FastRCNN total loss: 0.09525 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11979 RPN box loss: 0.00668 RPN score loss: 0.00469 RPN total loss: 0.01137 Total loss: 0.81377 timestamp: 1654981208.07305 iteration: 86685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06849 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.13354 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14657 RPN box loss: 0.02186 RPN score loss: 0.01023 RPN total loss: 0.03209 Total loss: 0.89957 timestamp: 1654981211.2388668 iteration: 86690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12175 FastRCNN class loss: 0.08791 FastRCNN total loss: 0.20966 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11352 RPN box loss: 0.00806 RPN score loss: 0.00549 RPN total loss: 0.01355 Total loss: 0.9241 timestamp: 1654981214.4237807 iteration: 86695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.17562 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.20613 RPN box loss: 0.0121 RPN score loss: 0.0057 RPN total loss: 0.01781 Total loss: 0.98692 timestamp: 1654981217.6552165 iteration: 86700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0621 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.12684 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.15532 RPN box loss: 0.00985 RPN score loss: 0.00245 RPN total loss: 0.0123 Total loss: 0.88182 timestamp: 1654981220.8954222 iteration: 86705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07276 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.14461 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.09781 RPN box loss: 0.00435 RPN score loss: 0.00338 RPN total loss: 0.00772 Total loss: 0.8375 timestamp: 1654981224.0505228 iteration: 86710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05895 FastRCNN class loss: 0.05759 FastRCNN total loss: 0.11654 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.15385 RPN box loss: 0.01392 RPN score loss: 0.00516 RPN total loss: 0.01909 Total loss: 0.87684 timestamp: 1654981227.2421987 iteration: 86715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06953 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.13022 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13755 RPN box loss: 0.01927 RPN score loss: 0.00183 RPN total loss: 0.0211 Total loss: 0.87623 timestamp: 1654981230.4436383 iteration: 86720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06565 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.13763 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11051 RPN box loss: 0.00628 RPN score loss: 0.00256 RPN total loss: 0.00884 Total loss: 0.84434 timestamp: 1654981233.6147656 iteration: 86725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11208 FastRCNN class loss: 0.08513 FastRCNN total loss: 0.19721 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13139 RPN box loss: 0.01386 RPN score loss: 0.00602 RPN total loss: 0.01988 Total loss: 0.93584 timestamp: 1654981236.822517 iteration: 86730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09715 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.17255 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.18849 RPN box loss: 0.01671 RPN score loss: 0.00464 RPN total loss: 0.02135 Total loss: 0.96976 timestamp: 1654981240.0252392 iteration: 86735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04744 FastRCNN class loss: 0.04733 FastRCNN total loss: 0.09477 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.06593 RPN box loss: 0.00857 RPN score loss: 0.00252 RPN total loss: 0.01109 Total loss: 0.75916 timestamp: 1654981243.2528152 iteration: 86740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05957 FastRCNN class loss: 0.06211 FastRCNN total loss: 0.12168 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.16025 RPN box loss: 0.01962 RPN score loss: 0.00217 RPN total loss: 0.02179 Total loss: 0.89108 timestamp: 1654981246.5020237 iteration: 86745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07835 FastRCNN class loss: 0.03579 FastRCNN total loss: 0.11414 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.08165 RPN box loss: 0.00894 RPN score loss: 0.00441 RPN total loss: 0.01335 Total loss: 0.7965 timestamp: 1654981249.7128932 iteration: 86750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10579 FastRCNN class loss: 0.0976 FastRCNN total loss: 0.20339 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11909 RPN box loss: 0.00496 RPN score loss: 0.00417 RPN total loss: 0.00914 Total loss: 0.91898 timestamp: 1654981252.973256 iteration: 86755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09714 FastRCNN class loss: 0.12836 FastRCNN total loss: 0.2255 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13457 RPN box loss: 0.01464 RPN score loss: 0.0038 RPN total loss: 0.01844 Total loss: 0.96587 timestamp: 1654981256.2473874 iteration: 86760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08321 FastRCNN class loss: 0.02755 FastRCNN total loss: 0.11075 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.08463 RPN box loss: 0.02401 RPN score loss: 0.00054 RPN total loss: 0.02456 Total loss: 0.8073 timestamp: 1654981259.3998559 iteration: 86765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09009 FastRCNN class loss: 0.06215 FastRCNN total loss: 0.15225 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13978 RPN box loss: 0.01351 RPN score loss: 0.00625 RPN total loss: 0.01976 Total loss: 0.89915 timestamp: 1654981262.605282 iteration: 86770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0823 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.14917 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.1266 RPN box loss: 0.01654 RPN score loss: 0.00427 RPN total loss: 0.02081 Total loss: 0.88395 timestamp: 1654981265.8056402 iteration: 86775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07776 FastRCNN class loss: 0.091 FastRCNN total loss: 0.16876 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13325 RPN box loss: 0.00941 RPN score loss: 0.00289 RPN total loss: 0.0123 Total loss: 0.90167 timestamp: 1654981268.9629726 iteration: 86780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04836 FastRCNN class loss: 0.03786 FastRCNN total loss: 0.08622 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.23054 RPN box loss: 0.00389 RPN score loss: 0.00146 RPN total loss: 0.00535 Total loss: 0.90947 timestamp: 1654981272.2331345 iteration: 86785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06572 FastRCNN class loss: 0.08228 FastRCNN total loss: 0.148 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.08065 RPN box loss: 0.00979 RPN score loss: 0.00166 RPN total loss: 0.01145 Total loss: 0.82747 timestamp: 1654981275.389691 iteration: 86790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09632 FastRCNN class loss: 0.05074 FastRCNN total loss: 0.14706 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11018 RPN box loss: 0.00664 RPN score loss: 0.00414 RPN total loss: 0.01078 Total loss: 0.85538 timestamp: 1654981278.6043785 iteration: 86795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09351 FastRCNN class loss: 0.08398 FastRCNN total loss: 0.17749 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11721 RPN box loss: 0.00715 RPN score loss: 0.00574 RPN total loss: 0.01289 Total loss: 0.89495 timestamp: 1654981281.8270066 iteration: 86800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04866 FastRCNN class loss: 0.04186 FastRCNN total loss: 0.09052 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13711 RPN box loss: 0.00693 RPN score loss: 0.00253 RPN total loss: 0.00946 Total loss: 0.82446 timestamp: 1654981284.9585786 iteration: 86805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.16269 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11462 RPN box loss: 0.00679 RPN score loss: 0.00236 RPN total loss: 0.00915 Total loss: 0.87383 timestamp: 1654981288.1499865 iteration: 86810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03564 FastRCNN class loss: 0.04666 FastRCNN total loss: 0.08231 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11926 RPN box loss: 0.02424 RPN score loss: 0.00084 RPN total loss: 0.02508 Total loss: 0.814 timestamp: 1654981291.3132112 iteration: 86815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06191 FastRCNN class loss: 0.07351 FastRCNN total loss: 0.13541 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.15372 RPN box loss: 0.01277 RPN score loss: 0.00259 RPN total loss: 0.01536 Total loss: 0.89186 timestamp: 1654981294.5609336 iteration: 86820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.0432 FastRCNN total loss: 0.1383 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.09617 RPN box loss: 0.00339 RPN score loss: 0.00441 RPN total loss: 0.0078 Total loss: 0.82964 timestamp: 1654981297.8054018 iteration: 86825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1063 FastRCNN class loss: 0.06532 FastRCNN total loss: 0.17163 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14273 RPN box loss: 0.02343 RPN score loss: 0.00168 RPN total loss: 0.02511 Total loss: 0.92682 timestamp: 1654981300.8834748 iteration: 86830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09178 FastRCNN class loss: 0.08785 FastRCNN total loss: 0.17963 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.09505 RPN box loss: 0.01009 RPN score loss: 0.00374 RPN total loss: 0.01383 Total loss: 0.87587 timestamp: 1654981304.0855649 iteration: 86835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12377 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.20138 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14013 RPN box loss: 0.01059 RPN score loss: 0.00551 RPN total loss: 0.0161 Total loss: 0.94497 timestamp: 1654981307.2649288 iteration: 86840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05852 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.11314 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.15974 RPN box loss: 0.01223 RPN score loss: 0.00238 RPN total loss: 0.01462 Total loss: 0.87485 timestamp: 1654981310.4561667 iteration: 86845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07584 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.13661 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10067 RPN box loss: 0.00755 RPN score loss: 0.01122 RPN total loss: 0.01877 Total loss: 0.84342 timestamp: 1654981313.6894023 iteration: 86850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08794 FastRCNN class loss: 0.05079 FastRCNN total loss: 0.13874 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10286 RPN box loss: 0.00579 RPN score loss: 0.00182 RPN total loss: 0.00761 Total loss: 0.83657 timestamp: 1654981316.9145477 iteration: 86855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05635 FastRCNN class loss: 0.03503 FastRCNN total loss: 0.09138 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13133 RPN box loss: 0.00503 RPN score loss: 0.00209 RPN total loss: 0.00712 Total loss: 0.81718 timestamp: 1654981320.055416 iteration: 86860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06732 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.12828 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.12365 RPN box loss: 0.01483 RPN score loss: 0.00214 RPN total loss: 0.01697 Total loss: 0.85626 timestamp: 1654981323.1972446 iteration: 86865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10425 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.19878 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.16044 RPN box loss: 0.01004 RPN score loss: 0.0074 RPN total loss: 0.01743 Total loss: 0.96402 timestamp: 1654981326.4211755 iteration: 86870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06137 FastRCNN class loss: 0.04349 FastRCNN total loss: 0.10485 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14592 RPN box loss: 0.0062 RPN score loss: 0.00657 RPN total loss: 0.01277 Total loss: 0.8509 timestamp: 1654981329.613549 iteration: 86875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07483 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.12848 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10739 RPN box loss: 0.01463 RPN score loss: 0.00089 RPN total loss: 0.01552 Total loss: 0.83875 timestamp: 1654981332.8230875 iteration: 86880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12619 FastRCNN class loss: 0.07042 FastRCNN total loss: 0.19661 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10248 RPN box loss: 0.00893 RPN score loss: 0.0045 RPN total loss: 0.01343 Total loss: 0.89988 timestamp: 1654981336.0119948 iteration: 86885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05687 FastRCNN class loss: 0.03025 FastRCNN total loss: 0.08713 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.08767 RPN box loss: 0.00721 RPN score loss: 0.00715 RPN total loss: 0.01436 Total loss: 0.77652 timestamp: 1654981339.1831706 iteration: 86890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06822 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.13289 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.09182 RPN box loss: 0.01326 RPN score loss: 0.00772 RPN total loss: 0.02098 Total loss: 0.83305 timestamp: 1654981342.4315794 iteration: 86895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.0734 FastRCNN total loss: 0.15256 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14302 RPN box loss: 0.01619 RPN score loss: 0.00494 RPN total loss: 0.02113 Total loss: 0.90407 timestamp: 1654981345.714325 iteration: 86900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13641 FastRCNN class loss: 0.06845 FastRCNN total loss: 0.20486 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14389 RPN box loss: 0.0304 RPN score loss: 0.01117 RPN total loss: 0.04158 Total loss: 0.97769 timestamp: 1654981348.8943362 iteration: 86905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07536 FastRCNN class loss: 0.0535 FastRCNN total loss: 0.12885 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.0926 RPN box loss: 0.00737 RPN score loss: 0.0012 RPN total loss: 0.00857 Total loss: 0.81739 timestamp: 1654981352.0585349 iteration: 86910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06475 FastRCNN class loss: 0.06767 FastRCNN total loss: 0.13242 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.12696 RPN box loss: 0.00654 RPN score loss: 0.0017 RPN total loss: 0.00823 Total loss: 0.85497 timestamp: 1654981355.2546058 iteration: 86915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09904 FastRCNN class loss: 0.09626 FastRCNN total loss: 0.1953 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.14996 RPN box loss: 0.01152 RPN score loss: 0.00693 RPN total loss: 0.01844 Total loss: 0.95106 timestamp: 1654981358.487573 iteration: 86920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06699 FastRCNN class loss: 0.04691 FastRCNN total loss: 0.1139 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11241 RPN box loss: 0.01279 RPN score loss: 0.0027 RPN total loss: 0.01549 Total loss: 0.82916 timestamp: 1654981361.742795 iteration: 86925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0753 FastRCNN class loss: 0.05151 FastRCNN total loss: 0.12681 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.12843 RPN box loss: 0.00797 RPN score loss: 0.00205 RPN total loss: 0.01002 Total loss: 0.85262 timestamp: 1654981365.0031404 iteration: 86930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1128 FastRCNN class loss: 0.09623 FastRCNN total loss: 0.20903 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.18345 RPN box loss: 0.01193 RPN score loss: 0.0041 RPN total loss: 0.01603 Total loss: 0.99586 timestamp: 1654981368.1707397 iteration: 86935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08437 FastRCNN class loss: 0.04241 FastRCNN total loss: 0.12678 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.10016 RPN box loss: 0.00948 RPN score loss: 0.00087 RPN total loss: 0.01034 Total loss: 0.82464 timestamp: 1654981371.3236964 iteration: 86940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1481 FastRCNN class loss: 0.0595 FastRCNN total loss: 0.2076 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.15266 RPN box loss: 0.00516 RPN score loss: 0.00778 RPN total loss: 0.01294 Total loss: 0.96055 timestamp: 1654981374.4811232 iteration: 86945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07584 FastRCNN class loss: 0.09035 FastRCNN total loss: 0.16619 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.13903 RPN box loss: 0.01415 RPN score loss: 0.00477 RPN total loss: 0.01892 Total loss: 0.91149 timestamp: 1654981377.6812372 iteration: 86950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1055 FastRCNN class loss: 0.07005 FastRCNN total loss: 0.17555 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.19045 RPN box loss: 0.00784 RPN score loss: 0.00308 RPN total loss: 0.01093 Total loss: 0.96428 timestamp: 1654981380.89001 iteration: 86955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03438 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.09711 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.11292 RPN box loss: 0.00678 RPN score loss: 0.00649 RPN total loss: 0.01327 Total loss: 0.81066 timestamp: 1654981384.1033266 iteration: 86960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16785 FastRCNN class loss: 0.05892 FastRCNN total loss: 0.22677 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.12383 RPN box loss: 0.00669 RPN score loss: 0.00698 RPN total loss: 0.01367 Total loss: 0.95163 timestamp: 1654981387.227177 iteration: 86965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10534 FastRCNN class loss: 0.09274 FastRCNN total loss: 0.19807 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.16579 RPN box loss: 0.01005 RPN score loss: 0.0106 RPN total loss: 0.02064 Total loss: 0.97187 timestamp: 1654981390.3767028 iteration: 86970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08222 FastRCNN class loss: 0.09542 FastRCNN total loss: 0.17764 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 4.0000e-05 Mask loss: 0.17093 RPN box loss: 0.00652 RPN score loss: 0.00229 RPN total loss: 0.0088 Total loss: 0.94473 timestamp: 1654981393.5791802 iteration: 86975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09488 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.16112 RPN box loss: 0.00625 RPN score loss: 0.0041 RPN total loss: 0.01035 Total loss: 0.92247 timestamp: 1654981396.7528877 iteration: 86980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06683 FastRCNN class loss: 0.06214 FastRCNN total loss: 0.12897 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12838 RPN box loss: 0.01086 RPN score loss: 0.00225 RPN total loss: 0.01311 Total loss: 0.85782 timestamp: 1654981400.0495303 iteration: 86985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07489 FastRCNN class loss: 0.04796 FastRCNN total loss: 0.12286 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11674 RPN box loss: 0.0071 RPN score loss: 0.00475 RPN total loss: 0.01186 Total loss: 0.83881 timestamp: 1654981403.3072233 iteration: 86990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06007 FastRCNN class loss: 0.04864 FastRCNN total loss: 0.10871 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11926 RPN box loss: 0.01201 RPN score loss: 0.00199 RPN total loss: 0.014 Total loss: 0.82932 timestamp: 1654981406.5425932 iteration: 86995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15136 FastRCNN class loss: 0.04844 FastRCNN total loss: 0.1998 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11664 RPN box loss: 0.01502 RPN score loss: 0.00395 RPN total loss: 0.01897 Total loss: 0.92276 timestamp: 1654981409.6669228 iteration: 87000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10157 FastRCNN class loss: 0.08015 FastRCNN total loss: 0.18172 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.10153 RPN box loss: 0.01124 RPN score loss: 0.00569 RPN total loss: 0.01693 Total loss: 0.88754 timestamp: 1654981412.8713927 iteration: 87005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04968 FastRCNN class loss: 0.04357 FastRCNN total loss: 0.09325 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.09868 RPN box loss: 0.02476 RPN score loss: 0.00215 RPN total loss: 0.02692 Total loss: 0.80621 timestamp: 1654981416.0598185 iteration: 87010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04648 FastRCNN class loss: 0.05793 FastRCNN total loss: 0.10441 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12142 RPN box loss: 0.0083 RPN score loss: 0.0012 RPN total loss: 0.0095 Total loss: 0.82268 timestamp: 1654981419.242018 iteration: 87015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09673 FastRCNN class loss: 0.05243 FastRCNN total loss: 0.14916 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.08675 RPN box loss: 0.02496 RPN score loss: 0.0044 RPN total loss: 0.02937 Total loss: 0.85262 timestamp: 1654981422.3625886 iteration: 87020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04979 FastRCNN class loss: 0.04174 FastRCNN total loss: 0.09153 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13094 RPN box loss: 0.01884 RPN score loss: 0.00141 RPN total loss: 0.02025 Total loss: 0.83008 timestamp: 1654981425.5715623 iteration: 87025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12346 FastRCNN class loss: 0.04896 FastRCNN total loss: 0.17242 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.07484 RPN box loss: 0.00755 RPN score loss: 0.00128 RPN total loss: 0.00883 Total loss: 0.84344 timestamp: 1654981428.745809 iteration: 87030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10295 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.16121 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11076 RPN box loss: 0.00587 RPN score loss: 0.0065 RPN total loss: 0.01237 Total loss: 0.87169 timestamp: 1654981431.9312549 iteration: 87035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1086 FastRCNN class loss: 0.108 FastRCNN total loss: 0.2166 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13287 RPN box loss: 0.01371 RPN score loss: 0.00713 RPN total loss: 0.02084 Total loss: 0.95765 timestamp: 1654981435.1411033 iteration: 87040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08251 FastRCNN class loss: 0.06209 FastRCNN total loss: 0.14461 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.131 RPN box loss: 0.01096 RPN score loss: 0.01006 RPN total loss: 0.02102 Total loss: 0.88397 timestamp: 1654981438.2844887 iteration: 87045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10169 FastRCNN class loss: 0.08954 FastRCNN total loss: 0.19124 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.19083 RPN box loss: 0.00699 RPN score loss: 0.00495 RPN total loss: 0.01195 Total loss: 0.98136 timestamp: 1654981441.503359 iteration: 87050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08583 FastRCNN class loss: 0.08084 FastRCNN total loss: 0.16667 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12104 RPN box loss: 0.02216 RPN score loss: 0.00395 RPN total loss: 0.02611 Total loss: 0.90117 timestamp: 1654981444.7208486 iteration: 87055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07926 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.14928 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12591 RPN box loss: 0.01559 RPN score loss: 0.00416 RPN total loss: 0.01975 Total loss: 0.88229 timestamp: 1654981448.0000184 iteration: 87060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05613 FastRCNN class loss: 0.04585 FastRCNN total loss: 0.10198 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.14811 RPN box loss: 0.00822 RPN score loss: 0.00214 RPN total loss: 0.01037 Total loss: 0.84781 timestamp: 1654981451.2144186 iteration: 87065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0466 FastRCNN class loss: 0.04511 FastRCNN total loss: 0.09171 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13769 RPN box loss: 0.00822 RPN score loss: 0.00939 RPN total loss: 0.01761 Total loss: 0.83437 timestamp: 1654981454.3791351 iteration: 87070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08172 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.14156 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.18321 RPN box loss: 0.01792 RPN score loss: 0.00113 RPN total loss: 0.01905 Total loss: 0.93118 timestamp: 1654981457.531914 iteration: 87075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06765 FastRCNN class loss: 0.04424 FastRCNN total loss: 0.11189 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.15823 RPN box loss: 0.01153 RPN score loss: 0.00115 RPN total loss: 0.01268 Total loss: 0.87015 timestamp: 1654981460.7513993 iteration: 87080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05982 FastRCNN class loss: 0.04969 FastRCNN total loss: 0.10951 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.17529 RPN box loss: 0.00393 RPN score loss: 0.00371 RPN total loss: 0.00764 Total loss: 0.87978 timestamp: 1654981463.967523 iteration: 87085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11195 FastRCNN class loss: 0.11186 FastRCNN total loss: 0.22381 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.16444 RPN box loss: 0.0107 RPN score loss: 0.00323 RPN total loss: 0.01393 Total loss: 0.98953 timestamp: 1654981467.1176322 iteration: 87090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11707 FastRCNN class loss: 0.06742 FastRCNN total loss: 0.1845 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11021 RPN box loss: 0.01963 RPN score loss: 0.00338 RPN total loss: 0.02301 Total loss: 0.90506 timestamp: 1654981470.2265086 iteration: 87095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07198 FastRCNN class loss: 0.04964 FastRCNN total loss: 0.12162 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12125 RPN box loss: 0.01463 RPN score loss: 0.01203 RPN total loss: 0.02666 Total loss: 0.85687 timestamp: 1654981473.4663763 iteration: 87100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04824 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.11492 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.17946 RPN box loss: 0.01416 RPN score loss: 0.00885 RPN total loss: 0.02301 Total loss: 0.90475 timestamp: 1654981476.669961 iteration: 87105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06586 FastRCNN class loss: 0.03358 FastRCNN total loss: 0.09944 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13846 RPN box loss: 0.00121 RPN score loss: 0.00238 RPN total loss: 0.00359 Total loss: 0.82884 timestamp: 1654981479.9154768 iteration: 87110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05001 FastRCNN class loss: 0.03373 FastRCNN total loss: 0.08375 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.08138 RPN box loss: 0.00256 RPN score loss: 0.001 RPN total loss: 0.00356 Total loss: 0.75604 timestamp: 1654981483.0581474 iteration: 87115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07166 FastRCNN class loss: 0.05703 FastRCNN total loss: 0.12869 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12369 RPN box loss: 0.00996 RPN score loss: 0.00151 RPN total loss: 0.01148 Total loss: 0.85121 timestamp: 1654981486.2373667 iteration: 87120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07604 FastRCNN class loss: 0.0939 FastRCNN total loss: 0.16994 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13186 RPN box loss: 0.02168 RPN score loss: 0.01059 RPN total loss: 0.03227 Total loss: 0.92143 timestamp: 1654981489.5233872 iteration: 87125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06531 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.12161 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.14017 RPN box loss: 0.00702 RPN score loss: 0.00239 RPN total loss: 0.00942 Total loss: 0.85856 timestamp: 1654981492.8010728 iteration: 87130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10668 FastRCNN class loss: 0.05752 FastRCNN total loss: 0.16419 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12685 RPN box loss: 0.00906 RPN score loss: 0.00108 RPN total loss: 0.01014 Total loss: 0.88854 timestamp: 1654981496.0189397 iteration: 87135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10199 FastRCNN class loss: 0.06966 FastRCNN total loss: 0.17165 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.10356 RPN box loss: 0.02941 RPN score loss: 0.00423 RPN total loss: 0.03364 Total loss: 0.89621 timestamp: 1654981499.248823 iteration: 87140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08067 FastRCNN class loss: 0.06155 FastRCNN total loss: 0.14222 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13539 RPN box loss: 0.00647 RPN score loss: 0.00336 RPN total loss: 0.00982 Total loss: 0.87478 timestamp: 1654981502.4319332 iteration: 87145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0758 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.15145 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.15866 RPN box loss: 0.00798 RPN score loss: 0.00401 RPN total loss: 0.01199 Total loss: 0.90945 timestamp: 1654981505.627578 iteration: 87150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05257 FastRCNN class loss: 0.05233 FastRCNN total loss: 0.1049 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11939 RPN box loss: 0.01909 RPN score loss: 0.0011 RPN total loss: 0.02018 Total loss: 0.83183 timestamp: 1654981508.8990982 iteration: 87155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06621 FastRCNN class loss: 0.075 FastRCNN total loss: 0.14121 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.10559 RPN box loss: 0.00909 RPN score loss: 0.00214 RPN total loss: 0.01123 Total loss: 0.84538 timestamp: 1654981512.0653899 iteration: 87160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.11905 FastRCNN total loss: 0.21027 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.16444 RPN box loss: 0.02499 RPN score loss: 0.00577 RPN total loss: 0.03076 Total loss: 0.99282 timestamp: 1654981515.2131207 iteration: 87165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0779 FastRCNN class loss: 0.05981 FastRCNN total loss: 0.13771 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12993 RPN box loss: 0.0193 RPN score loss: 0.00426 RPN total loss: 0.02356 Total loss: 0.87855 timestamp: 1654981518.3702424 iteration: 87170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12113 FastRCNN class loss: 0.07351 FastRCNN total loss: 0.19465 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.15736 RPN box loss: 0.00482 RPN score loss: 0.00111 RPN total loss: 0.00593 Total loss: 0.94528 timestamp: 1654981521.591129 iteration: 87175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11764 FastRCNN class loss: 0.11329 FastRCNN total loss: 0.23093 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.16078 RPN box loss: 0.01132 RPN score loss: 0.00489 RPN total loss: 0.01621 Total loss: 0.99526 timestamp: 1654981524.8219445 iteration: 87180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10948 FastRCNN class loss: 0.11103 FastRCNN total loss: 0.22051 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13225 RPN box loss: 0.01692 RPN score loss: 0.00306 RPN total loss: 0.01997 Total loss: 0.96008 timestamp: 1654981527.9562695 iteration: 87185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.09253 FastRCNN total loss: 0.18593 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.13787 RPN box loss: 0.01107 RPN score loss: 0.00381 RPN total loss: 0.01488 Total loss: 0.92603 timestamp: 1654981531.129215 iteration: 87190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09126 FastRCNN class loss: 0.07156 FastRCNN total loss: 0.16282 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.10116 RPN box loss: 0.00426 RPN score loss: 0.00192 RPN total loss: 0.00618 Total loss: 0.85751 timestamp: 1654981534.3560088 iteration: 87195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08827 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.15265 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.18603 RPN box loss: 0.00889 RPN score loss: 0.00573 RPN total loss: 0.01462 Total loss: 0.94065 timestamp: 1654981537.537515 iteration: 87200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07798 FastRCNN class loss: 0.09659 FastRCNN total loss: 0.17456 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.17365 RPN box loss: 0.0059 RPN score loss: 0.00142 RPN total loss: 0.00731 Total loss: 0.94288 timestamp: 1654981540.721989 iteration: 87205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09034 FastRCNN class loss: 0.13295 FastRCNN total loss: 0.22328 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.08166 RPN box loss: 0.00302 RPN score loss: 0.00223 RPN total loss: 0.00525 Total loss: 0.89754 timestamp: 1654981543.968138 iteration: 87210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05134 FastRCNN class loss: 0.04089 FastRCNN total loss: 0.09222 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.10835 RPN box loss: 0.00845 RPN score loss: 0.00454 RPN total loss: 0.01299 Total loss: 0.80092 timestamp: 1654981547.2288575 iteration: 87215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13307 FastRCNN class loss: 0.10172 FastRCNN total loss: 0.23479 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.15516 RPN box loss: 0.02075 RPN score loss: 0.00963 RPN total loss: 0.03038 Total loss: 1.00767 timestamp: 1654981550.4801042 iteration: 87220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06481 FastRCNN class loss: 0.05722 FastRCNN total loss: 0.12203 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.25023 RPN box loss: 0.01305 RPN score loss: 0.00372 RPN total loss: 0.01678 Total loss: 0.97639 timestamp: 1654981553.7374172 iteration: 87225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10955 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.17239 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11147 RPN box loss: 0.01436 RPN score loss: 0.00262 RPN total loss: 0.01698 Total loss: 0.88818 timestamp: 1654981556.8951814 iteration: 87230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10747 FastRCNN class loss: 0.09257 FastRCNN total loss: 0.20004 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.19238 RPN box loss: 0.01164 RPN score loss: 0.00089 RPN total loss: 0.01252 Total loss: 0.99229 timestamp: 1654981560.157686 iteration: 87235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14532 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.20443 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.09333 RPN box loss: 0.00335 RPN score loss: 0.00284 RPN total loss: 0.00619 Total loss: 0.8913 timestamp: 1654981563.409796 iteration: 87240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09376 FastRCNN class loss: 0.11879 FastRCNN total loss: 0.21255 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.19068 RPN box loss: 0.01152 RPN score loss: 0.00646 RPN total loss: 0.01799 Total loss: 1.00856 timestamp: 1654981566.5890393 iteration: 87245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10407 FastRCNN class loss: 0.07117 FastRCNN total loss: 0.17524 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11857 RPN box loss: 0.00572 RPN score loss: 0.01002 RPN total loss: 0.01575 Total loss: 0.8969 timestamp: 1654981569.7524695 iteration: 87250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11894 FastRCNN class loss: 0.06578 FastRCNN total loss: 0.18472 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.15389 RPN box loss: 0.03529 RPN score loss: 0.00265 RPN total loss: 0.03794 Total loss: 0.9639 timestamp: 1654981572.9037085 iteration: 87255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07682 FastRCNN class loss: 0.07784 FastRCNN total loss: 0.15466 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.1207 RPN box loss: 0.00743 RPN score loss: 0.00618 RPN total loss: 0.01361 Total loss: 0.87632 timestamp: 1654981575.9968112 iteration: 87260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.07969 FastRCNN total loss: 0.1754 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12988 RPN box loss: 0.04172 RPN score loss: 0.00637 RPN total loss: 0.04809 Total loss: 0.94071 timestamp: 1654981579.1583378 iteration: 87265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06499 FastRCNN class loss: 0.03915 FastRCNN total loss: 0.10414 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.08147 RPN box loss: 0.01162 RPN score loss: 0.00295 RPN total loss: 0.01457 Total loss: 0.78753 timestamp: 1654981582.3192716 iteration: 87270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05721 FastRCNN class loss: 0.06322 FastRCNN total loss: 0.12043 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.14153 RPN box loss: 0.00494 RPN score loss: 0.00314 RPN total loss: 0.00807 Total loss: 0.85737 timestamp: 1654981585.564162 iteration: 87275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06492 FastRCNN class loss: 0.0759 FastRCNN total loss: 0.14082 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11576 RPN box loss: 0.00589 RPN score loss: 0.00634 RPN total loss: 0.01222 Total loss: 0.85614 timestamp: 1654981588.7719052 iteration: 87280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08554 FastRCNN class loss: 0.06325 FastRCNN total loss: 0.14879 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.10469 RPN box loss: 0.00809 RPN score loss: 0.00844 RPN total loss: 0.01653 Total loss: 0.85736 timestamp: 1654981591.9752421 iteration: 87285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07053 FastRCNN class loss: 0.05213 FastRCNN total loss: 0.12265 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.09079 RPN box loss: 0.0093 RPN score loss: 0.00083 RPN total loss: 0.01013 Total loss: 0.81092 timestamp: 1654981595.2364106 iteration: 87290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10338 FastRCNN class loss: 0.05105 FastRCNN total loss: 0.15443 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.11313 RPN box loss: 0.00977 RPN score loss: 0.00358 RPN total loss: 0.01335 Total loss: 0.86826 timestamp: 1654981598.4038608 iteration: 87295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05572 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.11734 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.08315 RPN box loss: 0.00713 RPN score loss: 0.00487 RPN total loss: 0.012 Total loss: 0.79983 timestamp: 1654981601.622961 iteration: 87300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08938 FastRCNN class loss: 0.07025 FastRCNN total loss: 0.15963 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 4.0000e-05 Mask loss: 0.12599 RPN box loss: 0.00738 RPN score loss: 0.00527 RPN total loss: 0.01265 Total loss: 0.88561 timestamp: 1654981604.8882337 iteration: 87305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.05676 FastRCNN total loss: 0.13542 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11273 RPN box loss: 0.00655 RPN score loss: 0.00568 RPN total loss: 0.01223 Total loss: 0.84773 timestamp: 1654981608.0639935 iteration: 87310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11087 FastRCNN class loss: 0.05615 FastRCNN total loss: 0.16702 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.1256 RPN box loss: 0.01322 RPN score loss: 0.00508 RPN total loss: 0.01831 Total loss: 0.89827 timestamp: 1654981611.204547 iteration: 87315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05059 FastRCNN class loss: 0.054 FastRCNN total loss: 0.10459 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.14028 RPN box loss: 0.00698 RPN score loss: 0.00203 RPN total loss: 0.00901 Total loss: 0.84123 timestamp: 1654981614.4574256 iteration: 87320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11589 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.18903 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.16988 RPN box loss: 0.01379 RPN score loss: 0.00373 RPN total loss: 0.01752 Total loss: 0.96377 timestamp: 1654981617.6847088 iteration: 87325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08004 FastRCNN class loss: 0.08948 FastRCNN total loss: 0.16953 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11886 RPN box loss: 0.01635 RPN score loss: 0.01066 RPN total loss: 0.02701 Total loss: 0.90273 timestamp: 1654981620.8606226 iteration: 87330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12425 FastRCNN class loss: 0.11156 FastRCNN total loss: 0.23581 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.14494 RPN box loss: 0.02112 RPN score loss: 0.00764 RPN total loss: 0.02877 Total loss: 0.99686 timestamp: 1654981624.0713294 iteration: 87335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07657 FastRCNN class loss: 0.05595 FastRCNN total loss: 0.13252 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.1818 RPN box loss: 0.00384 RPN score loss: 0.00198 RPN total loss: 0.00582 Total loss: 0.90748 timestamp: 1654981627.2740428 iteration: 87340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06007 FastRCNN class loss: 0.04686 FastRCNN total loss: 0.10693 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.10619 RPN box loss: 0.01089 RPN score loss: 0.00403 RPN total loss: 0.01492 Total loss: 0.81538 timestamp: 1654981630.5131986 iteration: 87345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08062 FastRCNN class loss: 0.05716 FastRCNN total loss: 0.13777 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.15377 RPN box loss: 0.00892 RPN score loss: 0.00152 RPN total loss: 0.01044 Total loss: 0.88933 timestamp: 1654981633.7541177 iteration: 87350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06698 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.12882 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.13263 RPN box loss: 0.03517 RPN score loss: 0.00467 RPN total loss: 0.03985 Total loss: 0.88864 timestamp: 1654981636.9054453 iteration: 87355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13027 FastRCNN class loss: 0.07421 FastRCNN total loss: 0.20447 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.14871 RPN box loss: 0.00608 RPN score loss: 0.00498 RPN total loss: 0.01106 Total loss: 0.95158 timestamp: 1654981640.0891001 iteration: 87360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07798 FastRCNN class loss: 0.08178 FastRCNN total loss: 0.15975 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.1616 RPN box loss: 0.01294 RPN score loss: 0.00306 RPN total loss: 0.016 Total loss: 0.9247 timestamp: 1654981643.2207983 iteration: 87365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.03589 FastRCNN total loss: 0.10699 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.15053 RPN box loss: 0.00413 RPN score loss: 0.00312 RPN total loss: 0.00726 Total loss: 0.85212 timestamp: 1654981646.5730774 iteration: 87370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1167 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.19563 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.10907 RPN box loss: 0.03327 RPN score loss: 0.00369 RPN total loss: 0.03696 Total loss: 0.92901 timestamp: 1654981649.7988672 iteration: 87375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07418 FastRCNN class loss: 0.04519 FastRCNN total loss: 0.11937 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.12374 RPN box loss: 0.0201 RPN score loss: 0.00714 RPN total loss: 0.02725 Total loss: 0.8577 timestamp: 1654981653.0055594 iteration: 87380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05912 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.12626 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.15319 RPN box loss: 0.01842 RPN score loss: 0.00827 RPN total loss: 0.02669 Total loss: 0.89349 timestamp: 1654981656.0761316 iteration: 87385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08941 FastRCNN class loss: 0.07099 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.14285 RPN box loss: 0.00861 RPN score loss: 0.01302 RPN total loss: 0.02162 Total loss: 0.91222 timestamp: 1654981659.228438 iteration: 87390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11131 FastRCNN class loss: 0.06872 FastRCNN total loss: 0.18003 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.16333 RPN box loss: 0.01194 RPN score loss: 0.00309 RPN total loss: 0.01503 Total loss: 0.94573 timestamp: 1654981662.468206 iteration: 87395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0653 FastRCNN class loss: 0.05146 FastRCNN total loss: 0.11676 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11605 RPN box loss: 0.00734 RPN score loss: 0.0026 RPN total loss: 0.00994 Total loss: 0.83009 timestamp: 1654981665.6536539 iteration: 87400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09731 FastRCNN class loss: 0.06021 FastRCNN total loss: 0.15752 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.12531 RPN box loss: 0.0032 RPN score loss: 0.00549 RPN total loss: 0.00869 Total loss: 0.87886 timestamp: 1654981668.8625376 iteration: 87405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08502 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.12373 RPN box loss: 0.03273 RPN score loss: 0.00778 RPN total loss: 0.0405 Total loss: 0.91165 timestamp: 1654981672.0559154 iteration: 87410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09471 FastRCNN class loss: 0.08167 FastRCNN total loss: 0.17638 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.12402 RPN box loss: 0.00957 RPN score loss: 0.02191 RPN total loss: 0.03148 Total loss: 0.91922 timestamp: 1654981675.1983626 iteration: 87415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04394 FastRCNN class loss: 0.03068 FastRCNN total loss: 0.07462 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.08175 RPN box loss: 0.00999 RPN score loss: 0.00178 RPN total loss: 0.01177 Total loss: 0.75548 timestamp: 1654981678.4087164 iteration: 87420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08388 FastRCNN class loss: 0.04162 FastRCNN total loss: 0.1255 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11559 RPN box loss: 0.01586 RPN score loss: 0.00215 RPN total loss: 0.01802 Total loss: 0.84646 timestamp: 1654981681.5894108 iteration: 87425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0739 FastRCNN class loss: 0.03628 FastRCNN total loss: 0.11019 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.1067 RPN box loss: 0.00195 RPN score loss: 0.00858 RPN total loss: 0.01053 Total loss: 0.81475 timestamp: 1654981684.8182387 iteration: 87430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0638 FastRCNN class loss: 0.04313 FastRCNN total loss: 0.10693 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.12429 RPN box loss: 0.00853 RPN score loss: 0.00669 RPN total loss: 0.01522 Total loss: 0.83378 timestamp: 1654981688.0337458 iteration: 87435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13114 FastRCNN class loss: 0.10861 FastRCNN total loss: 0.23975 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.15771 RPN box loss: 0.01154 RPN score loss: 0.0057 RPN total loss: 0.01724 Total loss: 1.00204 timestamp: 1654981691.2709422 iteration: 87440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05196 FastRCNN class loss: 0.05681 FastRCNN total loss: 0.10877 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.09534 RPN box loss: 0.00311 RPN score loss: 0.00734 RPN total loss: 0.01045 Total loss: 0.8019 timestamp: 1654981694.47689 iteration: 87445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07445 FastRCNN class loss: 0.0519 FastRCNN total loss: 0.12636 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.10944 RPN box loss: 0.00551 RPN score loss: 0.00411 RPN total loss: 0.00962 Total loss: 0.83276 timestamp: 1654981697.6296377 iteration: 87450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07551 FastRCNN class loss: 0.05731 FastRCNN total loss: 0.13283 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.19675 RPN box loss: 0.01294 RPN score loss: 0.00316 RPN total loss: 0.0161 Total loss: 0.93302 timestamp: 1654981700.8403575 iteration: 87455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03738 FastRCNN class loss: 0.03589 FastRCNN total loss: 0.07327 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.0739 RPN box loss: 0.00578 RPN score loss: 0.00138 RPN total loss: 0.00716 Total loss: 0.74167 timestamp: 1654981703.9829297 iteration: 87460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07798 FastRCNN class loss: 0.05492 FastRCNN total loss: 0.1329 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.09661 RPN box loss: 0.00694 RPN score loss: 0.00604 RPN total loss: 0.01298 Total loss: 0.82983 timestamp: 1654981707.119803 iteration: 87465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1419 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.20859 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.12815 RPN box loss: 0.00889 RPN score loss: 0.00221 RPN total loss: 0.0111 Total loss: 0.93518 timestamp: 1654981710.3232574 iteration: 87470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07711 FastRCNN class loss: 0.09325 FastRCNN total loss: 0.17036 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.16019 RPN box loss: 0.01321 RPN score loss: 0.00671 RPN total loss: 0.01993 Total loss: 0.93781 timestamp: 1654981713.5426948 iteration: 87475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0723 FastRCNN class loss: 0.10005 FastRCNN total loss: 0.17236 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11049 RPN box loss: 0.01183 RPN score loss: 0.00615 RPN total loss: 0.01798 Total loss: 0.88817 timestamp: 1654981716.825367 iteration: 87480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09769 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.18046 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.14883 RPN box loss: 0.02942 RPN score loss: 0.00722 RPN total loss: 0.03664 Total loss: 0.95326 timestamp: 1654981720.0530384 iteration: 87485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07514 FastRCNN class loss: 0.05561 FastRCNN total loss: 0.13075 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.1173 RPN box loss: 0.00545 RPN score loss: 0.00305 RPN total loss: 0.00851 Total loss: 0.84389 timestamp: 1654981723.232792 iteration: 87490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13478 FastRCNN class loss: 0.07776 FastRCNN total loss: 0.21255 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.17125 RPN box loss: 0.02258 RPN score loss: 0.0045 RPN total loss: 0.02707 Total loss: 0.99821 timestamp: 1654981726.457296 iteration: 87495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13323 FastRCNN class loss: 0.0712 FastRCNN total loss: 0.20443 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11812 RPN box loss: 0.00987 RPN score loss: 0.0045 RPN total loss: 0.01437 Total loss: 0.92426 timestamp: 1654981729.6471715 iteration: 87500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10876 FastRCNN class loss: 0.0526 FastRCNN total loss: 0.16136 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.09767 RPN box loss: 0.00658 RPN score loss: 0.00291 RPN total loss: 0.00948 Total loss: 0.85585 timestamp: 1654981732.8203707 iteration: 87505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07708 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.14377 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.13091 RPN box loss: 0.01534 RPN score loss: 0.01085 RPN total loss: 0.02619 Total loss: 0.88821 timestamp: 1654981736.0200202 iteration: 87510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04254 FastRCNN class loss: 0.04795 FastRCNN total loss: 0.0905 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.10331 RPN box loss: 0.00389 RPN score loss: 0.0013 RPN total loss: 0.00519 Total loss: 0.78633 timestamp: 1654981739.2051795 iteration: 87515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12221 FastRCNN class loss: 0.09747 FastRCNN total loss: 0.21968 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.1636 RPN box loss: 0.01606 RPN score loss: 0.00717 RPN total loss: 0.02323 Total loss: 0.99385 timestamp: 1654981742.3554196 iteration: 87520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05691 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.10716 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.10964 RPN box loss: 0.01064 RPN score loss: 0.00474 RPN total loss: 0.01538 Total loss: 0.81951 timestamp: 1654981745.645267 iteration: 87525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10163 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.16746 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.15426 RPN box loss: 0.00652 RPN score loss: 0.00405 RPN total loss: 0.01057 Total loss: 0.91962 timestamp: 1654981748.8493688 iteration: 87530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13878 FastRCNN class loss: 0.10968 FastRCNN total loss: 0.24846 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.17578 RPN box loss: 0.02757 RPN score loss: 0.00622 RPN total loss: 0.03378 Total loss: 1.04536 timestamp: 1654981751.9767673 iteration: 87535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12082 FastRCNN class loss: 0.1014 FastRCNN total loss: 0.22222 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.21187 RPN box loss: 0.02617 RPN score loss: 0.00462 RPN total loss: 0.03079 Total loss: 1.05222 timestamp: 1654981755.1243684 iteration: 87540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07143 FastRCNN class loss: 0.05428 FastRCNN total loss: 0.12571 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.09932 RPN box loss: 0.01291 RPN score loss: 0.00314 RPN total loss: 0.01605 Total loss: 0.82841 timestamp: 1654981758.347075 iteration: 87545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06741 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.12584 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.19049 RPN box loss: 0.02857 RPN score loss: 0.0054 RPN total loss: 0.03398 Total loss: 0.93764 timestamp: 1654981761.5524762 iteration: 87550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06716 FastRCNN class loss: 0.0671 FastRCNN total loss: 0.13426 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.07564 RPN box loss: 0.01255 RPN score loss: 0.00319 RPN total loss: 0.01574 Total loss: 0.81298 timestamp: 1654981764.7600245 iteration: 87555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05345 FastRCNN class loss: 0.04914 FastRCNN total loss: 0.1026 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.15681 RPN box loss: 0.00519 RPN score loss: 0.00931 RPN total loss: 0.0145 Total loss: 0.86124 timestamp: 1654981768.0357323 iteration: 87560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1141 FastRCNN class loss: 0.07909 FastRCNN total loss: 0.19319 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.24031 RPN box loss: 0.01821 RPN score loss: 0.01216 RPN total loss: 0.03037 Total loss: 1.0512 timestamp: 1654981771.2875922 iteration: 87565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05435 FastRCNN class loss: 0.04602 FastRCNN total loss: 0.10037 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11114 RPN box loss: 0.0248 RPN score loss: 0.00353 RPN total loss: 0.02833 Total loss: 0.82718 timestamp: 1654981774.5389953 iteration: 87570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10204 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.17269 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.08562 RPN box loss: 0.01326 RPN score loss: 0.0032 RPN total loss: 0.01646 Total loss: 0.86211 timestamp: 1654981777.7080176 iteration: 87575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09423 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.17017 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.13744 RPN box loss: 0.00762 RPN score loss: 0.00537 RPN total loss: 0.01299 Total loss: 0.90794 timestamp: 1654981780.9178407 iteration: 87580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15316 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.2281 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.3425 RPN box loss: 0.02256 RPN score loss: 0.00562 RPN total loss: 0.02818 Total loss: 1.18611 timestamp: 1654981784.1122935 iteration: 87585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07141 FastRCNN class loss: 0.08141 FastRCNN total loss: 0.15282 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.13191 RPN box loss: 0.00831 RPN score loss: 0.00869 RPN total loss: 0.01699 Total loss: 0.88906 timestamp: 1654981787.2312715 iteration: 87590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05201 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.11278 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11524 RPN box loss: 0.00953 RPN score loss: 0.00986 RPN total loss: 0.0194 Total loss: 0.83475 timestamp: 1654981790.44572 iteration: 87595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09482 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.16577 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.16762 RPN box loss: 0.01254 RPN score loss: 0.00553 RPN total loss: 0.01807 Total loss: 0.9388 timestamp: 1654981793.6265678 iteration: 87600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10287 FastRCNN class loss: 0.0453 FastRCNN total loss: 0.14817 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.11701 RPN box loss: 0.01266 RPN score loss: 0.00128 RPN total loss: 0.01394 Total loss: 0.86646 timestamp: 1654981796.7878504 iteration: 87605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05514 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.10866 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.06471 RPN box loss: 0.00562 RPN score loss: 0.00107 RPN total loss: 0.00669 Total loss: 0.7674 timestamp: 1654981799.9612405 iteration: 87610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07006 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.12605 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.07196 RPN box loss: 0.01516 RPN score loss: 0.00053 RPN total loss: 0.01569 Total loss: 0.80103 timestamp: 1654981803.1709278 iteration: 87615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09013 FastRCNN class loss: 0.09363 FastRCNN total loss: 0.18376 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.14026 RPN box loss: 0.0115 RPN score loss: 0.01065 RPN total loss: 0.02216 Total loss: 0.9335 timestamp: 1654981806.4824986 iteration: 87620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0547 FastRCNN class loss: 0.04257 FastRCNN total loss: 0.09727 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 4.0000e-05 Mask loss: 0.10876 RPN box loss: 0.02588 RPN score loss: 0.00346 RPN total loss: 0.02934 Total loss: 0.82271 timestamp: 1654981809.751387 iteration: 87625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08415 FastRCNN class loss: 0.06636 FastRCNN total loss: 0.15051 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.16426 RPN box loss: 0.01587 RPN score loss: 0.00406 RPN total loss: 0.01994 Total loss: 0.92204 timestamp: 1654981812.9703643 iteration: 87630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0915 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.15938 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.15309 RPN box loss: 0.01873 RPN score loss: 0.00569 RPN total loss: 0.02442 Total loss: 0.92423 timestamp: 1654981816.1138747 iteration: 87635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11029 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.17798 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.14857 RPN box loss: 0.01201 RPN score loss: 0.00214 RPN total loss: 0.01414 Total loss: 0.92803 timestamp: 1654981819.3095996 iteration: 87640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09515 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.15477 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10726 RPN box loss: 0.01038 RPN score loss: 0.00244 RPN total loss: 0.01282 Total loss: 0.86219 timestamp: 1654981822.4828296 iteration: 87645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04028 FastRCNN class loss: 0.0335 FastRCNN total loss: 0.07378 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10578 RPN box loss: 0.00522 RPN score loss: 0.00425 RPN total loss: 0.00947 Total loss: 0.77637 timestamp: 1654981825.6517675 iteration: 87650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03793 FastRCNN class loss: 0.02924 FastRCNN total loss: 0.06717 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10888 RPN box loss: 0.00187 RPN score loss: 0.00169 RPN total loss: 0.00355 Total loss: 0.76694 timestamp: 1654981828.885364 iteration: 87655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07812 FastRCNN class loss: 0.05692 FastRCNN total loss: 0.13504 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10005 RPN box loss: 0.00497 RPN score loss: 0.00154 RPN total loss: 0.00651 Total loss: 0.82894 timestamp: 1654981832.0574114 iteration: 87660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08374 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.13828 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11016 RPN box loss: 0.00886 RPN score loss: 0.00196 RPN total loss: 0.01082 Total loss: 0.84659 timestamp: 1654981835.205542 iteration: 87665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0981 FastRCNN class loss: 0.05355 FastRCNN total loss: 0.15165 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12908 RPN box loss: 0.0071 RPN score loss: 0.0017 RPN total loss: 0.0088 Total loss: 0.87686 timestamp: 1654981838.401329 iteration: 87670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08872 FastRCNN class loss: 0.09129 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.1501 RPN box loss: 0.00807 RPN score loss: 0.00639 RPN total loss: 0.01446 Total loss: 0.93191 timestamp: 1654981841.560122 iteration: 87675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15746 FastRCNN class loss: 0.09376 FastRCNN total loss: 0.25122 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11712 RPN box loss: 0.0158 RPN score loss: 0.00061 RPN total loss: 0.0164 Total loss: 0.97208 timestamp: 1654981844.7585304 iteration: 87680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.03877 FastRCNN total loss: 0.12595 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.13653 RPN box loss: 0.02695 RPN score loss: 0.00305 RPN total loss: 0.03001 Total loss: 0.87981 timestamp: 1654981847.9543755 iteration: 87685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05215 FastRCNN class loss: 0.0452 FastRCNN total loss: 0.09735 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11556 RPN box loss: 0.01196 RPN score loss: 0.00342 RPN total loss: 0.01538 Total loss: 0.81562 timestamp: 1654981851.265355 iteration: 87690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09384 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.19134 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.15186 RPN box loss: 0.0143 RPN score loss: 0.00167 RPN total loss: 0.01597 Total loss: 0.9465 timestamp: 1654981854.4507146 iteration: 87695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07009 FastRCNN class loss: 0.06825 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12435 RPN box loss: 0.00841 RPN score loss: 0.00355 RPN total loss: 0.01197 Total loss: 0.86198 timestamp: 1654981857.6625109 iteration: 87700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08925 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.15638 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.09989 RPN box loss: 0.00699 RPN score loss: 0.00464 RPN total loss: 0.01163 Total loss: 0.85523 timestamp: 1654981860.9152358 iteration: 87705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07146 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.1318 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.13446 RPN box loss: 0.01153 RPN score loss: 0.00376 RPN total loss: 0.01529 Total loss: 0.86887 timestamp: 1654981864.07862 iteration: 87710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06771 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.12847 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.20393 RPN box loss: 0.01515 RPN score loss: 0.01281 RPN total loss: 0.02796 Total loss: 0.9477 timestamp: 1654981867.2256293 iteration: 87715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10366 FastRCNN class loss: 0.05033 FastRCNN total loss: 0.15399 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.14941 RPN box loss: 0.00575 RPN score loss: 0.00328 RPN total loss: 0.00903 Total loss: 0.89976 timestamp: 1654981870.402338 iteration: 87720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.18177 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.14223 RPN box loss: 0.01324 RPN score loss: 0.00338 RPN total loss: 0.01663 Total loss: 0.92796 timestamp: 1654981873.5249925 iteration: 87725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04541 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.10176 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.09849 RPN box loss: 0.00567 RPN score loss: 0.00559 RPN total loss: 0.01126 Total loss: 0.79884 timestamp: 1654981876.7901802 iteration: 87730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08452 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.1484 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.1706 RPN box loss: 0.01276 RPN score loss: 0.00971 RPN total loss: 0.02246 Total loss: 0.92879 timestamp: 1654981879.9710805 iteration: 87735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09892 FastRCNN class loss: 0.04937 FastRCNN total loss: 0.14829 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.08563 RPN box loss: 0.00936 RPN score loss: 0.00671 RPN total loss: 0.01606 Total loss: 0.83731 timestamp: 1654981883.1794379 iteration: 87740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14851 FastRCNN class loss: 0.06703 FastRCNN total loss: 0.21554 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.07741 RPN box loss: 0.00345 RPN score loss: 0.0019 RPN total loss: 0.00534 Total loss: 0.88562 timestamp: 1654981886.4044135 iteration: 87745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11328 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.18015 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11107 RPN box loss: 0.02041 RPN score loss: 0.00277 RPN total loss: 0.02318 Total loss: 0.90173 timestamp: 1654981889.6422536 iteration: 87750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.0641 FastRCNN total loss: 0.15866 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.13663 RPN box loss: 0.00945 RPN score loss: 0.00366 RPN total loss: 0.01311 Total loss: 0.89573 timestamp: 1654981892.834947 iteration: 87755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06757 FastRCNN class loss: 0.05827 FastRCNN total loss: 0.12584 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12781 RPN box loss: 0.01649 RPN score loss: 0.0091 RPN total loss: 0.02559 Total loss: 0.86656 timestamp: 1654981896.0186157 iteration: 87760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10771 FastRCNN class loss: 0.09996 FastRCNN total loss: 0.20767 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.15404 RPN box loss: 0.01551 RPN score loss: 0.0088 RPN total loss: 0.0243 Total loss: 0.97335 timestamp: 1654981899.2238386 iteration: 87765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04782 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.09496 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.08598 RPN box loss: 0.00888 RPN score loss: 0.00202 RPN total loss: 0.0109 Total loss: 0.77917 timestamp: 1654981902.3520935 iteration: 87770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05249 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.13861 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.0919 RPN box loss: 0.01432 RPN score loss: 0.00518 RPN total loss: 0.01951 Total loss: 0.83735 timestamp: 1654981905.5585835 iteration: 87775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08063 FastRCNN class loss: 0.04259 FastRCNN total loss: 0.12322 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12518 RPN box loss: 0.01184 RPN score loss: 0.00579 RPN total loss: 0.01764 Total loss: 0.85336 timestamp: 1654981908.7915897 iteration: 87780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0751 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.12814 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12554 RPN box loss: 0.00948 RPN score loss: 0.00133 RPN total loss: 0.01081 Total loss: 0.85182 timestamp: 1654981911.9760587 iteration: 87785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07634 FastRCNN class loss: 0.08831 FastRCNN total loss: 0.16465 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.15046 RPN box loss: 0.0066 RPN score loss: 0.00708 RPN total loss: 0.01367 Total loss: 0.91612 timestamp: 1654981915.2326233 iteration: 87790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.05324 FastRCNN total loss: 0.12979 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.1691 RPN box loss: 0.00583 RPN score loss: 0.00541 RPN total loss: 0.01125 Total loss: 0.89747 timestamp: 1654981918.4024208 iteration: 87795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07432 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.14212 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.0973 RPN box loss: 0.01061 RPN score loss: 0.00404 RPN total loss: 0.01465 Total loss: 0.84139 timestamp: 1654981921.6131096 iteration: 87800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06614 FastRCNN class loss: 0.04936 FastRCNN total loss: 0.1155 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.09261 RPN box loss: 0.00333 RPN score loss: 0.00593 RPN total loss: 0.00926 Total loss: 0.8047 timestamp: 1654981924.9088478 iteration: 87805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09909 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.15754 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.1113 RPN box loss: 0.03906 RPN score loss: 0.00254 RPN total loss: 0.0416 Total loss: 0.89778 timestamp: 1654981928.0963886 iteration: 87810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08582 FastRCNN class loss: 0.04212 FastRCNN total loss: 0.12794 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10996 RPN box loss: 0.01033 RPN score loss: 0.00817 RPN total loss: 0.01849 Total loss: 0.84373 timestamp: 1654981931.265081 iteration: 87815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09005 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.15488 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10569 RPN box loss: 0.00806 RPN score loss: 0.00501 RPN total loss: 0.01307 Total loss: 0.86097 timestamp: 1654981934.5042675 iteration: 87820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09183 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.14232 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.13152 RPN box loss: 0.0128 RPN score loss: 0.00647 RPN total loss: 0.01927 Total loss: 0.88044 timestamp: 1654981937.789918 iteration: 87825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07175 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.14534 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.18057 RPN box loss: 0.01346 RPN score loss: 0.00359 RPN total loss: 0.01704 Total loss: 0.93028 timestamp: 1654981941.0243633 iteration: 87830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08939 FastRCNN class loss: 0.0585 FastRCNN total loss: 0.14789 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10259 RPN box loss: 0.00775 RPN score loss: 0.00298 RPN total loss: 0.01073 Total loss: 0.84854 timestamp: 1654981944.253158 iteration: 87835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08964 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.16628 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.1083 RPN box loss: 0.00676 RPN score loss: 0.00366 RPN total loss: 0.01042 Total loss: 0.87233 timestamp: 1654981947.4560363 iteration: 87840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06458 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.12577 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.13533 RPN box loss: 0.01007 RPN score loss: 0.00223 RPN total loss: 0.0123 Total loss: 0.86073 timestamp: 1654981950.7053978 iteration: 87845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11754 FastRCNN class loss: 0.06553 FastRCNN total loss: 0.18307 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10386 RPN box loss: 0.01179 RPN score loss: 0.0032 RPN total loss: 0.015 Total loss: 0.88926 timestamp: 1654981953.9238849 iteration: 87850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08321 FastRCNN class loss: 0.06699 FastRCNN total loss: 0.15019 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12532 RPN box loss: 0.03479 RPN score loss: 0.00736 RPN total loss: 0.04215 Total loss: 0.905 timestamp: 1654981957.1343715 iteration: 87855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08723 FastRCNN class loss: 0.03847 FastRCNN total loss: 0.12569 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10799 RPN box loss: 0.00907 RPN score loss: 0.00153 RPN total loss: 0.0106 Total loss: 0.83161 timestamp: 1654981960.2935169 iteration: 87860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05043 FastRCNN class loss: 0.03462 FastRCNN total loss: 0.08505 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.0953 RPN box loss: 0.00803 RPN score loss: 0.00196 RPN total loss: 0.01 Total loss: 0.77767 timestamp: 1654981963.418876 iteration: 87865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11501 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.18559 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.13305 RPN box loss: 0.02513 RPN score loss: 0.00617 RPN total loss: 0.0313 Total loss: 0.93726 timestamp: 1654981966.5684004 iteration: 87870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06793 FastRCNN class loss: 0.05196 FastRCNN total loss: 0.1199 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12525 RPN box loss: 0.00643 RPN score loss: 0.00165 RPN total loss: 0.00807 Total loss: 0.84055 timestamp: 1654981969.7709897 iteration: 87875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08711 FastRCNN class loss: 0.04404 FastRCNN total loss: 0.13116 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11634 RPN box loss: 0.01153 RPN score loss: 0.00273 RPN total loss: 0.01426 Total loss: 0.84907 timestamp: 1654981972.944066 iteration: 87880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04302 FastRCNN class loss: 0.03627 FastRCNN total loss: 0.0793 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.14541 RPN box loss: 0.00566 RPN score loss: 0.00707 RPN total loss: 0.01274 Total loss: 0.82477 timestamp: 1654981976.129117 iteration: 87885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05746 FastRCNN class loss: 0.05705 FastRCNN total loss: 0.1145 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.18218 RPN box loss: 0.01273 RPN score loss: 0.00234 RPN total loss: 0.01507 Total loss: 0.89907 timestamp: 1654981979.3509028 iteration: 87890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08863 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.14985 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12029 RPN box loss: 0.01642 RPN score loss: 0.00119 RPN total loss: 0.01762 Total loss: 0.87509 timestamp: 1654981982.582413 iteration: 87895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08603 FastRCNN class loss: 0.04556 FastRCNN total loss: 0.13159 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11341 RPN box loss: 0.01286 RPN score loss: 0.00328 RPN total loss: 0.01614 Total loss: 0.84847 timestamp: 1654981985.7990704 iteration: 87900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04882 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.14229 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12453 RPN box loss: 0.00504 RPN score loss: 0.00136 RPN total loss: 0.0064 Total loss: 0.86055 timestamp: 1654981989.0280015 iteration: 87905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11512 FastRCNN class loss: 0.08382 FastRCNN total loss: 0.19893 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.12267 RPN box loss: 0.01133 RPN score loss: 0.00918 RPN total loss: 0.02051 Total loss: 0.92944 timestamp: 1654981992.1849155 iteration: 87910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06103 FastRCNN class loss: 0.04038 FastRCNN total loss: 0.10141 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.09347 RPN box loss: 0.00511 RPN score loss: 0.00177 RPN total loss: 0.00688 Total loss: 0.78909 timestamp: 1654981995.3182528 iteration: 87915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13959 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.20881 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.1373 RPN box loss: 0.01681 RPN score loss: 0.0038 RPN total loss: 0.02061 Total loss: 0.95405 timestamp: 1654981998.5012183 iteration: 87920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10236 FastRCNN class loss: 0.05319 FastRCNN total loss: 0.15555 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.10668 RPN box loss: 0.00866 RPN score loss: 0.00146 RPN total loss: 0.01012 Total loss: 0.85968 timestamp: 1654982001.715158 iteration: 87925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07446 FastRCNN class loss: 0.05488 FastRCNN total loss: 0.12934 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11569 RPN box loss: 0.01678 RPN score loss: 0.003 RPN total loss: 0.01978 Total loss: 0.85213 timestamp: 1654982004.9907615 iteration: 87930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08661 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.13665 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 4.0000e-05 Mask loss: 0.11405 RPN box loss: 0.01122 RPN score loss: 0.0051 RPN total loss: 0.01632 Total loss: 0.85435 timestamp: 1654982008.1599042 iteration: 87935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07302 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.1375 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10307 RPN box loss: 0.00735 RPN score loss: 0.00203 RPN total loss: 0.00938 Total loss: 0.83727 timestamp: 1654982011.4042077 iteration: 87940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05368 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.11059 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10143 RPN box loss: 0.00565 RPN score loss: 0.00145 RPN total loss: 0.0071 Total loss: 0.80644 timestamp: 1654982014.5887918 iteration: 87945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09292 FastRCNN class loss: 0.04374 FastRCNN total loss: 0.13666 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.09965 RPN box loss: 0.01376 RPN score loss: 0.00186 RPN total loss: 0.01562 Total loss: 0.83925 timestamp: 1654982017.734301 iteration: 87950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04578 FastRCNN class loss: 0.04091 FastRCNN total loss: 0.08669 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10474 RPN box loss: 0.0051 RPN score loss: 0.00381 RPN total loss: 0.0089 Total loss: 0.78766 timestamp: 1654982020.8715963 iteration: 87955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10223 FastRCNN class loss: 0.06423 FastRCNN total loss: 0.16646 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.13145 RPN box loss: 0.01841 RPN score loss: 0.01144 RPN total loss: 0.02985 Total loss: 0.91508 timestamp: 1654982024.086046 iteration: 87960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14425 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.20444 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1413 RPN box loss: 0.04087 RPN score loss: 0.00582 RPN total loss: 0.04669 Total loss: 0.97975 timestamp: 1654982027.3159618 iteration: 87965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04902 FastRCNN class loss: 0.04516 FastRCNN total loss: 0.09419 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.08338 RPN box loss: 0.01068 RPN score loss: 0.00182 RPN total loss: 0.0125 Total loss: 0.77739 timestamp: 1654982030.5077739 iteration: 87970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09529 FastRCNN class loss: 0.04515 FastRCNN total loss: 0.14044 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11562 RPN box loss: 0.01158 RPN score loss: 0.00234 RPN total loss: 0.01392 Total loss: 0.8573 timestamp: 1654982033.692054 iteration: 87975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11236 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.17935 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11076 RPN box loss: 0.0125 RPN score loss: 0.00677 RPN total loss: 0.01927 Total loss: 0.89671 timestamp: 1654982036.89152 iteration: 87980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07287 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.13674 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12353 RPN box loss: 0.01221 RPN score loss: 0.00335 RPN total loss: 0.01556 Total loss: 0.86316 timestamp: 1654982040.1242845 iteration: 87985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08711 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.16886 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12502 RPN box loss: 0.00579 RPN score loss: 0.0056 RPN total loss: 0.01139 Total loss: 0.8926 timestamp: 1654982043.3907003 iteration: 87990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12462 FastRCNN class loss: 0.09963 FastRCNN total loss: 0.22425 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1083 RPN box loss: 0.00806 RPN score loss: 0.00789 RPN total loss: 0.01595 Total loss: 0.93582 timestamp: 1654982046.576402 iteration: 87995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07658 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.13411 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12203 RPN box loss: 0.01854 RPN score loss: 0.0064 RPN total loss: 0.02494 Total loss: 0.8684 timestamp: 1654982049.7269502 iteration: 88000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06553 FastRCNN class loss: 0.03369 FastRCNN total loss: 0.09922 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.13217 RPN box loss: 0.00788 RPN score loss: 0.00562 RPN total loss: 0.01351 Total loss: 0.83222 timestamp: 1654982052.9406822 iteration: 88005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07821 FastRCNN class loss: 0.05836 FastRCNN total loss: 0.13657 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.09315 RPN box loss: 0.01268 RPN score loss: 0.00282 RPN total loss: 0.0155 Total loss: 0.83254 timestamp: 1654982056.106812 iteration: 88010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08836 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.16431 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.16555 RPN box loss: 0.01424 RPN score loss: 0.00452 RPN total loss: 0.01876 Total loss: 0.93594 timestamp: 1654982059.2496843 iteration: 88015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08048 FastRCNN class loss: 0.10221 FastRCNN total loss: 0.18269 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.09143 RPN box loss: 0.0179 RPN score loss: 0.0079 RPN total loss: 0.0258 Total loss: 0.88725 timestamp: 1654982062.4995759 iteration: 88020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06448 FastRCNN class loss: 0.07514 FastRCNN total loss: 0.13962 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.14617 RPN box loss: 0.00985 RPN score loss: 0.00525 RPN total loss: 0.0151 Total loss: 0.88821 timestamp: 1654982065.6996732 iteration: 88025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13557 FastRCNN class loss: 0.09015 FastRCNN total loss: 0.22572 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10817 RPN box loss: 0.01288 RPN score loss: 0.0075 RPN total loss: 0.02038 Total loss: 0.9416 timestamp: 1654982068.8969812 iteration: 88030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10806 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.17457 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10572 RPN box loss: 0.00805 RPN score loss: 0.00468 RPN total loss: 0.01273 Total loss: 0.88034 timestamp: 1654982072.0889838 iteration: 88035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08593 FastRCNN class loss: 0.10907 FastRCNN total loss: 0.195 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.16291 RPN box loss: 0.01569 RPN score loss: 0.01609 RPN total loss: 0.03178 Total loss: 0.97701 timestamp: 1654982075.2688527 iteration: 88040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07556 FastRCNN class loss: 0.05276 FastRCNN total loss: 0.12832 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.07447 RPN box loss: 0.00354 RPN score loss: 0.00501 RPN total loss: 0.00855 Total loss: 0.79866 timestamp: 1654982078.4443288 iteration: 88045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09654 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.1732 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.13314 RPN box loss: 0.00885 RPN score loss: 0.00407 RPN total loss: 0.01293 Total loss: 0.90659 timestamp: 1654982081.6189086 iteration: 88050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0869 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.14587 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11522 RPN box loss: 0.00759 RPN score loss: 0.00193 RPN total loss: 0.00952 Total loss: 0.85794 timestamp: 1654982084.8226793 iteration: 88055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07471 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.1176 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.13812 RPN box loss: 0.01469 RPN score loss: 0.00093 RPN total loss: 0.01562 Total loss: 0.85866 timestamp: 1654982088.0009155 iteration: 88060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04636 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.10989 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.07508 RPN box loss: 0.00866 RPN score loss: 0.00218 RPN total loss: 0.01084 Total loss: 0.78313 timestamp: 1654982091.169591 iteration: 88065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14885 FastRCNN class loss: 0.11706 FastRCNN total loss: 0.26591 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.13932 RPN box loss: 0.01605 RPN score loss: 0.00682 RPN total loss: 0.02286 Total loss: 1.01541 timestamp: 1654982094.3437362 iteration: 88070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05656 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.16684 RPN box loss: 0.00824 RPN score loss: 0.00216 RPN total loss: 0.01041 Total loss: 0.90084 timestamp: 1654982097.544261 iteration: 88075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05527 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.11392 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1511 RPN box loss: 0.01355 RPN score loss: 0.00231 RPN total loss: 0.01586 Total loss: 0.8682 timestamp: 1654982100.7620444 iteration: 88080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11437 FastRCNN class loss: 0.08199 FastRCNN total loss: 0.19636 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.14831 RPN box loss: 0.00943 RPN score loss: 0.0029 RPN total loss: 0.01234 Total loss: 0.94433 timestamp: 1654982103.9695494 iteration: 88085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0891 FastRCNN class loss: 0.05277 FastRCNN total loss: 0.14187 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.24158 RPN box loss: 0.00414 RPN score loss: 0.00474 RPN total loss: 0.00888 Total loss: 0.97965 timestamp: 1654982107.1960893 iteration: 88090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06514 FastRCNN class loss: 0.0413 FastRCNN total loss: 0.10644 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10063 RPN box loss: 0.00617 RPN score loss: 0.00444 RPN total loss: 0.01061 Total loss: 0.80499 timestamp: 1654982110.3415565 iteration: 88095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04632 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.10947 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.08943 RPN box loss: 0.01174 RPN score loss: 0.00723 RPN total loss: 0.01897 Total loss: 0.80519 timestamp: 1654982113.496774 iteration: 88100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06071 FastRCNN class loss: 0.03824 FastRCNN total loss: 0.09895 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11639 RPN box loss: 0.00907 RPN score loss: 0.00652 RPN total loss: 0.01559 Total loss: 0.81826 timestamp: 1654982116.6432269 iteration: 88105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08182 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.15164 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.16298 RPN box loss: 0.01848 RPN score loss: 0.00774 RPN total loss: 0.02622 Total loss: 0.92816 timestamp: 1654982119.728838 iteration: 88110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.14494 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.13607 RPN box loss: 0.01396 RPN score loss: 0.0019 RPN total loss: 0.01586 Total loss: 0.88419 timestamp: 1654982122.8609717 iteration: 88115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07295 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.13822 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10695 RPN box loss: 0.01345 RPN score loss: 0.00654 RPN total loss: 0.01998 Total loss: 0.85247 timestamp: 1654982126.067553 iteration: 88120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08907 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.15412 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11291 RPN box loss: 0.01138 RPN score loss: 0.00257 RPN total loss: 0.01395 Total loss: 0.8683 timestamp: 1654982129.2654614 iteration: 88125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10475 FastRCNN class loss: 0.11551 FastRCNN total loss: 0.22025 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.15966 RPN box loss: 0.03355 RPN score loss: 0.00898 RPN total loss: 0.04253 Total loss: 1.00976 timestamp: 1654982132.4834273 iteration: 88130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07426 FastRCNN class loss: 0.04763 FastRCNN total loss: 0.12189 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.08328 RPN box loss: 0.03499 RPN score loss: 0.00398 RPN total loss: 0.03896 Total loss: 0.83145 timestamp: 1654982135.7092419 iteration: 88135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05899 FastRCNN class loss: 0.04264 FastRCNN total loss: 0.10164 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11581 RPN box loss: 0.00396 RPN score loss: 0.00234 RPN total loss: 0.00631 Total loss: 0.81107 timestamp: 1654982139.0004117 iteration: 88140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07424 FastRCNN class loss: 0.05039 FastRCNN total loss: 0.12463 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10121 RPN box loss: 0.0126 RPN score loss: 0.00314 RPN total loss: 0.01574 Total loss: 0.8289 timestamp: 1654982142.1429574 iteration: 88145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06198 FastRCNN class loss: 0.06086 FastRCNN total loss: 0.12284 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.21739 RPN box loss: 0.01899 RPN score loss: 0.00477 RPN total loss: 0.02376 Total loss: 0.95131 timestamp: 1654982145.4439454 iteration: 88150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12526 FastRCNN class loss: 0.14081 FastRCNN total loss: 0.26608 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12696 RPN box loss: 0.00686 RPN score loss: 0.00493 RPN total loss: 0.01179 Total loss: 0.99215 timestamp: 1654982148.6069257 iteration: 88155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04888 FastRCNN class loss: 0.03836 FastRCNN total loss: 0.08724 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1178 RPN box loss: 0.00712 RPN score loss: 0.00633 RPN total loss: 0.01346 Total loss: 0.80582 timestamp: 1654982151.8030546 iteration: 88160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12514 FastRCNN class loss: 0.08787 FastRCNN total loss: 0.21302 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12663 RPN box loss: 0.01581 RPN score loss: 0.0036 RPN total loss: 0.01942 Total loss: 0.94638 timestamp: 1654982154.9301279 iteration: 88165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05911 FastRCNN class loss: 0.04097 FastRCNN total loss: 0.10008 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1215 RPN box loss: 0.01831 RPN score loss: 0.00138 RPN total loss: 0.01969 Total loss: 0.82859 timestamp: 1654982158.1361372 iteration: 88170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08621 FastRCNN class loss: 0.04467 FastRCNN total loss: 0.13088 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.17448 RPN box loss: 0.0154 RPN score loss: 0.01634 RPN total loss: 0.03174 Total loss: 0.92442 timestamp: 1654982161.280218 iteration: 88175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.13406 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11001 RPN box loss: 0.01019 RPN score loss: 0.00411 RPN total loss: 0.0143 Total loss: 0.84569 timestamp: 1654982164.5111563 iteration: 88180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08266 FastRCNN class loss: 0.1071 FastRCNN total loss: 0.18976 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12304 RPN box loss: 0.01143 RPN score loss: 0.01073 RPN total loss: 0.02215 Total loss: 0.92228 timestamp: 1654982167.632734 iteration: 88185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06397 FastRCNN class loss: 0.04513 FastRCNN total loss: 0.1091 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11569 RPN box loss: 0.00356 RPN score loss: 0.00257 RPN total loss: 0.00613 Total loss: 0.81824 timestamp: 1654982170.8977358 iteration: 88190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09253 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12591 RPN box loss: 0.01522 RPN score loss: 0.00118 RPN total loss: 0.01641 Total loss: 0.89629 timestamp: 1654982174.0758247 iteration: 88195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06552 FastRCNN class loss: 0.03291 FastRCNN total loss: 0.09843 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1092 RPN box loss: 0.00384 RPN score loss: 0.00348 RPN total loss: 0.00732 Total loss: 0.80226 timestamp: 1654982177.278608 iteration: 88200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06408 FastRCNN class loss: 0.05903 FastRCNN total loss: 0.1231 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12463 RPN box loss: 0.02516 RPN score loss: 0.00559 RPN total loss: 0.03076 Total loss: 0.8658 timestamp: 1654982180.421542 iteration: 88205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08931 FastRCNN class loss: 0.06641 FastRCNN total loss: 0.15572 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12393 RPN box loss: 0.02121 RPN score loss: 0.00842 RPN total loss: 0.02963 Total loss: 0.8966 timestamp: 1654982183.6741028 iteration: 88210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.04552 FastRCNN total loss: 0.13227 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12936 RPN box loss: 0.01867 RPN score loss: 0.00162 RPN total loss: 0.02029 Total loss: 0.86924 timestamp: 1654982186.873235 iteration: 88215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11184 FastRCNN class loss: 0.03571 FastRCNN total loss: 0.14755 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.07434 RPN box loss: 0.00739 RPN score loss: 0.00173 RPN total loss: 0.00912 Total loss: 0.81832 timestamp: 1654982190.1056552 iteration: 88220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0905 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.15436 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.11897 RPN box loss: 0.01121 RPN score loss: 0.00262 RPN total loss: 0.01383 Total loss: 0.87447 timestamp: 1654982193.2928574 iteration: 88225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06472 FastRCNN class loss: 0.05513 FastRCNN total loss: 0.11985 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.1306 RPN box loss: 0.0087 RPN score loss: 0.00402 RPN total loss: 0.01272 Total loss: 0.85048 timestamp: 1654982196.5231106 iteration: 88230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07215 FastRCNN class loss: 0.06649 FastRCNN total loss: 0.13864 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.12316 RPN box loss: 0.01026 RPN score loss: 0.00183 RPN total loss: 0.01209 Total loss: 0.86121 timestamp: 1654982199.7224736 iteration: 88235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0529 FastRCNN class loss: 0.04596 FastRCNN total loss: 0.09886 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10889 RPN box loss: 0.00647 RPN score loss: 0.0021 RPN total loss: 0.00857 Total loss: 0.80363 timestamp: 1654982202.985363 iteration: 88240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08722 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.1594 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.14143 RPN box loss: 0.00734 RPN score loss: 0.00345 RPN total loss: 0.01079 Total loss: 0.89894 timestamp: 1654982206.1123755 iteration: 88245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.06699 FastRCNN total loss: 0.16014 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.10439 RPN box loss: 0.00995 RPN score loss: 0.00784 RPN total loss: 0.0178 Total loss: 0.86965 timestamp: 1654982209.3488073 iteration: 88250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16219 FastRCNN class loss: 0.11526 FastRCNN total loss: 0.27745 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.20322 RPN box loss: 0.00732 RPN score loss: 0.01154 RPN total loss: 0.01886 Total loss: 1.08684 timestamp: 1654982212.522425 iteration: 88255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05103 FastRCNN class loss: 0.03219 FastRCNN total loss: 0.08322 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 4.0000e-05 Mask loss: 0.09173 RPN box loss: 0.00553 RPN score loss: 0.00532 RPN total loss: 0.01085 Total loss: 0.77311 timestamp: 1654982215.6804008 iteration: 88260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09696 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.15794 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11847 RPN box loss: 0.01047 RPN score loss: 0.00407 RPN total loss: 0.01454 Total loss: 0.87827 timestamp: 1654982218.873968 iteration: 88265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15676 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.21031 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13634 RPN box loss: 0.00934 RPN score loss: 0.00339 RPN total loss: 0.01272 Total loss: 0.94668 timestamp: 1654982222.0216515 iteration: 88270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10838 FastRCNN class loss: 0.08425 FastRCNN total loss: 0.19263 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.19413 RPN box loss: 0.01346 RPN score loss: 0.00534 RPN total loss: 0.01879 Total loss: 0.99287 timestamp: 1654982225.136566 iteration: 88275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08173 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.163 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14458 RPN box loss: 0.00548 RPN score loss: 0.00213 RPN total loss: 0.00761 Total loss: 0.9025 timestamp: 1654982228.3626783 iteration: 88280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10981 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.17528 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.1222 RPN box loss: 0.00708 RPN score loss: 0.0026 RPN total loss: 0.00968 Total loss: 0.89448 timestamp: 1654982231.6444082 iteration: 88285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09871 FastRCNN class loss: 0.04614 FastRCNN total loss: 0.14484 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10129 RPN box loss: 0.00964 RPN score loss: 0.00311 RPN total loss: 0.01275 Total loss: 0.84619 timestamp: 1654982234.8583584 iteration: 88290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12214 FastRCNN class loss: 0.08345 FastRCNN total loss: 0.2056 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.20537 RPN box loss: 0.01487 RPN score loss: 0.00534 RPN total loss: 0.02021 Total loss: 1.01849 timestamp: 1654982238.0680478 iteration: 88295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09765 FastRCNN class loss: 0.09277 FastRCNN total loss: 0.19042 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.17809 RPN box loss: 0.02063 RPN score loss: 0.01144 RPN total loss: 0.03207 Total loss: 0.9879 timestamp: 1654982241.2811594 iteration: 88300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09047 FastRCNN class loss: 0.10661 FastRCNN total loss: 0.19708 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.16441 RPN box loss: 0.02892 RPN score loss: 0.0089 RPN total loss: 0.03782 Total loss: 0.98662 timestamp: 1654982244.5240376 iteration: 88305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14099 FastRCNN class loss: 0.06202 FastRCNN total loss: 0.203 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10807 RPN box loss: 0.03202 RPN score loss: 0.00204 RPN total loss: 0.03407 Total loss: 0.93245 timestamp: 1654982247.6803832 iteration: 88310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12845 FastRCNN class loss: 0.11959 FastRCNN total loss: 0.24804 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.18087 RPN box loss: 0.01724 RPN score loss: 0.01714 RPN total loss: 0.03438 Total loss: 1.05061 timestamp: 1654982250.7780154 iteration: 88315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.10427 FastRCNN total loss: 0.2036 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.12627 RPN box loss: 0.01983 RPN score loss: 0.01018 RPN total loss: 0.03001 Total loss: 0.9472 timestamp: 1654982254.0153422 iteration: 88320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.16428 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11402 RPN box loss: 0.00778 RPN score loss: 0.00338 RPN total loss: 0.01117 Total loss: 0.87678 timestamp: 1654982257.2244275 iteration: 88325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0406 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.09852 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.09315 RPN box loss: 0.00614 RPN score loss: 0.00734 RPN total loss: 0.01348 Total loss: 0.79247 timestamp: 1654982260.4625647 iteration: 88330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05974 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.1132 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11733 RPN box loss: 0.00618 RPN score loss: 0.00083 RPN total loss: 0.00701 Total loss: 0.82486 timestamp: 1654982263.65654 iteration: 88335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06927 FastRCNN class loss: 0.06314 FastRCNN total loss: 0.13241 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.12878 RPN box loss: 0.00476 RPN score loss: 0.00458 RPN total loss: 0.00934 Total loss: 0.85785 timestamp: 1654982266.823899 iteration: 88340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08348 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.14788 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13332 RPN box loss: 0.00592 RPN score loss: 0.00302 RPN total loss: 0.00894 Total loss: 0.87746 timestamp: 1654982270.0771217 iteration: 88345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06829 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.11867 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14188 RPN box loss: 0.00593 RPN score loss: 0.00163 RPN total loss: 0.00756 Total loss: 0.85541 timestamp: 1654982273.2994637 iteration: 88350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10779 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.17455 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.15577 RPN box loss: 0.02017 RPN score loss: 0.00217 RPN total loss: 0.02234 Total loss: 0.93997 timestamp: 1654982276.5039105 iteration: 88355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12453 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.18563 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13656 RPN box loss: 0.01327 RPN score loss: 0.00324 RPN total loss: 0.01652 Total loss: 0.92602 timestamp: 1654982279.7113001 iteration: 88360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08158 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.14007 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11235 RPN box loss: 0.00813 RPN score loss: 0.00111 RPN total loss: 0.00924 Total loss: 0.84898 timestamp: 1654982282.9153543 iteration: 88365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04875 FastRCNN class loss: 0.04079 FastRCNN total loss: 0.08953 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11281 RPN box loss: 0.00394 RPN score loss: 0.0023 RPN total loss: 0.00624 Total loss: 0.79589 timestamp: 1654982286.1301696 iteration: 88370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07942 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.16907 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10572 RPN box loss: 0.01361 RPN score loss: 0.00073 RPN total loss: 0.01434 Total loss: 0.87643 timestamp: 1654982289.3442078 iteration: 88375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08687 FastRCNN class loss: 0.04622 FastRCNN total loss: 0.13309 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11853 RPN box loss: 0.00651 RPN score loss: 0.00143 RPN total loss: 0.00793 Total loss: 0.84687 timestamp: 1654982292.603737 iteration: 88380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09647 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.17068 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13582 RPN box loss: 0.0041 RPN score loss: 0.01213 RPN total loss: 0.01623 Total loss: 0.91003 timestamp: 1654982295.7296586 iteration: 88385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12913 FastRCNN class loss: 0.08253 FastRCNN total loss: 0.21166 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.15054 RPN box loss: 0.00584 RPN score loss: 0.00493 RPN total loss: 0.01077 Total loss: 0.96028 timestamp: 1654982298.973427 iteration: 88390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05547 FastRCNN class loss: 0.06034 FastRCNN total loss: 0.11582 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13206 RPN box loss: 0.00849 RPN score loss: 0.00388 RPN total loss: 0.01237 Total loss: 0.84756 timestamp: 1654982302.1433856 iteration: 88395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08435 FastRCNN class loss: 0.0404 FastRCNN total loss: 0.12474 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.0916 RPN box loss: 0.00363 RPN score loss: 0.00412 RPN total loss: 0.00774 Total loss: 0.8114 timestamp: 1654982305.2935956 iteration: 88400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11261 FastRCNN class loss: 0.09448 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.16261 RPN box loss: 0.02903 RPN score loss: 0.01006 RPN total loss: 0.03909 Total loss: 0.9961 timestamp: 1654982308.5350642 iteration: 88405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04479 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.0939 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.09606 RPN box loss: 0.00722 RPN score loss: 0.00448 RPN total loss: 0.0117 Total loss: 0.78897 timestamp: 1654982311.7058773 iteration: 88410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10513 FastRCNN class loss: 0.10255 FastRCNN total loss: 0.20768 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13806 RPN box loss: 0.01739 RPN score loss: 0.01239 RPN total loss: 0.02978 Total loss: 0.96283 timestamp: 1654982314.937223 iteration: 88415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13646 FastRCNN class loss: 0.09229 FastRCNN total loss: 0.22875 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14591 RPN box loss: 0.03369 RPN score loss: 0.00737 RPN total loss: 0.04106 Total loss: 1.00303 timestamp: 1654982318.1847422 iteration: 88420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05943 FastRCNN class loss: 0.07181 FastRCNN total loss: 0.13124 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14364 RPN box loss: 0.0226 RPN score loss: 0.0088 RPN total loss: 0.03141 Total loss: 0.8936 timestamp: 1654982321.3587904 iteration: 88425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06154 FastRCNN class loss: 0.04196 FastRCNN total loss: 0.10349 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.0761 RPN box loss: 0.00876 RPN score loss: 0.00168 RPN total loss: 0.01044 Total loss: 0.77735 timestamp: 1654982324.5451827 iteration: 88430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12927 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.19306 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.17137 RPN box loss: 0.0156 RPN score loss: 0.00391 RPN total loss: 0.01951 Total loss: 0.97124 timestamp: 1654982327.781589 iteration: 88435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09443 FastRCNN class loss: 0.07069 FastRCNN total loss: 0.16512 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14689 RPN box loss: 0.01264 RPN score loss: 0.00707 RPN total loss: 0.01971 Total loss: 0.91903 timestamp: 1654982330.9848628 iteration: 88440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04793 FastRCNN class loss: 0.03685 FastRCNN total loss: 0.08478 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10931 RPN box loss: 0.00517 RPN score loss: 0.00474 RPN total loss: 0.00991 Total loss: 0.79131 timestamp: 1654982334.2339947 iteration: 88445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.05568 FastRCNN total loss: 0.14741 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.0867 RPN box loss: 0.01594 RPN score loss: 0.00196 RPN total loss: 0.0179 Total loss: 0.83932 timestamp: 1654982337.4149382 iteration: 88450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17732 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.25281 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.15746 RPN box loss: 0.01891 RPN score loss: 0.00281 RPN total loss: 0.02172 Total loss: 1.0193 timestamp: 1654982340.6638901 iteration: 88455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0764 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.15751 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11731 RPN box loss: 0.023 RPN score loss: 0.00925 RPN total loss: 0.03225 Total loss: 0.89439 timestamp: 1654982343.8429983 iteration: 88460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07844 FastRCNN class loss: 0.06883 FastRCNN total loss: 0.14726 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.184 RPN box loss: 0.02561 RPN score loss: 0.00473 RPN total loss: 0.03034 Total loss: 0.94892 timestamp: 1654982347.0976512 iteration: 88465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05834 FastRCNN class loss: 0.0405 FastRCNN total loss: 0.09884 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.09559 RPN box loss: 0.0105 RPN score loss: 0.0017 RPN total loss: 0.0122 Total loss: 0.79394 timestamp: 1654982350.3047712 iteration: 88470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08626 FastRCNN class loss: 0.06615 FastRCNN total loss: 0.15241 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.16045 RPN box loss: 0.01026 RPN score loss: 0.0048 RPN total loss: 0.01507 Total loss: 0.91524 timestamp: 1654982353.5053022 iteration: 88475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06719 FastRCNN class loss: 0.06144 FastRCNN total loss: 0.12864 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.09727 RPN box loss: 0.00996 RPN score loss: 0.00176 RPN total loss: 0.01172 Total loss: 0.82494 timestamp: 1654982356.642146 iteration: 88480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.06192 FastRCNN total loss: 0.1428 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13051 RPN box loss: 0.01058 RPN score loss: 0.01361 RPN total loss: 0.0242 Total loss: 0.88481 timestamp: 1654982359.8048759 iteration: 88485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08484 FastRCNN class loss: 0.0537 FastRCNN total loss: 0.13854 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11551 RPN box loss: 0.02329 RPN score loss: 0.00385 RPN total loss: 0.02715 Total loss: 0.86851 timestamp: 1654982363.0524063 iteration: 88490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05441 FastRCNN class loss: 0.06047 FastRCNN total loss: 0.11488 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.09763 RPN box loss: 0.01251 RPN score loss: 0.00496 RPN total loss: 0.01747 Total loss: 0.81729 timestamp: 1654982366.3458104 iteration: 88495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07152 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.12665 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.07688 RPN box loss: 0.00658 RPN score loss: 0.00232 RPN total loss: 0.0089 Total loss: 0.79974 timestamp: 1654982369.5341969 iteration: 88500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0984 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.1741 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.16578 RPN box loss: 0.03121 RPN score loss: 0.00462 RPN total loss: 0.03583 Total loss: 0.96303 timestamp: 1654982372.813702 iteration: 88505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06838 FastRCNN class loss: 0.05378 FastRCNN total loss: 0.12216 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.1382 RPN box loss: 0.01 RPN score loss: 0.00645 RPN total loss: 0.01645 Total loss: 0.86412 timestamp: 1654982375.9523158 iteration: 88510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11508 FastRCNN class loss: 0.0775 FastRCNN total loss: 0.19258 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.20556 RPN box loss: 0.00733 RPN score loss: 0.00341 RPN total loss: 0.01074 Total loss: 0.99619 timestamp: 1654982379.1600804 iteration: 88515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09982 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.14697 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.08831 RPN box loss: 0.05018 RPN score loss: 0.00143 RPN total loss: 0.05161 Total loss: 0.87419 timestamp: 1654982382.3707187 iteration: 88520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0781 FastRCNN class loss: 0.05059 FastRCNN total loss: 0.12869 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10075 RPN box loss: 0.00542 RPN score loss: 0.00089 RPN total loss: 0.00631 Total loss: 0.82305 timestamp: 1654982385.5640786 iteration: 88525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06446 FastRCNN class loss: 0.04402 FastRCNN total loss: 0.10849 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.08725 RPN box loss: 0.00785 RPN score loss: 0.0024 RPN total loss: 0.01025 Total loss: 0.79329 timestamp: 1654982388.744846 iteration: 88530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13674 FastRCNN class loss: 0.06324 FastRCNN total loss: 0.19998 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.12423 RPN box loss: 0.004 RPN score loss: 0.00435 RPN total loss: 0.00835 Total loss: 0.91987 timestamp: 1654982391.976657 iteration: 88535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0576 FastRCNN class loss: 0.07985 FastRCNN total loss: 0.13745 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.1734 RPN box loss: 0.01543 RPN score loss: 0.00314 RPN total loss: 0.01857 Total loss: 0.91673 timestamp: 1654982395.1120846 iteration: 88540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13035 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.20639 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10647 RPN box loss: 0.00763 RPN score loss: 0.00435 RPN total loss: 0.01198 Total loss: 0.91214 timestamp: 1654982398.3625524 iteration: 88545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07157 FastRCNN class loss: 0.07398 FastRCNN total loss: 0.14555 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.13589 RPN box loss: 0.00941 RPN score loss: 0.00212 RPN total loss: 0.01153 Total loss: 0.88028 timestamp: 1654982401.558542 iteration: 88550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05057 FastRCNN class loss: 0.04962 FastRCNN total loss: 0.10019 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14967 RPN box loss: 0.01014 RPN score loss: 0.00714 RPN total loss: 0.01727 Total loss: 0.85444 timestamp: 1654982404.7599554 iteration: 88555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09636 FastRCNN class loss: 0.08525 FastRCNN total loss: 0.18161 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.17662 RPN box loss: 0.02401 RPN score loss: 0.01089 RPN total loss: 0.0349 Total loss: 0.98043 timestamp: 1654982407.9865613 iteration: 88560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.07891 FastRCNN total loss: 0.15958 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.14712 RPN box loss: 0.02285 RPN score loss: 0.00916 RPN total loss: 0.03201 Total loss: 0.92602 timestamp: 1654982411.1894717 iteration: 88565 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09251 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.15417 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.1122 RPN box loss: 0.01079 RPN score loss: 0.00148 RPN total loss: 0.01228 Total loss: 0.86595 timestamp: 1654982414.414607 iteration: 88570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06557 FastRCNN class loss: 0.06998 FastRCNN total loss: 0.13555 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.10573 RPN box loss: 0.00527 RPN score loss: 0.01487 RPN total loss: 0.02013 Total loss: 0.84872 timestamp: 1654982417.548227 iteration: 88575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10313 FastRCNN class loss: 0.06633 FastRCNN total loss: 0.16946 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.11457 RPN box loss: 0.01203 RPN score loss: 0.01173 RPN total loss: 0.02376 Total loss: 0.89509 timestamp: 1654982420.765333 iteration: 88580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09766 FastRCNN class loss: 0.07616 FastRCNN total loss: 0.17382 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 4.0000e-05 Mask loss: 0.12125 RPN box loss: 0.01109 RPN score loss: 0.00351 RPN total loss: 0.0146 Total loss: 0.89699 timestamp: 1654982423.9475698 iteration: 88585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09776 FastRCNN class loss: 0.06742 FastRCNN total loss: 0.16518 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.13085 RPN box loss: 0.00672 RPN score loss: 0.01199 RPN total loss: 0.0187 Total loss: 0.90204 timestamp: 1654982427.1846654 iteration: 88590 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.15645 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.19468 RPN box loss: 0.01515 RPN score loss: 0.0016 RPN total loss: 0.01675 Total loss: 0.95518 timestamp: 1654982430.371075 iteration: 88595 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07884 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.1432 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14837 RPN box loss: 0.00653 RPN score loss: 0.00474 RPN total loss: 0.01127 Total loss: 0.89014 timestamp: 1654982433.517612 iteration: 88600 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12611 FastRCNN class loss: 0.11428 FastRCNN total loss: 0.24039 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.16084 RPN box loss: 0.01438 RPN score loss: 0.00997 RPN total loss: 0.02435 Total loss: 1.01289 timestamp: 1654982436.612946 iteration: 88605 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0515 FastRCNN class loss: 0.06496 FastRCNN total loss: 0.11646 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12282 RPN box loss: 0.0097 RPN score loss: 0.0043 RPN total loss: 0.014 Total loss: 0.84059 timestamp: 1654982439.791657 iteration: 88610 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04867 FastRCNN class loss: 0.04249 FastRCNN total loss: 0.09116 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12175 RPN box loss: 0.00695 RPN score loss: 0.00359 RPN total loss: 0.01054 Total loss: 0.81075 timestamp: 1654982442.9543295 iteration: 88615 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07024 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.13263 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12971 RPN box loss: 0.01947 RPN score loss: 0.00628 RPN total loss: 0.02575 Total loss: 0.8754 timestamp: 1654982446.183843 iteration: 88620 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05395 FastRCNN class loss: 0.05526 FastRCNN total loss: 0.10921 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.09685 RPN box loss: 0.00785 RPN score loss: 0.01418 RPN total loss: 0.02203 Total loss: 0.81539 timestamp: 1654982449.3799598 iteration: 88625 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09955 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.15762 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14963 RPN box loss: 0.00512 RPN score loss: 0.00961 RPN total loss: 0.01473 Total loss: 0.90928 timestamp: 1654982452.55657 iteration: 88630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06668 FastRCNN class loss: 0.04488 FastRCNN total loss: 0.11156 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.08962 RPN box loss: 0.00512 RPN score loss: 0.00598 RPN total loss: 0.01109 Total loss: 0.79957 timestamp: 1654982455.7067456 iteration: 88635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15208 FastRCNN class loss: 0.08998 FastRCNN total loss: 0.24206 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15186 RPN box loss: 0.01645 RPN score loss: 0.00803 RPN total loss: 0.02449 Total loss: 1.00571 timestamp: 1654982458.872802 iteration: 88640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12593 FastRCNN class loss: 0.07437 FastRCNN total loss: 0.2003 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15702 RPN box loss: 0.00604 RPN score loss: 0.0017 RPN total loss: 0.00775 Total loss: 0.95237 timestamp: 1654982462.0332706 iteration: 88645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05425 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.10335 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.10867 RPN box loss: 0.03565 RPN score loss: 0.00245 RPN total loss: 0.03809 Total loss: 0.83741 timestamp: 1654982465.3232427 iteration: 88650 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07253 FastRCNN class loss: 0.06663 FastRCNN total loss: 0.13916 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11696 RPN box loss: 0.01404 RPN score loss: 0.00091 RPN total loss: 0.01495 Total loss: 0.85837 timestamp: 1654982468.489251 iteration: 88655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12131 FastRCNN class loss: 0.07457 FastRCNN total loss: 0.19587 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14157 RPN box loss: 0.01217 RPN score loss: 0.0026 RPN total loss: 0.01478 Total loss: 0.93952 timestamp: 1654982471.6379128 iteration: 88660 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13141 FastRCNN class loss: 0.13445 FastRCNN total loss: 0.26586 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15302 RPN box loss: 0.01229 RPN score loss: 0.00726 RPN total loss: 0.01954 Total loss: 1.02572 timestamp: 1654982474.8416753 iteration: 88665 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05292 FastRCNN class loss: 0.03998 FastRCNN total loss: 0.0929 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.09966 RPN box loss: 0.003 RPN score loss: 0.00091 RPN total loss: 0.00391 Total loss: 0.78377 timestamp: 1654982478.0296495 iteration: 88670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13714 FastRCNN class loss: 0.0959 FastRCNN total loss: 0.23303 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.16677 RPN box loss: 0.0091 RPN score loss: 0.00644 RPN total loss: 0.01554 Total loss: 1.00264 timestamp: 1654982481.207708 iteration: 88675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0872 FastRCNN class loss: 0.0544 FastRCNN total loss: 0.1416 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11265 RPN box loss: 0.0091 RPN score loss: 0.00616 RPN total loss: 0.01526 Total loss: 0.85682 timestamp: 1654982484.4052742 iteration: 88680 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0686 FastRCNN class loss: 0.03287 FastRCNN total loss: 0.10147 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.07467 RPN box loss: 0.00725 RPN score loss: 0.00581 RPN total loss: 0.01305 Total loss: 0.77649 timestamp: 1654982487.6201346 iteration: 88685 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13307 FastRCNN class loss: 0.08818 FastRCNN total loss: 0.22124 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14706 RPN box loss: 0.0117 RPN score loss: 0.00829 RPN total loss: 0.02 Total loss: 0.9756 timestamp: 1654982490.8197732 iteration: 88690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05242 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.11228 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12648 RPN box loss: 0.00606 RPN score loss: 0.0011 RPN total loss: 0.00716 Total loss: 0.83323 timestamp: 1654982493.970066 iteration: 88695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08162 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.13466 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14029 RPN box loss: 0.00911 RPN score loss: 0.00255 RPN total loss: 0.01166 Total loss: 0.87392 timestamp: 1654982497.209525 iteration: 88700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08196 FastRCNN class loss: 0.04643 FastRCNN total loss: 0.12839 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.13943 RPN box loss: 0.00965 RPN score loss: 0.00205 RPN total loss: 0.01171 Total loss: 0.86682 timestamp: 1654982500.4269245 iteration: 88705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08571 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.14154 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11141 RPN box loss: 0.00971 RPN score loss: 0.00433 RPN total loss: 0.01404 Total loss: 0.85428 timestamp: 1654982503.6358774 iteration: 88710 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07799 FastRCNN class loss: 0.03963 FastRCNN total loss: 0.11763 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11428 RPN box loss: 0.00373 RPN score loss: 0.0018 RPN total loss: 0.00553 Total loss: 0.82474 timestamp: 1654982506.862936 iteration: 88715 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09194 FastRCNN class loss: 0.07316 FastRCNN total loss: 0.1651 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.1317 RPN box loss: 0.01146 RPN score loss: 0.00701 RPN total loss: 0.01847 Total loss: 0.90257 timestamp: 1654982510.1373143 iteration: 88720 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1475 FastRCNN class loss: 0.08672 FastRCNN total loss: 0.23422 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14961 RPN box loss: 0.00876 RPN score loss: 0.00457 RPN total loss: 0.01333 Total loss: 0.98446 timestamp: 1654982513.3193922 iteration: 88725 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03571 FastRCNN class loss: 0.04724 FastRCNN total loss: 0.08296 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.0902 RPN box loss: 0.00498 RPN score loss: 0.00136 RPN total loss: 0.00634 Total loss: 0.7668 timestamp: 1654982516.6043904 iteration: 88730 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14205 FastRCNN class loss: 0.10917 FastRCNN total loss: 0.25123 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.13011 RPN box loss: 0.03315 RPN score loss: 0.00473 RPN total loss: 0.03789 Total loss: 1.00652 timestamp: 1654982519.8306425 iteration: 88735 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08555 FastRCNN class loss: 0.08088 FastRCNN total loss: 0.16643 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.16915 RPN box loss: 0.01774 RPN score loss: 0.00871 RPN total loss: 0.02645 Total loss: 0.94933 timestamp: 1654982522.998597 iteration: 88740 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1342 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.21653 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.17291 RPN box loss: 0.01876 RPN score loss: 0.00173 RPN total loss: 0.02048 Total loss: 0.99723 timestamp: 1654982526.1822977 iteration: 88745 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05868 FastRCNN class loss: 0.04194 FastRCNN total loss: 0.10063 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11318 RPN box loss: 0.00339 RPN score loss: 0.00263 RPN total loss: 0.00602 Total loss: 0.80713 timestamp: 1654982529.406603 iteration: 88750 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04533 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.11097 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.17413 RPN box loss: 0.00797 RPN score loss: 0.01521 RPN total loss: 0.02318 Total loss: 0.89557 timestamp: 1654982532.544176 iteration: 88755 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07722 FastRCNN class loss: 0.05756 FastRCNN total loss: 0.13478 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.0989 RPN box loss: 0.00618 RPN score loss: 0.00232 RPN total loss: 0.0085 Total loss: 0.82948 timestamp: 1654982535.7664819 iteration: 88760 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06885 FastRCNN class loss: 0.03574 FastRCNN total loss: 0.10458 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11532 RPN box loss: 0.00466 RPN score loss: 0.00104 RPN total loss: 0.0057 Total loss: 0.8129 timestamp: 1654982538.9632995 iteration: 88765 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07859 FastRCNN class loss: 0.10483 FastRCNN total loss: 0.18342 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.1394 RPN box loss: 0.01958 RPN score loss: 0.00703 RPN total loss: 0.02661 Total loss: 0.93673 timestamp: 1654982542.1432774 iteration: 88770 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05927 FastRCNN class loss: 0.03626 FastRCNN total loss: 0.09553 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.09106 RPN box loss: 0.00571 RPN score loss: 0.00358 RPN total loss: 0.00929 Total loss: 0.78318 timestamp: 1654982545.3362405 iteration: 88775 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12137 FastRCNN class loss: 0.10255 FastRCNN total loss: 0.22392 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14601 RPN box loss: 0.02722 RPN score loss: 0.00672 RPN total loss: 0.03394 Total loss: 0.99117 timestamp: 1654982548.5321617 iteration: 88780 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07294 FastRCNN class loss: 0.05804 FastRCNN total loss: 0.13099 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.08446 RPN box loss: 0.00784 RPN score loss: 0.0046 RPN total loss: 0.01244 Total loss: 0.81519 timestamp: 1654982551.720175 iteration: 88785 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08249 FastRCNN class loss: 0.0544 FastRCNN total loss: 0.13688 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.07469 RPN box loss: 0.03125 RPN score loss: 0.00485 RPN total loss: 0.0361 Total loss: 0.83497 timestamp: 1654982554.94289 iteration: 88790 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09951 FastRCNN class loss: 0.08377 FastRCNN total loss: 0.18328 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15906 RPN box loss: 0.01248 RPN score loss: 0.00438 RPN total loss: 0.01687 Total loss: 0.94651 timestamp: 1654982558.0584028 iteration: 88795 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10668 FastRCNN class loss: 0.05881 FastRCNN total loss: 0.16549 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14341 RPN box loss: 0.01025 RPN score loss: 0.00474 RPN total loss: 0.01499 Total loss: 0.91119 timestamp: 1654982561.1900556 iteration: 88800 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10895 FastRCNN class loss: 0.04695 FastRCNN total loss: 0.15591 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.09763 RPN box loss: 0.00713 RPN score loss: 0.00748 RPN total loss: 0.01461 Total loss: 0.85545 timestamp: 1654982564.4303677 iteration: 88805 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09834 FastRCNN class loss: 0.07132 FastRCNN total loss: 0.16966 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12294 RPN box loss: 0.00767 RPN score loss: 0.00126 RPN total loss: 0.00893 Total loss: 0.88882 timestamp: 1654982567.5788226 iteration: 88810 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06126 FastRCNN class loss: 0.04993 FastRCNN total loss: 0.11119 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.13113 RPN box loss: 0.00664 RPN score loss: 0.00161 RPN total loss: 0.00825 Total loss: 0.83787 timestamp: 1654982570.7749596 iteration: 88815 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07525 FastRCNN class loss: 0.0708 FastRCNN total loss: 0.14605 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.16659 RPN box loss: 0.01323 RPN score loss: 0.00927 RPN total loss: 0.0225 Total loss: 0.92243 timestamp: 1654982573.8915594 iteration: 88820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07598 FastRCNN class loss: 0.11143 FastRCNN total loss: 0.18741 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.17383 RPN box loss: 0.01536 RPN score loss: 0.02199 RPN total loss: 0.03735 Total loss: 0.98588 timestamp: 1654982577.0468059 iteration: 88825 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08987 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.16808 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.13103 RPN box loss: 0.00328 RPN score loss: 0.00089 RPN total loss: 0.00418 Total loss: 0.89058 timestamp: 1654982580.2828662 iteration: 88830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05518 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.09465 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.13902 RPN box loss: 0.00802 RPN score loss: 0.00061 RPN total loss: 0.00863 Total loss: 0.8296 timestamp: 1654982583.5145571 iteration: 88835 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07072 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.12587 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.18016 RPN box loss: 0.00812 RPN score loss: 0.00366 RPN total loss: 0.01178 Total loss: 0.90511 timestamp: 1654982586.705708 iteration: 88840 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10444 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.16067 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12158 RPN box loss: 0.01567 RPN score loss: 0.00364 RPN total loss: 0.0193 Total loss: 0.88885 timestamp: 1654982589.9626057 iteration: 88845 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0538 FastRCNN class loss: 0.06905 FastRCNN total loss: 0.12285 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14491 RPN box loss: 0.0154 RPN score loss: 0.00575 RPN total loss: 0.02115 Total loss: 0.87621 timestamp: 1654982593.1293547 iteration: 88850 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.19148 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.08995 RPN box loss: 0.01592 RPN score loss: 0.00574 RPN total loss: 0.02166 Total loss: 0.89039 timestamp: 1654982596.2861378 iteration: 88855 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1332 FastRCNN class loss: 0.07022 FastRCNN total loss: 0.20341 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12554 RPN box loss: 0.02523 RPN score loss: 0.00522 RPN total loss: 0.03045 Total loss: 0.9467 timestamp: 1654982599.572129 iteration: 88860 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07087 FastRCNN class loss: 0.04966 FastRCNN total loss: 0.12053 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.14334 RPN box loss: 0.01167 RPN score loss: 0.00166 RPN total loss: 0.01334 Total loss: 0.86451 timestamp: 1654982602.8170712 iteration: 88865 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08003 FastRCNN class loss: 0.04238 FastRCNN total loss: 0.12241 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15091 RPN box loss: 0.01337 RPN score loss: 0.00609 RPN total loss: 0.01946 Total loss: 0.88008 timestamp: 1654982606.0214784 iteration: 88870 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11275 FastRCNN class loss: 0.11875 FastRCNN total loss: 0.23151 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15685 RPN box loss: 0.01862 RPN score loss: 0.00642 RPN total loss: 0.02504 Total loss: 1.00069 timestamp: 1654982609.2943254 iteration: 88875 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07885 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.12693 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.09779 RPN box loss: 0.00907 RPN score loss: 0.00181 RPN total loss: 0.01087 Total loss: 0.82289 timestamp: 1654982612.4567492 iteration: 88880 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09106 FastRCNN class loss: 0.11162 FastRCNN total loss: 0.20268 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.15291 RPN box loss: 0.01804 RPN score loss: 0.00788 RPN total loss: 0.02592 Total loss: 0.9688 timestamp: 1654982615.672986 iteration: 88885 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10993 FastRCNN class loss: 0.04855 FastRCNN total loss: 0.15848 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.11525 RPN box loss: 0.00442 RPN score loss: 0.00502 RPN total loss: 0.00944 Total loss: 0.87046 timestamp: 1654982618.8805015 iteration: 88890 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0881 FastRCNN class loss: 0.05723 FastRCNN total loss: 0.14533 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12992 RPN box loss: 0.01048 RPN score loss: 0.00139 RPN total loss: 0.01187 Total loss: 0.87442 timestamp: 1654982622.0767071 iteration: 88895 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08145 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.13182 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.1222 RPN box loss: 0.01218 RPN score loss: 0.00333 RPN total loss: 0.01551 Total loss: 0.85683 timestamp: 1654982625.3016992 iteration: 88900 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08327 FastRCNN class loss: 0.06797 FastRCNN total loss: 0.15124 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.1079 RPN box loss: 0.00405 RPN score loss: 0.0031 RPN total loss: 0.00716 Total loss: 0.85359 timestamp: 1654982628.4768515 iteration: 88905 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.08957 FastRCNN total loss: 0.17908 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 4.0000e-05 Mask loss: 0.12156 RPN box loss: 0.01211 RPN score loss: 0.00493 RPN total loss: 0.01704 Total loss: 0.90497 timestamp: 1654982631.7065864 iteration: 88910 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.11136 FastRCNN total loss: 0.21425 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.15993 RPN box loss: 0.02724 RPN score loss: 0.01719 RPN total loss: 0.04443 Total loss: 1.00591 timestamp: 1654982634.86908 iteration: 88915 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12318 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.18231 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13652 RPN box loss: 0.00937 RPN score loss: 0.00835 RPN total loss: 0.01772 Total loss: 0.92384 timestamp: 1654982638.0804932 iteration: 88920 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.09153 FastRCNN total loss: 0.16962 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.1205 RPN box loss: 0.01514 RPN score loss: 0.00287 RPN total loss: 0.01801 Total loss: 0.89543 timestamp: 1654982641.2766001 iteration: 88925 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03973 FastRCNN class loss: 0.04249 FastRCNN total loss: 0.08222 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.09656 RPN box loss: 0.00161 RPN score loss: 0.00151 RPN total loss: 0.00312 Total loss: 0.7692 timestamp: 1654982644.482222 iteration: 88930 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06327 FastRCNN class loss: 0.07003 FastRCNN total loss: 0.13329 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.09333 RPN box loss: 0.00556 RPN score loss: 0.00651 RPN total loss: 0.01207 Total loss: 0.82599 timestamp: 1654982647.6819916 iteration: 88935 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11352 FastRCNN class loss: 0.09549 FastRCNN total loss: 0.20901 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.19384 RPN box loss: 0.01248 RPN score loss: 0.01052 RPN total loss: 0.023 Total loss: 1.01314 timestamp: 1654982650.8960922 iteration: 88940 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05826 FastRCNN class loss: 0.07443 FastRCNN total loss: 0.13269 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12311 RPN box loss: 0.01432 RPN score loss: 0.00255 RPN total loss: 0.01687 Total loss: 0.85996 timestamp: 1654982654.1075966 iteration: 88945 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09084 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.16728 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.22394 RPN box loss: 0.0111 RPN score loss: 0.0044 RPN total loss: 0.0155 Total loss: 0.99401 timestamp: 1654982657.3282094 iteration: 88950 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05211 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.11601 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11904 RPN box loss: 0.0099 RPN score loss: 0.00745 RPN total loss: 0.01735 Total loss: 0.8397 timestamp: 1654982660.558306 iteration: 88955 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04946 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.10885 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12089 RPN box loss: 0.00554 RPN score loss: 0.00249 RPN total loss: 0.00803 Total loss: 0.82506 timestamp: 1654982663.766263 iteration: 88960 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11514 FastRCNN class loss: 0.09297 FastRCNN total loss: 0.20812 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.125 RPN box loss: 0.01088 RPN score loss: 0.00345 RPN total loss: 0.01434 Total loss: 0.93475 timestamp: 1654982666.9685402 iteration: 88965 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12517 FastRCNN class loss: 0.05237 FastRCNN total loss: 0.17754 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12669 RPN box loss: 0.01662 RPN score loss: 0.0056 RPN total loss: 0.02221 Total loss: 0.91374 timestamp: 1654982670.1929595 iteration: 88970 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08254 FastRCNN class loss: 0.04525 FastRCNN total loss: 0.12779 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12106 RPN box loss: 0.01075 RPN score loss: 0.00073 RPN total loss: 0.01149 Total loss: 0.84763 timestamp: 1654982673.3820872 iteration: 88975 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08122 FastRCNN class loss: 0.09427 FastRCNN total loss: 0.17549 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12269 RPN box loss: 0.01149 RPN score loss: 0.00132 RPN total loss: 0.01281 Total loss: 0.89829 timestamp: 1654982676.5505955 iteration: 88980 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07363 FastRCNN class loss: 0.04548 FastRCNN total loss: 0.11912 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.08755 RPN box loss: 0.00887 RPN score loss: 0.00077 RPN total loss: 0.00964 Total loss: 0.8036 timestamp: 1654982679.6901178 iteration: 88985 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07105 FastRCNN class loss: 0.04885 FastRCNN total loss: 0.1199 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.08293 RPN box loss: 0.01321 RPN score loss: 0.00173 RPN total loss: 0.01494 Total loss: 0.80507 timestamp: 1654982682.858795 iteration: 88990 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09093 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.15529 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.1268 RPN box loss: 0.0098 RPN score loss: 0.00475 RPN total loss: 0.01454 Total loss: 0.88392 timestamp: 1654982686.0117502 iteration: 88995 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05682 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.12858 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.09986 RPN box loss: 0.00627 RPN score loss: 0.01207 RPN total loss: 0.01834 Total loss: 0.83408 timestamp: 1654982689.1495 iteration: 89000 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09722 FastRCNN class loss: 0.03579 FastRCNN total loss: 0.13301 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.09648 RPN box loss: 0.00363 RPN score loss: 0.00384 RPN total loss: 0.00747 Total loss: 0.82425 timestamp: 1654982692.4045246 iteration: 89005 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10872 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.17711 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.16052 RPN box loss: 0.00883 RPN score loss: 0.00244 RPN total loss: 0.01126 Total loss: 0.93618 timestamp: 1654982695.6403372 iteration: 89010 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12371 FastRCNN class loss: 0.08373 FastRCNN total loss: 0.20744 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.10274 RPN box loss: 0.01211 RPN score loss: 0.0039 RPN total loss: 0.016 Total loss: 0.91348 timestamp: 1654982698.8267853 iteration: 89015 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0681 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.13217 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13054 RPN box loss: 0.00872 RPN score loss: 0.00542 RPN total loss: 0.01414 Total loss: 0.86414 timestamp: 1654982702.082411 iteration: 89020 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08349 FastRCNN class loss: 0.04548 FastRCNN total loss: 0.12896 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13511 RPN box loss: 0.01329 RPN score loss: 0.00227 RPN total loss: 0.01557 Total loss: 0.86693 timestamp: 1654982705.3042297 iteration: 89025 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08342 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.16895 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12183 RPN box loss: 0.00917 RPN score loss: 0.00968 RPN total loss: 0.01885 Total loss: 0.89692 timestamp: 1654982708.5027637 iteration: 89030 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05136 FastRCNN class loss: 0.03869 FastRCNN total loss: 0.09005 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11271 RPN box loss: 0.00613 RPN score loss: 0.00265 RPN total loss: 0.00878 Total loss: 0.79883 timestamp: 1654982711.6287365 iteration: 89035 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14306 FastRCNN class loss: 0.13833 FastRCNN total loss: 0.28138 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.22616 RPN box loss: 0.01712 RPN score loss: 0.00517 RPN total loss: 0.02229 Total loss: 1.11712 timestamp: 1654982714.8578634 iteration: 89040 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12702 FastRCNN class loss: 0.13901 FastRCNN total loss: 0.26604 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.15745 RPN box loss: 0.00979 RPN score loss: 0.00263 RPN total loss: 0.01242 Total loss: 1.0232 timestamp: 1654982718.0235522 iteration: 89045 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14758 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.22038 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.16886 RPN box loss: 0.0172 RPN score loss: 0.00385 RPN total loss: 0.02105 Total loss: 0.99758 timestamp: 1654982721.1694777 iteration: 89050 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08968 FastRCNN class loss: 0.0857 FastRCNN total loss: 0.17538 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.18214 RPN box loss: 0.02604 RPN score loss: 0.00353 RPN total loss: 0.02957 Total loss: 0.97438 timestamp: 1654982724.3685513 iteration: 89055 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05596 FastRCNN class loss: 0.08876 FastRCNN total loss: 0.14472 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13079 RPN box loss: 0.00684 RPN score loss: 0.00353 RPN total loss: 0.01037 Total loss: 0.87317 timestamp: 1654982727.5098448 iteration: 89060 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10031 FastRCNN class loss: 0.118 FastRCNN total loss: 0.21831 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.1173 RPN box loss: 0.01037 RPN score loss: 0.00257 RPN total loss: 0.01293 Total loss: 0.93583 timestamp: 1654982730.7077785 iteration: 89065 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09152 FastRCNN class loss: 0.0644 FastRCNN total loss: 0.15592 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11133 RPN box loss: 0.0186 RPN score loss: 0.00163 RPN total loss: 0.02023 Total loss: 0.87477 timestamp: 1654982733.8861854 iteration: 89070 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06531 FastRCNN class loss: 0.04884 FastRCNN total loss: 0.11415 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11348 RPN box loss: 0.01327 RPN score loss: 0.00153 RPN total loss: 0.0148 Total loss: 0.82971 timestamp: 1654982737.0677137 iteration: 89075 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09282 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.1575 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13922 RPN box loss: 0.00878 RPN score loss: 0.00319 RPN total loss: 0.01197 Total loss: 0.89598 timestamp: 1654982740.237296 iteration: 89080 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06103 FastRCNN class loss: 0.04916 FastRCNN total loss: 0.11019 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11271 RPN box loss: 0.00607 RPN score loss: 0.00451 RPN total loss: 0.01058 Total loss: 0.82078 timestamp: 1654982743.4229934 iteration: 89085 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12037 FastRCNN class loss: 0.03442 FastRCNN total loss: 0.15478 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.1195 RPN box loss: 0.01448 RPN score loss: 0.00638 RPN total loss: 0.02086 Total loss: 0.88244 timestamp: 1654982746.6222858 iteration: 89090 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05994 FastRCNN class loss: 0.0389 FastRCNN total loss: 0.09884 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11928 RPN box loss: 0.00729 RPN score loss: 0.00217 RPN total loss: 0.00946 Total loss: 0.81488 timestamp: 1654982749.8701465 iteration: 89095 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09407 FastRCNN class loss: 0.06586 FastRCNN total loss: 0.15993 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.08337 RPN box loss: 0.00625 RPN score loss: 0.0009 RPN total loss: 0.00715 Total loss: 0.83774 timestamp: 1654982753.1033418 iteration: 89100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04927 FastRCNN class loss: 0.05852 FastRCNN total loss: 0.10779 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.09414 RPN box loss: 0.0041 RPN score loss: 0.00097 RPN total loss: 0.00507 Total loss: 0.79429 timestamp: 1654982756.278472 iteration: 89105 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12092 FastRCNN class loss: 0.06859 FastRCNN total loss: 0.18951 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.15115 RPN box loss: 0.04493 RPN score loss: 0.00542 RPN total loss: 0.05035 Total loss: 0.97831 timestamp: 1654982759.468755 iteration: 89110 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06796 FastRCNN class loss: 0.10139 FastRCNN total loss: 0.16935 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13422 RPN box loss: 0.02308 RPN score loss: 0.00609 RPN total loss: 0.02917 Total loss: 0.92002 timestamp: 1654982762.5944896 iteration: 89115 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07412 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.14367 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12188 RPN box loss: 0.01255 RPN score loss: 0.00674 RPN total loss: 0.01929 Total loss: 0.87213 timestamp: 1654982765.8131 iteration: 89120 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07018 FastRCNN class loss: 0.04727 FastRCNN total loss: 0.11745 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.10692 RPN box loss: 0.00513 RPN score loss: 0.00117 RPN total loss: 0.0063 Total loss: 0.81796 timestamp: 1654982769.0289552 iteration: 89125 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.03139 FastRCNN total loss: 0.10948 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.10139 RPN box loss: 0.00919 RPN score loss: 0.00182 RPN total loss: 0.01101 Total loss: 0.80916 timestamp: 1654982772.2109122 iteration: 89130 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07335 FastRCNN class loss: 0.07314 FastRCNN total loss: 0.14649 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.17527 RPN box loss: 0.00687 RPN score loss: 0.00849 RPN total loss: 0.01536 Total loss: 0.92441 timestamp: 1654982775.4441805 iteration: 89135 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07275 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.13347 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13532 RPN box loss: 0.01526 RPN score loss: 0.00579 RPN total loss: 0.02106 Total loss: 0.87713 timestamp: 1654982778.6332154 iteration: 89140 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11015 FastRCNN class loss: 0.07484 FastRCNN total loss: 0.18499 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11808 RPN box loss: 0.00995 RPN score loss: 0.00455 RPN total loss: 0.0145 Total loss: 0.90485 timestamp: 1654982781.8427496 iteration: 89145 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.05558 FastRCNN total loss: 0.14827 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.16807 RPN box loss: 0.04017 RPN score loss: 0.0016 RPN total loss: 0.04177 Total loss: 0.94539 timestamp: 1654982785.007533 iteration: 89150 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08144 FastRCNN class loss: 0.04948 FastRCNN total loss: 0.13091 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.18634 RPN box loss: 0.00602 RPN score loss: 0.00256 RPN total loss: 0.00858 Total loss: 0.91312 timestamp: 1654982788.1832724 iteration: 89155 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10535 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.16418 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12251 RPN box loss: 0.00564 RPN score loss: 0.00215 RPN total loss: 0.00779 Total loss: 0.88177 timestamp: 1654982791.4278731 iteration: 89160 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07182 FastRCNN class loss: 0.06288 FastRCNN total loss: 0.1347 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.13713 RPN box loss: 0.00444 RPN score loss: 0.00116 RPN total loss: 0.0056 Total loss: 0.86472 timestamp: 1654982794.6453407 iteration: 89165 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09015 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.14093 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11984 RPN box loss: 0.00885 RPN score loss: 0.01722 RPN total loss: 0.02607 Total loss: 0.87413 timestamp: 1654982797.8550763 iteration: 89170 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06788 FastRCNN class loss: 0.04056 FastRCNN total loss: 0.10845 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.06542 RPN box loss: 0.00326 RPN score loss: 0.00227 RPN total loss: 0.00552 Total loss: 0.76668 timestamp: 1654982801.0623124 iteration: 89175 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07006 FastRCNN class loss: 0.05041 FastRCNN total loss: 0.12047 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.0776 RPN box loss: 0.01116 RPN score loss: 0.00997 RPN total loss: 0.02113 Total loss: 0.80649 timestamp: 1654982804.2821176 iteration: 89180 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08554 FastRCNN class loss: 0.07209 FastRCNN total loss: 0.15763 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.08968 RPN box loss: 0.00561 RPN score loss: 0.00025 RPN total loss: 0.00585 Total loss: 0.84046 timestamp: 1654982807.5035899 iteration: 89185 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11115 FastRCNN class loss: 0.06657 FastRCNN total loss: 0.17772 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.17087 RPN box loss: 0.02721 RPN score loss: 0.00486 RPN total loss: 0.03207 Total loss: 0.96795 timestamp: 1654982810.775355 iteration: 89190 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06535 FastRCNN class loss: 0.06102 FastRCNN total loss: 0.12637 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12442 RPN box loss: 0.0074 RPN score loss: 0.00711 RPN total loss: 0.01451 Total loss: 0.85258 timestamp: 1654982813.9612496 iteration: 89195 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05968 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.10907 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11379 RPN box loss: 0.01371 RPN score loss: 0.00453 RPN total loss: 0.01824 Total loss: 0.82839 timestamp: 1654982817.2412639 iteration: 89200 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11017 FastRCNN class loss: 0.15251 FastRCNN total loss: 0.26268 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11689 RPN box loss: 0.01069 RPN score loss: 0.01343 RPN total loss: 0.02412 Total loss: 0.99098 timestamp: 1654982820.4167318 iteration: 89205 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08602 FastRCNN class loss: 0.05516 FastRCNN total loss: 0.14118 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12905 RPN box loss: 0.01033 RPN score loss: 0.00553 RPN total loss: 0.01587 Total loss: 0.87339 timestamp: 1654982823.5623784 iteration: 89210 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10071 FastRCNN class loss: 0.04709 FastRCNN total loss: 0.1478 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.07972 RPN box loss: 0.0086 RPN score loss: 0.00539 RPN total loss: 0.01398 Total loss: 0.82879 timestamp: 1654982826.7543323 iteration: 89215 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.06404 FastRCNN total loss: 0.14432 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.09245 RPN box loss: 0.00672 RPN score loss: 0.00153 RPN total loss: 0.00825 Total loss: 0.83231 timestamp: 1654982829.9685907 iteration: 89220 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09898 FastRCNN class loss: 0.04206 FastRCNN total loss: 0.14104 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.11443 RPN box loss: 0.01027 RPN score loss: 0.00125 RPN total loss: 0.01152 Total loss: 0.85427 timestamp: 1654982833.1506362 iteration: 89225 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06468 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.12527 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.12473 RPN box loss: 0.00598 RPN score loss: 0.00179 RPN total loss: 0.00777 Total loss: 0.84505 timestamp: 1654982836.4061666 iteration: 89230 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08458 FastRCNN class loss: 0.07143 FastRCNN total loss: 0.15602 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.10779 RPN box loss: 0.00744 RPN score loss: 0.00406 RPN total loss: 0.0115 Total loss: 0.86259 timestamp: 1654982839.5244021 iteration: 89235 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07212 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.1206 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.10686 RPN box loss: 0.00284 RPN score loss: 0.00341 RPN total loss: 0.00624 Total loss: 0.82099 timestamp: 1654982842.708138 iteration: 89240 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07641 FastRCNN class loss: 0.11073 FastRCNN total loss: 0.18714 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 4.0000e-05 Mask loss: 0.18864 RPN box loss: 0.01206 RPN score loss: 0.02577 RPN total loss: 0.03783 Total loss: 1.00089 timestamp: 1654982845.8260121 iteration: 89245 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09855 FastRCNN class loss: 0.08249 FastRCNN total loss: 0.18104 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15131 RPN box loss: 0.00835 RPN score loss: 0.00504 RPN total loss: 0.01339 Total loss: 0.93303 timestamp: 1654982849.0230532 iteration: 89250 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0942 FastRCNN class loss: 0.08322 FastRCNN total loss: 0.17742 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13772 RPN box loss: 0.01046 RPN score loss: 0.00599 RPN total loss: 0.01645 Total loss: 0.91887 timestamp: 1654982852.2399883 iteration: 89255 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05268 FastRCNN class loss: 0.04115 FastRCNN total loss: 0.09383 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13597 RPN box loss: 0.0139 RPN score loss: 0.00623 RPN total loss: 0.02013 Total loss: 0.83721 timestamp: 1654982855.4160929 iteration: 89260 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11821 FastRCNN class loss: 0.09207 FastRCNN total loss: 0.21028 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.16306 RPN box loss: 0.00574 RPN score loss: 0.00624 RPN total loss: 0.01198 Total loss: 0.9726 timestamp: 1654982858.6043591 iteration: 89265 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08569 FastRCNN class loss: 0.06465 FastRCNN total loss: 0.15034 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15784 RPN box loss: 0.0173 RPN score loss: 0.01183 RPN total loss: 0.02913 Total loss: 0.9246 timestamp: 1654982861.8782425 iteration: 89270 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07368 FastRCNN class loss: 0.07863 FastRCNN total loss: 0.1523 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12022 RPN box loss: 0.01559 RPN score loss: 0.00392 RPN total loss: 0.01951 Total loss: 0.87932 timestamp: 1654982865.0968614 iteration: 89275 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06744 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.12728 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.08617 RPN box loss: 0.00917 RPN score loss: 0.00076 RPN total loss: 0.00992 Total loss: 0.81065 timestamp: 1654982868.281573 iteration: 89280 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06597 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.11341 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.10516 RPN box loss: 0.00742 RPN score loss: 0.00325 RPN total loss: 0.01067 Total loss: 0.81653 timestamp: 1654982871.4620798 iteration: 89285 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14102 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.21631 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.1223 RPN box loss: 0.01307 RPN score loss: 0.00445 RPN total loss: 0.01752 Total loss: 0.94342 timestamp: 1654982874.622971 iteration: 89290 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10073 FastRCNN class loss: 0.06674 FastRCNN total loss: 0.16748 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.09651 RPN box loss: 0.0043 RPN score loss: 0.00197 RPN total loss: 0.00627 Total loss: 0.85754 timestamp: 1654982877.8361018 iteration: 89295 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06184 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.12138 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.09902 RPN box loss: 0.01088 RPN score loss: 0.00496 RPN total loss: 0.01584 Total loss: 0.82353 timestamp: 1654982881.0409338 iteration: 89300 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06056 FastRCNN class loss: 0.10489 FastRCNN total loss: 0.16545 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11319 RPN box loss: 0.01097 RPN score loss: 0.00462 RPN total loss: 0.01559 Total loss: 0.88152 timestamp: 1654982884.2832835 iteration: 89305 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08212 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.15256 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11636 RPN box loss: 0.00397 RPN score loss: 0.00441 RPN total loss: 0.00839 Total loss: 0.86459 timestamp: 1654982887.463252 iteration: 89310 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.04778 FastRCNN total loss: 0.13309 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11165 RPN box loss: 0.00981 RPN score loss: 0.00349 RPN total loss: 0.0133 Total loss: 0.84532 timestamp: 1654982890.6862416 iteration: 89315 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10169 FastRCNN class loss: 0.09223 FastRCNN total loss: 0.19392 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.14662 RPN box loss: 0.01007 RPN score loss: 0.00516 RPN total loss: 0.01523 Total loss: 0.94305 timestamp: 1654982893.9109588 iteration: 89320 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10907 FastRCNN class loss: 0.04084 FastRCNN total loss: 0.14992 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.1299 RPN box loss: 0.0033 RPN score loss: 0.00155 RPN total loss: 0.00485 Total loss: 0.87195 timestamp: 1654982897.0954747 iteration: 89325 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07711 FastRCNN class loss: 0.07072 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.18074 RPN box loss: 0.00496 RPN score loss: 0.00396 RPN total loss: 0.00892 Total loss: 0.92478 timestamp: 1654982900.346703 iteration: 89330 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08573 FastRCNN class loss: 0.06231 FastRCNN total loss: 0.14805 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12671 RPN box loss: 0.01347 RPN score loss: 0.00734 RPN total loss: 0.02081 Total loss: 0.88284 timestamp: 1654982903.5375464 iteration: 89335 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.18623 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.07604 RPN box loss: 0.00646 RPN score loss: 0.00126 RPN total loss: 0.00772 Total loss: 0.85728 timestamp: 1654982906.745632 iteration: 89340 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0691 FastRCNN class loss: 0.03508 FastRCNN total loss: 0.10418 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15182 RPN box loss: 0.01211 RPN score loss: 0.00572 RPN total loss: 0.01783 Total loss: 0.86111 timestamp: 1654982909.9672654 iteration: 89345 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08712 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.15794 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.14761 RPN box loss: 0.01087 RPN score loss: 0.00485 RPN total loss: 0.01571 Total loss: 0.90854 timestamp: 1654982913.1774611 iteration: 89350 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13139 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.19081 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11862 RPN box loss: 0.01687 RPN score loss: 0.00176 RPN total loss: 0.01863 Total loss: 0.91535 timestamp: 1654982916.3567944 iteration: 89355 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08748 FastRCNN class loss: 0.09507 FastRCNN total loss: 0.18255 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.1479 RPN box loss: 0.01439 RPN score loss: 0.00662 RPN total loss: 0.02101 Total loss: 0.93873 timestamp: 1654982919.5621135 iteration: 89360 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11939 FastRCNN class loss: 0.05634 FastRCNN total loss: 0.17573 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.07751 RPN box loss: 0.00528 RPN score loss: 0.00536 RPN total loss: 0.01064 Total loss: 0.85116 timestamp: 1654982922.7176175 iteration: 89365 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07905 FastRCNN class loss: 0.06038 FastRCNN total loss: 0.13943 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12897 RPN box loss: 0.00471 RPN score loss: 0.00163 RPN total loss: 0.00634 Total loss: 0.86202 timestamp: 1654982925.9145443 iteration: 89370 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.05392 FastRCNN total loss: 0.1348 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15202 RPN box loss: 0.01122 RPN score loss: 0.00816 RPN total loss: 0.01938 Total loss: 0.89349 timestamp: 1654982929.0466866 iteration: 89375 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07781 FastRCNN class loss: 0.08748 FastRCNN total loss: 0.1653 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13548 RPN box loss: 0.02156 RPN score loss: 0.00426 RPN total loss: 0.02582 Total loss: 0.91388 timestamp: 1654982932.3180866 iteration: 89380 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10207 FastRCNN class loss: 0.07539 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12624 RPN box loss: 0.01105 RPN score loss: 0.01209 RPN total loss: 0.02314 Total loss: 0.91412 timestamp: 1654982935.5160363 iteration: 89385 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06417 FastRCNN class loss: 0.09806 FastRCNN total loss: 0.16223 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11916 RPN box loss: 0.00769 RPN score loss: 0.00271 RPN total loss: 0.0104 Total loss: 0.87908 timestamp: 1654982938.6786268 iteration: 89390 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06263 FastRCNN class loss: 0.05559 FastRCNN total loss: 0.11821 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11133 RPN box loss: 0.01011 RPN score loss: 0.00117 RPN total loss: 0.01128 Total loss: 0.8281 timestamp: 1654982941.9205136 iteration: 89395 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09359 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.17549 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.1357 RPN box loss: 0.01212 RPN score loss: 0.01491 RPN total loss: 0.02702 Total loss: 0.9255 timestamp: 1654982945.1028605 iteration: 89400 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05344 FastRCNN class loss: 0.045 FastRCNN total loss: 0.09843 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.18078 RPN box loss: 0.01766 RPN score loss: 0.00165 RPN total loss: 0.01932 Total loss: 0.88581 timestamp: 1654982948.3299577 iteration: 89405 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0616 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.12633 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13236 RPN box loss: 0.02213 RPN score loss: 0.00466 RPN total loss: 0.02679 Total loss: 0.87276 timestamp: 1654982951.597475 iteration: 89410 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0736 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.13621 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.10125 RPN box loss: 0.00926 RPN score loss: 0.00076 RPN total loss: 0.01002 Total loss: 0.83476 timestamp: 1654982954.839809 iteration: 89415 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05502 FastRCNN class loss: 0.04694 FastRCNN total loss: 0.10196 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15351 RPN box loss: 0.00792 RPN score loss: 0.00782 RPN total loss: 0.01574 Total loss: 0.85849 timestamp: 1654982958.02796 iteration: 89420 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0491 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.0969 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13289 RPN box loss: 0.00787 RPN score loss: 0.00985 RPN total loss: 0.01771 Total loss: 0.83478 timestamp: 1654982961.220698 iteration: 89425 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05711 FastRCNN class loss: 0.05341 FastRCNN total loss: 0.11052 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13767 RPN box loss: 0.01487 RPN score loss: 0.01534 RPN total loss: 0.03021 Total loss: 0.86568 timestamp: 1654982964.46414 iteration: 89430 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11672 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.19708 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12277 RPN box loss: 0.02098 RPN score loss: 0.0077 RPN total loss: 0.02868 Total loss: 0.93581 timestamp: 1654982967.7576337 iteration: 89435 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10404 FastRCNN class loss: 0.07969 FastRCNN total loss: 0.18373 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15526 RPN box loss: 0.01103 RPN score loss: 0.00415 RPN total loss: 0.01518 Total loss: 0.94145 timestamp: 1654982970.987221 iteration: 89440 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06931 FastRCNN class loss: 0.05166 FastRCNN total loss: 0.12098 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12261 RPN box loss: 0.01176 RPN score loss: 0.00318 RPN total loss: 0.01494 Total loss: 0.8458 timestamp: 1654982974.2527056 iteration: 89445 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09615 FastRCNN class loss: 0.04686 FastRCNN total loss: 0.143 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.14921 RPN box loss: 0.02352 RPN score loss: 0.00763 RPN total loss: 0.03114 Total loss: 0.91063 timestamp: 1654982977.45872 iteration: 89450 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06497 FastRCNN class loss: 0.04308 FastRCNN total loss: 0.10805 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.08755 RPN box loss: 0.00317 RPN score loss: 0.00122 RPN total loss: 0.00439 Total loss: 0.78727 timestamp: 1654982980.7855604 iteration: 89455 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08956 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.16669 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.16192 RPN box loss: 0.00976 RPN score loss: 0.01057 RPN total loss: 0.02033 Total loss: 0.93622 timestamp: 1654982983.9044585 iteration: 89460 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1003 FastRCNN class loss: 0.07146 FastRCNN total loss: 0.17176 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11323 RPN box loss: 0.01562 RPN score loss: 0.00357 RPN total loss: 0.01919 Total loss: 0.89146 timestamp: 1654982987.0949156 iteration: 89465 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07422 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.13333 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11848 RPN box loss: 0.01018 RPN score loss: 0.0117 RPN total loss: 0.02188 Total loss: 0.86097 timestamp: 1654982990.370727 iteration: 89470 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06691 FastRCNN class loss: 0.05771 FastRCNN total loss: 0.12463 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.08473 RPN box loss: 0.00744 RPN score loss: 0.00159 RPN total loss: 0.00903 Total loss: 0.80567 timestamp: 1654982993.6105092 iteration: 89475 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12796 FastRCNN class loss: 0.10965 FastRCNN total loss: 0.23761 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.24036 RPN box loss: 0.03234 RPN score loss: 0.06757 RPN total loss: 0.09991 Total loss: 1.16515 timestamp: 1654982996.861292 iteration: 89480 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04255 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.08971 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13676 RPN box loss: 0.00456 RPN score loss: 0.00317 RPN total loss: 0.00773 Total loss: 0.82148 timestamp: 1654983000.1298308 iteration: 89485 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10448 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.1802 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.16882 RPN box loss: 0.00833 RPN score loss: 0.00185 RPN total loss: 0.01017 Total loss: 0.94647 timestamp: 1654983003.2793672 iteration: 89490 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09382 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.15191 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.14623 RPN box loss: 0.00498 RPN score loss: 0.0021 RPN total loss: 0.00707 Total loss: 0.89249 timestamp: 1654983006.430491 iteration: 89495 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12485 FastRCNN class loss: 0.07834 FastRCNN total loss: 0.20319 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.15032 RPN box loss: 0.0102 RPN score loss: 0.00508 RPN total loss: 0.01528 Total loss: 0.95607 timestamp: 1654983009.630454 iteration: 89500 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11197 FastRCNN class loss: 0.09704 FastRCNN total loss: 0.209 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13955 RPN box loss: 0.01324 RPN score loss: 0.00412 RPN total loss: 0.01736 Total loss: 0.95318 timestamp: 1654983012.836907 iteration: 89505 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08479 FastRCNN class loss: 0.05382 FastRCNN total loss: 0.13862 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.0904 RPN box loss: 0.00505 RPN score loss: 0.00643 RPN total loss: 0.01148 Total loss: 0.82777 timestamp: 1654983016.046726 iteration: 89510 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11753 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.16686 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.1074 RPN box loss: 0.02175 RPN score loss: 0.00144 RPN total loss: 0.02319 Total loss: 0.88472 timestamp: 1654983019.235975 iteration: 89515 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10896 FastRCNN class loss: 0.0808 FastRCNN total loss: 0.18976 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13733 RPN box loss: 0.01013 RPN score loss: 0.00212 RPN total loss: 0.01225 Total loss: 0.92662 timestamp: 1654983022.4367802 iteration: 89520 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07253 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.13568 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13788 RPN box loss: 0.0133 RPN score loss: 0.00114 RPN total loss: 0.01444 Total loss: 0.87528 timestamp: 1654983025.6642997 iteration: 89525 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08192 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.13327 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12841 RPN box loss: 0.00733 RPN score loss: 0.00618 RPN total loss: 0.01351 Total loss: 0.86247 timestamp: 1654983028.8153467 iteration: 89530 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10889 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.16341 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12256 RPN box loss: 0.01619 RPN score loss: 0.00353 RPN total loss: 0.01972 Total loss: 0.89297 timestamp: 1654983032.0422072 iteration: 89535 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07408 FastRCNN class loss: 0.08424 FastRCNN total loss: 0.15833 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13691 RPN box loss: 0.01112 RPN score loss: 0.00492 RPN total loss: 0.01605 Total loss: 0.89856 timestamp: 1654983035.2910886 iteration: 89540 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08258 FastRCNN class loss: 0.09588 FastRCNN total loss: 0.17846 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.12937 RPN box loss: 0.00992 RPN score loss: 0.0007 RPN total loss: 0.01062 Total loss: 0.90572 timestamp: 1654983038.4956613 iteration: 89545 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10815 FastRCNN class loss: 0.09561 FastRCNN total loss: 0.20376 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.14486 RPN box loss: 0.03072 RPN score loss: 0.00518 RPN total loss: 0.03591 Total loss: 0.9718 timestamp: 1654983041.7896504 iteration: 89550 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09748 FastRCNN class loss: 0.08079 FastRCNN total loss: 0.17827 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13461 RPN box loss: 0.00773 RPN score loss: 0.00822 RPN total loss: 0.01595 Total loss: 0.91611 timestamp: 1654983044.9897878 iteration: 89555 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10072 FastRCNN class loss: 0.05716 FastRCNN total loss: 0.15788 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.11087 RPN box loss: 0.00789 RPN score loss: 0.00386 RPN total loss: 0.01175 Total loss: 0.86777 timestamp: 1654983048.2212212 iteration: 89560 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08457 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.15358 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.10918 RPN box loss: 0.00828 RPN score loss: 0.00193 RPN total loss: 0.01021 Total loss: 0.86024 timestamp: 1654983051.3908818 iteration: 89565 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07244 FastRCNN class loss: 0.04898 FastRCNN total loss: 0.12142 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.09412 RPN box loss: 0.00945 RPN score loss: 0.00074 RPN total loss: 0.01019 Total loss: 0.81301 timestamp: 1654983054.5878398 iteration: 89570 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.08596 FastRCNN total loss: 0.17557 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 4.0000e-05 Mask loss: 0.13444 RPN box loss: 0.01588 RPN score loss: 0.0027 RPN total loss: 0.01858 Total loss: 0.91587 timestamp: 1654983057.7564743 iteration: 89575 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06986 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.14902 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.1174 RPN box loss: 0.02474 RPN score loss: 0.00446 RPN total loss: 0.02919 Total loss: 0.88289 timestamp: 1654983060.9312692 iteration: 89580 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12588 FastRCNN class loss: 0.07588 FastRCNN total loss: 0.20176 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11949 RPN box loss: 0.01471 RPN score loss: 0.00304 RPN total loss: 0.01775 Total loss: 0.92628 timestamp: 1654983064.1487558 iteration: 89585 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10968 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.17597 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13224 RPN box loss: 0.00949 RPN score loss: 0.00517 RPN total loss: 0.01466 Total loss: 0.91015 timestamp: 1654983067.351081 iteration: 89590 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10313 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.15778 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11582 RPN box loss: 0.00607 RPN score loss: 0.00148 RPN total loss: 0.00755 Total loss: 0.86843 timestamp: 1654983070.5722604 iteration: 89595 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14115 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.21715 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11046 RPN box loss: 0.00706 RPN score loss: 0.00192 RPN total loss: 0.00897 Total loss: 0.92386 timestamp: 1654983073.8191297 iteration: 89600 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05748 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.12459 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13771 RPN box loss: 0.00443 RPN score loss: 0.00394 RPN total loss: 0.00837 Total loss: 0.85794 timestamp: 1654983076.9615996 iteration: 89605 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07622 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.12728 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.1208 RPN box loss: 0.00582 RPN score loss: 0.00476 RPN total loss: 0.01058 Total loss: 0.84594 timestamp: 1654983080.2490163 iteration: 89610 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0887 FastRCNN class loss: 0.08425 FastRCNN total loss: 0.17294 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.15569 RPN box loss: 0.00815 RPN score loss: 0.00924 RPN total loss: 0.0174 Total loss: 0.9333 timestamp: 1654983083.4412024 iteration: 89615 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.04998 FastRCNN total loss: 0.1367 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.10068 RPN box loss: 0.01744 RPN score loss: 0.00353 RPN total loss: 0.02097 Total loss: 0.84563 timestamp: 1654983086.6880035 iteration: 89620 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04005 FastRCNN class loss: 0.01852 FastRCNN total loss: 0.05857 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.0772 RPN box loss: 0.01572 RPN score loss: 0.00109 RPN total loss: 0.01681 Total loss: 0.73985 timestamp: 1654983089.8854146 iteration: 89625 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0864 FastRCNN class loss: 0.04588 FastRCNN total loss: 0.13228 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12372 RPN box loss: 0.00391 RPN score loss: 0.00172 RPN total loss: 0.00563 Total loss: 0.84891 timestamp: 1654983092.966924 iteration: 89630 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13107 FastRCNN class loss: 0.09242 FastRCNN total loss: 0.22348 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.15264 RPN box loss: 0.01654 RPN score loss: 0.00629 RPN total loss: 0.02283 Total loss: 0.98622 timestamp: 1654983096.14974 iteration: 89635 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09119 FastRCNN class loss: 0.05258 FastRCNN total loss: 0.14376 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13832 RPN box loss: 0.00463 RPN score loss: 0.00519 RPN total loss: 0.00982 Total loss: 0.87917 timestamp: 1654983099.3464537 iteration: 89640 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09536 FastRCNN class loss: 0.04268 FastRCNN total loss: 0.13805 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13134 RPN box loss: 0.01582 RPN score loss: 0.00437 RPN total loss: 0.02019 Total loss: 0.87685 timestamp: 1654983102.592876 iteration: 89645 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12377 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.19466 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.10598 RPN box loss: 0.01646 RPN score loss: 0.00337 RPN total loss: 0.01983 Total loss: 0.90774 timestamp: 1654983105.832348 iteration: 89650 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06529 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.12405 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12519 RPN box loss: 0.01075 RPN score loss: 0.00639 RPN total loss: 0.01715 Total loss: 0.85365 timestamp: 1654983109.0514197 iteration: 89655 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07808 FastRCNN class loss: 0.05258 FastRCNN total loss: 0.13066 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11959 RPN box loss: 0.01398 RPN score loss: 0.00148 RPN total loss: 0.01546 Total loss: 0.85298 timestamp: 1654983112.319257 iteration: 89660 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07452 FastRCNN class loss: 0.11851 FastRCNN total loss: 0.19303 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13317 RPN box loss: 0.01699 RPN score loss: 0.00347 RPN total loss: 0.02046 Total loss: 0.93393 timestamp: 1654983115.533289 iteration: 89665 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09595 FastRCNN class loss: 0.08752 FastRCNN total loss: 0.18347 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.15676 RPN box loss: 0.00814 RPN score loss: 0.0015 RPN total loss: 0.00964 Total loss: 0.93713 timestamp: 1654983118.6763797 iteration: 89670 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10186 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.15947 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.08948 RPN box loss: 0.01024 RPN score loss: 0.00344 RPN total loss: 0.01369 Total loss: 0.84991 timestamp: 1654983121.8218768 iteration: 89675 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07553 FastRCNN class loss: 0.05647 FastRCNN total loss: 0.132 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.16847 RPN box loss: 0.00599 RPN score loss: 0.00245 RPN total loss: 0.00844 Total loss: 0.89618 timestamp: 1654983125.098798 iteration: 89680 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11661 FastRCNN class loss: 0.03873 FastRCNN total loss: 0.15533 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12372 RPN box loss: 0.00265 RPN score loss: 0.00158 RPN total loss: 0.00423 Total loss: 0.87055 timestamp: 1654983128.3351452 iteration: 89685 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05171 FastRCNN class loss: 0.04019 FastRCNN total loss: 0.0919 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.14183 RPN box loss: 0.01915 RPN score loss: 0.00175 RPN total loss: 0.0209 Total loss: 0.8419 timestamp: 1654983131.545769 iteration: 89690 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04969 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.10619 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12443 RPN box loss: 0.00658 RPN score loss: 0.00332 RPN total loss: 0.0099 Total loss: 0.82778 timestamp: 1654983134.7968588 iteration: 89695 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.13706 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.09232 RPN box loss: 0.00481 RPN score loss: 0.00587 RPN total loss: 0.01068 Total loss: 0.82733 timestamp: 1654983137.9951816 iteration: 89700 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11362 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.2 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.06562 RPN box loss: 0.00473 RPN score loss: 0.00109 RPN total loss: 0.00582 Total loss: 0.85871 timestamp: 1654983141.2164295 iteration: 89705 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06119 FastRCNN class loss: 0.07028 FastRCNN total loss: 0.13147 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.10491 RPN box loss: 0.00406 RPN score loss: 0.002 RPN total loss: 0.00606 Total loss: 0.82972 timestamp: 1654983144.4618127 iteration: 89710 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10626 FastRCNN class loss: 0.06179 FastRCNN total loss: 0.16805 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.09406 RPN box loss: 0.00802 RPN score loss: 0.00252 RPN total loss: 0.01055 Total loss: 0.85993 timestamp: 1654983147.6544204 iteration: 89715 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.08961 FastRCNN total loss: 0.17632 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.16185 RPN box loss: 0.0101 RPN score loss: 0.00901 RPN total loss: 0.01912 Total loss: 0.94455 timestamp: 1654983150.8714135 iteration: 89720 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09601 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.16728 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13961 RPN box loss: 0.00843 RPN score loss: 0.00414 RPN total loss: 0.01257 Total loss: 0.90673 timestamp: 1654983154.1233296 iteration: 89725 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11083 FastRCNN class loss: 0.06038 FastRCNN total loss: 0.17122 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.14194 RPN box loss: 0.01897 RPN score loss: 0.00333 RPN total loss: 0.0223 Total loss: 0.92273 timestamp: 1654983157.2984273 iteration: 89730 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06001 FastRCNN class loss: 0.03801 FastRCNN total loss: 0.09802 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.08918 RPN box loss: 0.00288 RPN score loss: 0.00237 RPN total loss: 0.00524 Total loss: 0.7797 timestamp: 1654983160.4927537 iteration: 89735 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04815 FastRCNN class loss: 0.0341 FastRCNN total loss: 0.08225 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11078 RPN box loss: 0.00562 RPN score loss: 0.00053 RPN total loss: 0.00614 Total loss: 0.78644 timestamp: 1654983163.7544403 iteration: 89740 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04647 FastRCNN class loss: 0.08026 FastRCNN total loss: 0.12673 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13906 RPN box loss: 0.04132 RPN score loss: 0.01779 RPN total loss: 0.05911 Total loss: 0.91216 timestamp: 1654983167.046884 iteration: 89745 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.058 FastRCNN class loss: 0.04847 FastRCNN total loss: 0.10647 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.16241 RPN box loss: 0.01484 RPN score loss: 0.00306 RPN total loss: 0.01789 Total loss: 0.87404 timestamp: 1654983170.2383978 iteration: 89750 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07551 FastRCNN class loss: 0.07695 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.1612 RPN box loss: 0.01841 RPN score loss: 0.00757 RPN total loss: 0.02599 Total loss: 0.92691 timestamp: 1654983173.4082959 iteration: 89755 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0499 FastRCNN class loss: 0.06117 FastRCNN total loss: 0.11107 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11513 RPN box loss: 0.02868 RPN score loss: 0.00437 RPN total loss: 0.03305 Total loss: 0.84652 timestamp: 1654983176.6956823 iteration: 89760 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04893 FastRCNN class loss: 0.05722 FastRCNN total loss: 0.10615 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.10647 RPN box loss: 0.00734 RPN score loss: 0.00655 RPN total loss: 0.01389 Total loss: 0.81378 timestamp: 1654983179.9218147 iteration: 89765 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07411 FastRCNN class loss: 0.08467 FastRCNN total loss: 0.15878 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.15097 RPN box loss: 0.00706 RPN score loss: 0.00511 RPN total loss: 0.01217 Total loss: 0.90919 timestamp: 1654983183.0745797 iteration: 89770 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13149 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.19267 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11709 RPN box loss: 0.00456 RPN score loss: 0.0029 RPN total loss: 0.00746 Total loss: 0.9045 timestamp: 1654983186.3035452 iteration: 89775 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09485 FastRCNN class loss: 0.07435 FastRCNN total loss: 0.1692 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.14481 RPN box loss: 0.03021 RPN score loss: 0.0022 RPN total loss: 0.03241 Total loss: 0.93369 timestamp: 1654983189.481035 iteration: 89780 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07203 FastRCNN class loss: 0.10144 FastRCNN total loss: 0.17347 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12387 RPN box loss: 0.01763 RPN score loss: 0.00328 RPN total loss: 0.02092 Total loss: 0.90553 timestamp: 1654983192.6086934 iteration: 89785 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06765 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.14063 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.15533 RPN box loss: 0.02838 RPN score loss: 0.00603 RPN total loss: 0.03441 Total loss: 0.91764 timestamp: 1654983195.8577392 iteration: 89790 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07988 FastRCNN class loss: 0.04877 FastRCNN total loss: 0.12865 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12061 RPN box loss: 0.00455 RPN score loss: 0.00203 RPN total loss: 0.00658 Total loss: 0.8431 timestamp: 1654983199.0208123 iteration: 89795 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12607 FastRCNN class loss: 0.15337 FastRCNN total loss: 0.27945 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.20122 RPN box loss: 0.03195 RPN score loss: 0.0102 RPN total loss: 0.04215 Total loss: 1.11009 timestamp: 1654983202.1639936 iteration: 89800 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07641 FastRCNN class loss: 0.05492 FastRCNN total loss: 0.13133 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.08883 RPN box loss: 0.0057 RPN score loss: 0.00318 RPN total loss: 0.00888 Total loss: 0.81631 timestamp: 1654983205.315022 iteration: 89805 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07431 FastRCNN class loss: 0.03703 FastRCNN total loss: 0.11134 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.09367 RPN box loss: 0.0025 RPN score loss: 0.00309 RPN total loss: 0.00559 Total loss: 0.79786 timestamp: 1654983208.567543 iteration: 89810 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04711 FastRCNN class loss: 0.04131 FastRCNN total loss: 0.08843 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.08913 RPN box loss: 0.00543 RPN score loss: 0.00778 RPN total loss: 0.01321 Total loss: 0.77804 timestamp: 1654983211.7504864 iteration: 89815 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.09271 FastRCNN total loss: 0.1751 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12704 RPN box loss: 0.01385 RPN score loss: 0.00589 RPN total loss: 0.01974 Total loss: 0.90914 timestamp: 1654983214.9395006 iteration: 89820 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07828 FastRCNN class loss: 0.05675 FastRCNN total loss: 0.13504 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.1462 RPN box loss: 0.01164 RPN score loss: 0.00647 RPN total loss: 0.01811 Total loss: 0.88661 timestamp: 1654983218.1576622 iteration: 89825 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12912 FastRCNN class loss: 0.09312 FastRCNN total loss: 0.22225 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.15011 RPN box loss: 0.00935 RPN score loss: 0.0016 RPN total loss: 0.01095 Total loss: 0.97057 timestamp: 1654983221.3253489 iteration: 89830 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.042 FastRCNN class loss: 0.03103 FastRCNN total loss: 0.07303 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.1264 RPN box loss: 0.00361 RPN score loss: 0.0012 RPN total loss: 0.00481 Total loss: 0.79151 timestamp: 1654983224.5611486 iteration: 89835 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14739 FastRCNN class loss: 0.08851 FastRCNN total loss: 0.2359 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.16533 RPN box loss: 0.01418 RPN score loss: 0.00208 RPN total loss: 0.01626 Total loss: 1.00475 timestamp: 1654983227.8340936 iteration: 89840 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06018 FastRCNN class loss: 0.0497 FastRCNN total loss: 0.10988 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12865 RPN box loss: 0.00402 RPN score loss: 0.00475 RPN total loss: 0.00877 Total loss: 0.83457 timestamp: 1654983231.038821 iteration: 89845 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06076 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.12261 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.10805 RPN box loss: 0.01193 RPN score loss: 0.01126 RPN total loss: 0.02319 Total loss: 0.84112 timestamp: 1654983234.2629306 iteration: 89850 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.05721 FastRCNN total loss: 0.14472 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13018 RPN box loss: 0.02034 RPN score loss: 0.00418 RPN total loss: 0.02453 Total loss: 0.8867 timestamp: 1654983237.5144458 iteration: 89855 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08946 FastRCNN class loss: 0.06925 FastRCNN total loss: 0.15872 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11664 RPN box loss: 0.00761 RPN score loss: 0.00622 RPN total loss: 0.01383 Total loss: 0.87645 timestamp: 1654983240.7356703 iteration: 89860 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06247 FastRCNN class loss: 0.04188 FastRCNN total loss: 0.10436 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.11587 RPN box loss: 0.00579 RPN score loss: 0.00209 RPN total loss: 0.00788 Total loss: 0.81537 timestamp: 1654983243.9689991 iteration: 89865 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06411 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.12245 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.14659 RPN box loss: 0.00513 RPN score loss: 0.00465 RPN total loss: 0.00978 Total loss: 0.86608 timestamp: 1654983247.1680098 iteration: 89870 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07593 FastRCNN class loss: 0.05357 FastRCNN total loss: 0.12951 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12871 RPN box loss: 0.01063 RPN score loss: 0.01091 RPN total loss: 0.02155 Total loss: 0.86703 timestamp: 1654983250.332314 iteration: 89875 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.078 FastRCNN class loss: 0.06178 FastRCNN total loss: 0.13979 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.14524 RPN box loss: 0.00993 RPN score loss: 0.00519 RPN total loss: 0.01512 Total loss: 0.88741 timestamp: 1654983253.531917 iteration: 89880 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09626 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.15773 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.14632 RPN box loss: 0.00367 RPN score loss: 0.01168 RPN total loss: 0.01535 Total loss: 0.90666 timestamp: 1654983256.7223127 iteration: 89885 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05756 FastRCNN class loss: 0.06396 FastRCNN total loss: 0.12152 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.12515 RPN box loss: 0.00649 RPN score loss: 0.00367 RPN total loss: 0.01016 Total loss: 0.84409 timestamp: 1654983259.9507198 iteration: 89890 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08201 FastRCNN class loss: 0.07793 FastRCNN total loss: 0.15995 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 4.0000e-05 Mask loss: 0.13244 RPN box loss: 0.01323 RPN score loss: 0.00723 RPN total loss: 0.02047 Total loss: 0.90011 timestamp: 1654983263.1976078 iteration: 89895 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08736 FastRCNN class loss: 0.04313 FastRCNN total loss: 0.1305 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.12716 RPN box loss: 0.01459 RPN score loss: 0.00059 RPN total loss: 0.01518 Total loss: 0.86011 timestamp: 1654983266.4918134 iteration: 89900 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07156 FastRCNN class loss: 0.07843 FastRCNN total loss: 0.14999 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.11262 RPN box loss: 0.00574 RPN score loss: 0.00332 RPN total loss: 0.00907 Total loss: 0.85894 timestamp: 1654983269.7449076 iteration: 89905 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12036 FastRCNN class loss: 0.10365 FastRCNN total loss: 0.22401 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.25312 RPN box loss: 0.01547 RPN score loss: 0.00748 RPN total loss: 0.02296 Total loss: 1.08736 timestamp: 1654983272.9056606 iteration: 89910 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.19246 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.16057 RPN box loss: 0.00733 RPN score loss: 0.00674 RPN total loss: 0.01407 Total loss: 0.95436 timestamp: 1654983276.0552547 iteration: 89915 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09853 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.15664 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.15205 RPN box loss: 0.02578 RPN score loss: 0.00825 RPN total loss: 0.03402 Total loss: 0.92999 timestamp: 1654983279.1677501 iteration: 89920 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.03716 FastRCNN total loss: 0.10293 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.0896 RPN box loss: 0.00855 RPN score loss: 0.00644 RPN total loss: 0.01499 Total loss: 0.79478 timestamp: 1654983282.392767 iteration: 89925 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12195 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.19736 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.21968 RPN box loss: 0.01278 RPN score loss: 0.00615 RPN total loss: 0.01893 Total loss: 1.02323 timestamp: 1654983285.638813 iteration: 89930 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11188 FastRCNN class loss: 0.08161 FastRCNN total loss: 0.19349 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.15816 RPN box loss: 0.01098 RPN score loss: 0.00533 RPN total loss: 0.0163 Total loss: 0.95521 timestamp: 1654983288.8164341 iteration: 89935 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10276 FastRCNN class loss: 0.06942 FastRCNN total loss: 0.17218 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.14589 RPN box loss: 0.01438 RPN score loss: 0.00362 RPN total loss: 0.018 Total loss: 0.92334 timestamp: 1654983291.974054 iteration: 89940 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08432 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.16325 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.17154 RPN box loss: 0.01166 RPN score loss: 0.00468 RPN total loss: 0.01634 Total loss: 0.93838 timestamp: 1654983295.2484145 iteration: 89945 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07276 FastRCNN class loss: 0.05519 FastRCNN total loss: 0.12795 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.11075 RPN box loss: 0.00762 RPN score loss: 0.00176 RPN total loss: 0.00937 Total loss: 0.83534 timestamp: 1654983298.4954495 iteration: 89950 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10944 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.17697 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.13655 RPN box loss: 0.01284 RPN score loss: 0.00247 RPN total loss: 0.01531 Total loss: 0.91609 timestamp: 1654983301.68394 iteration: 89955 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06572 FastRCNN class loss: 0.04841 FastRCNN total loss: 0.11413 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.15018 RPN box loss: 0.00287 RPN score loss: 0.0016 RPN total loss: 0.00447 Total loss: 0.85604 timestamp: 1654983304.8705006 iteration: 89960 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08962 FastRCNN class loss: 0.0466 FastRCNN total loss: 0.13622 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.11533 RPN box loss: 0.01183 RPN score loss: 0.00274 RPN total loss: 0.01457 Total loss: 0.85338 timestamp: 1654983308.0409677 iteration: 89965 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05721 FastRCNN class loss: 0.04001 FastRCNN total loss: 0.09723 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.09478 RPN box loss: 0.00357 RPN score loss: 0.00059 RPN total loss: 0.00416 Total loss: 0.78343 timestamp: 1654983311.1879442 iteration: 89970 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08268 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.1462 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.16586 RPN box loss: 0.01225 RPN score loss: 0.00353 RPN total loss: 0.01578 Total loss: 0.91511 timestamp: 1654983314.3831813 iteration: 89975 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0559 FastRCNN class loss: 0.04757 FastRCNN total loss: 0.10347 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.09612 RPN box loss: 0.00514 RPN score loss: 0.0011 RPN total loss: 0.00624 Total loss: 0.79308 timestamp: 1654983317.6280544 iteration: 89980 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11949 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.20655 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.11332 RPN box loss: 0.01757 RPN score loss: 0.00607 RPN total loss: 0.02364 Total loss: 0.93077 timestamp: 1654983320.8255239 iteration: 89985 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09931 FastRCNN class loss: 0.05715 FastRCNN total loss: 0.15647 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.16271 RPN box loss: 0.0175 RPN score loss: 0.008 RPN total loss: 0.0255 Total loss: 0.93194 timestamp: 1654983324.0215762 iteration: 89990 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09067 FastRCNN class loss: 0.08316 FastRCNN total loss: 0.17383 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.08729 RPN box loss: 0.00368 RPN score loss: 0.00393 RPN total loss: 0.00761 Total loss: 0.85599 timestamp: 1654983327.189609 iteration: 89995 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10299 FastRCNN class loss: 0.07397 FastRCNN total loss: 0.17696 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.22046 RPN box loss: 0.01573 RPN score loss: 0.00493 RPN total loss: 0.02066 Total loss: 1.00534 timestamp: 1654983330.3541143 iteration: 90000 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.087 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.16256 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.15178 RPN box loss: 0.01158 RPN score loss: 0.00282 RPN total loss: 0.01439 Total loss: 0.916 Saving checkpoints for 90000 into /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-90000.tlt. ================================= Start evaluation cycle 09 ================================= Loading weights from /workspace/tao-experiments/mask_rcnn/experiment_dir_unpruned/model.step-90000.tlt [*] Limiting the amount of sample to: 500 *********************** Building model graph... *********************** [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_2/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_3/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_4/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_5/ [ROI OPs] Using Batched NMS... Scope: MLP/multilevel_propose_rois/level_6/ [Inference Compute Statistics] 530.6 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.3349s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.3464s - Throughput: 11.5 imgs/s Running inference on batch 003/125... - Step Time: 0.3468s - Throughput: 11.5 imgs/s Running inference on batch 004/125... - Step Time: 0.3527s - Throughput: 11.3 imgs/s Running inference on batch 005/125... - Step Time: 0.3004s - Throughput: 13.3 imgs/s Running inference on batch 006/125... - Step Time: 0.3415s - Throughput: 11.7 imgs/s Running inference on batch 007/125... - Step Time: 0.3344s - Throughput: 12.0 imgs/s Running inference on batch 008/125... - Step Time: 0.3519s - Throughput: 11.4 imgs/s Running inference on batch 009/125... - Step Time: 0.3520s - Throughput: 11.4 imgs/s Running inference on batch 010/125... - Step Time: 0.3384s - Throughput: 11.8 imgs/s Running inference on batch 011/125... - Step Time: 0.3456s - Throughput: 11.6 imgs/s Running inference on batch 012/125... - Step Time: 0.2774s - Throughput: 14.4 imgs/s Running inference on batch 013/125... - Step Time: 0.3356s - Throughput: 11.9 imgs/s Running inference on batch 014/125... - Step Time: 0.3312s - Throughput: 12.1 imgs/s Running inference on batch 015/125... - Step Time: 0.3407s - Throughput: 11.7 imgs/s Running inference on batch 016/125... - Step Time: 0.3347s - Throughput: 11.9 imgs/s Running inference on batch 017/125... - Step Time: 0.3392s - Throughput: 11.8 imgs/s Running inference on batch 018/125... - Step Time: 0.3415s - Throughput: 11.7 imgs/s Running inference on batch 019/125... - Step Time: 0.3457s - Throughput: 11.6 imgs/s Running inference on batch 020/125... - Step Time: 0.3345s - Throughput: 12.0 imgs/s Running inference on batch 021/125... - Step Time: 0.3261s - Throughput: 12.3 imgs/s Running inference on batch 022/125... - Step Time: 0.3499s - Throughput: 11.4 imgs/s Running inference on batch 023/125... - Step Time: 0.3311s - Throughput: 12.1 imgs/s Running inference on batch 024/125... - Step Time: 0.3193s - Throughput: 12.5 imgs/s Running inference on batch 025/125... - Step Time: 0.3343s - Throughput: 12.0 imgs/s Running inference on batch 026/125... - Step Time: 0.3336s - Throughput: 12.0 imgs/s Running inference on batch 027/125... - Step Time: 0.3289s - Throughput: 12.2 imgs/s Running inference on batch 028/125... - Step Time: 0.3269s - Throughput: 12.2 imgs/s Running inference on batch 029/125... - Step Time: 0.3431s - Throughput: 11.7 imgs/s Running inference on batch 030/125... - Step Time: 0.3389s - Throughput: 11.8 imgs/s Running inference on batch 031/125... - Step Time: 0.3474s - Throughput: 11.5 imgs/s Running inference on batch 032/125... - Step Time: 0.3387s - Throughput: 11.8 imgs/s Running inference on batch 033/125... - Step Time: 0.3528s - Throughput: 11.3 imgs/s Running inference on batch 034/125... - Step Time: 0.3379s - Throughput: 11.8 imgs/s Running inference on batch 035/125... - Step Time: 0.3244s - Throughput: 12.3 imgs/s Running inference on batch 036/125... - Step Time: 0.3409s - Throughput: 11.7 imgs/s Running inference on batch 037/125... - Step Time: 0.3286s - Throughput: 12.2 imgs/s Running inference on batch 038/125... - Step Time: 0.3339s - Throughput: 12.0 imgs/s Running inference on batch 039/125... - Step Time: 0.3353s - Throughput: 11.9 imgs/s Running inference on batch 040/125... - Step Time: 0.3451s - Throughput: 11.6 imgs/s Running inference on batch 041/125... - Step Time: 0.3441s - Throughput: 11.6 imgs/s Running inference on batch 042/125... - Step Time: 0.3257s - Throughput: 12.3 imgs/s Running inference on batch 043/125... - Step Time: 0.3334s - Throughput: 12.0 imgs/s Running inference on batch 044/125... - Step Time: 0.3342s - Throughput: 12.0 imgs/s Running inference on batch 045/125... - Step Time: 0.3327s - Throughput: 12.0 imgs/s Running inference on batch 046/125... - Step Time: 0.3423s - Throughput: 11.7 imgs/s Running inference on batch 047/125... - Step Time: 0.3412s - Throughput: 11.7 imgs/s Running inference on batch 048/125... - Step Time: 0.3507s - Throughput: 11.4 imgs/s Running inference on batch 049/125... - Step Time: 0.3449s - Throughput: 11.6 imgs/s Running inference on batch 050/125... - Step Time: 0.3413s - Throughput: 11.7 imgs/s Running inference on batch 051/125... - Step Time: 0.3079s - Throughput: 13.0 imgs/s Running inference on batch 052/125... - Step Time: 0.3371s - Throughput: 11.9 imgs/s Running inference on batch 053/125... - Step Time: 0.3441s - Throughput: 11.6 imgs/s Running inference on batch 054/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 055/125... - Step Time: 0.3329s - Throughput: 12.0 imgs/s Running inference on batch 056/125... - Step Time: 0.3422s - Throughput: 11.7 imgs/s Running inference on batch 057/125... - Step Time: 0.3433s - Throughput: 11.7 imgs/s Running inference on batch 058/125... - Step Time: 0.3416s - Throughput: 11.7 imgs/s Running inference on batch 059/125... - Step Time: 0.3374s - Throughput: 11.9 imgs/s Running inference on batch 060/125... - Step Time: 0.3475s - Throughput: 11.5 imgs/s Running inference on batch 061/125... - Step Time: 0.3592s - Throughput: 11.1 imgs/s Running inference on batch 062/125... - Step Time: 0.3583s - Throughput: 11.2 imgs/s Running inference on batch 063/125... - Step Time: 0.3361s - Throughput: 11.9 imgs/s Running inference on batch 064/125... - Step Time: 0.3440s - Throughput: 11.6 imgs/s Running inference on batch 065/125... - Step Time: 0.3415s - Throughput: 11.7 imgs/s Running inference on batch 066/125... - Step Time: 0.3679s - Throughput: 10.9 imgs/s Running inference on batch 067/125... - Step Time: 0.3541s - Throughput: 11.3 imgs/s Running inference on batch 068/125... - Step Time: 0.3331s - Throughput: 12.0 imgs/s Running inference on batch 069/125... - Step Time: 0.3508s - Throughput: 11.4 imgs/s Running inference on batch 070/125... - Step Time: 0.3418s - Throughput: 11.7 imgs/s Running inference on batch 071/125... - Step Time: 0.3379s - Throughput: 11.8 imgs/s Running inference on batch 072/125... - Step Time: 0.3507s - Throughput: 11.4 imgs/s Running inference on batch 073/125... - Step Time: 0.3356s - Throughput: 11.9 imgs/s Running inference on batch 074/125... - Step Time: 0.3419s - Throughput: 11.7 imgs/s Running inference on batch 075/125... - Step Time: 0.3635s - Throughput: 11.0 imgs/s Running inference on batch 076/125... - Step Time: 0.3374s - Throughput: 11.9 imgs/s Running inference on batch 077/125... - Step Time: 0.3611s - Throughput: 11.1 imgs/s Running inference on batch 078/125... - Step Time: 0.3542s - Throughput: 11.3 imgs/s Running inference on batch 079/125... - Step Time: 0.3461s - Throughput: 11.6 imgs/s Running inference on batch 080/125... - Step Time: 0.3499s - Throughput: 11.4 imgs/s Running inference on batch 081/125... - Step Time: 0.3450s - Throughput: 11.6 imgs/s Running inference on batch 082/125... - Step Time: 0.3303s - Throughput: 12.1 imgs/s Running inference on batch 083/125... - Step Time: 0.3612s - Throughput: 11.1 imgs/s Running inference on batch 084/125... - Step Time: 0.3417s - Throughput: 11.7 imgs/s Running inference on batch 085/125... - Step Time: 0.3433s - Throughput: 11.7 imgs/s Running inference on batch 086/125... - Step Time: 0.3286s - Throughput: 12.2 imgs/s Running inference on batch 087/125... - Step Time: 0.3571s - Throughput: 11.2 imgs/s Running inference on batch 088/125... - Step Time: 0.3545s - Throughput: 11.3 imgs/s Running inference on batch 089/125... - Step Time: 0.3461s - Throughput: 11.6 imgs/s Running inference on batch 090/125... - Step Time: 0.3257s - Throughput: 12.3 imgs/s Running inference on batch 091/125... - Step Time: 0.3600s - Throughput: 11.1 imgs/s Running inference on batch 092/125... - Step Time: 0.3487s - Throughput: 11.5 imgs/s Running inference on batch 093/125... - Step Time: 0.3570s - Throughput: 11.2 imgs/s Running inference on batch 094/125... - Step Time: 0.3464s - Throughput: 11.5 imgs/s Running inference on batch 095/125... - Step Time: 0.3265s - Throughput: 12.3 imgs/s Running inference on batch 096/125... - Step Time: 0.3452s - Throughput: 11.6 imgs/s Running inference on batch 097/125... - Step Time: 0.3496s - Throughput: 11.4 imgs/s Running inference on batch 098/125... - Step Time: 0.3400s - Throughput: 11.8 imgs/s Running inference on batch 099/125... - Step Time: 0.3368s - Throughput: 11.9 imgs/s Running inference on batch 100/125... - Step Time: 0.3320s - Throughput: 12.0 imgs/s Running inference on batch 101/125... - Step Time: 0.3338s - Throughput: 12.0 imgs/s Running inference on batch 102/125... - Step Time: 0.3631s - Throughput: 11.0 imgs/s Running inference on batch 103/125... - Step Time: 0.2770s - Throughput: 14.4 imgs/s Running inference on batch 104/125... - Step Time: 0.3642s - Throughput: 11.0 imgs/s Running inference on batch 105/125... - Step Time: 0.3326s - Throughput: 12.0 imgs/s Running inference on batch 106/125... - Step Time: 0.3363s - Throughput: 11.9 imgs/s Running inference on batch 107/125... - Step Time: 0.3443s - Throughput: 11.6 imgs/s Running inference on batch 108/125... - Step Time: 0.3416s - Throughput: 11.7 imgs/s Running inference on batch 109/125... - Step Time: 0.3467s - Throughput: 11.5 imgs/s Running inference on batch 110/125... - Step Time: 0.3072s - Throughput: 13.0 imgs/s Running inference on batch 111/125... - Step Time: 0.3483s - Throughput: 11.5 imgs/s Running inference on batch 112/125... - Step Time: 0.3424s - Throughput: 11.7 imgs/s Running inference on batch 113/125... - Step Time: 0.3418s - Throughput: 11.7 imgs/s Running inference on batch 114/125... - Step Time: 0.3418s - Throughput: 11.7 imgs/s Running inference on batch 115/125... - Step Time: 0.3372s - Throughput: 11.9 imgs/s Running inference on batch 116/125... - Step Time: 0.3321s - Throughput: 12.0 imgs/s Running inference on batch 117/125... - Step Time: 0.3484s - Throughput: 11.5 imgs/s Running inference on batch 118/125... - Step Time: 0.3451s - Throughput: 11.6 imgs/s Running inference on batch 119/125... - Step Time: 0.3451s - Throughput: 11.6 imgs/s Running inference on batch 120/125... - Step Time: 0.3438s - Throughput: 11.6 imgs/s Running inference on batch 121/125... - Step Time: 0.3121s - Throughput: 12.8 imgs/s Running inference on batch 122/125... - Step Time: 0.3317s - Throughput: 12.1 imgs/s Running inference on batch 123/125... - Step Time: 0.3385s - Throughput: 11.8 imgs/s Running inference on batch 124/125... - Step Time: 0.3932s - Throughput: 10.2 imgs/s Running inference on batch 125/125... - Step Time: 0.3395s - Throughput: 11.8 imgs/s Loading and preparing results... 0/50000 1000/50000 2000/50000 3000/50000 4000/50000 5000/50000 6000/50000 7000/50000 8000/50000 9000/50000 10000/50000 11000/50000 12000/50000 13000/50000 14000/50000 15000/50000 16000/50000 17000/50000 18000/50000 19000/50000 20000/50000 21000/50000 22000/50000 23000/50000 24000/50000 25000/50000 26000/50000 27000/50000 28000/50000 29000/50000 30000/50000 31000/50000 32000/50000 33000/50000 34000/50000 35000/50000 36000/50000 37000/50000 38000/50000 39000/50000 40000/50000 41000/50000 42000/50000 43000/50000 44000/50000 45000/50000 46000/50000 47000/50000 48000/50000 49000/50000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Evaluation Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 11.8 samples/sec Total processed steps: 125 Total processing time: 0.0h 24m 21s ==================== Metrics ==================== AP: 0.213585272 AP50: 0.332958937 AP75: 0.210112900 APl: 0.249952510 APm: 0.046174791 APs: 0.002315852 ARl: 0.444749385 ARm: 0.103231668 ARmax1: 0.298959851 ARmax10: 0.379052222 ARmax100: 0.383193463 ARs: 0.021359559 mask_AP: 0.174005121 mask_AP50: 0.291336447 mask_AP75: 0.175721526 mask_APl: 0.206203327 mask_APm: 0.026861474 mask_APs: 0.000121235 mask_ARl: 0.327370971 mask_ARm: 0.069636092 mask_ARmax1: 0.232669011 mask_ARmax10: 0.276752353 mask_ARmax100: 0.279782563 mask_ARs: 0.008454106 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Training Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 25.0 samples/sec Total processed steps: 90000 Total processing time: 16h 08m 49s ==================== Metrics ==================== FastRCNN box loss: 0.087 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.16256 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 4.0000e-05 Mask loss: 0.15178 RPN box loss: 0.01158 RPN score loss: 0.00282 RPN total loss: 0.01439 Total loss: 0.916 Job finished with status: `SUCCESS`